bluuebunny/crossref_metadata_2025 huggingface dataset:
An Experimental Platform for Tomographic Reconstruction of Tissue Images in Brightfield Microscopy
Authors: Koudounas Panteleimon , Koniaris Efthymios , Manolis Ioannis , Asvestas Panteleimon , Kostopoulos Spiros , Cavouras Dionisis , Glotsos Dimitris
Published: November 2023

(1) Background: Reviewing biological material under the microscope is a demanding and time-consuming process, prone to diagnostic pitfalls. In this study, a methodology for tomographic imaging of tissue sections is presented, relying on the idea that each tissue sample has a finite thickness and, therefore, it is possible to create images at different levels within the sample, revealing details that would probably not be seen otherwise. (2) Methods: Optical slicing was possible by developing a custom-made microscopy stage controlled by an ARDUINO. The custom-made stage, besides the normal sample movements that it should provide along the x-, y-, and z- axes, may additionally rotate the sample around the horizontal axis of the microscope slide. This rotation allows the conversion of the optical microscope into a CT geometry, enabling optical slicing of the sample using projection-based tomographic reconstruction algorithms. (3) Results: The resulting images were of satisfactory quality, but they exhibited some artifacts, which are particularly evident in the axial plane images. (4) Conclusions: Using classical tomographic reconstruction algorithms at limited angles, it is possible to investigate the sample at any desired optical plane, revealing information that would be difficult to identify when focusing only on the conventional 2D images.
Large-Scale Multicast Group Secure Transmission Scheme Based on Multi-Carrier FDA
Authors: Wu Dan , Fei Yuqi , Gao Jianbang , Wang Fei , Gao Guowang
Published: November 2023

Aiming at the problem that the traditional physical layer technology cannot realize secure transmission due to the large number of users and wide dispersion in the multicast system, a layered transmission method is proposed, and a scheme for the secure transmission of the multicast group physical layer is designed. Firstly, the hierarchical transmission system model is established. Then, the array weighted vector of each layer is optimized according to the design criterion of maximizing the artificial noise interference power. At the same time, in the case where the number of users in a single multicast group is greater than the number of transmitting antennas, a multicast grouping strategy is introduced, and the singular value decomposition and Lagrange multiplier algorithms are utilized to obtain the optimal solution. Simulation results show that the proposed method can realize the secure communication of users with different distances in the same direction and can distinguish the multicast users with the same direction angle and different distances under the premise of mutual non-interference, thus realizing the secure communication of large-scale multicast users.
Sign Language Motion Generation from Sign Characteristics
Authors: Gil-Martín Manuel , Villa-Monedero María , Pomirski Andrzej , Sáez-Trigueros Daniel , San-Segundo Rubén
Published: November 2023

This paper proposes, analyzes, and evaluates a deep learning architecture based on transformers for generating sign language motion from sign phonemes (represented using HamNoSys: a notation system developed at the University of Hamburg). The sign phonemes provide information about sign characteristics like hand configuration, localization, or movements. The use of sign phonemes is crucial for generating sign motion with a high level of details (including finger extensions and flexions). The transformer-based approach also includes a stop detection module for predicting the end of the generation process. Both aspects, motion generation and stop detection, are evaluated in detail. For motion generation, the dynamic time warping distance is used to compute the similarity between two landmarks sequences (ground truth and generated). The stop detection module is evaluated considering detection accuracy and ROC (receiver operating characteristic) curves. The paper proposes and evaluates several strategies to obtain the system configuration with the best performance. These strategies include different padding strategies, interpolation approaches, and data augmentation techniques. The best configuration of a fully automatic system obtains an average DTW distance per frame of 0.1057 and an area under the ROC curve (AUC) higher than 0.94.
A Heart Image Segmentation Method Based on Position Attention Mechanism and Inverted Pyramid
Authors: Luo Jinbin , Wang Qinghui , Zou Ruirui , Wang Ying , Liu Fenglin , Zheng Haojie , Du Shaoyi , Yuan Chengzhi
Published: November 2023

In the realm of modern medicine, medical imaging stands as an irreplaceable pillar for accurate diagnostics. The significance of precise segmentation in medical images cannot be overstated, especially considering the variability introduced by different practitioners. With the escalating volume of medical imaging data, the demand for automated and efficient segmentation methods has become imperative. This study introduces an innovative approach to heart image segmentation, embedding a multi-scale feature and attention mechanism within an inverted pyramid framework. Recognizing the intricacies of extracting contextual information from low-resolution medical images, our method adopts an inverted pyramid architecture. Through training with multi-scale images and integrating prediction outcomes, we enhance the network’s contextual understanding. Acknowledging the consistent patterns in the relative positions of organs, we introduce an attention module enriched with positional encoding information. This module empowers the network to capture essential positional cues, thereby elevating segmentation accuracy. Our research resides at the intersection of medical imaging and sensor technology, emphasizing the foundational role of sensors in medical image analysis. The integration of sensor-generated data showcases the symbiotic relationship between sensor technology and advanced machine learning techniques. Evaluation on two heart datasets substantiates the superior performance of our approach. Metrics such as the Dice coefficient, Jaccard coefficient, recall, and F-measure demonstrate the method’s efficacy compared to state-of-the-art techniques. In conclusion, our proposed heart image segmentation method addresses the challenges posed by diverse medical images, offering a promising solution for efficiently processing 2D/3D sensor data in contemporary medical imaging.
Post-Resettlement Intimate Partner Domestic Violence in Afghan and Arab Refugees: A Scoping Review
Authors: Goliaei Zahra , Chaban Zaina , Amrei Seyedeh Ala Mokhtabad , Pashmineh Azar Yasamin , Afzal Laila , Hakim Rashim , Al-Ani Hadeer A. , Koga Patrick Marius , Guggenbickler Andrea M.
Published: November 2023

Intimate Partner Domestic Violence (IPDV) has been reported to be high in minorities across the US. Among minorities, refugees and immigrants encounter particular barriers that may influence their responses to IPDV. This scoping review examined three decades of literature (1980–2022) on resettled married Afghan and Arab refugee women’s attitudes and behaviors toward IPDV in their host countries, aiming to explore gaps in the research, practice, and policy recommendations. Based on the Arksey and O’Malley model, our scoping review conducted extensive searches in SCOPUS, PubMed, PsychInfo, CINAHL, the Web of Science, the Directory of Open Access Journals, and the Embase databases. Searches identified articles that examined resettled Afghan and/or Arab refugees’ responses to IPDV in Western countries. The search identified 439 unique citations; 17 met the inclusion/exclusion criteria. The major findings included acculturative changes in refugee attitudes and behaviors and in stakeholders’ perspectives. Significant attitudinal changes (acknowledgment, silence, justification, or IPDV disapproval) contrasted with less behavioral changes (help-seeking behaviors, or action plans), or changes in barriers to actions, and with a resistance to change in stakeholders (cultural norms and beliefs, the community patriarchal normalization of violence, service providers’ unfamiliarity with client diversity and refugee cultures) in supporting women’s decision-making regarding IPDV. Not a single article made explicit policy recommendations.
Blockchain’s Role in Enhancing Quality and Safety and Promoting Sustainability in the Food and Beverage Industry
Authors: Kshetri Nir
Published: November 2023

The objective of this paper is to assess the potential roles of blockchain technology in enhancing quality, safety, and sustainability throughout the production and distribution of food and beverage products. To achieve this, a multiple case study approach has been selected as the primary research methodology. This article underscores the transformative impact of blockchain implementation on inter-organizational transactions, reducing uncertainty among supply chain participants and fostering more equitable interdependence among partners in the value chain. These developments have the potential to bolster quality, safety, and sustainability within the food and beverage industry. The article also explores strategies for enhancing blockchain’s influence on interfirm governance structures within the food and beverage sector. It delves into the possibilities of broadening participation by increasing the number and variety of participants in blockchain networks. It investigates how the synergy between blockchain technology and other emerging technologies can further optimize their impact on reducing interfirm governance structures. Also addressed in the paper is the potential for blockchain-based solutions to enhance distributive fairness within the food and beverage industry, offering marginalized groups, such as small-holder farmers, greater opportunities for integration into the global economy. Special emphasis is placed on blockchain’s capacity to enhance interfirm governance in this industry by reducing uncertainty among supply chain participants and creating more symmetrical dependencies among them. The article also posits that by fostering entrepreneurial prospects for marginalized communities and promoting distributive fairness, blockchain technology can contribute to socially responsible actions. Overall, this study extends theories and concepts from information and communications technologies’ (ICTs) effects on agency, boundaries, and uncertainty in the context of organizational and inter-organizational dynamics.
Utilization of Spent Coffee Grounds as a Feed Additive for Enhancing the Nutritional Value of Tenebrio molitor Larvae
Authors: Kotsou Konstantina , Chatzimitakos Theodoros , Athanasiadis Vassilis , Bozinou Eleni , Athanassiou Christos G. , Lalas Stavros I.
Published: November 2023

Increasing demand for sustainable protein sources has spurred interest in the exploration of alternative protein sources with a reduced environmental impact. This study investigates the use of spent coffee grounds (SCG), a widely available by-product, as a feed additive for Tenebrio molitor larvae, aiming to contribute to the circular economy and enhance the nutritional quality of the insects. The larvae were fed with a mixture of bran (the conventional feed) and SCGs (10 and 25% w/w). Larval viability, growth, and nutritional composition, including protein, fat, carbohydrates, ash, carotenoids, vitamins A and C, and polyphenols, were evaluated. Increasing the proportion of SCGs in the larvae’s feed led to an enhanced nutritional value of the larvae. In particular, crude protein increased by 45.26%, vitamin C showed an increase of 81.28%, and vitamin A showed an increase of 822.79%, while polyphenol content increased by 29.01%. In addition, the oil extracted from these larvae showed enhanced nutritional value and greater resistance to oxidation. The results highlight the promising use of SCGs as a feed additive for T. molitor larvae, offering a sustainable approach to enhance their nutritional value. Delving deeper into the results, the addition of 10% SCGs resulted in a 45.26% increase in crude protein compared to the SCG0 sample. Concurrently, increasing SCGs in the dietary substrate led to an increase in vitamin content; in sample SCG25, vitamin C content increased by 81.28% while vitamin A content increased by 822.79% compared to the control sample. Moreover, there was a large increase in polyphenol content with the SCG25 sample showing the highest value, which was a 29.01% increase over the control sample.
Estimating the Intensity of Cargo Flows in Warehouses by Applying Guanxi Principles
Authors: Kuranovič Veslav , Sokolovskij Edgar , Bazaras Darius , Jarašūnienė Aldona , Čižiūnienė Kristina
Published: November 2023

Proper supply chain management helps to ensure business continuity considering the increased importance of globalization. Logistics processes play an important role in keeping the supply chain running smoothly, and warehouse management is one of the most important logistics activities. The movement of freight flows in the supply chain poses many challenges to the arrangement of sustainable processes at the international level. The stopping of these flows at warehouses and/or terminals temporarily and/or for longer periods of time is yet another challenge. In this respect, a number of analyses and studies have been conducted in the scientific literature to identify the most serious and frequent problems: lack of planning of work activities, partial accounting of the work performed, lack of timely accounting of the internal movement of goods within the warehouse, absence of a spare-parts management system, etc. On the other hand, warehousing processes have been analysed to identify certain efficiency gaps in freight flows within warehouses; thus, this article addresses this problem by applying guanxi principles. Using guanxi theory and practice to test various assumptions for efficient freight flow movement in warehouses, a study was conducted using quantitative and qualitative methods and expert judgment. Based on the results of the conducted empirical studies, guanxi philosophy can be concluded to have an impact on the efficient management of warehouse processes when goods are removed from a warehouse over 365 days with an annual daily loading flow rate of 103,490 t/m and a loading density of 280 kg/m3. This indicates that the application of guanxi principles is important, which reflects the intensity of the logistics processes of cargo flows and transport dynamics between guanxi and warehouse optimization.
An Assessment of the Heavy Metal Contamination, Risk, and Source Identification in the Sediments from the Liangtan River, China
Authors: Ma Teng-Fei , Wu Jin , Yu Yi-Chang , Chen Ting-Ting , Yao Yuan , Liao Wei-Ling , Feng Li , Pan Jiang
Published: November 2023

The contents of six heavy metals (HMs: Cr, Cu, As, Pb, Cd, and Zn) in sediments from the upper reaches of Liangtan River (LTR) were determined. The geo-accumulation index (Igeo), pollution load index (PLI), and potential ecological risk index (RI) were employed to assess the HM contamination in the sediments. Pearson’s correlation coefficient analysis (PCC), principal component analysis (PCA), and cluster analysis (CA) were used to infer the sources of HMs. The average concentrations of Cr, Cu, As, Pb, Cd, and Zn were 44.63 ± 25.36, 31.40 ± 22.56, 4.66 ± 2.07, 29.20 ± 27.73, 0.25 ± 0.06, and 68.87 ± 104.62 μg/g, respectively. The Igeo indicated that the Cd contamination level was unpolluted to moderately polluted. The mean PLI was 0.97 ± 0.53, suggesting that the sediments were unpolluted, but close to moderately contaminated. The RI values indicated that the potential environmental risk of HMs in the sediments of the LTR was low. The results of PCC, PCA, and CA suggested that the Cr, Cu, As, and Zn in the sediment may mainly originate from natural processes; Pb mainly comes from human industrial and agricultural production activities as well as natural processes; and the main source of Cd may be the production activities of the surrounding chemical enterprises and chemical fertilizer application in farmland.
What Drives Infrastructure Participants to Adopt Digital Technology: A Nexus of Internal and External Factors
Authors: Qiu Zhixia , Wang Shifa , Hou Yaxin , Xu Sheng
Published: November 2023

Given the potential of digital technologies in value-adding and decision support in infrastructure projects, the promotion of digital technologies, how factors of government promotion, technological development, and the organization’s technology capability and capacity influence digital technology adoption is necessary but still unclear. This research aims to identify the environmental, technological, and organizational factors, as well as the interactive relationships among them, for infrastructure participants’ intention to adopt digital technologies. The extended Technology Acceptance Model (e-TAM) was used as a theoretical base to develop a hypothesis of the influencing paths of internal and external factors, with perceived usefulness (PU), perceived ease of use (PEU), and perceived image improvement (PII) as critical internal factors, and technological and environmental factors as external factors. The questionnaire survey collected 172 valid responses and structural equation modeling was applied for the hypothesis testing. The model fitting results indicated that intentions of digital adoption are directly influenced by PU as internal factors and environmental factors, while PEU, PII, and technological factors play indirect roles. As the interaction of external and internal factors, environmental factors directly affect PEU, and technological factors significantly correlate with PU. The findings supported most of the hypothesis and contributed to providing guidance for infrastructure participants’ digital adoption practice.
Multiple-Criteria Methods for Assessing Social Sustainability in the Built Environment: A Systematic Review
Authors: Passos Neto George da Mota , Alencar Luciana Hazin , Valdes-Vasquez Rodolfo
Published: November 2023

Studies related to social sustainability assessment have presented a variety of methods and criteria, but there is a need to better understand how these studies incorporate multiple criteria along with the issues addressed, the decision-makers, and the overall process followed to promote more socially sustainable outcomes. A systematic literature review methodology is conducted to identify, analyze, and synthesize scholarly articles that use multiple criteria to assess the built environment’s social sustainability. This study explores types of problems, decision-makers, criteria, and methods adopted by researchers. The analysis involved 42 studies identified in the Web of Science, ScienceDirect, and Scopus databases. The results revealed a diverse range of studies, covering various issues, project types, and methodologies, highlighting the multifaceted nature of social sustainability evaluation in the context of the built environment. The most considered social sustainability issues in the studies were ‘Impacts in Community’ and ‘Employment’. While most of the selected papers used multi-criteria decision-making/aiding (MCDM/A), not all engaged in these methods for decision-making purposes. Moreover, despite the prevalence of studies involving multiple decision-makers, issues related to group decision-making were often insufficiently addressed. The types of problems that the methods are used for are discussed, as well as the decision context and the process for selecting methods, thereby highlighting future research opportunities. Future studies should ensure that the criteria used are manageable but encompass all facets of social sustainability in the built environment, prioritizing methodological rigor when selecting MCDM/A methods and focusing on the nuances of preference aggregation in group decision-making scenarios.
Does Low-Carbon City Construction Promote Integrated Economic, Energy, and Environmental Development? An Empirical Study Based on the Low-Carbon City Pilot Policy in China
Authors: Sun Yingshan , Zhang Rui , Du Xiaolu , Zhao Kang , Qie Xiaotong , Zhang Xiaoyi
Published: November 2023

Low-carbon urban transformation is considered the path to green economic growth in dual-carbon contexts. The low-carbon city pilot policy (LCCP) in China has vast potential to enhance the integrated development of the economy, energy, and environment (3Es). Taking 240 cities in China from 2005 to 2019 as research samples, this paper investigated the impact of LCCP on the integrated development level of the 3Es using the progressive difference-in-differences model and analyzed the mechanisms of influence. In addition, the implementation effects on different cities were analyzed using the triple difference model. The findings show that implementing the LCCP policy significantly improves the 3Es integrated development level in the sample cities, and a variety of robustness tests were used to validate this conclusion. The influence mechanism analysis shows that the primary avenues for pilot programs to contribute and successfully advance the enhancement of the low-carbon city 3Es integrated development level are technological innovation and financial development. Moreover, the heterogeneity analysis of resource endowment and geographical location shows that LCCP is beneficial to the 3Es integrated development in non-resource-based cities and eastern cities. Consequently, policy recommendations include the continuation of low-carbon pilot city expansion, joint promotion of regional 3Es integration, improving the level of technological innovation and financial development, and tailoring of policy to local circumstances. This study provides theoretical support for the evaluation of China’s LCCP and, to a certain extent, proves that the measures taken by China in the process of exploring green economic growth and realizing the dual-carbon goal are correct.
Assessing the Techno-Economic Feasibility of Waste Electric and Electronic Equipment Treatment Plant: A Multi-Decisional Modeling Approach
Authors: Cottes Mattia , Mainardis Matia , Simeoni Patrizia
Published: November 2023

Nowadays, sustainable approaches to waste management are becoming critical, due to increased generation and complex physicochemical composition. Waste electric and electronic equipment (WEEE) management, in particular, is being given increasing attention due to the continuous augment in electronic equipment usage and the limited recycling rates. In this work, a multi-objective engineering optimization approach using a decision support system (DSS) was used to analyze the feasibility of installing a WEEE treatment plant in the Friuli-Venezia Giulia region (Northeastern Italy), considering that most of the produced WEEE is currently exported outside the region. Meaningful economic and environmental parameters were considered in the assessment, together with current WEEE production and composition. Plant investment cost was in the range of EUR 7–35 M for a potentiality of 8000–40,000 ton of treated WEEE/yr, the lower bound corresponding to the WEEE produced in the region. Payback time was 4.3–10 yr, strongly depending on the market’s economic conditions as well as on plant potentiality. Proper public subsidies should be provided for a plant treating only the locally produced WEEE, establishing a circular economy. The fraction of recovered materials was 78–83%, fulfilling the current EU legislative requirements of 80% and stabilizing around values of 80% for a higher washing machine fraction. An increase in personal computers may allow to augment the economic revenues, due to the high conferral fees, while it reduces the amounts of recovered materials, due to their complex composition. CO2 emission reduction thanks to material recovery was in the range of 8000–38,000 ton CO2/yr, linearly depending on the plant potentiality. The developed DSS system could be used both by public authorities and private companies to preliminarily evaluate the most important technical, financial and environmental aspects to assess overall plant sustainability. The proposed approach can be exported to different locations and integrated with energy recovery (i.e., incineration of the non-recoverable fractions), analyzing both environmental and economic aspects flexibly.
The Fuzzy Bit
Authors: Aldana Milagrosa , Lledó María Antonia
Published: November 2023

In this paper, the formulation of Quantum Mechanics in terms of fuzzy logic and fuzzy sets is explored. A result by Pykacz, which establishes a correspondence between (quantum) logics (lattices with certain properties) and certain families of fuzzy sets, is applied to the Birkhoff–von Neumann logic, the lattice of projectors of a Hilbert space. Three cases are considered: the qubit, two qubits entangled, and a qutrit ‘nested’ inside the two entangled qubits. The membership functions of the fuzzy sets are explicitly computed and all the connectives of the fuzzy sets are interpreted as operations with these particular membership functions. In this way, a complete picture of the standard quantum logic in terms of fuzzy sets is obtained for the systems considered.
A Novel Detection and Identification Mechanism for Malicious Injection Attacks in Power Systems
Authors: Zhang Hongfeng , Wang Xinyu , Ban Lan , Sun Molin
Published: November 2023

The integration of advanced sensor technology and control technology has gradually improved the operational efficiency of traditional power systems. Due to the undetectability of these attacks using traditional chi-square detection techniques, the state estimation of power systems is vulnerable to cyber–physical attacks, For this reason, this paper presents a novel detection and identification framework for detecting malicious attacks in power systems from the perspective of cyber–physical symmetry. To consider the undetectability of cyber–physical attacks, a physical dynamics detection model using the unknown input observers (UIOs) and cosine similarity theorem is proposed. Through the design of UIO parameters, the influence of attacks on state estimation can be eliminated. A cosine similarity value-based detection criterion is proposed to replace the traditional detection threshold. To further cut down the effects caused by malicious attacks, an observer combination-based attack identification framework is established. Finally, simulations are given to demonstrate that the proposed security method can detect and identify the injected malicious attacks quickly and effectively.
Delay Differential Equations with Several Sublinear Neutral Terms: Investigation of Oscillatory Behavior
Authors: Muhsin Waed , Moaaz Osama , Askar Sameh S. , Alshamrani Ahmad M. , Elabbasy Elmetwally M.
Published: November 2023

In this work, new oscillation criteria are established for a second-order differential equation with several sublinear neutral terms and in the canonical case. To determine the oscillation conditions, we followed the Riccati approach and also compared the studied equation with a first-order delay equation. Obtaining the oscillation conditions required deducing some new relationships linking the solution to the corresponding function as well as its derivatives. The paper addresses some interesting analytical points in the study of the oscillation of equations with several sublinear neutral terms. These new findings complement some well-known findings in the literature. Furthermore, an example is provided to show the importance of the results.
Spatio-Functional Local Linear Asymmetric Least Square Regression Estimation: Application for Spatial Prediction of COVID-19 Propagation
Authors: Laksaci Ali , Bouzebda Salim , Alshahrani Fatimah , Litimein Ouahiba , Mechab Boubaker
Published: November 2023

The problem of estimating the spatio-functional expectile regression for a given spatial mixing structure Xi,Yi∈F×R, when i∈ZN,N≥1 and F is a metric space, is investigated. We have proposed the M-estimation procedure to construct the Spatial Local Linear (SLL) estimator of the expectile regression function. The main contribution of this study is the establishment of the asymptotic properties of the SLL expectile regression estimator. Precisely, we establish the almost-complete convergence with rate. This result is proven under some mild conditions on the model in the mixing framework. The implementation of the SLL estimator is evaluated using an empirical investigation. A COVID-19 data application is performed, allowing this work to highlight the substantial superiority of the SLL-expectile over SLL-quantile in risk exploration.
In Silico-Based Design of a Hybrid Peptide with Antimicrobial Activity against Multidrug-Resistant Pseudomonas aeruginosa Using a Spider Toxin Peptide
Authors: Shin Min Kyoung , Park Hye-Ran , Hwang In-Wook , Bu Kyung-Bin , Jang Bo-Young , Lee Seung-Ho , Oh Jin Wook , Yoo Jung Sun , Sung Jung-Suk
Published: November 2023

The escalating prevalence of antibiotic-resistant bacteria poses an immediate and grave threat to public health. Antimicrobial peptides (AMPs) have gained significant attention as a promising alternative to conventional antibiotics. Animal venom comprises a diverse array of bioactive compounds, which can be a rich source for identifying new functional peptides. In this study, we identified a toxin peptide, Lycotoxin-Pa1a (Lytx-Pa1a), from the transcriptome of the Pardosa astrigera spider venom gland. To enhance its functional properties, we employed an in silico approach to design a novel hybrid peptide, KFH-Pa1a, by predicting antibacterial and cytotoxic functionalities and incorporating the amino-terminal Cu(II)- and Ni(II) (ATCUN)-binding motif. KFH-Pa1a demonstrated markedly superior antimicrobial efficacy against pathogens, including multidrug-resistant (MDR) Pseudomonas aeruginosa, compared to Lytx-Pa1a. Notably, KFH-Pa1a exerted several distinct mechanisms, including the disruption of the bacterial cytoplasmic membrane, the generation of intracellular ROS, and the cleavage and inhibition of bacterial DNA. Additionally, the hybrid peptide showed synergistic activity when combined with conventional antibiotics. Our research not only identified a novel toxin peptide from spider venom but demonstrated in silico-based design of hybrid AMP with strong antimicrobial activity that can contribute to combating MDR pathogens, broadening the utilization of biological resources by incorporating computational approaches.
Structure-Based High-Throughput Virtual Screening and Molecular Dynamics Simulation for the Discovery of Novel SARS-CoV-2 NSP3 Mac1 Domain Inhibitors
Authors: Yazdani Behnaz , Sirous Hajar , Brogi Simone , Calderone Vincenzo
Published: November 2023

Since the emergence of SARS-CoV-2, many genetic variations within its genome have been identified, but only a few mutations have been found in nonstructural proteins (NSPs). Among this class of viral proteins, NSP3 is a multidomain protein with 16 different domains, and its largest domain is known as the macrodomain or Mac1 domain. In this study, we present a virtual screening campaign in which we computationally evaluated the NCI anticancer library against the NSP3 Mac1 domain, using Molegro Virtual Docker. The top hits with the best MolDock and Re-Rank scores were selected. The physicochemical analysis and drug-like potential of the top hits were analyzed using the SwissADME data server. The binding stability and affinity of the top NSC compounds against the NSP3 Mac1 domain were analyzed using molecular dynamics (MD) simulation, using Desmond software, and their interaction energies were analyzed using the MM/GBSA method. In particular, by applying subsequent computational filters, we identified 10 compounds as possible NSP3 Mac1 domain inhibitors. Among them, after the assessment of binding energies (ΔGbind) on the whole MD trajectories, we identified the four most interesting compounds that acted as strong binders of the NSP3 Mac1 domain (NSC-358078, NSC-287067, NSC-123472, and NSC-142843), and, remarkably, it could be further characterized for developing innovative antivirals against SARS-CoV-2.
Domestic Cat Hepadnavirus and Lymphoma
Authors: Beatty Julia A. , Tu Thomas , Pesavento Patricia A. , Cavasin Joao P. , Chen Min-Chun , Lidbury Jonathan A. , Steiner Joerg M. , Barrs Vanessa R. , Cullen John M.
Published: November 2023

We write to comment on Piewbang C et al [...]
A Managerial Approach towards Modeling the Different Strains of the COVID-19 Virus Based on the Spatial GeoCity Model
Authors: Vyklyuk Yaroslav , Nevinskyi Denys , Chopyak Valentyna , Škoda Miroslav , Golubovska Olga , Hazdiuk Kateryna
Published: November 2023

This study proposes a modification of the GeoCity model previously developed by the authors, detailing the age structure of the population, personal schedule on weekdays and working days, and individual health characteristics of the agents. This made it possible to build a more realistic model of the functioning of the city and its residents. The developed model made it possible to simulate the spread of three types of strain of the COVID-19 virus, and to analyze the adequacy of this model in the case of unhindered spread of the virus among city residents. Calculations based on the proposed model show that SARS-CoV 2 spreads mainly from contacts in workplaces and transport, and schoolchildren and preschool children are the recipients, not the initiators of the epidemic. The simulations showed that fluctuations in the dynamics of various indicators of the spread of SARS-CoV 2 were associated with the difference in the daily schedule on weekdays and weekends. The results of the calculations showed that the daily schedules of people strongly influence the spread of SARS-CoV 2. Under assumptions of the model, the results show that for the more contagious “rapid” strains of SARS-CoV 2 (omicron), immunocompetent people become a significant source of infection. For the less contagious “slow strains” (alpha) of SARS-CoV 2, the most active source of infection is immunocompromised individuals (pregnant women). The more contagious, or “fast” strain of the SARS-CoV 2 virus (omicron), spreads faster in public transport. For less contagious, or “slow” strains of the virus (alpha), the greatest infection occurs due to work and educational contacts.
Antiviral Potential of Azelastine against Major Respiratory Viruses
Authors: Fischhuber Katrin , Bánki Zoltán , Kimpel Janine , Kragl Natalie , Rössler Annika , Bolze Annika , Muellauer Brigitte , Angerer Joachim , Nagy Gábor , Nagy Eszter , Szijarto Valeria
Published: November 2023

The Coronavirus Disease 2019 (COVID-19) pandemic and the subsequent increase in respiratory viral infections highlight the need for broad-spectrum antivirals to enable a quick and efficient reaction to current and emerging viral outbreaks. We previously demonstrated that the antihistamine azelastine hydrochloride (azelastine-HCl) exhibited in vitro antiviral activity against SARS-CoV-2. Furthermore, in a phase 2 clinical study, a commercial azelastine-containing nasal spray significantly reduced the viral load in SARS-CoV-2-infected individuals. Here, we evaluate the efficacy of azelastine-HCl against additional human coronaviruses, including the SARS-CoV-2 omicron variant and a seasonal human coronavirus, 229E, through in vitro infection assays, with azelastine showing a comparable potency against both. Furthermore, we determined that azelastine-HCl also inhibits the replication of Respiratory syncytial virus A (RSV A) in both prophylactic and therapeutic settings. In a human 3D nasal tissue model (MucilAirTM-Pool, Epithelix), azelastine-HCl protected tissue integrity and function from the effects of infection with influenza A H1N1 and resulted in a reduced viral load soon after infection. Our results suggest that azelastine-HCl has a broad antiviral effect and can be considered a safe option against the most common respiratory viruses to prevent or treat such infections locally in the form of a nasal spray that is commonly available globally.
Enhancing Inactivated Yellow Fever 17D Vaccine-Induced Immune Responses in Balb/C Mice Using Alum/CpG
Authors: Zhang Yadan , Yang Rong , Yuan Guangying , Li Weidong , Cui Zihao , Xiao Zhuangzhuang , Dong Xiaofei , Yang Hongqiang , Liu Xiaojuan , Zhang Le , Hou Yirong , Liu Manyu , Liu Sushi , Hao Yu , Zhang Yuntao , Zheng Xiaotong
Published: November 2023

There are some concerns about the safety of live attenuated yellow fever vaccines (YF–live), particularly viscerotropic adverse events, which have a high mortality rate. The cellular production of the vaccine will not cause these adverse effects and has the potential to extend applicability to those who have allergic reactions, immunosuppression, and age. In this study, inactivated yellow fever (YF) was prepared and adsorbed with Alum/CpG. The cellular and humoral immunities were investigated in a mouse model. The results showed that Alum/CpG (20 μg/mL) could significantly increase the binding and neutralizing activities of the antibodies against YF. Moreover, the antibody level at day 28 after one dose was similar to that of the attenuated vaccine, but significantly higher after two doses. At the same time, Alum/CpG significantly increased the levels of IFN-γ and IL-4 cytokines.
Species Diversity of Zooplankton of Small Steppe Lakes of the Northern Part of Kazakhstan
Authors: Satybaldiyeva Gulmira , Sapargaliyeva Nazym , Sharakhmetov Sayat , Inelova Zarina , Boros Emil , Krupa Elena , Utarbayeva Aizhan , Shupshibayev Kazbek
Published: November 2023

The inland waters of Northern Kazakhstan are important components of the ecosystems of this region and have unique characteristics. Endorheic steppe lakes are important ecosystems with significant ecological value. They play an important role in maintaining biodiversity, they provide water resources for living organisms, they serve as breeding and migration sites for various animal species, and their zooplankton communities have a key role in the trophic web of these waters. Therefore, the purpose of this work is to study the diversity of zooplankton communities in some small steppe lakes in the northern part of Kazakhstan (Pavlodar, Kostanay, North Kazakhstan, and Akmola regions), which have different environmental conditions. Sampling to study the species diversity of zooplankton in the steppe water bodies of Northern Kazakhstan was carried out from 13 areas, 12 of which are plain lakes, and 1 of which is a reservoir, and sampling was performed in 2021 and 2022 during in the spring, summer, and autumn periods. Within the research period of 2021–2022, between 6 and 36 species of zooplankton were found in small steppe lakes. A total of 92 taxa were found. Rotifers (46 taxa) were found to have the richest number of species representatives. Cladocera were represented by 21 taxa, and Copepods by 25 taxa. All studied steppe lakes in the northern part of Kazakhstan are characterized by high specificity in terms of taxonomic composition, since the similarity indices did not exceed 0.632. According to cluster analysis, the studied samples of water bodies are divided into five clusters, in which lakes with a relatively similar taxonomic composition are combined. The halophile species (e.g., Arctodiaptomus salinarus) indicate water salinization. Our results confirm the applicability of the use of zooplankton in assessing water quality and the current ecological state of aquatic ecosystems.
Bed Topography Inference from Velocity Field Using Deep Learning
Authors: Kiani-Oshtorjani Mehrdad , Ancey Christophe
Published: November 2023

Measuring bathymetry has always been a major scientific and technological challenge. In this work, we used a deep learning technique for inferring bathymetry from the depth-averaged velocity field. The training of the neural network is based on 5742 laboratory data using a gravel-bed flume and reconstructed velocity fields, namely the topographies were obtained from real-world experiments, and the velocity fields were estimated using a statistical model. To examine the predictive power of the proposed neural network model for bathymetry inference, we applied the model to flume experiments, numerical simulations, and field data. The results showed the model properly estimates topography, leading to a model for riverine bathymetry estimation with a 31.3% maximum relative error for the case study (confluence of the Kaskaskia River with the Copper Slough in east-central Illinois state, USA).
Review of Isotope Hydrology Investigations on Aquifers of Cameroon (Central Africa): What Information for the Sustainable Management of Groundwater Resources?
Authors: Nlend Bertil , Huneau Frederic , Ngo Boum-Nkot Suzanne , Song Fricelle , Komba David , Gwodog Bernard , Meyoupe Parfait , Djieugoue Boris , Fongoh Enoh
Published: November 2023

In Central Africa, groundwater remains the least understood component of the water cycle. Isotopic techniques that are well known to be efficient in tracking the movement of water along its path have been applied for only three decades and can be summarized in a handful of case studies. This review aims to put together all the stable and radioactive isotopic data (>500 samples from rainfall, surface and groundwater) published in Cameroon to: (i) identify the drivers responsible for precipitation isotopes’ spatial variation and climatological implications, (ii) elucidate the groundwater recharge mechanisms over the countries and relationships with rivers, and (iii) highlight the existence of paleo-groundwater in the country. It is found that rainfall stable isotope variation is linked to the migration of the Intertropical Convergence Zone (ITCZ): the groundwater recharge can be diffuse and focused. This latter mechanism is mainly observed in the semi-arid region. It is in this relatively dry region that most of the paleo-groundwater resources are identified thanks to 14C dating. This information will be useful to develop water management strategies regarding all the challenges (e.g., climatic and demographic) faced by the country. Finally, this paper discusses the gaps groundwater isotope hydrology can still fill for contributing to a sustainable development of the country.
Environmental Degradation of Oxo-Biodegradable Polyethylene Bags
Authors: Heimowska Aleksandra
Published: November 2023

The purpose of the present study is the estimation of the environmental degradation process of oxo-biodegradable polyethylene bags. The degradation process of polyethylene samples, with the addition of a d2w prodegradant, was studied under natural weathering, freshwater (pond), and water in laboratory condition for a period of 48 months. The impact of characteristic parameters of environments on the extent of degradation, monitored by weight changes, mechanical properties, and surface morphology, has been discussed. The degraded polymer samples were also analyzed by FTIR spectroscopy. It was established that the oxo-biodegradable polyethylene samples were hardly prone to degradation in natural freshwater, but more vulnerable to environmental weathering. Abiotic parameters (oxygen, temperature, solar radiation) played a more important role in the degradation process of oxo-biodegradable polyethylene than biotic parameters (microorganisms). Natural weathering led to first fragmentation of the polymeric samples after 18 months, weight loss to 81.6% after 39 months, and complete assimilation after 45 months. In the pond, 48 months incubation resulted in an increase in the weight of the samples (+19%) and a decrease in mechanical properties: tensile strength from 26.31 to 17.35 MPa and elongation at break from 304 to 31%. The biofilm formed on the polymer surface made it difficult for oxygen to reach the degraded material, so oxydegradation in the pond was slower. ATR-FTIR analysis and microscopic observations confirm the degradation taking place in natural environments. No visible degradation changes were observed in the oxo-biodegradable polyethylene after incubation under laboratory water, because of the lack of microorganisms and solar radiation. The degradation of oxo-biodegradable polyethylene in natural environments required a longer incubation time compared to the degradation time declared by the manufacturer.
Ecotoxicity Assessment of the Water Extracts from Metal-Contaminated and Hydrocarbon-Contaminated Soils
Authors: Li Qian , Yin Juan , Wu Lingling , Fu Rongbing , Chen Ling
Published: November 2023

Soil water extracts could help to quickly assess the potential hazard of contaminants in soil, groundwater, and surrounding receiving water. In this study, the adverse effects of water extracts obtained from soils contaminated by heavy metals (sites A and B) or hydrocarbons (sites C, D and E) were evaluated using wheat, pak choi, and zebrafish. The test results obtained with freeze-dried soil samples showed a good correlation with those obtained from fresh wet soil samples. Phytotoxicity level was found to be greater in samples obtained from the metal-contaminated site B as compared to those from site A, whereas the opposite was observed for the zebrafish embryo acute toxicity. The water-soluble fractions of petroleum hydrocarbons in soils from sites C and D pose ecological risks to the environment, even though the concentrations of total petroleum hydrocarbon were below the established screening value. The results obtained with our battery of biological assays could complement the ecological risk estimation of a complex mixture of contaminants in soils. Site-specific ecological risk assessment using chemical analytical data, screening values, and ecotoxicity testing with soil water extracts could serve as a screening approach to identify the impact of contaminated soils on the freshwater environment.
Continuous Hydrogen Production via Hydrothermal Gasification of Biodiesel Industry Wastewater: Experimental Optimization and Energy Integration Simulation
Authors: Teixeira Isabela R. , Dias Isabela M. , Mourão Lucas C. , Andrade Laiane A. , Pavão Leandro V. , Abelleira-Pereira Jose M. , Souza Guilherme B. M. , Cardozo-Filho Lucio , Alonso Christian G. , Guirardello Reginaldo
Published: November 2023

This study reports the continuous production of H2 from the wastewater effluent of the biodiesel industry in a medium containing water under supercritical conditions. The effects of temperature and feed flow rate on the generation of hydrogen were evaluated and optimized. At a temperature of 700 °C and a 17.5 mL/min feed flow, a total gas flow of 5541 NmL/min was achieved. Among all identified gases, hydrogen represented the highest molar fraction of 73%. Under optimized conditions, a H2 yield of 357 NmL/geffluent feed was observed. The experimental results indicate a significant increase in the H2 production at the highest experimented temperatures. On the other hand, the feed flow only slightly influenced the process within the assessed range but showed a tendency to increase the H2 production at the highest values. Finally, information on energy efficiency optimization and scale-up are presented, and at the same time, different designs for industrial implementation of the hydrothermal gasification process are proposed.