Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Perceived Image Quality Using Steady-State Visual Evoked Potentials and Spatio-Spectral Decomposition

Steady-state visual evoked potentials (SSVEPs) are neural responses, measurable using electroencephalography (EEG), that are directly linked to sensory processing of visual stimuli. In this paper, SSVEP is used to assess the perceived quality of texture images. The EEG-based assessment method is compared with conventional methods, and recorded EEG data are correlated to obtained mean opinion scores (MOSs). A dimensionality reduction technique for EEG data called spatio-spectral decomposition (SSD) is adapted for the SSVEP framework and used to extract physiologically meaningful and plausible neural components from the EEG recordings. It is shown that the use of SSD not only increases the correlation between neural features and MOS to $r=-0.93$ , but also solves the problem of channel selection in an EEG-based image-quality assessment.
Spatio-Temporal Network Traffic Estimation and Anomaly Detection Based on Convolutional Neural Network in Vehicular Ad-Hoc Networks

Over the last decade, vehicular ad-hoc networks (VANETs) have received a greater attention in academia and industry due to their influence in intelligent transportation systems. Providing reliability and security to the VANET is essential in order to guarantee the efficiency of its applications. Anomaly detection has become a challenging problem due to the unique environment of VANETs with quick movement and short-lived link. In this paper, a method using the spatio-temporal feature of network traffic is proposed to implement network traffic estimation at first, and on this basis, an anomaly detection algorithm is put forward. The convolutional neural network is employed to extract the spatio-temporal features of the traffic matrix. In terms of the extracted features, network traffic is estimated by using a fully connected architecture as the output layer. Then, a threshold-based separation method is used to implement anomaly detection. The preliminary experiments comparing the proposed method with other machine learning-based methods show the effectiveness of the proposed anomaly detection method.
Analyzing Android App Privacy With GP-PP Model

Mobile devices have become the major platforms of the Internet of Things applications for industrial enterprises. The ever-increasing number of Android Phone users has raised great concerns regarding the privacy issues related to the use of Android Apps. Freely downloadable apps requesting a large number of permissions have resulted in severe privacy concerns. While granting the permissions, users usually do not read their details or are unable to judge an app based on the permissions requested. In this paper, we address the privacy issues by categorizing app permissions into privacy invasive and generic permissions and validating the classification using the Naïve Bayes classifier.
Pharmacokinetics of intravenous flumetasone and effects on plasma hydrocortisone concentrations and inflammatory mediators in the horse

BACKGROUND Flumetasone is a potent corticosteroid reportedly used in horses to decrease inflammation associated with strenuous exercise. There are currently no reports describing the use of this drug in horses. OBJECTIVES To describe the pharmacokinetics and effects on cortisol and eicosanoid concentrations, following administration of flumetasone to exercised horses. STUDY DESIGN Parallel design. METHODS Twelve exercised horses received a single i.v. administration of 5 mg of flumetasone. Blood and urine samples were collected before and for 72 h post-drug administration for determination of flumetasone and cortisol concentrations. Whole blood samples were collected at various time and challenged with lipopolysaccharide, calcium ionophore or methanol to induce ex vivo synthesis of eicosanoids. Concentrations of flumetasone, cortisol and eicosanoids were measured using LC-MS/MS and pharmacokinetic/pharmacodynamic analysis performed. RESULTS Flumetasone was detected for 23.5 ± 1.73 h in blood. The volume of distribution at steady state, systemic clearance and elimination half-life was 5.90 ± 0.200 L/kg, 30.7 ± 0.166 mL/min/kg and 4.84 ± 0.83 h respectively. Cortisol concentrations were still suppressed at last time point collected (72 h). For cortisol, Kin , Kout and the t1/2out were 30.3 ± 1.56 ng/mL × h, 0.331 ± 0.02 1/h and 2.1 h respectively. Stimulation with lipopolysaccharide resulted in a decrease in TXB2 , PGF2 , LTB4 , 15-HETE and 5-HETE for up to 72 h and PGE2 for 24 h post-flumetasone administration. Stimulation of whole blood with calcium ionophore resulted in a decrease in LTB4 for up to 6 h and 15-HETE at 8 h. MAIN LIMITATIONS Lack of sample collection for determination of biomarker concentrations beyond 72 h and the use of a single sample for determination of baseline cortisol concentrations. CONCLUSIONS Flumetasone is rapidly cleared from blood following administration to horses. It is a potent anti-inflammatory with prolonged effects on production of cortisol and other inflammatory mediators.
A Loss-of-Function HCN4 Mutation Associated With Familial Benign Myoclonic Epilepsy in Infancy Causes Increased Neuronal Excitability

HCN channels are highly expressed and functionally relevant in neurons and increasing evidence demonstrates their involvement in the etiology of human epilepsies. Among HCN isoforms, HCN4 is important in cardiac tissue, where it underlies pacemaker activity. Despite being expressed also in deep structures of the brain, mutations of this channel functionally shown to be associated with epilepsy have not been reported yet. Using Next Generation Sequencing for the screening of patients with idiopathic epilepsy, we identified the p.Arg550Cys (c.1648C>T) heterozygous mutation on HCN4 in two brothers affected by benign myoclonic epilepsy of infancy. Functional characterization in heterologous expression system and in neurons showed that the mutation determines a loss of function of HCN4 contribution to activity and an increase of neuronal discharge, potentially predisposing to epilepsy. Expressed in cardiomyocytes, mutant channels activate at slightly more negative voltages than wild-type (WT), in accordance with borderline bradycardia. While HCN4 variants have been frequently associated with cardiac arrhythmias, these data represent the first experimental evidence that functional alteration of HCN4 can also be involved in human epilepsy through a loss-of-function effect and associated increased neuronal excitability. Since HCN4 appears to be highly expressed in deep brain structures only early during development, our data provide a potential explanation for a link between dysfunctional HCN4 and infantile epilepsy. These findings suggest that it may be useful to include HCN4 screening to extend the knowledge of the genetic causes of infantile epilepsies, potentially paving the way for the identification of innovative therapeutic strategies.
Creamino: A Cost-Effective, Open-Source EEG-Based BCI System

This paper presents an open source framework called Creamino. It consists of an Arduino-based cost-effective quick-setup EEG platform built with off-the-shelf components and a set of software modules that easily allow users to connect this system to Simulink or BCI-oriented tools (such as BCI2000 or OpenViBE) and set up a wide number of neuroscientific experiments. Creamino is capable of processing multiple EEG channels in real-time and operates under Windows, Linux, and Mac OS X in real-time on a standard PC. Its objective is to provide a system that can be readily fabricated and used for neurophysiological experiments and, at the same time, can serve as the basis for development of novel BCI platforms by accessing and modifying its open source hardware and software libraries. Schematics, gerber files, bill of materials, source code, software modules, demonstration videos, and instructions on how to use these modules are available free of charge for research and educational purposes online at https://github.com/ArcesUnibo/creamino. Application cases show how the system can be used for neuroscientific or BCI experiments. Thanks to its low production cost and its compatibility with open-source BCI tools, the system presented is particularly suitable for use in BCI research and educational applications.
Auto-Tuning for the Era of Relatively High Bandwidth Memory Architectures: A Discussion Based on an FDM Application

This paper focuses on 3D stacking memory for obtaining higher memory access bandwidth to establish relatively high data movement performance instead of increasing computations in the post-Moore era. A revolution in conventional algorithms to utilize higher bandwidths is required in this era. Algorithms with conventional greedy-computational ability (FLOPS) have to be restructured to obtain algorithms with greedy-data movement ability (BYTES) in this era. Further, auto-tuning (AT) must also remain a crucial technology for the era of BYTES. As evidence supporting this argument, we choose a memory-bounded application from the Finite Difference Method (FDM) with AT facility to demonstrate the effectiveness of AT in a high bandwidth memory architecture. The Fujitsu PRIMEHPC FX10 and the Fujitsu PRIMEHPC FX100, machines with similar architectures but different memory bandwidth, are presented as evidence. The results of performance evaluation indicate an important aspect, when the Bytes per Flop (B/F) ratio is greater than 0.475, a high B/F kernel is faster than a low B/F kernel. The speedup factor in this case is not small, as it is as much as 4.47x. This indicates that the current trend of code optimization will change in the era of relatively high bandwidth memory architectures.
Venomix: a simple bioinformatic pipeline for identifying and characterizing toxin gene candidates from transcriptomic data

The advent of next-generation sequencing has resulted in transcriptome-based approaches to investigate functionally significant biological components in a variety of non-model organism. This has resulted in the area of “venomics”: a rapidly growing field using combined transcriptomic and proteomic datasets to characterize toxin diversity in a variety of venomous taxa. Ultimately, the transcriptomic portion of these analyses follows very similar pathways after transcriptome assembly often including candidate toxin identification using BLAST, expression level screening, protein sequence alignment, gene tree reconstruction, and characterization of potential toxin function. Here we describe the Python package Venomix, which streamlines these processes using common bioinformatic tools along with ToxProt, a publicly available annotated database comprised of characterized venom proteins. In this study, we use the Venomix pipeline to characterize candidate venom diversity in four phylogenetically distinct organisms, a cone snail (Conidae; Conus sponsalis), a snake (Viperidae; Echis coloratus), an ant (Formicidae; Tetramorium bicarinatum), and a scorpion (Scorpionidae; Urodacus yaschenkoi). Data on these organisms were sampled from public databases, with each original analysis using different approaches for transcriptome assembly, toxin identification, or gene expression quantification. Venomix recovered numerically more candidate toxin transcripts for three of the four transcriptomes than the original analyses and identified new toxin candidates. In summary, we show that the Venomix package is a useful tool to identify and characterize the diversity of toxin-like transcripts derived from transcriptomic datasets. Venomix is available at: https://bitbucket.org/JasonMacrander/Venomix/.
Effects of ethical leadership on nurses’ service behaviors

Background: Nurses’ service behaviors have critical implications for hospitals. However, few studies had adequate ethical considerations of service behaviors and accounted for how organizational or individual antecedents can induce nurses to engage in service behaviors. In addition, they mainly focused on the one side of role-prescribed or extra-role service behavior. Objective: This study aims to explore the chained mediation effect of ethical climate and moral sensitivity on the relationship between organizational ethical leadership and nurses’ service behaviors and to examine the relationship, from a comparative view, of the role-prescribed service behavior and extra-role service behavior. Methods: In all, 476 nurses from three tertiary hospitals were investigated with the Ethical Leadership Scale, Ethical Climate Scale, Moral Sensitivity Questionnaire and Service Behavior Questionnaire. Structural equation modeling was adopted to analyze the data. SPSS and Mplus statistical software was used in the data analysis. Ethical considerations: Approval was obtained from the Ethics Committee at School of Nursing, Hebei Medical University. Data privacy and confidentiality were maintained and assured by obtaining subjects’ informed consent to participate in the research before data collection. Results: The effects of ethical leadership on nurses’ service behaviors are mediated by two variables in turn: ethical climate and nurses’ moral sensitivity. Ethical climate and moral sensitivity partially mediated the relationship between ethical leadership and nurses’ role-prescribed service behavior and fully mediated the relationship between ethical leadership and nurses’ extra-role service behavior. Conclusion: Organizational ethical leadership positively affected ethical climate, which positively affected nurses’ moral sensitivity and affected both their role-prescribed service behavior and extra-role service behavior.
Predictive Utility of an Emergency Department Decision Support Tool in Patients With Active Suicidal Ideation

Emergency department (ED) clinicians routinely decide the disposition of patients with suicidal ideation, with potential consequences for patient safety, liability, and system costs and resources. An expert consensus panel recently created a 6-item decision support tool for patients with passive or active suicidal ideation. Individuals scoring a 0 (exhibiting none of the tool’s 6 items) are considered “lower risk” and suitable for discharge, while those with non-0 scores are considered “elevated risk” and should receive further evaluation. The current study tested the predictive utility of this tool using existing data from the Emergency Department Safety Assessment and Follow-up Evaluation. ED patients with active suicide ideation (n = 1368) were followed for 12 months after an index visit using telephone assessment and medical chart review. About 1 in 5 patients had attempted suicide during follow-up. Because of the frequency of serious warning signs and risk factors in this population, only three patients met tool criteria for “lower risk” at baseline. The tool had perfect sensitivity, but exceptionally low specificity, in predicting suicidal behavior within 6 weeks and 12 months. In logistic regression analyses, several tool items were significantly associated with suicidal behavior within 6 weeks (suicide plan, past attempt) and 12 months (suicide plan, past attempt, suicide intent, significant mental health condition, irritability/agitation/aggression). Although the tool did not perform well as a binary instrument among those with active suicidal ideation, having a suicide plan identified almost all attempters while suicide plan and past attempt identified over four-fifths of near-term attempts.
Insufficient Sleep Syndrome: Is it time to classify it as a major noncommunicable disease?

Over the last three to four decades, it has been observed that the average total number of hours of sleep obtained per night by normal individuals have decreased. Concomitantly, global figures indicate that insufficient sleep is associated with serious adverse health and social outcomes. Moreover, insufficient sleep has been linked to seven of the fifteen leading causes of death. Additionally, current evidence suggests that sleep plays a significant role in determining cognitive performance and workplace productivity. There is a great need for a systematic analysis of the economic impact of insufficient sleep, particularly given current evidence that this phenomenon, as well as the poor sleep hygiene practices which produce it, is increasing worldwide. This paper takes the view that health authorities around the world need to raise the general awareness of benefits of sleep. There is considerable scope for research into both the public health impact as well as the macroeconomic consequences of insufficient sleep syndrome (ISS). Additionally, various models which estimate the undiagnosed burden of ISS on the GDP (gross domestic product) are needed to prioritize health issues and to highlight the national policies that are necessary to combat this medical problem. Sleep insufficiency has been declared to be a ‘public health epidemic’; therefore, we propose ISS as a potential noncommunicable disease. This review elaborates on this topic further, exploring the causes and consequences of insufficient sleep, and thus providing a perspective on the policies that are needed as well as the research that will be required to support and justify these policies.
Modeled Tracheidograms Disclose Drought Influence on Pinus sylvestris Tree-Rings Structure From Siberian Forest-Steppe

Wood formation allows trees to adjust in a changing climate. Understanding what determine its adjustment is crucial to evaluate impacts of climatic changes on trees and forests growth. Despite efforts to characterize wood formation, little is known on its impact on the xylem cellular structure. In this study we apply the Vaganov-Shashkin model to generate synthetic tracheidograms and verify its use to investigate the formation of intra-annual density fluctuations (IADF), one of the most frequent climate tree-ring markers in drought-exposed sites. Results indicate that the model can produce realistic tracheidograms, except for narrow rings (<1 mm), when cambial activity stops due to an excess of drought or a lack of growth vigor. These observations suggest that IADFs are caused by a release of drought limitation to cells formation in the first half of the growing season, but that narrow rings are indicators of an even more extreme and persistent water stress. Taking the example of IADFs formation, this study demonstrated that the Vaganov-Shashkin model is a useful tool to study the climatic impact on tree-ring structures. The ability to produce synthetic tracheidogram represents an unavoidable step to link climate to tree growth and xylem functioning under future scenarios.
An Iterative Channel Estimation Method for Multi-Cell Massive MIMO Systems

For a massive multiple-input multiple-output system in the multi-cell scenarios, it generally suffers from pilot contamination due to the fact that the adjacent cells may use the same pilot sequences. In order to reduce the impact of pilot contamination on the system performance, a novel iterative channel estimation method is proposed. Specifically, in the proposed method, besides the pilot sequences, the data symbols decoded with high reliability are selected to enhance the channel estimation. Furthermore, the selection criteria are derived to determine which data symbols are reliably decoded. The simulation results show that the proposed method can effectively improve the channel estimation accuracy and the error performance of the considered systems.
Stress, Psychological Resources, and HPA and Inflammatory Reactivity During Late Adolescence

Abstract Psychosocial stress during childhood and adolescence is associated with alterations in the hypothalamic–pituitary–adrenal (HPA) axis and with heightened inflammation, both of which are implicated in poor health; however, factors that may protect against these effects relatively early in life are not well understood. Thus, we examined whether psychosocial resources protect against stress-related alterations in the HPA axis and heightened inflammation in a sample of 91 late adolescents. Participants completed measures of various stressors (major life events, daily interpersonal stress, early adversity), and psychosocial resources (mastery, optimism, self-esteem, and positive reappraisal). They also completed the Trier Social Stress Test and provided saliva and blood samples for the assessment of cortisol and interleukin-6 reactivity. Each of the stressors was associated with lower cortisol reactivity. Additionally, associations with major life events and daily stress were moderated by psychological resources, such that more life events and daily stress were associated with decreased HPA reactivity among adolescents with lower levels of psychological resources, but not among those with higher levels of psychological resources. This pattern of findings was observed only for cortisol reactivity and not for interleukin-6 reactivity. Findings suggest that psychological resources may counteract the effects of certain adversity-related decreases in cortisol reactivity.
Colourising Point Clouds Using Independent Cameras

We investigate the problem of colourising a point cloud using an arbitrary mobile mapping device and an independent camera. The loose coupling of sensors creates a number of challenges related to timing, point visibility, and colour determination. We address each of these problems and demonstrate our resulting algorithm on data captured using sensor payloads mounted to hand-held, aerial, and ground systems, illustrating the “plug-and-play” portability of the method.
Urinary angiotensinogen level is increased in renal transplant recipients with masked hypertension and is correlated with left ventricular mass index and albuminuria in these patients

Activation of the local renin‐angiotensin system (RAS) is an independent risk factor for the development of proteinuria and left ventricular hypertrophy (LVH) more commonly seen in masked hypertensives. It has been reported that urinary angiotensinogen (UAGT) level provides a specific index of the intrarenal RAS status. The aim of this study was to evaluate the association between UAGT and left ventricular mass index (LVMI) and urinary albumin‐creatinine ratio (UACR) in renal transplant recipients (RTRs) with masked hypertension (HT). A total of 116 non‐diabetic‐treated hypertensive RTRs were included in this study. The patients were divided into two groups: masked hypertensives and controlled hypertensives. Forty‐two (36.2%) of RTRs had masked HT. Mean UACR and LVMI levels were higher in RTRs with masked HT than in RTRs with controlled HT (P < 0.001). UAGT level was also higher in masked hypertensives compared to controlled hypertensives (P < 0.001). Multivariable regression analysis showed that UAGT was positively correlated with UACR (β = 0.024, P = 0.001) and LVMI (β = 0.082, P = 0.001) in masked hypertensives. Consequently, masked HT was considerably frequent (36.2%) in treated hypertensive RTRs and high UAGT levels accompanied by high albuminuria and LVMI levels were seen in these patients. Overproduction of the UAGT may play a pivotal role in the development of LVH and proteinuria in masked hypertensives.
Semantic Data Querying over NoSQL Databases with Apache Spark

The rapid growth of semantic data in the form of RDF triples demands a scalable distributed storage and efficient query processing engine for its management and reuse. To overcome the limitation of native RDF stores and traditional relational database management systems and scale adequately with the exponential increase in the size of RDF datasets, Big Data processing infrastructure like Hadoop with MapReduce have been used. NoSQL databases such as HBase and Cassandra for storing large-scale RDF data and in-memory data processing to execute SPARQL query as SQL query using Apache Spark is proposed in this paper. This paper presents techniques for distributed RDF data storage and querying schemes for HBase and Cassandra clusters. We also present a compiler that translates SPARQL queries into their Spark SQL equivalent for execution. An empirical comparison of HBase and Cassandra systems using datasets and queries from Berlin SPARQL Benchmark (BSBM) and SPARQL Performance Benchmark (SP2Bench) on Microsoft Azure cloud is presented.