Sample Paper free essay sample

State the law that governs the strength of the current passing through a metallic conductor when a p. d is applied across its end. Illustrate this law graphically? 2. Why is an ammeter connected in series and voltmeter in parallel in a circuit? 3. In an experiment the current flowing through a resistor and potential difference across it are measured. The values are given below. Show that these values confirm Ohm’s Law and also find the resistance of the resistor. I (ampere) I(ampere) 1. 0 1. 0 2 1. 5 2. 0 2. 0 2. 5 2. 5 3. 3. 0 V (volt) V(volt) 4. 0 4. 0 6. 0 6. 0 8. 0 8. 0 10. 0 10. 0 12. 0 12. 0 4. What are ohmic conductors? What are non ohmic conductors? Give example 5. Draw the VI graph for an ohmic and a non ohmic conductor. 6. Calculate the number of electrons constituting one coulomb of charge? 7. A piece of wire is redrawn by pulling it until its length is tripled. Compare the new resistance with the original value. 8. the ratio of resistivity’s of two materials a and b is 1:2, ratio of their length is 3:4 and if the ratio of radii is 2:3 find the ratio of resistance of a and b. We will write a custom essay sample on Sample Paper or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page . Two wires are of same length and radius but one of them is copper and the other is of iron. Which will have more resistance? (Given the resistivity of copper = 1. 62 x 10 -8 ohm meter and resistivity of iron = 10 x 10-8 ohm meter. 10. A wire of resistance 5 Ohm is spent in the form of closed circle. What is the resistance between 2 points at the ends of any diameter of the circle? 11. Two wires of equal cross sectional area, one of copper and other of manganin have same resistance. Which one will be longer? 2. Two students perform an experiment on series and parallel combinations of two given resistors R1 and R2 and plot following VI graph Which of the graph is (are) correctly labeled. Justify your answer. 13. Draw the circuit consisting of a battery of five 2V cells, 5ohm resistor, 10 ohm resistor, 15 ohm resistor and a plug key. All connected in series (b) Calculate the current passing through the above circuit when key is closed. 14. Three resistors of 4ohms, 6ohms and 12 ohms are connected in parallel. The combination of above resistors is connected in series to a resistance of 2 ohms and then to a battery of 6 volts. Draw a circuit diagram and calculate a) Current in main circuit b) Current flowing through each of the resistors in parallel c) P. d and the power used by the 2 ohm resistor. 15. State the law which governs the amount of heat produced in a metallic conductor when current is passed through it for a given time. Express this law mathematically? 16. State which has a higher resistance. A 50W or 25W lamp. Also find the ratio of their resistances. 17. Why is tungsten used almost exclusively for making the filaments of electric lamps? 18. Write the advantages of connecting electrical appliances in parallel and disadvantages of connecting them in series in a household circuit. 19. State the relation between the commercial and SI unit of electric energy. 20. For a heater rated at 4 kW and 220 V, calculate (a) the current, b) the resistance of the heater, ) the energy consumed in 2 hours, and d) the cost if 1 kWh is priced at Rs. 4. 60..

Listening Comprehension Strategies

Listening Comprehension Strategies Listening comprehension, also known as oral comprehension, can present a struggle for learning disabled children. Many disabilities can make it difficult for them to attend to information delivered orally, including difficulties in processing sounds and prioritizing sensory input. Even children with mild deficits may simply find auditory learning difficult since some students are visual or even kinesthetic learners. What Disabilities Affect Listening Comprehension? Auditory processing disorder, ADHD or a language-processing deficit can have serious impacts on listening comprehension. These children can hear, but imagine a world in which every noise you heard was at the same volume- its just impossible to sort out the important sounds from the unimportant ones. A ticking clock may be as loud and attention-grabbing as the lesson being taught by the teacher.    Reinforcing Listening Comprehension at Home and School For a child with these kinds of needs, listening comprehension work cant only happen in school. After all, parents will have the same struggles at home. Here are some general strategies for children with auditory processing delays. Reduce distraction. To help regulate volume and keep a child on task, its essential to eliminate extraneous noises and motion. A quiet room can help. Failing that, noise-canceling headphones can do wonders for easily distracted learners.Let the child see you when you speak. A child with difficulty interpreting sounds or making them on her own should see the shape of your mouth as you speak. Let him put his hand on his throat when saying words that present difficulty, and have him look in a mirror while speaking.Take movement breaks. Some children will need a refresher in the struggle to listen. Let them get up, move around, and then return to the task. They may need this support more often than you think!Read aloud, at least 10 minutes a day. You are the best example: Spend time reading aloud one-on-one to kids with auditory deficits. Its important to cater to the childs interests.Help her with the process of listening. Have the child repeat what youve said, summarize what shes read, or explain to you how she will complete a task. This builds the foundation of comprehension. When teaching a lesson, present information in short and simple sentences.Always check to ensure that the child understands by repeating or rephrasing your instructions or directions. Use voice intonation to keep his attention.Whenever possible, use visual aids and or charts. For visual learners, this can make all the difference.Help children with organization by presenting the sequence of the lesson before you teach it. e Reference them as youre giving instructions.Teach strategies to these students that include rehearsing mentally, focusing on keywords and using mnemonics. Making connections when presenting new material can help them overcome the sensory deficit.For students for whom distractibility is not the main issue, group learning situations may help. Peers will often help or direct a child with deficits and lend additional support that will preserve a childs self-esteem.   Remember, just because youve said it aloud doesnt mean the child understands. Part of our job as parents and as teachers is to ensure that comprehension is happening. Consistency is the most effective strategy to support children with challenges in listening comprehension.

Can Rational Choice Theory Explain Cyber Terrorism in the United Research Paper

Can Rational Choice Theory Explain Cyber Terrorism in the United States - Research Paper Example This defines the scope of cyber terrorism and I, in this paper, explore the scope of cyber terrorism and existence of a relationship between the scope of cyber terrorism and Rational Choice Theory and the theory’s applicability to cyber terrorism in the United States. Cyber terrorism The definition of cyber terrorism is controversial because of differences in professional perspectives. Information technology experts, for example, dispute diversified opinions over the term cyber terrorism and existence of such a crime. There are however many security based definitions of cyber terrorism and their consideration can coin a comprehensive meaning. The North Atlantic Treaty Organization (NATO), defines cyber terrorism as an offensive that employs â€Å"computer or communication networks† to inflict significant harm or disorientation with the aim of creating â€Å"fear or to intimidate† a group in order to achieve an objective (Centre of Excellence Defence Against Terro rism, 2008, p. 119). The organization however identifies limitation in this definition because of lack of the physical aspects in the scope of the alleged attacks. The National Infrastructure Protection Center however offers a more comprehensive definition that incorporates elements of violence in the offensive acts, confusion as the attackers’ intentions, and â€Å"political and social† influence as possible objectives (Centre of Excellence Defence Against Terrorism, 2008, p. 119). The federal Bureau of Investigations further incorporates pre-established plans into the acts that majorly target civilians (Centre of Excellence Defence Against Terrorism, 2008). Cyber terrorism is therefore a planned attack on a civilian group that is affiliated to a target political force, implemented using computer based applications and communication systems and leads to violence, destruction of property and disorientations in order to instill fear and intimidate people into the offend er’s desires political, social, or ideological needs. Elements of cyber terrorism The scope of cyber terrorism identifies many elements. One of its major elements is the speed with which it is executed and the number of people that it affects. Being an illegal act that authorities would wish to divert, the crime is conducted at a swift speed to ensure success through avoiding possible prevention measures. The faster nature of the crime also identifies with its medium of execution, the internet, which is instant. Cyber terrorism also affects many people because of the medium’s property and the crime’s aims. The internet condenses data and this means that extensive information that affects many people can be targeted by a single attack. Further, communication through the internet is fast, information is accessible to many people, and this spreads impacts of the offensive to a wider population (Keene, 2011). Illegal access to a system is another feature of cyber te rrorism whose scope includes hacking of a target’s website to interfere with its data or use the site to communicate the terrorists’ intended messages (Broadhurst, 2004). Application of computer and computer-based applications is another element of the

COMMUNICATION USING NEWER TECHNOLOGIES Essay Example | Topics and Well Written Essays - 250 words

COMMUNICATION USING NEWER TECHNOLOGIES - Essay Example Communicating with other people regardless what part of the world is possible in a very timely manner. We send invitations through an e-mail as well as e-cards to greet someone who celebrates birthday. Invitations can also be posted in Facebook so people can confirm if they are attending an event. In fact, communication is real-time because one can video conference with a friend, business partner or loved one through technologies like Skype. Last time, my childhood friends planned a get-together; however, a friend of ours couldn’t make it, since she is living abroad. All we had to do was set up the video camera and speaker on the PC, so she can be part of that wonderful celebration. She was there with us virtually all the time, watching us as we sing and played games. She heard the music in the background that reminded her of our good times together. She also saw the decorations we made as well as the clothes we wore that night. The only thing missing is the fact that she coul dn’t embrace us for all she has is a screen. Nevertheless, she felt she was almost there; in fact, everyone chatted with her, so she saw the smiles in our face. Aside from the Skype conference, we also sent our friend pictures by simply attaching it to our e-mail.

Proprietary and Contract Security Essay Example | Topics and Well Written Essays - 1000 words

Proprietary and Contract Security - Essay Example The problem has more to do with the thinking among executives proprietary security has no alternative. There is the feeling that contract security has a mix of the good and the bad. Why take the risk and get into trouble in case the security turns out to be bad (Shamus McGillicuddy). Nonetheless, reports from companies who have dared to venture and have the open system installed are encouraging. They work well and their cost is low. Some of them have gone on to say that they have better features than proprietary security. The function of security systems essentially includes spam, spyware and phishing blockers, virus protection, web filter, protocol control, intrusion prevention, a firewall and several other applications. The open sources all of these. Although company executives swear by contract security, they have only gone the extra mile and added this security along with proprietary sources in most cases. The time is not ripe for a complete recourse to the contract source and probably will never be. Proprietary security has too many aces up its sleeve that contract security will find hard to trump. Proprietary securities have access to far more rese... They also have more resources and access to critical ideas because of their size and reach. They have wide acceptance and are financially powerful to deal with any crisis. In case of any lacunae in a model, they have the capability to recall the entire lot and have replacement done at the same time. Disadvantages Because of mass production, they cannot have the maneuverability and diversity that contract security offers. They have enormous power to push their products but although they have wide range of features included in their products they cannot arrange for the maneuverability and diversity that contract sources can provide. In terms of cost, if they have to tailor make products for customers, they can be quite expensive. Contract Security The contract security segment has formed a National Association of Security Companies (NASCO). Organizations such as NASCO wield tremendous clout and are capable of bridging the gap that may exist between the proprietary and contract security. Tracy A. Henke, assistant secretary for the Office of Grants and Training, spoke about the importance of private security personnel participating in joint training with federal agencies. She also pointed out that the DHS is certifying more and more state training programs. The summit also featured sessions designed to foster an open discussion about issues directly impacting contract security operations (NASCO Concludes First Contract Security Summit). Advantages Contract securities can be powerful in applications and give value for money for niche organizations such as health and medicine. They are particularly useful for those seeking special attention in certain areas of professionals

Inter Firm Relationships in the Silicon Fen

Inter Firm Relationships in the Silicon Fen The attention that clusters have received from policy makers and academics has substantially increased in the last 20 years. Since Porters seminal work on The Competitive Advantage of Nations (1990) presented clusters as one of the determinants of the international competitiveness of nations and regions, many scholars have adopted and further developed his approach. Porter bases his arguments on what he describes as the globalization paradox, pointing out that despite the logical implications that the globalisation process might have in dismissing the relevance of regional factors, the most competitive firms in world are located in groups geographically concentrated in specific locations. That perspective contributed to attracting attention to the existence of characteristics tied to a local context that could not be accessed by firms positioned elsewhere, and more, to the positive effects that the concentration and the geographic proximity could exert on the firms competitiveness. However influential, Porters ideas were not the precursor to discussing the competitive outcomes originating from the geographic concentration of firms (Martin and Sunley, 2003). The roots of cluster theory go back to the industrial districts identified by Marshall (1890), who offered the first detailed description about the economic and social systems created as a result of the spacial concentrations of industrial activities. The Marshallian industrial districts were arrangements of small firms interconnected by commercial operations (buyers and sellers) and other firms engaged in the same or similar activities, that shared productive factors, such as the labour market, infrastructure and tacit knowledge (Becattini, 2004, p. 68). According to Marshals descriptions, a group of firms operating in one specific sector within a well-defined, concentrated and relatively small geographic area would experience higher levels of productivity and innovation, indeed the emergence of a fertile e nvironment for technical and organisational developments. Thus the local characteristics would enable the emergence of an industrial atmosphere that would increase the firms potential to acquire (especially tacit) knowledge, and create positive external economies accessible only to the firms located within the district (Asheim, 2003, p. 416). That perspective tried to evidence that firms geographically concentrated could accesses restricted positive exogenous benefits (exogenous to firms, but endogenous to the district), which would be an alternative to the scale economies achieved by a single (integrated) firm. Additionally, following some of the seminal ideas proposed by Marshall, it is possible to observe a significant number of economic geographers that also explored regional development using the spatial economic agglomeration to support their ideas. Some examples of concepts emerging from that theoretical trend are regional innovation milieux (Crevoisier, 2004), neo-Marshallian nodes (Amin and Thrift, 1992) and learning regions (Asheim, 1995). More examples can be found in Markusen (1996, p. 297), in which another three different types of industrial districts are described according to the firms configurations, internal versus external orientations and governance structures: a hub-and-spoke industrial district, which is concentrated around one or more dominant firms; a satellite platform, formed by a group of unconnected branches embedded in external links; and the state-anchored district, concentrated on one or more public-sector institutions. Despite the logical and robust assumption s found in many of those concepts, their influence and dissemination were not as successful as the more general cluster framework proposed by Porter. Martin and Sunley (2003) attributes the successful dissemination of the Porter concepts to the very general descriptions and delimitations that encompass a wide range of actors and many different structures. Following much of the concepts proposed by Porter, the description of advantages conferred on clustered firms associated with a general and structured analytical framework stimulated the development and dissemination of academic studies and subsidized the creation of supply-side competitiveness policies directed at structuring and supporting the development of clusters (Pitelis, 2010). That fact resulted in what Martin and Sunley (2003) describe as a policy panacea in the use of clusters as a standard (sometimes the unique) target for promoting competitiveness, innovation and economic growth. Moreover, in the last 20 years an increasing number of empirical studies in different countries and sectors have been observed, which aim to identify and discuss the competitive outcomes originating from the concentration of firms and other actors in the same location, for example: Brazil à ¢Ã¢â€š ¬Ã¢â‚¬Å" shoe manufacturing in the Sinos Valley (Schmitz, 2000); Spain à ¢Ã¢â€š ¬Ã¢â‚¬Å" the text ile and clothing industries in Catalonia (Porter, 1998); Taiwan à ¢Ã¢â€š ¬Ã¢â‚¬Å" electronic products at the Hsinchu Science Park (Chen, 2008); and the United States à ¢Ã¢â€š ¬Ã¢â‚¬Å" computer and information systems at the Silicon Valley (Saxenian, 1994). The large significant number of academic studies has resulted in a large number of definitions aiming to describe and establish an accepted cluster template (e.g., Enright, 1996; Swann and Prevezer, 1996, Rosenfeld, 1997; Porter, 1998) to support policy makers and academics has led to intense debates and controversial perspectives. Even though the concept of clusters has been increasingly widely disseminated and used by geographers, economists and policy makers, it has suffered from some conceptual confusion. Porter defines a cluster as a geographic concentration of interconnected companies, specialized suppliers, service providers firms in related industries, and associated institutions (for example, universities, standards agencies and trade associations) in particular fields that compete but also co-operate (1998, p. 197). However, Martin and Sunley (2003, p. 12) present consistent arguments that indicate the vagueness and superficiality of the concept proposed by Porter. Accordin g to their arguments, those characteristics make the concept of cluster means different things to different researchers and policy makers, creating problems for its proper use in the guidance of academics and governments. Those highly controversial aspects of the cluster theory have stimulated the continuous emergence of new concepts and definitions for clusters. Proposing a definition aiming to fill some of the gaps and failures found in extant cluster theory, Pitelis (2010, p. 5) defines clusters as geographical agglomerations of firms in particular, related, and/or complementary, activities, with a geographical dimension, that exhibit horizontal and/or vertical intra- and/or inter-sectoral linkages, which operate in the context of a facilitatory socio-institutional setting, and which co-operate and compete (co-opete) in inter-national markets. That definition tries offer to a more delimited approach that incorporates four major elements: geographical agglomeration, linkages, social-capital  [1]  and co-opetition (competition and cooperation). The use of those four elements in a single definition offers the possibility to cover the cluster characteristics using delimited criteria to identify and distinguish developed clusters from less complex geographical agglomerations of firms and institutions. Although it is possible to observe some level of ambiguity encompassing the clusters theory, the existence of links interconnecting local actors complemented by geographical dimensions constitute some of the main common points used to guide academics and policy makers with interesting by the competitive outcomes originating from clusters. Those characteristics have frequently been used as the starting point to understand the economic dynamics of clustered firms, putting emphasis on the levels of innovation and productivity emerging from the concentration of different actors in the same area. Suggesting conditional characteristics to the presence of competitive advantages obtained by firms inside clusters, Ketels (2004) considers that the positive economic effects originated from the geographical concentration will only take place if four critical characteristics are shared among firms and institutions: Proximity: they must be geographically close to allow the emergence of knowledge spillovers and to share the same common resources; Linkages: the necessity of similarities in their activities leading to the establishment of connections and synergies; Interactions: the social interactions developed among firms, clients, suppliers, research institutes, and so on, is what forms the social capital that becomes possible firms to achieve differentiated competitive performances; Critical mass: it is important to have a significant number of firms and institutions in order to create meaningful impacts on performance of the local actors. Those characteristics described by Ketels may be used to guide the identification and distinction between developed clusters (Pitelis, 2010) from incipient clusters (Schmitz, 1999) in order to dismiss some incorrect interpretations associated with the clusters dynamics. Considering that the presence of geographic concentration of firms in the same industry is strikingly common around the world (Porter, 1990, p.120), it is necessary the use of specific benchmarks to distinguish and classify different groups of firms geographically concentrated according to their specific characteristics (Gordon and McCann, 2000; Isbasoiu, 2006). Describing how the existence of local capabilities  [2]  create differentiated conditions for companies within real clusters, Menzel and Fornahl (2010) argue that clusters are essentially formed from path dependencies (Martin and Sunley, 2006), transaction costs economies (McCann and Sheppard, 2003) and small cognitive distances originating from spatial proximity (Maskell, 2001). Thus, that set of factors are expected to create a specific regional dynamics with influence on the firms economic performance. Taking into consideration the different stages of a cluster life cycle, and the misunderstandings related to the claims associated with the clusters and competitiveness, Schmitz points out that A group of small producers making the same or similar things in close vicinity to each other constitutes a cluster, but such concentration in itself brings few benefits (1999, p. 4), emphasizing that the mere presence of firms in a delimited area does not represent a source of value creat ion able to improve in a significant way the local economic performance. Following the arguments above, the differences between regional clusters and simple agglomerations (groups of firms) lie mainly on the interconnected nature and spatial proximity. Thus, clusters are characterized by intense collaborative networks and concentrations of collaboration and competition (co-opetitition) (Pitelis, 2010), conditions which offer significant opportunities and stimulate the emergence of regional competitive advantages (Steinle and Schiele, 2002). Complementarily, another critical characteristic observed within clusters is the diversity of actors. According to Porter (1990, 1998, 2000), an industrial cluster includes suppliers, consumers, related industries, governments, and supporting institutions such as universities. This way, the existence of a regional network formed by a significant group of interconnected local actors is one of the critical factors to understand the differentiated competitive performance of firms within clusters (Steinle and Schiele, 2002 ). Illustrating that argument, Saxenian (1994) observed that Hewlett Packard and other firms at the Silicon Valley had their performance improved by the development long-term partnerships with suppliers located geographically close. Moreover, based on that observation, Saxenian concluded that, especially in high-tech industries, the physical proximity represents a facilitator to the establishment of efficient collaborative arrangements required to create and manage complex products and services. 1.2 Evolutionary Stages of Industrial Clusters Despite the vast cluster literature, the number of academic works discussing the evolutionary patterns of clusters overtime is not so extensive. Some examples can be found in Pouder and John (1996), Klepper (2001, 2007), Wolter (2003) and Andersson et al., (2004), and despite the divergent perspectives, it is accepted that clusters follow a kind of life cycle comprised by different phases that significantly differ in their characteristics and influence on firms performance. Regarding the cluster dynamics, Pouder and John (1996) argue that comparative analysis between clustered and non-clustered firms during the industry life cycle reveal that firms within clusters outperform those geographically dispersed at the initial stages of development, and have a worse performance at its end. That fact suggests that the cluster life cycle is not just a local representation of the industry trajectory, but is a result from local peculiarities. The comparative analysis developed by Saxenian (1994 ) between the computer industry in Boston and Silicon Valley illustrates how different clusters belonging to the same industry are very likely to follow different trajectories (Menzel and Fornahl, 2010). Proposing a different perspective, Klepper (2001, 2007) suggests a model to demonstrate how the clusters life cycle is determined by some the industry patterns. Klepper analyzed the automobile, tire and television industries and observed that at the beginning of the industry life cycle it was not possible to observe clear geographic concentrations of firms, with most of the firms spatially dispersed. He observed that in those industries clusters started to emerge and develop according to the industry growth rates. Klepper argues that the local characteristics originating from the spacial proximity (e.g., intensive spin-off process) give the stimulus for the geographic agglomeration of the whole industry, not only for specific groups. At the time the industry growth rate reduces, the attractiveness to remain agglomerated will also decrease and the industry will become dispersed again. That model proposed by Klepper represents a Technology-Product- Industry (TIP) life cycle. The logic behind this model is on the impact that the evolution of products and innovations has on the size, number, and location of firms. Wolter (2003) criticizes the model proposed by Klepper arguing that the growth rate cannot explain the agglomeration process in all industries on equal basis. Moreover, Wolter disagrees with the determinist perspective proposed by the TIP model, once it neglects that mature industries can be reinvented by radical or incremental innovations of new products and process. Analyzing the economic performance of firms within clusters Pouder and John (1996) attribute to the existence of mental models and biased cognitive focus the characteristics responsible for shaping the movement through the clusters life cycle. Following that perspective, at initial stages the cluster dynamics creates an innovative environment that exerts positive impacts on the firms performance. However, overtime that initial condition is eroded by strong institutional pressures that create a homogeneous macroculture that acts inhibiting the innovative capacity of the firms within the cluster. As in the model presented by Klepper (2001, 2007), that trajectory proposed by Pouder and John may also be criticized by the determinism that ignores the possibility of adaptations or reconfigurations in order to avoid lock-ins and other negative effects. Considering the arguments proposed by Menzel and Fornahl (2010, p. 8) that very few clusters follow a rigid life cycle from emergence to growth and decline, it is expected that clusters evolve overtime according to the local dynamics created by economic and social interactions among firms and institutions. That dynamics may be influenced, but not strictly determined by industry patterns (Wolter, 2003). Following a generic and stylized trajectory, within successful clusters the local network formed by inter-firm connections will tend to be intensified overtime, with an increasing number of formal and informal interactions between the long-established companies and new the ones attracted to the cluster. Even though it is more conceivable to assume that the decisions adopted by firms and institutions are shaped by specific circumstances, a generic trajectory can be described following the stages illustrated in Figure 1. Figure 1: The cluster life cycle C:UsersLucasAppDataLocalMicrosoftWindowsTemporary Internet FilesContent.WordSem tÃÆ' ­tulo.jpg Source: Andersson et al. (2004, p. 43) Agglomeration: It is possible to observe the existence of a number of companies and other actors (e.g. banks, government agencies, universities, accountants, and lawyers offices) in a specific region working around the same or interrelated activities. Emerging cluster: Forming the embryo to the cluster some actors start to cooperation around some core activities, and start to realize the existence of common linkages. Developing cluster: The linkages are intensified by the emergence and attraction of new actors to the region, resulting in the creation of more interaction. In this context the development of inter-firm-cooperation becomes more evident through the development of joint efforts. The Mature cluster: This stage is configured by the presence of a certain critical mass of factors that consistently influence the competitive performance of the firms inside the cluster. The internal dynamics is characterized by the presence of an institutional environment, strong linkages, complementarities and the emergence of new firms through startups, joint ventures and spin-offs. Transformation: Indeed the process of continuous environmental change in markets, technologies, regulations and other process, to be successful a cluster have to innovate and adapt to these new conditions, other way stagnation and decay may affect the cluster dynamics. That process of change/adaptation may happen through the emergence of one or several interconnected clusters with focus in other activities, or by new configuration in terms of networks of firms and institutions. The presence of economic benefits for clustered firms described by authors like Schmitz and Nadvi (1999), Ketels (2004), Isbasoiu (2006) and Pitelis and Pseiridis (2006) are closely related to the stage of development that a cluster is experiencing. For example, an emerging cluster is not actually a cluster, since the small number of firms is not expected to present a high level of linkages and do not form a critical mass. Moreover, the absence of strong interdependencies such as labour mobility, spin-off, socioeconomic networks and intense exchange of good and services prevent the emergence of local capabilities. Thus, same considering that this stage constitutes the embryo that determines the future cluster orientation, at this point the firms are not expected to be strongly influenced by a complex local dynamics. Observing that fact, Menzel and Fornahl (2010) present a skeptical position regarding the effectiveness of any competitiveness policy intended to stimulate the development of clusters at initial stages (agglomeration and emerging), since the existence of horizontal and vertical links among firms concentrated in the same region constitutes a very common fact around the world. Thus, it is almost impossible to distinguish agglomerations with real potential to become a cluster from less complex structures. Consequently, emerging clusters are almost always only described ex-post. After the initial stages of the clusters life cycle it is expected the development and intensification of interdependencies between firms within cluster boundaries (Press, 2006). Indeed the development of those interdependencies, firms start to resemble more with each other, being observe the emergence of convergent designs in terms of technological models (Menzel and Fornahl, 2010), specialized labour market (Cooke et al., 2007), production systems (Pitelis, 2010) and inter-firm relationships (Blien and Maier, 2008). Moreover, developing clusters also attract a high number of start-ups that act stimulating the intensification of intra-cluster relationships. This way, that process of convergence and expansion of the number of firms within the cluster boundaries culminates in the development of self-reinforcing external economies that decrease the heterogeneity among firms at the same time that creates benefits like transactions cost economies and the privileged access to local knowle dge. As clusters reach the stage of maturity, the standards and configurations originating from past decisions become consolidate and it is observed a reduction in the growth rate of firms attracted to the cluster (Klepper, 2007). At this point the cluster trajectory may take two different directions. Keep unchanged, and suffer with a homogenization process that creates bias economic activities and therefore prevent firms to adapt to external shocks (Menzel and Fornahl, 2010). That situation traps firms in previous successful development path and lead to the geographic dispersion of the local actors and to the deterioration of the interdependencies and capabilities. The other possible trajectory is observed in clusters that reach the stage of maturity and successfully sustain the local dynamics by a continuous process of reconfiguration and adaptation to the external shocks (Wolter, 2003). 1.2 Clusters and Economic Performance The extant theory offers a wide range of explanations to justify the economic and competitive benefits experienced by firms located within clusters. Krugman (1991) stress the existence of increasing returns originating from the concentration of firms in the same area, arguing that the geographic proximity puts together the main parts related to firms activities (e.g., labours, firms, suppliers and costumers) resulting in transaction costs economies. Following other perspective, Schmitz and Nadvi (1999) argue that unintentional external economies are not sufficient to explain the competitiveness of firms located within clusters, attributing to the existence of deliberate joint actions (e.g., sharing equipments, associations, strategic alliances and producers improving components) a critical source of the competitive advantages. Pitelis and Pseiridis (2006) explain the levels of competitiveness and productivity associated with clustered firms considering the existence of specialized hu man resources, infrastructure and befits associated with unit costs economies complemented by the presence of an institutional atmosphere. Stressing a different point of view, Bahlmann and Huysman (2008) adopts the knowledge-based view of clusters to emphasize the relevance of knowledge spillovers among the firms to explain the advantages originated from the agglomeration process. Dupuy and Torre (2006) explains the existence of cluster in terms of the advantages originating from trust relationships that increase confidence and reduce risk and uncertainty about the intra-cluster operations taking place among the firms. Moreover, Zyglidopoulos et al. (2003), describe the positive effects that the reputation of a cluster may exert on the internalization process of small and micro enterprises through the alleviation of strategic constraints associated with factors like qualified work force, financing and reduction of the firms legitimation expenses. Despite that wide range of arguments, the most traditional perspective found in the cluster literature has explained the competitive advantages of clusters in terms of productivity and innovation (Pitelis, 1998; Porter, 1998), suggesting that the special characteristics originated from the economic and geographic proximity have significant impact on those two factors. Supplementary, Enright (1998) considers that the characteristics present inside the clusters local environment result in pressures, incentives and capabilities that increase the firms competitiveness comparatively to dispersed competitors, explaining the clustering process in terms of geographically restricted characteristics. Moreover, Solvell et al. (2003) suggests that the competitive advantages emerging from regional clusters may be classified as static and dynamics. According to this perspective, while the agglomeration process triggered and sustained intensively or exclusively by factors like natural resources, low cost labors and government subsidies offers a vulnerable (easy to be copied, substituted or simple eroded by environmental changes) competitive position, clusters based on dynamics characteristics like multi-sectorial externalities, advantages of scale and scope and specific knowledge spillovers are more dynamics and competitive. Extending the arguments presented by Solvell and his colleagues, Andersson et al. (2004) considers that the sustainability of static and dynamic competitive advantages is not strictly determined, arguing that static factors are the main responsible for the emergence of clusters, while the dynamics factors are only developed along the different stages of the cluste r life cycle. Complementing the understanding about the influence of the cluster dynamics on the firms economic performance some authors like Porter (2001); Garnsey and Heffernan (2007); Karlsson (2008) and Mason (2008) describe the existence of a self-reinforcing process originating from the agglomeration externalities that contribute to create a regional virtuous-circle of increasing productivity, competitiveness and value creation. Following that argument, the economic and geographic proximity will stimulate firms to innovate more indeed benefits originating from local capabilities, which will stimulate even more the agglomeration process through the intensification of inter-firm relationships and the attraction of other firms from outside the cluster, which in turn will strength the local capabilities (Blandy, 2003, p. 101). Thus, the dynamics of clusters is expected to be self-reinforced by agglomeration benefits with significant influence on the firms performance. Putting together the arguments associated with the economic impacts experienced by clustered firms indeed the existence of local factors, it is possible to identify and describe the following positive location-specific externalities: Cost savings indeed the geographic proximity with specialized suppliers, labours and distributors; Knowledge-spillovers (intentional and unintentional), since firms inside clusters can benefit from the knowledge dissemination process that may take place especially through inter-firm cooperation, specific linkages and labour mobility; Deliberate joint actions facilitated by the engagement in alliances and partnerships to achieve strategic objectives; Trust relationships, that through the geographic and economic proximity minimize the uncertainty associated with commercial operations, resulting in transactions costs economies; Pressures for higher performance, stimulated by the proximity with competitors; Specific Infrastructure and public goods that are oriented to attend the cluster demands, like roads, ports, laboratories and telecommunication networks; Complementarities, associated with firms in different activities but sharing common factors like raw material, clients and technologies that may enhance the cluster efficiency as whole. Discussing the role of regional clusters in shaping competitive patterns, Tallman et al. (2004) proposes a distinction between the types of competitive advantages emerging from clustered firms: based on traded interdependencies and based on untraded interdependencies. The concept of traded interdependencies is related to the existence of inter-firm transactions inside the cluster, and is observed in formal exchange operations that may take place in form of alliances, commercial operations and acquisitions. On the other hand, untraded interdependencies are related to less tangible effects, and are based on shared knowledge for which no market mechanism exists; with no formal exchange of value for value (Tallman et al. 2004, p. 261). To illustrate the mechanisms by which the untraded interdependencies take place, it is possible to mention unintentional external economies associated with tacit knowledge shared through mechanisms like labor mobility. Those different types of interdependencies, especially untraded, present at the cluster level, represent a source of competitive advantage that is likely to be causal ambiguous (for firms inside and outside the cluster) and high complex in terms of their origins, what consequently constitutes attributes difficult to be replicated by competitors. However, the presence of untraded effects, especially unintentional knowledge spillovers, is viewed Enright (1998) as a constraining factor for firms within clusters, since the establishment of an efficient information flow may limit the firms capacity to obtain monopoly profits from the development of innovations. Complementing the negative effects originating from the clusters dynamics, some authors also describe agglomeration diseconomies that have a negative impact firms located within clusters. For example, congestion effects (Arthur, 1990), institutional sclerosis (Pouder and John, 1996; Pitelis, 2010), rigidities associated with labour mobility and natural resources (Krugman, 1989) and pollution (Fan and Scott, 2003). This way, the dynamics and performance of a cluster is determined by the interplay between positive and negative externalities observed during the different stages of development that a cluster is expected to pass overtime (Wolter, 2003) Limitations in the Cluster Theory Notwithstanding the advances in the cluster theory some questions still remain insufficiently explored. One of the main limitations observed in the current state of the cluster literature is the lack of comparative perspectives to explain the advantages and disadvantages of clusters relatively to other alternative models of organization of economic activities. In his very novel approach, Pitelis (2010) suggests that any perspective trying to explain clusters in terms of absolute advantages is at the very best incomplete. In this context, Pitelis proposes the comparison of clusters vis-ÃÆ'  -vis to markets and hierarchies in order to understand the reasons and conditions that lead firms to engage in intra-clusters relationships, market operations (outside the cluster) or integrate within the firms hierarchy. In fact it is not necessary a great effort to conclude that most of the cluster theory has been developed following a mono-institutional approach (e.g. Porter, 1990, 1998; Saxe nian, 1994; Rosenfeld, 1998; Swann and Sennett, 1998; Schmitz and Nadvi, 1999), while some few exceptions concentrated on transactions costs (e.g. Fujita and Thisse, 1996; Iammarino and McCann, 2006; Takeda et al., 2008) and knowledge creation efficiency (e.g. Hendry et al., 2000; Tracey and Clark, 2003; Reinau, 2007; Kongmanila and Takahashi, 2009) have been drawn on a comparative approaches between clusters and open-market operations. Assuming the arguments proposed by many scholars that clusters are engines of innovation (Davis, 2006, p. 32), the lack of comparative perspectives do not answer the question why clusters are more efficient than markets or the hierarchy to improve the firms innovative capacity (Pitelis, 2010). Thus, despite the wide number of ramifications observed in the cluster theory such as innovative efficiency, productivity, social capital and social interactions, its explicative power remains almost always restricted Inter Firm Relationships in the Silicon Fen Inter Firm Relationships in the Silicon Fen The attention that clusters have received from policy makers and academics has substantially increased in the last 20 years. Since Porters seminal work on The Competitive Advantage of Nations (1990) presented clusters as one of the determinants of the international competitiveness of nations and regions, many scholars have adopted and further developed his approach. Porter bases his arguments on what he describes as the globalization paradox, pointing out that despite the logical implications that the globalisation process might have in dismissing the relevance of regional factors, the most competitive firms in world are located in groups geographically concentrated in specific locations. That perspective contributed to attracting attention to the existence of characteristics tied to a local context that could not be accessed by firms positioned elsewhere, and more, to the positive effects that the concentration and the geographic proximity could exert on the firms competitiveness. However influential, Porters ideas were not the precursor to discussing the competitive outcomes originating from the geographic concentration of firms (Martin and Sunley, 2003). The roots of cluster theory go back to the industrial districts identified by Marshall (1890), who offered the first detailed description about the economic and social systems created as a result of the spacial concentrations of industrial activities. The Marshallian industrial districts were arrangements of small firms interconnected by commercial operations (buyers and sellers) and other firms engaged in the same or similar activities, that shared productive factors, such as the labour market, infrastructure and tacit knowledge (Becattini, 2004, p. 68). According to Marshals descriptions, a group of firms operating in one specific sector within a well-defined, concentrated and relatively small geographic area would experience higher levels of productivity and innovation, indeed the emergence of a fertile e nvironment for technical and organisational developments. Thus the local characteristics would enable the emergence of an industrial atmosphere that would increase the firms potential to acquire (especially tacit) knowledge, and create positive external economies accessible only to the firms located within the district (Asheim, 2003, p. 416). That perspective tried to evidence that firms geographically concentrated could accesses restricted positive exogenous benefits (exogenous to firms, but endogenous to the district), which would be an alternative to the scale economies achieved by a single (integrated) firm. Additionally, following some of the seminal ideas proposed by Marshall, it is possible to observe a significant number of economic geographers that also explored regional development using the spatial economic agglomeration to support their ideas. Some examples of concepts emerging from that theoretical trend are regional innovation milieux (Crevoisier, 2004), neo-Marshallian nodes (Amin and Thrift, 1992) and learning regions (Asheim, 1995). More examples can be found in Markusen (1996, p. 297), in which another three different types of industrial districts are described according to the firms configurations, internal versus external orientations and governance structures: a hub-and-spoke industrial district, which is concentrated around one or more dominant firms; a satellite platform, formed by a group of unconnected branches embedded in external links; and the state-anchored district, concentrated on one or more public-sector institutions. Despite the logical and robust assumption s found in many of those concepts, their influence and dissemination were not as successful as the more general cluster framework proposed by Porter. Martin and Sunley (2003) attributes the successful dissemination of the Porter concepts to the very general descriptions and delimitations that encompass a wide range of actors and many different structures. Following much of the concepts proposed by Porter, the description of advantages conferred on clustered firms associated with a general and structured analytical framework stimulated the development and dissemination of academic studies and subsidized the creation of supply-side competitiveness policies directed at structuring and supporting the development of clusters (Pitelis, 2010). That fact resulted in what Martin and Sunley (2003) describe as a policy panacea in the use of clusters as a standard (sometimes the unique) target for promoting competitiveness, innovation and economic growth. Moreover, in the last 20 years an increasing number of empirical studies in different countries and sectors have been observed, which aim to identify and discuss the competitive outcomes originating from the concentration of firms and other actors in the same location, for example: Brazil à ¢Ã¢â€š ¬Ã¢â‚¬Å" shoe manufacturing in the Sinos Valley (Schmitz, 2000); Spain à ¢Ã¢â€š ¬Ã¢â‚¬Å" the text ile and clothing industries in Catalonia (Porter, 1998); Taiwan à ¢Ã¢â€š ¬Ã¢â‚¬Å" electronic products at the Hsinchu Science Park (Chen, 2008); and the United States à ¢Ã¢â€š ¬Ã¢â‚¬Å" computer and information systems at the Silicon Valley (Saxenian, 1994). The large significant number of academic studies has resulted in a large number of definitions aiming to describe and establish an accepted cluster template (e.g., Enright, 1996; Swann and Prevezer, 1996, Rosenfeld, 1997; Porter, 1998) to support policy makers and academics has led to intense debates and controversial perspectives. Even though the concept of clusters has been increasingly widely disseminated and used by geographers, economists and policy makers, it has suffered from some conceptual confusion. Porter defines a cluster as a geographic concentration of interconnected companies, specialized suppliers, service providers firms in related industries, and associated institutions (for example, universities, standards agencies and trade associations) in particular fields that compete but also co-operate (1998, p. 197). However, Martin and Sunley (2003, p. 12) present consistent arguments that indicate the vagueness and superficiality of the concept proposed by Porter. Accordin g to their arguments, those characteristics make the concept of cluster means different things to different researchers and policy makers, creating problems for its proper use in the guidance of academics and governments. Those highly controversial aspects of the cluster theory have stimulated the continuous emergence of new concepts and definitions for clusters. Proposing a definition aiming to fill some of the gaps and failures found in extant cluster theory, Pitelis (2010, p. 5) defines clusters as geographical agglomerations of firms in particular, related, and/or complementary, activities, with a geographical dimension, that exhibit horizontal and/or vertical intra- and/or inter-sectoral linkages, which operate in the context of a facilitatory socio-institutional setting, and which co-operate and compete (co-opete) in inter-national markets. That definition tries offer to a more delimited approach that incorporates four major elements: geographical agglomeration, linkages, social-capital  [1]  and co-opetition (competition and cooperation). The use of those four elements in a single definition offers the possibility to cover the cluster characteristics using delimited criteria to identify and distinguish developed clusters from less complex geographical agglomerations of firms and institutions. Although it is possible to observe some level of ambiguity encompassing the clusters theory, the existence of links interconnecting local actors complemented by geographical dimensions constitute some of the main common points used to guide academics and policy makers with interesting by the competitive outcomes originating from clusters. Those characteristics have frequently been used as the starting point to understand the economic dynamics of clustered firms, putting emphasis on the levels of innovation and productivity emerging from the concentration of different actors in the same area. Suggesting conditional characteristics to the presence of competitive advantages obtained by firms inside clusters, Ketels (2004) considers that the positive economic effects originated from the geographical concentration will only take place if four critical characteristics are shared among firms and institutions: Proximity: they must be geographically close to allow the emergence of knowledge spillovers and to share the same common resources; Linkages: the necessity of similarities in their activities leading to the establishment of connections and synergies; Interactions: the social interactions developed among firms, clients, suppliers, research institutes, and so on, is what forms the social capital that becomes possible firms to achieve differentiated competitive performances; Critical mass: it is important to have a significant number of firms and institutions in order to create meaningful impacts on performance of the local actors. Those characteristics described by Ketels may be used to guide the identification and distinction between developed clusters (Pitelis, 2010) from incipient clusters (Schmitz, 1999) in order to dismiss some incorrect interpretations associated with the clusters dynamics. Considering that the presence of geographic concentration of firms in the same industry is strikingly common around the world (Porter, 1990, p.120), it is necessary the use of specific benchmarks to distinguish and classify different groups of firms geographically concentrated according to their specific characteristics (Gordon and McCann, 2000; Isbasoiu, 2006). Describing how the existence of local capabilities  [2]  create differentiated conditions for companies within real clusters, Menzel and Fornahl (2010) argue that clusters are essentially formed from path dependencies (Martin and Sunley, 2006), transaction costs economies (McCann and Sheppard, 2003) and small cognitive distances originating from spatial proximity (Maskell, 2001). Thus, that set of factors are expected to create a specific regional dynamics with influence on the firms economic performance. Taking into consideration the different stages of a cluster life cycle, and the misunderstandings related to the claims associated with the clusters and competitiveness, Schmitz points out that A group of small producers making the same or similar things in close vicinity to each other constitutes a cluster, but such concentration in itself brings few benefits (1999, p. 4), emphasizing that the mere presence of firms in a delimited area does not represent a source of value creat ion able to improve in a significant way the local economic performance. Following the arguments above, the differences between regional clusters and simple agglomerations (groups of firms) lie mainly on the interconnected nature and spatial proximity. Thus, clusters are characterized by intense collaborative networks and concentrations of collaboration and competition (co-opetitition) (Pitelis, 2010), conditions which offer significant opportunities and stimulate the emergence of regional competitive advantages (Steinle and Schiele, 2002). Complementarily, another critical characteristic observed within clusters is the diversity of actors. According to Porter (1990, 1998, 2000), an industrial cluster includes suppliers, consumers, related industries, governments, and supporting institutions such as universities. This way, the existence of a regional network formed by a significant group of interconnected local actors is one of the critical factors to understand the differentiated competitive performance of firms within clusters (Steinle and Schiele, 2002 ). Illustrating that argument, Saxenian (1994) observed that Hewlett Packard and other firms at the Silicon Valley had their performance improved by the development long-term partnerships with suppliers located geographically close. Moreover, based on that observation, Saxenian concluded that, especially in high-tech industries, the physical proximity represents a facilitator to the establishment of efficient collaborative arrangements required to create and manage complex products and services. 1.2 Evolutionary Stages of Industrial Clusters Despite the vast cluster literature, the number of academic works discussing the evolutionary patterns of clusters overtime is not so extensive. Some examples can be found in Pouder and John (1996), Klepper (2001, 2007), Wolter (2003) and Andersson et al., (2004), and despite the divergent perspectives, it is accepted that clusters follow a kind of life cycle comprised by different phases that significantly differ in their characteristics and influence on firms performance. Regarding the cluster dynamics, Pouder and John (1996) argue that comparative analysis between clustered and non-clustered firms during the industry life cycle reveal that firms within clusters outperform those geographically dispersed at the initial stages of development, and have a worse performance at its end. That fact suggests that the cluster life cycle is not just a local representation of the industry trajectory, but is a result from local peculiarities. The comparative analysis developed by Saxenian (1994 ) between the computer industry in Boston and Silicon Valley illustrates how different clusters belonging to the same industry are very likely to follow different trajectories (Menzel and Fornahl, 2010). Proposing a different perspective, Klepper (2001, 2007) suggests a model to demonstrate how the clusters life cycle is determined by some the industry patterns. Klepper analyzed the automobile, tire and television industries and observed that at the beginning of the industry life cycle it was not possible to observe clear geographic concentrations of firms, with most of the firms spatially dispersed. He observed that in those industries clusters started to emerge and develop according to the industry growth rates. Klepper argues that the local characteristics originating from the spacial proximity (e.g., intensive spin-off process) give the stimulus for the geographic agglomeration of the whole industry, not only for specific groups. At the time the industry growth rate reduces, the attractiveness to remain agglomerated will also decrease and the industry will become dispersed again. That model proposed by Klepper represents a Technology-Product- Industry (TIP) life cycle. The logic behind this model is on the impact that the evolution of products and innovations has on the size, number, and location of firms. Wolter (2003) criticizes the model proposed by Klepper arguing that the growth rate cannot explain the agglomeration process in all industries on equal basis. Moreover, Wolter disagrees with the determinist perspective proposed by the TIP model, once it neglects that mature industries can be reinvented by radical or incremental innovations of new products and process. Analyzing the economic performance of firms within clusters Pouder and John (1996) attribute to the existence of mental models and biased cognitive focus the characteristics responsible for shaping the movement through the clusters life cycle. Following that perspective, at initial stages the cluster dynamics creates an innovative environment that exerts positive impacts on the firms performance. However, overtime that initial condition is eroded by strong institutional pressures that create a homogeneous macroculture that acts inhibiting the innovative capacity of the firms within the cluster. As in the model presented by Klepper (2001, 2007), that trajectory proposed by Pouder and John may also be criticized by the determinism that ignores the possibility of adaptations or reconfigurations in order to avoid lock-ins and other negative effects. Considering the arguments proposed by Menzel and Fornahl (2010, p. 8) that very few clusters follow a rigid life cycle from emergence to growth and decline, it is expected that clusters evolve overtime according to the local dynamics created by economic and social interactions among firms and institutions. That dynamics may be influenced, but not strictly determined by industry patterns (Wolter, 2003). Following a generic and stylized trajectory, within successful clusters the local network formed by inter-firm connections will tend to be intensified overtime, with an increasing number of formal and informal interactions between the long-established companies and new the ones attracted to the cluster. Even though it is more conceivable to assume that the decisions adopted by firms and institutions are shaped by specific circumstances, a generic trajectory can be described following the stages illustrated in Figure 1. Figure 1: The cluster life cycle C:UsersLucasAppDataLocalMicrosoftWindowsTemporary Internet FilesContent.WordSem tÃÆ' ­tulo.jpg Source: Andersson et al. (2004, p. 43) Agglomeration: It is possible to observe the existence of a number of companies and other actors (e.g. banks, government agencies, universities, accountants, and lawyers offices) in a specific region working around the same or interrelated activities. Emerging cluster: Forming the embryo to the cluster some actors start to cooperation around some core activities, and start to realize the existence of common linkages. Developing cluster: The linkages are intensified by the emergence and attraction of new actors to the region, resulting in the creation of more interaction. In this context the development of inter-firm-cooperation becomes more evident through the development of joint efforts. The Mature cluster: This stage is configured by the presence of a certain critical mass of factors that consistently influence the competitive performance of the firms inside the cluster. The internal dynamics is characterized by the presence of an institutional environment, strong linkages, complementarities and the emergence of new firms through startups, joint ventures and spin-offs. Transformation: Indeed the process of continuous environmental change in markets, technologies, regulations and other process, to be successful a cluster have to innovate and adapt to these new conditions, other way stagnation and decay may affect the cluster dynamics. That process of change/adaptation may happen through the emergence of one or several interconnected clusters with focus in other activities, or by new configuration in terms of networks of firms and institutions. The presence of economic benefits for clustered firms described by authors like Schmitz and Nadvi (1999), Ketels (2004), Isbasoiu (2006) and Pitelis and Pseiridis (2006) are closely related to the stage of development that a cluster is experiencing. For example, an emerging cluster is not actually a cluster, since the small number of firms is not expected to present a high level of linkages and do not form a critical mass. Moreover, the absence of strong interdependencies such as labour mobility, spin-off, socioeconomic networks and intense exchange of good and services prevent the emergence of local capabilities. Thus, same considering that this stage constitutes the embryo that determines the future cluster orientation, at this point the firms are not expected to be strongly influenced by a complex local dynamics. Observing that fact, Menzel and Fornahl (2010) present a skeptical position regarding the effectiveness of any competitiveness policy intended to stimulate the development of clusters at initial stages (agglomeration and emerging), since the existence of horizontal and vertical links among firms concentrated in the same region constitutes a very common fact around the world. Thus, it is almost impossible to distinguish agglomerations with real potential to become a cluster from less complex structures. Consequently, emerging clusters are almost always only described ex-post. After the initial stages of the clusters life cycle it is expected the development and intensification of interdependencies between firms within cluster boundaries (Press, 2006). Indeed the development of those interdependencies, firms start to resemble more with each other, being observe the emergence of convergent designs in terms of technological models (Menzel and Fornahl, 2010), specialized labour market (Cooke et al., 2007), production systems (Pitelis, 2010) and inter-firm relationships (Blien and Maier, 2008). Moreover, developing clusters also attract a high number of start-ups that act stimulating the intensification of intra-cluster relationships. This way, that process of convergence and expansion of the number of firms within the cluster boundaries culminates in the development of self-reinforcing external economies that decrease the heterogeneity among firms at the same time that creates benefits like transactions cost economies and the privileged access to local knowle dge. As clusters reach the stage of maturity, the standards and configurations originating from past decisions become consolidate and it is observed a reduction in the growth rate of firms attracted to the cluster (Klepper, 2007). At this point the cluster trajectory may take two different directions. Keep unchanged, and suffer with a homogenization process that creates bias economic activities and therefore prevent firms to adapt to external shocks (Menzel and Fornahl, 2010). That situation traps firms in previous successful development path and lead to the geographic dispersion of the local actors and to the deterioration of the interdependencies and capabilities. The other possible trajectory is observed in clusters that reach the stage of maturity and successfully sustain the local dynamics by a continuous process of reconfiguration and adaptation to the external shocks (Wolter, 2003). 1.2 Clusters and Economic Performance The extant theory offers a wide range of explanations to justify the economic and competitive benefits experienced by firms located within clusters. Krugman (1991) stress the existence of increasing returns originating from the concentration of firms in the same area, arguing that the geographic proximity puts together the main parts related to firms activities (e.g., labours, firms, suppliers and costumers) resulting in transaction costs economies. Following other perspective, Schmitz and Nadvi (1999) argue that unintentional external economies are not sufficient to explain the competitiveness of firms located within clusters, attributing to the existence of deliberate joint actions (e.g., sharing equipments, associations, strategic alliances and producers improving components) a critical source of the competitive advantages. Pitelis and Pseiridis (2006) explain the levels of competitiveness and productivity associated with clustered firms considering the existence of specialized hu man resources, infrastructure and befits associated with unit costs economies complemented by the presence of an institutional atmosphere. Stressing a different point of view, Bahlmann and Huysman (2008) adopts the knowledge-based view of clusters to emphasize the relevance of knowledge spillovers among the firms to explain the advantages originated from the agglomeration process. Dupuy and Torre (2006) explains the existence of cluster in terms of the advantages originating from trust relationships that increase confidence and reduce risk and uncertainty about the intra-cluster operations taking place among the firms. Moreover, Zyglidopoulos et al. (2003), describe the positive effects that the reputation of a cluster may exert on the internalization process of small and micro enterprises through the alleviation of strategic constraints associated with factors like qualified work force, financing and reduction of the firms legitimation expenses. Despite that wide range of arguments, the most traditional perspective found in the cluster literature has explained the competitive advantages of clusters in terms of productivity and innovation (Pitelis, 1998; Porter, 1998), suggesting that the special characteristics originated from the economic and geographic proximity have significant impact on those two factors. Supplementary, Enright (1998) considers that the characteristics present inside the clusters local environment result in pressures, incentives and capabilities that increase the firms competitiveness comparatively to dispersed competitors, explaining the clustering process in terms of geographically restricted characteristics. Moreover, Solvell et al. (2003) suggests that the competitive advantages emerging from regional clusters may be classified as static and dynamics. According to this perspective, while the agglomeration process triggered and sustained intensively or exclusively by factors like natural resources, low cost labors and government subsidies offers a vulnerable (easy to be copied, substituted or simple eroded by environmental changes) competitive position, clusters based on dynamics characteristics like multi-sectorial externalities, advantages of scale and scope and specific knowledge spillovers are more dynamics and competitive. Extending the arguments presented by Solvell and his colleagues, Andersson et al. (2004) considers that the sustainability of static and dynamic competitive advantages is not strictly determined, arguing that static factors are the main responsible for the emergence of clusters, while the dynamics factors are only developed along the different stages of the cluste r life cycle. Complementing the understanding about the influence of the cluster dynamics on the firms economic performance some authors like Porter (2001); Garnsey and Heffernan (2007); Karlsson (2008) and Mason (2008) describe the existence of a self-reinforcing process originating from the agglomeration externalities that contribute to create a regional virtuous-circle of increasing productivity, competitiveness and value creation. Following that argument, the economic and geographic proximity will stimulate firms to innovate more indeed benefits originating from local capabilities, which will stimulate even more the agglomeration process through the intensification of inter-firm relationships and the attraction of other firms from outside the cluster, which in turn will strength the local capabilities (Blandy, 2003, p. 101). Thus, the dynamics of clusters is expected to be self-reinforced by agglomeration benefits with significant influence on the firms performance. Putting together the arguments associated with the economic impacts experienced by clustered firms indeed the existence of local factors, it is possible to identify and describe the following positive location-specific externalities: Cost savings indeed the geographic proximity with specialized suppliers, labours and distributors; Knowledge-spillovers (intentional and unintentional), since firms inside clusters can benefit from the knowledge dissemination process that may take place especially through inter-firm cooperation, specific linkages and labour mobility; Deliberate joint actions facilitated by the engagement in alliances and partnerships to achieve strategic objectives; Trust relationships, that through the geographic and economic proximity minimize the uncertainty associated with commercial operations, resulting in transactions costs economies; Pressures for higher performance, stimulated by the proximity with competitors; Specific Infrastructure and public goods that are oriented to attend the cluster demands, like roads, ports, laboratories and telecommunication networks; Complementarities, associated with firms in different activities but sharing common factors like raw material, clients and technologies that may enhance the cluster efficiency as whole. Discussing the role of regional clusters in shaping competitive patterns, Tallman et al. (2004) proposes a distinction between the types of competitive advantages emerging from clustered firms: based on traded interdependencies and based on untraded interdependencies. The concept of traded interdependencies is related to the existence of inter-firm transactions inside the cluster, and is observed in formal exchange operations that may take place in form of alliances, commercial operations and acquisitions. On the other hand, untraded interdependencies are related to less tangible effects, and are based on shared knowledge for which no market mechanism exists; with no formal exchange of value for value (Tallman et al. 2004, p. 261). To illustrate the mechanisms by which the untraded interdependencies take place, it is possible to mention unintentional external economies associated with tacit knowledge shared through mechanisms like labor mobility. Those different types of interdependencies, especially untraded, present at the cluster level, represent a source of competitive advantage that is likely to be causal ambiguous (for firms inside and outside the cluster) and high complex in terms of their origins, what consequently constitutes attributes difficult to be replicated by competitors. However, the presence of untraded effects, especially unintentional knowledge spillovers, is viewed Enright (1998) as a constraining factor for firms within clusters, since the establishment of an efficient information flow may limit the firms capacity to obtain monopoly profits from the development of innovations. Complementing the negative effects originating from the clusters dynamics, some authors also describe agglomeration diseconomies that have a negative impact firms located within clusters. For example, congestion effects (Arthur, 1990), institutional sclerosis (Pouder and John, 1996; Pitelis, 2010), rigidities associated with labour mobility and natural resources (Krugman, 1989) and pollution (Fan and Scott, 2003). This way, the dynamics and performance of a cluster is determined by the interplay between positive and negative externalities observed during the different stages of development that a cluster is expected to pass overtime (Wolter, 2003) Limitations in the Cluster Theory Notwithstanding the advances in the cluster theory some questions still remain insufficiently explored. One of the main limitations observed in the current state of the cluster literature is the lack of comparative perspectives to explain the advantages and disadvantages of clusters relatively to other alternative models of organization of economic activities. In his very novel approach, Pitelis (2010) suggests that any perspective trying to explain clusters in terms of absolute advantages is at the very best incomplete. In this context, Pitelis proposes the comparison of clusters vis-ÃÆ'  -vis to markets and hierarchies in order to understand the reasons and conditions that lead firms to engage in intra-clusters relationships, market operations (outside the cluster) or integrate within the firms hierarchy. In fact it is not necessary a great effort to conclude that most of the cluster theory has been developed following a mono-institutional approach (e.g. Porter, 1990, 1998; Saxe nian, 1994; Rosenfeld, 1998; Swann and Sennett, 1998; Schmitz and Nadvi, 1999), while some few exceptions concentrated on transactions costs (e.g. Fujita and Thisse, 1996; Iammarino and McCann, 2006; Takeda et al., 2008) and knowledge creation efficiency (e.g. Hendry et al., 2000; Tracey and Clark, 2003; Reinau, 2007; Kongmanila and Takahashi, 2009) have been drawn on a comparative approaches between clusters and open-market operations. Assuming the arguments proposed by many scholars that clusters are engines of innovation (Davis, 2006, p. 32), the lack of comparative perspectives do not answer the question why clusters are more efficient than markets or the hierarchy to improve the firms innovative capacity (Pitelis, 2010). Thus, despite the wide number of ramifications observed in the cluster theory such as innovative efficiency, productivity, social capital and social interactions, its explicative power remains almost always restricted

Flying Squirrels Essay examples -- Biology, DNA

Flying squirrels is in subfamily Petauristinae. They are arboreal and nocturnal. They do not actually fly, but glide between trees by a gliding membrane (patagium). This membrane connects the front legs to the back legs (Parr, 2003). In another word, a furry parachute-like membrane stretches from wrist to ankle. Flaps of skin connecting limbs to body provide a wing-like surface. All species have reddish eyeshine, brighter in the large species than the smaller ones which may be quite dim. The subfamily shows severe taxonomic complications, with little agreement among mammalian researchers (Parr, 2003). Giant flying squirrels (Petaurista sp.) have highest diversity in term of richness in population in Southeast Asia. This species is large in size, being on average 422 mm long. The Red Giant Flying Squirrel is believed to mate twice a year and the young are typically born in March or August in litters of 2 - 3 (Parr, 2003). The Indochinese ground squirrel (Menetes berdmorei) is a member of the family Sciuridae. The family has only 29 species of 14 genera in Thailand (Lekagul and McNeely, 1977, 1988; Par, 2003). The characteristics of the Indochinese ground squirrel are black mid-dorsal stripe, two or three black stripes on the sides, and reddish brown fur on the back (Lekagul and McNeely, 1977, 1988; Par, 2003). Identification is more difficult during the dry season, however, when they are much less brightly colored. They have been found throughout Southeast Asia, from the east of Myanmar to Vietnam. As a ground squirrel, it is rarely found on trees, but spends most of the time in the thick underwoods of the rainforests. (Walston and Duckworth, 2008). The sizes of squirrels are variable between species. There are three types of... ...th at least one restriction enzyme and sequencing the ends of the resulting fragments using an Illumina Genome Analyzer in order to sample the genomes of multiple individuals in a population (Baird et al., 2008). The major advantage of RAD is that it gives information for a very large number of loci across the genome, and for the same loci in each individual sampled. The current method for accelerating targeted sequencing from ancient and highly degraded DNA includes the linking of multiplex PCR directly with sample barcoding and high-throughput sequencing. The method creates the chance to generate many kilobases of overlapping sequence data from 31 cave bear (Ursus spelaeus) ancient specimens at the same time (Stiller et al., 2010). It seems likely that in the future high-throughput sequencing technologies will have many advantages for the study of ancient DNA.

Creative Writing (Story beginnings) Essay

A golden haze encircled the angel’s head and its torso glowed dazzling white against the drab dreary wall behind. â€Å"What’s happe†¦Ã¢â‚¬  she willed her mouth to finish the sentence but it wouldn’t obey so she gave up. She fought too against the uplifting force taking her away from the slightly damp pavement but as every ounce of resistance drained out of her limbs, she went limp and was completely at its mercy. The final thought that crossed her mind before it succumbed to the black cloud that eventually engulfed her was that she recognised this angel. * Elizabeth Anne Johnson – Lizzie to her friends – was a beautiful girl. With endless jet-black locks flowing down her back and striking features, she looked straight off a catwalk. Tonight she was wearing her favourite pale pink mini-dress with manicured nails and dainty heels to match; and with her perfect figure, she was more than able to carry it off. A combination of her stunning looks and the confidence she exuded made every head turn when she walked past – a fact of which she was well aware. Lizzie had spent all night in Brighton’s new trendiest nightspot â€Å"Heaven†. The place was heaving with bodies bouncing to the thundering beats pounding out of the state of the art stereo system. They were puppets dancing to the tune of the headphone-wearing master in the glass booth above. Fluffy white clouds were suspended from the ceiling, in keeping with the paradisiacal theme, and the strobe lighting completed the effect. The drinks were flowing and the atmosphere was electric – just how Lizzie liked it – and as she cast her chocolate-brown eyes around the dance floor a wave of euphoria swept over her. She felt as though she was perched on top of the world. Already tonight, she had received fifteen requests to buy her a drink – a record even by her standards – and had accepted only one. This was one more than usual though. She may have seemed like the happy-go-lucky type but appearances can be deceptive and she was quite the opposite. Lizzie, a seasoned partygoer, was extremely cautious, especially after the letters†¦ Nevertheless, against her better judgement, she was drawn in by the hypnotic charms of this blonde-haired stranger and felt powerless to resist. His eyes were bottomless pools of baby blue and he had a passive, peaceful presence – she trusted him immediately and completely. She began chatting to him and it suddenly dawned on her that she was telling her life story to a total stranger but she pushed the thought out of her mind just as quickly as it had surfaced. Besides with his crisp white shirt, soft voice and wide grin, he seemed harmless enough. Chapter One (2) The sun was playing hide and seek behind the rows of trees as Detective Flynn drove up to the Heaton mansion. He was filled with the giddy excitement of a man about to change his life. He knew how lucky he was to be here and that this case could potentially make or break his career. Flynn was extremely tall and so scrawny one feared he might blow over in a sudden gust of wind. Through the flaming red curtains flopping over his forehead, intense blue eyes peered out inquisitively. As the mansion came into view for the first time he was awestruck. Beyond the wrought iron gates, it stood large and handsome. It was a huge stone structure with countless windows glinting in the afternoon sun and set in acres of sprawling grounds, of which every inch was flawless. The only thing blemishing this perfect watercolour was the black and yellow police tape running the length of the building. The old rusty Ford Escort coughed and spluttered to a halt in the immaculate courtyard and with an almighty heave Flynn managed to force the door open. As he stepped out gravel crunched beneath his feet. He was dressed in a pair of old faded ‘Marks and Sparks’ jeans and looking around, was suddenly painfully aware of how old and faded they really were. He was also regretting the rest of his wardrobe choice. His slightly off-white shirt had a ‘straight out of the laundry basket’ look and his black leather loafers hadn’t seen a dab of polish since†¦well ever. Despite this, John Heaton greeted Flynn with a warm friendly handshake. The two had been at school together and even though their lives had taken extremely different paths, they had remained the best of friends. As he was being introduced to Heaton’s wife Claudia, the detective couldn’t help but notice how much his friend had changed. A nervous and slightly awkward teenager, John Heaton had become a confident self-assured 35 year-old. He now spoke with the eloquence and poise that only a multi-billionaire could. He was dripping with expensive designer labels – a far cry from the washed out tee shirts and baggy jeans of his adolescence. Money oozed out of his every pore. One thing, however, had definitely not changed. Observing the dreamy look that descended upon his face as he gazed at his wife, Flynn could tell his old chum was still a sucker for a pretty girl. And this was one pretty girl! 15 years his junior, actress Claudia Gilbert-Heaton was a blonde-haired, blue-eyed beauty. Yet, as she tentatively extended her perfectly manicured hand to shake his, Detective Flynn took an instant disliking to her. Her broad smile was almost condescending and didn’t reach her eyes, which were icy and distant. â€Å"I’m so pleased to finally meet you,† she said, looking him up and down, staring pointedly at the ink stain on his shirt pocket. The disdainful look in her eyes betrayed her words and he could tell she was quite the opposite. The reason for this, he would soon discover†¦ Chapter One (3) It screamed at me. Its waving arms taunted me as they jerked up and down and the smiley face was more of a sneering face. At that moment all I wanted to do was shatter it into a thousand pieces but it was so far away and my legs were still sound asleep. I picked a rolled up sock up off the floor and with all the energy I could muster, sat up and launched it. It hit its intended destination with satisfying thud and mercifully, the screaming desisted. Putting the bright yellow, â€Å"Little Miss Sunshine† alarm clock so far out of reach had been a pre-emptive strike by mother against my Sunday morning lie-in. Ha, I thought, she’ll have to think of something better than that! I managed the beginnings of a triumphant grin before, exhausted from my exertions, I slumped onto the lumpy mattress and slid back into a peaceful slumber. Ten minutes later I heard the sprightly purposeful pounding that could only be her bounding up the stairs. She burst through the door, wearing her mechanical cheery smile. â€Å"Morning love, sleep well? Why aren’t you up yet, I heard the alarm go off ages ago?†Ã¢â‚¬  she asked, ruffling my unruly brown curls. She then marched over to the window, with unnatural liveliness considering the time and spread the curtains wide. â€Å"Oh Mum, it’s too bright,† I mumbled in complaint, raising an arm to shield my bleary eyes from the light. She ignored me. â€Å"I sometimes think you wouldn’t know an early morning if it came up and bit you on the behind. Now get up, I’m sure you’ve plenty of work to do today and we don’t want you falling behind now do we?† she chirped, practically, it seemed, in unison with the birds outside. â€Å"I need sleep,† I whined, yearning for some pity. It didn’t come. â€Å"You shouldn’t let sleep get in the way of things. Heaven knows I don’t; I can’t. What would happen if I did? Nothing would get done around here – that’s what!† she tutted and continued with renewed vigour, â€Å"Goodness, look at the state of this room! I’m sure you’ve forgotten what colour the carpet is! This is not a positive working environment. How on earth can you get anything done in here?† She asked and without pausing for an answer, delved into the abyss that was my bedroom floor. She began sorting tidying and organising like an unstoppable whirlwind of efficiency, her neat blonde bob bouncing up and down. I merely lounged on the bed and watched on in amazement. Within minutes she had transformed the cluttered chaotic mess into a tidy, orderly bedroom. When she finished, she stood up, brushed some imaginary specks of dirt from her skirt and staring at my sprawled out figure, flashed me the look. Oh no, I groaned inwardly. It was the I-am-so-disappointed-you-didn’t-turn-out-more-like-me look. This look was always followed by a stream of criticisms, of which most, to be fair, were usually quite accurate. I sighed and braced myself for the oncoming tirade. Literary Analysis of Story Beginning (1) When writing my own story opening, I tried to use techniques that would make the reader want to read on. For example, I described the main character’s appearance in detail so that the reader would be able to form a mental picture of her. Just from the first few paragraphs, the reader knows that she is â€Å"a beautiful girl† with â€Å"endless jet black locks† and â€Å"chocolate brown eyes†. The effect of this is to make the reader relate to her with empathy rather than objectivity because they feel they know her. I also tried to show her personality was sweet and kind. Her clothes and shoes are â€Å"powder-pink† and â€Å"dainty†. I also mentioned that she â€Å"seemed like the happy-go-lucky type†. I did this so the reader would like her and be affected by anything that may happen to her. I included her full name â€Å"Elizabeth Anne Johnson† so that the reader would feel like they were getting a complete picture of her. However, for the rest of the opening, I referred to her as Lizzie. This created a bond between the reader and the character because she is â€Å"Lizzie to her friends† so the reader feels like her friend. It is written in the 3rd person narrative so the reader can get a full overview of all the events in the story. The narrative structure deviates. This creates suspense, as there is no development of the action in the first paragraph in the rest of the opening. I purposely created a huge contrast between the eerie and spooky first paragraph and the rest of the opening, which seems like an ordinary night out, by using varying degrees of character and event description. In the first paragraph I did not use any description at all and just used non-specific terms like â€Å"she†. This was to create mystery and apprehension. In sharp contrast to this, I fully described character and events in the rest of the story. I began with telling the reader her full name so they felt they were being formally introduced. I then went on to describe her appearance, clothes what she is doing: â€Å"tonight she was wearing†¦Ã¢â‚¬  â€Å"She had spent all night†¦Ã¢â‚¬  because I did none of this in the first paragraph. I did however make some links. For example, in the first paragraph, the words â€Å"angel†, â€Å"uplifting† and â€Å"glowed† are used. In the rest of the opening, the words â€Å"Heaven†, â€Å"fluffy white clouds† and â€Å"euphoria† are used. This is to create a link between the two parts of the story and establish an ongoing theme of heaven and the supernatural. I also used a sense of vulnerability to link the two main characters. With the girl in the first paragraph it is obvious. I used carefully chosen vocabulary. â€Å"She willed her mouth†¦it wouldn’t obey† shows that she isn’t even in control of her own body. â€Å"She fought to against the uplifting force†¦was completely at its mercy†, â€Å"her mind†¦succumbed to the black cloud that eventually engulfed her†. Also the word succumbed is quite passive. However the vulnerability in Lizzie’s character is subtler. At the end, she is â€Å"drawn in† by the stranger and feels â€Å"powerless to resist†. This links Lizzie and the girl but also â€Å"the angel† and â€Å"the stranger† because they hold the power in the respective relationships. I think the links make the reader want to read on because it’s like giving them some pieces of a puzzle. They can see some of the picture so they read on so they can find the rest of it. To create further curiosity, the phrase â€Å"especially after the letters†¦Ã¢â‚¬  is not explained at any point in the opening, forcing the reader to form their own opinion. The fact that she was â€Å"extremely cautious especially after the letters† makes the letters seem sinister and let the reader know they were a cause for concern. I used ellipsis at the end so show it is an unfinished thought and an unanswered question. I carefully chose vocabulary to foreshadow dramatic events. For example, ‘on top of the world’ is a well-known phrase, which means in a position of great happiness or success. However I used the phrase â€Å"perched on top of the world† in my story opening. The word perched suggests instability and precariousness so implies that her happiness may be short lived. I also used the progression of time to create effect. The story begins with the girl trying to speak and then finally collapsing â€Å"†¦she willed her mouth to finish the sentence but it wouldn’t obey†¦succumbed to the black cloud that was threatening to engulf her† and then goes to a lively vibrant scene. I did this so the scene would seem like a flashback or a dream – as we know the main character is unconscious. The strobe lighting in the scene adds to the dream-like quality. I tried to create an image of the setting (the club) being beautiful and pure. I did this by calling it â€Å"heaven† and using description like â€Å"fluffy white clouds†. I then used words like â€Å"heaving with bodies† â€Å"thundering beats† and â€Å"pounding† when describing the people and what they are doing to create a contrast. I did this to imply that clubbing itself is innocent enough but the people make it dangerous. I used alliteration in several places for effect. â€Å"†¦drab dreary wall† emphasises how dull and grey the wall in contrast â€Å"dazzling white† of the angel, to to make it stand out more. In â€Å"bodies all bouncing to the thundering beat†, the ‘b’ sound is repeated to try and mirror the beat of the music. I used the phrases â€Å"bottomless pools of baby blue† and â€Å"passive, peaceful presence† because they are quite soft sounds and I wanted to make the stranger seem calm and therefore contrast with the setting, which is â€Å"electric†. I used a metaphor â€Å"They were puppets dancing to the tune of the headphone-wearing master in the glass booth above† because it emphasises the submissive nature of the clubbers and the idea of a person wielding power over someone else. The issue of power is explored in many different parts of the story. I also used repetition. The word seemed is used at the end the last paragraph. â€Å"She may have seemed like the happy-go-lucky type but appearances can be deceptive and she was quite the opposite† and â€Å"he seemed harmless enough†. This is to suggest that just because the stranger seems harmless he â€Å"may be quite the opposite† and to foreshadow him doing something harmful in the future. I put it in italics both times to add emphasis and draw the reader’s attention to it. In conclusion, I think the techniques I used were effective because there are unanswered questions right at the beginning, which are never answered and this appeals the curiosity of the reader, making them want to read on.

Madagascar essays

Madagascar essays Madagascar is a less popular covered subject in most geography textbooks, so I have set out on an internet, and encyclopedia journey in hopes of learning more about the publicity deprived section of Africa. In my research I have found coverage on: Madagascars geographic location, commodities and crops, agricultural, attributes, popular religious practices, and native languages spoken throughout the area. Throughout the repot I will touch on each topic, in hope of gaining more knowledge and insight. To start I will give a brief background of Madagascar followed by an in-depth look into Madagascars important facts. Madagascar is Formerly an independent kingdom, Madagascar became a French colony in 1896, but regained its independence in 1960. During 1992-93, free presidential and National Assembly elections were held, ending 17 years of single-party rule. In 1997, in the second presidential race, Didier RATSIRAKA, the leader during the 1970s and 1980s, was returned to the presidency. The 2001 presidential election was contested between the followers of Didier RATSIRAKA and Marc RAVALOMANANA, nearly causing secession of half of the country. In April 2002, the High Constitutional Court announced RAVALOMANANA the winner. Madagascars geographic location lies on the southern-eastern part of Africa, it is the closet island bordering Africa. Its geographic similarity resembles, Sicily to Italy. Its location is in the middle of the Indian Ocean, in Africa its closet neighbor is Mozambique; in which, it is directly east of. Madagascar is slightly less than double the size of Arizona. The Climate is Tropical along coast, temperate inland, arid in the south. Its terrain is: narrow coastal plains, high plateaus, and mountains in the center. Madagascars Elevation extremes go as the following: Lowest point = the Indian ocean at 0 meters. The highest point: Maromokotro at: 2,876 meters. The m...

Example Sentences of the English Verb Put

Example Sentences of the English Verb Put Learning irregular verb tenses can be difficult, and requires  putting a lot of time and effort into studying. This page provides example sentences of the verb put in all tenses including active and passive forms, as well as conditional and modal forms. Once youve reviewed all the examples, put your knowledge to the test with a quiz! All Forms of Put Base Form put / Past Simple put / Past Participle put / Gerund putting Present Simple He puts on his clothes before he has breakfast. Present Simple Passive The paper is put onto the porch by the paperboy. Present Continuous We are putting on a show this evening. Present Continuous Passive A show is being put on by the students this evening. Present Perfect Have you put on weight? Present Perfect Passive Has the exhibit been put up yet? Present Perfect Continuous We have been putting together the project all morning long. Past Simple They put us up last weekend. Past Simple Passive We were put up last weekend by the Smiths. Past Continuous We were putting on some music when he walked into the room. Past Continuous Passive Some music was being put on when he walked into the room. Past Perfect She had put on some weight before moving to Paris. Past Perfect Passive Jack had been put up by his friends before he moved in with me. Past Perfect Continuous We had been putting together the report for two hours when he finally arrived. Future (will) She will put Jack up for the weekend. Future (will) passive Jack will be put up by Jane for the weekend. Future (going to) I am going to put on some weight this summer. Future (going to) passive Some money is going to be put aside for the show. Future Continuous We will be putting the final touches on the project this time tomorrow. Future Perfect By the time you arrive I will have put everything together. Future Possibility She might put you up for the night. Real Conditional If she puts on some weight, she will go on a diet. Unreal Conditional If she put on some weight, she would go on a diet. Past Unreal Conditional If she had put on some weight, she would have gone on a diet. Present Modal She should put that book back. Past Modal She must have put on some weight. Quiz: Conjugate With Put Use the verb to put to conjugate the following sentences. Quiz answers are below. In some cases, more than one answer may be correct. They _____ us up last weekend.A show _____ on by the students right now.She _____ Jack up for the weekend.If she _____ on some weight, she will go on a diet.We _____ up last weekend by the Smiths.He _____ on his clothes before he has breakfast._____ the exhibit _____ up yet?The paper _____ onto the porch by the paperboy.If she _____ on some weight, she would go on a diet.Some money _____ aside for the show. Thats the plan. Quiz Answers putis being putwill putputsputputsHas been putis putputis going to be put