bluuebunny/crossref_metadata_2025 huggingface dataset:
Two new freshwater planarian species (Platyhelminthes: Tricladida: Dugesiidae) partially sympatric in Argentinean Patagonia
Authors: Lenguas Francavilla M. , Negrete L. , Martínez-Aquino A. , Damborenea C. , Brusa F.
Published: March 2021

Girardia Ball, 1974 is the most diverse and widely distributed genus of the family Dugesiidae (Platyhelminthes: Continenticola) in the Neotropical region. Seven out of the 52 species of the genus are known for Argentina. The Somuncurá Plateau is a region in northern Patagonia with several endemic flora and fauna, but little is known about the free-living Platyhelminthes. We describe two new species of Girardia partially inhabiting in sympatry in the Somuncurá Plateau: Girardia somuncura sp. nov. and Girardia tomasi sp. nov. The identification criteria that we followed was an integrative taxonomic approach based on morphological and molecular data. Thus, we used anatomical features focused on the reproductive system, together with a phylogenetic analysis, using a mitochondrial (COI barcode region) genetic marker. This study is the first phylogenetic analysis of the genus Girardia in which we include the southernmost representatives of America here described, thus making it possible to incorporate them in global phylogenies.
Ferromagnetic and spin-glass like transition in the q-neighbor Ising model on random graphs
Authors: Krawiecki A.
Published: March 2021

Theq-neighbor Ising model is investigated on homogeneous random graphs with a fraction of edges associated randomly with antiferromagnetic exchange integrals and the remaining edges with ferromagnetic ones. It is a nonequilibrium model for the opinion formation in which the agents, represented by two-state spins, change their opinions according to a Metropolis-like algorithm taking into account interactions with only a randomly chosen subset of theirqneighbors. Depending on the model parameters in Monte Carlo simulations, phase diagrams are observed with first-order ferromagnetic transition, both first- and second-order ferromagnetic transitions and second-order ferromagnetic and spin-glass-like transitions as the temperature and fraction of antiferromagnetic exchange integrals are varied; in the latter case, the obtained phase diagrams qualitatively resemble those for the dilute spin-glass model. Homogeneous mean-field and pair approximations are extended to take into account the effect of the antiferromagnetic exchange interactions on the ferromagnetic phase transition in the model. For a broad range of parameters, critical temperatures for the first- or second-order ferromagnetic transition predicted by the homogeneous pair approximation show quantitative agreement with those obtained from Monte Carlo simulations; significant differences occur mainly in the vicinity of the tricritical point in which the critical lines for the second-order ferromagnetic and spin-glass-like transitions meet.

Graphic abstract
GLOBAL VALUE CHAINS (GVCS) AND ECONOMIC GROWTH: A NONLINEAR ANALYSIS
Authors: MAO ZHUQING
Published: March 2021

This study examines the relationship between economic growth and participation in global value chains (GVCs) and demonstrates that the U-shaped nonlinear pattern of GVCs could be more effective than the simple linear pattern of GVCs in terms of economic growth in high- and middle-income economies. The U-shaped nonlinear pattern expresses that an economy decreases foreign dominated GVCs (increases domestic value chains) for building local value chains and then raises the GVCs participation to benefit at a better position in GVCs. This paper investigates a panel of 63 advanced and emerging economies and obtained significant evidence by using systemic quantitative analysis. This research suggests that emerging markets should decrease foreign-dominated GVCs (increase high value-added domestic value chain) and then raise the participation of the GVC for economic growth.
An Efficient Approach for Stochastic Vibration Analysis of High-Speed Maglev Vehicle-Guideway System
Authors: Yu Zhiwu , Zhang Peng , Mao Jianfeng , Spanos Pol D. , Chen Y. Frank
Published: March 2021

The high-speed maglev vehicle-guideway coupled system (MVGCS) is a complex system, whose random vibration characteristics have not been well studied due to a limited number of examples. To address this issue, a new efficient approach is proposed for the random vibration analysis of the MVGCS, which combines the probability density evolution method and multi-time step method with multiple random loads considered. The random model established for 10-degree-of-freedom maglev vehicles and guideway is time-dependent, considering two different supporting conditions. The Monte Carlo method is used to assess the accuracy and efficiency of the proposed approximate approach, and the random model is verified through comparison with available results. The stochastic dynamic responses of the vehicles, guideway, and electromagnetic levitation forces, including the mean values and standard deviations, are determined in a case study. The results show that the proposed method is feasible for the dynamic analysis of maglev systems with a reasonably good efficiency in computation. Furthermore, critical parametric analyses involving vehicle speed, irregularity, and cut-off wavelength are performed with the results discussed.
Stochastic Resonance and Self-Induced Stochastic Resonance in Bearing Fault Diagnosis
Authors: Zhang Shuai , Yang Jianhua , Wang Canjun , Liu Houguang , Yang Chen
Published: March 2021

Stochastic resonance (SR) and self-induced stochastic resonance (SISR) are two kinds of important dynamical phenomena in the nonlinear system. SR occurs at the frequency of the characteristic signal. However, SISR can occur at a frequency that is included in the excitation. In present, there are volumes of literatures focusing on extracting the bearing fault characteristics from the vibration signal by SR method. However, the occurrence of SISR may result in the fault features misjudgment in SR processing. Through experimental verifications, we find that the interference of SISR is illustrated strongly in the fault characteristics identification. More importantly, the transition from SISR to SR corresponds to the evolution process of bearing state from normal to damage. Therefore, this evolutionary process can not only judge the state of bearing, but also describe the severity of bearing failure. The result is verified by processing the signals of bearing fault with different severity in noise background. They are the most important findings in this work.
A Layout-Based Classification Method for Visualizing Time-Varying Graphs
Authors: Wang Yunzhe , Baciu George , Li Chenhui
Published: March 2021

Connectivity analysis between the components of large evolving systems can reveal significant patterns of interaction. The systems can be simulated by topological graph structures. However, such analysis becomes challenging on large and complex graphs. Tasks such as comparing, searching, and summarizing structures, are difficult due to the enormous number of calculations required. For time-varying graphs, the temporal dimension even intensifies the difficulty. In this article, we propose to reduce the complexity of analysis by focusing on subgraphs that are induced by closely related entities. To summarize the diverse structures of subgraphs, we build a supervised layout-based classification model. The main premise is that the graph structures can induce a unique appearance of the layout. In contrast to traditional graph theory-based and contemporary neural network-based methods of graph classification, our approach generates low costs and there is no need to learn informative graph representations. Combined with temporally stable visualizations, we can also facilitate the understanding of sub-structures and the tracking of graph evolution. The method is evaluated on two real-world datasets. The results show that our system is highly effective in carrying out visual-based analytics of large graphs.
Popular Matching in Roommates Setting Is NP-hard
Authors: Gupta Sushmita , Misra Pranabendu , Saurabh Saket , Zehavi Meirav
Published: March 2021

An input to the P
OPULAR
M
ATCHING
problem, in the roommates setting (as opposed to the marriage setting), consists of a graph
G
(not necessarily bipartite) where each vertex ranks its neighbors in strict order, known as its preference. In the P
OPULAR
M
ATCHING
problem the objective is to
test
whether there exists a matching
M
* such that there is no matching
M
where more vertices prefer their matched status in
M
(in terms of their preferences) over their matched status in
M
*. In this article, we settle the computational complexity of the P
OPULAR
M
ATCHING
problem in the roommates setting by showing that the problem is NP-complete. Thus, we resolve an open question that has been repeatedly and explicitly asked over the last decade.
Melodie
Authors: Borgos-Rodriguez Katya , Das Maitraye , Piper Anne Marie
Published: March 2021

Despite the promise of the maker movement as empowering individuals and democratizing design, people with disabilities still face many barriers to participation. Recent work has highlighted the inaccessible nature of making and introduced more accessible maker technologies, practices, and workspaces. One less explored area of accessible making involves supporting more traditional forms of craftwork, such as weaving and fiber arts. The present study reports an analysis of existing practices at a weaving studio within a residential community for people with vision impairments and explores the creation of an audio-enhanced loom to support this practice. Our iterative design process began with 60 hours of field observations at the weaving studio, complemented by 15 interviews with residents and instructors at the community. These insights informed the design of Melodie, an interactive floor loom that senses and provides audio feedback during weaving. Our design exploration of Melodie revealed four scenarios of use among this community: promoting learning among novice weavers, raising awareness of system state, enhancing the aesthetics of weaving, and supporting artistic performance. We identify recommendations for designing audio-enhanced technologies that promote accessible crafting and reflect on the role of technology in predominantly manual craftwork.
Laugh your way to persuasive communication
Authors: Yaffe Philip
Published: March 2021

Each "Communication Corner" essay is self-contained; however, they build on each other. For best results, before reading this essay and doing the exercise, go to the first essay "How an Ugly Duckling Became a Swan," then read each succeeding essay.

Have you ever noticed that people who tell jokes well usually give good speeches? This is not a coincidence. Telling jokes and giving speeches have more in common than it might appear. We can benefit from these similarities.
Pennington Corner: Adapting–and Advancing–Through Unforeseen Circumstances
Authors: Jannuzzi Christopher J.
Published: March 2021

Someone much wiser than I once said, “Sometimes, the situation is the boss.” I was reminded of this sobering fact as I was writing my 2020 annual work review and setting my goals for the year to come. Looking back at all that happened in 2020, and trying, as best I could, to peer forward into 2021, the inescapable truth of this axiom hit me head-on. I realized that while we may be in charge, we are by no means in control. Some might say that is a fatalistic, somewhat helpless point of view, but I beg to differ.
Prognostic Nomograms for Nonelderly Adults with Gastric Signet Ring Cell Carcinoma
Authors: Wang Hui , Peng Yao , Huang Qi , Wu Jingjing , Zhang Mingjun
Published: March 2021

Background. Nomograms were established to predict the survival for gastric signet ring cell carcinoma (GSRC) in young and middle‐aged adults. Material and Methods. Eligible patients with GSRC from 2004 to 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database and then divided into a training and a testing cohort in proportion. Independent prognostic factors were picked by univariate and multivariate Cox regression analysis to set up nomograms. The predictive effect and clinical value of nomograms were evaluated by the concordance index (C‐index), calibration curves, and receiver operating characteristic curve (ROC). Results. A total of 1686 GSRC patients were subsumed into this case for analysis, including a training (n = 1180) and a testing cohort (n = 506). Independent risk factors related to overall survival (OS) and cancer‐specific survival (CSS) comprised of race, TNM stage, tumor size, number of positive lymph nodes (PLNE), and chemotherapy. For OS, the C‐indexes of the training and testing cohorts were 0.737 and 0.752, while for CSS, C‐indexes were, respectively, 0.749 and 0.751. These revealed that nomograms accurately predicted OS and CSS. Calibration curves and ROC demonstrated the apparent superiority of nomograms. Conclusion. We built a well‐understood and comprehensive prognostic assessment model for GSRC, which provided an individualized survival prediction in the form of a quantitative score that can be considered for clinical practice.
Research on High-Precision Attitude Control of Joint Actuator of Three-Axis Air-Bearing Test Bed
Authors: Chen Zhiming , Luo Zhouhuai , Wu Yunhua , Xue Wei , Li Wenxing
Published: March 2021

Three-axis air-bearing test bed is important semiphysical simulation equipment for spacecraft, which can simulate spacecraft attitude control, rendezvous, and docking with high confidence. When the three-axis air-bearing table is maneuvering at a large angle, if it is only controlled by the flywheel, it will cause the problems of slow maneuvering speed and high energy consumption, and when the external interference torque becomes large, the control accuracy will decline. A combined actuator including flywheel, air-conditioner thruster, and automatic balancing device is designed, and a hierarchical saturation PD control algorithm is proposed to improve the control accuracy and anti-interference ability of the three-axis air-bearing test bed. Finally, the mathematical simulation of the proposed control algorithm is carried out, and the physical verification is carried out on the three-axis air-bearing test bed. The results show that the control algorithm has higher control accuracy than the traditional control algorithm, and the control accuracy is better than

0.1

∘

and basically meets the attitude control requirements of the ground simulation in-orbit satellite.
Achillea Species as Sources of Active Phytochemicals for Dermatological and Cosmetic Applications
Authors: Strzępek-Gomółka Marcelina , Gaweł-Bęben Katarzyna , Kukula-Koch Wirginia
Published: March 2021

Achillea spp. is well known for its broad range of applications and long history of use in traditional medicine around the world. Health benefits of Achillea extracts result from the multitude of secondary metabolites identified in the plants from this genus that include flavonoids, phenolic acids, terpenes, guaianolides, phytosterols, fatty acids, and organic acids. The properties of several Achillea extracts meet also the expectations of a vividly developing cosmetic market. An increasing number of studies on the dermatological properties of Achillea spp. are observed in the recent years, with Achillea millefolium L. being the most studied and used representative of the genus. There is strong scientific evidence showing that also other yarrow species might be rich sources of effective cosmetic ingredients, with skin calming and rejuvenating properties, wound healing activity, and anti‐inflammatory potential. Several Achillea extracts and isolated compounds were also shown to display significant tyrosinase inhibitory, antioxidant, and antimicrobial properties and thus are interesting candidates for active ingredients of medications and cosmetic products protecting the skin from the harmful impact of environmental stressors. The aim of this review is to collect the current information on the composition and cosmeceutical significance of different Achillea species.
[Retracted] Multiomics Analysis of Genetics and Epigenetics Reveals Pathogenesis and Therapeutic Targets for Atrial Fibrillation
Authors: Liu Li , Huang Jianjun , Wei Baomin , Mo Jianjiao , Wei Qinjiang , Chen Chengcai , Yan Wei , Huang Xiannan , He Fengzhen , Qin Lingling , Huang Hehua , Li Xue , Pan Xingshou
Published: March 2021

Objective. This study is aimed at understanding the molecular mechanisms and exploring potential therapeutic targets for atrial fibrillation (AF) by multiomics analysis. Methods. Transcriptomics and methylation data of AF patients were retrieved from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) and differentially methylated sites between AF and normal samples were screened. Then, highly expressed and hypomethylated and lowly expressed and hypermethylated genes were identified for AF. Weighted gene coexpression network analysis (WGCNA) was presented to construct AF‐related coexpression networks. 52 AF blood samples were used for whole exome sequence. The mutation was visualized by the maftools package in R. Key genes were validated in AF using independent datasets. Results. DEGs were identified between AF and controls, which were enriched in neutrophil activation and regulation of actin cytoskeleton. RHOA, CCR2, CASP8, and SYNPO2L exhibited abnormal expression and methylation, which have been confirmed to be related to AF. PCDHA family genes had high methylation and low expression in AF. We constructed two AF‐related coexpression modules. Single‐nucleotide polymorphism (SNP) was the most common mutation type in AF, especially T > C. MUC4 was the most frequent mutation gene, followed by PHLDA1, AHNAK2, and MAML3. There was no statistical difference in expression of AHNAK2 and MAML3, for AF. PHLDA1 and MUC4 were confirmed to be abnormally expressed in AF. Conclusion. Our findings identified DEGs related to DNA methylation and mutation for AF, which may offer possible therapeutic targets and a new insight into the pathogenesis of AF from a multiomics perspective.
Influence of Design Parameters on Static Bifurcation Behavior of Magnetic Liquid Double Suspension Bearing
Authors: Zhao Jianhua , Wu Xiaochen , Han Fang , Ma Xuchao , Yan Weidong , Liang Yingna , Gao Dianrong , Du Guojun
Published: March 2021

Magnetic liquid double suspension bearing (MLDSB) includes electromagnetic system and hydrostatic system, and the bearing capacity and stiffness can be greatly improved. It is very suitable for the occasions of medium speed, heavy load, and starting frequently. Due to the mutual coupling and interaction between electromagnetic system and hydrostatic system, the probability and degree of static bifurcation are greatly increased and the operation stability is reduced. And flow of bearing cavity, coil current, oil film thickness, and galvanized layer thickness are the key parameters to ensure operation safe and stable, which has an important influence on the static bifurcation behavior. So this article intends to establish the coupling model of MLDSB to reveal the range of parameter combination in the case of static bifurcation. The influences of different parameter groups on the singularity characteristics, phase trajectory,

x
−
t

curves, and suction basin of the single DOF bearing system are analyzed. The result shows that there are nonzero singularities and static bifurcation occurs when

ε

2

>
0

or

δ

2

>
0

. As the flow of bearing cavity, coil current, oil film thickness, and galvanized layer thickness changes in turn, the singularities will convert between stable focus, unstable focus, stable node, and saddle point, and then the stable limit cycle may be generated. The attractiveness of singularity will change greatly with the flow of the bearing cavity and coil current changes slightly in the case of small current or large flow. The minimal change of galvanized layer thickness will lead to the fundamental change of the final stable equilibrium point of the rotor, while the final equilibrium point is slightly affected by the oil film thickness. This study can provide a reference for the supporting stability of MLDSB.
Identification and Assessment of Subway Construction Risk: An Integration of AHP and Experts Grading Method
Authors: Liu Junyan , Du Zijian , Ma Lixing , Liu Chao
Published: March 2021

Qing Dao is one of the earliest cities that included the idea of subway construction into the city’s transportation plan. However, the construction period of a subway project is long, and the uncertainties caused by the geological conditions and surrounding environments are huge, thus a risk assessment method in subway construction is essential. To ensure the tunnel safety, many researchers have raised different methods for risk assessment. The process of risk assessment can be characterized in three steps: (1) data acquisition; (2) complete the uncertainty model; (3) evaluate the possible risk during the construction. This paper introduces a novel risk assessment method that combines the Analytic Hierarchy Process (AHP) and Experts Grading Method (EGM). The advantage of AHP is that it can quantify the qualitative factors, inspect and reduce the subjective influence to a certain extent, and make the evaluation more scientific. As for the EGM, simplicity and directness are the main characteristics. Assisted by this method, proper measures can be taken to eliminate the potential risk. The integrated method was implemented during the construction of Taishan Road Station of Qingdao Subway to evaluate the potential risk. With the help of this integrated method, the general risk sources during the construction period are well marked and the control measures corresponding to the risk sources are provided.
Modeling and Solution of Vehicle Routing Problem with Grey Time Windows and Multiobjective Constraints
Authors: Yuan Xiaojian , Zhang Qishan , Zeng Jiaoyan
Published: March 2021

Purpose. In order to study the impact of grey delivery time uncertainty on customer satisfaction and delivery costs, a vehicle routing problem with grey delivery time windows and multiobjective constraints is defined. Method. The paper first defines the uncertainty of the delivery vehicle’s arrival time to the customer as grey uncertainty and then whitens the grey time windows; at the same time, the customer’s hard time windows is expanded into a soft time windows to measure customer satisfaction when the vehicle arrives. Experiment. In order to verify the validity of the established model, numerical experiments are carried out in two groups based on the Solomon example, and the solution is solved based on the improved quantum evolution algorithm. Analysis. Distribution cost fluctuations and customer satisfaction fluctuations with grey time windows are relatively small; under different satisfaction threshold conditions, the distribution cost is increased gently with the satisfaction threshold. Conclusion. The grey delivery time windows have certain advantages in solving the random travel time vehicle routing problem.
Development of Deep Learning Model for the Recognition of Cracks on Concrete Surfaces
Authors: Le Tien-Thinh , Nguyen Van-Hai , Le Minh Vuong
Published: March 2021

This paper is devoted to the development of a deep learning- (DL-) based model to detect crack fractures on concrete surfaces. The developed model for the classification of images was based on a DL Convolutional Neural Network (CNN). To train and validate the CNN model, a database containing 40,000 images of concrete surfaces (with and without cracks) was collected from the available literature. Several conditions on the concrete surfaces were taken into account such as illumination and surface finish (i.e., exposed, plastering, and paint). Various error measurement criteria such as accuracy, precision, recall, specificity, and F1-score were employed for accessing the quality of the developed model. Results showed that for the training dataset (50% of the database), the precision, recall, specificity, F1-score, and accuracy were 99.5%, 99.8%, 99.5%, 99.7%, and 99.7%, respectively. On the other hand, for the validating dataset, the precision, recall, specificity, F1-score, and accuracy are 96.5%, 98.8%, 96.6%, 97.7%, and 97.7%, respectively. Thus, the developed CNN model may be considered valid because it performs the classification of cracks well using the testing data. It is also confirmed that the developed DL-based model was robust and efficient, as it can take into account different conditions on the concrete surfaces. The CNN model developed in this study was compared with other works in the literature, showing that the CNN model could improve the accuracy of image classification, in comparison with previously published results. Finally, in further work, such model could be combined with Unmanned Aerial Vehicles (UAVs) to increase the productivity of concrete infrastructure inspection.
Experimental Study on Relationship between Free Load Swelling Rate and Water Content of Medium Expansive Soil
Authors: Song Cheng , Yang Ligong , Xia Wei , Ji Wendong , Zhang Yuting
Published: March 2021

Expansive soil has the property of water swelling, which is related not only to the hydrophilic mineral composition of soil particles and the microstructure of soil, but also to the initial moisture content, dry density, and overburden condition of soil. Based on the typical expansive soil in a certain area, the samples were sampled and remodeled at the site. Extensive experimental tests were conducted to investigate the relationship between the hygroscopic expansion rate and the water content of the expansive soil under different initial moisture content, dry density, and free load. The results showed that, under the condition of natural initial water content and dry density, although the hygroscopic expansion rate of the medium expansive soil was nonlinear with the subsequent water content, in the range of large water content (within about 50%), the expansive soil swelled linearly. There was a linear relationship between the rate and the water content. With the increase of the initial water content, the hygroscopic expansion rate and expansion rate of the expansive soil decreased. With the increase of the dry density, the hygroscopic expansion rate and the expansion rate of the expansive soil increased. The water absorption performance did not decrease, and the soil continued to maintain the previous moisture absorption rate and expansion rate after the soil reached saturation, while after the water content reached 1.5∼2.0 times the saturated water content, the soil moisture absorption expansion rate gradually decreased until it finally stabilized. The slope k of the expansion rate increased with the initial dry density and decreased with the initial moisture content. As dry density was increased, the slope k was increased at an increased rate. Moreover, as the initial moisture content was decreased, the slope k was increased at an increased rate.
An Improvement of Stochastic Gradient Descent Approach for Mean-Variance Portfolio Optimization Problem
Authors: Su Stephanie S. W. , Kek Sie Long
Published: March 2021

In this paper, the current variant technique of the stochastic gradient descent (SGD) approach, namely, the adaptive moment estimation (Adam) approach, is improved by adding the standard error in the updating rule. The aim is to fasten the convergence rate of the Adam algorithm. This improvement is termed as Adam with standard error (AdamSE) algorithm. On the other hand, the mean-variance portfolio optimization model is formulated from the historical data of the rate of return of the S&P 500 stock, 10-year Treasury bond, and money market. The application of SGD, Adam, adaptive moment estimation with maximum (AdaMax), Nesterov-accelerated adaptive moment estimation (Nadam), AMSGrad, and AdamSE algorithms to solve the mean-variance portfolio optimization problem is further investigated. During the calculation procedure, the iterative solution converges to the optimal portfolio solution. It is noticed that the AdamSE algorithm has the smallest iteration number. The results show that the rate of convergence of the Adam algorithm is significantly enhanced by using the AdamSE algorithm. In conclusion, the efficiency of the improved Adam algorithm using the standard error has been expressed. Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.
Sequence Analysis of the Putative E3 Region of Bovine Adenovirus Type 2
Authors: Esford L.E. , Haj-Ahmad Y.
Published: March 2021

Adenoviruses are nonenveloped icosahedral-shaped particles. The double-stranded viral DNA genome contains four major early transcription units, designated El (a and b), E2 (a and b), E3 and E4, which are expressed in a regulated manner soon after infection. The gene products of the region E3, shown to be nonessential for viral replication in vitro, are believed to be involved in counteracting host immunosurveillance. Human adenovirus type 5 DNA sequences of transcription units L4 and L5 adjacent to E3 were used to localize E3 within the bovine adenovirus type 2. The DNA sequences between 74.8 and 84.4 mu containing E3 and the fiber gene were determined. The E3 region was found to consist of about 2.3 kb pairs and to encode four proteins longer than 60 amino acids. However, these four open reading frames did not show significant homology to any other known adenovirus DNA or protein sequence.
Analysis of Glycemic Improvement in Hemodialysis Patients Based on Time in Range, Assessed by Flash Glucose Monitoring
Authors: Hu Keyan , Peng Huifang , Ma Yujin , Li Xuefeng , Bai RuiFeng , Wang Junxia , Xu Jiayun , Fu Liujun , Liu Jing , Bai Jinlei , Wu Hongli , Wang Hongyun , Jiang Hongwei
Published: March 2021

Introduction: This study aimed to investigate the application value of “time in ranges (TIRs)” in dialysis patients with diabetes and summarize the experience of optimizing glycemic control by flash glucose monitoring (FGM) system. Methods: In this monocentric 2-week pilot study, FGM was applied for 14 days in 57 type 2 diabetes mellitus medically stable patients under maintenance hemodialysis to determine their glycemic improvement. The diagnostic value of TIR versus HbA1c in detecting glucose fluctuations and levels was evaluated using receiver operating characteristic analysis. Results: Average glucose exhibited stronger association with TIR (r = −0.785, p < 0.001) than HbA1c (r = 0.644, p < 0.001), and mean amplitude of glycemic excursion (MAGE) had the same conclusion (r = −0.568, p < 0.001 for TIR vs. r = 0.423, p = 0.016 for HbA1c). TIR exhibited a higher area under curve than HbA1c in detecting significant derangements in glucose fluctuation, using a 14-day average FGM-derived coefficient of variation >36% as the reference standard (difference between areas: 0.237; 95% CI 0.092–0.383, p = 0.001). We found a significant improvement in TIR (58.38 ± 19.42 vs. 46.45 ± 24.42 mmol/L, p < 0.001) and a significant decline in MAGE (median 5.64 vs.7.42 mmol/L, p < 0.001) compared to the baseline without deterioration of time spent in hypoglycemia. Conclusion: TIR seems to be feasible and clinically useful for AGP analysis in dialysis patients with diabetes, and FGM can be used to improve glycemic control.
Effects of Exercise on Acute Kidney Injury Biomarkers and the Potential Influence of Fluid Intake
Authors: Juett Loris Allan , James Lewis J. , Mears Stephen Andrew
Published: March 2021

Acute kidney injury (AKI) incidence (diagnosed by changes in serum creatinine [Cr]) following prolonged endurance events has been reported to be anywhere from 4 to 85%, and hypohydration may contribute to this. Whilst an increase in serum Cr indicates impaired kidney function, this might be influenced by muscle damage. Therefore, the use of other AKI biomarkers which can detect renal tubular injury may be more appropriate. The long-term consequences of AKI are not well understood, but there are some potential concerns of an increased subsequent risk of chronic kidney disease (CKD). Therefore, this brief review explores the effects of exercise training/competition on novel AKI biomarkers and the potential influence of fluid intake. The increase in novel AKI biomarkers following prolonged endurance events suggests renal tubular injury. This is likely due to the long duration and relatively high exercise intensity, producing increased sympathetic tone, body temperature, hypohydration, and muscle damage. Whilst muscle damage appears to be an important factor in the pathophysiology of exercise-associated AKI, it may require coexisting hypohydration. Fluid intake seems to play a role in exercise-associated AKI, as maintaining euhydration with water ingestion during simulated physical work in the heat appears to attenuate rises in AKI biomarkers. The composition of fluid intake may also be important, as high-fructose drinks have been shown to exacerbate AKI biomarkers. However, it is yet to be seen if these findings are applicable to athletes performing strenuous exercise in a temperate environment. Additionally, further work should examine the effects of repeated bouts of strenuous exercise on novel AKI biomarkers.
Animal Hosts and Experimental Models of SARS-CoV-2 Infection
Authors: Parolin Cristina , Virtuoso Sara , Giovanetti Marta , Angeletti Silvia , Ciccozzi Massimo , Borsetti Alessandra
Published: March 2021

Viruses arise through cross-species transmission and can cause potentially fatal diseases in humans. This is the case of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which recently appeared in Wuhan, China, and rapidly spread worldwide, causing the outbreak of coronavirus disease 2019 (COVID-19) and posing a global health emergency. Sequence analysis and epidemiological investigations suggest that the most likely original source of SARS-CoV-2 is a spillover from an animal reservoir, probably bats, that infected humans either directly or through intermediate animal hosts. The role of animals as reservoirs and natural hosts in SARS-CoV-2 has to be explored, and animal models for COVID-19 are needed as well to be evaluated for countermeasures against SARS-CoV-2 infection. Experimental cells, tissues, and animal models that are currently being used and developed in COVID-19 research will be presented.
Ungewöhnliche Manifestationsform einer allergischen bronchopulmonalen Aspergillose während des COVID-19-Lockdowns. Ein Fallbericht
Authors: Savi Daniela , Valente Giada , Iacovelli Alessandra , Olmati Federica , Bezzi Mario , Palange Paolo
Published: March 2021

Hintergrund: Die Lockdown-Phasen während der anhaltenden Coronavirus-Pandemie mit der Erkrankung COVID-19 haben die Art und Weise verändert, wie Personen und Gemeinschaften leben, arbeiten und interagieren. Fallvorstellung: Der vorliegende Fallbericht beschreibt eine ungewöhnliche, aber bedeutende Manifestationsform der allergischen bronchopulmonalen Aspergillose (ABPA) bei einem zuvor gesunden Mann, der zu Beginn des landesweiten Lockdowns in Italien während der COVID-19-Pandemie beschloss, in den Keller seines Hauses zu ziehen. Da eine hochauflösende Computertomographie (HRCT) des Thorax bei Aufnahme des Patienten diffuse miliäre Noduli zeigte, bestand initial der Verdacht auf eine Miliartuberkulose. Weitergehende Untersuchungen führten allerdings zur Diagnose einer ungewöhnlichen Manifestationsform der ABPA. Schlussfolgerungen: Der vorliegende Fall unterstreicht die Bedeutung einer ungebrochenen Aufmerksamkeit in Bezug auf Aspergillus-assoziierte Erkrankungen des Respirationstrakts während der COVID-19-Pandemie, insbesondere aufgrund dessen, dass Änderungen der Lebensführung im Zusammenhang mit häuslicher Isolation mit dem erhöhten Risiko für eine Exposition gegenüber Schimmelpilzsporen in einigen Wohnräumen verbunden sind.
Changed avian assemblage of Savitribai Phule Pune University campus in last four decades
Authors: Choudaj Kiran , Wankhade Varsha
Published: March 2021

Savitribai Phule Pune University is known for its biodiversity in Pune.  In the present study, we have analyzed changes which have occurred on the campus and surrounding area over the last 40 years.  Of the 90 bird species reported in the campus and Khadki pond in 1976, we failed to notice 34 species in 2018.  A major reason for the decline in bird diversity could be changes in the campus habitat from low scrub jungle, fallow lands and grassland to buildings, roads, and exotic plantations.  Increase in human settlement surrounding the campus may also be a contributing factor.  Replacing exotic plants by indigenous plant species and control of land use can prevent further loss of biodiversity.
Distribution and diversity of climbing species in Papum Pare District of Arunachal Pradesh, India
Authors: Kashung Soyala , Gajurel Padma Raj , Singh Binay
Published: March 2021

An investigation on the taxonomic diversity of climbing plants occurring in Papum Pare District, Arunachal Pradesh, northeastern India was conducted.  A total of 187 species distributed over 55 families and 117 genera were collected and identified from the various forest areas of the district.  Apart from one gymnosperm and five pteridophytes, all species belong to the angiosperm group.  Fabaceae, Cucurbitaceae, Convolvulaceae, Vitaceae, and Apocynaceae were found to be the most dominant.  Piper, Dioscorea, Ipomoea, and Rubus were dominant at the genus level.  The study also revealed that majority of the climbers adopted twining mechanisms (43.85%) to ascend their host.  It  was found that a majority of the species were distributed below 500m with a decrease in diversity with altitudinal increment.  The diversity of species above 1,500m was very limited where only 23 species were reported.  Habitat degradation because of rapid developmental activities with limitation of the supporting tree species was found to be a serious threat to climbing plants.
The Picture of Language in Seeing the Nature of God in Kabbalah and Tantra
Authors: Martin Paul C.
Published: March 2021

In this paper I aim to show how a meaningful correlation can be made between the two mystical traditions of Kabbalah and Tantra by drawing upon ideas from the philosophy of art and aesthetics, especially as it relates to the intersection of images and words. A common leitmotif is that both of these traditions nominate a perception of God which through its manifold expression can be realized as a work of art. It represents a creative response to envisioning or “seeing” the divine realm, one that is renderable by the artist-writer on the material support of the enunciation. As an intentional account of his experiential consciousness of being with God, the artifact is aesthetically designed for the edification of the reader. A comparative connection between the two traditions can be found in this depictive and linguistic endeavor.
Expulsion Legitimacy from the Perspective of International and Emirati Law
Authors: Zakaria Aliaa , Barafi Jamal
Published: March 2021

Every country has the right to restrict the entry, stay, and deportation of aliens in accordance with international law. However, although States have the right to expel aliens, the expulsion mechanism is subject to domestic and international norms. In the United Arab Emirates, legislation has been enacted to deal with the significant number of aliens residing in or visiting the country.

This study clarifies the legality of expulsion and the safeguards stipulated in international and UAE federal law for this procedure, by reviewing the rulings of international and Emirati courts. It concludes that, although international law allows States to regulate foreign affairs in their territory, the mechanism for implementing expulsion and deportation remain subject to legal and judicial guarantees. The paper recommends that deportation decisions be made with caution. It clarifies the weaknesses of the international instruments pertaining to such decisions, and also commends the UAE’s experience in this field.
Discrepant effects of atmospheric adjustments in shaping the spatial pattern of SST anomalies between extreme and moderate El Niños
Authors: Ying Jun , Lian Tao , Huang Ping , Huang Gang , Chen Dake , Chen Shangfeng
Published: March 2021

The surface heat flux anomalies during El Niño events have always been treated as an atmospheric response to sea surface temperature anomalies (SSTAs). However, whether they play roles in the formation of SSTAs remain unclear. In this study, we find that the surface net heat flux anomalies in different El Niño types have different effects on the development of the spatial pattern of SSTAs. By applying the fuzzy clustering method, El Niño events during 1982–2018 are classified into two types: extreme (moderate) El Niños with strong (moderate) positive SSTAs, with the largest SSTAs in the eastern (central) equatorial Pacific. The surface net heat flux anomalies in extreme El Niños generally display a “larger warming gets more damping” zonal paradigm, and essentially do not impact the formation of the spatial pattern of SSTAs. Those in moderate El Niños, however, can impact the formation of the spatial pattern of SSTA, by producing more damping effects in the eastern than in the central equatorial Pacific, thus favoring the largest SSTAs being confined to the central equatorial Pacific. The more damping effects of net heat flux anomalies in the eastern equatorial Pacific in moderate El Niños are contributed by the surface latent heat flux anomalies, which are mainly regulated by the negative relative humidity–SST feedback and the positive wind–evaporation–SST feedback. Therefore, we highlightthat these two atmospheric adjustments should be considered during the development of moderate El Niños in order to obtain a comprehensive understanding of the formation of El Niño diversity.
Tied Infections: How Social Connectedness to Other COVID-19 Patients Influences Illness Severity
Authors: Yan Xuewen , Qu Tianyao , Sperber Nathan , Lu Jinyuan , Fan Mengzhen , Cornwell Benjamin
Published: March 2021

Expanding on recent research on the transmission of COVID-19 via social networks, this article argues that exposure to familial and other close contacts who already have the disease may increase the severity of one’s subsequent illness. We hypothesize that having family members or close contacts who were diagnosed with COVID-19 before one’s own diagnosis exacerbates illness severity due to several potential mechanisms including changes in available social support access, increased stress and strain, and increased viral load due to the nature of one’s exposure to the novel coronavirus. We analyze administrative data of all 417 patients who were diagnosed with COVID-19 in the Chinese city of Shenzhen between January 8 and February 25, 2020. Our analyses show that, when patients had family members or close ties diagnosed with COVID-19, they experienced more severe illness. We also find that patients with infected family members or close contacts did not have significantly extended total illness duration, due to their reduced time to diagnosis. The implications of both findings are discussed.
The Rhetorical Impact of the Scopes Trial’s Interconnected Public Memory Places
Authors: Bloomfield Emma Frances
Published: March 2021

In 1925, the Scopes Trial, one of the first legal battles over teaching evolution in public schools, was held in Dayton, Tennessee. Dayton commemorates the trial with a trinity of sites: The Scopes Trial Museum, the Scopes Trial Trail, and Bryan College. I argue that the trail connects the two other public memory places physically and symbolically, inviting visitors to follow the journey of William Jennings Bryan’s death at the Scopes Trial Museum to a rebirth of creationism at Bryan College. This inquiry attends to the influence of creationist messages at historical landmarks in shaping public understanding of the past. Furthermore, I explore how a museum experience can be felt across multiple memory places to elicit subject positions in visitors.
Incidence of Communicable and Non-communicable Diseases in India: Trends, Distributional Pattern and Determinants
Authors: Yadav Arvind Kumar , Paltasingh Kirtti Ranjan , Jena Pabitra Kumar
Published: March 2021

The recent trends and distributional patterns of communicable diseases (CD) and non-communicable diseases (NCD) in India are analysed in this study. Utilising the unit-level health-specific data from three rounds (1995, 2004 and 2014) of the National Sample Survey Office, it is found that the incidence of CDs is declining while that of NCDs increasing over time. The state-wise pattern shows that both the least-developed states and relatively developed states have a high incidence of diseases. But the incidence of CDs is relatively high in backward states like Rajasthan, Odisha, Assam, Bihar and UP, whereas the prevalence of NCDs is high in advanced states like Kerala, Maharashtra, Tamil Nadu and others. The multinomial logistic regression results also confirm that income, sex and availability of safe drinking water are key determinants of the presence of diseases. Thus, the policy implication of the study calls for the availability and accessibility of adequate medical facilities at affordable costs, development of a strong network of public health facilities in rural India primarily. Bringing the rural as well as urban poor into the fold of health insurance schemes would ensure a huge benefit to the masses who struggle to get the basic treatment. The development of an effective ‘health information system’ can be a better policy instrument in arresting the rising incidence of NCDs.

JEL Classification codes: C12, C51, I15, I18
Deep learning algorithm evaluation of hypertension classification in less photoplethysmography signals conditions
Authors: Yen Chih-Ta , Chang Sheng-Nan , Liao Cheng-Hong
Published: March 2021

This study used photoplethysmography signals to classify hypertensive into no hypertension, prehypertension, stage I hypertension, and stage II hypertension. There are four deep learning models are compared in the study. The difficulties in the study are how to find the optimal parameters such as kernel, kernel size, and layers in less photoplethysmographyt (PPG) training data condition. PPG signals were used to train deep residual network convolutional neural network (ResNetCNN) and bidirectional long short-term memory (BILSTM) to determine the optimal operating parameters when each dataset consisted of 2100 data points. During the experiment, the proportion of training and testing datasets was 8:2. The model demonstrated an optimal classification accuracy of 76% when the testing dataset was used.
The Role of Human Values in Explaining Support for European Union Membership
Authors: Dennison James , Seddig Daniel , Davidov Eldad
Published: March 2021

In recent years, there has been greater scholarly enquiry into explaining variation in support for European Union membership. We theorise that one cause of such variation is likely to be non-political psychological predispositions, such as one’s personal values. We test this proposition by applying Schwartz’s theory of basic human values to predict voting intentions in hypothetical referendums on EU membership. We theorise that these values determine both voting intentions and more proximate explanatory variables of support for EU membership: attitudes to immigration and identifying as European. Using data on 13 countries from the European Social Survey ( N=24,703 citizens) and multigroup structural equation modeling, we demonstrate that this psychological framework effectively predicts voting intentions, notably in terms of the consistent cross-country evidence for indirect effects of values on support for membership via European identity and attitudes to immigration. We then discuss the implications of our findings, including differences in effects between countries.