nils-herrmann/clean_scirepeval huggingface dataset:
Executive Function, Visual Attention and the Cocktail Party Problem in Musicians and Non-Musicians

The goal of this study was to investigate how cognitive factors influence performance in a multi-talker, "cocktail-party" like environment in musicians and non-musicians. This was achieved by relating performance in a spatial hearing task to cognitive processing abilities assessed using measures of executive function (EF) and visual attention in musicians and non-musicians. For the spatial hearing task, a speech target was presented simultaneously with two intelligible speech maskers that were either colocated with the target (0° azimuth) or were symmetrically separated from the target in azimuth (at ±15°). EF assessment included measures of cognitive flexibility, inhibition control and auditory working memory. Selective attention was assessed in the visual domain using a multiple object tracking task (MOT). For the MOT task, the observers were required to track target dots (n = 1,2,3,4,5) in the presence of interfering distractor dots. Musicians performed significantly better than non-musicians in the spatial hearing task. For the EF measures, musicians showed better performance on measures of auditory working memory compared to non-musicians. Furthermore, across all individuals, a significant correlation was observed between performance on the spatial hearing task and measures of auditory working memory. This result suggests that individual differences in performance in a cocktail party-like environment may depend in part on cognitive factors such as auditory working memory. Performance in the MOT task did not differ between groups. However, across all individuals, a significant correlation was found between performance in the MOT and spatial hearing tasks. A stepwise multiple regression analysis revealed that musicianship and performance on the MOT task significantly predicted performance on the spatial hearing task. Overall, these findings confirm the relationship between musicianship and cognitive factors including domain-general selective attention and working memory in solving the "cocktail party problem".
Diagnostic imaging of psoriatic arthritis. Part I: etiopathogenesis, classifications and radiographic features

Psoriatic arthritis is one of the spondyloarthritis. It is a disease of clinical heterogenicity, which may affect peripheral joints, as well as axial spine, with presence of inflammatory lesions in soft tissue, in a form of dactylitis and enthesopathy. Plain radiography remains the basic imaging modality for PsA diagnosis, although early inflammatory changes affecting soft tissue and bone marrow cannot be detected with its use, or the image is indistinctive. Typical radiographic features of PsA occur in an advanced disease, mainly within the synovial joints, but also in fibrocartilaginous joints, such as sacroiliac joints, and additionally in entheses of tendons and ligaments. Moll and Wright classified PsA into 5 subtypes: asymmetric oligoarthritis, symmetric polyarthritis, arthritis mutilans, distal interphalangeal arthritis of the hands and feet and spinal column involvement. In this part of the paper we discuss radiographic features of the disease. The next one will address magnetic resonance imaging and ultrasonography.
Examining Rotation Gain in CAVE-like Virtual Environments

When moving through a tracked immersive virtual environment, it is sometimes useful to deviate from the normal one-to-one mapping of real to virtual motion. One option is the application of rotation gain, where the virtual rotation of a user around the vertical axis is amplified or reduced by a factor. Previous research in head-mounted display environments has shown that rotation gain can go unnoticed to a certain extent, which is exploited in redirected walking techniques. Furthermore, it can be used to increase the effective field of regard in projection systems. However, rotation gain has never been studied in CAVE systems, yet. In this work, we present an experiment with 87 participants examining the effects of rotation gain in a CAVE-like virtual environment. The results show no significant effects of rotation gain on simulator sickness, presence, or user performance in a cognitive task, but indicate that there is a negative influence on spatial knowledge especially for inexperienced users. In secondary results, we could confirm results of previous work and demonstrate that they also hold for CAVE environments, showing a negative correlation between simulator sickness and presence, cognitive performance and spatial knowledge, a positive correlation between presence and spatial knowledge, a mitigating influence of experience with 3D applications and previous CAVE exposure on simulator sickness, and a higher incidence of simulator sickness in women.
Evaluation of the setup accuracy of a stereotactic radiotherapy head immobilization mask system using kV on‐board imaging†


The purpose of this study was to evaluate setup accuracy and quantify random and systematic errors of the BrainLAB stereotactic immobilization mask and localization system using kV on-board imaging. Nine patients were simulated and set up with the BrainLAB stereotactic head immobilization mask and localizer to be treated for brain lesions using single and hypofractions. Orthogonal pairs of projections were acquired using a kV on-board imager mounted on a Varian Trilogy machine. The kV projections were then registered with digitally-reconstructed radiographs (DRR) obtained from treatment planning. Shifts between the kV images and reference DRRs were calculated in the different directions: anterior-posterior (A-P), medial-lateral (R-L) and superior-inferior (S-I). If the shifts were larger than 2mm in any direction, the patient was reset within the immobilization mask until satisfying setup accuracy based on image guidance has been achieved. Shifts as large as 4.5 mm, 5.0 mm, 8.0 mm in the A-P, R-L and S-I directions, respectively, were measured from image registration of kV projections and DRRs. These shifts represent offsets between the treatment and simulation setup using immobilization mask. The mean offsets of 0.1 mm, 0.7 mm, and -1.6 mm represent systematic errors of the BrainLAB localizer in the A-P, R-L and S-I directions, respectively. The mean of the radial shifts is about 1.7 mm. The standard deviations of the shifts were 2.2 mm, 2.0 mm, and 2.6 mm in A-P, R-L and S-I directions, respectively, which represent random patient setup errors with the BrainLAB mask. The Brain-LAB mask provides a noninvasive, practical and flexible immobilization system that keeps the patients in place during treatment. Relying on this system for patient setup might be associated with significant setup errors. Image guidance with the kV on-board imager provides an independent verification technique to ensure accuracy of patient setup. Since the patient may relax or move during treatment, uncontrolled and undetected setup errors may be produced with patients that are not well-immobilized. Therefore, the combination of stereotactic immobilization and image guidance achieves more controlled and accurate patient setup within 2mm in A-P, R-L and S-I directions.
Structural Mechanism for Rifampicin Inhibition of Bacterial RNA Polymerase

Rifampicin (Rif) is one of the most potent and broad spectrum antibiotics against bacterial pathogens and is a key component of anti-tuberculosis therapy, stemming from its inhibition of the bacterial RNA polymerase (RNAP). We determined the crystal structure of Thermus aquaticus core RNAP complexed with Rif. The inhibitor binds in a pocket of the RNAP beta subunit deep within the DNA/RNA channel, but more than 12 A away from the active site. The structure, combined with biochemical results, explains the effects of Rif on RNAP function and indicates that the inhibitor acts by directly blocking the path of the elongating RNA when the transcript becomes 2 to 3 nt in length.
Overt and relational aggression in adolescents: social-psychological adjustment of aggressors and victims.

Examined the relative and combined associations among relational and overt forms of aggression and victimization and adolescents' concurrent depression symptoms, loneliness, self-esteem, and externalizing behavior. An ethnically diverse sample of 566 adolescents (55% girls) in Grades 9 to 12 participated. Results replicated prior work on relational aggression and victimization as distinct forms of peer behavior that are uniquely associated with concurrent social-psychological adjustment. Victimization was associated most closely with internalizing symptoms, and peer aggression was related to symptoms of disruptive behavior disorder. Findings also supported the hypothesis that victims of multiple forms of aggression are at greater risk for adjustment difficulties than victims of one or no form of aggression. Social support from close friends appeared to buffer the effects of victimization on adjustment.
Log-Periodic patch antenna with tunable frequency

This paper describes the design and analysis of a Log-Periodic Microstrip Antenna Array operating between 3.3 Gigahertz (GHz) and 4.5 GHz. A five square patches fed by inset feed line technique are connected with a single transmission line by a log-periodic array formation. By applying five PIN Diodes at the transmission line with a quarter-wave length radial stub biasing, four different sub-band frequencies are configured by switching ON and OFF the PIN Diode. Simulation as well as measurement results with antenna design is presented and it shows that a good agreement in term of return loss. The simulated radiation pattern and realized gain for every sub bands also presented and discussed.
Design of a Negative Pressure Absorption Wall-Climbing Robot with the muCOS-II System

This paper introduced a centrifugal impeller-based wall-climbing robot with the μCOS-II System. Firstly, the climber's basic configurations of mechanical were described. Secondly, the mechanic analyses of walking mechanism was presented, which was essential to the suction device design. Thirdly, the control system including the PC remote control system and the STM32 master slave system was designed. Finally, an experiment was conducted to test the performance of negative pressure generating system and general abilities of wall-climbing robot.
Image Processing Based Real Time Vehicle Theft Detection and Prevention System

A major problem today for car owners is that they are in constant fear of having their vehicles stolen from a common parking lot or from outside their home. Image processing based real time vehicle theft detection and prevention system provide an ultimate solution for this problem. The system described in this paper automatically take photos of driver and compares his or her face with database to check whether he is an authenticated driver or not. He can have access to the vehicle only if he is an authenticated driver. If he is not an authenticated driver an alarm rings and electrical connections are not activated. The technology used here is face recognition and face detection in real time. As the photos are taken in real time, several problems like unequal illumination and changes in the background may affect the system. To overcome this problem DCT normalization and background cancellation algorithms are incorporated along with basic face detection and face recognition algorithm. In this paper software and hardware details of the system are discussed. Technologically system is simple, accurate and maintainable.
A Digital Phase Leading Filter Current Compensation (PLFCC) Technique for CCM Boost PFC Converter to Improve PF in High Line Voltage and Light Load Conditions

This paper proposes a digital phase leading filter current compensation (PLFCC) technique for a continuous conduction mode boost power factor correction to improve PF in high line voltage and light load conditions. The proposed technique provides a corrected average inductor current reference and utilizes an enhanced duty ratio feed-forward technique which can cancel the adverse effect of the phase leading currents caused by filter capacitors. Moreover, the proposed PLFCC technique also provides the switching dead-zone in nature so the switching loss can be reduced. Therefore, the proposed PLFCC can significantly improve power quality and can achieve a high efficiency in high line voltage and light load conditions. The principle and analysis of the proposed PLFCC are presented, and performance and feasibility are verified by experimental results from the universal input (90-260 VAC) and 750 W-400 V output laboratory prototype.
An Interactive Simulator for Imposing Virtual Musculoskeletal Dynamics

disease processes are often marked by both neural and muscular changes that alter movement control and execution, but these adaptations are difficult to tease apart because they occur simultaneously. This is addressed by swapping an individual's limb dynamics with a neurally controlled facsimile using an interactive musculoskeletal simulator (IMS) that allows controlled modifications of musculoskeletal dynamics. This paper details the design and operation of the IMS, quantifies and describes human adaptation to the IMS, and determines whether the IMS allows users to move naturally, a prerequisite for manipulation experiments.  Methods: healthy volunteers (n = 4) practiced a swift goal-directed task (back-and-forth elbow flexion/extension) for 90 trials with the IMS off (normal dynamics) and 240 trials with the IMS on, i.e., the actions of a user's personalized electromyography-driven musculoskeletal model are robotically imposed back onto the user.  after practicing with the IMS on, subjects could complete the task with end-point errors of 1.56°, close to the speed-matched IMS-off error of 0.57°. Muscle activity, joint torque, and arm kinematics for IMS-on and -off conditions were well matched for three subjects (root-mean-squared error [RMSE] = 0.16 N·m), but the error was higher for one subject with a small stature (RMSE = 0.25 N·m).  a well-matched musculoskeletal model allowed IMS users to perform a goal-directed task nearly as well as when the IMS was not active.  this advancement permits real-time manipulations of musculoskeletal dynamics, which could increase our understanding of muscular and neural co-adaptations to injury, disease, disuse, and aging.
Learning for serving deadline-constrained traffic in multi-channel wireless networks

We study the problem of serving randomly arriving and delay-sensitive traffic over a multi-channel communication system with time-varying channel states and unknown statistics. This problem deviates from the classical exploration-exploitation setting in that the design and analysis must accommodate the dynamics of packet availability and urgency as well as the cost of each channel use at the time of decision. To that end, we have developed and investigated two policies, one index-based (UCB-Deadline) and the other Bayesian (TS-Deadline), both of which perform dynamic channel allocation decisions that incorporate these traffic requirements and costs. Under symmetric channel conditions, we have proved that the UCB-Deadline policy can achieve bounded regret in the likely case where the cost of using a channel is not too high to prevent all transmissions, and logarithmic regret otherwise. In our numerical studies, we also show that TS-Deadline achieves superior performance over its UCB counterpart, making it a potentially useful alternative when fast convergence to optimal is important.
Use of platelet-rich fibrin in regenerative dentistry: a systematic review

Research across many fields of medicine now points towards the clinical advantages of combining regenerative procedures with platelet-rich fibrin (PRF). This systematic review aimed to gather the extensive number of articles published to date on PRF in the dental field to better understand the clinical procedures where PRF may be utilized to enhance tissue/bone formation. Manuscripts were searched systematically until May 2016 and separated into the following categories: intrabony and furcation defect regeneration, extraction socket management, sinus lifting procedures, gingival recession treatment, and guided bone regeneration (GBR) including horizontal/vertical bone augmentation procedures. Only human randomized clinical trials were included for assessment. In total, 35 articles were selected and divided accordingly (kappa = 0.94). Overall, the use of PRF has been most investigated in periodontology for the treatment of periodontal intrabony defects and gingival recessions where the majority of studies have demonstrated favorable results in soft tissue management and repair. Little to no randomized clinical trials were found for extraction socket management although PRF has been shown to significantly decrease by tenfold dry sockets of third molars. Very little to no data was available directly investigating the effects of PRF on new bone formation in GBR, horizontal/vertical bone augmentation procedures, treatment of peri-implantitis, and sinus lifting procedures. Much investigation now supports the use of PRF for periodontal and soft tissue repair. Despite this, there remains a lack of well-conducted studies demonstrating convincingly the role of PRF during hard tissue bone regeneration. Future human randomized clinical studies evaluating the use of PRF on bone formation thus remain necessary. PRF was shown to improve soft tissue generation and limit dimensional changes post-extraction, with little available data to date supporting its use in GBR.
Challenges for Agile Development of COTS Components and COTS-based Systems - A Theoretical Examination

Component-based software engineering has had great impact in the desktop and server domain and is spreading to other domains as well, such as embedded systems. Agile software development is another approach which has gained much attention in recent years, mainly for smaller-scale production of less critical systems. Both of them promise to increase system quality, development speed and flexibility, but so far little has been published on the combination of the two approaches. This paper presents a comprehensive analysis of the applicability of the agile approach in the development processes of 1) COTS components and 2) COTS-based systems. The study method is a systematic theoretical examination and comparison of the fundamental concepts and characteristics of these approaches. The contributions are: first, an enumeration of identified contradictions between the approaches, and suggestions how to bridge these incompatibilities to some extent. Second, the paper provides some more general comments, considerations, and application guidelines concerning the introduction of agile principles into the development of COTS components or COTS-based systems. This study thus forms a framework which will guide further empirical studies.
An efficient Hadoop data replication method design for heterogeneous clusters

The performance of each datanode in a heterogeneous Hadoop cluster differs, and the number of slots that can be numbered to simultaneously execute tasks differs. For this reason, Hadoop is susceptible to replica placement problems and data replication problems. Because of this, replication problems and allocation problems occur. These problems can deteriorate the performance of Hadoop. In this paper, we summarize existing research to improve data locality, and design a data replication method to solve replication and allocation problems.
Oral vaccination of fish: Lessons from humans and veterinary species.

The limited number of oral vaccines currently approved for use in humans and veterinary species clearly illustrates that development of efficacious and safe oral vaccines has been a challenge not only for fish immunologists. The insufficient efficacy of oral vaccines is partly due to antigen breakdown in the harsh gastric environment, but also to the high tolerogenic gut environment and to inadequate vaccine design. In this review we discuss current approaches used to develop oral vaccines for mass vaccination of farmed fish species. Furthermore, using various examples from the human and veterinary vaccine development, we propose additional approaches to fish vaccine design also considering recent advances in fish mucosal immunology and novel molecular tools. Finally, we discuss the pros and cons of using the zebrafish as a pre-screening animal model to potentially speed up vaccine design and testing for aquaculture fish species.
A novel approach to on-line handwriting recognition based on bidirectional long short-term memory networks

In this paper we introduce a new connectionist approach to on-line handwriting recognition and address in particular the problem of recognizing handwritten whiteboard notes. The approach uses a bidirectional recurrent neural network with long short-term memory blocks. We use a recently introduced objective function, known as Connectionist Temporal Classification (CTC), that directly trains the network to label unsegmented sequence data. Our new system achieves a word recognition rate of 74.0 %, compared with 65.4 % using a previously developed HMMbased recognition system.
Aesthetic Inference for Smart Mobile Devices

The convenience of cell-phone cameras has made them one of the most common ways by which people document their lives, whether it is everyday pleasures or celebrations. With thousands of images, it might prove to be a daunting task to organize them by hand. When applying automated algorithms to help us, we would like to have both images that are dear to us but are also of good quality. In this paper we explore the performance of the MobileNet CNN architecture, and the different design (inputs size, and layer depth) choices, in their ability in solving various aesthetic inference task: binary classification, regression, image cropping. We show that the baseline MobileNet architecture achieves near state-of-the-art results for binary classification on the AVA dataset while being more than 10 times smaller and compute efficient. We further show that these models, when trained for fine-grained aesthetics inference, achieve better cropping performance than other aestheticsbased croppers.
Learning Depth From Single Images With Deep Neural Network Embedding Focal Length

Learning depth from a single image, as an important issue in scene understanding, has attracted a lot of attention in the past decade. The accuracy of the depth estimation has been improved from conditional Markov random fields, non-parametric methods, to deep convolutional neural networks most recently. However, there exist inherent ambiguities in recovering 3D from a single 2D image. In this paper, we first prove the ambiguity between the focal length and monocular depth learning and verify the result using experiments, showing that the focal length has a great influence on accurate depth recovery. In order to learn monocular depth by embedding the focal length, we propose a method to generate synthetic varying-focal-length data set from fixed-focal-length data sets, and a simple and effective method is implemented to fill the holes in the newly generated images. For the sake of accurate depth recovery, we propose a novel deep neural network to infer depth through effectively fusing the middle-level information on the fixed-focal-length data set, which outperforms the state-of-the-art methods built on pre-trained VGG. Furthermore, the newly generated varying-focal-length data set is taken as input to the proposed network in both learning and inference phases. Extensive experiments on the fixed- and varying-focal-length data sets demonstrate that the learned monocular depth with embedded focal length is significantly improved compared to that without embedding the focal length information.