nils-herrmann/clean_scirepeval huggingface dataset:
Foresight: Rapid Data Exploration Through Guideposts

Current tools for exploratory data analysis (EDA) require users to manually select data attributes, statistical computations and visual encodings. This can be daunting for large-scale, complex data. We introduce Foresight, a visualization recommender system that helps the user rapidly explore large high-dimensional datasets through “guideposts.” A guidepost is a visualization corresponding to a pronounced instance of a statistical descriptor of the underlying data, such as a strong linear correlation between two attributes, high skewness or concentration about the mean of a single attribute, or a strong clustering of values. For each descriptor, Foresight initially presents visualizations of the “strongest” instances, based on an appropriate ranking metric. Given these initial guideposts, the user can then look at “nearby” guideposts by issuing “guidepost queries” containing constraints on metric type, metric strength, data attributes, and data values. Thus, the user can directly explore the network of guideposts, rather than the overwhelming space of data attributes and visual encodings. Foresight also provides for each descriptor a global visualization of ranking-metric values to both help orient the user and ensure a thorough exploration process. Foresight facilitates interactive exploration of large datasets using fast, approximate sketching to compute ranking metrics. We also contribute insights on EDA practices of data scientists, summarizing results from an interview study we conducted to inform the design of Foresight.
Automated Detection and Classification for Packed Android Applications

Android packing services provide significant benefits in code protection by hiding original executable code, which help app developers to protect their code against reverse engineering. However, adversaries take the advantage of packers to hide their malicious code. A number of unpacking approaches have been proposed to defend against malicious packed apps. Unfortunately, most of the unpacking approaches work only for a limited time or for a particular type of packers. The analysis for different packers often requires specific domain knowledge and a significant amount of manual effort. In this paper, we conducted analyses of known Android packers appeared in recent years and propose to design an automatic detection and classification framework. The framework is capable of identifying packed apps, extracting the execution behavioral pattern of packers, and categorizing packed apps into groups. The variants of packer families share typical behavioral patterns reflecting their activities and packing techniques. The behavioral patterns obtained dynamically can be exploited to detect and classify unknown packers, which shed light on new directions for security researchers.
Degenerative lumbar spinal stenosis: evaluation and management.

Degenerative lumbar spinal stenosis is caused by mechanical factors and/or biochemical alterations within the intervertebral disk that lead to disk space collapse, facet joint hypertrophy, soft-tissue infolding, and osteophyte formation, which narrows the space available for the thecal sac and exiting nerve roots. The clinical consequence of this compression is neurogenic claudication and varying degrees of leg and back pain. Degenerative lumbar spinal stenosis is a major cause of pain and impaired quality of life in the elderly. The natural history of this condition varies; however, it has not been shown to worsen progressively. Nonsurgical management consists of nonsteroidal anti-inflammatory drugs, physical therapy, and epidural steroid injections. If nonsurgical management is unsuccessful and neurologic decline persists or progresses, surgical treatment, most commonly laminectomy, is indicated. Recent prospective randomized studies have demonstrated that surgery is superior to nonsurgical management in terms of controlling pain and improving function in patients with lumbar spinal stenosis.
Reconfigurable helical antenna based on an origami structure for wireless communication system

This paper presents a reconfigurable axial mode helical antenna which could be folded and unfolded using rigidly foldable origami structure to work at different resonant frequencies for kinds of wireless systems. Measured results show that the folded state could operate at both 1.82 GHz and 2.14 GHz. And the measured operating frequency for the unfolded state is 860 MHz. The frequency reconfigurability up to 1.28 GHz was achieved, and the height of the folded state could be reduced to 17% of the height of the unfolded state.
Skier's Thumb.

In brief: Diagnosis of skier's thumb-a common sports injury-is based on physical examination and history of the injury. The most important findings from the physical exam are point tenderness over the ulnar collateral ligament and instability, which is tested with the thumb at 0° and at 20° to 30° of flexion. Grade 1 and 2 injuries, which involve torn fibers but no loss of integrity, can be treated with casting and/or splinting and physical therapy. Grade 3 injuries involve complete disruption of the ligament and usually require surgical repair. Results from treatment are generally excellent, and with appropriate rehabilitation, athletes recover pinch and grip strength and return to sports.
The first five computer science principles pilots: summary and comparisons

Attracting Diverse Students As indicated in other articles in this issue, a major goal of the CS Principles effort was to attract a population of students that includes many who are not predisposed to study computing. The field not only battles negative stereotypes, but its labor pool must be enlarged both to meet expected demand, but also to introduce more diverse opinions, especially considering the importance of social media. The results are very encouraging.
Design, Realization, and Test of a UWB Radar Sensor for Breath Activity Monitoring

An analytical model of an ultrawideband range gating radar is developed. The model is used for the system design of a radar for breath activity monitoring having sub-millimeter movement resolution and fulfilling the requirements of the Federal Communications Commission in terms of effective isotropic radiated power. The system study has allowed to define the requirements of the various radar subsystems that have been designed and realized by means of a low cost hybrid technology. The radar has been assembled and some performance factors, such as range and movement resolution, and the receiver conversion factor have been experimentally evaluated and compared with the model predictions. Finally, the radar has been tested for remote breath activity monitoring, showing recorded respiratory signals in very good agreement with those obtained by means of a conventional technique employing a piezoelectric belt.
A ?5-V CMOS analog multiplier

A four-quadrant CMOS analog multiplier is presented. The device is nominafly biased with +5-V supplies, has identicaf full-scafe single-ended x and y inputs of +4 V, and exhibits less than 0.5 percent Manuscript received March 1, 1987; revised July 18, 1987. The authors are with the Department of Electrical Engineering, Texas A&M University, College Station, TX 77843-3128.  Number 8716852. + I–— ————_—
LABDA at SemEval-2017 Task 10: Relation Classification between keyphrases via Convolutional Neural Network

In this paper, we describe our participation at the subtask of extraction of relationships between two identified keyphrases. This task can be very helpful in improving search engines for scientific articles. Our approach is based on the use of a convolutional neural network (CNN) trained on the training dataset. This deep learning model has already achieved successful results for the extraction relationships between named entities. Thus, our hypothesis is that this model can be also applied to extract relations between keyphrases. The official results of the task show that our architecture obtained an F1-score of 0.38% for Keyphrases Relation Classification. This performance is lower than the expected due to the generic preprocessing phase and the basic configuration of the CNN model, more complex architectures are proposed as future work to increase the classification rate.
Interferon dimers: IFN-PEG-IFN.

Increasingly complex proteins can be made by a recombinant chemical approach where proteins that can be made easily can be combined by site-specific chemical conjugation to form multifunctional or more active protein therapeutics. Protein dimers may display increased avidity for cell surface receptors. The increased size of protein dimers may also increase circulation times. Cytokines bind to cell surface receptors that dimerise, so much of the solvent accessible surface of a cytokine is involved in binding to its target. Interferon (IFN) homo-dimers (IFN-PEG-IFN) were prepared by two methods: site-specific bis-alkylation conjugation of PEG to the two thiols of a native disulphide or to two imidazoles on a histidine tag of two His8-tagged IFN (His8IFN). Several control conjugates were also prepared to assess the relative activity of these IFN homo-dimers. The His8IFN-PEG20-His8IFN obtained by histidine-specific conjugation displayed marginally greater in vitro antiviral activity compared to the IFN-PEG20-IFN homo-dimer obtained by disulphide re-bridging conjugation. This result is consistent with previous observations in which enhanced retention of activity was made possible by conjugation to an N-terminal His-tag on the IFN. Comparison of the antiviral and antiproliferative activities of the two IFN homo-dimers prepared by disulphide re-bridging conjugation indicated that IFN-PEG10-IFN was more biologically active than IFN-PEG20-IFN. This result suggests that the size of PEG may influence the antiviral activity of IFN-PEG-IFN homo-dimers.
Near optimal placement of virtual network functions

Network Function Virtualization (NFV) is a new networking paradigm where network functions are executed on commodity servers located in small cloud nodes distributed across the network, and where software defined mechanisms are used to control the network flows. This paradigm is a major turning point in the evolution of networking, as it introduces high expectations for enhanced economical network services, as well as major technical challenges. In this paper, we address one of the main technical challenges in this domain: the actual placement of the virtual functions within the physical network. This placement has a critical impact on the performance of the network, as well as on its reliability and operation cost. We perform a thorough study of the NFV location problem, show that it introduces a new type of optimization problems, and provide near optimal approximation algorithms guaranteeing a placement with theoretically proven performance. The performance of the solution is evaluated with respect to two measures: the distance cost between the clients and the virtual functions by which they are served, as well as the setup costs of these functions. We provide bi-criteria solutions reaching constant approximation factors with respect to the overall performance, and adhering to the capacity constraints of the networking infrastructure by a constant factor as well. Finally, using extensive simulations, we show that the proposed algorithms perform well in many realistic scenarios.
A nurses’ alarm fatigue questionnaire: development and psychometric properties

Alarm fatigue can adversely affect nurses’ efficiency and concentration on their tasks, which is a threat to patients’ safety. The purpose of the present study was to develop and test the psychometric accuracy of an alarm fatigue questionnaire for nurses. This study was conducted in two stages: in stage one, in order to establish the different aspects of the concept of alarm fatigue, the researchers reviewed the available literature—articles and books—on alarm fatigue, and then consulted several experts in a meeting to define alarm fatigue and develop statements for the questionnaire. In stage two, after the final draft had been approved, the validity of the instrument was measured using the two methods of face validity (the quantitative and qualitative approaches) and content validity (the qualitative and quantitative approaches). Test–retest, Cronbach’s alpha, and Principal Component Analysis were used for item reduction and reliability analysis. Based on the results of stage one, the researchers extracted 30 statements based on a 5-point Likert scale. In stage two, after the face and content validity of the questionnaire had been established, 19 statements were left in the instrument. Based on factor loadings of the items and “alpha if item deleted” and after the second round of consultation with the expert panel, six items were removed from the scale. The test of the reliability of nurses’ alarm fatigue questionnaire based on the internal homogeneity and retest methods yielded the following results: test–retest correlation coefficient = 0.99; Guttman split-half correlation coefficient = 0.79; Cronbach’s alpha = 0.91. Regarding the importance of recognizing alarm fatigue in nurses, there is need for an instrument to measure the phenomenon. The results of the study show that the developed questionnaire is valid and reliable enough for measuring alarm fatigue in nurses.
Sporadic and familial hemiplegic migraine: pathophysiological mechanisms, clinical characteristics, diagnosis, and management

Hemiplegic migraine is a rare form of migraine with aura that involves motor aura (weakness). This type of migraine can occur as a sporadic or a familial disorder. Familial forms of hemiplegic migraine are dominantly inherited. Data from genetic studies have implicated mutations in genes that encode proteins involved in ion transportation. However, at least a quarter of the large families affected and most sporadic cases do not have a mutation in the three genes known to be implicated in this disorder, suggesting that other genes are still to be identified. Results from functional studies indicate that neuronal hyperexcitability has a pivotal role in the pathogenesis of hemiplegic migraine. The clinical manifestations of hemiplegic migraine range from attacks with short-duration hemiparesis to severe forms with recurrent coma and prolonged hemiparesis, permanent cerebellar ataxia, epilepsy, transient blindness, or mental retardation. Diagnosis relies on a careful patient history and exclusion of potential causes of symptomatic attacks. The principles of management are similar to those for common varieties of migraine, except that vasoconstrictors, including triptans, are historically contraindicated but are often used off-label to stop the headache, and prophylactic treatment can include lamotrigine and acetazolamide.
An improved threshold estimation technique for partial discharge signal denoising using Wavelet Transform

Recent research have shown that the Wavelet Transform (WT) can potentially be used to extract Partial Discharge (PD) signals from severe noise like White noise, Random noise and Discrete Spectral Interferences (DSI). It is important to define that noise is a significant problem in PD detection. Accordingly, the paper mainly deals with denoising of PD signals, based on improved WT techniques namely Translation Invariant Wavelet Transform (TIWT). The improved WT method is distinct from other traditional method called as Fast Fourier Transform (FFT). The TIWT not only remain the edge of the original signal efficiently but also reduce impulsive noise to some extent. Additionally Translation Invariant (TI) Wavelet Transform denoising is used to suppress Pseudo Gibbs phenomenon. In this paper an attempt has been made to review the methodology of denoising the partial discharge signals and shows that the proposed denoising method results are better when compared to other wavelet-based approaches like FFT, wavelet hard thresholding, wavelet soft thresholding, by evaluating five different parameters like, Signal to noise ratio, Cross correlation coefficient, Pulse amplitude distortion, Mean square error, Reduction in noise level.
Developing global managers' competencies using the fuzzy DEMATEL method

Modern global managers are required to possess a set of competencies or multiple intelligences in order to meet pressing business challenges. Hence, expanding global managersâ€TM competencies is becoming an important issue. Many scholars and specialists have proposed various competency models containing a list of required competencies. But it is hard for someone to master a broad set of competencies at the same time. Here arises an imperative issue on how to enrich global managersâ€TM competencies by way of segmenting a set of competencies into some portions in order to facilitate competency development with a stepwise mode. To solve this issue involving the vagueness of human judgments, we have proposed an effective method combining fuzzy logic and Decision Making Trial and Evaluation Laboratory (DEMATEL) to segment required competencies for better promoting the competency development of global managers. Additionally, an empirical study is presented to illustrate the Purchase Export Previous article Next article Check if you have access through your login credentials or your institution.
EVALUATION OF THE ZYGOMATIC BUTTRESS AS A DONOR SITE FOR RIDGE AUGMENTATION PRIOR TO IMPLANT INSERTION IN THE ESTHETIC ZONE

Traumatic loss of teeth in the esthetic zone commonly results in significant loss of buccal bone. This leads to reduced esthetics, problems with phonetics and reduction in function. Single tooth replacement has become an indication for implant-based restoration. In case of lack of bone volume the need of surgical reconstruction of the alveolar ridge is warranted. Several bone grafting techniques have been described to ensure sufficient bone volume for implantation.  Evaluation of using the zygomatic buttress as an intraoral bone harvesting donor site for pre-implant grafting.  Twelve patients were selected with limited alveolar ridge defect in the esthetic zone that needs bone grafting procedure prior to dental implants. Patients were treated using a 2-stage technique where bone blocks harvested from the zygomatic buttress region were placed as onlay grafts and fixed with osteosynthesis micro screws. After 4 months of healing, screws were removed for implant placement  Harvesting of 12 bone blocks were performed for all patients indicating a success rate of 100% for the zygomatic buttress area as a donor site. Final rehabilitation with dental implants was possible in 11 of 12 patients, yielding a success rate of 91.6%. Three patients (25%) had postoperative complications at the donor site and one patient (8.3%) at the recipient site. The mean value of bone width pre-operatively was 3.64 ± .48 mm which increased to 5.47 ± .57 mm post-operatively, the increase in mean value of bone width was statistically significant (p < 0.001).  Harvesting of intraoral bone blocks from the zygomatic buttress region is an effective and safe method to treat localized alveolar ridge defect before implant placement.
Ten-fold Improvement in Visual Odometry Using Landmark Matching

Our goal is to create a visual odometry system for robots and wearable systems such that localization accuracies of centimeters can be obtained for hundreds of meters of distance traveled. Existing systems have achieved approximately a 1% to 5% localization error rate whereas our proposed system achieves close to 0.1% error rate, a ten-fold reduction. Traditional visual odometry systems drift over time as the frame-to-frame errors accumulate. In this paper, we propose to improve visual odometry using visual landmarks in the scene. First, a dynamic local landmark tracking technique is proposed to track a set of local landmarks across image frames and select an optimal set of tracked local landmarks for pose computation. As a result, the error associated with each pose computation is minimized to reduce the drift significantly. Second, a global landmark based drift correction technique is proposed to recognize previously visited locations and use them to correct drift accumulated during motion. At each visited location along the route, a set of distinctive visual landmarks is automatically extracted and inserted into a landmark database dynamically. We integrate the landmark based approach into a navigation system with 2 stereo pairs and a low-cost inertial measurement unit (IMU) for increased robustness. We demonstrate that a real-time visual odometry system using local and global landmarks can precisely locate a user within 1 meter over 1000 meters in unknown indoor/outdoor environments with challenging situations such as climbing stairs, opening doors, moving foreground objects etc..
Finding Clues for Your Secrets: Semantics-Driven, Learning-Based Privacy Discovery in Mobile Apps

A long-standing challenge in analyzing information leaks within mobile apps is to automatically identify the code operating on sensitive data. With all existing solutions relying on System APIs (e.g., IMEI, GPS location) or features of user interfaces (UI), the content from app servers, like user’s Facebook profile, payment history, fall through the crack. Finding such content is important given the fact that most apps today are web applications, whose critical data are often on the server side. In the meantime, operations on the data within mobile apps are often hard to capture, since all server-side information is delivered to the app in the same way, sensitive or not. A unique observation of our research is that in modern apps, a program is essentially a semantics-rich documentation carrying meaningful program elements such as method names, variables and constants that reveal the sensitive data involved, even when the program is under moderate obfuscation. Leveraging this observation, we develop a novel semantics-driven solution for automatic discovery of sensitive user data, including those from the server side. Our approach utilizes natural language processing (NLP) to automatically locate the program elements (variables, methods, etc.) of interest, and then performs a learning-based program structure analysis to accurately identify those indeed carrying sensitive content. Using this new technique, we analyzed 445,668 popular apps, an unprecedented scale for this type of research. Our work brings to light the pervasiveness of information leaks, and the channels through which the leaks happen, including unintentional over-sharing across libraries and aggressive data acquisition behaviors. Further we found that many high-profile apps and libraries are involved in such leaks. Our findings contribute to a better understanding of the privacy risk in mobile apps and also highlight the importance of data protection in today’s software composition.
The effect of Instagram "likes" on women's social comparison and body dissatisfaction.

Photo-based activity on social networking sites has recently been identified as contributing to body image concerns. The present study aimed to investigate experimentally the effect of number of likes accompanying Instagram images on women's own body dissatisfaction. Participants were 220 female undergraduate students who were randomly assigned to view a set of thin-ideal or average images paired with a low or high number of likes presented in an Instagram frame. Results showed that exposure to thin-ideal images led to greater body and facial dissatisfaction than average images. While the number of likes had no effect on body dissatisfaction or appearance comparison, it had a positive effect on facial dissatisfaction. These effects were not moderated by Instagram involvement, but greater investment in Instagram likes was associated with more appearance comparison and facial dissatisfaction. The results illustrate how the uniquely social interactional aspects of social media (e.g., likes) can affect body image.