Miracle-dz/UniFAR-FTUs huggingface dataset:
Teaching Statistics to Social Science Students: Making It Valuable.

In this age of rapid information expansion and technology, statistics is playing an ever increasing role in education, particularly also in the training of social scientists. Statistics enables the social scientist to obtain a quantitative awareness of socioeconomic phenomena hence is essential in their training. Statistics, however, is becoming increasingly problematic in its influence on the lives of social science students. Has statistics education of social science students evolved in order to keep pace with changes in modern society? This article examines the common trends in teaching statistics to social science students and then makes some suggestions that would potentially increase the social science graduate's appreciation for the power of statistics in their profession. South African Journal of Higher Education Vol. 20(4) 2006: pp.503-514
The Design of Writing: Unfolding systems of meaning

This article explores the findings of a small research study that asked writers to describe a meaningful, personal incident using first narrative and then poetic forms. The poetry raised many anxieties about writing, including the revelations of subjectivity and the risks in sharing such work with a group. To understand some of the complexities of these responses, the researchers thought of writing as an ecology with interdependent systems influencing the writing. Rereading the research texts, they traced some of those systems that affect students' writing and understanding of poetry.
Overdrive an overlay-based geocast service for smart traffic applications

For smart traffic scenarios, communication between traffic participants is of high importance. Classical approaches (e.g. for information about congestions) employ a server-based architecture, which raises scalability and privacy concerns. In this paper, we propose OverDrive, a decentralized overlay-based geocast service that is applicable in smart traffic scenarios and not prone to the shortcomings of centralized designs. Information requests for points in geographic space are routed directly via traffic participants until they reach a node in the proximity of that point. In contrast to other approaches, our overlay is specifically tailored towards supporting mobile nodes-vehicles connected via cellular networks-and leverages their speed and direction for optimizing peering decisions and minimizing maintenance overhead. Exhaustive simulations in complex smart traffic scenarios show that OverDrive achieves high delivery ratios even in high mobility environments. At the same time, communication overhead is kept low, making OverDrive suitable for the use with cellular networks.
Electronic Reprint Biological Crystallography Likelihood-enhanced Fast Translation Functions Biological Crystallography Likelihood-enhanced Fast Translation Functions

Author(s) of this paper may load this reprint on their own web site provided that this cover page is retained. Republication of this article or its storage in electronic databases or the like is not permitted without prior permission in writing from the IUCr. This paper is a companion to a recent paper on fast rotation functions [Storoni et al. which showed how a Taylor-series expansion of the maximum-likelihood rotation function leads to improved likelihood-enhanced fast rotation functions. In a similar manner, it is shown here how linear and quadratic Taylor-series expansions and least-squares approximations of the maximum-likelihood translation function lead to likelihood-enhanced translation functions, which can be calculated by FFT and which are more sensitive to the correct translation than the traditional correlation-coefficient fast translation function. These likelihood-enhanced translation targets for molecular-replacement searches have been implemented in the program Phaser using the Computational Crystallography Toolbox (cctbx).
CD8α+ Dendritic Cells Selectively Present MHC Class I-Restricted Noncytolytic Viral and Intracellular Bacterial Antigens In Vivo1

CD8α+ dendritic cells (DCs) have been shown to be the principal DC subset involved in priming MHC class I-restricted CTL immunity to a variety of cytolytic viruses, including HSV type 1, influenza, and vaccinia virus. Whether priming of CTLs by CD8α+ DCs is limited to cytolytic viruses, which may provide dead cellular material for this DC subset, or whether these DCs selectively present intracellular Ags, is unknown. To address this question, we examined Ag presentation to a noncytolytic virus, lymphocytic choriomeningitis virus, and to an intracellular bacterium, Listeria monocytogenes. We show that regardless of the type of intracellular infection, CD8α+ DCs are the principal DC subset that initiate CD8+ T cell immunity.
On the numerical stability and accuracy of the conventional recursive least squares algorithm

We study the nonlinear round-off error accumulation system of the conventional recursive least squares algorithm, and we derive bounds for the relative precision of the computations in terms of the conditioning of the problem and the exponential forgetting factor, which guarantee the numerical stability of the finite-precision implementation of the algorithm; the positive definiteness of the finite-precision inverse data covariance matrix is also guaranteed. Bounds for the accumulated round-off errors in the inverse data covariance matrix are also derived. In our simulations, the measured accumulated roundoffs satisfied, in steady state, the analytically predicted bounds. We consider the phenomenon of explosive divergence using a simplified approach; we identify the situations that are likely to lead to this phenomenon; simulations confirm our findings.
A signature pattern of stress-responsive microRNAs that can evoke cardiac hypertrophy and heart failure

Diverse forms of injury and stress evoke a hypertrophic growth response in adult cardiac myocytes, which is characterized by an increase in cell size, enhanced protein synthesis, assembly of sarcomeres, and reactivation of fetal genes, often culminating in heart failure and sudden death. Given the emerging roles of microRNAs (miRNAs) in modulation of cellular phenotypes, we searched for miRNAs that were regulated during cardiac hypertrophy and heart failure. We describe >12 miRNAs that are up- or down-regulated in cardiac tissue from mice in response to transverse aortic constriction or expression of activated calcineurin, stimuli that induce pathological cardiac remodeling. Many of these miRNAs were similarly regulated in failing human hearts. Forced overexpression of stress-inducible miRNAs was sufficient to induce hypertrophy in cultured cardiomyocytes. Similarly, cardiac overexpression of miR-195, which was up-regulated during cardiac hypertrophy, resulted in pathological cardiac growth and heart failure in transgenic mice. These findings reveal an important role for specific miRNAs in the control of hypertrophic growth and chamber remodeling of the heart in response to pathological signaling and point to miRNAs as potential therapeutic targets in heart disease.
Skill Acquisition Through Program-Level Imitation in a Real-Time Domain

This paper presents an imitation learning system capable of learning tasks in a complex dynamic real-time environment. In this paper, we argue that social learning should be thought of as a special case of general skill learning, and that the biases it presents to the skill learning problem radically simplify learning for species with sufficient innate predisposition to harness this power. We decompose skill learning into four subproblems, then show how a modification of Roy's CELL system can address all these problems simultaneously. Our system is demonstrated working in the domain of a real-time virtual-reality game, Unreal Tournament
Ribosomal frameshifting in decoding antizyme mRNAs from yeast and protists to humans: close to 300 cases reveal remarkable diversity despite underlying conservation

The protein antizyme is a negative regulator of intracellular polyamine levels. Ribosomes synthesizing antizyme start in one ORF and at the codon 5′ adjacent to its stop codon, shift +1 to a second and partially overlapping ORF which encodes most of the protein. The ribosomal frameshifting is a sensor and effector of an autoregulatory circuit which is conserved in animals, fungi and protists. Stimulatory signals encoded 5′ and 3′ of the shift site act to program the frameshifting. Despite overall conservation, many individual branches have evolved specific features surrounding the frameshift site. Among these are RNA pseudoknots, RNA stem-loops, conserved primary RNA sequences, nascent peptide sequences and branch-specific ‘shifty’ codons.
Beyond the core: Enabling software-defined control at the network edge

Software-defined networking (SDN) changes the structure of core networks from statically planned to flexible and adaptable to the network conditions. The de facto standard for the interaction between the controller and the forwarding devices (e.g., SDN switches) is the OpenFlow protocol. With increasing interest in SDN technologies, researchers found solutions to extend these paradigms to end devices, like it is done with the protocol virtualization framework VirtualStack. However, the current SDN protocols such as OpenFlow are unsuitable for controlling end devices, since they are designed for core network nodes. In this paper, we close this gap by presenting TROLL — a protocol suggestion for realizing software-defined control at the network edge. With the communication between the controller and the VirtualStack-enabled end devices being defined by TROLL, control decisions can be made jointly for both the network core and the edge, improving the flexibility, adaptability, and efficiency of the network system significantly.
Constraint based recipe recommendation using forward checking algorithm

With the advanced research in medical science and technology, quality of our life has improved, also life span has been increased. With life style, diet habits has changed and work pressure increased which resulted in number of diseases, such as diabetes, Blood Pressure, heart problem etc. These diseases can be controlled to certain extent by avoiding uneven and inappropriate diet. Hence it is important to understand good diet and intake habits. Our objective is to recommend recipes to maintain health condition for people with disease and without disease which will satisfy the user needs. To present the recommendations, recommended system uses user's profile, favorite items and recipe details. This explicit knowledge satisfies the constraints for the recommendation. In this paper we propose a recommendation system for recipe using constraint knowledge based recommendation method (CKRM) and forward checking algorithm. The proposed system suggests recipe for diabetes disease which provides improved precision and recall. This depicts that proposed system is efficient than existing system. The reason to select this method is that it does not have ramp-up problem. The constraints which satisfy user's requirement will be the good recipe recommendation.
An energy efficient DRAM subsystem for 3D integrated SoCs

Energy efficiency is the key driver for the design optimization of System-on-Chips for mobile terminals (smartphones and tablets). 3D integration of heterogeneous dies based on TSV (through silicon via) technology enables stacking of multiple memory or logic layers and has the advantage of higher bandwidth at lower energy consumption for the memory interface. In this work we propose a highly energy efficient DRAM subsystem for next-generation 3D integrated SoCs, which will consist of a SDR/DDR 3D-DRAM controller and an attached 3D-DRAM cube with a fine-grained access and a very flexible (WIDE-IO) interface. We implemented a synthesizable model of the SDR/DDR 3D-DRAM channel controller and a functional model of the 3D-stacked DRAM which embeds an accurate power estimation engine. We investigated different DRAM families (WIDE IO DDR/SDR, LPDDR and LPDDR2) and densities that range from 256Mb to 4Gb per channel. The implementation results of the proposed 3D-DRAM subsystem show that energy optimized accesses to the 3D-DRAM enable an overall average of 37% power savings as compared to standard accesses. To the best of our knowledge this is the first design of a 3D-DRAM channel controller and 3D-DRAM model featuring co-optimization of memory and controller architecture.
Empowering people through reframing: experiences of guidance practitioners in a public network of career centres

In this article, empowerment is assumed as a phenomenon strictly related to agency dynamics and to the reflective abilities of actors in a given organisational context, which allow their own personal and professional fulfilment. The article is the outcome of a reflective interview in which the authors involved themselves, at the end of a two‐year co‐operation for the development of the Leonardo da Vinci Reflect‐OR project. Five main processes of empowerment are taken into account related to the paths of professional identity construction, the opportunities for competence development, the functioning of the community of practice, the spaces for emotions and the opportunities for transformation. In the final remarks, the subjective side of empowerment is emphasised and some lines for future deepening of the above issues are highlighted.
The Development and Psychometric Testing of the Geriatric Health Promotion Scale

Background: As life expectancy increases, being old is no longer synonymous with frailty, weakness, or poor health. Today, most people expect to maintain or promote their health by adopting healthy lifestyle habits. Purpose: This study developed and tested the psychometric Geriatric Health Promotion (GHP) scale. The GHP scale is a multidimensional instrument that attempts to evaluate lifestyle patterns prevalent among senior citizens in Taiwan. Methods: Data used in this study were acquired from a large health-promotion study that targeted elderly residents of rural areas in Taiwan. All subjects were aged 65 years or older and resided in the four communities with the highest mean age ratios in the nation. Trained research assistants assisted the participants to answer the research instrument questions. Results: A total of 520 participants over 65 years of age (mean = 75.02 ± 6.04) were enrolled in this study. The initial draft of the GHP scale included 33 items. After conducting the item analysis, correlation analysis, and factor analysis, the final draft of the GHP was reduced to 22 items. A six-factor solution with Varimax rotation offered the most parsimonious model, with health habits, community participation, health responsibilities, healthy diet, regular exercise, and oral health, explaining 68% of the total variance. The Cronbach’s alpha for the developed model scored as high as . 94, with a test–retest reliability of . 72 (p < .001). Conclusions/Implications for Practice: The GHP scale is a valid self-report instrument for community-dwelling older adults. The GHP scale is easily administered in less than 10 minutes. We recommend that healthcare providers use the GHP scale to evaluate the effectiveness of health promotion programs targeting older adults.
Experiencing Ethnic Economies: Brazilian Immigrants and Returnees

Brazilian immigrants in the United States experience socioeconomic changes and engage in various professional occupations. Migrant livelihoods and experiences are affected in two receiving communities in the United States (Framingham, Massachusetts, and Marietta, Georgia), and in two sending communities in Brazil (Governador Valadares and Piracanjuba). What are the most common professional occupations among Brazilians immigrants, and what were their professional occupations prior to migrating? How are immigrants’ livelihoods and experiences being shaped by current economic exchanges spurred by immigration? I evaluate these important questions by looking at changes at the micro-level, within migrants’ occupations, experiences, and economic transactions. By weaving though survey results and excerpts from a total of 273 interviews in two receiving communities and returnees in two sending communities, I illustrate how migration processes have significantly affected ethnic economies and livelihoods at the micro-level in both receiving and sending communities. Most returnees had worked in service sector occupations, such as construction work among men, and housecleaning among women; and, among those who remained in the United States, became business owners, teachers, or continued to work within service sectors.
The Influence Factors of Energy Efficiency in China Based on Meta-Regression

This paper is based on the controversies which the existing empirical researches about the impact of the basic factors affecting energy efficiency have in index selection and direction, using the method of meta-regression to analyze the related domestic empirical studies comprehensively. We conduct a study on the differences of research design, data characteristics, time span and the index selection, to check whether these differences cause the controversies in index selection and direction. The result shows that the research design, empirical methods, and the characteristics of the selection of indicators have significant impact on the result of empirical researches. The contradiction between higher energy consumption and lower energy efficiency makes energy shortage more and more serious. In 2010, the World Bank in its "Report of the development level of human society" considered the energy efficiency as one of the key indicators to measure the progress of human society and economic development. As the developing countries faces the challenge of economic growth resulted by energy shortages and energy crises, the 18th of the National People's Congress pointed out to control energy consumption, and used "Energy Revolution" to reveal the importance and seriousness of the energy efficiency. Thus make efficient use of energy become a hot topic for scholars competing to study, then confirm the influence factor on energy efficiency and find out the interaction mechanism of these factors become the starting point to solve the lower energy efficiency. The researches in this field are rather rich.
Learning Table Extraction from Examples

Information extraction from tables in web pages is a challenging problem due to the diverse nature of table formats and the vocabulary variants in attribute names. This paper presents a new approach to automated table extraction that exploits formatting cues in semi-structured HTML tables, learns lexical variants from training examples and uses a vector space model to deal with non-exact matches among labels. We conducted experiments with this method on a set of tables collected from 157 university web sites, and obtained the information extraction performance of 91.4% in the Fl-measure, showing the effectiveness of the combined use of structural table parsing and example-based label learning.
Capacity of Mass Participant Sport Events for the Development of Activity Commitment and Future Exercise Intention

Mass participation sport events are often cited as increasing population-level physical activity, but empirical evidence is scarce as to their effectiveness. The current research examined the developmental role of these events in increasing positive attitudes toward physically active leisure by a) determining its motivational capacity and b) investigating how sport event participation contributes to activity commitment and future exercise intentions. A multiattribute survey was distributed on-line to participants of a running event held in Philadelphia, Pennsylvania, (N = 2,791) three months after the event. Inferential statistics revealed that 10 motives directed participation across 75% of the population. Multivariate multiple linear regression analyses revealed event participation motives combined with event satisfaction and physical activity involvement explained 30% of running commitment and 31% of future exercise intentions. Most notably, the event promoted stronger attitudes toward regular exercise among participants who were more satisfied with their event experience, least active before the event, and had completed fewer prior organized events. This evidence demonstrates that mass participant sporting events can serve as important social and environmental correlates of physical activity.
Limitations of the TheraMon®‐microsensor in monitoring occlusion therapy

A proof of principle study showed that the TheraMon®‐microsensor can reliably measure wearing times of glasses and occlusion patches while having no discomfort for the bearer. The goal of this study was to identify specific temperature profiles in a larger patient group wearing the microsensor with an occlusion patch on the eye, the forehead or in the trouser pocket.
Deciding Weak Weighted Bisimulation

Weighted labelled transition systems are LTSs whose transitions are given weights drawn from a commutative monoid, subsuming a wide range of systems with quantitative aspects. In this paper we extend this theory towards other behavioural equivalences, by considering semirings of weights. Taking advantage of this extra structure, we consider a general notion of weak weighted bisimulation, which coincides with the usual weak bisimulations in the cases of non-deterministic and fully-probabilistic systems. We present a general algorithm for deciding weak weighted bisimulation. The procedure relies on certain systems of linear equations over the semiring of weights hence it can be readily instantiated to a wide range of models. We prove that these systems admit a unique solution for ω-continuous semirings.
Spirometry Data Analysis and Classification Using Data Mining: An Approach

milind.btk gmail.com Abstract- In this paper, the acquisition of Spirometry data such as Forced Expiratory Volume in 1 second (FEV1), Force Vital Capacity (FVC) and Small Vital Capacity will be carried out using Spirometer. At current, numbers of lung diseases are main hazard to the human health due to air pollution, smoking and other infections. The various Artificial Neural Network methods for the taxonomy of Spirometry data are Back Propagation Network (BPN), Radial Basis Function (RBF) and Multilayer Perceptron Neural Network (MLPNN). The aim of the present study is to acquire parameter such as FVC, FEV1 and SVC data and use Data Mining Algorithm for classification of the Spirometer data into Normal, Obstructive and Restrictive dataset. This approach is used to increase the efficiency of classification