nils-herrmann/clean_scirepeval huggingface dataset:
Impaired recognition of emotion in facial expressions following bilateral damage to the human amygdala

STUDIES in animals have shown that the amygdala receives highly processed visual input1,2, contains neurons that respond selectively to faces3, and that it participates in emotion4,5 and social behaviour6. Although studies in epileptic patients support its role in emotion7, determination of the amygdala's function in humans has been hampered by the rarity of patients with selective amygdala lesions8. Here, with the help of one such rare patient, we report findings that suggest the human amygdala may be indispensable to: (1) recognize fear in facial expressions; (2) recognize multiple emotions in a single facial expression; but (3) is not required to recognize personal identity from faces. These results suggest that damage restricted to the amygdala causes very specific recognition impairments, and thus constrains the broad notion that the amygdala is involved in emotion.
A New Phase Correction Method in NMR Imaging Based on Autocorrelation and Histogram Analysis

A new statistical approach to phase correction in NMR imaging is proposed. The proposed scheme consists of first-and zero-order phase corrections each by the inverse multiplication of estimated phase error. The first-order error is estimated by the phase of autocorrelation calculated from the complex valued phase distorted image while the zero-order correction factor is extracted from the histogram of phase distribution of the first-order corrected image. Since all the correction procedures are performed on the spatial domain after completion of data acquisition, no prior adjustments or additional measurements are required. The algorithm can be applicable to most of the phase-involved NMR imaging techniques including inversion recovery imaging, quadrature modulated imaging, spectroscopic imaging, and flow imaging, etc. Some experimental results with inversion recovery imaging as well as quadrature spectroscopic imaging are shown to demonstrate the usefulness of the algorithm.
A Highly-Efficient Memory-Compression Scheme for GPU-Accelerated Intrusion Detection Systems

Pattern Matching is a computationally intensive task used in many research fields and real world applications. Due to the ever-growing volume of data to be processed, and increasing link speeds, the number of patterns to be matched has risen significantly. In this paper we explore the parallel capabilities of modern General Purpose Graphics Processing Units (GPGPU) applications for high speed pattern matching. A highly compressed failure-less Aho-Corasick algorithm is presented for Intrusion Detection Systems on off-the-shelf hardware. This approach maximises the bandwidth for data transfers between the host and the Graphics Processing Unit (GPU). Experiments are performed on multiple alphabet sizes, demonstrating the capabilities of the library to be used in different research fields, while sustaining an adequate throughput for intrusion detection systems or DNA sequencing. The work also explores the performance impact of adequate prefix matching for alphabet sizes and varying pattern numbers achieving speeds up to 8Gbps and low memory consumption for intrusion detection systems.
Artificial Bee Colony Algorithm to improve brain MR Image Segmentation

Image segmentation is a primary step in image analysis used to separate the input image into meaningful regions. MRI is an advanced medical imaging technique widely used in detecting brain tumors. Segmentation of Brain MR image is a complex task. Among the many approaches developed for the segmentation of MR images, a popular method is fuzzy C-mean (FCM). In the proposed method, Artificial Bee Colony (ABC) algorithm is used to improve the efficiency of FCM on abnormal brain images.
Transition control of tilt rotor unmanned aerial vehicle based on multi-model adaptive method

Tilt rotor unmanned aerial vehicle (TRUAV) with ability of hovering and high-speed cruise has attached much attention, but its transition control is still a difficult point because of varying dynamics. This paper proposes a multi-model adaptive control (MMAC) method for a quad-TRUAV, and the stability in the transition procedure could be ensured by considering corresponding dynamics. For safe transition, tilt corridor is considered firstly, and actual flight status should locate within it. Then, the MMAC controller is constructed according to mode probabilities, which are calculated by solving a quadratic programming problem based on a set of input- output plant models. Compared with typical gain scheduling control, this method could ensure transition stability more effectively.
Kettlebell swing targets semitendinosus and supine leg curl targets biceps femoris: an EMG study with rehabilitation implications.

The medial hamstring muscle has the potential to prevent excessive dynamic valgus and external rotation of the knee joint during sports. Thus, specific training targeting the medial hamstring muscle seems important to avoid knee injuries.



The aim was to investigate the medial and lateral hamstring muscle activation balance during 14 selected therapeutic exercises.



The study design involved single-occasion repeated measures in a randomised manner. Sixteen female elite handball and soccer players with a mean (SD) age of 23 (3) years and no previous history of knee injury participated in the present study. Electromyographic (EMG) activity of the lateral (biceps femoris - BF) and medial (semitendinosus - ST) hamstring muscle was measured during selected strengthening and balance/coordination exercises, and normalised to EMG during isometric maximal voluntary contraction (MVC). A two-way analysis of variance was performed using the mixed procedure to determine whether differences existed in normalised EMG between exercises and muscles.



Kettlebell swing and Romanian deadlift targeted specifically ST over BF (Δ17-22%, p<0.05) at very high levels of normalised EMG (73-115% of MVC). In contrast, the supine leg curl and hip extension specifically targeted the BF over the ST (Δ 20-23%, p<0.05) at very high levels of normalised EMG (75-87% of MVC).



Specific therapeutic exercises targeting the hamstrings can be divided into ST dominant or BF dominant hamstring exercises. Due to distinct functions of the medial and lateral hamstring muscles, this is an important knowledge in respect to prophylactic training and physical therapist practice.
On regularization parameter estimation under covariate shift

This paper identifies a problem with the usual procedure for L2-regularization parameter estimation in a domain adaptation setting. In such a setting, there are differences between the distributions generating the training data (source domain) and the test data (target domain). The usual cross-validation procedure requires validation data, which can not be obtained from the unlabeled target data. The problem is that if one decides to use source validation data, the regularization parameter is underestimated. One possible solution is to scale the source validation data through importance weighting, but we show that this correction is not sufficient. We conclude the paper with an empirical analysis of the effect of several importance weight estimators on the estimation of the regularization parameter.
A New Constant Factor Approximation to Construct Highly Fault-Tolerant Connected Dominating Set in Unit Disk Graph

This paper proposes a new polynomial time constant factor approximation algorithm for a more-a-decade-long open NP-hard problem, the minimum four-connected <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>-dominating set problem in unit disk graph UDG with any positive integer <inline-formula> <tex-math notation="LaTeX">$m \geq 1$ </tex-math></inline-formula> for the first time in the literature. We observe that it is difficult to modify the existing constant factor approximation algorithm for the minimum three-connected <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>-dominating set problem to solve the minimum four-connected <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>-dominating set problem in UDG due to the structural limitation of Tutte decomposition, which is the main graph theory tool used by Wang <i>et al.</i> to design their algorithm. To resolve this issue, we first reinvent a new constant factor approximation algorithm for the minimum three-connected <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>-dominating set problem in UDG and later use this algorithm to design a new constant factor approximation algorithm for the minimum four-connected <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>-dominating set problem in UDG.
Performance Improvement in the Axial Flux-Segmented Rotor-Switched Reluctance Motor

Axial flux-segmented rotor-switched reluctance motor (SSRM) topology could be a potential candidate for in-wheel electric vehicle application. This topology has the advantage of the increased active surface area for the torque production as compared to the radial flux SSRM for a given volume. To improve the performance of axial flux SSRM (AFSSRM), various stator slot/rotor segment combinations and winding polarities are studied. It is observed that the torque ripple is high for the designed three-phase, 12/8 pole AFSSRM. Therefore, the influence of the stator pole and rotor segment arc angles on the average torque and the torque ripple is studied. In addition, the adjacent rotor segments are displaced with respect to the stator, to reduce the torque dips in the phase commutation region. The proposed arrangement is analyzed using the quasi-3-D finite-element method-based simulation study and it is found that the torque ripple can be reduced by 38%. Furthermore, the low-frequency harmonic content in the torque output is analyzed and compared. The variation of the axial electromagnetic attractive force with displaced rotor segments is discussed. The effectiveness of the proposed technique is verified experimentally.
Antecedents of big data quality: An empirical examination in financial service organizations

Big data has been acknowledged for its enormous potential. In contrast to the potential, in a recent survey more than half of financial service organizations reported that big data has not delivered the expected value. One of the main reasons for this is related to data quality. The objective of this research is to identify the antecedents of big data quality in financial institutions. This will help to understand how data quality from big data analysis can be improved. For this, a literature review was performed and data was collected using three case studies, followed by content analysis. The overall findings indicate that there are no fundamentally new data quality issues in big data projects. Nevertheless, the complexity of the issues is higher, which makes it harder to assess and attain data quality in big data projects compared to the traditional projects. Ten antecedents of big data quality were identified encompassing data, technology, people, process and procedure, organization, and external aspects.
Modeling and simulation of Electrostatic Adhesion for Wall Climbing Robot

Electrostatic Adhesion (ESA) was chosen as the surface attachment mechanism for Wall Climbing Robot (WCR) for its qualitative advantages. ESA model was developed to account for both parallel-plane and fringing static fields. Such Electrostatic Pad model yields equations governing the ESA force and the geometrical conditions for maximum ESA pressure per pad area. This paper shows that the parameters due to applied voltage, and also geometrical properties, material properties and compliance to wall surface of the Electrostatic Pad do affect the ESA force. The simulation also shows that fringing fields may account up to above 10% of total generated ESA force.
Documents topic classification model in social networks using classifiers voting system

Topic model uncovers abstract topics within texts documents, which is an essential task in text analysis in social networks. However, identifying topics in text documents in social networks is challenging since the texts are short, unlabeled, and unstructured. For this reason, we propose a topic classification system regarding the features of text documents in social networks. The proposed system is based on several machine-learning algorithms and voting system. The accuracy of the system has been tested using text documents that were classified into three topics. The experiment results show that the proposed system guarantees high accuracy rates in documents topic classification.
Burnout and health behaviors in health professionals from seven European countries.

Within an underlying health-impairing process, work stressors exhaust employees' mental and physical resources and lead to exhaustion/burnout and to health problems, with health-impairing behaviors being one of the potential mechanisms, linking burnout to ill health. The study aims to explore the associations between burnout and fast food consumption, exercise, alcohol consumption and painkiller use in a multinational sample of 2623 doctors, nurses and residents from Greece, Portugal, Bulgaria, Romania, Turkey, Croatia and Macedonia, adopting a cross-national approach.



Data are part of the international cross-sectional quantitative ORCAB survey. The measures included the Maslach Burnout Inventory and the Health Behaviors Questionnaire.



Burnout was significantly positively associated with higher fast food consumption, infrequent exercise, higher alcohol consumption and more frequent painkiller use in the full sample, and these associations remained significant after the inclusion of individual differences factors and country of residence. Cross-national comparisons showed significant differences in burnout and health behaviors, and some differences in the statistical significance and magnitude (but not the direction) of the associations between them. Health professionals from Turkey, Greece and Bulgaria reported the most unfavorable experiences.



Burnout and risk health behaviors among health professionals are important both in the context of health professionals' health and well-being and as factors contributing to medical errors and inadequate patient safety. Organizational interventions should incorporate early identification of such behaviors together with programs promoting health and aimed at the reduction of burnout and work-related stress.
Genome sequence and analysis of the tuber crop potato

Potato (Solanum tuberosum L.) is the world’s most important non-grain food crop and is central to global food security. It is clonally propagated, highly heterozygous, autotetraploid, and suffers acute inbreeding depression. Here we use a homozygous doubled-monoploid potato clone to sequence and assemble 86% of the 844-megabase genome. We predict 39,031 protein-coding genes and present evidence for at least two genome duplication events indicative of a palaeopolyploid origin. As the first genome sequence of an asterid, the potato genome reveals 2,642 genes specific to this large angiosperm clade. We also sequenced a heterozygous diploid clone and show that gene presence/absence variants and other potentially deleterious mutations occur frequently and are a likely cause of inbreeding depression. Gene family expansion, tissue-specific expression and recruitment of genes to new pathways contributed to the evolution of tuber development. The potato genome sequence provides a platform for genetic improvement of this vital crop.
Self-organized control of irregular or perturbed network traffic; Optimal Control and Dynamic Games

We present a fluid-dynamic model for the simulation of urban traffic networks with road sections of different lengths and capacities. The model allows one to efficiently simulate the transitions between free and congested traffic, taking into account congestion-responsive traffic assignment and adaptive traffic control. We observe dynamic traffic patterns which significantly depend on the respective network topology. Synchronization is only one interesting example and implies the emergence of green waves. In this connection, we will discuss adaptive strategies of traffic light control which can considerably improve throughputs and travel times, using self-organization principles based on local interactions between vehicles and traffic lights. Similar adaptive control principles can be applied to other queueing networks such as production systems. In fact, we suggest to turn push operation of traffic systems into pull operation: By removing vehicles as fast as possible from the network, queuing effects can be most efficiently avoided. The proposed control concept can utilize the cheap sensor technologies available in the future and leads to reasonable operation modes. It is flexible,
Internally generated cell assembly sequences in the rat hippocampus.

A long-standing conjecture in neuroscience is that aspects of cognition depend on the brain's ability to self-generate sequential neuronal activity. We found that reliably and continually changing cell assemblies in the rat hippocampus appeared not only during spatial navigation but also in the absence of changing environmental or body-derived inputs. During the delay period of a memory task, each moment in time was characterized by the activity of a particular assembly of neurons. Identical initial conditions triggered a similar assembly sequence, whereas different conditions gave rise to different sequences, thereby predicting behavioral choices, including errors. Such sequences were not formed in control (nonmemory) tasks. We hypothesize that neuronal representations, evolved for encoding distance in spatial navigation, also support episodic recall and the planning of action sequences.
Optic Ataxia: From Balint’s Syndrome to the Parietal Reach Region

Optic ataxia is a high-order deficit in reaching to visual goals that occurs with posterior parietal cortex (PPC) lesions. It is a component of Balint's syndrome that also includes attentional and gaze disorders. Aspects of optic ataxia are misreaching in the contralesional visual field, difficulty preshaping the hand for grasping, and an inability to correct reaches online. Recent research in nonhuman primates (NHPs) suggests that many aspects of Balint's syndrome and optic ataxia are a result of damage to specific functional modules for reaching, saccades, grasp, attention, and state estimation. The deficits from large lesions in humans are probably composite effects from damage to combinations of these functional modules. Interactions between these modules, either within posterior parietal cortex or downstream within frontal cortex, may account for more complex behaviors such as hand-eye coordination and reach-to-grasp.
Disguised executable files in spear-phishing emails: detecting the point of entry in advanced persistent threat

In recent years, cyber attacks have caused substantial financial losses and been able to stop fundamental public services. Among the serious attacks, Advanced Persistent Threat (APT) has emerged as a big challenge to the cyber security hitting selected companies and organisations. The main objectives of APT are data exfiltration and intelligence appropriation. As part of the APT life cycle, an attacker creates a Point of Entry (PoE) to the target network. This is usually achieved by installing malware on the targeted machine to leave a back-door open for future access. A common technique employed to breach into the network, which involves the use of social engineering, is the spear phishing email. These phishing emails may contain disguised executable files. This paper presents the disguised executable file detection (DeFD) module, which aims at detecting disguised exe files transferred over the network connections. The detection is based on a comparison between the MIME type of the transferred file and the file name extension. This module was experimentally evaluated and the results show a successful detection of disguised executable files.
Electrochemical Sensors Application Note 2 Design of Electronics for Electrochemical Gas Sensors

This application note gives guidance on the design of electronic circuits for use with SGX Sensortech electrochemical gas sensors. The information is provided for general advice and care should be taken to adapt the circuits to the particular requirements of the application. By following the recommendations of this application note the user should be able to achieve excellent performance with SGX Sensortech electrochemical gas sensors.
A gender recognition system from facial images using SURF based BoW method

Gender recognition from facial images has become one of challenging research problem in computer vision, security, verbal-nonverbal communication and human computer interaction applications nowadays. Because facial images include many information such as gender, facial expressions, age, ethnic origin in computer-aided applications, the success rate of the gender recognition depends on quality of facial images. In this paper, it is proposed a new gender recognition method combining Speed Up Robust Features (SURF) based Bags of Visual Words (BoW) and Support Vector Machine (SVM) algorithm unlike previous work. The method is tested on realistic frontal, left and right face images from modern gender recognition FERET dataset with 3560 samples to see efficiency of the proposed method. Experimental results show that the proposed method can obtain better gender recognition performance on FERET database and the accuracy level of on left and right face images is a bit lower than the average accuracy level of frontal ones.
Transanal pullthrough Soave and Swenson techniques for pediatric patients with Hirschsprung disease

Both the Swenson and the Soave procedures have been adapted as transanal approaches. Our purpose is to compare the outcomes and complications between transanal Swenson and Soave procedures.This clinical analysis involved a retrospective series of 148 pediatric patients with HD from Dec, 2001, to Dec, 2015. Perioperative/operative characteristics, postoperative complications, and outcomes between the 2 groups were analyzed. Students' t-test and chi-squared analysis were performed.In total 148 patients (Soave 69, Swenson 79) were included in our study. Mean follow-up was 3.5 years. There are no significant differences in overall hospital stay and bowel function. We noted significant differences regarding mean operating time, blood loss, and overall complications. We noted significant differences in mean operating time, blood loss, and overall complications in favor of the Swenson group when compared to the Soave group (P < 0.05).According to our results, although transanal pullthrough Swenson cannot reduce overall hospital stay and improve bowel function compared with the Soave procedure, it results in less blood loss, shorter operation time, and a lower complication rate.