LLukas22/scidocs huggingface dataset:
Violent pornography and self-reported likelihood of sexual aggression

Two hundred twenty-two undergraduate males were administered an “attitudes survey” examining pornography use, attitudes, and self-reported likelihood of rape (LR) or using sexual force (LF). Nonviolent pornography was used by 81% of subjects within the last year, whereas 41 and 35% had used violent and sexually violent pornography, respectively. Twenty-seven percent of subjects indicated some hypothetical likelihood of raping or using sexual force against a woman. Discriminant function analysis revealed that use of sexually violent pornography and acceptance of interpersonal violence against women were uniquely associated with LF and LR. It is hypothesized that the specific fusion of sex and violence in some pornographic stimuli and in certain belief systems may produce a propensity to engage in sexually aggressive behavior. Results are interpreted in terms of Malamuth and Briere’s (1986, Journal of Social Issues, 42, 75-92) model of the effects of SeXUally violent media.
A review of the recent advances in antimicrobial coatings for urinary catheters.

More than 75% of hospital-acquired or nosocomial urinary tract infections are initiated by urinary catheters, which are used during the treatment of 15-25% of hospitalized patients. Among other purposes, urinary catheters are primarily used for draining urine after surgeries and for urinary incontinence. During catheter-associated urinary tract infections, bacteria travel up to the bladder and cause infection. A major cause of catheter-associated urinary tract infection is attributed to the use of non-ideal materials in the fabrication of urinary catheters. Such materials allow for the colonization of microorganisms, leading to bacteriuria and infection, depending on the severity of symptoms. The ideal urinary catheter is made out of materials that are biocompatible, antimicrobial, and antifouling. Although an abundance of research has been conducted over the last forty-five years on the subject, the ideal biomaterial, especially for long-term catheterization of more than a month, has yet to be developed. The aim of this review is to highlight the recent advances (over the past 10years) in developing antimicrobial materials for urinary catheters and to outline future requirements and prospects that guide catheter materials selection and design.


STATEMENT OF SIGNIFICANCE
This review article intends to provide an expansive insight into the various antimicrobial agents currently being researched for urinary catheter coatings. According to CDC, approximately 75% of urinary tract infections are caused by urinary catheters and 15-25% of hospitalized patients undergo catheterization. In addition to these alarming statistics, the increasing cost and health related complications associated with catheter associated UTIs make the research for antimicrobial urinary catheter coatings even more pertinent. This review provides a comprehensive summary of the history, the latest progress in development of the coatings and a brief conjecture on what the future entails for each of the antimicrobial agents discussed.
Vision-Based Mobile Robot Localization with Simple Artificial Landmarks

This article presents a vision-based method for mobile robot localization in partially known environments. Simple, unobtrusive artificial landmarks are used as external localization aids. The landmarks are labelled with unique code patterns, what enables unambiguous global localization. The analysis is presented which enables prediction of the uncertainty of the position and orientation of the robot relative to the landmark. Experimental evidence is provided, demonstrating that the proposed method can be reliably used over a wide range of relative positions between the camera and the landmark. Copyright c © 2003 IFAC
Entanglement For Ideal Quantum Ensembles

This paper has been withdrawn by the authors, due to the discovery of paper 0201028 which predates it and contains most of it's results.
Association between physical activity and academic performance in Korean adolescent students

BACKGROUND
Recently, physical activity (PA) was found to improve cognitive and memory functions in the brain; however, no epidemiological studies have specifically investigated this phenomenon in the Korean adolescent student population. The purpose of this study was to investigate the effects of various types of PA undertaken at various frequencies, on the academic performance of Korean adolescent students.


METHODS
A total of 75,066 adolescent students (39,612 males and 35,454 females) from the 7th to the 12th grades took part in the 5th Korea Youth Risk Behavior Web-based Survey (KYRBWS-V) project, conducted in 2009. Using data acquired by that survey, potential relations between PA and academic performance were explored in this current study through multivariate logistic regression analysis incorporating adjustment for covariate variables including age, body mass index, the parents' education level, and the income status of the family.


RESULTS
Compared with boys who did not regularly participate in any vigorous PA, those who did so 2, 3, or 4 times a week had greater odds of reporting an average or above-average academic performance. Compared with boys who did not participate in any moderate PA, those who did so 1, 2, 3, 4, or ≥5 times a week also had greater odds of reporting an average or above-average academic performance. Interestingly, when compared with boys who did not participate in any strengthening exercises, those undertaking strengthening exercises ≥5 times a week had lesser odds of reporting a below-average academic performance. Compared with girls who did not regularly participate in any vigorous PA, those who did so ≥5 times a week had greater odds of reporting an average or above-average academic performance. Compared with girls who did not participate in any moderate PA, those that did so 2 or 3 times a week had greater odds of reporting an average or above-average academic performance. Interestingly, when compared with girls who did not regularly participate in any strengthening exercises, those undertaking strengthening exercises ≥5 times a week had lesser odds of reporting a below-average academic performance.


CONCLUSIONS
Our analyses of the relevant data from the KYRBWS-V suggested that vigorous PA was positively correlated with academic performance in the case of boys, and moderate PA was positively correlated with academic performance in both boys and girls. However, strengthening exercises were not positively correlated with academic performance in boys or girls. Furthermore, when undertaken 5 or more times a week, vigorous PA in boys and strengthening exercises in both boys and girls were negatively correlated with academic performance. The results from this study are potentially relevant to the development of future education policies in Korean schools, particularly with regard to early intervention strategies designed to identify and counteract potential factors contributing to academic underachievement.
Reinforcement Learning Neural Turing Machines

The expressive power of a machine learning model is closely r elated to the number of sequential computational steps it can learn. For exam ple, Deep Neural Networks have been more successful than shallow networks be caus they can perform a greater number of sequential computational steps (ea ch highly parallel). The Neural Turing Machine (NTM) [8] is a model that can compac tly express an even greater number of sequential computational steps, so i t is even more powerful than a DNN. Its memory addressing operations are designed to be differentiable; thus the NTM can be trained with backpropagation. While differentiable memory is relatively easy to implemen t a d train, it necessitates accessing the entire memory content at each computati onal step. This makes it difficult to implement a fast NTM. In this work, we use the Re inforce algorithm to learnwhere to access the memory, while using backpropagation to learn what to write to the memory. We call this model the RL-NTM. Reinfor ce allows our model to access a constant number of memory cells at each comp utational step, so its implementation can be faster. The RL-NTM is the first mo del that can, in principle, learn programs of unbounded running time. We suc cessfully trained the RL-NTM to solve a number of algorithmic tasks that are simple r than the ones solvable by the fully differentiable NTM. As the RL-NTM is a fairly intricate model, we needed a method f r verifying the correctness of our implementation. To do so, we developed a s imple technique for numerically checking arbitrary implementations of mod els that use Reinforce, which may be of independent interest.
Automated Detection and Classification of Glaucoma from Eye Fundus Images : A Survey

the identification of eye diseases in retinal image is the subject of several researches in the field of medical image processing. this research proposed a computerized aid diagnosis system to help specialists by displaying useful information such as the location of abnormalities in fundus images This paper is a survey of techniques for Automatic detection of retina image now a days it is plying a vital role in screening tool. This procedure helps to detect various kind of risks and diseases of eyes. Identification of Glaucoma using fundus images involves the measurement of the size, shape of the Optic cup and Neuroretinal rim One of the most common diseases which cause blindness is glaucoma. Early detection of this disease is essential to prevent the permanent blindness. Screenings of glaucoma based on digital images of the retina have been performed in the past few years. Several techniques are there to detect the anomaly of retina due to glaucoma. The key image processing techniques are image registration, image fusion, image segmentation, feature extraction, image enhancement, morphology, pattern matching, image classification, analysis and statistical measurements. The main idea behind this paper is to illustrate a system which is mainly based on image processing and classification techniques for automatic detection of glaucoma by comparing and measuring different parameters of fundus images of glaucoma patients and normal patients. Keywords—Glaucoma, Cup to disk ratio, Neuroretinalrim Fundus Image, ISNT (inferior, superior, nasal, temporal quadrants), ANN, K-Means Clustering, Thresholding, CDR, ISNT, SVM, Bayesian.
Giving and Getting : Philanthropy

In the decade since the Filer Commission Report, a growing body of research and theory has sought to clarify the nature of philanthropy, the institutional boundaries of the nonprofit sector, and the giving behavior of individuals and organizations. Most of this research conceptualizes and studies the philanthropic world as a world of donors. This work, including some done by the present authors, has focused on explanations of why and how and under what circumstances people 'ive voluntarily of their money and time. This research is important and should continue. It is also important to recognize that an exclusive focus on donors runs the risk of obscuring issues that are of concern to recipients and therefore to philanthropy as a whole. The common language of giver and receiver used to characterize philanthropy suggests a one-way relationship in which valued goods and services move only in one direction, a point of view we challenge here. A donor focus also ignores the ways in which recipients actively take part in defining what goes on in the world of philanthropy, ways in which recipients are agents in creating philanthropic institutions and relations.
Expectation Particle Belief Propagation

We propose an original particle-based implementation of the Loopy Belief Propagation (LPB) algorithm for pairwise Markov Random Fields (MRF) on a continuous state space. The algorithm constructs adaptively efficient proposal distributions approximating the local beliefs at each note of the MRF. This is achieved by considering proposal distributions in the exponential family whose parameters are updated iterately in an Expectation Propagation (EP) framework. The proposed particle scheme provides consistent estimation of the LBP marginals as the number of particles increases. We demonstrate that it provides more accurate results than the Particle Belief Propagation (PBP) algorithm of [1] at a fraction of the computational cost and is additionally more robust empirically. The computational complexity of our algorithm at each iteration is quadratic in the number of particles. We also propose an accelerated implementation with sub-quadratic computational complexity which still provides consistent estimates of the loopy BP marginal distributions and performs almost as well as the original procedure.
Factors affecting pass-along email intentions (PAEIs): Integrating the social capital and social cognition theories

1567-4223/$34.00 Crown Copyright 2008 Publishe doi:10.1016/j.elerap.2008.11.001 * Corresponding author. Tel.: +886 7 5254713; fax: E-mail address: tw_cchuang@hotmail.com (C.-C. H While eWOM advertising has recently emerged as an effective marketing strategy among marketing practitioners, comparatively few studies have been conducted to examine the eWOM from the perspective of pass-along emails. Based on social capital theory and social cognitive theory, this paper develops a model involving social enablers and personal cognition factors to explore the eWOM behavior and its efficacy. Data collected from 347 email users have lent credit to the model proposed. Tested by LISREL 8.70, the results indicate that the factors such as message involvement, social interaction tie, affection outcome expectations and message passing self-efficacy exert significant influences on pass-along email intentions (PAEIs). The study result may well be useful to marketing practitioners who are considering email marketing, especially to those who are in the process of selecting key email users and/or designing product advertisements to heighten the eWOM effect. Crown Copyright 2008 Published by Elsevier B.V. All rights reserved.
EMG pattern recognition and grasping force estimation: Improvement to the myocontrol of multi-DOF prosthetic hands

The multi-DOF prosthetic hand's myocontrol needs to recognize more hand gestures (or motions) based on myoelectric signals. This paper presents a classification method, which is based on the support vector machine (SVM), to classify 19 different hand gesture modes through electromyographic (EMG) signals acquired from six surface myoelectric electrodes. All hand gestures are based on a 3-DOF configuration, which makes the hand perform like three-fingered. The training performance is very high within each test session, but the cross-session validation is typically low. Acceptable cross-session performance can be achieved by training with more sessions or fewer gesture modes. A fast rhythm muscle contraction is suggested, which can make the training samples more resourceful and improve the prediction accuracy comparing with a relative slow muscle contraction method. For many precise grasp tasks, it is beneficial to the prosthetic hand's myocontrol if we can efficiently extract the grasp force directly from EMG signals. Through grasping a JR3 6 dimension force/torque sensor, the force signal applying to the sensor can be recorded synchronously with myoelectric signals. This paper uses three methods, local weighted projection regression (LWPR), artificial neural network (ANN) and SVM, to find the best regression relationship between these two kinds of signals. It reveals that the SVM method is better than ANN and LWPR, especially in the case of cross-session validation. Also, the performance of grasping force estimation based on specific hand gestures is superior to the performance of grasping with random fingers.
Cloud security issues and challenges: A survey

The cloud computing provides on demand services over the Internet with the help of a large amount of virtual storage. The main features of cloud computing is that the user does not have any setup of expensive computing infrastructure and the cost of its services is less. In the recent years, cloud computing integrates with the industry and many other areas, which has been encouraging the researcher to research on new related technologies. Due to the availability of its services & scalability for computing processes individual users and organizations transfer their application, data and services to the cloud storage server. Regardless of its advantages, the transformation of local computing to remote computing has brought many security issues and challenges for both consumer and provider. Many cloud services are provided by the trusted third party which arises new security threats. The cloud provider provides its services through the Internet and uses many web technologies that arise new security issues. This paper discussed about the basic features of the cloud computing, security issues, threats and their solutions. Additionally, the paper describes several key topics related to the cloud, namely cloud architecture framework, service and deployment model, cloud technologies, cloud security concepts, threats, and attacks. The paper also discusses a lot of open research issues related to the cloud security. Keywords—Cloud Computing, Cloud Framework, Cloud Security, Cloud Security Challenges, Cloud Security Issues
Effect on dynamic mechanical stability and interfragmentary movement of angle-stable locking of intramedullary nails in unstable distal tibia fractures: a biomechanical study.

BACKGROUND
Unstable distal tibia fractures are challenging injuries that require surgery. Increasingly, intramedullary nails are being used. However, fracture site anatomy may cause distal-fragment stabilization and fixation problems and lead to malunion/nonunion. We studied the influence of angle-stable nail locking on fracture gap movement and other biomechanical parameters.


METHODS
Eight pairs of fresh human cadaver tibiae were used. The bone mineral density (BMD) was determined. All tibiae were nailed with a Synthes Expert tibial nail. Within each pair, one tibia was randomized to receive conventional locking screws; the other, angle-stable screws with sleeves. A 7-mm osteotomy was created 10 mm above the upper distal locking screw, to simulate an AO 42-A3 fracture. Biomechanical testing involved nondestructive mediolateral and anteroposterior pure bending, followed by cyclic combined axial and torsional loading to catastrophic failure. The neutral zone was determined. Fracture gap movement was monitored with 3-D motion tracking.


RESULTS
The angle-stable locked constructs had a significantly smaller mediolateral neutral zone (mean: 0.04 degree; p=0.039) and significantly smaller fracture gap angulation (p=0.043). The number of cycles to failure did not differ significantly between the locking configurations. BMD was a significant covariate affecting the number of cycles to failure (p=0.008). However, over the first 20,000 cycles, there was no significant correlation in the angle-stable construct.


CONCLUSIONS
Angle-stable locking of the Expert tibial nail was associated with a significant reduction in the mediolateral neutral zone and in fracture gap movement. Angle-stable fixation also reduced the influence of BMD over the first 20,000 cycles.
Update on the biological effects of ionizing radiation, relative dose factors and radiation hygiene.

Diagnostic imaging is an indispensable part of contemporary medical and dental practice. Over the last few decades there has been a dramatic increase in the use of ionizing radiation for diagnostic imaging. The carcinogenic effects of high-dose exposure are well known. Does diagnostic radiation rarely cause cancer? We don't know but we should act as if it does. Accordingly, dentists should select patients wisely - only make radiographs when there is patient-specific reason to believe there is a reasonable expectation the radiograph will offer unique information influencing diagnosis or treatment. Low-dose examinations should be made: intraoral imaging - use fast film or digital sensors, thyroid collars, rectangular collimation; panoramic and lateral cephalometric imaging - use digital systems or rare-earth film screen combinations; and cone beam computed tomography - use low-dose machines, restrict field size to region of interest, reduce mA and length of exposure arc as appropriate.
Model-driven Transformation-based Generation of Java Stress Tests

This paper describes a practical application of transformation-based analysis and code generation. An overview is given of an approach for automatically constructing Java stress tests whose execution exercises all ''interesting'' class initialization sequence possibilities for a given class hierarchy.
Effect of episodic and working memory impairments on semantic and cognitive procedural learning at alcohol treatment entry.

BACKGROUND
Chronic alcoholism is known to impair the functioning of episodic and working memory, which may consequently reduce the ability to learn complex novel information. Nevertheless, semantic and cognitive procedural learning have not been properly explored at alcohol treatment entry, despite its potential clinical relevance. The goal of the present study was therefore to determine whether alcoholic patients, immediately after the weaning phase, are cognitively able to acquire complex new knowledge, given their episodic and working memory deficits.


METHODS
Twenty alcoholic inpatients with episodic memory and working memory deficits at alcohol treatment entry and a control group of 20 healthy subjects underwent a protocol of semantic acquisition and cognitive procedural learning. The semantic learning task consisted of the acquisition of 10 novel concepts, while subjects were administered the Tower of Toronto task to measure cognitive procedural learning.


RESULTS
Analyses showed that although alcoholic subjects were able to acquire the category and features of the semantic concepts, albeit slowly, they presented impaired label learning. In the control group, executive functions and episodic memory predicted semantic learning in the first and second halves of the protocol, respectively. In addition to the cognitive processes involved in the learning strategies invoked by controls, alcoholic subjects seem to attempt to compensate for their impaired cognitive functions, invoking capacities of short-term passive storage. Regarding cognitive procedural learning, although the patients eventually achieved the same results as the controls, they failed to automate the procedure. Contrary to the control group, the alcoholic groups' learning performance was predicted by controlled cognitive functions throughout the protocol.


CONCLUSION
At alcohol treatment entry, alcoholic patients with neuropsychological deficits have difficulty acquiring novel semantic and cognitive procedural knowledge. Compared with controls, they seem to use more costly learning strategies, which are nonetheless less efficient. These learning disabilities need to be considered when treatment requiring the acquisition of complex novel information is envisaged.
Management of Type 2 Diabetes Mellitus Among Patients Attending a Primary Health Care Setting in Qatar: A Study on Medication Use Pattern and Clinical Outcomes.

burdensome and expensive chronic diseases worldwide.  A strategy of therapy management is required by using resources efficiently and effectively to optimize the escalating medical costs associated with the management of DM.  There are several studies related to DM that have been conducted in Qatar, but none looked at the impact of insulin-containing regimens vs. oral anti-diabetic therapy on economic and clinical outcomes of type 2 diabetes mellitus management in a primary health care setting. Background Management of Type 2 Diabetes Mellitus among Patients Attending a Primary Health Care Setting in Qatar: A Study on Medication Use Pattern and Clinical Outcomes