nils-herrmann/clean_scirepeval huggingface dataset:
Laser stripe peak detector for 3D scanners. A FIR filter approach

The accuracy of a 3D reconstruction using laser scanners is significantly determined by the detection of the laser stripe. Since the energy pattern of such a stripe corresponds to a Gaussian profile, it makes sense to detect the point of maximum light intensity (or peak) by computing the zero-crossing point of the first derivative of such Gaussian profile. However, because noise is present in every physical process, such as electronic image formation, it is not sensitive to perform the derivative of the image of the stripe in almost any situation, unless a previous filtering stage is done. Considering that stripe scanning is an inherently row-parallel process, every row of a given image must be processed independently in order to compute its corresponding peak position in the row. This paper reports on the use of digital filtering techniques in order to cope with the scanning of different surfaces with different optical properties and different noise levels, leading to the proposal of a more accurate numerical peak detector, even at very low signal-to-noise ratios.
Evaluation on Feature Importance for Favorite Song Detection

Detecting whether a song is favorite for a user is an important but also challenging task in music recommendation. One of critical steps to do this task is to select important features for the detection. This paper presents two methods to evaluate feature importance, in which we compared nine available features based on a large user log in the real world. The set of features includes song metadata, acoustic feature, and user preference used by Collaborative Filtering techniques. The evaluation methods are designed from two views: i) the correlation between the estimated scores by song similarity in respect of a feature and the scores estimated by real play count, ii) feature selection methods over a binary classification problem, i.e., “like” or “dislike”. The experimental results show the user preference is the most important feature and artist similarity is of the second importance among these nine features.
Magnetic resonance imaging parameters for assessing risk of recurrent hamstring injuries in elite athletes.

Magnetic resonance (MR) imaging has established its usefulness in diagnosing hamstring muscle strain and identifying features correlating with the duration of rehabilitation in athletes; however, data are currently lacking that may predict which imaging parameters may be predictive of a repeat strain.



This study was conducted to identify whether any MR imaging-identifiable parameters are predictive of athletes at risk of sustaining a recurrent hamstring strain in the same playing season.



Cohort study; 
Forty-one players of the Australian Football League who sustained a hamstring injury underwent MR examination within 3 days of injury between February and August 2002. The imaging parameters measured were the length of injury, cross-sectional area, the specific muscle involved, and the location of the injury within the muscle-tendon unit. Players who suffered a repeat injury during the same season were reimaged, and baseline and repeat injury measurements were compared. Comparison was also made between this group and those who sustained a single strain.



Forty-one players sustained hamstring strains that were positive on MR imaging, with 31 injured once and 10 suffering a second injury. The mean length of hamstring muscle injury for the isolated group was 83.4 mm, compared with 98.7 mm for the reinjury group (P = .35). In the reinjury group, the second strain was also of greater length than the original (mean, 107.5 mm; P = .07). Ninety percent of players sustaining a repeat injury demonstrated an injury length greater than 60 mm, compared with only 58% in the single strain group (P = .01). Only 7% of players (1 of 14) with a strain <60 mm suffered a repeat injury. Of the 27 players sustaining a hamstring strain >60 mm, 33% (9 of 27) suffered a repeat injury. Of all the parameters assessed, only a history of anterior cruciate ligament sprain was a statistically significant predictor for suffering a second strain during the same season of competition.



A history of anterior cruciate ligament injury was the only statistically significant risk factor for a recurrent hamstring strain in our study. Of the imaging parameters, the MR length of a strain had the strongest correlation association with a repeat hamstring strain and therefore may assist in identifying which athletes are more likely to suffer further reinjury.
Artificial neural networks in hardware: A survey of two decades of progress

This article presents a comprehensive overview of the hardware realizations of artificial neural network (ANN) models, known as hardware neural networks (HNN), appearing in academic studies as prototypes as well as in commercial use. HNN research has witnessed a steady progress for more than last two decades, though commercial adoption of the technology has been relatively slower. We study applications. We outline underlying design approaches for mapping an ANN model onto a compact, reliable, and energy efficient hardware entailing computation and communication and survey a wide range of illustrative examples. Chip design approaches (digital, analog, hybrid, and FPGA based) at neuronal level and as neurochips realizing complete ANN models are studied. We specifically discuss, in detail, neuromorphic designs including spiking neural network hardware, cellular neural network implementations, reconfigurable FPGA based implementations, in particular, for stochastic ANN models, and optical implementations. Parallel digital implementations employing bit-slice, systolic, and SIMD architectures, implementations for associative neural memories, and RAM based implementations are also outlined. We trace the recent trends and explore potential future research directions. & 2010 Elsevier B.V. All rights reserved.
Query reformulation using WordNet and genetic algorithm

Search on the web is a delay process and it can be hard task especially for beginners when they attempt to use a keyword query language. Beginner (inexpert) searchers commonly attempt to find information with ambiguous queries. These ambiguous queries make the search engine returns irrelevant results. This work aims to get more relevant pages to query through query reformulation and expanding search space. The proposed system has three basic parts WordNet, Google search engine and Genetic Algorithm. Every part has a special task. The system uses WordNet to remove ambiguity from queries by displaying the meaning of every keyword in user query and selecting the proper meaning for keywords. The system obtains synonym for every keyword from WordNet and generates query list. Genetic algorithm is used to create generation for every query in query list. Every query in system is navigated using Google search engine to obtain results from group of documents on the Web. The system has been tested on number of ambiguous queries and it has obtained more relevant URL to user query especially when the query has one keyword. The results are promising and therefore open further research directions.
Tools for Generating and Analyzing Attack Graphs

Attack graphs depict ways in which an adversary exploits system vulnerabilities to achieve a desired state. System administrators use attack graphs to determine how vulnerable their systems are and to determine what security measures to deploy to defend their systems. In this paper, we present details of an example to illustrate how we specify and analyze network attack models. We take these models as input to our attack graph tools to generate attack graphs automatically and to analyze system vulnerabilities. While we have published our generation and analysis algorithms in earlier work, the presentation of our example and toolkit is novel to this paper.
PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes

DNA microarrays can be used to identify gene expression changes characteristic of human disease. This is challenging, however, when relevant differences are subtle at the level of individual genes. We introduce an analytical strategy, Gene Set Enrichment Analysis, designed to detect modest but coordinate changes in the expression of groups of functionally related genes. Using this approach, we identify a set of genes involved in oxidative phosphorylation whose expression is coordinately decreased in human diabetic muscle. Expression of these genes is high at sites of insulin-mediated glucose disposal, activated by PGC-1α and correlated with total-body aerobic capacity. Our results associate this gene set with clinically important variation in human metabolism and illustrate the value of pathway relationships in the analysis of genomic profiling experiments.
Adenomyosis is a potential cause of recurrent implantation failure during IVF treatment.

Four women, who previously had undergone multiple unsuccessful in vitro fertilisation (IVF) cycles because of failure of implantation of good quality embryos, were identified as having coexisting uterine adenomyosis. Endometrial biopsies showed that adenomyosis was associated with a prominent aggregation of macrophages within the superficial endometrial glands, potentially interfering with embryo implantation. The inactivation of adenomyosis by an ultra-long pituitary downregulation regime promptly resulted in successful pregnancy for all women in this case series.
Improving academic performance and mental health through a stress management intervention: outcomes and mediators of change.

Two hundred and nine pupils were randomly allocated to either a cognitive behaviourally based stress management intervention (SMI) group, or a non-intervention control group. Mood and motivation measures were administered pre and post intervention. Standardized examinations were taken 8-10 weeks later. As hypothesized, results indicated that an increase in the functionality of pupils' cognitions served as the mechanism by which mental health improved in the SMI group. In contrast, the control group demonstrated no such improvements. Also, as predicted, an increase in motivation accounted for the SMI group's significantly better performance on the standardized, academic assessments that comprise the United Kingdom's General Certificate of Secondary Education. Indeed, the magnitude of this enhanced performance was, on average, one-letter grade. Discussion focuses on the theoretical and practical implications of these findings.
Accurate 3D ground plane estimation from a single image

Accurate localization of landmarks in the vicinity of a robot is a first step towards solving the SLAM problem. In this work, we propose algorithms to accurately estimate the 3D location of the landmarks from the robot only from a single image taken from its on board camera. Our approach differs from previous efforts in this domain in that it first reconstructs accurately the 3D environment from a single image, then it defines a coordinate system over the environment, and later it performs the desired localization with respect to this coordinate system using the environment's features. The ground plane from the given image is accurately estimated and this precedes segmentation of the image into ground and vertical regions. A Markov Random Field (MRF) based 3D reconstruction is performed to build an approximate depth map of the given image. This map is robust against texture variations due to shadows, terrain differences, etc. A texture segmentation algorithm is also applied to determine the ground plane accurately. Once the ground plane is estimated, we use the respective camera's intrinsic and extrinsic calibration information to calculate accurate 3D information about the features in the scene.
Inverse Association between Air Pressure and Rheumatoid Arthritis Synovitis

Rheumatoid arthritis (RA) is a bone destructive autoimmune disease. Many patients with RA recognize fluctuations of their joint synovitis according to changes of air pressure, but the correlations between them have never been addressed in large-scale association studies. To address this point we recruited large-scale assessments of RA activity in a Japanese population, and performed an association analysis. Here, a total of 23,064 assessments of RA activity from 2,131 patients were obtained from the KURAMA (Kyoto University Rheumatoid Arthritis Management Alliance) database. Detailed correlations between air pressure and joint swelling or tenderness were analyzed separately for each of the 326 patients with more than 20 assessments to regulate intra-patient correlations. Association studies were also performed for seven consecutive days to identify the strongest correlations. Standardized multiple linear regression analysis was performed to evaluate independent influences from other meteorological factors. As a result, components of composite measures for RA disease activity revealed suggestive negative associations with air pressure. The 326 patients displayed significant negative mean correlations between air pressure and swellings or the sum of swellings and tenderness (p = 0.00068 and 0.00011, respectively). Among the seven consecutive days, the most significant mean negative correlations were observed for air pressure three days before evaluations of RA synovitis (p = 1.7 × 10(-7), 0.00027, and 8.3 × 10(-8), for swellings, tenderness and the sum of them, respectively). Standardized multiple linear regression analysis revealed these associations were independent from humidity and temperature. Our findings suggest that air pressure is inversely associated with synovitis in patients with RA.
End-to-end Multi-Modal Multi-Task Vehicle Control for Self-Driving Cars with Visual Perceptions

Convolutional Neural Networks (CNN) have been successfully applied to autonomous driving tasks, many in an end-to-end manner. Previous end-to-end steering control methods take an image or an image sequence as the input and directly predict the steering angle with CNN. Although single task learning on steering angles has reported good performances, the steering angle alone is not sufficient for vehicle control. In this work, we propose a multi-task learning framework to predict the steering angle and speed control simultaneously in an end-to-end manner. Since it is nontrivial to predict accurate speed values with only visual inputs, we first propose a network to predict discrete speed commands and steering angles with image sequences. Moreover, we propose a multi-modal multi-task network to predict speed values and steering angles by taking previous feedback speeds and visual recordings as inputs. Experiments are conducted on the public Udacity dataset and a newly collected SAIC dataset. Results show that the proposed model predicts steering angles and speed values accurately. Furthermore, we improve the failure data synthesis methods to solve the problem of error accumulation in real road tests.
Energy-efficient routing protocols in wireless sensor networks for health communication systems

Wireless Sensor Networks (WSNs) have their own unique nature of distributed resources and dynamic topology. This introduces very special requirements that should be met by the proposed routing protocols for the WSNs. A Wireless Sensor Network routing protocol is a standard which controls the number of nodes that come to an agreement about the way to route packets between all the computing devices in mobile wireless networks. Today, wireless networks are becoming popular and many routing protocols have been proposed in the literature. Considering these protocols we made a survey on the WSNs energy-efficient routing techniques which are used for Health Care Communication Systems concerning especially the Flat Networks Protocols that have been developed in recent years. Then, as related work, we discuss each of the routing protocols belonging to this category and conclude with a comparison of them.
Prognostic implications of abnormalities in renal function in patients with acute coronary syndromes.

Outcomes in patients with mild to moderate renal function (RF) abnormalities presenting with acute coronary syndromes (ACS) are not well defined.



A convenience sample of 4 ACS trial databases including all enrolled patients was assessed to determine 30- and 180-day outcomes. The 4 trials were Global Use of Strategies to Open Occluded Coronary Arteries (GUSTO) IIb, GUSTO-III, Platelet Glycoprotein IIb/IIIa in Unstable Angina: Receptor Suppression Using Integrilin Therapy (PURSUIT), and Platelet IIb/IIIa Antagonism for the Reduction of Acute coronary syndrome events in a Global Organization Network (PARAGON-A). Patients were stratified into ST-segment elevation (STE) and non-ST-segment elevation (NSE) groups and by the presence or absence of abnormal RF (creatinine clearance <70 mL/min). In the STE group, 7670 of 18 621 patients (41%) had abnormal RF. In the NSE group, 8152 of 19 304 (42%) had abnormal RF. Patients with abnormal RF were older, more often female, and more likely to have adverse baseline characteristics. They had higher mortality and higher mortality/nonfatal myocardial infarction (MI) at both 30 and 180 days, regardless of ST-segment status. Creatinine clearance was independently associated with risk of mortality (hazard ratio 0.79 in the STE group and 0.81 in the NSE group) and with risk of mortality/MI (hazard ratio 0.93) in the NSE group at 180 days.



Patients presenting with ACS frequently have abnormal RF. Abnormal RF is a marker of adverse baseline clinical characteristics and is independently associated with increased risk of death and death/MI.
Female autoerotic asphyxial death - features and issues.

A 44-year-old woman was found by her partner and a friend hanging from a stair well at her home address. Her partner, who had been looking at a social media site in a downstairs room while she was upstairs, had gone to the front door when the friend had arrived. It was then that they noticed the body suspended from side railings at the top of the stairs by a Chinese silk dressing robe sash. The subsequent history from her partner was that the decedent had a history of hanging herself while masturbating. Their friend confirmed that she had also previously told him that she enjoyed “auto asphyxiation” and had wanted to put up a curtain at the top of the stairs so that she would have some privacy during this activity. He had warned her that she should have some type of knot that would give way if too much weight was suspended from it (i.e. a ‘fail safe’ mechanism). The decedent’s other past history included possible bipolar illness, intravenous drug use and hepatitis C positivity. Police investigations found no suspicious features. At autopsy the decedent was wearing a leopard skin patterned bustier  and black lace panty hose over leopard skin patterned panties . The panties had been cut at the front so that the decedent’s labia were protruding . A parchmented ligature mark was present around the neck rising to a point of suspension over the right side of the occiput . There were no facial or conjunctival petechaie. Heavy dark eye liner makeup had been applied. Apart from evidence of recent attempted resuscitation by ambulance personnel the only other injuries were minor superficial abrasions over the dorsa of both feet and a right-sided subgaleal bruise without underlying skull fracture or cerebral contusion. These minor injuries would have been compatible with agonal movements in the stair well. The vagina and rectum were unremarkable with no foreign bodies or injuries. No underlying organic diseases were present which could have caused or contributed to death. Toxicological analyses of blood revealed a high level of methadone (0.7 mg/L) most likely associated with habituation from chronic use, methylamphetamine and non-toxic concentrations of diazepam and olanzapine. Given the history and circumstances of the death these were not thought to be involved in the fatal episode. Death was therefore attributed to neck compression from hanging in the context of autoerotic activity.
SynCoPation: Interactive Synthesis-Coupled Sound Propagation

Recent research in sound simulation has focused on either sound synthesis or sound propagation, and many standalone algorithms have been developed for each domain. We present a novel technique for coupling sound synthesis with sound propagation to automatically generate realistic aural content for virtual environments. Our approach can generate sounds from rigid-bodies based on the vibration modes and radiation coefficients represented by the single-point multipole expansion. We present a mode-adaptive propagation algorithm that uses a perceptual Hankel function approximation technique to achieve interactive runtime performance. The overall approach allows for high degrees of dynamism - it can support dynamic sources, dynamic listeners, and dynamic directivity simultaneously. We have integrated our system with the Unity game engine and demonstrate the effectiveness of this fully-automatic technique for audio content creation in complex indoor and outdoor scenes. We conducted a preliminary, online user-study to evaluate whether our Hankel function approximation causes any perceptible loss of audio quality. The results indicate that the subjects were unable to distinguish between the audio rendered using the approximate function and audio rendered using the full Hankel function in the Cathedral, Tuscany, and the Game benchmarks.
A comprehensive analysis of off-state stress in drain extended PMOS transistors: Theory and characterization of parametric degradation and dielectric failure

In this paper, we provide the first systematic and comprehensive analysis of off-state degradation in Drain-Extended PMOS transistors - an enabling input/output (I/O) component in many systems and a prototypical example of devices with correlated degradation (i.e., hot carrier damage leading to gate dielectric failure). We use a wide range of characterization tools (e.g., Charge-pumping and multi-frequency charge pumping to probe damage generation, IDLIN measurement for parametric degradation, current-ratio technique to locate breakdown spot, etc.) along with broad range of computational models (e.g., process, device, Monte Carlo models for hot-carrier profiling, asymmetric percolation for failure statistics, etc.) to carefully and systematically map the spatial and temporal dynamics of correlated trap generation in DePMOS transistors. Our key finding is that, despite the apparent complexity and randomness of the trap-generation process, appropriate scaling shows that the mechanics of trap generation is inherently universal. We use the universality to understand the parametric degradation and TDDB of DePMOS transistors and to perform lifetime projections from stress to operating conditions.