Miracle-dz/UniFAR-FTUs huggingface dataset:
Choice of Received Long-Term Care – Individual Responses to Regional Nursing Home Provisions

Existing literature analyzing the choice of received long-term care by frail elderly (65+ years) predominantly focuses on physical and psychological conditions of elderly people as factors that influence the decision for a particular type of care. Until now, however, the regional in-patient long-term care supply has been neglected as influential factor in the individual's decision-making process. In this study, we analyze the choice of received long-term care by explicitly taking the regional supply of nursing homes into account. When estimating a discrete choice model, we distinguish between four different types of formal and informal care provision. We find that the decision for long-term in-patient care is significantly correlated with the regional supply of nursing home places, while controlling for physical and psychological conditions of the individual.
Modal factorization of time-varying models for nonlinear circuits by the Riccati transform

In this paper, general linear time-varying systems are addressed. They are considered as small-signal models of nonlinear circuit solutions. The transition matrix is constructed by repeated Riccati transforms. It is shown that each transform factors out a single mode. Key concepts of time-invariant theory are generalized to the time-varying context. They provide a unified mathematical framework, suitable for assessing the local behavior of nonlinear dynamic circuits.
Robotic Object Detection: Learning to Improve the Classifiers Using Sparse Graphs for Path Planning

Object detection is a basic skill for a robot to perform tasks in human environments. In order to build a good object classifier, a large training set of labeled images is required; this is typically collected and labeled (often painstakingly) by a human. This method is not scalable and therefore limits the robot's detection performance. We propose an algorithm for a robot to collect more data in the environment during its training phase so that in the future it could detect objects more reliably. The first step is to plan a path for collecting additional training images, which is hard because a previously visited location affects the decision for the future locations. One key component of our work is path planning by building a sparse graph that captures these dependencies. The other key component is our learning algorithm that weighs the errors made in robot's data collection process while updating the classifier. In our experiments, we show that our algorithms enable the robot to improve its object classifiers significantly.
Prevalence and clinical significance of systolic impairment in hypertrophic cardiomyopathy

Objectives: To determine the frequency of systolic impairment (SI) and its impact on the natural history of hypertrophic cardiomyopathy (HCM). Methods: 1080 patients (mean (SD) age 43 (15) years, 660 men) with HCM were evaluated. Initial assessment included history, examination, 48 hour Holter monitoring, cardiopulmonary exercise testing, and echocardiography; SI was defined as a fractional shortening (FS) ⩽ 25%. Survival data were collected at clinic visits or by direct communication with patients and their general practitioners. The results of serial echocardiography in 462 patients with normal FS at presentation are also reported. Results: 26 (2.4%) patients (49 (14) years, 18 men) had SI at the initial visit. During follow up (58 (49) months), nine (34.6%) died or underwent cardiac transplantation compared with 108 (10.2%) patients with normal FS (p = 0.01). Five year survival from death (any cause) or transplantation was 90.1% (95% confidence interval (CI) 87.8 to 92.4) in patients with normal systolic function versus 52.4% (95% CI 25.2 to 79.6, p < 0.0001) in patients with SI. In patients who underwent serial echocardiography, 22 (4.8%, aged 41 (15) years) developed SI over 66 (40) months; the annual incidence of SI was 0.87% (95% CI 0.54 to 1.31). On initial evaluation patients who developed SI had a higher frequency of syncope (67 (15.2%) v 10 (45.5%) of those who did not develop SI, p = 0.001), non-sustained ventricular tachycardia (91 (20.6%) v 11 (50%), p = 0.002), and an abnormal blood pressure response on exercise (131 (29.7%) v 15 (68.2%), p = 0.001). Patients with SI had greater wall thinning (p = 0.001), left ventricular cavity enlargement (p < 0.0005), and deterioration in New York Heart Association functional class (p = 0.001) during follow up. Thirteen (59.1%) patients who progressed to SI died or underwent transplantation compared with 38 (8.6%) patients who maintained normal systolic function. Conclusions: SI is an infrequent complication of HCM but, when present, is associated with a poor prognosis.
A space-time FIR equalizer training algorithm for MIMO-OFDM systems

In this paper, we propose several new direct training-based methods for FIR space-time equalizer design in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems employing spatial multiplexing. We propose a two-stage receiver structure consisting of an initial space-time equalization for suppressing the co-channel interference (CCI), shortening the channel, and mitigating asynchronicity followed by parallel equalization and detection in the frequency domain. The coefficients of the equalizers and the shortened post-equalization channel response are jointly derived from the training data of the desired users under various constraints. Simulations show that training based methods have good error rate performance and are robust to MIMO co-channel interference.
The trade-off between speed and complexity

Abstract The hypothesis that there has been selection pressure for mechanisms which enable us to perceive the present tends to be conflated with the hypothesis that there has been selection pressure for mechanisms that compensate for inevitable neural delay. The relationship between the two is more subtle, because increases in neural delay can be advantageous for building more useful perceptions.
Support Vector Machine for Chinese Part-Of-Speech Tagging in Speech Synthesis Systems

The paper presents a support vector machine based Part-Of-Speech tagging on Chinese database which is part of our speech synthesis system. The model can be classified as SVM model and uses many sequential features to predict the POS tag. The text database was download from the internet with 1,280,000 words and 33 parts of Speech. The total accuracy of our experiments is 99.31%.
Regulation of starvation-induced hyperactivity by insulin and glucagon signaling in adult Drosophila

Starvation induces sustained increase in locomotion, which facilitates food localization and acquisition and hence composes an important aspect of food-seeking behavior. We investigated how nutritional states modulated starvation-induced hyperactivity in adult Drosophila. The receptor of the adipokinetic hormone (AKHR), the insect analog of glucagon, was required for starvation-induced hyperactivity. AKHR was expressed in a small group of octopaminergic neurons in the brain. Silencing AKHR+ neurons and blocking octopamine signaling in these neurons eliminated starvation-induced hyperactivity, whereas activation of these neurons accelerated the onset of hyperactivity upon starvation. Neither AKHR nor AKHR+ neurons were involved in increased food consumption upon starvation, suggesting that starvation-induced hyperactivity and food consumption are independently regulated. Single cell analysis of AKHR+ neurons identified the co-expression of Drosophila insulin-like receptor (dInR), which imposed suppressive effect on starvation-induced hyperactivity. Therefore, insulin and glucagon signaling exert opposite effects on starvation-induced hyperactivity via a common neural target in Drosophila. DOI: http://dx.doi. org/10.7554/eLife.15693. 001
A new approach for multiple instance learning based on a homogeneity bag operator

Multiple Instance Learning (MIL) proposes a new paradigm when instance labeling, in the learning step, is not possible or infeasible, by assigning a single label (positive or negative) to a set of instances called bag. In this paper, an operator based on homogeneity of positive bags for MIL is introduced. Our method consists in removing instances from the positives bags according to their similarity with the ones from the negative bags. The experimental results show that our operator always increases the accuracy of the Citation kNN algorithm achieving the best results in 2 out of 4 datasets when compared with other classic methods in the literature.
PROTECTED SHARED LIBRARIES

Protected shared libraries are a new mechanism for building fast user-level operating system services. They retain the isolation properties of other userlevel implementation approaches with improved performance and flexibility. The approach can be used with either microkernel-based or monolithic operating systems. Operating system services are built as shared libraries that can be linked into client tasks. However, the classic notion of dynamically linkable shared libraries is extended to isolate the services from the clients, from other services and from the kernel. Thus, protected shared library services avoid the interdependencies that inhibit changes and complicate maintenance in monolithic systems. However, they also eliminate the overhead of full context switches that limit the performance of classic microkernels. Since they retain the key protection features of microkernels, they represent a much more attractive performance improvement approach than co-location. Unlike migratable threads or hand-off scheduling, they provide an ideal basis for flexible system services through the use of common memory. A prototype implementation of protected shared libraries is being built for IBM RS/6000 workstations running AIX 3.2. 5. Early results indicates that the performance of protected shared libraries is better than for other service invocation mechanisms, including thread migration. Finally, system services that are implemented as protected shared libraries are well-matched to the structure of classic objects.
Ieee Transactions on Visualization and Computer Graphics 1 Visual Perception and Mixed-initiative Interaction for Assisted Visualization Design

— This paper describes the integration of perceptual guidelines from human vision with an AI-based mixed-initiative search strategy. The result is a visualization assistant called ViA, a system that collaborates with its users to identify perceptually salient visualizations for large, multidimensional datasets. ViA applies knowledge of low-level human vision to: (1) evaluate the effectiveness of a particular visualization for a given dataset and analysis tasks; and (2) rapidly direct its search towards new visualizations that are most likely to offer improvements over those seen to date. Context, domain expertise, and a high-level understanding of a dataset are critical to identifying effective visualizations. We apply a mixed-initiative strategy that allows ViA and its users to share their different strengths and continually improve ViA's understanding of a user's preferences. We visualize historical weather conditions to compare ViA's search strategy to exhaustive analysis, simulated annealing, and reactive tabu search, and to measure the improvement provided by mixed-initiative interaction. We also visualize intelligent agents competing in a simulated online auction to evaluate ViA's perceptual guidelines. Results from each study are positive, suggesting that ViA can construct high-quality visualizations for a range of real-world datasets.
Evaluation of Never Die Network for a Rural Area in an Ultra Large Scale Disaster

About 80 percent of Japan is located in the mountain or coast sides, and so most cities should be concerned to be isolated when a ultra large disaster happens such as Japan Earthquake and Tsunami on March 11th, 2011. In fact, in the earthquake, there were many areas in the coast side of northern Japan where is isolated because of the damages, blackouts, and congestions of network information systems. In case of such a large-scale disaster, it is important to keep connectivity to avoid the isolation from other areas, and to reactivate network connections quickly within disaster areas such as between evacuation shelters and disaster headquarter. In this paper, Never Die Network consisted of cognitive wireless networks and satellite system that we have proposed is introduced, and the evaluations are held in assumptions of rural areas such as the coast cities of Iwate Prefecture where heavily disaster by Japan Earthquake and Tsunami on March 11th, 2011. The results shows that the proposed system is quickly recovered than other traditional network systems such as wired, wireless, and cognitive wireless network systems, and it is considered to be useful for the isolation by a ultra large scale disaster.
PERIODICITY IN THE PERIODIC LAMBDA ALGEBRA SPUR FINAL PAPER

The periodic lambda algebra is a co-Koszul complex of the Steenrod algebra whose homology gives the E2 term for the Adams spectral sequence. Its elements are closely related to periodic homotopy theory, and exhibit periodic properties. In this paper we discuss an algorithm to compute the homology of the periodic lambda algebra, and investigate the algebraic structure for the E2 page of the vn periodic elements.
Flexible docking allowing induced fit in proteins: Insights from an open to closed conformational isomers

Here we dock a ligand onto a receptor surface allowing hinge‐bending domain/substructural movements. Our approach mimics and manifests induced fit in molecular recognition. All angular rotations are allowed on the one hand, while a conformational space search is avoided on the other. Rather than dock each of the molecular parts separately with subsequent reconstruction of the consistently docked molecules, all parts are docked simultaneously while still utilizing the position of the hinge from the start. Like pliers closing on a screw, the receptor automatically closes on its ligand in the best surface‐matching way. Movements are allowed either in the ligand or in the larger receptor, hence reproducing induced molecular fit. Hinge bending movements are frequently observed when molecules associate. There are numerous examples of open versus closed conformations taking place upon binding. Such movements are observed when the substrate binds to its respective enzyme. In particular, such movements are of interest in allosteric enzymes. The movements can involve entire domains, subdomains, loops, (other) secondary structure elements, or between any groups of atoms connected by flexible joints. We have implemented the hinges at points and at bonds. By allowing 3‐dimensional (3‐D) rotation at the hinge, several rotations about (consecutive or nearby) bonds are implicitly taken into account. Alternatively, if required, the point rotation can be restricted to bond rotation. Here we illustrate this hinge‐bending docking approach and the insight into flexibility it provides on a complex of the calmodulin with its M13 ligand, positioning the hinges either in the ligand or in the larger receptor. This automated and efficient method is adapted from computer vision and robotics. It enables utilizing entire molecular surfaces rather than focusing a priori on active sites. Hence, allows attaining the overall optimally matching surfaces, the extent and type of motions which are involved. Here we do not treat the conformational flexibility of side‐chains or of very small pieces of the molecules. Therefore, currently available methods addressing these issues and the method presented here, are complementary to each other, expanding the repertoire of computational docking tools foreseen to aid in studies of recognition, conformational flexibility and drug design. Proteins 32:159–174, 1998. © 1998 Wiley‐Liss, Inc.
Transmitter Concentration Pro les in the Synaptic Cleft : An Analytical Model of Release and Di usion

A three-dimensional model for release and di usion of glutamate in the synaptic cleft was developed and solved analytically. The model consists of a source function describing transmitter release from the vesicle and a di usion function describing the spread of transmitter in the cleft. Concentration pro les of transmitter at the postsynaptic side were calculated for di erent transmitter concentrations in a vesicle, release scenarios and di usion coe cients. From the concentration pro les the receptor occupancy could be determined using AMPA receptor kinetics. It turned out that saturation of receptors and su ciently fast currents could only be obtained if the di usion coe cient was one order of magnitude lower than generally assumed, and if the postsynaptic receptors formed clusters with a diameter of roughly 100 nm directly opposite the release sites. Under these circumstances the gradient of the transmitter concentration at the postsynaptic membrane outside the receptor clusters was steep with minimal crosstalk among neighboring receptor clusters. These ndings suggest, that to each release site a corresponding receptor aggregate exists, subdividing an individual synapse into independent functional subunits without the need for speci c lateral di usion barriers.
Model refactorings through rule-based inconsistency resolution

The goal of model-driven engineering is to raise the level of abstraction by shifting the focus to models. As a result, complex software development activities move to the modelling level as well. One such activity is model refactoring, a technique for restructuring the models in order to improve some quality attributes of the models. As a first contribution of this paper, we argue and show that refactoring a model is enabled by inconsistency detection and resolution. Inconsistencies in or between models occur since models typically describe a software system from different viewpoints and on different levels of abstraction. A second contribution of this paper is rule-based inconsistency resolution, which enables reuse of different inconsistency resolutions across model refactorings and manages the flow of inconsistency resolution steps automatically.
Cluster-based training data preselection and classification for remote sensing images

In classical image classification approaches, it assumes that there are a number of labeled training data per class. In real applications, labeled data generally are difficult to obtain while unlabeled data are sufficient and helpful to improve the accuracy of classifier. Bipartition based clustering method is to generate better initial cluster centers and to preselect representative data samples from each cluster region with given area under clustering model. To attack the quantity and quality problems of training samples, we propose a Cluster-based Classification Algorithm (CCA) for remote sensing images, and different data samples selection methods are evaluated. Using this approach, the confident unlabeled data both cluster centroid and the ones nearest to the centroid are labeled as training data and extracted. SVM can subsequently be trained with the labeled dataset. The conducted experiments by clustering and classification on real remote sensing Images have validated the proposed approach.
The effect of retirement and age at retirement on self-perceived health after three years of follow-up in Dutch 55–64-year-olds

ABSTRACT Health consequences of retirement have not been included in the current public debate about increasing the age at retirement, which might be due to the fact that studies aimed at health consequences of retirement show ambiguous results. The literature indicates that various contextual characteristics might explain conflicting results. The current study examines the effect of retirement and age at retirement (55–64 years) on self-perceived health. Characteristics tested for confounding and effect modification were: demographic, health, psychological, job, and retirement characteristics. Subjects were 506 participants in the Longitudinal Aging Study Amsterdam (LASA). After three years, 216 retired and 290 remained employed. Multinomial logistic regression analyses show no main effect for retirement compared to continued employment. Modal (59–60) retirees were more likely to attain excellent or good self-perceived health (less than good self-perceived health as the reference category). Early (55–58) and late (61–64) retirees were unaffected by retirement if they did not receive a disability pension. Early and late retirees who received a disability pension were less likely to attain excellent self-perceived health after retirement. Higher educated were less likely to attain excellent self-perceived health after retirement, especially at late retirement age, although health selection might explain this result. Finally, mastery possibly acts as an adjustment resource. The paper concludes with a discussion on explanations for the effect of retirement and age at retirement.
Managing differences, interaction, and partnership quality in global inter-firm relationships

Purpose The purpose of this paper is to develop and to empirically test a model that explains how managing differences between an information technology (IT) provider and an overseas client influences partnership quality and ultimately affects the continuity of the relationship. Design/methodology/approach A field survey by distributing questionnaires to Indonesian IT providers was conducted over four months, yielding 78 completed responses. These empirical data were analyzed by the partial least squares–structural equation modeling technique to examine the measurement and structural models. Findings Managing differences, i.e. cultural, temporal and standards differences, has a positive impact on partnership quality through inter-firm interaction, i.e. information exchange, coordination and participation. Partnership quality, consisting of the dimensions of commitment, trust and integration, has a substantial positive impact on the continuity of the relationship. Research limitations/implications This study was limited by the use of a limited number of samples, reducing the precision of the results. Practical implications This study suggests that if the IT provider is able to manage the cultural, temporal and standards differences with the overseas client, it increases information exchange, coordination and participation between both parties, which are necessary for establishing a high-quality partnership. Originality/value This study is the first empirical examination of how the management of differences between an IT provider and an overseas client influences the continuity of their relationship through interaction and partnership quality.
Metrics and Diagnostics for Precipitation-Related Processes in Climate Model Short-Range Hindcasts

AbstractIn this study, several metrics and diagnostics are proposed and implemented to systematically explore and diagnose climate model biases in short-range hindcasts and quantify how fast hindcast biases approach to climate biases with an emphasis on tropical precipitation and associated moist processes. A series of 6-day hindcasts with NCAR and the U.S. Department of Energy Community Atmosphere Model, version 4 (CAM4) and version 5 (CAM5), were performed and initialized with ECMWF operational analysis every day at 0000 UTC during the Year of Tropical Convection (YOTC). An Atmospheric Model Intercomparison Project (AMIP) type of ensemble climate simulations was also conducted for the same period. The analyses indicate that initial drifts in precipitation and associated moisture processes (“fast processes”) can be identified in the hindcasts, and the biases share great resemblance to those in the climate runs. Comparing to Tropical Rainfall Measuring Mission (TRMM) observations, model hindcasts produce .