Miracle-dz/UniFAR-FTUs huggingface dataset:
Stochastic Optimal Design for Unknown Linear Networked Control System Zero-sum Games via Q-Learning

In this paper, stochastic optimal strategy for unknown linear networked control system (NCS) quadratic zero-sum games related to which satisfies a corresponding Game Theoretic Riccati equation (GRE). An adaptive estimator (AE) is proposed to learn the Q-function online and value and policy iterations are not needed unlike in traditional ADP schemes. Update laws for tuning the unknown parameters of adaptive estimator (AE) are derived. Lyapunov theory is used to show that all signals are asymptotic stable (AS) and that the approximated control and disturbance signals converge to optimal control and disturbance inputs. Simulation results are included to show the effectiveness of the scheme.
An adaptive link caching scheme for on-demand routing in MANETs

With on-demand routing protocols for mobile ad hoc networks (MANETs), for example, dynamic source routing (DSR), a source node tries to find a route to the destination node only when it has a packet addressed to that destination node. And the source node can find a route either from its own route cache or by initializing a route discovery. To reduce the traffic generated by such route discoveries, caching of routing information is necessary. And in the design of caching schemes, cache timeout (i.e., the time period that a link would stay in the cache) is a critical parameter. However, only a few works have been done on how to set it. In this paper, we propose a new link caching scheme with adaptive timeouts. In this scheme, the cache timeout of a link is decided based on the estimation of the link's lifetime. Simulation results show that the proposed scheme can adapt to scenario changes and hence improve the performance of on-demand routing for MANETs.
Assessment of the acoustic shear velocity in SiO2 and Mo layers for acoustic reflectors

We present a method to assess the shear acoustic velocity in SiO2 and Mo sputtered films, which are materials commonly used as low and high acoustic impedance layers in the acoustic reflectors of solidly mounted resonators. The method consists in the analysis of the frequency response of AlN-based resonators operating in the shear mode using acoustic mirrors specifically designed to obtain a half-wavelength resonance in the layer under study, the thickness of which is thickened to achieve a significant signal. After measuring the thickness and mass densities of all the layers composing the resonator, the fitting by Mason's model of the electrical response in a wide frequency range provides accurate values of both the longitudinal and the shear mode velocities. The shear acoustic velocities of porous SiO2 and Mo are 3150 m/s and 3450 m/s respectively. This method allows assessing the shear mode acoustic velocity of any material by adequately designing the test structure.
ACOUSTIC EMISSION MONITORING OF BUCKLING BEHAVIOUR IN IMPACT-DAMAGED COMPOSITE PLATES.

In composite structures subjected to compressive loads, impact damage is a major problem as it promotes delamination, which severely reduces the buckling strength. The problem is further complicated by the fact that internal defects cannot be detected by a visual inspection. In order to assess the effect on a component of any damage it is desirable to determine the behaviour of a defect during the loading of the component. In this work, epoxy glass fibre specimens were damaged at various levels using a drop impact technique. All specimens were tested to failure under a buckling load and monitored by Acoustic Emission (AE). Test data show that the compression strength of composite structures is significantly reduced by low-speed damage even at levels where damage can not be detected by visual inspection Defects in the panels due to impact damage were successfully located by Acoustic Emission using a linear time-of arrival technique to an accuracy of 30 mm. It was possible to identify damage using AE even where the damage was not discernibly visible. A relationship was established between AE parameters, such as peak amplitude, counts and rise time, and levels of damage in the specimens.
Plus disease in retinopathy of prematurity: development of composite images by quantification of expert opinion.

PURPOSE To demonstrate a methodology for generating composite wide-angle images of plus disease in retinopathy of prematurity (ROP), using quantitative analysis of expert opinions. METHODS Thirty-four wide-angle retinal images were independently interpreted by 22 ROP experts as "plus" or "not plus. " All images were processed by the computer-based Retinal Image multiScale Analysis (RISA) system to calculate two parameters: arterial integrated curvature (AIC) and venous diameter (VD). Using a reference standard defined by expert consensus, sensitivity and specificity curves were calculated by varying the diagnostic cutoffs for AIC and VD. From these curves, individual vessels from multiple images were identified with particular diagnostic cutoffs, and were combined into composite wide-angle images using graphics-editing software. RESULTS The values associated with 75% underdiagnosis of true plus disease (i.e., 25% sensitivity cutoff) were AIC 0.061 and VD 4.272, the values associated with 50% underdiagnosis of true plus disease (i.e., a 50% sensitivity cutoff) were AIC 0.049 and VD 4.088, and the values associated with 25% underdiagnosis of true plus disease (i.e., 75% sensitivity cutoff) were AIC 0.042 and VD 3.795. Composite wide-angle images were generated by identifying and combining individual vessels with these characteristics. CONCLUSIONS Computer-based image analysis permits quantification of retinal vascular features, and a spectrum of abnormalities is seen in ROP. Selection of appropriate vessels from multiple images can produce composite plus disease images corresponding to expert opinions. This method may be useful for educational purposes, and for development of future disease definitions based on objective, quantitative principles.
Systematic development of optimized SNEDDS of artemether with improved biopharmaceutical and antimalarial potential

Abstract The current studies entail systematic development of self-nanoemulsifying drug delivery systems (SNEDDS) containing medium-chain triglycerides (MCTs) and long-chain triglycerides (LCTs) for augmenting the biopharmaceutical performance of artemether. Equilibrium solubility and pseudoternary phase diagram studies facilitated selection of Captex 355 and Ethyl oleate as MCTs and LCTs, and Cremophor RH 40 and Tween 80 as surfactants, while Transcutol HP as cosolvent for formulating the SNEDDS. Systematic optimization was performed employing the Box–Behnken design taking concentrations of lipid, surfactant and cosolvent as the critical material attributes (CMAs), while evaluating for globule size, emulsification time, dissolution efficiency and permeation as the critical quality attributes (CQAs). In situ single pass intestinal perfusion (SPIP) studies in Wistar rats substantiated significant augmentation in the absorption (5- to 6-fold) and permeation (4- to 5-fold) parameters from the optimized MCT and LCT-SNEDDS vis-à-vis the pure drug. In vivo pharmacodynamic studies in Plasmodium berghi infected laca mice exhibited superior reduction in the levels of percent parasitemia, SGOT, SGPT and bilirubin, followed by higher survival rate of the animals by optimized MCT-SNEDDS followed by LCT-SNEDDS vis-à-vis the pure drug, which was subsequently ratified through histopathological examination of liver tissues. Overall, the studies construed successful development of the optimized SNEDDS of artemether with distinctly improved biopharmaceutical and antimalarial potential.
Fuzzy controlled genetic algorithm for environmental/economic dispatch with shunt FACTS devices

In recent year and with the growth in electricity demand, environmental considerations have become one of the major management concerns. This paper presents an hybrid Genetic Algorithm and Fuzzy Logic rules for solving the economic dispatch problem under constrained emission with multi shunt Flexible AC Transmission Systems (FACTS). The economic dispatch problem is formulated as a nonlinear constrained multi objective optimization problem with both equality and inequality constraints. The problem is decomposed into, the optimal power generation subproblem that is searched by a flexible Genetic Algorithm which crossover and mutation adjusted by Fuzzy practical rules and a simple practical reasoning fuzzy rules designed as a second subproblem to control the reactive power exchanged with the network. The proposed method guarantees the near optimal solution and remarkably reduces the computation time. A global database generated based in reactive index sensitivity (RIS) as a flexible tool to choose economically the size of the shunt FACTS devices. This proposed approach is implemented with Matlab program with various case studies, and compared with conventional method and genetic algorithm (GA). The results show that the approach proposed can converge to optimum solution faster than other methods, and obtains the solution with high accuracy.
The hdrRM Operon of Streptococcus mutans Encodes a Novel Regulatory System for Coordinated Competence Development and Bacteriocin Production

ABSTRACT The Streptococcus mutans hdrRM operon encodes a novel two-gene regulatory system induced by high cell density. Previous studies identified hdrM as the only known negative regulator of competence development in S. mutans. In the present study, we demonstrated that the HdrRM system bypasses the prototypical competence gene regulators ComC and ComDE in the transcriptional regulation of the competence-specific sigma factor comX and the late competence genes. Similarly, the HdrRM system can abrogate the requirement for ComE to produce the bacteriocin mutacin IV. To further probe the regulatory mechanism of hdrRM, we created an hdrR overexpression strain and showed that it could reproduce each of the hdrM competence and mutacin phenotypes, indicating that HdrM acts as a negative regulator of HdrR activity. Using a mutacin IV-luciferase reporter, we also demonstrated that the hdrRM system utilizes the same promoter elements recognized by ComE and thus appears to comprise a novel regulatory pathway parallel to ComCDE.
Two-stage space-time receiver structure for multiuser hybrid mmW massive MIMO systems

This paper considers a hybrid two-stage space-time receiver structure for uplink millimeter wave (mmW) based systems, where the user terminals (UTs) and the base station (BS) are equipped with a large antenna array and the number of radio frequency (RF) chains is lower than the number of antennas. In the first stage the analog transmit and receive beam-formers/precoders are computed for each UT - BS pair considering multi-user interference free links, to maximize the desired signal power for each UT. In the second one, an iterative block space-time equalizer is designed to explicitly remove the multi-user interference. The designed space-time equalizer is optimized by using as a metric the mean square error (MSE) between the transmitted data vector and its estimate after the digital equalizer. Our performance results havye shown that the proposed iterative space-time equalizer outperforms the linear MMSE based receivers for hybrid mmW massive MIMO architectures.
Model-Based Active Learning in Hierarchical Policies

Hierarchical task decompositions play an essential role in the design of complex simulation and decision systems, such as the ones that arise in video games. Game designers find it very natural to adopt a divide-and-conquer philosophy of specifying hierarchical policies, where decision modules can be constructed somewhat independently. The process of choosing the parameters of these modules manually is typically lengthy and tedious. The hierarchical reinforcement learning (HRL) field has produced elegant ways of decomposing policies and value functions using semi-Markov decision processes. However, there is still a lack of demonstrations in larger nonlinear systems with discrete and continuous variables. To narrow this gap between industrial practices and academic ideas, we address the problem of designing efficient algorithms to facilitate the deployment of HRL ideas in more realistic settings. In particular, we propose Bayesian active learning methods to learn the relevant aspects of either policies or value functions by focusing on the most relevant parts of the parameter and state spaces respectively. To demonstrate the scalability of our solution, we have applied it to The Open Racing Car Simulator (TORCS), a 3D game engine that implements complex vehicle dynamics. The environment is a large topological map roughly based on downtown Vancouver, British Columbia. Higher
A method for improving classification reliability of multilayer perceptrons

Criteria for evaluating the classification reliability of a neural classifier and for accordingly making a reject option are proposed. Such an option, implemented by means of two rules which can be applied independently of topology, size, and training algorithms of the neural classifier, allows one to improve the classification reliability. It is assumed that a performance function P is defined which, taking into account the requirements of the particular application, evaluates the quality of the classification in terms of recognition, misclassification, and reject rates. Under this assumption the optimal reject threshold value, determining the best trade-off between reject rate and misclassification rate, is the one for which the function P reaches its absolute maximum. No constraints are imposed on the form of P, but the ones necessary in order that P actually measures the quality of the classification process. The reject threshold is evaluated on the basis of some statistical distributions characterizing the behavior of the classifier when operating without reject option; these distributions are computed once the training phase of the net has been completed. The method has been tested with a neural classifier devised for handprinted and multifont printed characters, by using a database of about 300000 samples. Experimental results are discussed.
Cardiovascular Health Score and the Risk of Cardiovascular Diseases

In 2010 the American Heart Association proposed a definition of ideal health behaviors and health factors to measure cardiovascular health, from which Huffman et al. created the Cardiovascular Health Score (CVH score) to estimate these metrics on an individual level. We performed a prospective cohort study among employees of the Kailuan Group Corporation, who underwent a physical examination in 2006–2007 to investigate the relationship between the CVH score and the risk of cardiovascular disease (CVD). A total of 91,598 individuals free of stroke and myocardial infarction at baseline were included in the final analysis. We calculated baseline CVH score for each metric (poor=0, intermediate=1, ideal=2 points; range=0–14 points for all seven metrics) and categorized them into three groups: inadequate (0–4 points), average (5–9 points), and optimum (10–14 points). Incidence of total number of CVD events, myocardial infarction, and stroke was analyzed among these three groups and each incremental point on the CVH score. During an average 6.81 years of follow-up, there were 3276 CVD events, 2579 strokes and 747 myocardial infarction occurred. After adjusting for several confounding factors, each better health category of the CVH score was associated with reduced odds of 47% for all CVD events, and each point higher on the CVH score was associated with reduced odds of 18%. Similar trends were detected in the risks for myocardial infarction and stroke. A higher CVH score is therefore a protective factor for CVD, myocardial infarction, and stroke.
Phonetic alignment for speech synthesis in under-resourced languages

The rapid development of concatenative speech synthesis systems in resource scarce languages requires an efficient and accurate solution with regard to automated phonetic alignment. However, in this context corpora are often minimally designed due to a lack of resources and expertise necessary for large scale development. Under these circumstances many techniques toward accurate segmentation are not feasible and it is unclear which approaches should be followed. In this paper we investigate this problem by evaluating alignment approaches and demonstrating how these approaches can be applied to limit manual interaction while achieving acceptable alignment accuracy with minimal ideal resources. Index Terms: speech synthesis, phonetic speech segmentation, resource scarce language
Union for the Mediterranean—Pragmatic Multilateralism and the Depoliticization of EU-Middle Eastern Relations

The Union for the Mediterranean (UfM) was launched by French President Nicolas Sarkozy together with 42 European and Middle Eastern state leaders in Paris on July 13, 2008. It was established as an attempt to revitalize the Barcelona Process, but at the same time the founding document stated that the UfM takes ‘into account the shortcomings and difficulties in . multilateral co-operation which the EU has pursued since 1995. ’ The UfM creates a new political and institutional framework for the relationship between the EU and the Middle East. But rather than following the normative, regionalist approach of the Barcelona Declaration, the UfM attaches importance to selected projects, dealing with issues like depollution, infrastructure, civil protection and solar power. These are designed not to cause significant political problems. Thus, with the UfM a tendency to a depoliticization of European-Middle Eastern relations seems to be developing. In this sense—and compared to former practices—the UfM apparently represents discontinuation. Yet, at the same time it stands on the shoulders of the Barcelona Process and the European Neighborhood Policy (ENP), and in this way can be seen as part of a continuing political and institutional development. The purpose of this article is to discuss whether it is meaningful to characterize the UfM as a depoliticization of relations in the Mediterranean. A classic line of thought concerning European integration in the second half of the twentieth century claims that in order to defuse the antagonism between France and Germany, it would be necessary to find uncontroversial ways of developing integration, so that future conflicts could be avoided. Jean Monnet and other architects of European integration, having failed to promote direct routes to federalism, found a second-best solution: to integrate the coal and steel sectors. Ernst Haas, in his influential work,
Genomics and proteomics--the way forward.

The Post-Genomic Era is characterized by huge numbers. This will only increase in the future when more will become known about proteins, which not only outnumber the genes, but also can be functionally altered in various ways. These "big numbers" have two consequences. Studies, which were despisingly called Fishing Expeditions only a few years ago are now respectfully dubbed Discovery Science, which answers questions and generate new hypotheses. Secondly, it is not always easy to select the way forward in Genomics and Proteomics. Therefore emerging technologies are updated and the hallmarks of cancer cells briefly discussed. Promising applications for screening/early disease detection, diagnosis and tumour classification, prognostication, predictive response and tailoring therapy are described. Strategic choices as to certain types of study, which diseases or organ sites should be analyzed or techniques used, are mainly political and very much determined by loco-regional and national interests. However, in post-genomic research the following practical points must be considered. To avoid non-informative noise, homogeneous groups (preferably of small lesions) should be analyzed. Adequate sampling will be even more important than in the past to minimize the risk of non-informative benign cells inclusion. Accurate, biologically relevant, well reproducible quantitative morphological information is of the utmost importance to define the lesions, as mixtures of functionally different cells will obscure important signals. RNA and proteins degrade quickly under hypoxic conditions, so that for reliable results the interval between tumour excision and freezing must be minimized and standardized. Promising results must always be independently validated as the use of relatively few patients combined with the enormous number of variables analyzed, carries a serious risk of selection bias and too optimistic results. An integrated collaboration structure of multiple disciplines becomes increasingly important.
A Model of IT-enabled Organizational Integration and Sustained Competitive Advantage

Organizational integration is a phenomenon occurring inexorably in recent years due to rapid advances in IT and intense competition. Past research has found organizational integration, between and within firms, to be positively-related to performance, with IT resources playing a pivotal role in facilitating this trend. In this paper, we argue that IT resources, comprising of IT assets and capabilities, are critical antecedents to organizational integration. We examine the role of service-oriented architecture (SOA) as an IT asset in enabling the integration of organizational resources. As an IT-dependent strategic initiative, IT-enabled organizational integration provides significant barriers to competition and gives rise to sustained competitive advantage. Drawing upon the resource-based theory, we develop a model by conceptualizing both IT assets and IT capabilities as higher-order constructs comprising of IT infrastructure and IT architecture, and IT technical skills and managerial skills respectively. Next, we explore the mediating effects of causal ambiguity to further elucidate the relationship between organizational integration and sustained competitive advantage. Our proposed model provides managers with invaluable insights regarding the nature and application of IT to achieve organizational integration and to sustain their competitive edge in the global marketplace.
Evaluation of Transcendental Functions on Imagine Architecture

The fast and accurate evaluation of transcendental functions (e.g. exp, log, sin, and atan) is quite important in many domains. We implement a software inline function library that can be called from KernelC programming language to compute 8 typical functions on Imagine architecture. By exploiting some of the key features of Imagine architecture, we have been able to provide single precision transcendental functions that are very accurate yet can typically be evaluated to get 16 function values in between 18 and 43 clock cycles. In this paper, we also discuss the algorithms and implementation details of these functions.
Motion Planning for Car-like Robots Using Hierarchical Genetic Algorithms

The problem of optimal motion generation is still a major focus of research in mobile robotics. Although many solutions have been proposed, it has always had to take into account new factors and constraints that may be related either to the environment (obstacles) or the robot itself. For a car-like vehicle, nonholonomic kinematic constraints force the robot to follow a trajectory imposed by the angle of its steering wheels. In this paper, we present an algorithm for motion planning in order to generate optimal movements for a nonholonomic mobile robot using a probabilistic network method (PRM) associated with two artificial intelligence techniques: the A * algorithm to search for the shortest path and genetic algorithms for optimization. We used the Hierarchical Genetic Algorithms (AGH) that played on two criteria: collision and path length to calculate the optimal path without collision. One of the key points of our approach lies in the evaluation of the individuals; we used the principle of artificial potential field that has yielded interesting results in terms of quality and optimization of trajectories.