Miracle-dz/UniFAR-FTUs huggingface dataset:
The Means Testing Of Benefits And The Labour Supply Of The Wives Of Unemployed Men: Results From A Mover-Stayer Model

Women married to unemployed men in Britain have lower participation rates than those married to employed men. Possible reasons include (1) husbands and wives fac-ing similar unfavourable local labour market conditions, (2) their both having characteristics which make it more likely that they will be unemployed, and (3) the means testing of benefit income, which creates a disincentive for the wife to work. These is-sues are investigated using a British survey of unemployed men and their families. Econometric results from a Mover-Stayer model indicate a limited effect of means testing on the labour supply of the wives.
Multitone interference detection after dehopping process in slow FH/BFSK systems over Rayleigh fading channels

This paper presents an algorithm to detect unknown multitone interference (MTI) which is commonly encountered in slow frequency-hopped spread spectrum (FH-SS) systems over a Rayleigh fading channel. The least-squares (LS) autoregressive (AR) spectral estimation method is used in our algorithm. The proposed algorithm performs the detection process after dehopping, hence, it can be used to provide the side information whether the MTI is present or absent for optimum maximum-likelihood (ML) FH-SS receivers. The fast Fourier transform (FFT) can also be used to implement this detection algorithm. Computer simulations are conducted to evaluate detection performance of both algorithms and comparisons are presented. Numerical results show that the MTI can be detected by both algorithms even at very low interference power (10 dB lower than signal power). Performance comparisons reveal that the proposed algorithm using the AR method is able to locate the MTI within the desired FH band more precisely than the FFT-based algorithm.
Semi-Supervised Maximum Margin Clustering with Pairwise Constraints

The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such as k-means and spectral clustering for the performance enhancement. Nevertheless, the issue of pairwise constraints has not been well studied in the recently proposed maximum margin clustering (MMC), which extends the maximum margin framework in supervised learning for clustering and often shows a promising performance. This paper therefore proposes a pairwise constrained MMC algorithm. Based on the maximum margin idea in MMC, we propose a set of effective loss functions for discouraging the violation of given pairwise constraints. For the resulting optimization problem, we show that the original nonconvex problem in our approach can be decomposed into a sequence of convex quadratic program problems via constrained concave-convex procedure (CCCP). Subsequently, we present an efficient subgradient projection optimization method to solve each convex problem in the CCCP sequence. Experiments on a number of real-world data sets show that the proposed constrained MMC algorithm is scalable and outperforms the existing constrained MMC approach as well as the typical semi-supervised clustering counterparts.
Activation of the Medial Septum Reverses Age-Related Hippocampal Encoding Deficits: A Place Field Analysis

When a rat runs through a familiar environment, the hippocampus retrieves a previously stored spatial representation of the environment. When the environment is modified a new representation is seen, presumably corresponding to the hippocampus encoding the new information. The medial septum is hypothesized to modulate whether the hippocampus engages in retrieval or encoding. The cholinergic agonist carbachol was infused into the medial septum, and hippocampal CA1 place cells were recorded in freely moving rats. In a familiar environment, septal activation impaired the retrieval of a previously stored hippocampal place cell representation regardless of age. When the environment was changed, medial septal activation impaired the encoding process in young, but facilitated the encoding of the new information in aged rats. Moreover, the improved encoding was evident during a subsequent exposure to the modified environment 24 h later. The findings support the role the septum plays in modulating hippocampal retrieval/encoding states. Furthermore, our data indicate a mechanism of age-related cognitive impairment.
Ant-genetic algorithms based on multi-objective optimization

In this paper, a new algorithm called multi-objective ant-genetic algorithms, which is based on the continuous space optimization is presented to solve constrained multi-objective function optimization problems. For the trait of multi-objective optimization, we define the pheromone instruction inheritance searching strategy and the method of pheromone updating. Then we combine four means of pheromone instruction inheritance searching, introduction of excellent decision-making, decision set updating and changing algorithm termination condition together so that the constringent speed of searching has improved a lot and the quantity of Pareto optimal decisions were controlled, also the distributing area of decisions were enlarged, the diversity of the swarm was maintained. At the same time, the termination conditions of multi-objective ant-genetic algorithms were presented. In the end, an example was listed to prove that the algorithms were effective, and it can find a group of widely distributed Pareto optimal decisions.
Efficient Community Detection in Large Scale Networks

One of the most important features of a network is its division into communities, groups of nodes with many internal and few external connections. Furthermore, the community structure of a network can be organized hierarchically, which reflects a natural behavior of real life phenomena. It is a difficult task to detect and understand the community structure of a network and it becomes even more challenging as data availability (and networks sizes) increases. This work presents a efficient implementation for community detection in networks aiming on modularity maximization based on the Newman's spectral method with a fine tuning(FT) stage. This work presents a modification on the FT which substantially reduces the execution time, while preserving the division quality. A high performance implementation of the method enables their application to large real world networks. The Newman's spectral method can be applied to networks with more than 1 million nodes in a personal computer.
Enteric neurons show a primary cilium

The primary cilium is a non‐motile cilium whose structure is 9+0. It is involved in co‐ordinating cellular signal transduction pathways, developmental processes and tissue homeostasis. Defects in the structure or function of the primary cilium underlie numerous human diseases, collectively termed ciliopathies. The presence of single cilia in the central nervous system (CNS) is well documented, including some choroid plexus cells, neural stem cells, neurons and astrocytes, but the presence of primary cilia in differentiated neurons of the enteric nervous system (ENS) has not yet been described in mammals to the best of our knowledge. The enteric nervous system closely resembles the central nervous system. In fact, the ultrastructure of the ENS is more similar to the CNS ultrastructure than to the rest of the peripheral nervous system. This research work describes for the first time the ultrastructural characteristics of the single cilium in neurons of rat duodenum myenteric plexus, and reviews the cilium function in the CNS to propose the possible role of cilia in the ENS cells.
Nonlinear order-reduced adaptive controller for a DC motor driven electric cart

The precise control of a voltage-controlled, DC motor driven electric cart would be a 3rd order task since Classical Mechanics relates the acceleration of the cart to driving torques, while these torques are proportional to the current that cannot be modified abruptly. Abrupt jumps in the control voltage cause abrupt change only in the time-derivative of the motor current. Therefore a 2nd order controller can only approximate the operation of a 3rd order one. Modeling imprecisions further complicate the control task. Furthermore, if the cart has two independently driven main wheels and a supporting caster, no exact trajectory tracking can be prescribed simultaneously for the location of the cart in the (x, y) plane and its rotational orientation (θ) since for three prescribed quantities only two control signals are available. For the tracking error of these components, some kinematically formulated compromise must be applied. The aim of the present paper is to show that the simultaneous problems caused by the order reduction, the modeling errors and the necessary kinematic compromises can be elegantly solved by the adaptive controllers designed on the basis of Robust Fixed Point Transformations (RFPT). This statement is substantiated by simulation results.
An interconnection method for ultra-compliant electrodes.

We are developing a novel interconnection method to form reliable joints between truly stretchable electrode mounts and rigid substrates. This is needed as the electrodes must be connected to implanted electronics if they are to be used for long term implantation, and the components are most often mounted on a rigid substrate and protected within a solid enclosure. In this paper we describe the concept and report on preliminary results. Eight test samples were prepared, four of which started the underwater test. Their initial impedance ranged from 107 to 413 and remained constant (standard deviation 6) for over two months submersion.
Classification of Forefoot Plantar Pressure Distribution in Persons with Diabetes: A Novel Perspective for the Mechanical Management of Diabetic Foot?

Background The aim of this study was to identify groups of subjects with similar patterns of forefoot loading and verify if specific groups of patients with diabetes could be isolated from non-diabetics. Methodology/Principal Findings Ninety-seven patients with diabetes and 33 control participants between 45 and 70 years were prospectively recruited in two Belgian Diabetic Foot Clinics. Barefoot plantar pressure measurements were recorded and subsequently analysed using a semi-automatic total mapping technique. Kmeans cluster analysis was applied on relative regional impulses of six forefoot segments in order to pursue a classification for the control group separately, the diabetic group separately and both groups together. Cluster analysis led to identification of three distinct groups when considering only the control group. For the diabetic group, and the computation considering both groups together, four distinct groups were isolated. Compared to the cluster analysis of the control group an additional forefoot loading pattern was identified. This group comprised diabetic feet only. The relevance of the reported clusters was supported by ANOVA statistics indicating significant differences between different regions of interest and different clusters. Conclusion/s Significance There seems to emerge a new era in diabetic foot medicine which embraces the classification of diabetic patients according to their biomechanical profile. Classification of the plantar pressure distribution has the potential to provide a means to determine mechanical interventions for the prevention and/or treatment of the diabetic foot.
Distinct Glycan Structures of Uroplakins Ia and Ib

Although it has been shown that mouse uroplakin (UP) Ia, a major glycoprotein of urothelial apical surface, can serve as the receptor for the FimH lectin adhesin of type 1-fimbriated Escherichia coli, the organism that causes a great majority of urinary tract infections, the glycan structure of this native receptor was unknown. Using a sensitive approach that combines in-gel glycosidase and protease digestions, permethylation of released glycans, and mass spectrometry, we have elucidated for the first time the native glycoform structures of the mouse UPIa receptor and those of its non-binding homolog, UPIb, and have determined the glycosylation site occupancy. UPIa presents a high level of terminally exposed mannose residues (located on Man6GlcNAc2 to Man9GlcNAc2) that are capable of specifically interacting with FimH. We have shown that this property is conserved not only in the mouse uroplakins but also in cattle and, even more importantly, in human UPIa, thus establishing the concept that UPIa is a major urothelial receptor in humans and other mammals for the mannose-specific FimH variant. In contrast, our results indicate that most terminally exposed glycans of mouse UPIb are non-mannose residues, thus explaining the failure of FimH to bind to this UPIb. In cattle, on the other hand, complex carbohydrates constituted only about 20% of the UPIb N-linked glycans. Human UPIa contained exclusively high mannose glycans, and human UPIb contained only complex glycans. The drastically different carbohydrate processing of the UPIa and UPIb proteins, two closely related members of the tetraspanin family, may reflect differences in their folding and masking due to their interactions with their associated proteins, UPII and UPIIIa, respectively. Results from this study shed light on the molecular pathogenesis of urinary tract infections and may aid in the design of glyco-mimetic inhibitors for preventing and treating this disease.
Computing the Rate Distortion Region for the CEO Problem With Independent Sources

A method for numerically calculating the rate distortion region for the central estimation officer (CEO) problem when the sources are independent is derived by generalizing the Blahut-Arimoto algorithm. Unlike the traditional rate distortion function computation problem, the Lagrangian for the CEO rate distortion region can be nonconvex. When the Lagrangian is convex, the presented algorithm is converged from every initialization to the global optimum under some additional uniqueness conditions. When the Lagrangian is nonconvex, the convergent value obtained by the algorithm can be initialization dependent. To handle these nonconvex cases, an explicit nonrandom initialization that is in the region of attraction of the global optimum for low distortions is provided. Some example problems motivated by remote lossy function computation in sensor networks and wireless resource controllers highlight that both the convex and nonconvex cases occur in practice and the utility of the algorithm in computing their rate distortion regions.
Learning about Atrial Fibrillation using Social Media : A Qualitative Inquiry

Health information is one of the major topics searched on-line. Social media is increasingly used by patients for health education, empowerment and support. There is a lack of systematic data on what kind of information is being sought by patients via social medial channels. By analyzing information exchange in an on-line support group we can better understand what information is not provided reliably to patients in a clinical setting. The aim of this study was to analyze a content of messages exchanged between participants in an online support group for people with atrial fibrillation. Using Grounded Theory, we conducted a content analysis of 626 messages, which were grouped into seven categories. We described each category and provided examples of users citations belonging to each category. In addition, proportion of initial posts and responses to them was analyzed depending on message category. Social media facilitated health education on major topics related to atrial fibrillation. Practical implications of qualitative analysis of messages posted on an online support group are discussed.
REFRACTIVE: An Open Source Tool to Extract Knowledge from Syntactic and Semantic Relations

The extraction of semantic propositions has proven instrumental in applications like IBM Watson and in Google’s knowledge graph . One of the core components of IBM Watson is the PRISMATIC knowledge base consisting of one billion propositions extracted from the English version of Wikipedia and the New York Times. However, extracting the propositions from the English version of Wikipedia is a time-consuming process. In practice, this task requires multiple machines and a computation distribution involving a good deal of system technicalities. In this paper, we describe Refractive, an open-source tool to extract propositions from a parsed corpus based on the Hadoop variant of MapReduce. While the complete process consists of a parsing part and an extraction part, we focus here on the extraction from the parsed corpus and we hope this tool will help computational linguists speed up the development of applications.
Automated Re nement ofFirst-Order Horn-Clause Domain

Knowledge acquisition is a diicult, error-prone, and time-consuming task. The task of automatically improving an existing knowledge base using learning methods is addressed by the class of systems performing theory reenement. This paper presents a system, Forte (First-Order Revision of Theories from Examples), which reenes rst-order Horn-clause theories by integrating a variety of diierent revision techniques into a coherent whole. Forte uses these techniques within a hill-climbing framework, guided by a global heuristic. It identiies possible errors in the theory and calls on a library of operators to develop possible revisions. The best revision is implemented, and the process repeats until no further revisions are possible. Operators are drawn from a variety of sources, including propositional theory reenement, rst-order induction, and inverse resolution. Forte is demonstrated in several domains, including logic programming and qualitative modelling.
Education to a Healthy Lifestyle Improves Symptoms and Cardiovascular Risk Factors – AsuRiesgo Study

Background Cardiovascular diseases are the current leading causes of death and disability globally. Objective To assess the effects of a basic educational program for cardiovascular prevention in an unselected outpatient population. Methods All participants received an educational program to change to a healthy lifestyle. Assessments were conducted at study enrollment and during follow-up. Symptoms, habits, ATP III parameters for metabolic syndrome, and American Heart Association’s 2020 parameters of cardiovascular health were assessed. Results A total of 15,073 participants aged ≥ 18 years entered the study. Data analysis was conducted in 3,009 patients who completed a second assessment. An improvement in weight (from 76.6 ± 15.3 to 76.4 ± 15.3 kg, p = 0.002), dyspnea on exertion NYHA grade II (from 23.4% to 21.0%) and grade III (from 15.8% to 14.0%) and a decrease in the proportion of current active smokers (from 3.6% to 2.9%, p = 0.002) could be documented. The proportion of patients with levels of triglycerides > 150 mg/dL (from 46.3% to 42.4%, p < 0.001) and LDL cholesterol > 100 mg/dL (from 69.3% to 65.5%, p < 0.001) improved. A ≥ 20% improvement of AHA 2020 metrics at the level graded as poor was found for smoking (-21.1%), diet (-29.8%), and cholesterol level (-23.6%). A large dropout as a surrogate indicator for low patient adherence was documented throughout the first 5 visits, 80% between the first and second assessments, 55.6% between the second and third assessments, 43.6% between the third and fourth assessments, and 38% between the fourth and fifth assessments. Conclusion A simple, basic educational program may improve symptoms and modifiable cardiovascular risk factors, but shows low patient adherence.
Neural decoding using a nonlinear generative model for brain-computer interface

Kalman filters have been used to decode neural signals and estimate hand kinematics in many studies. However, most prior work assumes a linear system model, an assumption that is almost certainly violated by neural systems. In this paper, we show that adding nonlinearities to the decoding algorithm improves the accuracy of tracking hand movements using neural signal acquired via a 32-channel micro-electrocorticographic (μECoG) grid placed over the arm and hand representations in the motor cortex. Experimental comparisons indicate that a Kalman filter with a fifth order polynomial generative model relating the hand kinematics signals to the neural signals improved the mean-square tracking performance in the hand movements over a conventional Kalman filter employing a linear system model. This finding is in accord with the current neurophysiological understanding of the decoded signals.
Fortran vs . C + + : Electrostatic Plasma PIC Simulation on the IntelParagon & IBM SP 1 yCharles

We discuss the software development issues involved in designing parallel programs using object oriented techniques. Simulations involving 1D and 2D Particle In Cell plasma codes illustrate how C++ programs can eeectively describe complex simulations while performing with reasonable ef-ciency when compared to the equivalent Fortran programs. The scalable object oriented modeling techniques closely match the physical view of the problem, thus supporting modiiability and porta-bility of the code. Selection of a parallel programming paradigm must consider the important factors of eeciency of the computation and the programming implementation eeort. C++ and For-tran implementation paradigms are compared and discussed from this point of view.
Expression and Function of TNF and IL-1 Receptors on Human Regulatory T Cells

Regulatory T cells (Tregs) suppress immune activation and are critical in preventing autoimmune diseases. While the ability of Tregs to inhibit proliferation of other T cells is well established, it is not yet clear whether Tregs also modulate inflammatory cytokines during an immune response. Here, we show that the expression of inflammatory cytokine receptors IL-1R1 and TNFR2 were higher on resting mature Tregs compared to naïve or memory T cells. While upon activation through the T cell receptor (TCR), expression of IL-1R1 and TNFR2 were upregulated on all T cell subsets, IL-1R1 maintained significantly higher expression on activated Tregs as compared to other T cell subsets. The decoy receptor for IL-1 (IL-1R2) was not expressed by any of the resting T cells but was rapidly upregulated and preferentially expressed upon TCR-stimulation on Tregs. In addition, we found that Tregs also expressed high levels of mRNA for IL-1 antagonist, IL-1RA. TCR-stimulation of naïve T cells in the presence of TGFβ, which induces FOXP3 expression, however did not result in upregulation of IL-1R1 or IL-1R2. In addition, ectopic expression of FOXP3 in non-Tregs, while causing significant upregulation of IL-1R1 and IL-1R2, did not achieve the levels seen in bona fide Tregs. We also determined that resting human Tregs expressing IL-1R1 did not have higher suppressive capacity compared to IL-1R1- Tregs, suggesting that IL-1R1 does not discriminate suppressive resting Tregs in healthy individuals. Functionally, activated human Tregs displayed a capacity to neutralize IL-1β, which suggests a physiological significance for the expression of IL-1 decoy receptor on Tregs. In conclusion, our findings that human Tregs preferentially express receptors for TNF and IL-1 suggest a potential function in sensing and dampening local inflammation.