Miracle-dz/UniFAR-FTUs huggingface dataset:
fMRI repetition suppression reveals no sensitivity to trait judgments from faces in face perception or theory-of-mind networks

The human face cues a wealth of social information, but the neural mechanisms that underpin social attributions from faces are not well known. In the current fMRI experiment, we used repetition suppression to test the hypothesis that populations of neurons in face perception and theory-of-mind neural networks would show sensitivity to faces that cue distinct trait judgments. Although faces were accurately discriminated based on associated traits, our results showed no evidence that face or theory-of-mind networks showed repetition suppression for face traits. Thus, we do not provide evidence for population coding models of face perception that include sensitivity to high and low trait features. Due to aspects of the experimental design, which bolstered statistical power and sensitivity, we have reasonable confidence that we could detect effects of a moderate size, should they exist. The null findings reported here, therefore, add value to models of neural organisation in social perception by showing instances where effects are absent or small. To test the generalisability of our findings, future work should test different types of trait judgment and different types of facial stimuli, in order to further probe the neurobiological bases of impression formation based on facial appearance.
DeMONS: A DDoS Mitigation NFV Solution

Distributed Denial of Service (DDoS) attacks become increasingly sophisticated and massive in traffic volume. These attacks can be mainly classified as IP Spoofing or Real Source IP. In special, Real Source IP attacks are characterized by the use of malware-infected hosts to simulate real network traffic. Those attacks are constantly evolving, new and sophisticated infection methods are always being employed by attackers. To deal with such constant change, the research community is always searching for advanced approaches to mitigate, or even eliminate, those threats. One of these new approaches, is the use of Network Function Virtualization (NFV). This new paradigm supports the creation of more scalable and flexible, thus resilient, network infrastructures. We, therefore, propose a DDoS mitigation system - called DeMONS - that uses NFV concept together both a dynamic allocation and a reputation mechanisms. The results demonstrate that the employed techniques are a feasible solution to reach higher utilization rates.
Sleep fragmentation delays wound healing in a mouse model of type 2 diabetes

Study Objectives This study tested the hypothesis that sleep fragmentation (SF) delays wound healing in obese B6.BKS(D)-Leprdb/J (db/db) mice with impaired leptin signaling and type 2 diabetes compared with wild-type C57BL/6J (B6) mice. Methods Adult male mice (n = 34) were anesthetized and bilateral full-thickness excisional wounds were created on the back of each mouse. Half of the db/db and B6 mice were housed in SF cages equipped with a bar that moved across the cage floor every 2 min, 12 hr/day for 23 days. The other half of each group of mice was housed in the same room and did not experience SF. The dependent measures were number of days required to achieve wound closure, mRNA expression of four inflammatory mediators, blood glucose, insulin, and corticosterone. Results SF in the db/db mice caused a significant delay in wound healing relative to db/db mice with no SF. Days to achieve 50 per cent wound healing were 13.3 ± 0.4 with SF compared with 10.3 ± 0.7 without SF. All B6 mice achieved 50 per cent wound healing within 6 days and complete healing after 16 days. SF caused a significant increase in wound levels of TNF-α mRNA only in the db/db mice and an increase in corticosterone only in the B6 mice. Conclusions The delayed wound healing in obese, diabetic mice caused by SF is homologous to delayed wound healing in some patients with type 2 diabetes. The results support the interpretation that altered leptinergic signaling and inflammatory proteins contribute to delayed wound healing.
Validation of miR-31-3p Expression to Predict Cetuximab Efficacy When Used as First-Line Treatment in RAS Wild-Type Metastatic Colorectal Cancer

Purpose: MiR-31-3p expression has been shown to be associated with response to anti-EGFR therapy. We investigated the predictive role of this biomarker in the FIRE-3 study population, including its ability to differentiate outcomes between patients receiving anti-EGFR and anti-VEGF therapy. Experimental Design: MiR-31-3p expression was measured in primary tumors obtained from 340 patients with RAS WT mCRC enrolled in the FIRE-3 Trial. This included 164 patients randomized to receive FOLFIRI plus cetuximab (FOLFIRI+Cetux) and 176 to FOLFIRI plus bevacizumab (FOLFIRI+Beva). Patients were divided into subgroups defined by low or high miR-31-3p expression using a prespecified cut-off and by treatment arm. Analyses were performed to assess treatment efficacy by subgroup. Overall survival (OS) and progression-free survival (PFS) were analyzed using Kaplan–Meier curves and Cox regression models. Investigator-assessed objective response (iOR), early tumor shrinkage at 6 weeks (ETS), and centrally reviewed objective response (cOR) were analyzed using logistic regression models. The predictive value of miR-31-3p expression level was assessed through a treatment interaction test using multivariate models adjusted for potential confounding factors. Results: Low miR-31-3p expressers benefited from cetuximab compared with bevacizumab for PFS [HR, 0.74; 95% confidence interval (CI), 0.55–1.00; P = 0.05], OS (HR, 0.61; 95% CI, 0.41–0.88; P < 0.01), iOR (OR, 4.0; 95% CI, 1.9–8.2; P < 0.01), ETS (OR, 4.0; 95% CI, 2.1–7.7; P < 0.01 and cOR (OR, 4.9; 95% CI, 2.3–10.5; P < 0.01) in multivariate analyses. There was no difference in outcomes for high expressers between treatment arms. MiR-31-3p expression level was predictive of treatment effect for PFS (P = 0.03), OS (P = 0.05), iOR (P = 0.02), ETS (P = 0.04), and cOR (P < 0.01). Conclusions: MiR-31-3p expression level was validated as a predictive biomarker of cetuximab therapy efficacy for patients with RAS WT mCRC.
Game change in Indian Health Care System through reforms in medical education curriculum focusing on primary care- Recommendations of a joint working group

Despite the stated aim of Medical Council of India (body regulating medical education in India) to produce an Indian Medical Graduate with requisite knowledge, skills, attitudes, values and responsiveness, so that he or she may function appropriately and effectively as a doctor of first contact of the community while being globally relevant, it appears that we failed. The joint working group extensively consisting of medical teachers have come up with suggestions which may work as the game changer in Indian Health care system. The key is to dedicate medical education towards primary care.
Biprism-based monocular stereovision system parameter optimization

Abstract. Biprism-based monocular stereovision systems can acquire different views of the same object at a single shot, which have several advantages over conventional two-camera systems. To measure the position or recover the shape of the object, effective image pairs have to be captured first, which depends on the field of view of the system. In this paper, we propose a common method for establishing a practical biprism-based monocular stereovision system. The relationship between system parameters and object distance has been analyzed in details. The criterion for parameter optimization and procedure for system setup have been introduced. Experimental results show that our method can effectively calculate different conditions under different parameters and optimize the parameter configurations for the particular system.
Antioxidant and angiotensin I-converting enzyme inhibitory activities of Xuanwei ham before and after cooking and in vitro simulated gastrointestinal digestion

Xuanwei ham is especially rich in a large amount of peptides and free amino acids under the action of protein degradation. Some of these peptides can potentially exert bioactivities of interest for human health. Traditionally, Xuanwei ham should undergo Chinese household cooking treatments before eating. However, it has not been known how its bioactivity changes after cooking and gastrointestinal digestion. Herein, Xuanwei ham is analysed before and after cooking, as well as gastrointestinal digestion being simulated so as to evaluate and compare its effect on antioxidant and angiotensin I-converting enzyme (ACE) inhibitory activities. The antioxidant activity is analysed using five different methods, and results demonstrate that cooking has some negative effects on antioxidative capacity when determined using different antioxidant methods except for a significant increment in 1,1'-diphenyl-2-picrylhydrazyl radical-scavenging activity, while ACE inhibitory activity increases significantly after cooking compared with control samples. After gastrointestinal digestion of samples, there is a significant increment of the antioxidant and ACE inhibitory activities in comparison with control and cooked samples. Particularly, after gastrointestinal digestion, free thiols content and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) radical-cation-scavenging activity of Xuanwei ham, respectively, increase about twice and fourfold, while ACE inhibitory activity increases about twice compared to cooked samples, reaching the value of 83.73%. Therefore, through cooking the antioxidant activity and ACE inhibitory activity of Xuanwei ham are not completely lost and a part of them is still maintained, while gastrointestinal digestion produces a significant enhancement in both bioactivities, highlighting a greater potential for a beneficial physiological effect on human health after eating it.
Resource Allocation Robust to Traffic and Channel Variations in Multihop Wireless Networks

In a multihop wireless network, the traffic at each node and the channel over each link may fluctuate with time. Thus, traditional optimal resource allocation needs to be computed for each moment with instantaneous information of channel states over all links and the traffic rates at all nodes, leading to huge communication overhead and computation cost. To solve this challenge, in this correspondence, we propose to use robust resource allocation, in which the only needed information is the mean and variance of the wireless channels and the traffic rates. In the formulated problem, there are probabilistic constraints, which are difficult to handle. Effective methods are provided that can transform the probabilistic constraints to convex constraints. As the resource allocation does not need instantaneous channel state information or instantaneous traffic rate information, it is robust to channel and traffic variations, with very little communication and computation overhead.
Pseudo-Shape Sensation by Stereoscopic Projection Mapping

Pseudo-haptics employ visual information rather than active haptic devices to generate haptic sensations by exploiting a cross-modal effect in the brain between visual and haptic sensations. To date, little research has focused on pseudo-haptics in the projection mapping research field. This paper investigates the effect of stereoscopic projection mapping on haptic shape perception. We developed a perspective projection mapping technique that visually deforms a physical surface and translates a finger touching the surface. Psychophysical experiments were conducted to investigate the relationship between the degree of deformation and the haptically perceived shape relative to the height and curvature radius. The results indicate that the proposed stereoscopic projection mapping technique can manipulate haptic shape sensation, i.e., perceived deformation increases as the projected deformation increases. In addition, we found that the perceived shape was in between the physical and projected shapes, and converged to both the upper and lower limits. Further analysis revealed that the pseudo-haptic sensation of the curvature radius was stronger than that of the height.
EFETIVIDADE DE PROGRAMAS DE INTERVENÇÃO PARA OBESIDADE COM BASE EM ORIENTAÇÕES PARA ESCOLARES ADOLESCENTES: REVISÃO SISTEMÁTICA

RESUMO Objetivo: Verificar a efetividade de intervenções educacionais baseadas na orientação sobre atividade física e nutrição em escolares. Fonte de dados: Foi realizada busca sistemática em quatro bancos e bases de dados eletrônicos, com artigos publicados entre outubro de 2007 e janeiro de 2017 que abordaram a realização de intervenções educacionais com ênfase em educação nutricional e atividade física ou exercício físico em escolares com idades entre 10 e 19 anos. Síntese dos dados: Foram selecionados 12 artigos para esta revisão. Desses estudos, quatro incluíram a intervenção educacional; quatro associaram intervenções educacionais à inclusão de alimentos saudáveis e atividade física; dois estudos relacionaram as orientações e a atividade física; e, por fim, dois ligaram as orientações com o consumo de alimentos saudáveis. Conclusões: As intervenções baseadas na orientação de atividade física e/ou nutrição foram eficientes, com resultados superiores nos estudos que associaram a prática de atividade física à orientação. Entretanto, observou-se a necessidade da realização de novos estudos que abordem as intervenções educacionais em escolares.
Open-Circuit Fault Diagnosis and Fault- Tolerant Model Predictive Control of SubMultilevel Inverter

This paper proposes a simple open-circuit fault diagnosis and fault-tolerant control approaches for a 15-level submultilevel inverter (SMI). The proposed strategy uses a model predictive control (MPC) to regulate the output current. The fault and its location are detected by comparing the total harmonic distortion (THD) level of the inverter output voltage with the predefined performance metrics. The proposed fault-tolerant control algorithm reconfigures the switching states of the inverter according to the location of fault. Experimental investigations are conducted to show that the proposed control strategy exhibits a good performance in achieving the required control objectives in case of open-circuit faults.
Permethrin Susceptibility for the Vector Culex tarsalis and a Nuisance Mosquito Aedes vexans in an Area Endemic for West Nile Virus

In 2016, we compared susceptibility to the insecticide, permethrin, between the West Nile virus vector, Culex tarsalis Coquillett, and a major nuisance mosquito, Aedes vexans (Meigen), using baseline diagnostic dose and time values determined using the CDC bottle bioassay protocol. Mosquitoes were collected in the wild in Brookings County, South Dakota, situated in the Northern Great Plains of the USA. The determined diagnostic dose and time were then used in 2017 to validate these measurements for the same 2 mosquito species, collected at a second location within Brookings County. The diagnostic dose was determined for multiple time periods and ranged from 27.0 µg/ml at 60 min to 38.4 µg/ml at 30 min. There was no significant difference detected in mortality rates between Cx. tarsalis and Ae. vexans for any diagnostic time and dose. For practical purposes, mosquitoes in 2017 were tested at 38 µg/ml for 30 min; expected mortality rates were 93.38% for Cx. tarsalis and 94.93% for Ae. vexans. Actual 2017 mortality rates were 92.68% for Cx. tarsalis and 96.12% for Ae. vexans, validating the usefulness of this baseline at an additional location and year.
Vocalic Segments Classification Assisted by Mouth Motion Capture

Visual features convey important information for automatic speech recognition (ASR), especially in noisy environment. The purpose of this study is to evaluate to what extent visual data (i.e. lip reading) can enhance recognition accuracy in the multi-modal approach. For that purpose motion capture markers were placed on speakers' faces to obtain lips tracking data during speaking. Different parameterizations strategies were tested and the accuracy of phonemes recognition in different experiments was analyzed. The obtained results and further challenges related to the bi-modal feature extraction process and decision systems employment are discussed.
Hardware Implementation of Power Quality Improvement in Photo-Voltaic Fed Cascaded H-Bridge Multilevel Inverter

Cascaded H-bridge multilevel inverter (CHMLI) is the most popular high/medium power converter for interconnection of renewable energy sources as they require isolated and constant power supply. With the adverse of technology in the field of power electronics more complex system emerges which requires sophisticated algorithms and high performance processors to overcome the emerging challenges. This study aims to eliminate harmonics in a PV fed CHMLI using selective harmonics elimination (SHE) technique with different algorithms such as Newton Raphson (NR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The Real-time implementation of 3 Φ 11 level PV fed CHMLI modelled using MATLABTM/ SIMULINKTM has been carried out using power MOSFET based Intelligent Power Module controlled by FPGA Based Spartan 3 A DSP Board. The effectiveness of harmonic elimination using SHE technique with different algorithms such as NR, PSO and GA have been validated using the laboratory prototype of an 11 level CHMLI. A comparative analysis of these algorithms based on Total Harmonic Distortion (THD) and the selective lower order harmonic contents up to 13th order using FFT analysis have been presented in this study.
Behavioral Variant Frontotemporal Dementia-like Syndrome With Novel Heterozygous TREM2 Frameshift Mutation.

N asu-Hakola disease (NHD) is characterized by largescale destruction of cancellous bone resulting in bone cysts which cause pain, swelling, and sometimes fracture of wrists and ankles in the third decade of life, followed by presenile dementia of frontal lobe type in the fourth decade, sometimes with epileptic seizures. NHD is an autosomal recessive disorder, also sometimes known as polycystic lipomembranous osteodysplasia with sclerosing leukoencephalopathy, or presenile dementia with bone cysts. Magnetic resonance (MR) brain imaging shows frontal myelin loss and massive gliosis, “sclerosing leukoencephalopathy,” as well as basal ganglia calcification. NHD is genetically heterogeneous. In some families homozygous mutations have been identified in the Tyro protein tyrosine kinase–binding protein (TYROBP), also known as DNAX-activation protein 12 or DAP12, gene on chromosome 19q13.12. In other families, homozygous mutations in the triggering receptor expressed on myeloid cells 2 (TREM2) protein gene on chromosome 6p21.1 are described.1 Paloneva et al2 were the first to link TREM2 sequence variants with NHD, since when many reports of homozygous TREM2 mutations causing NHD have appeared.3 TREM2 variants have now been linked to increased susceptibility to Alzheimer disease and possibly also frontotemporal dementia.4 In addition, homozygous and heterozygous TREM2 mutations have been identified in cases of autosomal recessive behavioral variant frontotemporal dementia (bvFTD) without clinical or radiologic evidence of bone involvement.5 We present a patient with a bvFTD-like syndrome with compound heterozygosity for a previously recognized TREM2 missense mutation and a novel TREM2 frameshift mutation.
SciSports: Learning football kinematics through two-dimensional tracking data

SciSports is a Dutch startup company specializing in football analytics. This paper describes a joint research effort with SciSports, during the Study Group Mathematics with Industry 2018 at Eindhoven, the Netherlands. The main challenge that we addressed was to automatically process empirical football players' trajectories, in order to extract useful information from them. The data provided to us was two-dimensional positional data during entire matches. We developed methods based on Newtonian mechanics and the Kalman filter, Generative Adversarial Nets and Variational Autoencoders. In addition, we trained a discriminator network to recognize and discern different movement patterns of players. The Kalman-filter approach yields an interpretable model, in which a small number of player-dependent parameters can be fit; in theory this could be used to distinguish among players. The Generative-Adversarial-Nets approach appears promising in theory, and some initial tests showed an improvement with respect to the baseline, but the limits in time and computational power meant that we could not fully explore it. We also trained a Discriminator network to distinguish between two players based on their trajectories; after training, the network managed to distinguish between some pairs of players, but not between others. After training, the Variational Autoencoders generated trajectories that are difficult to distinguish, visually, from the data. These experiments provide an indication that deep generative models can learn the underlying structure and statistics of football players' trajectories. This can serve as a starting point for determining player qualities based on such trajectory data.
Deciphering Key Pharmacological Pathways of Qingdai Acting on Chronic Myeloid Leukemia Using a Network Pharmacology-Based Strategy

Qingdai, a traditional Chinese medicine (TCM) used for the treatment of chronic myeloid leukemia (CML) with good efficacy, has been used in China for decades. However, due to the complexity of traditional Chinese medicinal compounds, the pharmacological mechanism of Qingdai needs further research. In this study, we investigated the pharmacological mechanisms of Qingdai in the treatment of CML using network pharmacology approaches. First, components in Qingdai that were selected by pharmacokinetic profiles and biological activity predicted putative targets based on a combination of 2D and 3D similarity measures with known ligands. Then, an interaction network of Qingdai putative targets and known therapeutic targets for the treatment of chronic myeloid leukemia was constructed. By calculating the 4 topological features (degree, betweenness, closeness, and coreness) of each node in the network, we identified the candidate Qingdai targets according to their network topological importance. The composite compounds of Qingdai and the corresponding candidate major targets were further validated by a molecular docking simulation. Seven components in Qingdai were selected and 32 candidate Qingdai targets were identified; these were more frequently involved in cytokine-cytokine receptor interaction, cell cycle, p53 signaling pathway, MAPK signaling pathway, and immune system-related pathways, which all play important roles in the progression of CML. Finally, the molecular docking simulation showed that 23 pairs of chemical components and candidate Qingdai targets had effective binding. This network-based pharmacology study suggests that Qingdai acts through the regulation of candidate targets to interfere with CML and thus regulates the occurrence and development of CML.
Security Issues in the Internet of Vehicles

This paper is part of a comprehensive study the main author is currently involved. Although being a major research theme in the last decade, the security aspects of the Vehicular Communications Environment requires further effort in terms of standardization and implementation. Beginning with the security aspects implied in the classical Vehicular Ad Hoc Networks, to the ones in the new Internet of Vehicles evolving concept, as a part of the Internet of Things, all of them are still in research. Classical approaches all have benefits and weakness, but still, even though there are standards in this domain (IEEE 1609 suite, ETSI ITS G5), there is still a lot of progress to be made.