bluuebunny/crossref_metadata_2025 huggingface dataset:
A RoBERTa Approach for Automated Processing of Sustainability Reports
Authors: Angin Merih , Taşdemir Beyza , Yılmaz Cenk Arda , Demiralp Gökcan , Atay Mert , Angin Pelin , Dikmener Gökhan
Published: December 2022

There is a strong need and demand from the United Nations, public institutions, and the private sector for classifying government publications, policy briefs, academic literature, and corporate social responsibility reports according to their relevance to the Sustainable Development Goals (SDGs). It is well understood that the SDGs play a major role in the strategic objectives of various entities. However, linking projects and activities to the SDGs has not always been straightforward or possible with existing methodologies. Natural language processing (NLP) techniques offer a new avenue to identify linkages for SDGs from text data. This research examines various machine learning approaches optimized for NLP-based text classification tasks for their success in classifying reports according to their relevance to the SDGs. Extensive experiments have been performed with the recently released Open Source SDG (OSDG) Community Dataset, which contains texts with their related SDG label as validated by community volunteers. Results demonstrate that especially fine-tuned RoBERTa achieves very high performance in the attempted task, which is promising for automated processing of large collections of sustainability reports for detection of relevance to SDGs.
RSU Cluster Deployment and Collaboration Storage of IoV Based Blockchain
Authors: Chen Chen , Quan Shi
Published: December 2022

The Internet of Vehicles is increasingly becoming an indispensable platform to make interactions among vehicles, humans, and roadside infrastructures, and it is continuing to evolve with improvements on its application scenarios and service robustness. Academia and industry have also been concerned with the security issue of Internet of Vehicles (IoV). The Blockchain technology provides a new solution to improve security of the IoV, and it has drawn increased attention. Blockchain technology deals with the network model, identity authentication, trust management, and access control. However, there are insufficient studies on strategy of nodes deployment in the existing BIoV (Blockchain-based IoV). Based on the principle of partition, this paper studies the Blockchain-based IoV model in which the vehicle network system consists of vehicles and Road Side Unit (RSU) nodes. The Blockchain network is formed by the RSU nodes. By optimizing the LEACH algorithm, we partition RSUs and select cluster heads in BIoV, which has good scalability while maintaining a reasonable scale of Blockchain. Simulation results indicated that the improved-LEACH algorithm (I-LEACH) is more effective than the LEACH, DEEC, and the improved-DEEC algorithms (I-DEEC) with respect to the network life cycle and data transmission. Additionally, in order to reduce dependence of the storage resources from BIoV, we designed an intra-cluster collaborative storage scheme by adopting three algorithms for comparison—the genetic algorithm (GA), particle swarm optimization (PSO) algorithm, and the model quantum genetic algorithm (QGA). It revealed that the intra-cluster collaborative storage scheme is effective to ease the bottleneck of storage space demanded in BIoV, and verified by the simulation experiments.
Spatial Structure of China’s Green Development Efficiency: A Perspective Based on Social Network Analysis
Authors: Gao Xiaotong , Cao Naigang , Zhang Yushuo , Zhao Lin
Published: December 2022

Clarifying the spatial correlation network structure of green development efficiency (GDE) is of great significance for realizing coordinated and sustainable development in China. By constructing the evaluation index system of GDE, this study used the super epsilon-based measure (EBM) model that considers undesirable output to measure the GDE of China from 2000 to 2018, based on which the characteristics of the spatial correlation network characteristics and influencing factors were analyzed using social network analysis (SNA) and a geographical detector. The results indicated that: (1) The GDE of China as a whole remained relatively stable, and there was a significant spatial spillover effect of GDE between provinces; the spatial correlation network demonstrated complex and dense characteristics, and the closeness and stability of the network gradually increased. However, the strict hierarchical structure of the network still existed. (2) The eastern coastal provinces exhibited significant spillover effects and connectivity functions, while the northeastern and central-western provinces are located at the edges of the spatial correlation network. (3) The GDE spatial correlation network is divided into a leader subgroup, bridge subgroup and net benefit subgroup, with no isolated subgroup. (4) The economic development level, urbanization and financial development have a decisive impact on the formation of the GDE spatial correlation network.
Nonlinear Diffusion Evolution Model of Unethical Behavior among Green Food Enterprise
Authors: Yang Qi , Hou Yuejuan , Wei Haoran , Chen Tingqiang , Wang Jining
Published: December 2022

Under the background of low-carbon economy, the unethical behavior of green food enterprises has aggravated the uncertainty and frequency of green food safety problems and even triggered a contagion of unethical behavior among green food enterprises. In view of this, considering the characteristics of organizational behavior, external environmental intervention and social networks, we construct an infectious disease model of the nonlinear spread of unethical behavior in green food enterprises and simulated the mechanism and evolution characteristics of the spread of unethical behavior among them. The main conclusions are as follows. (1) Single adjustment of the level of enterprise moral clarity, damage degree of unethical behavior, and enterprise influence can only reduce the diffusion probability of unethical behavior to a certain extent. (2) Enterprise ethical climate plays a crucial role in the diffusion of unethical behavior among green food enterprises and exerts a “strengthening effect” on other organizational behavior and external environmental intervention factors. (3) The strength of external supervision and strength of punishment exert a “suppression effect” on the diffusion of unethical behavior among green food enterprises.
The Role of Skepticism and Transparency in Shaping Green Brand Authenticity and Green Brand Evangelism
Authors: Li Juan , Sun Xixiang , Hu Canwei
Published: December 2022

Green brand evangelism builds an important psychological and behavioral basis on promoting the positive interaction between green brands and consumers, as well as on realizing the co-creation of green brand value. This study selects brand authenticity issues as the entry point and investigates brand authenticity on green brand evangelism. In particular, this study tests the effects of green transparency and green skepticism on brand authenticity, as well as the role of self-brand connection and the need for cognition on the relationship between brand authenticity and green brand evangelism. With a sample of 641 Chinese respondents of green building materials, the dimension and scale of green brand evangelism were acquired by utilizing the grounded theory, and the hypothesized relationships were tested by employing structural equation modeling. The findings suggest that green transparency and green skepticism yield an influence on brand authenticity, and brand authenticity exerts a great influence on green brand authenticity. Moreover, brand authenticity positively affects self-brand connection, which in turn positively influences green brand authenticity, and the relationship between brand authenticity and green brand evangelism is regulated by the need for cognition.
Analysis of the Transfer Time and Influencing Factors of Air-Rail Integration Passengers: A Case Study of Shijiazhuang Zhengding International Airport
Authors: Jiang Fan , Wang Lichao , Huang Shiyu
Published: December 2022

As China’s high-speed rail and civil aviation gradually move from a competitive relationship to a cooperative relationship, air-rail integration services (ARISs) have begun to be promoted, and an increasing number of passengers are choosing the combined travel mode of high-speed rail and aviation. As two long-distance transportation modes are involved, transfer time also affects transfer service satisfaction, and the factors affecting the transfer time of ARIS need to be further clarified. In this study, a stated preference (SP) survey on the transfer reservation time of ARIS passengers was conducted, the perception accuracy of the transfer reservation time was analyzed, and the influencing factors of the transfer reservation time in each link were analyzed by using a multivariate ordered logistic regression model. The results show that the average transfer time of air-rail combined transportation passengers is 102 to 128 min; more than half of passengers’ reservation time is reasonable; and passengers’ genders, educations, occupations, incomes, travel modes, costs, and distances have different degrees of impact on the transfer reservation time. This study holds a certain guiding significance for improving the service quality of air-rail intermodal transportation and improving transfer efficiency and provides a theoretical basis for personalized and customized services for air-rail intermodal passengers.
Spatial Analysis of Soil Properties and Site-Specific Management Zone Delineation for the South Hail Region, Saudi Arabia
Authors: Aggag Ahmed M. , Alharbi Abdulaziz
Published: December 2022

Sustainable soil management with the appropriate understanding of soil characteristics is vital in maintaining and improving agriculture soil management. The objectives of the present study are to characterize the spatial variability of soil using the GIS technique and used agglomerative hierarchical clustering (AHC) for the delineation of management zones (MZs) for precision agriculture. A total of 111 soil samples were collected from 37 soil profiles in systematic depths (0–50, 50–100, and 100–150 cm) from the South Hail region, KSA. Samples were analyzed for pH, ECe, CaCO3, available macro and micronutrients, and hydrological properties. The best fit models, using ArcGIS software, were J-Bessel for pH, Clay, bulk density (BD), and available water (AW); K-Bessel for EC and available N; Stable for CaCO3, P, K, Fe, Zn, Sand, field capacity (FC) and saturated hydraulic conductivity (Ks); Spherical for Mn and Cu; Gaussian for saturation percentage (SP); whereas exponential for permanent wilting point (PWP). The principal component analysis (PCA) resulted in six principal components (PCs) explaining 79.75% of the total variance of soil properties. The PC1 was strongly influenced by soil BD, FC, clay, PWP, Ks, and sand. PC2 was dominated by N, ECe, and CaCO3; PC3 was dominated by pH; PC4 was dominated primarily by K and P, PC5 was mainly dominated by Fe; Mn, and Cu, and PC6 was mainly dominated by SP and Zn. Based on AHC, four soil management zones (MZs) cover 77.94, 14.10, 7.11 and 0.85% of the studied area. Management zone 1 (MZ1) and Management zone 3 (MZ3) are classified as moderately saline while Management zone 2 (MZ2) is classified as highly saline soils, greater than the limiting critical value for the sensitive crops. The potential solutions to reduce salinization in the area include: reducing irrigation, moving to salt-tolerant crops or applying humic acids to fix anions and cations and eliminate them from the root zone of the plants. Treating the area with diluted sulfuric acid to remove salts and reduce ECe to less than 2 dSm−1, to get maximum productivity. This finding is diagnostic for determining the amount of fertilizer and irrigation water to be applied to soils in different management zones. Its emphasis’s the importance of site-specific management for long-term crop productivity and, as a result, reducing environmental hazards caused by uneven fertilizers and water applications.
Rapid Analysis of Composition of Coal Gangue Based on Deep Learning and Thermal Infrared Spectroscopy
Authors: Song Liang , Yu Ying , Yan Zelin , Xiao Dong , Sun Yongqi , Zhang Xuanxuan , Li Xingkai , Cheng Binbin , Gao Han , Bai Dong
Published: December 2022

Coal gangue is the main solid waste in coal mining areas, and its annual emissions account for about 10% of coal production. The composition information of coal gangue is the basis of reasonable utilization of coal gangue, and according to the composition information of coal gangue, one can choose the appropriate application scene. The reasonable utilization of coal gangue can not only effectively alleviate the environmental problems in mining areas but also produce significant economic and social benefits. Chemical analysis techniques are the principal ones used in traditional coal gangue analysis; however, they are slow and expensive. Many researchers have used machine learning techniques to analyze the spectral data of coal gangue, primarily random forests (RFs), extreme learning machines (ELMs), and two-hidden-layer extreme learning machines (TELMs). However, these techniques are heavily reliant on the preprocessing of the spectral data. This research suggests a quick analysis approach for coal gangue based on thermal infrared spectroscopy and deep learning in light of the drawbacks of the aforementioned methodologies. The proposed deep learning model is named SR-TELM, which extracts spectral features using a convolutional neural network (CNN) consisting of a spatial attention mechanism and residual connections and implements content prediction with TELM as a regressor, which can effectively overcome the dependence on preprocessing. The usefulness and speed of SR-TELM in coal gangue analysis were demonstrated by comparing several models in order to verify the proposed coal gangue analysis model. The experimental findings show that, for the prediction tasks of moisture, ash, volatile matter, and fixed carbon content, respectively, the SR-TELM model attained an R2 of 0.947, 0.972, 0.967, and 0.981 and an RMSE of 0.274, 4.040, 1.567, and 2.557 with a test time of just 0.03 s. It offers a method for the analysis of coal gangue that is low cost, highly effective, and highly reliable.
Investigation of Product–Service System Components as Control Points for Value Creation and Development Process
Authors: Wahyudi Rahman Dwi , Singgih Moses Laksono , Suef Mokh
Published: December 2022

Since the early 2000s, product–service systems (PSS) have become a research concern because the benefits provided cover many aspects. PSS is divided into three types, namely, Type 1: product-oriented, Type 2: use-oriented, and Type 3: result-oriented. PSS is a system comprising different components. As a system compiler, the components are the starting point for the value-creation process and continue to impact the PSS’s life cycle. However, elaboration of PSS components in previous studies has lacked. This situation indicates an urgent need to investigate PSS components and, thus, our evaluations of the value creation and the developmental processes of PSS seek to be broad and divergent. The investigation that forms the purpose of this article includes an elaboration of the PSS components, a calculation of the PSS components’ importance levels, statistical testing of the differences in importance levels due to PSS type, correlation testing between components, and a determination of the PSS components concerning the sustainability aspect based on the perspective of customers. The investigation began with the development of a questionnaire and a reliability–validity test. In addition, we identify the PSS components, test the difference in importance level using the Mann–Whitney test, and survey customers to determine the sustainability-related components. This article’s findings can be used to specify the critical point for value creation and PSS development. The elaborated PSS components are products, services, actors, stakeholder relationships, and technology. The difference in importance level indicates that PSS Type 2 customers perceive a distinction in the importance of technology. The essential components of each type of PSS are distinct, necessitating the use of different development strategies, including for sustainability aspects.
E-Commerce Parcel Distribution in Urban Areas with Sustainable Performance Indicators
Authors: Prastyantoro Riharsono , Putro Heru Purboyo Hidayat , Yudoko Gatot , Dirgahayani Puspita
Published: December 2022

E-commerce transactions have increased during the pandemic as people living in urban areas turn to buy goods online rather than offline. A two-echelon distribution system using parcel mobile hubs (PMHs) with small vehicles can increase operational cost efficiency and reduce greenhouse gas emissions. The originality of this study is in building and testing a conceptual framework for selecting PMH locations with three variables (parcel distribution, internet quota for e-commerce, and center of e-buyer) and two constraints (space availability and traffic flow). Spatial analysis is used as a method to test the conceptual framework with a parcel distribution database from Bandung. As a city whose profile represents urban areas in developing countries well, Bandung is chosen as a case study. The proportion of distance to variables and the outermost point of each cluster is less than 10%, which proves that the three variables are correlated. This study proves that the selection of PMH locations based on this conceptual framework results in better sustainable performance compared to existing conditions. Using PMHs combined with city freighters can reduce operational costs by 19.7% and prevent 3.4 tons of CO2 emissions per year with conventional motorcycles and 7.2 tons of CO2 emissions per year with electric motorcycles or scooters.
The Development of Skills as a Key Factor of the Cooperative System: Analysis of the Cooperative of Artisan Women Tejemujeres-Gualaceo-Ecuador from the WWP Model
Authors: Ortuño Mauricio , De los Ríos Ignacio , Sastre-Merino Susana
Published: December 2022

This research analyzed the importance of competencies within the development of the cooperative system through the case study of the Tejemujeres Women’s Artisan Cooperative, for which a documentary and field investigation was conducted with a descriptive and explanatory scope under a mixed approach. The importance of cooperatives as tools of social cohesion has been considered due to the progress of their members, their strengthening of social capital, and generation of the necessary conditions to adapt to the demands of the place in which they operate. From this perspective, research tools such as surveys, interviews, and focus groups were implemented for a total of 85 participants of the entity under a census and incidental sample approach to analyze each of the responses under the Working With People model, from its dimensions: ethical-social, technical-business, and political-contextual. These responses have been collected in such a way that the skills of the most significant relevance to artisans are identified, which have allowed the strengthening of the cooperative system. The results demonstrate the level of incidence of a group of indigenous women from the rural area of the Gualaceo canton. The development of their skills has participated in the construction and implementation of a social model of company cooperative that—due to the complexity of its members and its environment—must face several scenarios to adequately articulate the social-business vision and achieve its sustainability over time.
Electrochemical Properties and the Adsorption of Lithium Ions in the Brine of Lithium-Ion Sieves Prepared from Spent Lithium Iron Phosphate Batteries
Authors: Hsiang Hsing-I , Chen Wei-Yu
Published: December 2022

Because used LiFePO4 batteries contain no precious metals, converting the lithium iron phosphate cathode into recycled materials (Li2CO3, Fe, P) provides no economic benefits. Thus, few researchers are willing to recycle them. As a result, environmental sustainability can be achieved if the cathode material of spent lithium-iron phosphate batteries can be directly reused via electrochemical technology. Lithium iron phosphate films were developed in this study through electrophoretic deposition using spent lithium-iron phosphate cathodes as raw materials to serve as lithium-ion sieves. The lithium iron phosphate films were then coated with a layer of polypyrrole (PPy) conductive polymer to improve the electrochemical properties and the lithium-ion adsorption capacity for brine. Cyclic voltammetry, charge/discharge testing, and an AC impedance test were used to determine the electrochemical properties and lithium-ion adsorption capacity of lithium-ion sieves. The findings indicate that lithium iron phosphate films prepared from spent LiFePO4 cathodes have a high potential as a lithium-ion sieve for electro-sorption from brine.
A Surface Crack Damage Evaluation Method Based on Kernel Density Estimation for UAV Images
Authors: Liang Yusheng , Zhang Fan , Yang Kun , Hu Zhenqi
Published: December 2022

The development of UAV (unmanned aerial vehicle) technology provides an ideal data source for the information extraction of surface cracks, which can be used for efficient, fast, and easy access to surface damage in mining areas. Understanding how to effectively assess the degree of development of surface cracks is a prerequisite for the reasonable development of crack management measures. However, there are still no studies that have carried out a reasonable assessment of the damage level of cracks. Given this, this article proposes a surface crack damage evaluation method based on kernel density estimation for UAV images. Firstly, the surface crack information from the UAV images is quickly and efficiently obtained based on a machine learning method, and the kernel density estimation method is used to calculate the crack density. The crack nuclear density is then used as a grading index to classify the damage degree of the study area into three levels: light damage, moderate damage, and severe damage. It is found that the proposed method can effectively extract the surface crack information in the study area with an accuracy of 0.89. The estimated bandwidth of the crack kernel density was determined to be 3 m based on existing studies on the effects of surface cracks on soil physicochemical properties and vegetation. The maximum crack density value in the study area was 316.956. The surface damage area due to cracks was 14376.75 m2. The damage grading criteria for surface cracks in the study area (light: 0–60; moderate: 60–150; severe: >150) were determined based on the samples selected from the field survey by crack management experts. The percentages of light, moderate, and severe damage areas were 72.77%, 23.22%, and 4.01%, respectively. The method proposed in this article can effectively realize the graded damage evaluation of surface cracks and provide effective data support for the management of surface cracks in mining areas.
Associated Information and Communication Technologies Challenges of Smart City Development
Authors: Balfaqih Mohammed , Alharbi Soltan Abed
Published: December 2022

Smart cities development relies on information and communication technologies (ICTs) to improve all urban aspects, including governance, economy, mobility, and environment. The development is usually associated with several challenges and negative effects. This study relies on revealing ICTs challenges by firstly conducting a comprehensive literature review to identify the challenges that are most associated with ICTs. Then, a questionnaire survey was distributed among the Saudi population to study their expectations, perceptions, and concerns on the smart city concept and services. The questionnaire also investigated ICTs challenges identified from the literature review, including information security risks, privacy violation, incompatibility, and digital skill gaps. Consequently, semi-structured interviews were conducted to perceive the reasons for the incompatibility between different systems and digital skill gaps between the public. The findings show that the most likely challenges are information security risks and privacy violations, which are due to the increase in vulnerability, potential attacks, and lack of public awareness regarding personal data protection. The incompatibility between different systems and services in smart cities arouses worries among the public due to the expected high cost and difficulty of adaptation and utilization. Moreover, digital skill gaps arises between members of the population that have a low education level or are elderly persons.
Subjective Social Class and the Retention Intentions of Teachers from the Publicly Funded Normal Students Program in China: The Dual Mediating Effect of Organizational and Professional Identity
Authors: Li Tingzhou , Zhang Luo , Fu Wangqian
Published: December 2022

A stable teaching force is an important guarantee for the sustainable development of education. Teacher turnover is one of the reasons for the teacher shortage in rural areas. Although studies have examined the influencing factors of teachers’ turnover intention, little is known about the effect of subjective social status on teachers’ turnover intention, especially for publicly funded normal students program (PFNSP) teachers who play a vital role in improving the quality of education in less developed regions of central and western China. A questionnaire survey was conducted, which returned a total of 16,731 responses (8141 public recruited teachers and 1498 teachers from PFNSP). The study explores the influence of subjective social class on PFNSP teachers’ retention intention and the mediating role of organizational and professional identity on this impact. Except for organizational identity, the subjective social class, professional identity, and retention intentions of PFNSP teachers were significantly lower than those of publicly recruited teachers. There was a significant association between subjective social class and retention intentions of PFNSP teachers. In addition, organizational identity and professional identity had a significant positive relationship to PFNSP teachers’ retention intention, and played partial mediating roles in the relationship between subjective social class and retention intentions.
Convergence of Inexact Iterates of an Algorithm Based on Unions of Nonexpansive Mappings in Metric Spaces
Authors: Zaslavski Alexander J.
Published: December 2022

In our recent paper we obtained an extension of a theorem of Tam (2018), which was established for iterates of a set-valued paracontracting operators in a finite-dimensional Euclidean space. This extension was obtained for exact iterates of maps in a metric space. In the present paper we prove two analogs of this result for inexact iterates under the presence of computational errors. In the first result, the errors are summable, while for the second one they converge to zero. In a particular case of a Banach space, if all the operators are symmetric, then the set of all limit points of iterates is symmetric too.
A Particle Swarm Optimization Method for AI Stream Scheduling in Edge Environments
Authors: Zhang Ming , Liu Luanqi , Li Changzhen , Wang Haifeng , Li Ming
Published: December 2022

With the development of IoT and 5G technologies, edge computing has become a key driver for providing compute, network and storage services. The dramatic increase in data size and the complexity of AI computation models have put higher demands on the performance of edge computing. Rational and optimal scheduling of AI data-intensive computation tasks can greatly improve the overall performance of edge computing. To this end, a particle swarm algorithm based on objective ranking is proposed to optimize task execution time and scheduling cost by designing a task scheduling model to achieve task scheduling in an edge computing environment. It is necessary to fully understand the concept of symmetry of resource utilization and task execution cost indicators. The method utilizes nonlinear inertia weights and shrinkage factor update mechanisms to improve the optimization-seeking ability and convergence speed of the particle-to-task scheduling solution space. The task execution time and scheduling cost are greatly reduced. Simulation experiments are conducted using the Cloudsim toolkit to experimentally compare the proposed algorithm TS-MOPSO with three other particle swarm improvement algorithms, and the experimental results show that the task execution time, maximum completion time and total task scheduling cost are reduced by 31.6%, 23.1% and 16.6%, respectively. The method is suitable for handling large and complex AI data-intensive task scheduling optimization efforts.
Defect Detection inside a Rail Head by Ultrasonic Guided Waves
Authors: Xie Jingsong , Ding Wenxiang , Zou Wen , Wang Tiantian , Yang Jinsong
Published: December 2022

Early detection of defects inside a rail is of great significance to ensure the safety of rail transit. This work investigated the ability of ultrasonic guided waves (UGWs) to detect internal defects in a rail head. First, the model of UGW propagation in rail, which has an irregular cross-section, was constructed based on the semi-analytical finite element (SAFE) method. Fundamental characteristics, such as wavenumber, phase or group velocity, and wave structure inside the rail, were then calculated. Following modal and vibration energy distribution analysis, a guided wave mode that is sensitive to transverse fissure (TF) defects was selected, and its excitation method was proposed. The effectiveness of the excitation method was confirmed by simulations performed in the ABAQUS software. According to the simulation data, the dispersion curve calculated by using the two-dimensional Fourier fast transform (2D-FFT) coincided well with that of the SAFE method. After that, the sensitivity of the selected mode to internal rail defects was validated and its ability to locate defects was also demonstrated. Finally, the effects of excitation frequency, defect size, and vertical and horizontal defect depth on the reflection waveforms were investigated.
Sustainable Innovation through Developing Hybrid Agri-Food Supply Chains: A Case in South-Eastern Spain
Authors: Navarro-del Aguila Irene , de Burgos-Jiménez Jerónimo
Published: December 2022

We analyze the incipient development of short supply chains for fresh fruit and vegetables from conventional agri-food chains, leading to the emergence of hybrid chains. We have sought to answer the research question of how and why hybrid food supply chains has been initiated by studying this phenomenon in south-eastern Spain. We analyzed the 20 main Spanish fruit and vegetable exporters, identifying the 9 that have developed short channels. Subsequently, we conducted a case study of the one considered most relevant, identifying the stages of this short chain, analyzing the tasks to be performed in the different phases of the SCS, studying which are common to both and where the differences in the processes arise. The results show the synergies that make them coexist successfully, such as the sharing of personnel, infrastructures and services, complementarity in the product range, thus avoiding food waste, or knowledge of consumer tastes and needs.
Copper and Zinc Treatments Alter the Thyroid Endocrine System in Zebrafish Embryos/Larvae
Authors: Zhong Liqiao , Zhang He , Wu Luyin , Ru Huijun , Wei Nian , Yao Fan , Ni Zhaohui , Duan Xinbin , Li Yunfeng
Published: December 2022

Copper (Cu2+) and zinc (Zn2+) are two kinds of heavy metals essential to living organisms. Cu2+ and Zn2+ at excessive concentrations can cause adverse effects on animals, but little is known about the thyroid-disrupting effects of these metals in fish, especially in the early developmental transition stage from embryos to larvae. Wild-type zebrafish embryos were used to expose to Cu2+ (0, 1.5, 15, and 150 μg/L) and Zn2+ (0, 20, 200, and 2000 μg/L) for 120 h. Thyroid hormone contents and transcriptional changes of the genes connected with the hypothalamic-pituitary-thyroid (HPT) axis were measured. Results showed that zebrafish embryos/larvae malformation rates were significantly increased in the Cu2+ and Zn2+ groups. Remarkably elevated thyroxine (T4) concentrations and reduced triiodothyronine (T3) concentrations were observed in Cu2+ and Zn2+ exposure fish. And the expression patterns of genes connected with the HPT axis were changed after Cu2+ and Zn2+ treatment. Based on principal component analysis (PCA) results, Zn2+ caused significant effects on the thyroid endocrine system at 200 μg/L, while Cu2+ resulted in thyroid disruption as low as 1.5 μg/L. In short, our study demonstrated that exposure to Cu2+ and Zn2+ induced developmental toxicity and thyroid disruption to zebrafish embryos/larvae.
Microbial and Plant Derived Low Risk Pesticides Having Nematocidal Activity
Authors: Evidente Antonio
Published: December 2022

Microorganisms, virus, weeds, parasitic plants, insects, and nematodes are among the enemies that induce severe economic losses to agrarian production. Farmers have been forced to combat these enemies using different methods, including mechanical and agronomic strategies, since the beginning of agriculture. The development of agriculture, due to an increased request for food production, which is a consequence to the rapid and noteworthy growth of the world’s population, requires the use of more efficient methods to strongly elevate the yield production. Thus, in the last five-to-six decades, a massive and extensive use of chemicals has occurred in agriculture, resulting in heavy negative consequences, such as the increase in environmental pollution and risks for human and animal health. These problems increased with the repetition of treatments, which is due to resistance that natural enemies developed against this massive use of pesticides. There are new control strategies under investigation to develop products, namely biopesticides, with high efficacy and selectivity but based on natural products which are not toxic, and which are biodegradable in a short time. This review is focused on the microbial and plant metabolites with nematocidal activity with potential applications in suitable formulations in greenhouses and fields.
Coronal Field Geometry and Solar Wind Speed
Authors: Berezin Ivan , Tlatov Andrey
Published: December 2022

The Wang–Sheeley–Arge (WSA) solar wind (SW) model is based on the idea that weakly expanding coronal magnetic field tubes are associated with sources of fast SWs and vice versa. A parameter called the “flux tube expansion” (FTE) is used to determine the degree of expansion of magnetic tubes. The FTE is calculated based on the coronal magnetic field model, usually in the potential approximation. The second input parameter for the WSA model is the great circle distance from the base of the open magnetic field line in the photosphere to the boundary of the corresponding coronal hole (DCHB). These two coronal magnetic field parameters are related by an empirical relationship with the solar wind velocity near the Sun. The WSA model has shortcomings and does not fully explain the solar wind formation mechanisms. In the present work, we model various coronal magnetic field parameters in the potential-field source-surface (PFSS) approximation from a long series of magnetographic observations: the Solar Telescope-magnetograph for Operative Prognoses (STOP) (Kislovodsk Mountain Astronomical Station), the Helioseismic and magnetic imager (SDO/HMI), and data from the Wilcox Solar Observatory (WSO). Our main goal is to identify correlations between the coronal magnetic field parameters and the observed SW velocity in order to use them for modeling SW. We found that the SW velocity correlates relatively well with some geometric properties of the magnetic tubes, including the force line length, the latitude of the force line footpoints, and the DCHB. We propose a formula for calculating the SW velocity based on these parameters. The presented relationship does not use FTE and showed a better correlation with observations compared to the WSA model.
Multifunctional Protein A Is the Only Viral Protein Required for Nodavirus RNA Replication Crown Formation
Authors: den Boon Johan A. , Zhan Hong , Unchwaniwala Nuruddin , Horswill Mark , Slavik Kailey , Pennington Janice , Navine Amanda , Ahlquist Paul
Published: December 2022

Positive-strand RNA virus RNA genome replication occurs in membrane-associated RNA replication complexes (RCs). Nodavirus RCs are outer mitochondrial membrane invaginations whose necked openings to the cytosol are “crowned” by a 12-fold symmetrical proteinaceous ring that functions as the main engine of RNA replication. Similar protein crowns recently visualized at the openings of alphavirus and coronavirus RCs highlight their broad conservation and functional importance. Using cryo-EM tomography, we earlier showed that the major nodavirus crown constituent is viral protein A, whose polymerase, RNA capping, membrane interaction and multimerization domains drive RC formation and function. Other viral proteins are strong candidates for unassigned EM density in the crown. RNA-binding RNAi inhibitor protein B2 co-immunoprecipitates with protein A and could form crown subdomains that protect nascent viral RNA and dsRNA templates. Capsid protein may interact with the crown since nodavirus virion assembly has spatial and other links to RNA replication. Using cryoelectron tomography and complementary approaches, we show that, even when formed in mammalian cells, nodavirus RC crowns generated without B2 and capsid proteins are functional and structurally indistinguishable from mature crowns in infected Drosophila cells expressing all viral proteins. Thus, the only nodaviral factors essential to form functional RCs and crowns are RNA replication protein A and an RNA template. We also resolve apparent conflicts in prior results on B2 localization in infected cells, revealing at least two distinguishable pools of B2. The results have significant implications for crown structure, assembly, function and control as an antiviral target.
High-Risk Human Papillomavirus Detection via Cobas® 4800 and REBA HPV-ID® Assays
Authors: Liewchalermwong Sasiprapa , Oranratanaphan Shina , Termrungruanglert Wichai , Triratanachat Surang , Tantbirojn Patou , Kitkumthorn Nakarin , Bhattarakosol Parvapan , Chaiwongkot Arkom
Published: December 2022

Persistent infection with high-risk human papillomaviruses (HR-HPVs), particularly HPV16 and 18, has long been known to induce cervical cancer progression. However, given that a minority of HPV-infected women develop cancer, analysis of HR-HPV-infected women could help to predict who is at risk of acquiring cervical cancer. Therefore, to improve HR-HPVs detection, we used the FDA-approved cobas® 4800 HPV and REBA HPV-ID® HPV assays to detect HR-HPVs in colposcopy-derived cervical cells from 303 patients, detecting 72.28% (219) and 71.62% (217) of HR-HPVs positive cases, with HPV16 detection rates of 35.64% (108) and 30.69% (93), respectively. Of the HPV16-positive cases, cobas® 4800 and REBA HPV-ID® identified 28.81% (51) and 25.42% (45) of the CIN1 cases, and 55% (33) and 50% (30) of the 60 CIN2/3 cases, respectively. HPV-diagnostic concordance was 82.17% overall (kappa = 0.488), 87.45% for HR-HPVs (kappa = 0.689), and 88.33% for CIN2/3 (kappa = 0.51). The HR-HPVs detection rates of these assays were comparable. Our findings reveal that the FDA-approved HR-HPVs detection assay is appropriate for screening women with HR-HPVs infection, and for predicting increased risk of cervical cancer progression. REBA HPV-ID® can be used to detect low risk-HPV types in high-grade cervical lesions that are HR-HPV negative as well as in the distribution of HPV types.
Impact of Supplementing Phytobiotics as a Substitute for Antibiotics in Broiler Chicken Feed on Growth Performance, Nutrient Digestibility, and Biochemical Parameters
Authors: Zaikina Anastasiya S. , Buryakov Nikolai P. , Buryakova Maria A. , Zagarin Artem Yu. , Razhev Artem A. , Aleshin Dmitrii E.
Published: December 2022

To determine the level of application and the effectiveness of the use of plant feed additives from sweet chestnut wood extract (Castanea Sativa Mill) in the diet of Cobb-500 cross broiler chickens, four groups were formed via the balanced groups method. The chickens in the experimental groups were supplemented with sweet chestnut wood extract in the main diet rather than a feed antibiotic at an amount of 500 g per ton of compound starter feed and 250 g per ton of grower and finisher in the second experimental group; 650 g per ton of compound starter feed and 325 g per ton of grower and finisher in the third experimental group; and 800 g per ton of compound starter feed and 400 g per ton of grower and finisher in the fourth experimental group. Supplementation with phytobiotics led to an increase in the digestibility of the dry matter in the second and third groups compared to the first experimental group. Furthermore, broiler chickens supplemented with a medium dose of phytobiotics revealed a significant difference in both crude protein and fiber when compared to the second experimental group (91.95% and 12.11% vs. 88.98% and 10.07%, respectively). The preslaughter weight of the birds in the phytobiotics supplemented groups was higher than in those fed with the lowest dosage of phytobiotic by 5.47%, and the difference was significant. There were no significant differences in terms of the blood biochemical parameters between the groups. In summary, the inclusion of plant feed additives from sweet chestnut wood extract as a substitute for an antibacterial drug in the diet of broiler chickens did not deteriorate the blood biochemical parameters and improved the intensity of the nutrient digestion process. As a result, it enhanced the quality indicators of the broiler carcass during the entire growth period.
Experimental Infection with Mycoplasma hyopneumoniae Strain 232 in Swine Influences the Lower Respiratory Microbiota
Authors: Almeida Henrique Meiroz de Souza , Sonalio Karina , Mechler-Dreibi Marina Lopes , Petri Fernando Antônio Moreira , Storino Gabriel Yuri , Maes Dominiek , de Oliveira Luís Guilherme
Published: December 2022

Mycoplasma (M.) hyopneumoniae, the etiological agent of swine enzootic pneumonia, has been reported to increase the susceptibility to secondary infections and modulate the respiratory microbiota in infected pigs. However, no studies have assessed the influence of M. hyopneumoniae on the respiratory microbiota diversity under experimental conditions. Therefore, this study evaluated the impact of M. hyopneumoniae infection on the respiratory microbiota of experimentally infected swine over time. To accomplish this, 12 weaned pigs from a M. hyopneumoniae-free farm were divided into two groups: M. hyopneumoniae strain 232 infected (n = 8) and non-infected (n = 4). The first group received 10 mL of Friis medium containing 107 CCU/mL of M. hyopneumoniae while the control group received 10 mL of sterile Friis medium. Inoculation of both groups was performed intratracheally when the animals were 35 days old (d0). At 28 days post-inoculation (dpi) and 56 dpi, 4 infected animals plus 2 controls were humanely euthanized, and biopsy samples of nasal turbinates (NT) and bronchus-alveolar lavage fluid (BALF) samples were collected. The DNA was extracted from the individual samples, and each group had the samples pooled and submitted to next-generation sequencing. Taxonomic analysis, alpha and beta diversity indexes, weighted unifrac, and unweighted unifrac distances were calculated. A high relative frequency (99%) of M. hyopneumoniae in BALF samples from infected animals was observed with no significant variation between time points. The infection did not seem to alter the diversity and evenness of bacterial communities in NT, thus, M. hyopneumoniae relative frequency was low in NT pools from infected animals (28 dpi—0.83%; 56 dpi—0.89%). PCoA diagrams showed that BALF samples from infected pigs were grouped and far from the control samples, whereas NT from infected animals were not separated from the control. Under the present coditions, M. hyopneumoniae infection influenced the lower respiratory microbiota, which could contribute to the increased susceptibility of infected animals to respiratory infections.
Application of ORF3 Subunit Vaccine for Avian Hepatitis E Virus
Authors: Yan Hongjian , Chi Zengna , Zhao Hui , Zhang Yawen , Zhang Yuduo , Wang Yixin , Chang Shuang , Zhao Peng
Published: December 2022

Avian hepatitis E virus (HEV) is the main etiologic pathogen of chicken big liver and spleen disease which is widely prevalent in China in recent years. However, due to the lack of a highly effective culture system in vitro, a genetically engineered subunit vaccine is the main direction of vaccine development. In this study, ORF3 genes of VaHEV strain from laying hens and YT-aHEV strain from broilers were amplified, respectively, and ORF3 protein was successfully expressed by Escherichia coli prokaryotic expression system. The serum samples were collected periodically to detect avian HEV antibodies by indirect immunofluorescence after specific pathogen free chickens immunized with the two proteins and their mixed proteins, the results showed that all serum samples were positive for antibodies to avian HEV. The antibody-positive chickens were artificially challenged with the cell-adapted strain YT-aHEV strain. The chickens from the immunized control group were infected successfully; no fecal detoxification was detected in the immunized group. In this study, two representative strains of ORF3 subunit vaccines of laying hens and broilers were prepared by prokaryotic expression, the immune effects of different proteins of these were evaluated through immunization and challenge studies in vivo, which provided a new technical possibility for prevention and control of avian HEV.
Sand/Polyethyleneimine Composites with Enhanced Sorption/Desorption Properties toward Pollutants
Authors: Bucatariu Florin , Petrila Larisa-Maria , Zaharia Marius-Mihai , Simon Frank , Mihai Marcela
Published: December 2022

The direct deposition of polyethyleneimine (PEI), a weak polycation with a large content of amino groups, onto sand fractions with different sizes (F70, F100, F200, and F355), resulted in versatile core-shell sorbents for water cleaning. Herein, PEI and the weak polyanion poly(acrylic acid) (PAA) were directly precipitated as an nonstoichiometric polyelectrolyte complex ([PEI]:[PAA] = 2:1) onto a sand surface followed by cross-linking with glutaraldehyde (GA) at three molar ratios ([CHO]:[amine] = 1:10; 1:5; 1:1 = r). Non-crosslinked polyelectrolyte chains were washed out in strongly basic (pH 14) and acidic (pH 0) media. The sand/PEI-GA composites were evaluated to determine the organic shell stability using swelling experiments and X-ray photoelectron spectroscopy. The sorbed/desorbed amount of two model pollutants (copper ions and bromocresol green) in column experiments depended on the sand fraction size and cross-linking degree of the PEI shell. The maximum recorded values, after five loading/release cycles of pollutant species onto F70/PEI-GAr, F100/PEI-GAr, F200/PEI-GAr, and F355/PEI-GAr, were situated between the 0.7–5.5 mg Cu2+/mL column and 3.7–15 mg BCG/mL column. Sand/PEI-GAr composites could act as promising sorbents, low-cost and eco-friendly, which could be applied for water purification procedures.