nils-herrmann/clean_scirepeval huggingface dataset:
Neurodynamic Techniques Versus "Sham" Therapy in the Treatment of Carpal Tunnel Syndrome: A Randomized Placebo-Controlled Trial.

To evaluate the efficacy of neurodynamic techniques used as the sole therapeutic component compared with sham therapy in the treatment of mild and moderate carpal tunnel syndromes (CTS).



Single-blinded, randomized placebo-controlled trial.



Several medical clinics.



Volunteer sample of patients (N=250) diagnosed with CTS (n=150).



Neurodynamic techniques were used in the neurodynamic techniques group, and sham therapy was used in the sham therapy group. In the neurodynamic techniques group, neurodynamic sequences were used, and sliding and tension techniques were also used. In the sham therapy group, no neurodynamic sequences were used, and therapeutic procedures were performed in an intermediate position. Therapy was conducted twice weekly for a total of 20 therapy sessions.



Symptom severity (symptom severity scale) and functional status (functional status scale) of the Boston Carpal Tunnel Questionnaire.



A baseline assessment revealed no intergroup differences in all examined parameters (P>.05). After therapy, there was statistically significant intragroup improvement in nerve conduction study (sensory and motor conduction velocity and motor latency) only for the neurodynamic techniques group (P<.01). After therapy, intragroup statistically significant changes also occurred for the neurodynamic techniques group in pain assessment, 2-point discrimination sense, symptom severity scale, and functional status scale (in all cases P<.01). There were no group differences in assessment of grip and pinch strength (P>.05).



The use of neurodynamic techniques has a better therapeutic effect than sham therapy in the treatment of mild and moderate forms of CTS.
How do APIs evolve? A story of refactoring

Frameworks and libraries change their APIs. Migrating an application to the new API is tedious and disrupts the development process. Although some tools and ideas have been proposed to solve the evolution of APIs, most updates are done manually. To better understand the requirements for migration tools, we studied the API changes of four frameworks and one library. We discovered that the changes that break existing applications are not random, but tend to fall into particular categories. Over 80% of these changes are refactorings. This suggests that refactoring-based migration tools should be used to update applications.
Biodegradable polymer needle with various tip angles and effect of vibration and surface tension on easy insertion

This paper proposes a fabrication method of microneedles with various tip angles made of biodegradable polymer (polylactic acid, referred to herein as PL A). It was confirmed by finite element method (FEM) simulation that stress concentration occurs more severely at the tip area, as the needle becomes thin, and tip angle becomes sharp. Masks for silicon cavities (negative dies for micromolding) with various tip angles are designed. The fabrication process involves etching a groove on the surface of a silicon die, molding the polymer into this groove, and then releasing it. The resistance force during inserting a fabricated needle to an artificial skin of silicone rubber was investigated. Effectiveness of sharp tip angle and thin shank for easy insertion is confirmed. Imitating mosquito's needle, the effectiveness of vibrating needle, and giving surface tension to object surface was also confirmed.
Harmony-based monarch butterfly optimization algorithm

Monarch butterfly optimization (MBO) is a new metaheuristic algorithm mimics the migration of butterflies from northern USA to Mexico. In MBO, there are mainly two processes. In the first process, the algorithm emulates how some of the butterflies move from the current position to the new position by the migration operator. In the latter process, the algorithm tunes the position of other butterflies by adjusting operator. In order to enhance the search ability of MBO, an innovation method called MBHS is introduced to tackle the optimization problem. In MBHS, the harmony search (HS) adds mutation operators to the process of adjusting operator to enhance the exploitation, exploration ability, and speed up the convergence rate of MBO. For the purpose to validate the performance of MBHS, 14 benchmark functions are used, and the performance is compared with well-known search algorithms. The experimental results demonstrate that MBHS performs better than the basic MBO and other algorithms.
Flow-Induced Inertial Steady Vector Field Topology

Traditionally, vector field visualization is concerned with 2D and 3D flows. Yet, many concepts can be extended to general dynamical systems, including the higher-dimensional problem of modeling the motion of finite-sized objects in fluids. In the steady case, the trajectories of these so-called inertial particles appear as tangent curves of a 4D or 6D vector field. These higher-dimensional flows are difficult to map to lower-dimensional spaces, which makes their visualization a challenging problem. We focus on vector field topology, which allows scientists to study asymptotic particle behavior. As recent work on the 2D case has shown, both extraction and classification of isolated critical points depend on the underlying particle model. In this paper, we aim for a model-independent classification technique, which we apply to two different particle models in not only 2D, but also 3D cases. We show that the classification can be done by performing an eigenanalysis of the spatial derivatives’ velocity subspace of the higher-dimensional 4D or 6D flow. We construct glyphs that depict not only the types of critical points, but also encode the directional information given by the eigenvectors. We show that the eigenvalues and eigenvectors of the inertial phase space have sufficient symmetries and structure so that they can be depicted in 2D or 3D, instead of 4D or 6D.
Key Issues in IS Management in Norway: An Empirical Study Based on Q Methodology

Information systems (IS) departments face many challenges in todays rapidly changing environment. One approach to understanding these challenges is to survey IS managers to elicit what they consider are key issues. Studies of key IS management issues have been conducted for some years in many nations and regions. However, most of these surveys lack a theoretical basis for the selection of key issues. Furthermore, most studies have used a single-round or a multi-round Delphi method. This chapter provides an overview of research approaches to key issues studies combined with key issues results from previous research. The chapter presents methodological issues and choices for a survey on key issues in IS management which was conducted in Norway. A three step procedure for key issues selection is introduced, and a Q-sort analysis is adopted. The chapter presents results from the Q-sort survey and analysis. The highest ranked key issue in Norway, according to the survey, is concerned with improving links between information systems strategy and business strategy.
Cross-cloud MapReduce for Big Data

MapReduce plays a critical role as a leading framework for big data analytics. In this paper, we consider a geodistributed cloud architecture that provides MapReduce services based on the big data collected from end users all over the world. Existing work handles MapReduce jobs by a traditional computation-centric approach that all input data distributed in multiple clouds are aggregated to a virtual cluster that resides in a single cloud. Its poor efficiency and high cost for big data support motivate us to propose a novel data-centric architecture with three key techniques, namely, cross-cloud virtual cluster, data-centric job placement, and network coding based traffic routing. Our design leads to an optimization framework with the objective of minimizing both computation and transmission cost for running a set of MapReduce jobs in geo-distributed clouds. We further design a parallel algorithm by decomposing the original large-scale problem into several distributively solvable subproblems that are coordinated by a high-level master problem. Finally, we conduct real-world experiments and extensive simulations to show that our proposal significantly outperforms the existing works.
Data Models in Database Management

It is a combination of three components: 1) a collection of data structure types (the building blocks of any database that conforms to the model);
 2) a collection of operators or inferencing rules, which can be applied to any valid instances of the data types listed in (1), to retrieve or derive data from any parts of those structures in any combinations desired;
 3) a collection of general integrity rules, which implicitly or explicitly define the set of consistent database states or changes of state or both—these rules may sometimes be expressed as insert-update-delete rules.
New diagnostics in forensic pathology

In forensic autopsies it is important to determine the age of early vital skin wounds as accurate as possible. In addition to inflammation, coagulation is also induced in vital wounds. Analysis of blood coagulation markers in wound hemorrhage could therefore be an important additional discriminating factor in wound age determination. The aim of this study was to develop a wound age probability scoring system, based on the immunohistochemical expression levels of Fibronectin, CD62p and Factor VIII in wound hemorrhage.  Tissue samples of (A) non injured control skin (n=383), and samples of mechanically induced skin injuries of known wound age, (B) injuries inflicted shortly before death (up to a few minutes old) (n=382), and (C) injuries inflicted 15-30 minutes before death (n=42) were obtained at autopsy in order to validate wound age estimation. Tissue slides were stained for Fibronectin, CD62p and Factor VIII and were subsequently scored for staining intensity (IHC score) in wound hemorrhage (1=minor, 2=moderate, 3=strong positive). Finally, probability scores of these markers were calculated.  In at most 14% of the non-injured control samples, hemorrhage was found, with mean ± standard deviation IHC scores of 0.1 ± 0.4, 0.2 ± 0.4 and 0.2 ± 0.5 for Fibronectin, CD62p, and Factor VIII, respectively. Expression of these markers significantly increased to mean IHC scores 1.4 ± 0.8 (Fibronectin), 1.2 ± 0.6 (CD62p), and 1.6 ± 0.8 (Factor VIII) in wounds inflicted shortly before death (few minutes old) and to 2.6 ± 0.5 (Fibronectin), 2.5 ± 0.6 (CD62p), and 2.8 ± 0.4 (Factor VIII) in 15-30 minutes old wounds. The probabilities that a wound was non vital in case of an IH score 0 were 87%, 88% and 90% for Fibronectin, CD62p, and Factor VIII, respectively. In case of an IHC score 1 or 2, the probabilities that a wound was a few minutes old were 82/90%, 82/83% and 72/93%. Finally, in case of an IHC score 3, the probabilities that a wound was 15-30 minutes old were 65%, 76% and 55%.
Performance of a stand-alone renewable energy system based on hydrogen energy storage

In this paper, an ac-linked hybrid electrical energy system comprising of photo voltaic (PV) and fuel cell (FC) with electrolyzer for standalone applications is proposed. PV is the primary power source of the system, and an FC-electrolyzer combination is used as a backup and as long-term storage system. A Fuzzy Logic controller is developed for the maximum power point tracking for the PV system. A simple power management strategy is designed for the proposed system to manage power flows among the different energy sources. A simulation model for the hybrid energy has been developed using MATLAB/Simulink.
Prediabetes and subsequent pancreatic fat accumulation

Yamazaki et al.  investigated the effect of prediabetes on subsequent pancreatic fat accumulation, based on the hypothesis that pancreatic fat was a manifestation of disturbed glucose metabolism. Prediabetes was defined as fasting plasma glucose of 100–125 mg/dl or hemoglobin A1c of 5.7–6.4%, and the change of pancreatic fat was evaluated by computed tomography (CT). A total of 198 nondiabetic participants were composed of 48 prediabetes and 150 non-prediabetes participants. By multiple linear regression analysis, baseline prediabetes was associated with future pancreatic fat accumulation with beta value (95% confidence interval) of 3.14 (1.25–5.03). In addition, body mass index (BMI) and impaired fasting glucose (IFG) were also risk factors of pancreatic fat accumulation. I have some queries on their study. First, the authors used prediabetes or IFG as an independent variable for the change of pancreatic fat accumulation, by adjusting several variables. As impaired glucose tolerance (IGT) value could not be used as an independent variable, the lack of IGT information for the definition of prediabetes should be specified by further study . Second, BMI was selected as a significant independent variable for the change of pancreatic fat accumulation. I suppose that the amount of visceral fat at baseline by CT could also be used as an independent variable. Although liver fat did not become a predictor, visceral fat as another obesity indicator should be checked for the analysis . Finally, the authors selected multiple linear regression analysis. I think that the authors could use prediabetes indictors at baseline as continuous variables. In addition, the change of prediabetes information can be used in combination with the change of pancreatic fat accumulation. Anyway, further studies are needed to know the causal association to confirm the hypothesis that pancreatic fat is a manifestation of disturbed glucose metabolism.
Tissue-Specific Signals Control Reversible Program of Localization and Functional Polarization of Macrophages

Tissue-resident macrophages are highly heterogeneous in terms of their functions and phenotypes as a consequence of adaptation to different tissue environments. Local tissue-derived signals are thought to control functional polarization of resident macrophages; however, the identity of these signals remains largely unknown. It is also unknown whether functional heterogeneity is a result of irreversible lineage-specific differentiation or a consequence of continuous but reversible induction of diverse functional programs. Here, we identified retinoic acid as a signal that induces tissue-specific localization and functional polarization of peritoneal macrophages through the reversible induction of transcription factor GATA6. We further found that GATA6 in macrophages regulates gut IgA production through peritoneal B-1 cells. These results provide insight into the regulation of tissue-resident macrophage functional specialization by tissue-derived signals.
Rupture of the Distal Tendon of the Biceps Brachii

Rupture of the distal biceps tendon is a relatively uncommon clinical entity. Typically, patients are middle-aged males who experience a sudden forced extension against an actively contracting biceps muscle. Patients usually describe a “pop” or tearing sensation in the anterior elbow region. The dominant extremity is involved in a majority of cases. While the etiology is usually traumatic, some believe that distal tendon rupture occurs through an area of prior tendon degeneration. Sudden pain, weakness with supination and elbow flexion, and deformity at the distal biceps tendon insertion are the common presenting symptoms. Diagnosis is made by history and physical findings. While plain x-rays are not usually helpful, magnetic resonance image (MRI) scans have been used to assist in diagnosing difficult cases and partial tendon ruptures. The best results are achieved when early reattachment of the tendon to the radial tuberosity is performed. The authors’ preferred surgical approach is a modified two-incision technique with primary reattachment to the radial tuberosity, but use of a single anterior incision has been described. Complications include radial nerve injury and radioulnar synostosis. Postoperative management involves elbow splinting in a position of flexion with gradual range of motion exercises 2–4 weeks following repair with a return to full activities including lifting by 4–5 months. Excellent results are achieved in most cases with this approach.
Mindfulness as a means of reducing aggressive behavior: dispositional and situational evidence.

Recent research and theory suggest that mindfulness, or enhanced attention and awareness in the present moment [Brown and Ryan, 2003], may be linked to lower levels of ego-involvement and, as a result, may have implications for lowering hostility and aggressive behavior. Accordingly, we conducted two studies to examine the potential aggression-mitigating role of mindfulness. In Study 1, we found that dispositional mindfulness correlated negatively with self-reported aggressiveness and hostile attribution bias. In Study 2, participants made mindful before receiving social rejection feedback displayed less-aggressive behavior than did rejected participants not made mindful. Discussion centers on potential mechanisms by which mindfulness operates to reduce aggressive behavior.
Microbial contamination of computer user interfaces ( keyboard , mouse ) in a tertiary care centre under conditions of practice

coming into contact with hands are often contaminated with nosocomial pathogens and can serve as vehicles for infection transmission [3,4,5]. In addition to various other types of surfaces, some authors have also suggested that computer user interfaces were also implicated here, albeit using very different methods and with very different results [6,7,8,9,10]. The aim of our study was therefore to investigate the extent of microbial contamination found on computer user interfaces (keyboard, mouse) under everyday use conditions in a university hospital and, as far as possible, to identify predictors of elevated contamination rates.
Advances, Challenges, and Opportunities in Automatic Facial Expression Recognition

In this chapter we consider the problem of automatic facial expression analysis. Our take on this is that the field has reached a point where it needs to move away from considering experiments and applications under in-the-lab conditions, and move towards so-called in-the-wild scenarios. We assume throughout this chapter that the aim is to develop technology that can be deployed in practical applications under unconstrained conditions. While some first efforts in this direction have been reported very recently, it is still unclear what the right path to achieving accurate, informative, robust, and real-time facial expression analysis will be. To illuminate the journey ahead, we first provide in Sec. 1 an overview of the existing theories and specific problem formulations considered within the computer vision community. Then we describe in Sec. 2 the standard algorithmic pipeline which is common to most facial expression analysis algorithms. We include suggestions as to which of the current algorithms and approaches are most suited to the scenario considered. In section 3 we describe our view of the remaining challenges, and the current opportunities within the field. This chapter is thus not intended as a review of different approaches, but rather a selection of what we believe are the most suitable state-of-the-art algorithms, and a selection of exemplars chosen to characterise a specific approach. We review in section 4 some of the exciting opportunities for the application of automatic facial expression analysis to everyday practical problems and current commercial applications being exploited. Section 5 ends the chapter by summarising the major conclusions drawn. Brais Martinez School of Computer Science, Jubilee Campus, Wollaton Road, Nottingham, NG8 1BB  brais.martinez@nottingham.ac.uk Michel F. Valstar School of Computer Science, Jubilee Campus, Wollaton Road, Nottingham, NG8 1BB
Similarity-Based Context-Aware Recommendation

Context-aware recommender systems (CARS) take context into consideration when modeling user preferences. There are two general ways to integrate context with recommendation: contextual filtering and contextual modeling. Currently, the most effective context-aware recommendation algorithms are based on a contextual modeling approach that estimate deviations in ratings across different contexts. In this paper, we propose context similarity as an alternative contextual modeling approach and examine different ways to represent context similarity and incorporate it into recommendation. More specifically, we show how context similarity can be integrated into the sparse linear method and matrix factorization algorithms. Our experimental results demonstrate that learning context similarity is a more effective approach to contextaware recommendation than modeling contextual rating deviations.
Quantify-me: Consumer Acceptance of Wearable Self-tracking Devices

The usage of wearable self-tracking technology has recently emerged as a new big trend in lifestyle and personal optimization in terms of health, fitness and well-being. Currently, only little is known about why people plan or start using such devices. Thus, in our research project, we aim at answering the question of what drives the usage intention of wearable self-tracking technology. Therefore, based on established technology acceptance theories, we deductively develop an acceptance model for wearable self-tracking technologies which sheds light on the pre-adoption criteria of such devices. We validate our proposed model by means of structural equation modeling using empirical data collected in a survey among 206 potential users. Our study identifies perceived usefulness, perceived enjoyment, social influence, trust, personal innovativeness, and perceived support of well-being as the strongest drivers for the intention to use wearable self-tracking technologies. By accounting for the influence of the demographic factors age and gender, we provide a further refined picture.
A Practical Application Combining Wireless Sensor Networks and Internet of Things: Safety Management System for Tower Crane Groups

The so-called Internet of Things (IoT) has attracted increasing attention in the field of computer and information science. In this paper, a specific application of IoT, named Safety Management System for Tower Crane Groups (SMS-TC), is proposed for use in the construction industry field. The operating status of each tower crane was detected by a set of customized sensors, including horizontal and vertical position sensors for the trolley, angle sensors for the jib and load, tilt and wind speed sensors for the tower body. The sensor data is collected and processed by the Tower Crane Safety Terminal Equipment (TC-STE) installed in the driver's operating room. Wireless communication between each TC-STE and the Local Monitoring Terminal (LMT) at the ground worksite were fulfilled through a Zigbee wireless network. LMT can share the status information of the whole group with each TC-STE, while the LMT records the real-time data and reports it to the Remote Supervision Platform (RSP) through General Packet Radio Service (GPRS). Based on the global status data of the whole group, an anti-collision algorithm was executed in each TC-STE to ensure the safety of each tower crane during construction. Remote supervision can be fulfilled using our client software installed on a personal computer (PC) or smartphone. SMS-TC could be considered as a promising practical application that combines a Wireless Sensor Network with the Internet of Things.