bluuebunny/crossref_metadata_2025 huggingface dataset:
Born to Be Green: Antecedents of Green Entrepreneurship Intentions among Higher Education Students
Authors: Shabeeb Ali Mohamed Ali , Ammer Mohammed Abdullah , Elshaer Ibrahim A.
Published: April 2023

Green entrepreneurship has become a growing area of interest among researchers and practitioners as it has the potential to address the sustainability challenges faced by the global economy. The purpose of this study is to evaluate six antecedents (self-efficacy, attitude, green consumption commitment, country support, university support, and subjective norms) that can predict the intention to engage in green entrepreneurship among higher education students. A total of 690 higher education students were surveyed, and the results were analyzed using partial least squares structural equation modeling (PLS-SEM). The results showed that the internal antecedents of green entrepreneurship intention (self-efficacy, attitude, and green consumption commitment) have a higher significant predictive power than the external antecedents of green entrepreneurship intention (country support, university support, and subjective norms) among higher education students. The findings of this study provide valuable insights into the factors that influence green entrepreneurship intention (GEI) and can be used to inform policy and educational initiatives aimed at promoting green entrepreneurship. The findings of this research could also draw attention from the government and universities who are interested in understanding the factors that influence students’ inclination towards green entrepreneurship. This could lead to the creation of relevant course materials, programs, and funding to promote sustainable initiatives.
Influence of the Antimicrobial LL-37 Peptide on Legionella dumoffii Phospholipids Adsorbed at the Air–Liquid Interface
Authors: Pastuszak Katarzyna , Kowalczyk Bożena , Tarasiuk Jacek , Jurak Małgorzata , Palusińska-Szysz Marta
Published: April 2023

Legionella dumoffii is an intracellular pathogen of freshwater protozoans capable of infecting and multiplying in mammalian cells, causing a severe respiratory disease called Legionnaires’ disease. The pathomechanism of infection development is very complex and depends on many factors, including the structure and properties of macromolecules that build the components of the L. dumoffii cell envelope. Phospholipids (PLs) forming biological membranes have a significant impact on the integrity of the membrane as well as on the interactions with the host cells. L. dumoffii changes its lipid profile under the influence of external factors, which allows it to adapt to the living environment. One of the factors altering the PL composition is the presence of exogenous choline. The aim of this study was to determine the physicochemical properties of the model bacterial membranes adsorbed at the air–liquid interface (Langmuir monolayers). They were composed of phospholipids isolated from L. dumoffii cultured with (PL+choline) and without (PL−choline) choline. Moreover, the effect of the human cathelicidin (LL-37 peptide) added to the subphase on these monolayers was analyzed in terms of phospholipid–peptide interactions. The results indicated that the monolayers of PL+choline were slightly more condensed than PL−choline. In the presence of LL-37, the elasticity of both monolayers increased; thus, their molecular packing and ordering decreased. The disturbing effect was related to the peptide’s antibacterial activity.
Analysis on Trade Competition and Complementarity of High-Quality Agricultural Products in Countries along the Belt and Road Initiative
Authors: Wang Xiao , Shi Jinming , Li Jia , Chen Yu , Liu Jianxu , Sriboonchitta Songsak
Published: April 2023

The Belt and Road Initiative was proposed by China in 2013 as a response to sluggish global economic growth. With most countries along the Belt and Road being developing countries, it is crucial to strengthen trade cooperation in agricultural products. However, the current literature lacks an analysis of the competitiveness and complementarity of agricultural products in these countries. This study aims to fill this gap by showing that the Belt and Road Initiative has reduced agricultural export competitiveness and increased agricultural trade complementarity. Several factors influence the similarity and complementarity of agricultural exports in participating countries along the Belt and Road, including geographical distance, level of economic development, free trade agreements, degree of country openness, exchange rates, cultural differences, share of agricultural value added, and level of infrastructure. The detailed analysis shows that the Belt and Road Initiative has significantly improved the quality of the agricultural exports of participating countries. The results of this paper provide a theoretical basis for the high-quality development of agricultural products in participating countries along the Belt and Road.
Metaheruistic Optimization Based Ensemble Machine Learning Model for Designing Detection Coil with Prediction of Electric Vehicle Charging Time
Authors: Alshammari Abdulaziz , Chabaan Rakan C.
Published: April 2023

An efficient charging time forecasting reduces the travel disruption that drivers experience as a result of charging behavior. Despite the machine learning algorithm’s success in forecasting future outcomes in a range of applications (travel industry), estimating the charging time of an electric vehicle (EV) is relatively novel. It can help the end consumer plan their trip based on the estimation data and, hence, reduce the waste of electricity through idle charging. This increases the sustainability factor of the electric charging station. This necessitates further research into the machine learning algorithm’s ability to predict EV charging time. Foreign object recognition is an essential auxiliary function to improve the security and dependability of wireless charging for electric vehicles. A comparable model is used to create the object detection circuit in this instance. Within this research, the ensemble machine learning methods employed to estimate EV charging times included random forest, CatBoost, and XGBoost, with parameters being improved through the metaheuristic Ant Colony Optimization algorithm to obtain higher accuracy and robustness. It was demonstrated that the proposed Ensemble Machine Learning Ant Colony Optimization (EML_ACO) algorithm achieved 20.5% of R2, 19.3% of MAE, 21% of RMSE, and 23% of MAPE in the training process. In comparison, it achieves 12.4% of R2, 13.3% of MAE, 21% of RMSE, and 12.4% of MAPE during testing.
Sustainability Indicators for Materials and Processes
Authors: Trucillo Paolo , Erto Alessandro
Published: April 2023

The concept of sustainability is nowadays employed to compare manufacturing processes or to define the correct path for material selection. Sometimes, this concept is only partially defined, including just low costs, profit maximization and/or CO2 emission reduction. Actually, a process or material can be defined as sustainable only if an objective function related to the economic, environmental and social impacts is simultaneously maximized. To this aim, it is necessary to define appropriate and specific sustainability indicators (i.e., values related to the economic, social and environmental aspects of a process or material under analysis). These indicators come about from simple calculations, and they are defined in terms of percentages and represented and compared using radar diagrams. Then, a process or specific material is identified by an objective function (i.e., the area included by the polygon that links the scores reported on the diagram). The scope of this representation of data is to individuate the major weaknesses of the process/material, proposing methods of optimization and trying to maximize the objective function in the retrieved diagram. This work aims to propose a general and simple method to calculate sustainability indicators on the basis of specific definitions related to a given process/material. To highlight the potential of this calculation and comparison instrument, two case studies are proposed: the first aims at comparing processes for the production of energy, while the second aims at driving the choice of manufacturing material. The selected indicators and adopted algorithm allowed for the identification of hydroelectric and eolic as the most sustainable processes for energy production; for materials, the results strictly depended on the assumptions made regarding favorable mechanical properties.
Editorial of Low Energy Nuclear Astrophysics and Sterile Neutrinos as Dark Matter
Authors: Kisslinger Leonard S.
Published: April 2023

This is an editorial on low energy nuclear astrophysics and sterile neutrinos as dark matter. First, the symmetric cosmic microwave background radiation and the the symmetric evolution of the Universe are editorialized. Then, low energy astrophysics with the evolution of the Sun, supernovae, and the Galaxy’s rotation are editorialized. In the final section, sterile neutrinos as dark matter is editorialized.
EcReID: Enhancing Correlations from Skeleton for Occluded Person Re-Identification
Authors: Zhu Minling , Zhou Huimin
Published: April 2023

Person re-identification is a challenging task due to the lack of person image information in occluded scenarios. The current methods for person re-identification only take into account global information, neglect local information, and are not responsive to changes in input. Additionally, these methods do not address the issue of inaccurate joint detection caused by occlusion. In this paper, we propose an occluded person re-identification method based on a graph model and deformable method, which is able to simultaneously focus on global and local information and can flexibly adapt to local information and changes in the input, efficiently resolving issues such as occluded or incorrect joint information. Our method consists of three modules: the mutual help denoising module, inter-node aggregation and update module, and graph matching module. The mutual help denoising module acquires global features and person skeleton node features using a CNN backbone network and a pose estimation model, respectively. It uses symmetric deformable graph attention to obtain the local and global features of the joint points in different views, correcting the information of incorrect nodes and extracting favorable human features. The inter-node aggregation and update module employs deformable graph convolution operations to enhance the relations between the nodes in the same view, resulting in higher-order information. The graph matching module uses graph matching methods based on the human topology to obtain a more accurate similarity calculation for masked images. Experimental results on the Occluded-Duck and Occluded-REID datasets show that our proposed method achieves Rank-1 accuracies of 64.8% and 84.5%, respectively, outperforming current mainstream methods such as HOReID. Our method also achieves good results on the MARKET-1501 and DukeMTMC-ReID datasets. These results demonstrate that our proposed method can extract person features well and effectively improve the accuracy of person re-identification tasks.
Modeling the Characteristics of Unhealthy Air Pollution Events Using Bivariate Copulas
Authors: Ismail Mohd Sabri , Masseran Nurulkamal
Published: April 2023

Investigating the dependence structures among the characteristics of the current unhealthy air pollution events is a valuable endeavor to understand the pollution behavior more clearly and determine the potential future risks. This study determined the characteristics of air pollution events based on their duration, severity, and intensity. It focused on modeling the dependence structures for all the possible pairs of characteristics, which were (duration, intensity), (severity, intensity), and (duration, severity), using various parametric copula models. The appropriate copula models for describing the behavior of the relationship pairs of the (duration, intensity), (severity, intensity), and (duration, severity) were found to be the Tawn type 1, 180°-rotated Tawn type 1, and Joe, respectively. This result showed that the dependence structures for the pairs were skewed and asymmetric. Therefore, the obtained copulas were appropriate models for such non-elliptical structures. These obtained models can be further extended in future work through the vine copula approach to provide a more comprehensive insight into the tri-variate relationship of the duration–intensity–severity characteristics.
Effect of Symmetry/Asymmetry of Shear Rotation of a Plasma Column in a Radial Electric Field on the Level of Turbulent Density Fluctuations
Authors: Karbushev Dmitry N. , Chirkov Alexei Yu.
Published: April 2023

The influence of the properties of the profile of a radial static electric field E(r) on the evolution of an unstable ion temperature–gradient (ITG) drift wave in a nonuniformly rotating plasma column in a magnetic field is studied. The effect of symmetry on the decrease in the level of turbulent fluctuations, which are associated with the limiting state of the ITG wave during its destruction, is discussed. The level of turbulence is estimated in the framework of approximation of finite amplitudes depending on the electric field structure. It is shown that the maximum decrease in the level of fluctuations occurs with a symmetrical configuration of the radial electric field.
Sweeping Surfaces Due to Conjugate Bishop Frame in 3-Dimensional Lie Group
Authors: Al-Jedani Awatif , Abdel-Baky Rashad
Published: April 2023

In this work, we present a new Bishop frame for the conjugate curve of a curve in the 3-dimensional Lie group G3. With the help of this frame, we derive a parametric representation for a sweeping surface and show that the parametric curves on this surface are curvature lines. We then examine the local singularities and convexity of this sweeping surface and establish the sufficient and necessary conditions for it to be a developable ruled surface. Additionally, we provide detailed explanations and examples of its applications.
A New Approach for Stabilization Criteria of n-Order Function Differential Equation by Distributed Control Function
Authors: Volinsky Irina
Published: April 2023

In the current paper, we demonstrate a new approach for an stabilization criteria for n-order functional-differential equation with distributed feedback control in the integral form. We present a correlation between the order of the functional-differential equation and degree of freedom of the distributed control function. We present two cases of distributed control function in the integral form. Such a case of stabilization control functions plays a very important role in physics, aeronautics, aerospace, ship navigation and traffic network control management. Structure of functional-differential equations is based on the symmetry properties.
BEM-SM: A BERT-Encoder Model with Symmetry Supervision Module for Solving Math Word Problem
Authors: Zhang Yijia , Zhang Tiancheng , Xie Peng , Yu Minghe , Yu Ge
Published: April 2023

In order to find solutions to math word problems, some modules have been designed to check the generated expressions, but they neither take into account the symmetry between math word problems and their corresponding mathematical expressions, nor do they utilize the efficiency of pretrained language models in natural language understanding tasks. Anyway, designing fine-tuning tasks for pretrained language models that encourage cooperation with other modules to improve the performance of math word problem solvers is an unaddressed problem. To solve these problems, in this paper we propose a BERT-based model for solving math word problems with a supervision module. Based on pretrained language models, we present a fine-tuning task to predict the number of different operators in the expressions to learn the potential relationships between the problems and the expressions. Meanwhile, a supervision module is designed to check the incorrect expressions generated and improve the model’s performance by optimizing the encoder. A series of experiments are conducted on three datasets, and the experimental results demonstrate the effectiveness of our model and its component’s designs.
Some Identities with Multi-Generalized q-Hyperharmonic Numbers of Order r
Authors: Chen Zhihua , Ömür Neşe , Koparal Sibel , Khan Waseem Ahmad
Published: April 2023

The main purpose of this paper is to define multiple alternative q-harmonic numbers, Hnk;q and multi-generalized q-hyperharmonic numbers of order r, Hnrk;q by using q-multiple zeta star values (q-MZSVs). We obtain some finite sum identities and give some applications of them for certain combinations of q-multiple polylogarithms Liq;k1,k2,…,kdt1,t2,…,td with the help of generating functions. Additionally, one of the applications is the sum involving q-Stirling numbers and q-Bernoulli numbers.
Photovoltaic Inverter Reliability Study through SiC Switches Redundant Structures
Authors: Villanueva Ignacio , Vázquez Nimrod , Vaquero Joaquín , Hernández Claudia , López-Tapia Héctor , Osorio-Sánchez Rene
Published: April 2023

Reliability is a very important issue in power electronics; however, sometimes it is not considered, studied, or analyzed. At present, renewables have become more popular, and more complex setups are required to drive this type of system. In the specific case of inverters in photovoltaic systems, the user’s safety, quality, reliability, and the system’s useful life must be guaranteed. In this paper, the reliability of a full bridge inverter is predicted by calculating metrics such as failure rates and Mean Time Between Failures. Reliability is obtained using different types of structures for SiC MOSFETs: serial systems, active parallel redundant systems, and passive parallel redundant systems. Finally, the reliability study shows that a system with a passive parallel redundant structure is more reliable and has a higher useful life compared to the other structures.
Comparative Aspects of Ricin Toxicity by Inhalation
Authors: Stoll Alexander , Shenton Daniel P. , Green A. Christopher , Holley Jane L.
Published: April 2023

The pathogenesis of ricin toxicity following inhalation has been investigated in many animal models, including the non-human primate (predominantly the rhesus macaque), pig, rabbit and rodent. The toxicity and associated pathology described in animal models are broadly similar, but variation appears to exist. This paper reviews the published literature and some of our own unpublished data and describes some of the possible reasons for this variation. Methodological variation is evident, including method of exposure, breathing parameters during exposure, aerosol characteristics, sampling protocols, ricin cultivar, purity and challenge dose and study duration. The model species and strain used represent other significant sources of variation, including differences in macro- and microscopic anatomy, cell biology and function, and immunology. Chronic pathology of ricin toxicity by inhalation, associated with sublethal challenge or lethal challenge and treatment with medical countermeasures, has received less attention in the literature. Fibrosis may follow acute lung injury in survivors. There are advantages and disadvantages to the different models of pulmonary fibrosis. To understand their potential clinical significance, these factors need to be considered when choosing a model for chronic ricin toxicity by inhalation, including species and strain susceptibility to fibrosis, time it takes for fibrosis to develop, the nature of the fibrosis (e.g., self-limiting, progressive, persistent or resolving) and ensuring that the analysis truly represents fibrosis. Understanding the variables and comparative aspects of acute and chronic ricin toxicity by inhalation is important to enable meaningful comparison of results from different studies, and for the investigation of medical countermeasures.
Pathophysiological and Clinical Significance of Crotalus durissus cascavella Venom-Induced Pulmonary Impairment in a Murine Model
Authors: Figueiredo Ricardo G. , Guerreiro Marcos Lázaro da Silva , Azevedo Elen , de Moura Mateus Souza , Trindade Soraya Castro , de Bessa José , Biondi Ilka
Published: April 2023

Crotalus venom has broad biological activity, including neurotoxic, myotoxic, hematologic, and cytotoxic compounds that induce severe systemic repercussions. We evaluated the pathophysiological and clinical significance of Crotalus durissus cascavella (Cdc) venom-induced pulmonary impairment in mice. We conducted a randomized experimental study, involving 72 animals intraperitoneally inoculated with saline solution in the control group (CG), as well as venom in the experimental group (EG). The animals were euthanized at predetermined intervals (1 h, 3 h, 6 h, 12 h, 24 h, and 48 h), and lung fragments were collected for H&E and Masson histological analysis. The CG did not present inflammatory alterations in pulmonary parenchyma. In the EG, interstitial and alveolar swelling, necrosis, septal losses followed by alveolar distensions, and areas of atelectasis in the pulmonary parenchyma were observed after three hours. The EG morphometric analysis presented pulmonary inflammatory infiltrates at all time intervals, being more significant at three and six (p = 0.035) and six and 12 h (p = 0.006). The necrosis zones were significant at intervals of one and 24 h (p = 0.001), one and 48 h (p = 0.001), and three and 48 h (p = 0.035). Crotalus durissus cascavella venom induces a diffuse, heterogeneous, and acute inflammatory injury in the pulmonary parenchyma, with potential clinical implications for respiratory mechanics and gas exchange. The early recognition and prompt treatment of this condition are essential to prevent further lung injury and to improve outcomes.
Solar Sail Trajectories to Earth’s Trojan Asteroids
Authors: Quarta Alessandro A. , Mengali Giovanni
Published: April 2023

The recent discovery of Earth’s second Trojan asteroid (2020 XL5), which will remain in the vicinity of the Sun–[Earth+Moon] triangular Lagrangian point L4 for at least 4000 years, has attracted the attention of the scientific community as a remarkable example of those elusive objects that are the witnesses of the first phase of our Solar System. The possibility that an Earth’s Trojan asteroid (ETa) may represent a pristine record of the initial conditions of the Solar System formation makes these small objects an interesting target for a robotic exploration mission. This paper analyzes orbit-to-orbit Earth–ETa transfer trajectories of an interplanetary spacecraft propelled by a solar sail. In the last decade, some pioneering space missions have confirmed the feasibility and potentiality of the solar sail concept as a propellantless propulsion system able to convert the solar radiation pressure in a continuous thrust by means of a large, lightweight and highly reflective surface. Using the state-of-the-art level of solar sail technology, this paper studies the performance of a solar-sail-based transfer trajectory toward an ETa from an optimal viewpoint and with a parametric approach.
Canine Parvovirus in Turkey: First Whole-Genome Sequences, Strain Distribution, and Prevalence
Authors: Temizkan Mehmet Cevat , Sevinc Temizkan Secil
Published: April 2023

Canine parvovirus (CPV) is a significant pathogenic virus with up to 100% morbidity and 91% mortality rates, especially in unvaccinated puppies. The emergence of new strains, interspecies transmission, and vaccine effectiveness can be enabled by just a few base changes in the CPV genome. Therefore, to cope with CPV disease, it is important to identify the viral agent and regularly monitor vaccine effectiveness against new strains. The present study has investigated CPV’s genetic profile in Turkey by collecting 80 samples from dogs in Turkey between 2020 and 2022. These samples and all sequences previously studied for CPV in Turkey were analyzed for whole-genome sequences, nationwide strain distribution over the two years, and the central Turkey prevalence rate. Next-generation sequencing was used for the genome study, Sanger sequencing for strain detection, and PCR for the prevalence analyses. The CPV-2 variants circulating in Turkey form their own cluster while being closely related to Egypt variants. Substantial amino acid changes were detected in antigenically important regions of the VP2 gene. Moreover, CPV-2b has become the most frequent genotype in this region, while the incidence of CPV-2c is predicted to increase gradually over the coming years. The prevalence of CPV in central Turkey was 86.27%. This study thus provides powerful insights to further our understanding of CPV’s genetic profile in Turkey and suggests that up-to-date vaccination efficacy studies are urgently needed.
Revision of Cytomegalovirus Immunoglobulin M Antibody Titer Cutoff in a Maternal Antibody Screening Program in Japan: A Cohort Comparison Involving a Total of 32,000 Pregnant Women
Authors: Kitamura Asa , Toriyabe Kuniaki , Hagimoto-Akasaka Miki , Hamasaki-Shimada Kyoko , Ikejiri Makoto , Minematsu Toshio , Suga Shigeru , Kondo Eiji , Kihira Masamichi , Morikawa Fumihiro , Ikeda Tomoaki
Published: April 2023

Cytomegalovirus (CMV) is associated with congenital infections. We aimed to validate the revised CMV immunoglobulin (Ig) M titer cutoff for IgG avidity measurements as a reflex test in maternal screening to identify women with primary CMV infection and newborn congenital cytomegalovirus (cCMV). We screened maternal CMV antibodies (the Denka assay) in Japan, from 2017 to 2019, using a revised IgM cutoff (≥4.00 index). Participants were tested for IgG and IgM antibodies, and for IgG avidity if IgM levels exceeded the cutoff. We compared these with corresponding results from 2013 to 2017 based on the original cutoff (≥1.21) and recalculated using the revised cutoff. Newborn urine CMV DNA tests were performed for women with low avidity (≤35.0%). Among 12,832 women screened in 2017–2019, 127 (1.0%) had IgM above the revised cutoff. Thirty-five exhibited low avidity, and seven infants developed cCMV. Of 19,435 women screened in 2013–2017, 184 (1.0%) had IgM above the revised cutoff, 67 had low avidity, and 1 had cCMV. The 2017–2019 results were not significantly different from the 2013–2017 results. The revised IgM cutoff improves maternal screening in identifying primary infection and newborn cCMV; however, further study related to other assays than Denka is required.
Efficacy of Plant-Made Human Recombinant ACE2 against COVID-19 in a Golden Syrian Hamster Model
Authors: Kim Choon-Mee , Kim Dong-Min , Bang Mi-Seon , Seo Jun-Won , Kim Da-Young , Yun Na-Ra , Lim Sung-Chul , Lee Ju-Hyung , Sohn Eun-Ju , Kang Hyangju , Min Kyungmin , Choi Bo-Hwa , Lee Sangmin
Published: April 2023

Coronavirus disease 2019 (COVID-19) is a novel infectious respiratory disease caused by SARS-CoV-2. We evaluated the efficacy of a plant-based human recombinant angiotensin-converting enzyme 2 (hrACE2) and hrACE2-foldon (hrACE2-Fd) protein against COVID-19. In addition, we analyzed the antiviral activity of hrACE2 and hrACE2-Fd against SARS-CoV-2 using real-time reverse-transcription PCR and plaque assays. The therapeutic efficacy was detected using the Golden Syrian hamster model infected with SARS-CoV-2. Both hrACE2 and hrACE2-Fd inhibited SARS-CoV-2 by 50% at concentrations below the maximum plasma concentration, with EC50 of 5.8 μg/mL and 6.2 μg/mL, respectively. The hrACE2 and hrACE2-Fd injection groups showed a tendency for decreased viral titers in nasal turbinate tissues on day 3 after virus inoculation; however, this decrease was not detectable in lung tissues. Histopathological examination on day 9 after virus inoculation showed continued inflammation in the SARS-CoV-2 infection group, whereas decreased inflammation was observed in both the hrACE2 and hrACE2-Fd injection groups. No significant changes were observed at other time points. In conclusion, the potential therapeutic efficacy of plant-based proteins, hrACE2 and hrACE2-Fd, against COVID-19 was confirmed in a SARS-CoV-2-inoculated Golden Syrian hamster model. Further preclinical studies on primates and humans are necessary to obtain additional evidence and determine the effectiveness of these therapies.
Nationwide Laboratory Surveillance of Progressive Multifocal Leukoencephalopathy in Japan: Fiscal Years 2011–2020
Authors: Nakamichi Kazuo , Miura Yoshiharu , Shimokawa Toshio , Takahashi Kenta , Suzuki Tadaki , Funata Nobuaki , Harada Masafumi , Mori Koichiro , Sanjo Nobuo , Yukitake Motohiro , Takahashi Kazuya , Hamaguchi Tsuyoshi , Izaki Shoko , Oji Satoru , Nakahara Jin , Ae Ryusuke , Kosami Koki , Nukuzuma Souichi , Nakamura Yosikazu , Nomura Kyoichi , Kishida Shuji , Mizusawa Hidehiro , Yamada Masahito , Takao Masaki , Ebihara Hideki , Saijo Masayuki
Published: April 2023

Progressive multifocal leukoencephalopathy (PML) is a devastating demyelinating disease caused by JC virus (JCV), predominantly affecting patients with impaired cellular immunity. PML is a non-reportable disease with a few exceptions, making national surveillance difficult. In Japan, polymerase chain reaction (PCR) testing for JCV in the cerebrospinal fluid (CSF) is performed at the National Institute of Infectious Diseases to support PML diagnosis. To clarify the overall profile of PML in Japan, patient data provided at the time of CSF-JCV testing over 10 years (FY2011–2020) were analyzed. PCR testing for 1537 new suspected PML cases was conducted, and 288 (18.7%) patients tested positive for CSF-JCV. An analysis of the clinical information on all individuals tested revealed characteristics of PML cases, including the geographic distribution, age and sex patterns, and CSF-JCV-positivity rates among the study subjects for each type of underlying condition. During the last five years of the study period, a surveillance system utilizing ultrasensitive PCR testing and widespread clinical attention to PML led to the detection of CSF-JCV in the earlier stages of the disease. The results of this study will provide valuable information not only for PML diagnosis, but also for the treatment of PML-predisposing conditions.
Exploring the Pattern of Immunization Dropout among Children in India: A District-Level Comparative Analysis
Authors: Dhalaria Pritu , Kapur Sanjay , Singh Ajeet Kumar , Priyadarshini Pretty , Dutta Mili , Arora Himanshu , Taneja Gunjan
Published: April 2023

The dropout rate is one of the determinants of immunization coverage and program performance, program continuity, and follow-up. The dropout rate refers to the proportion of vaccine recipients who did not finish their vaccination schedules, and it is determined by comparing the number of infants who started the schedule to the number who completed it. It is the rate difference between the first and final dosage or the rate difference between the first vaccination and the last vaccine dropout; thus, it denotes that the first recommended dose of vaccine was received, but that the subsequently recommended dose was missed. In India, immunization coverage has shown significant improvements over the last two decades, but full immunization coverage has remained stagnant at 76.5%, of which 19.9% are partially immunized, and 3.6% are children who have been left out. In India, the Universal Immunization Programme (UIP) is challenged with cases related to dropout in immunization. Although immunization coverage in India is improving, the program is challenged by vaccination dropouts. This study provides an analysis of the determinants of vaccination dropout in India using data from two rounds of the National Family Health Survey. The finding shows that the mother’s age, education, family wealth, antenatal care visit, and place of delivery were some of the variables that significantly contributed to reducing the dropout rate of immunization among children. The findings of this paper show that the dropout rate has reduced over a certain period of time. The overall improvement in the rates of dropout and increase in full immunization coverage could be attributed to various policy measures taken in the last decade in India, which brought structural changes with a positive impact on full immunization coverage and its components.
Histopathological Analysis of Selected Organs of Rats with Congenital Babesiosis Caused by Babesia microti
Authors: Jasik Krzysztof , Kleczka Anna , Filipowska Sandra
Published: April 2023

Babesiosis is a tick-borne disease with an increasing number of cases each year. Due to the non-specific symptoms of babesiosis, insightful analyses of the pathogenesis of babesiosis are still very important. Transmission of the disease occurs in a few ways, which makes laboratory diagnosis of piroplasmosis important. Complications associated with the infection can be tragic, especially in patients with immunological disorders. The aim of this study was the histopathological analysis of the spleen and kidney of young Wistar rats infected transplacentally with Babesia microti. Female rats were infected with a reference strain of B. microti (ATCC 30221), and then, birth 3-week-old males were euthanized with isoflurane. Subsequently, the material was collected at autopsy for microscopic and ultrastructural examination. Microscopic and ultrastructural analysis of the spleen and kidney showed degenerative changes within the organ parenchyma and the capsules surrounding the organ. Regenerative and reparative changes through mitotic divisions of parenchymal cells were also evident. Merozoites of B. microti were visible in the section of erythrocytes and the cells building the organ stroma. The results presented in this study proved the negative effects of B. microti on cells and tissues in rats with congenital babesiosis.
Urinary Proteins of Female Domestic Dog (Canis familiaris) during Ovarian Cycle
Authors: Woszczyło Martyna , Pasikowski Paweł , Devaraj Sankarganesh , Kokocińska Agata , Szumny Antoni , Skwark Marcin J. , Niżański Wojciech , Dzięcioł Michał
Published: April 2023

The presence and identity of non-volatile chemical signals remain elusive in canines. In this study, we aim to evaluate the urinary proteins of female domestic dogs in the estrus and anestrus phases to evidence the presence of non-volatile chemical signals and to elucidate their identities. We collected urine samples from eight female dogs in the estrus and anestrus phases. A total of 240 proteins were identified in the urine samples using liquid chromatography–mass spectrometry (LC–MS analysis). The comparison of the proteins revealed a significant difference between the estrus and anestrus urine. We identified proteins belonging to the lipocalin family of canines (beta-lactoglobulin-1 and beta-lactoglobulin-2, P33685 and P33686, respectively), one of whose function was the transport of pheromones and which was present only in the estrus urine samples. Moreover, proteins such as Clusterin (CLU), Liver-expressed antimicrobial peptide 2 (LEAP2), and Proenkephalin (PENK) were more abundant in the estrus urine when compared to the anestrus urine. LEAP2 was recently described as a ghrelin receptor antagonist and implicated in regulating food intake and body weight in humans and mice. Proenkephalin, a polypeptide hormone cleaved into opioid peptides, was also recognized as a candidate to determine kidney function. As of yet, none of these have played a role in chemical communication. Clusterin, an extracellular chaperone protecting from protein aggregation implicated in stress-induced cell apoptosis, is a plausible candidate in chemical communication, which is a claim that needs to be ascertained further. Data are available via ProteomeXchange with the identifier PXD040418.
Knowledge and Practices of Cypriot Bovine Farmers towards Effective and Safe Manure Management
Authors: Christophe Soteris , Pentieva Kristina , Botsaris George
Published: April 2023

Manure from bovine farms is commonly used as an organic fertiliser. However, if not properly managed, it can spread significant biological and chemical hazards, threatening both human and animal health. The effectiveness of risk control hugely relies on farmers’ knowledge regarding safe manure management and on the application of suitable management practices. This study aims to evaluate the knowledge and practices of Cypriot bovine farmers towards safer manure management, from its generation to its final use, in line with the One Health approach. Factors affecting farmers’ knowledge and applied practices are also investigated through a questionnaire survey. The questionnaire was developed and sent to all eligible bovine farmers in Cyprus (n = 353), and 30% (n = 105) of them returned the completed questionnaire. Results revealed there are some gaps in farmers’ knowledge. The use of manure for fertilising crops dominated. Only half of the farmers stored manure in appropriate facilities, with 28.5% of them using a dedicated area with cement floors and 21.5% utilising leakproof tanks. The majority (65.7%) stored manure for more than three months before its use as a fertiliser in a dried form. In multiple regression analysis, education level and farming purpose were significant determinants of farmer knowledge. In conclusion, Cypriot farmers’ knowledge must be reinforced to ensure proper manure management. The results highlight the importance of providing relevant training to farmers. Although the current practices partially decrease manure pathogens, interventions to promote the use of more effective treatment methods, such as biogas transformation and composting, would be beneficial.
Static Terrestrial Laser Scanning (TLS) for Heritage Building Information Modeling (HBIM): A Systematic Review
Authors: Liu Junshan , Azhar Salman , Willkens Danielle , Li Botao
Published: April 2023

Heritage Building Information Modeling (HBIM) is an essential technology for heritage documentation, conservation, and management. It enables people to understand, archive, advertise, and virtually reconstruct their built heritage. Creating highly accurate HBIM models requires the use of several reality capture tools, such as terrestrial laser scanning (TLS), photogrammetry, unmanned aerial vehicles (UAV), etc. However, the existing literature did not explicitly review the applications and impacts of TLS in implementing HBIM. This paper uses the PRISMA protocol to present a systematic review of TLS utilization in capturing reality data in order to recognize the status of applications of TLS for HBIM and identify the knowledge gaps on the topic. A thorough examination of the 58 selected articles revealed the state-of-the-art practices when utilizing static TLS technology for surveying and processing captured TLS data for developing HBIM models. Moreover, the absence of guidelines for using static TLS surveys for HBIM data acquisition, the lack of robust automated frameworks for producing/transferring 3D geometries and their attributes from TLS data to BIM entities, and the under-utilized application of TLS for long-term monitoring and change detection were identified as gaps in knowledge. The findings of this research provide stakeholders with a good grasp of static TLS for HBIM and therefore lay the foundation for further research, strategies, and scientific solutions for improving the utilization of TLS when documenting heritage structures and developing HBIM.
On ST6 Source Terms Model Assessment and Alternative
Authors: Pushkarev Andrei , Geogjaev Vladimir , Zakharov Vladimir
Published: April 2023

We present the study of the ST6 balanced set of wind energy input and wave energy dissipation due to wave breaking source terms, offered as the option in operational wave forecasting models and based on theoretical self-similarity analysis and numerical simulation of the wave energy radiative transfer equation. The study relies on the classical limited fetch wind wave excitation problem with constant wind blowing orthogonally to the shoreline toward the open ocean. It is found that the ST6 model exhibits asymptotic quasi self-similar behavior for fetches exceeding ≃25 km, as well as non-universal wave energy growth for shorter fetches, depending on the shoreline wave energy levels. We construct the alternative model PGZ-2 from a self-similar consideration, which reproduces field experimental data almost in the whole fetch span and reduces wave energy evolution dependence on the shoreline energy level. We assert that the PGZ-2 model is more accurate than the ST6 model. Moreover, it has a wider area of applicability.
Research on the Tolerance and Degradation of o-Cresol by Microalgae
Authors: Han Guangshuo , Ma Longtan , Zhang Caisong , Wang Baihui , Sheng Xianghao , Wang Zhongpeng , Wang Xiuju , Wang Liguo
Published: April 2023

o-Cresol shows high toxicity and stability. To explore a better degradation method of o-cresol, the degradation of o-cresol by three kinds of microalgae (Selenastrum capricornutum, Scenedesmus obliquus, and Microcystis aeruginosa) was researched in this paper. The growth status and degradation rate were used to reflect the tolerance and degradation effect of microalgae. The effects of the medium’s initial pH, microalgal density, and different exogenous pollutants on the degradation of o-cresol by Selenastrum capricornutum were investigated. The results showed that Selenastrum capricornutum had the best degradation effect on o-cresol. microalgal density increased after adaptation to different concentrations of o-cresol for some time. At pH 7.0 as the initial condition, the microalgal exhibited the best results of degradation. When the microalgal density OD680 was 0.20, o-cresol was the first to be completely degraded within 5 days. At higher initial concentrations of o-cresol, the microalgae preferentially degraded glucose to promote the growth of the microalgae under mixotrophic cultivation. Selenastrum capricornutum could degrade phenol and o-cresol at the same time, and the degradation was completed within 8 days when the initial concentration of o-cresol and phenol were 100 and 120 mg/L. It was proven that the degradation of o-cresol by Selenastrum capricornutum is feasible under suitable conditions.
Evaluation of the Effect of WRF Physical Parameterizations on Typhoon and Wave Simulation in the Taiwan Strait
Authors: Luo Chenghan , Shang Shaoping , Xie Yanshuang , He Zhigang , Wei Guomei , Zhang Feng , Wang Lei
Published: April 2023

Typhoons and typhoon waves can cause disasters in coastal areas around the world. The Taiwan Strait often experiences typhoons, especially in summer. Numerical models have been adopted to predict typhoons and reduce losses. The Weather Research and Forecasting (WRF) model is widely used in typhoon simulations, and the Simulating WAves Nearshore (SWAN) model performs well in wave simulations. However, significant uncertainty remains in terms of choosing suitable WRF physical parameterizations in different situations. To evaluate the effect of WRF physical parameterizations on wind and wave simulations, 27 simulation experiments were designed. Three typhoon events (Goni, Dujuan, and Meranti) with different tracks that influenced the Taiwan Strait were simulated. Three parameters (wind speed, wind direction and significant wave height) were assessed using Taylor diagrams, and it was found that the best simulation experiment changed according to typhoon tracks and physical parameters. In wind speed simulation, the best simulation experiment is 12 for typhoon Dujuan and 19 for typhoon Goni and Meranti. From the perspective of wind direction simulation, experiments 26, 23, and 2 performed best for typhoons Goni, Dujuan, and Meranti. And experiments 19, 1, and 20 had the best performances in significant wave height simulation for typhoons Goni, Dujuan, and Meranti. The WRF-SWAN model using the best simulation experiment reduced the error and exhibited good performance in the wind and wave simulations. Skill scores of three parameters were all over 70 for typhoon Goni and 80 for typhoon Dujuan and Meranti. The applicability of the best simulation experiments was demonstrated in typhoon simulations with similar tracks. The accuracy of the wave simulation depended on wind speed, wind direction, and their interaction. In addition, a scheme’s sensitivity changed with different typhoon tracks. This study provides references for designing physical parameterizations for use with the WRF-SWAN model, which may help to simulate typhoons and typhoon waves in the Taiwan Strait more accurately in the future.
State Selection and Cost Estimation for Deep Reinforcement Learning-Based Real-Time Control of Urban Drainage System
Authors: Tian Wenchong , Xin Kunlun , Zhang Zhiyu , Liao Zhenliang , Li Fei
Published: April 2023

In recent years, a real-time control method based on deep reinforcement learning (DRL) has been developed for urban combined sewer overflow (CSO) and flooding mitigation and is more advantageous than traditional methods in the context of urban drainage systems (UDSs). Since current studies mainly focus on analyzing the feasibility of DRL methods and comparing them with traditional methods, there is still a need to optimize the design and cost of DRL methods. In this study, state selection and cost estimation are employed to analyze the influence of the different states on the performance of DRL methods and provide relevant suggestions for practical applications. A real-world combined UDS is used as an example to develop DRL models with different states. Their control effect and data monitoring costs are then compared. According to the results, the training process for DRL is difficult when using fewer nodes information or water level as the input state. Using both upstream and downstream nodes information as input improves the control effect of DRL. Also, using the information on upstream nodes as the input state is more effective than using downstream nodes; using flow as input is more likely to have a better control effect than using water level, while using both flow and water level cannot significantly further improve the control effect. Because the cost of flow monitoring is higher than water level monitoring, the number of monitoring nodes and the use of flow/water level need to be balanced based on cost-effectiveness.
Mapping Specific Constituents of an Ochre-Coloured Watercourse Based on In Situ and Airborne Hyperspectral Remote Sensing Data
Authors: Ulrich Christoph , Hupfer Michael , Schwefel Robert , Bannehr Lutz , Lausch Angela
Published: April 2023

It is a well-known fact that water bodies are crucial for human life, ecosystems and biodiversity. Therefore, they are subject to regulatory monitoring in terms of water quality. However, land-use intensification, such as open-cast mining activities, can have a direct impact on water quality. Unfortunately, in situ measurements of water quality parameters are spatially limited, costly and time-consuming, which is why we proposed a combination of hyperspectral data, in situ data and simple regression models in this study to estimate and thus monitor various water quality parameters. We focused on the variables of total iron, ferrous iron, ferric iron, sulphate and chlorophyll-a. Unlike other studies, we used a combination of airborne hyperspectral and RGB data to ensure a very high spatial resolution of the data. To investigate the potential of our approach, we conducted simultaneous in situ measurements and airborne hyperspectral/RGB aircraft campaigns at different sites of the Spree River in Germany to monitor the impact of pyrite weathering on water bodies after open-cast mining activities. Appropriate regression models were developed to estimate the five variables mentioned above. The model with the best performance for each variable gave a coefficient of determination R2 of 64% to 79%. This clearly shows the potential of airborne hyperspectral/RGB data for water quality monitoring. In further investigations, we focused on the use of machine learning techniques, as well as transferability to other water bodies. The approach presented here has great potential for the development of a monitoring method for the continuous monitoring of still waters and large watercourses, especially given the freely available space-based hyperspectral missions via EnMAP.