917 resultados para Distributed Generator, Network Loss, Primal-Dual Interior Point Algorithm, Sitting and Sizing


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Selective oxidation is one of the simplest functionalization methods and essentially all monomers used in manufacturing artificial fibers and plastics are obtained by catalytic oxidation processes. Formally, oxidation is considered as an increase in the oxidation number of the carbon atoms, then reactions such as dehydrogenation, ammoxidation, cyclization or chlorination are all oxidation reactions. In this field, most of processes for the synthesis of important chemicals used vanadium oxide-based catalysts. These catalytic systems are used either in the form of multicomponent mixed oxides and oxysalts, e.g., in the oxidation of n-butane (V/P/O) and of benzene (supported V/Mo/O) to maleic anhydride, or in the form of supported metal oxide, e.g., in the manufacture of phthalic anhydride by o-xylene oxidation, of sulphuric acid by oxidation of SO2, in the reduction of NOx with ammonia and in the ammoxidation of alkyl aromatics. In addition, supported vanadia catalysts have also been investigated for the oxidative dehydrogenation of alkanes to olefins , oxidation of pentane to maleic anhydride and the selective oxidation of methanol to formaldehyde or methyl formate [1]. During my PhD I focused my work on two gas phase selective oxidation reactions. The work was done at the Department of Industrial Chemistry and Materials (University of Bologna) in collaboration with Polynt SpA. Polynt is a leader company in the development, production and marketing of catalysts for gas-phase oxidation. In particular, I studied the catalytic system for n-butane oxidation to maleic anhydride (fluid bed technology) and for o-xylene oxidation to phthalic anhydride. Both reactions are catalyzed by systems based on vanadium, but catalysts are completely different. Part A is dedicated to the study of V/P/O catalyst for n-butane selective oxidation, while in the Part B the results of an investigation on TiO2-supported V2O5, catalyst for o-xylene oxidation are showed. In Part A, a general introduction about the importance of maleic anhydride, its uses, the industrial processes and the catalytic system are reported. The reaction is the only industrial direct oxidation of paraffins to a chemical intermediate. It is produced by n-butane oxidation either using fixed bed and fluid bed technology; in both cases the catalyst is the vanadyl pyrophosphate (VPP). Notwithstanding the good performances, the yield value didn’t exceed 60% and the system is continuously studied to improve activity and selectivity. The main open problem is the understanding of the real active phase working under reaction conditions. Several articles deal with the role of different crystalline and/or amorphous vanadium/phosphorous (VPO) compounds. In all cases, bulk VPP is assumed to constitute the core of the active phase, while two different hypotheses have been formulated concerning the catalytic surface. In one case the development of surface amorphous layers that play a direct role in the reaction is described, in the second case specific planes of crystalline VPP are assumed to contribute to the reaction pattern, and the redox process occurs reversibly between VPP and VOPO4. Both hypotheses are supported also by in-situ characterization techniques, but the experiments were performed with different catalysts and probably under slightly different working conditions. Due to complexity of the system, these differences could be the cause of the contradictions present in literature. Supposing that a key role could be played by P/V ratio, I prepared, characterized and tested two samples with different P/V ratio. Transformation occurring on catalytic surfaces under different conditions of temperature and gas-phase composition were studied by means of in-situ Raman spectroscopy, trying to investigate the changes that VPP undergoes during reaction. The goal is to understand which kind of compound constituting the catalyst surface is the most active and selective for butane oxidation reaction, and also which features the catalyst should possess to ensure the development of this surface (e.g. catalyst composition). On the basis of results from this study, it could be possible to project a new catalyst more active and selective with respect to the present ones. In fact, the second topic investigated is the possibility to reproduce the surface active layer of VPP onto a support. In general, supportation is a way to improve mechanical features of the catalysts and to overcome problems such as possible development of local hot spot temperatures, which could cause a decrease of selectivity at high conversion, and high costs of catalyst. In literature it is possible to find different works dealing with the development of supported catalysts, but in general intrinsic characteristics of VPP are worsened due to the chemical interaction between active phase and support. Moreover all these works deal with the supportation of VPP; on the contrary, my work is an attempt to build-up a V/P/O active layer on the surface of a zirconia support by thermal treatment of a precursor obtained by impregnation of a V5+ salt and of H3PO4. In-situ Raman analysis during the thermal treatment, as well as reactivity tests are used to investigate the parameters that may influence the generation of the active phase. Part B is devoted to the study of o-xylene oxidation of phthalic anhydride; industrially, the reaction is carried out in gas-phase using as catalysts a supported system formed by V2O5 on TiO2. The V/Ti/O system is quite complex; different vanadium species could be present on the titania surface, as a function of the vanadium content and of the titania surface area: (i) V species which is chemically bound to the support via oxo bridges (isolated V in octahedral or tetrahedral coordination, depending on the hydration degree), (ii) a polymeric species spread over titania, and (iii) bulk vanadium oxide, either amorphous or crystalline. The different species could have different catalytic properties therefore changing the relative amount of V species can be a way to optimize the catalytic performances of the system. For this reason, samples containing increasing amount of vanadium were prepared and tested in the oxidation of o-xylene, with the aim of find a correlations between V/Ti/O catalytic activity and the amount of the different vanadium species. The second part deals with the role of a gas-phase promoter. Catalytic surface can change under working conditions; the high temperatures and a different gas-phase composition could have an effect also on the formation of different V species. Furthermore, in the industrial practice, the vanadium oxide-based catalysts need the addition of gas-phase promoters in the feed stream, that although do not have a direct role in the reaction stoichiometry, when present leads to considerable improvement of catalytic performance. Starting point of my investigation is the possibility that steam, a component always present in oxidation reactions environment, could cause changes in the nature of catalytic surface under reaction conditions. For this reason, the dynamic phenomena occurring at the surface of a 7wt% V2O5 on TiO2 catalyst in the presence of steam is investigated by means of Raman spectroscopy. Moreover a correlation between the amount of the different vanadium species and catalytic performances have been searched. Finally, the role of dopants has been studied. The industrial V/Ti/O system contains several dopants; the nature and the relative amount of promoters may vary depending on catalyst supplier and on the technology employed for the process, either a single-bed or a multi-layer catalytic fixed-bed. Promoters have a quite remarkable effect on both activity and selectivity to phthalic anhydride. Their role is crucial, and the proper control of the relative amount of each component is fundamental for the process performance. Furthermore, it can not be excluded that the same promoter may play different role depending on reaction conditions (T, composition of gas phase..). The reaction network of phthalic anhydride formation is very complex and includes several parallel and consecutive reactions; for this reason a proper understanding of the role of each dopant cannot be separated from the analysis of the reaction scheme. One of the most important promoters at industrial level, which is always present in the catalytic formulations is Cs. It is known that Cs plays an important role on selectivity to phthalic anhydride, but the reasons of this phenomenon are not really clear. Therefore the effect of Cs on the reaction scheme has been investigated at two different temperature with the aim of evidencing in which step of the reaction network this promoter plays its role.

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Many research fields are pushing the engineering of large-scale, mobile, and open systems towards the adoption of techniques inspired by self-organisation: pervasive computing, but also distributed artificial intelligence, multi-agent systems, social networks, peer-topeer and grid architectures exploit adaptive techniques to make global system properties emerge in spite of the unpredictability of interactions and behaviour. Such a trend is visible also in coordination models and languages, whenever a coordination infrastructure needs to cope with managing interactions in highly dynamic and unpredictable environments. As a consequence, self-organisation can be regarded as a feasible metaphor to define a radically new conceptual coordination framework. The resulting framework defines a novel coordination paradigm, called self-organising coordination, based on the idea of spreading coordination media over the network, and charge them with services to manage interactions based on local criteria, resulting in the emergence of desired and fruitful global coordination properties of the system. Features like topology, locality, time-reactiveness, and stochastic behaviour play a key role in both the definition of such a conceptual framework and the consequent development of self-organising coordination services. According to this framework, the thesis presents several self-organising coordination techniques developed during the PhD course, mainly concerning data distribution in tuplespace-based coordination systems. Some of these techniques have been also implemented in ReSpecT, a coordination language for tuple spaces, based on logic tuples and reactions to events occurring in a tuple space. In addition, the key role played by simulation and formal verification has been investigated, leading to analysing how automatic verification techniques like probabilistic model checking can be exploited in order to formally prove the emergence of desired behaviours when dealing with coordination approaches based on self-organisation. To this end, a concrete case study is presented and discussed.

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With the goal of studying ML along the RGB, mid-IR observations of a carefully selected sample of 17 Galactic globular clusters (GGCs) with different metallicity and horizontal branch (HB) morphology have been secured with IRAC on board Spitzer: a global sample counting about 8000 giant has been obtained. Suitable complementary photometry in the optical and near-IR has been also secured in order to properly characterize the stellar counterparts to the Spitzer sources and their photospheric parameters. Stars with color (i.e. dust) excess have been identified, their likely circumstellar emission quantified and modelled, and empirical estimates of mass loss rates and timescales obtained. We find that mass loss rates increases with increasing stellar luminosity and decreasing metallicity. For a given luminosity, we find that ML rates are systematically higher than the prediction by extrapolating the Reimers law. CMDs constructed from ground based near-IR and IRAC bands show that at a given luminosity some stars have dusty envelopes and others do not. From this, we deduce that the mass loss is episodic and is ``on'' for some fraction of the time. The total mass lost on the RGB can be easily computed by multiplying ML rates by the ML timescales and integrating over the evolutionary timescale. The average total mass lost moderately increases with increasing metallicity, and for a given metallicity is systematically higher in clusters with extended blue HB.

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In this work we are concerned with the analysis and numerical solution of Black-Scholes type equations arising in the modeling of incomplete financial markets and an inverse problem of determining the local volatility function in a generalized Black-Scholes model from observed option prices. In the first chapter a fully nonlinear Black-Scholes equation which models transaction costs arising in option pricing is discretized by a new high order compact scheme. The compact scheme is proved to be unconditionally stable and non-oscillatory and is very efficient compared to classical schemes. Moreover, it is shown that the finite difference solution converges locally uniformly to the unique viscosity solution of the continuous equation. In the next chapter we turn to the calibration problem of computing local volatility functions from market data in a generalized Black-Scholes setting. We follow an optimal control approach in a Lagrangian framework. We show the existence of a global solution and study first- and second-order optimality conditions. Furthermore, we propose an algorithm that is based on a globalized sequential quadratic programming method and a primal-dual active set strategy, and present numerical results. In the last chapter we consider a quasilinear parabolic equation with quadratic gradient terms, which arises in the modeling of an optimal portfolio in incomplete markets. The existence of weak solutions is shown by considering a sequence of approximate solutions. The main difficulty of the proof is to infer the strong convergence of the sequence. Furthermore, we prove the uniqueness of weak solutions under a smallness condition on the derivatives of the covariance matrices with respect to the solution, but without additional regularity assumptions on the solution. The results are illustrated by a numerical example.

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Motivated by the need to understand which are the underlying forces that trigger network evolution, we develop a multilevel theoretical and empirically testable model to examine the relationship between changes in the external environment and network change. We refer to network change as the dissolution or replacement of an interorganizational tie, adding also the case of the formation of new ties with new or preexisting partners. Previous research has paid scant attention to the organizational consequences of quantum change enveloping entire industries in favor of an emphasis on continuous change. To highlight radical change we introduce the concept of environmental jolt. The September 11 terrorist attacks provide us with a natural experiment to test our hypotheses on the antecedents and the consequences of network change. Since network change can be explained at multiple levels, we incorporate firm-level variables as moderators. The empirical setting is the global airline industry, which can be regarded as a constantly changing network of alliances. The study reveals that firms react to environmental jolts by forming homophilous ties and transitive triads as opposed to the non jolt periods. Moreover, we find that, all else being equal, firms that adopt a brokerage posture will have positive returns. However, we find that in the face of an environmental jolt brokerage relates negatively to firm performance. Furthermore, we find that the negative relationship between brokerage and performance during an environmental jolt is more significant for larger firms. Our findings suggest that jolts are an important predictor of network change, that they significantly affect operational returns and should be thus incorporated in studies of network dynamics.

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Untersucht werden in der vorliegenden Arbeit Versionen des Satzes von Michlin f¨r Pseudodiffe- u rentialoperatoren mit nicht-regul¨ren banachraumwertigen Symbolen und deren Anwendungen a auf die Erzeugung analytischer Halbgruppen von solchen Operatoren auf vektorwertigen Sobo- levr¨umen Wp (Rn

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Modern software systems, in particular distributed ones, are everywhere around us and are at the basis of our everyday activities. Hence, guaranteeing their cor- rectness, consistency and safety is of paramount importance. Their complexity makes the verification of such properties a very challenging task. It is natural to expect that these systems are reliable and above all usable. i) In order to be reliable, compositional models of software systems need to account for consistent dynamic reconfiguration, i.e., changing at runtime the communication patterns of a program. ii) In order to be useful, compositional models of software systems need to account for interaction, which can be seen as communication patterns among components which collaborate together to achieve a common task. The aim of the Ph.D. was to develop powerful techniques based on formal methods for the verification of correctness, consistency and safety properties related to dynamic reconfiguration and communication in complex distributed systems. In particular, static analysis techniques based on types and type systems appeared to be an adequate methodology, considering their success in guaranteeing not only basic safety properties, but also more sophisticated ones like, deadlock or livelock freedom in a concurrent setting. The main contributions of this dissertation are twofold. i) On the components side: we design types and a type system for a concurrent object-oriented calculus to statically ensure consistency of dynamic reconfigurations related to modifications of communication patterns in a program during execution time. ii) On the communication side: we study advanced safety properties related to communication in complex distributed systems like deadlock-freedom, livelock- freedom and progress. Most importantly, we exploit an encoding of types and terms of a typical distributed language, session π-calculus, into the standard typed π- calculus, in order to understand their expressive power.

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During the perinatal period the developing brain is most vulnerable to inflammation. Prenatal infection or exposure to inflammatory factors can have a profound impact on fetal neurodevelopment with long-term neurological deficits, such as cognitive impairment, learning deficits, perinatal brain damage and cerebral palsy. Inflammation in the brain is characterized by activation of resident immune cells, especially microglia and astrocytes whose activation is associated with a variety of neurodegenerative disorders like Alzheimer´s disease and Multiple sclerosis. These cell types express, release and respond to pro-inflammatory mediators such as cytokines, which are critically involved in the immune response to infection. It has been demonstrated recently that cytokines also directly influence neuronal function. Glial cells are capable of releaseing the pro-inflammatory cytokines MIP-2, which is involved in cell death, and tumor necrosis factor alpha (TNFalpha), which enhances excitatory synaptic function by increasing the surface expression of AMPA receptors. Thus constitutively released TNFalpha homeostatically regulates the balance between neuronal excitation and inhibition in an activity-dependent manner. Since TNFalpha is also involved in neuronal cell death, the interplay between neuronal activity MIP-2 and TNFalpha may control the process of cell death and cell survival in developing neuronal networks. An increasing body of evidence suggests that neuronal activity is important in the regulation of neuronal survival during early development, e.g. programmed cell death (apoptosis) is augmented when neuronal activity is blocked. In our study we were interested on the impact of inflammation on neuronal activity and cell survival during early cortical development. To address this question, we investigated the impact of inflammation on neuronal activity and cell survival during early cortical development in vivo and in vitro. Inflammation was experimentally induced by application of the endotoxin lipopolysaccharide (LPS), which initiates a rapid and well-characterized immune response. I studied the consequences of inflammation on spontaneous neuronal network activity and cell death by combining electrophysiological recordings with multi-electrode arrays and quantitative analyses of apoptosis. In addition, I used a cytokine array and antibodies directed against specific cytokines allowing the identification of the pro-inflammatory factors, which are critically involved in these processes. In this study I demonstrated a direct link between inflammation-induced modifications in neuronal network activity and the control of cell survival in a developing neuronal network for the first time. Our in vivo and in vitro recordings showed a fast LPS-induced reduction in occurrence of spontaneous oscillatory activity. It is indicated that LPS-induced inflammation causes fast release of proinflammatory factors which modify neuronal network activity. My experiments with specific antibodies demonstrate that TNFalpha and to a lesser extent MIP-2 seem to be the key mediators causing activity-dependent neuronal cell death in developing brain. These data may be of important clinical relevance, since spontaneous synchronized activity is also a hallmark of the developing human brain and inflammation-induced alterations in this early network activity may have a critical impact on the survival of immature neurons.

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Escherichia coli kann C4-Dicarboxylate sowohl unter aeroben als auch unter anaeroben Bedingungen zur Energiekonservierung nutzen. Die Synthese der beteiligten Transporter und Enzyme wird auf der Transkriptionsebene durch das Zweikomponentensystem DcuSR reguliert. DcuS ist der Sensor für C4-Dicarboxylate. Der Antwortregulator DcuR wird von DcuS aktiviert und induziert die Expression des C4-Dicarboxylat-Transporters DctA unter aeroben Verhältnissen. Anaerob verstärkt DcuSR die Expression des Fumarat/Succinat-Antiporters DcuB, der Fumarase B und der Fumaratreduktase FrdABCD. DctA und DcuB agieren als Co-Sensoren von DcuS und üben einen negativen Effekt auf die Genexpression von dctA bzw. dcuB aus.rnIn dieser Arbeit wurde die Funktion von DctA und DcuB als Co-Sensoren von DcuS untersucht. Sowohl für DcuB als auch für DctA wurde eine direkte Protein-Protein-Interaktion mit DcuS über ein bakterielles Two-Hybrid System nachgewiesen. DcuS bildete ein Transporter-Sensor-Cluster mit DctA und DcuB. C-terminale Verkürzung und die Mutagenese einzelner Aminosäuren der C-terminalen Helix 8b von DctA führten zu einem Verlust der Interaktion mit DcuS. Mit dieser Interaktion gingen sowohl die regulatorische Funktion als auch die Transportfunktion der Punktmutante DctA-L414A verloren. Ein Verlust der Interaktion wurde ebenfalls zwischen einer konstitutiv aktiven DcuS-Mutante und wildtypischem DctA beobachtet. Ebenso zeigte sich eine partielle Reduktion der Interaktion von DcuS mit DctA, wenn DcuS nach der zweiten Transmembranhelix verkürzt wurde. Die Interaktion zwischen DcuS und DctA wurde durch den Effektor Fumarat modifiziert, ging aber nicht komplett verloren.rnDctA konnte in verschiedenen Plasmidsystemen überproduziert werden und bildete Homotrimere. Die Topologie von DctA wurde mit experimentellen und in silico Methoden aufgeklärt. DctA ähnelt der Struktur und Topologie des Aminosäuretransporters Glt aus Pyrococcus horikoshii. DctA besitzt acht Transmembranhelices mit einem cytosolischen N- und C-Terminus sowie zwei Haarnadelschleifen. Die Substratbindung findet höchstwahrscheinlich in den Haarnadelschleifen statt und der Transport erfolgt nach dem „alternating access“ Modell.rnAußerdem wurde die Funktion des Transporters YfcC untersucht. Das Gen yfcC wurde mit Schlüsselgenen des Acetatstoffwechsels co-transkribiert. In yfcC-Deletionsstämmen zeigte sich ein stammspezifischer Defekt bei Wachstum mit Acetat und Transport von Acetat.

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In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

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Drug-drug interaction between statins metabolised by cytochrome P450 3A4 and clopidogrel have been claimed to attenuate the inhibitory effect of clopidogrel. However, published data regarding this drug-drug interaction are controversial. We aimed to determine the effect of fluvastatin and atorvastatin on the inhibitory effect of dual antiplatelet therapy with acetylsalicylic acid (ASA) and clopidogrel. One hundred one patients with symptomatic stable coronary artery disease undergoing percutaneous coronary intervention and drug-eluting stent implantation were enrolled in this prospective randomised study. After an interval of two weeks under dual antiplatelet therapy with ASA and clopidogrel, without any lipid-lowering drug, 87 patients were randomised to receive a treatment with either fluvastatin 80 mg daily or atorvastatin 40 mg daily in addition to the dual antiplatelet therapy for one month. Platelet aggregation was assessed using light transmission aggregometry and whole blood impedance platelet aggregometry prior to randomisation and after one month of receiving assigned statin and dual antiplatelet treatment. Platelet function assessment after one month of statin and dual antiplatelet therapy did not show a significant change in platelet aggregation from 1st to 2nd assessment for either statin group. There was also no difference between atorvastatin and fluvastatin treatment arms. In conclusion, neither atorvastatin 40 mg daily nor fluvastatin 80 mg daily administered in combination with standard dual antiplatelet therapy following coronary drug-eluting stent implantation significantly interfere with the antiaggregatory effect of ASA and clopidogrel.

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This study examines the links between human perceptions, cognitive biases and neural processing of symmetrical stimuli. While preferences for symmetry have largely been examined in the context of disorders such as obsessive-compulsive disorder and autism spectrum disorders, we examine various these phenomena in non-clinical subjects and suggest that such preferences are distributed throughout the typical population as part of our cognitive and neural architecture. In Experiment 1, 82 young adults reported on the frequency of their obsessive-compulsive spectrum behaviors. Subjects also performed an emotional Stroop or variant of an Implicit Association Task (the OC-CIT) developed to assess cognitive biases for symmetry. Data not only reveal that subjects evidence a cognitive conflict when asked to match images of positive affect with asymmetrical stimuli, and disgust with symmetry, but also that their slowed reaction times when asked to do so were predicted by reports of OC behavior, particularly checking behavior. In Experiment 2, 26 participants were administered an oddball Event-Related Potential task specifically designed to assess sensitivity to symmetry as well as the OC-CIT. These data revealed that reaction times on the OC-CIT were strongly predicted by frontal electrode sites indicating faster processing of an asymmetrical stimulus (unparallel lines) relative to a symmetrical stimulus (parallel lines). The results point to an overall cognitive bias linking disgust with asymmetry and suggest that such cognitive biases are reflected in neural responses to symmetrical/asymmetrical stimuli.

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A new 2-D hydrophone array for ultrasound therapy monitoring is presented, along with a novel algorithm for passive acoustic mapping using a sparse weighted aperture. The array is constructed using existing polyvinylidene fluoride (PVDF) ultrasound sensor technology, and is utilized for its broadband characteristics and its high receive sensitivity. For most 2-D arrays, high-resolution imagery is desired, which requires a large aperture at the cost of a large number of elements. The proposed array's geometry is sparse, with elements only on the boundary of the rectangular aperture. The missing information from the interior is filled in using linear imaging techniques. After receiving acoustic emissions during ultrasound therapy, this algorithm applies an apodization to the sparse aperture to limit side lobes and then reconstructs acoustic activity with high spatiotemporal resolution. Experiments show verification of the theoretical point spread function, and cavitation maps in agar phantoms correspond closely to predicted areas, showing the validity of the array and methodology.

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A central design challenge facing network planners is how to select a cost-effective network configuration that can provide uninterrupted service despite edge failures. In this paper, we study the Survivable Network Design (SND) problem, a core model underlying the design of such resilient networks that incorporates complex cost and connectivity trade-offs. Given an undirected graph with specified edge costs and (integer) connectivity requirements between pairs of nodes, the SND problem seeks the minimum cost set of edges that interconnects each node pair with at least as many edge-disjoint paths as the connectivity requirement of the nodes. We develop a hierarchical approach for solving the problem that integrates ideas from decomposition, tabu search, randomization, and optimization. The approach decomposes the SND problem into two subproblems, Backbone design and Access design, and uses an iterative multi-stage method for solving the SND problem in a hierarchical fashion. Since both subproblems are NP-hard, we develop effective optimization-based tabu search strategies that balance intensification and diversification to identify near-optimal solutions. To initiate this method, we develop two heuristic procedures that can yield good starting points. We test the combined approach on large-scale SND instances, and empirically assess the quality of the solutions vis-à-vis optimal values or lower bounds. On average, our hierarchical solution approach generates solutions within 2.7% of optimality even for very large problems (that cannot be solved using exact methods), and our results demonstrate that the performance of the method is robust for a variety of problems with different size and connectivity characteristics.

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PURPOSE: To prospectively evaluate whether intravenous morphine co-medication improves bile duct visualization of dual-energy CT-cholangiography. MATERIALS AND METHODS: Forty potential donors for living-related liver transplantation underwent CT-cholangiography with infusion of a hepatobiliary contrast agent over 40min. Twenty minutes after the beginning of the contrast agent infusion, either normal saline (n=20 patients; control group [CG]) or morphine sulfate (n=20 patients; morphine group [MG]) was injected. Forty-five minutes after initiation of the contrast agent, a dual-energy CT acquisition of the liver was performed. Applying dual-energy post-processing, pure iodine images were generated. Primary study goals were determination of bile duct diameters and visualization scores (on a scale of 0 to 3: 0-not visualized; 3-excellent visualization). RESULTS: Bile duct visualization scores for second-order and third-order branch ducts were significantly higher in the MG compared to the CG (2.9±0.1 versus 2.6±0.2 [P<0.001] and 2.7±0.3 versus 2.1±0.6 [P<0.01], respectively). Bile duct diameters for the common duct and main ducts were significantly higher in the MG compared to the CG (5.9±1.3mm versus 4.9±1.3mm [P<0.05] and 3.7±1.3mm versus 2.6±0.5mm [P<0.01], respectively). CONCLUSION: Intravenous morphine co-medication significantly improved biliary visualization on dual-energy CT-cholangiography in potential donors for living-related liver transplantation.