Miracle-dz/UniFAR-FTUs huggingface dataset:
Particle swarm based simplex optimization implemented in a nonlinear, multiple-coupled finite-element-model for stress grading in generator end windings

Due to highly nonlinear material characteristics in combination with electrical-thermal coupled partial differential equations and the complex geometry the design of stress grading systems for large rotating machines is a difficult and time consuming process. In order to accelerate this process, a finite element model is developed. The model takes the nonlinear electrical and thermal coupled material properties into account. Furthermore it is able to calculate the electric and thermal behavior of a painted or taped stress grading system. The goal of this work is to present strategies to determine optimal stress grading-configurations for a minimization of the electrical as well as the combined electrical-thermal stress caused by the potential grading. Therefore, several numerical, global bounded optimization algorithms are implemented in the finite-element-model and analyzed regarding efficiency and effectiveness. As a result a self developed partial swarm based simplex optimization algorithm (PSBSO), is introduced which obtains the best result for this special optimization problem. This hybrid-algorithm combines the positive features of particle swarm optimization (PSO) and globalized bounded nelder-mead algorithm (GBNM).
The differential impact of observational learning and practice-based learning on the development of oral presentation skills in higher education

The present study focuses on the design and evaluation of an innovative instructional approach to developing oral presentation skills. The intervention builds on the observational learning theoretical perspective. This perspective is contrasted with the traditional training and practice approach. Two sequencing approaches – learners starting with observational learning versus learners starting with practice opportunities only – were compared. It was hypothesised that learners starting with observational learning would outperform learners in the practice only condition. The results suggest a significant differential impact on development of oral presentation skills. This impact of the observational learning training approach is only found in a limited number of evaluation criteria. Results additionally suggest that students are highly motivated to learn this type of skill. Interaction effects between student characteristics and instructional interventions were not significant.
Losing Control: The Case for Emergent Software Systems Using Autonomous Assembly, Perception, and Learning

Architectural self-organisation, in which different configurations of software modules are dynamically assembled based on the current context, has been shown to be an effective way for software to self-optimise over time. Current approaches to this rely heavily on human-led definitions: models, policies and processes to control how self-organisation works. We present the case for a paradigm shift to fully emergent computer software which places the burden of understanding entirely into the hands of software itself. These systems are autonomously assembled at runtime from discovered constituent parts and their internal health and external deployment environment continually monitored. An online, unsupervised learning system then uses runtime adaptation to explore alternative system assemblies and locate optimal solutions. Based on our experience to date, we define the problem space of emergent software, and we present a working case study of an emergent web server. Our results demonstrate two aspects of the problem space for this case study: that different assemblies of behaviour are optimal in different deployment environment conditions, and that these assemblies can be autonomously learned from generalised perception data while the system is online.
Osteoprotegrin and the bone homing and colonization potential of breast cancer cells

Breast cancer cells preferentially metastasize to bone, leading to the formation of primarily osteolytic lesions. Osteoprotegerin (OPG) plays multifactorial roles in the development of osteolytic bone metastases. An increase in the ratio of receptor activator of nuclear factor κB ligand (RANKL) to OPG increases osteoclastogenesis within the bone microenvironment. OPG also acts as a survival factor for cancer cells by protecting them from tumor necrosis factor‐related apoptosis‐inducing ligand (TRAIL) mediated apoptosis. This study compares OPG production in vitro in a number of breast cancer cell lines exhibiting both differences in metastatic capacity and in preferential metastasis to bone. Our studies demonstrated that OPG expression by MDA‐231, MDA‐MET, and MDA‐231/K cancer cells was directly correlated with bone specific homing and colonization potential but not with metastasis of cancer cells to other organs; both in IL‐1β stimulated and control cells. We also demonstrated expression of other bone‐related markers including type I collagen, osteocalcin, osteopontin, and Runx2 in these cells. However, the generally lower expression of these markers in the bone selective cell line MDA‐MET suggested that increased OPG expression in the bone specific variant was not merely a consequence of enhanced osteomimicry by these cells but that it has a significant role in the metastatic process. Co‐culture of breast cancer cells with osteoblastic cells (hFOB 1.19) led to an overall downregulation in OPG production, which was not affected by the bone homing and colonization potential of the cell lines, suggesting that OPG alone is not indicative of osteolytic bone activity by breast cancer cells. J. Cell. Biochem. 103: 30–41, 2008. © 2007 Wiley‐Liss, Inc.
Visual and cognitive perspective-taking impairments in schizophrenia: A failure of allocentric simulation ?

Introduction. Poor mentalising in some patients with schizophrenia has been attributed to disruption of a cognitive module dedicated to computing meta - representations (representations of beliefs about propositions) and linked specifically to paranoia. Because meta-representational capacity is needed to infer beliefs but is not needed to judge visual perspectives (which can be done by mentally rotating primary representations of seen objects), this view predicts that patients with selective mentalising deficits will show intact visual perspectivetaking. Method. This study tested that prediction by investigating visual perspective-taking in patients and healthy controls, known to differ in mentalising ability. Item questions (asking locations of array-features) and appearance questions (asking how an array appears from another perspective) were presented with both viewer-rotation instructions (asking subjects to imagine moving themselves relative to an array) and array-rotation instructions (asking subjects to imagine rotating an array relative to their fixed viewpoint). Results. Whereas patients performed as well as controls on item questions (regardless of instruction) and appearance questions under array-rotation instructions, patients made more egocentric errors than controls judging appearance questions under viewer-rotation instructions. Conclusions. Our findings count against traditional theory-of-mind accounts and suggest instead that poor mentalising in schizophrenia is better understood as an impairment of perspective-taking.
Training Parents to Manage Difficult Children: A Comparison of Methods

This study examined the efficacy of training parents in different methods of child management, using social learning theory/behavioural principles. Following an encouraging pilot study, thirty-seven pre-school children, six girls and thirty-one boys, were allocated to one of four methods of parent training: group, home visit, telephone, or waiting list/delayed intervention control. Assessment conducted pre- and post-intervention and at twelve to eighteen months follow-up indicated clinical improvement for all three active intervention conditions compared to the waiting list control condition. There were no significant differences between the three active intervention conditions either at post-intervention or at follow-up. Results are discussed in terms of their theoretical and practical implications.
Towards Adaptive Social Behavior Generation for Assistive Robots Using Reinforcement Learning

In this paper we explore whether a social robot can learn, in and from a task-oriented interaction with a human user, how to employ different social behaviors to achieve interactional goals under specific situational circumstances. We present a multimodal behavior generation architecture that maps high-level interactional functions and behaviors onto low-level behaviors executable by a robot. While high-level behaviors are selected based on the state of the user as well as the interaction, reinforcement learning is used within each behavior to optimize its local mapping onto lower-level behaviors. The approach is implemented and applied in a scenario in which a social robot (Furhat) assists a human player in solving a Memory game by guiding the attention of the user to target objects. Results of an evaluation study demonstrate that participants are able to solve the Memory faster with the adaptive, assistive robot.
General Mental Ability and Selection in Private Sector Organizations: A Commentary

Key considerations are summarized relating to the design of cognitively oriented selection procedures for the purpose of minimizing group differences and maximizing selection effectiveness. It is concluded that selection effectiveness and selection rate equality trade off within the cognitive domain and that design efforts to minimize group differences are likely to result in differential prediction where it was previously absent. It is also suggested that the frequently cited premise that selection procedures of equal validity are substitutable is not, in general, true. Equal validity does not imply equal value for the organization. Finally, it is argued that additional research and discussion is necessary to clarify and reach professional consensus regarding two competing perspectives about the meaning of differential prediction. One perspective views differential prediction as an extension of validation requiring the criterion to be theoretically construct-relevant to the predictor. The other views dif.
Explaining family interactions

PART ONE: THE DEVELOPMENT OF FAMILY COMMUNICATION PATTERNS Communication in Infancy - Marguerite Stevenson Barratt The Socialization of Person-Centered Communication - Brant R Burleson, Jesse G Delia and James L Applegate Parents' Contributions to their Children's Social-Cognitive and Communication Skills Parent-Adolescent Relationships - Patricia Noller Accounts and Demystification of Courtship - Catherine A Surra, Michelle L Batchelder and Debra K Hughes PART TWO: FAMILY RELATIONSHIPS IN PROCESS How Parenthood Affects Marriage - Ted L Huston and Anita L Vangelisti Family Interaction during Problem Solving - Samuel Vuchinich and Jospeh Angelelli Family Conflict, Divorce, and Children's Adjustment - Susan Gano-Phillips and Frank D Fincham Postdivorce Relations - Sandra Metts and William R Cupach PART THREE: EXTENDING FAMILY BOUNDARIES Communication in Three Types of Dual-Career Marriages - Lawrence B Rosenfeld, Gary L Bowen and Jack M Richman Communication Patterns in Stepfamilies - Nancy A Burrell Redefining Family Roles, Themes, and Conflict Styles Communication, Gender, and Power - Sara Steen and Pepper Schwartz Homosexual Couples as a Case Study The Aging Family - Marie-Louise Mares Communication and Family Culture - Alan L Sillars
A família e a escola como contextos de desenvolvimento humano

School and family constitute two developmental contexts essential for the lifespan trajectories. In this article, it is highlighted the contribution of both contexts to human development promotion, emphasizing their implications on evolutionary processes. The issues about family links, configurations, and the importance of the social support network for family development are discussed. The school functions are focused considering their influences on developing persons. Considerations are also made about the necessity of understanding the inter-relations between the school and the family, aiming to promote learning and human development. The integration between these two contexts is a challenge for both the professional practice and the empirical research.
Processing of Sexual Media Messages Improves Due to Media Literacy Effects on Perceived Message Desirability

This study tested the double-edged desirability hypothesis to investigate whether a lack of reduction in desirability perceptions signified failure of a media literacy intervention to reduce the appeal of sexual portrayals or whether it instead represented an improved awareness of message-design techniques and, therefore, a successful intervention. Data from two media literacy curriculum evaluations, both pretest–posttest quasi-experiments with control groups (N1 = 922, M = 14.13, SD = 1.07; N2 = 1,098, M = 14.26, SD = 1.06) showed that the media literacy treatment in both studies eliminated the effect of desirability on participants’ attitudes, reduced the effect of message desirability on participants’ expectancies, and reduced the effect of message desirability on participants’ efficacy in one of the evaluations. The results supported the double-edged desirability hypothesis, which holds that media literacy education can diminish the influence of desirable but unrealistic sexual media messages on adolescents’ decision making concerning sex, regardless of whether it decreases their affinity for the messages. This approach appears to represent a more effective alternative to demonizing media messages teens find desirable.
‘People Is All That Is Left to Privatize’: Water Supply Privatization, Globalization and Social Justice in Belize City, Belize

This article presents the findings of an extensive survey on public and policy level perceptions of the failed water supply and sanitation system privatization in Belize City. Drawing upon the burgeoning critical geographical literature on the commodification and privatization of water, we formulate a conceptual framework for analyzing the ethnographic data on perceptions and experience of privatization by Belize City water users. The experience of water supply privatization was largely negative. Residents complained bitterly about an increase in water tariffs and excessive disconnection rates by the privatized Belize Water Supply Limited (BWSL). Many policy makers also accused BWSL of front-loading profits and not making strategic investments in infrastructure. But the symbolic significance of water privatization for the residents of a small Caribbean country like Belize exceeded its practical implications. We argue that the major themes to emerge from the ethnographic data collected for the study can be synthesized into three 'popular privatization narratives' (PPNs). The first was based on the perception that poor governance led to privatization; the second on a preference for national- over global-scale politics, so that objections to privatization were based on nationalism; the third on angst about losing control to the systemic compulsions of neoliberal globalization. Overall the privatization process not only had important (largely negative) material consequences for Belizeans but, given their historical and cultural geography, profound discursive and symbolic consequences for their sense of identity in a condition of neoliberal globalization. Copyright (c) 2009 The Authors. Journal Compilation (c) 2009 Joint Editors and Blackwell Publishing Ltd.
Associations between diet and cancer, ischemic heart disease, and all-cause mortality in non-Hispanic white California Seventh-day Adventists.

Results associating diet with chronic disease in a cohort of 34192 California Seventh-day Adventists are summarized. Most Seventh-day Adventists do not smoke cigarettes or drink alcohol, and there is a wide range of dietary exposures within the population. About 50% of those studied ate meat products <1 time/wk or not at all, and vegetarians consumed more tomatoes, legumes, nuts, and fruit, but less coffee, doughnuts, and eggs than did nonvegetarians. Multivariate analyses showed significant associations between beef consumption and fatal ischemic heart disease (IHD) in men [relative risk (RR) = 2.31 for subjects who ate beef > or =3 times/wk compared with vegetarians], significant protective associations between nut consumption and fatal and nonfatal IHD in both sexes (RR approximately 0.5 for subjects who ate nuts > or =5 times/wk compared with those who ate nuts <1 time/wk), and reduced risk of IHD in subjects preferring whole-grain to white bread. The lifetime risk of IHD was reduced by approximately 31% in those who consumed nuts frequently and by 37% in male vegetarians compared with nonvegetarians. Cancers of the colon and prostate were significantly more likely in nonvegetarians (RR of 1.88 and 1.54, respectively), and frequent beef consumers also had higher risk of bladder cancer. Intake of legumes was negatively associated with risk of colon cancer in nonvegetarians and risk of pancreatic cancer. Higher consumption of all fruit or dried fruit was associated with lower risks of lung, prostate, and pancreatic cancers. Cross-sectional data suggest vegetarian Seventh-day Adventists have lower risks of diabetes mellitus, hypertension, and arthritis than nonvegetarians. Thus, among Seventh-day Adventists, vegetarians are healthier than nonvegetarians but this cannot be ascribed only to the absence of meat.
Using Three Machine Learning Techniques for Predicting Breast Cancer Recurrence

Objective: The number and size of medical databases are increasing rapidly but most of these data are not analyzed for finding the valuable and hidden knowledge. Advanced data mining techniques can be used to discover hidden patterns and relationships. Models developed from these techniques are useful for medical practitioners to make right decisions. The present research studied the application of data mining techniques to develop predictive models for breast cancer recurrence in patients who were followed-up for two years. Method: The patients were registered in the Iranian Center for Breast Cancer (ICBC) program from 1997 to 2008. The dataset contained 1189 records, 22 predictor variables, and one outcome variable. We implemented machine learning techniques, i.e., Decision Tree (C4.5), Support Vector Machine (SVM), and Artificial Neural Network (ANN) to develop the predictive models. The main goal of this paper is to compare the performance of these three well-known algorithms on our data through sensitivity, specificity, and accuracy. Results and Conclusion: Our analysis shows that accuracy of DT, ANN and SVM are 0.936, 0.947 and 0.957 respectively. The SVM classification model predicts breast cancer recurrence with least error rate and highest accuracy. The predicted accuracy of the DT model is the lowest of all. The results are achieved using 10-fold cross-validation for measuring the unbiased prediction accuracy of each model.
Registered Sex Offenders in the United States

Although sex offender registration and notification policies have occupied an increasingly prominent place on state and federal crime control agendas, much policy discourse has occurred amid a dearth of reliable and relevant national data. This article presents the results of a study designed to broaden knowledge about the registered sex offender (RSO) population and the content of the nation’s sex offender registries. The authors analyze state-level RSO populations across several dimensions, including levels of public Internet disclosure, RSO residential status, supervision status, and assigned risk levels. Findings suggest significant interstate variation across these dimensions, and indicate that the nation’s RSO population is considerably more diverse and complex than commonly portrayed in the media and in policy debates. Implications for federal and state policies aimed at reforming the nation’s sex offender registries are discussed.
A combined Markov random field and wave-packet transform-based approach for image segmentation

The author formulates a novel segmentation algorithm which combines the use of Markov random field models for image-modeling with the use of the discrete wavepacket transform for image analysis. Image segmentations are derived and refined at a sequence of resolution levels, using as data selected wave-packet transform images or "channels". The segmentation algorithm is compared with nonmultiresolution Markov random field-based image segmentation algorithms in the context of synthetic image example problems, and found to be both significantly more efficient and effective.
Supporting STEM Education in Secondary Science Contexts

Science education scholars emphasize the significance of an integrative, interdisciplinary STEM (Science, Technology, Engineering, and Mathematics) education that encourages students to learn about the natural world through exploration, inquiry, and problemsolving experiences. This article reports on a professional development program aimed at improving a group of secondary science and mathematics teachers’ competence in using a problem-based approach in the teaching of STEM. Through surveys, qualitative interviews and focus groups, the study investigated the teachers’ understanding and perceptions of problem-based learning (PBL) as an approach to interdisciplinary STEM education as well as their perceptions of the personal and systemic challenges in implementing such an approach in their professional practice. This investigation offers insight into how university-based professional development programs can support secondary educators’ understanding of, and ability to use an interdisciplinary problem-based STEM approach in their schools and classrooms. The study concludes with implications for practice and a discussion of how future interdisciplinary professional development can be conceptualized.
The First Measurement of Spectral Lines in a Short-Period Star Bound to the Galaxy’s Central Black Hole: A Paradox of Youth

We have obtained the first detection of spectral absorption lines in one of the high-velocity stars in the vicinity of the Galaxy's central supermassive black hole. Both Brγ (2.1661 μm) and He I (2.1126 μm) are seen in absorption in S0-2 with equivalent widths (2.8 ± 0.3 and 1.7 ± 0.4 Å) and an inferred stellar rotational velocity (220 ± 40 km s-1) that are consistent with that of an O8-B0 dwarf, which suggests that it is a massive (~15 M☉) young (less than 10 Myr) main-sequence star. This presents a major challenge to star formation theories, given the strong tidal forces that prevail over all distances reached by S0-2 in its current orbit (130-1900 AU) and the difficulty in migrating this star inward during its lifetime from farther out where tidal forces should no longer preclude star formation. The radial velocity measurements ( = -510 ± 40 km s-1) and our reported proper motions for S0-2 strongly constrain its orbit, providing a direct measure of the black hole mass of 4.1(±0.6) × 106 3 M☉. The Keplerian orbit parameters have uncertainties that are reduced by a factor of 2-3 compared to previously reported values and include, for the first time, an independent solution for the dynamical center; this location, while consistent with the nominal infrared position of Sgr A*, is localized to a factor of 5 more precisely (±2 mas). Furthermore, the ambiguity in the inclination of the orbit is resolved with the addition of the radial velocity measurement, indicating that the star is behind the black hole at the time of closest approach and counterrevolving against the Galaxy. With further radial velocity measurements in the next few years, the orbit of S0-2 will provide the most robust estimate of the distance to the Galactic center.