bluuebunny/crossref_metadata_2025 huggingface dataset:
Rheological Properties and Modification Mechanism of Emulsified Asphalt Modified with Waterborne Epoxy/Polyurethan Composite
Authors: Li Maorong , He Zhaoyi , Yu Jiahao , Yu Le , Shen Zuzhen , Kong Lin
Published: November 2024

In research aimed at improving the brittleness of WER (waterborne epoxy)-modified emulsified asphalt, commonly encountered issues are that the low-temperature performance of this type of asphalt becomes insufficient and the long curing time leads to low early strength. Matrix-emulsified asphalt was modified with WPU (waterborne polyurethane), WER, and DMP-30 (accelerator). Firstly, the performance changes of modified emulsified asphalt at different single-factor dosages were explored through conventional performance tests and assessments of its adhesion, tensile properties, and curing time. Secondly, based on a response surface methodology test design, the material composition of the composite-modified emulsified asphalt was optimized, and its rheological properties were analyzed by a DSR test and a force–ductility test. Finally, the modification mechanism was explored by scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). The results show that WER can improve the adhesion strength of modified emulsified asphalt and greatly reduce elongation at break. WPU can effectively improve the elongation at break of composite-modified emulsified asphalt, but it has a negative impact on adhesion strength. DMP-30 mainly affects the curing time of modified emulsified asphalt; EPD (composite modification) can effectively improve the high-temperature rutting resistance of matrix-emulsified asphalt, and its low-temperature performance is significantly improved compared with WER-modified emulsified asphalt. The EPD modification process mainly consists of physical blending. In the case of increasing the curing rate, it is recommended that the contents of WER and WPU be lower than 10% and 6%, respectively, to achieve excellent comprehensive performance of the composite modification.
Effect of Interlayer Temperature on Microstructure and Properties of High-Strength Low-Alloy Steel Manufactured Using Submerged-Arc Additive Manufacturing (SAAM)
Authors: Hu Meijuan , Chi Qiang , Ji Lingkang , Li Weiwei , Yan Shuai , Cheng Fangjie
Published: November 2024

Controlled interlayer temperature has a profound impact on both the microstructure and mechanical properties of the deposited components. In this study, thin-walled structures made of high-strength low-alloy steel were fabricated using the submerged-arc additive manufacturing process. The effects of varying temperature on the microstructure and mechanical properties of the components were studied. The results showed that the cooling rate within T8/5 decreased as the interlayer temperature increased, which caused the microstructure to transition from a fine-grained structure dominated by bainitic ferrite and granular bainite to a coarse-grained structure dominated by polygonal ferrite. The measurement of mechanical properties showed that due to the influence of the fine-grained structure, the components with low interlayer temperatures exhibit excellent hardness, high strength, and outstanding ductility and toughness. Furthermore, a faster cooling rate disrupts the stability of carbon diffusion, resulting in the development of increased quantities of residual austenitic films within the components with controlled low interlayer temperatures. This augmentation in residual austenite films strengthens the components’ ductility and toughness, enabling the deposited components to exhibit exceptional impact toughness in low-temperature environments.
On the Nature of the Interactions That Govern COV-2 Mutants Escape from Neutralizing Antibodies
Authors: Sussman Fredy , Villaverde Daniel S.
Published: November 2024

The most fruitful prevention and treatment tools for the COVID-19 pandemic have proven to be vaccines and therapeutic antibodies, which have reduced the spread of the disease to manageable proportions. The search for the most effective antibodies against the widest set of COV-2 variants has required a long time and substantial resources. It would be desirable to have a tool that will enable us to understand the structural basis on which mutants escape at least some of the epitope-bound antibodies, a tool that may substantially reduce the time and resources invested in this effort. In this work, we applied a computational-based tool (employed previously by us to understand COV-2 spike binding to its cognate cell receptor) to the study of the effect of Delta and Omicron mutations on the escape tendencies. Our binding energy predictions agree extremely well with the experimentally observed escape tendencies. They have also allowed us to set forth a structural explanation for the results that could be used for the screening of antibodies. Lastly, our results explain the differences in molecular interactions that govern interaction of the spike variants with the receptor as opposed to those with antibodies.
Ultra-Processed Food Intake and Risk of Insomnia: A Systematic Review and Meta-Analysis
Authors: Pourmotabbed Ali , Awlqadr Farhang Hameed , Mehrabani Sanaz , Babaei Atefeh , Wong Alexei , Ghoreishy Seyed Mojtaba , Talebi Sepide , Kermani Mohammad Ali Hojjati , Jalili Faramarz , Moradi Sajjad , Bagheri Reza , Dutheil Fred
Published: November 2024

Objectives: The objective of this investigation was to compile existing observational research and quantify the potential association between ultra-processed foods (UPFs) and the risk of insomnia using meta-analysis. Setting: We conducted a systematic search of the PubMed/MEDLINE, Scopus, and ISI Web of Science databases with no restrictions until 29 June 2024. Odds ratios (OR) and 95% confidence intervals (CI) were aggregated using a random-effects model, while the Newcastle-Ottawa Scale and Egger’s regression asymmetry test assessed study quality and publication bias, respectively. Results: Analysis of data from seven studies showed a significant positive association between higher intake of UPFs and an increased risk of insomnia (OR = 1.53; 95% CI: 1.20, 1.95; I2 = 62.3%; p = 0.014). Subgroup analysis indicated this positive relationship was particularly strong under the NOVA food classification (OR = 1.57; 95% CI: 1.03, 2.40; I2 = 78.5%; p = 0.009; n = 3) and with snack intake (OR = 1.33; 95% CI: 1.04, 1.71; I2 = 0.0%; p < 0.001; n = 2), compared to adherence to Western dietary patterns. Moreover, subgroup analysis based on age group showed that higher UPF intake was significantly associated with increased risk of insomnia among adolescents (OR = 1.55; 95% CI: 1.21, 1.99; I2 = 57.4%; p < 0.001) but not in adults. Conclusions: Our findings underscore a significant association between higher consumption of UPFs and increased risk of insomnia, particularly among adolescents. Further research is necessary to explore the intricacies of this association and to ensure the generalizability of these results.
Therapeutic Potential of Novel Silver Carbonate Nanostructures in Wound Healing and Antibacterial Activity Against Pseudomonas chengduensis and Staphylococcus aureus
Authors: Khan Tehmina , Umar Ali , Subhan Zakia , Khan Muhammad Saleem , Ali Hafeeza Zafar , Ullah Hayat , Sabri Sabeen , Wajid Muhammad , Iqbal Rashid , Bhat Mashooq Ahmad , Ali Hamid
Published: November 2024

Background/Objectives: Metallic NPs have been explored for various therapeutic uses owing to utilitarian physicochemical characteristics such as antibacterial, anti-inflammatory, and healing properties. The objective of this study is to evaluate the therapeutic potential of novel silver carbonate nanostructures in promoting wound healing and their antibacterial activity against Pseudomonas chengduensis and Staphylococcus aureus. Methods: In this work, we prepared Ag2CO3 nanoparticles through a two-step methodology that was expected to improve the material’s biomedical performance and biocompatibility. The characterization and assessment of synthesized NPs biocompatibility were conducted using hemolysis assays on the blood of a healthy male human. Further, we performed molecular docking analysis to confirm interactions of silver NPs with biological molecules. Results: In detail, the synthesized NPs showed <5% hemolysis activity at various concentrations, confirming their therapeutic applicability. Additionally, the NPs had good metabolic activities; they raised the T3/T4 hormone content and acted effectively on Insulin-like Growth Factor 1 (IGF-1) in diabetic models. They also facilitated the rate of repair by having the diabetic wounds reach 100% re-epithelialization by day 13, unlike the control group, which reached the same level only by day 16. The synthesized Ag2CO3 NPs exhibited high antimicrobial potential against both Pseudomonas chengduensis and Staphylococcus aureus, hence being a potential material that can be used for infection control in biomedical tissue engineering applications. Conclusions: These findings concluded that novel synthesis methods lead to the formation of NPs with higher therapeutic prospects; however, studies of their metaphysical and endocrinological effects are necessary.
Comprehensive Advanced Physicochemical Characterization and In Vitro Human Cell Culture Assessment of BMS-202: A Novel Inhibitor of Programmed Cell Death Ligand
Authors: Shafi Hasham , Lora Andrea J. , Donow Haley M. , Dickinson Sally E. , Wondrak Georg T. , Chow H.-H. Sherry , Curiel-Lewandrowski Clara , Mansour Heidi M.
Published: November 2024

Background/Objectives: BMS-202, is a potent small molecule with demonstrated antitumor activity. The study aimed to comprehensively characterize the physical and chemical properties of BMS-202 and evaluate its suitability for topical formulation, focusing on uniformity, stability and safety profiles. Methods: A range of analytical techniques were employed to characterize BMS-202. Scanning Electron Microscopy (SEM) was used to assess morphology, Differential Scanning Calorimetry (DSC) provided insights of thermal behavior, and Hot-Stage Microscopy (HSM) corroborated these thermal behaviors. Molecular fingerprinting was conducted using Raman spectroscopy and Fourier Transform Infrared (FTIR) spectroscopy, with chemical uniformity of the batch further validated by mapping through FTIR and Raman microscopies. The residual water content was measured using Karl Fisher Coulometric titration, and vapor sorption isotherms examined moisture uptake across varying relative humidity levels. In vitro safety assessments involved testing with skin epithelial cell lines, such as HaCaT and NHEK, and Transepithelial Electrical Resistance (TEER) to evaluate barrier integrity. Results: SEM revealed a distinctive needle-like morphology, while DSC indicated a sharp melting point at 110.90 ± 0.54 ℃ with a high enthalpy of 84.41 ± 0.38 J/g. HSM confirmed the crystalline-to-amorphous transition at the melting point. Raman and FTIR spectroscopy, alongside chemical imaging, confirmed chemical uniformity as well as validated the batch consistency. A residual water content of 2.76 ± 1.37 % (w/w) and minimal moisture uptake across relative humidity levels demonstrated its low hygroscopicity and suitability for topical formulations. Cytotoxicity testing showed dose-dependent reduction in skin epithelial cell viability at high concentrations (100 µM and 500 µM), with lower doses (0.1 µM to 10 µM) demonstrating acceptable safety. TEER studies indicated that BMS-202 does not disrupt the HaCaT cell barrier function. Conclusions: The findings from this study establish that BMS-202 has promising physicochemical and in vitro characteristics at therapeutic concentrations for topical applications, providing a foundation for future formulation development focused on skin-related cancers or localized immune modulation.
A Study on Typhoon Center Localization Based on an Improved Spatio-Temporally Consistent Scale-Invariant Feature Transform and Brightness Temperature Perturbations
Authors: Yan Chaoyu , Guang Jie , Li Zhengqiang , de Leeuw Gerrit , Chen Zhenting
Published: November 2024

Extreme weather events like typhoons have become more frequent due to global climate change. Current typhoon monitoring methods include manual monitoring, mathematical morphological methods, and artificial intelligence. Manual monitoring is accurate but labor-intensive, while AI offers convenience but requires accuracy improvements. Mathematical morphology methods, such as brightness temperature perturbation (BTP) and a spatio-temporally consistent (STC) Scale-Invariant Feature Transform (SIFT), remain mainstream for typhoon positioning. This paper enhances BTP and STC SIFT methods for application to Fengyun 4A (FY-4A) Advanced Geosynchronous Radiation Imager (AGRI) L1 data, incorporating parallax correction for more accurate surface longitude and latitude positioning. The applicability of these methods for different typhoon intensities and monitoring time resolutions is analyzed. Automated monitoring with one-hour observation intervals in the northwest Pacific region demonstrates high positioning accuracy, reaching 25 km or better when compared to best path data from the China Meteorological Administration (CMA). For 1 h remote sensing observations, BTP is more accurate for typhoons at or above typhoon intensity, while STC SIFT is more accurate for weaker typhoons. In the current era of a high temporal resolution of typhoon monitoring using geostationary satellites, the method presented in this paper can serve the national meteorological industry for typhoon monitoring, which is beneficial to national pre-disaster prevention work as well as global meteorological research.
Mapping Seasonal Spatiotemporal Dynamics of Alpine Grassland Forage Phosphorus Using Sentinel-2 MSI and a DRL-GP-Based Symbolic Regression Algorithm
Authors: Shi Jiancong , Zhang Aiwu , Wang Juan , Gao Xinwang , Hu Shaoxing , Chai Shatuo
Published: November 2024

An accurate estimation of seasonal spatiotemporal dynamics of forage phosphorus (P) content in alpine grassland is crucial for effective grassland and livestock management. In this study, we integrated Sentinel-2 multispectral imagery (MSI) with computational hyperspectral features (CHSFs) and developed a novel symbolic regression algorithm based on deep reinforcement learning and genetic programming (DRL-GP) to estimate forage P content in alpine grasslands. Using 243 field observations collected during the regreening, grass-bearing, and yellowing periods in 2023 from the Shaliu River Basin, we generated 10 CHSF images (CHSFIs) with varying spectral dispersions (1–10 nm). Our results demonstrated the following: (1) The DRL-GP-based symbolic regression model identified the optimal CHSF and spectral dispersion for each growing season, significantly enhancing estimation accuracy. (2) Forage P content estimations using the combined CHSF and DRL-GP-based symbolic regression algorithm significantly outperformed traditional methods. Compared to original spectral features, the R2 improved by 99.5%, 57.4%, and 86.2% during the regreening, grass-bearing, and yellowing periods, with corresponding MSE reductions of 84.8%, 41.5%, and 75.8% and MAE decreases of 70.7%, 57.5%, and 50.4%. Across these growing seasons, the R2 increased by 322.2%, 68.2%, and 639.8% compared to MLR, 128.9%, 97.4%, and 469.2% compared to RF, and 485.1%, 65.3%, and 231.3% compared to DNN. The MSE decreased by 31%, 82.9%, and 52.4% compared to MLR, 39.9%, 42.4%, and 31.4% compared to RF, and 84.5%, 73.4%, and 81.9% compared to DNN. The MAE decreased by 32.6%, 67%, and 44.2% compared to MLR, 42.6%, 47.6%, and 37.9% compared to RF, and 60.2%, 50%, and 56.3% compared to DNN. (3) Proximity to the water system notably influenced forage P variation, with the highest increases observed within 1–2 km of water sources. These findings provide critical insights for optimizing grassland management and improving livestock productivity.
Preliminary Global NO2 Retrieval from EMI-II Onboard GF5B/DQ1 and Comparison to TROPOMI
Authors: Cheng Liangxiao , Wang Yapeng , Yan Huanhuan , Tao Jinhua , Wang Hongmei , Lin Jun , Xu Jian , Chen Liangfu
Published: November 2024

The Environmental Trace Gases Monitoring Instrument (EMI-II) onboard the Chinese GaoFen-5B (GF5B) and DaQi-1 (DQ1) satellites is the successor of the previous EMI onboard the Chinese GaoFen-5 (GF5) satellite, and has a higher spatial resolution and a better signal-to-noise ratio. The GF5B and DQ1 were launched in September 2021 and April 2022, respectively. As part of China’s ultraviolet-visible hyperspectral satellite instrument series, the EMI-II aims to conduct network observations of pollution gases globally in the morning and early afternoon. In this study, NO2 data were retrieved from the EMI-II payloads on the GF5B and DQ1 satellites using the Differential Optical Absorption Spectroscopy (DOAS) algorithm. The two satellites were consistently compared, and the results showed strong consistency on various spatial and temporal scales (R2 > 0.8). In four representative regions worldwide, NO2 data from the EMI-II exhibited good spatial consistency with those from the TROPOMI. The correlation coefficient (R2) of the total vertical column density (VCD) between the EMI-II and TROPOMI exceeded 0.85, and that of the tropospheric NO2 VCD exceeded 0.57. Compared with single-satellite observations, the dual-satellite network of the GF5B and DQ1 can effectively increase the observation frequency. On a daily scale, dual-satellite observations can reduce the impact of cloud coverage by 6–8% compared to single-satellite observations, and there are two valid observations of nearly 50% of the world’s regions. Additionally, the differences between the two satellites can reflect the NO2 diurnal variations, which demonstrates the potential for studying pollutant gas diurnal variations.
The Role of Subsurface Changes and Environmental Factors in Shaping Urban Heat Islands in Southern Xinjiang
Authors: Wen Cong , Sayit Hajigul , Mamtimin Ali , Wang Yu , Peng Jian , Aihaiti Ailiyaer , Song Meiqi , Gao Jiacheng , Liu Junjian , Wulayin Yisilamu , Yang Fan , Huo Wen , Zhou Chenglong
Published: November 2024

The urban heat island (UHI) effect is one of the most prominent surface climate changes driven by human activities. This study examines the UHI characteristics and influencing factors in the Southern Xinjiang urban agglomeration using MODIS satellite data combined with observational datasets. Our results reveal a significant increase in impervious surfaces in the region between 1995 and 2015, with the most rapid expansion occurring from 2010 to 2015. This urban expansion is the primary driver of changes in UHI intensity. The analysis from 2000 to 2015 shows substantial spatial variation in UHI effects across cities. Hotan recorded the highest annual average daytime UHI intensity of 3.7 °C, while Aksu exhibited the lowest at approximately 1.6 °C. Daytime UHI intensity generally increased during the study period, with the highest intensities observed in the summer. However, nighttime UHI trends varied across cities, with most showing an increase in intensity. Temperature, precipitation, and aerosol optical depth (AOD) were identified as the main factors influencing annual average daytime UHI intensity, while PM10 concentration showed a weak and inconsistent correlation with UHI intensity, varying by city and season.
Spatiotemporal Evolution Analysis of Surface Deformation on the Beihei Highway Based on Multi-Source Remote Sensing Data
Authors: Shan Wei , Xu Guangchao , Hou Peijie , Du Helong , Du Yating , Guo Ying
Published: November 2024

Under the interference of climate warming and human engineering activities, the degradation of permafrost causes the frequent occurrence of geological disasters such as uneven foundation settlement and landslides, which brings great challenges to the construction and operational safety of road projects. In this paper, the spatial and temporal evolution of surface deformations along the Beihei Highway was investigated by combining the SBAS-InSAR technique and the surface frost number model after considering the vegetation factor with multi-source remote sensing observation data. After comprehensively considering factors such as climate change, permafrost degradation, anthropogenic disturbance, and vegetation disturbance, the surface uneven settlement and landslide processes were analyzed in conjunction with site surveys and ground data. The results show that the average deformation rate is approximately −16 mm/a over the 22 km section of the study area. The rate of surface deformation on the pavement is related to topography, and the rate of surface subsidence on the pavement is more pronounced in areas with high topographic relief and a sunny aspect. Permafrost along the roads in the study area showed an insignificant degradation trend, and at landslides with large surface deformation, permafrost showed a significant degradation trend. Meteorological monitoring data indicate that the annual minimum mean temperature in the study area is increasing rapidly at a rate of 1.266 °C/10a during the last 40 years. The occurrence of landslides is associated with precipitation and freeze–thaw cycles. There are interactions between permafrost degradation, landslides, and vegetation degradation, and permafrost and vegetation are important influences on uneven surface settlement. Focusing on the spatial and temporal evolution process of surface deformation in the permafrost zone can help to deeply understand the mechanism of climate change impact on road hazards in the permafrost zone.
Efficient Music Genre Recognition Using ECAS-CNN: A Novel Channel-Aware Neural Network Architecture
Authors: Ding Yang , Zhang Hongzheng , Huang Wanmacairang , Zhou Xiaoxiong , Shi Zhihan
Published: November 2024

In the era of digital music proliferation, music genre classification has become a crucial task in music information retrieval. This paper proposes a novel channel-aware convolutional neural network (ECAS-CNN) designed to enhance the efficiency and accuracy of music genre recognition. By integrating an adaptive channel attention mechanism (ECA module) within the convolutional layers, the network significantly improves the extraction of key musical features. Extensive experiments were conducted on the GTZAN dataset, comparing the proposed ECAS-CNN with traditional convolutional neural networks. The results demonstrate that ECAS-CNN outperforms conventional methods across various performance metrics, including accuracy, precision, recall, and F1-score, particularly in handling complex musical features. This study validates the potential of ECAS-CNN in the domain of music genre classification and offers new insights for future research and applications.
Evaluating the Accuracy of Virtual Reality in Replicating Real-Life Human Postures and Forces for Injury Risk Assessment
Authors: Ji Xiaoxu , Gao Xin , Swierski Ethan
Published: November 2024

The objective of this study was to assess the accuracy of virtual reality (VR) technology in replicating real-life environments for the adoption of appropriate human postures and forces. Despite the widespread implementation of VR in various applications, there is a lack of research evaluating the accuracy of human postures and sensory aspects in the VR environment compared to real-life scenarios. A total of twenty-two student participants were recruited for this study, which involved a common lifting task. Two specific poses were identified as having potentially excessive forces exerted on the lower back. By comparing the angles of seven anatomical joints in both the real environment and the VR environment at each pose, we observed that depth perception may influence posture adoption in the VR setting. Moreover, the presence of a physical load applied to both hands significantly influenced the postures adopted by participants compared to those in the VR environment. These deviations in postures directly led to significant differences in predicted spinal forces exerted on the lower back, which in turn could result in inaccurate assessments of injury risks and the design of injury prevention programs. Therefore, it is crucial to understand the accuracy of VR technology as a substitute for real-life environments.
Predicting Sustainable Crop Yields: Deep Learning and Explainable AI Tools
Authors: Malashin Ivan , Tynchenko Vadim , Gantimurov Andrei , Nelyub Vladimir , Borodulin Aleksei , Tynchenko Yadviga
Published: November 2024

Optimizing agricultural productivity and promoting sustainability necessitates accurate predictions of crop yields to ensure food security. Various agricultural and climatic variables are included in the analysis, encompassing crop type, year, season, and the specific climatic conditions of the Indian state during the crop’s growing season. Features such as crop and season were one-hot encoded. The primary objective was to predict yield using a deep neural network (DNN), with hyperparameters optimized through genetic algorithms (GAs) to maximize the R2 score. The best-performing model, achieved by fine-tuning its hyperparameters, achieved an R2 of 0.92, meaning it explains 92% of the variation in crop yields, indicating high predictive accuracy. The optimized DNN models were further analyzed using explainable AI (XAI) techniques, specifically local interpretable model-agnostic explanations (LIME), to elucidate feature importance and enhance model interpretability. The analysis underscored the significant role of features such as crops, leading to the incorporation of an additional dataset to classify the most optimal crops based on more detailed soil and climate data. This classification task was also executed using a GA-optimized DNN, aiming to maximize accuracy. The results demonstrate the effectiveness of this approach in predicting crop yields and classifying optimal crops.
Digital Transformation and Carbon Intensity: Evidence from Chinese Tourism Companies
Authors: Lin Yi , Qi Xin , Wang Lijuan
Published: November 2024

The flourishing of the tourism market generates gigantic carbon emissions. It is imperative for tourism companies to take action to achieve decarbonization. The emergence of digital technology is gradually becoming an important strategic path for global corporations’ technological evolution. Undoubtedly, digital tools provide a fresh opportunity for tourism companies to reduce their carbon footprint. Realizing the positive interaction between digitization and greenization is essential for tourism companies to achieve high-quality development. Aiming to clarify the relationship between digital transformation and company carbon intensity in tourism companies, this study analyzes the influence and mechanism of digital transformation on tourism companies’ carbon intensity using data from Chinese A-share listed tourism companies over the period 2005–2020. With the help of textual analysis and high-dimensional fixed effects model, this paper builds a proxy for digital transformation and further tests the causal link between digital transformation and company carbon intensity. The findings indicate that digital transformation significantly reduces the carbon intensity of tourism companies. Alleviating managerial myopia, attracting external resources, and fostering a collaborative culture are three mechanisms through which digital transformation can exert its carbon reduction efficacy. The heterogeneity analysis reveals that this effect is more prominent among state-owned tourism companies, companies with greater board diversity, or companies situated in more favorable business environments. This paper makes three contributions. First, this paper broadens the exploration of how digital advancements affect tourism, discussing the relationship between digital transformation and the carbon intensity of tourism companies. Second, this paper looks beyond a macro perspective commonly used in tourism carbon emission research, undertaking the research at the micro level, filling the research gap in tourism companies’ carbon performance. Third, from the aspect of informational effect, this paper provides the mechanism between digital transformation and tourism company carbon intensity creatively. The conclusions offer empirical insights to assist tourism companies in effectively fulfilling their environmental commitments in the digital era. Meanwhile, this paper also provides a useful decision-making basis for the government to promote tourism companies’ decarbonization transformation. From the company perspective, tourism companies should take digitalization seriously, fully exploiting the environmental benefits of digital transformation. From the government perspective, local government should further improve the environment for company development, supporting tourism companies’ digital transformation with unremitting efforts.
Waste-Cooking-Oil-Derived Polyols to Produce New Sustainable Rigid Polyurethane Foams
Authors: Cappello Miriam , Filippi Sara , Rossi Damiano , Cinelli Patrizia , Anguillesi Irene , Camodeca Caterina , Orlandini Elisabetta , Polacco Giovanni , Seggiani Maurizia
Published: November 2024

Polyurethanes (PUs) are one of the most versatile polymeric materials, making them suitable for a wide range of applications. Currently, petroleum is still the main source of polyols and isocyanates, the two primary feedstocks used in the PU industry. However, due to future petroleum price uncertainties and the need for eco-friendly alternatives, recent efforts have focused on replacing petrol-based polyols and isocyanates with counterparts derived from renewable resources. In this study, waste cooking oil was used as feedstock to obtain polyols (POs) for new sustainable polyurethane foams (PUFs). POs with various hydroxyl numbers were synthesized through epoxidation followed by oxirane ring opening with diethylene glycol. By adjusting reagent amounts (acetic acid and H2O2), epoxidized oils (EOs) with different epoxidation degrees (50–90%) and, consequently, POs with different OH numbers (200–300 mg KOH/g) were obtained. Sustainable PUFs with high bio-based content were produced by mixing the bio-based POs with a commercial partially bio-based aliphatic isocyanate and using water as the blowing agent in the presence of a gelling catalyst and additives. Various water (4, 8, 15 php) and gelling catalyst (0, 1, 2 php) amounts were tested to assess their effect on foam properties. PUFs were also prepared using EOs instead of POs to investigate the potential use of EOs directly in PUF production. Characterization included morphological, chemical, physical, thermal, and mechanical analyses. The rigid PUFs exhibited high density (150–300 kg/m³) and stability up to 200 °C. The combined use of bio-based polyols with partially bio-based isocyanate and water enabled PUFs with a bio-based content of up to 77 wt.%. EOs demonstrated potential in PUF production by bypassing the second synthesis step, enhancing sustainability, and significantly reducing energy and costs; however, PUF formulations with EOs require optimization due to lower epoxy ring reactivity.
A Hybrid MCDM Approach to Sports Center Site Selection in a Sustainable Environment
Authors: Chou Tsung-Yu
Published: November 2024

In order to achieve the goal of good health and well-being in Sustainable Development Goals (SDGs), the government has actively promoted the concept of sports and fitness. People expect the government could effectively build leisure facilities and sports centers that can provide high-quality services and activities. The purpose of this research is to establish a systematic model to help the government improve the quality of decision making and integrate various methods to expand the evaluation of site selection more objectively. This paper develops a hybrid MCDM model based on AHP, entropy and gray relational analysis methods to realize the location-selection process of sports centers. In this paper, a hybrid MCDM model was developed to realize the location-selection process of a sports center. Three perspectives and six major factors (including the 16 criteria) for the sports center location selection are presented. Among them, geographical conditions are the most important perspective, surrounding environment is the most important factor and the second most important factor is future development. The results of this research will provide reference for relevant government departments.
Repurposing Quality-Downgraded Fluorinated Carbon Nanotubes as Eco-Additives in Microgel Composites for Sustained Water Release
Authors: Ezeogu Favour Lewechi , Ojha Gunendra Prasad , Otuokere Promise Uzoamaka , Islam Mohammad Tarequl , Grady Tony , Gao Yunxiang
Published: November 2024

While significant efforts have been made to recycle metals like lithium or cobalt for sustainable development in the battery industry, the reuse of other high-value materials, such as fluorinated carbon nanotubes (FCNTs), remains underexplored. This study introduces a novel, eco-friendly method to repurpose quality-downgraded FCNTs (QD-FCNTs) as effective nano-additives in polyacrylamide (PAAm) microgel composites for water retention applications. Because QD-FCNTs are rich in surface defects, by employing a mild surface treatment with a low dosage of organic electron donor N,N,N′,N′-tetramethyl-p-phenylenediamine, we enhanced the hydrophilicity of QD-FCNTs without additional energy input or a large quantity of harmful chemicals. This treatment significantly improved the interaction between QD-FCNTs and PAAm microgels, leading to a 55% increase in water retention time compared to the composites made of untreated QD-FCNTs. Our findings present a sustainable approach to extending the lifecycle of FCNTs, contributing to the circular economy and offering practical solutions for potential water management in agriculture and environmental technologies.
Ecological Flow Assessment: Balancing Trout and Grayling Habitat Ecology and Hydroelectric Production
Authors: Angeles Raphaël , Della Croce Patrick , Ferrario Federico , De Cesare Giovanni
Published: November 2024

In light of Switzerland’s 2050 energy goals, the nation aims to boost its domestic hydroelectric output, notably focusing on small-scale hydroelectric power plants. Concurrently, there is an effort to renovate hydroelectric plants to make them more environmentally friendly, emphasizing ecological flow regulation to improve river conditions. This study explores the application of a non-proportional flow allocation method to better assess both ecological and economic outcomes. Unlike traditional fixed or proportional flow methods, this approach allows for a more dynamic balance between hydropower generation and riverine ecosystem health. This study focuses on two key species, brown trout and grayling. In particular, this work highlighted that trout are better suited for low-flow conditions (Weighted Usable Area, WUA, peaks below 1 m3/s), while grayling require significantly higher flows (WUA peaks over 4.5 m3/s). This disparity in habitat preferences raises concerns about the current reliance on single-species models, emphasizing the need for multi-species ecological assessment in future studies. When applied to a small hydropower plant in the Swiss Jura, the non-proportional flow method resulted in an improvement of ecological conditions of at least 37.7%, which consequently led to a reduction of the hydroelectric production of at least 10%. Through strategic upgrades to the facility (e.g., by minimizing hydraulic losses, implementing more efficient turbines, or incorporating photovoltaic panels over water channels), it is possible to simultaneously enhance both energy output and environmental sustainability. These findings suggest that non-proportional flow allocation holds significant potential for broader use in sustainable hydropower management, providing a pathway toward meeting both energy production and ecological conservation goals.
Adopting Circular Economy Principles: How Do Conflict Management Strategies Help Adopt Smart Technology in Jordanian SMEs?
Authors: Almasri Aydah , Ying Ma
Published: November 2024

Smart technology is essential for integrating circular economy principles. This research investigates how conflict management strategies (collaboration, accommodation, avoidance, compromise, and competition) impact the adoption of smart technology, particularly blockchain, in Jordanian SMEs. Additionally, the study explores the moderating role of customer-centric green supply chain management in the relationship between blockchain adoption and circular economy principles. This research addresses a gap in the literature by focusing on Jordanian SMEs, an under-explored context. Data were collected from 421 senior managers, department heads, and executives of Jordanian SMEs, and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), to test the hypotheses and analyze complex relationships. The findings reveal that conflict management strategies are critical in blockchain adoption, with collaboration and compromise emerging as the most influential. Moreover, blockchain adoption positively impacts the implementation of circular economy principles. The moderating effect of customer-centric green supply chain management enhances the sustainability and competitiveness of SMEs through blockchain technology. This research contributes to theory and practice by providing valuable insights into the strategic role of conflict management in driving technological innovation and sustainability within the circular economy framework, particularly in the context of Jordanian SMEs.
Landslide Susceptibility Assessment Using a CNN–BiLSTM-AM Model
Authors: Ju Xiaoxiao , Li Junjie , Sun Chongxiang , Li Bo
Published: November 2024

Landslides are common geological hazards worldwide, posing significant threats to both the environment and human lives. The preparation of a landslides susceptibility map is a major method to address the challenge related to sustainability. The study area, Nyingchi, is located in the southeastern region of the Qinghai-Tibet plateau, characterized by diverse terrain and complex geological formations. In this study, CNN was used to extract high-order features from the influencing factors, while BiLSTM was utilized to mine the historical data. Additionally, the attention mechanism was added to adjust the model weights dynamically. We constructed a hybrid CNN–BiLSTM-AM model to assess landslide susceptibility. A spatial database of 949 landslides was established using remote sensing images and field surveys. The effects of various feature selection methods were analyzed, and model performance was compared to that of six advanced models. The results show that the proposed model achieved a high prediction accuracy of 90.12% and exhibits strong generalization capabilities over large areas. It should be noted, however, that the influence of feature selection methods on model performance remains uncertain under complex conditions and is affected by multiple mechanisms.
Assessing the Potential of Alternative Food Networks for the Sale and Distribution of Local Varieties in Granada (Spain)
Authors: Ibáñez-Jiménez Álvaro , Jiménez-Olivencia Yolanda , Mesa-Pedrazas Ángela , Porcel-Rodríguez Laura
Published: November 2024

The process of standardization within the dominant agrifood system is being accompanied by growing demand for differentiated high-quality food products that are environmentally sustainable. In this scenario, Alternative Food Networks (AFNs) could help the local agrifood sector and local or traditional variety crops regain their pivotal role. The objective of this paper is to assess the potential of AFNs in the metropolitan area of Granada and in the nearby mountain region of the Alpujarra in the promotion and distribution of local varieties of fruit and vegetables from this region. The research took the form of case studies in which the information was collected in semi-structured interviews with the AFNs and then subjected to content analysis. The results highlight that the socioenvironmental commitment of the AFNs is their strongest asset for the conservation, sale, and distribution of biodiverse local variety produce. However, these organizations still have very limited knowledge of local varieties and there are doubts as to their capacity to mobilize sufficient volumes of these products and successfully establish themselves in rural areas.
The Effects of 6 February 2023 Earthquakes on the Production and Marketing Process of Firms in the Agriculture and Food Sector: The Case of Malatya Province, Türkiye
Authors: Aydın Can Bahar , Gerdan Serpil , Aslan Ramazan
Published: November 2024

Ensuring sustainability in the production and marketing of agricultural and food products after natural disasters is of critical importance to maintain beneficial nutrition for society. Examining the effects of earthquakes on the agricultural and food sectors is important in terms of drawing attention to the possible risks they may pose to societies that have not experienced large-scale earthquakes. This study examines firms in the agriculture and food sectors of Malatya province that were affected by the devastating earthquakes centered in Kahramanmaraş on 6 February 2023. This study aimed to determine the effects of earthquakes on firms in the agriculture and food sectors, the factors affecting firms’ production and marketing processes, and the priority issues for them. Data obtained from 44 firms registered in the agricultural and food sectors of the Organized Industrial Zone of Malatya province were used. This study reports their general structure and frequency distributions by firm characteristics. In addition, statistical analysis methods, such as the chi-squared test, t-test, and factor analysis, were used for data evaluation. The results showed that 79.5% of firms export and make a significant contribution to Türkiye’s agricultural and food product trade. The primary factors influencing firms, based on their size, included workforce availability, raw material supply, transportation logistics, and financial assistance. Firms’ earthquake insurance, providing earthquake training for their employees, and constructing durable buildings were the most important factors in ensuring sustainability in production and marketing. These results further show that firms in the agriculture and food sectors in Malatya province were greatly affected economically by the earthquakes. Important lessons emerged as a result of these earthquakes experienced in Türkiye. The economic disruption following earthquakes may be overcome with less damage by constructing disaster-resistant buildings, instilling awareness of living with earthquakes in society, and creating safe production environments. This field study will guide sector stakeholders in building a resilient supply, production, and marketing network in preparation for future earthquakes.
How Quasi-Internal Resources Enhance Firm Performance During Large-Scale Emergencies: The Role of Trade-Off Between CSR and Business Innovations
Authors: He Xilin , da Costa Renato Lopes , Ni Debing , Han Wucheng
Published: November 2024

Although quasi-internal resources—such as strategic alliances, long-term partnerships, and collaborative networks—typically enhance a firm’s adaptability, their effectiveness can be compromised in crisis situations due to supply chain disruptions, strained partnerships, and volatile market conditions. This research explores how quasi-internal resources influence firm performance through the trade-off between corporate social responsibility (CSR) and business innovation, with a particular focus on the moderating role of market environmental uncertainty. We developed a theoretical model grounded in resource dependence theory and tested our hypotheses using PLS-SEM analysis on data from 397 valid questionnaires collected from various companies. The findings reveal that quasi-internal resources do not directly enhance firm performance during large-scale emergencies. However, they play a critical role in strengthening the trade-off between CSR and business innovation, particularly through strategic adjustments and decision-making processes, which mediate their impact on performance. Conversely, the trade-off in incentive mechanisms does not significantly mediate this relationship. Additionally, market environmental uncertainty positively moderates the relationship between quasi-internal resources and the trade-offs in incentive mechanisms and decision-making processes, but it does not significantly affect strategic adjustments. These insights underscore the importance of strategic resource management in sustaining firm performance amidst uncertainty.
Sustainable Urban Heat Risk Resilience: Lessons on Opportunities and Barriers to Action from Colombo, Sri Lanka
Authors: Simath Shifana , Emmanuel Rohinton , Aarrevaara Eeva
Published: November 2024

Cities face increasing heat risk due to global and local warming, and the risk is greater in the developing world. South Asia, in particular, faces increasing urban climate risk, but the translation of urban climate knowledge into sustainable climate-sensitive planning is weak. In this paper, we report on our conversations with experts from the Sri Lankan urban planning community on the barriers to and opportunities for urban climate mitigation action. We uncover six themes (insights, integrate, specify, exhort, commitment, and continuity) that best exemplify both the barriers to and opportunities for enhancing heat risk resilience in this primate city. We then map a set of agencies and actors that need to be involved in any holistic risk resilience plan and draw wider lessons to sustainably manage the urgent practical gaps in heat health planning.
The Spatial Patterns and Architectural Form Characteristics of Chinese Traditional Villages: A Case Study of Guanzhong, Shaanxi Province
Authors: Lian Mengchen , Li Yanjun
Published: November 2024

This study examined the decline of traditional villages due to urbanization, focusing on their spatial patterns and architectural characteristics in China, particularly in the Guanzhong region. Using ArcGIS tools, kernel density and nearest-neighbor analyses quantitatively assessed the spatial distribution of these villages at macro- and micro-levels. Additionally, 3D laser scanning was employed to qualitatively analyze architectural features. The study demonstrated that (1) traditional villages are unevenly clustered nationwide, primarily in the southeast and southwest, creating a “three cores and multiple points” spatial pattern. (2) In the Guanzhong region, traditional village distribution also shows clustering with diverse patterns, including regiment, belt, and point formations. Higher densities are found in the eastern and northern regions, while the west and south are sparsely populated. Most villages are located at altitudes of 501–700 m, on slopes of 6–15°, and near water sources. (3) The basic residential structures in Guanzhong included the single, vertical multi-entry, and horizontal coupled courtyards, as well as the vertical and horizontal interleaved layouts; these buildings typically featured the foundations and walls made of earth, stone, and brick, combined with various wooden frames and single- or double-sloped roofs. This study overcomes the limitations of the traditional literature and field surveys by quantitatively and qualitatively analyzing the spatial patterns of traditional villages and the architectural forms of residential buildings from an architectural perspective. It graphically presents the data to provide an efficient and practical theoretical basis for the heritage preservation and development of traditional villages.