Miracle-dz/UniFAR-FTUs huggingface dataset:
A relationship power scale for female adolescents: preliminary development and psychometric testing.

OBJECTIVES To develop and test psychometric characteristics of the Relationship Power Scale (RPS), which can be used to explore the relationship power of female adolescents in heterosexual relationships. METHODS Cross-sectional design. Female adolescents in Kaohsiung City, Taiwan, who had a steady relationship with a boyfriend at the time of the study were recruited as study subjects (n=414) to test validity and reliability of the RPS. RESULTS Confirmatory factor analysis revealed that a one-factor model with correlated uniqueness among the positively worded items best fits the data. There were significantly different scores in 3 different response groups on 2 items regarding who (participants, both themselves and their boyfriends equally, or their boyfriends) had more power in the relationship, and who was more emotionally involved in the relationship for all subjects. For subjects having sex with their steady boyfriends, RPS scores significantly differ among the 3 different response groups on 2 items regarding who had more say about having sex, and who had more say about using condoms. Cronbach's alpha for the RPS was . 69. Test-retest reliability coefficients for the RPS were . 83. CONCLUSIONS The RPS exhibited acceptable reliability and validity. Further research is recommended to use the RPS in sex-related behavior research among heterosexual female adolescents.
Efficient pairwise statistical significance estimation for local sequence alignment using GPU

Pairwise statistical significance has been found to be quite accurate in identifying related sequences (homologs), which is a key step in numerous bioinformatics applications. However, it is computational and data intensive, particularly for a large amount of sequence data. To prevent it from becoming a performance bottleneck, we resort to Graphics Processing Units (GPUs) for accelerating the computation. In this paper, we present a GPU memory-access optimized implementation for a pairwise statistical significance estimation algorithm. By exploring the algorithm's data access characteristics, we developed a tile-based scheme that can produce a contiguous memory accesses pattern to GPU global memory and sustain a large number of threads to achieve a high GPU occupancy. Our experimental results present both single- and multi-pair statistical significance estimations. The performance evaluation was carried out on an NVIDIA Telsa C2050 GPU. We observe more than 180× end-to-end speedup over the CPU implementation on an Intel© Core™ i7 processor. The proposed memory access optimizations and efficient framework are also applicable to many other sequence comparison based applications, such as DNA sequence mapping and database search.
Effects of Predator Satiation on Seed Predation in New Roadside Prairie Plantings

Restoration efforts in the tallgrass prairie ecosystem are inhibited by high seed cost and as little as 10% emergence of planted, pure live seed. This study examined the portion of loss due to seed predation and sought to reduce this predation in new roadside prairie plantings. Studies document the occurrence of predation in several plant communities and across all plant families, but little is known about how to reduce the impact of seed predators, especially in a restoration setting. On three sites where native prairie seed was recently drilled, we attempted to satiate seed predators by broadcasting a supplemental food source—birdseed at ten times the rate of the prairie seed. The goal of this method was to capitalize on the evolutionary principals of optimal diet theory and masting in order to protect seed from predation. We quantified seed predation through the use of a buffet experiment during the same fall as the planting, and by monitoring early seedling establishment the following summer. We predicted a reduced loss of prairie seed in the supplemental seed treatment of the buffet experiment. During the growing season, we expected to find increased seedling establishment in the supplemental seed treatment. Results of the buffet experiment show limited seed predation, with no significant effect of the supplemental seed treatment and temporal variation at each of the sites. As this data was collected after a frost, lack of invertebrate seed predators could have influenced the low rates of predation. Results from the growing season showed that the supplemental seed treatment increased early seedling establishment, yielding 37% more seedlings than in control plots. Detecting a treatment effect in the summer, but not in the fall may suggest that these plantings did not face high predation pressure this late in the fall, but that predators found the seeds sometime over the winter or in the spring. Further studies should test the most optimal time of year to apply the treatment and look at the effect of the treatment on sites with different disturbance characteristics. It is also important to use the treatment along with the recommended management guidelines for the site. Reducing predation on prairie seed through the use of supplemental seed could provide a practical, inexpensive strategy to improve prairie restorations across the Midwest. EFFECTS OF PREDATOR SATIATION ON SEED PREDATION IN NEW ROADSIDE PRAIRIE PLANTINGS A Thesis Submitted in Partial Fulfillment Of the Requirements for the Degree Master of Science Jessica Riebkes University of Northern Iowa May 2016
Multi-attribute spaces: Calibration for attribute fusion and similarity search

Recent work has shown that visual attributes are a powerful approach for applications such as recognition, image description and retrieval. However, fusing multiple attribute scores - as required during multi-attribute queries or similarity searches - presents a significant challenge. Scores from different attribute classifiers cannot be combined in a simple way; the same score for different attributes can mean different things. In this work, we show how to construct normalized “multi-attribute spaces” from raw classifier outputs, using techniques based on the statistical Extreme Value Theory. Our method calibrates each raw score to a probability that the given attribute is present in the image. We describe how these probabilities can be fused in a simple way to perform more accurate multiattribute searches, as well as enable attribute-based similarity searches. A significant advantage of our approach is that the normalization is done after-the-fact, requiring neither modification to the attribute classification system nor ground truth attribute annotations. We demonstrate results on a large data set of nearly 2 million face images and show significant improvements over prior work. We also show that perceptual similarity of search results increases by using contextual attributes.
MODAClouds: A model-driven approach for the design and execution of applications on multiple Clouds

Cloud computing is emerging as a major trend in the ICT industry. While most of the attention of the research community is focused on considering the perspective of the Cloud providers, offering mechanisms to support scaling of resources and interoperability and federation between Clouds, the perspective of developers and operators willing to choose the Cloud without being strictly bound to a specific solution is mostly neglected. We argue that Model-Driven Development can be helpful in this context as it would allow developers to design software systems in a cloud-agnostic way and to be supported by model transformation techniques into the process of instantiating the system into specific, possibly, multiple Clouds. The MODAClouds (MOdel-Driven Approach for the design and execution of applications on multiple Clouds) approach we present here is based on these principles and aims at supporting system developers and operators in exploiting multiple Clouds for the same system and in migrating (part of) their systems from Cloud to Cloud as needed. MODAClouds offers a quality-driven design, development and operation method and features a Decision Support System to enable risk analysis for the selection of Cloud providers and for the evaluation of the Cloud adoption impact on internal business processes. Furthermore, MODAClouds offers a run-time environment for observing the system under execution and for enabling a feedback loop with the design environment. This allows system developers to react to performance fluctuations and to re-deploy applications on different Clouds on the long term.
Factors Contributing to the Successful Implementation of a Community College Service Learning Program: Proactive Leadership, Program Infrastructure, Professional Development, and Program Evaluation

This case study will focus on the implementation of a community college service learning program with special emphasis placed upon four central factors. A major factor impacting the launch of this program was the presence of a proactive leadership. These leaders were well-versed in service learning methodology and philosophy, committed to securing campus-wide support, and acted as mentors/recruiters of promising service learning faculty members. Additionally, the leadership was actively engaged in the development of program infrastructure, which included the appointment of director, coordinator, and service learning council membership. Regarding professional development, it was imperative to provide opportunities to faculty who were involved with the service learning program in order to ensure curricular integrity, adherence to the service learning methodology, and commitment to the spirit of the service learning philosophy. Program evaluation was a crucial element in ascertaining both strengths and challenges that manifested within the program. The resulting outcomes of the program evaluation held the potential for adaptation that resulted in greater program quality. In addition to these four factors are service learning curriculum and pedagogy issues, the process of implementing the service learning program (which includes the four factors), and a specific service learning project exemplar.
Collective strength

Current theories of social power suggest that development of a shared social identity can create the possibility of bringing about political and attitudinal change as well as benefiting individual psychological well-being. This exploratory, qualitative, internet-based study extending over two years explored the impact of developing a shared social identity among a group of people with early-stage dementia. We investigated the experience of belonging to the self-help network Dementia Advocacy and Support International (DASNI), and its effect on self-concept and adjustment, from the perspective of DASNI members in order to understand more about the factors that promote self-help, and the effects of engaging in self-help, mutual support and advocacy in this context. Seven active members of DASNI with a dementia diagnosis volunteered to participate. Interviews were conducted via email, and Interpretative Phenomenological Analysis (IPA) was used to develop a thematic account. The challenges engendered by the onset of dementia were reflected in descriptions of loss, struggle and uncertainty. Participating in DASNI, in contrast, engendered a sense of collective strength and having something valuable to contribute, and made it possible to discover that there can be life after diagnosis. Belonging to DASNI helped to counteract the challenges to self and identity posed by developing dementia, thus significantly affecting the experience of living with dementia, and creating the possibility of effecting social change. Gradually, people in the mild to moderate stages of dementia are developing a `voice' and rejecting the passive patient role. One important element in this process is the way in which people with dementia band together to help themselves and one another, and influence social attitudes, through mutual support and collaborative advocacy. The development of DASNI, consistent with recent theoretical developments in conceptualizing processes of social power and influence, offers significant potential for change.
Achievement motivation, educational attainment, cycles of disadvantage and social competence : some longitudinal data

Summary. The social and familial background, intelligence and personality of children and adolescents have been shown to contribute to their status in society, their educational attainment and to social competence in general as adults (Rutter and Madge, 1976; Garmezy, 1987). This study considers how these factors are translated into behaviour through the mediation of achievement motivation. Using a multidimensional approach to achievement motivation (Cassidy and Lynn, 1989), the achievement factors that predicted educational attainment and socioeconomic status in a sample of 451 young adults were identified. Data for the sample of 199 males and 252 females were collected at two points over a seven-year period. Initial assessment occurred at age 16 and final assessment at age 23 approximately. It is suggested that a focus on the development of cognitive-behavioural styles of achievement motivation, problem-solving and attribution may provide a useful future direction for research on social competence. The implications of such a focus are discussed.
The role of action research in transforming teacher identity: modes of belonging and ecological perspectives

While teacher identity has been conceptualized in different ways, research in teacher education has shown that the development of self‐understanding about being a teacher is critical to learning how to teach and can be shaped in multiple ways. Etienne Wenger argues that the formation of communities of practice is influenced strongly by the negotiation of identity and thus, to understand learning in relation to identity formation and communities of practice, three modes of belonging should be considered. Using data from a three‐year action research project, the author examines how modes of belonging (engagement, alignment, and imagination) were enacted in teacher‐centred action research communities of practice. As well, an ecological perspective is adopted to provide insight into how teachers' identities are formed and reformed in the context of teacher‐centred action research.
Closer to Noninvasive Out-of-Office Aortic Blood Pressure Assessment: A Time to Think and Act

See related article, pp 825–832 The noninvasive assessment of central (aortic or carotid) blood pressure (BP) is a challenge to the clinical investigation of arterial hypertension. The importance of central BP was recognized decades ago on the basis of invasive hemodynamic studies1 but has become widely acknowledged during the last 15 years.2 This is largely attributed to the work of highly respected pioneers, like Michael O'Rourke's team, who created the first commercial device (SphygmoCor, AtCor, Sydney, Australia), enabling the wide application of the noninvasive assessment of aortic BP.3 In this issue of Hypertension , Weber et al4 present the validation of a novel BP recording device that noninvasively assesses aortic BP based on the brachial cuff oscillometric method and the application of mathematical transformation. The present invasive and noninvasive validation is of importance because it is a straightforward demonstration of the strengths and disadvantages of a new generation of BP devices that opens the way to out-of-office aortic BP self-assessment. After briefly reviewing the reasons for estimating central BP, we discuss the novelty of this device, the findings, and limitations of this study.4 and some of the major issues that should arise in future clinical research and practice. ### Why Assess Central Pressure? The reasons have been extensively addressed in recent expert opinions and reviews1,5 and are only summarized here. Normally, central systolic BP (SBP) and pulse pressure (PP) are lower than peripheral SBP and PP (from 1 to 30 mm Hg). This PP disparity, defined as PP amplification,1 is an undisputable physiological phenomenon and depends on the individual's hemodynamic and pathophysiological characteristics.1,6 Notably, PP amplification exhibits substantial within-subject time variability (eg, from 5 to 20 mm Hg; Figure) that is mainly attributed to variations in heart rate, pressure wave reflections, and arterial …
Eccentric contractions increase the phosphorylation of tuberous sclerosis complex‐2 (TSC2) and alter the targeting of TSC2 and the mechanistic target of rapamycin to the lysosome

• Mechanical stimuli play a major role in the regulation of skeletal muscle mass. • Signalling through a protein kinase called the mechanistic target of rapamycin (mTOR) is essential for mechanically induced changes in muscle mass; however, the mechanism(s) via which mechanical stimuli regulate mTOR signalling have not been defined. • In this study, mouse skeletal muscles were stimulated with eccentric contractions (ECs) to determine if the mechanical activation of mTOR signalling is associated with changes in the phosphorylation of the tuberous sclerosis complex‐2 (TSC2) and the targeting of both mTOR and TSC2 to the lysosome. • Our results demonstrate that ECs induce hyper‐phosphorylation of TSC2, enhanced lysosomal targeting of mTOR and nearly abolish the lysosomal targeting of TSC2. • These novel observations suggest that alterations in the lysosomal targeting of mTOR/TSC2 could play a fundamental role in the mechanism via which mechanical stimuli regulate mTOR signalling and ultimately skeletal muscle mass.
Detection of Aspergillus fumigatus PCR products by a microtitre plate based DNA hybridisation assay.

AIMS: To develop a DNA based plate hybridisation assay for the detection of polymerase chain reaction (PCR) products amplified from Aspergillus fumigatus DNA; and to determine the sensitivity of this technique and compare it with Southern blotting. METHODS: A half-log dilution series of DNA extracted from A fumigatus was amplified with specific primers, one of which was 5' end labelled with biotin. PCR products were subsequently detected by agarose gel electrophoresis, Southern blotting, and binding of the products to a streptavidin coated microtitre well, followed by non-radioactive colorimetric detection. Amplification was carried out 10 times for each DNA dilution and a plot of initial DNA concentration against signal intensity was made. RESULTS: A DNA concentration of 1.5 pg could be detected by agarose gel electrophoresis and Southern blotting with a non-radioactively labelled aspergillus specific probe; 1.5 pg was detectable by streptavidin binding of the PCR products to a microtitre plate. The signal from the microtitre plate detection was proportional to the amount of DNA in the PCR reaction on a log-log scale between 100 and 1 pg of DNA. CONCLUSIONS: A DNA based plate hybridisation assay for the detection of A fumigatus PCR products is as sensitive as Southern blotting. However, results are obtained in three hours rather than the three days required for agarose gel electrophoresis, blotting, hybridisation, and detection.
A machine learning approach to web personalization

Most web sites today are designed one-size-fits-all: all visitors see the exact same pages regardless of interests, previous interactions, or, frequently, even browsing client (desktop PC or wireless PDA). But one size often does not fit all. Instead of presenting the same content, the web experience should be dynamic and personalized, adapting to visitors' preferences as evinced in previous interactions. This thesis proposes a framework for personalizing the web experience. Within our PROTEUS framework, we view personalization as a two-step process of first modeling users, and then improving the site given the model. We frame this problem as a machine learning task: the goal is to predict users' web navigation given their previous behavior. We explore several means of personalization, including improving the wireless web and building personalized, dynamic portals, and concentrate on one in particular—automatically adding shortcuts to likely navigation destinations. A challenge in modeling web navigation is that training data for an entire site may be plentiful, but sparse for any individual page. This difficulty can be overcome, however, by noting that most large web sites have a rich underlying relational structure that can be exploited for generalization: pages can belong to different types (e.g., pages about laptop computers versus pages about printers), with each type described by a different set of attributes (e.g., size of display versus printing speed). We leverage this structure by developing relational Markov models (RMMs), a novel extension to Markov models. States in an RMM belong to relations and are described by variables over hierarchically structured domains. Based on these hierarchies, the RMM defines sets of related states, learns transition probabilities between these sets, and uses shrinkage to estimate transitions between individual pages. This thesis presents RMMs in detail and provides results showing that they outperform traditional Markov models for predicting web navigation by a substantial margin.
Mast Cells Granular Contents Are Crucial for Deep Vein Thrombosis in Mice

Rationale: Deep vein thrombosis (DVT) and its complication pulmonary embolism have high morbidity reducing quality of life and leading to death. Cellular mechanisms of DVT initiation remain poorly understood. Objective: We sought to determine the role of mast cells (MCs) in DVT initiation and validate MCs as a potential target for DVT prevention. Methods and Results: In a mouse model, DVT was induced by partial ligation (stenosis) of the inferior vena cava. We demonstrated that 2 strains of mice deficient for MCs were completely protected from DVT. Adoptive transfer of in vitro differentiated MCs restored thrombosis. MCs were present in the venous wall, and the number of granule-containing MCs decreased with thrombosis. Pharmacological depletion of MCs granules or prevention of MC degranulation also reduced DVT. Basal plasma levels of von Willebrand factor and recruitment of platelets to the inferior vena cava wall after DVT induction were reduced in MC-deficient mice. Stenosis application increased plasma levels of soluble P-selectin in wild-type but not in MC-deficient mice. MC releasate elevated ICAM-1 (intercellular adhesion molecule-1) expression on HUVEC (human umbilical vein endothelial cells) in vitro. Topical application of compound 48/80, an MC secretagogue, or histamine, a Weibel–Palade body secretagogue from MCs, potentiated DVT in wild-type mice, and histamine restored thrombosis in MC-deficient animals. Conclusions: MCs exacerbate DVT likely through endothelial activation and Weibel–Palade body release, which is, at least in part, mediated by histamine. Because MCs do not directly contribute to normal hemostasis, they can be considered potential targets for prevention of DVT in humans.