24 resultados para Eutrophication. Ecological modeling. Eutrophication model. Top-down control

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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Constraints are widely present in the flight control problems: actuators saturations or flight envelope limitations are only some examples of that. The ability of Model Predictive Control (MPC) of dealing with the constraints joined with the increased computational power of modern calculators makes this approach attractive also for fast dynamics systems such as agile air vehicles. This PhD thesis presents the results, achieved at the Aerospace Engineering Department of the University of Bologna in collaboration with the Dutch National Aerospace Laboratories (NLR), concerning the development of a model predictive control system for small scale rotorcraft UAS. Several different predictive architectures have been evaluated and tested by means of simulation, as a result of this analysis the most promising one has been used to implement three different control systems: a Stability and Control Augmentation System, a trajectory tracking and a path following system. The systems have been compared with a corresponding baseline controller and showed several advantages in terms of performance, stability and robustness.

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Mental retardation in Down syndrome (DS) has been imputed to the decreased brain volume, which is evident starting from the early phases of development. Recent studies in a widely used mouse model of DS, the Ts65Dn mouse, have shown that neurogenesis is severely impaired during the early phases of brain development, suggesting that this defect may be a major determinant of brain hypotrophy and mental retardation in individuals with DS. Recently, it has been found that in the cerebellum of Ts65Dn mice there is a defective responsiveness to Sonic Hedgehog (Shh), a potent mitogen that controls cell division during brain development, suggesting that failure of Shh signaling may underlie the reduced proliferation potency in DS. Based on these premises, we sought to identify the molecular mechanisms underlying derangement of the Shh pathway in neural precursor cells (NPCs) from Ts65Dn mice. We found that the expression levels of the Shh receptor Patched1 (Ptch1) were increased compared to controls both at the RNA and protein level. Partial silencing of Ptch1 expression in trisomic NPCs restored cell proliferation, indicating that proliferation impairment was due to Ptch1 overexpression. We further found that the overexpression of Ptch1 in trisomic NPCs is related to increased levels of AICD, a transcription-promoting fragment of amyloid precursor protein (APP). Increased AICD binding to the Ptch1 promoter favored its acetylated status, thus enhancing Ptch1 expression. Taken together, these data provide novel evidence that Ptch1 over expression underlies derangement of the Shh pathway in trisomic NPCs, with consequent proliferation impairment. The demonstration that Ptch1 over expression in trisomic NPCs is due to an APP fragment provides a link between this trisomic gene and the defective neuronal production that characterizes the DS brain.

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Down syndrome (DS) is a genetic pathology characterized by brain hypotrophy and severe cognitive disability. Although defective neurogenesis is an important determinant of cognitive impairment, a severe dendritic pathology appears to be an equally important factor. It is well established that serotonin plays a pivotal role both on neurogenesis and dendritic maturation. Since the serotonergic system is profoundly altered in the DS brain, we wondered whether defects in the hippocampal development can be rescued by treatment with fluoxetine, a selective serotonin reuptake inhibitor and a widely used antidepressant drug. A previous study of our group showed that fluoxetine fully restores neurogenesis in the Ts65Dn mouse model of DS and that this effect is accompanied by a recovery of memory functions. The goal of the current study was to establish whether fluoxetine also restores dendritic development and maturation. In mice aged 45 days, treated with fluoxetine in the postnatal period P3-P15, we examined the dendritic arbor of newborn and mature granule cells of the dentate gyrus (DG). The granule cells of trisomic mice had a severely hypotrophic dendritic arbor, fewer spines and a reduced innervation than euploid mice. Treatment with fluoxetine fully restored all these defects. Moreover the impairment of excitatory and inhibitory inputs to CA3 pyramidal neurons was fully normalized in treated trisomic mice, indicating that fluoxetine can rescue functional connectivity between the DG and CA3. The widespread beneficial effects of fluoxetine on the hippocampal formation suggest that early treatment with fluoxetine can be a suitable therapy, possibly usable in humans, to restore the physiology of the hippocampal networks and, hence, memory functions. These findings may open the way for future clinical trials in children and adolescents with DS.

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Study Objectives. The use of mouse models in sleep apnea research is limited by the belief that central (CSA) but not obstructive sleep apneas (OSA) occur in rodents. With this study we wanted to develop a protocol to look for the presence of OSAs in wild-type mice and, then, to apply it to a mouse model of Down Syndrome (DS), a human pathology characterized by a high incidence of OSAs. Methods. Nine C57Bl/6J wild-type mice were implanted with electrodes for electroencephalography (EEG), neck electromyography (nEMG), diaphragmatic activity (DIA) and then placed in a whole-body-plethysmographic (WBP) chamber for 8h during the resting (light) phase to simultaneously record sleep and breathing activity. The concomitant analysis of WBP and DIA signals allowed the discrimination between CSA and OSA. The same protocol was then applied to 12 Ts65Dn mice (a validated model of DS) and 14 euploid controls. Results. OSAs represented about half of the apneic events recorded during rapid-eye-movement sleep (REMS) in each experimental group while almost only CSAs were found during non-REMS. Ts65Dn mice had similar rate of apneic events than euploid controls but a significantly higher occurrence of OSAs during REMS. Conclusions. We demonstrated for the first time that mice physiologically exhibit both CSAs and OSAs and that the latter are more prevalent in the Ts65Dn mouse model of DS. These findings indicate that mice can be used as a valid tool to accelerate the comprehension of the pathophysiology of all kind of sleep apnea and for the development of new therapeutical approaches to contrast these respiratory disorders.

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In the last decades, global food supply chains had to deal with the increasing awareness of the stakeholders and consumers about safety, quality, and sustainability. In order to address these new challenges for food supply chain systems, an integrated approach to design, control, and optimize product life cycle is required. Therefore, it is essential to introduce new models, methods, and decision-support platforms tailored to perishable products. This thesis aims to provide novel practice-ready decision-support models and methods to optimize the logistics of food items with an integrated and interdisciplinary approach. It proposes a comprehensive review of the main peculiarities of perishable products and the environmental stresses accelerating their quality decay. Then, it focuses on top-down strategies to optimize the supply chain system from the strategical to the operational decision level. Based on the criticality of the environmental conditions, the dissertation evaluates the main long-term logistics investment strategies to preserve products quality. Several models and methods are proposed to optimize the logistics decisions to enhance the sustainability of the supply chain system while guaranteeing adequate food preservation. The models and methods proposed in this dissertation promote a climate-driven approach integrating climate conditions and their consequences on the quality decay of products in innovative models supporting the logistics decisions. Given the uncertain nature of the environmental stresses affecting the product life cycle, an original stochastic model and solving method are proposed to support practitioners in controlling and optimizing the supply chain systems when facing uncertain scenarios. The application of the proposed decision-support methods to real case studies proved their effectiveness in increasing the sustainability of the perishable product life cycle. The dissertation also presents an industry application of a global food supply chain system, further demonstrating how the proposed models and tools can be integrated to provide significant savings and sustainability improvements.

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In recent years, there has been exponential growth in using virtual spaces, including dialogue systems, that handle personal information. The concept of personal privacy in the literature is discussed and controversial, whereas, in the technological field, it directly influences the degree of reliability perceived in the information system (privacy as trust). This work aims to protect the right to privacy on personal data (GDPR, 2018) and avoid the loss of sensitive content by exploring sensitive information detection (SID) task. It is grounded on the following research questions: (RQ1) What does sensitive data mean? How to define a personal sensitive information domain? (RQ2) How to create a state-of-the-art model for SID?(RQ3) How to evaluate the model? RQ1 theoretically investigates the concepts of privacy and the ontological state-of-the-art representation of personal information. The Data Privacy Vocabulary (DPV) is the taxonomic resource taken as an authoritative reference for the definition of the knowledge domain. Concerning RQ2, we investigate two approaches to classify sensitive data: the first - bottom-up - explores automatic learning methods based on transformer networks, the second - top-down - proposes logical-symbolic methods with the construction of privaframe, a knowledge graph of compositional frames representing personal data categories. Both approaches are tested. For the evaluation - RQ3 we create SPeDaC, a sentence-level labeled resource. This can be used as a benchmark or training in the SID task, filling the gap of a shared resource in this field. If the approach based on artificial neural networks confirms the validity of the direction adopted in the most recent studies on SID, the logical-symbolic approach emerges as the preferred way for the classification of fine-grained personal data categories, thanks to the semantic-grounded tailor modeling it allows. At the same time, the results highlight the strong potential of hybrid architectures in solving automatic tasks.

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Asset Management (AM) is a set of procedures operable at the strategic-tacticaloperational level, for the management of the physical assets performance, associated risks and costs within its whole life-cycle. AM combines the engineering, managerial and informatics points of view. In addition to internal drivers, AM is driven by the demands of customers (social pull) and regulators (environmental mandates and economic considerations). AM can follow either a top-down or a bottom-up approach. Considering rehabilitation planning at the bottom-up level, the main issue would be to rehabilitate the right pipe at the right time with the right technique. Finding the right pipe may be possible and practicable, but determining the timeliness of the rehabilitation and the choice of the techniques adopted to rehabilitate is a bit abstruse. It is a truism that rehabilitating an asset too early is unwise, just as doing it late may have entailed extra expenses en route, in addition to the cost of the exercise of rehabilitation per se. One is confronted with a typical Hamlet-isque dilemma to repair or not to repair; or put in another way, to replace or not to replace. The decision in this case is governed by three factors, not necessarily interrelated quality of customer service, costs and budget in the life cycle of the asset in question. The goal of replacement planning is to find the juncture in the assets life cycle where the cost of replacement is balanced by the rising maintenance costs and the declining level of service. System maintenance aims at improving performance and maintaining the asset in good working condition for as long as possible. Effective planning is used to target maintenance activities to meet these goals and minimize costly exigencies. The main objective of this dissertation is to develop a process-model for asset replacement planning. The aim of the model is to determine the optimal pipe replacement year by comparing, temporally, the annual operating and maintenance costs of the existing asset and the annuity of the investment in a new equivalent pipe, at the best market price. It is proposed that risk cost provide an appropriate framework to decide the balance between investment for replacing or operational expenditures for maintaining an asset. The model describes a practical approach to estimate when an asset should be replaced. A comprehensive list of criteria to be considered is outlined, the main criteria being a vis- vis between maintenance and replacement expenditures. The costs to maintain the assets should be described by a cost function related to the asset type, the risks to the safety of people and property owing to declining condition of asset, and the predicted frequency of failures. The cost functions reflect the condition of the existing asset at the time the decision to maintain or replace is taken: age, level of deterioration, risk of failure. The process model is applied in the wastewater network of Oslo, the capital city of Norway, and uses available real-world information to forecast life-cycle costs of maintenance and rehabilitation strategies and support infrastructure management decisions. The case study provides an insight into the various definitions of asset lifetime service life, economic life and physical life. The results recommend that one common value for lifetime should not be applied to the all the pipelines in the stock for investment planning in the long-term period; rather it would be wiser to define different values for different cohorts of pipelines to reduce the uncertainties associated with generalisations for simplification. It is envisaged that more criteria the municipality is able to include, to estimate maintenance costs for the existing assets, the more precise will the estimation of the expected service life be. The ability to include social costs enables to compute the asset life, not only based on its physical characterisation, but also on the sensitivity of network areas to social impact of failures. The type of economic analysis is very sensitive to model parameters that are difficult to determine accurately. The main value of this approach is the effort to demonstrate that it is possible to include, in decision-making, factors as the cost of the risk associated with a decline in level of performance, the level of this deterioration and the assets depreciation rate, without looking at age as the sole criterion for making decisions regarding replacements.

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A prevalent claim is that we are in knowledge economy. When we talk about knowledge economy, we generally mean the concept of Knowledge-based economy indicating the use of knowledge and technologies to produce economic benefits. Hence knowledge is both tool and raw material (peoples skill) for producing some kind of product or service. In this kind of environment economic organization is undergoing several changes. For example authority relations are less important, legal and ownership-based definitions of the boundaries of the firm are becoming irrelevant and there are only few constraints on the set of coordination mechanisms. Hence what characterises a knowledge economy is the growing importance of human capital in productive processes (Foss, 2005) and the increasing knowledge intensity of jobs (Hodgson, 1999). Economic processes are also highly intertwined with social processes: they are likely to be informal and reciprocal rather than formal and negotiated. Another important point is also the problem of the division of labor: as economic activity becomes mainly intellectual and requires the integration of specific and idiosyncratic skills, the task of dividing the job and assigning it to the most appropriate individuals becomes arduous, a supervisory problem (Hogdson, 1999) emerges and traditional hierarchical control may result increasingly ineffective. Not only specificity of know how makes it awkward to monitor the execution of tasks, more importantly, top-down integration of skills may be difficult because the nominal supervisors will not know the best way of doing the job or even the precise purpose of the specialist job itself and the worker will know better (Hogdson,1999). We, therefore, expect that the organization of the economic activity of specialists should be, at least partially, self-organized. The aim of this thesis is to bridge studies from computer science and in particular from Peer-to-Peer Networks (P2P) to organization theories. We think that the P2P paradigm well fits with organization problems related to all those situation in which a central authority is not possible. We believe that P2P Networks show a number of characteristics similar to firms working in a knowledge-based economy and hence that the methodology used for studying P2P Networks can be applied to organization studies. Three are the main characteristics we think P2P have in common with firms involved in knowledge economy: - Decentralization: in a pure P2P system every peer is an equal participant, there is no central authority governing the actions of the single peers; - Cost of ownership: P2P computing implies shared ownership reducing the cost of owing the systems and the content, and the cost of maintaining them; - Self-Organization: it refers to the process in a system leading to the emergence of global order within the system without the presence of another system dictating this order. These characteristics are present also in the kind of firm that we try to address and that why we have shifted the techniques we adopted for studies in computer science (Marcozzi et al., 2005; Hales et al., 2007 [39]) to management science.

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Nanoscience is an emerging and fast-growing field of science with the aim of manipulating nanometric objects with dimension below 100 nm. Top down approach is currently used to build these type of architectures (e.g microchips). The miniaturization process cannot proceed indefinitely due to physical and technical limitations. Those limits are focusing the interest on the bottom-up approach and construction of nano-objects starting from nano-bricks like atoms, molecules or nanocrystals. Unlike atoms, molecules can be fully programmable and represent the best choice to build up nanostructures. In the past twenty years many examples of functional nano-devices able to perform simple actions have been reported. Nanocrystals which are often considered simply nanostructured materials, can be active part in the development of those nano-devices, in combination with functional molecules. The object of this dissertation is the photophysical and photochemical investigation of nano-objects bearing molecules and semiconductor nanocrystals (QDs) as components. The first part focuses on the characterization of a bistable rotaxane. This study, in collaboration with the group of Prof. J.F. Stoddart (Northwestern University, Evanston, Illinois, USA) who made the synthesis of the compounds, shows the ability of this artificial machine to operate as bistable molecular-level memory under kinetic control. The second part concerns the study of the surface properties of luminescent semiconductor nanocrystals (QDs) and in particular the effect of acid and base on the spectroscopical properties of those nanoparticles. In this section is also reported the work carried out in the laboratory of Prof H. Mattoussi (Florida State University, Tallahassee, Florida, USA), where I developed a novel method for the surface decoration of QDs with lipoic acid-based ligands involving the photoreduction of the di-thiolane moiety.

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People are daily faced with intertemporal choice, i.e., choices differing in the timing of their consequences, frequently preferring smaller-sooner rewards over larger-delayed ones, reflecting temporal discounting of the value of future outcomes. This dissertation addresses two main goals. New evidence about the neural bases of intertemporal choice is provided. Following the disruption of either the medial orbitofrontal cortex or the insula, the willingness to wait for larger-delayed outcomes is affected in odd directions, suggesting the causal involvement of these areas in regulating the value computation of rewards available with different timings. These findings were also supported by a reported imaging study. Moreover, this dissertation provides new evidence about how temporal discounting can be modulated at a behavioral level through different manipulations, e.g., allowing individuals to think about the distant time, pairing rewards with aversive events, or changing their perceived spatial position. A relationship between intertemporal choice, moral judgements and aging is also discussed. All these findings link together to support a unitary neural model of temporal discounting according to which signals coming from several cortical (i.e., medial orbitofrontal cortex, insula) and subcortical regions (i.e., amygdala, ventral striatum) are integrated to represent the subjective value of both earlier and later rewards, under the top-down regulation of dorsolateral prefrontal cortex. The present findings also support the idea that the process of outcome evaluation is strictly related to the ability to pre-experience and envision future events through self-projection, the anticipation of visceral feelings associated with receiving rewards, and the psychological distance from rewards. Furthermore, taking into account the emotions and the state of arousal at the time of decision seems necessary to understand impulsivity associated with preferring smaller-sooner goods in place of larger-later goods.

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The thesis work deals with topics that led to the development of innovative control-oriented models and control algorithms for modern gasoline engines. Knock in boosted spark ignition engines is the widest topic discussed in this document because it remains one of the most limiting factors for maximizing combustion efficiency in this kind of engine. First chapter is thus focused on knock and a wide literature review is proposed to summarize the preliminary knowledge that even represents the background and the reference for discussed activities. Most relevant results achieved during PhD course in the field of knock modelling and control are then presented, describing every control-oriented model that led to the development of an adaptive model-based combustion control system. The complete controller has been developed in the context of the collaboration with Ferrari GT and it allowed to completely redefine the knock intensity evaluation as well as the combustion phase control. The second chapter is focused on the activity related to a prototyping Port Water Injection system that has been developed and tested on a turbocharged spark ignition engine, within the collaboration with Magneti Marelli. Such system and the effects of injected water on the combustion process were then modeled in a 1-D simulation environment (GT Power). Third chapter shows the development and validation of a control-oriented model for the real-time calculation of exhaust gas temperature that represents another important limitation to the performance increase in modern boosted engines. Indeed, modelling of exhaust gas temperature and thermocouple behavior are themes that play a key role in the optimization of combustion and catalyst efficiency.

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This Thesis is composed of a collection of works written in the period 2019-2022, whose aim is to find methodologies of Artificial Intelligence (AI) and Machine Learning to detect and classify patterns and rules in argumentative and legal texts. We define our approach hybrid, since we aimed at designing hybrid combinations of symbolic and sub-symbolic AI, involving both top-down structured knowledge and bottom-up data-driven knowledge. A first group of works is dedicated to the classification of argumentative patterns. Following the Waltonian model of argument and the related theory of Argumentation Schemes, these works focused on the detection of argumentative support and opposition, showing that argumentative evidences can be classified at fine-grained levels without resorting to highly engineered features. To show this, our methods involved not only traditional approaches such as TFIDF, but also some novel methods based on Tree Kernel algorithms. After the encouraging results of this first phase, we explored the use of a some emerging methodologies promoted by actors like Google, which have deeply changed NLP since 2018-19 i.e., Transfer Learning and language models. These new methodologies markedly improved our previous results, providing us with best-performing NLP tools. Using Transfer Learning, we also performed a Sequence Labelling task to recognize the exact span of argumentative components (i.e., claims and premises), thus connecting portions of natural language to portions of arguments (i.e., to the logical-inferential dimension). The last part of our work was finally dedicated to the employment of Transfer Learning methods for the detection of rules and deontic modalities. In this case, we explored a hybrid approach which combines structured knowledge coming from two LegalXML formats (i.e., Akoma Ntoso and LegalRuleML) with sub-symbolic knowledge coming from pre-trained (and then fine-tuned) neural architectures.

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Although the prominent role of neural oscillations in perception and cognition has been continuously investigated, some critical questions remain unanswered. My PhD thesis was aimed at addressing some of them. First, can we dissociate oscillatory underpinnings of perceptual accuracy and subjective awareness? Current work would strongly suggest that this dissociation can be drawn. While the fluctuations in alpha-amplitude decide perceptual bias and metacognitive abilities, the speed of alpha activity (i.e., alpha-frequency) dictates sensory sampling, shaping perceptual accuracy. Second, how are these oscillatory mechanisms integrated during attention? The obtained results indicate that a top-down visuospatial mechanism modulates neural assemblies in visual areas via oscillatory re-alignment and coherence in the alpha/beta range within the fronto-parietal brain network. These perceptual predictions are reflected in the retinotopically distributed posterior alpha-amplitude, while perceptual accuracy is explained by the higher alpha-frequency at the to-be-attended location. Finally, sensory input, elaborated via fast gamma oscillations, is linked to specific phases of this slower activity via oscillatory nesting, enabling integration of the feedback-modulated oscillatory activity with sensory information. Third, how can we relate this oscillatory activity to other neural markers of behaviour (i.e., event-related potentials)? The obtained results favour the oscillatory model of ERP genesis, where alpha-frequency shapes the latency of early evoked-potentials, namely P1, with both neural indices being related to perceptual accuracy. On the other hand, alpha-amplitude dictates the amplitude of later P3 evoked-response, whereas both indices shape subjective awareness. Crucially, by combining different methodological approaches, including neurostimulation (TMS) and neuroimaging (EEG), current work identified these oscillatory-behavior links as causal and not just as co-occurring events. Current work aimed at ameliorating the use of the TMS-EEG approach by explaining inter-individual differences in the stimulation outcomes, which could be proven crucial in the way we design entrainment experiments and interpret the results in both research and clinical settings.

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The globalization process of the last twenty years has changed the world through international flows of people, policies and practices. International cooperation to development is a part of that process and brought International Organizations (IOs) and Non Governmental Organizations (NGOs) from the West to the rest of the world. In my thesis I analyze the Italian NGOs that worked in Bosnia Herzegovina (BH) to understand which development projects they realized and how they faced the ethnic issue that characterized BH. I consider the relation shaped between Italian NGOs and Bosnian civil society as an object of ethnic interests. In BH, once part of former Yugoslavia, the transition from the communist regime to a democratic country has not been completed. BHs social conditions are characterized by strong ethnic divisions. The legacy of the early 1990s crisis was a phenomenon of ethnic identities created before the war and that still endure today. The Dayton Peace Agreement signed in 1995 granted the peace and reinforced the inter-ethnic hate between the newly recognized three principal ethnicities: Serbs, Croats and Bosniak. Through the new constitution, the institutions were characterized by division at every level, from the top to the bottom of society. Besides it was the first constitution ever written and signed outside the own country; that was the root of the state of exception that characterized BH. Thus ethnic identities culture survived through the international political involvement. At the same time ethnic groups that dominated the political debate clashed with the international organizations democratic purpose to build a multicultural and democratic state. Ethnic and also religious differences were the instruments for a national statement that might cause the transition and development projects failure. Fifteen years later social fragmentation was still present and it established an atmosphere of daily cultural violence. Civil society suffered this condition and attended to recreate the ethnic fragmentation in every day life. Some cities became physically divided and other cities dont tolerated the minority presence. In rural areas, the division was more explicit, from village to village, without integration. In my speech, the anthropology for development the derivative study from applied anthropology constitutes the point of view that I used to understand how ethnic identities still influenced the development process in BH. I done ethnographic research about the Italian cooperation for development projects that were working there in 2007. The target of research were the Italian NGOs that created a relation with Bosnian civil society; they were almost twenty divided in four main field of competences: institutional building, education, agriculture and democratization. I assumed that NGOs work needed a deep study because the bottom of society is the place where people could really change their representation and behavior. Italian NGOs operated in BH with the aim of creating sustainable development. They found cultural barricade that both institutions and civil society erected when development projects have been applied. Ethnic and religious differences were stressed to maintain boundaries and fragmented power. Thus NGOs tried to negotiate development projects by social integration. I found that NGOs worked among ethnic groups by pursuing a new integration. They often gained success among people; civil society was ready to accept development projects and overcome differences. On the other hand NGOs have been limited by political level that sustained the ethnic talk and by their representation of Bosnian issue. Thus development policies have been impeded by ethnic issue and by cooperation practices established on a top down perspective. Paradoxically, since international community has approved the political ethnic division within DPA, then the willing of development followed by funding NGOs cooperation projects was not completely successful.