nils-herrmann/clean_scirepeval huggingface dataset:
Short-term effects of high-intensity laser therapy versus ultrasound therapy in the treatment of people with subacromial impingement syndrome: a randomized clinical trial.

Subacromial impingement syndrome (SAIS) is a painful condition resulting from the entrapment of anatomical structures between the anteroinferior corner of the acromion and the greater tuberosity of the humerus.



The aim of this study was to evaluate the short-term effectiveness of high-intensity laser therapy (HILT) versus ultrasound (US) therapy in the treatment of SAIS.



The study was designed as a randomized clinical trial.



The study was conducted in a university hospital.



Seventy patients with SAIS were randomly assigned to a HILT group or a US therapy group.



Study participants received 10 treatment sessions of HILT or US therapy over a period of 2 consecutive weeks.



Outcome measures were the Constant-Murley Scale (CMS), a visual analog scale (VAS), and the Simple Shoulder Test (SST).



For the 70 study participants (42 women and 28 men; mean [SD] age=54.1 years [9.0]; mean [SD] VAS score at baseline=6.4 [1.7]), there were no between-group differences at baseline in VAS, CMS, and SST scores. At the end of the 2-week intervention, participants in the HILT group showed a significantly greater decrease in pain than participants in the US therapy group. Statistically significant differences in change in pain, articular movement, functionality, and muscle strength (force-generating capacity) (VAS, CMS, and SST scores) were observed after 10 treatment sessions from the baseline for participants in the HILT group compared with participants in the US therapy group. In particular, only the difference in change of VAS score between groups (1.65 points) surpassed the accepted minimal clinically important difference for this tool.



This study was limited by sample size, lack of a control or placebo group, and follow-up period.



Participants diagnosed with SAIS showed greater reduction in pain and improvement in articular movement functionality and muscle strength of the affected shoulder after 10 treatment sessions of HILT than did participants receiving US therapy over a period of 2 consecutive weeks.
Global network alignment using multiscale spectral signatures

Protein interaction networks provide an important system-level view of biological processes. One of the fundamental problems in biological network analysis is the global alignment of a pair of networks, which puts the proteins of one network into correspondence with the proteins of another network in a manner that conserves their interactions while respecting other evidence of their homology. By providing a mapping between the networks of different species, alignments can be used to inform hypotheses about the functions of unannotated proteins, the existence of unobserved interactions, the evolutionary divergence between the two species and the evolution of complexes and pathways.



We introduce GHOST, a global pairwise network aligner that uses a novel spectral signature to measure topological similarity between subnetworks. It combines a seed-and-extend global alignment phase with a local search procedure and exceeds state-of-the-art performance on several network alignment tasks. We show that the spectral signature used by GHOST is highly discriminative, whereas the alignments it produces are also robust to experimental noise. When compared with other recent approaches, we find that GHOST is able to recover larger and more biologically significant, shared subnetworks between species.


AVAILABILITY
An efficient and parallelized implementation of GHOST, released under the Apache 2.0 license, is available at http://cbcb.umd.edu/kingsford_group/ghost
Scrutinizing Immutability: Research on Sexual Orientation and U.S. Legal Advocacy for Sexual Minorities.

We review scientific research and legal authorities to argue that the immutability of sexual orientation should no longer be invoked as a foundation for the rights of individuals with same-sex attractions and relationships (i.e., sexual minorities). On the basis of scientific research as well as U.S. legal rulings regarding lesbian, gay, and bisexual (LGB) rights, we make three claims: First, arguments based on the immutability of sexual orientation are unscientific, given what we now know from longitudinal, population-based studies of naturally occurring changes in the same-sex attractions of some individuals over time. Second, arguments based on the immutability of sexual orientation are unnecessary, in light of U.S. legal decisions in which courts have used grounds other than immutability to protect the rights of sexual minorities. Third, arguments about the immutability of sexual orientation are unjust, because they imply that same-sex attractions are inferior to other-sex attractions, and because they privilege sexual minorities who experience their sexuality as fixed over those who experience their sexuality as fluid. We conclude that the legal rights of individuals with same-sex attractions and relationships should not be framed as if they depend on a certain pattern of scientific findings regarding sexual orientation.
Faster SGD training by minibatch persistency

It is well known that, for most datasets, the use of large-size minibatches for Stochastic Gradient Descent (SGD) typically leads to slow convergence and poor generalization. On the other hand, large minibatches are of great practical interest as they allow for a better exploitation of modern GPUs. Previous literature on the subject concentrated on how to adjust the main SGD parameters (in particular, the learning rate) when using large minibatches. In this work we introduce an additional feature, that we call minibatch persistency, that consists in reusing the same minibatch for K consecutive SGD iterations. The computational conjecture here is that a large minibatch contains a significant sample of the training set, so one can afford to slightly overfitting it without worsening generalization too much. The approach is intended to speedup SGD convergence, and also has the advantage of reducing the overhead related to data loading on the internal GPU memory. We present computational results on CIFAR-10 with an AlexNet architecture, showing that even small persistency values (K = 2 or 5) already lead to a significantly faster convergence and to a comparable (or even better) generalization than the standard “disposable minibatch” approach (K = 1), in particular when large minibatches are used. The lesson learned is that minibatch persistency can be a simple yet effective way to deal with large minibatches.
Webcam-based Eye Gaze Tracking under Natural Head Movement

The estimation of the human’s point of visual gaze is important for many applications. This information can be used in visual gaze based human-computer interaction, advertisement, human cognitive state analysis, attentive interfaces, human behavior analysis. Visual gaze direction can also provide high-level semantic cues such as who is speaking to whom, information on non-verbal communication and the mental state/attention of a human (e.g., a driver). Overall, the visual gaze direction is important to understand the human’s attention, motivation and intention. There is a tremendous amount of research concerned with the estimation of the point of visual gaze first attempts can be traced back 1989. Many visual gaze trackers are offered to this date, although they all share the same drawbacks either they are highly intrusive (head mounted systems, electro-ocolography methods, sclera search coil methods), either they restrict the user to keep his/her head as static as possible (PCCR methods, neural network methods, ellipse fitting methods) or they rely on expensive and sophisticated hardware and prior knowledge in order to grant the freedom of natural head movement to the user (stereo vision methods, 3D eye modeling methods). Furthermore, all proposed visual gaze trackers require an user specific calibration procedure that can be uncomfortable and erroneous, leading to a negative impact on the accuracy of the tracker. Although, some of these trackers achieve extremely high accuracy, they lack of simplicity and can not be efficiently used in everyday life. This manuscript investigates and proposes a visual gaze tracker that tackles the problem using only an ordinary web camera and no prior knowledge in any sense (scene set-up, camera intrinsic and/or extrinsic parameters). The tracker we propose is based on the observation that our desire to grant the freedom of natural head movement to the user requires 3D modeling of the scene set-up. Although, using a single low resolution web camera bounds us in dimensions (no depth can be recovered), we propose ways to cope with this drawback and model the scene in front of the user. We tackle this three-dimensional problem by
Bilious vomiting in the newborn: rapid diagnosis of intestinal obstruction.

Bilious vomiting in newborns is an urgent condition that requires the immediate involvement of a team of pediatric surgeons and neonatologists for perioperative management. However, initial detection, evaluation and treatment are often performed by nurses, family physicians and general pediatricians. Bilious vomiting, with or without abdominal distention, is an initial sign of intestinal obstruction in newborns. A naso- or orogastric tube should be placed immediately to decompress the stomach. Physical examination should be followed by plain abdominal films. Dilated bowel loops and air-fluid levels suggest surgical obstruction. Contrast radiography may be required. Duodenal atresia, midgut malrotation and volvulus, jejunoileal atresia, meconium ileus and necrotizing enterocolitis are the most common causes of neonatal intestinal obstruction.
Generating Nontrivial Melodies for Music as a Service

We present a hybrid neural network and rule-based system that generates pop music. Music produced by pure rule-based systems often sounds mechanical. Music produced by machine learning sounds better, but still lacks hierarchical temporal structure. We restore temporal hierarchy by augmenting machine learning with a temporal production grammar, which generates the music’s overall structure and chord progressions. A compatible melody is then generated by a conditional variational recurrent autoencoder. The autoencoder is trained with eight-measure segments from a corpus of 10,000 MIDI files, each of which has had its melody track and chord progressions identified heuristically. The autoencoder maps melody into a multi-dimensional feature space, conditioned by the underlying chord progression. A melody is then generated by feeding a random sample from that space to the autoencoder’s decoder, along with the chord progression generated by the grammar. The autoencoder can make musically plausible variations on an existing melody, suitable for recurring motifs. It can also reharmonize a melody to a new chord progression, keeping the rhythm and contour. The generated music compares favorably with that generated by other academic and commercial software designed for the music-as-a-service industry.
A Component-based Simulator for MIPS32 Processors

Processor concepts, implementation details, and performance analysis are fundamental in computer architecture education, and MIPS (microprocessor without interlocked pipeline stages) processor designs are used by many universities in teaching the subject. In this paper we present a MIPS32 processor simulator, which enriches students’ learning and instructors’ teaching experiences. A family of single-cycle, multi-cycle, and pipeline processor models for the MIPS32 architecture are developed according to the parallel Discrete Event System Specification (DEVS) modeling formalism. A collection of elementary sequential and combinational model components along with the processor models are implemented in DEVS-Suite. The simulator supports multi-level model abstractions, register-transfer level animation, performance data collection, and time-based trajectory observation. These features, which are partially supported by a few existing simulators, enable important structural and behavioral details of computer architectures to be described and understood. The MIPS processor models can be reused and systematically extended for modeling and simulating other MIPS processors.
ERM proteins and merlin: integrators at the cell cortex

A fundamental property of many plasma-membrane proteins is their association with the underlying cytoskeleton to determine cell shape, and to participate in adhesion, motility and other plasma-membrane processes, including endocytosis and exocytosis. The ezrin–radixin–moesin (ERM) proteins are crucial components that provide a regulated linkage between membrane proteins and the cortical cytoskeleton, and also participate in signal-transduction pathways. The closely related tumour suppressor merlin shares many properties with ERM proteins, yet also provides a distinct and essential function.
Time series forecasting by recurrent product unit neural networks

Time series forecasting (TSF) consists on estimating models to predict future values based on previously observed values of time series, and it can be applied to solve many real-world problems. TSF has been traditionally tackled by considering autoregressive neural networks (ARNNs) or recurrent neural networks (RNNs), where hidden nodes are usually configured using additive activation functions, such as sigmoidal functions. ARNNs are based on a short-term memory of the time series in the form of lagged time series values used as inputs, while RNNs include a long-term memory structure. The objective of this paper is twofold. First, it explores the potential of multiplicative nodes for ARNNs, by considering product unit (PU) activation functions, motivated by the fact that PUs are specially useful for modelling highly correlated features, such as the lagged time series values used as inputs for ARNNs. Second, it proposes a new hybrid RNN model based on PUs, by estimating the PU outputs from the combination of a long-term reservoir and the short-term lagged time series values. A complete set of experiments with 29 data sets shows competitive performance for both model proposals, and a set of statistical tests confirms that they achieve the state of the art in TSF, with specially promising results for the proposed hybrid RNN. The experiments in this paper show that the recurrent model is very competitive for relatively large time series, where longer forecast horizons are required, while the autoregressive model is a good selection if the data set is small or if a low computational cost is needed.
Photovoltaic DC Arc Fault Detector testing at Sandia National Laboratories

The 2011 National Electrical Code® (NEC®) added Article 690.11 that requires photovoltaic (PV) systems on or penetrating a building to include a listed DC arc fault protection device. To fill this new market, manufacturers are developing new Arc Fault Circuit Interrupters (AFCIs). Comprehensive and challenging testing has been conducted using a wide range of PV technologies, system topologies, loads and noise sources. The Distributed Energy Technologies Laboratory (DETL) at Sandia National Laboratories (SNL) has used multiple reconfigurable arrays with a variety of module technologies, inverters, and balance of system (BOS) components to characterize new Photovoltaic (PV) DC AFCIs and Arc Fault Detectors (AFDs). The device's detection capabilities, characteristics and nuisance tripping avoidance were the primary purpose of the testing. SNL and Eaton Corporation collaborated to test an Eaton AFD prototype and quantify arc noise for a wide range of PV array configurations and the system responses. The tests were conducted by generating controlled, series PV arc faults between PV modules. Arc fault detection studies were performed on systems using aged modules, positive- and negative-grounded arrays, DC/DC converters, 3-phase inverters, and on strings with branch connectors. The tests were conducted to determine if nuisance trips would occur in systems using electrically noisy inverters, with series arc faults on parallel strings, and in systems with inverters performing anti-islanding and maximum power point tracking (MPPT) algorithms. The tests reported herein used the arc fault detection device to indicate when the trip signal was sent to the circuit interrupter. Results show significant noise is injected into the array from the inverter but AFCI functionality of the device was generally stable. The relative locations of the arc fault and detector had little influence on arc fault detection. Lastly, detection of certain frequency bands successfully differentiated normal operational noise from an arc fault signal.
HiSPEED: a system for mining performance appraisal data and text

Performance appraisal (PA) is a crucial HR process that enables an organization to periodically measure and evaluate every employee’s performance and also to drive performance improvements. In this paper, we describe a novel system called HiSPEED to analyze PA data using automated statistical, data mining and text mining techniques, to generate novel and actionable insights/patterns and to help in improving the quality and effectiveness of the PA process. The goal is to produce insights that can be used to answer (in part) the crucial “business questions” that HR executives and business leadership face in talent management. The business questions pertain to (1) improving the quality of the goal setting process, (2) improving the quality of the self-appraisal comments and supervisor feedback comments, (3) discovering high-quality supervisor suggestions for performance improvements, (4) discovering evidence provided by employees to support their self-assessments, (5) measuring the quality of supervisor assessments, (6) understanding the root causes of poor and exceptional performances, (7) detecting instances of personal and systemic biases and so forth. The paper discusses specially designed algorithms to answer these business questions and illustrates them by reporting the insights produced on a real-life PA dataset from a large multinational IT services organization.
DOTA: Delay Bounded Optimal Cloudlet Deployment and User Association in WMANs

In the large-scale Wireless Metropolitan Area Network (WMAN) consisting of many wireless Access Points (APs),choosing the appropriate position to place cloudlet is very important for reducing the user's access delay. For service provider, it isalways very costly to deployment cloudlets. How many cloudletsshould be placed in a WMAN and how much resource eachcloudlet should have is very important for the service provider. In this paper, we study the cloudlet placement and resourceallocation problem in a large-scale Wireless WMAN, we formulatethe problem as an novel cloudlet placement problem that givenan average access delay between mobile users and the cloudlets, place K cloudlets to some strategic locations in the WMAN withthe objective to minimize the number of use cloudlet K. Wethen propose an exact solution to the problem by formulatingit as an Integer Linear Programming (ILP). Due to the poorscalability of the ILP, we devise a clustering algorithm K-Medoids(KM) for the problem. For a special case of the problem whereall cloudlets computing capabilities have been given, we proposean efficient heuristic for it. We finally evaluate the performanceof the proposed algorithms through experimental simulations. Simulation result demonstrates that the proposed algorithms areeffective.
Unilateral posterior crossbite with mandibular shift: a review.

Based on this literature review, early orthodontic treatment of unilateral posterior crossbites with mandibular shifts is recommended. Treatment success is high if it is started early. Evidence that crossbites are not self-correcting, have some association with temporomandibular disorders and cause skeletal, dental and muscle adaptation provides further rationale for early treatment. It can be difficult to treat unilateral crossbites in adults without a combination of orthodontics and surgery. The most appropriate timing of treatment occurs when the patient is in the late deciduous or early mixed dentition stage as expansion modalities are very successful in this age group and permanent incisors are given more space as a result of the expansion. Treatment of unilateral posterior crossbites generally involves symmetric expansion of the maxillary arch, removal of selective occlusal interferences and elimination of the mandibular functional shift. The general practitioner and pediatric dentist must be able to diagnose unilateral posterior crossbites successfully and provide treatment or referral to take advantage of the benefits of early treatment.
The Synthesis of Complex Audio Spectra by Means of Frequency Modulation

.  Of interest in both acoustical re-search and electronic music is the synthesis of natural sound. For the researcher, it is the ultimate test of acoustical theory, while for the composer of electronic music it is an extraordinarily rich point of departure in the domain of timbre, or tone quality. The synthesis of natural sounds has been elusive; however, recent research in computer analysis and synthesis of some tones of musical instruments has yielded an insight which may prove to have general relevance in all natural sounds: the character of the temporal evolution of the spectral components is of critical importance in the determination of timbre. In natural sounds the amplitudes of the frequency components of the spectrum are time-variant, or dynamic. The energy of the components often evolves in complicated ways, in particular, during the attack and decay portions of the sound. The temporal evolution of the spectrum is in some cases easily followed as with bells, whereas in other cases not, because the evolution occurs in a very short time period, but it is nevertheless perceived and is an important cue in the recognition of timbre. Many natural sounds seem to have characteristic spectral evolutions that, in addition to providing their "signature," are largely responsible for what we judge to be their lively quality. In contrast, it is largely the fixed proportion spectrum of most synthesized sounds that so readily imparts to the listener the electronic cue and lifeless quality. The special application of the equation for frequency modulation, described below, allows the production of complex spectra with very great simplicity. The fact that the temporal evolution of the frequency components of the spectrum can be easily controlled is perhaps the most striking attribute of the technique, for dynamic spectra are achieved only with considerable difficulty using current techniques of synthesis. At the end of this paper some simulations of brass, woodwind, and percussive sounds are given. The importance of these simulations is as much in their elegance and simplicity as it is in their accuracy. This frequency modulation technique, although not a physical model for natural sound, is shown to be a very powerful perceptual model for at least some. FREQUENCY MODULATION Frequency modulation (FM) is well understood as applied in radio transmission, but the relevant equations have not been applied in any significant way to the generation of audio spectra where both the carrier and the modulating frequencies are in the audio band and the side frequencies form the spectrum directly. In FM, the instantaneous frequency of a carrier wave is varied according to a modulating wave, such that the rate at which the carrier varies is the frequency of the modulating wave, or modulating frequency. The amount the carrier varies around its average, or peak frequency deviation, is proportional to the amplitude of the modulating wave. The parameters of a frequency-modulated signal are