bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimum Planning of Carbon Capture and Storage Network Using Goal Programming
Authors: Ayyad Fatma M. , Shehata Walaa M. , Bhran Ahmed A. , Gadallah Abdelrahman G. , Shoaib Abeer M.
Published: November 2024

Carbon capture and storage (CCS) is a critical technology used for mitigating climate change by capturing carbon dioxide emissions from industrial sources and storing them underground to prevent their release into the atmosphere. Despite its potential, optimizing CCS systems for cost-effectiveness and efficiency improvement remains a significant challenge. In this paper, the optimization of CCS systems through the development and application of two mathematical optimization techniques is introduced. The first technique is based on using a superstructure optimization model, while the second technique relies on applying a goal programming optimization model. These models were solved using LINGO software version API 14.0.5099.166 to enhance the efficiency and cost-effectiveness of CCS systems. The first model, seeking to maximize the exchange of CO2 flowrate from sources to sinks, achieved a CO2 capture rate of 93.36% with an annual total cost of USD 1.175 billion. The second model introduced a novel mixed-integer non-linear programming (MINLP) approach for multi-objective optimization, targeting the minimization of total system cost, alternative storage, and unutilized storage while maximizing CO2 load exchange. The application of the second model, when prioritized to maximize CO2 flowrate exchange using the goal programming technique, resulted in a cost reduction of 36.46% and a CO2 capture rate of 75.87%. In contrast, when the second model prioritized minimizing the total annual cost, a 48% cost reduction was achieved, and the CO2 capture rate was decreased by 68.37%. A comparison of the two models’ results is presented. The results showed that the second model, with the priority of maximizing CO2 capture, provides the best economic–environmental objective balance, which offers notable cost reductions while keeping an efficient CO2 capture rate. This study highlights the potential of advanced mathematical modeling in increasing the feasibility of CCS as one of the very important strategies of mitigating climate change and reducing global warming.
The Influence of Rock and Natural Weak Plane Properties on the Vertical Propagation of Hydraulic Fractures
Authors: Yang Xuefeng , Chang Cheng , Cheng Qiuyang , Xie Weiyang , Hu Haoran , Li Yongming , Huang Yitao , Peng Yu
Published: November 2024

China has abundant shale gas resources with good exploration value and development potential, making it a recent hotspot for exploration and development. It is widely agreed that large-scale hydraulic fracturing is essential for reservoir enhancement in shale formations. However, the evolution of fractures during hydraulic fracturing is highly complex, necessitating research on the influence of various factors on the vertical propagation of hydraulic fractures. Based on geological and engineering parameters from the Luzhou block in southern Sichuan, this study employed the finite element method (FEM) and the cohesive element method to establish a coupled fluid-solid model for the vertical propagation of hydraulic fractures. Numerical simulations were conducted to investigate the interaction between hydraulic fractures and natural weak planes, clarifying the mechanisms involved. This study elucidates how different rock and natural weak plane properties affect the vertical propagation of hydraulic fractures and draws diagrams illustrating these interactions. The research indicated three fracture distribution patterns after the intersection of hydraulic fractures with natural weak planes: passive fractures, ‘I’-shaped fractures, and crossing fractures. The main fractures in these patterns exhibit initial damage and damage evolution characterized by tensile failure. Specifically, in passive fractures, the initial damage and damage evolution of natural weak planes manifest as shear failure. In ‘I’-shaped fractures, the initial damage in natural weak planes is characterized by shear failure, with damage evolution showing tensile failure. Crossing fractures show minimal damage in the weak planes. Under conditions of high natural weak plane cohesive strength, high Young’s modulus, low interlayer rock cohesive strength, high vertical stress difference, low interlayer stress difference, and high intersection angles, crossing fractures tend to form. Conversely, conditions of low natural weak plane cohesive strength, low Young’s modulus, high interlayer rock cohesive strength, low vertical stress difference, high interlayer stress difference, and low intersection angles favor the formation of ‘I’-shaped fractures. Passive fractures form under conditions of low natural weak plane cohesive strength and high vertical stress difference. This study found that Poisson’s ratio has a minimal effect on the vertical expansion of hydraulic fractures under the studied conditions, with natural weak plane strength being the primary control factor for fracture patterns. These findings enhance the theoretical foundation for the vertical propagation of hydraulic fractures in deep shale formations, facilitating the development and implementation of strategies for enhancing production in shale reservoirs with natural weak planes and better optimizing production in different types of shale reservoirs.
Metallic Ca Aggregates Formed Along Ion Tracks and Optical Anisotropy in CaF2 Crystals Irradiated with Swift Heavy Ions
Authors: Amekura Hiroshi , Ishikawa Norito , Okubo Nariaki , Chen Feng , Narumi Kazumasa , Chiba Atsuya , Hirano Yoshimi , Yamada Keisuke , Yamamoto Shunya , Saitoh Yuichi
Published: November 2024

It is known that swift heavy ion (SHI) irradiation induces the shape elongation of metal nanoparticles (NPs) embedded in transparent insulators, which results in anisotropic optical absorption. Here, we report another type of the optical anisotropy induced in CaF2 crystals without including intentionally embedded metal NPs. The CaF2 samples were irradiated with 200 MeV Xe14+ ions with an incident angle of 45° from the surface normal. With the increasing fluence, an absorption band at ~550 nm, which is ascribed to Ca aggregates, increases both the intensity and the anisotropy. XTEM observation clarified the formation of the continuous line structures and the discontinuous NP chains parallel to the SHI beam. Numerical simulations of the optical absorption spectra suggested the NP chains but not the continuous line structures as the origin of the anisotropy. The optical anisotropy in CaF2 irradiated with SHIs is different from the shape elongation of NPs.
Copper-Catalyzed Sonogashira-Type Coupling Reaction of Vinylacetylene ortho-Carborane with Boronic Acid in the Synthesis of Luminophores with Phosphorescent Emission
Authors: Moseev Timofey D. , Idrisov Tair A. , Varaksin Mikhail V. , Tsmokaluk Anton N. , Charushin Valery N. , Chupakhin Oleg N.
Published: November 2024

A synthetic approach to prepare boron-enriched π-conjugated photoactive molecular systems based on ortho-carborane using the Cu(I)-catalyzed Sonogashira-type coupling reaction has been developed. The obtained luminophores have been found to possess absorption in the range of 300 to 400 nm, emission of up to 700 nm, and photoluminescence quantum yields of up to 99% in non-polar solvents. TD-DFT calculations have demonstrated that the luminophores are characterized by phosphorescent emission behavior with a lifetime of about 7 μs. In addition, the rigidochromism for the synthesized compounds has been revealed; particularly, the transition electronic state and bathochromic shift have been elucidated in the emission spectra. The exhibited luminescent characteristics indicate that the elaborated vinylcarborane fluorophores could be considered as promising building blocks in the design of advanced photofunctional materials for molecular electronics.
Menno Simons and the Sword: From Oldeklooster to Wüstenfelde
Authors: McGinnis Scott
Published: November 2024

This article traces the evolution of the attitudes of Anabaptist Menno Simons with respect to state-sponsored violence by examining the theme through his written works over the course of his career as a reformer. Particular attention is given to the circumstances that surround key writings. Menno’s sometimes deliberate ambiguity and the evolution in his beliefs reflect his precarious position as an itinerant preacher, as well as the fragile state of the group of would-be revolutionaries and other dissenters whose leadership he inherited shortly after renouncing his role as a priest. The position he ultimately took against the execution of criminals is unusual for his day and shows the extent of his thoroughgoing rejection of violence for Christians.
The Influence of “Using the Temple Property for Schools” Movement on the Organization of Han Buddhist Monastic Education in Modern China
Authors: Hu Yonghui
Published: November 2024

Under the influence of “Using the Temple Property for Schools”(UTPSs) movement, the monastic education of Han Buddhism 漢傳佛教僧教育 in modern China, as a whole, has gradually moved towards the mode of Buddhist colleges, through the establishment of the Buddhist Educational Affairs Public Office (BEAPO) 佛教學務公所, the Institution of Monastic Education (IME) 僧教育會, and the institution of Buddhist education 佛教教育機構 with international outlook and has become the prototype of the educational institution of Han Buddhism in contemporary China. The attempts to run schools during the period of the BEAPO at the late Qing Dynasty objectively stimulated the awakening of the consciousness of the Buddhist community to establish schools and to promote education 辦學興教 and became the precursor of the rise of the wave of monastic education after the Xinhai Revolution, especially since the 1920s. The goal of “uniting the national Buddhism” proposed by the BEAPO became the direction for the development of subsequent Buddhist organizations. The BEAPO also accumulated experiences for the construction of later Buddhist organizations and stimulated the awakening of the monks’ sense of subjectivity. The organizational structure and many ideas of the BEAPO were later inherited by the IME; most of the contents of the constitution of it were also inherited and improved by the IME. As a Buddhist organization, the BEAPO made positive efforts to reconcile the tensions between monks and laypeople under the context of UTPS at that time. After the Xinhai Revolution, the Han Buddhist community focused on interacting with secular society, and the practice of Buddhist education reflected the awakening of self-consciousness to “establish schools to promote education”. In terms of the school operation mode, the diversified curriculum and modernized academic system reflect the characteristic of a balance between internal and external studies. During this period, the establishment of Buddhist educational institutions with an international outlook provided a guarantee of talent for the path of the “universalization” of Han Buddhism, as well as provided continuity for the sustainable development of it. Under the influence of the two UTPS movements, the tortuous development of Han Buddhist monastic education in modern China is, in fact, the epitome of the situation of the whole Chinese Buddhism in modern society. At the same time, it also reflects the proactive adaptation of Chinese Buddhism, in modern times, to external pressures and its self-remodeling in the struggle for survival space.
Solar Power Generation Forecasting in Smart Cities and Explanation Based on Explainable AI
Authors: Petrosian Ovanes , Zhang Yuyi
Published: November 2024

The application of black-box models, namely ensemble and deep learning, has significantly advanced the effectiveness of solar power generation forecasting. However, these models lack explainability, which hinders comprehensive investigations into environmental influences. To address this limitation, we employ explainable artificial intelligence (XAI) techniques to enhance the interpretability of these black-box models, while ensuring their predictive accuracy. We carefully selected 10 prominent black-box models and deployed them using real solar power datasets. Within the field of artificial intelligence, it is crucial to adhere to standardized usage procedures to guarantee unbiased performance evaluations. Consequently, our investigation identifies LightGBM as the model that requires explanation. In a practical engineering context, we utilize XAI methods to extract understandable insights from the selected model, shedding light on the varying degrees of impact exerted by diverse environmental factors on solar power generation. This approach facilitates a nuanced analysis of the influence of the environment. Our findings underscore the significance of “Distance from the Noon” as the primary factor influencing solar power generation, which exhibits a clear interaction with “Sky Cover.” By leveraging the outcomes of our analyses, we propose optimal locations for solar power stations, thereby offering a tangible pathway for the practical.
Interplay Between Structural, Electronic, and Magnetic Properties in the d0-d Semi-Heusler Compounds; the Case of the K-Based Compounds
Authors: Özdoğan Kemal , Galanakis Iosif
Published: November 2024

Heusler compounds and alloys represent a rapidly expanding family of materials that exhibit novel properties of significant interest for advanced technological applications. Electronic band structure calculations play a pivotal role in advancing research in this area. In an earlier study, we explored the properties of a new class of Heusler compounds based on Li, referred to as “p0-d semi-Heusler Compounds”. In this study, we take the research a step further by focusing on “d0-d semi-Heusler Compounds”, with the chemical formula KZ(Ga, Ge, As, or Se), where Z represents a transition metal. Our investigation centers on the structural, electronic, and magnetic properties of these compounds, particularly in relation to the three possible C1b structures. Most of these compounds are found to be magnetic and, notably, several among them exhibit half-metallicity making them appealing for applications in spintronics. Our findings provide a foundation for future experimental research on these materials.
Problems of Sustainable Agriculture with Regard to the Destruction of the European Corn Borer in Maize Plantations
Authors: Zastempowski Marcin , Lamparski Robert , Bochat Andrzej , Kaszkowiak Jerzy , Sendel Sebastian , Gierz Łukasz
Published: November 2024

This article describes the results of the studies related to the occurrence of the European corn borer (Ostrinia nubilalis Hbn) pest carried out at the Technical University of Bydgoszcz. The studies concerned the real occurrence of the pest in corn stubble (cultivated variety SY Collosseum). The research issue undertaken is in line with an IPM (integrated pest management) system and is important since the feeding of the European corn borer can lead to large, direct yield losses estimated nationally at an average of up to about 20%, which does not differ significantly from that of world crops. Corn, for the purposes of this study, was harvested for green fodder in September, and for grain in November 2022, using a John Deere X9 1110 harvester. The average stubble height when cut for green fodder was 280 mm, while for grain it was 265 mm. The experimental studies conducted clearly showed that European corn borer larvae colonized as much as 12% of corn samples harvested for grain at an average stubble height of 155 mm, and 19% of corn samples harvested for grain at an average height of 75 mm. The conducted studies also showed that the average diameter of the stems at the height of the residence of the corn borer larvae when harvested for green fodder is 19.80 mm, and 21.80 mm for grain. The studies conducted by the authors showed the randomness of the locations of the pest larvae, which clearly indicates that the generally known and used mechanical methods of its control are not fully effective. Therefore, the authors presented their own design of a machine construction (filed with the patent office of the Republic of Poland) for destroying the European corn borer in a mechanical way without the use of crop protection chemicals. The presented research problem in this paper is of national and global importance considering the fact that corn is grown on an area of nearly 162 million hectares, where we have to deal with the European corn borer pest. In the case of implementing the design of the construction of a machine for destroying the pest, there will be no need to use chemical pesticides, which will significantly contribute to environmental protection.
Identification and Trend Analysis of Ecological Security Pattern in Mudanjiang City Based on MSPA-MCR-PLUS Model
Authors: Liu Pei-Xian , Liu Ying , Li Tie-Nan , Guo Wei-Wei , Yang A-Long , Yang Xiao , Li En-Zhong , Wang Zheng-Jun
Published: November 2024

The ecological security pattern plays a crucial role in maintaining ecosystem health and ensuring ecological security. The establishment of the ecological security pattern in Mudanjiang City can provide a scientific basis and effective support for stabilizing the ecological environment, mitigating regional human–land conflicts, and rational land- use planning. This paper utilizes the theory of constructing an ecological security pattern using a source-resistance plane-corridor node to grade the importance of source areas based on the connectivity index. It combines morphological spatial pattern analysis and PLUS model to generate and identify the present value of 2022 in Mudanjiang City, as well as predict eight land types and seven landscape types under three development scenarios by 2032. A transfer matrix and transfer-intensity map are introduced to explore the structural characteristics of landscape transfer, while four fragmentation indexes are combined with principal component analysis and the coefficient of variation method to form comprehensive fragmentation indexes for different classes. Finally, based on constructing the ecological security pattern of Mudanjiang City in 2022, an analysis method is developed that establishes logical connections between land-use structure, a comprehensive fragmentation of land types, landscape transformation mechanism, and the importance of ecological sources. The results are as follows: (1) In Mudanjiang City, 23 ecological source areas, 65 corridors, and 66 ecological nodes were extracted. The overall ecological security pattern shows a “U” shape with openings to the northeast. (2) The cumulative weight of economic and social factors on the ecological resistance surface in Mudanjiang City reached 51.36%. (3) The response between the comprehensive fragmentation degree of forest land and the importance of primary and tertiary source areas was highly significant, with R values reaching 0.9675 and −0.8746, respectively. The comparative study comprehensively showed that the best scenario for the sustainable development of the ecological security pattern in the future is an ecological priority scenario, where the tertiary source area with the smallest area proportion but strongest disturbance fluctuation becomes a key area affecting connectivity and overall ecological security pattern in Mudanjiang City.
Effects of Land Use Data Spatial Resolution on SDG Indicator 11.3.1 (Urban Expansion) Assessments: A Case Study Across Ethiopia
Authors: Cardenas-Ritzert Orion S. E. , Vogeler Jody C. , Shah Heydari Shahriar , Fekety Patrick A. , Laituri Melinda , McHale Melissa R.
Published: November 2024

Geospatial data play a significant role in the United Nation’s Sustainable Development Goals, particularly through assessments of monitoring indicators. Sustainable Development Goal (SDG) Indicator 11.3.1 assessments utilize land and population geospatial data to monitor urban expansion, and were implemented to enhance inclusive and sustainable urbanization, and capacity for participatory, integrated and sustainable human settlement planning and management in all countries by 2030. Data-limited countries often rely on accessible, wide-coverage geospatial datasets for SDG Indicator 11.3.1 assessments which may have characteristics (e.g., coarse spatial resolution) influential to assessment outcomes. The presented work examines the effect of land use data spatial resolution on SDG Indicator 11.3.1 assessment components including urban area delineation, SDG Indicator 11.3.1 and supporting spatial metrics, spatial patterns of urban land development, and land use change patterns for urbanizing areas in Ethiopia from 2016 to 2020. A comparison was made between a single land use map at the spatial resolution in which it was originally produced, 30 m, and at a majority-resampled spatial resolution comparable to many global coverage datasets, 90 m. Analyses revealed changes in the urban areas identified, observed boundaries of urban areas, and all quantified metrics from 30 m resolution to 90 m resolution, with the decrease in resolution resulting in smaller urban areas being missed and differences in the delineated hinterland areas connected to an urban core. Statistical testing indicated significant differences in SDG Indicator 11.3.1 values, developed land use area per capita, and spatial patterns of urban development between the two spatial resolutions. The relative order of land use conversion types remained similar across both resolutions, with agricultural land experiencing the greatest conversion to developed land, followed by rangeland and forest, although the total area of each conversion type differed. This study illustrates the possible discrepancies in SDG Indicator 11.3.1 and related outputs when utilizing differing resolution datasets and the importance of data characteristic consideration when conducting SDG Indicator 11.3.1 assessments.
Driving Factors and Control Strategies of the Environmental Pollution Litigation Cases in China
Authors: Liu Bing , He Bailin , Zhou Jiaxu , Chen Xueyan , Duan Haiyan , Duan Zhiyuan
Published: November 2024

Environmental pollution litigation cases (EPLCs) are experiencing a significant upward trend attributable to the extensive discharge of pollutants in China. However, the driving factors of EPLCs remain ambiguous. Herein, a comprehensive research framework is established by using the logarithmic mean divisia index (LMDI) method for investigating the driving factors of China’s EPLCs. The provinces of Henan, Jilin, Shandong, Zhejiang, Jiangsu, and Guangdong stand out as the regions with the highest number of EPLCs. The GDP per capita and incidence rate promote the incidence of EPLCs, while emission intensity and emission intensity per unit area inhibit the occurrence of EPLCs. Population and population density have less impact on EPLCs. These findings should serve as references for controlling the occurrence of EPLCs in different provinces in China.
Manufacture and Analysis of a Textile Sensor Response to Chemical Stimulus Using Printing Techniques and Embroidery for Health Protection
Authors: Skrzetuska Ewa , Szablewska Paulina , Patalas Aleksander
Published: November 2024

The development of the field of textronics covers many directions, but the neediest are safety, medicine, and environmental protection. The solutions developed can combine the needs of many people from different social groups and ages. This leads to sustainable socio-economic, scientific and integrated approaches to sustainable development. The authors, seeing the growing need to monitor air pollution in order to increase safety, decided to develop textronic chemical sensors based on carbon-based inks and metal thread embroidery, sensitive to harmful gases and vapors based on textiles. This was to limit the production of subsequent sensors made in plastic housings containing difficult-to-recycle materials and replace them with sensors incorporated into everyday materials such as clothing, which will inform us about emerging threats not only in the place where a large plastic sensor is placed, but in every place at home, at work and outside where we will be. The authors assume that the sensors can be incorporated into clothing, e.g. work clothes, and can also be fastened from one piece of clothing to another. This increases their economic aspect and usability on a larger scale. Three materials of different composition were tested: cotton, polyester and viscose. These materials were selected based on their properties, namely the easier determination of their ability to achieve full circularity of the final product.Functional and mechanical tests of resistance to factors occurring during everyday use were carried out for the use of systems in clothing materials and to produce roller blinds and curtains. To examine the durability of the systems, electrical conductivity was checked before and after the tests. The results showed changes in resistance values after individual tests and during contact with harmful gases. Particularly noticeable are the differences between samples with embroidery and samples with inkjet paste applied. It was shown that the selected materials are suitable for the intended application, and selected modifications together with conductive materials show proper functioning in detecting harmful gases. This project demonstrates the possibility of creating chemical sensors based on printing techniques using carbon printing pastes and embroidery with a metal thread with silver on a textile substrate. Possible applications considering health and environmental aspects are presented.
Environmental Impacts of Natural Resources, Renewable Energy, Technological Innovation, and Globalization: Evidence from the Organization of Turkic States
Authors: Faizi Azizullah , AK Mehmet Zeki , Shahzad Mohammad Rahim , Yüksel Selay , Toffanin Renato
Published: November 2024

Environmental challenges have intensified as a result of global warming and climate change, creating significant threats to environmental quality. The member nations of the Organization of Turkic States (OTS) are especially impacted by these issues, primarily because of their reliance on fossil fuels, leading to elevated carbon emissions. This study examines the influence of natural resources, renewable energy, technological innovation, and globalization on environmental degradation in five OTS member countries—Azerbaijan, Kazakhstan, Kyrgyzstan, Türkiye, and Uzbekistan—covering the years 1996 to 2020. The ecological footprint and CO2 emissions are employed as the main indicators of environmental harm. Through the application of the Method of Moments Quantile Regression (MMQR), the findings reveal that natural resources significantly contribute to CO2 emissions in the lower quantiles but show a lesser impact on the ecological footprint. Conversely, renewable energy consistently improves environmental quality across all quantiles, whereas technological innovation and globalization are both associated with increased environmental degradation. Additionally, the causality test reveals a bidirectional causality between renewable energy consumption and both CO2 emissions and the ecological footprint (EF), as well as between technological innovation and EF. Moreover, a unidirectional causal relationship is observed from globalization to EF. Based on the findings, policy recommendations for OTS member states include promoting the adoption of renewable energy, fostering green technological innovations, and addressing the negative environmental effects of globalization. Such measures are vital for achieving the Sustainable Development Goals and ensuring long-term environmental sustainability.
Assessing the Effectiveness of Market-Oriented Environmental Policies on CO2 Emissions from Household Consumption: Evidence from a Quasi-Natural Experiment in Carbon Trading Pilots
Authors: Li Xiang , Huang Yuzhuo , Matsumoto Ken’ichi
Published: November 2024

The enhancement of the carbon trading mechanism signifies a gradual transition in China’s environmental regulatory framework, shifting from a command and control approach to a market-based incentive model. Despite the significance of this shift, existing research has insufficiently explored the impact of market-oriented environmental policies on consumption-based emissions. This study leverages the carbon trading policies implemented in 2013 as a quasi-natural experiment, combined with a precise measurement of urban and rural household carbon emissions (HCE) during 2005–2021. Employing a difference-in-differences method, we evaluate the heterogeneous impact of these policies on urban and rural HCE. The results demonstrate a significantly negative effect of the policies on indirect HCE, a conclusion that remains robust across various placebo and robustness tests. Furthermore, we identify the transmission mechanisms through which carbon trading policies affect the reduction in HCE. The results indicate that the policy has a significant negative impact on indirect HCE, with a notable urban–rural difference. The effect of the policy is −0.829 for urban areas and −0.365 for rural areas, a conclusion that remains robust across various placebo and robustness checks. Additionally, we identified two transmission mechanisms through which carbon trading policies operate: financial deepening and employment effects. Lastly, we found that carbon trading policies can reduce carbon inequality between urban and rural areas by 46.8%.
Symmetrical Generalized Pareto Dominance and Adjusted Reference Vector Cooperative Evolutionary Algorithm for Many-Objective Optimization
Authors: Zhu Shuwei , Zeng Liusheng , Cui Meiji
Published: November 2024

In Pareto-based many-objective evolutionary algorithms, performance usually degrades drastically as the number of objectives increases due to the poor discriminability of Pareto optimality. Although some relaxed Pareto domination relations have been proposed to relieve the loss of selection pressure, it is hard to maintain good population diversity, especially in the late phase of evolution. To solve this problem, we propose a symmetrical Generalized Pareto Dominance and Adjusted Reference Vectors Cooperative (GPDARVC) evolutionary algorithm to deal with many-objective optimization problems. The symmetric version of generalized Pareto dominance (GPD), as an efficient framework, provides sufficient selection pressure without degrading diversity, no matter of the number of objectives. Then, reference vectors (RVs), initially generated evenly in the objective space, guide the selection with good diversity. The cooperation of GPD and RVs in environmental selection in part ensures a good balance of convergence and diversity. Also, to further enhance the effectiveness of RV-guided selection, we regenerate more RVs according to the proportion of valid RVs; thereafter, we select the most valid RVs for adjustment after the association operation. To validate the performance of GPDARVC, we compare it with seven representative algorithms on commonly used sets of problems. This comprehensive analysis results in 26 test problems with different objective numbers and 6 practical problems, which show that GPDARVC outperforms other algorithms in most cases, indicating its great potential to solve many-objective optimization problems.
A Novel Machine Learning Model and a Web Portal for Predicting the Human Skin Sensitization Effects of Chemical Agents
Authors: Scheufen Tieghi Ricardo , Moreira-Filho José Teófilo , Martin Holli-Joi , Wellnitz James , Otoch Miguel Canamary , Rath Marielle , Tropsha Alexander , Muratov Eugene N. , Kleinstreuer Nicole
Published: November 2024

Skin sensitization is a significant concern for chemical safety assessments. Traditional animal assays often fail to predict human responses accurately, and ethical constraints limit the collection of human data, necessitating a need for reliable in silico models of skin sensitization prediction. This study introduces HuSSPred, an in silico tool based on the Human Predictive Patch Test (HPPT). HuSSPred aims to enhance the reliability of predicting human skin sensitization effects for chemical agents to support their regulatory assessment. We have curated an extensive HPPT database and performed chemical space analysis and grouping. Binary and multiclass QSAR models were developed with Bayesian hyperparameter optimization. Model performance was evaluated via five-fold cross-validation. We performed model validation with reference data from the Defined Approaches for Skin Sensitization (DASS) app. HuSSPred models demonstrated strong predictive performance with CCR ranging from 55 to 88%, sensitivity between 48 and 89%, and specificity between 37 and 92%. The positive predictive value (PPV) ranged from 84 to 97%, versus negative predictive value (NPV) from 22 to 65%, and coverage was between 75 and 93%. Our models exhibited comparable or improved performance compared to existing tools, and the external validation showed the high accuracy and sensitivity of the developed models. HuSSPred provides a reliable, open-access, and ethical alternative to traditional testing for skin sensitization. Its high accuracy and reasonable coverage make it a valuable resource for regulatory assessments, aligning with the 3Rs principles. The publicly accessible HuSSPred web tool offers a user-friendly interface for predicting skin sensitization based on chemical structure.
Semi-Symmetric Metric Gravity: A Brief Overview
Authors: Chaudhary Himanshu , Csillag Lehel , Harko Tiberiu
Published: November 2024

We present a review of the Semi-Symmetric Metric Gravity (SSMG) theory, representing a geometric extension of standard general relativity, based on a connection introduced by Friedmann and Schouten in 1924. The semi-symmetric connection is a connection that generalizes the Levi-Civita one by allowing for the presence of a simple form of the torsion, described in terms of a torsion vector. The Einstein field equations are postulated to have the same form as in standard general relativity, thus relating the Einstein tensor constructed with the help of the semi-symmetric connection, with the energy–momentum tensor. The inclusion of the torsion contributions in the field equations has intriguing cosmological implications, particularly during the late-time evolution of the Universe. Presumably, these effects also dominate under high-energy conditions, and thus SSMG could potentially address unresolved issues in general relativity and cosmology, such as the initial singularity, inflation, or the 7Li problem of the Big-Bang Nucleosynthesis. The explicit presence of torsion in the field equations leads to the non-conservation of the energy–momentum tensor, which can be interpreted within the irreversible thermodynamics of open systems as describing particle creation processes. We also review in detail the cosmological applications of the theory, and investigate the statistical tests for several models, by constraining the model parameters via comparison with several observational datasets.
Overlooked Risk of Microplastic from Kitchen Waste Short Stacking Phase
Authors: Qian Jialu , Zhou Fanping , Shen Dongsheng , Shentu Jiali , Lu Li , Qi Shengqi , Zhu Min , Long Yuyang
Published: November 2024

Current research on microplastics (MPs) in kitchen waste primarily focuses on their end-of-life disposal processes, neglecting the rapid decomposition phase prior to disposal. This study investigated MPs’ instantaneous release during a 20 h kitchen waste stacking process. The results revealed significant temperature-dependent release, with up to 96.1% entering the liquid phase and 5768 items/kg released and with an average of 85.7% of the MPs transferring into the entrapped water released from the tiny tissue structures and membranes. These MPs were primarily in small sizes (4–400 μm) as particles and fragments. Hydrolysis acidification primarily influences MPs’ release, with temperature and stacking time as intermediate factors. Acetic acid drives MPs’ release, contributing up to 38.5%. High temperatures accelerate organic matter dissolution and MP migration, while low temperatures slow down the release of MPs. The findings confirmed MPs’ release risks during kitchen waste stacking and contributed to optimize kitchen waste management to control MP pollution at its source.
Food Waste Fermentation Liquid as a Supplementary Carbon Source for Enhanced Biological Nitrogen Removal from Rural Wastewater
Authors: Zhang Yanju , Su Yu , Wang Feng , Feng Leiyu , Wang Xiaojuan , Mustafa Ahmed M.
Published: November 2024

Large variations in water quality and quantity are the main characteristics of rural wastewater in China, and the biggest impact caused by this is the lack of carbon sources. In this study, an anoxic–oxic (A/O) biological contact oxidation (BCO) reactor was used to explore the feasibility of using food waste fermentation liquid as the supplementary carbon source for enhanced nitrogen removal from rural wastewater. After using the carbon source supplements, the removal performance of the A/O BCO system was improved, with the removal efficiencies of COD, NH4+–N, and TN at 92.4%, 97.8%, and 67.6%, respectively. Mechanism studies showed that the activities of key denitrifying enzymes (NAR, NIR, NOR, and NOS) for nitrogen removal were improved, with NIR activity increasing by 36.9%. Microbial community analysis revealed that food waste fermentation liquid increased the diversity of denitrifying microbial populations. Notably, insights from metagenomics showed that the relative abundances of two key genes (nirS and nirK), which are vital indicators of the denitrification process, were significantly improved with the addition of food waste fermentation liquid as a supplemental carbon source, resulting in the enhancement of nitrogen removal from rural wastewater.
Multiple Types of Missing Precipitation Data Filling Based on Ensemble Artificial Intelligence Models
Authors: Qiu He , Chen Hao , Xu Bingjiao , Liu Gaozhan , Huang Saihua , Nie Hui , Xie Huawei
Published: November 2024

The completeness of precipitation observation data is a crucial foundation for hydrological simulation, water resource analysis, and environmental assessment. Traditional data imputation methods suffer from poor adaptability, lack of precision, and limited model diversity. Rapid and accurate imputation using available data is a key challenge in precipitation monitoring. This study selected precipitation data from the Jiaojiang River basin in the southeastern Zhejiang Province of China from 1991 to 2020. The data were categorized based on various missing rates and scenarios, namely MCR (Missing Completely Random), MR (Missing Random), and MNR (Missing Not Random). Imputation of precipitation data was conducted using three types of Artificial Intelligence (AI) methods (Backpropagation Neural Network (BPNN), Random Forest (RF), and Support Vector Regression (SVR)), along with a novel Multiple Linear Regression (MLR) imputation method built upon these algorithms. The results indicate that the constructed MLR imputation method achieves an average Pearson’s correlation coefficient (PCC) of 0.9455, an average Nash–Sutcliffe Efficiency (NSE) of 0.8329, and an average Percent Bias (Pbias) of 10.5043% across different missing rates. MLR simulation results in higher NSE and lower Pbias than the other three single AI models, thus effectively improving the estimation performance. The proposed methods in this study can be applied to other river basins to improve the quality of precipitation data and support water resource management.
Study on the Cavitation Performance in the Impeller Region of a Mixed-Flow Pump Under Different Flow Rates
Authors: Yang Xu , Zhu Jianzhong , Zhang Yi , Chen Buqing , Tang Yiping , Jiang Rui , Kan Kan , Ye Changliang , Zheng Yuan
Published: November 2024

Mixed-flow pumps, optimized for marine engineering, provide a balance of high efficiency and adaptability, accommodating varied flow and head demands across challenging oceanic settings and are essential for reliable operations in tidal energy and subsea applications. The primary purpose of this paper is to perform a numerical analysis of the cavitation flow characteristics of the mixed-flow pump under differing operational circumstances. The cavitation simulation was implemented to explore the cavitation bubbles evolution and the pressure pulsation characteristics in the impeller region under diverse flow rates, utilizing the Shear Stress Transport (SST) turbulence model and the Zwart-Gerber-Belamri cavitation model as a foundation. The findings indicate that cavitation bubbles initially distribute at the leading edge of blade suction surfaces at the cavitation growth stage. The bubbles spread gradually with the decline of the available net positive suction head (NPSHa). At the same time, many bubbles appear in the area below the blade and extend to the rim of the suction side of blades. As the flow rate decreases, the critical net positive suction head (NPSHc) gradually declines. The dominant pressure pulsation frequency at the impeller inlet is the blade passing frequency, and the vibration at the impeller shroud inlet is more intense than that at the hub. The dominant frequency at the impeller outlet is mainly the blade passing frequency. With the development of cavitation, it changes to impeller rotation frequency at low flow rates, while the dominant frequency remains unchanged at high flow rates.
Evaluating Stormwater Infiltration Systems in High Water Table Areas: Insights from Southwest Florida
Authors: Herman John P. , Tsegaye Seneshaw , Missimer Thomas M.
Published: November 2024

Infiltration-based stormwater best management practices (BMPs) are progressively being utilized to mitigate issues such as increased runoff and poor water quality associated with urbanization. However, they are often difficult to accurately model due to the extensive design variables involved, particularly in high water table regions where groundwater mounding can cause primary infiltration to shift from vertical to horizontal. This study assessed an infiltration-based stormwater management system for a commercial property in Southwest Florida using integrated ArcMap 10.8.2 -ICPR4 software. A unique modeling technique captured the shift from vertical to horizontal infiltration in high water table conditions, employing ICPR4’s “percolation ring” and “percolation link”. The integration of GIS with the ICPR model enabled detailed modeling, assessment, and visualization of runoff in high water table areas. Three site-specific design storms were employed to analyze the pre- and post-developed conditions of the study area and assess whether existing BMPs met Environmental Resource Permit (ERP) requirements. While the system complies with ERP standards, it was found to be oversized based on storage basin stages and stormwater discharges from the simulated 100-year/24-h storm event. This is because 45–68% of the total volume entering the stormwater management basins infiltrated during the analysis period. The infiltration rate in the models was initially heavily dependent on vertical infiltration. However, horizontal groundwater flow substantially increased with the increasing water stage in the detention ponds after vadose zone saturation. These findings highlight the significance of modeling techniques in accurately capturing the performance of infiltration-based stormwater management systems in high water table conditions.
Optimization Research on Energy Management Strategies and Powertrain Parameters for Plug-In Hybrid Electric Buses
Authors: Wang Lufeng , Zhou Juanying , Zhao Jianyou
Published: November 2024

The power split plug-in hybrid electric bus (PHEB) boasts the capability for concurrent decoupling of rotation speed and torque, emerging as the key technology for energy conservation. The optimization of energy management strategies (EMSs) and powertrain parameters for PHEB contributes to bolstering vehicle performance and fuel economy. This paper revolves around optimizing fuel economy in PHEBs by proposing an optimization algorithm for the combination of a multi-layer rule-based energy management strategy (MRB-EMS) and powertrain parameters, with the former incorporating intelligent algorithms alongside deterministic rules. It commences by establishing a double-planetary-gear power split model for PHEBs, followed by parameter matching for powertrain components in adherence to relevant standards. Moving on, this paper plunges into the operational modes of the PHEB and assesses the system efficiency under each mode. The MRB-EMS is devised, with the battery’s State of Charge (SOC) serving as the hard constraint in the outer layer and the Charge Depletion and Charge Sustaining (CDCS) strategy forming the inner layer. To address the issue of suboptimal adaptive performance within the inner layer, an enhancement is introduced through the integration of optimization algorithms, culminating in the formulation of the enhanced MRB (MRB-II)-EMS. The fuel consumption of MRB-II-EMS and CDCS, under China City Bus Circle (CCBC) and synthetic driving cycle, decreased by 12.02% and 10.35% respectively, and the battery life loss decreased by 33.33% and 31.64%, with significant effects. Subsequent to this, a combined multi-layer powertrain optimization method based on Genetic Algorithm-Optimal Adaptive Control of Motor Efficiency-Particle Swarm Optimization (GOP) is proposed. In parallel with solving the optimal powertrain parameters, this method allows for the synchronous optimization of the Electric Driving (ED) mode and the Shutdown Charge Hold (SCH) mode within the MRB strategy. As evidenced by the results, the proposed optimization method is tailored for the EMSs and powertrain parameters. After optimization, fuel consumption was reduced by 9.04% and 18.11%, and battery life loss was decreased by 3.19% and 7.42% under the CCBC and synthetic driving cycle, which demonstrates a substantial elevation in the fuel economy and battery protection capabilities of PHEB.
Intelligent Vehicle Trajectory Tracking Based on Horizontal and Vertical Integrated Control
Authors: Xu Jingbo , Zhao Jingbo , Zheng Jianfeng , Liu Haimei
Published: November 2024

To address the common issues of accuracy and stability in trajectory tracking tasks for autonomous vehicles, this study proposes an innovative composite control strategy that skillfully integrates lateral and longitudinal dynamic control. For lateral control, model predictive control (MPC) theory is introduced to compute the front wheel steering angle that ensures optimal trajectory following. On the longitudinal control level, the vehicle’s acceleration and deceleration logic are finely tuned to ensure precise adherence to the preset speed trajectory. More importantly, by deeply integrating these two control methods, the comprehensive coordination of the vehicle’s lateral and longitudinal movements is achieved. To validate the effectiveness of the proposed control strategy, simulations were conducted using the CarSim and MATLAB/Simulink platforms. The analysis of the simulation results confirms that the proposed method effectively improves speed tracking stability and significantly enhances path tracking accuracy and overall driving stability.