Miracle-dz/UniFAR-FTUs huggingface dataset:
Anterior cingulate cortex connectivity is associated with suppression of behaviour in a rat model of chronic pain

A cardinal feature of persistent pain that follows injury is a general suppression of behaviour, in which motivation is inhibited in a way that promotes energy conservation and recuperation. Across species, the anterior cingulate cortex is associated with the motivational aspects of phasic pain, but whether it mediates motivational functions in persistent pain is less clear. Using burrowing behaviour as an marker of non-specific motivated behaviour in rodents, we studied the suppression of burrowing following painful confirmatory factor analysis or control injection into the right knee joint of 30 rats (14 with pain) and examined associated neural connectivity with ultra-high-field resting state functional magnetic resonance imaging. We found that connectivity between anterior cingulate cortex and subcortical structures including hypothalamic/preoptic nuclei and the bed nucleus of the stria terminalis correlated with the reduction in burrowing behaviour observed following the pain manipulation. In summary, the findings implicate anterior cingulate cortex connectivity as a correlate of the motivational aspect of persistent pain in rodents.
An analysis and comparative user study on interactions in mobile virtual reality games

Mobile Virtual Reality (MVR) makes Virtual Reality games more accessible to a broader audience. Interaction design guidelines and best practices for MVR experiences are available for developers. In this paper, we specifically explore interactions in MVR games, a particular subset of MVR experiences that is becoming popular. A set of MVR games is analyzed with a special focus on head gaze, categorizing and isolating their mechanics implemented with this common MVR technique. This analysis is the basis of a test application in the MVR interactions are implemented and later compared to a traditional game pad controller in three different challenges. A comparative user study has been carried out from the perspective of both gamers and non-gamers facing these challenges. Results show the preferences and performances of the players using all the interactions, highlighting an interesting generalized preference for MVR interactions over the traditional controller in some of the analyzed cases.
Radar Emitter Recognition Based on the Energy Cumulant of Short Time Fourier Transform and Reinforced Deep Belief Network

To cope with the complex electromagnetic environment and varied signal styles, a novel method based on the energy cumulant of short time Fourier transform and reinforced deep belief network is proposed to gain a higher correct recognition rate for radar emitter intra-pulse signals at a low signal-to-noise ratio. The energy cumulant of short time Fourier transform is attained by calculating the accumulations of each frequency sample value with the different time samples. Before this procedure, the time frequency distribution via short time Fourier transform is processed by base noise reduction. The reinforced deep belief network is proposed to employ the input feature vectors for training to achieve the radar emitter recognition and classification. Simulation results manifest that the proposed method is feasible and robust in radar emitter recognition even at a low SNR.
A distributed approach for calculating inundation height based on Dijkstra's algorithm

This research proposed a parallelized approach to scaling up the calculation of inundation height, the minimum sea‐level rise required to inundate a cell on a digital elevation model, which is based on Dijkstra's algorithm for shortest‐path calculations on a graph. Our approach is based on the concepts of spatial decomposition, calculate‐and‐correct, and a master/worker parallelization paradigm. The approach was tested using the U.S. Coastal Relief Model (CRM) dataset from the National Geophysical Data Center on a multicore desktop computer and various supercomputing resources through the U.S. Extreme Science and Engineering Discovery Environment (XSEDE) program. Our parallel implementation not only enables computations that were larger than previously possible, but also significantly outperforms serial implementations with respect to running time and memory footprint as the number of processing cores increases. The efficiency of the scalability seemed to be tied to tile size and flattened out at a certain number of workers.
A decentralized architecture and simple consensus algorithm for autonomous agents

Autonomous agents not only need to make decisions, but also might need to negotiate situations with other autonomous systems and arrange how to proceed. Architecting such systems requires developers to weigh several options and decide, whether a central authority is beneficial or if consensus can be delegated to the agents themselves. We present a decentralized architecture accompanied by a simple consensus algorithm for autonomous agents and demonstrate its application within a simulated traffic system with model cars. We furthermore compare this concept with an older, centralized incarnation, and elaborate advantages and disadvantages.
Regulation of islet glucagon secretion: Beyond calcium

The islet of Langerhans plays a key role in glucose homeostasis through regulated secretion of the hormones insulin and glucagon. Islet research has focused on the insulin‐secreting β‐cells, even though aberrant glucagon secretion from α‐cells also contributes to the aetiology of diabetes. Despite its importance, the mechanisms controlling glucagon secretion remain controversial. Proper α‐cell function requires the islet milieu, where β‐ and δ‐cells drive and constrain α‐cell dynamics. The response of glucagon to glucose is similar between isolated islets and that measured in vivo, so it appears that the glucose dependence requires only islet‐intrinsic factors and not input from blood flow or the nervous system. Elevated intracellular free Ca2+ is needed for α‐cell exocytosis, but interpreting Ca2+ data is tricky since it is heterogeneous among α‐cells at all physiological glucose levels. Total Ca2+ activity in α‐cells increases slightly with glucose, so Ca2+may serve a permissive, rather than regulatory, role in glucagon secretion. On the other hand, cAMP is a more promising candidate for controlling glucagon secretion and is itself driven by paracrine signalling from β‐ and δ‐cells. Another pathway, juxtacrine signalling through the α‐cell EphA receptors, stimulated by β‐cell ephrin ligands, leads to a tonic inhibition of glucagon secretion. We discuss potential combinations of Ca2+, cAMP, paracrine and juxtacrine factors in the regulation of glucagon secretion, focusing on recent data in the literature that might unify the field towards a quantitative understanding of α‐cell function.
Dispersal biophysics and adaptive significance of dimorphic diaspores in the annual Aethionema arabicum (Brassicaceae)

Summary Heteromorphic diaspores (fruits and seeds) are an adaptive bet‐hedging strategy to cope with spatiotemporally variable environments, particularly fluctuations in favourable temperatures and unpredictable precipitation regimes in arid climates. We conducted comparative analyses of the biophysical and ecophysiological properties of the two distinct diaspores (mucilaginous seed (M+) vs indehiscent (IND) fruit) in the dimorphic annual Aethionema arabicum (Brassicaceae), linking fruit biomechanics, dispersal aerodynamics, pericarp‐imposed dormancy, diaspore abscisic acid (ABA) concentration, and phenotypic plasticity of dimorphic diaspore production to its natural habitat and climate. Two very contrasting dispersal mechanisms of the A. arabicum dimorphic diaspores were revealed. Dehiscence of large fruits leads to the release of M+ seed diaspores, which adhere to substrata via seed coat mucilage, thereby preventing dispersal (antitelechory). IND fruit diaspores (containing nonmucilaginous seeds) disperse by wind or water currents, promoting dispersal (telechory) over a longer range. The pericarp properties confer enhanced dispersal ability and degree of dormancy on the IND fruit morph to support telechory, while the M+ seed morph supports antitelechory. Combined with the phenotypic plasticity to produce more IND fruit diaspores in colder temperatures, this constitutes a bet‐hedging survival strategy to magnify the prevalence in response to selection pressures acting over hilly terrain.
Déjà Vu: an empirical evaluation of the memorization properties of ConvNets

Convolutional neural networks memorize part of their training data, which is why strategies such as data augmentation and drop-out are employed to mitigate overfitting. This paper considers the related question of "membership inference", where the goal is to determine if an image was used during training. We consider it under three complementary angles. We show how to detect which dataset was used to train a model, and in particular whether some validation images were used at train time. We then analyze explicit memorization and extend classical random label experiments to the problem of learning a model that predicts if an image belongs to an arbitrary set. Finally, we propose a new approach to infer membership when a few of the top layers are not available or have been fine-tuned, and show that lower layers still carry information about the training samples. To support our findings, we conduct large-scale experiments on Imagenet and subsets of YFCC-100M with modern architectures such as VGG and Resnet.
Impact of federal transfers upon US infant mortality rates: a secondary analysis using a fixed effects regression approach

Objectives In order to improve health outcomes, the federal government allocates hundreds of billions of annual dollars to individual states in order to further the well-being of its citizens. This study examines the impact of such federal intergovernmental transfers on reducing state-level infant mortality rates. Setting Annual data are collected from all 50 US states between 2004 and 2013. Participants Entire US population under the age of 1 year between 2004 and 2013. Primary and secondary outcome measures State-level infant mortality rate, neonatal mortality rate and postneonatal mortality rate. Results Using a fixed effects regression model to control for unmeasurable differences between states, the impact of federal transfers on state-level infant mortality rates is estimated. After controlling for differences across states, increases in per capita federal transfers are significantly associated with lower infant, neonatal and postneonatal mortality rates. Holding all other variables constant, a $200 increase in the amount of federal transfers per capita would save one child’s life for every 10 000 live births. Conclusions Considerable debate exists regarding the role of federal transfers in improving the well-being of children and families. These findings indicate that increases in federal transfers are strongly associated with reductions in infant mortality rates. Such benefits should be carefully considered when state officials are deciding whether to accept or reject federal funds.
Effect of Sudarshan Kriya Pranayama on periodontal status and human salivary beta-defensin-2: An interventional study

Background: Yogic stretching (asana) has been proven to have an effect on salivary human beta-defensin-2 (HBD-2) concentration, which is an antimicrobial peptide and is an inflammatory marker in periodontal disease. Sudarshan Kriya Pranayama (SKP) is a part of yoga which involves rhythmic breathing. Hence, we aim to evaluate the periodontal parameters and to estimate the salivary HBD-2 level before and after SKP program in periodontitis individuals. Materials and Methods: An interventional study was designed and individuals were divided into three groups: Group I – healthy periodontium, Group II – chronic gingivitis, and Group III – chronic periodontitis. SKP was the interventional tool. The clinical parameters such as plaque index (PI), gingival index (GI), probing pocket depth (PPD), clinical attachment level (CAL), and salivary HBD-2 level were analyzed at baseline and 90 days after the SKP practice. Enzyme-linked immunosorbent assay (ELISA) was used to evaluate salivary HBD-2. McNemar's Chi-square, Paired samples t-test, and one-way ANOVA were used to analyze the results. P < 0.05 was considered statistically significant. Results: Following the SKP intervention, the clinical parameters such as PI and GI improved significantly in all the groups (P < 0.001); however, Group III showed a significant reduction as compared to the other groups. The mean baseline salivary HBD-2 levels of Group I, Group II, and Group III were 91.78 ng/μl, 110.22 ng/μl, and 157.63 ng/μl which was further decreased to 95.22 ng/μl, 98.22 ng/μl, and 132.88 ng/μl, respectively, following SKP intervention (P < 0.001). However, Group III had a higher HBD-2 level at 90 th day as compared to other groups. Conclusion: There was an improvement in PI and GI with a decrease in salivary HBD-2 in chronic periodontitis patients following SKP. Hence, SKP can be considered as an adjunct to treatment modality in patients with periodontal disease.
Ipragliflozin Ameliorates Liver Damage in Non-alcoholic Fatty Liver Disease

Abstract Background There are few effective medications for non-alcoholic steatohepatitis (NASH). We investigated the efficacy of ipragliflozin (selective sodium-glucose cotransporter-2 inhibitor [SGLT2I]) for the treatment of patients with type 2 diabetes mellitus (T2DM) complicated by non-alcoholic fatty liver disease (NAFLD). Methods We prospectively enrolled patients with T2DM complicated by NAFLD treated at our institutions from January 2015 to December 2016. Patients received oral ipragliflozin (50 mg/day) once daily for 24 weeks. Body composition was evaluated using an InBody720 analyzer. We used transient elastography to measure liver stiffness and the controlled attenuation parameter for the quantification of liver steatosis in patients with NASH. Results Forty-three patients with T2DM and NAFLD were enrolled (12 with biopsy-proven NASH and 31 with NAFLD diagnosed by ultrasonography). After 24 weeks, body weight, hemoglobin A1c (HbA1c), aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transpeptidase, body fat mass, and steatosis were significantly decreased compared to baseline measurements in patients with NASH. However, muscle mass was not reduced, and liver stiffness showed a statistically insignificant tendency to decrease. NAFLD patients also showed a significant reduction in body weight, HbA1c, AST, and ALT compared to baseline measurements. Conclusion Ipragliflozin may be effective in patients with T2DM complicated by NAFLD.
Preliminary Evaluation of Variables for Communicating Uncertainties Using a Haptic Seat

Recent findings have indicated that the communication of uncertainties is a promising approach for overcoming human factors challenges associated with overtrust issues. The existing approaches, however, are limited in that they require operators to monitor the instrument cluster to perceive changes. As a consequence, significant changes may be missed and operators are regularly interrupted in the execution of non-driving related tasks even if the system is performing well. To overcome this, unobtrusive interfaces are required that are only interruptive if needed. This paper presents a lab-based study aiming at the preliminary evaluation of haptic variables for communicating automation uncertainties using a haptic vehicle seat. The initial results indicate that particularly increases in amplitude as well as a rhythm consisting of long vibrations separated by short breaks are well suited for communicating the exceedance of specified uncertainty thresholds. The communication of decreases in uncertainty using vibration cannot be recommended.
Multifunctional Compounds for Activation of the p53-Y220C Mutant in Cancer.

The p53 protein plays a major role in cancer prevention, and over 50 % of cancer diagnoses can be attributed to p53 malfunction. The common p53 mutation Y220C causes local protein unfolding, aggregation, and can result in a loss of Zn in the DNA-binding domain. Structural analysis has shown that this mutant creates a surface site that can be stabilized using small molecules, and herein a multifunctional approach to restore function to p53-Y220C is reported. A series of compounds has been designed that contain iodinated phenols aimed for interaction and stabilization of the p53-Y220C surface cavity, and Zn-binding fragments for metallochaperone activity. Their Zn-binding affinity was characterized using spectroscopic methods and demonstrate the ability of compounds L4 and L5 to increase intracellular levels of Zn2+ in a p53-Y220C-mutant cell line. The in vitro cytotoxicity of our compounds was initially screened by the National Cancer Institute (NCI-60), followed by testing in three stomach cancer cell lines with varying p53 status', including AGS (WTp53), MKN1 (V143A), and NUGC3 (Y220C). Our most promising ligand, L5, is nearly 3-fold more cytotoxic than cisplatin in a large number of cell lines. The impressive cytotoxicity of L5 is further maintained in a NUGC3 3D spheroid model. L5 also induces Y220C-specific apoptosis in a cleaved caspase-3 assay, reduces levels of unfolded mutant p53, and recovers p53 transcriptional function in the NUGC3 cell line. These results show that these multifunctional scaffolds have the potential to restore wild-type function in mutant p53-Y220C.
Fast-BoW: Scaling Bag-of-Visual-Words Generation

The bag-of-visual-words (BoW) generation is a widely used unsupervised feature extraction method for the variety of computer vision applications. However, space and computational complexity of bag-of-visual-words generation increase with an increase in the size of the dataset because of computational complexities involved in underlying algorithms. In this paper, we present Fast-BoW, a scalable method for BoW generation for both hard and soft vector-quantization with time complexities O(|h| log2 k) and O(|h|k), respectively1. We replace the process of finding the closest cluster center with a softmax classifier which improves the cluster boundaries over k-means and also can be used for both hard and soft BoW encoding. To make the model compact and faster, we quantize the real weights into integer weights which can be represented using few bits (2−8) only. Also, on the quantized weights, we apply the hashing to reduce the number of multiplications which makes the process further faster. We evaluated the proposed approach on several public benchmark datasets. The experimental results outperform the existing hierarchical clustering tree-based approach by ≈ 12 times.
A scheme for the simulation of networked agent systems modeled by timed hybrid Petri nets

A novel scheme for simulating networked agent systems is presented. In this approach, the system is composed of identical communicating agents, which have multi-role capabilities in such a manner that they can perform diverse tasks, according to a given execution context. The agent’s behavior is modeled using a timed hybrid Petri net (THPN) whose evolution, valid for all the agents, is computed off-line using Matlab. The agents are interconnected and simulated in a Java platform using the JADE middle-ware.
Evaluation of a Third-Party Logistics (3PL) Provider Using a Rough SWARA-WASPAS Model Based on a New Rough Dombi Aggregator

For companies active in various sectors, the implementation of transport services and other logistics activities has become one of the key factors of efficiency in the total supply chain. Logistics outsourcing is becoming more and more important, and there is an increasing number of third party logistics providers. In this paper, logistics providers were evaluated using the Rough SWARA (Step-Wise Weight Assessment Ratio Analysis) and Rough WASPAS (Weighted Aggregated Sum Product Assessment) models. The significance of the eight criteria on the basis of which evaluation was carried out was determined using the Rough SWARA method. In order to allow for a more precise consensus in group decision-making, the Rough Dombi aggregator was developed in order to determine the initial rough matrix of multi-criteria decision-making. A total of 10 logistics providers dealing with the transport of dangerous goods for chemical industry companies were evaluated using the Rough WASPAS approach. The obtained results demonstrate that the first logistics provider is also the best one, a conclusion confirmed by a sensitivity analysis comprised of three parts. In the first part, parameter ρ was altered through 10 scenarios in which only alternatives four and five change their ranks. In the second part of the sensitivity analysis, a calculation was performed using the following approaches: Rough SAW (Simple Additive Weighting), Rough EDAS (Evaluation Based on Distance from Average Solution), Rough MABAC (MultiAttributive Border Approximation Area Comparison), and Rough TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). They showed a high correlation of ranks determined by applying Spearman’s correlation coefficient in the third part of the sensitivity analysis.
People Like Me

Increases in data complexity in personal informatics systems require new ways of contextualizing personal data to facilitate meaningful reflection. An emerging approach for providing such context includes augmenting one's personal data with the data of others "like them" to help individuals make sense of their data. However, we do not yet understand how an individual's self-reflection process is affected when the data of others is made available. In this paper, we investigate how people reflect on three types of personal data when presented alongside a large set of aggregated data of multiple cohorts. We conducted personal and cohort data reviews using a subset of participants from a mobile-sensing study that collected physical activity, digital social activity, and perceived stress, from 47 students over three weeks. Participants preferred to use characteristics of the data (e.g., maxima, minima) and graphical presentation (e.g., appearance of trends) along with demographic identities (e.g., age, gender) when relating to cohorts. We further characterize how participants incorporated cohort data into their self-reflection process, and conclude with discussion of the implications for personal informatics systems that leverage the data of "people like me" to enable meaningful reflection.
Heading in soccer increases serum neurofilament light protein and SCAT3 symptom metrics

Objectives To determine the effect of heading a soccer ball on serum neurofilament light (NF-L) protein, plasma tau protein and symptom metrics including total number of symptoms reported and symptom severity scores on the Standardized Concussion Assessment Tool— 3rd edition (SCAT3). Methods Eleven male collegiate soccer players were recruited to take part in three experimental conditions including heading, sham and control conditions. Participants were required to perform 40 headers in 20 min in the heading condition, and control 40 soccer balls directed at them with their hands, chest or thigh in the sham condition. No ball contact was made during the control condition. Blood sampling and SCAT3 symptom assessments were completed prior to and 1 hour following conditions. A subset of participants returned 3 weeks following the heading condition for blood sampling. Results NF-L was elevated at 1 hour (p=0.004) and 1 month (p=0.04) following the heading condition, and at 1 hour (p=0.02) following the control condition. Tau levels remained unchanged following all conditions. The total number of symptoms (TS) and symptom severity (SS) scores from the SCAT3 were both elevated following the heading condition (p=0.01 and p=0.03, respectively). Both TS and SS decreased following sham (p=0.04 and p=0.04) and control conditions (p=0.04 and p=0.04). Conclusion An acute bout of soccer heading is associated with increased NF-L concentrations at 1 hour and 1 month following the session and can lead to symptoms commonly reported following sport-related concussion.