Miracle-dz/UniFAR-FTUs huggingface dataset:
The perception of school foodservice professionals on the implementation of the Healthy , Hunger-Free Kids Act of 2010 : a mixed-methods study

Objective: To: (i) understand the nutrition attitudes, self-efficacy, knowledge and practices of school food-service personnel (SFP) in Nebraska and (ii) identify potential barriers that schools face in offering healthy school meals that meet the US Department of Agriculture (USDA) nutrition standards. Design: Convergent parallel mixed-methods study. Setting: Kindergarten–12th grade schools in Nebraska, USA. Participants: SFP (260 survey participants; fifteen focus group participants) working at schools that participate in the USDA National School Lunch Program. Results: Mixed-methods themes identified include: (i) ‘Mixed attitudes towards healthy meals’, which captured a variety of conflicting positive and negative attitudes depending on the situation; (ii) ‘Positive practices to promote healthy meals’, which captured offering, serving and promotion practices; (iii) ‘Mixed nutrition-related knowledge’, which captured the variations in knowledge depending on the nutrition concept; and (iv) ‘Complex barriers’, which captured challenges with time, support and communication. Conclusions: The study produced relevant findings to address the barriers identified by SFP. Implementing multicomponent interventions and providing training to SFP may help reduce some of the identified barriers of SFP.
Extracting Transportation Information and Traffic Problems from Tweets during a Disaster

—In a disaster, one of the most important issues for victims is how to find evacuation routes to safety from hazardous areas. To offer such routes, we propose methods automatically extracting transportation information and traffic problems from tweets written in Japanese and posted during a disaster. To investigate the effectiveness of our methods, we conducted some experiments using tweets posted during the Great Eastern Japan Earthquake in March 2011. From the experimental results, we obtained precision of 78.2% and recall of 53.4% in automatic extraction of transportation information. For extracting traffic problems, we identified tweets containing relevant information (we call them traffic problem tweets), and extracted traffic problem from them. In identifying traffic problem tweets, we obtained precision of 77.7% and recall of 70.7%. In extracting traffic problems, we obtained precision of 87.0% and recall of 57.1%. Thus, we have constructed a system for providing transportation information and traffic problems in a disaster.
ASSOCIATION OF TETA AND TETB GENES AND DRUG RESISTANCE PATTERN OF K . PNEMONIAE ISOLATED FROM PATIENTS VISITING GONDAR UNIVERSITY TEACHING HOSPITAL

Klebsiella pneumoniae found as a common flora in intestinal tract, mouth and skin of humans do not cause disease. However, when the bacterium founds other parts of the body, it is associated with many different types of human disease. K. pneumoniae is one of the pathogen that contains a variety of resistance genes. The objective of this study was to detect tetA and tetB resistance genes in K. pneumoniae. Experimental study was conducted on a totality of 50 K. pneumoniae isolates from different specimens of patients at Gondar University hospital from November, 2014 to April, 2016. The Klebsiella pneumoniae genomic DNA was isolated by phenol chloroform method. PCR was performed to detect tetA and tetB genes by specific pair of primers. K. pneumoniae showed resistance against Amoxicillin 50(100%), followed by Streptomycin 23 (60%). From total, forty (80%) of K. pneumonia isolates were multidrug resistance which showed a resistance to two or more antibiotics. The occurrence of the genes tetA and tetB were 2 (4%) and 1(2%) for tetA tetB genes, respectively. The presence of multidrug resistance K. pneumoniae strains that harbor resistance genes (tetA and tetB), might be serving as indicators for the role of these genes in antibiotic resistance.
Gender Similarities and Differences in Written Business Communication

The purpose of this research study is to determine whether there are differences between how men and women communicate through written business communication. The study focuses on four aspects of business writing including length of response, readability of the writing, me versus you orientation, and overall positive or negative tone of written communication. No statistically significant differences were found between males and females in the sample used when analyzing the first three variables. However, the use of positive language, as measured by overall positive or negative tone in each writing sample, was more prevalent with women than men.
Data Compression Techniques : A Comparative Study

Data compression is one of many technologies that enables today’s information revolution. Image compression is an application of data compression. Image compression is now essential for applications such as transmission and storage in data bases. In this paper we review and discuss about the image compression, need of compression, its principles, and classes of compression and various algorithm of image compression. This paper attempts to give a recipe for selecting one of the popular image compression algorithms based on Wavelet, JPEG/DCT, VQ, and Fractal approaches. We review and discuss the advantages and disadvantages of data compression techniques and algorithms for compressing grayscale images; give an experimental comparison on 256×256 commonly used image of Lenna and one 400×400 fingerprint image.
Into the Wild: Transitioning from Recognizing Mood in Clinical Interactions to Personal Conversations for Individuals with Bipolar Disorder

Bipolar Disorder, a mood disorder with recurrent mania and depression, requires ongoing monitoring and specialty management. Current monitoring strategies are clinically-based, engaging highly specialized medical professionals who are becoming increasingly scarce. Automatic speech-based monitoring via smartphones has the potential to augment clinical monitoring by providing inexpensive and unobtrusive measurements of a patient’s daily life. The success of such an approach is contingent on the ability to successfully utilize “in-the-wild” data. However, most existing work on automatic mood detection uses datasets collected in clinical or laboratory settings. This study presents experiments in automatically detecting depression severity in individuals with Bipolar Disorder using data derived from clinical interviews and from personal conversations. We find that mood assessment is more accurate using data collected from clinical interactions, in part because of their highly structured nature. We demonstrate that although the features that are most effective in clinical interactions do not extend well to personal conversational data, we can identify alternative features relevant in personal conversational speech to detect mood symptom severity. Our results highlight the challenges unique to working with “in-the-wild” data, providing insight into the degree to which the predictive ability of speech features is preserved outside of a clinical interview.
Internal workings of a genetic circuit

Genetic circuits implement computational operations within a cell. Debugging them is difficult because their function is defined by multiple states (e.g., combinations of inputs) that vary in time. Here, we develop RNA-seq methods that enable the simultaneous measurement of: (i) the states of internal gates, (ii) part performance (promoters, insulators, terminators), and (iii) impact on host gene expression. This is applied to a three-input one-output circuit consisting of three sensors, five NOR/NOT gates, and 46 genetic parts. Transcription profiles are obtained for all eight combinations of inputs, from which biophysical models can extract part activities and the response functions of sensors and gates. Various unexpected failure modes are identified, including cryptic antisense promoters, terminator failure, and a sensor malfunction due to media-induced changes in host gene expression. This can guide the selection of new parts to fix these problems, which we demonstrate by using a bidirectional terminator to disrupt observed antisense transcription. This work introduces RNA-seq as a powerful method for circuit characterization and debugging that overcomes the limitations of fluorescent reporters and scales to large systems composed of many parts.
eview oltage gated sodium and calcium channel blockers for the treatment f chronic inflammatory pain

The inflammatory response is a natural response of the body that occurs immediately following tissue damage, which may be due to injury, infection or disease. The acute inflammatory response is an essential mechanism that promotes healing and a key aspect is the ensuing pain, which warns the subject to protect the site of injury. Thus, it is common to see a zone of primary sensitization as well as consequential central sensitization that generally, is maintained by a peripheral drive from the zone of tissue injury. Inflammation associated with chronic pain states, such as rheumatoid and osteoarthritis, cancer and migraine etc. is deleterious to health and often debilitating for the patient. Thus there is a large unmet clinical need. The mechanisms underlying both acute and chronic inflammatory pain are extensive and complex, involving a diversity of cell types, receptors and proteins. Among these the contribution of voltage gated sodium and calcium channels on peripheral nociceptors is critical for nociceptive transmission beyond the peripheral transducers and changes in their distribution, accumulation, clustering and functional activities have been linked to both inflammatory and neuropathic pain. The latter has been the main area for trials and use of drugs that modulate ion channels such as carbamazepine and gabapentin, but given the large peripheral drive that follows tissue damage, there is a clear rationale for blocking voltage gated sodium and calcium channels in these pain states. It has been hypothesized that pain of inflammatory origin may evolve into a condition that resembles neuropathic pain, but mixed pains such as low back pain and cancer pain often include elements of both pain states. This review considers the therapeutic potential for sodium and calcium channel blockers for the treatment of chronic inflammatory pain states. © 2013 Published by Elsevier Ireland Ltd.
The symplectic geometry of the deformation space of complex projective structures on a surface

This thesis investigates the complex symplectic geometry of the deformation space of complex projective structures on a surface. The author attempts to give a global and unifying picture of this symplectic geometry by exploring the connections between different possible approaches. The cotangent symplectic structure given by the Schwarzian parametrization is studied in detail and compared to the canonical symplectic structure on the character variety, clarifying and generalizing a theorem of S. Kawai [Kaw96]. Generalizations of results of C. McMullen are derived, notably quasifuchsian reciprocity. The cotangent symplectic structure is also addressed through the notion of minimal surfaces in hyperbolic 3-manifolds. Finally, the symplectic geometry is described in a Hamiltonian setting with the complex Fenchel-Nielsen coordinates on the quasifuchsian space, recovering results of I. Platis [Pla01].
MicroRNA-124 induces apoptosis of MHCC 97 H cells through downregulation of KIAP

Hepatocarcinoma is a great threat to global health. microRNA-124 was proved to influence growth and apoptosis in some cell lines. Our study aimed to investigate the effect of microRNA-124 on growth, proliferation and apoptosis of MHCC97H, a hepatocarcinoma cell line, and explored potential mechanism of such pro-apoptosis effect. microRNA-124 and control microRNA (scramble miRNA, for short as miRNA) were synthesized with routine protocol. Lipofection transfection was performed in hepatocarcinoma cell line MHCC97H. MTT assay, caspase-3 activity detection and flow cytometry were performed to examine growth, proliferation and apoptosis of hepatocarcinoma cell line MHCC97H, respectively. KIAP siRNA was synthesized for inhibition of KIAP. KIAP plasmid was established for activation of KIAP. Western blot was performed to examine protein expression of KIAP and caspase protein family after transfection of KIAP siRNA or KIAP plasmid. Compared with miRNA transfection, microRNA-124 transfection significantly reduced growth of MHCC97H cells, and decreased expression of KIAP. Enhanced translocation of phosphatidylserine and activation of caspase-3 were observed in microRNA-124 transfection cells. Moreover, inhibition of KIAP enhanced pro-apoptosis effect of microRNA-124, while activation of KIAP abrogated pro-apoptosis effect of microRNA-124. microRNA-124 inhibits growth and proliferation of MHCC97H cells, and promotes apoptosis of MHCC97H cells via down-regulating KIAP. KIAP could be a potential therapeutic target for hepatocarcinoma treatment.
Optimizing Automated Triaging Using Contextual Information and Feature Extraction

As software systems are getting larger and complex day by day, software bugs are inevitable. A software crash is one of the most severe manifestations of a defect (bug) in software, and is typically assigned a high priority to be fixed. To facilitate debugging process, many crash reporting systems such as Windows Error Reporting, Apple crash report, and Mozilla crash report have been deployed to automatically collect crash reports from users at the time of crash. Bug reports can also accompany other malfunctions of the software, mostly for the beta or unstable versions of the software. Most often, these bug reports are augmented with user contributed experiences as to what actually faced by him/her. Bugs occur for a variety of reasons, ranging from ill-defined specifications, to carelessness, to a programmers misunderstanding of the problem, technical issues, non-functional qualities, corner cases, etc. Addressing these bugs frequently accounts for the majority of effort spent in the maintenance phase of a software project’s life-cycle. This is why, researchers have been trying to enhance the bug-tracking systems to facilitate the bug-fixing process. The person who is in charge of processing the newly reported bugs, checking for duplicates and passing them to appropriate developers to get fixed is called a triager and this process is called triaging. In this paper, an model of automated triaging process is proposed based on contextual information and bug report textual similarity features. In proposed model, the preprocessed bug reports are analyzed for contextual information, to relate them to the non-functional requirements of the software. This extends the feature extraction a step further. The weighted sum of similarity score of all the features, including textual and contextual, is evaluated and used to classify bug reports. Positive and negative sets of existing classification are used to train SVM model. Simulation is done using R simulation package and the results shows a considerable improvement against classification without contextual information.
Unravelling Employer Loyalty : Employer loyalty and its effects on commitment , job satisfaction , organizational citizenship behavior and turnover intention

Loyalty from the employer to the employee has been hardly investigated in prior research. Therefore, two studies investigated the phenomenon of employer loyalty by a survey research in which a questionnaire was completed by 260 employees. Current research confirmed a positive effect of employer loyalty on organizational citizenship behavior (OCB), commitment, job satisfaction and a negative effect on turnover intention (Hypothesis 1a). Also, the unique contribution of employer loyalty to the prediction of these variables above and beyond the predicting value of perceived organizational support (POS) and procedural fairness was examined but not confirmed (Hypothesis 1b). Furhtermore, current research examined whether perceived external threat was related to have been on a mission or not (Hypothesis 2a), whether mission moderates the relationship between employer loyalty and the criterion variables (Hypothesis 2b) and whether threat is a mediator in the moderating effect of mission (2c). Hypotheses 2a/b/c could not be confirmed, although employer loyalty was a predictor of the variables by itself but not above and beyond POS and procedural justice. Furhermore, interesting findings emerged from exploratory analyses which confirm that employer loyalty was a unique predictor of turnover intention above and beyond POS and procedural fairness. Psychological safety was mediating the effect of employer loyalty on commitment and OCB (but not on job satisfaction and turnover intention). Also POS was mediating the relationship between employer loyalty and commitment, job satisfaction, OCB, turnover intention and psychological safety. These results demonstrate the importance of employer loyalty and provide new perspectives for future research.
Understanding Reuse, Performance, and Hardware Cost of DNN Dataflow: A Data-Centric Approach

The data partitioning and scheduling strategies used by DNN accelerators to leverage reuse and perform staging are known as dataflow, which directly impacts the performance and energy efficiency of DNN accelerators. An accelerator micro architecture dictates the dataflow(s) that can be employed to execute layers in a DNN. Selecting a dataflow for a layer can have a large impact on utilization and energy efficiency, but there is a lack of understanding on the choices and consequences of dataflow, and of tools and methodologies to help architects explore the co-optimization design space. In this work, we first introduce a set of data-centric directives to concisely specify the DNN dataflow space in a compiler-friendly form. We then show how these directives can be analyzed to infer various forms of reuse and to exploit them using hardware capabilities. We codify this analysis into an analytical cost model, MAESTRO (Modeling Accelerator Efficiency via Patio-Temporal Reuse and Occupancy), that estimates various cost-benefit tradeoffs of a dataflow including execution time and energy efficiency for a DNN model and hardware configuration. We demonstrate the use of MAESTRO to drive a hardware design space exploration experiment, which searches across 480M designs to identify 2.5M valid designs at an average rate of 0.17M designs per second, including Pareto-optimal throughput- and energy-optimized design points.
DOES REPEATED EXPOSURE TO SEGMENTAL SOUNDS IMPROVE PERCEPTUAL ABILITY IN NON-NATIVE SPEAKERS?

Previous studies have shown that native (L1) speakers adapt to regional dialects and foreign accents rapidly. Some studies show that non-native (L2) speakers also adapt to foreign accents, but little is known about how they adapt to L2 segmental sounds difficult to perceive in the development of L2 phonetic acquisition. This study explores whether adaptation (learning effects) occurs as Japanese language learners of English are exposed to the English phonetic contrasts /ɑ/–/æ/ and /s/–/θ/ posing perceptual difficulties for them during an identification task. The results showed decreased response times over the course of the experiment only when participants were exposed to the same set of minimal pairs. Accuracy rates did not change, irrespective of whether target items were identical or different. Taken together, the present study observed reduced auditory processing cost, however, this processing advantage resulted from enhanced comprehensibility rather than from the improvement of perceptual ability.
A Mathematical Model for the Influence of Glucose-Insulin Dynamics on the Estrous Cycle in Dairy Cows

Nutrition plays a crucial role in regulating reproductive hormones and follicular development in cattle. This is visible particularly during the time of negative energy balance at the onset of milk production after calving. Here, elongated periods of anovulation have been observed, resulting from alterations in luteiniz- ing hormone concentrations, likely caused by lower glucose and insulin concen- trations in the blood. The mechanisms that result in a reduced fertility are not completely understood, although a close relationship to the glucose-insulin metabolism is widely supported. Following this idea, a mathematical model of the hormonal network combining reproductive hormones and hormones that are coupled to the glucose compartments within the body of the cow was developed. The model is built on ordinary differential equations and relies on previously introduced models on the bovine estrous cycle and the glucose-insulin dynam- ics. Necessary modifications and coupling mechanisms are thoroughly discussed. Depending on the composition and the amount of food, in particular the glu- cose content in the dry matter, the model quantifies reproductive hormones and follicular development over time. Simulation results for different nutritional regimes in lactating and non-lactating dairy cows are examined and compared with experimental studies. Regarding its applicability, this work is an early attempt towards developing in silico feeding strategies and may eventually help refining and reducing animal experiments.
Diffusion of Inclusion: Measuring Willingness

DIFFUSION OF INCLUSION: MEASURING WILLINGNESS TO ADOPT INCLUSIVE TEACHING STRATEGIES IN NURSING EDUCATIONAL ENVIRONMENTS Janet A. Levey MSN, RN-BC, CNE Marquette University, 2015 The purpose of the study was to: (1) examine psychometric properties of the Willingness to Adopt Inclusive Teaching Strategies (ITSinNE) instrument and (2) measure factors influencing a nurse educator’s willingness to adopt inclusive teaching strategies based in universal design for instruction (UDI). Universal design for instruction (UDI) is one approach to facilitate multiple ways of learning and evaluation in various learning environments for all learners; however, it is not well known or researched in nursing education. Diffusion of innovation theory (Rogers, 2003) and universal design for instruction (McGuire & Scott, 2006) provided the theoretical framework for the study. A cross-sectional design was used to measure educators’ willingness to adopt inclusive teaching strategies in nursing educational settings. A total of 311 nurse educators were recruited from professional nursing organization electronic mailing lists and conferences. The ITSinNE (55-items) consisted of four domains: Previous Teaching Strategies, Knowledge of Inclusive Teaching Strategies, Social System Support for Inclusive Teaching Strategies, and Willingness to Adopt Inclusive Teaching Strategies in Nursing Education. Cronbach’s alphas for almost all of the domain subscales were . 7 or greater. The confirmatory factor analysis demonstrated adequate model fit on most indices (exogenous model: χ = 0.00; RMSEA = .08; GFI = .96; TLI = .95; WRWR = 1.64; endogenous model: χ = 0.00; RMSEA = .18; GFI = .89; TLI = .87; WRWR = 2.64). When the endogenous model domains were all freestanding, model fit indexes improved (χ = 0.00; RMSEA = .098; GFI = .97; TLI = .96; WRWR = 1.24). The model as a whole explained 44.8% (R = .448) of the variance in WillAdITS. None of the characteristics of a nurse educator contributed to the model, except for years of teaching (B =.-.008, p < .001) Reliability and validity estimates support the continued development of an instrument to examine nurse educator’s knowledge, support, and willingness to adopt inclusive teaching strategies. This will enable intervention research to enhance professional development fostering access to content and environments for all learners.