bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization of asbestos exposures associated with the use of facial makeups
Authors: Holton Michael , Ellis Jennifer , Anderson Evan , Poole James
Published: January 2022

There has been renewed interest in the safety of cosmetics that may contain asbestos or other elongate mineral particles at very low levels as a naturally occurring contaminant. The authors evaluated asbestos exposure during the application of facial makeups in a constructed chamber simulating a bathroom space. The facial makeups tested included products previously found to have very low or “trace” asbestos content by governmental and commercial laboratories using a variety of bulk analysis methods. Tremolite asbestos was detected in five of 54 personal air samples and three of 72 area air samples in 18 simulations. The calculated geometric mean and 95th percentile task‐based asbestos concentration associated with personal facial makeup use in this study, incorporating censored data, is 0.0015 and 0.0018 fiber per cubic centimeter (f/cc), respectively, with a corresponding 95th percentile 24‐h time‐weighted average (TWA) asbestos concentration of 0.00008 f/cc for three applications per day in a simulated bathroom with no active ventilation. Based on these results, cumulative non‐occupational asbestos exposures confer a less than one in 1,000,000 risk of asbestos‐related disease based on many typical usage patterns and less than 1/100,000 risk with upper‐end lifetime usage patterns, using the US Environmental Protection Agency asbestos risk model.
Information effects on lay tradeoffs between national regulatory costs and benefits
Authors: Johnson Branden B. , Finkel Adam M.
Published: January 2022

A novel stated‐preference “macro‐risk” approach introduced to estimate the life‐prolonging benefits of proposed environmental, health, and safety regulations may answer questions unasked or wrongly answered by conventional revealed‐preference (e.g., “wage premiums” for high occupational risks) and stated‐preference methods (e.g., willingness to pay for tiny reductions in one's own premature death risk). This new approach asks laypeople to appraise directly their preferred tradeoffs between national regulatory costs and lives prolonged nationwide (regulatory benefits). However, this method may suffer from incomplete lay understanding of national‐scale consequences (e.g., billions of dollars in regulatory costs; hundreds of lives prolonged) or tradeoffs (e.g., what are lives prolonged worth?). Here we (1) tested effects of numerical contextual examples to ground each hypothetical regulatory tradeoff, and (2) explored why some people implicitly offer “implausible” values (< $10,000 or > $1 billion) for the social benefit of prolonging one life. In Study 1 (n = 356), after testing their separate effects, we combined three contextual‐information aids: (1) comparing hypothetical regulatory costs and benefits to real‐life higher and lower values; (2) reframing large numbers into smaller, more familiar terms; and (3) framing regulatory costs as having diffuse versus concentrated impacts. Information increased social benefits values on average (from $4.5 million to $13.8 million). Study 2 (n = 402) found that the most common explanations for “implausible” values included inattention, strong attitudes about regulation, and problems translating values into responses. We discuss implications for this novel stated‐preferences method, and for comparing it to micro‐risk methods.
Integrated approach for spatial flood susceptibility assessment in Bhagirathi sub‐basin, India using entropy information theory and geospatial technology
Authors: Rehman Sufia , Hasan Mohd. Sayeed Ul , Rai Abhishek Kumar , Rahaman Md. Hibjur , Avtar Ram , Sajjad Haroon
Published: January 2022

Globally, floods as dynamic hydraulic hazard have caused widespread damages to both socioeconomic conditions and environment at various scales. Managing flood and management of water resource is a global challenge under the changing climatic condition. This study assessed flood susceptibility in the Bhagirathi sub‐basin, India using entropy information theory and geospatial technology. Twelve flood susceptibility parameters such as land use/land cover, normalized difference vegetation index (NDVI), slope, elevation, geology, geomorphology, normalized difference water index (NDWI), soil, drainage density, average rainfall, maximum temperature, and humidity during monsoon season were utilized to examine flood susceptibility. Receiver operating characteristics (ROC) curve and Leave‐One‐Out Cross‐Validation (LOOCV) techniques were carried out to validate flood susceptibility map. Kappa statistics was also used to check the reliability of the flood susceptibility model. Findings of the study revealed that nearly 45% area of the sub‐basin was highly susceptible to flood followed by moderate (29.3%), very high (19%), low (6.9%), and very low (0.2%). These findings also revealed that nearly 92% area in the eastern, north‐eastern, and deltaic sub‐basin was susceptible to floods. ROC analysis indicated high success (0.932) and prediction (0.903) rates for the susceptibility map while LOOCV (R2 being 0.97) and Kappa (k = 0.934) have shown substantial prediction of the model. Hence, the susceptibility maps are useful for the local planners and government organization in designing the early flood warning system, and reducing the human and economic losses. The methodology used in this study is applicable for analyzing flood susceptibility at spatial scales in similar systems.
The role of trust and risk perception in current German nuclear waste management
Authors: Seidl Roman , Drögemüller Cord , Krütli Pius , Walther Clemens
Published: January 2022

One of the lessons learned in various countries that have to deal with spent nuclear fuel is that finding a proper place and siting a repository for high‐level nuclear waste (HLW) cannot be achieved without public consent. After decades of obstruction, Germany recently launched a new, participatory, site‐selection process for the disposal of HLW in deep geological formations. Nonetheless, significant opposition is assumed. Therefore, citizens’ trust in the procedure and the agents involved may be paramount. We conducted an online survey (N ≈ 5000) in March/April 2020 to test a theoretical model on trust, perceived risks and benefits, and acceptance. We differentiated acceptance as a dependent variable according to distinct phases: the procedure, a possible decision on a disposal location, and the repository facility itself. The results show that trust is mainly important for explaining acceptance of the ongoing procedure and less so for the acceptance of the decision or the repository facility itself. Moreover, our investigation of the sample using a cluster analysis reveals characteristic patterns of trust, risk perception, and acceptance by three clusters: a cluster focusing on risk perception, an ambivalent cluster, and an indifferent cluster. Trust is lowest in the risk‐focused cluster and highest in the ambivalent cluster.
Sustainability and Wealth of Rural Households: Measurement and Inequality Analysis
Authors: Gansonré Soumaïla , Al‐Hassan Ramatu M. , Ouédraogo Idrissa M. , Kwadzo George T. , Onumah Edward E.
Published: January 2022

A small but growing literature is linking well‐being with the value of assets, measured comprehensively. This measure, called comprehensive wealth, has appeared as a leading economic indicator of sustainability by reflecting the potential of future well‐being. Despite the concerns of sustainability for policy interventions at the micro‐level, the existing literature is limited to country‐level estimations. This paper applies the general framework of weak sustainability to measure wealth at the household level. Using data from three rounds of household survey, market prices, and yield data from rural Burkina Faso, we measure wealth, income, and consumption per adult. The results show that wealth has consistently increased over time in contrast to income and consumption which have fluctuated. Wealth is also less unequally distributed. Finally, consumption is found to be more correlated with wealth. This suggests that wealth‐based interventions are more likely to improve well‐being in a sustainable way.
Survey of companion animal veterinarians' antimicrobial drug prescription practices and awareness of antimicrobial drug use guidelines in the United States
Authors: Taylor Daniel D. , Martin Jennifer N. , Scallan Walter Elaine J.
Published: January 2022

Antimicrobial drug use in companion animal medicine, the subsequent development of antimicrobial resistance and the potential hazard of animals transmitting resistant bacteria to humans are of increasing concern. Antimicrobial prescription patterns among companion animal veterinarians in the United States are understudied, and the association between antimicrobial drug use guideline awareness and antimicrobial drug prescription practices is unknown. Information on antimicrobial recommendations for five hypothetical clinical scenarios, including canine pyoderma, acute canine diarrhoea, feline lower urinary tract illness, canine dental procedures and feline upper respiratory illness, was gathered using an anonymous, online cross‐sectional survey. A logistic regression approach was used to assess the association between self‐reported awareness of antimicrobial drug use guidelines and prescribing recommendations for the five hypothetical scenarios. Responses (n = 2,410) indicated antimicrobial drugs were commonly recommended for the five hypothetical clinical scenarios. After controlling for key demographic characteristics, prescribers who reported an awareness of existing antimicrobial drug use guidelines were significantly less likely to recommend antimicrobial drugs for the scenarios describing feline lower urinary symptoms, feline upper respiratory illness and canine acute diarrhoea. Results from hypothetical clinical scenarios point to the possibility for widespread unsupported prescribing of antimicrobial drugs in companion animal medicine. Additionally, results provide evidence of an association between awareness of antimicrobial drug use guidelines and lower prescribing levels for certain hypothetical disease presentations.
Vinni goola: Percepción de la vejez entre las mujeres zapotecas del istmo de Tehuantepec en el siglo XXI
Authors:   INSTITUTO POLITECNICO NACIONAL (ESM), Fuentes Valdivieso Rocio
Published: January 2022

Este trabajo aborda el tema de la vejez desde la percepción social y cultural de las mujeres del istmo de Tehuantepec hablantes de la lengua zapoteca. Con esta investigación buscamos conocer la significación que le dan a la edad. Partimos de una pregunta ¿Se entiende igual la vejez de las mujeres en todas las sociedades? ¿Cómo entienden las mujeres zapotecas del istmo de Tehuantepec la vejez? La presente exposición es el resultado de un trabajo etnográfico de una investigación basado en la convivencia diaria con las mujeres del istmo de Tehuantepec. El tema está orientado hacia las mujeres grandes y ancianas que en el zapoteco del istmo se llaman vinni goola y su traducción es gente ampliada o grande Elegimos dos grupos de mujeres para conocer cómo se ve la vida desde donde están y cómo lo han contextualizado ellas. La manera de ver y significar la vida a partir de la vejez, nos dice mucho sobre la subjetividad de las mujeres desde la visión de un grupo étnico como son los zapotecas en el siglo XXI. El objetivo es conocer las maneras de percibir y significar la vejez por ellas mismas. Nos enfocamos principalmente, en mujeres profesionistas y en las que no asistieron a una universidad, pero que también han trabajado de diversas maneras en diferentes oficios como ser cocineras, comerciantes, rezadoras y una diversidad de empleos que ellas fueron creando de acuerdo a las demandas sociales del comercio local.
An assessment of hybridization potential between Atlantic and Pacific salmon
Authors: Devlin Robert H. , Biagi Carlo A. , Sakhrani Dionne , Fujimoto Takafumi , Leggatt Rosalind A. , Smith Jack L. , Yesaki Timothy Y.
Published: February 2022

Salmonids possess straying abilities that allows them to exploit open territory and establish new populations. Atlantic salmon (Salmo salar) are expanding their distribution primarily as first-generation escapes from aquaculture, whereas Pacific salmon (Oncorhynchus spp.) are expanding their range in polar and temperate regions due to both anthropogenic and natural influences. Here we utilize artificial intergeneric reciprocal crosses to assess the ability of seven species of Pacific salmon to hybridize with Atlantic salmon. Most cross types were found to produce low numbers of hatched embryos, but none survived to sexual maturation. Survivors consisted of diploids and triploids containing both Atlantic and Pacific salmon parental genomes. Thus, introgression of DNA between Pacific and Atlantic salmon may occur to form F1 hybrids, but transmission to subsequent generations is expected to be rare and occur only over evolutionary time scales. Further, the low viability observed for the most part at early stages of development and in both reciprocal crosses indicates that intergeneric crosses in nature between Atlantic and Pacific salmon are expected to have severe fitness consequences for both dams and sires.
NSRT diagram for identification of SACA and TACA rules in null-boundary
Authors: Dalui Mamata , Chakraborty Bidesh , Das Nilanjana , Sikdar Biplab K.
Published: January 2022

This work reports characterization of one-dimensional null-boundary cellular automata (CA) rules in 3-neighborhood. The outcome of this characterization is the identification of CA rules that are the probable candidates for producing single length cycle attractor (fixed point). It targets synthesis of CA with only one fixed point (referred to as the single length cycle single attractor CA (SACA)) and the CA with only two fixed points (referred to as single length cycle two attractors CA (TACA)) for arbitrary length. A tool referred to as Next State RMT Transition Diagram (NSRTD) is developed to identify the fixed points as well as the cycles, involving multiple states (multi-length cycles) of a CA. The NSRTD provides the theoretical basis to search for the rules that form SACA and TACA, for all lengths, in null-boundary.
On the Taylor–Couette flow of fractional oldroyd-B fluids in a cylindrically symmetric configuration using transforms
Authors: Almutairi Bander , Kamran Muhammad , Farooq Aamir , Ahmad Hijaz , Shahzad Azeem , Khan Farman Ullah , Khan Ali Sikandar , Almohsen Bandar
Published: January 2022

The focus in this study is to examine the flow formation of Taylor–Couette (T–C) for some fluids exhibiting non-Newtonian properties in a region of cylindrical annulus due to the effect of imposed stresses on the periphery of the inner cylinder while the outer cylinder is hanging around inert. This tangential shear will be liable for the motion of the fluid through the annulus. It is very often when researchers in different fields like engineering, mathematics and physics come across the complexity that the given mathematical model cannot be solved in the existing space and requires to be transformed in the space in which it can be easily solved. Thus, transforms are being used as a key tool for solving many dominant problems in different fields. Many transformations have been introduced by researchers but for solving problems in this study, we will make use of Hankel transform and Laplace transform to obtain the velocity field and the corresponding shear stresses (SS) for the fractional Oldroyd-B fluid (O-B fluid). In the end, a graphical presentation is given for the comparison of the effect on fluid motion due to different parameters like fractional parameters, relaxation and retardation times.
LEVERAGING ON ENERGY SECURITY TO ALLEVIATE POVERTY IN ASIAN ECONOMIES
Authors: TAGHIZADEH-HESARY FARHAD , ZAKARI ABDULRASHEED , YOSHINO NAOYUKI , KHAN IRFAN
Published: January 2022

This study examines the role of energy security in poverty reduction in the 12 poorest Asian economies from 2000 to 2019. We postulated an energy security index using principal component analysis. We adopted the system generalized method of a moment technique to manage endogeneity and dynamism in the model. For robustness, we applied a panel-corrected standard error (PCSE). We found a negative relationship between energy security and poverty reduction, suggesting that energy security helps reduce poverty. We conclude that energy security promotes sustainable poverty alleviation and recommends feed-in tariffs, net metering, tax credits, and energy resource diversification away from fossil fuels.
DOES IMPORTED PRODUCER SERVICE AFFECT MANUFACTURING EXPORT? EVIDENCE FROM CHINA
Authors: YU ZHEN , XIAO YAO , GU XIN , XIE XUBIN
Published: January 2022

Based on a panel data of 44 countries and 18 industries spanning 14 years, this paper provides a novel insight into the driving force behind the expanding volume of China’s export. We match the global input–output database with micro-level data from Chinese manufacturing firms and find a positive effect of imported producer service inputs on domestic manufacturing exports. Foreign producer service inputs assist domestic firms in entering foreign markets and maintaining foreign relations, thus contributing to their exporting performance. The results confirm the specialization effect and information cost reduction effect led by imported service inputs.
HOUSEHOLD ECONOMIC PRUDENCE IN THAILAND
Authors: PAWEENAWAT SASIWIMON WARUNSIRI
Published: January 2022

The countercyclical pattern of saving in Thailand in the 1990s and 2000s raised questions about household saving behaviors in the country. Using constructed pseudo-panel data sets from the Thai Household Socioeconomic Surveys (SESs) from 1992 to 2011, this paper estimates the intensity of the precautionary saving motive, measured by the coefficient of relative prudence of households in Thailand. By using a dynamic pseudo-panel approach to address concerns with regard to individual heterogeneity causing bias in estimation, the estimated relative prudence of Thai households is around 2, which shows a low precautionary saving motive among these households compared to other countries. Estimates based on disaggregation by demographic characteristics show that as a result of the government-assistance policy, older cohorts and those who live in the rural areas show lower prudence.
On complete Leibniz algebras
Authors: Ayupov Sh. A. , Khudoyberdiyev A. Kh. , Shermatova Z. Kh.
Published: January 2022

This paper is devoted to the so-called complete Leibniz algebras. We construct some complete Leibniz algebras with complete radical and prove that the direct sum of complete Leibniz algebras is also complete. It is known that a Lie algebra with a complete ideal is split. We discuss the analogs of this result for the Leibniz algebras and show that it is true for some special classes of Leibniz algebras. Finally, we consider derivations of Leibniz algebras and present some classes of Leibniz algebras which are not complete, since they admit outer derivation.
Design and simulation of the all-optical XOR logic gate by XPM mechanism using photonic crystal semiconductor optical amplifier based on Mach–Zehnder interferometer
Authors: Heydarian Khosro , Nosratpour Arez , Razaghi Mohammad
Published: January 2022

In the presented structure, the performance of the all-optical XOR logic gate (AO-XOR-LG) is investigated. The XOR-LG is designed and simulated using a photonic crystal semiconductor optical amplifier (PC-SOA) based on Mach–Zehnder interferometer (MZI) and cross-phase modulation (XPM) nonlinear mechanism. The input optical pulse train used in this simulation is the type of RZ (Return-to-Zero). The finite difference method (FDM) has been used to solve the rate and propagation equations. The effect of input signal energy, bias current, and group refractive index on the output signal and gain of the XOR-LG is studied. The optimal mode is obtained for the XOR-LG with a bit rate of 80 Gbps. Furthermore, for the first time, the effects of quality factor (QF), conversion efficiency (CE), extinction ratio (ER), pattern effect (PE), and gain recovery are simultaneously analyzed in the simulation to increase PC-SOA performance. According to the results, PC-SOA has a more reasonable logic performance than conventional SOA, and due to its much shorter length than SOA, it can be a much better choice for integrated optical circuits.
Assessing and Improving Intelligent Physical Education Approaches Using Modified Cat Swarm Optimization Algorithm
Authors: Li Nianmao , Dhiman Rajiv , Shanmugapriyan J.
Published: January 2022

In general, technological innovations have transformed sports training or physical education classrooms constructively. Physical education instructors can develop personalized and realistic expectations for their students using software, streaming videos, cameras, and trackers. However, the intelligent physical education models seek efficient assessment to improve its real-time acceptance. This paper proposes Enhanced Cat Swarm Optimization (ECSO) algorithm to create a physical education system assessment model and increase the evaluation impact of sports training methods. This research identifies and explains various factors to design a multi-functional physical education monitoring device based on visual sensing that meets the real needs of users. To find out how sensitive the parameters are, this study uses the local sensitivity analysis theory. It incorporates real-world needs to suggest an optimized CSO algorithm with modified searching and tracking modes. Subsequently, the proposed methodology implements a randomized experiment to assess the model’s success. The proposed ECSO algorithm employing modified searching and tracing modes gives the best assessment of 98.8%.
A Malicious Intrusion Detection Model of Network Communication in Cloud Data Center
Authors: Dong Ni
Published: January 2022

To enhance the efficiency of malicious intrusion detection of network communication, a malicious intrusion detection model for the network communication in cloud data center is designed. Firstly, the data preprocessing includes three parts: normal sample data modeling, standard data membership calculation and standard data membership calculation. Then, the characteristic value collection stage is completed. Finally, the intrusion detection classification and trust value calculation are completed to conclude the malicious intrusion detection of the network communication in cloud data center. Exploratory findings show that the malicious intrusion detection model for the network communication in cloud data center improves the intrusion detection rate, and reduces the detection time and false alarm rate.
Real-Time Implementation and Testing of VoIP Vocoders with Asterisk PBX Using Wireshark Packet Analyzer
Authors: Chinna Rao R. , Lakshmi K. Mohana , Raja Ch. , Varma P. Bharat Siva , Rao Ganga Rama Koteswara , Patibandla Anitha
Published: January 2022

In the present-day digital world, the transmission of information like voice, text, video, etc. demands more bandwidth for fast and accurate transmission. Usually, 90% of information transmitted is the human voice, and various speech processing techniques are adapted for optimizing the bandwidth requirement and enhancing the performance of multiple modules like vocoders in mobile networks. To test the performance analysis of various vocoders, we used a Wireshark simulator with an Asterisk, and it is a software implementation of a private branch exchange (PBX). This work presents the performance evolution of existing voice over internet protocol (VoIP) vocoders using Wireshark with PBX Asterisk’s, The PBX Asterisk’s to analyze and capture the packets or sniffers. The Wireshark tools can diagnose the errors, the traffic flow with a graphical view and generate the statistics in the network. It is a software tool to analyze the traffic data with an intuitive and simple graphical interface in software tools are used to study. The extensive simulations are performed, and the percentage of data saved was calculated and compared with the various vocoders.
Research on the Detection Method of Disconnection of Low Voltage Anti-Theft Transformer
Authors: Cai Xiaowei
Published: January 2022

Theft of electricity is a significant loss of power sources. This fraud is mostly attributed to users’ actions such as removing the power supply, misuse of the power supply, etc. This analysis provides a way to handle the bypass and abuse of energy meters. A detection method of disconnection of low voltage anti-theft transformer (DM-DLVATT) to detect electricity theft is proposed in this research. The device architecture on a designed microcontroller’s measurement of two sensors. Although one of the new sensors controls the consumer charge’s power, the consumer has mounted the energy consumed by all modules while maintaining the device. The robbery suggests some difference between the interpreted values. There is also a temporary adjustment in the meter to restart the meter until it is altered. To recharge power products and track carbon emissions, the consumer often has remote access to electricity monitors. The device has been calculated correctly, and any effort has been made to circumvent or modify the voltage regulator. Finally, all disreputable actions using GSM technologies have been registered.
AI Intelligence Chatbot to Improve Students Learning in the Higher Education Platform
Authors: Liu Li , Subbareddy Rama , Raghavendra C. G.
Published: January 2022

The integrated chatbot for artificial intelligence customizes the learning experience for the students in higher education platform. The chatbot tests the answers of the students and offers insights for the students to improve their learning skills. Further, It helps to improve students’ thinking ability and expectations in higher education platform. The demanding factors for the students in the higher education platform include the need for interactive learning in a non-linear world, enhancing the thinking ability and expectations of the students. This paper proposes Artificial Intelligence Based Inquiry Evaluation Student Learning System (AI-IESLS) to increase interactive learning experience in a non-linear environment. The principal aim of this system is to improve the learning ability of the student on a specific subject using concept mapping in the chatbot. In addition, mapping has been validated for students based on the probability distribution analysis using a concept mapping. Besides, the probability graph’s curve generated by this system assesses the student’s understanding of the topic. The simulation results have been analyzed among students based on concept mapping using the AI-IESLS system in correlation with the traditional approach based on assessment ratio, feedbacks, reciprocity, timing analysis, expectation ratio, and active learning factor.
Machine Learning Assisted Energy Optimization in Smart Grid for Smart City Applications
Authors: Tang Ziqiang , Xie Hongping , Du Changqing , Liu Yinying , Khalaf Osamah Ibrahim , Allimuthu Udaya Kumar
Published: January 2022

Peer-to-peer electricity transaction is predicted to play a substantial role in research into future power infrastructures as energy consumption in intelligent microgrids increases. However, the on-demand usage of Energy is a major issue for families to obtain the best cost. This article provides a machine learning predictive power trading framework for supporting distributed power resources in real-time, day-to-day monitoring, and generating schedules. Furthermore, the energy optimization algorithm used in machine learning (EOA-ML) is proposed in this article. The machine learning-based platform suggested two modules: fuel trading and intelligent contracts based on machine learning implemented predictive analytical components. The Blockchain module enables peers to track energy use in real-time, manage electricity trading, model rewards, and irreversible transaction records of electricity trading. A predictive analysis component based on previous power usage data is designed to anticipate short-term energy usage in the Intelligent Contracts. This study utilizes data from the provincial Jeju, Korea’s electricity department on true energy utilization. This study seeks to establish optimal electricity flow and crowdsourced, promoting electricity between consumers and prosumers. Power trading relies on day-to-day, practical environmental control and the planning of decentralized power capitals to satisfy the demands of smart grids. Furthermore, it employs data mining technologies to obtain and study time-series research from the past electricity utilization data. Thus, the time series analytics promotes power controllingto better future efficient planning and managingelectricity supplies. It utilized numerous statistical methods to assess the effectiveness of the suggested prediction model, mean square error in different models of machine learning, recurring neural networks. The efficacy of the proposed system regarding the delay, throughput, and resource using hyperleader caliper is shown. Finally, the suggested approach is successfully applied for power crowdsourcing between prosumer and customer to reach service reliability based on trial findings. The actual and predicted cost analysis has been increased (95%). It minimizes the delay rate to (40.3%) by improving the efficiency rate.
Research on Marine Economic Development Information Management System Based on Supply Chain Technology
Authors: Chen Qunping
Published: January 2022

In the economic growth of the industry, the marine economic prediction management system occupies a significant position. The Marine Forecast Management System is of considerable importance to help establish rules and clues on the potential progress of the Marine Forecast Management System. Many investigations into the risk of the maritime supply chain currently concentrate on risk assessment and control and seldom undertake a detailed study of each factor’s reasoning structure. It is difficult to monitor and regulate the globalization of supply chains. Blockchain technology promises to provide accountability, traceability, and safety certain global supply chain management concerns as a distributed digital technology leader. This article critically analyzes blockchain technologies and intelligent contracts with future supply chain management applications. The interpretation framework model uses the Supply Chain Management based on Marine Economic Development (SCM-MED) methods to analyze the maritime supply chain risk mechanism. The model examines the structure and processes of the marine supply chain risk mechanism, offers a scientific framework for controlling the risk of the marine supply chain, and makes corresponding proposals for reducing and monitoring marine supply chain risk. It aims to test this belief by strictly calculating the exchanging value of information and comparing this improved value in the supply chain to reduce lead times and increase the pace of distribution by decreasing load sizes. The experimental result recommended SCM-MED improves the marine economic development ratio (98.2%) and total losses per year (25%).
Enhancement of Energy Efficiency and Network Lifetime Using Modified MPCT Algorithm in Wireless Sensor Networks
Authors: Satyanarayana P. , Mahalakshmi T. , Rao P. Rama Koteswara , Sheeba Adlin , Ravi Jampani , Rao J. Nageswara
Published: January 2022

Wireless sensor networks (WSN) allude to gathering of spatially fragmented and committed sensors for observing and documenting various physical and climatic variables like temperature, moistness and, so on. WSN is quickly growing its work in different fields like clinical, enterprises, climate following and so on. However, the sensor nodes have restricted battery life and substitution or re-energizing of these batteries in the sensor nodes is exceptionally troublesome for the most parts. Energy effectiveness is the significant worry in the remote sensor networks as it is significant for keeping up its activity. In this paper, clustering algorithms based on sensor module energy states to strengthen the network longevity of wireless sensor networks is proposed (i.e. modified MPCT algorithm) in which cluster head determination depends on the every cluster power centroid as well as power of the sensor nodes. Correspondence between cluster leader and sink module employ a parameter distance edge for lessening energy utilization. The outcome got shows a normal increment of 60% in network lifetime compared to Low energy adaptive protocol, Energy efficient midpoint initialization algorithm (EECPK-means), Park K-means algorithm and Mobility path selection protocol.
Building Construction Operation Simulation Based on BIM Technology and Intelligent Robots
Authors: Cai Hanying
Published: January 2022

In order to improve the effect of artificial intelligence technology in construction operations, this paper conducts in-depth research on the trajectory planning algorithm and servo system controller of artificial construction machinery structure, analyzes the operation system of intelligent construction structure, and establishes an error model based on the D-H rule, which provides a research basis for calibration and trajectory planning. Moreover, this paper constructs a construction operation simulation system based on BIM technology and artificial intelligence, which mainly analyzes the simulation technology of construction operation intelligent mechanism movement and construction operation. In addition, this paper combines BIM technology and artificial intelligence technology according to the actual needs of construction operations, simulate robot operations in BIM. Finally, this paper proves the effectiveness of the intelligent system proposed in this paper through experimental research.
The Correlation Analysis Between Financial Subsidy and Research and Development Investment of High-Tech Enterprises Under 6G Environment
Authors: Han Chunwei
Published: January 2022

In order to improve the competitiveness of high-tech enterprises, the investment in scientific and technological innovation of Chinese high-tech enterprises has been gradually improved. Therefore, the correlation between financial subsidies and research and development investment of high-tech enterprises is analyzed in 6G environment. The incentive form can promote the research and development investment of enterprises and improve the economic benefits of enterprises. Through the research on the relationship between the incentive of senior executives’ shareholding, the allocation of senior executives and the relationship between research and development investment and financial subsidy, the paper analyzes the incentive intensity and the relationship between incentive period and research and development investment. After using the correlation and regression analysis, we can see that incentive can promote research and development investment and strengthen the correlation between research and development investment and financial subsidy.
Correction Method of Visual Errors in Pole Vault Take-off Action Images
Authors: Lan Xiang , Zhang Jian , Chen Sisi
Published: January 2022

Pole Vault is one of the most difficult and complicated sport in athletic and tracks events; it is high jumping action with vaulting pole stick. In the study of Pole Vault technology, the rapid advancement of Augmented Reality (AR) technology has considerable significance for the visual error correction of the pole vault take-off action images in the simulated world. The key objective is to evaluate the correction algorithm of the visual errors of take-off action images of pole vault sport. This study analyzes the AR framework, features, and pole vault, as well as province methods for correcting visual defects. Pole vault take-off action images have been simulated with AR computation technique, and the AR images of continues pole vault made. This paper primarily provides an overview of augmented reality (AR) technology, including its properties and benefits, as well as a few visual error correcting methods. AR discusses how to choose an aerobics instructor who can help you maintain an aerobics regimen on a regular basis. Augmented reality has been used to model these pictures, and AR images of aerobics have been created. The visual error correction of the longitudinal direction, transverse direction, and height direction of AR simulated continue pole vault images with Scale Invariant Feature Transform (SIFT) algorithm, Mean Absolute Deviation (MAD) algorithm, Normalize Cross-Correlation (NCC) algorithm, and Sobel Edge Detection (SED) algorithm is proposed in this study. This revealed that poor performance in the pole vault sport is due in large part to a lack of a well-planned structure for implementing a corrective mechanism for visual mistake correction in take-off action images. The statistical result of perfect pole vault technique dissected and described, including the best manage, takeoff, drive and swing, and bar separation. Along with technical work, a pole vaulters training regimen should involve sprinting, weight lifting, and gymnastics as well.
Eshelby tensors and overall properties of nano-composites considering both interface stretching and bending effects
Authors: Huang Yezeng , Yan Peng , Wang Junbo , Dong Leiting , Atluri Satya N.
Published: January 2022

In this study, analytical micromechanical models are developed for nanocomposites with both interface stretching and bending effects. First, the interior and exterior Eshelby tensors for a spherical nano-inclusion, with an interface defined by the Steigmann–Ogden (S–O) model, subjected to an arbitrary uniform eigenstrain are derived. Correspondingly, the stress/strain concentration tensors for a spherical nano-inhomogeneity subjected to arbitrary uniform far-field stress/strain loadings are also derived. Using the obtained concentration tensors, the effective bulk and shear moduli are derived by employing the dilute approximation and the Mori–Tanaka method, respectively, which can be used for both nano-composites and nano-porous materials. An equivalent interface curvature parameter reflecting the influence of the interface bending resistance is found, which can significantly simplify the complex expressions of the effective properties. In addition to size-dependency, the closed form expressions show that the effective bulk modulus is invariant to interface bending resistance parameters, in contrast to the effective shear modulus. We also put forward a characteristic interface curvature parameter, near which the effective shear modulus is affected significantly. Numerical results show that the effective shear moduli of nano-composites and nano-porous materials can be greatly improved by an appropriate surface modification. Finally, the derived effective modulus with the S–O interface model is provided in the supplemental MATLAB code, which can be easily executed, and used as a benchmark for semi-analytical solutions and numerical solutions in future studies.
An End-to-End Deep Learning Pipeline for Assigning Secondary Structure in Proteins
Authors: Jisna V. A. , Jayaraj P. B.
Published: January 2022

Protein secondary structure assignment, a subdiscipline of computational chemistry, is yet to be explored using deep learning techniques. Protein secondary structure elements are assigned to support structural analysis and prediction. Algorithms like DSSP, generally regarded as the gold standard for assigning the secondary structure of proteins, need full atom information to label protein coordinates. The PDB database has been the major repository for data on the 3D structures of proteins, nucleic acids, and other complex assemblies since 1971. However, a significant fraction of protein structures contains missing atoms. As a result, new approaches to reliably and consistently assigning secondary structures based on coarse-grained atomic coordinates are needed. While deep learning architectures have an unparalleled track record in applications such as protein structure prediction, there are only a few known deep learning solutions for structure assignment problems. While the gold standard methods are based on bonding information and other geometric characteristics, deep learning methods extract features themselves without human intervention. The benefit that standardised datasets provide to the effectiveness of deep learning systems in multiple domains motivated us to create a labeled dataset for protein structure assignment tasks. Additionally, a deep learning model, named PSSADL, solely based on [Formula: see text] coordinates was trained on the generated dataset to validate its potency. The proposed method, which combines Convolutional Neural Networks (CNN) and Long Short Term Memory (LSTM)/Bidirectional LSTM networks, has been compared to the established standards and more recent techniques. The model achieved an accuracy of [Formula: see text] on the benchmark and individual test sets. The results show that deep learning techniques have a promising future in protein structure analysis, implying that the dataset developed as part of our work will be a valuable resource for further protein structure research.
Operando Nanoindentation: A Perfect Platform to Measure the Mechanical Properties of Electrodes during Electrochemical Reactions
Authors: Zhao Kejie
Published: January 2022

We present an experimental platform of operando nanoindentation that probes the dynamic mechanical behaviors of electrodes during real-time electrochemical reactions. The setup consists of a nanoindenter, an electrochemical station, and a custom fluid cell integrated in an inert environment. We evaluate the influence of the argon atmosphere, electrolyte solution, structural degradation and volumetric change of electrodes upon Li reactions, as well as the surface layer and substrate effects by control experiments. Results inform on the system limitations and capabilities, and provide guidelines on the best experimental practices. Furthermore, we present a thorough investigation of the elastic-viscoplastic properties of amorphous Si electrodes, during cell operation at different C-rates and at open circuit. Pure Li metal is characterized separately. We measure the continuous evolution of the elastic modulus, hardness, and creep stress exponent of lithiated Si and compare the results with prior reports. Operando indentation will provide a perfect platform to understand the fundamental coupling between mechanics and electrochemistry in energy materials.
Research on Fast Recommendation Algorithm of Library Personalized Information Based on Density Clustering
Authors: Shi Yuqing , Zhu Yuelong
Published: January 2022

In order to improve the accuracy and efficiency of library information recommendation, this paper proposes a fast recommendation algorithm for library personalized information based on density clustering. According to the analysis of the clustering principle, the algorithm achieves the clustering of library information by designing density interval function. Then, the collection priority of library personalized information is judged, and the library personalized information is recommended quickly by designing tags according to the library users’ preferences. Experimental results show that the recommendation accuracy and F value of the proposed algorithm are higher than those of the two traditional algorithms, and its coverage rate is higher and the mean absolute error is lower, indicating that the proposed algorithm effectively achieves the design expectation.
Punicalagin Alleviates Aged Bronchial Asthma by Inhibiting Th2 Differentiation through IL-4/STAT6 and Jagged1/Notch Pathways
Authors: Yu Li , Li Jianying
Published: January 2022

Objective. To explore the therapeutic effect and mechanism of punicalagin on bronchial asthma in the elderly. Methods. Peripheral venous blood was collected from healthy people and elderly patients with bronchial asthma. Peripheral blood mononuclear cells (PBMCs) were isolated and cultured. PBMCs in the patient group were treated with different concentrations (0, 50, 100, and 200 mg/L) of punicalagin (PUN). MTT assay was used to detect cell activity, ELISA was used to detect the levels of IFN-γ, IL-2, IL-4, and IL-5, and Western blotting was used to detect the protein levels of p-STAT6, Jagged1, and GATA3. Result. MTT results showed that 50–200 mg/L PUN had no cytotoxicity to PBMCs within 24 h. ELISA results showed that the levels of IFN-γ and IL-2 in the serum of the patients were significantly lower than those of healthy people, and the levels of IL-4 and IL-5 were significantly higher than those of the healthy people. PUN treatment significantly increased the levels of IFN-γ and IL-2 in the supernatant of PBMCs culture, while significantly decreased the levels of IL-4 and IL-5, and the change was proportional to the concentration of PUN. Western blotting results showed that the levels of p-STAT6, Jagged1, and GATA3 protein in PBMCs of patients were significantly higher than those of the healthy people. PUN treatment could significantly reduce the expression of p-STAT6, Jagged1, and GATA3 protein in PBMCs of patients, and the reduction level was proportional to PUN concentration. Conclusion. PUN can inhibit Th2 differentiation and regulate Th1/Th2 balance by regulating IL-4/STAT6 and Jagged1/Notch pathways to alleviate the progress of bronchial asthma in the elderly.
PPARγ Alleviates Sepsis-Induced Liver Injury by Inhibiting Hepatocyte Pyroptosis via Inhibition of the ROS/TXNIP/NLRP3 Signaling Pathway
Authors: Li Zeyu , Liu Tong , Feng Yang , Tong Yingmu , Jia Yifan , Wang Cong , Cui Ruixia , Qu Kai , Liu Chang , Zhang Jingyao
Published: January 2022

Sepsis is a systemic inflammatory response syndrome caused by a dysregulated host response to infection. Peroxisome proliferator-activated receptor gamma (PPARγ) exerts anti-inflammatory and antioxidative properties. To investigate the potential effects of PPARγ on sepsis-induced liver injury and determine the related mechanisms, C57BL/6 male mice were subjected to cecal ligation and puncture (CLP) to create a sepsis model which was treated with GW1929 or GW9662 to upregulate or downregulate the expression of PPARγ. We found that upregulation of PPARγ decreased the serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin (TBIL), and liver pathological damage and improved the 5-day survival rate. Increased expression of PPARγ also decreased sepsis-induced reactive oxygen species (ROS) by promoting the expression of Nrf2. In addition, upregulated PPARγ inhibited the expression of the TXNIP/NLRP3 signaling pathway by reducing ROS-induced injury in the liver during sepsis, which further reduced NLRP3-mediated pyroptosis and the inflammatory response. The role of PPARγ was further examined in in vitro experiments, where lipopolysaccharide- (LPS-) treated HepG2 and Hep3B cells were incubated with GW1929 or GW9662 to upregulate or downregulate the expression of PPARγ. We found that upregulated PPARγ ameliorated LDH release and improved cell viability. Our results indicated that increased expression of PPARγ reduced ROS levels and inhibited the TXNIP/NLRP3 signaling pathway, resulting in decreased pyroptosis and reduced liver dysfunction during sepsis.