Miracle-dz/UniFAR-FTUs huggingface dataset:
On-line Metalearning in Changing Contexts: METAL(B) and METAL(IB)

Many real-world concepts are heavily contextdependent. Changes in context can produce more or less radical changes in the associated concepts. On-line concept learning in such domains requires the ability to recognize and adapt to such changes. This paper concentrates on a class of learning tasks where the domain provides explicit clues as to the current context (e.g., attributes with characteristic values). A general two-level learning model is presented that effectively adjusts to changing contexts by trying to detect (via ’meter learning’) contextual clues and using this information to focus the learning process. Context learning and detection occur during regular online learning, without separate training phases for context recognition. Two operational systems based on this model are presented that differ in the underlying learning algorithm and in the way they use contextual information: METAL(B) combines meta-learning with a Bayesian classifier, while M~-TAL(IB) based on an instance-based learning algorithm. Experiments with synthetic domains as well as a ’real-world’ problem show that the algorithms are robust in a variety of dimensions, and that rectalearning produces substantial improvement over simple object-level learning in situations with changing contexts.
A clean four-quadrant sinusoidal power rectifier using multistage converters for subway applications

A special 27-level four-quadrant rectifier for subway applications is analyzed. The arrangement uses only three H-bridges per phase, common dc bus, and independent input transformers for each H-bridge. The transformers allow galvanic isolation and power escalation to obtain high-quality voltage waveforms, with total harmonic distortion of less than 1%. Some advantages of this 27-level rectifier are: 1) only one of the three H-bridges, called the main converter, manages more than 80% of the total active power in each phase and 2) it switches at fundamental frequency, reducing the switching losses at a minimum value. The rectifier analyzed in this paper is a current-controlled voltage-source type, with a conventional feedback control loop. Some simulations in a rectifier substation, including power reversal at full load are displayed (750 Vdc, 1200 A). The rectifier shows the ability to produce clean ac and dc waveforms without any ripple, and fast reversal of power. Some experimental results with a small prototype, showing voltage and current waveforms, are finally displayed.
PBTrust: A Priority-Based Trust Model for Service Selection in General Service-Oriented Environments

How to choose the best service provider (agent), which a service consumer can trust in terms of the quality and success rate of the service in an open and dynamic environment, is a challenging problem in many service-oriented applications such as Internet-based grid systems, e-trading systems, as well as service-oriented computing systems. This paper presents a Priority-Based Trust (PBTrust) model for service selection in general service-oriented environments. The PBTrust is robust and novel from several perspectives. (1) The reputation of a service provider is derived from referees who are third parties and had interactions with the provider in a rich context format, including attributes of the service, the priority distribution on attributes and a rating value for each attribute from a third party, (2) The concept of `Similarity' is introduced to measure the difference in terms of distributions of priorities on attributes between requested service and a refereed service in order to precisely predict the performance of a potential provider on the requested service, (3) The concept of general performance of a service provider on a service in history is also introduced to improve the success rate on the requested service. The experimental results can prove that PBtrust has a better performance than that of the CR model in a service-oriented environment.
Timing of the Onset of Acute Respiratory Distress Syndrome: A Population-Based Study

BACKGROUND: Many patients with acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) have had recent healthcare interventions prior to developing ALI/ARDS. OBJECTIVE: To determine the timing of ALI/ARDS onset in relation to hospital admission and other healthcare interventions. METHODS: We conducted a population-based observational cohort study with a validated electronic surveillance tool, and identified patients with possible ALI/ARDS among critically ill adults at Mayo Clinic hospitals that provide critical care services for Olmsted County, Minnesota, in 2006. Trained investigators independently reviewed electronic medical records and confirmed the presence and timing of ALI/ARDS based on the American-European consensus definition. RESULTS: Of 124 episodes of ALI in 118 patients, only 5 did not fulfill the ARDS criteria. The syndrome developed a median 30 hours (IQR 10–82 h) after hospital admission in 79 patients (67%). ARDS was present on admission in 39 patients (33%), of whom 14 had recent hospitalization, 6 were transferred from nursing homes, and 3 had recent out-patient contact (1 antibiotic prescription, 1 surgical intervention, and 1 chemotherapy). Only 16 ARDS patients (14%) did not have known recent contact with a healthcare system. Compared to ARDS on admission, hospital-acquired ARDS was more likely to occur in surgery patients (54% vs 15%, P < .001), and had longer adjusted hospital stay (mean difference 8.9 d, 95% CI 0.3–17.4, P = .04). CONCLUSIONS: ARDS in the community most often develops either during hospitalization or in patients who recently had contact with a healthcare system. These findings have important implications for potential preventive strategies.
Identifying semantic differences in AspectJ programs

Program differencing is a common means of software debugging. Although many differencing algorithms have been proposed for procedural and object-oriented languages like C and Java, there is no differencing algorithm for aspect-oriented languages so far. In this paper we propose an approach for difference analysis of aspect-oriented programs. The proposed algorithm contains a novel way of matching two versions of a module of which the signature has been modified. For this, we also work out a set of well defined signatures for the new elements in the AspectJ language. In accordance with these signatures, and with those existent for elements of the Java language, we investigate a set of signature patterns to be used with the module matching algorithm. Furthermore, we demonstrate successful application of a node-by-node comparison algorithm originally developed for object-oriented programs. Using a tool which implements our algorithms, we set up and evaluate a set of test cases. The results demonstrate the effectiveness of our approach for a large subset of the AspectJ language.
Efficient Synchronization : Let Them Eat QOLB 1

Efficient synchronization primitives are essential for achieving high performance in fine-grain, shared-memory parallel programs. One function of synchronization primitives is to enable exclusive access to shared data and critical sections of code. This paper makes three contributions. (1) We enumerate the five sources of overhead that locking synchronization primitives can incur. (2) We describe four mechanisms (local spinning, queue-based locking, collocation, and synchronized prefetch) that reduce these synchronization overheads. (3) With detailed simulations, we show the extent to which these four mechanisms can improve the performance of shared-memory programs. We evaluate the space of these mechanisms using seventeen synchronization constructs, which are formed from six base types of locks ( TEST&SET, TEST&TEST&SET, MCS, LH, M, and QOLB). We show that large performance gains (speedups of more than 1.5 for three of five benchmarks) can be achieved if at least three optimizing mechanisms are used simultaneously. We find that QOLB, which incorporates all four mechanisms, outperforms all other primitives (including reactive synchronization) in all cases. Finally, we demonstrate the superior performance of a low-cost implementation of QOLB, which runs on an unmodified cluster of commodity workstations.
"Wörter des Tages" - Tagesaktuelle wissensbasierte Analyse und Visualisierung von Zeitungen und Newsdiensten

In this paper we describe a web service which presents media analysis results as both, structured lists of Words of the Day, as well as visualizations of relevant concepts in their semantic context and concept relevance timelines. Media analysis is based on a daily collection of online newspapers and news services. For each day, this collection is processed by a text mining suite.
Kidney Donor Risk Index (KDRI) Fails to Predict Kidney Allograft Survival in HIV (+) Recipients

Introduction We used the United Network of Organ Sharing Standard Transplant Analysis and Research Files (STAR files) to investigate the utility of the Kidney Donor Risk Index (KDRI) versus delayed graft function (DGF) to predict graft survival in the HIV (+) kidney transplant recipients. Methods Individual matching (one case to five controls) was used to investigate predictive ability of the KDRI for graft survival in HIV (+) recipients (cases) as compared to HIV (−) recipients (controls) leaving 400 HIV (+) recipients matched with 1,904 HIV (−) recipients. Cox proportional hazard regression model was used to test association of the KDRI and DGF with graft survival. The relationship of the KDRI with graft survival was also explored by using Kaplan-Meier analysis. Results HIV (+) and HIV (−) cohorts were well matched in terms of race, HCV co-infection, panel reactive antibody, and wait time except HIV + were more frequently diabetic. Donor qualities were similar between the cohorts, including method of allograft preservation pretransplant, HLA matching, and calculated KDRI. There was no significant difference in survival based on the KDRI quintiles among the HIV (+) cohort (logrank sum P=0.4986). Graft survival within the HIV (+) cohort was significantly worse in the DGF (+) group than the DGF (−) group (logrank P<0.01). Discussion We found that the KDRI did not predict graft survival for HIV (+) kidney transplant recipients; however, the presence of DGF continues to have a negative impact on the graft survival. Future predictive models should include DGF as a variable.
Improving quality of life in patients with chronic kidney disease: influence of acceptance and personality.

BACKGROUND A low health-related quality of life (HQL) is associated with the evolution of chronic kidney disease (CKD) and mortality in patients in end-stage of the disease. Therefore research on psychological determinants of HQL is emerging. We investigate whether acceptance of the disease contributes to a better physical and mental health-related quality of life (PHQL and MHQL). We also examine the impact of personality characteristics on acceptance, PHQL and MHQL. METHODS In this cross-sectional study, patients from an outpatient clinic of nephrology completed self-report questionnaires on quality of life, acceptance and personality characteristics. We performed correlations, regression analyses and a path analysis. RESULTS Our sample of 99 patients had a mean duration of CKD of 10.81 years and a mean estimated Glomerular Filtration Rate (eGFR) by Modification of Diet in Renal Disease (MDRD)-formula of 34.49 ml/min (SD 21.66). Regression analyses revealed that acceptance had a significant positive contribution to the prediction of PHQL and MHQL. Neuroticism was negatively associated with acceptance and MHQL. Path analysis showed that 37% of the total effect of neuroticism on MHQL was mediated by acceptance. CONCLUSIONS Acceptance is an important positive variable in accounting for HQL, however, clinicians must be aware that if patients have a high level of neuroticism they are likely to have more difficulties with this coping strategy. These results provide a better understanding of psychological determinants of HQL in CKD, which can initiate another approach of these patients by nephrologists, specific psychological interventions, or other supporting public health services.
On Epsilon-Nets, Distance Oracles, and Metric Embeddings

We give two new applications of an observation from \cite{ADFGW11}. The first is an almost linear sized constant time data structure for reporting very large distances in undirected graphs. The second is a generic transformation of results about $\ell_1$-embeddability of metrics to a setting, where we are interested in preservation of large distances only.
Co-Occurring Mental Disorders Among Incarcerated Women

Abstract There is a growing awareness of the incidence of mental disorders among women involved in the criminal justice system. Two hundred and eighty-three women were participants in a federally-funded study and all met DSM-IVcriteria for at least two Axis I disorders, including one substance abuse diagnosis. Posttraumatic Stress Disorder (chronic) was the primary mental health diagnosis for 75% of the sample. Based on findings, the need for rigorous and accurate diagnostic evaluation for women in criminal justice settings is discussed; specific recommendations include: providing evidence-based, integrated, trauma-informed treatment, and designing comprehensive gender-specific programs to improve outcomes for incarcerated women.
Efficient spark-based framework for big geospatial data query processing and analysis

The exponential amount of geospatial data that has been accumulated in an accelerated pace has inevitably motivated the scientific community to examine novel parallel technologies for tuning the performance of spatial queries. Managing spatial data for an optimized query performance is particularly a challenging task. This is due to the growing complexity of geometric computations involved in querying spatial data, where traditional systems failed to beneficially expand. However, the use of large-scale and parallel-based computing infrastructures based on cost-effective commodity clusters and cloud computing environments introduces new management challenges to avoid bottlenecks such as overloading scarce computing resources, which may be caused by an unbalanced loading of parallel tasks. In this paper, we aim to fill those gaps by introducing a generic framework for optimizing the performance of big spatial data queries on top of Apache Spark. Our framework also supports advanced management functions including a unique self-adaptable load-balancing service to self-tune framework execution. Our experimental evaluation shows that our framework is scalable and efficient for querying massive amounts of real spatial datasets.
Characterization of 11p14-p12 deletion in WAGR syndrome by array CGH for identifying genes contributing to mental retardation and autism

WAGR (Wilms tumor, Aniridia, Genitourinary malformations and mental Retardation) syndrome is a rare genomic disorder caused by deletion of the 11p14-p12 chromosome region. The majority of WAGR patients have mental retardation and behavioral problems, and more than 20% of the patients also have features of autism. While the Wilms tumor/genitourinary anomalies and aniridia are caused by deletion of WT1 and PAX6 respectively, the genomic cause of mental retardation and autism in WAGR syndrome remains unknown. Using oligonucleotide arrays, we have characterized the 11p14-p12 deletions in 31 patients and identified all the genes involved in each deletion. The deletions had sizes ranging from 4.9 to 23 Mb that encompass 18–62 genes (40 on average). In addition to WT1 and PAX6, all the patients had deletion of PRRG4 (transmembrane gamma-carboxyglutamic acid protein 4). The majority of them had deletion of BDNF (brain-derived neurotrophic factor) and SLC1A2 [solute carrier family 1 (glial high affinity glutamate transporter) member 2]. Deletion of BDNF and SLC1A2 occurred in patients with autism more frequently than in those without autism. Literature review on the functions of the genes suggests that haploinsufficiency of SLC1A2, PRRG4, and BDNF may contribute to mental retardation and behavioral problems. In particular, BDNF may modulate the risk of autism in WAGR patients as suggested by its link with Rett syndrome as a target of MECP2. We observed that all the de novo deletions occurred in the chromosome 11 inherited from the father in the families genotyped, implying a predisposition for de novo mutations occurring in spermatogenesis and possible involvement of imprinting in cognitive impairment in WAGR patients.
Multi-Antenna Selection Using Space Shift Keying in MIMO Systems

We investigate the MIMO antenna selection using space shift keying (SSK) modulation and amplitude/phase modulation (APM). In the joint SSK and APM, both the constellation of APM and the antenna indexes of SSK convey information. The multiple-input multiple-output (MIMO) system increases the capacity and data rates at the cost of the multiple RF chains, which can be reduced by antenna selection techniques. In this paper, the antenna selection techniques are jointly designed with the SSK-based MIMO systems, and the decoding scheme achieving maximum-likelihood (ML) criterion is explicitly described. The proposed antenna selection criteria pursue the best antenna configuration by utilizing channel state information. The simulations demonstrate significant performance improvements of SSK-based MIMO systems over conventional systems.
A New Learning Algorithm for Blind Signal Separation

A new on-line learning algorithm which minimizes a statistical dependency among outputs is derived for blind separation of mixed signals. The dependency is measured by the average mutual information (MI) of the outputs. The source signals and the mixing matrix are unknown except for the number of the sources. The Gram-Charlier expansion instead of the Edgeworth expansion is used in evaluating the MI. The natural gradient approach is used to minimize the MI. A novel activation function is proposed for the on-line learning algorithm which has an equivariant property and is easily implemented on a neural network like model. The validity of the new learning algorithm are verified by computer simulations.
Mind-body relationships in elite apnea divers during breath holding: a study of autonomic responses to acute hypoxemia

The mental control of ventilation with all associated phenomena, from relaxation to modulation of emotions, from cardiovascular to metabolic adaptations, constitutes a psychophysiological condition characterizing voluntary breath-holding (BH). BH induces several autonomic responses, involving both autonomic cardiovascular and cutaneous pathways, whose characterization is the main aim of this study. Electrocardiogram and skin conductance (SC) recordings were collected from 14 elite divers during three conditions: free breathing (FB), normoxic phase of BH (NPBH) and hypoxic phase of BH (HPBH). Thus, we compared a set of features describing signal dynamics between the three experimental conditions: from heart rate variability (HRV) features (in time and frequency-domains and by using nonlinear methods) to rate and shape of spontaneous SC responses (SCRs). The main result of the study rises by applying a Factor Analysis to the subset of features significantly changed in the two BH phases. Indeed, the Factor Analysis allowed to uncover the structure of latent factors which modeled the autonomic response: a factor describing the autonomic balance (AB), one the information increase rate (IIR), and a latter the central nervous system driver (CNSD). The BH did not disrupt the FB factorial structure, and only few features moved among factors. Factor Analysis indicates that during BH (1) only the SC described the emotional output, (2) the sympathetic tone on heart did not change, (3) the dynamics of interbeats intervals showed an increase of long-range correlation that anticipates the HPBH, followed by a drop to a random behavior. In conclusion, data show that the autonomic control on heart rate and SC are differentially modulated during BH, which could be related to a more pronounced effect on emotional control induced by the mental training to BH.
A fast parametric assignment algorithm with applications in max‐algebra

This article presents a fast algorithm for a class of parametric assignment problems. Moreover, it is shown how this algorithm can be applied to a problem arising in the so‐called max‐algebra which results as an analogue of classical linear algebra by replacing the classical addition and multiplication by a ⊕ b = max(a,b) and a ⊗ b = a + b, respectively. An instance of the linear parametric assignment problem is given by a bipartite graph G = (U,V,E) with 2n vertices, m edges and affine‐linear parametric edge weights cλ(i,j) = c(i,j) − b(i,j)λ for (i,j) ∈ E. The task is to find an assignment with minimum weight with respect to the parametric weights cλ for all values of λ. We develop an algorithm which solves the special case for which b(i,j) ∈ {0, 1} for all (i,j) ∈ E in 𝒪(mn+n2 log n) time. Our algorithm can be extended to solve the special parametric assignment problem which arises in connection with computing the essential terms of the so‐called characteristic max‐polynomial. The resulting algorithm runs in 𝒪(n3) time and thus improves upon the best‐known algorithm for computing the characteristic max‐polynomial due to Burkard and Butkovič (Appl Math 130 (2003), 367–380) by a factor of n. © 2009 Wiley Periodicals, Inc. NETWORKS, 2010
Organizing Security Patterns Related to Security and Pattern Recognition Requirements

Software security is an emerging area in software development. More and more vulnerabilities are published and highlight the endangerment of systems. Hence, software designers and programmers are increasingly faced with the need to apply security solutions to software systems. Security patterns are best practices to handle recurring security problems. The abundance of documented security patterns calls for meaningful classifications to ease searching and assessing the right pattern for a security problem at hand. Existing classifications for security patterns consider only a small number of patterns and their purpose is often focused on implementation issues. Therefore, we identify missing aspects in existing classifications and the similarities between design and security pattern classifications. Based on that, we introduce two new classification schemes. The first is based on application domains formed by a literature survey on security patterns published in the period of 1997 to mid-2012 to cover the whole bandwidth of existing security patterns. The second is based on a subset of the collected patterns that are concerned with software and combines pattern-recognition needs and security aspects. Keywords-Security Patterns, Design Patterns.
A Novel Approach for Multiple Mobile Robot Path Planning in Dynamic Unknown Environment

Multiple mobile robot path planning in dynamic unknown environment is challenging. In this paper a novel artificial potential field (APF) based approach is proposed. In this approach, a robot was pulled to the goal position with the influence of the goal and static obstacles. When two or more robots meet at the range of safe distance, those robots was prioritized according to the priority of the task they undertake, velocity and their size. The robot with higher priority will pass the intersection first. If they have the same priority, they will generate a priority order randomly to each other. By this way, they will avoid collision between each other. Simulation results are provided to validate the concepts and analyses are made to show the effectiveness of the approach