bluuebunny/crossref_metadata_2025 huggingface dataset:
TI-ION IMPLANTATION EFFECTS ON THE ELECTRICAL RESISTIVITY, HARDNESS AND MICROSTRUCTURE OF BRASS ALLOY
Authors: SHAHNAWAZ MUHAMMAD , MUHAMMAD NAWAZ
Published: May 2022

Extensive progress in brass alloys has been done in surface properties and microstructure. Ti-ion implantation is studied for its effects on electrical resistivity, hardness and microstructure by using scanning electron microscopy, X-ray diffractometer, four-point probe apparatus and Vickers microhardness tester. Ion distribution profile and stopping powers were calculated by Stopping and Range of Ions in Matter (SRIM) code. Nonuniformity in shape, and agglomeration of defects were observed at the surface in SEM micrographs. XRD analysis of (2 0 0) plane for crystallite size, strain, stress and dislocation density is also done. The peak intensity of (2 0 0) is found to be increased by increasing the ion fluence and tensile stresses were also found generated. Increase in the lattice parameter values from 3.681 Å to 3.686 Å appeared as a change in crystallite size, which, in turn, caused an increase in hardness. An increment in electrical resistivity from 7.9[Formula: see text][Formula: see text] to 18[Formula: see text][Formula: see text] (127.85%) is also observed. For a maximum ion fluence of [Formula: see text] ions/cm2, the surface turned out to be amorphous, which helped in making the brass more reliable in its practical usage.
Global solutions for semilinear rough partial differential equations
Authors: Hesse Robert , Neamţu Alexandra
Published: May 2022

We construct global-in-time solutions for semilinear parabolic rough partial differential equations. We work on a scale of Banach spaces tailored to the controlled rough path approach and derive suitable a priori estimates of the solution which do not contain quadratic terms.
An Experimental Study of Characteristics of Solitary-Wave-Induced Scour Around a Pile Breakwater with a Discussion on Effects of the Distance between Piles
Authors: Xu Conghao , Huang Zhenhua
Published: May 2022

Understanding tsunami-induced scour at a pile breakwater is important for the foundation safety of this type of coastal defense structures. A series of wave-flume tests were performed for [Formula: see text], with [Formula: see text] being the gap size and [Formula: see text] the pile diameter, to study the characteristics of the solitary-wave-induced local scour around a pile breakwater, including the scour-hole depth, scour-hole length, deposition sandbar height and the scoured volume. It was found that the jet flow through the gaps between piles caused the local scour around individual piles. A more or less two-dimensional deposition sandbar was found on the down-wave side of the pile breakwater in the later stage of the scour process. A new empirical equation was introduced to approximate the evolution of the depth of the scour hole induced by a series of solitary waves. The equation was verified by existing data reported in the literature for [Formula: see text] and the new data reported in this study. Effects of the distance between piles on the characteristics of the local scour were discussed by comparing the results for [Formula: see text] and 0.39. The comparison showed that the scour-hole depth and height of the sandbar for [Formula: see text] were all noticeably larger than the corresponding values for [Formula: see text].
Optimal vaccination strategy for a mean-field stochastic susceptible-infected-vaccinated system
Authors: Wang Zong , Zhang Qimin
Published: May 2022

The parameters of biological system may change under the influence of different states or state processes. The change of parameters can also affect the dynamic behaviors of epidemic disease. This paper presents a mean field stochastic susceptible-infected-vaccinated (SIV) epidemic model which parameters depend on the state process. The sufficient and necessary conditions of optimal control of the novel epidemic model are obtained by maximum principle. Finally, we perform representative numerical simulations to illustrate the theoretical results and further discuss the feasibility based on the hand, foot and mouth disease (HFMD) data in China.
Large deviations for spectral measures of some spiked matrices
Authors: Noiry Nathan , Rouault Alain
Published: May 2022

We prove large deviations principles for spectral measures of perturbed (or spiked) matrix models in the direction of an eigenvector of the perturbation. In each model under study, we provide two approaches, one of which relying on large deviations principle of unperturbed models derived in the previous work “Sum rules via large deviations” (Gamboa et al. [Sum rules via large deviations, J. Funct. Anal. 270(2) (2016) 509–559]).
Analysis of Energy Conservation Big Data of Embedded Large Public Buildings and Construction of the Information Model by 5G
Authors: Zhao Xing , Yan Zengfeng
Published: May 2022

The problem of energy shortage has become one of the most serious problems in the process of economic development. The research is aimed at studying the energy conservation data and information model of large public buildings. Based on the theories of 5G technology, embedded system, and energy conservation of large public buildings, firstly, 5G technology is used to collect research data. Secondly, some large public buildings in Northwest China are analyzed for energy conservation by using ZigBee and other related technologies and algorithms. Finally, the office buildings in large public buildings are used as samples for the construction of the information model to be analyzed. The research results denote that large public buildings are mainly concentrated in hospitals, hotels, shopping malls, and so on. The south-facing window to wall ratio is higher than that of the north-facing window to wall ratio, and the east-west-facing window to wall ratio has the lowest probability of appearing. In addition, the thermal conductivity of the roof of most of the large buildings is less than 1.0 W, while the thermal conductivity of the outer wall of the roof is distributed around 2.5 W, and the thermal conductivity of the outer wall is around 0.6 W. Finally, commercial buildings have higher heating and cooling loads than residential buildings. In the construction of the information model for energy conservation of large public buildings, the neural networks (NNs) and clustering analysis algorithm are introduced into the prediction model of energy consumption data, and it is found that compared with the actual observed value, the overall trend shows consistency, both of which are periodic fluctuations. However, there are still some errors in some data. Therefore, an analysis of energy conservation data of embedded large public buildings and the construction of information models based on 5G has important guiding significance for the construction industry to improve business performance and market competitiveness.
A UAV Pursuit-Evasion Strategy Based on DDPG and Imitation Learning
Authors: Fu Xiaowei , Zhu Jindong , Wei Zhaoying , Wang Hui , Li Sili
Published: May 2022

The UAV pursuit-evasion strategy based on Deep Deterministic Policy Gradient (DDPG) algorithm is a current research hotspot. However, this algorithm has the defect of low efficiency in sample exploration. To solve this problem, this paper uses the imitation learning (IL) to improve the DDPG exploration strategy. A kind of quasiproportional guidance control law is designed to generate effective learning samples, which are used as the data of the initial experience pool of DDPG algorithm. The UAV pursuit-evasion strategy based on DDPG and imitation learning (IL-DDPG) is proposed, and the algorithm obtains the data from the experience pool for experience playback learning, which improves the exploration efficiency of the algorithm in the initial stage of training and avoids the problem of too many useless exploration in the training process. The simulation results show that the trained pursuit-UAV can flexibly adjust the flight speed and flight attitude to pursuit the evasion-UAV quickly. It also verifies that the improved DDPG algorithm is more effective than the basic DDPG algorithm to improve the training efficiency.
Legal Model Construction Approach of Big Data Transaction Management in the Digital Information Perspective
Authors: Yuan Quan
Published: May 2022

This paper constructs and applies the legal model of transaction management in the digital information perspective based on the approach of big data. To solve the problem, it is necessary to integrate various legal tools, construct an idealized legal model of big data transaction management, conduct interprofessional and interdisciplinary research on the big data transaction management problems that are difficult to be regulated by the existing legal norms, and selectively design and arrange the corresponding system, to provide the digital regulatory tools for the operation of the digital economy and promote the scientific and standardized development of the digital economy. Based on the decentralized blockchain platform, sealed bidding is used to achieve information isolation among nonconspiratorial data buyers, and through the big data auction algorithm, the purpose of the conspirators cannot be achieved and anticomplicity is realized. The model is based on smart contracts and combined with auction theory to achieve anticollision in the process of big data auctions. Based on the model, we construct an anticomplicity big data auction mechanism and dissect the big data auction algorithm. The correctness of the model and algorithm is demonstrated through simulation. After the data is hosted, the data will be completely owned by the big data trading center. In the data transaction process, the big data transaction center provides data resource information to data buyers, so that data buyers can select the required data. Second is the construction of a multilevel regulatory system in the administrative supervision of the construction of the central national security leading institutions led by the interregional collaborative regulatory system and in the industry self-regulatory supervision of the implementation of the data trading platform data trading supervision obligations. The balance between the development of the data trading industry and data trading security is comprehensively maintained from multiple perspectives of legislation and law enforcement.
The Application of Intelligent Speech Analysis Technology in the Spoken English Language Learning Model
Authors: Zhu Min
Published: May 2022

In order to improve the effect of spoken English processing, it is necessary to improve the spoken English processing technology from the perspective of the characteristics of spoken English, combined with intelligent algorithms. This paper combines the intelligent speech analysis technology to improve the spoken English recognition technology and combines the actual and needs of English learning to improve the system algorithm. Moreover, this paper combines the intelligent speech analysis to construct the intelligent spoken English learning model structure and combines the statistical method and the intelligent evaluation method to analyze the model effect. After obtaining the system function structure, this paper designs experiments to verify the effect of the model proposed in this paper. From the experimental analysis results, it can be seen that the intelligent English speech analysis model proposed in this paper can play an important role in the learning of spoken English.
Impacts of Chemical Reaction and Suction/Injection on the Mixed Convective Williamson Fluid past a Penetrable Porous Wedge
Authors: Hussain Majid , Ali Akhtar , Inc Mustafa , Sene Ndolane , Hussan Muhammad
Published: May 2022

The impacts of chemical reaction and suction/injection in Williamson fluid flow along a porous stretching wedge are discussed in the present paper. Recently, a lot of numerical and theoretical studies are accessible for illustrating the chemical reaction impact on non‐Newtonian fluids with different geometries and conditions. Considering this fact, we inspect the heat transport behavior of Williamson fluid due to a stretching porous wedge with suction or injection. The governing PDEs are converted into ODEs with reliable similarity transformation. These ODEs are solved numerically by BVP4C based in MATLAB system, and the assessment of outcomes for the validation tenacity is presented in Table. Combined plots are sketched to discern the impact of dominant sundry parameters on the flow fields. Along with them, the Sherwood number, skin friction factor, and the rate of heat transfer are also bestowed in graphs.
Applicability of 14 Formulas for Estimating Glomerular Filtration Rate in the Evaluation of Renal Function before and after Nephron‐Sparing Surgery in Patients with Renal Tumors
Authors: Li Qiuyan , Yang ZeSong , Zheng Shiwen , Wu Yangbiao , Cai Wanghai , Hu Minxiong , Zhu Qingguo , Ye Liefu
Published: May 2022

To compare the applicability of 14 equations of estimating glomerular filtration rate (eGFR) before and after nephron‐sparing surgery (NSS) for renal function assessment of patients with renal tumors. Preoperative and postoperative GFR is measured by emission computed tomography (ECT) with 99mTc‐DTPA as an imaging agent as reference GFR (rGFR) to compare with all formulas. Spearman correlation analysis and Bland–Altman agreement analysis were used to evaluate the correlation between rGFR and eGFR1 to 14 before and after surgery. A total of 50 cases including 22 males and 28 females were included. The results of preoperative eGFR1–14 correlated with rGFR (P < 0.05). The calculation results of all estimation formulas have a significant correlation with preoperative GFR. Preoperative MDRD‐I, CKD‐EPI SCysC, and FAS Scr-SCysC have good consistency. The CG formula has the highest precision and FAS Scr-SCysC has the highest accuracy. A total of 30 patients followed up after surgery, and postoperative rGFR correlated with CG, CKD‐EPI, FAS, and BIS formulas (P < 0.05). But postoperative rGFR has no significant correlation with MDRD and Schwartz (P > 0.05). Postoperative CKD‐EPI Scr-SCysC has best consistency, and FAS Scr-SCysC has the highest accuracy and precision. Our data suggest that eGFR equations evaluated by both serum creatinine (Scr) and cystatin C (SCysC) is not necessarily better than those evaluated by one of them alone. Among all enrolled equations, FAS Scr-SCysC is the best one to evaluate postoperative GFR in patients with renal tumors.
Machine Learning-Based Sine-Cosine Algorithm for Wastewater Quality Assessment Using Activated Carbon
Authors: Alsolai Hadeel , Asiri Mashael M. , Alabdan Rana , Al-Hagery Mohammed Abdullah , Hilal Anwer Mustafa , Rizwanullah Mohammed , Motwakel Abdelwahed , Yaseen Ishfaq
Published: May 2022

Activated carbon is one of the most highly proven adsorbents for organic chemicals from wastewater. It acts as a filter and adsorbs various chemicals from the wastewater. It has large pore size and strong adsorptive capacity. The quality of wastewater is generally determined by chemical oxygen demand (COD), biochemical oxygen demand (BOD5), total suspended solids (TSSs), total phosphorus (TP), and total nitrogen (TN). Wastewater contaminant measurement is significant for saving aquatic life and reusing treated water. Adsorption of contaminants that contribute for wastewater quality indicators uses machine learning algorithm for prediction. Many research works have been done, and the issues are inefficiency and time consuming in the adsorption of contaminants by activated carbon in wastewater management. To overcome these issues, this paper introduces hybrid technique of Voting-Based Extreme Learning Machine with sine cosine algorithm (VELM-SCA). The accuracy of VELM-SCA algorithm in classification of water quality status produced improved accuracy is 0.97.
Rapidly Progressive Bladder Cancer Diagnosed because of Spontaneous Bladder Rupture
Authors: Hagimoto Hiroki , Sano Takeshi , Kashima Soki , Yoshino Takayuki , Goto Takayuki , Sawada Atsuro , Akamatsu Shusuke , Yamasaki Toshinari , Fujimoto Masakazu , Kajita Yoichiro , Kobayashi Takashi , Ogawa Osamu
Published: May 2022

Background. Spontaneous bladder rupture (SBR) is very rare and can be associated with advanced bladder cancer. Because of its rarity, the optimal management of bladder cancer with SBR has not been established. Herein, we report a case of SBR due to locally advanced bladder cancer, which rapidly invaded the ileum and caused peritoneal dissemination. Case Presentation. An 86-year-old man presented with sudden-onset lower abdominal pain and distension. The patient was diagnosed with bladder perforation and bladder tumor on contrast-enhanced computed tomography (CECT). Transurethral resection of the bladder tumor revealed an invasive urothelial carcinoma with squamous differentiation. Although radical cystectomy with lymph node dissection was planned, preoperative CECT and magnetic resonance imaging revealed enlargement of the bilateral iliac regional lymph nodes, multiple peritoneal nodules, and invasion of the bladder tumor to the ileocecum. Therefore, cystectomy and resection of ileocecum with palliative intent and bilateral cutaneous ureterostomy were performed. However, the patient’s general condition rapidly worsened after surgery, and he died 74 days after the initial diagnosis. Conclusions. We encountered a case of SBR accompanied by bladder cancer with extremely rapid progression, which suggested the importance of short-interval repeat imaging examinations. Emergency surgery should be considered when bladder cancer is suspected in patients with SBR so as not to miss the window period of a possible cure.
First General Zagreb Co‐Index of Graphs under Operations
Authors: Javaid Muhammad , Ibraheem Muhammad , Bonyah Ebenezer , Ahmad Uzma , Wang Shaohui
Published: May 2022

Topological indices are graph‐theoretic parameters which are widely used in the subject of chemistry and computer science to predict the various chemical and structural properties of the graphs respectively. Let G be a graph; then, by performing subdivision‐related operations S, Q, R, and T on G, the four new graphs S(G) (subdivision graph), Q(G) (edge‐semitotal), R(G) (vertex‐semitotal), and T(G) (total graph) are obtained, respectively. Furthermore, for two simple connected graphs G and H, we define F‐sum graphs (denoted by G+FH) which are obtained by Cartesian product of F(G) and H, where F ∈ {S, R, Q, T}. In this study, we determine first general Zagreb co‐index of graphs under operations in the form of Zagreb indices and co‐indices of their basic graphs.
A Dynamic CGE Model for Consumer Trust Mechanism within an E-Commerce Market
Authors: Wang Chongye
Published: May 2022

This study aims to use the computable general equilibrium (CGE) model to evaluate the economic consequences of foreign direct online purchases on the chain economy and to forecast the future development of e-commerce. We expected that international online direct shopping reduced transaction costs in two ways: duty equivalent were reduced, and direct import prices were reduced. The development of e-commerce markets for products, services, and information is important for consumer trust. Customers are becoming more interested in these industries because companies increased in number and users. Rules and regulations that are customized to the demands of both businesses and consumers are important for the industries’ continued growth. This study proposes a CGE model and analyzed the dynamic trust mechanisms of individual customers in the financial inclusion market to achieve the entire equilibrium state of the rural financial sector and maintain the stable development of the financial inclusion consumer market. Through the initiation of the era of big data, e-commerce has become a key part of the development of the new economy. In order to ensure the reliability, security, and service quality of e-commerce transactions in different transaction environments, how to accurately and quantitatively express and predict the trust relationship enhance the trust of both parties. This paper uses artificial intelligence to check relevant materials, then passes the problem to experts for processing, analyzes the security issues in e-commerce, summarizes the e-commerce security system framework centered on trust management, and describes the contextual trust management model. Experimental outcomes show that the proposed technique can accurately assess the trust of individual consumers and plan the e-commerce market based on the trust mechanism.
Optimal HARA Investments with Terminal VaR Constraints
Authors: Escobar-Anel Marcos , Keller Maximilian , Zagst Rudi
Published: May 2022

This paper studies the impact of Value at Risk (VaR) constraints on investors with hyperbolic absolute risk aversion (HARA) risk preferences. We derive closed-form representations for the “triplet”: optimal investment, terminal wealth, and value function, via extending the Bellman-based methodology from constant relative risk aversion (CRRA) utilities to HARA utilities. In the numerical part, we compare our solution (HARA-VaR) to three critical embedded cases, namely, CRRA, CRRA-VaR, and HARA, assessing the influence of key parameters like the VaR probability and floor on the optimal wealth distribution and allocations. The comparison highlights a stronger impact of VaR on a CRRA-VaR investor compared to a HARA-VaR (HV). This is in terms of not only lower Sharpe ratios but also higher tail risk and lower returns on wealth. The HV analysis demonstrates that combining both, capital guarantee and VaR, may lead to a correction of the partially adverse effects of the VaR constraint on the risk appetite. Moreover, the HV portfolio strategy also does not show the high kurtosis observed for the PV strategy. A wealth-equivalent loss (WEL) analysis is also implemented demonstrating that, for a HV investor, losses would be more serious if adopting a CRRA-VaR strategy as compared to a HARA strategy.
Network Rumor Detection Method Using Deep Learning in Big Data Environment
Authors: Lei Xi
Published: May 2022

Aiming to achieve efficient and accurate network rumor detection, this paper proposes a rumor detection method based on deep learning network. First, this method uses API interface and web crawler to construct a large data set of information samples on the microblog platform. Then, this method processes and analyzes the large data set through multiple embedded layers to provide a complete and reliable analysis data set for the detection model. The rumor detection model is composed of bidirectional long- and short-term memory (Bi-LSTM) network and convolutional neural network (CNN), which can realize deep and efficient feature extraction for the analysis data set and ensure the optimal performance of rumor detection method. The simulation results show that the precision and accuracy of the proposed method are 0.9771 and 0.9726, respectively, which are better than the comparison algorithms. The proposed method has effective network rumor screening and identification performance.
Berberine Alleviates Gastroesophageal Reflux-Induced Airway Hyperresponsiveness in a Transient Receptor Potential A1-Dependent Manner
Authors: Zou Bo , Cao Chaofan , Fu Yue , Pan Dianzhu , Wang Wei , Kong Lingfei
Published: May 2022

Background. To investigate the beneficial effect of berberine on gastroesophageal reflux-induced airway hyperresponsiveness (GERAHR) and explore the underlying mechanism. Methods. Coword cluster analysis and strategic coordinates were used to identify hotspots for GERAHR research, and an online tool (STRING, https://string-db.org/) was used to predict the potential relationships between proteins. Guinea pigs with chemically induced GERAHR received PBS or different berberine-based treatments to evaluate the therapeutic effect of berberine and characterize the underlying mechanism. Airway responsiveness was assessed using a plethysmography system, and protein expression was evaluated by western blotting, immunohistochemical staining, and quantitative PCR analysis. Results. Bioinformatics analyses revealed that TRP channels are hotspots of GERAHR research, and TRPA1 is related to the proinflammatory neuropeptide substance P (SP). Berberine, especially at the middle dose tested (MB, 150 mg/kg), significantly improved lung function, suppressed inflammatory cell infiltration, and protected inflammation-driven tissue damage in the lung, trachea, esophagus, and nerve tissues in GERAHR guinea pigs. MB reduced the expression of TRPA1, SP, and tumor necrosis factor-alpha (TNF-α) in evaluated organs and tissues. Meanwhile, the MB-mediated protective effects were attenuated by simultaneous TRPA1 activation. Conclusions. Mechanistically, berberine was found to suppress GERAHR-induced upregulation of TRPA1, SP, and TNF-α in many tissues. Our study has highlighted the potential therapeutic value of berberine for the treatment of GERAHR.
Pullout Characteristics and Damage Softening Model of the Geogrid-Soil Interface
Authors: Liang Xiaoyong , Jin Jing , Yang Guangqing , Wang Xizhao , Zhou Yitao
Published: May 2022

The mechanical properties of geogrid-soil interface is very important in design and stability analysis of reinforced soil structure. In order to study the complicated mechanism of geogrid-soil interface, a series of pullout tests of HDPE uniaxial tensile geogrids with the different transverse ribs spacing is used to investigate the interaction characteristics in the laboratory. The test results show that pullout force and displacement curves are characterized as strain softening; compared with the no-reinforced case, the case reinforced with geogrid has larger cohesion and lower friction angles. The ductility of soil is enhanced due to geogrid reinforcement. Based on the basic control equations of the interface and damage theory, trilinear shear stress-displacement damage softening model is proposed to describe the strain-softening characteristics of geogrid-soil interface. Analytical solutions of interface tension, shear stress, and displacement at different stages are derived considering strain softening based on damage, and the development of shear stress and progressive failure mode of the geogrid-soil interface at different pullout stages is revealed. Furthermore, the proposed model is verified by experimental results.
Administrative Punishment Supervision System Based on Internet of Things Driven by Big Data
Authors: Wang Junliang
Published: May 2022

In order to study the administrative punishment supervision system based on the Internet of things driven by big data, firstly, based on the full collection of materials, this paper makes a detailed induction and analysis from the perspective of demonstration, and discusses the problems existing in the practice of administrative punishment. In terms of theory, first determine the concept of administrative punishment from the overall direction, and then locate it to administrative punishment. Then, it analyzes the specific contents of the construction of the supervision system based on the Internet of things driven by big data and the key technologies of the cloud platform system of the Internet of things. Finally, focusing on the judgment cases published by the municipal and county courts in a province from 2014 to 2017, the analysis results are displayed, discussed, and summarized. The results show that the construction of intelligent supervision system is realized, the intelligent response to supervision needs is completed, and the scientific and effective supervision is promoted.
Experimental Study on Dynamic Characteristics of Annular Coal Mine Sandstone after Different Temperatures
Authors: Ping Qi , Wu Yulin , Gao Qi , Wang Shuo , Shen Kaifan , Wang Chen , Li Xiangyang
Published: May 2022

The rock mass is the main carrier of underground engineering. Many rock engineering involves rock mass excavation, and the temperature of deep rock mass increases with the depth rising. The study on the dynamic mechanical properties of annular coal mine sandstone under different temperatures has important guiding significance for mine excavation and rock engineering design and construction. To research the effect of high temperatures on the physical and dynamic mechanical characteristics of annular coal mine sandstone specimens, the physical parameters of the samples after the heating temperature from 25°C to 500°C were tested, and the dynamic splitting tests under the same loading condition were conducted by using SHPB test equipment. The findings indicate that with the temperature rising, the volume of samples increases, the mass and density decrease, and the change rate of the physical parameters of the annular sample is a little greater than that of the intact sample; as the temperature goes up, the dynamic tensile strength increases first and then decreases, there is a quadratic polynomial relationship with temperature; both the dynamic strain and the average strain rate decrease first and then increase as the temperature grows, showing a quadratic polynomial relationship with temperature; the damage degree of the annular and intact samples become worse as the temperature improved, and the fragments of specimen increase obviously after 200°C.
Evaluation of Children’s Physical Fitness Index and Prediction of Health Risk Trend Based on BP Neural Network Algorithm
Authors: Wu Renle , Zhang Siyu
Published: May 2022

On the basis of literature review and expert interview, this study constructs the indexes of health fitness evaluation, obtains the difference of the indexes before and after the 15-week health fitness intervention, and establishes the health risk trend predictive equation based on BP neural network algorithm. The results of the study are as follows: after 15 weeks of health fitness intervention, there were significant differences in body fat rate, waist circumference, and waist-to-hip ratio (

P
<
0.01

). There were significant differences in maximal oxygen uptake, 12-minute running distance, one-minute sit-ups, push-ups, standing long jump, pull-ups, and sitting forward flexion (

P
<
0.05

). Body fat percentage, maximal oxygen uptake, forward bending in sitting position, and standing long jump can be used to evaluate the level of children’s physical fitness. In conclusion, after 15 weeks of health and fitness intervention course, the children’s health and fitness were improved. Health and Physical Fitness Intervention Curriculum can be promoted in schools so that more children can benefit from it. And the health risk trend prediction model based on BP neural network algorithm has a certain validity.
Macular Morphologic and Microvascular Analysis in Pseudophakic Children with Previous Pediatric Cataract Using Optical Coherence Tomography Angiography
Authors: Zhang Yunjie , Li Zhangliang , Liu Songjia , Fu Yana , Chen Ding , Meng Ziqi , Zhu Zehui , Zou Rui , Zhao Yun-e
Published: May 2022

Introduction: The macular morphologic and microvascular changes in children with pseudophakia after pediatric cataract surgery remain unknown. The aim of this study was to analyze macular morphologic and microvascular remodeling in children with pseudophakia after pediatric cataract surgery using optical coherence tomography angiography (OCTA). Methods: Consecutive cases between December 1, 2018, and November 31, 2020 were recruited. Sixty-one participants (31 pseudophakic children and 30 healthy controls) met the inclusion criteria and were included for final analysis. OCTA was used to measure macular vascular density, the foveal avascular zone (FAZ), and macular thickness. The parameters were compared between pseudophakic and healthy eyes using binary logistic regression, with adjustment for the effect of refractive error, age, and axial length. Results: Compared with normal eyes, a significantly reduced area of the FAZ (p = 0.042), increased superficial foveal vascular density (p = 0.033), and increased inner and outer foveal thickness (p = 0.034 and 0.029, respectively) were noted in pseudophakic eyes. The deep parafoveal vascular density was generally lower in eyes with cataracts (p ≤ 0.044). The inner foveal thickness was positively correlated with the superficial foveal vascular density (r = 0.889, p < 0.001) and negatively correlated with the area of the FAZ (r = −0.903, p < 0.001). The outer foveal thickness was positively correlated with the deep foveal vascular density (r = 0.399, p = 0.002). Conclusions: Morphological and microvascular remodeling in children with previous pediatric cataract indicates foveal underdevelopment. The underlying mechanism requires further investigation.
Comparison of Tumor Size and Gene Expression at Presentation in Uveal Melanoma Patients before and during the COVID-19 Pandemic
Authors: Hasegawa Naomi , Rusakevich Alexander , Bernicker Eric , Teh Bin S. , Schefler Amy
Published: May 2022

Introduction: The aim of this study was to compare the clinical and gene expression variables of uveal melanoma patients presenting before and after the start of the COVID-19 pandemic as surrogate markers in order to assess the pandemic’s potential impact on care. Methods: We conducted a retrospective chart review of uveal melanoma patients at Retina Consultants of Texas and assessed tumor size, staging, and gene expression data during two time periods: May 2019 to February 2020 (Group 1: Before the COVID-19 pandemic declaration by the WHO in March 2020) and May 2020 to March 2021 (Group 2: After the start of the COVID-19 pandemic). Results: A total of 80 patients with uveal melanoma were studied (Group 1: 40 [50%] and Group 2: 40 [50%]). There was no statistically significant difference in the tumor thickness (p = 0.768), largest base dimension (p = 0.758), Collaborative Ocular Melanoma Study size class (p = 0.762), and American Joint Committee on Cancer stages (p = 0.872) between the two groups. Additionally, there was no difference in the tumors’ gene expression data including gene expression profile class (p = 0.587) and PRAME expressivity (p = 0.861) between the two groups. Discussion/Conclusion: The COVID-19 pandemic had no effect on the presentation of uveal melanoma patients across all tumor characteristics including size, staging, and gene expression data, suggesting there was not a significant diagnostic delay in care for uveal melanoma patients at our center due to the pandemic.
Os tempos da Ladeira da Preguiça: etnografia de longa duração de uma micro localidade do centro histórico de Salvador
Authors: Uriarte Urpi Montoya
Published: May 2022

Este artigo descreve e reflete sobre dois tempos que coexistem no espaço atual da Preguiça, uma das várias micro áreas que compõem a poligonal do Centro Histórico de Salvador (CHS). Trata-se de um velho “tempo do fechamento”, fruto de mudanças estruturais na cidade de Salvador, que se desenvolveram a partir da segunda metade do século XIX, e de um novo “tempo de (re)abertura”, forjado muito recentemente pelo esforço de alguns e algumas jovens moradores e moradoras da Preguiça, que criaram e mantêm o Centro Cultural Que Ladeira É Essa? Esses tempos foram captados e analisados mediante o método etnográfico (num trabalho de campo que vem sendo efetuado desde inícios de 2019) e o método histórico (com pesquisa em fontes históricas e na historiografia, realizada em 2018). Ambos os métodos nos permitiram relacionar os séculos XIX, XX e XXI e encontrar uma impressionante continuidade entre o que a Preguiça foi (abertura) e o que seus moradores atuais esperam que ela seja no futuro (reabertura), rejeitando abertamente o que se fez dela no século XX, até o presente (fechamento).
Preparing for a Second Attack: A Lesion Simulation Study on Network Resilience After Stroke
Authors: van Assche Mitsouko , Klug Julian , Dirren Elisabeth , Richiardi Jonas , Carrera Emmanuel
Published: May 2022

Background:

Does the brain become more resilient after a first stroke to reduce the consequences of a new lesion? Although recurrent strokes are a major clinical issue, whether and how the brain prepares for a second attack is unknown. This is due to the difficulties to obtain an appropriate dataset of stroke patients with comparable lesions, imaged at the same interval after onset. Furthermore, timing of the recurrent event remains unpredictable.

Methods:

Here, we used a novel clinical lesion simulation approach to test the hypothesis that resilience in brain networks increases during stroke recovery. Sixteen highly selected patients with a lesion restricted to the primary motor cortex were recruited. At 3 time points of the index event (10 days, 3 weeks, 3 months), we mimicked recurrent infarcts by deletion of nodes in brain networks (resting-state functional magnetic resonance imaging). Graph measures were applied to determine resilience (global efficiency after attack) and wiring cost (mean degree) of the network.

Results:

At 10 days and 3 weeks after stroke, resilience was similar in patients and controls. However, at 3 months, although motor function had fully recovered, resilience to clinically representative simulated lesions was higher compared to controls (cortical lesion
P
=0.012; subcortical:
P
=0.009; cortico-subcortical:
P
=0.009). Similar results were found after random (
P
=0.012) and targeted (
P
=0.015) attacks.

Conclusions:

Our results suggest that, in this highly selected cohort of patients with lesions restricted to the primary motor cortex, brain networks reconfigure to increase resilience to future insults. Lesion simulation is an innovative approach, which may have major implications for stroke therapy. Individualized neuromodulation strategies could be developed to foster resilient network reconfigurations after a first stroke to limit the consequences of future attacks.
Duration of Ischemia Impacts Postreperfusion Clinical Outcomes Independent of Follow‐Up Infarct Volume
Authors: Desai Shashvat M. , Aghaebrahim Amin , Siegler James E. , Monteiro Andre , Jha Ruchira M. , Jadhav Ashutosh P. , Jovin Tudor G.
Published: May 2022

Background

Time to reperfusion is believed to influence clinical outcomes following thrombectomy mainly through reduction of infarct growth. In this study, we aim to understand whether clinical outcomes can be influenced by ischemia duration (penumbral time) independent of postintervention infarct volume by comparing outcomes following thrombectomy in patients with similar (and small) follow‐up infarct volumes.

Methods

We performed a retrospective analysis of a prospectively maintained large‐vessel occlusion stroke thrombectomy database across 3 US centers. Demographic, clinical, radiological, and outcomes data of patients with anterior circulation large‐vessel occlusion (internal carotid or middle cerebral artery M1) stroke who had a witnessed‐onset stroke, had substantial penumbral volumes, achieved successful reperfusion (modified thrombolysis in cerebral infarction 2b‐3), and had a follow‐up infarct volume of <20 mL were analyzed.

Results

A total of 233 patients (center A, 25; center B, 33; center C, 175) were included. Mean age was 71±16 years, and median National Institutes of Health Stroke Scale was 15 (10–20). Median penumbral time was 4.7 (2.9–10) hours, and median follow‐up infarct volume was 4.7 (0.2–9.4) mL. Despite comparable baseline characteristics and 24‐hour infarct volumes, patients reperfused in the 0‐ to 6‐hour time window had significantly higher rates of modified Rankin scale 0 to 2 (61% versus 40%;
P
=0.002) and numerically lower rates of mortality (11% versus 17%;
P
=0.16) at 90 days when compared with patients reperfused in the 6‐ to 24‐hour time window. Duration of ischemia is an independent predictor of modified Rankin scale 0 to 2 (odds ratio, 0.91 [0.80–0.99];
P
=0.012). In multivariable analysis accounting for age and baseline National Institutes of Health Stroke Scale score, the association between penumbral time and modified Rankin scale 0 to 2 remained significant (absolute risk difference, −1.2% [(95% CI, −1.9 to −0.4)]/h delay).

Conclusion

Longer penumbral duration is associated with a lower likelihood of functional independence among large‐vessel occlusion strokes with small and comparable 24‐hour follow‐up infarct volume. Our findings indicate that delays in time to reperfusion affect clinical outcomes through mechanisms mediated by factors not solely limited to infarct reduction.
How Important Are Russia's External Economic Links?
Authors: Korhonen Iikka , Simola Heli
Published: May 2022

In this note, we review recent data concerning Russia's economic integration with other countries. We first analyze the general picture of Russia's economic integration with the rest of the world and the importance of foreign economic relations for the country. We then turn to China, an increasingly significant economic partner for Russia. The European Union remains Russia's most important trading partner and is by far the most important source of foreign direct investment to Russia as well as source of other financing. China's importance to Russia has also increased, especially with respect to merchandise trade.
Role of Interaction Delays in the Synchronization of Inhibitory Networks
Authors: Roohi Nariman , Valizadeh Alireza
Published: May 2022

Neural oscillations provide a means for efficient and flexible communication among different brain areas. Understanding the mechanisms of the generation of brain oscillations is crucial to determine principles of communication and information transfer in the brain circuits. It is well known that the inhibitory neurons play a major role in the generation of oscillations in the gamma range, in pure inhibitory networks, or in the networks composed of excitatory and inhibitory neurons. In this study, we explore the impact of different parameters and, in particular, the delay in the transmission of the signals between the neurons, on the dynamics of inhibitory networks. We show that increasing delay in a reasonable range increases the synchrony and stabilizes the oscillations. Unstable gamma oscillations characterized by a highly variable amplitude of oscillations can be observed in an intermediate range of delays. We show that in this range of delays, other experimentally observed phenomena such as sparse firing, variable amplitude and period, and the correlation between the instantaneous amplitude and period could be observed. The results broaden our understanding of the mechanism of the generation of the gamma oscillations in the inhibitory networks, known as the ING (interneuron-gamma) mechanism.
The Perils of Being Unhinged: On the Accuracy of Classifiers Minimizing a Noise-Robust Convex Loss
Authors: Long Philip M. , Servedio Rocco A.
Published: May 2022

van Rooyen, Menon, and Williamson (2015) introduced a notion of convex loss functions being robust to random classification noise and established that the “unhinged” loss function is robust in this sense. In this letter, we study the accuracy of binary classifiers obtained by minimizing the unhinged loss and observe that even for simple linearly separable data distributions, minimizing the unhinged loss may only yield a binary classifier with accuracy no better than random guessing.
Effect of cell size and thresholds in NDM/NVDM methods on recognizing areas of endemism
Authors: SANTIAGO-ALVARADO MARGARITA , LUNA-VEGA ISOLDA , RIVAS GERARDO , ESPINOSA DAVID
Published: May 2022

Identifying areas of endemism has represented a great challenge, from the search for their definition, the design of methodologies, and the management of essential information to identify areas where the distributions of at least two taxa overlap. Endemicity Analysis is a widely used method that offers good results; however, an evaluation of the results is necessary. We evaluated the previous establishment of the minimum endemicity index of the species as a criterion to identify areas of endemism, applicated to a set of taxa with endemic and preferential distribution to the Sierra Madre Oriental. The taxa included in our analyses were 178 species of plants, vertebrates, and invertebrates. First, we varied the parameter set minimum score species in the software and the size of the cell. Next, we established criteria to evaluate the results obtained: areas supported by unique sets of species, good fit to the area, and sympatric distribution of taxa (extensive or homopatrid). After choosing the minimum ei with the best performance, we modified the study method for the endemicity analysis (Endemicity Analysis with Progressive Species Elimination). Our results indicate that the variation of the ei influenced the number of areas obtained by the program, decreasing considerably after evaluating the first criterion. The best fit to the cells occurred when we set 0.8 as the minimum ei in both cell sizes. The visually-preview of the sympatrid relationships allowed to recognize areas that do not present congruent distributions, although they meet the two previous criteria evaluated. The areas of endemism identified at different scales and those identified with the implementation of our modification were complementary.
Neodontobutis lani, a new sleeper fish of the family Odontobutidae (Teleostei: Gobiiformes) from Guangxi, southern China
Authors: ZHOU MINGWEI , HE ANYOU , WANG FANGXIN , LI YUSEN , LI CHENHONG
Published: May 2022

A new species, Neodontobutis lani (Odontobutidae) is described from the Zuojiang River, a tributary of the Xijiang River of the Pearl River basin, at Longzhou Town, Guangxi Zhuang Autonomous Region, Southern China. This species can be distinguished from other Neodontobutis species by following characters: anterior head flat, with interorbital width / eye diameter = 1.4–1.9 (vs. less than 1.4); several rows (vs. single row) of transforming ctenii on posterior edges of body scales; sensory papilla on lower jaw arranged in two oblong clusters (vs. two single lines). It can be distinguished from Odontobutis species by: separated right and left gill membrane (vs. joined); barbel-like projection present on sensory papillae. Molecular phylogenetic analysis of 2,076 nuclear coding loci indicates that N. lani is a sister species of N. hainanensis, the only Neodontobutis species that has been described from China.