bluuebunny/crossref_metadata_2025 huggingface dataset:
Behaviors, symptoms, and outcomes of North American patients with autoimmune hepatitis during the COVID-19 pandemic
Authors: Vuppalanchi Vahin , Gelow Kayla , Green Kelsey , Vuppalanchi Raj , Lammert Craig
Published: July 2021

The management of patients with autoimmune hepatitis (AIH) in the era of SARS-CoV-2 is challenging given minimal published clinical data. We used a large cohort of patients with AIH across the USA to investigate the differences in known risk factors for severe SARS-CoV-2 and AIH characteristics among patients who experienced symptoms consistent with COVID-19 illness versus those who did not. Additionally, we explored the effect of living through the SARS-CoV-2 pandemic on the extrahepatic symptoms and behaviors of patients with AIH. An invitation to complete a COVID-19-specific questionnaire was publicized in well-established social media cohorts of patients with AIH. Eligibility criteria were age ≥18 years, US residency, and an AIH diagnosis by a physician. A total of 420 individuals were eligible for the study. Symptoms consistent with COVID-19 were reported in 11% (n=48) with 3 patients requiring hospitalizations. Body mass index (BMI) >40 kg/m2 (23% vs 10%, p =0.01) and exposure to house (33% vs 3%, p=0.0001) or work (38% vs 17%, p =0.02) contacts with COVID-19 were factors found higher in those with symptoms. Cirrhosis or steroid use or immunosuppression was not significantly different between symptomatic and non-symptomatic groups. Worsening fatigue (45% vs 30%, p=0.06), anxiety (89% vs 70%, p=0.08), and itch (40% vs 18%, p=0.03) were more common among those reporting COVID-19 symptoms compared with those without. BMI >40 kg/m2 and exposure to contacts with COVID-19 illness but not cirrhosis or immunosuppression were associated with increased risk of COVID-19 illness in patients with AIH.
A telerehabilitation programme in post-discharge COVID-19 patients (TERECO): a randomised controlled trial
Authors: Li Jian'an , Xia Wenguang , Zhan Chao , Liu Shouguo , Yin Zhifei , Wang Jiayue , Chong Yufei , Zheng Chanjuan , Fang Xiaoming , Cheng Wei , Reinhardt Jan D
Published: July 2021

Objectives

To investigate superiority of a telerehabilitation programme for COVID-19 (TERECO) over no rehabilitation with regard to exercise capacity, lower limb muscle strength (LMS), pulmonary function, health-related quality of life (HRQOL) and dyspnoea.

Design

Parallel-group randomised controlled trial with 1:1 block randomisation.

Setting

Three major hospitals from Jiangsu and Hubei provinces, China.

Participants

120 formerly hospitalised COVID-19 survivors with remaining dyspnoea complaints were randomised with 61 allocated to control and 59 to TERECO.

Intervention

Unsupervised home-based 6-week exercise programme comprising breathing control and thoracic expansion, aerobic exercise and LMS exercise, delivered via smartphone, and remotely monitored with heart rate telemetry.

Outcomes

Primary outcome was 6 min walking distance (6MWD) in metres. Secondary outcomes were squat time in seconds; pulmonary function assessed by spirometry; HRQOL measured with Short Form Health Survey-12 (SF-12) and mMRC-dyspnoea. Outcomes were assessed at 6 weeks (post-treatment) and 28 weeks (follow-up).

Results

Adjusted between-group difference in change in 6MWD was 65.45 m (95% CI 43.8 to 87.1; p<0.001) at post-treatment and 68.62 m (95% CI 46.39 to 90.85; p<0.001) at follow-up. Treatment effects for LMS were 20.12 s (95% CI 12.34 to 27.9; p<0.001) post-treatment and 22.23 s (95% CI 14.24 to 30.21; p<0.001) at follow-up. No group differences were found for lung function except post-treatment maximum voluntary ventilation. Increase in SF-12 physical component was greater in the TERECO group with treatment effects estimated as 3.79 (95% CI 1.24 to 6.35; p=0.004) at post-treatment and 2.69 (95% CI 0.06 to 5.32; p=0.045) at follow-up.

Conclusions

This trial demonstrated superiority of TERECO over no rehabilitation for 6MWD, LMS, and physical HRQOL.

Trial registration number

ChiCTR2000031834.
Increased carbohydrate availability effects energy and nutrient periodisation of professional male athletes from the Australian Football League
Authors: Salagaras Brie S. , Mackenzie-Shalders Kristen L. , Slater Gary J. , McLellan Chris , Coffey Vernon G.
Published: July 2021

This research aimed to explore the effect of increased carbohydrate availability intervention on energy intake and distribution in professional Australian Football athletes. Six 24-h energy and macronutrient intakes were quantified (n = 19 males; age 24 ± 4 y, stature 187 ± 8 cm, mass 87 ± 9 kg) using photographic food diaries and Foodworks analyses. Energy expenditure was estimated for the same period using GeneActiv accelerometers. During 3 control days, athletes had ad libitum access to food, while the 3 intervention days increased carbohydrate availability, through greater prompting and access to carbohydrate foods. Daily energy intake was higher during intervention (185 ± 40 kJ/kg/d) compared with control (172 ± 31 kJ/kg/d; p < 0.05) but remained below estimated expenditure, and carbohydrate intake was also greater with intervention (5.0 ± 0.2 g/kg/d) than control (4.0 ± 0.2 g/kg/d; p < 0.05). Expenditure was highest during the morning, which coincided with lowest intake on all days, while the intervention was associated with greater carbohydrate intake in the morning (0.6 g/kg, p < 0.05) compared with control. Increasing availability of carbohydrate during high-load training generated a modest increase in carbohydrate and energy intake, and the intervention was most effective in improving carbohydrate intake during mornings.

Novelty: Increased access and provision of carbohydrate foods increased carbohydrate consumption and energy intake on high training load days. Daily distribution of energy intake can be modified through actively promoting carbohydrate consumption.
Leptogenesis in supersymmetry with one L violating coupling
Authors: Adhikari Rathin , Dasgupta Arnab
Published: July 2021

We have shown a new scenario of successful leptogenesis with one L violating coupling and a relative Majorana phase playing the role of CP violation. This is in contrast to the usual consideration of Feynman diagram with at least two L violating couplings. We have considered R-parity violating minimal supersymmetric standard model (MSSM) for leptogenesis at TeV scale. This scenario is also consistent with generating light neutrino mass if asymmetry is generated through semileptonic $$\lambda ^{\prime }$$

λ
′

coupling.
A Multi-Objective Evolutionary Approach Based on Graph-in-Graph for Neural Architecture Search of Convolutional Neural Networks
Authors: Xue Yu , Jiang Pengcheng , Neri Ferrante , Liang Jiayu
Published: July 2021

With the development of deep learning, the design of an appropriate network structure becomes fundamental. In recent years, the successful practice of Neural Architecture Search (NAS) has indicated that an automated design of the network structure can efficiently replace the design performed by human experts. Most NAS algorithms make the assumption that the overall structure of the network is linear and focus solely on accuracy to assess the performance of candidate networks. This paper introduces a novel NAS algorithm based on a multi-objective modeling of the network design problem to design accurate Convolutional Neural Networks (CNNs) with a small structure. The proposed algorithm makes use of a graph-based representation of the solutions which enables a high flexibility in the automatic design. Furthermore, the proposed algorithm includes novel ad-hoc crossover and mutation operators. We also propose a mechanism to accelerate the evaluation of the candidate solutions. Experimental results demonstrate that the proposed NAS approach can design accurate neural networks with limited size.
Twisted crystallographic T-duality via the Baum–Connes isomorphism
Authors: Gomi Kiyonori , Kubota Yosuke , Thiang Guo Chuan
Published: July 2021

We establish the twisted crystallographic T-duality, which is an isomorphism between Freed–Moore twisted equivariant K-groups of the position and momentum tori associated to an extension of a crystallographic group. The proof is given by identifying the map with the Dirac homomorphism in twisted Chabert–Echterhoff KK-theory. We also illustrate how to exploit it in K-theory computations.
Synchronization of time-varying coupled complex networks via adaptive pinning control
Authors: Lin Hai , Wang Jincheng
Published: July 2021

Pinning synchronization of complex networks with two different kinds of time-varying coupling are studied in this paper. Inner coupling of the state variables and outer coupling in the complex network are taken into consideration. Based on the Lyapunov function theory, some general criteria and a simplified corollary for ensuring network synchronization are proposed. Linear pinning controllers, adaptive pinning controllers and adaptive coupling strength are designed for achieving complex network time-varying synchronization. Furthermore, the analytic relationship between control parameters is studied. Numerical simulations further illustrate the effectiveness of conclusions.
Proximal Gradient-Type Algorithms for a Class of Bilevel Programming Problems
Authors: Li Dan , Chen Shuang , Pang Li-Ping
Published: July 2021

A class of proximal gradient-type algorithm for bilevel nonlinear nondifferentiable programming problems with smooth substructure is developed in this paper. The original problem is approximately reformulated by explicit slow control technique to a parameterized family function which makes full use of the information of smoothness. At each iteration, we only need to calculate one proximal point analytically or with low computational cost. We prove that the accumulation iterations generated by the algorithms are solutions of the original problem. Moreover, some results of complexity of the algorithms are presented in convergence analysis. Numerical experiments are implemented to verify the efficiency of the proximal gradient algorithms for solving this kind of bilevel programming problems.
Complex Dynamics in a Closed-Loop Supply Chain with Risk Aversion and Fairness Concerns Under Supply Disruption
Authors: Zhang Yuhao , Zhang Tao
Published: July 2021

In this paper, we consider a closed-loop supply chain (CLSC) consisting of two suppliers, one manufacturer, one risk-averse retailer and one fair-caring third-party in the presence of supply disruption. We focus on establishing a dynamic Stackelberg game model with bounded rational expectation and analyzing the game evolution process. The effects of key parameters on the Nash equilibrium solutions and their stability are investigated, as well as the complex dynamical behaviors of the CLSC system are explored by using the stability region, bifurcation graph, the largest Lyapunov exponent (LLE), strange attractors, etc. Moreover, the performance of channel members under different values of parameters is researched by utilizing the (average) expected profits or utilities index. The analysis results reveal that the excessive fast adjustment speed of the manufacturer will lead to the system losing stability and falling into chaos. Also, the retailer’s risk aversion and the third party’s fairness concerns have a destabilization effect on the Nash equilibrium point, while the possibility of supply disruption has different effects on the scope of the adjustment speed of decision variables of the manufacturer. Furthermore, in most cases, an over the top adjustment speed of the manufacturer is disadvantageous to all the channel members for more expected profits, but the third-party can achieve a better performance when the system is in periodic state. Finally, the time-delay feedback control method is proposed to eliminate the system chaos.
3D topological quantum computing
Authors: Asselmeyer-Maluga Torsten
Published: July 2021

In this paper, we will present some ideas to use 3D topology for quantum computing extending ideas from a previous paper. Topological quantum computing used “knotted” quantum states of topological phases of matter, called anyons. But anyons are connected with surface topology. But surfaces have (usually) abelian fundamental groups and therefore one needs non-Abelian anyons to use it for quantum computing. But usual materials are 3D objects which can admit more complicated topologies. Here, complements of knots do play a prominent role and are in principle the main parts to understand 3-manifold topology. For that purpose, we will construct a quantum system on the complements of a knot in the 3-sphere (see T. Asselmeyer-Maluga, Quantum Rep. 3 (2021) 153, arXiv:2102.04452 for previous work). The whole system is designed as knotted superconductor, where every crossing is a Josephson junction and the qubit is realized as flux qubit. We discuss the properties of this systems in particular the fluxion quantization by using the A-polynomial of the knot. Furthermore, we showed that 2-qubit operations can be realized by linked (knotted) superconductors again coupled via a Josephson junction.
U-Net-Based Surrogate Model for Evaluation of Microfluidic Channels
Authors: Le Tuyen Quang , Chiu Pao-Hsiung , Ooi Chinchun
Published: July 2021

Microfluidics have shown great promise in multiple applications, especially in biomedical diagnostics and separations. While the flow properties of these microfluidic devices can be solved by numerical methods such as computational fluent dynamics (CFD), the process of mesh generation and setting up a numerical solver requires some domain familiarity, while more intuitive commercial programs such as fluent and StarCCM can be expensive. Hence, in this work, we demonstrated the use of a U-Net convolutional neural network as a surrogate model for predicting the velocity and pressure fields that would result for a particular set of microfluidic filter designs. The surrogate model is fast, easy to set-up and can be used to predict and assess the flow velocity and pressure fields across the domain for new designs of interest via the input of a geometry-encoding matrix. In addition, we demonstrate that the same methodology can also be used to train a network to predict pressure based on velocity data, and propose that this can be an alternative to numerical algorithms for calculating pressure based on velocity measurements from particle image velocimetry measurements. Critically, in both applications, we demonstrate prediction test errors of less than 1%, suggesting that this is indeed a viable method.
Finite Rings Whose Graphs Have Clique Number Less than Five
Authors: Liu Qiong , Wu Tongsuo , Guo Jin
Published: July 2021

Let [Formula: see text] be a commutative ring and [Formula: see text] be its zero-divisor graph. We completely determine the structure of all finite commutative rings whose zero-divisor graphs have clique number one, two, or three. Furthermore, if [Formula: see text] (each [Formula: see text] is local for [Formula: see text]), we also give algebraic characterizations of the ring [Formula: see text] when the clique number of [Formula: see text] is four.
Enhancement of Condensation Heat Transfer, Anti-Frosting and Water Harvesting by Hybrid Wettability Coating
Authors: Chen Xintao , Wu Xian , Li Fang , Zhao Xiaofeng , Wang Shanlin
Published: July 2021

Hydrophilic–hydrophobic hybrid wettability structures, inspired by desert beetles, have been widely designed to enhance the dewdrops’ migration under subcooled or/and high-humidity environment. However, it is still a challenge to regulate the graded distribution of the hydrophilic micro-regions for condensation applications. In this paper, we design a simple spray method to prepare the superamphiphilic–superamphiphobic hybrid wettability coatings by controlling the mass ratio (MR) of superamphiphobic SiO2 nano-powder and superamphiphilic gypsum micro-powder. We compare the macroscopical wettability, condensation heat transfer efficiency, frosting delayed time and water harvesting rate to demonstrate the unique advantage of hybrid wettability structures. The results show that the condensation heat transfer efficiency, frosting delayed time and water harvesting rate can be respectively promoted to about 131.50% [Formula: see text], 134.74% [Formula: see text] and 135.62% [Formula: see text], although their macroscopical wettability will gradually reduce with the MR increase. This work will provide substantial insights into the fabrication of efficient superhydrophilic–superhydrophobic hybrid wettability surfaces for condensation heat transfer, anti-frosting and water harvesting applications.
4D Printing of Self-Folding Hydrogel Tubes for Potential Tissue Engineering Applications
Authors: Zhao Yu-Dong , Lai Jia-Hui , Wang Min
Published: July 2021

In recent years, 4D printing has gained increasing attention in the tissue engineering field since this advanced manufacturing platform can create stimulus-responsive structures, which can change their shapes, functions, and/or properties when appropriate external stimulus/stimuli is/are applied. A number of hydrogels with swellable/shrinkable abilities have been explored for 4D printing to fabricate different shape-morphing structures for tissue engineering. Among them, gelatin methacryloyl (GelMA) has been 4D printed, which can self-fold into microtubular structures. Currently, the self-folding ability of 4D printed GelMA hydrogels is mainly based on the different cross-linking degrees (which control and govern the swelling degrees) across the thickness of hydrogels. However, this strategy alone can only form self-folding GelMA tubes with diameters at the micrometer level and cannot create self-folding GelMA tubes with diameters at the millimeter level, which is mainly due to the insufficient internal force generated in 4D printed GelMA hydrogels when they are exposed to water. To overcome this limitation, this study has investigated a new strategy to fabricate self-folding GelMA tubes with large diameters at the millimeter level for tissue engineering applications. The new strategy introduced a cross-linking degree gradient across the GelMA plane in addition to its thickness by printing a second layer of strips on the first 4D printed GelMA film. In the aqueous environment, under the current fabrication condition, such bilayer GelMA hydrogels could self-fold into tubes of larger diameters up to 6[Formula: see text]mm. The in vitro release behavior of heparin incorporated into the 4D printed GelMA was also studied. It was shown that heparin release could be controlled by the GelMA concentration and heparin content in 4D printed GelMA. The 4D printed GelMA hydrogels with the improved self-folding ability and controlled release of a drug are promising for targeted tissue engineering applications.
Prehistoric landscapes, humans and ostriches: highlighting geoarchaeological issues in the Tapi Basin of Maharashtra (west-central India) – a multidisciplinary approach
Authors: Sukumaran Prabhin , Li Hong-Chun , Lin Jih-Pai , Chauhan Parth R.
Published: July 2021

The formal beginning of geoarchaeology in India can be traced back to 1863 when the first palaeolith was documented and collected by Robert Bruce Foote in Tamil Nadu and later described in a detailed geological context. Today, various geological tools such as geospatial analytical tools are available to provide extra mileage to geoarchaeological investigations. They supplement field evidence and enable researchers to display, manipulate, and model geological data and the associated archaeological evidence. The present paper attempts to summarize the current status of understanding of the Quaternary geoarchaeology of the Tapi River basin in west-central India. The aspects considered include geomorphology, landform evolution, morphometric parameters, relationships between climate and basin evolution and Palaeolithic and Mesolithic evidence. This present study uses Landsat imagery, locational data, Survey of India topographic sheets and Shuttle Radar Topography Mission data in ArcGIS software. The study is the first comprehensive attempt to summarize the issue of prehistoric human adaptations (dominated mainly by Late Pleistocene evidence) through changing environments, with an assumption that the two occurred in synchronization. Another assumption is that the reported lithic and fossil sites and the surrounding areas have preserved signatures of original landforms and sedimentary contexts. Through these perspectives and visual integration of topography, drainage networks and Landsat image parameters in a Geographic Information System platform, along with other variable field inputs, a testable hypothetical model of the Quaternary evolution of Central Tapi valley is proposed. Additionally, an accelerator mass spectrometry (AMS) date of 47 145 cal BP for a newly discovered ostrich eggshell fragment from Sakegaon near Bhusawal is presented and its palaeoanthropological implications are discussed. Altogether, our observations from the study area, such as an expansion of land use from the Acheulean onwards, signatures of arid phases and the oldest reported ostrich eggshell, warrant further detailed multidisciplinary research. An in-depth understanding of the first-to-last occurrences of ostriches in the region and comprehensive picture of their pan-South Asian distribution in general will help address the issue of prehistoric human adaptations through changing environments.
Responsible AI
Authors: Shneiderman Ben
Published: July 2021

Recommendations for increasing the benefits of artificial intelligence technologies.
What does saying that 'programming is hard' really say, and about whom?
Authors: Becker Brett A.
Published: July 2021

Shifting the focus from the perceived difficulty of learning programming to making programming more universally accessible.
Current Challenges and Recent Developments in Mass Spectrometry–Based Metabolomics
Authors: Collins Stephanie L. , Koo Imhoi , Peters Jeffrey M. , Smith Philip B. , Patterson Andrew D.
Published: July 2021

High-resolution mass spectrometry (MS) has advanced the study of metabolism in living systems by allowing many metabolites to be measured in a single experiment. Although improvements in mass detector sensitivity have facilitated the detection of greater numbers of analytes, compound identification strategies, feature reduction software, and data sharing have not kept up with the influx of MS data. Here, we discuss the ongoing challenges with MS-based metabolomics, including de novo metabolite identification from mass spectra, differentiation of metabolites from environmental contamination, chromatographic separation of isomers, and incomplete MS databases. Because of their popularity and sensitive detection of small molecules, this review focuses on the challenges of liquid chromatography-mass spectrometry–based methods. We then highlight important instrumentational, experimental, and computational tools that have been created to address these challenges and how they have enabled the advancement of metabolomics research.
Biophysical and Quantitative Principles of Centrosome Biogenesis and Structure
Authors: Gomes Pereira Sónia , Dias Louro Marco António , Bettencourt-Dias Mónica
Published: July 2021

The centrosome is a main orchestrator of the animal cellular microtubule cytoskeleton. Dissecting its structure and assembly mechanisms has been a goal of cell biologists for over a century. In the last two decades, a good understanding of the molecular constituents of centrosomes has been achieved. Moreover, recent breakthroughs in electron and light microscopy techniques have enabled the inspection of the centrosome and the mapping of its components with unprecedented detail. However, we now need a profound and dynamic understanding of how these constituents interact in space and time. Here, we review the latest findings on the structural and molecular architecture of the centrosome and how its biogenesis is regulated, highlighting how biophysical techniques and principles as well as quantitative modeling are changing our understanding of this enigmatic cellular organelle.
Evolution and Plasticity of Genome-Wide Meiotic Recombination Rates
Authors: Henderson Ian R. , Bomblies Kirsten
Published: July 2021

Sex, as well as meiotic recombination between homologous chromosomes, is nearly ubiquitous among eukaryotes. In those species that use it, recombination is important for chromosome segregation during gamete production, and thus for fertility. Strikingly, although in most species only one crossover event per chromosome is required to ensure proper segregation, recombination rates vary considerably above this minimum and show variation within and among species. However, whether this variation in recombination is adaptive or neutral and what might shape it remain unclear. Empirical studies and theory support the idea that recombination is generally beneficial but can also have costs. Here, we review variation in genome-wide recombination rates, explore what might cause this, and discuss what is known about its mechanistic basis. We end by discussing the environmental sensitivity of meiosis and recombination rates, how these features may relate to adaptation, and their implications for a broader understanding of recombination rate evolution.
Physiological Consequences of Oceanic Environmental Variation: Life from a Pelagic Organism's Perspective
Authors: Denny Mark W. , Dowd W. Wesley
Published: July 2021

To better understand life in the sea, marine scientists must first quantify how individual organisms experience their environment, and then describe how organismal performance depends on that experience. In this review, we first explore marine environmental variation from the perspective of pelagic organisms, the most abundant life forms in the ocean. Generation time, the ability to move relative to the surrounding water (even slowly), and the presence of environmental gradients at all spatial scales play dominant roles in determining the variation experienced by individuals, but this variation remains difficult to quantify. We then use this insight to critically examine current understanding of the environmental physiology of pelagic marine organisms. Physiologists have begun to grapple with the complexity presented by environmental variation, and promising frameworks exist for predicting and/or interpreting the consequences for physiological performance. However, new technology needs to be developed and much difficult empirical work remains, especially in quantifying response times to environmental variation and the interactions among multiple covarying factors. We call on the field of global-change biology to undertake these important challenges.
Fast and Selective Ionic Transport: From Ion-Conducting Channels to Ion Exchange Membranes for Flow Batteries
Authors: Kreuer Klaus-Dieter , Münchinger Andreas
Published: July 2021

This review discusses selective and fast transport of ionic species (ions and their associates) through systems as diverse as ion-conducting transmembrane proteins and ion exchange membranes (IEMs) in aqueous environments, with special emphasis on the role of electrostatics, specific chemical interactions, and morphology (steric effects). Contrary to the current doctrine, we suggest that properly balanced ion-coordinating interactions are more important than steric effects for selective ion transport in biological systems. Steric effects are more relevant to the selectivity of ionic transport through IEMs. As a general rule, decreased hydration leads to higher selectivity but also to lower transport rate. Near-perfect selectivity is achieved by ion-conducting channels in which unhydrated ions transfer through extremely short hydrophobic passages separating aqueous environments. In IEMs, ionic species practically keep their hydration shell and their transport is sterically constrained by the width of aqueous pathways. We discuss the trade-off between selectivity and transport rates and make suggestions for choosing, optimizing, or developing membranes for technological applications such as vanadium-redox-flow batteries.
Bayesian identification of candidate transcription factors for the regulation of Aqp2 gene expression
Authors: Kikuchi Hiroaki , Jung Hyun Jun , Raghuram Viswanathan , Leo Kirby T. , Park Euijung , Yang Chin-Rang , Chou Chun-Lin , Chen Lihe , Knepper Mark A.
Published: July 2021

Abetted by the advent of systems biology-based (“-omics”) techniques in the 21st century, there has been a massive expansion of published data relevant to virtually every physiological question. The authors have developed a large-scale data integration approach based on the application of Bayes’' theorem. In the current work, they integrated 12 different -omics data sets to identify the transcription factors most likely to mediate vasopressin-dependent regulation of transcription of the aquaporin-2 gene.
[Retracted] A Diagnostic Scoring System for Distinguishing between Tuberculous and Bacterial Meningitis Based on Clinical and Laboratory Findings
Authors: He Hongyan , Zou Yueli , He Junying , Bu Hui , Liu Yaling
Published: July 2021

It is very difficult to diagnose and distinguish tuberculous meningitis, and the current laboratory methods are unsubstantial in developing countries. The study is aimed at creating a scoring system on the basis of basic laboratory and clinical achievements that could be used as diagnostic aid for tuberculous meningitis for Chinese patients. A retrospective study of cases was conducted for comparison between clinical characteristics and laboratory features of 241 patients on admission who conformed to inclusion criteria of tuberculous meningitis (n = 141) or bacterial meningitis (n = 100). Logistic regression was employed to establish a diagnostic formula to distinguish between tuberculous meningitis and bacterial meningitis. The receiver operating characteristic curve analysis was applied to determine the best diagnostic critical point of the diagnostic formula. It was found that five variables (disease course, white blood cell count, serum sodium, total white cell count of cerebrospinal fluid, and neutrophil proportion in cerebrospinal fluid) were independently associated with tuberculous meningitis. The 87% sensitivity and 94% specificity were included in the diagnostic scoring system derived from these variables. Especially in the case of limited microbial resources, doctors can use this diagnostic scoring system to distinguish tuberculous meningitis from bacterial meningitis.
A Design of a Developable Automatic Avoidance System of UAV Based on ADS‐B
Authors: Zhang Xuzheng , Meng Yifei , Mao Chenxiao , Xu Yaohua , Bai Na
Published: July 2021

There are two primary defects in the existing UAV avoidance systems: the system is memoryless; airborne radars are used to detect long‐distance barriers, which are unreliable and expensive. The paper adopts the deep learning algorithm and ADS‐B communication system based on a satellite base station to solve the above problems. It divides the avoidance problem into two parts: short‐distance obstacle avoidance and long‐distance route planning. On the one hand, the system establishes the knowledge base storing the previous avoidance experience and the matching mechanism, realizing the correspondence between input and experience through a deep learning algorithm. They can dramatically improve the reaction speed and safety of UAVs. On the other hand, the system realizes the interconnection between UAV and the satellite base station through the ADS‐B communication system to replace the radars, putting the task of route planning on the satellite platform. Therefore, the satellite can achieve large‐scale and all‐weather detection to improve the overall safety of UAVs depending on its high and long‐range characteristics. The paper also illustrates the design elements of the RF baseband integrated ADS‐B transceiver and the simulation performance of the short‐distance avoidance system in the end, whose results show that the system can be applied to dense obstacle environments and significantly improve the security of UAVs in a complex domain.
ARHGEF3 Associated with Invasion, Metastasis, and Proliferation in Human Osteosarcoma
Authors: Gong Jie , Tang Wei , Lv Bin , Zhang Shushu , Fan Tingjuan , Gao Guangyu , Chen Dong , Liu Yulong
Published: July 2021

Background. Osteosarcoma is a malignant bone tumor composed of mesenchymal cells producing osteoid and immature bone. This study is aimed at developing novel potential prognostic biomarkers and constructing a miRNA‐mRNA network for progression in osteosarcoma. Method. GSE70367 and GSE70414 were obtained in the Gene Expression Omnibus (GEO) database. GEO software and the GEO2R calculation method were used to analyze two gene profiles. The coexpression of differentially expressed miRNAs (DEMs) and genes (DEGs) was identified and searched for in the FunRich database for pathway and ontology analysis. Cytoscape was utilized to construct the mRNA‐miRNA network. Survival analysis of identified miRNAs and mRNAs was performed by utilizing the Kaplan‐Meier Plotter. Besides, expression levels of DEMs and target mRNAs were verified by performing quantitative real‐time PCR (qRT‐PCR) and Western blot (WB). Results. Six differentially expressed microRNAs (DEMs) were identified, and 8 target genes were selected after screening. By using the KM Plotter software, miRNA‐124 and ARHGEF3 were obviously associated with the overall survival of patients with osteosarcoma. Furthermore, ARHGEF3 was found downregulated in osteosarcoma cells by performing qRT‐PCR and WB experiments. Results also showed that downregulated ARHGEF3 may associate with invasion, metastasis, and proliferation. Conclusions. By using microarray and bioinformatics analysis, DEMs were selected, and a complete miRNA‐mRNA network was constructed. ARHGEF3 may act as a therapeutic and prognostic target of osteosarcoma.
A Novel Massive Big Data Analysis of Educational Examination Research Using a Linear Mixed‐Effects Model
Authors: Zhao Jing , Wang Yiwen
Published: July 2021

To further solve the problems of storage bottlenecks and excessive calculation time when calculating estimators under two different formats of massive longitudinal data, an examination data analysis and evaluation method based on an improved linear mixed‐effects model is proposed in this paper. First, a three‐step estimation method is proposed to improve the parameters of the linear‐effects model, avoiding the complicated iterative steps of maximum likelihood estimation. Second, we perform spectral clustering based on test data on the basis of defining data attributes and basic evaluation rules. Finally, based on cloud technology, a cross‐regional, multiuser educational examination big data analysis and evaluation service platform is developed for evaluating the proposed method. Experimental results have shown that the proposed model can not only effectively improve the efficiency of test data acquisition and storage but also reduce the computational burden and the memory usage, solve the problem of insufficient memory, and increase the calculation speed.
EARP: Extended Area Multihop Node Localization Algorithm for Anisotropic Wireless Sensor Networks
Authors: Meng Yinghui , Chen Yuewen , Zhang Qiuwen , Tian Erlin
Published: July 2021

Localization is one of the essential problems in the Internet of Things (IoT) and other wireless sensor applications. Most traditional range-free localization algorithms ignore the anisotropy factors, which are frequently observed in wireless sensor networks (WSNs) and result in low positioning precision. To mitigate the impact of anisotropy on localization, this paper proposes an extended area multihop node localization method. The proposed method classifies and discusses the boundaries of the concave area within the communication range of the node and then uses the maximum split communication distance of the node to identify and mark the boundary of the concave area. When the shortest communication path between the nodes is affected by the concave area, the boundary of the concave area is expanded to obtain the new shortest communication path, and the node distance is obtained by comparing the changes in the communication path. After a large number of simulation tests, it is shown that the calculation accuracy of this scheme is better than that of similar modern mainstream localization algorithms.
Study on the Water Invasion and Its Effect on the Production from Multilayer Unconsolidated Sandstone Gas Reservoirs
Authors: Hu Yong , Li Xizhe , Shen Weijun , Guo Changmin , Jiao Chunyan , Xu Xuan , Jia Yuze
Published: July 2021

Water invasion is a common occurrence in multilayer unconsolidated gas reservoirs, which results in excessive water production and reduces the economic life of gas wells. However, due to multiple layers, active edge water, and strong heterogeneity, the mechanism of water invasion and its effect in the unconsolidated sandstone gas reservoir require understanding in order to improve efficiency and minimize economic cost. In this study, an experimental study on edge water invasion of the multilayer commingled production in unconsolidated sandstone gas reservoirs was conducted to understand the water invasion process along with different permeability layers. The results show that the edge water invasion in the commingling production is mainly affected by two major factors including reservoir permeability and gas production rate, which jointly control the encroaching water advance path and speed. The nonuniform invade of edge water may occur easily and water prefers to invade toward the gas well along with high permeability layers when the commingling production is in the condition of large permeability gradient and high production rate. The bypass flow will occur when there are high permeability channels between the layers, which causes water blocking to low-permeability layers and periphery reservoirs far away from gas wells. The findings of this study can help for a better understanding of water invasion and the effects of reservoir properties so as to optimize extraction conditions and predict gas productivity in unconsolidated sandstone gas reservoirs.
Detection of Dental Caries’ and Dermatoglyphics’ Association with Relative Enamel Thickness Using CBCT Images in Saudi Subpopulation: A Novel Approach
Authors: Dawasaz A. A. , Alshahrani Ibrahim , Yassin Syed M. , Syed Sadatullah , Hameed Mohammad Shahul , Baig Fawaz , Togoo Rafi Ahmad , Master Luqman
Published: July 2021

Background. Dental caries is the localized destruction of dental hard tissues (enamel and dentine). Decayed, Missing, and Filled Teeth (DMFT) index is the most commonly used dental caries index. Thickness of the outermost part of the tooth called the enamel is determined by the rate of deposition of enamel proteins. Relative enamel thickness (RET) gives a measure of enamel thickness with respect to dentine. Dental caries is influenced by a genetically determined factor called dermatoglyphics (DG). As the genes responsible for RET and DG lie on the same chromosome and develop during the same time of intrauterine life, it is biologically plausible to correlate RET and DG. Aims. This study consists of two primary aims: (1) to assess RET using cone beam computed tomography images and correlate it with caries and (2) to correlate RET with DG. Materials and Methods. 148 dental subjects were assessed for DMFT caries score and were categorized as Group 1 with DMFT = 0 and Group 2 with DMFT ≥ 1. Following this, their DG pattern was recorded digitally. The CBCT images of these subjects were assessed for RET, and the data were analyzed statistically. Results. Mean RET in our sample population is 18.45 (SD 3.79) while mean DMFT is 5.34 (SD 5.13). Mean RET in Group 1 subjects was 19.82 (SD 4.05) while that in the Group 2 was 17.68 (SD 3.43). RET and DMFT showed a statistically significant negative correlation (p = 0.007). The “Single Loop” DG characteristic showed a statistically significant difference between males and females (p = 0.031). The “Simple Arch” type of DG was positively correlated with RET. Conclusion. This is the first in vivo study to assess RET using CBCT images and correlate with DMFT and DG. RET is inversely related to DMFT while directly proportional to the “Simple arch” DG pattern. Males and females differed in their “Single Loop” DG characteristic.
Reduced‐Order Modeling of Cavity Flow Oscillations across Multi‐Mach Numbers Using Deep Learning
Authors: Liu Zhe , Ning Fangli , Ding Hui , Zhai Qingbo , Wei Juan
Published: July 2021

The reduced‐order model can accurately and efficiently predict unsteady problems in many aerospace engineering applications. The traditional reduced‐order model based on proper orthogonal decomposition (POD) and Galerkin projection has poor robustness and large error in predicting complex problems. In this paper, a reduced‐order model combining POD and deep learning is proposed to predict cavity flow oscillations under different flow conditions. Firstly, POD modes and corresponding coefficients are obtained by POD. Then, two deep learning frameworks, including multilayer perceptron (MLP) and long short‐term memory (LSTM) neural networks, are used to predict the future POD coefficients, respectively. Finally, the cavity flow oscillations across multi‐Mach numbers are predicted by the POD modes and the future coefficients. The results show that both of these frameworks can accurately predict cavity flow oscillations when the flow conditions change, and the time cost is reduced by order of magnitude. In addition, due to the performance of LSTM is better than that of MLP, its calculation speed is faster.
Identifying Sequence Variants of 18 Hereditary Ovarian Cancer‐Associated Genes in Chinese Epithelial Ovarian Cancer Patients
Authors: Wu Xiao , Chen Zhengzheng , Ren Pingping , Zhao Xuxu , Tang Dongdong , Geng Hao , Xu Xiaofeng , Zhao Weidong
Published: July 2021

Objectives. The causes of ovarian cancer (OC) have been confirmed to be closely related to genetic factors. Identifying sequence variants of hereditary ovarian cancer (HOC) susceptibility genes can increase clinical surveillance, facilitate early detection, and provide personalized treatment for patients. This study is aimed at investigating the variation frequency of HOC susceptibility genes in the Chinese population and providing information for the etiology and genetics of OC. Methods. 118 epithelial OC patients were recruited in this clinical study. Variants of 18‐gene panel were detected in blood samples by next‐generation sequencing (NGS) technology. Results. Overall, 36.44% (43/118) of patients carried at least one pathogenic variant. Among these, BRCA1 pathogenic variants were detected in 31 (26.27%) patients, and 5 (4.24%) patients carried pathogenic variants of BRCA2. Moreover, 27.12% (32/118) of patients carried variants of unknown significance (VUSs). Importantly, we detected eight variants that were not reported previously. Conclusions. Our study enlarged the spectrum of HOC‐associated gene sequence variants in the Chinese population and also proved the necessity of multigene testing in epithelial OC patients. The identification of patients with HOC will allow family members to undergo cascade testing where identification of unaffected carriers can facilitate early detection, risk reduction, or prevention of OC and ultimately improve long‐term outcomes.
The Leading Coefficients for an Affine Weyl Group of Type

G

2

˜

: The Lowest Two-Sided Cell Case
Authors: Guo Pengfei , Zheng Zhu-Jun
Published: July 2021

This study focusses on the leading coefficients

μ

u
,
w

of the Kazhdan–Lusztig polynomials

P

u
,
w

for the lowest cell

c

0

of an affine Weyl group of type

G

2

˜

and gives an estimation

μ

u
,
w

≤
3

for

u
,
w
∈

c

0

.
Effect of Curvature‐Dependent Surface Elasticity on the Flexural Properties of Nanowire
Authors: Wu Mengjun , Yuan Quan , Li Honglin , Wu Bin , Fang Lin , Huang Mengyang
Published: July 2021

Surface elasticity and residual stress strongly influence the flexural properties of nanowire due to the excessively large ratio of surface area to volume. In this work, we adopt linearized surface elasticity theory, which was proposed by Chhapadia et al., to capture the influence of surface curvature on the flexural rigidity of nanowire with rectangular cross section. Additionally, we have tried to study the bending deformation of circular nanowire. All stresses and strains are measured relative to the relaxed state in which the difference in surface residual stress between the upper and lower faces of rectangular nanowire with no external load induces additional bending. The bending curvature of nanowire in the reference and relaxed states is obtained. We find that flexural rigidity is composed of three parts. The first term is defined by the precept of continuum mechanics, and the last two terms are defined by surface elasticity. The normalized curvature increases with the decrease in height, thereby stiffening the nanowire. We also find that not only sizes but also surface curvature induced by surface residual stress influence the bending rigidity of nanowire.
[Retracted] Information Spreading on Memory Activity‐Driven Temporal Networks
Authors: Zhong Linfeng , Bai Yu , Liu Changjiang , Du Juan , Pan Weijun
Published: July 2021

Information spreading dynamics on temporal networks have attracted significant attention in the field of network science. Extensive real‐data analyses revealed that network memory widely exists in the temporal network. This paper proposes a mathematical model to describe the information spreading dynamics with the network memory effect. We develop a Markovian approach to describe the model. Using the Monte Carlo simulation method, we find that network memory may suppress and promote the information spreading dynamics, which depends on the degree heterogeneity and fraction of bigots. The network memory effect suppresses the information spreading for small information transmission probability. The opposite situation happens for large value of information transmission probability. Moreover, network memory effect may benefit the information spreading, which depends on the degree heterogeneity of the activity‐driven network. Our results presented in this paper help us understand the spreading dynamics on temporal networks.
Water Production Problem in Gas Reservoirs: Concepts, Challenges, and Practical Solutions
Authors: Roozshenas Ali Akbar , Hematpur Hamed , Abdollahi Reza , Esfandyari Hamid
Published: July 2021

Gas resources play a key role in nowadays energy supply and provide 24% of the diverse energy portfolio. Water encroachment is one of the main trapping mechanisms in gas reservoirs. It decreases recovery by reduction of reservoir life, limits productivity and efficiency of wells, and elevates safety risks in gas production. The lack of a comprehensive study about water production problems is the primary motivation for this study. Contrary to the serious concern over the standalone investigation of an actual water production case study, less concern is put to deal with the problem comprehensively through an investigation of all potential sources and mechanisms, required methods, and available techniques. This study presents the potential sources of the problem, methods to identify it, and approaches to address it. Firstly, possible sources are described. Secondly, the diagnostic techniques are expressed. Then, practical solutions used in actual cases to overcome problems are elaborated. The solutions include both well- and reservoir-oriented approaches. Finally, all proper strategies are summarized to tackle the water problems in gas fields. The current study comprehensively presents the available methods for water control problems in parallel with conceptual and qualitative comparison. The finding of this study can be very constructive for better understanding of water sources, available diagnostic tools, and solutions for controlling water production in gas reservoirs and, consequently, taking the best decision in real case studies before attempting many water shut-off approaches.