bluuebunny/crossref_metadata_2025 huggingface dataset:
Does the Improvement of the Business Environment Improve the Innovation Efficiency of Enterprises? Evidence from the Listed Companies in China
Authors: Han Yan , Pan Cheng , Jin Fengjun
Published: July 2023

The quality of the business environment influences the speed and quality of economic development, and optimizing the business environment helps improve enterprises’ innovation ability. This article selects urban business environment and micro-enterprise data of Chinese listed companies from 2013 to 2019. It constructs a comprehensive evaluation index system for the urban business environment in China through the entropy method, exploring the specific path of promoting enterprise innovation ability through the business environment. The empirical results indicate that optimizing the business environment can encourage improving innovation efficiency in enterprises. A good business environment can increase government subsidies and enterprises’ Assumption of risk ability to promote technological innovation. Financing constraints and supply chain concentration can negatively enhance the driving effect of the business environment on enterprise innovation. Heterogeneity analysis indicates that the business environment is more conducive to stimulating the drive for technological innovation among state-owned enterprises, large-scale enterprises, and manufacturing enterprises. This article provides new insights into the relationship between the business environment and the innovation efficiency of enterprises.
Computation of Matrix Determinants by Cross-Multiplication: A Rethinking of Dodgson’s Condensation and Reduction by Elementary Row Operations Methods
Authors: Protacio Judel Villas
Published: July 2023

We formulate a more straightforward, symmetry-based technique for manually computing the determinant of any n×n matrix by revisiting Dodgson’s condensation method, as well as strategically applying elementary row (column) operations and the definition and properties of determinants. The result yields a more streamlined algorithm that is generalized through formulas and employs a smaller number of operations and succeeding matrices than the existing methods.
A Novel Algorithm for Merging Bayesian Networks
Authors: Vaniš Miroslav , Lokaj Zdeněk , Šrotýř Martin
Published: July 2023

The article presents a novel algorithm for merging Bayesian networks generated by different methods, such as expert knowledge and data-driven approaches, while leveraging a symmetry-based approach. The algorithm combines the strengths of each input network to create a more comprehensive and accurate network. Evaluations on traffic accident data from Prague in the Czech Republic and accidents on railway crossings demonstrate superior predictive performance, as measured by prediction error metric. The algorithm identifies and incorporates symmetric nodes into the final network, ensuring consistent representations across different methods. The merged network, incorporating nodes selected from both the expert and algorithm networks, provides a more comprehensive and accurate representation of the relationships among variables in the dataset. Future research could focus on extending the algorithm to deal with cycles and improving the handling of conditional probability tables. Overall, the proposed algorithm demonstrates the effectiveness of combining different sources of knowledge in Bayesian network modeling.
A Study on Perception of Visual–Tactile and Color–Texture Features of Footwear Leather for Symmetric Shoes
Authors: Xu Dan-Dan , Wu Chih-Fu , Wang Chung-Shing
Published: July 2023

The study applies Kansei engineering in analyzing the color and texture of leather footwear, utilizing neural network verification to mirror consumers’ visual and tactile imageries onto varieties of leather. This aids in the development of an advanced system for selecting leather footwear based on such impressions. Initially, representative word pairs denoting consumers’ visual and tactile perceptions of leather footwear were delineated. Post-evaluation of these perceptions through a sensibility assessment questionnaire was administered, using 54 samples of leather footwear provided by manufacturers, with each leather type codified in terms of visual and tactile sensibilities. Subsequently, a customized software algorithm was crafted to isolate the primary color and adhesiveness as color features from the leather sample images. Analyzing grayscale values of the images and using pixel neighborhood as a base, the associated calculation methods, such as LBP, SCOV, VAR, SAC, etc., were proposed to extract texture features from the images. The derived color and texture feature values were used as the input layer and the sensory vocabulary quantified values as the output layer. Backpropagation neural network training was conducted on 49 leather samples, with five leather samples used for testing, culminating in the verification of neural network training for three types and 17 combinations. The outcome was an optimal method for leather footwear Kansei engineering and neural network training, establishing a design process for leather footwear characteristics assisted by sensory vocabulary and a backpropagation neural network. Additionally, a computer-aided system for selecting leather footwear, based on these impressions, was designed and validated through footwear design. This study utilized symmetry in footwear design. By using the design of a single shoe to represent the imagery of a pair of symmetrical shoes, we verified whether the leather samples recommended by the leather imagery selection query system met the expected system input settings.
Virtual Restoration System for 3D Digital Cultural Relics Based on a Fuzzy Logic Algorithm
Authors: Li Feng , Gao Yongli , Candeias António , Wu Yao
Published: July 2023

This research proposes a virtual restoration system and method for 3D digital cultural relics based on a fuzzy logic algorithm, aiming to solve the problems of the low classification accuracy and poor splicing effect of Terra Cotta Warrior fragments. This method adopts a series of steps to improve the efficiency and accuracy of fragment splicing. Firstly, features such as curvature, torsion, and left and right chord lengths were extracted from the fracture surface contour lines of the cultural relic fragments to form feature vectors. Then, the feature vector was fused and compressed by using the multilayer perceptron. The multilayer perceptron is a neural network model that can process and learn input data via multiple levels of computation, resulting in more expressive feature representations. Next, we used the calculation results of the multilayer perceptron to perform the splicing operation on the fragments. This means that, based on the calculation results of the feature vectors, the system can automatically select appropriate splicing methods to accurately match and splice fragments. Finally, by adjusting the weight of the multilayer perceptron, the error rate of fragment splicing can be reduced, further improving the accuracy of repair. The experimental results show that the method proposed in this article is significantly better than traditional methods in terms of time consumption and can effectively improve the efficiency of fragment matching and stitching. Conclusion: The fragment-stitching algorithm based on multi-feature adaptive fusion improved the speed and effectiveness of stitching in fragment-stitching tasks. In summary, the fragment-stitching algorithm based on multi-feature adaptive fusion can improve the speed and effectiveness of stitching in fragment-stitching tasks. The application of this method is expected to play an important role in the field of cultural relic protection, such as the restoration of Terra Cotta Warrior fragments.
Optimal Government Subsidy Decision and Its Impact on Sustainable Development of a Closed-Loop Supply Chain
Authors: Gu Yujie , Xue Menghao , Zhao Mingxuan , Long Yufu
Published: July 2023

Government subsidies generally play an important role in the sustainable operations management of a closed-loop supply chain (CLSC). This paper investigates the optimal government subsidy decision and its influence on the sustainable development of the CLSC, consisting of one manufacturer, one retailer, and one third-party collector, from the economic, environmental, and social perspectives. Based on game analysis technology, different Stackelberg game models among the government and the CLSC members are formulated to analyze the optimal decisions under different power structures. By conducting theoretic comparative and sensitivity analyses and a case study, the effects of the government subsidy and the power structure are explored from the total profit, environmental benefit, and social welfare. Results show that the subsidy is good for sustainable development of the CLSC, which improves the total profit of the CLSC members, environmental benefit, and social welfare and the improvement effect is more prominent when the CLSC members have unequal bargaining power. Moreover, according to the growth proportion of profit, the retailer and collector benefit more from the subsidy among the CLSC members when they have different bargaining power, otherwise, the CLSC members benefit equally from the subsidy, and the subsidy is more beneficial to the environment compared with the total supply chain profit and social welfare.
Evolution Mechanism of Public–Private Partnership Project Trust from the Perspective of the Supply Chain
Authors: Li Huimin , Zhang Yu , Liang Mengxuan , Cao Yongchao , Zhang Wenjuan , Su Limin
Published: July 2023

In the public–private partnership (PPP) supply chain, trust serves as the foundation for collaboration between investment companies and suppliers. However, due to many uncertain factors, the evolution of trust remains a “black box” phenomenon. In order to analyze the impact of the evolution of trust in the PPP supply chain on investment companies and suppliers’ strategic choices, and promote the healthy and sustainable development of PPP supply chain projects, this paper establishes a trust evolutionary game model, which analyzes the evolutionary paths under different scenarios and explores the impact of parameters on the cooperative strategies of participants. The findings indicate that trust asymmetry or an increase in trust can facilitate investment companies and suppliers to opt for positive cooperation strategies. Furthermore, both parties’ strategies are less influenced by their initial willingness and more by trust degree. The moral risk coefficient and information asymmetry coefficient have a negative effect on the cooperative strategies, with the moral risk coefficient of investment companies exhibiting a more significant impact on the entire cooperation process. Moreover, both parties can only choose positive strategies when the information asymmetry coefficient is low. This study holds significant implications for promoting cooperation, enhancing contract performance, safeguarding the interests of all parties, and increasing cooperation satisfaction.
Doppler Examination of the Testicular Artery of Beagle-Breed Dogs from Birth to Puberty
Authors: Venianaki Athina P. , Barbagianni Mariana S. , Fthenakis George C. , Galatos Apostolos D. , Gouletsou Pagona G.
Published: July 2023

The objectives were (a) the study of haemodynamic parameters of blood flow within the testicular artery, (b) the assessment of differences in these parameters at different segments of the artery (i.e., sequentially, as the artery flows through different regions of the testis), and (c) the identification of potential associations with measures of testicular maturation. Eight healthy beagle-breed male dogs were monitored at fortnightly intervals from the 4th to the 40th week of life, by using clinical, seminological, and ultrasonographic (B-mode, pulsed-wave Doppler) examinations. Haemodynamic parameters were assessed at four different segments of the testicular artery: at the distal supra-testicular, the marginal testicular at the cranial pole of the testis, the marginal testicular at the caudal pole of the testis, and the intratesticular. The study period was divided into three time slots (pre-puberty, puberty, and post-puberty) depending on testicular maturation and sperm production. No clinically evident abnormalities were seen in any animal throughout the study. Semen ejaculates were first collected on the 28th week, and spermatozoa were first seen on the 30th week of life. The results of B-mode examination indicated that in all dogs, the echogenicity of the testicular parenchyma was homogeneous. The waveforms of the blood flow in the testicular artery were monophasic with systolic peaks, low diastolic flow, and low vascular resistance. Most cases of significant differences between the three age periods were noted for the comparison of the pre-pubertal to pubertal periods (n = 11); among the parameters studied, the blood volume (n = 9) showed most instances of significant differences; finally, most cases of significant differences were noted in the distal supra-testicular artery (n = 12). Correlations were mainly seen for the end diastolic velocity, the peak systolic velocity and the blood volume (each with two semen evaluation parameters). The distal supra-testicular and the marginal artery at the cranial pole of the testis are recommended as the most appropriate segments of the vessel for performing a Doppler examination in the testicular artery due to the adequate size and the clear spectral waveforms as early as the 12th week of age of the animals.
The Accumulation of Toxic Elements (Pb, Hg, Cd, As, and Cu) in Red Swamp Crayfish (Procambarus clarkii) in Qianjiang and the Associated Risks to Human Health
Authors: Zhang Lang , Song Ziwei , Zhou Yuntao , Zhong Shan , Yu Yali , Liu Ting , Gao Xiaoping , Li Lekang , Kong Chiping , Wang Xinna , He Li , Gan Jinhua
Published: July 2023

Due to rapidly expanding crayfish consumption worldwide, the food safety of red swamp crayfish (Procambarus clarkii) is of great concern. China is the largest consumer and producer of crayfish globally. As of yet, it is unknown whether the main crayfish production cities in China are within safe levels of toxic heavy metals and metalloids. For 16 consecutive years, Qianjiang city ranked first in China in processing export volumes of red swamp crayfish. This study presents a comprehensive analysis of the enrichment levels and associated health risks of the species in Qianjiang. In our research, samples of four crayfish tissues, including the head, hepatopancreas, gills, and muscles, were collected from 38 sampling sites distributed in Qianjiang to evaluate the concentration levels of five heavy metals (Pb, Hg, Cd, As, and Cu). The concentration levels of all five metals in muscle did not surpass the national standard. Furthermore, eight significant correlations have been found. For further in-depth assess risk of crayfish in Qianjiang, estimated daily intake (EDI), target hazard quotient (THQ), carcinogenic risk (CR), and estimated maximum allowable consumption rates (CRmm) were evaluated in the abdomen muscle and hepatopancreas. The THQ values for each metal were found to be less than 1, while the CR values were below 10–6. Additionally, the CRmm for adults was determined to be 17.2 meals per month. These findings, based on the analysis of five metallic elements included in this study, suggest that the consumption of crayfish abdomen muscle in Qianjiang does not pose any significant health risks. However, it is noteworthy that certain regions exhibit elevated levels of arsenic in the hepatopancreas, surpassing the national standard, thereby rendering them unsuitable for excessive consumption. In general, the findings can be used to provide guidance for safe dietary practices in China.
Biodegradation Capabilities of Paraquat-Degrading Bacteria Immobilized on Nanoceramics
Authors: Jindakaraked Manee , Khan Eakalak , Kajitvichyanukul Puangrat
Published: July 2023

The biodegradation of paraquat was investigated using immobilized microbial cells on nanoceramics fabricated from nanoscale kaolinite. Pseudomonas putida and Bacillus subtilis, which degrade paraquat, were immobilized separately on nanoceramics (respectively called ICnc−P and ICnc−B). The attachment of bacteria to nanoceramics resulted from electrostatic force interactions, hydrogen bonding, and covalent bonding (between the cells and the support materials). The initial 10 mg L−1 concentration of paraquat in water was removed by the adsorption process using nanoceramics at 68% and ceramics at 52%, respectively. The immobilized cells on the nanoceramics were able to remove approximately 92% of the paraquat within 10 h, whereas the free cells could only remove 4%. When the paraquat was removed, the cell−immobilized nanoceramics exhibited a significant decrease in dissolved organic nitrogen (DON). ICnc−B was responsible for 34% of DON biodegradation, while ICnc−P was responsible for 22%. Ammonia was identified as the end product of ammonification resulting from paraquat mineralization.
Spectroscopic and Microestructural Evidence for T-2 Toxin Adsorption Mechanism by Natural Bentonite Modified with Organic Cations
Authors: García-García Fernando Abiram , Cristiani-Urbina Eliseo , Morales-Barrera Liliana , Rodríguez-Peña Olga Nelly , Hernández-Portilla Luis Barbo , Flores-Ortíz Cesar Mateo
Published: July 2023

Aluminosilicates are adsorbents able to bind mycotoxins, and their chemical modification increases their affinity to adsorb low-polarity mycotoxins. To further investigate if the inclusion of salts in bentonite modifies its adsorptive capacity, we studied T-2 toxin adsorption in natural bentonite (NB) and when modified with quaternary ammonium salts differing in polarity and chain length: myristyl trimethyl ammonium bromide (B14), cetyl trimethyl ammonium bromide (B16) and benzyl dimethyl stearyl ammonium chloride (B18). The results showed that quaternary salts made bentonite: displace monovalent (Na+1, K+1) and divalent (Mg+2, Ca+2) ions; reduce its porosity; change its compaction and structure, becoming more crystalline and ordered; and modify the charge balance of sheets. T-2 adsorption was higher in all modified materials compared to NB (p ≤ 0.0001), and B16 (42.96%) better adsorbed T-2 compared to B18 (35.80%; p = 0.0066). B14 (38.40%) showed no differences compared to B16 and B18 (p > 0.05). We described the T-2 adsorption mechanism in B16, in which hydrogen bond interactions, Van der Waals forces and the replacement of the salt by T-2 were found. Our results showed that interaction types due to the inclusion in B16 might be more important than the hydrocarbon chain length to improve the adsorptive capacity of bentonite.
Differential Geometry of the Family of Helical Hypersurfaces with a Light-like Axis in Minkowski Spacetime L4
Authors: Güler Erhan
Published: July 2023

We investigate the class of helical hypersurfaces parametrized by x=x(u,v,w), characterized by a light-like axis in Minkowski spacetime L4. We determine the matrices that represent the fundamental forms, Gauss map, and shape operator of x. Furthermore, employing the Cayley–Hamilton theorem, we compute the curvatures associated with x. We explore the conditions under which the curvatures of x possess the property of being umbilical. Moreover, we provide the Laplace–Beltrami operator for the family of helical hypersurfaces with a light-like axis in L4.
Excitation Functions of Related Temperatures of η and η0 Emission Sources from Squared Momentum Transfer Spectra in High-Energy Collisions
Authors: Wang Qi , Liu Fu-Hu , Olimov Khusniddin K.
Published: July 2023

The squared momentum transfer spectra of η and η0, produced in high-energy photon–proton (γp) →η(η0)+p processes in electron–proton (ep) collisions performed at CEBAF, NINA, CEA, SLAC, DESY, and WLS are analyzed. The Monte Carlo calculations are used in the analysis of the squared momentum transfer spectra, where the transfer undergoes from the incident γ to emitted η(η0) or equivalently from the target proton to emitted proton. In the calculations, the Erlang distribution and Tsallis–Levy function are used to describe the transverse momentum (pT) spectra of emitted particles. Our results show that the average transverse momentum (⟨pT⟩), the initial-state temperature (Ti), and the final-state temperature (T0) roughly decrease from the lower center-of-mass energy (W) to the higher one in the concerned energy range of a few GeV, which is different from the excitation function from heavy-ion collisions in the similar energy range.
Differences in Trends in Admissions and Outcomes among Patients from a Secondary Hospital in Madrid during the COVID-19 Pandemic: A Hospital-Based Epidemiological Analysis (2020–2022)
Authors: Garcia-Carretero Rafael , Vazquez-Gomez Oscar , Ordoñez-Garcia María , Garrido-Peño Noelia , Gil-Prieto Ruth , Gil-de-Miguel Angel
Published: July 2023

Spain had some of Europe’s highest incidence and mortality rates for coronavirus disease 2019 (COVID-19). This study highlights the impact of the COVID-19 pandemic on daily health care in terms of incidence, critical patients, and mortality. We describe the characteristics and clinical outcomes of patients, comparing variables over the different waves. We performed a descriptive, retrospective study using the historical records of patients hospitalized with COVID-19. We describe demographic characteristics, admissions, and occupancy. Time series allowed us to visualize and analyze trends and patterns, and identify several waves during the 27-month period. A total of 3315 patients had been hospitalized with confirmed COVID-19. One-third of these patients were hospitalized during the first weeks of the pandemic. We observed that 4.6% of all hospitalizations had been admitted to the intensive care unit, and we identified a mortality rate of 9.4% among hospitalized patients. Arithmetic- and semi-logarithmic-scale charts showed how admissions and deaths rose sharply during the first weeks, increasing by 10 every few days. We described a single hospital’s response and experiences during the pandemic. This research highlights certain demographic profiles in a population and emphasizes the importance of identifying waves when performing research on COVID-19. Our results can extend the analysis of the impact of COVID-19 and can be applied in other contexts, and can be considered when further analyzing the clinical, epidemiological, or demographic characteristics of populations with COVID-19. Our findings suggest that the pandemic should be analyzed not as a whole but rather in different waves.
System Biology Approach to Identify the Hub Genes and Pathways Associated with Human H5N1 Infection
Authors: Chaudhary Raushan , L. Ananthesh , Patil Prakash , Mateti Uday , Sah Sanjit , Mohanty Aroop , Rath Rama , Padhi Bijaya , Malik Sumira , Jassim Kadhim , Al-Shammari Moustafa , Waheed Yasir , Satapathy Prakasini , Barboza Joshuan , Rodriguez-Morales Alfonso , Sah Ranjit
Published: July 2023

Introduction: H5N1 is a highly pathogenic avian influenza virus that can infect humans and has an estimated fatality rate of 53%. As shown by the current situation of the COVID-19 pandemic, emerging and re-emerging viruses such as H5N1 have the potential to cause another pandemic. Thus, this study outlined the hub genes and pathways associated with H5N1 infection in humans. Methods: The genes associated with H5N1 infection in humans were retrieved from the NCBI Gene database using “H5N1 virus infection” as the keyword. The genes obtained were investigated for protein–protein interaction (PPI) using STRING version 11.5 and studied for functional enrichment analysis using DAVID 2021. Further, the PPI network was visualised and analysed using Cytoscape 3.7.2, and the hub genes were obtained using the local topological analysis method of the cytoHubba plugin. Results: A total of 39 genes associated with H5N1 infection in humans significantly interacted with each other, forming a PPI network with 38 nodes and 149 edges modulating 74 KEGG pathways, 76 biological processes, 13 cellular components, and 22 molecular functions. Further, the PPI network analysis revealed that 33 nodes interacted, forming 1056 shortest paths at 0.282 network density, along with a 1.947 characteristic path length. The local topological analysis predicted IFNA1, IRF3, CXCL8, CXCL10, IFNB1, and CHUK as the critical hub genes in human H5N1 infection. Conclusion: The hub genes associated with the H5N1 infection and their pathways could serve as diagnostic, prognostic, and therapeutic targets for H5N1 infection among humans.
Adaptation and Formative Evaluation of Online Decision Support to Implement Evidence-Based Strategies to Increase HPV Vaccination Rates in Pediatric Clinics
Authors: Shegog Ross , Savas Lara S. , Frost Erica L. , Thormaehlen Laura C. , Teague Travis , Steffy Jack , Healy Catherine Mary , Shay Laura Aubree , Preston Sharice , Vernon Sally W.
Published: July 2023

Human papilloma virus (HPV) vaccination rates remain below national goals in the United States despite the availability of evidence-based strategies to increase rates. The Adolescent Vaccination Program (AVP) is a multi-component intervention demonstrated to increase HPV vaccination rates in pediatric clinics through the implementation of six evidence-based strategies. The purpose of this study, conducted in Houston, Texas, from 2019–2021, was to adapt the AVP into an online decision support implementation tool for standalone use and to evaluate its feasibility for use in community clinics. Phase 1 (Adaptation) comprised clinic interviews (n = 23), literature review, Adolescent Vaccination Program Implementation Tool (AVP-IT) design documentation, and AVP-IT development. Phase 2 (Evaluation) comprised usability testing with healthcare providers (HCPs) (n = 5) and feasibility testing in community-based clinics (n = 2). AVP-IT decision support provides an Action Plan with tailored guidance on implementing six evidence-based strategies (immunization champions, assessment and feedback, continuing education, provider prompts, parent reminders, and parent education). HCPs rated the AVP-IT as acceptable, credible, easy, helpful, impactful, and appealing (≥80% agreement). They rated AVP-IT supported implementation as easier and more effective compared to usual practice (p ≤ 0.05). The clinic-based AVP-IT uses facilitated strategy implementation by 3-month follow-up. The AVP-IT promises accessible, utilitarian, and scalable decision support on strategies to increase HPV vaccination rates in pediatric clinic settings. Further feasibility and efficacy testing is indicated.
Hepatitis a Vaccine as Opportunity of Primary Prevention for Food Handlers: A Narrative Review
Authors: Fallucca Alessandra , Restivo Vincenzo , Sgariglia Maria Chiara , Roveta Marco , Trucchi Cecilia
Published: July 2023

The hepatitis A virus (HAV) is still a leading cause of viral hepatitis worldwide. After a long incubation period, the clinical manifestations range from asymptomatic infection to acute liver failure. The severity of the disease increases with age and pre-existing liver disease. The transmission is mainly via person-to-person contact or ingestion of contaminated food or water. Food contamination can occur at any step of the food chain, especially when infected people handle not-heated or otherwise-treated food. HAV is endemic in low-income countries because of poor sanitary and sociodemographic conditions. The populations of developed countries are highly susceptible, and large outbreaks occur when HAV is introduced from endemic countries due to globalization, travel, and movement of foodstuffs. HAV prevention includes hygiene practices, immunoglobulins, and vaccination. Safe and effective inactivated and live attenuated vaccines are available and provide long-term protection. The vaccine targets are children and subjects at increased risk of HAV exposure or serious clinical outcomes. This review discusses the critical role of food handlers in the spread of HAV and the opportunity for food industry employers to consider food handler immunization a tool to manage both food safety in compliance with HACCP principles and food operators’ biologic risk.
COVID-19 Vaccination Personas in Yemen: Insights from Three Rounds of a Cross-Sectional Survey
Authors: Nikoloski Zlatko , Chimenya Dennis , Alshehari Abdullah , Hassan Hauwa , Bain Robert , Menchini Leonardo , Gillespie Amaya
Published: July 2023

We used three rounds of a repeated cross-sectional survey on COVID-19 vaccination conducted throughout the entire territory of Yemen to: (i) describe the demographic and socio-economic characteristics associated with willingness to be vaccinated; (ii) analyse the link between beliefs associated with COVID-19 vaccines and willingness to be vaccinated; and (iii) analyse the potential platforms that could be used to target vaccine hesitancy and improve vaccine coverage in Yemen. Over two-thirds of respondents were either unwilling or unsure about vaccination across the three rounds. We found that gender, age, and educational attainment were significant correlates of vaccination status. Respondents with better knowledge about the virus and with greater confidence in the capacity of the authorities (and their own) to deal with the virus were more likely to be willing to be vaccinated. Consistent with the health belief model, practising one (or more) COVID-19 preventative measures was associated with a higher willingness to get a COVID-19 vaccination. Respondents with more positive views towards COVID-19 vaccines were also more likely to be willing to be vaccinated. By contrast, respondents who believed that vaccines are associated with significant side effects were more likely to refuse vaccination. Finally, those who relied on community leaders/healthcare workers as a trusted channel for obtaining COVID-19-related information were more likely to be willing to be vaccinated. Strengthening the information about the COVID-19 vaccination (safety, effectiveness, side effects) and communicating it through community leaders/healthcare workers could help increase the COVID-19 vaccine coverage in Yemen.
Meta-Analysis on the Global Prevalence of Tetracycline Resistance in Escherichia coli Isolated from Beef Cattle
Authors: Messele Yohannes E. , Werid Gebremeskel Mamu , Petrovski Kiro
Published: July 2023

Antimicrobial resistance (AMR) is an emerging global concern, with the widespread use of antimicrobials in One Health contributing significantly to this phenomenon. Among various antimicrobials, tetracyclines are extensively used in the beef cattle industry, potentially contributing to the development of resistance in bacterial populations. This meta-analysis aimed to examine the association between tetracycline use in beef cattle and the development of tetracycline resistance in Escherichia coli isolates. A comprehensive search was conducted using multiple databases to gather relevant observational studies evaluating tetracycline use and tetracycline resistance in Escherichia coli isolates from beef cattle. The rate of tetracycline resistance from each study served as the effect measure and was pooled using a random-effects model, considering possible disparities among studies. The meta-analysis of 14 prospective longitudinal studies resulted in a 0.31 prevalence of tetracycline resistance in Escherichia coli in non-intervention (no exposure), contrasting numerically elevated resistance rates in the intervention (exposed) groups of 0.53 and 0.39 in those receiving tetracyclines via feed or systemically, respectively. Despite the observed numerical differences, no statistically significant differences existed between intervention and non-intervention groups, challenging the conventional belief that antimicrobial use in livestock inherently leads to increased AMR. The findings of this study underscore the need for additional research to fully understand the complex relationship between antimicrobial use and AMR development. A considerable degree of heterogeneity across studies, potentially driven by variations in study design and diverse presentation of results, indicates the intricate and complex nature of AMR development. Further research with standardized methodologies might help elucidate the relationship between tetracycline use and resistance in Escherichia coli isolated from beef cattle.
A Bilevel Optimal Water Allocation Model Considering Water Users’ Satisfaction Degree and Water Rights Transaction: A Case Study in Qingzhang River Basin, China
Authors: Chu Yu , Xiao Yi , Zhu Jiulong
Published: July 2023

The contradiction between water supply and demand in China is becoming increasingly prominent. A water allocation scheme that satisfies various water users can effectively solve it. In this paper, considering both individual rationality and collective rationality, a bilevel optimal allocation model for river basin water resources is established. Firstly, water users’ satisfaction degree was defined, to characterize their satisfaction with the water resource allocation scheme, and principles of water users’ satisfaction degree were mathematically expressed, to represent water users’ negotiation activities in the initial water rights allocation. Then, based on the initial allocation results, water users’ water intake quantity, water-saving amount, and water-trade amount were optimized by water rights trading. Finally, an algorithm based on the response surface was put forward for solving the proposed bilevel optimal allocation model. The validity and feasibility of the model and algorithm were verified by a case study in the Qingzhang River Basin in China.
Hydrochemical Characteristics and Quality Evaluation of Irrigation and Drinking Water in Bangong Co Lake Watershed in Northwest Tibetan Plateau
Authors: Shao Yuxiang , Yan Buqing , Liu Lubaiyang , Yu Xiao , Feng Gang , Zhang Kun , Gong Kang
Published: July 2023

Bangong Lake is a narrow and long lake in the arid region of the plateau in northern Tibet. The salinity of the east of the lake is different from that the west, resulting in differences in the natural environment and human living conditions on each side. Watershed hydrochemical analysis and spatial statistical analysis can help to understand regional hydrochemical evolution and water quality evaluation. In this study, the hydrochemical characteristics of surface water (glacier, river, and lake) and groundwater in the Bangong Co Lake Watershed were investigated to reveal the relationships between various water bodies. The drinking water quality index (DWQI) and USSL classification were applied to assess groundwater quality suitability for agricultural and drinking purposes. The hydrochemical characteristics show the differences among water bodies and their spatial distribution. The analyzed groundwater and surface water samples, such as river water and glaciers, were mainly Ca-HCO3-type and the lake water was mainly categorized as Na-Cl-type with some Na-HCO3-Cl type. The lake water’s chemical components are mainly affected by evaporative karst decomposition. The main mineralization process of groundwater and river water was related to the dissolution of reservoir minerals, such as dolomite and calcite, as well as halite. The drinking water quality index (DWQI) indicates that 79% of the groundwater samples in the study area were of good enough quality for drinking. In terms of irrigation water quality, the electrical conductivity (EC), calculated sodium adsorption ratio (SAR), and magnesium hazardous ratio (MHR) showed that more than 13% of the total samples were not suitable for irrigation. However, the USSL classification indicated that glacier and river water are relatively suitable for irrigation. Additionally, some groundwater and lake water has very high alkalinity or salinity, which is alarming when considering them for irrigation.
Vibration Prediction and Evaluation System of the Pumping Station Based on ARIMA–ANFIS–WOA Hybrid Model and D-S Evidence Theory
Authors: Wang Shuo , Zhang Liaojun , Yin Guojiang
Published: July 2023

Research on the vibration response prediction and safety early warning is of great significance to the operation and management of pumping station engineering. In the current research, a hybrid prediction method was proposed to predict vibration responses of the pumping station based on a single model of autoregressive integrated moving average (ARIMA), a combined model of the adaptive network-based fuzzy inference system (ANFIS) and whale optimization algorithm (WOA). The performance of the developed models was studied based on the effective stress vibration data of the blades in a shaft tubular pumping station. Then, the D-S evidence theory was adopted to perform safety early warning of the operation state by integrating the displacement, velocity, acceleration and stress indicators of the vibration responses of the pumping station. The research results show that the proposed prediction model ARIMA–ANFIS–WOA exhibited better accuracy in obtaining both linear and nonlinear characteristics of vibration data than the single prediction model and hybrid model with different optimization algorithms. The D-S evidence fusion results quantitatively demonstrate the safe operation state of the pumping station. This research could provide a scientific basis for the real-time analysis and processing of data in pumping station operation and maintenance systems.
An Event-Based Resilience Index to Assess the Impacts of Land Imperviousness and Climate Changes on Flooding Risks in Urban Drainage Systems
Authors: Li Jiada , Strong Courtenay , Wang Jun , Burian Steven
Published: July 2023

Assessing the resilience of urban drainage systems requires the consideration of future disturbances that will disrupt the system’s performance and trigger urban flooding failures. However, most existing resilience assessments of urban drainage systems rarely consider the uncertain threats from future urban redevelopment and climate change, which leads to the underestimation of future disturbances toward system performance. This paper fills in the gap of assessing the combined and relative impacts of future impervious land cover and rainfall changes on flooding resilience in the context of a densely infilled urban catchment served by an urban drainage system in Salt Lake City, Utah, USA. An event-based resilience index is proposed to measure climate change and urbanization impacts on urban floods. Compared with the traditional resilience metric, the event-based resilience index can consider climatic and urbanized impacts on each urban flooding event; the new resilience index assist engineers in harvesting high-resolution infrastructure adaptation strategies at vulnerable spots from the system level to the junction level. Impact comparison for the case study shows that impervious urban surface changes induce greater effects on the system performance curves by magnifying the maximum failure level, lengthening the recovery duration, and aggravating the flooding severity than rainfall intensity changes. A nonlinear logarithmic resilience correlation is found; this finding shows that flooding resilience is more sensitive to the land imperviousness change due to urban redevelopment than rainfall intensity changes in the case study. This research work predicts the system response to the disturbances induced by climate change and urban redevelopment, improving the understanding of impact analysis, and contributes to the advancement of resilient urban drainage systems in changing environments.
Removal of Ibuprofen and Diclofenac in Batch Nitrifying Reactors: Effect of Natural Zeolite on the Process
Authors: Escobar Jenny , Hernández Leslie , González Jorge Leiva , Salazar-González Ricardo , Calzadilla Wendy , Guerrero Lorna , Escalona Néstor , Huiliñir César
Published: July 2023

Ibuprofen (IBP) and diclofenac (DFC) are two of the most commonly used non-steroidal anti-inflammatory drugs (NSAIDs) to treat inflammation and pain. However, they can impact the environment if not treated adequately before discharge into waterways. Biodegradation through the nitrification process is an alternative to reducing the concentration of these micropollutants (MPs) in wastewater. Thus, this work aimed to evaluate the effect of natural zeolite on IBP and DFC removal in a nitrifying batch reactor. Mini-reactors were set up with 90 mL of inoculum and 110 mL of synthetic wastewater with a concentration of 25 mg total ammonia nitrogen TAN/L, at 25 °C and 1 vvm (volume of air/volume liquid∙min) of aeration. Two conditions were tested: high concentrations (IBP = 700 μg/L, DFC = 100 μg/L) and low concentrations (IBP = 30 μg/L, DFC = 20 μg/L). The research used a concentration of 5 g/L of the natural zeolite. Results indicated that the zeolite negatively affected the nitrification rate. At high MPs concentration, the natural zeolite negatively affects the removal of IBP and DFC, where biodegradation and sorption are the mechanisms that eliminate both NSAIDs. Conversely, at low DFC and IBP concentrations, the natural zeolite improves the removal of IBP and DFC, wherein biodegradation is the primary removal mechanism.
Research on the dq-Axis Current Reaction Time of an Interior Permanent Magnet Synchronous Motor for Electric Vehicle
Authors: Huang Anxue , Chen Zhongxian , Wang Juanjuan
Published: July 2023

An interior permanent magnet synchronous motor (IPMSM) is a kind of drive motor with high power density that is suitable for electric vehicles. In this paper, the dq-axis current reaction time of IPMSM was investigated in order to improve the reaction time of the electric vehicle. Firstly, the mathematical model of the current-loop decoupling of IPMSM was presented. Secondly, the controller design of dq-axis current-loop decoupling of IPMSM was investigated by the methods of proportional integral (PI) and internal model control PI (IMC-PI). Thirdly, based on the methods of PI and IMC-PI, the influence of the inverter switching frequency on the dq-axis current reaction time of IPMSM was analyzed and simulated, and it was found that the inverter switching frequency only had a significant influence on the parameters set of the PI controller. Lastly, compared with the PI method, the results of the simulation and hardware experiment demonstrate that the dq-axis current reaction time of IPMSM was improved by the IMC-PI method, and the IMC-PI method had the advantage of simple parameters setting and was not influenced by the inverter switching frequency.
Blockchain-based Scalable and Secure EHR Data Sharing using Proxy Re-Encryption
Authors: Sammeta Naresh , Parthiban Latha
Published: July 2023

Electronic Health Record (EHR) includes highly sensitive data like medical images, prescriptions, medical test result, medical history of patients, etc., These sensitive data cannot be transmitted in its original form in the network due to security issues. Hence, encryption is done prior to transmission. To increase the speed of data transfer and to overcome the storage issues, data is usually transferred through the cloud. Hence, to ensure the security and scalability of the data, a third-party encryption called re-encryption is performed at the proxy cloud. This re-encryption ensures that the data can be reliably transmitted through the network. In this research, a novel scheme called block-chain based EHR data sharing using chaotic re-encryption (BC-EDS-CR) is proposed. In the proposed scheme, re-encryption is performed using chaos theory. The proposed re-encryption scheme ensures that the cloud administrator cannot access the medical data. Metrics such as Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Structural Similarity Index (SSIM), entropy and correlation coefficient are used in evaluating this scheme. It was found that the proposed scheme outperforms the existing methods by achieving a PSNR of 57.66, SSIM of 0.985 and MSE of 0.058.
A Robot Path Planning Method Based on Synergy Behavior of Cockroach Colony
Authors: Cheng Le , Chang Lyu , Song Yanhong , Wang Haibo , Bian Yuetang
Published: July 2023

By studying the biological behavior of cockroaches, a bionic algorithm, Cooperative Learning Cockroach Colony Optimization (CLCCO), is presented in this paper. The aim of CLCCO is to provide an efficient method to solve Robot Path Planning (RPP) problems. The CLCCO algorithm is based on the idea of synergy behavior of cockroach colony and machine learning. With pheromone, the cockroach colony achieves population synergy, which includes the follow and diversion behaviors. The strategy of Fibonacci transformation is used for the cockroach individual to choose the next feasible cell. The technologies of λ-geometry and multi-objective search make the paths searched smoother and greatly improve the algorithm search efficiency. In particular, the CLCCO algorithm requires only two parameters to be set. When CLCCO is applied to real robots, a path compression technique is designed. The simulation results show that the CLCCO algorithm demonstrates high efficiency in mostly tests.
Migration, Selection and Income Differentials in Brazilian Labor Market.
Authors: Filho Luís , Maia Alexandre
Published: July 2023

Migration is understood in the economic literature as a decision based on prospects of better working conditions and the search for higher remuneration at the destination, compared to the origin of the workforce. In this sense, this article aims to test the hypothesis of favorable migratory selectivity in Brazil based on the model with sample selection bias correction proposed by Heckman (1979). Based on census information for the years 2000 and 2010, the aim is to analyze the population aged between 15 and 60 years who declared themselves to be employed in the Brazilian labor market. Suppose it is confirmed that migrants are a positively selected population group. In that case, they have unobservable characteristics that affect the decision to migrate and, consequently, labor earnings. The second step is to decompose the characteristics that affect the earnings differentials between migrants and non-migrants, considering those of an observable and non-observable nature. The results show that Brazilian intercity migrants make up a positively selected group. Concerning the breakdown of income differentials, labor income is more remarkable in favor of migrants, and the largest share of income differences between migrants and non-migrants is due to unobservable factors. Therefore, the implications of this study show that the migration of qualified human capital in Brazil, that is, those with the best professional performance in the labor market (positively selected), may end up deepening regional socioeconomic inequalities since migrants always seek opportunities in more economically dynamic regions. This suggests that policies be developed to reduce regional inequalities that aim, above all, to boost the growth of less developed regions so that their human capital has the opportunity to develop internally in their regions, contributing to the growth and development of the original region.