bluuebunny/crossref_metadata_2025 huggingface dataset:
Historical Trend Analysis and Forecasting of Shoreline Change at the Nile Delta Using RS Data and GIS with the DSAS Tool
Authors: Abd-Elhamid Hany F. , Zeleňáková Martina , Barańczuk Jacek , Gergelova Marcela Bindzarova , Mahdy Mohamed
Published: March 2023

Coastal areas are increasingly endangered by climate change and associated sea level rise, which could have serious consequences, such as shoreline erosion and coastal city submergence. The current study aims to conduct a historical trend analysis (HTA) and predict the shoreline changes of the Nile Delta coasts. The Digital Shoreline Analysis System (DSAS) software, with the GIS environment, is used for monitoring the shoreline changes using a number of statistical methods (SCE, NSM, EPR, WLR and LRR). Satellite images from 1974 to 2022 were collected and geometrically corrected using supervised classification to detect the shoreline change of the Nile Delta. The GIS was used for detecting and monitoring changes in the shoreline, as well as forecasting future changes in the shoreline for the next 10 and 20 years (2033–2043). The critical sections of the Nile Delta were identified, and a time series analysis of shoreline changes was conducted. For each section, linear equations were established to predict probable changes in the shoreline. Between 1974 and 2022, the shoreline of the Nile Delta moved inland in different directions due to coastal erosion, and predictions indicate that this erosion will continue until both 2033 and 2043, particularly affecting the Rosetta and Damietta sections. The erosion rate ranged between 30–60 and 10–25 m/year at Rosetta and Damietta, respectively, but at Manzala, it ranged between 8–15 m/year. Continued erosion of the Nile Delta shoreline could have severe consequences that could affect the inhabitants, economy, buildings, roads, railways, and ports. These areas need an integrated coastal management strategy which incorporates increasing consciousness, urban development, and the implementation of rules and adaptation plans. The results of the current study and forecasting the shoreline change could help in protecting such areas.
Simultaneous Retrieval of Corn Growth Status and Soil Water Content Based on One GNSS Antenna
Authors: Li Jie , Hong Xuebao , Wang Feng , Yang Lei , Yang Dongkai
Published: March 2023

The retrieval of crop growth status using Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) has become a major area of interest within the field of vegetation remote sensing in recent years. Using only a single GNSS antenna, it is difficult to determine the crop growth status and soil water content (SWC) in vegetation-covered regions due to plenty of multi-path signals. Based on the empirical mode decomposition and the spectrum difference, this study presents an algorithm that can decompose and separate signals reflected by the soil surface or corn canopy. Because the low-roughness soil surface is isotropic while the corn canopy is anisotropic, the signals reflected by the soil surface have a higher proportion of coherent components than those reflected by the corn canopy. The moduli between the retrieved heights and the actual heights (for the same interval from different satellites) have the least variance. In this study, the signals reflected by the soil surface and the corn canopy are separated using the variance of retrieved heights. When the corn grows taller than the GNSS antenna, the vegetation water content (VWC) of the corn leaves becomes the primary factor affecting the direct signal’s intensity, as the leaves obstruct the signal. Hence, the VWC of corn leaves can be calculated through the power attenuation of signals. An experiment performed on a plot of land covered with corn shows that, after multi-GPS-satellite fusion, the correlations between the retrieved corn canopy height, leaf VWC, soil water content (SWC), and in situ data reach 0.94, 0.92, and 0.88, respectively. The corresponding root mean square errors are 0.195 m, 0.0055 kg/cm2, and 0.0484 cm3/cm3, respectively.
Impacts of Water Resources Management on Land Water Storage in the Lower Lancang River Basin: Insights from Multi-Mission Earth Observations
Authors: Zhang Xingxing
Published: March 2023

Climate change and heavy reservoir regulation in the lower Lancang River basin (LLRB) have caused significant impacts on terrestrial water storage (TWS) in several ways, including changes in surface water storage (SWS), soil moisture storage (SMS), and groundwater storage (GWS). Understanding these impacts is crucial for promoting comprehensive cooperation in managing and utilizing water resources within the basin. This study utilized multi-mission Earth observation (EO) datasets, i.e., gravimetry (GRACE/-FO), altimetry (Jason-2, Sentinel-3, and Cryosat-2), imagery (Sentinel-1/2), and microwave sensors (IMERG), as well as gauged meteorological, hydrological data and reanalysis products, to investigate the spatial-temporal variation of water resources in the LLRB. The study shows that the fluctuations in precipitation and the construction of reservoirs are the primary drivers of changes in the TWS anomaly (TWSA) in the region. Precipitation decreased significantly from 2010 to 2019 (−34.68 cm/yr), but the TWSA showed a significant increase (8.96 cm/yr) due to enhanced water storage capacity in the Xiaowan and Nuozhadu reservoirs. SWS and GWS were also analyzed, with SWS showing a decrease (−5.48 cm/yr) from 2010 to 2019 due to declining precipitation and increasing evaporation. GWS exhibited a steady rise (9.73 cm/yr) due to the maintenance of groundwater levels by the reservoirs. This study provides valuable insights into the potential of EO data for monitoring water resources at a regional scale.
The “Greenium” in Green Bonds: How Did It Change with COVID-19?
Authors: Intonti Mariantonietta , Serlenga Laura , Ferri Giovanni , De Leonardis Matteo , Starace Giuseppe
Published: March 2023

This paper focuses on the study of the “greenium”, i.e., the premium on Green Bonds (GBs) vs. Traditional Bonds (TBs) whereby investors accept lower yields of GBs vs. TBs, which is caused by the important difference between them with reference to their contribution to the green transition, specifically paying attention to the influence of the COVID-19 pandemic on it. The conjecture of this paper is that the negative shock of rates due to the pandemic crisis has increased the greenium, as it has also increased the interest in projects of the green transition. In addition, a hypothesis is made that the risk of breaking the green promises might be higher for corporations than for governments and, hence, that the greenium would be lower for corporate GBs than for government GBs. Finally, the possibility that the post-pandemic changes of the greenium might vary depending on individual GBs’ liquidity is considered. The empirical analyses provide support for the first two hypotheses but not for the third one.
Modified Nanocellulose-Based Adsorbent from Sago Waste for Diclofenac Removal
Authors: Che Su Noorhaslin , Basirun Ain Aqilah , Hameed Sultan Nor Shahroon , Kanakaraju Devagi , Wilfred Cecilia Devi
Published: March 2023

A nanocellulose-based adsorbent was successfully synthesized via a hydrothermal process. It was characterized by X-ray diffraction, Fourier Transform Infrared Spectroscopy, Field Emission Electron Microscopy and Brunauer–Emmett–Teller surface area analysis. Photocatalysis has the best potential to replace the conventional wastewater treatment technology through the photodegradation of organic contaminants. This study focuses on the preparation of a photocatalytic adsorbent of nanocellulose prepared from sago waste for the removal of diclofenac from industrial wastewater. Its photocatalytic activity was evaluated through the degradation of diclofenac (100 mg/L) under ultraviolet (UV) light. The effect of different loadings of TiO2 and kinetics on the photocatalytic activity was investigated. To study its removal, the experiments were carried out under UV light with different contact times ranging from 30 to 120 min at room temperature. The maximum removal percentage was found to be 57.5% for 200 µL of TiO2, and this increased up to 82.4% for 800 µL of TiO2. The maximum removal capacity was found to be 13.3 mg/g. The kinetics was well fitted with “pseudo-first order model” (PSO). Kinetic analysis using the PSO model at 100 ppm of diclofenac sodium gave a value of equilibrium adsorption capacity, qe of 13.52 mg/g. The adsorption kinetics gave a value of calculated equilibrium adsorption capacity, qe of 13.52 mg/g using different non-linear regression plots. It obeyed a pseudo-first-order reaction with the lowest AICc, RSME values of 0.56 and 0.53 and the highest correlation coefficient, R2, of 0.99. Three kinetics models were fitted for the current adsorption kinetics data, and their suitability was inferred as the following: pseudo-first-order > pseudo-second-order > Langmuir–Hinshelwood.
Application of Fuzzy Logic and SNA Tools to Assessment of Communication Quality between Construction Project Participants
Authors: Trach Roman , Khomenko Oleksandr , Trach Yuliia , Kulikov Oleksii , Druzhynin Maksym , Kishchak Nataliia , Ryzhakova Galyna , Petrenko Hanna , Prykhodko Dmytro , Obodіanska Olha
Published: March 2023

The purpose of this research is to study the communication network among the participants in a construction project. The proposed approach contains the solving of the following tasks: identification of the key factors that affect the communication quality; calculation of the “communication quality” indicator between each pair of participants using fuzzy logic; and evaluation of the key measures of centrality using the tools of a Social Network Analysis. Solving the set tasks can help break the problem of the low level of efficiency of construction project deliveries. This study was conducted when the design stage was already complete and the construction project had 17 participants. We used the following factors influencing communication quality: timeliness, understanding, bidirectionality, use of IT tools in communication acts and adequacy. The use of fuzzy logic tools can minimise the subjectivity of the qualitative data obtained from the questionnaires. The analysis of five centrality measures showed that “Project manager”, “Chief engineer”, “Construction site manager”, “Construction works manager” and “Architect” had the greatest values in comparison with other network participants. On the one hand, this organisational structure of communication can be considered correct because the main information flows through the project managers, who make the decisions. On the other hand, this indicates a significant dependence of the construction project on these participants and, in the event of certain risk events, may lead to a decrease in the efficiency of its implementation. The methods presented in this article can be used in project management to analyse a real communication network.
Research on a Sustainable Teaching Model Based on the OBE Concept and the TSEM Framework
Authors: Zheng Wei , Wen Shiting , Lian Bin , Nie Ya
Published: March 2023

This paper reports the results of a study on the implementation of a sustainable teaching model based on the OBE (Outcome-Based Education) concept and the TSEM (Teach, Study, Evaluate, and Manage) framework in computer science and technology at NingboTech University, China. In the context of digital education, the OBE concept and the TSEM framework are integrated to explore sustainable teaching and learning models based on “artificial intelligence and education”. Based on the core concept of engineering professional education accreditation, the course is designed by using the PCCM (Professional Competency Correlation Matrix) method to build a model based on big data analysis, deepen the classroom teaching reform of “artificial intelligence and education”, and explore the integrated digital sustainable teaching mode of “teaching, learning, evaluation, and management”. The aim of this study is to explore the effectiveness of the teaching model based on OBE and the TSEM framework on students’ sustainable development. The results show that students deepen their learning in computer science while enhancing their own learning initiative, teamwork skills, innovation skills, and awareness of sustainable development. Research shows that our teaching model plays an important role in the development of student sustainable education, enhancing student engineering practice and innovation capabilities and cultivating applied innovative talents. The efficacy of the teaching model based on the OBE concept and the TSEM framework for improving students’ competence in sustainable education warrants further investigation.
Appraisal of Climate Response to Vegetation Indices over Tropical Climate Region in India
Authors: Awasthi Nitesh , Tripathi Jayant Nath , Petropoulos George P. , Gupta Dileep Kumar , Singh Abhay Kumar , Kathwas Amar Kumar , Srivastava Prashant K.
Published: March 2023

Extreme climate events are becoming increasingly frequent and intense due to the global climate change. The present investigation aims to ascertain the nature of the climatic variables association with the vegetation variables such as Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI). In this study, the impact of climate change with respect to vegetation dynamics has been investigated over the Indian state of Haryana based on the monthly and yearly time-scale during the time period of 2010 to 2020. A time-series analysis of the climatic variables was carried out using the MODIS-derived NDVI and LAI datasets. The spatial mean for all the climatic variables except rainfall (taken sum for rainfall data to compute the accumulated rainfall) and vegetation parameters has been analyzed over the study area on monthly and yearly basis. The liaison of NDVI and LAI with the climatic variables were assessed at multi-temporal scale on the basis of Pearson correlation coefficients. The results obtained from the present investigation reveals that NDVI and LAI has strong significant relationship with climatic variables during the cropping months over study area. In contrast, during the non-cropping months, the relationship weakens but remains significant at the 0.05 significance level. Furthermore, the rainfall and relative humidity depict strong positive relationship with NDVI and LAI. On the other, negative trends were observed in case of other climatic variables due to the limitations of NDVI viz. saturation of values and lower sensitivity at higher LAI. The influence of aerosol optical depth was observed to be much higher on LAI as compared to NDVI. The present findings confirmed that the satellite-derived vegetation indices are significantly useful towards the advancement of knowledge about the association between climate variables and vegetation dynamics.
Heterogenous Urbanization and Agricultural Green Development Efficiency: Evidence from China
Authors: Ge Pengfei , Liu Tan , Wu Xiaoxu , Huang Xiulu
Published: March 2023

Realizing green development in agriculture is fundamental to sustained economic development. As a measure to facilitate the transfer of rural population, urbanization is considered to be strategic in promoting agricultural green development. This paper employs a SBM-DDF–Luenberger method to measure agricultural green total factor productivity (AGTFP) and the agricultural labor surplus in China, and empirically tests the heterogeneous effects of household registration urbanization, permanent residence urbanization, and employment urbanization on the efficiency of agricultural green development. The results reveal that: (1) the average annual growth rate of China’s AGFTP is 4.4374%, which is achieved mainly through improvements in green scale efficiency. (2) The agricultural sector in China is suffering a large surplus of labor force, with an estimation of 20.64 million in 2020. (3) Both household registration urbanization and permanent residence urbanization have a significant promoting effect on agricultural green development efficiency, though the former promotes less. (4) Employment urbanization improves agricultural green development efficiency by providing employment guidance for migrant workers, and employment urbanization of the tertiary industry has a more pronounced improvement effect. The findings suggest that governments remove restrictions on the household registration system and actively guide surplus agricultural laborers to engage in urban service industries to provide an impetus for promoting green agricultural development.
Looking Back—Australia’s Sustainable Development and Climate Change Policy Agendas
Authors: Brolan Claire E.
Published: March 2023

In November 2022, a climate change performance index report released at the COP27 United Nations conference in Egypt, ranked Australia 55th on a list of 63 countries and country groupings in addressing the climate crisis. Australia is a leading development partner in the Pacific region; a region economically, environmentally, socially, and culturally impacted by climate change and global warming in the form of (e.g.,) rapid sea level rises, alarming shifts in marine ecosystems, and extreme weather events. How did Australia, a high-income country situated in the Pacific, become a nation that trails other developed countries in addressing climate change? Why has there been a lack of urgency for uptake of sustainable development policy and planning? A new Federal Government, elected in May 2022, has indicated willingness to meaningfully progress Australia’s interconnected climate change, wellbeing, and sustainability policy agendas, in which futures public health policy is inextricably linked. This change in government provides an important moment to review Australia’s sustainable-development climate change policy landscape over a 35-year period. By examining this landscape through a health lens, this paper can provide one of many critical perspectives tracing Australia’s slippage to the bottom of the global climate rankings today.
Hybrid Statistical and Machine Learning Methods for Daily Evapotranspiration Modeling
Authors: Küçüktopcu Erdem , Cemek Emirhan , Cemek Bilal , Simsek Halis
Published: March 2023

Machine learning (ML) models, including artificial neural networks (ANN), generalized neural regression networks (GRNN), and adaptive neuro-fuzzy interface systems (ANFIS), have received considerable attention for their ability to provide accurate predictions in various problem domains. However, these models may produce inconsistent results when solving linear problems. To overcome this limitation, this paper proposes hybridizations of ML and autoregressive integrated moving average (ARIMA) models to provide a more accurate and general forecasting model for evapotranspiration (ET0). The proposed models are developed and tested using daily ET0 data collected over 11 years (2010–2020) in the Samsun province of Türkiye. The results show that the ARIMA–GRNN model reduces the root mean square error by 48.38%, the ARIMA–ANFIS model by 8.56%, and the ARIMA–ANN model by 6.74% compared to the traditional ARIMA model. Consequently, the integration of ML with ARIMA models can offer more accurate and dependable prediction of daily ET0, which can be beneficial for many branches such as agriculture and water management that require dependable ET0 estimations.
Emerging Virtual Communities of Practice during Crises: A Sustainable Model Validating the Levels of Peer Motivation and Support
Authors: Fayez Orchida , Ismail Hala , Aboelnagah Hadeer
Published: March 2023

The purpose of this study is to validate the role of social media among peers in a virtual community of practice, VCoP, by applying the Delphi technique of data collection and analysis. The study adopts the Grounded Theory methodology to identify the theoretical frame that is developed from the data analysis. The research design identified the areas of social and professional support from Maslow’s hierarchy of human needs from the faculty members’ responses that were chosen by “purposive sampling” rather than random sampling The qualitative data collection took three months, wherein 26 faculty members interacting on WhatsApp during COVID-19 were identified as experts: one of the corner elements of the Delphi technique. The thematic analysis of the results indicated that fulfilling Maslow’s needs was an integral component of social media VCoP. However, unlike Maslow’s model, expressions of the need for safety, belonging, self-esteem, and self-actualization took turns as the most important need depending on changing context, gender, and individual preferences. The answer to the research questions, thus, becomes embedded in the research methodology that involves instructors’ perceptions as a validating element of the findings. The main recommendation is to replicate the study in various contexts to monitor faculty well-being to reach a sustainable educational environment.
Affecting of Nature and Human Activities on the Trend of Vegetation Health Indices in Dak Nong Province, Vietnam
Authors: Hiep Nguyen Van , Thao Nguyen Thi Thanh , Viet Luong Van , Luc Huynh Cong , Ba Le Huy
Published: March 2023

This study aims to evaluate the effects of natural and human conditions on vegetation covers using VCI and TCI indices (the satellite-based Vegetation Health Indices (VHIs)) in Dak Nong province. Factors affecting the VHIs included in the analysis involve land use, soil, population, topography, distance to roads and surface water. The data analysis period is the dry season from 2000 to 2020. The trend of the VHIs’ change in this study is analyzed using Sen’s method with monitoring data from Modis. The effects of factors affecting the VHIs are based on logistic regression and discriminant analysis. The analysis results show that the VHIs are clear and show both increasing and decreasing trends. Based on logistic regression analysis, the influence of land use types on the trend of the VHIs in the direction of increasing from negative to positive will be from PdF, UnL, AnC, SpF, PtF, PeA and then to PdR. Corresponding to the soil will be from ACa, FRp, FRx, FRr, ACh, LVx, FLg and then to LVg. Based on the discriminant analysis method, it was found that there are only four primary factors affecting the trend of the VHIs in order of decreasing level of closure: population density, land use, soil and population growth rate and to the road. These results show that in places where labour resources are available, plants are interested in investment due to high profits, nutrient-rich soil and convenience for plant care; the VHIs tend to increase and vice versa. Compared with VCI, the trend of TCI tends to be sloping negative and more pessimistic. Through the coefficients of the logistic regression equation and the difference function, the TCI is more sensitive than the VCI when the independent variables change, especially for changes in population density and land use. Thus, TCI can be considered the preferred option for assessing vegetation health trends in the context of climate change.
Effects of Different Materials on Biogas Production during Anaerobic Digestion of Food Waste
Authors: Dompara Iliana , Maragkaki Angeliki , Papastefanakis Nikolaos , Floraki Christina , Vernardou Dimitra , Manios Thrassyvoulos
Published: March 2023

One of the best methods for turning different types of biomass into clean energy is anaerobic digestion (AD). Organic and inorganic additives may be employed in the AD process to increase biogas output. It has been demonstrated that inorganic additives, such as micronutrients, can improve the efficiency of biogas producing reactors. These trace items can be introduced to the AD process as powders. The use of metal oxides in engineering and environmental research has become more popular. This study focuses on the role of TiO2 and ZnO/Ag powders on anaerobic digestion. Food waste studies on biochemical methane potential were performed with and without TiO2 and ZnO/Ag powders to examine their impact on AD. All powders are grown through the hydrothermal procedure, which has proved to be environmentally friendly and low in cost, presenting the capability to simply control the materials’ characteristics at mild temperatures. The addition of ZnO/Ag and TiO2 improved the biogas cumulative yield by 12 and 44%, respectively, compared to the control reactor. In addition, volatile solids (VS) removal efficiency increased by 5.7% in the food wastes (FW) and TiO2 reactor, while total chemical oxygen demand (TCOD) removal efficiency increased by 22% after the addition of ZnO/Ag.
RETRACTED: Baig et al. Digital Entrepreneurship: Future Research Directions and Opportunities for New Business Model. Sustainability 2022, 14, 5004
Authors: Baig Umair , Hussain Batool Muhammad , Meidute-Kavaliauskiene Ieva , Davidavicius Sigitas
Published: March 2023

The Journal retracts the article entitled “Digital Entrepreneurship: Future Research Directions and Opportunities for New Business Model” by Baig et al [...]
Mathematical Modeling for Evaluating the Sustainability of Biogas Generation through Anaerobic Digestion of Livestock Waste
Authors: Abilmazhinov Yermek , Shakerkhan Kapan , Meshechkin Vladimir , Shayakhmetov Yerzhan , Nurgaliyev Nurzhan , Suychinov Anuarbek
Published: March 2023

The paper investigates the mathematical modeling of anaerobic fermentation for the utilization of animal wastes. It analyzes various approaches to the mathematical modeling of anaerobic digestion processes. However, most of the models previously proposed do not take into account a number of key parameters such as the levels of micro and macronutrientls (such as K, Na, Ca, Mg, Mo, etc.), values of volatile fatty acids, C/N ratio, pH levels, extent of grinding, moisture, and others. This paper proposes a new mathematical model of anaerobic fermentation under industrial scale conditions. The model was developed on the basis of regression analysis and correlation. It found empirical relationships between biogas yield and 26 different parameters. These parameters are measured by appropriate biosensors in industrial production. Some of them have more significant influence on the fermentation process than others. Overall, the developed mathematical model has the potential to provide useful insights into biogas production and can be used to optimize anaerobic fermentation processes.
Sustaining English Language Education with Social Networking Sites (SNSs): A Systematic Review
Authors: Tan Siok Yong , Md Yunus Melor
Published: March 2023

Mastery of the English language has always been major impediment to many educators and learners around the world. In this rapidly globalising world, social networking sites (SNSs) have risen to the top, especially during the unprecedented advent of the COVID-19 pandemic. Nevertheless, the review of SNSs regarding the English education field is scant, in spite of its significance for sustainability education. On that account, this systematic literature review highlights the potential benefits of using SNSs for educational practices. Using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement, 23 articles from 2018 to 2022 were accessed from three databases, particularly Scopus, Web of Science (WoS), and Educational Resources Information Centre (ERIC). First, the reviewed articles manifest that Facebook is the most frequently used SNSs for English educational purposes. Second, the findings indicated that SNSs have shown a positive impact in enhancing English language competency and improving learning attributes. Third, this review addressed the challenges of using SNSs in the English education field. These findings inferred that there are still research gaps related to the use of SNSs in sustaining English language education. Substantially, this review is advantageous for prospective researchers in identifying the research gaps regarding the use of SNSs for English teaching and learning.
Overview of Walking Rates, Walking Safety, and Government Policies to Encourage More and Safer Walking in Europe and North America
Authors: Buehler Ralph , Pucher John
Published: March 2023

Walking is the most sustainable means of daily travel for short trip distances and is a key component of the overall transport system. This paper documents variation in walking rates among countries, cities in the same country, and in different parts of the same city. Our international analysis of official government statistics shows that walking rates are highest for short trips, higher for women than for men, decline with increasing income, and remain constant as age increases. Walking fatality rates are much higher in the USA compared with the other countries we examined, both per capita and per km walked. Government policies that would increase walking rates while improving pedestrian safety include: integrated networks of safe and convenient walking infrastructure; roadways and intersections designed for the needs of pedestrians; land-use regulations that encourage mixed uses and short trip distances; lower city-wide speed limits and traffic calming in residential neighborhoods; reduced supply and increased price of parking; traffic laws that give priority to pedestrians; improved traffic education for motorists and non-motorists; tax surcharges on large personal vehicles; and strict enforcement of laws against drink and distracted driving. Five decades of success with these policies in many European cities provide practical examples for car-oriented cities to follow, especially in North America.
Estimation of Modulus of Deformation Using Rock Mass Rating—A Review and Validation Using 3D Numerical Modelling
Authors: Bellapu Hema Vijay Sekar , Sinha Rabindra Kumar , Naik Sripad Ramchandra
Published: March 2023

The Himalayan region has enormous potential for hydropower development. However, variations in geological and geotechnical conditions pose challenging tasks for the designers. If these variations are not tackled in a timely manner during underground excavations, especially for caverns, instabilities may occur, resulting in time and cost over-runs. For sustainable hydropower development, minimizing these over-runs is necessary. The modulus of deformation (Ed) of a rock mass is an essential input parameter required in the design of underground excavations. This study involves collecting the results of extensive in situ tested values for various hydroelectric projects in the Himalayan regions, along with the rock mass rating (RMR) values at 35 test sites. Ed is estimated empirically based on statistical analysis. Comparisons were made with the empirical equations already available in the literature, using RMR and the proposed equation for estimating Ed. Although different researchers have proposed many equations for estimating the value of Ed using RMR, a gap exists in validating such equations. In this regard, the proposed equation for Ed was verified by carrying out 3D numerical-modelling studies using FLAC3D, an explicit finite-difference software for an underground powerhouse cavern and comparing the displacement values with the field instrumentation data.
Tourist Behavior and Sustainable Tourism Policy Planning in the COVID-19 Era: Insights from Thailand
Authors: Srisawat Purim , Zhang Wuyi , Sukpatch Kassara , Wichitphongsa Wachira
Published: March 2023

The COVID-19 outbreak has drastically altered the behavior of tourists, posing a significant challenge to countries that heavily rely on the tourism industry to develop sustainable policies. This study utilizes structural equation modeling (SEM) techniques to analyze the effects of four variable groups on travel decisions during the pandemic. These groups include tourism potential, tourism logistics efficiency, the impact of COVID-19 on tourism potential, and the impact of COVID-19 on logistics efficiency. We collected data from a sample group of 943 foreign tourists visiting Thailand through online and on-site questionnaires. Our findings reveal that accommodation and information flow were the most significant factors affecting travel decisions during the pandemic, while the mode of transport had minimal impact. Based on our results, we recommend that post-COVID-19 tourism policies focus on improving accommodation quality and hygiene standards and building networks that offer comprehensive and up-to-date information about the pandemic. Our proposed approach is more efficient and cost-effective than mobilizing resources across all tourism industry sectors. It promotes sustainable tourism recovery planning while minimizing adverse effects on the community. These results are particularly relevant to stakeholders and policymakers who have been heavily affected by the COVID-19 pandemic and need to develop effective tourism policies.
A Shuffled Frog-Leaping Algorithm with Cooperations for Distributed Assembly Hybrid-Flow Shop Scheduling with Factory Eligibility
Authors: Lei Deming , Dai Tao
Published: March 2023

The distributed assembly scheduling problem with a hybrid-flow shop for fabrication is seldom studied, and some real-life constraints such as factory eligibility are seldom handled. In this study, a distributed assembly hybrid-flow shop-scheduling problem (DAHFSP) with factory eligibility is investigated, which has some symmetries on machines. A shuffled frog-leaping algorithm with cooperations (CSFLA) is applied to minimize makespan. A problem-related feature is used. Memeplexes are evaluated, and group 1, with the two best memeplexes, and group 2, with the two worst memeplexes, are formed. A new cooperation between memeplexes and an adaptive search strategy are implemented in groups 1 and 2, respectively. An adaptive cooperation between groups 1 and 2 is also given. Population shuffling is executed every T generations. A number of computational experiments are conducted. Computational results demonstrate that new strategies are effective and CSFLA is a very competitive algorithm for DAHFSP with factory eligibility.
A Quasi-Affine Transformation Evolutionary Algorithm Enhanced by Hybrid Taguchi Strategy and Its Application in Fault Detection of Wireless Sensor Network
Authors: Pan Jeng-Shyang , Wang Ru-Yu , Chu Shu-Chuan , Tseng Kuo-Kun , Fan Fang
Published: March 2023

A quasi-affine transformation evolutionary algorithm improved by the Taguchi strategy, levy flight and the restart mechanism (TLR-QUATRE) is proposed in this paper. This algorithm chooses the specific optimization route according to a certain probability, and the Taguchi strategy helps the algorithm achieve more detailed local exploitation. The latter two strategies help particles move at random steps of different sizes, enhancing the global exploration ability. To explore the new algorithm’s performance, we make a detailed analysis in seven aspects through comparative experiments on CEC2017 suite. The experimental results show that the new algorithm has strong optimization ability, outstanding high-dimensional exploration ability and excellent convergence. In addition, this paper pays attention to the demonstration of the process, which makes the experimental results credible, reliable and explainable. The new algorithm is applied to fault detection in wireless sensor networks, in which TLR-QUATRE is combined with back-propagation neural network (BPNN). This study uses the symmetry of generation and feedback for network training. We compare it with other optimization structures through eight public datasets and one actual landing dataset. Five classical machine learning indicators and ROC curves are used for visualization. Finally, the robust adaptability of TLR-QUATRE on this issue is confirmed.
Trihalomethane Cancer Risk Assessment for Private and Shared Residences: Addressing the Differences in Inhalation Exposure
Authors: Parveen Naseeba , Goel Sudha
Published: March 2023

The multi-pathway cancer risk (CR) assessment of trihalomethanes (THM) involves considering exposure via ingestion, dermal contact, and inhalation. Inhalation occurs during showering due to the volatilization of THMs from chlorinated water to the air. When assessing inhalation risks, exposure models commonly assume that the initial THM concentration in the shower room is zero. However, this assumption is only valid in private shower rooms where single or infrequent showering events take place. It fails to account for continuous or successive showering events in shared showering facilities. To address this issue, we incorporated the accumulation of THM in the shower room air. We studied a community (population ≈ 20,000) comprising two types of residences with the same water supply: population A with private shower rooms, and population B with communal shower stalls. The total THM concentration in the water was 30.22 ± 14.45 µg L−1. For population A, the total CR was 58.5 × 10−6, including an inhalation risk of 1.11 × 10−6. However, for population B, the accumulation of THM in the shower stall air resulted in increased inhalation risk. By the tenth showering event, the inhalation risk was 2.2 × 10−6, and the equivalent total CR was 59.64 × 10−6. We found that the CR significantly increased with increasing shower duration. Nevertheless, introducing a ventilation rate of 5 L s−1 in the shower stall reduced the inhalation CR from 1.2 × 10−6 to 7.9 × 10−7.
Stopping Feline Coronavirus Shedding Prevented Feline Infectious Peritonitis
Authors: Addie Diane D. , Bellini Flora , Covell-Ritchie Johanna , Crowe Ben , Curran Sheryl , Fosbery Mark , Hills Stuart , Johnson Eric , Johnson Carrie , Lloyd Steven , Jarrett Oswald
Published: March 2023

After an incubation period of weeks to months, up to 14% of cats infected with feline coronavirus (FCoV) develop feline infectious peritonitis (FIP): a potentially lethal pyogranulomatous perivasculitis. The aim of this study was to find out if stopping FCoV faecal shedding with antivirals prevents FIP. Guardians of cats from which FCoV had been eliminated at least 6 months earlier were contacted to find out the outcome of their cats; 27 households were identified containing 147 cats. Thirteen cats were treated for FIP, 109 cats shed FCoV and 25 did not; a 4–7-day course of oral GS-441524 antiviral stopped faecal FCoV shedding. Follow-up was from 6 months to 3.5 years; 11 of 147 cats died, but none developed FIP. A previous field study of 820 FCoV-exposed cats was used as a retrospective control group; 37 of 820 cats developed FIP. The difference was statistically highly significant (p = 0.0062). Cats from eight households recovered from chronic FCoV enteropathy. Conclusions: the early treatment of FCoV-infected cats with oral antivirals prevented FIP. Nevertheless, should FCoV be re-introduced into a household, then FIP can result. Further work is required to establish the role of FCoV in the aetiology of feline inflammatory bowel disease.
DRAVP: A Comprehensive Database of Antiviral Peptides and Proteins
Authors: Liu Yanchao , Zhu Youzhuo , Sun Xin , Ma Tianyue , Lao Xingzhen , Zheng Heng
Published: March 2023

Viruses with rapid replication and easy mutation can become resistant to antiviral drug treatment. With novel viral infections emerging, such as the recent COVID-19 pandemic, novel antiviral therapies are urgently needed. Antiviral proteins, such as interferon, have been used for treating chronic hepatitis C infections for decades. Natural-origin antimicrobial peptides, such as defensins, have also been identified as possessing antiviral activities, including direct antiviral effects and the ability to induce indirect immune responses to viruses. To promote the development of antiviral drugs, we constructed a data repository of antiviral peptides and proteins (DRAVP). The database provides general information, antiviral activity, structure information, physicochemical information, and literature information for peptides and proteins. Because most of the proteins and peptides lack experimentally determined structures, AlphaFold was used to predict each antiviral peptide’s structure. A free website for users (http://dravp.cpu-bioinfor.org/, accessed on 30 August 2022) was constructed to facilitate data retrieval and sequence analysis. Additionally, all the data can be accessed from the web interface. The DRAVP database aims to be a useful resource for developing antiviral drugs.
Design and Identification of a Novel Antiviral Affinity Peptide against Fowl Adenovirus Serotype 4 (FAdV-4) by Targeting Fiber2 Protein
Authors: Chen Xiao , Wei Qiang , Si Fusheng , Wang Fangyu , Lu Qingxia , Guo Zhenhua , Chai Yongxiao , Zhu Rongfang , Xing Guangxu , Jin Qianyue , Zhang Gaiping
Published: March 2023

Outbreaks of hydropericardium hepatitis syndrome caused by fowl adenovirus serotype 4 (FAdV-4) with a novel genotype have been reported in China since 2015, with significant economic losses to the poultry industry. Fiber2 is one of the important structural proteins on FAdV-4 virions. In this study, the C-terminal knob domain of the FAdV-4 Fiber2 protein was expressed and purified, and its trimer structure (PDB ID: 7W83) was determined for the first time. A series of affinity peptides targeting the knob domain of the Fiber2 protein were designed and synthesized on the basis of the crystal structure using computer virtual screening technology. A total of eight peptides were screened using an immunoperoxidase monolayer assay and RT-qPCR, and they exhibited strong binding affinities to the knob domain of the FAdV-4 Fiber2 protein in a surface plasmon resonance assay. Treatment with peptide number 15 (P15; WWHEKE) at different concentrations (10, 25, and 50 μM) significantly reduced the expression level of the Fiber2 protein and the viral titer during FAdV-4 infection. P15 was found to be an optimal peptide with antiviral activity against FAdV-4 in vitro with no cytotoxic effect on LMH cells up to 200 μM. This study led to the identification of a class of affinity peptides designed using computer virtual screening technology that targeted the knob domain of the FAdV-4 Fiber2 protein and may be developed as a novel potential and effective antiviral strategy in the prevention and control of FAdV-4.
Rhinovirus—A True Respiratory Threat or a Common Inconvenience of Childhood?
Authors: Ljubin-Sternak Sunčanica , Meštrović Tomislav
Published: March 2023

A decade-long neglect of rhinovirus as an important agent of disease in humans was primarily due to the fact that they were seen as less virulent and capable of causing only mild respiratory infections such as common cold. However, with an advent of molecular diagnostic methods, an increasing number of reports placed them among the pathogens found in the lower respiratory tract and recognized them as important risk factors for asthma-related pathology in childhood. As the spread of rhinovirus was not severely affected by the implementation of social distancing and other measures during the coronavirus disease 2019 (COVID-19) pandemic, its putative pathogenic role has become even more evident in recent years. By concentrating on children as the most vulnerable group, in this narrative review we first present classification and main traits of rhinovirus, followed by epidemiology and clinical presentation, risk factors for severe forms of the disease, long-term complications and the pathogenesis of asthma, as well as a snapshot of treatment trials and studies. Recent evidence suggests that the rhinovirus is a significant contributor to respiratory illness in both high-risk and low-risk populations of children.
Recent Advances in MXene-Based Nanocomposites for Wastewater Purification and Water Treatment: A Review
Authors: Pouramini Zahra , Mousavi Seyyed Mojtaba , Babapoor Aziz , Hashemi Seyyed Alireza , Pynadathu Rumjit Nelson , Garg Shivani , Ahmed Shakeel , Chiang Wei-Hung
Published: March 2023

The increase in pollutants such as hazardous refractory contaminants, organic dyes, pharmaceuticals, and pesticides entering water resources on a large scale due to global population growth and industrialization has become a significant health concern worldwide. The two-dimensional (2D) MXene material is a new type of transition metal carbide or carbonitride material, which has demonstrated the capability to adsorb various heavy contaminants, particularly metals such as chromium, copper, lead, and mercury. In addition, MXenes have a tunable band gap (0.92–1.75 eV) and exhibit good thermal stability and considerable damage resistance, which means that they are well suited as adsorbents for waste removal. In this review article, MXene nanocomposites are introduced for the removal of pollutants from water. The idea of water remediation, the applications of MXene-based nanocomposites, and the effects on the degradation of water and wastewater contaminants are reviewed. Future trends in MXene-based nanocomposites for water treatment and environmental applications will also be discussed.
Driving Decisions for Autonomous Vehicles in Intersection Environments: Deep Reinforcement Learning Approaches with Risk Assessment
Authors: Yu Wangpengfei , Qian Yubin , Xu Jiejie , Sun Hongtao , Wang Junxiang
Published: March 2023

Intersection scenarios are one of the most complex and high-risk traffic scenarios. Therefore, it is important to propose a vehicle driving decision algorithm for intersection scenarios. Most of the related studies have focused on considering explicit collision risks while lacking consideration for potential driving risks. Therefore, this study proposes a deep-reinforcement-learning-based driving decision algorithm to address these problems. In this study, a non-deterministic vehicle driving risk assessment method is proposed for intersection scenarios and introduced into a learning-based intelligent driving decision algorithm. In addition, this study proposes an attention network based on state information. In this study, a typical intersection scenario was constructed using simulation software, and experiments were conducted. The experimental results show that the algorithm proposed in this paper can effectively derive a driving strategy with both driving efficiency and driving safety in the intersection driving scenario. It is also demonstrated that the attentional neural network designed in this study helps intelligent vehicles to perceive the surrounding environment more accurately, improves the performance of intelligent vehicles, as well as accelerates the convergence speed.
THE METHOD OF DIAGNOSINGA CAR BATTERY
Authors:   Military Academy of Logistics, Vitaly Viktorovich Nechaev
Published: March 2023

A method is presented that allows in the shortest possible time, with insignificant labor costs and with reliable accuracy to determine the technical condition of the battery, providing increased efficiency and validity of decisions on its further use, contributing to guaranteed engine start and trouble-free operation of the car.
THE DEVELOPMENT OF THE TRAFFIC FLOW CONTROL MATHEMATICAL MODEL
Authors:   Belgorod state technological university, Sergey Nikolaevich Glagolev , Ivan Alekseevich Novikov ,   Belgorod state technological university, Liliya Evgen’evna Kushchenko ,   Belgorod state technological university, Liliya Aleksandrovna Koroleva ,   Belgorod state technological university
Published: March 2023

The paper analyzes the statistics of traffic accidents in the urban agglomeration. Sections of the road network with repeated types of traffic accidents have been identified. The issues of development of the theory of modeling of transport flows are considered. A fuzzy inference model based on the basic data of the traffic situation has been developed. A rule base has been formulated that allows determining the speed of traffic flow depending on the parameters of the traffic flow and the traffic situation.