nils-herrmann/clean_scirepeval huggingface dataset:
The academic achievement of African American students during early adolescence: an examination of multiple risk, promotive, and protective factors.

This study examined the effects of multiple risk, promotive, and protective factors on three achievement-related measures (i.e., grade point average, number of absences, and math achievement test scores) for African American 7th-grade students (n = 837). There were 3 main findings. First, adolescents had lower grade point averages, more absences, and lower achievement test scores as their exposure to risk factors increased. Second, different promotive and protective factors emerged as significant contributors depending on the nature of the achievement-related outcome that was being assessed. Third, protective factors were identified whose effects were magnified in the presence of multiple risks. Results were discussed in light of the developmental tasks facing adolescents and the contexts in which youth exposed to multiple risks and their families live.
Knee Injury and Osteoarthritis Outcome Score (KOOS)--development of a self-administered outcome measure.

There is broad consensus that good outcome measures are needed to distinguish interventions that are effective from those that are not. This task requires standardized, patient-centered measures that can be administered at a low cost. We developed a questionnaire to assess short- and long-term patient-relevant outcomes following knee injury, based on the WOMAC Osteoarthritis Index, a literature review, an expert panel, and a pilot study. The Knee injury and Osteoarthritis Outcome Score (KOOS) is self-administered and assesses five outcomes: pain, symptoms, activities of daily living, sport and recreation function, and knee-related quality of life. In this clinical study, the KOOS proved reliable, responsive to surgery and physical therapy, and valid for patients undergoing anterior cruciate ligament reconstruction. The KOOS meets basic criteria of outcome measures and can be used to evaluate the course of knee injury and treatment outcome.
Change Detection from a Street Image Pair using CNN Features and Superpixel Segmentation

This paper proposes a method for detecting changes of a scene using a pair of its vehicular, omnidirectional images. Previous approaches to the problem require the use of a 3D scene model and/or pixel-level registration between different time images. They are also computationally costly for estimating city-scale changes. We propose a novel change detection method that uses features of convolutional neural network (CNN) in combination with superpixel segmentation. Comparison of CNN features gives a lowresolution map of scene changes that is robust to illumination changes and viewpoint differences. Superpixel segmentation of the scene images is integrated with this lowresolution map to estimate precise segmentation boundaries of the changes. Our motivation is to develop a method for detecting city-scale changes, which can be used for visualization of damages of a natural disaster and subsequent recovery processes as well as for the purpose of maintaining/updating the 3D model of a city. We have created a dataset named Panoramic Change Detection Dataset, which will be made publicly available for evaluating the performances of change detection methods in these scenarios. The experimental results using the dataset show the effectiveness of our approach.
Balance Training Programs in Athletes – a Systematic Review

It has become almost routine practice to incorporate balance exercises into training programs for athletes from different sports. However, the type of training that is most efficient remains unclear, as well as the frequency, intensity and duration of the exercise that would be most beneficial have not yet been determined. The following review is based on papers that were found through computerized searches of PubMed and SportDiscus from 2000 to 2016. Articles related to balance training, testing, and injury prevention in young healthy athletes were considered. Based on a Boolean search strategy the independent researchers performed a literature review. A total of 2395 articles were evaluated, yet only 50 studies met the inclusion criteria. In most of the reviewed articles, balance training has proven to be an effective tool for the improvement of postural control. It is difficult to establish one model of training that would be appropriate for each sport discipline, including its characteristics and demands. The main aim of this review was to identify a training protocol based on most commonly used interventions that led to improvements in balance. Our choice was specifically established on the assessment of the effects of balance training on postural control and injury prevention as well as balance training methods. The analyses including papers in which training protocols demonstrated positive effects on balance performance suggest that an efficient training protocol should last for 8 weeks, with a frequency of two training sessions per week, and a single training session of 45 min. This standard was established based on 36 reviewed studies.
Multilevel SOT-MRAM cell with a novel sensing scheme for high-density memory applications

This paper presents a multilevel spin-orbit torque magnetic random access memory (SOT-MRAM). The conventional SOT-MRAMs enables a reliable and energy efficient write operation. However, these cells require two access transistors per cell, hence the efficiency of the SOT-MRAMs can be questioned in high-density memory application. To deal with this obstacle, we propose a multilevel cell which stores two bits per memory cell. In addition, we propose a novel sensing scheme to read out the stored data in the multilevel SOT-MRAM cell. Our simulation results show that the proposed cell can achieve 3X more energy efficient write operation in comparison with the conventional STT-MRAMs. In addition, the proposed cell store two bits without any area penalty in comparison to the conventional one bit SOT-MRAM cells.
THE BLACK-SCHOLES MODEL AND EXTENSIONS

This paper will derive the Black-Scholes pricing model of a European option by calculating the expected value of the option. We will assume that the stock price is log-normally distributed and that the universe is riskneutral. Then, using Ito’s Lemma, we will justify the use of the risk-neutral rate in these initial calculations. Finally, we will prove put-call parity in order to price European put options, and extend the concepts of the Black-Scholes formula to value an option with pricing barriers.
Unraveling the Mechanisms of Manual Therapy: Modeling an Approach.

Synopsis Manual therapy interventions are popular among individual health care providers and their patients; however, systematic reviews do not strongly support their effectiveness. Small treatment effect sizes of manual therapy interventions may result from a "one-size-fits-all" approach to treatment. Mechanistic-based treatment approaches to manual therapy offer an intriguing alternative for identifying patients likely to respond to manual therapy. However, the current lack of knowledge of the mechanisms through which manual therapy interventions inhibit pain limits such an approach. The nature of manual therapy interventions further confounds such an approach, as the related mechanisms are likely a complex interaction of factors related to the patient, the provider, and the environment in which the intervention occurs. Therefore, a model to guide both study design and the interpretation of findings is necessary. We have previously proposed a model suggesting that the mechanical force from a manual therapy intervention results in systemic neurophysiological responses leading to pain inhibition. In this clinical commentary, we provide a narrative appraisal of the model and recommendations to advance the study of manual therapy mechanisms.
Endoscopic correction of frontal bossing.

Frontal bossing is a displeasing prominence of the supraorbital area. Aesthetic correction has been described as an open surgical technique. This report introduces an endoscopic approach to correction.



A retrospective review was performed on all patients who underwent endoscopic repair of frontal bossing from 2002 to 2009. Demographics, intraoperative and postoperative course, and outcome variables were collected. Standardized preoperative and postoperative photographs were used for analysis. Aesthetic improvement of the forehead was assessed with a four-point scale (1 = no improvement at all, 4 = significant improvement) by six randomly selected observers. Preoperative facial imaging (lateral skull radiography or computed tomography) was obtained on all patients to assess the thickness of the anterior wall of the frontal sinus.



Ten patients met the study inclusion criteria. Overall, the observers assessed the degree of frontal bossing correction as moderate improvement (2.67 on a four-point scale survey). All endoscopic frontal bossing corrections were performed on an outpatient basis by the senior author (B.G.). No patient was admitted to the hospital for postoperative complications. No complications (such as alopecia, hematoma, contour deformities, or penetration into the frontal sinus) were seen. The limiting factor in achieving optimal outcomes was inadequate thickness of the anterior wall of the frontal sinus. All patients had various concurrent facial rejuvenation procedures.



Endoscopic correction of frontal bossing is an effective and safe surgical technique in forehead aesthetics. This technique is ideal for patients with a mild frontal bossing deformity who have an adequately thick anterior frontal sinus wall.
Biomimetic artificial organelles with in vitro and in vivo activity triggered by reduction in microenvironment

Despite tremendous efforts to develop stimuli-responsive enzyme delivery systems, their efficacy has been mostly limited to in vitro applications. Here we introduce, by using an approach of combining biomolecules with artificial compartments, a biomimetic strategy to create artificial organelles (AOs) as cellular implants, with endogenous stimuli-triggered enzymatic activity. AOs are produced by inserting protein gates in the membrane of polymersomes containing horseradish peroxidase enzymes selected as a model for natures own enzymes involved in the redox homoeostasis. The inserted protein gates are engineered by attaching molecular caps to genetically modified channel porins in order to induce redox-responsive control of the molecular flow through the membrane. AOs preserve their structure and are activated by intracellular glutathione levels in vitro. Importantly, our biomimetic AOs are functional in vivo in zebrafish embryos, which demonstrates the feasibility of using AOs as cellular implants in living organisms. This opens new perspectives for patient-oriented protein therapy. The efficacy of stimuli-responsive enzyme delivery systems is usually limited to in vitro applications. Here the authors form artificial organelles by inserting stimuli-responsive protein gates in membranes of polymersomes loaded with enzymes and obtain a triggered functionality both in vitro and in vivo.
StoryGAN: A Sequential Conditional GAN for Story Visualization

In this work we propose a new task called Story Visualization. Given a multi-sentence paragraph, the story is visualized by generating a sequence of images, one for each sentence. In contrast to video generation, story visualization focuses less on the continuity in generated images (frames), but more on the global consistency across dynamic scenes and characters – a challenge that has not been addressed by any single-image or video generation methods. Therefore, we propose a new story-to-image-sequence generation model, StoryGAN, based on the sequential conditional GAN framework. Our model is unique in that it consists of a deep Context Encoder that dynamically tracks the story flow, and two discriminators at the story and image levels, respectively, to enhance the image quality and the consistency of the generated sequences. To evaluate the model, we modified existing datasets to create the CLEVR-SV and PororoSV datasets. Empirically, StoryGAN outperformed stateof-the-art models in image quality, contextual consistency metrics, and human evaluation.
Towards a fully automated 3D printability checker

3D printing has become one of the most popular evolutionary techniques with diverse application, even as normal people's hobby. As printing target, enormous 3D virtual models from game industry and virtual reality flood the internet, shared in various online forums, such as thingiverse. But which of them can really be printed? In this paper we propose the 3D Printability Checker, which can be used to automatically answer this non-trivial question. One of the major novelties of this paper is the process of dependable software engineering we use to build this Printability Checker. Firstly, we prove that this question is decidable with a given 3D object and a list of printer profiles. Secondly, we design and implement such a checker. Finally, we show our experimental results and use them further for a machine learning approach to improve our system in an automatic way. The generic framework provides a useful basis of automatic self-improvement of the software by combining current techniques in the area of formal method, geometry modelling and machine learning.
Study on Two-Dimensional Sparse MIMO UWB Arrays for High Resolution Near-Field Imaging

A novel generic topology for two-dimensional (2-D) sparse multiple-input-multiple-output (MIMO) ultrawideband (UWB) arrays is suggested. Based on the proposed topology, a 2-D MIMO UWB array for high-resolution short-range imaging is developed. The focusing properties of this array are studied both theoretically and experimentally and are shown to be superior to those of arrays with a similar number of antennas and based on known topologies such as Mills Cross, rectangular, and spiral configurations. Decisive impact of a large operational bandwidth and short focusing distance on MIMO array performance is shown. Imaging capabilities of the proposed array are experimentally demonstrated for distributed targets.
Theoretical Bases for Using Virtual Reality in Education

This article elaborates on how the technical capabilities of virtual reality support the constructivist learning principles. It introduces VRID, a model for instructional design and development that offers explicit guidance on how to produce an educational virtual environment. The define phase of VRID consists of three main tasks: forming a participatory team, analyzing the appropriateness of employing virtual reality technology to tackle a known learning problem, and performing a feasibility study. The design phase of VRID comprises the macro-strategy that provides guidance on the selection, sequencing, and organization of the subject-matter topics that are to be presented, and the micro-strategy that provides strategies for effective presentation of the learning contents. The development phase includes all the necessary tasks to implement the outcome of the design phase. Among the tasks for this development phase include determining the developmental platform, developing the various components of the educational virtual environment, performing specialist evaluation as well as conducting oneto-one learner evaluation. Conducting a small group evaluation and performing an effectiveness evaluation study are the two important tasks of the evaluation phase.
A probabilistic justification for using tf×idf term weighting in information retrieval

This paper presents a new probabilistic model of information retrieval. The most important modeling assumption made is that documents and queries are defined by an ordered sequence of single terms. This assumption is not made in well-known existing models of information retrieval, but is essential in the field of statistical natural language processing. Advances already made in statistical natural language processing will be used in this paper to formulate a probabilistic justification for using tf×idf term weighting. The paper shows that the new probabilistic interpretation of tf×idf term weighting might lead to better understanding of statistical ranking mechanisms, for example by explaining how they relate to coordination level ranking. A pilot experiment on the TREC collection shows that the linguistically motivated weighting algorithm outperforms the popular BM25 weighting algorithm.
Child maltreatment and psychological symptoms in a Portuguese adult community sample: the harmful effects of emotional abuse

Child maltreatment (CM) is associated with poor long-term health outcomes. However, knowledge about CM prevalence and related consequences is scarce among adults in South European countries. We examined the self-reported prevalence of five different forms of CM in a community sample of 1,200 Portuguese adults; we compared the results with similar samples from three other countries, using the same instrument. We also explored the relationship between CM and psychological symptoms. Cross-sectional data using the Childhood Trauma Questionnaire-Short Form and the Brief Symptom Inventory were analyzed. Moderate or severe CM exposure was self-reported by 14.7 % of the sample, and 67 % was exposed to more than one form of CM. Emotional neglect was the most endorsed experience, with women reporting greater emotional abuse and men reporting larger physical abuse. Physical and sexual abuse was less self-reported by Portuguese than by American or German subjects. CM exposure predicted 12.8 % of the psychological distress. Emotional abuse was the strongest predictor for psychological symptoms, namely for paranoid ideation, depression, and interpersonal sensitivity. Emotional abuse overlapped with the exposure to all other CM forms, and interacted with physical abuse, physical neglect, and emotional neglect to predict psychological distress. Low exposure to emotional abuse was directly associated with the effects of physical abuse, physical neglect, and emotional neglect to predict adult psychological distress. Verbal abuse experiences were frequently reported and had the highest correlations with adult psychological distress. Our results underline the potential hurtful effects of child emotional abuse among Portuguese adults in the community. They also highlight the need to improve prevention and intervention actions to reduce exposure and consequences of CM, particularly emotional abuse.
Multimodal Vigilance Estimation with Adversarial Domain Adaptation Networks

Robust vigilance estimation during driving is very crucial in preventing traffic accidents. Many approaches have been proposed for vigilance estimation. However, most of the approaches require collecting subject-specific labeled data for calibration which is high-cost for real-world applications. To solve this problem, domain adaptation methods can be used to align distributions of source subject features (source domain) and new subject features (target domain). By reusing existing data from other subjects, no labeled data of new subjects is required to train models. In this paper, our goal is to apply adversarial domain adaptation networks to cross-subject vigilance estimation. We adopt two kinds of recently proposed adversarial domain adaptation networks and compare their performance with those of several traditional domain adaptation methods and the baseline without domain adaptation. A publicly available dataset, SEED-VIG, is used to evaluate the methods. The dataset includes electroencephalography (EEG) and electrooculography (EOG) signals, as well as the corresponding vigilance level annotations during simulated driving. Compared with the baseline, both adversarial domain adaptation networks achieve improvements over 10% in terms of Pearson’s correlation coefficient. In addition, both methods considerably outperform the traditional domain adaptation methods.
Periprosthetic humeral fractures during shoulder arthroplasty.

Currently, there is little information available on the treatment and outcome of intraoperative periprosthetic humeral fractures that occur during shoulder arthroplasty. The purpose of this study was to report on the incidence, treatment, and outcome of, as well as the risk factors for, intraoperative periprosthetic humeral fractures.



Between 1980 and 2002, forty-five intraoperative periprosthetic humeral fractures occurred during shoulder arthroplasty at our institution. Twenty-eight fractures occurred during primary total shoulder arthroplasty, three occurred during primary hemiarthroplasty, and fourteen occurred during revision arthroplasty. Nineteen fractures involved the greater tuberosity, sixteen involved the humeral shaft, six involved the metaphysis, three involved the greater tuberosity and the humeral shaft, and one involved both the greater and lesser tuberosities. All patients were followed for a minimum of two years. At the time of the latest follow-up, outcomes were assessed, radiographs were examined, and relative risks were calculated.



Over the twenty-two-year study period, the rate of intraoperative humeral fractures at our institution was 1.5%. All fractures healed at a mean of seventeen weeks. In the primary arthroplasty group (thirty-one patients), range of motion and pain scores improved significantly (p < 0.05) at the time of follow-up. In the revision arthroplasty group (fourteen patients), range of motion remained unchanged whereas pain scores improved significantly (p < 0.005). Transient nerve injuries occurred in six patients. Four fractures displaced postoperatively and were then treated nonoperatively; all four healed. Significant relative risks for intraoperative fracture were female sex, revision surgery, and press-fit implants (p < 0.05).



The data from the present study suggest that although intraoperative humeral fractures are associated with a high rate of healing, there was a substantial rate of associated complications, including transient nerve injuries and fracture displacement. Significant risk factors for intraoperative fractures include female sex, revision surgery, and press-fit humeral implants.
Forebrain engraftment by human glial progenitor cells enhances synaptic plasticity and learning in adult mice.

Human astrocytes are larger and more complex than those of infraprimate mammals, suggesting that their role in neural processing has expanded with evolution. To assess the cell-autonomous and species-selective properties of human glia, we engrafted human glial progenitor cells (GPCs) into neonatal immunodeficient mice. Upon maturation, the recipient brains exhibited large numbers and high proportions of both human glial progenitors and astrocytes. The engrafted human glia were gap-junction-coupled to host astroglia, yet retained the size and pleomorphism of hominid astroglia, and propagated Ca2+ signals 3-fold faster than their hosts. Long-term potentiation (LTP) was sharply enhanced in the human glial chimeric mice, as was their learning, as assessed by Barnes maze navigation, object-location memory, and both contextual and tone fear conditioning. Mice allografted with murine GPCs showed no enhancement of either LTP or learning. These findings indicate that human glia differentially enhance both activity-dependent plasticity and learning in mice.