Miracle-dz/UniFAR-FTUs huggingface dataset:
Does Government Spending Influence Charitable Contributions or Vice Versa?

We exploit the time series properties of charitable giving data to provide additional insights into the relationship between charitable contributions and government spending. Cointegration tests reveal a significant long-run relationship between several categories of charitable giving and government spending. Granger causality tests are designed to capture any short-run giving and spending relationship, and provide the opportunity to examine whether changes in fundraising efforts by charities influence government spending. Evidence suggests that charitable contributions to education responds quite differently to state and local government education expenditures versus federal government expenditures. We argue that the government spending and charitable giving relationship is dependent upon the source of government revenue and how this revenue is used by institutions of learning.
The relation of balance performance and balance confidence with physical activity in elderly fallers and non-fallers

Balance is an important issue in aging research since it is undoubtedly linked with motor performance affecting, thus, activities of daily living and consecutively the quality of life in the elderly. Maintenance of good balance ability reduces the chance of a fall which, especially in the elderly, is not only an important predictor of mortality but also a major problem with important negative health and socio-economic consequences. The fear of falling, on the other hand, results in restrictions of physical activity, functional ability, and consequently may lead to reduced quality of life and adverse health consequences [5]. Another psychological variable linked to the fear of falling is balance confidence or falls self-efficacy, which refers to personal beliefs in one’s ability to engage in certain activities of daily living without falling or losing balance [8]. Increased balance confidence, which is determined to a great extent by balance performance [2], is associated with lower fear of falling and better functional ability [6]. Physical activity seems to have a positive relation with balance confidence but the outcomes of this relation are not well understood. Some findings suggest that the improvement in balance confidence through an exercise intervention program is only weakly correlated with improved general physical function and not associated with improvements in postural stability [7]. Other findings, however, suggest that balance confidence plays a mediatory role in the effects of fear of falling on functional outcomes [6], and if the exercise program is aimed at the enhancement of balance confidence then the fear of falling is likely to be reduced [4]. Balance confidence and balance performance have been found to be significant predictors of fall status [3]. It is not, known however, if the relationship between balance confidence, balance performance and habitual physical activity, is different in fallers than in nonfallers. This study aimed to examine the relationship between balance performance, balance confidence and physical activity, which is reflected in the number of steps performed in everyday life, taking into account the fall history of elderly persons.
Phase-Locked Loops: Application to Coherent Receiver Design

GENERALITIES. Working Principles. Loop Components. General Equations. Phase-Locked Loop Stability. LINEAR BEHAVIOR. Transient Response. Sinusoidal Operating Conditions. Additive Noise Response. Response to Random Modulations. Parameter Variation. NONLINEAR OPERATION. Natural Acquisition of the Input Signal. Acquisition Subsidiary Devices. Nonlinear Operation in the Presence of Noise.
To Project More or to Quantize More: Minimize Reconstruction Bias for Learning Compact Binary Codes

We present a novel approach called Minimal Reconstruction Bias Hashing (MRH) to learn similarity preserving binary codes that jointly optimize both projection and quantization stages. Our work tackles an important problem of how to elegantly connect optimizing projection with optimizing quantization, and to maximize the complementary effects of two stages. Distinct from previous works, MRH can adaptively adjust the projection dimensionality to balance the information loss between projection and quantization. It is formulated as a problem of minimizing reconstruction bias of compressed signals. Extensive experiment results have shown the proposed MRH significantly outperforms a variety of state-of-the-art methods over several widely used benchmarks.
Vision-based scene representation for 3D interaction of service robots

In this paper, we present a new approach for scene understanding by an autonomous robot, using imaging sensors only. Our goal is to build in real-time a 3D representation of the scene which is suitable for further 3D interaction. We assume the scene is composed of a mix of known and unknown objects. We present a strategy to automatically build online a consistent 3D representation from a set computer vision algorithms results. We especially focus on 2 important aspects: the constraints and choices of each parts of the system, as well as the global layout of these parts, and the final step where all information are merged together to build a unique 3D representation. Results on real scene and system performance are finally showed to validate the proposed approach
ILLC-UvA translation system for EMNLP-WMT 2011

In this paper we describe the Institute for Logic, Language and Computation (University of Amsterdam) phrase-based statistical machine translation system for English-to-German translation proposed within the EMNLP-WMT 2011 shared task. The main novelty of the submitted system is a syntax-driven pre-translation reordering algorithm implemented as source string permutation via transfer of the source-side syntax tree.
Gauge fields, scalars, warped geometry, and strings

We review results on several interesting phenomena in warped compactifications of M theory, as presented at Strings 2000. The behavior of gauge fields in dimensional reduction from d + 1 to d dimensions in various backgrounds is explained from the point of view of the holographic duals (and a point raised in the question session at the conference is addressed). We summarize the role of additional fields (in particular scalar fields) in 5d warped geometries in making it possible for Poincare-invariant domain wall solutions to exist to a nontrivial order in a controlled approximation scheme without fine-tuning of parameters in the 5d action (and comment on the status of the singularities arising in the general relativistic description of these solutions). Finally, we discuss briefly the emergence of excitations of wrapped branes in warped geometries whose effective thickness, as measured along the Poincare slices in the geometry, grows as the energy increases.
Design guidance through the controlled application of constraints

Seeks to facilitate the development of high-quality software designs and architectures by using rigorous process definitions to guide the application of the complex structure of relations and constraints that define well-formedness. We identify various types of constraints and demonstrate specific instances of these types. We endorse the value of maintaining the integrity of these constraints by reacting to their violation with diagnostics and remedies. The sheer number and diversity of these constraints, however, indicates the desirability of a mechanism for controlling the scope and effect of their enforcement. Thus, we propose to use proactive process specifications to control the enforcement of and reaction to the various constraints. This results in a process-driven system that supports designers and architects by guiding them through orderly development and rework processes, disciplined by the application of constraint enforcement at the right times and in the right ways. This work entails research in defining both types and instances of constraints with programmable enforcement strategies, in embedding such constraints in processes, and in appropriate process definition formalisms.
An exploration of the characteristics and embeddedness of entrepreneurs in a rural community

A major objective of recent supranational and national policies has been the socio-economic equity and cohesion of all regions within the European Union (EU) and in the Irish state. Pezzini (2001) identifies that current policies reflect a shift in political thinking; policy makers now see sustainable development occurring through development strategies rather than fiscal ones. Rural entrepreneurship has been acknowledged in academic and government circles as a key driver in rural socio-economic development (Wortman, Jr., 1990; Irish Rural Development Programme 2007-2013; Common Agricultural Policy (CAP) Rural Development Plan 2007-2013). Despite its recognized importance, rural entrepreneurship has attracted little research attention, resulting in extensive knowledge gaps (Wortman, Jr. 1990; Statopoulou et al., 2004). Emergent literature suggests that the utilization of Actors Network Theory and a qualitative methodology will provide insights into the entrepreneurial process and how the rural context and the entrepreneur‟s social embeddedness within the local community (identified as the major differentiators between rural and urban entrepreneurship) both inhibits and enhances the entrepreneurial process (Statopoulou et al., 2004; Jack and Anderson 2002). Based on the foregoing, the objective of this study is to substantially contribute to extant knowledge by determining those factors that inhibit and facilitate rural entrepreneurs. In order to achieve the research objectives, a multi-case study approach is utilised, involving two rural destinations. Dunhill Enterprise Centre (DEC) and Dunhill, Fenor, Boatstrand and Annestown (DFBA) communities, as case examples. Consistent with the findings of the European Commission (2003), this study indicates that demographic and psychological characteristics do impact on rural entrepreneurs. This research found that the characteristics most likely to impact on rural entrepreneurs were sex, age, and period of time spent in business in the rural community. Also included under the demographic umbrella were education, previous work experience and family influences. When investigating psychological characteristics, the study found that the characteristics that directly impacted on rural entrepreneurs were independence, need for achievement, locus of control, risk-taking and tolerance of ambiguity. The study also revealed the importance of rural community embeddedness, in the form of relational, structural and positional embeddedness, in addition to highlighting the importance of business networking. These findings have particular implications for practitioners and policy makers in an Irish entrepreneurial context.
Detection and Characterization of Autoantibodies to Neuronal Cell-Surface Antigens in the Central Nervous System

Autoimmune encephalitis (AIE) is a group of disorders in which autoantibodies directed at antigens located on the plasma membrane of neurons induce severe neurological symptoms. In contrast to classical paraneoplastic disorders, AIE patients respond well to immunotherapy. The detection of neuronal surface autoantibodies in patients’ serum or CSF therefore has serious consequences for the patients’ treatment and follow-up and requires the availability of sensitive and specific diagnostic tests. This mini-review provides a guideline for both diagnostic and research laboratories that work on the detection of known surface autoantibodies and/or the identification of novel surface antigens. We discuss the strengths and pitfalls of different techniques for anti-neuronal antibody detection: (1) Immunohistochemistry (IHC) and immunofluorescence on rat/primate brain sections; (2) Immunocytochemistry (ICC) of living cultured hippocampal neurons; and (3) Cell Based Assay (CBA). In addition, we discuss the use of immunoprecipitation and mass spectrometry analysis for the detection of novel neuronal surface antigens, which is a crucial step in further disease classification and the development of novel CBAs.
Moderating Role of Thought Suppression Between Work Centrality, Life Role Salience and Dyadic Adjustment in Emergency Service Providers

Dyadic adjustment is a major facilitating factor in lifestyle of Emergency Service Providers (ESP). This research hypothesized that work centrality and life role salience are likely to be positively related to dyadic adjustment of ESP and thought suppression is likely to moderate the relationship between the above mentioned. using a within group research design, a sample of 110 male emergency service providers with age range from 24 to 40 years was obtained from Rescue 1122 headquarters and two government hospitals of Lahore, Pakistan. Dyadic Adjustment Scale (Spanier, 1988); Work Centrality Scale (Paullay, Alliger, & Stone-Romero, 1994); Life Role Salience Scale (Amatea, Cross, Clark, & Bobby, 1986); and White Bear Suppression Inventory (Wegner & Zanakos, 1994); were translated in Urdu. The findings indicated that occupational role commitment has significant positive relationship with dyadic adjustment while parental and homecare role commitment has significant negative relationships with it. Hierarchal Moderated Regression revealed that thought suppression significantly moderates the relationship between variables. This research offers an avenue to researchers to explore the trauma coping strategies and their influence in other healthcare professionals and implementation of couple and counseling therapies for those working under stressful conditions.
Mobility of legged robot by non-contact impedance control

In this paper, a legged mobile robot carrying the human is developed considering the adaptiveness for inaccessible environment at existing infrastructure. Also, as a method for avoiding the obstacles, the virtual impedance control method is proposed. This method can avoid an obstacle without contacting by receiving virtual force from virtual spring and damper installed in virtual surface region. Finally, the mobility of the legged robot by non-contacting impedance control is presented through some experiments.
Exploiting the Inter-cluster Record Reuse for Stream Processors

Memory accesses limit the performance of stream processors. The stream compiler exploits the reuse of records distributed on different ALU clusters by introducing inter-cluster communications, which decreases the program performance. The paper presents the Stream Transpose (ST) approach to exploit such reuse. The approach, by reorganizing the data, puts data that have been distributed on neighboring ALU clusters on the same ALU cluster, hence exploiting the reuse without any inter-Cluster communications. The experimental results show the approach can exploit the reuse of records distributed among ALU clusters without any inter-cluster communications or any decrease of accessing streams, and gains at most 1.46 speedup over the approach with inter-cluster communication.
Dynamic Adaptation of EHR Structure for Automated Compliance Evaluation

Integration of Clinical Practice Guidelines (CPGs) within Electronic Health Record (EHR) systems improves dissemination, implementation, and effective enactment of CPGs in the organizational workflow, but requires that some inherent contrasts be faced. On the one hand, tailoring the EHR structure so as to fit a restricted set of CPGs induces a bias towards specific pathologies. On the other hand, representation of all medical concepts that may become relevant for any applicable CPGs definitely impairs practical feasibility and usability.
Visual Error Analysis for Entity Linking

We present the Visual Entity Explorer (VEX), an interactive tool for visually exploring and analyzing the output of entity linking systems. VEX is designed to aid developers in improving their systems by visualizing system results, gold annotations, and various mention detection and entity linking error types in a clear, concise, and customizable manner.
Probabilistic combination of static and dynamic gait features for verification

This paper describes a novel probabilistic framework for biometric identification and data fusion. Based on intra and inter-class variation extracted from training data, posterior probabilities describing the similarity between two feature vectors may be directly calculated from the data using the logistic function and Bayes rule. Using a large publicly available database we show the two imbalanced gait modalities may be fused using this framework. All fusion methods tested provide an improvement over the best modality, with the weighted sum rule giving the best performance, hence showing that highly imbalanced classifiers may be fused in a probabilistic setting; improving not only the performance, but also generalized application capability.
Dependency analysis and loop transformation characteristics of auto-parallelizers

Automatic Parallelization play a key role in parallelizing legacy codes and manually written single-threaded codes. Auto-parallelizers like Cetus, Par4all, Pluto and Parallware help to parallelize sequential code without any manual intervention. Programmers working in the domain of parallel programming meet with challenges in maintaining the semantics of the code by preserving the dependencies of their original code. Parallelization in loops is significant since it takes maximum time for execution. It is to be noted that all loops are not parallelizable when the instructions in loops are dependent. Dependency analysis has become absolutely essential to retain the order in which the original code flows so that the code could run in parallel. Loop optimizations are significant in automatic parallelization for maximizing parallelism. This paper gives an outline of parallelization mechanisms mainly dependency analysis and loop transformation techniques. A case study has been carried out with auto-parallelizer tools to study and analyze their ability in locating and handling the dependencies by applying code transformation techniques in serial code while converting to parallel codes.
Politeness in the Contemporary Perspective

The purpose of this study is to determine the politeness view across academic community consisting of lecturers, students and education personnel in higher education to build a conductive climate in the academic world. This research uses descriptive qualitative method with descriptive analysis to find differences in politeness perceptions. The results of the study show a change in dress and language among academics. The diversity of perceptions that change requires contact in order to avoid misunderstandings in building communication during the learning process on campus.
A Pipeline for Computational Historical Linguistics

There are many parallels between historical linguistics and molecular phylogenetics. In this paper we describe an algorithmic pipeline that mimics, as closely as possible, the traditional workflow of language reconstruction known as the comparative method. The pipeline consists of suitably modified algorithms based on recent research in bioinformatics, which are adapted to the specifics of linguistic data. This approach can alleviate much of the laborious research needed to establish proof of historical relationships between languages. Equally important to our proposal is that each step in the workflow of the comparative method is implemented independently, so language specialists have the possibility to scrutinize intermediate results. We have used our pipeline to investigate two groups of languages, the Tsezic languages of the Caucasus and the Mataco-Guaicuruan languages of South America, based on the lexical data from the Intercontinental Dictionary Series (IDS). The results of these tests show that the current approach is a viable and useful extension to historical linguistic research.
Inverse reinforcement learning of behavioral models for online-adapting navigation strategies

To increase the acceptance of autonomous systems in populated environments, it is indispensable to teach them social behavior. We would expect a social robot, which plans its motions among humans, to consider both the social acceptability of its behavior as well as task constraints, such as time limits. These requirements are often contradictory and therefore resulting in a trade-off. For example, a robot has to decide whether it is more important to quickly achieve its goal or to comply with social conventions, such as the proximity to humans, i.e., the robot has to react adaptively to task-specific priorities. In this paper, we present a method for priority-adaptive navigation of mobile autonomous systems, which optimizes the social acceptability of the behavior while meeting task constraints. We learn acceptability-dependent behavioral models from human demonstrations by using maximum entropy (MaxEnt) inverse reinforcement learning (IRL). These models are generative and describe the learned stochastic behavior. We choose the optimum behavioral model by maximizing the social acceptability under constraints on expected time-limits and reliabilities. This approach is evaluated in the context of driving behaviors based on the highway scenario of Levine et al. [1].
Detecting Circles on Ego Network Based on Structure

As the online social network (OSN) develops, the social media data can be easily obtained, which leads to a large scale social network data. In our offline social networks, social relationships that an individual (ego) maintains with other people (alters) can also be organized into circles or groups according to the ego network model [1]. As to online social network, in order to help users cope with personal social network, many OSN sites provide services for users to group their friends. With many restrictions, such as on Facebook one cannot access other's personal information unless they establish ties with each other, the network structure is the only information known by users. In this paper, we propose an algorithm to find circles on personal social network mainly from the structural view. Based on the defined structural similarity and the condition where nodes constitute a circle, the algorithm is able to cluster the most similar nodes into the same circle. We then give proof to demonstrate the convergence of our algorithm. To show the effectiveness of our algorithm, we realize the algorithm on Facebook datasets. Compared with the community detection algorithm, the results are evaluated from the visualized quantified aspect. From the results, we find that community detection algorithm cannot directly deal with the circle detection problem due to the characteristic of ego network and our algorithm can effectively handle the circle detection on ego network.