bluuebunny/crossref_metadata_2025 huggingface dataset:
Role of Digital Transformation on Carbon Performance: Evidence from Firm-Level Analysis in China
Authors: Guo Borui , Huang Xiaoxia
Published: September 2023

The continuous proliferation of the global digital wave has increased the contribution of firms’ digital transformation as a vital force propelling economic growth and sustainable development, highlighting the importance of digital transformation and the environment. However, only limited studies focused on how digital transformation influences carbon performance. To fill in this gap, this study investigates the impact of digital transformation on corporate carbon performance using a sample of 2286 Chinese A-share listed firms from 2008 to 2020 and employs the ordinary least squares (OLS) model as the principal research methodology. According to the results, the adoption of digital transformation strategies by firms exhibits a notable capacity to enhance carbon performance, which holds after a series of robustness tests. Green technology innovation and total factor productivity exhibit a partially mediating influence on the relationship between digital transformation and carbon performance. Further analyses reveal that enhanced green management practices and government subsidies have the potential to further amplify this positive effect. However, the impact is diminished by financing constraints and political connections. The findings of this research hold significance for firms striving for sustainable development within the era.
Benefits of Adopting Innovation and Sustainability Practices in Project Management within the SME Context
Authors: Lima Orlando , Fernandes Gabriela , Tereso Anabela
Published: September 2023

The economic activity of Small and Medium-Sized Enterprises (SMEs) has become increasingly project-oriented. Given SMEs’ significant role in promoting social and economic well-being, Project Management (PM) has emerged as a crucial tool for fostering innovation and sustainability within these companies and society as a whole. However, there is a gap in the existing literature concerning identifying practices that ensure innovation and sustainability throughout PM within SMEs and the associated benefits of adopting these practices. To address this gap, a comprehensive Systematic Literature Review (SLR) was conducted, gathering articles from reputable databases such as Scopus and Web of Science. In addition, this study seeks to explore the practical, political, and theoretical implications of these findings. The review identified 166 innovation practices, 86 sustainability practices, and 61 benefits, which were categorized based on their primary subject areas. The results of this study contribute to both the academic and practical understanding of the interplay between PM, innovation, and sustainability in SMEs. By identifying these practices and associated benefits, this research provides valuable insights for practitioners and policymakers, enabling them to foster innovation and sustainability within SMEs. In conclusion, this research fills a critical gap in the literature by providing an in-depth analysis of innovation and sustainability practices in the context of PM in SMEs. Also, it identifies that the benefits of adopting these practices extend well beyond economic considerations. The practical, political, and theoretical implications of these findings underscore the importance of integrating PM, innovation, and sustainability for the overall well-being of SMEs and society.
Biodiesel Production through Rhodotorula toruloides Lipids and Utilization of De-Oiled Biomass for Congo Red Removal
Authors: Almuhayawi Mohammed S. , Hassan Elhagag A. , Almasaudi Saad , Zabermawi Nidal , Azhar Esam I. , Najjar Azhar , Alkuwaity Khalil , Abujamel Turki S. , Alamri Turki , Harakeh Steve
Published: September 2023

The current study aimed to investigate the potentiality of yeast isolate Rhodotorula toruloides Y1124 to be used as a feedstock for biodiesel production, and the reutilization of the de-oiled yeast biomass wastes as a biosorbent for the biosorption of Congo red from aquatic solutions was investigated. From screening results, eight yeast isolates were referred to as oleaginous microorganisms, of which yeast isolate Rhodotorula toruloides Y1124 was the highest lipid-accumulating isolate and was used as a feedstock for biodiesel production. The highest lipid accumulation (64.8%) was significantly dependent on the glucose concentration, pH, and incubation temperature according to Plackett–Burman and central composite design results. Under optimized conditions, the estimated amount of biodiesel synthesis from Rhodotorula toruloides biomass represented 82.12% of total analytes. The most prevalent fatty acid methyl esters were hexadecanoic and 11-octadecenoic, comprising 30.04 and 39.36% of total methyl esters which were compatible with plant oils. The optimum biosorption conditions for Congo red removal were pH 6, a 15 min contact time, and an initial dye concentration of 40 mg L−1. The biosorption isothermal and kinetics fitted well with the Langmuir model and the maximal biosorption capacity (qmax) was 81.697 mg g−1. Therefore, the current study may offer a sustainable feedstock with potential viability for both the synthesis of biodiesel and the removal of organic dyes.
The Spread of MaaS Initiatives in Europe: The Leading Role of Public Governance Emerging from an Italian Regional Application
Authors: Caballini Claudia , Olivari Erika , Gasparini Carlotta , Dalla Chiara Bruno
Published: September 2023

Mobility as a service (MaaS) is a promising lever to achieve a more sustainable, co-modal, and flexible urban system for daily mobility. MaaS is crucial to addressing the challenges imposed by hyper-urbanization, social changes, saturation of public soil with private motor vehicles, and local and global environmental issues. The aim of this paper is to analyse important characteristics of MaaS, namely public governance, regional scale, and high level of development. A total of 13 MaaS initiatives implemented in some European cities were compared using multi-criteria analysis. The results show that, although the MaaS implementation process is faster for private initiatives, public governance is shown to be the most appropriate entity to develop stable MaaS services, as it can enable the achievement of a higher level of integration, coupled with a high rate of service adoption, as well as reduce market entry barriers for service providers while also guaranteeing fair competition, and consequently fostering a higher level of service provided to users. The regional coverage of MaaS is crucial to ensure service provision to a wider population, living in both metropolitan and rural areas. These important features are included in the BIPforMaaS project run by the Italian region of Piedmont, described in detail in this paper.
A Constitutive Model Study of Chemical Corrosion Sandstone Based on Support Vector Machine and Artificial Bee Colony Algorithm
Authors: Lin Yun , Li Chong , Zhou Keping , Guo Zhenghai , Zang Chuanwei
Published: September 2023

The mechanical characteristics of rock are greatly influenced by hydrochemical corrosion. The chemical corrosion impact and deformation properties of the meso-pore structure of rock under the action of different hydrochemical solutions for the stability evaluation of rock mass engineering are of high theoretical relevance and applied value. Based on actual data, a support vector machine (SVM) rock constitutive model based on artificial bee colony algorithm (ABC) optimization is constructed in this article. The impact of porosity (chemical deterioration), confining pressure, and other aspects is thoroughly examined. It is used to mimic the triaxial mechanical behavior of rock under various hydration conditions, with high nonlinear prediction ability. Simultaneously, the statistical damage constitutive model and the ABC-SVM constitutive model are used to forecast the sample’s stress–strain curve and compare it to the experimental data. The two models’ correlation coefficients (R2), root mean square error (RMSE), and mean absolute percentage error (MAPE) are computed and examined. The correlation coefficient between the ABC-SVM constitutive model calculation results and the experimental results is found to be larger (R2 = 0.998), and the error is smaller (RMSE = 0.7730, MAPE = 1.51), indicating that it has better prediction performance on the conventional triaxial constitutive relationship of rock. It is a highly promising new way of describing the rock’s constitutive connection.
South African Postgraduate STEM Students’ Use of Mobile Digital Technologies to Facilitate Participation and Digital Equity during the COVID-19 Pandemic
Authors: Singh-Pillay Asheena
Published: September 2023

The transition to online mobile teaching and learning during the COVID-19 pandemic required more than access to mobile digital technologies, particularly in South Africa, a country trying to address the injustices and inequalities of the pre-democracy period. The argument advanced in this research is that the transition to online mobile teaching and learning could be used as leverage to promote active participation, quality inclusive learning, develop relevant and responsive content and achieve mobile digital equity. This interpretative case study was conducted at a South African teacher-training institution. The primary aim of this study is to explore the following question: How did postgraduate STEM students use mobile digital technologies to facilitate teaching and learning under COVID-19 conditions? Data was obtained from 20 purposively selected postgraduate STEM students enrolled for their Bachelor of Education honours degree. They participated in online discussion forums and maintained reflective journals. Due diligence was taken to ensure all the required ethical protocols were observed. Mishra and Koehler’s Technological Pedagogical and Content Knowledge (TPACK) model framed this study. The constructs of the model were used during the analysis of data. The findings highlight that mobile digital technologies were used for translanguaging, supporting students in developing disciplinary science understanding through exposure to practical work and linking cross-cutting concepts in STEM subjects. The findings of this study are significant as they indicate how to operationalize STEM teaching in developing countries; how to address issues of access and social justice; and how to leverage mobile technologies to improve practice in STEM subjects, post-COVID.
Coal Mine Rock Burst and Coal and Gas Outburst Perception Alarm Method Based on Visible Light Imagery
Authors: Cheng Jijie , Liu Yi , Li Xiaowei
Published: September 2023

To solve the current reliance of coal mine rock burst and coal and gas outburst detection on mainly manual methods and the problem wherein it is still difficult to ensure disaster warning required to meet the needs of coal mine safety production, a coal mine rock burst and coal and gas outburst perception alarm method based on visible light imagery is proposed. Real-time video images were collected by color cameras in key areas of underground coal mines; the occurrence of disasters was determined by noting when the black area of a video image increases greatly, when the average brightness is less than the set brightness threshold, and when the moving speed of an object resulting in a large increase in the black area is greater than the set speed threshold (V > 13 m/s); methane concentration characteristics were used to distinguish rock burst and coal and gas outburst accidents, and an alarm was created. A set of disaster-characteristic simulation devices was designed. A Φ315 mm white PVC pipe was used to simulate the roadway and background equipment; Φ10 mm rubber balls were used to replace crushed coal rocks; a color camera with a 2.8 mm focal length, 30 FPS, and 110° field angle was used for image acquisition. The results of our study show that the recognition effect is good, which verifies the feasibility and effectiveness of the method.
Sample Expansion and Classification Model of Maize Leaf Diseases Based on the Self-Attention CycleGAN
Authors: Guo Hongliang , Li Mingyang , Hou Ruizheng , Liu Hanbo , Zhou Xudan , Zhao Chunli , Chen Xiao , Gao Lianxing
Published: September 2023

In order to address the limited scale and insufficient diversity of research datasets for maize leaf diseases, this study proposes a maize disease image generation algorithm based on the cycle generative adversarial network (CycleGAN). With the disease image transfer method, healthy maize images can be transformed into diseased crop images. To improve the accuracy of the generated data, the category activation mapping attention mechanism is integrated into the original CycleGAN generator and discriminator, and a feature recombination loss function is constructed in the discriminator. In addition, the minimum absolute error is used to calculate the differences between the hidden layer feature representations, and backpropagation is employed to enhance the contour information of the generated images. To demonstrate the effectiveness of this method, the improved CycleGAN algorithm is used to transform healthy maize leaf images. Evaluation metrics, such as peak signal-to-noise ratio (PSNR), structural similarity (SSIM), Fréchet inception distance (FID), and grayscale histogram can prove that the obtained maize leaf disease images perform better in terms of background and detail preservation. Furthermore, using this method, the original CycleGAN method, and the Pix2Pix method, the dataset is expanded, and a recognition network is used to perform classification tasks on different datasets. The dataset generated by this method achieves the best performance in the classification tasks, with an average accuracy rate of over 91%. These experiments indicate the feasibility of this model in generating high-quality maize disease leaf images. It not only addresses the limitation of existing maize disease datasets but also improves the accuracy of maize disease recognition in small-sample maize leaf disease classification tasks.
Air Traffic Sector Network: Motif Identification and Resilience Evaluation Based on Subgraphs
Authors: Shi Zongbei , Zhang Honghai , Li Yike , Zhou Jinlun
Published: September 2023

Air traffic control systems play a critical role in ensuring the sustainable and resilient flow of air traffic. The air traffic sector serves as a fundamental topological unit and is responsible for overseeing and maintaining the system’s sustainable operation. Examining the structural characteristics of the air traffic sector network is a useful approach to gaining an intuitive understanding of the system’s sustainability and resilience. In this paper, an air traffic sector network (ATSN) was established in mainland China using the complex network theory, and its motif characteristics were analyzed from a microscopic perspective. Additionally, subgraph resilience was defined in order to describe the network topology by analyzing changes in subgraph motif concentration and subgraph residual concentration. Our empirical findings indicated that motifs exhibit high connectivity, while anti-motifs are found in subgraph structures with low connectivity. The motif concentration of subgraphs can efficiently reflect the distribution of heterogeneous subgraph structures within a network. During the process of resilience evaluation, the subgraph motif concentration remains relatively stable but is sensitive to the transition state of the network from disturbance to recovery. The resilience of the system at the macroscopic scale is aligned with the resilience of each heterogeneous subgraph structure to some extent. Topological indicators have a more significant impact on the resilience of the ATSN than air traffic flow characteristics. This study has the outcome of uncovering the preference for connection among nodes and the rationality of sector structure delineation in ATSNs. Additionally, this research addresses the fundamental mechanism behind the network disturbance recovery process, and identifies the connection between network macro- and microstructure in the resilience process.
Identification of Risk Influential Factors for Fishing Vessel Accidents Using Claims Data from Fishery Mutual Insurance Association
Authors: Wang Fang , Du Weijie , Feng Hongxiang , Ye Yun , Grifoll Manel , Liu Guiyun , Zheng Pengjun
Published: September 2023

This research aims to identify and analyze the significant risk factors contributing to accidents involving fishing vessels, a crucial step towards enhancing safety and promoting sustainable practices in the fishing industry. Using a data-driven Bayesian network (BN) model that incorporates feature selection through the random forest (RF) method, we explore these key factors and their interconnected relationships. A review of past academic studies and accident investigation reports from the Fishery Mutual Insurance Association (FMIA) revealed 17 such factors. We then used the random forest model to rank these factors by importance, selecting 11 critical ones to build the Bayesian network model. The data-driven Bayesian network (BN) model is further utilized to delve deeper into the central factors influencing fishing vessel accidents. Upon validation, the study results show that incorporating the random forest feature selection method enhances the simplicity, reliability, and precision of the BN model. This finding is supported by a thorough performance evaluation and scenario analysis.
Research on the Influences of Task Interdependence on Team Performance in the Context of the Leader–Member Exchange Differentiation in the Public–Private Partnership Projects
Authors: Shi Shiying , Zhao Fangfang , Zhang Han , Li Hujun , Ye Xiaosu
Published: September 2023

Task interdependence is essential in sustainable cooperation, conflict prevention, and performance improvement of public–private partnership (PPP) project teams and promotes the sustainable development of PPP projects. Based on the theoretical logic of Input–Process–Output (IPO), integrating Team Process Theory and Leader–Member Exchange (LMX) Theory, we constructed a mediated model of task interdependence, team reflection, team performance, and leader–member exchange differentiation in PPP projects. Based on this, we conducted questionnaire research and research analysis on 168 PPP project teams. The results of the study indicate that task interdependence in PPP projects has a significant positive effect on team performance, and there is a significant mediating role of team reflection in the relationship between task interdependence and team performance. The leader–member exchange differentiation in teams not only moderates the relationship between task interdependence and team reflection and team reflection and team performance but also further moderates the indirect effect of task interdependence in PPP projects on team performance through team reflection. The findings extend the impact effects of task interdependence in engineering projects, as well as the moderating mechanisms of leader–member exchange differentiation in Chinese organizational scenarios, providing lessons for PPP project team performance management and sustainable development of PPP projects.
Determination of River Ecological Base Flow Based on the Coupling Relationship of Sediment–Water Quality–Biodiversity in Water Shortage Area of Northwest China
Authors: Cheng Bo , Li Huaien
Published: September 2023

Maintaining the integrity of ecosystem service functions of rivers has become the top issue in the water shortage area of Northwest China. By combining the coupling relationship of sediment, water quality, and biodiversity and the hydraulic relationship of the section, we established a quantitative calculation method for the river ecological base flow, which is mainly divided into the following three steps: first, we determined the reasonable ecological flow velocity range of rivers via water purification, maintaining the river geometry and biodiversity; second, we combined the hydraulic relationship between the river ecological velocity range and the river ecological base flow to determine the protection target of the river ecological base flow; finally, we combined the remaining water volume of rivers and ecological base flow protection target of rivers to determine their protection rate. Take the Baoji section of the Weihe River as an example: the results show that the ecological base flow in the Baoji section of the Weihe River is [6.26, 9.17 m3/s] and [32.94, 38.93 m3/s] from October of this year to May of next year and from June to September, respectively, and the protection rates of the ecological base flow for five typical years are 62.47%, 41.10%, 16.16%, 15.07%, and 10.68%. These coupling methods can also be used in the world’s river basin, which has similar problems.
A Symmetrical Fuzzy Neural Network Regression Method Coordinating Structure and Parameter Identifications for Regression
Authors: Zhang Ke , Hao Wenning , Yu Xiaohan , Shao Tianhao
Published: September 2023

Fuzzy neural networks have both the interpretability of fuzzy systems and the self-learning ability of neural networks, but they will face the challenge of “rule explosion” when dealing with high-dimensional data. Moreover, the structure and parameter identifications of models are generally performed in two stages, and this always attends to one thing and loses another in terms of interpretability and predictive performance. In this paper, a fuzzy neural network regression method (FNNR) that coordinates structure identification and parameter identification is proposed. To alleviate the problem of rule explosion, the structure identification and parameter identification are coordinated in the training process, and the numbers of fuzzy rules and fuzzy partitions are effectively limited, while the parameters of fuzzy rules are optimized. The symmetrical architecture of the FNNR is designed for automatic structure identification. An alternate training strategy is adopted by treating discrete and continuous parameters differently, and thus the convergence efficiency of the algorithm is improved. To enhance interpretability, regularized terms are designed from fuzzy rule level and fuzzy partition level to guide the model to learn fuzzy rules with simple structures and clear semantics. The experimental results show that the proposed method has both a compact structure and high precision.
Development of a Smart Metered-Dose Inhaler for Asthma Based on Computational Fluid Dynamics
Authors: Zhang Zhiguo , Wei Maoning
Published: September 2023

Asthma is a common respiratory disease with symptoms such as repeated wheezing, shortness of breath, and coughing. However, currently, asthma cannot be cured but only controlled or relieved using medication. The metered-dose inhaler (MDI) is known to lead to high deposition fractions of drug particles in the mouth and throat, resulting in inadequate drug efficacy. Therefore, herein, the factors influencing the deposition fraction of asthma drugs in the mouth and throat regions were explored by computational fluid dynamics and a smart MDI for asthma was designed. The smart MDI was designed based on the obtained simulation results, which demonstrated that the deposition fraction gradually increased from 55.78% to 65.75% with an increase in the peak inspiratory flow rate at an angle of incidence of 0°. The deposition fraction first decreased and then increased as the angle of incidence increased at a constant peak inspiratory flow rate. The deposition fraction increased as the inspiration–press interval time increased at a constant angle of incidence and peak inspiratory flow rate. Meanwhile, performance analysis of the designed smart MDI indicated that the inhaler could effectively reduce the deposition fraction of drugs in the mouth and throat regions by 17% on average.
Symmetric Graph-Based Visual Question Answering Using Neuro-Symbolic Approach
Authors: Moon Jiyoun
Published: September 2023

As the applications of robots expand across a wide variety of areas, high-level task planning considering human–robot interactions is emerging as a critical issue. Various elements that facilitate flexible responses to humans in an ever-changing environment, such as scene understanding, natural language processing, and task planning, are thus being researched extensively. In this study, a visual question answering (VQA) task was examined in detail from among an array of technologies. By further developing conventional neuro-symbolic approaches, environmental information is stored and utilized in a symmetric graph format, which enables more flexible and complex high-level task planning. We construct a symmetric graph composed of information such as color, size, and position for the objects constituting the environmental scene. VQA, using graphs, largely consists of a part expressing a scene as a graph, a part converting a question into SPARQL, and a part reasoning the answer. The proposed method was verified using a public dataset, CLEVR, with which it successfully performed VQA. We were able to directly confirm the process of inferring answers using SPARQL queries converted from the original queries and environmental symmetric graph information, which is distinct from existing methods that make it difficult to trace the path to finding answers.
Inorganic Thin-Film Solar Cells: Challenges at the Terawatt-Scale
Authors: Buonomenna Maria Giovanna
Published: September 2023

Thin-film solar cells have been referred to as second-generation solar photovoltaics (PV) or next-generation solutions for the renewable energy industry. The layer of absorber materials used to produce thin-film cells can vary in thickness, from nanometers to a few micrometers. This is much thinner than conventional solar cells. This review focuses on inorganic thin films and, therefore, hybrid inorganic–organic perovskite, organic solar cells, etc., are excluded from the discussion. Two main families of thin-film solar cells, i.e., silicon-based thin films (amorphous (a-Si) and micromorph silicon (a-Si/c-Si), and non-silicon-based thin films (cadmium telluride (CdTe) and copper–indium–gallium diselenide (CIGS)), are being deployed on a commercial scale. These commercial technologies, until a few years ago, had lower efficiency values compared to first-generation solar PV. In this regard, the concept of driving enhanced performance is to employ low/high-work-function metal compounds to form asymmetric electron and hole heterocontacts. Moreover, there are many emerging thin-film solar cells conceived to overcome the issue of using non-abundant metals such as indium (In), gallium (Ga), and tellurium (Te), which are components of the two commercial thin-film technologies, and therefore to reduce the cost-effectiveness of mass production. Among these emerging technologies are kesterite CZTSSE, intensively investigated as an alternative to CIGS, and Sb2(S,Se)3. In this review, after a general overview of the current scenario of PV, the three main challenges of inorganic thin-film solar cells, i.e., the availability of (safe) metals, power conversion efficiency (PCE), and long-term stability, are discussed.
Using Simple Interactive Technology to Help People with Intellectual and Visual Disabilities Exercise Functional Physical Responses: A Case Series Study
Authors: Lancioni Giulio E. , Alberti Gloria , Filippini Chiara , Chiariello Valeria , Singh Nirbhay N. , O’Reilly Mark F. , Sigafoos Jeff
Published: September 2023

The study assessed a new interactive technology system for helping six people with intellectual and visual disabilities exercise relevant physical responses embedded within a fairly straightforward activity (i.e., placing objects in containers). Activity responses consisted of the participants taking objects from the floor or a low shelf and placing those objects in a container high up in front of them (thus bending their body and legs and stretching their arms and hands). The technology involved a portable computer, a webcam, and three mini speakers whose basic functions included monitoring the participants’ responses, delivering preferred stimulation contingent on the responses and verbal encouragements/prompts for lack of responses, and assisting in data recording. The study was conducted following a non-concurrent multiple baseline design across participants. During baseline (i.e., when the system was used only for data recording), the participants’ mean frequency of responses per session varied between zero and nearly 12. During intervention (i.e., when the system was fully working), the participants’ mean frequency of responses per session increased to between about 34 and 59. Mean session duration varied between nearly 10 and over 14 min. The new system may be a valuable tool for supporting relevant physical activity engagement in people with intellectual and multiple disabilities.
A Hypertuned Lightweight and Scalable LSTM Model for Hybrid Network Intrusion Detection
Authors: Bibi Aysha , Sampedro Gabriel Avelino , Almadhor Ahmad , Javed Abdul Rehman , Kim Tai-hoon
Published: September 2023

Given the increasing frequency of network attacks, there is an urgent need for more effective network security measures. While traditional approaches such as firewalls and data encryption have been implemented, there is still room for improvement in their effectiveness. To effectively address this concern, it is essential to integrate Artificial Intelligence (AI)-based solutions into historical methods. However, AI-driven approaches often encounter challenges, including lower detection rates and the complexity of feature engineering requirements. Finding solutions to overcome these hurdles is critical for enhancing the effectiveness of intrusion detection systems. This research paper introduces a deep learning-based approach for network intrusion detection to overcome these challenges. The proposed approach utilizes various classification algorithms, including the AutoEncoder (AE), Long-short-term-memory (LSTM), Multi-Layer Perceptron (MLP), Linear Support Vector Machine (L-SVM), Quantum Support Vector Machine (Q-SVM), Linear Discriminant Analysis (LDA), and Quadratic Discriminant Analysis (QDA). To validate the effectiveness of the proposed approach, three datasets, namely IOT23, CICIDS2017, and NSL KDD, are used for experimentation. The results demonstrate impressive accuracy, particularly with the LSTM algorithm, achieving a 97.7% accuracy rate on the NSL KDD dataset, 99% accuracy rate on the CICIDS2017 dataset, and 98.7% accuracy on the IOT23 dataset. These findings highlight the potential of deep learning algorithms in enhancing network intrusion detection. By providing network administrators with robust security measures for accurate and timely intrusion detection, the proposed approach contributes to network safety and helps mitigate the impact of network attacks.
Functional Characterization and Toxicological Study of Proanthocyanidins in Weaned Pigs
Authors: Liu Jiahao , Qiao Yong , Yu Bing , Luo Yuheng , Huang Zhiqing , Mao Xiangbing , Yu Jie , Zheng Ping , Yan Hui , Li Yan , He Jun
Published: September 2023

Proanthocyanidin (PRO) has been implicated in a variety of biological functions, such as antibacterial, antioxidant, and anti-obesity effects. However, little is known about its safety dose for animals. To explore its safety and effect on growth performance and intestinal health, thirty weaned pigs were divided into five groups and fed with basal diet containing 0, 30, 300, 600, and 1200 mg/kg PRO for 42 days. Results showed that PRO supplementation at 30 and 300 mg/kg significantly decreased the feed/gain ratio (F:G) and diarrhea rate (p < 0.05). PRO also increased the digestibilities of dry matter, ether extract, gross energy, and ash (p < 0.05). Interestingly, PRO not only elevated the villus height and the ratio of villus height to crypt depth (V/C) in duodenum and jejunum (p < 0.01), but also decreased the crypt depth in the duodenum (p < 0.01). Moreover, PRO supplementation at 30, 300, and 600 mg/kg elevated the expression levels of mucin 1 (MUC1), MUC2, and fatty acid transport protein 1 (FATP-1) in the duodenum (p < 0.05). The expression levels of FATP-4 in jejunum and ileum were also elevated by PRO (p < 0.05). Importantly, histopathological findings of tissues (e.g., heart, liver, kidney, spleen, lungs, pancreas, thymus, mesenteric lymph nodes, stomach, small intestine), serum clinical chemistry, and major hematological parameters were not affected by PRO supplementation. These results suggest that PRO may act as a safe and effective supplement to decrease F:G and improve intestinal health in weaned pigs.
Study on Morphological Changes and Interference in the Development of Aedes aegypti Caused by Some Essential Oil Constituents
Authors: Serdeiro Michele Teixeira , Dias Thiago Dutra , de Lima Natanael Teles Ramos , Barbosa-Filho José Maria , Belato Renato de Souza , Santos-Mallet Jacenir Reis dos , Maleck Marise
Published: September 2023

Dengue, Chikungunya and Zika are arboviruses, transmitted by the mosquito Aedes aegypti, that cause high mortality and serious health consequences in human populations. Efforts to control Ae. aegypti are important for preventing outbreaks of these diseases. Essential oil constituents are known to exhibit many activities, such as their use as larvicides. Given their potential, the present study aimed to characterize the larvicidal effect of dihydrojasmone, p-cymene, carvacrol, thymol, farnesol and nerolidol on the larvae of Ae. aegypti and their interference over the morphology of the mosquitos. The essential oil constituents were dissolved in dimethylsulfoxide at concentrations of 1–100 μg/mL and were applied in the breeding environment of third-stage larvae. The larvae from bioassays were fixed, dehydrated and embedded. Ultrathin sections were contrasted using 5% uranyl acetate and 1% lead citrate for observation through transmission electron microscopy. The oil with the highest larvicidal efficiency was found to be nerolidol, followed by farnesol, p-cymene, carvacrol, thymol and dihydrojasmone, with an LC50 of 11, 21, 23, 40, 45 and 66 µg/mL, respectively. The treated Ae. aegypti larvae caused alteration to the tegument or internal portions of larvae. The present study demonstrated which of these oils—dihydrojasmone, farnesol, thymol, p-cymene, carvacrol and nerolidol—have effective larvicidal activity.
Phase Transitions in the Interacting Relativistic Boson Systems
Authors: Anchishkin Dmitry , Gnatovskyy Volodymyr , Zhuravel Denys , Karpenko Vladyslav , Mishustin Igor , Stoecker Horst
Published: September 2023

The thermodynamic properties of the interacting particle–antiparticle boson system at high temperatures and densities were investigated within the framework of scalar and thermodynamic mean-field models. We assume isospin (charge) density conservation in the system. The equations of state and thermodynamic functions are determined after solving the self-consistent equations. We study the relationship between attractive and repulsive forces in the system and the influence of these interactions on the thermodynamic properties of the bosonic system, especially on the development of the Bose–Einstein condensate. It is shown that under “weak” attraction, the boson system has a phase transition of the second order, which occurs every time the dependence of the particle density crosses the critical curve or even touches it. It was found that with a “strong” attractive interaction, the system forms a Bose condensate during a phase transition of the first order, and, despite the finite value of the isospin density, these condensate states are characterized by a zero chemical potential. That is, such condensate states cannot be described by the grand canonical ensemble since the chemical potential is involved in the conditions of condensate formation, so it cannot be a free variable when the system is in the condensate phase.
Small Molecules Targeting 3C Protease Inhibit FMDV Replication and Exhibit Virucidal Effect in Cell-Based Assays
Authors: Theerawatanasirikul Sirin , Lueangaramkul Varanya , Pantanam Achiraya , Mana Natjira , Semkum Ploypailin , Lekcharoensuk Porntippa
Published: September 2023

Foot-and-mouth disease (FMD) is a highly contagious disease in cloven-hoofed animals, caused by the foot-and-mouth disease virus (FMDV). It is endemic in Asia and Africa but spreads sporadically throughout the world, resulting in significant losses in the livestock industry. Effective anti-FMDV therapeutics could be a supportive control strategy. Herein, we utilized computer-aided, structure-based virtual screening to filter lead compounds from the National Cancer Institute (NCI) diversity and mechanical libraries using FMDV 3C protease (3Cpro) as the target. Seven hit compounds were further examined via cell-based antiviral and intracellular protease assays, in which two compounds (NSC116640 and NSC332670) strongly inhibited FMDV, with EC50 values at the micromolar level of 2.88 µM (SI = 73.15) and 5.92 µM (SI = 11.11), respectively. These compounds could inactivate extracellular virus directly in a virucidal assay by reducing 1.00 to 2.27 log TCID50 of the viral titers in 0–60 min. In addition, the time-of-addition assay revealed that NSC116640 inhibited FMDV at the early stage of infection (0–8 h), while NSC332670 diminished virus titers when added simultaneously at infection (0 h). Both compounds showed good FMDV 3Cpro inhibition with IC50 values of 10.85 µM (NSC116640) and 4.21 µM (NSC332670). The molecular docking of the compounds on FMDV 3Cpro showed their specific interactions with amino acids in the catalytic triad of FMDV 3Cpro. Both preferentially reacted with enzymes and proteases in physicochemical and ADME analysis studies. The results revealed two novel small molecules with antiviral activities against FMDV and probably related picornaviruses.
A Comparison of Clinical Manifestations and Outcomes between Acute Sporadic Hepatitis A and Hepatitis E Infections in Thailand
Authors: Khongviwatsathien Sirajuk , Thaweerat Wajana , Atthakitmongkol Thanapat , Chotiyaputta Watcharasak , Tanwandee Tawesak
Published: September 2023

Hepatitis A virus (HAV) and hepatitis E virus (HEV) infections often present as acute hepatitis with prodromal symptoms. These infections, transmitted via the oral–enteral route, constitute significant public health challenges, particularly in developing countries with subpar sanitary systems. The aim of the study was to describe the clinical manifestations, laboratory findings, and outcomes of hepatitis A and hepatitis E infections in Thailand. We conducted a retrospective chart review and analysis of 152 patients diagnosed with acute hepatitis A or hepatitis E from January 2007 to August 2018 at Siriraj Hospital. The hepatitis E cohort was older with a greater prevalence of comorbidities (hypertension, diabetes mellitus, chronic kidney disease, chronic hepatitis B, and post-kidney transplantation status) than the hepatitis A cohort. While the majority of hepatitis A patients presented with fever (98%) and jaundice (96%), these symptoms were less pronounced in hepatitis E patients. Furthermore, hepatitis A patients exhibited significantly higher aminotransferase and total bilirubin levels. However, clinical outcomes, such as hospitalization rates, progression to acute liver failure, and mortality, were comparable across both groups. In conclusion, although the clinical manifestations of hepatitis A and hepatitis E were similar, fever and jaundice were more prevalent and aminotransferase and bilirubin levels were higher in the HAV-infected group.
Transmission Dynamics of Crimean–Congo Haemorrhagic Fever Virus (CCHFV): Evidence of Circulation in Humans, Livestock, and Rodents in Diverse Ecologies in Kenya
Authors: Omoga Dorcus C. A. , Tchouassi David P. , Venter Marietjie , Ogola Edwin O. , Osalla Josephine , Kopp Anne , Slothouwer Inga , Torto Baldwyn , Junglen Sandra , Sang Rosemary
Published: September 2023

Crimean–Congo haemorrhagic fever virus (CCHFV) is the causative agent of CCHF, a fatal viral haemorrhagic fever disease in humans. The maintenance of CCHFV in the ecosystem remains poorly understood. Certain tick species are considered as vectors and reservoirs of the virus. Diverse animals are suspected as amplifiers, with only scarce knowledge regarding rodents in virus epidemiology. In this study, serum samples from febrile patients, asymptomatic livestock (cattle, donkeys, sheep, and goats), and peridomestic rodents from Baringo (Marigat) and Kajiado (Nguruman) counties within the Kenyan Rift Valley were screened for acute CCHFV infection by RT-PCR and for CCHFV exposure by ELISA. RT-PCR was performed on all livestock samples in pools (5–7/pool by species and site) and in humans and rodents individually. CCHFV seropositivity was significantly higher in livestock (11.9%, 113/951) compared to rodents (6.5%, 6/93) and humans (5.9%, 29/493) (p = 0.001). Among the livestock, seropositivity was the highest in donkeys (31.4%, 16/51), followed by cattle (14.1%, 44/310), sheep (9.8%, 29/295) and goats (8.1%, 24/295). The presence of IgM antibodies against CCHFV was found in febrile patients suggesting acute or recent infection. CCHFV RNA was detected in four pooled sera samples from sheep (1.4%, 4/280) and four rodent tissues (0.83%, 4/480) showing up to 99% pairwise nucleotide identities among each other. Phylogenetic analyses of partial S segment sequences generated from these samples revealed a close relationship of 96–98% nucleotide identity to strains in the CCHFV Africa 3 lineage. The findings of this study suggest active unnoticed circulation of CCHFV in the study area and the involvement of livestock, rodents, and humans in the circulation of CCHFV in Kenya. The detection of CCHF viral RNA and antibodies against CCHFV in rodents suggests that they may participate in the viral transmission cycle.
Genetic Diversity of Type A Influenza Viruses Found in Swine Herds in Northwestern Poland from 2017 to 2019: The One Health Perspective
Authors: Rabalski Lukasz , Kosinski Maciej , Cybulski Piotr , Stadejek Tomasz , Lepek Krzysztof
Published: September 2023

Influenza A viruses (IAV) are still a cause of concern for public health and veterinary services worldwide. With (−) RNA-segmented genome architecture, influenza viruses are prone to reassortment and can generate a great variety of strains, some capable of crossing interspecies barriers. Seasonal IAV strains continuously spread from humans to pigs, leading to multiple reassortation events with strains endemic to swine. Due to its high adaptability to humans, a reassortant strain based on “human-like” genes could potentially be a carrier of avian origin segments responsible for high virulence, and hence become the next pandemic strain with unseen pathogenicity. The rapid evolution of sequencing methods has provided a fast and cost-efficient way to assess the genetic diversity of IAV. In this study, we investigated the genetic diversity of swine influenza viruses (swIAVs) collected from Polish farms. A total of 376 samples were collected from 11 farms. The infection was confirmed in 112 cases. The isolates were subjected to next-generation sequencing (NGS), resulting in 93 full genome sequences. Phylogenetic analysis classified 59 isolates as genotype T (H1avN2g) and 34 isolates as genotype P (H1pdmN1pdm), all of which had an internal gene cassette (IGC) derived from the H1N1pdm09-like strain. These data are consistent with evolutionary trends in European swIAVs. The applied methodology proved to be useful in monitoring the genetic diversity of IAV at the human–animal interface.
Effectiveness of the Booster Dose in Protecting against COVID-19, Colombia 2022
Authors: Gálvez Jubby Marcela , Pinzón-Rondón Ángela María , Chaparro-Solano Henry Mauricio , Tovar-Romero Hanna Valentina , Ramírez-Prieto Juliana , Ortigoza-Espitia Sergio Andrés , Ruiz-Sternberg Ángela María
Published: September 2023

Vaccination has proven to be one of the most effective strategies against the COVID-19 pandemic. Several studies have evaluated and confirmed its effectiveness in different populations, particularly in reducing severe outcomes such as hospitalization and death. Some studies have investigated the effectiveness of vaccination against the infection, identifying the need for booster doses. This study aimed to explore the effectiveness of the vaccination schedule on the probability of infection in a sample of Colombian patients during the fourth wave of the COVID-19 pandemic, which was associated with the emergence and predominance of the Omicron variant. A cross-sectional study was conducted on individuals who underwent RT-PCR testing for COVID-19 detection in a dedicated laboratory in Bogotá, Colombia, between 30 December 2021 and 7 February 2022. A total of 1468 subjects was included in the study, of whom 36.6% (n = 538) had a positive PCR test for COVID-19. The comparison between fully vaccinated individuals with a booster dose and those without the booster dose revealed a 28% reduction in the odds of infection (OR = 0.719 CI 0.531–0.971). Age (OR = 1.009 CI 1.001–1.018) and low economic status (OR = 1.812 CI 1.416–2.319) were associated with an increased risk of infection. These findings suggest the need for a booster vaccination in the general population to improve the prevention rates of SARS-CoV-2 infection and mitigate severe outcomes.
Characteristics of Vaccine- and Infection-Induced Systemic IgA Anti-SARS-CoV-2 Spike Responses
Authors: Norton Natasha J. , Ings Danielle P. , Fifield Kathleen E. , Barnes David A. , Barnable Keeley A. , Harnum Debbie O. A. , Holder Kayla A. , Russell Rodney S. , Grant Michael D.
Published: September 2023

Mucosal IgA is widely accepted as providing protection against respiratory infections, but stimulation of mucosal immunity, collection of mucosal samples and measurement of mucosal IgA can be problematic. The relationship between mucosal and circulating IgA responses is unclear, however, whole blood is readily collected and circulating antigen-specific IgA easily measured. We measured circulating IgA against SARS-CoV-2 spike (S) to investigate vaccine- and infection-induced production and correlation with protection. Circulating IgA against ancestral (Wuhan-Hu-1) and Omicron (BA.1) S proteins was measured at different time points in a total of 143 subjects with varied backgrounds of vaccination and infection. Intramuscular vaccination induced circulating anti-SARS-CoV-2 S IgA. Subjects with higher levels of vaccine-induced IgA against SARS-CoV-2 S (p = 0.0333) or receptor binding domain (RBD) (p = 0.0266) were less likely to experience an Omicron breakthrough infection. The same associations did not hold for circulating IgG anti-SARS-CoV-2 S levels. Breakthrough infection following two vaccinations generated stronger IgA anti-SARS-CoV-2 S responses (p = 0.0002) than third vaccinations but did not selectively increase circulating IgA against Omicron over ancestral S, indicating immune imprinting of circulating IgA responses. Circulating IgA against SARS-CoV-2 S following breakthrough infection remained higher than vaccine-induced levels for over 150 days. In conclusion, intramuscular mRNA vaccination induces circulating IgA against SARS-CoV-2 S, and higher levels are associated with protection from breakthrough infection. Vaccination with ancestral S enacts imprinting within circulating IgA responses that become apparent after breakthrough infection with Omicron. Breakthrough infection generates stronger and more durable circulating IgA responses against SARS-CoV-2 S than vaccination alone.