nils-herrmann/clean_scirepeval huggingface dataset:
Physical examination tests of the shoulder: a systematic review with meta-analysis of individual tests.

To compile and critique research on the diagnostic accuracy of individual orthopaedic physical examination tests in a manner that would allow clinicians to judge whether these tests are valuable to their practice.



A computer-assisted literature search of MEDLINE, CINAHL, and SPORTDiscus databases (1966 to October 2006) using keywords related to diagnostic accuracy of physical examination tests of the shoulder. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool was used to critique the quality of each paper. Meta-analysis through meta-regression of the diagnostic odds ratio (DOR) was performed on the Neer test for impingement, the Hawkins-Kennedy test for impingement, and the Speed test for superior labral pathology.



Forty-five studies were critiqued with only half demonstrating acceptable high quality and only two having adequate sample size. For impingement, the meta-analysis revealed that the pooled sensitivity and specificity for the Neer test was 79% and 53%, respectively, and for the Hawkins-Kennedy test was 79% and 59%, respectively. For superior labral (SLAP) tears, the summary sensitivity and specificity of the Speed test was 32% and 61%, respectively. Regarding orthopaedic special tests (OSTs) where meta-analysis was not possible either due to lack of sufficient studies or heterogeneity between studies, the list that demonstrates both high sensitivity and high specificity is short: hornblowers's sign and the external rotation lag sign for tears of the rotator cuff, biceps load II for superior labral anterior to posterior (SLAP) lesions, and apprehension, relocation and anterior release for anterior instability. Even these tests have been under-studied or are from lower quality studies or both. No tests for impingement or acromioclavicular (AC) joint pathology demonstrated significant diagnostic accuracy.



Based on pooled data, the diagnostic accuracy of the Neer test for impingement, the Hawkins-Kennedy test for impingement and the Speed test for labral pathology is limited. There is a great need for large, prospective, well-designed studies that examine the diagnostic accuracy of the numerous physical examination tests of the shoulder. Currently, almost without exception, there is a lack of clarity with regard to whether common OSTs used in clinical examination are useful in differentially diagnosing pathologies of the shoulder.
Mitigating DoS Attacks Against Pseudonymous Authentication Through Puzzle-Based Co-Authentication in 5G-VANET

The upcoming Fifth Generation (5G) networks can provide ultra-reliable ultra-low latency vehicle-to-everything for vehicular ad hoc networks (VANET) to promote road safety, traffic management, information dissemination, and automatic driving for drivers and passengers. However, 5G-VANET also attracts tremendous security and privacy concerns. Although several pseudonymous authentication schemes have been proposed for VANET, the expensive cost for their initial authentication may cause serious denial of service (DoS) attacks, which furthermore enables to do great harm to real space via VANET. Motivated by this, a puzzle-based co-authentication (PCA) scheme is proposed here. In the PCA scheme, the Hash puzzle is carefully designed to mitigate DoS attacks against the pseudonymous authentication process, which is facilitated through collaborative verification. The effectiveness and efficiency of the proposed scheme is approved by performance analysis based on theory and experimental results.
Aspect-Based Sentiment Analysis Using Convolutional Neural Network and Bidirectional Long Short-Term Memory

In order to improve performance of previous aspect-based sentiment analysis (ABSA) on restaurant reviews in Indonesian language, this paper adapts the research achieving the highest F1 at SemEval 2016. We use feedforward neural network with one-vs-all strategy for aspect category classification (Slot 1), Conditional Random Field (CRF) for opinion target expression extraction (Slot 2), and Convolutional Neural Network (CNN) for sentiment polarity classification (Slot 3). Aside from lexical features we also use additional features learned from neural networks. We train our model on 992 sentences and evaluate them on 382 sentences. Higher performances are achieved for Slot 1 (F1 0.870) and Slot 3 (F1 0.764) but lower on Slot 2 (F1 0.787).
A Single-Phase Asymmetrical T-Type Five-Level Transformerless PV Inverter

This paper presents a transformerless single-phase inverter topology based on a modified H-bridge-based multilevel converter. The topology comprises two legs, namely, a usual two-level leg and a T-type leg. The latter is based on a usual two-level leg, which has been modified to gain access to the midpoint of the split dc-link by means of a bidirectional switch. The topology is referred as an asymmetrical T-type five-level (5L-T-AHB) inverter. An ad hoc modulation strategy based on sinusoidal pulsewidth modulation is also presented to control the 5L-T-AHB inverter, where the two-level leg is commuted at fundamental frequency. Numerical and experimental results show that the proposed 5L-T-AHB inverter achieves high efficiency, exhibits reduced leakage currents, and complies with the transformerless norms and regulations, which makes it suitable for the transformerless PV inverters market.11This updated version includes experimental evidence, considerations for practical implementation, efficiency studies, visualization of semiconductor losses distribution, a deeper and corrected common mode analysis, and an improved notation among other modifications.
Optimal Choice of Parameters for Firefly Algorithm

The firefly algorithm (FA) is a novel metaheuristic algorithm inspired by the social behavior of fireflies and the phenomenon of bioluminescent communication. The effects of the major parameters on FA were systematically investigated based on some benchmark functions. The step size factor, absorption coefficient and population size all have significant impact on the performance of FA. The absorption coefficient and step size factor have optimal values in practical application, and improper choice of these factors will lead to bad results. Increasing population size can improve the solution quality, although the computing time will be longer. In this paper, the characteristics of FA parameters are discribed and guidelines for determining parameter values are given.
Peer-to-Peer Accommodation Rentals : Text Analytics of Consumer Reviews in Portland , Oregon

Peer-to-peer (P2P) accommodation rentals continue to grow at a phenomenal rate. Examining how this business model affects the competitive landscape of accommodation services is of strategic importance to hotels and tourism destinations. This study explores the competitive edge of P2P accommodation in comparison to hotels by extracting key content and themes from online reviews to explain the key service attributes sought by guests. The results from text analytics using terminology extraction and word co-occurrence networks indicate that even though guests expect similar core services such as clean rooms and comfortable beds, different attributes support the competitive advantage of hotels and P2P rentals. While conveniences offered by hotels are unparalleled by P2P accommodation, the latter appeal to consumers driven by experiential and social motivations. Managerial implications for hotels and P2P accommodation
A 51.3-MHz 21.8-ppm/°C CMOS Relaxation Oscillator With Temperature Compensation

A 51.3-MHz 18-<inline-formula><tex-math notation="LaTeX">$\mu\text{W}$</tex-math></inline-formula> 21.8-ppm/°C relaxation oscillator is presented in 90-nm CMOS. The proposed oscillator employs an integrated error feedback and composite resistors to minimize its sensitivity to temperature variations. For a temperature range from −20 °C to 100 °C, the fabricated circuit demonstrates a frequency variation less than ±0.13%, leading to an average frequency drift of 21.8 ppm/°C. As the supply voltage changes from 0.8 to 1.2 V, the frequency variation is ±0.53%. The measured rms jitter and phase noise at 1-MHz offset are 89.27 ps and −83.29 dBc/Hz, respectively.
Application of UAV and Low Power Wide Area Communication Technology for Monitoring of River Water Quality

Pollution has been recognized as the major threat to sustainability of river in Malaysia. Some of the limitations of existing methods for river monitoring are cost of deployment, non-real-time monitoring, and low resolution both in time and space. To overcome these limitations, a smart river monitoring solution is proposed for river water quality in Malaysia. The proposed method incorporates unmanned aerial vehicle (UAV), internet of things (IoT), low power wide area (LPWA) and data analytic (DA). A setup of the proposed method and preliminary results are presented. The proposed method is expected to deliver an efficient and real-time solution for river monitoring in Malaysia.
Hypoglycemic Potential of Aqueous Extract of Moringa oleifera Leaf and In Vivo GC-MS Metabolomics

Moringa oleifera Lam. (family; Moringaceae), commonly known as drumstick, have been used for centuries as a part of the Ayurvedic system for several diseases without having any scientific data. Demineralized water was used to prepare aqueous extract by maceration for 24 h and complete metabolic profiling was performed using GC-MS and HPLC. Hypoglycemic properties of extract have been tested on carbohydrate digesting enzyme activity, yeast cell uptake, muscle glucose uptake, and intestinal glucose absorption. Type 2 diabetes was induced by feeding high-fat diet (HFD) for 8 weeks and a single injection of streptozotocin (STZ, 45 mg/kg body weight, intraperitoneally) was used for the induction of type 1 diabetes. Aqueous extract of M. oleifera leaf was given orally at a dose of 100 mg/kg to STZ-induced rats and 200 mg/kg in HFD mice for 3 weeks after diabetes induction. Aqueous extract remarkably inhibited the activity of α-amylase and α-glucosidase and it displayed improved antioxidant capacity, glucose tolerance and rate of glucose uptake in yeast cell. In STZ-induced diabetic rats, it produces a maximum fall up to 47.86% in acute effect whereas, in chronic effect, it was 44.5% as compared to control. The fasting blood glucose, lipid profile, liver marker enzyme level were significantly (p < 0.05) restored in both HFD and STZ experimental model. Multivariate principal component analysis on polar and lipophilic metabolites revealed clear distinctions in the metabolite pattern in extract and in blood after its oral administration. Thus, the aqueous extract can be used as phytopharmaceuticals for the management of diabetes by using as adjuvants or alone.
SSVM: a simple SVM algorithm

We present a fast iterative algorithm for identifying the Support Vectors of a given set of points. Our algorithm works by maintaining a candidate Support Vector set. It uses a greedy approach to pick points for inclusion in the candidate set. When the addition of a point to the candidate set is blocked because of other points already present in the set we use a backtracking approach to prune away such points. To speed up convergence we initialize our algorithm with the nearest pair of points from opposite classes. We then use an optimization based approach to increment or prune the candidate Support Vector set. The algorithm makes repeated passes over the data to satisfy the KKT constraints. The memory requirements of our algorithm scale as O(|S|) in the average case, where|S| is the size of the Support Vector set. We show that the algorithm is extremely competitive as compared to other conventional iterative algorithms like SMO and the NPA. We present results on a variety of real life datasets to validate our claims.
Euclidean Voronoi diagram of 3D balls and its computation via tracing edges

Despite its important applications in various disciplines in science and engineering, the Euclidean Voronoi diagram for spheres, also known as an additively weighted Voronoi diagram, in 3D space has not been studied as much as it deserves. In this paper, we present an algorithm to compute the Euclidean Voronoi diagram for 3D spheres with different radii. The presented algorithm follows Voronoi edges one by one until the construction is completed in O(mn) time in the worst-case, where m is the number of edges in the Voronoi diagram and n is the number of spherical balls. As building blocks, we show that Voronoi edges are conics that can be precisely represented as rational quadratic Bézier curves. We also discuss how to conveniently represent and process Voronoi faces which are hyperboloids of two sheets. q 2005
Prostitution and Human Trafficking : A model-based exploration and policy analysis

The meeting of the oldest profession with modern slavery is the topic of this paper. After a brief introduction to prostitution and prostitution-related human trafficking, this paper focuses on the Dutch policy debate. A System Dynamics simulation model related to the Dutch situation developed to explore and provide insights related to the effects of proposed policies is presented in this paper. Using the simulation model, a ‘quick and dirty’ policy analysis is first of all performed, and preliminary conclusions are drawn. These preliminary conclusions are further tested under uncertainty, using two different but relatively similar simulation models. The main conclusions are that demand side measures are necessary, but not sufficient. The topic is so complex and uncertain that simple (combinations of) basic policies will not hold in all circumstances, which is why this topic requires further exploration and policy testing under deep uncertainty.
Exploiting Spatial Relationship between Scenes for Hierarchical Video Geotagging

Predicting the location of a video based on its content is a very meaningful, yet very challenging problem. Most existing work has focused on developing representative visual features and then searching for visually nearest neighbors in the development set to achieve a prediction. Interestingly, the relationship between scenes has been overlooked in prior work. Two scenes that are visually different, but frequently co-occur in same location, should naturally be considered similar for the geotagging problem. To build upon the above ideas, we propose to model the geo-spatial distributions of scenes by Gaussian Mixture Models (GMMs) and measure the distribution similarity by the Jensen-Shannon divergence (JSD). Subsequently, we present the Spatial Relationship Model (SRM) for geotagging which integrates the geo-spatial relationship of scenes into a hierarchical framework. We segment the Earth's surface into multiple levels of grids and measure the likelihood of input videos with an adaptation to region granularities. We have evaluated our approach using the YFCC100M dataset in the context of the MediaEval 2014 placing task. The total set of 35,000 geotagged videos is further divided into a training set of 25,000 videos and a test set of 10,000 videos. Our experimental results demonstrate the effectiveness of our proposed framework, as our solution achieves good accuracy and outperforms existing visual approaches for video geotagging.
Evolution of high-speed operational amplifier architectures

Strengths and weaknesses of modern widebandwidth bipolar transistor operational amplifiers are investigated and compared with respect to bandwidth, slew rate, noise, distortion, and power. This paper traces the evolution of operational amplifier designs since vacuum tube days to give a perspective of the large number of circuit variations used over time. Of particular value is the ability to use many of these circuit design options as the basis of new amplifiers. In addition, an array of operational amplifier components fabricated on the AT&T CBIC V2  process is described. This design incorporates many of the architectural techniques that Vin have evolved over the years to produce four separate operational amplifier on a single base wafer. The process design methodology requires identifying the common elements in each architecture and the minimum number of additional components required to implement four unique architectures on the array.
WR-3 Waveguide Bandpass Filters Fabricated Using High Precision CNC Machining and SU-8 Photoresist Technology

This paper presents two WR-3 band (220–325 GHz) filters, one fabricated in metal using high precision computer numerically controlled milling and the other made with metallized SU-8 photoresist technology. Both are based on three coupled resonators, and are designed for a 287.3–295.9-GHz passband, and a 30-dB rejection between 317.7 and 325.9 GHz. The first filter is an extracted pole filter coupled by irises, and is precision milled using the split-block approach. The second filter is composed of three silver-coated SU-8 layers, each 432 μm thick. The filter structures are specially chosen to take advantage of the fabrication processes. When fabrication tolerances are accounted for, very good agreement between measurements and simulations are obtained, with median passband insertion losses of 0.41 and 0.45 dB for the metal and SU-8 devices, respectively. These two filters are potential replacements of frequency selective surface filters used in heterodyne radiometers for unwanted sideband rejection.
Robust Single-Image Super-Resolution Based on Adaptive Edge-Preserving Smoothing Regularization

Single-image super-resolution (SR) reconstruction via sparse representation has recently attracted broad interest. It is known that a low-resolution (LR) image is susceptible to noise or blur due to the degradation of the observed image, which would lead to a poor SR performance. In this paper, we propose a novel robust edge-preserving smoothing SR (REPS-SR) method in the framework of sparse representation. An EPS regularization term is designed based on gradient-domain-guided filtering to preserve image edges and reduce noise in the reconstructed image. Furthermore, a smoothing-aware factor adaptively determined by the estimation of the noise level of LR images without manual interference is presented to obtain an optimal balance between the data fidelity term and the proposed EPS regularization term. An iterative shrinkage algorithm is used to obtain the SR image results for LR images. The proposed adaptive smoothing-aware scheme makes our method robust to different levels of noise. Experimental results indicate that the proposed method can preserve image edges and reduce noise and outperforms the current state-of-the-art methods for noisy images.
On the State of the Art of Evaluation in Neural Language Models

Ongoing innovations in recurrent neural network architectures have provided a steady influx of apparently state-of-the-art results on language modelling benchmarks. However, these have been evaluated using differing codebases and limited computational resources, which represent uncontrolled sources of experimental variation. We reevaluate several popular architectures and regularisation methods with large-scale automatic black-box hyperparameter tuning and arrive at the somewhat surprising conclusion that standard LSTM architectures, when properly regularised, outperform more recent models. We establish a new state of the art on the Penn Treebank and Wikitext-2 corpora, as well as strong baselines on the Hutter Prize dataset.
Optimal Design of an Axial Flux Permanent Magnet Synchronous Motor for the Electric Bicycle

Design of an electric machine such as the axial flux permanent magnet synchronous motor (AFPMSM) requires a 3-D finite-element method (FEM) analysis. The AFPMSM with a 3-D FEM model involves too much time and effort to analyze. To deal with this problem, we apply a surrogate assisted multi-objective optimization (SAMOO) algorithm that can realize an accurate and well-distributed Pareto front set with a few number of function calls, and considers various design variables in the motor design process. The superior performance of the SAMOO is verified by comparing it with conventional multi-objective optimization algorithms in a test function. Finally, the optimal design result of the AFPMSM for the electric bicycle is obtained by using the SAMOO algorithm.
Towards Dialogue-Based Navigation with Multivariate Adaptation Driven by Intention and Politeness for Social Robots

Service robots need to show appropriate social behaviour in order to be deployed in social environments such as healthcare, education, retail, etc. Some of the main capabilities that robots should have are navigation and conversational skills. If the person is impatient, the person might want a robot to navigate faster and vice versa. Linguistic features that indicate politeness can provide social cues about a person’s patient and impatient behaviour. The novelty presented in this paper is to dynamically incorporate politeness in robotic dialogue systems for navigation. Understanding the politeness in users’ speech can be used to modulate the robot behaviour and responses. Therefore, we developed a dialogue system to navigate in an indoor environment, which produces different robot behaviours and responses based on users’ intention and degree of politeness. We deploy and test our system with the Pepper robot that adapts to the changes in user’s politeness.
Healthy youth development as a model for youth health promotion. A review.

Risk and resilience as a conceptual model has captured the imagination of researchers and program planners over the past decade. The concept assumes that stress is a universal experience; success in life is less determined by the stress experienced and more related to the resources available to address the stress. Likewise, it assumes that negative life events are not rare experiences; neither do such experiences inexorably lead to a life of deprivation. Rather, resiliency research questions why some who are reared under adverse circumstances appear to live healthy and productive lives while others do not appear to overcome the adversities experienced in early life. Garmezy (1) defined resilience as “the capacity to recover and maintain adaptive behavior after insult.” Those who are resilient are flexible. They are not invincible (2) or invulnerable (3). Resilience is not a trait (4) that some have and others do not; rather, it represents an interaction between the individual and the environment. Resilience implies resistance to threat, but it is a graded phenomenon. Cumulative risk can defeat the most resilient individual. Rutter (4) noted that resilience is interactive with risk; it is developmental in nature, stemming from biology and experiences earlier in life and protective factors may operate in different ways at different stages of development (e.g., parental protectiveness in infancy is highly protective, but in adolescence comparable parental oversight may impede healthy development).