Miracle-dz/UniFAR-FTUs huggingface dataset:
Iktishaf+: A Big Data Tool with Automatic Labeling for Road Traffic Social Sensing and Event Detection Using Distributed Machine Learning

Digital societies could be characterized by their increasing desire to express themselves and interact with others. This is being realized through digital platforms such as social media that have increasingly become convenient and inexpensive sensors compared to physical sensors in many sectors of smart societies. One such major sector is road transportation, which is the backbone of modern economies and costs globally 1.25 million deaths and 50 million human injuries annually. The cutting-edge on big data-enabled social media analytics for transportation-related studies is limited. This paper brings a range of technologies together to detect road traffic-related events using big data and distributed machine learning. The most specific contribution of this research is an automatic labelling method for machine learning-based traffic-related event detection from Twitter data in the Arabic language. The proposed method has been implemented in a software tool called Iktishaf+ (an Arabic word meaning discovery) that is able to detect traffic events automatically from tweets in the Arabic language using distributed machine learning over Apache Spark. The tool is built using nine components and a range of technologies including Apache Spark, Parquet, and MongoDB. Iktishaf+ uses a light stemmer for the Arabic language developed by us. We also use in this work a location extractor developed by us that allows us to extract and visualize spatio-temporal information about the detected events. The specific data used in this work comprises 33.5 million tweets collected from Saudi Arabia using the Twitter API. Using support vector machines, naïve Bayes, and logistic regression-based classifiers, we are able to detect and validate several real events in Saudi Arabia without prior knowledge, including a fire in Jeddah, rains in Makkah, and an accident in Riyadh. The findings show the effectiveness of Twitter media in detecting important events with no prior knowledge about them.
Effectiveness of the Comirnaty (BNT162b2, BioNTech/Pfizer) vaccine in preventing SARS-CoV-2 infection among healthcare workers, Treviso province, Veneto region, Italy, 27 December 2020 to 24 March 2021

Data on effectiveness of the BioNTech/Pfizer COVID-19 vaccine in real-world settings are limited. In a study of 6,423 healthcare workers in Treviso Province, Italy, we estimated that, within the time intervals of 14–21 days from the first and at least 7 days from the second dose, vaccine effectiveness in preventing SARS-CoV-2 infection was 84% (95% confidence interval (CI): 40–96) and 95% (95% CI: 62–99), respectively. These results could support the ongoing vaccination campaigns by providing evidence for targeted communication.
eHMI: Review and Guidelines for Deployment on Autonomous Vehicles

Human–machine interaction is an active area of research due to the rapid development of autonomous systems and the need for communication. This review provides further insight into the specific issue of the information flow between pedestrians and automated vehicles by evaluating recent advances in external human–machine interfaces (eHMI), which enable the transmission of state and intent information from the vehicle to the rest of the traffic participants. Recent developments will be explored and studies analyzing their effectiveness based on pedestrian feedback data will be presented and contextualized. As a result, we aim to draw a broad perspective on the current status and recent techniques for eHMI and some guidelines that will encourage future research and development of these systems.
Anomalous hybridization complementation effect on phonon transport in heterogeneous nanowire cross junction

Controlling phonon transport via its wave nature in nanostructures can achieve unique properties for various applications. In this paper, thermal conductivity of heterogeneous nano cross junction (hetero-NCJ) is studied through molecular dynamics simulation. It is found that decreasing or increasing the atomic mass of four side wires (SWs) severed as resonators, thermal conductivity of hetero-NCJ is enhanced, which is larger than that of homogeneous NCJ (homo-NCJ). Interestingly, by setting two SWs with larger atomic mass and other two SWs with smaller atomic mass, thermal conductivity of hetero-NCJ is abnormally decreased, which is even smaller than that of homo-NCJ. After further non-equilibrium Green’s function calculations, it is demonstrated that origin of increase is attributed to the hybridization broken induced by unidirectional shift of resonant modes. However, the decrease in thermal conductivity originates from hybridization complementation induced by bidirectional shift of resonant modes, which synergistically blocks phonon transport. This work provides a mechanism for further strengthening resonant hybridization effect and manipulating thermal transport.
Employing machine learning and microscopy images of AIB1‐stained biopsy material to assess the 5‐year survival of patients with colorectal cancer

Our purpose was to employ microscopy images of amplified in breast cancer 1 (AIB1)‐stained biopsy material of patients with colorectal cancer (CRC) to: (a) find statistically significant differences (SSDs) in the texture and color of the epithelial gland tissue, between 5‐year survivors and non‐survivors after the first diagnosis and (b) employ machine learning (ML) methods for predicting the CRC‐patient 5‐year survival. We collected biopsy material from 54 patients with diagnosed CRC from the archives of the University Hospital of Patras, Greece. Twenty‐six of the patients had survived 5 years after the first diagnosis. We selected regions of interest containing the epithelial gland at different microscope lens magnifications. We computed 69 textural and color features. Furthermore, we identified features with SSDs between the two groups of patients and we designed a supervised ML system for predicting the CRC‐patient 5‐year survival. Additionally, we employed the VGG16 pretrained convolution neural network to extract deep learning (DL) features, the support vector machines classifier, and the bootstrap cross‐validation method for boosting the accuracy of predicting 5‐year survival. Fourteen features sustained SSDs between the two groups of patients. The supervised ML system achieved 87% accuracy in predicting 5‐year survival. In comparison, the DL system, using images from all magnifications, gave 97% classification accuracy. Glandular texture in 5‐year non‐survivors appeared to be of lower contrast, coarseness, roughness, local pixel correlation, and lower AIB1 variation, all indicating loss of textural definition. The supervised ML system revealed useful information regarding features that discriminate between 5‐year survivors and non‐survivors while the DL system displayed superior accuracy by employing DL features.
Long-Term Iron and Vitamin B12 Deficiency Are Present after Bariatric Surgery, despite the Widespread Use of Supplements

There are few long-term nutritional studies in subjects undergoing bariatric surgery that have assessed weight regain and nutritional deficiencies. In this study, we report data 8 years after surgery on weight loss, use of dietary supplements and deficit of micronutrients in a cohort of patients from five centres in central and northern Italy. The study group consisted of 52 subjects (age: 38.1 ± 10.6 y, 42 females): 16 patients had Roux-en-Y gastric bypass (RYGB), 25 patients had sleeve gastrectomy (SG) and 11 subjects had adjustable gastric banding (AGB). All three bariatric procedures led to sustained weight loss: the average percentage excess weight loss, defined as weight loss divided by excess weight based on ideal body weight, was 60.6% ± 32.3. Despite good adherence to prescribed supplements, 80.7% of subjects (72.7%, AGB; 76.7%, SG; 93.8 %, RYGB) reported at least one nutritional deficiency: iron (F 64.3% vs. M 30%), vitamin B12 (F 16.6% vs. M 10%), calcium (F 33.3% vs. M 0%) and vitamin D (F 38.1% vs. M 60%). Long-term nutritional deficiencies were greater than the general population among men for iron and among women for vitamin B12.
A Particle Filtering Approach for Fault Detection and Isolation of UAV IMU Sensors: Design, Implementation and Sensitivity Analysis

Sensor fault detection and isolation (SFDI) is a fundamental topic in unmanned aerial vehicle (UAV) development, where attitude estimation plays a key role in flight control systems and its accuracy is crucial for UAV reliability. In commercial drones with low maximum take-off weights, typical redundant architectures, based on triplex, can represent a strong limitation in UAV payload capabilities. This paper proposes an FDI algorithm for low-cost multi-rotor drones equipped with duplex sensor architecture. Here, attitude estimation involves two 9-DoF inertial measurement units (IMUs) including 3-axis accelerometers, gyroscopes and magnetometers. The SFDI algorithm is based on a particle filter approach to promptly detect and isolate IMU faulted sensors. The algorithm has been implemented on a low-cost embedded platform based on a Raspberry Pi board. Its effectiveness and robustness were proved through experimental tests involving realistic faults on a real tri-rotor aircraft. A sensitivity analysis was carried out on the main algorithm parameters in order to find a trade-off between performance, computational burden and reliability.
Association of plasma acylcarnitines with insulin sensitivity, insulin secretion, and prediabetes in a biracial cohort

The ability to predict prediabetes, which affects ∼90 million adults in the US and ∼400 million adults worldwide, would be valuable to public health. Acylcarnitines, fatty acid metabolites, have been associated with type 2 diabetes risk in cross-sectional studies of mostly Caucasian subjects, but prospective studies on their link to prediabetes in diverse populations are lacking. Here, we determined the association of plasma acylcarnitines with incident prediabetes in African Americans and European Americans enrolled in a prospective study. We analyzed 45 acylcarnitines in baseline plasma samples from 70 adults (35 African-American, 35 European-American) with incident prediabetes (progressors) and 70 matched controls (non-progressors) during 5.5-year (mean 2.6 years) follow-up in the Pathobiology of Prediabetes in a Biracial Cohort (POP-ABC) study. Incident prediabetes (impaired fasting glucose/impaired glucose tolerance) was confirmed with OGTT. We measured acylcarnitines using tandem mass spectrometry, insulin sensitivity by hyperinsulinemic euglycemic clamp, and insulin secretion using intravenous glucose tolerance test. The results showed that progressors and non-progressors during POP-ABC study follow-up were concordant for 36 acylcarnitines and discordant for nine others. In logistic regression models, beta-hydroxy butyryl carnitine (C4-OH), 3-hydroxy-isovaleryl carnitine/malonyl carnitine (C5-OH/C3-DC), and octenoyl carnitine (C8:1) were the only significant predictors of incident prediabetes. The combined cut-off plasma levels of <0.03 micromol/L for C4-OH, <0.03 micromol/L for C5-OH/C3-DC, and >0.25 micromol/L for C8:1 acylcarnitines predicted incident prediabetes with 81.9% sensitivity and 65.2% specificity. Thus, circulating levels of one medium-chain and two short-chain acylcarnitines may be sensitive biomarkers for the risk of incident prediabetes among initially normoglycemic individuals with parental history of type 2 diabetes.
Modification of the Uranyl Acetate Replacement Staining Protocol for Transmission Electron Microscopy

A uranyl acetate replacement staining protocol has eliminated the need for highly toxic uranyl acetate in the electron microscopy laboratory. However, the method results in undesirable charging effects when viewed under the transmission electron microscope and can be further improved. A modification of the uranyl acetate replacement staining protocol that simplifies the process is described. The modified method takes less time, and produces better contrast and less charging effects compared to the existing uranyl acetate replacement staining protocol.
CSConv2d: A 2-D Structural Convolution Neural Network with a Channel and Spatial Attention Mechanism for Protein-Ligand Binding Affinity Prediction

The binding affinity of small molecules to receptor proteins is essential to drug discovery and drug repositioning. Chemical methods are often time-consuming and costly, and models for calculating the binding affinity are imperative. In this study, we propose a novel deep learning method, namely CSConv2d, for protein-ligand interactions’ prediction. The proposed method is improved by a DEEPScreen model using 2-D structural representations of compounds as input. Furthermore, a channel and spatial attention mechanism (CS) is added in feature abstractions. Data experiments conducted on ChEMBLv23 datasets show that CSConv2d performs better than the original DEEPScreen model in predicting protein-ligand binding affinity, as well as some state-of-the-art DTIs (drug-target interactions) prediction methods including DeepConv-DTI, CPI-Prediction, CPI-Prediction+CS, DeepGS and DeepGS+CS. In practice, the docking results of protein (PDB ID: 5ceo) and ligand (Chemical ID: 50D) and a series of kinase inhibitors are operated to verify the robustness.
LGBTPQ Youth Negotiating Access to Sexual Health Education and Resources in a Rural South African University

ABSTRACT This article draws on sexual citizenship theory to analyze how some lesbian, gay, bisexual, transgender, pansexual and queer (LGBTPQ) youth in a low socio-economic rural South African context negotiate access to inclusive sexual health education programmes and resources. Participants are students aged 19 to 32 years old at a South African university. Using in-depth individual interviews, participants reflected on their experiences of sexual health education when they were still at school. The findings show the continuing silencing of sexual health issues concerning LGBTPQ youth in South African schools. Disadvantaged by the lack of sexual health education programmes in schools, findings show how the students sought LGBTPQ centered knowledge through self-study and other ways to empower themselves with information on sexual health matters. Participants also reflected on accessing the student health clinic at the university where they are students. Accessing condoms, lubricants, dental dams and HIV pre-exposure prophylaxis (PrEP) remains a challenge. Implications suggest ways of improving the provision of LGBTPQ inclusive sexual health education programmes and resources in poor rural contexts in South Africa.
Low Repeatability of Aversive Learning in Zebrafish (Danio rerio)

Aversive learning – avoiding certain situations based on negative experiences – can profoundly increase fitness in animal species. The extent to which this cognitive mechanism could evolve depends upon individual differences in aversive learning being stable through time, and heritable across generations, yet no published study has quantified the stability of individual differences in aversive learning using the repeatability statistic, R (also known as the intra-class correlation). We assessed the repeatability of aversive learning by conditioning approximately 100 zebrafish (Danio rerio) to avoid a colour cue associated with a mild electric shock. Across eight different colour conditions zebrafish did not show consistent individual differences in aversive learning (R = 0.04). Within conditions, when zebrafish were twice conditioned to the same colour, blue conditioning was more repeatable than green conditioning (R = 0.15 and R = 0.02). In contrast to the low repeatability estimates for aversive learning, zebrafish showed moderately consistent individual differences in colour preference during the baseline period (i.e. prior to aversive conditioning; R ~ 0.45). Overall, aversive learning responses of zebrafish were weak and variable (difference in time spent near the aversive cue <6 seconds per minute), but individual differences in learning ability did not explain substantial variability. We speculate that either the effect of aversive learning was too weak to quantify consistent individual differences, or directional selection might have eroded additive genetic variance. Finally, we discuss how confounded repeatability assays and publication bias could have inflated average estimates of repeatability in animal behaviour publications. Summary Statement Zebrafish exhibit low repeatability (intra-class correlation) in an aversive learning assay possibly due to past selection pressure exhausting genetic variance in this learning trait.
The Genus Plagiothecium Schimp. (Plagiotheciaceae, Bryophyta) in Eurasia: An Annotated Checklist with Distribution and Ecological Data

An annotated checklist of the pleurocarpous moss genus Plagiothecium in Eurasia is presented for the first time based on a thorough review of the literature. Data have been compiled from previous relevant works conducted on the genus over more than 70 years and published up to the end of June 2020 for 107 Eurasian countries (and islands). Sectional classification is based on molecular phylogeny of the genus published recently. A total of 41 taxa are reported, including 29 species and 12 infraspecific taxa (nine varieties and three forms) belonging to eight sections. The highest numbers of taxa were found in China (20 taxa), the Russian Federation (20 taxa) and Japan (18 taxa), while the smallest numbers of taxa were recorded in the Middle East, Central Asia and the islands area. Not a single species of Plagiothecium was recorded in 26 regions, whereas P. denticulatum, P. nemorale and P. cavifolium turned out to be the most widespread species in the entire study area. They were recorded in most of the surveyed countries and islands. For each accepted taxon, information on relevant literature, synonyms, distribution within Eurasia and globally are provided. Comments on each taxon, ecological preferences, and notes on doubtful records are also included. Additionally, distribution maps for each recognised taxon are supplied. This checklist can enlighten and foster a better understanding of the distribution, diversity, and ecology of Plagiothecium in Eurasia and provides an incentive for future research on the genus.
Tissue Distribution of Oleocanthal and Its Metabolites after Oral Ingestion in Rats

Claims for the potential health benefits of oleocanthal (OLC), a dietary phenolic compound found in olive oil, are based mainly on in vitro studies. Little is known about the tissue availability of OLC, which is rapidly metabolized after ingestion. In this study, the distribution of OLC and its metabolites in rat plasma and tissues (stomach, intestine, liver, kidney, spleen, lungs, heart, brain, thyroid and skin) at 1, 2 and 4.5 h after the acute intake of a refined olive oil containing 0.3 mg/mL of OLC was examined by LC-ESI-LTQ-Orbitrap-MS. OLC was only detected in the stomach and intestine samples. Moreover, at 2 and 4.5 h, the concentration in the stomach decreased by 36% and 74%, respectively, and in the intestine by 16% and 33%, respectively. Ten OLC metabolites arising from phase I and phase II reactions were identified. The metabolites were widely distributed in rat tissues, and the most important metabolizing organs were the small intestine and liver. The two main circulating metabolites were the conjugates OLC + OH + CH3 and OLC + H2O + glucuronic acid, which may significantly contribute to the beneficial health effects associated with the regular consumption of extra virgin olive oil. However, more studies are necessary to determine the concentrations and molecular structures of OLC metabolites in human plasma and tissues when consumed with the presence of other phenolic compunds present in EVOO.
Gene Expression Analysis of Microtubers of Potato Solanum tuberosum L. Induced in Cytokinin Containing Medium and Osmotic Stress

Potato microtuber productions through in vitro techniques are ideal propagules for producing high quality seed potatoes. Microtuber development is influenced by several factors, i.e., high content sucrose and cytokinins are among them. To understand a molecular mechanism of microtuberization using osmotic stress and cytokinin signaling will help us to elucidate this process. We demonstrate in this work a rapid and efficient protocol for microtuber development and gene expression analysis. Medium with high content of sucrose and gelrite supplemented with 2iP as cytokinin under darkness condition produced the higher quantity and quality of microtubers. Gene expression analysis of genes involved in the two-component signaling system (StHK1), cytokinin signaling, (StHK3, StHP4, StRR1) homeodomains (WUSCHEL, POTH1, BEL5), auxin signaling, ARF5, carbon metabolism (TPI, TIM), protein synthesis, NAC5 and a morphogenetic regulator of tuberization (POTH15) was performed by qPCR real time. Differential gene expression was observed during microtuber development. Gene regulation of two component and cytokinin signaling is taking place during this developmental process, yielding more microtubers. Further analysis of each component is required to elucidate it.
Drinking Molecular Hydrogen Water Is Beneficial to Cardiovascular Function in Diet-Induced Obesity Mice

Simple Summary Molecular hydrogen (MH) reportedly exerts therapeutic effects against inflammatory diseases by alleviating oxidative stress. We investigated the cardiovascular protective effects of molecular hydrogen water (MHW) intake using high-fat diet-induced obesity (DIO) mice. We observed that MHW intake for 2 weeks did not improve the blood sugar level or body weight but decreased heart weight in DIO mice. Notably, MHW intake alleviated oxidative stress in both the heart and the adipose tissue. Moreover, it improved cardiac hypertrophy and restored left ventricular function in DIO mice, and promoted the histological conversion of energy storage to expenditure in adipose tissues with the upregulation of thermogenic and cardiovascular protective genes. Furthermore, MHW restored endothelial progenitor cell (EPC) bioactivity to maintain vascular homeostasis. Taken together, MHW intake exerts cardiovascular protective effects in DIO mice. Hence, MHW intake is a potential prophylactic strategy against cardiovascular disorders in metabolic syndrome. Abstract Molecular hydrogen (MH) reportedly exerts therapeutic effects against inflammatory diseases as a suppressor of free radical chain reactions. Here, the cardiovascular protective effects of the intake of molecular hydrogen water (MHW) were investigated using high-fat diet-induced obesity (DIO) mice. MHW was prepared using supplier sticks and degassed water as control. MHW intake for 2 weeks did not improve blood sugar or body weight but decreased heart weight in DIO mice. Moreover, MHW intake improved cardiac hypertrophy, shortened the width of cardiomyocytes, dilated the capillaries and arterioles, activated myocardial eNOS-Ser-1177 phosphorylation, and restored left ventricular function in DIO mice. MHW intake promoted the histological conversion of hypertrophy to hyperplasia in white and brown adipose tissues (WAT and BAT) with the upregulation of thermogenic and cardiovascular protective genes in BAT (i.e., Ucp-1, Vegf-a, and eNos). Furthermore, the results of a colony formation assay of bone-marrow-derived endothelial progenitor cells (EPCs) indicated that MHW activated the expansion, differentiation, and mobilization of EPCs to maintain vascular homeostasis. These findings indicate that the intake of MHW exerts cardiovascular protective effects in DIO mice. Hence, drinking MHW is a potential prophylactic strategy against cardiovascular disorders in metabolic syndrome.