nils-herrmann/clean_scirepeval huggingface dataset:
Trunk muscle activity during lumbar stabilization exercises on both a stable and unstable surface.

Controlled laboratory study.



To clarify whether differences in surface stability influence trunk muscle activity.



Lumbar stabilization exercises on unstable surfaces are performed widely. One perceived advantage in performing stabilization exercises on unstable surfaces is the potential for increased muscular demand. However, there is little evidence in the literature to help establish whether this assumption is correct.



Nine healthy male subjects performed lumbar stabilization exercises. Pairs of intramuscular fine-wire or surface electrodes were used to record the electromyographic signal amplitude of the rectus abdominis, the external obliques, the transversus abdominis, the erector spinae, and lumbar multifidus. Five exercises were performed on the floor and on an unstable surface: elbow-toe, hand-knee, curl-up, side bridge, and back bridge. The EMG data were normalized as the percentage of the maximum voluntary contraction, and data between doing each exercise on the stable versus unstable surface were compared using a Wilcoxon signed-rank test.



With the elbow-toe exercise, the activity level for all muscles was enhanced when performed on the unstable surface. When performing the hand-knee and side bridge exercises, activity level of the more global muscles was enhanced when performed on an unstable surface. Performing the curl-up exercise on an unstable surface, increased the activity of the external obliques but reduced transversus abdominis activation.



This study indicates that lumbar stabilization exercises on an unstable surface enhanced the activities of trunk muscles, except for the back bridge exercise.
Using Personality Information in Collaborative Filtering for New Users

Recommender systems help users more easily and quickly find products that they truly prefer amidst the enormous volume of information available to them. Collaborative filtering (CF) methods, making recommendations based on opinions from “most similar” users, have been widely adopted in various applications. In spite of the overall success of CF systems, they encounter one crucial issue remaining to be solved, namely the cold-start problem. In this paper, we propose a method that combines human personality characteristics into the traditional rating-based similarity computation in the framework of user-based collaborative filtering systems with the motivation to make good recommendations for new users who have rated few items. This technique can be especially useful for recommenders that are embedded in social networks where personality data can be more easily obtained. We first analyze our method in terms of the influence of the parameters such as the number of neighbors and the weight of rating-based similarity. We further compare our method with pure traditional ratings-based similarity in several experimental conditions. Our results show that applying personality information into traditional user-based collaborative filtering systems can efficiently address the new user problem.
Aspect-Based Relational Sentiment Analysis Using a Stacked Neural Network Architecture

Sentiment analysis can be regarded as a relation extraction problem in which the sentiment of some opinion holder towards a certain aspect of a product, theme or event needs to be extracted. We present a novel neural architecture for sentiment analysis as a relation extraction problem that addresses this problem by dividing it into three subtasks: i) identification of aspect and opinion terms, ii) labeling of opinion terms with a sentiment, and iii) extraction of relations between opinion terms and aspect terms. For each subtask, we propose a neural network based component and combine all of them into a complete system for relational sentiment analysis. The component for aspect and opinion term extraction is a hybrid architecture consisting of a recurrent neural network stacked on top of a convolutional neural network. This approach outperforms a standard convolutional deep neural architecture as well as a recurrent network architecture and performs competitively compared to other methods on two datasets of annotated customer reviews. To extract sentiments for individual opinion terms, we propose a recurrent architecture in combination with word distance features and achieve promising results, outperforming a majority baseline by 18% accuracy and providing the first results for the USAGE dataset. Our relation extraction component outperforms the current state-of-the-art in aspect-opinion relation extraction by 15% F-Measure.
Appropriation of Information Systems: Using Cognitive Mapping for Eliciting Users' Sensemaking

This paper explores the use of cognitive mapping for eliciting users' sensemaking during information system (IS) appropriation. Despite the potential usefulness of sensemaking, few studies in IS research use it as a theoretical lens to address IS appropriation. A possible reason for this may be that sensemaking does not easily lend itself to be used in practice. We introduce cognitive mapping as a way to elicit users' sensemaking and illustrate its value by reporting on findings from an empirical study of the introduction of an Electronic Patient Record (EPR) system. The contribution of the paper is threefold: first, our findings demonstrate cognitive mapping's use for eliciting users' sensemaking during IS appropriation. Second, our findings illustrate how cognitive mapping can be used as a dynamic approach facilitating collective negotiation of meaning. Third, we contribute with a thorough discussion of the epistemological and methodological assumptions underlying cognitive mapping to ensure its validity and trustworthiness.
A Practical Guide to Developing and Validating Computer Science Knowledge Assessments with Application to Middle School

Knowledge assessment instruments, or tests, are commonly created by faculty in classroom settings to measure student knowledge and skill. Another crucial role for assessment instruments is in gauging student learning in response to a computer science education research project, or intervention. In an increasingly interdisciplinary landscape, it is crucial to validate knowledge assessment instruments, yet developing and validating these tests for computer science poses substantial challenges. This paper presents a seven-step approach to designing, iteratively refining, and validating knowledge assessment instruments designed not to assign grades but to measure the efficacy or promise of novel interventions. We also detail how this seven-step process is being instantiated within a three-year project to implement a game-based learning environment for middle school computer science. This paper serves as a practical guide for adapting widely accepted psychometric practices to the development and validation of computer science knowledge assessments to support research.
First off the mark: early seed germination.

Most plant seeds are dispersed in a dry, mature state. If these seeds are non-dormant and the environmental conditions are favourable, they will pass through the complex process of germination. In this review, recent progress made with state-of-the-art techniques including genome-wide gene expression analyses that provided deeper insight into the early phase of seed germination, which includes imbibition and the subsequent plateau phase of water uptake in which metabolism is reactivated, is summarized. The physiological state of a seed is determined, at least in part, by the stored mRNAs that are translated upon imbibition. Very early upon imbibition massive transcriptome changes occur, which are regulated by ambient temperature, light conditions, and plant hormones. The hormones abscisic acid and gibberellins play a major role in regulating early seed germination. The early germination phase of Arabidopsis thaliana culminates in testa rupture, which is followed by the late germination phase and endosperm rupture. An integrated view on the early phase of seed germination is provided and it is shown that it is characterized by dynamic biomechanical changes together with very early alterations in transcript, protein, and hormone levels that set the stage for the later events. Early seed germination thereby contributes to seed and seedling performance important for plant establishment in the natural and agricultural ecosystem.
Extraction of extracellular polymeric substances (EPS) from anaerobic granular sludges: comparison of chemical and physical extraction protocols

The characteristics of the extracellular polymeric substances (EPS) extracted with nine different extraction protocols from four different types of anaerobic granular sludge were studied. The efficiency of four physical (sonication, heating, cationic exchange resin (CER), and CER associated with sonication) and four chemical (ethylenediaminetetraacetic acid, ethanol, formaldehyde combined with heating, or NaOH) EPS extraction methods was compared to a control extraction protocols (i.e., centrifugation). The nucleic acid content and the protein/polysaccharide ratio of the EPS extracted show that the extraction does not induce abnormal cellular lysis. Chemical extraction protocols give the highest EPS extraction yields (calculated by the mass ratio between sludges and EPS dry weight (DW)). Infrared analyses as well as an extraction yield over 100% or organic carbon content over 1 g g−1 of DW revealed, nevertheless, a carry-over of the chemical extractants into the EPS extracts. The EPS of the anaerobic granular sludges investigated are predominantly composed of humic-like substances, proteins, and polysaccharides. The EPS content in each biochemical compound varies depending on the sludge type and extraction technique used. Some extraction techniques lead to a slightly preferential extraction of some EPS compounds, e.g., CER gives a higher protein yield.
Dermal fillers in aesthetics: an overview of adverse events and treatment approaches

The ever-expanding range of dermal filler products for aesthetic soft tissue augmentation is of benefit for patients and physicians, but as indications and the number of procedures performed increase, the number of complications will likely also increase.



To describe potential adverse events associated with dermal fillers and to provide structured and clear guidance on their treatment and avoidance.



Reports of dermal filler complications in the medical literature were reviewed and, based on the publications retrieved and the authors' extensive experience, recommendations for avoiding and managing complications are provided.



Different dermal fillers have widely varying properties, associated risks, and injection requirements. All dermal fillers have the potential to cause complications. Most are related to volume and technique, though some are associated with the material itself. The majority of adverse reactions are mild and transient, such as bruising and trauma-related edema. Serious adverse events are rare, and most are avoidable with proper planning and technique.



For optimum outcomes, aesthetic physicians should have a detailed understanding of facial anatomy; the individual characteristics of available fillers; their indications, contraindications, benefits, and drawbacks; and ways to prevent and avoid potential complications.
Creating full view panoramic image mosaics and environment maps

This paper presents a novel approach to creating full view panoramic mosaics from image sequences. Unlike current panoramic stitching methods, which usually require pure horizontal camera panning, our system does not require any controlled motions or constraints on how the images are taken (as long as there is no strong motion parallax). For example, images taken from a hand-held digital camera can be stitched seamlessly into panoramic mosaics. Because we represent our image mosaics using a set of transforms, there are no singularity problems such as those existing at the top and bottom of cylindrical or spherical maps. Our algorithm is fast and robust because it directly recovers 3D rotations instead of general 8 parameter planar perspective transforms. Methods to recover camera focal length are also presented. We also present an algorithm for efficiently extracting environment maps from our image mosaics. By mapping the mosaic onto an artibrary texture-mapped polyhedron surrounding the origin, we can explore the virtual environment using standard 3D graphics viewers and hardware without requiring special-purpose players.
Full-mouth adhesive rehabilitation of a severely eroded dentition: the three-step technique. Part 1.

Traditionally, a full-mouth rehabilitation based on full-crown coverage has been the recommended treatment for patients affected by severe dental erosion. Nowadays, thanks to improved adhesive techniques, the indications for crowns have decreased and a more conservative approach may be proposed. Even though adhesive treatments simplify both the clinical and laboratory procedures, restoring such patients still remains a challenge due to the great amount of tooth destruction. To facilitate the clinician's task during the planning and execution of a full-mouth adhesive rehabilitation, an innovative concept has been developed: the three-step technique. Three laboratory steps are alternated with three clinical steps, allowing the clinician and the laboratory technician to constantly interact to achieve the most predictable esthetic and functional outcome. During the first step, an esthetic evaluation is performed to establish the position of the plane of occlusion. In the second step, the patient's posterior quadrants are restored at an increased vertical dimension. Finally, the third step reestablishes the anterior guidance. Using the three-step technique, the clinician can transform a full-mouth rehabilitation into a rehabilitation for individual quadrants. This article illustrates only the first step in detail, explaining all the clinical parameters that should be analyzed before initiating treatment.
Single-dose versus multiple-dose antibiotic prophylaxis for the surgical treatment of closed fractures

Recent meta-analyses have suggested similar wound infection rates when using single- or multiple-dose antibiotic prophylaxis in the operative management of closed long bone fractures. In order to assist clinicians in choosing the optimal prophylaxis strategy, we performed a cost-effectiveness analysis comparing single- and multiple-dose prophylaxis.



A cost-effectiveness analysis comparing the two prophylactic strategies was performed using time horizons of 60 days and 1 year. Infection probabilities, costs, and quality-adjusted life days (QALD) for each strategy were estimated from the literature. All costs were reported in 2007 US dollars. A base case analysis was performed for the surgical treatment of a closed ankle fracture. Sensitivity analysis was performed for all variables, including probabilistic sensitivity analysis using Monte Carlo simulation.



Single-dose prophylaxis results in lower cost and a similar amount of quality-adjusted life days gained. The single-dose strategy had an average cost of $2,576 for an average gain of 272 QALD. Multiple doses had an average cost of $2,596 for 272 QALD gained. These results are sensitive to the incidence of surgical site infection and deep wound infection for the single-dose treatment arm. Probabilistic sensitivity analysis using all model variables also demonstrated preference for the single-dose strategy.



Assuming similar infection rates between the prophylactic groups, our results suggest that single-dose prophylaxis is slightly more cost-effective than multiple-dose regimens for the treatment of closed fractures. Extensive sensitivity analysis demonstrates these results to be stable using published meta-analysis infection rates.
DEVELOPMENT OF HIGH-PERFORMANCE , HIGH-VOLUME CONSUMER MEMS GYROSCOPES

This paper discusses the challenges and success factors for creating the world’s first integrated MEMS gyroscopes for the consumer electronics market. A disruptive MEMS processing platform called Nasiri-Fabrication is described which has enabled Motion Processing applications, creating the largest and fastest growing MEMS sensors market segment. The paper also presents the design challenges and methodology behind the creation of the world’s smallest and best performing consumer grade gyroscope.
SELF-ESTEEM AND JOB PERFORMANCE : THE MODERATING ROLE OF SELF-ESTEEM CONTINGENCIES

Although theoretical perspectives suggest self-esteem level (i.e., high/low) should have main and moderating effects on job performance, empirical and narrative reviews of the literature suggest such effects are either nonexistent or highly variable. To account for these mixed findings, we hypothesized that self-esteem level should only have main and moderating effects on job performance when one’s self-esteem is not contingent upon workplace performance. Using multisource ratings across 2 samples of working adults, we found that the importance of performance to self-esteem (IPSE) moderated the effect of self-esteem level on job performance and moderated the buffering interaction between self-esteem level and role conflict in the prediction of job performance. Our results thus support IPSE as an important moderator of both main and moderating effects of self-esteem level.
Pool Physics Simulation by Event Prediction 2: Collisions

A predictive event-based method to simulate the physics of the game of pool is described, including event time prediction for collisions between balls and between balls and the rails and pockets of the table. The method uses the vector parameterization of the equation of motion of a moving ball to analytically predict the time of occurence of collision events. The method is both accurate, since it returns exact analytical solutions for ball trajectories using no linear approximations, and efficient, since it requires a minimal number of floating point operations for trajectory solution and collision prediction. It is suitable for use within a game tree search, which requires a great many potential shots to be modeled efficiently, and within a robotic pool system, which requires high accuracy in predicting shot outcomes.
Almost Linear VC-Dimension Bounds for Piecewise Polynomial Networks

We compute upper and lower bounds on the VC dimension and pseudodimension of feedforward neural networks composed of piecewise polynomial activation functions. We show that if the number of layers is fixed, then the VC dimension and pseudo-dimension grow as W log W, where W is the number of parameters in the network. This result stands in opposition to the case where the number of layers is unbounded, in which case the VC dimension and pseudo-dimension grow as W2. We combine our results with recently established approximation error rates and determine error bounds for the problem of regression estimation by piecewise polynomial networks with unbounded weights.
6-Year follow-up of ventral monosegmental spondylodesis of incomplete burst fractures of the thoracolumbar spine using three cortical iliac crest bone grafts

Autologous bone graft is the gold standard for vertebral body replacement. Currently, after modern implants for vertebral body replacement are available, controversies exist regarding the optimal implant strategy. Between 2002 and 2003, 17 patients were included in this study, all suffering from incomplete burst fractures of the thoracolumbar spine. All of them were treated by ventral monosegmental spondylodesis using iliac crest bone graft. The individual treatment strategy depended on the fracture situation and patient’s condition. After an average of 74 months (range 66–84) a clinical and computer tomographic follow-up examination was performed in 14 patients (average age, 35.2 years) including VAS spine score and SF 36 score. Nine patients were treated ventral only five patients dorsoventrally. Complete osseous consolidation was visible in nine, partial consolidation (>30 %) in four, and lysis in one patient, without any significant differences between ventral only or dorsoventral approach. After removal of the fixateur interne the level of consolidation improved in all patients, treated dorsoventrally. There was no significant correlation between percentage of osseous consolidation and the clinical follow-up parameters. After 6 years, 71 % of the patients suffered from persistent pain associated with the approach to the iliac crest. Two revision surgeries have been necessary. High rates of osseous consolidation are visible 6 years after ventral spondylodesis by iliac crest bone grafts. A further improvement of consolidation can be expected after dorsal implant removal. But the surgical approach to the iliac crest is accompanied with a relevant complication rate.
Learning End-to-end Video Classification with Rank-Pooling

We introduce a new model for representation learning and classification of video sequences. Our model is based on a convolutional neural network coupled with a novel temporal pooling layer. The temporal pooling layer relies on an inner-optimization problem to efficiently encode temporal semantics over arbitrarily long video clips into a fixed-length vector representation. Importantly, the representation and classification parameters of our model can be estimated jointly in an end-to-end manner by formulating learning as a bilevel optimization problem. Furthermore, the model can make use of any existing convolutional neural network architecture (e.g., AlexNet or VGG) without modification or introduction of additional parameters. We demonstrate our approach on action and activity recognition tasks.
Personality , Ideology , Intelligence , and Self-Rated Strengths

This study looked at the individual difference correlates of self-rated character strengths and virtues. In all, 280 adults completed a short 24-item measure of strengths, a short personality measure of the Big Five traits and a fluid intelligence test. The Cronbach alphas for the six higher order virtues were satisfactory but factor analysis did not confirm the a priori classification yielding five interpretable factors. These factors correlated significantly with personality and intelligence. Intelligence and neuroticism were correlated negatively with all the virtues, while extraversion and conscientiousness were positively correlated with all virtues. Structural equation modeling showed personality and religiousness moderated the effect of intelligence on the virtues. Extraversion and openness were the largest correlates of the virtues. The use of shortened measured in research is discussed.
InputFinder: Reverse Engineering Closed Binaries using Hardware Performance Counters

The effectiveness of many dynamic program analysis techniques depends heavily on the completeness of the test suite applied during the analysis process. Test suites are often composed by developers and aim at testing all of the functionality of a software system. However, test suites may not be complete, if they exist at all. To date, only two methods exist for automatically generating test input for closed binaries: fuzzing and symbolic execution. Despite previous successes of these methods in identifying bugs, both techniques have limitations. In this paper, we propose a new method for autonomously generating valid input and identifying protocols for closed x86 binaries. The method presented can be used as a standalone tool or can be combined with other techniques for improved results. To assess its effectiveness, we test InputFinder, the implementation of our method, against binaries from the DARPA Cyber Grand Challenge example set. Our evaluations show that our method is not only effective in finding input and determining whether a protocol is expected but can also find unexpected control flow paths.