Miracle-dz/UniFAR-FTUs huggingface dataset:
Kernel-based mixture of experts models for linear regression

This paper proposes a novel kernel-based mixture of experts model for linear regression. The method is novel in that it formulates the mixture of experts model for linear regression so that kernel functions can be used. This allows the method to work directly in terms of kernels and avoids the explicit introduction of the feature vector, allowing one to use feature spaces of high, even infinite dimensionality. Other advantages of the model include the ability to take advantage of all the work related to kernels, a closed-form solution for maximization, as well as maintaining all the advantages of a linear expert. In this paper the supervised version is formulated. The model is verified and tested with simulated data. It was also found that the model had overall better performance than standard mixture of experts for regression on the well-known Boston Housing data set. Kernels used included polynomial, radial basis function and the ANOVA kernel.
Outcomes of Mandated and Nonmandated New York City Jail Diversion for Offenders with Alcohol, Drug, and Mental Disorders

The authors studied 175 mentally ill, substance-using adult jail detainees assessed at baseline, 3, and 12 months through a quasi-experimental comparison design. The study examines the effect of diversion, treatment, and individual characteristics on criminal justice, mental health, substance use, and life satisfaction outcomes. The intervention group included nonmandated and mandated diversion tracks. The comparison participants met diversion acceptance criteria but underwent standard criminal justice processes. Main findings included that mandated diversion clients were less likely to spend as much time in prison and more likely to spend time in the community, have been linked to residential and outpatient treatment, have received more treatment, and decrease drug use. However, those who did not perceive themselves coerced and had insight into their mental illness received more treatment regardless of diversion condition. Although mandated diversion was found effective for some outcomes, individual characteristics, treatment, and diversion in general significantly contributed.
Analysis techniques for amorphous silicon solar cells

The dependence of photocurrent (Iph) on voltage (V) and light intensity (ø) in p-i-n a-Si solar cells was studied, showing flatband voltage (Vfb) and conversion efficiency to increase with ø. To isolate the i-layer properties, we utilized Crandall's uniform-field collection efficiency model and tested its applicability limits. We found that p-layer properties and p-i interface can affect the fill factor (FF). Behavior of I(V) curves near the maximum power point (MPP), however, was not well-described by the model, leading us to propose a new metric: the MPP curvature of the I(V) curve normalized to I=1, V=1 at MPP (MPP K). Simulated and measured data show no unique relationship between FF and MPP K. Our analysis reveals that gradients in cross-flow PECVD growth chamber and the choice of transparent conductive oxide (TCO) substrates can affect i-layer properties and the overall quality of p-i-n solar cells.
Factors affecting return of symptoms 1 year after treatment in a 62-week controlled study of fluoxetine in major depression.

BACKGROUND In spite of impressive results in acute studies, the long-term treatment of major depression remains problematic. To explore the return of depressive symptoms and their interaction with social factors on long-term outcome, we assessed 55 patients whose depression had been treated during a 62-week, fluoxetine maintenance study, 1 year after the study's termination. METHOD During the year following the study termination, patients were free to select treatment options. Assessments at the 1-year follow-up included measures of depressive symptoms (using the Hamilton Rating Scale for Depression [HAM-D]), social and marital impairment (using the Weissman Social Adjustment Scale [SAS]), personal stressors (using the Holmes Social Readjustment Rating Scale), and history of treatment during the past year. RESULTS At the time of the naturalistic follow-up, 53% of patients sustained their improvement in mood. Factors associated with return of depressive symptoms included personal stresses, marital maladjustment, personal decision to discontinue antidepressants, and medication failure. Psychosocial variables were associated with poor outcome in over 90% of impaired subjects. Development of subsyndromal symptoms during the 50-week double-blind phase was predictive of poorer outcome at the long-term follow-up. CONCLUSION The study demonstrates that no matter how effective initial pharmacologic therapy may be, without ongoing clinical monitoring and support, particularly in dealing with issues such as marriage and handling significant life stresses, and compliance with medications, it will not be successful in the long-term treatment for a significant portion of patients with depression.
Dismantling the ‘Master’s House’: Feminist Reflections on Institutional Transformation

In 2001, the US National Science Foundation inaugurated the ADVANCE Institutional Transformation program with the primary objective of increasing the participation and advancement of women at American Universities in all science, technology, engineering, and mathematics disciplines. Although ADVANCE has been received very well, its effects have been uneven among institutions receiving the ADVANCE grant. In this paper, we reflect on the NSF’s goals for ADVANCE and initiatives ADVANCE schools undertake to increase gender equity in the context of gender organizations theory. Specifically, we comment on tensions that emerged through our own research concerning the relationship between feminist objectives of equity and justice and the nature of the ADVANCE program and transformational initiatives. We conclude by raising the perennial feminist question: ‘Can the master’s tools dismantle the master’s house? ’
Did I make a mistake? Finding the impact of code change on energy regression

Software energy consumption is a performance related non-functional requirement that complicates building software on mobile devices today. Energy hogging applications are a liability to both the end-user and software developer. Measuring software energy consumption is non-trivial, requiring both equipment and expertise, yet many researchers have found that software energy consumption can be modelled. Prior works have hinted that with more energy measurement data one can make more accurate energy models but this data was expensive to extract because it required energy measurement of running test cases (rare) or time consuming manually written tests. We address these concerns by automatically generating test cases to drive applications undergoing energy measurement. Automatic test generation allows a model to be continuously improved in a model building process whereby applications are extracted, tests are generated, energy is measured and combined with instrumentation to train a grander big-data model of software energy consumption. This continuous process has allowed the authors to generate and extract measurements from hundreds of applications in order to build accurate energy models capable of predicting the energy consumption of applications without end-user energy measurement. We clearly show that models built from more applications reduce energy modelling error.
Metamorphosis of a Language Learner: The Dynamic Interplay Between Identity, Motivation and Autonomy – An Autobiographical Account

In the last thirty to forty years, the concept of autonomy has been a key area of inquiry and pedagogical focus in language education. An autonomous learner is one who takes charge of and assumes responsibility for her learning. As befits her identity as an autonomous learner, she is said to possess certain characteristics, hold certain beliefs and exhibit certain behaviours. In language learning, such attributes can be collectively referred to as individual differences or learner factors. Crucially, when it comes to successful language acquisition, the autonomous learner recognises and accepts that the onus falls on her, not anyone else. Closely related to autonomy is the notion of self or identity. In the last decade or so, learner identity has garnered the attention of many researchers and practitioners in applied linguistics. Identity has been shown to have an important place in language learning. Further, it is postulated that a learner’s success at language learning is intimately linked to her motivation for learning the language. In this paper, the author reflects upon her English learning history, detailing her budding love of the English language as a young child growing up in colonial Hong Kong, her subsequent arrival in England as a teenager, and the education she received there. By retracing the steps of her learning journey in which she explores the role of autonomy in conjunction with individual difference factors and sociocultural theory, the author argues that successful language learning necessitates a very subtle alchemy, highlighting the dynamic interplay between identity, motivation and autonomy.
Can computing academics assess the difficulty of programming examination questions?

This paper reports the results of a study investigating how accurately programming teachers can judge the level of difficulty of questions in introductory programming examinations. Having compiled a set of 45 questions that had been used in introductory programming exams, we took three measures of difficulty for the questions: the expectations of the person who taught the course and set the exams; the consensus expectations of an independent group of programming teachers; and the actual performance of the students who sat the exams. Good correlations were found between all pairs of the three measures. The conclusion, which is not controversial but needed to be established, is that computing academics do have a fairly good idea of the difficulty of programming exam questions, even for a course that they did not teach. However, the discussion highlights some areas where the relationships show weaknesses.
The message and ministry of Howard G. Hendricks in Christian higher education

Howard G. Hendricks influenced generations of leaders in Christian education during the last half of the 20th century through the practical communication of his unique message and the personal nature of his teaching ministry. This study explored his life through interpretive biography, compared his message with current models of secular and religious education, and evaluated his ministry through case study research. Hendricks has contributed to the field of Christian higher education through the publication of several books and periodical articles, as well as film series, audiotapes, and videotapes. He has presented thousands of messages across America and in over 75 countries worldwide. Hendricks has spent his entire 50-year educational career at Dallas Theological Seminary, teaching in the classroom, mentoring his students, and modeling positive values of Christian leadership. Chapter 1 introduces the study, explains the purpose and significance of the project, and defines key terms. Chapter 2 describes the methodology employed for the study. Chapter 3 provides an interpretive biography of Hendricks, and chapter 4 compares the educational philosophy of Hendricks with secular and Christian models. Chapter 5 examines the ministry of Hendricks in a case study approach. Chapter 6 summarizes the study and offers conclusions and implications for future research.
An octree cells occupancy geometric dimensionality descriptor for massive on-server point cloud visualisation and classification

Lidar datasets are becoming more and more common. They are appreciated for their precise 3D nature, and have a wide range of applications, such as surface reconstruction, object detection, visualisation, etc. For all this applications, having additional semantic information per point has potential of increasing the quality and the efficiency of the application. In the last decade the use of Machine Learning and more specifically classification methods have proved to be successful to create this semantic information. In this paradigm, the goal is to classify points into a set of given classes (for instance tree, building, ground, other). Some of these methods use descriptors (also called feature) of a point to learn and predict its class. Designing the descriptors is then the heart of these methods. Descriptors can be based on points geometry and attributes, use contextual information, etc. Furthermore, descriptors can be used by humans for easier visual understanding and sometimes filtering. In this work we propose a new simple geometric descriptor that gives information about the implicit local dimensionality of the point cloud at various scale. For instance a tree seen from afar is more volumetric in nature (3D), yet locally each leaves is rather planar (2D). To do so we build an octree centred on the point to consider, and compare the variation of the occupancy of the cells across the levels of the octree. We compare this descriptor with the state of the art dimensionality descriptor and show its interest. We further test the descriptor for classification within the Point Cloud Server, and demonstrate efficiency and correctness results.
Understanding IPv6 internet background radiation

We report the results of a study to collect and analyze IPv6 Internet background radiation. This study, the largest of its kind, collects unclaimed traffic on the IPv6 Internet by announcing five large covering prefixes; these cover the majority of allocated IPv6 space on today's Internet. Our analysis characterizes the nature of this traffic across regions, over time, and by the allocation and routing status of the intended destinations, which we show help to identify the causes of this traffic. We compare results to unclaimed traffic in IPv4, and highlight case studies that explain a large fraction of the data or highlight notable properties. We describe how announced covering prefixes differ from traditional network telescopes, and show how this technique can help both network operators and the research community identify additional potential issues and misconfigurations in this critical Internet transition period.
Whole and fractionated yellow pea flours reduce fasting insulin and insulin resistance in hypercholesterolaemic and overweight human subjects

The objective of the present study was to compare whole pea flour (WPF) to fractionated pea flour (FPF; hulls only) for their ability to reduce risk factors associated with CVD and diabetes in overweight hypercholesterolaemic individuals. Using a cross-over design, twenty-three hypercholesterolaemic overweight men and women received two-treatment muffins/d containing WPF, FPF or white wheat flour (WF) for 28 d, followed by 28 d washout periods. Daily doses of WPF and FPF complied with the United States Department of Agriculture's recommended level of intake of half a cup of pulses/d (approximately 50 g/d). Dietary energy requirements were calculated for each study subject, and volunteers were only permitted to eat food supplied by the study personnel. Fasting insulin, body composition, urinary enterolactone levels, postprandial glucose response, as well as fasting lipid and glucose concentrations, were assessed at the beginning and at the end of each treatment. Insulin concentrations for WPF (37·8 (sem 3·4) pmol/ml, P = 0·021) and FPF (40·5 (sem 3·4) pmol/ml, P = 0·037) were lower compared with WF (50·7 (sem 3·4) pmol/ml). Insulin homeostasis modelling assessment showed that consumption of WPF and FPF decreased (P < 0·05) estimates of insulin resistance (IR) compared with WF. Android:gynoid fat ratios in women participants were lower (P = 0·027) in the WPF (1·01 (sem 0·01) group compared with the WF group (1·06 (sem 0·01). Urinary enterolactone levels tended to be higher (P = 0·087) in WPF compared with WF. Neither treatment altered circulating fasting lipids or glucose concentrations. In conclusion, under a controlled diet paradigm, a daily consumption of whole and fractionated yellow pea flours at doses equivalent to half a cup of yellow peas/d reduced IR, while WPF reduced android adiposity in women.
Assessment and Implementation of Positive Behavior Support in Preschools

There is increasing concern over the number of young children who exhibit challenging behaviors in early childhood settings. Comprehensive prevention models are needed to support teachers' management of challenging behaviors and to avert the development of such behaviors within at-risk populations. One approach utilizes a three-tier prevention model called positive behavior support (PBS). The present research first assessed one region's implementation of PBS in 15 early childhood settings and found that on average, few features of PBS (30.79%) were implemented. Next, the impact of PBS consultation on teachers' use of universal PBS practices and children's behavior was evaluated in a multiple baseline design across four classrooms. A functional relationship was established between PBS consultation and teachers' implementation of universal PBS practices, but overall low levels of problem behavior prevented assessment of the impact of these changes on child problem behavior. Implications for future applications of PBS to early childhood settings are discussed.
SNRK (Sucrose Nonfermenting 1-Related Kinase) Promotes Angiogenesis In Vivo

Objective— SNRK (sucrose nonfermenting 1-related kinase) is a novel member of the AMPK (adenosine monophosphate-activated protein kinase)-related superfamily that is activated in the process of angiogenesis. Currently, little is known about the function of SNRK in angiogenesis in the physiological and pathological conditions. Approach and Results— In this study, in Snrk global heterozygous knockout mice, retina angiogenesis and neovessel formation after hindlimb ischemia were suppressed. Consistently, mice with endothelial cell (EC)-specific Snrk deletion exhibited impaired retina angiogenesis, and delayed perfusion recovery and exacerbated muscle apoptosis in ischemic hindlimbs, compared with those of littermate wide-type mice. Endothelial SNRK expression was increased in the extremity vessel samples from nonischemic human. In ECs cultured in hypoxic conditions, HIF1&agr; (hypoxia inducible factor 1&agr;) bound to the SNRK promoter to upregulate SNRK expression. In the nuclei of hypoxic ECs, SNRK complexed with SP1 (specificity protein 1), and together, they bound to an SP1-binding motif in the ITGB1 (&bgr;1 integrin) promoter, resulting in enhanced ITGB1 expression and promoted EC migration. Furthermore, SNRK or SP1 deficiency in ECs ameliorated hypoxia-induced ITGB1 expression and, consequently, inhibited EC migration and angiogenesis. Conclusions— Taken together, our data have revealed that SNRK/SP1-ITGB1 signaling axis promotes angiogenesis in vivo.
The Involvement of Social Workers in Fundraising

Abstract Despite growing interest in fundraising as part of the social worker's role, there has been no comprehensive research on this subject. The purpose of the present research is to begin to bridge that gap. Five dimensions of fundraising are defined and a theoretical framework, comprised of factors that may be related to social workers' involvement in this activity, is developed. Data were collected by means of a structured questionnaire, administered to social workers in welfare departments in Israel. Statistical analysis of the findings indicates low to moderate mean levels of social worker involvement in fundraising. The variable that contributes most to involvement in fundraising is the social worker's sense of efficacy for this activity. The paper offers several theoretical and practical conclusions and suggests directions for further research.
SABR: sparse, anchor-based representation of the speech signal

We present SABR (Sparse, Anchor-Based Representation), an analysis technique to decompose the speech signal into speaker-dependent and speaker-independent components. Given a collection of utterances for a particular speaker, SABR uses the centroid for each phoneme as an acoustic “anchor,” then applies Lasso regularization to represent each speech frame as a sparse non-negative combination of the anchors. We illustrate the performance of the method on a speaker-independent phoneme recognition task and a voice conversion task. Using a linear classifier, SABR weights achieve significantly higher phoneme recognition rates than Mel frequency Cepstral coefficients. SABR weights can also be used directly to perform accent conversion without the need to train a speakerto-speaker regression model.
Identifying novel genes contributing to asthma pathogenesis

Purpose of review To illustrate recent examples of novel asthma genes such as those encoding G-protein-coupled receptor for asthma susceptibility, filaggrin and tenascin-C, and to describe the process that is needed to translate these findings to the clinic. Recent findings Many hundreds of studies have been published investigating the association of genetic polymorphisms in candidate genes with asthma. These genes were selected on the basis of the gene's product known involvement in the disease process. Moreover, it is the identification of novel genes through hypothesis-independent approaches such as genome-wide linkage studies that is likely to radically alter our understanding of asthma pathophysiology. The identification of a gene is, however, only the first step in a long process that may eventually lead from gene to treatment. This process includes replication, functional studies and, finally, intervention studies. Summary While significant progress has been made in the identification of asthma susceptibility genes, it is clear that issues such as replication and functional characterization mean that considerably more research is required. This may enable us to realize benefits to patient treatment that studies of the genetic basis of asthma have the potential to deliver.
AFFINITY CHROMATOGRAPHY ISOLATION AND CHARACTERIZATION OF SOLUBLE cGMP-BINDING PROTEINS FROM AVENA SATIVA L. SEEDLINGS

Summary. In attempt to elucidate the early molecular events associated with the biological action of cyclic guanosine 3 / ,5 / - monophosphate (cGMP) its binding to the structural components of Avena sativa L. plant cell has been studied. cGMP was shown to be bound specifically to proteins located predominantly in the soluble cytosolic fraction. cGMP-agarose affinity purification procedure followed by SDS-PAGE has revealed about ten specific cGMP-binding proteins in the cytosol. The nature of the purified proteins has been discussed.
A Content-Aware Stream Authentication Scheme Optimized for Distortion and Overhead

This paper proposes a content-aware authentication scheme optimized to account for distortion and overhead for media streaming. When authenticated media is streamed over a lossy network, a received packet is consumed only when it is both decodable and authenticated. In most media formats, some packets are more important than others. This naturally motivates allocating more redundant authentication information for the more important packets in order to maximize their probability of authentication and thereby minimize distortion at the receiver. Toward this goal, with awareness of the media content, we formulate an optimization framework to compute an authentication graph to maximize the expected media quality at the receiver, given specific authentication overhead and knowledge of network loss rates. Experimental results with JPEG-2000 coded images demonstrate that the proposed method achieves our design goal in that the R-D curve of the authenticated image is very close to the R-D curve when no authentication is required