Miracle-dz/UniFAR-FTUs huggingface dataset:
Short‐ and long‐term modulation of upper limb motor‐evoked potentials induced by acupuncture

The aim of this study was to investigate in humans the effects of acupuncture upon upper‐limb motor‐evoked potentials (MEPs), elicited by transcranial magnetic stimulation of the primary motor cortex. It is known that peripheral sensory stimulation can be used to induce short‐ and long‐term changes in motor cortex excitability. Data show that the simple insertion of the needle is an adequate somatosensory stimulus to induce a significant modulation of MEP amplitude, the sign of which (facilitation or inhibition) is specific to the investigated muscle and to the point of needle insertion. Moreover, MEP changes in upper‐limb muscles are also observed following needling of lower‐limb sites, revealing the presence of long‐distance effects of acupuncture. Finally, the modulation in muscle excitability considerably outlasts the time period of needle application, demonstrating the induction of long‐term plastic changes in the central nervous system. In addition, results have shown that the effects on muscle excitability are not restricted to the stimulation of well‐coded acupoints, as described in traditional Chinese medicine, but they can also be induced by needling of nonacupoints, normally not used for therapeutic purposes. The possible neuronal mechanisms underlying the observed effects of acupuncture are discussed in relation to the available neurophysiological data regarding the interlimb reflexes and the changes in the representational cortical maps induced in humans by a prolonged somatosensory stimulation.
Effects of Green Revolution strategies on tenants and small-scale landowners in the Chilalo region of Ethiopia

Ethiopia is one of the least developed countries in the world, yet it has a natural endowment of adequate land mass, generally fertile soils, sufficient rainfall, and a considerable variety of climates and elevations. ' This natural resource base and the existence of a large, hardworking peasantry indicate that Ethiopia has enormous agrarian potential, but unfortunately a potential far from realization. More than 85 percent of the 25 million Ethiopian people earn their livelihood from subsistence agriculture. Total agricultural output is 55-60 percent of gross domestic product (one of the highest such figures in the world), and the nonmonetary sector is probably 75 percent of this total. The monetary sector of agrieulture accounts for more than 90 percent of exports, with some 60 percent of this figure depending on coffee. Finally, the annual growth rate in agriculture during the last decade averaged about 2.4 percent, which is probably less than the overall population growth during the same period. As a result, Ethiopia has one of the lowest per capita income levels in the world.
Thermal Interface Resistance Measurements for GaN-on-Diamond Composite Substrates

The performance of high-power gallium nitride (GaN) high-electron-mobility transistors (HEMTs) is limited by self-heating effects. High thermal resistances within micrometers of the active device junction often dominate the junction temperature rise and fundamentally limit the device power handling capability. The use of high-thermal-conductivity diamond in close proximity to the transistor junction can mitigate this thermal constraint, but careful attention is required to the quality of the thermal interface between the GaN and diamond. Here we apply time-domain thermoreflectance (TDTR) to two GaN-on-diamond composite substrates with varying GaN thicknesses to measure the thermal interface resistance between the GaN and diamond (29 m2 K GW-1) as well as the thermal conductivity of the GaN buffer layer (112 W m-1 K-1) at room temperature. Informed by these data, we perform finite-element analysis to quantify the relative impact of the GaN-diamond thermal interface resistance, diamond substrate thermal conductivity, and a convective cooling solution on the device channel temperature rise.
PriCal: dynamic privacy adaptation of collaborative calendar displays

Office wall calendars often contain only entries considered public, which reduces their utility for scheduling meetings or gaining an overview of one's schedule. PriCal is a collaborative calendar display that dynamically adapts to present persons and their privacy preferences. We outline our current prototype, consisting of a calendar agent for display adaptation, a mobile app for managing individual calendars and privacy settings, and a system for detecting present persons and identifying registered users.
Title I Elementary School Principals' Perspectives on Teacher Preparedness: University-Based Alternative Teacher Preparation for Urban Schools

TITLE I ELEMENTARY SCHOOL PRINCIPALS‘ PERSPECTIVES ON TEACHER PREPAREDNESS: UNIVERSITY-BASED ALTERNATIVE TEACHER PREPARATION FOR URBAN SCHOOLS by Pamela L. Gayles Colleges of education produce the majority of teacher educators in the United States. Additionally, over half of the alternative teacher preparation programs in the United States are administered by colleges of education. However, the literature reveals that few institutions concentrate on urban teacher preparation and that teacher-reform efforts have continuously insisted on high-quality teachers for high-need urban schools. This work addresses the existing gap in the extant research on urban schools by including the voices of school principals that are often unsolicited when discussing teacher preparation reform, particularly reform efforts responding to the staffing needs of Title I urban schools. This study explores the perceptions that Title I principals have of urban teaching, urban school challenges, and, most importantly, of urban teacher preparation. Individual interviews were conducted with four Title I urban elementary school principals from public schools in the Southeast. Additionally, an analysis of documents was conducted from five university-based urban alternative teacher preparation programs. Results from this research reveal that Title I school principals are aware of their staffing needs and challenges and are equally attuned to what they consider to be critical aspects of teacher preparation for Title I urban schools. This dissertation also highlights efforts underway in colleges and universities across the United States that are utilizing urban alternative teacher preparation to address staffing needs in urban schools. These efforts challenge the negative accusations about and allegations against both college of education and alternative teacher preparation programs‘ inability to produce wellprepared teachers for all children, especially disadvantaged youth. TITLE I ELEMENTARY SCHOOL PRINCIPALS‘ PERSPECTIVES ON TEACHER PREPAREDNESS: UNIVERSITY-BASED ALTERNATIVE TEACHER PREPARATION FOR URBAN SCHOOLS by Pamela L. Gayles
Closed-Form Solutions to an Economic Growth Logistic Model with Migration

This paper presents a Solow Growth Model with the labor force ruled by the logistic equation added by a constant migration rate, I. We prove the global asymptotic stability of the capital and production per capita. Considering a Cobb-Douglas production function, we show this model to have a closed-form solution. This transient behavior is expressed in terms of the Beta and Appell F1 functions. We also show that if I > 0, it implies in a higher (minor) output of the economy, and in a minor (greater) capital and production per capita in the short term (middle and long term); furthermore, these ratios converge to the same steady-state value of the no-migration model; if I
Constructive synchronization of networked feedback systems

This paper is concerned with global asymptotic output synchronization in networks of identical feedback systems. Using an operator theoretic approach based on an incremental small gain theorem, the method reformulates the synchronization problem as one of achieving incremental stability using a coupling operator that plays the role of an incrementally stabilizing feedback. In this way, conditions on static or dynamic coupling operators that achieve output synchronization of nodes of arbitrary structure are derived. These conditions lead to a methodology for the construction of coupling architectures that ensure output synchronization of a wide range of systems. The result is illustrated for a network of biochemical oscillators.
Dysfunctional beliefs and attitudes about sleep (DBAS): validation of a brief version (DBAS-16).

STUDY OBJECTIVE Sleep related cognitions (e.g., faulty beliefs and appraisals, unrealistic expectations, perceptual and attention bias) play an important role in perpetuating insomnia. This paper presents new psychometric data on an abbreviated version of the Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS-16), a 16-item self-report measure designed to evaluate a subset of those sleep related cognitions. DESIGN Psychometric study of a patient-reported measure of sleep related beliefs based on existing clinical and research databases. PARTICIPANTS A total of 283 individuals (60% women; mean age of 46.6 years old) with insomnia, including 124 clinical patients and 159 research participants. MEASUREMENTS AND RESULTS Participants completed the DBAS, Insomnia Severity Index, Beck Depression and Anxiety Inventories, daily sleep diaries for 2 weeks, and 3 nights of polysomnography (research sample only) as part of a baseline assessment. The DBAS-16 was found to be reliable, as evidenced by adequate internal consistency (Cronbach alpha = 0.77 for clinical and 0.79 for research samples) and temporal stability (r = 0.83). The factor structure was similar to the original 30-item version, with 4 factors emerging and reflecting: (a) perceived consequences of insomnia, (b) worry/helplessness about insomnia, (c) sleep expectations, and (d) medication. DBAS total scores were significantly correlated with other self-report measures of insomnia severity, anxiety, and depression, but not with specific sleep parameters. CONCLUSION The psychometric qualities of this abbreviated DBAS-16 version seem adequate. This patient-reported measure should prove a useful instrument to evaluate the role of sleep related beliefs and attitudes in insomnia and to monitor change on this cognitive variable as a potential moderator of treatment outcome.
G-path: flexible path pattern query on large graphs

With the socialization trend of web sites and applications, the techniques of effective management of graph-structured data have become one of the most important modern web technologies. In this paper, we present a system of path query on large graphs, known as G-Path. Based on Hadoop distributed framework and bulk synchronized parallel model, the system can process generic queries without preprocessing or building indices. To demonstrate the system, we developed a web-based application which allows searching entities and relationships on a large social network, e.g., DBLP publication network or Twitter dataset. With the flexibility of G-Path, the application is able to handle different kinds of queries. For example, a user may want to search for a publication graph of an author while another user may want to search for all publications of the author's co-authors. All these queries can be done by an interactive user interface and the results will be shown in a visual graph.
The Credit Scoring Toolkit: Theory and Practice for Retail Credit Risk Management and Decision Automation

The Credit Scoring Toolkit provides an all-encompassing view of the use of statistical models to assess retail credit risk and provide automated decisions. In eight modules, the book provides frameworks for both theory and practice. It first explores the economic justification and history of Credit Scoring, risk linkages and decision science, statistical and mathematical tools, the assessment of business enterprises, and regulatory issues ranging from data privacy to Basel II. It then provides a practical how-to-guide for scorecard development, including data collection, scorecard implementation, and use within the credit risk management cycle. Including numerous real-life examples and an extensive glossary and bibliography, the text assumes little prior knowledge making it an indispensable desktop reference for graduate students in statistics, business, economics and finance, MBA students, credit risk and financial practitioners.
Finding directed acyclic graphs for vector autoregressions.

In this paper graphical modelling is used to select a sparse structure for a multivariate time series model of New Zealand interest rates. In particular, we consider a recursive structural vector autoregressions that can subsequently be described parsimoniously by a directed acyclic graph, which could be given a causal interpretation. A comparison between competing models is then made by considering likelihood and possibly economic theory.
Benchmark graphs for the evaluation of clustering algorithms

Artificial graphs are commonly used for the evaluation of community mining and clustering algorithms. Each artificial graph is assigned a pre-specified clustering, which is compared to clustering solutions obtained by the algorithms under evaluation. Hence, the pre-specified clustering should comply with specifications that are assumed to delimit a good clustering. However, existing construction processes for artificial graphs do not set explicit specifications for the pre-specified clustering. We call these graphs, randomly clustered graphs. Here, we introduce a new class of benchmark graphs which are clustered according to explicit specifications. We call them optimally clustered graphs. We present the basic properties of optimally clustered graphs and propose algorithms for their construction. Experimentally, we compare two community mining algorithms using both randomly and optimally clustered graphs. Results of this evaluation reveal interesting insights both for the algorithms and the artificial graphs.
Number detection in natural image with boosting classifier

The number detection is useful in various applications such as license plate localization, detection of number button in elevator, and detection of exit number sign in public transport station. In this paper, we propose number detection methods in natural image using AdaBoost based on Modified Census Transform (MCT) features. It is a difficult task to detect numbers, characters, and specific symbols, because natural image includes many noises. Especially, illumination change is one of the most annoying sources of noise in the field of number detection based on image processing. Our number detection method uses many MCT features, which are robust to illumination change and AdaBoost for the feature selection to overcome this restriction. Experimental results show that the proposed method has a high detection rate in our license plate database which has been captured in the natural environment.
Making more flexible ATISMART+ model for traffic simulations using a CAS

Traffic simulations usually require the search of a path to join two different points. Dijkstra’s algorithm [1] is one of the most commonly used for this task due to its easiness and quickness. In [2, 3] we developed an accelerated time simulation of car traffic in a smart city using Dijkstra’s algorithm to compute the paths. Dijkstra’s algorithm provides a shortest path between two different points but this is not a realistic situation for simulations. For example, in a car traffic situation, the driver may not know the shortest path to follow. This ignorance can be produced, among others, because one of the following two facts: the driver may not know the exact length of the lanes, or, even knowing the exact length, the driver may not know how to find the shortest path. Even more, in many cases, a mixture of both facts occurs. A more realistic simulation should therefore consider these kind of facts. The algorithm used to compute the path from one point to another in a traffic simulation might consider the possibility of not using the shortest path. In this talk, we use a new probabilistic extension of Dijkstra’s algorithm which covers the above two situations. For this matter, two different modifications in Dijkstra’s algorithm have been introduced: using non-exact length in lanes, and the choice of a non-shortest path between two different points. Both modifications are used in a non-deterministic way by means of using probability distributions (classical distributions such as Normal or Poisson distributions or even "ad hoc" ones). A precise, fast, natural and elegant way of working with such probability distributions is the use of a CAS in order to deal with exact and explicit computations. As an example of use of this extension of Dijkstra’s algorithm, we will show the ATISMART+ model. This model provides more realistic accelerated time simulations of car traffics in a smart city and was first introduced in [4] and extended in [5]. This model was developed combining JAVA for the GUI and MAXIMA for the mathematical core of the algorithm. The studies developed in the above mentioned works, dealt with Poisson, Exponential, Uniform and Normal distributions. In this talk we will introduce, as a novelty, the possibility of using other continuous probability distributions such as: Lognormal, Weibul, Gamma, Beta, Chi-Square, Student’s t, Z, Pareto, Logistic, Cauchy or Irwin-Hall, and other discrete distributions such as: Bernouille, Rademacher, Binomial, Geometric, Negative Binomial or Hypergeometric. Even
The Reform of the Dutch Public Employment Service

This book argues that active labour market policies are necessary to improve the position of the unemployed but have so far performed relatively poorly. The contributing authors seek ways to improve active labour market policy and consider three means of doing so: improving the quality by better targeting and by better-designed measures, more efficient implementation and delivery, and better performance by benchmarking the various implementation agencies involved.
Privacy and Security in the Genomic Era

With the help of rapidly developing technology, DNA sequencing is becoming less expensive. As a consequence, the research in genomics has gained speed in paving the way to personalized (genomic) medicine, and geneticists need large collections of human genomes to further increase this speed. Furthermore, individuals are using their genomes to learn about their (genetic) predispositions to diseases, their ancestries, and even their (genetic) compatibilities with potential partners. This trend has also caused the launch of health-related websites and online social networks (OSNs), in which individuals share their genomic data (e.g., OpenSNP or 23andMe). On the other hand, genomic data carries much sensitive information about its owner. By analyzing the DNA of an individual, it is now possible to learn about his disease predispositions (e.g., for Alzheimer's or Parkinson's), ancestries, and physical attributes. The threat to genomic privacy is magnified by the fact that a person's genome is correlated to his family members' genomes, thus leading to interdependent privacy risks. This short tutorial will help computer scientists better understand the privacy and security challenges in today's genomic era. We will first highlight the significance of genomic data and the threats for genomic privacy. Then, we will present the high level descriptions of the proposed solutions to protect the privacy of genomic data and we will discuss future research directions. No prerequisite knowledge on biology or genomics is required for the attendees of this proposal. We only require the attendees to have a slight background on cryptography and statistics.
A review of methods of analysis in contouring studies for radiation oncology

Inter‐observer variability in anatomical contouring is the biggest contributor to uncertainty in radiation treatment planning. Contouring studies are frequently performed to investigate the differences between multiple contours on common datasets. There is, however, no widely accepted method for contour comparisons. The purpose of this study is to review the literature on contouring studies in the context of radiation oncology, with particular consideration of the contouring comparison methods they employ. A literature search, not limited by date, was conducted using Medline and Google Scholar with key words: contour, variation, delineation, inter/intra observer, uncertainty and trial dummy‐run. This review includes a description of the contouring processes and contour comparison metrics used. The use of different processes and metrics according to tumour site and other factors were also investigated with limitations described. A total of 69 relevant studies were identified. The most common tumour sites were prostate (26), lung (10), head and neck cancers (8) and breast (7). The most common metric of comparison was volume used 59 times, followed by dimension and shape used 36 times, and centre of volume used 19 times. Of all 69 publications, 67 used a combination of metrics and two used only one metric for comparison. No clear relationships between tumour site or any other factors that may influence the contouring process and the metrics used to compare contours were observed from the literature. Further studies are needed to assess the advantages and disadvantages of each metric in various situations.
Face Recognition with Statistical Local Line Binary Pattern

In this paper, we present an improved method for face recognition named statistical Local Line Binary Pattern (SLLBP), which is based on Local Binary Pattern (LBP). The basic idea of the algorithm is to first obtain the local binary code along with horizontal and vertical direction separately and the gray-level difference between neighbor pixels, which is also important to describe a face feature and often been ignored, is then computed. To deal with the gray-level difference we firstly take a statistical analysis on the probability distribution of the gray-level difference values, and then a mapping function is used to encode the range of these values. Our algorithm is tested on the public ORL face database. The experimental results show that the method improves the performance significantly.
Si(3)N(4)-bioglass composites stimulate the proliferation of MG63 osteoblast-like cells and support the osteogenic differentiation of human bone marrow cells.

The in vitro osteocompatibility of a novel Si(3)N(4)-bioglass composite (70-30% weight proportion) with improved mechanical properties (fracture toughness = 4.4 M Pa m(1/2); bending strength = 383 +/- 47 MPa) is reported. Immersion of the composite samples in culture medium (30 min to 7 days) resulted in rapid protein adsorption to the surface and, also, dissolution of the intergranular phase of bioglass (time-dependent process) with the formation of different size cavities. "As-received" and pre-treated material samples presented a similar behaviour concerning the proliferation of MG63 osteoblast-like cells, evaluated during a 5-day culture period. Seeded materials showed a higher cell growth rate as compared to cultures performed on the standard plastic culture plates. To assess the osteogenic potential of the composite, "as-received" material samples were seeded with human bone marrow cells and cultured for 35 days in experimental conditions that favour the development of the osteoblastic phenotype. The cell adhesion process was similar to that observed in control cultures. Cells successfully adapted to the irregularities of the surface and were able to grow towards inside the cavities; in addition, osteogenic differentiation occurred with the formation of abundant cell-mediated mineralised deposits. Results suggest that this Si(3)N(4)-bioglass composite seems to be a promising candidate for high-stress medical applications.