nils-herrmann/clean_scirepeval huggingface dataset:
Synchronous Firefly Algorithm for Cluster Head Selection in WSN

Wireless Sensor Network (WSN) consists of small low-cost, low-power multifunctional nodes interconnected to efficiently aggregate and transmit data to sink. Cluster-based approaches use some nodes as Cluster Heads (CHs) and organize WSNs efficiently for aggregation of data and energy saving. A CH conveys information gathered by cluster nodes and aggregates/compresses data before transmitting it to a sink. However, this additional responsibility of the node results in a higher energy drain leading to uneven network degradation.  In this work, a modified firefly heuristic, synchronous firefly algorithm, is proposed to improve the network performance. Extensive simulation shows the proposed technique to perform well compared to LEACH and energy-efficient hierarchical clustering. Simulations show the effectiveness of the proposed method in decreasing the packet loss ratio by an average of 9.63% and improving the energy efficiency of the network when compared to LEACH and EEHC.
Anatomy and histology of the newly discovered adipose sac structure within the labia majora: international original research

To determine whether there is any new anatomical structure present within the labia majora. A case serial study was executed on eleven consecutive fresh human female cadavers. Stratum-by-stratum dissections of the labia majora were performed. Twenty-two anatomic dissections of labia majora were completed. Eosin and Hematoxylin agents were used to stain newly discovered adipose sac’s tissues of the labia majora and the cylinder-like structures, which cover condensed adipose tissues. The histology of these two structures was compared. All dissected labia majora demonstrated the presence of the anatomic existence of the adipose sac structure. Just under the dermis of the labia majora, the adipose sac was located, which was filled with lobules containing condensed fatty tissues in the form of cylinders. The histological investigation established that the well-organized fibro-connective-adipose tissues represented the adipose sac. The absence of descriptions of the adipose sac within the labia majora in traditional anatomic and gynecologic textbooks was noted. In this study group, the newly discovered adipose sac is consistently present within the anatomical structure of the labia majora. The well-organized fibro-connective-adipose tissue represents microscopic characteristic features of the adipose sac.
Selenium in food and the human body: a review.

Selenium levels in soil generally reflect its presence in food and the Se levels in human populations. Se food content is influenced by geographical location, seasonal changes, protein content and food processing. Periodic monitoring of Se levels in soil and food is necessary. Diet is the major Se source and approximately 80% of dietary Se is absorbed depending on the type of food consumed. Se bioavailability varies according to the Se source and nutritional status of the subject, being significantly higher for organic forms of Se. Se supplements can be beneficial for subjects living in regions with very low environmental levels of Se. Several strategies have been followed: (1) employment of Se-enriched fertilizers; (2) supplementation of farm animals with Se; (3) consumption of multimicronutrient supplements with Se. Nevertheless, detailed investigations of possible interactions between Se supplements and other food components and their influence on Se bioavailability are needed. Suppliers also need to provide more information on the specific type of Se used in supplements. In addition, research is lacking on the mechanisms through which Se is involved in hepatocyte damage during hepatopathies. Although Se potential as an antioxidant for the prevention of cardiovascular diseases (CVD) is promising, additional long-term intervention trials are necessary. As a result, indiscriminate Se supplements cannot be reliably recommended for the prevention of CVD in human beings. Some interesting findings reported an association of Se intake with a reduced prevalence and risk for prostate and colon cancer. However, random trials for other cancer types are inconclusive. As a final conclusion, the general population should be warned against the employment of Se supplements for prevention of hepatopathies, cardiovascular or cancer diseases, because benefits of Se supplementation are still uncertain, and their indiscriminate use could generate an increased risk of Se toxicity.
PRECISION PIVOT IRRIGATION CONTROLS TO OPTIMIZE WATER APPLICATION

A precision control system that enables a center pivot irrigation system (CP) to precisely supply water in optimal rates relative to the needs of individual areas within fields was developed through a collaboration between the Farmscan group (Perth, Western Australia) and the University of Georgia Precision Farming team at the National Environmentally Sound Production Agriculture Laboratory (NESPAL) in Tifton, GA. The control system, referred to as Variable-Rate Irrigation (VRI), varies application rate by cycling sprinklers on and off and by varying the CP travel speed. Desktop PC software is used to define application maps which are loaded into the VRI controller. The VRI system uses GPS to determine pivot position/angle of the CP mainline. Results from VRI system performance testing indicate good correlation between target and actual application rates and also shows that sprinkler cycling on/off does not alter the CP uniformity. By applying irrigation water in this precise manner, water application to the field is optimized. In many cases, substantial water savings can be realized.
Domestic Violence Crisis Identification From Facebook Posts Based on Deep Learning

Domestic violence (DV) is a cause of concern due to the threat it poses toward public health and human rights. There is a need for quick identification of the victims of this condition so that DV crisis service (DVCS) can offer necessary support in a timely manner. The availability of social media has allowed DV victims to share their stories and receive support from the community, which opens an opportunity for DVCS to actively approach and support DV victims. However, it is time consuming and inefficient to manually browse through a massive number of available posts. This paper adopts deep learning as an approach for automatic identification of DV victims in critical need. Empirical evidence on a ground truth data set has achieved an accuracy of up to 94%, which outperforms traditional machine-learning techniques. The analysis of informative features helps to identify important words which might indicate critical posts in the classification process. The experimental results are helpful to researchers and practitioners in developing techniques for identifying and supporting DV victims.
A randomized clinical trial of eye movement desensitization and reprocessing (EMDR), fluoxetine, and pill placebo in the treatment of posttraumatic stress disorder: treatment effects and long-term maintenance.

The relative short-term efficacy and long-term benefits of pharmacologic versus psychotherapeutic interventions have not been studied for posttraumatic stress disorder (PTSD). This study compared the efficacy of a selective serotonin reup-take inhibitor (SSRI), fluoxetine, with a psychotherapeutic treatment, eye movement desensitization and reprocessing (EMDR), and pill placebo and measured maintenance of treatment gains at 6-month follow-up.



Eighty-eight PTSD subjects diagnosed according to DSM-IV criteria were randomly assigned to EMDR, fluoxetine, or pill placebo. They received 8 weeks of treatment and were assessed by blind raters posttreatment and at 6-month follow-up. The primary outcome measure was the Clinician-Administered PTSD Scale, DSM-IV version, and the secondary outcome measure was the Beck Depression Inventory-II. The study ran from July 2000 through July 2003.



The psychotherapy intervention was more successful than pharmacotherapy in achieving sustained reductions in PTSD and depression symptoms, but this benefit accrued primarily for adult-onset trauma survivors. At 6-month follow-up, 75.0% of adult-onset versus 33.3% of child-onset trauma subjects receiving EMDR achieved asymptomatic end-state functioning compared with none in the fluoxetine group. For most childhood-onset trauma patients, neither treatment produced complete symptom remission.



This study supports the efficacy of brief EMDR treatment to produce substantial and sustained reduction of PTSD and depression in most victims of adult-onset trauma. It suggests a role for SSRIs as a reliable first-line intervention to achieve moderate symptom relief for adult victims of childhood-onset trauma. Future research should assess the impact of lengthier intervention, combination treatments, and treatment sequencing on the resolution of PTSD in adults with childhood-onset trauma.
On Communicating Finite-State Machines

A model of commumcations protocols based on finite-state machines is investigated. The problem addressed is how to ensure certain generally desirable properties, which make protocols "wellformed," that is, specify a response to those and only those events that can actually occur. It is determined to what extent the problem is solvable, and one approach to solving it ts described. Categories and SubJect Descriptors' C 2 2 [Computer-Conununication Networks]: Network Protocols-protocol verification; F 1 1 [Computation by Abstract Devices] Models of Computation--automata;  Graph Theory--graph algoruhms; trees General Terms: Reliability, Verification Additional
Unobtrusive monitoring of cardiorespiratory signals during sleep based on PVDF sensor and singular spectrum analysis

Unobtrusive cardiorespiratory monitoring in the period of sleep could facilitate researchers for sleep analysis and sleep disorders diagnosis. With the recent advancement of biomedical health informatics, it is possible to monitor individual's sleep disorders through cardiovascular parameters. This paper proposes a polyvinylidene fluoride (PVDF) sensor based system for unobtrusive measurements of respiration and heartbeat while sleeping; the sensing unit is deployed on the mattress below the back area of the subject. The PVDF sensor generates the sensory activations due to pulsatile pressure change caused by respiratory and heartbeat movement. To extract and separate the heartbeat and respiration accurately, the method singular spectrum analysis (SSA) was applied while the empirical mode decomposition (EMD) and wavelet analysis methods were used for comparison. Experiments are conducted on two healthy subjects to obtain the respiratory rate and heart rate. To verify and compare the performance of the proposed system, the polysomnography (PSG) system was used to record the thorax effort signal and electrocardiography (ECG) as the gold standard for extracting the respiratory rate and heart rate respectively. The average error rate (AER) of respiratory rate extraction is noted 8.53%, with segmenting the data as 2 mins epochs. Meanwhile, the AERs of the heart rate are 8.01%, 8.80%, 8.55% by utilizing the SSA, EMD and wavelet methods respectively. Overall, the proposed system can obtain accurate respiration and heart rate detection. And the novelty lies in introducing a flexible PVDF sensor which can be combined with the sleep mat for cardiorespiratory signal monitoring in home environment; and new SSA algorithm to extract respiration and heart rates. The experimental results are promising which demonstrated that the proposed system satisfied the basic requirements for cardiorespiratory signal monitoring during sleep.
Cognitive modeling of polymorphic malware using fractal based semantic characterization

Polymorphic malware belong to the class of host based threats which defy signature based detection mechanisms. Threat actors use various code obfuscation methods to hide the code details of the polymorphic malware and each dynamic iteration of the malware bears different and new signatures therefore makes its detection harder by signature based antimalware programs. Sandbox based detection systems perform syntactic analysis of the binary files to find known patterns from the un-encrypted segment of the malware file. Anomaly based detection systems can detect polymorphic threats but generate enormous false alarms. In this work, authors present a novel cognitive framework using semantic features to detect the presence of polymorphic malware inside a Microsoft Windows host using a process tree based temporal directed graph. Fractal analysis is performed to find cognitively distinguishable patterns of the malicious processes containing polymorphic malware executables. The main contributions of this paper are; the presentation of a graph theoretic approach for semantic characterization of polymorphism in the operating system's process tree, and the cognitive feature extraction of the polymorphic behavior for detection over a temporal process space.
A Survey of Robot Interaction Control Schemes with Experimental Comparison

A great many control schemes for a robot manipulator interacting with the environment have been developed in the literature in the past two decades. This paper is aimed at presenting a survey of robot interaction control schemes for a manipulator, the end effector of which comes in contact with a compliant surface. A salient feature of the work is the implementation of the schemes on an industrial robot with open control architecture equipped with a wrist force sensor. Two classes of control strategies are considered, namely, those based on static model-based compensation and those based on dynamic model-based compensation. The former provide a good steadystate behavior, while the latter enhance the behavior during the transient. The performance of the various schemes is compared in the light of disturbance rejection, and a thorough analysis is developed by means of a number of case studies.
A Reliability-Aware Approach for Resource Efficient Virtual Network Function Deployment

Network function virtualization (NFV) is a promising technique aimed at reducing capital expenditures (CAPEX) and operating expenditures (OPEX), and improving the flexibility and scalability of an entire network. In contrast to traditional dispatching, NFV can separate network functions from proprietary infrastructure and gather these functions into a resource pool that can efficiently modify and adjust service function chains (SFCs). However, this emerging technique has some challenges. A major problem is reliability, which involves ensuring the availability of deployed SFCs, namely, the probability of successfully chaining a series of virtual network functions while considering both the feasibility and the specific requirements of clients, because the substrate network remains vulnerable to earthquakes, floods, and other natural disasters. Based on the premise of users’ demands for SFC requirements, we present an ensure reliability cost saving algorithm to reduce the CAPEX and OPEX of telecommunication service providers by reducing the reliability of the SFC deployments. The results of extensive experiments indicate that the proposed algorithms perform efficiently in terms of the blocking ratio, resource consumption, time consumption, and the first block.
Machine learning in adversarial environments

Whenever machine learning is used to prevent illegal or unsanctioned activity and there is an economic incentive, adversaries will attempt to circumvent the protection provided. Constraints on how adversaries can manipulate training and test data for classifiers used to detect suspicious behavior make problems in this area tractable and interesting. This special issue highlights papers that span many disciplines including email spam detection, computer intrusion detection, and detection of web pages deliberately designed to manipulate the priorities of pages returned by modern search engines. The four papers in this special issue provide a standard taxonomy of the types of attacks that can be expected in an adversarial framework, demonstrate how to design classifiers that are robust to deleted or corrupted features, demonstrate the ability of modern polymorphic engines to rewrite malware so it evades detection by current intrusion detection and antivirus systems, and provide approaches to detect web pages designed to manipulate web page scores returned by search engines. We hope that these papers and this special issue encourages the multidisciplinary cooperation required to address many interesting problems in this relatively new area including predicting the future of the arms races created by adversarial learning, developing effective long-term defensive strategies, and creating algorithms that can process the massive amounts of training and test data available for internet-scale problems.
Big data set privacy preserving through sensitive attribute-based grouping

There is a growing trend towards attacks on database privacy due to great value of privacy information stored in big data set. Public's privacy are under threats as adversaries are continuously cracking their popular targets such as bank accounts. We find a fact that existing models such as K-anonymity, group records based on quasi-identifiers, which harms the data utility a lot. Motivated by this, we propose a sensitive attribute-based privacy model. Our model is the early work of grouping records based on sensitive attributes instead of quasi-identifiers which is popular in existing models. Random shuffle is used to maximize information entropy inside a group while the marginal distribution maintains the same before and after shuffling, therefore, our method maintains a better data utility than existing models. We have conducted extensive experiments which confirm that our model can achieve a satisfying privacy level without sacrificing data utility while guarantee a higher efficiency.
Isolated anterior talofibular ligament Broström repair for chronic lateral ankle instability: 9-year follow-up.

Lateral ankle sprains may result in pain and disability in the short term, decreased sport activity and early retirement from sports in the mid term, and secondary injuries and development of early osteoarthritis to the ankle in the long term.



This combined approach to chronic lateral instability and intra-articular lesions of the ankle is safe and in the long term maintains mechanical stability, functional ability, and a good level of sport activity.



Case series; 
We present the long-term outcomes of 42 athletes who underwent ankle arthroscopy and anterior talofibular Broström repair for management of chronic lateral ankle instability. We assessed in all patients preoperative and postoperative anterior drawer test and side-to-side differences, American Orthopaedic Foot and Ankle Society (AOFAS) score, and Kaikkonen grading scales. Patients were asked about return to sport and level of activity. Patients were also assessed for development of degenerative changes to the ankle, and preoperative versus postoperative findings were compared.



Thirty-eight patients were reviewed at an average of 8.7 years (range, 5-13 years) after surgery; 4 patients were lost to follow-up. At the last follow-up, patients were significantly improved for ankle laxity, AOFAS scores, and Kaikkonen scales. The mean AOFAS score improved from 51 (range, 32-71) to 90 (range, 67-100), and the mean Kaikkonen score improved from 45 (range, 30-70) to 90 (range, 65-100). According to outcome criteria set preoperatively, there were 8 failures by the AOFAS score and 9 by the Kaikkonen score. Twenty-two (58%) patients practiced sport at the preinjury level, 6 (16%) had changed to lower levels but were still active in less demanding sports (cycling and tennis), and 10 (26%) had abandoned active sport participation although they still were physically active. Six of these patients did not feel safe with their ankle because of the occurrence of new episodes of ankle instability. Of the 27 patients who had no evidence of degenerative changes preoperatively, 8 patients (30%) had radiographic signs of degenerative changes (5 grade I and 3 grade II) of the ankle; 4 of the 11 patients (11%) with preexisting grade I changes remained unchanged, and 7 patients (18%) had progressed to grade II. No correlation was found between osteoarthritis and status of sport activity (P = .72).



Combined Broström repair and ankle arthroscopy are safe and allow most patients to return to preinjury daily and sport activities.
A Real Time Ball Detection Framework For Soccer Video

Despite a lot of research efforts, it is still challenging to detect the ball in soccer video, especially in long shot frames. In this paper, we propose a novel real time ball detection framework for broadcast soccer video in long shot frames. Firstly each frame of the video is preprocessed to remove the regions outside ground field and build a saliency binary map. Then, the ball candidates are detected and examined by a rule-based algorithm proposed in this paper. At last, making use of Kalman filter as an effective supplement, the ball location is decided. Experimental results demonstrate that the proposed framework is quite effective to recognize the ball. KeywordsReal time ball detection, Soccer Video,
A Differential CMOS T/R Switch for Multistandard Applications

This brief presents a differential transmit-receive (T/R) switch integrated in a 0.18-mum standard CMOS technology for wireless applications up to 6 GHz. This switch design employs fully differential architecture to accommodate the design challenge of differential transceivers and improve the linearity performance. It exhibits less than 2-dB insertion loss, higher than 15-dB isolation, in a 60 mumtimes40 mum area. 15-dBm power at 1-dB compression point (P1dB) is achieved without using additional techniques to enhance the linearity. This switch is suitable for differential transceiver front-ends with a moderate power level. To the best of the authors' knowledge, this is the first reported differential T/R switch in CMOS for multistandard and wideband wireless applications
An overall view of knowledge management challenges for global business

The purpose of this paper is to offer an overall view of knowledge management challenges for global business via discussing the challenges and proposing theoretical and managerial implications.  Based on a comprehensive literature review, the paper identifies six main knowledge management challenges faced by global business today. Then, the challenges are discussed in relation to managerial practice.  The paper argues that developing a working definition of knowledge, dealing with tacit knowledge and utilization of information technology, adaptation to cultural complexity, attention to human resources, developing new organizational structures, and coping with increased competition are the main knowledge management challenges faced by global business today.  Suggested implications include a more significant managerial emphasis on considering and dealing with the knowledge management challenges in a holistic manner, taking into account all internal and external factors influencing the knowledge-management process.  The paper evaluates the critical findings of the literature within the historical progress of knowledge management, clarifies the main knowledge management challenges faced by global business organizations today, and offers a basic framework for further studies.