bluuebunny/crossref_metadata_2025 huggingface dataset:
Mucolipidoses Overview: Past, Present, and Future
Authors: Khan Shaukat A. , Tomatsu Saori C.
Published: September 2020

Mucolipidosis II and III (ML II/III) are caused by a deficiency of uridine-diphosphate N-acetylglucosamine: lysosomal-enzyme-N-acetylglucosamine-1-phosphotransferase (GlcNAc-1-phosphotransferase, EC2.7.8.17), which tags lysosomal enzymes with a mannose 6-phosphate (M6P) marker for transport to the lysosome. The process is performed by a sequential two-step process: first, GlcNAc-1-phosphotransferase catalyzes the transfer of GlcNAc-1-phosphate to the selected mannose residues on lysosomal enzymes in the cis-Golgi network. The second step removes GlcNAc from lysosomal enzymes by N-acetylglucosamine-1-phosphodiester α-N-acetylglucosaminidase (uncovering enzyme) and exposes the mannose 6-phosphate (M6P) residues in the trans-Golgi network, in which the enzymes are targeted to the lysosomes by M6Preceptors. A deficiency of GlcNAc-1-phosphotransferase causes the hypersecretion of lysosomal enzymes out of cells, resulting in a shortage of multiple lysosomal enzymes within lysosomes. Due to a lack of GlcNAc-1-phosphotransferase, the accumulation of cholesterol, phospholipids, glycosaminoglycans (GAGs), and other undegraded substrates occurs in the lysosomes. Clinically, ML II and ML III exhibit quite similar manifestations to mucopolysaccharidoses (MPSs), including specific skeletal deformities known as dysostosis multiplex and gingival hyperplasia. The life expectancy is less than 10 years in the severe type, and there is no definitive treatment for this disease. In this review, we have described the updated diagnosis and therapy on ML II/III.
Deep Learning-Based Action Recognition Using 3D Skeleton Joints Information
Authors: Tasnim Nusrat , Islam Md. Mahbubul , Baek Joong-Hwan
Published: September 2020

Human action recognition has turned into one of the most attractive and demanding fields of research in computer vision and pattern recognition for facilitating easy, smart, and comfortable ways of human-machine interaction. With the witnessing of massive improvements to research in recent years, several methods have been suggested for the discrimination of different types of human actions using color, depth, inertial, and skeleton information. Despite having several action identification methods using different modalities, classifying human actions using skeleton joints information in 3-dimensional space is still a challenging problem. In this paper, we conceive an efficacious method for action recognition using 3D skeleton data. First, large-scale 3D skeleton joints information was analyzed and accomplished some meaningful pre-processing. Then, a simple straight-forward deep convolutional neural network (DCNN) was designed for the classification of the desired actions in order to evaluate the effectiveness and embonpoint of the proposed system. We also conducted prior DCNN models such as ResNet18 and MobileNetV2, which outperform existing systems using human skeleton joints information.
Correction: Abramov, R. The Random Gas of Hard Spheres. J 2019, 2, 162–205
Authors: Abramov Rafail V.
Published: September 2020

In the published paper [1], we used the spatial correlation function R(σ) of two spheres, each of diameter σ, to construct a closure to the BBGKY hierarchy of hard spheres [...]
Thermoplastic Polyurethane/Lead Zirconate Titanate/Carbon Nanotube Composites with Very High Dielectric Permittivity and Low Dielectric Loss
Authors: Petrossian Gayaneh , Aliheidari Nahal , Ameli Amir
Published: September 2020

Ternary composites of flexible thermoplastic polyurethane (TPU), lead zirconate titanate (PZT), and multiwalled carbon nanotubes (MWCNTs) with very high dielectric permittivity (εr) and low dielectric loss (tan δ) are reported. To assess the evolution of dielectric properties with the interactions between conductive and dielectric fillers, composites were designed with a range of content for PZT (0–30 vol%) and MWCNT (0–1 vol%). The microstructure was composed of PZT-rich and segregated MWCNT-rich regions, which could effectively prevent the formation of macroscopic MWCNT conductive networks and thus reduce the high ohmic loss. Therefore, εr increased by a maximum of tenfold, reaching up to 166 by the addition of up to 1 vol% MWCNT to TPU/PZT. More importantly, tan δ remained relatively unchanged at 0.06–0.08, a similar range to that of pure TPU. εr/tan δ ratio reached 2870 at TPU/30 vol% PZT/0.5 vol% MWCNT, exceeding most of the reported values. This work demonstrates the potential of three-phase polymer/conductive filler/dielectric filler composites for efficient charge storage applications.
Understanding the Effects of Optimal Combination of Spectral Bands on Deep Learning Model Predictions: A Case Study Based on Permafrost Tundra Landform Mapping Using High Resolution Multispectral Satellite Imagery
Authors: Bhuiyan Md Abul Ehsan , Witharana Chandi , Liljedahl Anna K. , Jones Benjamin M. , Daanen Ronald , Epstein Howard E. , Kent Kelcy , Griffin Claire G. , Agnew Amber
Published: September 2020

Deep learning (DL) convolutional neural networks (CNNs) have been rapidly adapted in very high spatial resolution (VHSR) satellite image analysis. DLCNN-based computer visions (CV) applications primarily aim for everyday object detection from standard red, green, blue (RGB) imagery, while earth science remote sensing applications focus on geo object detection and classification from multispectral (MS) imagery. MS imagery includes RGB and narrow spectral channels from near- and/or middle-infrared regions of reflectance spectra. The central objective of this exploratory study is to understand to what degree MS band statistics govern DLCNN model predictions. We scaffold our analysis on a case study that uses Arctic tundra permafrost landform features called ice-wedge polygons (IWPs) as candidate geo objects. We choose Mask RCNN as the DLCNN architecture to detect IWPs from eight-band Worldview-02 VHSR satellite imagery. A systematic experiment was designed to understand the impact on choosing the optimal three-band combination in model prediction. We tasked five cohorts of three-band combinations coupled with statistical measures to gauge the spectral variability of input MS bands. The candidate scenes produced high model detection accuracies for the F1 score, ranging between 0.89 to 0.95, for two different band combinations (coastal blue, blue, green (1,2,3) and green, yellow, red (3,4,5)). The mapping workflow discerned the IWPs by exhibiting low random and systematic error in the order of 0.17–0.19 and 0.20–0.21, respectively, for band combinations (1,2,3). Results suggest that the prediction accuracy of the Mask-RCNN model is significantly influenced by the input MS bands. Overall, our findings accentuate the importance of considering the image statistics of input MS bands and careful selection of optimal bands for DLCNN predictions when DLCNN architectures are restricted to three spectral channels.
Host Immune Defense upon Fungal Infections with Mucorales: Pathogen-Immune Cell Interactions as Drivers of Inflammatory Responses
Authors: Montaño Dolly E. , Voigt Kerstin
Published: September 2020

During the last few decades, mucormycosis has emerged as one of the most common fungal infections, following candidiasis and aspergillosis. The fungal order responsible for causing mucormycosis is the Mucorales. The main hallmarks of this infection include the invasion of blood vessels, infarction, thrombosis, and tissue necrosis, which are exhibited at the latest stages of the infection. Therefore, the diagnosis is often delayed, and the rapid progression of the infection severely endangers the life of people suffering from diabetes mellitus, hematological malignancies, or organ transplantation. Given the fact that mortality rates for mucormycosis range from 40 to 80%, early diagnosis and novel therapeutic strategies are urgently needed to battle the infection. However, compared to other fungal infections, little is known about the host immune response against Mucorales and the influence of inflammatory processes on the resolution of the infection. Hence, in this review, we summarized our current understanding of the interplay among pro-inflammatory cytokines, chemokines, and the host-immune cells in response to mucoralean fungi, as well as their potential use for immunotherapies.
Second Language Acquisition and the Mastery of Discourse Connectives: Assessing the Factors That Hinder L2-Learners from Mastering French Connectives
Authors: Wetzel Mathis , Zufferey Sandrine , Gygax Pascal
Published: September 2020

Even though the mastery of discourse connectives represents an important step toward reaching high language proficiency, it remains highly difficult for L2-learners to master them. We conducted an experiment in which we tested the mastery of 12 monofunctional French connectives conveying six different coherence relations by 151 German-speaking learners of French, as well as a control group of 63 native French speakers. Our results show that the cognitive complexity of the coherence relation and connectives’ frequency, both found to be important factors for native speakers’ connective mastery, play a minor role for the mastery by non-native speakers. Instead, we argue that two specific factors, namely the connectives’ register and meaning transparency, seem to be more predictive variables. In addition, we found that a higher exposure to print in L1, correlates with a better mastery of the connectives in L2. We discuss the implications of our findings in the context of second language acquisition.
Low-Temperature Rheological Properties and Microscopic Characterization of Asphalt Rubbers Containing Heterogeneous Crumb Rubbers
Authors: Chang Mingfeng , Zhang Yixing , Pei Jianzhong , Zhang Jiupeng , Wang Min , Ha Fugui
Published: September 2020

Asphalt rubbers mixed with untreated and plasticized crumb rubbers and a compounding coupling agent were investigated in this study. The low-temperature rheological properties of asphalt rubbers at different aging levels were tested using a dynamic shear rheometer (DSR). An interconversion between linear viscoelastic material functions was used to obtain converted evaluation indexes for the asphalt rubbers at low temperatures. Lastly, the physicochemical characteristics and the microscopic morphology of the asphalt rubbers were evaluated using Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM), respectively. In conclusion, the storage moduli of the asphalt rubbers containing heterogeneous crumb rubbers increased with the plasticized crumb rubber content and the aging level. The converted relaxation moduli were consistent with the change trend of the storage moduli, and the relaxation rate decreased as the plasticized crumb rubber content and the aging level increased. The process of mixing the base asphalt with crumb and plasticized crumb rubbers was physical blending, and the effect of aging on the absorption peak change of asphalt rubber with plasticized crumb rubbers was less than that of asphalt rubber with ordinary crumb rubbers. Aging deteriorated the blending between the crumb rubber and the base asphalt, and a distinct interface appeared between the crumb rubber and the base asphalt. The particle cores of the plasticized crumb rubber in the asphalt rubber were difficult to maintain. Furthermore, as the plasticized crumb rubber content increased, more fine particles stripped off the plasticized crumb rubber after aging.
Experimental Investigation of Impactor Diameter Effect on Low-Velocity Impact Response of CFRP Laminates in a Drop-Weight Impact Event
Authors: Cao Hongyi , Ma Mengyuan , Jiang Mingshun , Sun Lin , Zhang Lei , Jia Lei , Tian Aiqin , Liang Jianying
Published: September 2020

The present study delved into the effect of impactor diameter on low velocity impact response and damage characteristics of CFRP. Moreover, the phased array ultrasonic technique (PAUT) was adopted to identify the impact damages based on double-sided scanning. Low-velocity impact tests were carried out using three hemispherical impactors with different diameters. The relationship of impact response and impactor diameters was analyzed by ultrasonic C-scans and S-scans, combined with impact response parameters. Subsequently, the damage characteristics were assessed in terms of dent depth, delamination area and extension shape via the thickness, and the relationships between absorbed energy, impactor displacement, dent depth and delamination area were elucidated. As revealed from experiment results, double-sided PAUT is capable of representing the internal damage characteristics more accurately. Moreover, the impactor diameter slightly affects the impact response under small impact energy, whereas it significantly affects the impact response under large impact energy.
Thermomechanical Response of Fullerene-Reinforced Polymers by Coupling MD and FEM
Authors: Giannopoulos Georgios I. , Georgantzinos Stelios K. , Anifantis Nick K.
Published: September 2020

The aim of the present study is to provide a computationally efficient and reliable hybrid numerical formulation capable of characterizing the thermomechanical behavior of nanocomposites, which is based on the combination of molecular dynamics (MD) and the finite element method (FEM). A polymeric material is selected as the matrix—specifically, the poly(methyl methacrylate) (PMMA) commonly known as Plexiglas due to its expanded applications. On the other hand, the fullerene C240 is adopted as a reinforcement because of its high symmetry and suitable size. The numerical approach is performed at two scales. First, an analysis is conducted at the nanoscale by utilizing an appropriate nanocomposite unit cell containing the C240 at a high mass fraction. A MD-only method is applied to accurately capture all the internal interfacial effects and accordingly its thermoelastic response. Then, a micromechanical, temperature-dependent finite element analysis takes place using a representative volume element (RVE), which incorporates the first-stage MD output, to study nanocomposites with small mass fractions, whose atomistic-only simulation would require a substantial computational effort. To demonstrate the effectiveness of the proposed scheme, numerous numerical results are presented while the investigation is performed in a temperature range that includes the PMMA glass transition temperature, Tg.
Numerical Non-Linear Modelling Algorithm Using Radial Kernels on Local Mesh Support
Authors: Navarro-González Francisco José , Villacampa Yolanda , Cortés-Molina Mónica , Ivorra Salvador
Published: September 2020

Estimation problems are frequent in several fields such as engineering, economics, and physics, etc. Linear and non-linear regression are powerful techniques based on optimizing an error defined over a dataset. Although they have a strong theoretical background, the need of supposing an analytical expression sometimes makes them impractical. Consequently, a group of other approaches and methodologies are available, from neural networks to random forest, etc. This work presents a new methodology to increase the number of available numerical techniques and corresponds to a natural evolution of the previous algorithms for regression based on finite elements developed by the authors improving the computational behavior and allowing the study of problems with a greater number of points. It possesses an interesting characteristic: Its direct and clear geometrical meaning. The modelling problem is presented from the point of view of the statistical analysis of the data noise considered as a random field. The goodness of fit of the generated models has been tested and compared with some other methodologies validating the results with some experimental campaigns obtained from bibliography in the engineering field, showing good approximation. In addition, a small variation on the data estimation algorithm allows studying overfitting in a model, that it is a problematic fact when numerical methods are used to model experimental values.
Quantized-Feedback-Based Adaptive Event-Triggered Control of a Class of Uncertain Nonlinear Systems
Authors: Choi Yun Ho , Yoo Sung Jin
Published: September 2020

A quantized-feedback-based adaptive event-triggered tracking problem is investigated for strict-feedback nonlinear systems with unknown nonlinearities and external disturbances. All state variables are quantized through a uniform quantizer and the quantized states are only measurable for the control design. An approximation-based adaptive event-triggered control strategy using quantized states is presented. Compared with the existing recursive quantized feedback control results, the primary contributions of the proposed strategy are (1) to derive a quantized-states-based function approximation mechanism for compensating for unknown and unmatched nonlinearities and (2) to design a quantized-states-based event triggering law for the intermittent update of the control signal. A Lyapunov-based stability analysis is provided to conclude that closed-loop signals are uniformly ultimately bounded and there exists a minimum inter-event time for excluding Zeno behavior. In simulation results, it is shown that the proposed quantized-feedback-based event-triggered control law can be implemented with less than 10% of the total sample data of the existing quantized-feedback continuous control law.
Set-Valued Symmetric Generalized Strong Vector Quasi-Equilibrium Problems with Variable Ordering Structures
Authors: Li Jing-Nan , Wang San-Hua , Xu Yu-Ping
Published: September 2020

In this paper, two types of set-valued symmetric generalized strong vector quasi-equilibrium problems with variable ordering structures are discussed. By using the concept of cosmically upper continuity rather than the one of upper semicontinuity for cone-valued mapping, some existence theorems of solutions are established under suitable assumptions of cone-continuity and cone-convexity for the equilibrium mappings. Moreover, the results of compactness for solution sets are proven. As applications, some existence results of strong saddle points are obtained. The main results obtained in this paper unify and improve some recent works in the literature.
Electrochemical Performance of Micropillar Array Electrodes in Microflows
Authors: Liu Bo , Lv Chuanwen , Chen Chaozhan , Ran Bin , Lan Minbo , Chen Huaying , Zhu Yonggang
Published: September 2020

The microchip-based electrochemical detection system (μEDS) has attracted plenty of research attention due to its merits including the capability in high-density integration, high sensitivity, fast analysis time, and reduced reagent consumption. The miniaturized working electrode is usually regarded as the core component of the μEDS, since its characteristic directly determines the performance of the whole system. Compared with the microelectrodes with conventional shapes such as the band, ring and disk, the three-dimensional (3D) micropillar array electrode (μAE) has demonstrated significant potential in improving the current response and decreasing the limits of detection due to its much larger reaction area. In this study, the numerical simulation method was used to investigate the performance of the μEDS, and both the geometrical and hydrodynamic parameters, including the micropillars shape, height, arrangement form and the flow rate of the reactant solution, were taken into consideration. The tail effect in μAEs was also quantitatively analyzed based on a pre-defined parameter of the current density ratio. In addition, a PDMS-based 3D μAE was fabricated and integrated into the microchannel for the electrochemical detection. The experiments of cyclic voltammetry (CV) and chronoamperometry (CA) were conducted, and a good agreement was found between the experimental and simulation results. This study would be instructive for the configuration and parameters design of the μEDS, and the presented method can be adopted to analyze and optimize the performance of nanochip-based electrochemical detection system (nEDS).
Broadband High-Efficiency Grating Couplers for Perfectly Vertical Fiber-to-Chip Coupling Enhanced by Fabry-Perot-like Cavity
Authors: Zhang Zan , Huang Beiju , Zhang Zanyun , Cheng Chuantong , Bai Bing , Gao Tianxi , Xu Xiaobo , Gu Wenping , Zhang Lin , Chen Hongda
Published: September 2020

We propose a broadband high-efficiency grating coupler for perfectly vertical fiber-to-chip coupling. The up-reflection is reduced, hence enhanced coupling efficiency is achieved with the help of a Fabry-Perot-like cavity composed of a silicon nitride reflector and the grating itself. With the theory of the Fabry-Perot cavity, the dimensional parameters of the coupler are investigated. With the optimized parameters, up-reflection in the C-band is reduced from 10.6% to 5%, resulting in an enhanced coupling efficiency of 80.3%, with a 1-dB bandwidth of 58 nm, which covers the entire C-band. The minimum feature size of the proposed structure is over 219 nm, which makes our design easy to fabricate through 248 nm deep-UV lithography, and lowers the fabrication cost. The proposed design has potential in efficient and fabrication-tolerant interfacing applications, between off-chip light sources and integrated chips that can be mass-produced.
Viral Abundance and Diversity of Production Fluids in Oil Reservoirs
Authors: Zheng Liangcan , Liang Xiaolong , Shi Rongjiu , Li Ping , Zhao Jinyi , Li Guoqiao , Wang Shuang , Han Siqin , Radosevich Mark , Zhang Ying
Published: September 2020

Viruses are widely distributed in various ecosystems and have important impacts on microbial evolution, community structure and function and nutrient cycling in the environment. Viral abundance, diversity and distribution are important for a better understanding of ecosystem functioning and have often been investigated in marine, soil, and other environments. Though microbes have proven useful in oil recovery under extreme conditions, little is known about virus community dynamics in such systems. In this study, injection water and production fluids were sampled in two blocks of the Daqing oilfield limited company where water flooding and microbial flooding were continuously used to improve oil recovery. Virus-like particles (VLPs) and bacteria in these samples were extracted and enumerated with epifluorescence microscopy, and viromes of these samples were also sequenced with Illumina Hiseq PE150. The results showed that a large number of viruses existed in the oil reservoir, and VLPs abundance of production wells was 3.9 ± 0.7 × 108 mL−1 and virus to bacteria ratio (VBR) was 6.6 ± 1.1 during water flooding. Compared with water flooding, the production wells of microbial flooding had relative lower VLPs abundance (3.3 ± 0.3 × 108 mL−1) but higher VBR (7.9 ± 2.2). Assembled viral contigs were mapped to an in-house virus reference data separate from the GenBank non-redundant nucleotide (NT) database, and the sequences annotated as virus accounted for 35.34 and 55.04% of total sequences in samples of water flooding and microbial flooding, respectively. In water flooding, 7 and 6 viral families were identified in the injection and production wells, respectively. In microbial flooding, 6 viral families were identified in the injection and production wells. The total number of identified viral species in the injection well was higher than that in the production wells for both water flooding and microbial flooding. The Shannon diversity index was higher in the production well of water flooding than in the production well of microbial flooding. These results show that viruses are very abundant and diverse in the oil reservoir’s ecosystem, and future efforts are needed to reveal the potential function of viral communities in this extreme environment.
Fungicide Resistance in Powdery Mildew Fungi
Authors: Vielba-Fernández Alejandra , Polonio Álvaro , Ruiz-Jiménez Laura , de Vicente Antonio , Pérez-García Alejandro , Fernández-Ortuño Dolores
Published: September 2020

Powdery mildew fungi (Erysiphales) are among the most common and important plant fungal pathogens. These fungi are obligate biotrophic parasites that attack nearly 10,000 species of angiosperms, including major crops, such as cereals and grapes. Although cultural and biological practices may reduce the risk of infection by powdery mildew, they do not provide sufficient protection. Therefore, in practice, chemical control, including the use of fungicides from multiple chemical groups, is the most effective tool for managing powdery mildew. Unfortunately, the risk of resistance development is high because typical spray programs include multiple applications per season. In addition, some of the most economically destructive species of powdery mildew fungi are considered to be high-risk pathogens and are able to develop resistance to several chemical classes within a few years. This situation has decreased the efficacy of the major fungicide classes, such as sterol demethylation inhibitors, quinone outside inhibitors and succinate dehydrogenase inhibitors, that are employed against powdery mildews. In this review, we present cases of reduction in sensitivity, development of resistance and failure of control by fungicides that have been or are being used to manage powdery mildew. In addition, the molecular mechanisms underlying resistance to fungicides are also outlined. Finally, a number of recommendations are provided to decrease the probability of resistance development when fungicides are employed.
An In-Depth Exploration of Knowledge and Beliefs Associated with Soda and Diet Soda Consumption
Authors: Miller Caroline , Ettridge Kerry , Wakefield Melanie , Pettigrew Simone , Coveney John , Roder David , Durkin Sarah , Wittert Gary , Martin Jane , Dono Joanne
Published: September 2020

The need to reduce sugar-sweetened beverage (SSB) consumption is widely accepted, but whether artificially sweetened beverages (ASBs) are a recommended alternative is a growing policy issue because of emerging evidence of potential health effects associated with excess consumption. This study aimed to establish the extent of the Australian population’s knowledge of the risks associated with consuming SSBs (e.g., soda) and ASBs (e.g., diet soda), which is essential for identifying which facets of knowledge to target with public health interventions. A national computer-assisted telephone survey of 3430 Australian adults was conducted in 2017. The survey included a range of measures to test associations between SSB and ASB knowledge and beliefs, demographic characteristics, and soda and diet soda consumption. Participants had an overall awareness that there were health risks associated with SSB and ASB consumption, but they lacked more detailed knowledge of health effects and nutritional composition of these drinks. These knowledge gaps are concerning given that SSBs and ASBs are consumed in large quantities in Australia. Public health interventions targeting consumers’ limited knowledge and perceptions of health risks associated with excess sugar, calorie intake and artificial sweeteners are essential in reducing the health burden of obesity.
Nutritional Therapy to Modulate Tryptophan Metabolism and Aryl Hydrocarbon-Receptor Signaling Activation in Human Diseases
Authors: Ghiboub Mohammed , Verburgt Charlotte M. , Sovran Bruno , Benninga Marc A. , de Jonge Wouter J. , Van Limbergen Johan E.
Published: September 2020

The aryl hydrocarbon receptor (AhR) is a nuclear protein which, upon association with certain endogenous and exogenous ligands, translocates into the nucleus, binds DNA and regulates gene expression. Tryptophan (Trp) metabolites are one of the most important endogenous AhR ligands. The intestinal microbiota is a critical player in human intestinal homeostasis. Many of its effects are mediated by an assembly of metabolites, including Trp metabolites. In the intestine, Trp is metabolized by three main routes, leading to kynurenine, serotonin, and indole derivative synthesis under the direct or indirect involvement of the microbiota. Disturbance in Trp metabolism and/or AhR activation is strongly associated with multiple gastrointestinal, neurological and metabolic disorders, suggesting Trp metabolites/AhR signaling modulation as an interesting therapeutic perspective. In this review, we describe the most recent advances concerning Trp metabolism and AhR signaling in human health and disease, with a focus on nutrition as a potential therapy to modulate Trp metabolites acting on AhR. A better understanding of the complex balance between these pathways in human health and disease will yield therapeutic opportunities.
Is Drinking Alcohol Really Linked to Cardiovascular Health? Evidence from the Kardiovize 2030 Project
Authors: Maugeri Andrea , Hlinomaz Ota , Agodi Antonella , Barchitta Martina , Kunzova Sarka , Bauerova Hana , Sochor Ondrej , Medina-Inojosa Jose R. , Lopez-Jimenez Francisco , Vinciguerra Manlio , Stokin Gorazd Bernard , González-Rivas Juan Pablo
Published: September 2020

Existing data have described benefits and drawbacks of alcohol consumption on cardiovascular diseases (CVD), but no research has evaluated its association with the cardiovascular health (CVH) score proposed by the American Heart Association. Here, we conducted a cross-sectional analysis on the Kardiovize cohort (Brno, Czech Republic), to investigate the relationship between alcohol consumption and CVH. We included 1773 subjects (aged 25–64 years; 44.2% men) with no history of CVD. We compared CVD risk factors, CVH metrics (i.e., BMI, healthy diet, physical activity level, smoking status, blood pressure, fasting glucose, and total cholesterol) and CVH score between and within several drinking categories. We found that the relationship between drinking habits and CVH was related to the amount of alcohol consumed, drinking patterns, and beverage choices. Heavy drinkers were more likely to smoke tobacco, and to report diastolic blood pressure, fasting glucose, triglycerides, and low-density lipoprotein (LDL)-cholesterol at higher level than non-drinkers. Among drinkers, however, people who exclusively drank wine exhibited better CVH than those who exclusively drank beer. Although our findings supported the hypothesis that drinking alcohol was related to the CVH in general, further prospective research is needed to understand whether the assessment of CVH should incorporate information on alcohol consumption.
Association of Maternal Plasma Total Cysteine and Growth among Infants in Nepal: A Cohort Study
Authors: Arora Nikhil , Strand Tor A. , Chandyo Ram K. , Elshorbagy Amany , Shrestha Laxman , Ueland Per M. , Ulak Manjeswori , Schwinger Catherine
Published: September 2020

Cysteine is a semi-essential amino acid that has been positively associated with growth in children. However, transgenerational effects remain unclear. The aim of this analysis was to assess whether maternal plasma total cysteine (tCys) concentration is associated with various growth indicators in infants living in peri-urban settings in Bhaktapur, Nepal. We used data from the 561 mothers enrolled in an ongoing randomized controlled trial. We built linear regression models to evaluate the associations between maternal tCys and birth weight, length-for-age Z-scores (LAZ) and weight-for-length Z-scores (WLZ) at birth and six months of age. Maternal tCys was inversely associated with birth weight among boys after adjusting for confounders (p < 0.05). In addition, there was a negative association between maternal tCys and LAZ at birth (p < 0.01). No associations between maternal tCys and the other anthropometric indicators were found significant, although there was a tendency for maternal tCys to be associated positively with WLZ at birth among girls (p < 0.10). This is a first study evaluating transgenerational relation of tCys on growth in infants. Further, larger and more comprehensive studies are needed to determine if and how maternal tCys alters child growth.
Quercetin Supplementation Improves Neuromuscular Function Recovery from Muscle Damage
Authors: Bazzucchi Ilenia , Patrizio Federica , Ceci Roberta , Duranti Guglielmo , Sabatini Stefania , Sgrò Paolo , Di Luigi Luigi , Sacchetti Massimo
Published: September 2020

This study was aimed at investigating whether quercetin (Q) may improve the recovery of neuromuscular function and biochemical parameters in the 7 days following an eccentric exercise-induced muscle damage (EEIMD). Sixteen men (25.9 ± 3.3 y) ingested Q (1000 mg/day) or placebo (PLA) for 14 days following a double-blind crossover study design. A neuromuscular (NM) test was performed pre–post, 24 h, 48 h, 72 h, 96 h and 7 days after an intense eccentric exercise. The force–velocity relationship of the elbow flexor muscles and their maximal voluntary isometric contraction (MVIC) were recorded simultaneously to the electromyographic signals (EMG). Pain, joint angle, arm circumference, plasma creatine kinase (CK) and lactate-dehydrogenase (LDH) were also assessed. The results showed that Q supplementation significantly attenuated the strength loss compared to PLA. During the recovery, force–velocity relationship and mean fibers conduction velocity (MFCV) persisted significantly less when participants consumed PLA rather than Q, especially at the highest angular velocities (p < 0.02). A greater increase in biomarkers of damage was also evident in PLA with respect to Q. Q supplementation for 14 days seems able to ameliorate the recovery of eccentric exercise-induced weakness, neuromuscular function impairment and biochemical parameters increase probably due to its strong anti-inflammatory and antioxidant action.
Curvature Invariants for the Accelerating Natário Warp Drive
Authors: Mattingly Brandon , Kar Abinash , Gorban Matthew , Julius William , Watson Cooper K. , Ali M.D. , Baas Andrew , Elmore Caleb , Lee Jeffrey S. , Shakerin Bahram , Davis Eric W. , Cleaver Gerald B.
Published: September 2020

A process for using curvature invariants is applied to evaluate the accelerating Natário warp drive. Curvature invariants are independent of coordinate bases and plotting the invariants is free of coordinate mapping distortions. While previous works focus mainly on the mathematical description of the warp bubble, plotting curvature invariants provides a novel pathway to investigate the Natário spacetime and its characteristics. For warp drive spacetimes, there are four independent curvature invariants the Ricci scalar, r1, r2, and w2. The invariant plots demonstrate how each curvature invariant evolves over the parameters of time, acceleration, skin depth and radius of the warp bubble. They show that the Ricci scalar has the greatest impact of the invariants on the surrounding spacetime. They also reveal key features of the Natário warp bubble such as a flat harbor in the center of it, a dynamic wake, and the internal structures of the warp bubble.
Drug Utilisation and Off-Label Use on a German Neonatal Intensive Care Unit: A Retrospective Cohort Study and 10-Year Comparison
Authors: Geißler Carmen , Schulze Christopher , Botzenhardt Sebastian , Rascher Wolfgang , Neubert Antje
Published: September 2020

Pharmacotherapy of neonates is complex and marked to a large extent of off-label use. The implementation of the Paediatric Regulation (2007) gave hope for a change in the safety and efficacy for drugs used in neonatal intensive care units (NICU). This study investigates drug utilisation patterns and off-label use in a German neonatal intensive care unit (NICU) in 2014. A 12-months retrospective, observational cohort study was performed at the NICU of the University Children’s Hospital Erlangen, Germany. Licensing status was determined using the Summary of Product Characteristics (SmPC). Results are compared with a similar study conducted 10 years earlier. The study included 204 patients (57.8% male) (2004: 183) and 2274 drug prescriptions were recorded (2004: 1978). The drugs that were mostly prescribed were drugs for the nervous system (2004: 22.6%; 2014: 26.9%) and anti-infectives for systemic use (2004: 26.0%; 2014: 24.9%);34.3% (2004) and 39.2% (2014) of all prescriptions were off-label;62.7% of all patients received at least one off-label or unlicensed drug (2004: 70%). For 13 drugs, the licensing status changed either from off-label to label (n = 9) or vice versa (n = 4). Overall, there was no significant change neither in terms of the drugs used nor regarding their licensing status. Further studies are needed to validate these findings in a European context.
Socheongryongtang Modulates Asthma-Related Changes via Modulation of TNF-α and T-bet as well as IFN-γ in an Asthma Murine Model
Authors: Bok So-Hyeon , Cho Seung Sik , Bae Chun-Sik , Kang Bossng , Son Hong-Seok , Park Dae-Hun
Published: September 2020

In 2017 the World Health Organization (WHO) reported that 235 million people suffered from asthma, and that 383,000 deaths were due to asthma in 2015. Asthma cannot be completely eradicated and the medications for asthma are associated with many adverse effects. Socheongryongtang is one of the prescriptions which has traditionally been used for the treatment of pulmonary disease, but the anti-asthmatic mechanism is unclear. To investigate the anti-asthmatic mechanism of socheongryongtang, BALB/c mice were divided into five groups: control, asthma-induced control, dexamethasone treatment, and 150 mg/kg or 1500 mg/kg socheongryongtang treatment and several biomarkers were analyzed, such as white blood cell (WBC) and differential counts in broncheoalveolar fluid (BALF), immunoglobulin E (IgE) in serum, and morphological changes/helper T cell-related cytokines/transcription factor in the lung. The therapeutic ingredients were also analyzed. Socheongryongtang inhibited the neutrophils differentiation in BALF, controlled interleukin (IL)-12p40 releasing, down-regulated not only GATA-3 and helper 2 T (Th2) cell transcription factors but also IL-4, and also decreased the level of tumor necrosis factor (TNF)-α in the lung. In addition, through high-performance liquid chromatography (HPLC) analysis, we confirmed that the therapeutic ingredients in socheongryongtang were paeoniflorin, liquiritin, and glycyrrhizin. The oral intake of 7.3 g of socheongryongtang is beneficial for suppressing the possibility of the occurrence of asthma via modulation of TNF-α and T-bet as well as IFN-γ.
Bridge Inspection Using Unmanned Aerial Vehicle Based on HG-SLAM: Hierarchical Graph-Based SLAM
Authors: Jung Sungwook , Choi Duckyu , Song Seungwon , Myung Hyun
Published: September 2020

With the increasing demand for autonomous systems in the field of inspection, the use of unmanned aerial vehicles (UAVs) to replace human labor is becoming more frequent. However, the Global Positioning System (GPS) signal is usually denied in environments near or under bridges, which makes the manual operation of a UAV difficult and unreliable in these areas. This paper addresses a novel hierarchical graph-based simultaneous localization and mapping (SLAM) method for fully autonomous bridge inspection using an aerial vehicle, as well as a technical method for UAV control for actually conducting bridge inspections. Due to the harsh environment involved and the corresponding limitations on GPS usage, a graph-based SLAM approach using a tilted 3D LiDAR (Light Detection and Ranging) and a monocular camera to localize the UAV and map the target bridge is proposed. Each visual-inertial state estimate and the corresponding LiDAR sweep are combined into a single subnode. These subnodes make up a “supernode” that consists of state estimations and accumulated scan data for robust and stable node generation in graph SLAM. The constraints are generated from LiDAR data using the normal distribution transform (NDT) and generalized iterative closest point (G-ICP) matching. The feasibility of the proposed method was verified on two different types of bridges: on the ground and offshore.
Flood Inundation Mapping by Combining GNSS-R Signals with Topographical Information
Authors: Unnithan S L Kesav , Biswal Basudev , Rüdiger Christoph
Published: September 2020

The Cyclone Global Navigation Satellite System (CYGNSS) mission collects near-global hourly, pseudo-randomly distributed Global Navigation Satellite System - Reflectometry (GNSS-R) signals in the form of signal-to-noise ratio (SNR) point data, which is sensitive to the presence of surface water, due to their operating frequency at L-band. However, because of the pseudo-random nature of these points, it is not possible to obtain continuous flood inundation maps at adequately high resolution. By considering topological indicators, such as height above nearest drainage (HAND) and slope of nearest drainage (SND), which indicate the probability of a certain area being prone to flooding, we hypothesize that combining static topographic information with the dynamic GNSS-R signals can result in large-scale, high-resolution flood inundation maps. Flood mapping was performed and validated with flood extent derived using available Sentinel-1A synthetic aperture radar (SAR) data for flooding in Kerala during August 2018, and North India during August 2017. The results obtained after thresholding indicate that the model exhibits a flooding accuracy ranging from 60% to 80% for lower threshold values. We observed significant overestimation error in mapping inundation across the flooding period, resulting in an optimal critical success index of 0.22 for threshold values between 17–19.
Assessing Reef Island Sensitivity Based on LiDAR-Derived Morphometric Indicators
Authors: Bonesso Joshua Louis , Cuttler Michael V.W. , Browne Nicola , Hacker Jorg , O’Leary Michael
Published: September 2020

Reef islands are some of the most highly sensitive landforms to the impacts of future environmental change. Previous assessments of island morphodynamics primarily relied on historical aerial and satellite imagery. These approaches limit analysis to two-dimensional parameters, with no ability to assess long-term changes to island volume or elevation. Here, we use high-resolution airborne LiDAR data to assess three-dimensional reef island features for 22 islands along the north-western coast of Australia. Our primary objective was to utilize two regional LiDAR datasets to identify characteristics indicative of island sensitivity and future vulnerability. Results show reef platform area to be an accurate predictor of island area and volume suggesting larger island volumes may reflect (1) increased carbonate production and supply from the reef platform and/or (2) enhanced shoreline protection by larger reef platforms. Locations of foredune scarping (an erosional signature) and island orientations were aligned to the regional wind and wave climate. Reef island characteristics (island area, volume, elevation, scarping, and platform area) were used to rank islands according to sensitivity, using a new Island Sensitivity Characteristics Index (ISCi) where low ISCi indicates stable islands (large areas and volumes, high elevations, and fewer scarped areas) and high ISCi indicates unstable islands (small areas and volumes, low elevations, and more scarped areas). Comparison of two LiDAR surveys from 2016 and 2018 validates the use of 3D morphometrics as important (direct) measurements of island landform change, and can complement the use of 2D parameters (e.g., area) moving forward. Results demonstrate that ongoing use of airborne LiDAR and other 3D technology for monitoring coral reef islands at regional scales will enable more accurate quantification of their sensitivity to future impacts of global environmental change.
Reconstruction of Wet Refractivity Field Using an Improved Parameterized Tropospheric Tomographic Technique
Authors: Chen Biyan , Dai Wujiao , Xia Pengfei , Ao Minsi , Tan Jingshu
Published: September 2020

In most previous studies of tropospheric tomography, water vapor is assumed to have a homogeneous distribution within each voxel. The parameterization of voxels can mitigate the negative effects of the improper assumption to the tomographic solution. An improved parameterized algorithm is proposed for determining the water vapor distribution by Global Navigation Satellite System (GNSS) tomography. Within a voxel, a generic point is determined via horizontal inverse distance weighted (IDW) interpolation and vertical exponential interpolation from the wet refractivities at the eight surrounding voxel nodes. The parameters involved in exponential and IDW interpolation are dynamically estimated for each tomography by using the refractivity field of the last process. By considering the quasi-exponential behavior of the wet refractivity profile, an optimal algorithm is proposed to discretize the vertical layers of the tomographic model. The improved parameterization algorithm is validated with the observational data collected over a 1-month period from 124 Global Positioning System (GPS) stations of Hunan Province, China. Assessments by GPS, radiosonde, and European Centre for Medium-Range Weather Forecasts (ECMWF) ReAnalysis 5 (ERA5) data, demonstrate that the improved model outperforms the traditional nonparametric model and the parameterized model using trilinear interpolation. In the assessment by GPS data, the improved model performs better than the traditional model and the trilinear parameterized model by 54% and 10%, respectively. Such improvements are 31% and 10% in the validation by radiosonde profiles. In comparison with the ERA5 reanalysis, the improved model yields a minimum overall root mean square (RMS) error of 8.94 mm/km, while those of the traditional and trilinear parametrized models are 10.79 and 9.73 mm/km, respectively. The RMS errors vertically decrease from ~20 mm/km at the bottom to ~5 mm/km at the top layer.
Coil Positioning for Wireless Power Transfer System of Automatic Guided Vehicle Based on Magnetic Sensing
Authors: Liang Ce , Zhang Yanchi , Li Zhonggang , Yuan Feng , Yang Guang , Song Kai
Published: September 2020

As an auxiliary function of the wireless power transfer (WPT) system, coil positioning can solve the power and efficiency degradation during power transmission caused by misalignment of the magnetic coupler. In this paper, a Hall sensor array is used to measure the change of magnetic flux density. By comparing the multisensor data fusion results with the preset data obtained from the coil alignment, the real-time accurate positioning of the receiving coil can be realized. Firstly, the positioning model of the receiving coil is built and the variation of magnetic flux density with the coil misalignment is analyzed. Secondly, the arrangement of the Planar 8-direction symmetric sensor array and the positioning algorithm based on data fusion of magnetic flux density variations are proposed. In order to avoid coil positioning misalignment caused by the unstable magnetic field distribution which is actually affected by the change of mutual inductance during automatic guided vehicle (AGV) alignment, the constant current strategy of primary and secondary sides is proposed. Finally, the coil positioning experimental platform is built. The experimental results show that the coil positioning method proposed in this paper has high accuracy, and the positioning error is within 4 cm.