bluuebunny/crossref_metadata_2025 huggingface dataset:
Enzymatic Synthesis, Structural Analysis, and Evaluation of Antibacterial Activity and α-Glucosidase Inhibition of Hesperidin Glycosides
Authors: Chaisin Titaporn , Rudeekulthamrong Prakarn , Kaulpiboon Jarunee
Published: April 2021

This study was designed to investigate the structure of synthesized hesperidin glycosides (HGs) and evaluate their antibacterial and α-glucosidase inhibitory activities. The preliminary structure of HGs was confirmed by glucoamylase treatment and analyzed on thin layer chromatography (TLC). The LC-MS/MS profiles of HGs showed the important fragments at m/z ratios of 345.21 (added glucose to glucose of rutinose in HG1) and 687.28 (added maltose to glucose of rutinose in HG2), confirming that the structures of HG1 and HG2 were α-glucosyl hesperidin and α-maltosyl hesperidin, respectively. In addition, 1H and 13C-NMR of hesperidin derivatives were performed to identify their α-1,4-glycosidic bonds. The MIC and MBC studies showed that transglycosylated HG1 and HG2 had better antibacterial and bactericidal activities than hesperidin and diosmin, and were more active against Staphylococcus aureus than Escherichia coli. Hesperidin, HG1, HG2, and diosmin inhibited α-glucosidase with IC50 values of 2.75 ± 1.57, 2.48 ± 1.61, 2.36 ± 1.48, and 2.99 ± 1.23 mg/mL, respectively. The inhibition kinetics of HG2 shown by a Lineweaver–Burk plot confirmed HG2 was an α-glucosidase competitive inhibitor with an inhibitor constant, Ki, of 2.20 ± 0.10 mM. Thus, HGs have the potential to be developed into antibacterial drugs and treatments for treating α-glucosidase-associated type 2 diabetes.
In Situ Growth of ZIF-8 Nanocrystals on the Pore Walls of 3D Ordered Macroporous TiO2 for a One-Pot Cascade Reaction
Authors: Chen Jing , Guo Yingchun , Kang Tengteng , Liu Xingchi , Wang Xiaomei , Zhang Xu
Published: April 2021

It is wise to mimic a bioinspired system to design a nanoreactor as a catalyst containing multiple components for a cascade reaction. Here, we report the uniform growth of well-dispersed nano-scale ZIF-8 crystals on the pore walls of 3DOM TiO2 via the TEA-assisted crystallization process. The UV-vis spectra indicate that the ZIF-8 photosensitizer can extend the visible-light absorption of 3DOM TiO2. The obtained nanoreactor can efficiently catalyze the one-pot aromatic alcohol oxidization and Knoevenagel condensation cascade reaction for larger molecules. This work offers an important strategy for preparing semiconductor–MOF multifunctional composites with a spatially separated compartmentation for the cascade reaction.
Extracellular Vesicle Associated Non-Coding RNAs in Lung Infections and Injury
Authors: Kwok Zhi Hao , Ni Kareemah , Jin Yang
Published: April 2021

Extracellular vesicles (EVs) refer to a heterogenous population of membrane-bound vesicles that are released by cells under physiological and pathological conditions. The detection of EVs in the majority of the bodily fluids, coupled with their diverse cargo comprising of DNA, RNA, lipids, and proteins, have led to the accumulated interests in leveraging these nanoparticles for diagnostic and therapeutic purposes. In particular, emerging studies have identified enhanced levels of a wide range of specific subclasses of non-coding RNAs (ncRNAs) in EVs, thereby suggesting the existence of highly selective and regulated molecular processes governing the sorting of these RNAs into EVs. Recent studies have also illustrated the functional relevance of these enriched ncRNAs in a variety of human diseases. This review summarizes the current state of knowledge on EV-ncRNAs, as well as their functions and significance in lung infection and injury. As a majority of the studies on EV-ncRNAs in lung diseases have focused on EV-microRNAs, we will particularly highlight the relevance of these molecules in the pathophysiology of these conditions, as well as their potential as novel biomarkers therein. We also outline the current challenges in the EV field amidst the tremendous efforts to propel the clinical utility of EVs for human diseases. The lack of published literature on the functional roles of other EV-ncRNA subtypes may in turn provide new avenues for future research to exploit their feasibility as novel diagnostic and therapeutic targets in human diseases.
Store-Operated Calcium Entry: Shaping the Transcriptional and Epigenetic Landscape in Pancreatic Cancer
Authors: Kutschat Ana P. , Johnsen Steven A. , Hamdan Feda H.
Published: April 2021

Pancreatic ductal adenocarcinoma (PDAC) displays a particularly poor prognosis and low survival rate, mainly due to late diagnosis and high incidence of chemotherapy resistance. Genomic aberrations, together with changes in the epigenomic profile, elicit a shift in cellular signaling response and a transcriptional reprograming in pancreatic tumors. This endows them with malignant attributes that enable them to not only overcome chemotherapeutic challenges, but to also attain diverse oncogenic properties. In fact, certain genetic amplifications elicit a rewiring of calcium signaling, which can confer ER stress resistance to tumors while also aberrantly activating known drivers of oncogenic programs such as NFAT. While calcium is a well-known second messenger, the transcriptional programs driven by aberrant calcium signaling remain largely undescribed in pancreatic cancer. In this review, we focus on calcium-dependent signaling and its role in epigenetic programs and transcriptional regulation. We also briefly discuss genetic aberration events, exemplifying how genetic alterations can rewire cellular signaling cascades, including calcium-dependent ones.
Increasing Adult Hippocampal Neurogenesis Promotes Resilience in a Mouse Model of Depression
Authors: Planchez Barbara , Lagunas Natalia , Le Guisquet Anne-Marie , Legrand Marc , Surget Alexandre , Hen René , Belzung Catherine
Published: April 2021

Many studies evaluated the functional role of adult hippocampal neurogenesis (AHN) and its key role in cognitive functions and mood regulation. The effects of promoting AHN on the recovery of stress-induced symptoms have been well studied, but its involvement in stress resilience remains elusive. We used a mouse model enabling us to foster AHN before the exposure to unpredictable chronic mild stress (UCMS) to evaluate the potential protective effects of AHN on stress, assessing the depressive-like phenotype and executive functions. For this purpose, an inducible transgenic mouse model was used to delete the pro-apoptotic gene Bax from neural progenitors four weeks before UCMS, whereby increasing the survival of adult-generated neurons. Our results showed that UCMS elicited a depressive-like phenotype, highlighted by a deteriorated coat state, a higher immobility duration in the tail suspension test (TST), and a delayed reversal learning in a water maze procedure. Promoting AHN before UCMS was sufficient to prevent the development of stressed-induced behavioral changes in the TST and the water maze, reflecting an effect of AHN on stress resilience. Taken together, our data suggest that increasing AHN promotes stress resilience on some depressive-like symptoms but also in cognitive symptoms, which are often observed in MD.
Postprandial Glycogen Content Is Increased in the Hepatocytes of Human and Rat Cirrhotic Liver
Authors: Bezborodkina Natalia N. , Okovityi Sergey V. , Kudryavtsev Boris N.
Published: April 2021

Chronic hepatitises of various etiologies are widespread liver diseases in humans. Their final stage, liver cirrhosis (LC), is considered to be one of the main causes of hepatocellular carcinoma (HCC). About 80–90% of all HCC cases develop in LC patients, which suggests that cirrhotic conditions play a crucial role in the process of hepatocarcinogenesis. Carbohydrate metabolism in LC undergoes profound disturbances characterized by altered glycogen metabolism. Unfortunately, data on the glycogen content in LC are few and contradictory. In this study, the material was obtained from liver biopsies of patients with LC of viral and alcohol etiology and from the liver tissue of rats with CCl4-induced LC. The activity of glycogen phosphorylase (GP), glycogen synthase (GS), and glucose-6-phosphatase (G6Pase) was investigated in human and rat liver tissue by biochemical methods. Total glycogen and its labile and stable fractions were measured in isolated individual hepatocytes, using the cytofluorometry technique of PAS reaction in situ. The development of LC in human and rat liver was accompanied by an increase in fibrous tissue (20- and 8.8-fold), an increase in the dry mass of hepatocytes (by 25.6% and 23.7%), and a decrease in the number of hepatocytes (by 50% and 28%), respectively. The rearrangement of the liver parenchyma was combined with changes in glycogen metabolism. The present study showed a significant increase in the glycogen content in the hepatocytes of the human and the rat cirrhotic liver, by 255% and 210%, respectively. An increased glycogen content in cells of the cirrhotic liver can be explained by a decrease in glycogenolysis due to a decreased activity of G6Pase and GP.
Anodic ZnO Microsheet Coating on Zn with Sub-Surface Microtrenched Zn Layer Reduces Risk of Localized Corrosion and Improves Bioactivity of Pure Zn
Authors: Dong Hongzhou , Virtanen Sannakaisa
Published: April 2021

Zinc-based alloys are emerging as an alternative to magnesium- and iron-based alloys for biodegradable implant applications, due to their appropriate corrosion performance and biocompatibility. However, localized corrosion occurring on the zinc surface, which is generally associated with restricted mass transport at specific surface sites, such as in confined crevices, declines mechanical strength and can lead to the failure of implant materials. In order to improve corrosion behavior and bioactivity, we explore the effect of a ZnO microsheet coating fabricated on pure Zn via anodic oxidization. Samples were characterized with Scanning Electron Microscope (SEM) (including Energy Dispersive Spectroscopy (EDS), X-ray Photoelectron spectroscopy (XPS), Fourier Transform Infrared Spectroscopy (FTIR), and X-ray Diffraction (XRD)). The microstructured surface consists of parallel Zn trenches on the bottom and ZnO/Zn3O(SO4)2 sheets on the top. This layer shows favorable Ca-phosphate precipitation as well as bovine serum albumin (BSA) adsorption properties. Electrochemical experiments indicate an increased corrosion resistance of surface-modified Zn by the presence of BSA in simulated body fluid. Most noteworthily, localized corrosion that has been previously observed for pure Zn in BSA-containing electrolytes does not occur on the Zn/ZnO-coated surface.
Passive Layers and Corrosion Resistance of Biomedical Ti-6Al-4V and β-Ti Alloys
Authors: Bocchetta Patrizia , Chen Liang-Yu , Tardelli Juliana Dias Corpa , Reis Andréa Cândido dos , Almeraya-Calderón Facundo , Leo Paola
Published: April 2021

The high specific strength, good corrosion resistance, and great biocompatibility make titanium and its alloys the ideal materials for biomedical metallic implants. Ti-6Al-4V alloy is the most employed in practical biomedical applications because of the excellent combination of strength, fracture toughness, and corrosion resistance. However, recent studies have demonstrated some limits in biocompatibility due to the presence of toxic Al and V. Consequently, scientific literature has reported novel biomedical β-Ti alloys containing biocompatible β-stabilizers (such as Mo, Ta, and Zr) studying the possibility to obtain similar performances to the Ti-6Al-4V alloys. The aim of this review is to highlight the corrosion resistance of the passive layers on biomedical Ti-6Al-4V and β-type Ti alloys in the human body environment by reviewing relevant literature research contributions. The discussion is focused on all those factors that influence the performance of the passive layer at the surface of the alloy subjected to electrochemical corrosion, among which the alloy composition, the method selected to grow the oxide coating, and the physicochemical conditions of the body fluid are the most significant.
Hydrothermal Synthesis, Characterization and Exploration of Photocatalytic Activities of Polyoxometalate: Ni-CoWO4 Nanoparticles
Authors: Alharthi Fahad A. , Alanazi Hamdah S. , Alsyahi Amjad Abdullah , Ahmad Naushad
Published: April 2021

This study demonstrated the hydrothermal synthesis of bimetallic nickel-cobalt tungstate nanostructures, Ni-CoWO4 (NCW-NPs), and their phase structure, morphology, porosity, and optical properties were examined using X-ray Diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), Scanning electron microscopy- energy dispersive X-ray spectroscopy (SEM-EDS), high resolution Transmission electron microscopy (HR-TEM), Brunauer-Emmett-Teller (BET) and Raman instruments. It was found that as-calcined NCW-NPs have a monoclinic phase with crystal size ~50–60 nm and is mesoporous. It possessed smooth, spherical, and cubic shape microstructures with defined fringe distance (~0.342 nm). The photocatalytic degradation of methylene blue (MB) and rose bengal (RB) dye in the presence of NCW-NPs was evaluated, and about 49.85% of MB in 150 min and 92.28% of RB in 90 min degraded under visible light. In addition, based on the scavenger’s study, the mechanism for photocatalytic reactions is proposed.
Recent Developments in Carbon Nanotubes-Reinforced Ceramic Matrix Composites: A Review on Dispersion and Densification Techniques
Authors: Chan Kar Fei , Zaid Mohd Hafiz Mohd , Mamat Md Shuhazlly , Liza Shahira , Tanemura Masaki , Yaakob Yazid
Published: April 2021

Ceramic matrix composites (CMCs) are well-established composites applied on commercial, laboratory, and even industrial scales, including pottery for decoration, glass–ceramics-based light-emitting diodes (LEDs), commercial cooking utensils, high-temperature laboratory instruments, industrial catalytic reactors, and engine turbine blades. Despite the extensive applications of CMCs, researchers had to deal with their brittleness, low electrical conductivity, and low thermal properties. The use of carbon nanotubes (CNTs) as reinforcement is an effective and efficient method to tailor the ceramic structure at the nanoscale, which provides considerable practicability in the fabrication of highly functional CMC materials. This article provides a comprehensive review of CNTs-reinforced CMC materials (CNTs-CMCs). We critically examined the notable challenges during the synthesis of CNTs-CMCs. Five CNT dispersion processes were elucidated with a comparative study of the established research for the homogeneity distribution in the CMCs and the enhanced properties. We also discussed the effect of densification techniques on the properties of CNTs-CMCs. Additionally, we synopsized the outstanding microstructural and functional properties of CNTs in the CNTs-CMCs, namely stimulated ceramic crystallization, high thermal conductivity, bandgap reduction, and improved mechanical toughness. We also addressed the fundamental insights for the future technological maturation and advancement of CNTs-CMCs.
Evaluation of the Performance of Published Point Defect Parameter Sets in Cone and Body Phase of a 300 mm Czochralski Silicon Crystal
Authors: Sabanskis Andrejs , Plāte Matīss , Sattler Andreas , Miller Alfred , Virbulis Jānis
Published: April 2021

Prediction and adjustment of point defect (vacancies and self-interstitials) distribution in silicon crystals is of utmost importance for microelectronic applications. The simulation of growth processes is widely applied for process development and quite a few different sets of point defect parameters have been proposed. In this paper the transient temperature, thermal stress and point defect distributions are simulated for 300 mm Czochralski growth of the whole crystal including cone and cylindrical growth phases. Simulations with 12 different published point defect parameter sets are compared to the experimentally measured interstitial–vacancy boundary. The results are evaluated for standard and adjusted parameter sets and generally the best agreement in the whole crystal is found for models considering the effect of thermal stress on the equilibrium point defect concentration.
Automated CT Lung Density Analysis of Viral Pneumonia and Healthy Lungs Using Deep Learning-Based Segmentation, Histograms and HU Thresholds
Authors: Romanov Andrej , Bach Michael , Yang Shan , Franzeck Fabian C. , Sommer Gregor , Anastasopoulos Constantin , Bremerich Jens , Stieltjes Bram , Weikert Thomas , Sauter Alexander Walter
Published: April 2021

CT patterns of viral pneumonia are usually only qualitatively described in radiology reports. Artificial intelligence enables automated and reliable segmentation of lungs with chest CT. Based on this, the purpose of this study was to derive meaningful imaging biomarkers reflecting CT patterns of viral pneumonia and assess their potential to discriminate between healthy lungs and lungs with viral pneumonia. This study used non-enhanced and CT pulmonary angiograms (CTPAs) of healthy lungs and viral pneumonia (SARS-CoV-2, influenza A/B) identified by radiology reports and RT-PCR results. After deep learning segmentation of the lungs, histogram-based and threshold-based analyses of lung attenuation were performed and compared. The derived imaging biomarkers were correlated with parameters of clinical and biochemical severity (modified WHO severity scale; c-reactive protein). For non-enhanced CTs (n = 526), all imaging biomarkers significantly differed between healthy lungs and lungs with viral pneumonia (all p < 0.001), a finding that was not reproduced for CTPAs (n = 504). Standard deviation (histogram-derived) and relative high attenuation area [600–0 HU] (HU-thresholding) differed most. The strongest correlation with disease severity was found for absolute high attenuation area [600–0 HU] (r = 0.56, 95% CI = 0.46–0.64). Deep-learning segmentation-based histogram and HU threshold analysis could be deployed in chest CT evaluation for the differentiating of healthy lungs from AP lungs.
The Primacy of High B-Value 3T-DWI Radiomics in the Prediction of Clinically Significant Prostate Cancer
Authors: Bevilacqua Alessandro , Mottola Margherita , Ferroni Fabio , Rossi Alice , Gavelli Giampaolo , Barone Domenico
Published: April 2021

Predicting clinically significant prostate cancer (csPCa) is crucial in PCa management. 3T-magnetic resonance (MR) systems may have a novel role in quantitative imaging and early csPCa prediction, accordingly. In this study, we develop a radiomic model for predicting csPCa based solely on native b2000 diffusion weighted imaging (DWIb2000) and debate the effectiveness of apparent diffusion coefficient (ADC) in the same task. In total, 105 patients were retrospectively enrolled between January–November 2020, with confirmed csPCa or ncsPCa based on biopsy. DWIb2000 and ADC images acquired with a 3T-MRI were analyzed by computing 84 local first-order radiomic features (RFs). Two predictive models were built based on DWIb2000 and ADC, separately. Relevant RFs were selected through LASSO, a support vector machine (SVM) classifier was trained using repeated 3-fold cross validation (CV) and validated on a holdout set. The SVM models rely on a single couple of uncorrelated RFs (ρ < 0.15) selected through Wilcoxon rank-sum test (p ≤ 0.05) with Holm–Bonferroni correction. On the holdout set, while the ADC model yielded AUC = 0.76 (95% CI, 0.63–0.96), the DWIb2000 model reached AUC = 0.84 (95% CI, 0.63–0.90), with specificity = 75%, sensitivity = 90%, and informedness = 0.65. This study establishes the primary role of 3T-DWIb2000 in PCa quantitative analyses, whilst ADC can remain the leading sequence for detection.
Relationship between Brain Tissue Changes and Blood Biomarkers of Cyclophilin A, Heme Oxygenase-1, and Inositol-Requiring Enzyme 1 in Patients with Alzheimer’s Disease
Authors: Choi Hyon-Il , Kim Kiyoon , Lee Jiyoon , Chang Yunjung , Rhee Hak Young , Park Soonchan , Lee Woo-In , Choe Wonchae , Ryu Chang-Woo , Jahng Geon-Ho
Published: April 2021

Cyclophilin A (CypA), heme oxygenase-1 (HO-1), and inositol-requiring enzyme 1 (IRE1) are believed to be associated with Alzheimer’s disease (AD). In this study, we investigated the association between gray matter volume (GMV) changes and blood levels of CypA, HO-1, and IRE1 in cognitively normal (CN) subjects and those with amnestic mild cognitive impairment (aMCI) and AD. Forty-five elderly CN, 34 aMCI, and 39 AD subjects were enrolled in this study. The results of voxel-based multiple regression analysis showed that blood levels of CypA, HO-1, and IRE1 were correlated with GMV on brain magnetic resonance imaging (MRI) in the entire population (p = 0.0005). The three serum protein levels were correlated with GMV of signature AD regions in the population as a whole. CypA values increased with increasing GMV in the occipital gyrus (r = 0.387, p < 0.0001) and posterior cingulate (r = 0.196, p = 0.034). HO-1 values increased with increasing GMV at the uncus (r = 0.307, p = 0.0008), lateral globus pallidus and putamen (r = 0.287, p = 0.002), and hippocampus (r = 0.197, p = 0.034). IRE1 values decreased with increasing GMV at the uncus (r = −0.239, p = 0.010) and lateral globus pallidus and putamen (r = −0.335, p = 0.0002). Associations between the three serum protein levels and regional GMV indicate that the blood levels of these biomarkers may reflect the pathological mechanism of AD in the brain.
Identification of Tumor-Specific MRI Biomarkers Using Machine Learning (ML)
Authors: Hajjo Rima , Sabbah Dima A. , Bardaweel Sanaa K. , Tropsha Alexander
Published: April 2021

The identification of reliable and non-invasive oncology biomarkers remains a main priority in healthcare. There are only a few biomarkers that have been approved as diagnostic for cancer. The most frequently used cancer biomarkers are derived from either biological materials or imaging data. Most cancer biomarkers suffer from a lack of high specificity. However, the latest advancements in machine learning (ML) and artificial intelligence (AI) have enabled the identification of highly predictive, disease-specific biomarkers. Such biomarkers can be used to diagnose cancer patients, to predict cancer prognosis, or even to predict treatment efficacy. Herein, we provide a summary of the current status of developing and applying Magnetic resonance imaging (MRI) biomarkers in cancer care. We focus on all aspects of MRI biomarkers, starting from MRI data collection, preprocessing and machine learning methods, and ending with summarizing the types of existing biomarkers and their clinical applications in different cancer types.
Omics and Artificial Intelligence to Improve In Vitro Fertilization (IVF) Success: A Proposed Protocol
Authors: Siristatidis Charalampos , Stavros Sofoklis , Drakeley Andrew , Bettocchi Stefano , Pouliakis Abraham , Drakakis Peter , Papapanou Michail , Vlahos Nikolaos
Published: April 2021

The prediction of in vitro fertilization (IVF) outcome is an imperative achievement in assisted reproduction, substantially aiding infertile couples, health systems and communities. To date, the assessment of infertile couples depends on medical/reproductive history, biochemical indications and investigations of the reproductive tract, along with data obtained from previous IVF cycles, if any. Our project aims to develop a novel tool, integrating omics and artificial intelligence, to propose optimal treatment options and enhance treatment success rates. For this purpose, we will proceed with the following: (1) recording subfertile couples’ lifestyle and demographic parameters and previous IVF cycle characteristics; (2) measurement and evaluation of metabolomics, transcriptomics and biomarkers, and deep machine learning assessment of the oocyte, sperm and embryo; (3) creation of artificial neural network models to increase objectivity and accuracy in comparison to traditional techniques for the improvement of the success rates of IVF cycles following an IVF failure. Therefore, “omics” data are a valuable parameter for embryo selection optimization and promoting personalized IVF treatment. “Omics” combined with predictive models will substantially promote health management individualization; contribute to the successful treatment of infertile couples, particularly those with unexplained infertility or repeated implantation failures; and reduce multiple gestation rates.
Entropic Dynamics on Gibbs Statistical Manifolds
Authors: Pessoa Pedro , Costa Felipe Xavier , Caticha Ariel
Published: April 2021

Entropic dynamics is a framework in which the laws of dynamics are derived as an application of entropic methods of inference. Its successes include the derivation of quantum mechanics and quantum field theory from probabilistic principles. Here, we develop the entropic dynamics of a system, the state of which is described by a probability distribution. Thus, the dynamics unfolds on a statistical manifold that is automatically endowed by a metric structure provided by information geometry. The curvature of the manifold has a significant influence. We focus our dynamics on the statistical manifold of Gibbs distributions (also known as canonical distributions or the exponential family). The model includes an “entropic” notion of time that is tailored to the system under study; the system is its own clock. As one might expect that entropic time is intrinsically directional; there is a natural arrow of time that is led by entropic considerations. As illustrative examples, we discuss dynamics on a space of Gaussians and the discrete three-state system.
Research on Multi-Dimensional Optimal Location Selection of Maintenance Station Based on Big Data of Vehicle Trajectory
Authors: Zhang Shoujing , Tong Fujiao , Li Mengdan , Jin Shoufeng , Li Zhixiong
Published: April 2021

In order to rationally lay out the location of automobile maintenance service stations, a method of location selection of maintenance service stations based on vehicle trajectory big data is proposed. Taking the vehicle trajectory data as the demand points, the demand points are divided according to the region by using the idea of zoning, and the location of the second-level maintenance station is selected for each region. The second-level maintenance stations selected in the whole country are set as the demand points of the first-level maintenance stations. Considering the objectives of the two dimensions of cost and service level, the location model of the first-level maintenance stations under two-dimensional programming is established, and the improved particle swarm optimization algorithm and immune algorithm, respectively, are used to solve the problem. In this way, the first-level maintenance stations in each region are obtained. The example verification shows that the location selection results for the maintenance stations using the vehicle trajectory big data are reasonable and closer to the actual needs.
HEVC Fast Intra-Mode Selection Using World War II Technique
Authors: Tariq Junaid , Armghan Ammar , Alenezi Fayadh , Ijaz Amir , Rehman Saad , Alfalou Ayman , Ali Khan Junaid
Published: April 2021

High-Efficiency Video Coding (HEVC) applies 35 intra modes to every block of a frame and selects the mode that gives the best prediction. This brute-force nature of HEVC makes it complex and unfit for real-time applications. Therefore, a fast intra-mode estimation algorithm is presented here based on the classic World War II (WW2) technique known as the ‘German Tanks Problem’ (GTP). This not only is the first article to use GTP for early estimation of intra mode, but also expedites the estimation process of GTP. Secondly, the various elements of the intra process are efficiently mapped to the elements of GTP estimation. Finally, the two variations of GPT are modeled and are also minimum-variance estimates. These experimental results indicate that proposed GTP-based fast estimation reduced the compression time of HEVC from 23.88% to 31.44%.
Wearable Wireless Physiological Monitoring System Based on Multi-Sensor
Authors: Li Hongru , Sun Guiling , Li Yue , Yang Runzhuo
Published: April 2021

The purpose of wearable technology is to use multimedia, sensors, and wireless communication to integrate specific technology into user clothes or accessories. With the help of various sensors, the physiological monitoring system can collect, process, and transmit physiological signals without causing damage. Wearable technology has been widely used in patient monitoring and people’s health management because of its low-load, mobile, and easy-to-use characteristics, and it supports long-term continuous work and can carry out wireless transmissions. In this paper, we established a Wi-Fi-based physiological monitoring system that can accurately measure heart rate, body surface temperature, and motion data and can quickly detect and alert the user about abnormal heart rates.
Wireless Loss Detection over Fairly Shared Heterogeneous Long Fat Networks
Authors: Briones Alan , Mallorquí Adrià , Zaballos Agustín , Martin de Pozuelo Ramon
Published: April 2021

The quality of inter-network communication is often detrimentally affected by the large deployment of heterogeneous networks, including Long Fat Networks, as a result of wireless media introduction. Legacy transport protocols assume an independent wired connection to the network. When a loss occurs, the protocol considers it as a congestion loss, decreasing its throughput in order to reduce the network congestion without evaluating a possible channel failure. Distinct wireless transport protocols and their reference metrics are analyzed in order to design a mechanism that improves the Aggressive and Adaptative Transport Protocol (AATP) performance over Heterogeneous Long Fat Networks (HLFNs). In this paper, we present the Enhanced-AATP, which introduces the designed Loss Threshold Decision maker mechanism for the detection of different types of losses in the AATP operation. The degree to which the protocol can maintain throughput levels during channel losses or decrease production while congestion losses occur depends on the evolution of the smooth Jitter Ratio metric value. Moreover, the defined Weighted Fairness index enables the modification of protocol behavior and hence the prioritized fair use of the node’s resources. Different experiments are simulated over a network simulator to demonstrate the operation and performance improvement of the Enhanced-AATP. To conclude, the Enhanced-AATP performance is compared with other modern protocols.
Transparent All-Oxide Hybrid NiO:N/TiO2 Heterostructure for Optoelectronic Applications
Authors: Aivalioti Chrysa , Papadakis Alexandros , Manidakis Emmanouil , Kayambaki Maria , Androulidaki Maria , Tsagaraki Katerina , Pelekanos Nikolaos T. , Stoumpos Constantinos , Modreanu Mircea , Crăciun Gabriel , Romanitan Cosmin , Aperathitis Elias
Published: April 2021

Nickel oxide (NiO) is a p-type oxide and nitrogen is one of the dopants used for modifying its properties. Until now, nitrogen-doped NiO has shown inferior optical and electrical properties than those of pure NiO. In this work, we present nitrogen-doped NiO (NiO:N) thin films with enhanced properties compared to those of the undoped NiO thin film. The NiO:N films were grown at room temperature by sputtering using a plasma containing 50% Ar and 50% (O2 + N2) gases. The undoped NiO film was oxygen-rich, single-phase cubic NiO, having a transmittance of less than 20%. Upon doping with nitrogen, the films became more transparent (around 65%), had a wide direct band gap (up to 3.67 eV) and showed clear evidence of indirect band gap, 2.50–2.72 eV, depending on %(O2-N2) in plasma. The changes in the properties of the films such as structural disorder, energy band gap, Urbach states and resistivity were correlated with the incorporation of nitrogen in their structure. The optimum NiO:N film was used to form a diode with spin-coated, mesoporous on top of a compact, TiO2 film. The hybrid NiO:N/TiO2 heterojunction was transparent showing good output characteristics, as deduced using both I-V and Cheung’s methods, which were further improved upon thermal treatment. Transparent NiO:N films can be realized for all-oxide flexible optoelectronic devices.
Revisiting Dropout: Escaping Pressure for Training Neural Networks with Multiple Costs
Authors: Woo Sangmin , Kim Kangil , Noh Junhyug , Shin Jong-Hun , Na Seung-Hoon
Published: April 2021

A common approach to jointly learn multiple tasks with a shared structure is to optimize the model with a combined landscape of multiple sub-costs. However, gradients derived from each sub-cost often conflicts in cost plateaus, resulting in a subpar optimum. In this work, we shed light on such gradient conflict challenges and suggest a solution named Cost-Out, which randomly drops the sub-costs for each iteration. We provide the theoretical and empirical evidence of the existence of escaping pressure induced by the Cost-Out mechanism. While simple, the empirical results indicate that the proposed method can enhance the performance of multi-task learning problems, including two-digit image classification sampled from MNIST dataset and machine translation tasks for English from and to French, Spanish, and German WMT14 datasets.
Efficiently Estimating Joining Cost of Subqueries in Regular Path Queries
Authors: Nguyen Van-Quyet , Nguyen Van-Hau , Nguyen Minh-Quy , Huynh Quyet-Thang , Kim Kyungbaek
Published: April 2021

Evaluating Regular Path Queries (RPQs) have been of interest since they were used as a powerful way to explore paths and patterns in graph databases. Traditional automata-based approaches are restricted in the graph size and/or highly complex queries, which causes a high evaluation cost (e.g., memory space and response time) on large graphs. Recently, although using the approach based on the threshold rare label for large graphs has been achieving some success, they could not often guarantee the minimum searching cost. Alternatively, the Unit-Subquery Cost Matrix (USCM) has been studied and obtained the viability of the usage of subqueries. Nevertheless, this method has an issue, which is, it does not cumulate the cost among subqueries that causes the long response time on a large graph. In order to overcome this issue, this paper proposes a method for estimating joining cost of subqueries to accelerate the USCM based parallel evaluation of RPQs on a large graph, namely USCM-Join. Through real-world datasets, we experimentally show that the USCM-Join outperforms others and estimating the joining cost enhances the USCM based approach up to around 20% in terms of response time.
Acid Treatment as a Way to Reduce Shale Rock Mechanical Strength and to Create a Material Prone to the Formation of Permanent Well Barrier
Authors: Gawel Kamila , Lozovyi Maksym , Bhuiyan Mohammad Hossain , Bjørge Ruben , Fjær Erling
Published: April 2021

Utilization of natural shale formations for the creation of annular barriers in oil and gas wells is currently discussed as a mean of simplifying cumbersome plugging and abandonment procedures. Shales that are likely to form annular barriers are shales with high content of swelling clays and relatively low content of cementation material (e.g., quartz, carbonates). Shales with large content of quartz and low content of swelling clays will be rather brittle and not easily deformable. In this paper we ask the question whether and to what extent it is possible to modify the mechanical properties of relatively brittle shales by chemically removing some cementation material. To answer this question, we have leached out carbonates from Pierre I shale matrix using hydrochloric acid and we have compared mechanical properties of shale before and after leaching. We have also followed leaching dynamics using X-ray tomography. The results show that removal of around 4–5 wt% of cementation material results in 43% reduction in Pierre I shale shear strength compared to the non-etched shale exposed to sodium chloride solution for the same time. The etching rate was shown to be strongly affected by the volume of fluid staying in direct contact with the shale sample.
An Experimental Investigation on Photovoltaic Array Power Output Affected by the Different Partial Shading Conditions
Authors: Abdullah Ghoname , Nishimura Hidekazu , Fujita Toshio
Published: April 2021

This paper presents an experimental investigation on photovoltaic array (PV array) power output affected by partial shading conditions (PSCs). An experiment setup of a PV array with a series configuration using 2 × 4 photovoltaic modules (PV modules) was built. The power output loss due to the shading effect on the first photovoltaic cells (PV cell) connected with bypass diodes of each photovoltaic module, installed in the PV array in the horizontal direction, was evaluated. Depending on the direction of the sun relative to the PV array configuration, the shading percentage was measured during the test and recorded the current and voltage of the PV array. The performance evaluation of the PV array configurations is referred to with respect to the values of maximum power voltage, the maximum power current, maximum power output, power output losses and fill factor (FF). The experimental results show that 44% shading of the first PV cells affects PV array power output loss by more than 80%.
Stability Enhancement of a Single-Stage Transonic Axial Compressor Using Inclined Oblique Slots
Authors: Vuong Tien-Dung , Kim Kwang-Yong
Published: April 2021

A casing treatment using inclined oblique slots (INOS) is proposed to improve the stability of the single-stage transonic axial compressor, NASA Stage 37, during operation. The slots are installed on the casing of the rotor blades. The aerodynamic performance was estimated using three-dimensional steady Reynolds-Averaged Navier-Stokes analysis. The results showed that the slots effectively increased the stall margin of the compressor with slight reductions in the pressure ratio and adiabatic efficiency. Three geometric parameters were tested in a parametric study. A single-objective optimization to maximize the stall margin was carried out using a Genetic Algorithm coupled with a surrogate model created by a radial basis neural network. The optimized design increased the stall margin by 37.1% compared to that of the smooth casing with little impacts on the efficiency and pressure ratio.
Identification of Stray Gassing of Dodecylbenzene in Bushings
Authors: Duval Michel , Ene Constantin
Published: April 2021

Several high voltage condenser type OIP (oil impregnated paper) bushings used in the electrical industry are filled with dodecylbenzene, because of its ability to absorb hydrogen formed by corona partial discharges in the thick paper insulation of these pieces of equipment. Some of them form large quantities of ethane, raising the concern of overheating faults in their paper insulation, which may be risky for their safe operation in service. The article presents dissolved gas analysis results of oil samples taken from the bushings with high ethane formation, together with results of laboratory tests of stray gassing of dodecylbenzene performed according to CIGRE procedure. By using Duval Pentagon 2 it is possible to compare patterns in the laboratory and in bushings and evaluate the temperature range of possible defects. Stray gassing/overheating of dodecylbenzene in bushings within the stray gassing temperature range and whatever the possible other causes, is not a concern for their safe operation according to observations published by CIGRE.
Smart Cities and Positive Energy Districts: Urban Perspectives in 2020
Authors: Clerici Maestosi Paola
Published: April 2021

This Special Issue of Energies “Smart Cities and Positive Energy Districts: Urban Perspectives in 2020” introduce contemporary research on Smart Cities and on Positive Energy Districts. The topic highlights the variety of research within this field: from the analysis of 61 Positive Energy Districts cases to papers illustrating the Positive Energy Districts dimension or Smart Energy Communities supporting low carbon energy transition as well as selected Smart Cities Experiences. The focus is thus given on how RD&I stakeholders and Municipalities are facing sustainable urban development challenges. An overview of Horizon Europe RD&I program on sustainable urban areas is provided.
Enclosure Design for Brake Wear Particle Measurement Using Computational Fluid Dynamics
Authors: Zhang Tuo , Choi Sungjin , Ahn Seoyeon , Nam Chanhyuk , Lee Geesoo
Published: April 2021

The harmfulness of fine dust generated by automobile brakes to the environment has recently received attention. Therefore, we aimed to analyze and regulate the brake wear particles in dynamometers. To accurately measure the number of particles and particle mass, the sampling system used needs to minimize transportation losses and reduce the residence time in the brake enclosure system. The brake dust measurement system currently used can estimate the main transportation loss but cannot evaluate the complex flow field in the brake enclosure system under different design conditions. We used computational fluid dynamics (CFD) technology to predict the behavior of brake wear particles and analyze the static pressure characteristics, the uniformity of the system flow, and the residence time of the brake dust particles in the system. In addition, we compared the design of the basic structure of the brake enclosure system, combined with the four factors affecting the design of the brake dynamometer, with the enclosure system. As a result, we proposed that the design of the cross section of the brake dynamometer enclosure should be circular, the outlet angle of the enclosure should be 15°, the caliper should be fixed to 150°, and two sets of splitters should be added. This design improves pressure loss and reduces the residence time of brake dust particles in the brake enclosure system.
Salmonella, Food Safety and Food Handling Practices
Authors: Ehuwa Olugbenga , Jaiswal Amit K. , Jaiswal Swarna
Published: April 2021

Salmonellosis is the second most reported gastrointestinal disorder in the EU resulting from the consumption of Salmonella-contaminated foods. Symptoms include gastroenteritis, abdominal cramps, bloody diarrhoea, fever, myalgia, headache, nausea and vomiting. In 2018, Salmonella accounted for more than half of the numbers of foodborne outbreak illnesses reported in the EU. Salmonella contamination is mostly associated with produce such as poultry, cattle and their feeds but other products such as dried foods, infant formula, fruit and vegetable products and pets have become important. Efforts aimed at controlling Salmonella are being made. For example, legislation and measures put in place reduced the number of hospitalizations between 2014 and 2015. However, the number of hospitalizations started to increase in 2016. This calls for more stringent controls at the level of government and the private sector. Food handlers of “meat processing” and “Ready to Eat” foods play a crucial role in the spread of Salmonella. This review presents an updated overview of the global epidemiology, the relevance of official control, the disease associated with food handlers and the importance of food safety concerning salmonellosis.
Polar Lipids of Commercial Ulva spp. of Different Origins: Profiling and Relevance for Seaweed Valorization
Authors: Moreira Ana S. P. , da Costa Elisabete , Melo Tânia , Lopes Diana , Pais Adriana C. S. , Santos Sónia A. O. , Pitarma Bárbara , Mendes Madalena , Abreu Maria H. , Collén Pi Nyvall , Domingues Pedro , Domingues M. Rosário
Published: April 2021

Macroalgae of the genus Ulva have long been used as human food. Local environmental conditions, among other factors, can have an impact on their nutrient and phytochemical composition, as well as on the value of the seaweed for food and non-food applications. This study is the first to initiate a comparison between commercial Ulva spp. from different European origins, France (FR, wild-harvested Ulva spp.), and Portugal (PT, farm-raised Ulva rigida), in terms of proximate composition, esterified fatty acids (FA), and polar lipids. The ash content was higher in PT samples, while FR samples had higher levels of proteins, lipids, and carbohydrates and other compounds. The profile of esterified FA, as well as FA-containing polar lipids at the class and species levels were also significantly different. The FR samples showed about three-fold higher amount of n-3 polyunsaturated FA, while PT samples showed two-fold higher content of monounsaturated FA. Quantification of glycolipids and phospholipids revealed, respectively, two-fold and three-fold higher levels in PT samples. Despite the differences found, the polar lipids identified in both batches included some lipid species with recognized bioactivity, valuing Ulva biomass with functional properties, increasing their added value, and promoting new applications, namely in nutraceutical and food markets.
Achromobacter xylosoxidans and Stenotrophomonas maltophilia: Emerging Pathogens Well-Armed for Life in the Cystic Fibrosis Patients’ Lung
Authors: Menetrey Quentin , Sorlin Pauline , Jumas-Bilak Estelle , Chiron Raphaël , Dupont Chloé , Marchandin Hélène
Published: April 2021

In patients with cystic fibrosis (CF), the lung is a remarkable ecological niche in which the microbiome is subjected to important selective pressures. An inexorable colonization by bacteria of both endogenous and environmental origin is observed in most patients, leading to a vicious cycle of infection–inflammation. In this context, long-term colonization together with competitive interactions among bacteria can lead to over-inflammation. While Pseudomonas aeruginosa and Staphylococcus aureus, the two pathogens most frequently identified in CF, have been largely studied for adaptation to the CF lung, in the last few years, there has been a growing interest in emerging pathogens of environmental origin, namely Achromobacter xylosoxidans and Stenotrophomonas maltophilia. The aim of this review is to gather all the current knowledge on the major pathophysiological traits, their supporting mechanisms, regulation and evolutionary modifications involved in colonization, virulence, and competitive interactions with other members of the lung microbiota for these emerging pathogens, with all these mechanisms being major drivers of persistence in the CF lung. Currently available research on A. xylosoxidans complex and S. maltophilia shows that these emerging pathogens share important pathophysiological features with well-known CF pathogens, making them important members of the complex bacterial community living in the CF lung.