Miracle-dz/UniFAR-FTUs huggingface dataset:
Extension of local linear controllers to global piecewise affine controllers for uncertain non-linear systems

A two-step controller synthesis method is proposed in this article for a class of uncertain non-linear systems described by piecewise affine differential inclusions. In the first step, a robust linear controller is designed for the linear differential inclusion that describes the dynamics of the non-linear system close to the equilibrium point. In the second step, a stabilising piecewise affine controller is designed that coincides with the linear controller in a region around the equilibrium point. The proposed method has two objectives: global stability and local performance. It thus enables us to use well-known techniques in linear control design for local stability and performance while delivering a global piecewise affine controller that is guaranteed to stabilise the non-linear system. To construct the required theoretical framework, a stability theorem for non-smooth Lyapunov functions is presented and proved. The new method will be applied to two examples.
Different Fluorophore Labeling Strategies and Designs Affect Millisecond Kinetics of DNA Hairpins

Changes in molecular conformations are one of the major driving forces of complex biological processes. Many studies based on single-molecule techniques have shed light on conformational dynamics and contributed to a better understanding of living matter. In particular, single-molecule FRET experiments have revealed unprecedented information at various time scales varying from milliseconds to seconds. The choice and the attachment of fluorophores is a pivotal requirement for single-molecule FRET experiments. One particularly well-studied millisecond conformational change is the opening and closing of DNA hairpin structures. In this study, we addressed the influence of base- and terminal-labeled fluorophores as well as the fluorophore DNA interactions on the extracted kinetic information of the DNA hairpin. Gibbs free energies varied from ∆G0 = −3.6 kJ/mol to ∆G0 = −0.2 kJ/mol for the identical DNA hairpin modifying only the labeling scheme and design of the DNA sample. In general, the base-labeled DNA hairpin is significantly destabilized compared to the terminal-labeled DNA hairpin and fluorophore DNA interactions additionally stabilize the closed state of the DNA hairpin. Careful controls and variations of fluorophore attachment chemistry are essential for a mostly undisturbed measurement of the underlying energy landscape of biomolecules.
Improving performance of MapReduce framework on InterCloud by avoiding transmission of unnecessary data

Recently, cloud computing and MapReduce have become attractive computing environments as the need for data processing rapidly increases. This inflation in the demand for resources led to the introduction of InterCloud, which provisions resources from two or more cloud service providers. However, when MapReduce applications run on InterCloud environments, they underperform contrary to our expectations. In this paper, we suggest a technique that mitigates the performance problem of MapReduce applications on InterCloud environments. As shown in our preliminary results, our technique leads to up to five times better performance in InterCloud environments.
Robust speech recognition using articulatory information

Current automatic speech recognition systems make use of a single source of information about their input, viz. a preprocessed form of the acoustic speech signal, which encodes the time-frequency distribution of signal energy. The goal of this thesis is to investigate the benefits of integrating articulatory information into state-of-the art speech recognizers, either as a genuine alternative to standard acoustic representations, or as an additional source of information. Articulatory information is represented in terms of abstract articulatory classes or "features", which are extracted from the speech signal by means of statistical classifiers. A higher-level classifier then combines the scores for these features and maps them to standard subword unit probabilities. The main motivation for this approach is to improve the robustness of speech recognition systems in adverse acoustic environments, such as background noise. Typically, recognition systems show a sharp decline of performance under these conditions. We argue and demonstrate empirically that the articulatory feature approach can lead to greater robustness by enhancing the accuracy of the bottom-up acoustic modeling component in a speech recognition system. The second focus point of this thesis is to provide detailed analyses of the different types of information provided by the acoustic and the articulatory representations, respectively, and to develop strategies to optimally combine them. To this effect we investigate combination methods at the levels of feature extraction, subword unit probability estimation, and word recognition. The feasibility of this approach is demonstrated with respect to two different speech recognition tasks. The first of these is an American English corpus of telephone-bandwidth speech; the recognition domain is continuous numbers. The second is a German database of studio-quality speech consisting of spontaneous dialogues. In both cases recognition performance will be tested not only under clean acoustic conditions but also under deteriorated conditions.
Automatic predictor generator & behaviour rule extractor - A system proposal

In this paper we present a proposal for a data-mining system deployed as a cloud service which is supposed to be used for a big data analysis. The main purpose of the system is the analysis of a vast number of event logs using means of data aggregation, clustering, classification and prediction. The system is composed of two components implemented as software services. The Automatic Predictor Generator is supposed to provide a meaningful way to aggregate large amounts of data and the Automatic Behavior Rule Extractor deals with proper analysis of these aggregations. Results of the system are the prediction rules usable for support of decision-making and in areas such as management, marketing, customer segmentation, classification, behavior prediction etc.
IDENTIFICATION OF LOCATION USING ROUTING BASED PROTOCOLS

Many problems in Ad-Hoc network is divided as an optimization problem such as consumption in energy, localization, routing, use of nodes in effective way. To solve these problems set of routing algorithm have been developed based on swarm intelligence. Ant colony algorithm is based on the behavior of ants in swarm intelligence. To enhance the communication we use different protocols and also location of the nodes in the cluster is also identified using location based routing protocols.
A Credit-Based Congestion-Aware Incentive Scheme for DTNs

In Delay-Tolerant Networks (DTNs), nodes may be selfish and reluctant to expend their precious resources on forwarding messages for others. Therefore, an incentive scheme is necessary to motivate selfish nodes to cooperatively forward messages. However, the current incentive schemes mainly focus on encouraging nodes to participate in message forwarding, without considering the node congestion problem. When many messages are forwarded to the nodes with high connection degree, these nodes will become congested and deliberately discard messages, which will seriously degrade the routing performance and reduce the benefits of other nodes. To address this problem, we propose a credit-based congestion-aware incentive scheme (CBCAIS) for DTNs. In CBCAIS, a check and punishment mechanism is proposed to prevent forwarding nodes from deliberately discarding message. In addition, a message acceptance selection mechanism is proposed to allow the nodes to decide whether to accept other messages, according to self congestion degree. The experimental results show that CBCAIS can effectively stimulate selfish nodes to cooperatively forward messages, and achieve a higher message delivery ratio with lower overhead ratio, compared with other schemes.
Gender and age affect NK 1 receptors in the human brain – a positron emission tomography study with [ 18 F ] SPARQ

Substance P (SP) is a neurotransmitter and neuromodulator that mediates its effects in the brain predominantly via the neurokinin-1 receptors (NK1Rs). NK1Rs and SP have been shown clinically to be involved in nausea and emesis after chemotherapy (CINV) and have been implicated preclinically in a range of neuropsychiatric disorders but unlike CINV their blockade in these conditions does not have proven clinical value. We investigated whether age and gender affects NK1R binding potential (NK1R-BP; an index of receptor availability) in the living human brain using PET and [18F]SPA-RQ, a highly specific NK1R antagonist. Forty-five healthy volunteers (35 male and 10 female), aged between 19 and 55 years were studied. NK1R-BP was estimated using the simplified reference tissue model with cerebellum as a reference region. A regression analysis indicated that that a loss of NK1R is associated with normal ageing as shown by decreased NK1R-BP (average rate 7% per decade). Statistically significant negative associations between age and NK1R-BP were observed in temporal, parietal and frontal cortex, hippocampus and parahippocampal formation. In addition preliminary data were obtained suggesting possible gender differences in NK1R-BP in the cortex and putamen with females having a lower NK1R-BP. The exact physiological significance of these results remains to be elucidated but conceptually they could be involved in age-related CNS disorders or those with gender differences in prevalence. Received 5 September 2005 ; Reviewed 2 November 2005 ; Revised 25 January 2006 ; Accepted 25 January 2006 ; First published online 30 March 2006
Experimental Removal of Sexual Selection Reverses Intersexual Antagonistic Coevolution and Removes a Reproductive Load Materials and Methods

Although sexual selection can provide benefits to both sexes, it also can be costly because of expanded opportunities for intersexual conf lict. We evaluated the role of sexual selection in a naturally promiscuous species, Drosophila melanogaster. In two replicate populations, sexual selection was removed through enforced monogamous mating with random mate assignment or retained in promiscuous controls. Monogamous mating constrains the reproductive success of mates to be identical, thereby converting prior conf licts between mates into opportunities for mutualism. Random mate assignment removes the opportunity for females to choose beneficial qualities in their mate. The mating treatments were maintained for 47 generations, and evolution was allowed to proceed naturally within the parameters of the design. In the monogamous populations, males evolved to be less harmful to their mates, and females evolved to be less resistant to male-induced harm. The monogamous populations also evolved a greater net reproductive rate than their promiscuous controls. These results indicate a potentially widespread cost of sexual selection caused by conf licts inherent to promiscuity. A large body of theoretical and empirical evidence indicates that sexual selection can provide a variety of benefits to females (reviewed in refs. 1 and 2). Laboratory populations of Drosophila melanogaster have proven to be a valuable model system for measuring such benefits, e.g., improved survival (3–5). However, sexual selection is also demographically costly, reducing male viability through encumbering traits (6, 7). The costs of sexual selection that apply to females and those that arise from intersexual conflict have not been studied as thoroughly as the benefits. Theory and experiments indicate that some sexually selected traits increase male fitness at the expense of females (7–31). D. melanogaster has proven to be a valuable model here as well: (i) females experiencing experimentally reduced courtship (19) or mating rates (18) survive longer than controls but reproduce at the same rate; (ii) seminal-fluid components increase the competitive ability of accompanying sperm (32, 33) but also increase the mortality rate of inseminated females (27); and (iii) net male fitness increases at the expense of female survival when females are artificially prevented from coevolving with males (30). Conflict between mates hinges on sexual infidelity. Under strict, lifelong monogamy, any trait that lowers the reproductive success of one's mate lowers one's own reproductive success equally. Alternatively, whenever an individual has multiple mates, the lifetime reproductive success of that individual will differ from the success of its mates. …
HEALPix: A Framework for High-Resolution Discretization and Fast Analysis of Data Distributed on the Sphere

HEALPix—the Hierarchical Equal Area isoLatitude Pixelization—is a versatile structure for the pixelization of data on the sphere. An associated library of computational algorithms and visualization software supports fast scientific applications executable directly on discretized spherical maps generated from very large volumes of astronomical data. Originally developed to address the data processing and analysis needs of the present generation of cosmic microwave background experiments (e.g., BOOMERANG, WMAP), HEALPix can be expanded to meet many of the profound challenges that will arise in confrontation with the observational output of future missions and experiments, including, e.g., Planck, Herschel, SAFIR, and the Beyond Einstein inflation probe. In this paper we consider the requirements and implementation constraints on a framework that simultaneously enables an efficient discretization with associated hierarchical indexation and fast analysis/synthesis of functions defined on the sphere. We demonstrate how these are explicitly satisfied by HEALPix.
Hedge Classification in Biomedical Texts with a Weakly Supervised Selection of Keywords

Since facts or statements in a hedge or negated context typically appear as false positives, the proper handling of these language phenomena is of great importance in biomedical text mining. In this paper we demonstrate the importance of hedge classification experimentally in two real life scenarios, namely the ICD9-CM coding of radiology reports and gene name Entity Extraction from scientific texts. We analysed the major differences of speculative language in these tasks and developed a maxent-based solution for both the free text and scientific text processing tasks. Based on our results, we draw conclusions on the possible ways of tackling speculative language in biomedical texts.
Dysphagia, Speech, Voice, and Trismus following Radiotherapy and/or Chemotherapy in Patients with Head and Neck Carcinoma: Review of the Literature

Introduction. Patients with head and neck cancer suffer from various impairments due to the primary illness, as well as secondary consequences of the oncological treatment. This systematic review describes the effects of radiotherapy and/or chemotherapy on the functions of the upper aerodigestive tract in patients with head and neck cancer. Methods. A systematic literature search was performed by two independent reviewers using the electronic databases PubMed and Embase. All dates up to May 2016 were included. Results. Of the 947 abstracts, sixty articles met the inclusion criteria and described one or more aspects of the sequelae of radiotherapy and/or chemotherapy. Forty studies described swallowing-related problems, 24 described voice-related problems, seven described trismus, and 25 studies described general quality of life. Only 14 articles reported that speech pathologists conducted the interventions, of which only six articles described in detail what the interventions involved. Conclusion. In general, voice quality improved following intervention, whereas quality of life, dysphagia, and oral intake deteriorated during and after treatment. However, as a consequence of the diversity in treatment protocols and patient characteristics, the conclusions of most studies cannot be easily generalised. Further research on the effects of oncological interventions on the upper aerodigestive tract is needed.
Recognizing and Responding to Plan-Oriented Misconceptions

This paper discusses the problem of recognizing and responding to plan-oriented misconceptions in advice-seeking dialogs, concentrating on the problems of novice computer users. A cooperative response is one that not only corrects the user's mistaken belief, but also addresses the missing or mistaken user beliefs that led to it. Responding appropriately to a potentially incorrect user belief is presented as a process of 1. checking whether the advisor holds the user's belief; 2. confirming the belief as a misconception by finding an explanation for why the advisor does not hold this belief; 3. detecting the mistaken beliefs underlying the misconception by trying to explain why the user holds the incorrect belief, and 4. providing these explanations to the user. An explanation is shown to correspond to a set of advisor beliefs, and searching for an explanation to proving whether various abstract configurations of advisor beliefs hold. A taxonomy of domain-independent explanations for potential user misconceptions involving plan applicability conditions, preconditions, and effects is presented.
An adaptive energy aware routing protocol for WSNs

Wireless Sensor Network (WSN) is a promising technology with potential applications. Being the pivotal component of WSN, it is essential for WSN routing protocol to make data transmission more energy-efficient and to be adaptive to constant topology changes due to the departure of nodes that run out of energy. In this paper, we propose a new routing algrithm for WSN: Adaptive Energy-Aware routing Protocol (AEAP), which is based on Link Estimation and Parent Selection (LEPS) protocol and adopts broadcast delay method, energy-aware forwarding strategy, and adaptive reorganization mechanism as well. The simulation results show that compared with LEPS, AEAP reduces redundant data transmission, balances energy consumption of nodes, improves the success rate of data collection and network lifetime.
Proteomic Analysis of Mycoplasma gallisepticum Vaccine Strain F

The persistence and displacement abilities of the Mycoplasma gallisepticum vaccine strain F (F-strain) are well documented. Understanding the mechanism(s) of colonization and persistence of F-strain will aid in the current intervention strategies to diagnose and control MG infections in poultry. In the present study, phase partition and liquid chromatography along with electrospray mass spectrometry were used to evaluate the proteome of F-strain. A total of 586, 478 and 339 proteins were recognized from whole cell lysate (total protein), aqueous (cytosolic) and detergent phases (membrane), respectively. The proteins identified with the database searches were then grouped into three categories: (1) proteins from the membrane phase and found in the total proteins (TM); (2) proteins from the cytosolic phase and found in the total proteins (TC) and (3) proteins derived from the membrane and cytosolic phases and found in the total proteins (TMC). There were a total of 93 (33 as putative membrane proteins predicted by SOSUI), 207(13) and 79(6) proteins in the TM, TC and TMC, respectively. The identified proteins were distributed among John Craig Venter Institute (JCVI) categories, with the majority predicted to be involved in protein synthesis. Investigation of the Mycoplasma gallisepticum F-strain proteome may aid in the identification and characterization of F-strain proteins that are important in host colonization.
The Political and Social Contexts of Health

This analysis of the political and social forces that shape the well-being and quality of life of populations in developed capitalist countries is written by scholars based in several different countries. The book shows how the varying political traditions in the developed world - social democratic, Christian democratic, conservative, and liberal traditions - have affected populations' health and quality of life in the western democracies. The contributors also analyze the public and social policies derived from each of these political traditions that have affected levels of social inequality (through changes in the welfare states and labor markets) and on health and quality of life.
Forecasting Stock Exchange Movements Using Neural Networks: A Case Study

Financial time series are very complex and dynamic, so they are characterized as chaotic time series. The major aim of this research is to forecast the stock exchange of Euro vs. Japanese Yen (EURJPY) closing price movements using hourly dataset from September 20, 2010 to January 21, 2011. One neural network (MLP) is used to predict the EURJPY closing price movements. The results of this study show that neuro-computational models are useful tools in forecasting stock exchange movements in emerging markets. These results also indicate that filtering of noises have an enormous effect on prediction improvements.
Nonlinear Complexity Analysis of Brain fMRI Signals in Schizophrenia

We investigated the differences in brain fMRI signal complexity in patients with schizophrenia while performing the Cyberball social exclusion task, using measures of Sample entropy and Hurst exponent (H). 13 patients meeting diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV) criteria for schizophrenia and 16 healthy controls underwent fMRI scanning at 1.5 T. The fMRI data of both groups of participants were pre-processed, the entropy characterized and the Hurst exponent extracted. Whole brain entropy and H maps of the groups were generated and analysed. The results after adjusting for age and sex differences together show that patients with schizophrenia exhibited higher complexity than healthy controls, at mean whole brain and regional levels. Also, both Sample entropy and Hurst exponent agree that patients with schizophrenia have more complex fMRI signals than healthy controls. These results suggest that schizophrenia is associated with more complex signal patterns when compared to healthy controls, supporting the increase in complexity hypothesis, where system complexity increases with age or disease, and also consistent with the notion that schizophrenia is characterised by a dysregulation of the nonlinear dynamics of underlying neuronal systems.
Capital flows without crisis? : reconciling capital mobility and economic stability

Part 1. Crises in a World of Mobile Capital Part 2. The Management and Prevention of Crises Part 3. European Experiences Part 4. Latin American Crises Part 5. The East Asian Crisis Economies Part 6. East Asian Experiences with Capital Controls Part 7. Looking to the Future Part 8. Conclusions
Robustness of Oscillatory Behavior in Correlated Networks

Understanding network robustness against failures of network units is useful for preventing large-scale breakdowns and damages in real-world networked systems. The tolerance of networked systems whose functions are maintained by collective dynamical behavior of the network units has recently been analyzed in the framework called dynamical robustness of complex networks. The effect of network structure on the dynamical robustness has been examined with various types of network topology, but the role of network assortativity, or degree–degree correlations, is still unclear. Here we study the dynamical robustness of correlated (assortative and disassortative) networks consisting of diffusively coupled oscillators. Numerical analyses for the correlated networks with Poisson and power-law degree distributions show that network assortativity enhances the dynamical robustness of the oscillator networks but the impact of network disassortativity depends on the detailed network connectivity. Furthermore, we theoretically analyze the dynamical robustness of correlated bimodal networks with two-peak degree distributions and show the positive impact of the network assortativity.