Miracle-dz/UniFAR-FTUs huggingface dataset:
Altered hamstring strength profile in Gaelic footballers with a previous hamstring injury

Hamstring injuries are common in many sports involving high-load eccentric hamstring activation, including Gaelic football. Eccentric hamstring peak torque (PT) and hamstring angle to peak torque (AngPT) have not been examined in previously injured Gaelic footballers. This study aimed to determine whether significant hamstring and quadriceps PT deficits were present in Gaelic footballers after a hamstring injury. Concentric hamstring and quadriceps PT at 60 and 180 degrees/second ( � /s) and eccentric hamstring PT at 30 � /s were measured using an isokinetic dynamometer in 18 male Gaelic footballers (nine previously injured, nine controls). Hamstring AngPT, as well as hamstring and quadriceps PT and PT ratios were analysed. For previously injured limbs, hamstring AngPT occurred at significantly sh orter muscle lengths (p = 0.038) than for the contralateral uninjured limbs in eccentric testing only. There were no other signific ant differences (p > 0.05) at any velocity, for within-subject or between-subject comparisons. The results showed that the previously injured hamstrings generated their eccentric ha mstring AngPT at significantly shorter muscle lengths than the contr alateral hamstrings. The results imply footballers with a p revious hamstring injury who have returned to full participation may remain at increased risk of re-injury because of an alterat ion in their eccentric hamstring AngPT.
Midwifery and Childbirth in America

List of Tables Foreword Charles S. Mahan, M.D. Preface Acknowledgments 1. What Is Midwifery? 2. Brief History of Midwifery in the West 3. The Beginning of Nurse-Midwifery 4. Midwifery Amid the Social Movements of the 1960s and 1970s 5. Maternal and Infant Health and the Health Care System, 1980-1995 6. Midwifery in America: Philosophy, Objectives, and Body of Knowledge 7. Midwifery in America, 1980-1994: Percent of Births, Place of Birth, and Clientele 8. Nurse-Midwifery in America, 1980-1995 9. Development of Direct-Entry Midwifery, 1980-1995 10. The Quality, Safety, and Effectiveness of Midwifery as Practiced in the United States 11. Safety of Out-of-Hospital Births in the United States 12. Effects of Midwifery Care on Costs and Other Special Contributions 13. Midwifery in Europe, Canada, Australia, New Zealand, and Japan 14. The Current Situation and Recommendations for the Future References Index
Application of the Warping Methods in Dental Radiology Images Analysis

The “image warping” functions are useful techniques to match image objects when there are strong correlations between the positions of these objects in space. In order to do this, a function f, called warping function, is defined and is used to convert a given image into a reference known image. Several types of warping functions are described in the specialized literature – affine function, Procrustes transformation, bilinear transformation, perspective transformation and mosaic transformation. In this work, we present these functions and apply them to process several dental radiology images in a controlled manner, defined by a variation range of parameters.
A Textual Analysis of Book Reviews of Critically Acclaimed & Chick Lit Novels, 1998-2008

This study explores the hierarchy of symbolic value between literary and genre fiction through a discourse analysis of book reviews of chick lit and critically acclaimed books published between 1998-2008 in leading review publications such as The New York Times, Library Journal, Publishers Weekly, Kirkus Reviews, and Booklist. Genre fiction is typically accorded less symbolic value than literary fiction, and, at times, distaste for genre fiction has lead to distaste for its audience. Evidence for these assertions can be found in the type of language employed in book reviews of chick lit and critically acclaimed novels, especially in the use of adjectives, opinion words, as well as terms used to describe writing techniques, characters, authors, and
POMDP-Based Energy Cooperative Transmission Policy for Multiple Access Model Powered by Energy Harvesting

To efficiently use harvested energy, we often consider energy cooperation between transmitter nodes in a multiple access wireless network. However the imperfect observations of current network states will degrade the energy transfer policy. In addition, it is difficult to derive an optimal data transmission policy based on the imperfect observation states. In order to solve these problems, we design a partially observed Markov decision process based energy cooperative transmission policy to maximize long-term system throughput. This policy optimizes the energy transfer and data transmission when we cannot observe energy harvesting states and channel states in a current time interval. We adopt the piecewise linearity of the value function and incremental pruning algorithm to obtain the optimal policy for all states in three energy harvesting scenarios. Simulation results show that the proposed cooperative optimal policy converges fast and produces higher sum throughput compared with other policies. Specifically, this policy could be used in device-to-device communication and vehicular networks.
An upper-bound algorithm for gate-level delay analysis

An upper-bound algorithm for gate-level delay analysis dynamically updates path timing information. When conflicting logic value occurs, the algorithm switches to the most promising path according to the updated path delay. The execution time has been greatly shortened by reducing the number of paths to be traced. The algorithm has been run on ten benchmark circuits. The results show its advantages in efficiency and accuracy over the PERT approach. <<ETX>>
Technology Acceptance of a Novel Mobile Learning Application among University Undergraduates

This paper identifies factors affecting the adoption of mobile learning application in the classroom. The principles of the Innovation Diffusion Theory (IDT) and Technology Acceptance Model (TAM) were adopted as the main elements that were investigated in this study, namely relative advantage, complexity, mobile learning acceptance, and intention to use mobile learning. The research design was based on a quantitative approach using an online survey involving a group of 200 undergraduates. Data collected were analyzed using the Comparative Fit Index (CFI) and Tucker-Lewis Index (TLI) on AMOS 20.0. Interestingly, the main research findings showed that all the indices fit the hypothesized model perfectly and all the technology acceptance constructs were significantly correlated. The finding encourage that UPSI’s undergraduates are perceptive to utilizing mobile learning approach with the utilize of novel mobile applications, which surely would have an enormous impact on the current teaching and learning practice in the campus. From the practical standpoint, such a learning paradigm would become more prevalent in many institutions of higher learning as mobile technology keeps on improving and becoming more affordable, hence enabling more students to gain unrivaled access to mobile online learning content.
Simple Approach to Bandwidth Enhancement Of Compact Pifa For Wireless System Applications

Bandwidth is a critical parameter that must be considered in the design of electrically small antennas for compact wireless system. In order to overcome the demerit of narrow bandwidth, a simple method of bandwidth enhancement through parametric study of PIFA is proposed. The PIFA understudied was designed and simulated by the use of theoretical equations based on transmission line model and High Frequency Structural Simulator (HFSS) respectively. It has initial bandwidth of The study reveals that by reducing the size ratio of the planar element (radiating patch) of PIFA, bandwidth enhancement of was achieved. Increasing the distance between short plate and feed gave rise to increment in bandwidth while increasing the length of ground plane while keeping the width of ground plane constant enhanced bandwidth by . The designed compact PIFA of patch size can be employed in wireless systems such as cell phone and implantable medical devices .
Dynamic Task Scheduling Algorithm with Deadline Constraint in Heterogeneous Volunteer Computing Platforms

Volunteer computing (VC) is a distributed computing paradigm, which provides unlimited computing resources in the form of donated idle resources for many large-scale scientific computing applications. Task scheduling is one of the most challenging problems in VC. Although, dynamic scheduling problem with deadline constraint has been extensively studied in prior studies in the heterogeneous system, such as cloud computing and clusters, these algorithms can’t be fully applied to VC. This is because volunteer nodes can get offline whenever they want without taking any responsibility, which is different from other distributed computing. For this situation, this paper proposes a dynamic task scheduling algorithm for heterogeneous VC with deadline constraint, called deadline preference dispatch scheduling (DPDS). The DPDS algorithm selects tasks with the nearest deadline each time and assigns them to volunteer nodes (VN), which solves the dynamic task scheduling problem with deadline constraint. To make full use of resources and maximize the number of completed tasks before the deadline constraint, on the basis of the DPDS algorithm, improved dispatch constraint scheduling (IDCS) is further proposed. To verify our algorithms, we conducted experiments, and the results show that the proposed algorithms can effectively solve the dynamic task assignment problem with deadline constraint in VC.
The impact of mandatory continuous professional development and training to deliver the new contract on female community pharmacists: A qualitative study

This paper discusses female community pharmacists’ views on continuous professional development (CPD) and the impact of the new community pharmacy contract on training requirements. It describes interviewees’ experiences of accessing, completing and recording training including CPD. Additionally, it discusses incentives for completing additional training, and considers the likely effect of mandatory CPD on participation in the workforce. The study involved face-to-face semi- structured interviews with 30 female community pharmacists from a diverse range of backgrounds. This study found that although most interviewees agreed that CPD was necessary, the majority found accessing, completing and recording training challenging. Most interviewees had avoided entering CPD online offering a range of reasons. This study suggests that some female community pharmacists would benefit from information technology (IT) coaching, internet access in the workplace and time in work to enter CPD online. It seems however that most interviewees did not intend to quit pharmacy in response to mandatory CPD.
Research of Hadoop Parameters Tuning Based on Function Monitoring

Hadoop is a popular software framework supports distributed processing of large data sets. However, with Hadoop being a relatively new technology, practitioners and administers often lack the expertise to tune it to get better performance. Hadoop parameters configuration is one of the key factors which influence the performance. In this article, we present a novel Hadoop parameters tuning method based on function monitoring. This method monitors the function call information during task run to analyze why the performance of Hadoop changes when tuning parameters, which will be helpful for practitioners and administer to tune parameters to get better performance.
Pattern Recognition Receptor Polymorphisms as Predictors of Oxaliplatin Benefit in Colorectal Cancer

Abstract Background Constitutional loss of function (LOF) single nucleotide polymorphisms (SNPs) in pattern recognition receptors FPR1, TLR3, and TLR4 have previously been reported to predict oxaliplatin benefit in colorectal cancer. Confirmation of this association could substantially improve patient stratification. Methods We performed a retrospective biomarker analysis of the Short Course in Oncology Therapy (SCOT) and COIN/COIN-B trials. Participant status for LOF variants in FPR1 (rs867228), TLR3 (rs3775291), and TLR4 (rs4986790/rs4986791) was determined by genotyping array or genotype imputation. Associations between LOF variants and disease-free survival (DFS) and overall survival (OS) were analyzed by Cox regression, adjusted for confounders, using additive, dominant, and recessive genetic models. All statistical tests were two-sided. Results Our validation study populations included 2929 and 1948 patients in the SCOT and COIN/COIN-B cohorts, respectively, of whom 2728 and 1672 patients had functional status of all three SNPs determined. We found no evidence of an association between any SNP and DFS in the SCOT cohort, or with OS in either cohort, irrespective of the type of model used. This included models for which an association was previously reported for rs867228 (recessive model, multivariable-adjusted hazard ratio [HR] for DFS in SCOT = 1.19, 95% confidence interval [CI] = 0.99 to 1.45, P = .07; HR for OS in COIN/COIN-B = 0.92, 95% CI = 0.63 to 1.34, P = .66), and rs4986790 (dominant model, multivariable-adjusted HR for DFS in SCOT = 0.86, 95% CI = 0.65 to 1.13, P = .27; HR for OS in COIN/COIN-B = 1.08, 95% CI = 0.90 to 1.31, P = .40). Conclusion In this prespecified analysis of two large clinical trials, we found no evidence that constitutional LOF SNPs in FPR1, TLR3, or TLR4 are associated with differential benefit from oxaliplatin. Our results suggest these SNPs are unlikely to be clinically useful biomarkers.
FACADE RECONSTRUCTION FOR TEXTURED LOD2 CITYGML MODELS BASED ON DEEP LEARNING AND MIXED INTEGER LINEAR PROGRAMMING

Abstract. The paper describes a workflow for generating LoD3 CityGML models (i.e. semantic building models with structured facades) based on textured LoD2 CityGML models by adding window and door objects. For each wall texture, bounding boxes of windows and doors are detected using “Faster R-CNN”, a deep neural network. We evaluate results for textures with different resolutions on the ICG Graz50 facade dataset. In general, detected bounding boxes match very well with the rectangular shape of most wall openings. Thus, no further classification of shapes is required. Windows are typically aligned to rows and columns, and only a few different types of windows exist for each facade. However, the neural network proposes rectangles of varying sizes, which are not always aligned perfectly. Thus, we use post-processing to obtain a more realistic appearance of facades. Window and door rectangles get aligned by solving a mixed integer linear optimization problem, which automatically leads to a clustering of these openings into few different classes of window and door types. Furthermore, an a-priori knowledge about the number of clusters is not required.
Generation of 3D Hair Model from Multiple Pictures ( Image Media Technology for Virtual Reality Applications)

This research proposes image-based hair modeling algorithm that is effective at producing a realistic hair model for virtual characters in the world of virtual reality, movies, television commercials, and simulation games. To create a realistic and physically accurate hair model, the importance of hair cutting and bending must he considered. The problems of cutting and bending are solved through the use of multiple images of a human model. Multiple hair images taken from different directions provide the cutting criteria. To calculate the bending angle, hair volume is produced from three images of the head taken from the right, back and top. This hair volume represents the real space volume where hair is found and guides the bending process until the hair strands are inside the hair volume. The use of the hair volume together with the hair-area-outlines produces a hair model that is not only realistic but also closely resembles the human model in the picture.One main advantage of this hair model is the ability to model hair for specific individuals which is very difficult to achieve with other methods.
Shape-based pedestrian detection and tracking

This paper presents a large scale experimental study on pedestrian detection. The focus of the study is the Chamfer System, a generic system for shape-based object recognition. Matching involves a simultaneous coarse-to-fine approach over a template hierarchy and over the transformation parameters based on correlation with (chamfer) distance-transformed images. Candidate solutions are verified by a neural network with local receptive fields, using a richer set of texture features. Detection is supplemented by an alpha-beta tracker which integrates results over time; the tracker compensates for momentarily missing detections due to image noise or occlusions. For this study, an extensive database of 4762 pedestrian images was compiled with precise ground-truth data. System performance was analyzed by several ROC curves. Although not viable for real-world deployment yet, system performance is shown to be quite promising.
Physical activity or estradiol supplementation can prevent increases in fat mass in ovariectomized mice

Title of Thesis Defense: PHYSICAL ACTIVITY OR ESTRADIOL SUPPLEMENTATION CAN PREVENT THE METABOLIC SYNDROME IN OVARIECTOMIZED MICE Degree Candidate: Lindsay Michelle Wohlers Degree and year: Master of Arts, 2008 Thesis directed by: Espen E. Spangenburg, PhD Department of Kinesiology Loss of ovarian hormones (ie. menopause) results in a significant increase in risk for developing the metabolic syndrome. Thus, the purpose of this study is to investigate the effectiveness of exercise in preventing the metabolic syndrome in a model of menopause. Female C57/BL6 mice were divided into three groups, ovariectomized (OVX), SHAM, and ovariectomized supplemented with 17β-estradiol (OVX+E2), with mice placed in either voluntary running wheel cages or standard cages for eight weeks. OVX animals ran significantly less than SHAM animals, with the OVX+E2 group exhibiting a partial recovery in distance. Visceral fat mass and blood glucose levels were elevated in the OVX sedentary group as compared to SHAM and OVX+E groups. 2 Voluntary wheel running and 17-β estradiol supplementation attenuated increases in visceral fat mass, blood glucose levels, and ERK1/2 phosphorylation in OVX animals, thus preventing symptoms of the metabolic syndrome which accompany loss of ovarian hormones. PHYSICAL ACTIVITY OR ESTRADIOL SUPPLEMENTATION CAN PREVENT INCREASES IN FAT MASS IN OVARIECTOMIZED MICE
Determining similarity and inferring relations in a lexical knowledge base

This dissertation describes the creation of a large-scale, richly structured lexical knowledge base (LKB) from complex structures of labeled semantic relations. These structures were automatically extracted using a natural language parser from the definitions and example sentences contained in two machine readable dictionaries. The structures were then completely inverted and propagated across all of the relevant headwords in the dictionaries to create the LKB. A method is described for efficiently accessing salient paths of semantic relations between words in the LKB using weights assigned to those paths. The weights are based on a unique computation called averaged vertex probability. Extended paths, created by joining sub-paths from two different semantic relation structures, are allowed in order to increase the coverage of the information in the LKB. A novel procedure is used to determine the similarity between words in the LKB based on the patterns of the semantic relation paths connecting those words. The patterns were obtained by extensive training using word pairs from an online thesaurus and a specially created anti-thesaurus. The similarity procedure and the path accessing mechanism are used in a procedure to infer semantic relations that are not explicitly stored in the LKB. In particular, the utility of such inferences is discussed in the context of disambiguating phrasal attachments in a natural language understanding system. Quantitative results indicate that the size and coverage of the LKB created in this research and the effectiveness of the methods for accessing explicit and implicit information contained therein represent significant progress toward the development of a truly broad-coverage semantic component for natural language processing.
Color Reconstruction for CFA Images

The color image enhancement is an important topic for last few decades and still many researchers are working and presenting their research findings in literature. There are two issues in digital camera, firstly color filtering and secondly low spatial resolution. To solve both issues, this paper presents a new super resolution approach. Although Bayer pattern CFA is widely used in camera industry, there are few alternatives such as X-Trans CFA pattern. As color restoration method for X-Trans CFA pattern is not many, this paper introduce filter based demosaicking method. We firstly design filters then apply it to X-Trans CFA pattern. Then, full color images are obtained. Experimental results indicate that the presented method provides satisfactory results.
Validation of Learning Hierarchies for Objective-Based Instructional Systems.

The need for an empirically defensible means of sequencing instruction appears to have been the primary motivator for research into learning hierarchies. Also, valid learning hierarchies could act as congealing forces in individualizing instructional systems by providing psychological roadmaps for diagnosing students' preinstructional skills and monitoring students' progress through instructional systems. Four methods for generating candidates for learning hierarchies are available: introspection, formal analysis, observation, and statistical nfishing. " Experimental transfer of training studies and statistical studies have been used to evaluate posited hierarchies. white recently made significant modifications of these standard evaluation methods to improve the internal validity of research into learning hierarchies. Several external validity issues remain to be resolved before scarce resources should continue to be allocated for additional learning hierarchy research. (Author) S DEPARTMENT GP HEALTM EDUCATION &WELFARE NA TiONAL INSTITUTE Of E CNC ATtON ki-PRO . ; f fl f 11.1 . S' t ROM sTf ief -,1% I A" ON 0R,G.N S' . f A 04 OPINONS ;. ,f r. r PEpin . f 'il,f F A. ,-, r-e, IV SA . e T GO C BEST COPT AVAILABLE VALIDATION OF LEARNING HIERARCHIES FOR OBJECTIVE-RASED INSTRUCTIONAL SYSTEMS
Flat-panel-detector-based cone-beam volume CT breast imaging: phantom and specimen study

Conventional film-screen mammography is the most effective tool for the early detection of breast cancer currently available. However, conventional mammography has relatively low sensitivity to detect small breast cancers (under several millimeters) owing to an overlap in the appearances of benign and malignant lesions, and surrounding structure. The limitations accompanying conventional mammography is to be addressed by incorporating a cone beam volume CT imaging technique with a recently developed flat panel detector. A computer simulation study has been performed to prove the feasibility of developing a flat panel detector-based cone beam volume CT breast imaging (FPD-CBVCTBI) technique. In this study, a phantom and specimen experiment is performed to confirm the findings in the computer simulation using the current prototype cone beam volume CT scanner. The results indicate that the CBVCTBI technique effectively removes structure overlap and significantly improves the detectability of small breast tumors. More importantly, the results also demonstrate the patient dose level required for FPD-based CBVCTBI to detect a small tumor (under 5 mm) and a small calcification is less than or equal to that of conventional mammography. The results from this study suggest that FPD-CBVCTBI is a potentially powerful breast-imaging tool.