Miracle-dz/UniFAR-FTUs huggingface dataset:
EXPERIMENTAL STUDIES OF PERSONALITY ETHIC-PSYCHOLOGICAL CHARACTERISTICS

The study is devoted to the actual problem, which is of great practical importance. The process of developing influence of psychologists on the ethical and psychological characteristics is not supported often by an adequate, valid psychodiagnostic support. In this regard, the problem of effective method development for the diagnosis of the ethic-psychological qualities of a person becomes evident. At the same time, the most relevant are the studies of ethical and psychological characteristics development in the adolescent and youth environment, since it is this age that is sensitive in the moral development of an individual. Therefore, the dissertation study of the ethical and psychological characteristics dynamics concerning the personality of adolescent and young students is relevant.
Variational Model Selection for Sparse Gaussian Process Regression

Sparse Gaussian process methods that use inducing variables require the selection of the inducing inputs and the kernel hyperparameters. We introduce a variational formulation for sparse approximations that jointly infers the inducing inputs and the kernel hyperparameters by maximizing a lower bound of the true log marginal likelihood. The key property of this formulation is that the inducing inputs are defined to be variational parameters which are selected by minimizing the Kullback-Leibler divergence between the variational distribution and the exact posterior distribution over the latent function values. We apply this technique to regression and we compare it with other approaches in the literature.
Investigating a DTV-based physical activity application to facilitate wellbeing in older adults

This paper describes a study that examined the usability and acceptability of a physical exercise application using the digital television platform for older adults. A key aim of this study was to obtain feedback from representative older users to inform further development of this application. Other key outcomes were to measure physical exertion objectively and subjectively whilst using this application and to investigate potential acute effects of the session on cognitive function and mood. The results indicated that the settings used for the current exercises did not produce physical exertion at a high enough intensity to have significant health benefits, although a positive impact on mood was found. Subjective feedback identified a number of issues regarding various application features and possible adaptations for the future design and development of this application, including the use of gesture based user-control and the potential importance of monitoring user heart-rate to set exercise parameters.
The Enhanced Intra Prediction Algorithm for H.264

When the current block is at the edge of the objects, the prediction accuracy of H.264 intra-frame coding will be decreased. An enhanced intra prediction method is proposed in this paper based on the directional of intra prediction and correlation among adjacent pixels in the current block. The proposed algorithm use the pixels calculated already as the reference pixels to predict the rest pixels in the current block, and then dynamically update the prediction mode order to achieve more most_probable_modes. Experimental results show that the proposed scheme is able to achieve a remarkable reduction of bit rate, meanwhile the peak signal-noise ratio (PSNR) is slightly increased compared with the original H.264 reference software.
Auto-tuning of parameters in hybrid sampling method for class imbalance problem

the class imbalance is a major problem in machine learning. This problem affects the performance of a model prediction. The DBSM algorithm, a hybrid-sampling technique, was developed to deal with the class imbalance for two-class classification problem. Although the DBSM algorithm is the effective solution, there are too many parameters for tuning in the algorithm. Thus, this paper proposes an automatic parameter tuning for the DBSM algorithm by using a genetic algorithm (GA), called GADBSM. The experimental results of GADBSM are compared with the DBSM algorithm. The results show that the GADBSM can enhance the classification performance of the DBSM algorithm. Moreover, the GADBSM provides the best in F-measure and AUC in all datasets.
High-performance work systems and firms' operational performance: the moderating role of technology

This paper analyses the moderating effect of technology on the potential impact of high-performance work systems (HPWS) on firms' operational performance. The paper distinguishes between production technology and the technological intensity of the industry. This potential effect is analysed in a sample of 965 Spanish manufacturing firms. Results support the moderating role of the technological intensity of the industry, while qualifying the hypothesized moderating effect of production technology.
Beyond the two-child family

Based on retrospective data from the German Family Survey (DJI Familiensurvey) 2000, we investigate factors associated with the transition from the second to the third child for West German women of the birth cohorts 1944-1979 and contrast them to the determinants of the transition from the first to the second child. Applying event history analysis, we confirm effects of timing and spacing of children and mothers’ labor force participation reported in previous studies. In addition, we find a higher third birth rate for women with two children of the same sex, who might wish to have a child of the opposite sex. Further, we find a higher third birth rate for women with two or more siblings, which we interpret as transmission of family values. Finally, women with a new partner since the first birth as well as women with a new partner since the second birth show higher third birth rates, which might result from a union-confirmation effect of shared children in combination with a two child norm.
Text management of large organizations based on services

In view of the knowledge management of organizations, this paper focuses on the text knowledge management. The characteristics and problems of knowledge management of organizations are analyzed. The thought that text knowledge can be seen as services is put forward. The key technologies for building and managing text services are analyzed. Cloud architecture for text service management is put forward. A prototype system about microorganism is built for verification.
On Bregman Distances and Divergences of Probability Measures

This paper introduces scaled Bregman distances of probability distributions which admit nonuniform contributions of observed events. They are introduced in a general form covering not only the distances of discrete and continuous stochastic observations, but also the distances of random processes and signals. It is shown that the scaled Bregman distances extend not only the classical ones studied in the previous literature, but also the information divergence and the related wider class of convex divergences of probability measures. An information-processing theorem is established too, but only in the sense of invariance w.r. t. statistically sufficient transformations and not in the sense of universal monotonicity. Pathological situations where coding can increase the classical Bregman distance are illustrated by a concrete example. In addition to the classical areas of application of the Bregman distances and convex divergences such as recognition, classification, learning, and evaluation of proximity of various features and signals, the paper mentions a new application in 3-D exploratory data analysis. Explicit expressions for the scaled Bregman distances are obtained in general exponential families, with concrete applications in the binomial, Poisson, and Rayleigh families, and in the families of exponential processes such as the Poisson and diffusion processes including the classical examples of the Wiener process and geometric Brownian motion.
A composition method for manipulating detectable situations to provide situation-aware services

One of the hot topics in ubiquitous computing is context-aware services, which automaticlly adapt user based on user's context information, e.g., location, time, favorite etc. Situation-aware services are advanced context-aware services, such that more complex context information and relations among users, objects, and environment are taken into consideration. In order to provide the situation-aware services, it is necessary to describe the situations, to define and link services which will be provided in the situations, and to detect the happening of the situations in the real world. Though many researches have worked on context-aware services, there are not so many on situation aware services, especially on describing and detecting the situations uniformly. In this paper, we take a composition approach to solve the problems. We first define primitive situations which are based on J. Barwise's situation theory and can be detected by current ubiquitous techniques. And then, we present several manipulation rules, by which more complex situations can be composed. Our methods can be used as a building block in construction situation-aware services, such as warning to a user to prevent him/her from dangerous situations, reminding a user not forgetting to bring belongings with him/her, navigation to a handicapped user, etc.
Robust Stability and Stabilization of a Class of Uncertain Linear Neutral Systems with Multiple Delays

The problems of robust stability and stabilization of a class of linear neutral systems with norm-bounded uncertainties are studied in this paper. We focus on the delay dependent robust stability and stabilization problem with respect to the uncertainty (i.e., finding robust stability conditions containing delay information). Some sufficient conditions on stability and stabilization are derived in terms of linear matrix inequalities (LMIs), which extend the parts of the previous results For delay-dependent case, an estimation of the maximum admissible delay bound is given by a generalized eigenvalue problem, which can be solved numerically with efficient LMI toolbox. Finally, a numerical example is worked out to illustrate the efficiency and less conservatism of the proposed approach.
Boosted Noise Filters for Identifying Mislabeled Data

In many practical classification problems, mislabeled data instances (i.e., class noise) exist in the acquired (training) data and often have a detrimental effect on the classification performance. Identifying such noisy instances and removing them from training data can significantly improve the trained classifiers. One such effective noise detector is the so-called ensemble filter, which predicts the instances misclassified by multiple learned classifiers as noise. This paper proposes a novel noise detection method that uses a boosting ensemble of the ensemble noise filters. Multiple ensemble noise filters are built sequentially, with each one working on weighted instances. The weighting scheme follows the general boosting idea and reduces the weights of those instances that are confidently predicted as noise in previous runs. This method essentially wraps an existing ensemble filter-based noise detector with a second layer of boosting ensemble. Our experimental results on a range of real datasets from the UCI repository show the superiority of the proposed boosted noise detectors.
Web-Based Issue Tracking for Large Software-Projects

Many problems are found and fixed during the development of a software system. The Project Issue Tracking System toolkit, a Web-based issue-management tool, can be used to organize issue reports during development and to communicate with different project teams around the world. The Project Issue Tracking System (PITS) is a tool that supports the IV&V effort for two major NASA projects: the Earth Observation System Data and Information System (EOSDIS) and the Earth Science Data and Information System (ESDIS). The EOSDIS IV&V effort teams several companies and organizations at several sites with Intermetrics, Inc, serving as the lead contractor. We examine the PITS Web-based mechanisms for tracking issue reports.
Research Statement for Hyrum D. Carroll

Computational biology is an area of research at the intersection of computer science and biology. This is my research area because I get to leverage high performance computing to answer computational problems for molecular biology. As a doctoral student and a postdoctoral researcher, I have worked on a variety of projects including homology search, multiple sequence alignment, phylogeny search, and biological networks. My future work will continue along these lines with an expansion into leveraging high-throughput sequencing (also called next-generation sequencing).
Representations of the ‘Good Life’: Hospitality Training for Young People with Learning Difficulties at The Special Needs Hotel, UK

This paper examines representations of young people with learning disabilities in the popular television documentary series ‘The Special Needs Hotel’. The TV series followed the experiences of young people with a learning disability as they received hands-on training in ‘the art of hospitality’ at the Foxes Hotel & Academy in Minehead, England. Drawing on the work of Hall (1997), we used a reflective approach in this paper to identify how the hospitality work and the trainees are represented. The method of inductive thematic analysis was used to determine the key communication about hospitality training for people with a learning disability in the episodes. The data collection involved both researchers watching separately all three episodes of The Special Needs Hotel, and then we used investigator triangulation to validate and draw common themes (Denzin, 1970). The researchers held frequent conversations about their analysis and discussion of the scene descriptions (Harris, Tregidga, & Williamson, 2011). The key themes which emerged from our analysis will be presented. Some possible implications of the identity and ideals constructed in this documentary series are discussed—in particular, those relating to the impact of images and language used, boundaries and strategies for accessible environments, and the social pursuit of enabling the ‘good life’ and ‘independence’ through hospitality training for people with learning disabilities. This study suggests more fundamental concerns about the training and employment of people with disabilities in the hospitality industry. It also considers broader notions of hospitality toward a group of young people who are more excluded from the workplace than any other group of disabled people. References: Denzin, N.K. (1970). The research act: A theoretical introduction to sociological methods. Chicago: Aldine. Hall, S. (1997). Representation: Cultural representations and signifying practices. London: Sage. Harris, C. , Tregidga, H. , & Williamson, D. (2011). Cinderella in Babylon: The representation of housekeeping and housekeepers in the UK television series Hotel Babylon. Hospitality & Society, 1(1), 47–66. 1 McIntosh and Harris: Representations of the ‘Good Life’: Hospitality Training for Youn Published by Digital Commons @ TRU Library, 2017
Haemanthus coccineus extract and its main bioactive component narciclasine display profound anti-inflammatory activities in vitro and in vivo

Haemanthus coccineus extracts (HCE) have traditionally been used to treat a variety of diseases, like febrile colds or asthma. Since new therapeutic options against inflammatory processes are still urgently needed, we aimed to pharmacologically characterise the anti‐inflammatory potential of HCEin vitro and in vivo and to identify the underlying bioactive component(s). The action of HCE on oedema formation and leucocyte infiltration were analysed in two murine models of inflammation (dermal oedema induced by arachidonic acid and croton oil; kidney injury caused by unilateral ureteral obstruction). The interaction of leucocytes with endothelial cells (ECs) as well as the activation parameters of these two cell types were analysed. Moreover, the nuclear factor κB (NFκB) pathway was investigated in detail in ECs. Using different fractions of HCE, the bioactive principle was identified. In vivo, HCE (450 mg/kg orally or 2 mg/kg intraperitoneally) inhibited oedema formation, leucocyte infiltration and cytokine synthesis. In vitro, HCE (100–300 ng/ml) blocked leucocyte‐EC interaction as well as the activation of isolated leucocytes (cytokine synthesis and proliferation) and of primary ECs (adhesion molecule expression). HCE suppressed NFκB‐dependent gene transcription in the endothelium, but did not interfere with the NFκB activation cascade (IκB degradation, p65 nuclear translocation and NFκB DNA‐binding activity). The alkaloid narciclasine was elucidated as the bioactive compound responsible for the anti‐inflammatory action of HCE. Our study highlights HCE and its main alkaloid narciclasine as novel interesting approach for the treatment of inflammation‐related disorders.
The Secreted Lipoprotein, MPT83, of Mycobacterium tuberculosis Is Recognized during Human Tuberculosis and Stimulates Protective Immunity in Mice

The long-term control of tuberculosis (TB) will require the development of more effective anti-TB vaccines, as the only licensed vaccine, Mycobacterium bovis bacille Calmette-Guérin (BCG), has limited protective efficacy against infectious pulmonary TB. Subunit vaccines have an improved safety profile over live, attenuated vaccines, such as BCG, and may be used in immuno-compromised individuals. MPT83 (Rv2873) is a secreted mycobacterial lipoprotein expressed on the surface of Mycobacterium tuberculosis. In this study, we examined whether recombinant MPT83 is recognized during human and murine M. tuberculosis infection. We assessed the immunogenicity and protective efficacy of MPT83 as a protein vaccine, with monophosphyl lipid A (MPLA) in dimethyl-dioctadecyl ammonium bromide (DDA) as adjuvant, or as a DNA vaccine in C57BL/6 mice and mapped the T cell epitopes with peptide scanning. We demonstrated that rMPT83 was recognised by strong proliferative and Interferon (IFN)-γ-secreting T cell responses in peripheral blood mononuclear cells (PBMC) from patients with active TB, but not from healthy, tuberculin skin test-negative control subjects. MPT83 also stimulated strong IFN-γ T cell responses during experimental murine M. tuberculosis infection. Immunization with either rMPT83 in MPLA/DDA or DNA-MPT83 stimulated antigen-specific T cell responses, and we identified MPT83127–135 (PTNAAFDKL) as the dominant H-2b-restricted CD8+ T cell epitope within MPT83. Further, immunization of C57BL/6 mice with rMPT83/MPLA/DDA or DNA-MPT83 stimulated significant levels of protection in the lungs and spleens against aerosol challenge with M. tuberculosis. Interestingly, immunization with rMPT83 in MPLA/DDA primed for stronger IFN-γ T cell responses to the whole protein following challenge, while DNA-MPT83 primed for stronger CD8+ T cell responses to MPT83127–135. Therefore MPT83 is a protective T cell antigen commonly recognized during human M. tuberculosis infection and should be considered for inclusion in future TB subunit vaccines.
Managing Software Performance in the Globally Distributed Software Development Paradigm

The information technology (IT) industry continues to lose close to GBP 45 billion each year as a result of under per forming applications. Our observations, while troubleshooting a number of projects on performance related issues, has been that the root cause for most of these problems lies in shortcomings at the requirements engineering, architecture and design or system integration testing phases of the software development lifecycle (SDLC). We attribute this to a lack of awareness on the basic principles of performance engineering in terms of the activities that need to be performed in this context and when and how in the SDLC should these be done. This problem is particularly accentuated in projects executed using the globally distributed software development model owing to the geographic dispersion of the development teams. This paper proposes an experience based methodology on how to manage the performance of an application that is developed under this radically new development paradigm
Leadership Styles and Access of Women to Top Level Business Positions

The research investigates the impact of leadership styles on the access to top level business positions by women. Gender specific leadership styles and skills have been discussed and the leadership skills impact model has been newly created and tested in German speaking countries. It was found out that a transformational leadership style, a high educational level, interpersonal and conceptual skills as well as practical training play an important role for men to reach a top job. Even though women possess transformational leadership skills and have good knowledge and skills it doesn’t aid them for career progression in the same extent as for men. The deduction can be drawn that women face constraining factors like prejudice and stereotyping, a masculine corporate culture, general norms and cultural practices, a lack of role models, a lack of flexible work solutions, raising children, personal values, social norms as well as less practical training skills, which hinder female career progression.
Improving Microblog Retrieval with Feedback Entity Model

When searching over the microblogging, users prefer using queries including terms that represent some specific entities. Meanwhile, tweets, though limited within 140 characters, are often generated with one or more entities. Entities, as an important part of tweets, usually convey rich information for modeling relevance from new perspectives. In this paper, we propose a feedback entity model and integrate it into an adaptive language modeling framework in order to improve the retrieval performance. The feedback entity model is estimated with the latest entity-associated tweets based upon a regularized maximum likelihood criterion. More specifically, we assume that the entity-associated tweets are generated by a mixture model, which consists of the entity model, the domain-specific language model and the collection language model. Experimental results on two public Text Retrieval Conference (TREC) Twitter corpora demonstrate the significant superiority of our approach over the state-of-the-art baselines.
Radio-Interferometric Object Trajectory Estimation

In this paper a novel radio-interferometric object trajectory estimation method is proposed, which can be used to track moving objects. The system utilizes a low number of fixed infrastructure nodes equipped with radio transceivers, and the tracked object also carries a simple transceiver. Selected transmitter infrastructure nodes produce interference signals at the fixed infrastructure receivers and the tracked receiver. Transmitter and receiver roles are rotated, thus multiple interference signals are produced, which is measured by synchronized receiver pairs. Measurements are then compared to pre-computed phase maps while the object is moving. During object movement the system resolves position ambiguities and the exact object trajectory is determined. The performance of the proposed method is illustrated by simulation examples and real measurements.