nils-herrmann/clean_scirepeval huggingface dataset:
Pharmacogenetics of response to methylphenidate in adult patients with Attention-Deficit/Hyperactivity Disorder (ADHD): a systematic review.

Methylphenidate (MPH) is a first line option in the psychopharmacologic treatment of adults with Attention-Deficit/Hyperactivity Disorder (ADHD). However, there is a considerable proportion of adult patients who do not respond to treatment with MPH or discontinue drug therapy. Since effects of genetic variants in the response to MPH treatment might explain these negative outcomes, we conducted an electronic systematic search of MEDLINE-indexed literature looking for articles containing information about pharmacogenetics of ADHD in adults published until January, 2012. The keywords used were 'ADHD', 'Attention-Deficit/Hyperactivity Disorder' and 'gene' in combination with methylphenidate, amphetamine or atomoxetine. Only 5 pharmacogenetic studies on adult ADHD met inclusion criteria. The results evidenced that most findings obtained so far are negative, and all studies focused on MPH response. There is only one positive result, for a polymorphism at the dopamine transporter gene (DAT1) gene. The current state of the art in adult ADHD implies that pharmacogenetic tests are far from routine clinical practice. However, the integration of these studies with neuroimaging and neuropsychological tests may help to understand mechanisms of drug action and the pathophysiology of ADHD.
A Fine-to-Coarse Convolutional Neural Network for 3D Human Action Recognition

This paper presents a new framework for human action recognition from a 3D skeleton sequence. Previous studies do not fully utilize the temporal relationships between video segments in a human action. Some studies successfully used very deep Convolutional Neural Network (CNN) models but often suffer from the data insufficiency problem. In this study, we first segment a skeleton sequence into distinct temporal segments in order to exploit the correlations between them. The temporal and spatial features of a skeleton sequence are then extracted simultaneously by utilizing a fine-to-coarse (F2C) CNN architecture optimized for human skeleton sequences. We evaluate our proposed method on NTU RGB+D and SBU Kinect Interaction dataset. It achieves 79.6% and 84.6% of accuracies on NTU RGB+D with cross-object and cross-view protocol, respectively, which are almost identical with the state-of-the-art performance. In addition, our method significantly improves the accuracy of the actions in two-person interactions.
IN-SILICO INTERACTION STUDIES ON INHIBITORY ACTION OF TETRANORTRITERPENOIDS ON ACTIN

In-silico interaction studies on forty two tetranortriterpenoids, which include four classes of compounds azadiratchins, salannins, nimbins and intact limonoids, with actin have been carried out using Autodock Vina and Surflex Dock. The docking scores and predicted hydrogen bonds along with spatial confirmation of the molecules indicate that actin could be a possible target for insect antifeedant studies, and a good correlation has been obtained between the percentage feeding index (PFI) and the binding energy of these molecules. The enhancement of the activity in the photo products and its reduction in microwave products observed in in-vivo studies are well brought out by this study. The study reveals Arg 183 in actin to be the most favoured residue for binding in most compounds whereas Tyr 69 is favoured additionally for salannin and nimbin type of compounds. In the case of limonoids Gln 59 seems to have hydrogen bonding interactions with most of the compounds. The present study reveals that the fit for PFI vs. binding energy is better for individual classes of compounds and can be attributed to the binding of ligand with different residues. This comprehensive in-silico analysis of interaction between actin as a receptor and tetranortriterpenoids may help in the understanding of the mode of action of bioinsecticides, and designing better lead molecules.
Enabling Sparse Winograd Convolution by Native Pruning

Sparse methods and the use of Winograd convolutions are two orthogonal approaches, each of which significantly accelerates convolution computations in modern CNNs. Sparse Winograd merges these two and thus has the potential to offer a combined performance benefit. Nevertheless, training convolution layers so that the resulting Winograd kernels are sparse has not hitherto been very successful. By introducing a Winograd layer in place of a standard convolution layer, we can learn and prune Winograd coefficients “natively” and obtain sparsity level beyond 90% with only 0.1% accuracy loss with AlexNet on ImageNet dataset. Furthermore, we present a sparse Winograd convolution algorithm and implementation that exploits the sparsity, achieving up to 31.7 effective TFLOP/s in 32-bit precision on a latest Intel Xeon CPU, which corresponds to a 5.4× speedup over a state-of-the-art dense convolution implementation.
Improved Localization Accuracy by LocNet for Faster R-CNN Based Text Detection

Although Faster R-CNN based approaches have achieved promising results for text detection, their localization accuracy is not satisfactory in certain cases. In this paper, we propose to use a LocNet to improve the localization accuracy of a Faster R-CNN based text detector. Given a proposal generated by region proposal network (RPN), instead of predicting directly the bounding box coordinates of the concerned text instance, the proposal is enlarged to create a search region so that conditional probabilities to each row and column of this search region can be assigned, which are then used to infer accurately the concerned bounding box. Experiments demonstrate that the proposed approach boosts the localization accuracy for Faster R-CNN based text detection significantly. Consequently, our new text detector has achieved superior performance on ICDAR-2011, ICDAR-2013 and MULTILIGUL text detection benchmark tasks.
Determining the cause of vulvovaginal symptoms.

Both patients and clinicians may incorrectly diagnose vulvovaginitis symptoms. Patients often self-treat with over-the-counter antifungals or home remedies, although they are unable to distinguish among the possible causes of their symptoms. Telephone triage practices and time constraints on office visits may also hamper effective diagnosis. This review is a guide to distinguish potential causes of vulvovaginal symptoms. The first section describes both common and uncommon conditions associated with vulvovaginitis, including infectious vulvovaginitis, allergic contact dermatitis, systemic dermatoses, rare autoimmune diseases, and neuropathic vulvar pain syndromes. The focus is on the clinical presentation, specifically 1) the absence or presence and characteristics of vaginal discharge; 2) the nature of sensory symptoms (itch and/or pain, localized or generalized, provoked, intermittent, or chronic); and 3) the absence or presence of mucocutaneous changes, including the types of lesions observed and the affected tissue. Additionally, this review describes how such features of the clinical presentation can help identify various causes of vulvovaginitis.
Antibody–drug conjugates as novel anti-cancer chemotherapeutics

Over the past couple of decades, antibody-drug conjugates (ADCs) have revolutionized the field of cancer chemotherapy. Unlike conventional treatments that damage healthy tissues upon dose escalation, ADCs utilize monoclonal antibodies (mAbs) to specifically bind tumour-associated target antigens and deliver a highly potent cytotoxic agent. The synergistic combination of mAbs conjugated to small-molecule chemotherapeutics, via a stable linker, has given rise to an extremely efficacious class of anti-cancer drugs with an already large and rapidly growing clinical pipeline. The primary objective of this paper is to review current knowledge and latest developments in the field of ADCs. Upon intravenous administration, ADCs bind to their target antigens and are internalized through receptor-mediated endocytosis. This facilitates the subsequent release of the cytotoxin, which eventually leads to apoptotic cell death of the cancer cell. The three components of ADCs (mAb, linker and cytotoxin) affect the efficacy and toxicity of the conjugate. Optimizing each one, while enhancing the functionality of the ADC as a whole, has been one of the major considerations of ADC design and development. In addition to these, the choice of clinically relevant targets and the position and number of linkages have also been the key determinants of ADC efficacy. The only marketed ADCs, brentuximab vedotin and trastuzumab emtansine (T-DM1), have demonstrated their use against both haematological and solid malignancies respectively. The success of future ADCs relies on improving target selection, increasing cytotoxin potency, developing innovative linkers and overcoming drug resistance. As more research is conducted to tackle these issues, ADCs are likely to become part of the future of targeted cancer therapeutics.
Asymmetry of Inframammary Folds in Patients Undergoing Augmentation Mammaplasty.

Variation in the anatomical position of the inframammary fold (IMF) in women remains poorly studied.



The purpose of this study was to evaluate the incidence of asymmetry between IMF locations on the chest wall of women undergoing breast augmentation and to determine breast measurements associated with IMF asymmetry.



Three-dimensional imaging analysis of the breasts was performed in 111 women with micromastia, using the Vectra Imaging System(TM). The following measurements were recorded: vertical distance between right and left IMF (inter-fold distance), vertical distance between nipples (inter-nipple distance), and difference between projection of right and left breasts in anterior-posterior direction.



Asymmetry between the right and left IMF positions was found in the majority of patients (95.4%), with symmetry only found in 5 patients (4.6%). In the majority of patients (60.3%), the right IMF was located inferior to the left IMF with median inter-fold distance 0.4 cm (range, 0.1, 2.1 cm). In 39 patients (35.1%), the left IMF was located inferior to the right with median inter-fold distance 0.4 cm (range, 0.1, 1.7 cm). There was strong correlation between the degree of asymmetry of IMF and asymmetry of nipple areola complex (NAC) positions (r = 0.687, P < .01).



The majority of women with micromastia demonstrate asymmetry of the IMF, which correlates with asymmetry of NAC location. The authors propose a classification system based on most commonly observed IMF locations as types I (right IMF inferior to left), type II (left IMF inferior to right) and type III (both IMF located on the same level).
The immune system and the gut microbiota: friends or foes?

The mammalian intestine is home to a complex community of trillions of bacteria that are engaged in a dynamic interaction with the host immune system. Determining the principles that govern host–microbiota relationships is the focus of intense research. Here, we describe how the intestinal microbiota is able to influence the balance between pro-inflammatory and regulatory responses and shape the host's immune system. We suggest that improving our understanding of the intestinal microbiota has therapeutic implications, not only for intestinal immunopathologies but also for systemic immune diseases.
A Deep Convolutional Neural Network for Lung Cancer Diagnostic

In this paper, we examine the strength of deep learning technique for diagnosing lung cancer on medical image analysis problem. Convolutional neural networks (CNNs) models become popular among the pattern recognition and computer vision research area because of their promising outcome on generating high-level image representations. We propose a new deep learning architecture for learning high-level image representation to achieve high classification accuracy with low variance in medical image binary classification tasks. We aim to learn discriminant compact features at beginning of our deep convolutional neural network. We evaluate our model on Kaggle Data Science Bowl 2017 (KDSB17) data set, and compare it with some related works proposed in the Kaggle competition.
Robot control system for window cleaning

A two-stage process is performed by human operator for cleaning windows. The first being the application of cleaning fluid, which is usually achieved by using a wetted applicator. The aim of this task being to cover the whole window area in the shortest possible time. This depends on two parameters: the size of the applicator and the path which the applicator travels without significantly overlapping previously wetted area. The second is the removal of cleaning fluid by a squeegee blade without spillage on to other areas of the facade or previously cleaned areas of glass. This is particularly difficult for example if the window is located on the roof of a building and cleaning is performed from inside by the human window cleaner.
An Overview of Non-contact Photoplethysmography

—Prior to the successful use of non-contact photoplethysmography, several engineering issues regarding this monitoring technique must be considered. These issues include ambient light and motion artefacts, the wide dynamic signal range and the effect of direct light source coupling. The latter issue was investigated and preliminary results show that direct coupling can cause attenuation of the detected PPG signal. It is shown that a physical offset can be introduced between the light source and the detector in order to reduce this effect.
The use of e-learning course management systems to support learning strategies and to improve self-regulated learning

The adoption of Course Management Systems (CMSs) for web-based instruction continues to increase in today’s higher education. A CMS is a software program or integrated platform that contains a series of web-based tools to support a number of activities and course management procedures (Severson, 2004). Examples of Course Management Systems are Blackboard, WebCT, eCollege, Moodle, Desire2Learn, Angel, etc. An argument for the adoption of elearning environments using CMSs is the flexibility of such environments when reaching out to potential learners in remote areas where brick and mortar institutions are non-existent. It is also believed that e-learning environments can have potential added learning benefits and can improve students’ and educators’ self-regulation skills, in particular their metacognitive skills. In spite of this potential to improve learning by means of using a CMS for the delivery of e-learning, the features and functionalities that have been built into these systems are often underutilized. As a consequence, the created learning environments in CMSs do not adequately scaffold learners to improve their selfregulation skills. In order to support the improvement of both the learners’ subject matter knowledge and learning strategy application, the e-learning environments within CMSs should be designed to address learners’ diversity in terms of learning styles, prior knowledge, culture, and self-regulation skills. Self-regulative learners are learners who can demonstrate ‘personal initiative, perseverance and adaptive skill in pursuing learning’ (Zimmerman, 2002). Self-regulation requires adequate monitoring strategies and metacognitive skills. The created e-learning environments should encourage the application of learners’ metacognitive skills by prompting learners to plan, attend to relevant content, and monitor and evaluate their learning. This position paper sets out to inform policy makers, educators, researchers, and others of the importance of a metacognitive e-learning approach when designing instruction using Course Management Systems. Such a metacognitive approach will improve the utilization of CMSs to support learners on their path to self-regulation. We argue that a powerful CMS incorporates features and functionalities that can provide extensive scaffolding to learners and support them in becoming self-regulated learners. Finally, we believe that extensive training and support is essential if educators are expected to develop and implement CMSs as powerful learning tools.
Diagnosis of Oral Hairy Leukoplakia: The Importance of EBV In Situ Hybridization

Oral hairy leukoplakia (OHL) is caused by the Epstein-Barr virus (EBV), which has been related to HIV infection. In situ hybridization (ISH) is the gold-standard diagnosis of OHL, but some authors believe in the possibility of performing the diagnosis based on clinical basis. The aim of this study is diagnose incipient lesions of OHL by EBV ISH of HIV-infected patients and the possible correlations with clinical characteristics of the patients. Ninety-four patients were examined and those presenting with clinical lesions compatible to OHL were submitted to biopsy prior to EBV ISH. Twenty-eight patients had lesions clinically compatible to the diagnosis of OHL, but only 20 lesions were confirmed by EBV ISH. The patients with OHL had a mean age of 41.9 years and were HIV-infected for 11.2 years, on average, including CD4 count of 504.7 cells/mm3 and log10 viral load = 1.1. Among the quantitative variables, there was a statistically significant correlation with age only (P = 0.030). In conclusion, the presence of OHL in patients with HIV/AIDS results in changes in the epidemiological characteristics of the disease, and this fact allied with subtle clinical-morphological features makes clinical diagnosis very difficult. Therefore, EBV ISH is important for a definitive diagnosis of OHL.
Large-Scale Detection of DOM-Based XSS Based on Publisher and Subscriber Model

Cross-site scripting (also referred to as XSS) is a vulnerability that allows an attacker to send malicious code (usually in the form of JavaScript) to another user. XSS is one of the top 10 vulnerabilities on Web application. While a traditional cross-site scripting vulnerability exploits server-side codes, DOM-based XSS is a type of vulnerability which affects the script code being executed in the clients browser. DOM-based XSS vulnerabilities are much harder to be detected than classic XSS vulnerabilities because they reside on the script codes from Web sites. An automated scanner needs to be able to execute the script code without errors and to monitor the execution of this code to detect such vulnerabilities. In this paper, we introduce a distributed scanning tool for crawling modern Web applications on a large scale and detecting, validating DOMbased XSS vulnerabilities. Very few Web vulnerability scanners can really accomplish this.
Factors influencing food choices of adolescents: findings from focus-group discussions with adolescents.

To assess adolescents' perceptions about factors influencing their food choices and eating behaviors.



Data were collected in focus-group discussions.



The study population included 141 adolescents in 7th and 10th grade from 2 urban schools in St Paul, Minn, who participated in 21 focus groups.



Data were analyzed using qualitative research methodology, specifically, the constant comparative method.



Factors perceived as influencing food choices included hunger and food cravings, appeal of food, time considerations of adolescents and parents, convenience of food, food availability, parental influence on eating behaviors (including the culture or religion of the family), benefits of foods (including health), situation-specific factors, mood, body image, habit, cost, media, and vegetarian beliefs. Major barriers to eating more fruits, vegetables, and dairy products and eating fewer high-fat foods included a lack of sense of urgency about personal health in relation to other concerns, and taste preferences for other foods. Suggestions for helping adolescents eat a more healthful diet include making healthful food taste and look better, limiting the availability of unhealthful options, making healthful food more available and convenient, teaching children good eating habits at an early age, and changing social norms to make it "cool" to eat healthfully.



The findings suggest that if programs to improve adolescent nutrition are to be effective, they need to address a broad range of factors, in particular environmental factors (e.g., the increased availability and promotion of appealing, convenient foods within homes schools, and restaurants).
Technologies for 3D wafer level heterogeneous integration

3D integration is a fast growing field that encompasses different types of technologies. The paper addresses one of the most promising technology which uses Through Silicon Vias (TSV) for interconnecting stacked devices on wafer level to perform high density interconnects with a good electrical performance at the smallest form factor for 3D architectures. Fraunhofer IZM has developed a post front-end 3D integration process which allows stacking of functional and tested FE-devices e.g. sensors, ASICs on wafer level as well as a technology portfolio for passive silicon interposer with redistribution layers and TSV.
Monostotic Fibrous Dysplasia : A Case Report

Fibrous dysplasia (FD) is a benign fibro-osseous bone disease of unknown etiology and uncertain pathogenesis. When bone maturation is completed, indicating the occurence of stabilization is a strong evidence of mechanism. The lesion frequently affects the craniofacial skeleton. The maxilla is affected twice comparing mandible and occurs more frequently in the posterior area. In this case, a 16 year-old female patient is presented who was diagnosed as having maxillofacial fibrous dysplasia.  Gözde Canıtezer, Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Ondokuz Mayıs University, 55139 Kurupelit, Samsun, Turkey, Tel: +90 362 3121919-3012, +90 505 8659063; ; E-mail: gozde.canitezer@omu.edu.tr Received October 02, 2013;  2013;  Canıtezer G, Gunduz K, Ozden B, Kose HI (2013) Monostotic Fibrous Dysplasia: A  1667.
Measuring Latency in Virtual Environments

Latency of interactive computer systems is a product of the processing, transport and synchronisation delays inherent to the components that create them. In a virtual environment (VE) system, latency is known to be detrimental to a user's sense of immersion, physical performance and comfort level. Accurately measuring the latency of a VE system for study or optimisation, is not straightforward. A number of authors have developed techniques for characterising latency, which have become progressively more accessible and easier to use. In this paper, we characterise these techniques. We describe a simple mechanical simulator designed to simulate a VE with various amounts of latency that can be finely controlled (to within 3ms). We develop a new latency measurement technique called Automated Frame Counting to assist in assessing latency using high speed video (to within 1ms). We use the mechanical simulator to measure the accuracy of Steed's and Di Luca's measurement techniques, proposing improvements where they may be made. We use the methods to measure latency of a number of interactive systems that may be of interest to the VE engineer, with a significant level of confidence. All techniques were found to be highly capable however Steed's Method is both accurate and easy to use without requiring specialised hardware.