bluuebunny/crossref_metadata_2025 huggingface dataset:
3,6-Dimethoxythieno[3,2-b]thiophene-Based Bifunctional Electrodes for High-Performance Electrochromic Supercapacitors Prepared by One-Step Electrodeposition
Authors: Yu Zhixuan , Wang Rui , Tang Huayu , Zheng Ding , Yu Junsheng
Published: August 2024

An integrated visual energy system consisting of conjugated polymer electrodes is promising for combining electrochromism with energy storage. In this work, we obtained copolymer bifunctional electrodes poly(3,6-dimethoxythieno[3,2-b]thiophene-co-2,3-dihydrothieno[3,4-b][1,4]dioxin-3-ylmethanol)(P(TT-OMe-co-EDTM)) by one-step electrochemical copolymerization, which exhibits favorable electrochromic and capacitive energy storage properties. Because of the synergistic effect of PTT-OMe and PEDTM, the prepared copolymers show better flexibility. Moreover, the morphology and electrochemical properties of the copolymers could be adjusted by depositing different molar ratios of 3,6-dimethoxythieno[3,2-b]thiophene (TT-OMe) and 2,3-dihydrothieno[3,4-b][1,4] dioxin-3-ylmethanol (EDTM). The P(TT-OMe-co-EDTM) electrodes realized a high specific capacitance (190 F/g at 5 mV/s) and recognizable color conversion. This work provides a novel and simple way to synergistically improve electrochromic and energy storage properties and develop thiophene-based conducting polymers for electrochromic energy storage devices.
Overview of Salt Cavern Oil Storage Development and Site Suitability Analysis
Authors: Zhang Nan , Gao Xinrong , Yan Baoxu , Zhang Yun , Ji Songtao , Shi Xilin
Published: August 2024

Salt cavern storage, characterized by its safety, stability, large scale, economic viability, and efficiency, stands out as a cost-effective and relatively secure method for large-scale petroleum reserves. This paper provides an overview of the current development status of salt cavern storage technologies both domestically and internationally, analyzes the advantageous conditions and numerous challenges faced by salt cavern Strategic Petroleum Reserve (SPR) storage in China, and forecasts the development trends of this technology. The conclusions indicate that China possesses all of the necessary conditions for the development of salt cavern storage. Moreover, utilizing the Analytical Hierarchy Process (AHP), a macro suitability hierarchical evaluation system is constructed for the site selection and construction of salt cavern storage facilities. This system quantifies various site selection indicators, integrating expert opinions and findings from relevant theoretical research to establish grading standards for the suitability indices of salt cavern storage construction. Applied to the site evaluation of salt cavern storage at the Jintan Salt Mine in Jiangsu, the results indicate its high suitability for storage construction, making it an ideal location for establishing such facilities. The evaluation results are consistent with expert opinions, demonstrating the rationality of this method.
Novel Efficiency Calculation Model Based on Fine Particle Tracking Behavior
Authors: Liu Xiulin , Chen Jianyi , Cui Hao , Ma Xiao , Zhang Hongbin , Shan Yongrui
Published: August 2024

The underflow entrainment of fine particles occurs during the hydrocyclone separation process, resulting in a “fishhook” effect on grade efficiency. Traditional efficiency models fail to address this phenomenon. This study examines the tracking behavior of fine particles, using variations in centrifugal settling velocity to characterize separation performance. The effect of this behavior on particle separation is quantified through a tracking coefficient for small particles and an entrainment coefficient for large particles, together forming a novel efficiency calculation model. The experimental research shows that the new model is applicable for the efficiency calculation of particles with different shapes, and can calculate grade efficiency curves with fishhook segments. By comparing with the existing research results, the accuracy and universality of the new model have been demonstrated. This model facilitates the accurate computation of grade efficiency curves, thereby significantly enhancing the precision of efficiency calculations, which provides guidance for the design and selection of hydrocyclones.
Mitigation of Fracturing Fluid Leak-Off and Subsequent Formation Damage Caused by Coal Fine Invasion in Fractures: An Experimental Study
Authors: Wang Fengbin , Huang Fansheng , Guan Yiting , Xu Zihan
Published: August 2024

During the hydraulic fracturing process of coalbed methane (CBM) reservoirs, significant amounts of secondary coal fines are generated due to proppant grinding and crack propagation, which migrate with the fracturing fluid into surrounding fracture systems. To investigate whether coal fines can form plugs to reduce fluid leak-off during the hydraulic fracturing stage, we conducted physical simulation experiments on coal seam plugging and unplugging to demonstrate that coal fines indeed contribute to reducing fluid leak-off during hydraulic fracturing. We also explored the plugging mechanisms of coal fines under different concentrations and particle sizes in fracturing fluids, and revealed the damage law of coal fines of temporary plugging on reservoir permeability. Research results indicate the leak-off volume of fracturing fluids containing coal fines is lower than an order without coal fines, demonstrating a significant effect of coal fines in decreasing fluid leak-off. The temporary plugging rate of coal fines increases with higher concentrations and decreases with larger particle sizes, achieving rates exceeding 90%. The high temporary plugging effect of coal fines results from the superposition of internal and external filter cakes. Under conditions of small particle size and high concentration, the damage to fractures during the fine return process is minimized. Considering the potential damage of coal fines to propping fractures and wellbore, the concentration of coal fines in fracturing fluids should be kept relatively low while ensuring a high temporary plugging effect. Overall, these findings provide crucial insights into optimizing the temporary plugging performance of coal fines during the hydraulic fracturing stage and controlling their behavior during the fracturing fluid flow-back stage, thereby enhancing reservoir fracturing effectiveness and improving CBM production rates.
Research on the Effect of Static Pressure on the Rheological Properties of Waxy Crude Oil
Authors: Yang Chao , Qi Jingjing , Li Bingfan , Luo Haijun
Published: August 2024

In this paper, with the application of a MARS 60 high-pressure rheometer, experimental tests are conducted on Shengli crude oil to test its gel point, viscosity and thixotropy under different static pressures. Consequently, the effect of static pressure on the rheological parameters of waxy crude oil is revealed. It is proven that with the increase in the static pressure, the gel point of Shengli crude oil increases linearly, and the viscosity also gradually increases. The power law equation is employed to describe the relationship between the apparent viscosity and shear rate of Shengli crude oil under different static pressures. With the increase in the static pressure, the consistency coefficient (K) increases linearly, and the rheological index (n) decreases linearly. The relationship between the viscosity of Shengli crude oil and the static pressure and shear rate can be obtained. The Cross thixotropic model is used to describe the thixotropic curve of Shengli crude oil under different static pressures. With the increase in the static pressure, the thixotropic coefficient of consistency (ΔK) and the structure fracture constant (b) increase linearly. This is because a high pressure results in high structure strength and strong non-Newton rheological behavior in gelled crude oil and also causes remarkable structure fracture in crude oil. The results in this paper can provide an important theoretical basis for crude oil production and transportation.
Assessing Quality Attributes and Antioxidant Effects in Chocolate Milk Formulated with Gum Arabic and Desert Truffle
Authors: Alsaleem Khalid A. , Musa Khalid H. , Hamouda Mahmoud E. A. , Hamad Essam M.
Published: August 2024

The increasing demand for functional and nutritious beverages necessitates the exploration of novel ingredients and formulations. This study evaluated the impact of supplementing chocolate milk with desert truffles powder and varying concentrations of gum arabic on its chemical composition, viscosity, color characteristics, antioxidant activity, and sensory attributes. Desert truffles powder was consistently incorporated at 2% across all treatments, while gum arabic concentrations varied from 0% to 1.5%. The results revealed significant enhancements in the nutritional profile, particularly in treatments with higher gum arabic concentrations, which showed increased solids-not-fat, protein, and carbohydrate contents. Additionally, the viscosity and shear stress values of the chocolate milk improved with the addition of gum arabic, enhancing its texture and stability. Color analysis demonstrated a darker and more intense coloration in samples with higher gum arabic levels. Antioxidant activity, assessed through total phenolic content, DPPH, and ABTS scavenging activity, was highest at moderate gum arabic concentrations but declined at higher levels. A high correlation was observed between total phenolic content and both DPPH and ABTS scavenging activities. Sensory evaluation indicated no significant differences in flavor, consistency, color, and overall acceptability across treatments, suggesting that the nutritional enhancements did not compromise sensory qualities. Overall, this study highlights that incorporating desert truffles powder and gum arabic can effectively improve the functional and nutritional properties of chocolate milk, presenting it as a viable option for health-oriented consumers.
Risk Assessment Approach of Electronic Component Selection in Equipment R&D Using the XGBoost Algorithm and Domain Knowledge
Authors: Wu Chuanwen , Zhang Shumei , Bao Xiaoli , Wang Yang , Miao Zhikun , Liu Huixin
Published: August 2024

Risk management in electronic component selection is crucial for ensuring inherent system quality dependability in aerospace equipment research and development (R&D). Therefore, it is of great significance to conduct rapid and accurate risk assessment research of electronic components based on engineering practice. This article utilizes the extreme gradient boosting (XGBoost) algorithm and domain knowledge to assess electronic component selection risk. Firstly, an innovative risk assessment system is established for electronic component selection based on business materials analysis and investigation by questionnaire. Then, the values of factors in the system are quantified based on domain knowledge and empirical formulae. Finally, an XGBoost-based risk assessment model is constructed that can explore learning strategies and develop latent features by integrating multiple decision trees. The model is compared against the random forest (RF), support vector machine (SVM) and decision tree (DT) algorithms. Accuracy, precision, recall, and F1 score are used as evaluation indexes. The results obtained from the above algorithms illustrate the effectiveness of the proposed method in electronic component selection risk assessment.
An “Older Old” Woman with Large Squamous Cell Carcinoma of the Nasal Pyramid: Excellent Response to Ultra-Hypofractionated Radiation Therapy
Authors: Pisani Carla , Gennari Alessandra , Carriero Alessandro , Krengli Marco , Franco Pierfrancesco
Published: August 2024

A 98-year-old patient with cognitive impairment and a history of squamous cell carcinoma of the nasal pyramid was referred to the radiation oncology department of our institution’s hospital given that surgery was not recommended. The lesion was sized 6 × 6 cm, ulcerated, and bleeding; was significantly impairing the patient’s health-related quality of life, causing pain; and was not responsive to analgesics, including opioids. The patient experienced deterioration of her general conditions, with a Karnofsky performance status of 40. A single radiotherapy (RT) fraction was delivered on a weekly basis for 3 weeks, up to a total dose of 21 Gy, using a VMAT technique (7 Gy/fraction). The patient was given three fractions of radiotherapy, during which she received continuous assistance due to episodes of mental disorientation and an altered sense of consciousness. One month after the conclusion of the treatment, the patient exhibited a nearly complete clinical response, with full pain relief and an improved health-related quality of life. This favourable clinical outcome was maintained for a period of four months following the conclusion of RT. A brief review was performed on the role of hypofractionated radiation therapy in elderly patients with locally advanced skin cancer of the head and neck region.
Assessment of Rooftop Photovoltaic Potential Considering Building Functions
Authors: Zhang Zhixin , Pu Yingxia , Sun Zhuo , Qian Zhen , Chen Min
Published: August 2024

Urban expansion and fossil fuel dependence have led to energy and environmental concerns, highlighting the need for sustainable solutions. Rooftop photovoltaic (RPV) systems offer a viable solution for urban energy transition by utilizing idle rooftop space and meeting decentralized energy needs. However, due to limited information on building function attributes, detailed assessments of RPV potential at the city scale are still complicated. This study introduces a cost-effective framework that combines big Earth data and deep learning to evaluate RPV potential for various investment entities. We introduced a sample construction strategy that considers built environment and location awareness to improve the effectiveness and generalizability of the framework. Applied to Shanghai, our building function recognition model achieved 88.67%, 88.51%, and 67.18% for accuracy, weighted-F1, and kappa, respectively. We identified a potential installed capacity of 42 GW with annual electricity generation of 17 TWh for industrial and commercial, 16 TWh for residential, and 10 TWh for public RPVs. The levelized cost of electricity ranges from 0.32 to 0.41 CNY/kWh, demonstrating that both user-side and plant-side grid parity was achieved. This study supports sustainable development by providing detailed urban energy assessments and guiding local energy planning. The methods and findings may offer insights for similar studies globally.
SDG 11.3 Assessment of African Industrial Cities by Integrating Remote Sensing and Spatial Cooperative Simulation: With MFEZ in Zambia as a Case Study
Authors: Huang Yuchen , Ming Dongping
Published: August 2024

Urban areas in sub-Saharan Africa are facing significant developmental challenges due to rapid population growth and urban expansion, this study aims to predict urban growth and assess the SDG 11.3.1 indicator in the Chambishi multi-facility economic zone (CFEMZ) in Zambia through the integration of remote sensing data and spatial cooperative simulation so as to realize sustainable development goals (SDGs). The study utilized DMSP-OLS and VIIRS nighttime light data between 2000 and 2020 to extract the urban built-up area by applying the Pseudo-Invariant Features (PIFs) method to determine thresholds. The land-use and population changes under several development scenarios in 2030 were simulated in the study using the Spatial Cooperative Simulation (SCS) approach. The changes in SDG 11.3.1 indicators were also calculated in the form of a spatialized kilometer grid. The findings show a substantial rise in the built-up area and especially indicate a most notable increase in Chambishi. The primary cause of this growth is the development of industrial parks, which act as the region’s principal engine for urban expansion. Under the natural scenario, the land-use distribution in the study area presents an unplanned state that will make it difficult to realize SDGs. The results of the spatialization form of the SDG 11.3.1 indicator demonstrate the areas and problems of imbalance between urban construction and population growth in the CMFEZ. This study demonstrates the importance of remote sensing of nighttime lighting and spatial simulation in urban planning to achieve SDG 11.3.1 for sustainable urbanization in industrial cities.
A Method for Constructing an Empirical Model of Short-Term Offshore Ocean Tide Loading Displacement Based on PPP
Authors: Wang Hai , Yan Xingyuan , Yang Meng , Feng Wei , Zhong Min
Published: August 2024

The ocean tide loading (OTL) can result in displacements of centimeters or even decimeters at nearshore stations. Global ocean tide models exhibit errors in nearshore regions, which limit the accuracy of maintaining the coordinates of these stations. GNSS positioning can obtain tidal load displacements in nearshore areas, but it often requires long-term observation data and cannot provide timely correction models for newly established reference stations. This paper proposes a method for an empirical correction model of short-term OTL displacements using GNSS observations, where the kinematic coordinate sequences are first obtained by multi-GNSS precise point positioning with ambiguity resolution (PPP-AR), and then the OTL corrections are obtained by window-sliding forecast based on random forest modeling. Through experiments conducted in the Hong Kong region, the empirical model with a window of 15 days is established by the proposed method. After applying the empirical model, root mean square errors of the residuals are reduced by 1.5 (30.6%), 3.7 (53.6%), and 3.7 mm (37.8%) in the East, North, and Up (ENU) components, respectively. When using the global ocean tide model FES2014, the RMSE values are reduced by 1.2 (24.5%), 0.3 (4.3%), and 3.7 mm (37.8%) in the ENU components, respectively. The empirical model shows better effects for the OTL displacement compared to FES2014, especially in the N component, with an improvement ratio of about 49.3%.
Multi-GNSS Precise Point Positioning with Ambiguity Resolution Based on the Decoupled Clock Model
Authors: Liu Shuai , Yuan Yunbin , Guo Xiaosong , Wang Kezhi , Xiao Gongwei
Published: August 2024

Ambiguity resolution (AR) can markedly enhance the precision of precise point positioning (PPP) and accelerate the convergence process. The decoupled clock model represents a pivotal approach for ambiguity resolution, yet current research on this topic is largely confined to GPS. Consequently, in this study, we extend the investigation of the decoupled clock model to multi-GNSS. Firstly, based on the conventional model, we derive the multi-GNSS decoupled clock estimation model and the precise point positioning with ambiguity resolution (PPP-AR) model. Secondly, we provide a detailed explanation of the estimation process for the multi-GNSS decoupled clock estimation. To validate the efficacy of the proposed model, we conduct multi-GNSS decoupled clock estimation and PPP-AR experiments using six days of observation data. The results demonstrate that the decoupled clocks of GPS, Galileo, and BDS-3 can all achieve high accuracy, thus fully meeting the requirement of ambiguity resolution. In terms of positioning performance, the joint three systems have higher positioning accuracy, reaching 3.10 cm and 6.13 cm in horizontal and vertical directions, respectively. Furthermore, the convergence time (CT) and time to first fix (TTFF) are shortened, to 23.13 min and 13.65 min, respectively. The experimental findings indicate that the proposed multi-GNSS decoupled clock model exhibits high precision and rapid positioning service capabilities.
High-Throughput and Accurate 3D Scanning of Cattle Using Time-of-Flight Sensors and Deep Learning
Authors: Omotara Gbenga , Tousi Seyed Mohamad Ali , Decker Jared , Brake Derek , DeSouza G. N.
Published: August 2024

We introduce a high-throughput 3D scanning system designed to accurately measure cattle phenotypes. This scanner employs an array of depth sensors, i.e., time-of-flight (ToF) sensors, each controlled by dedicated embedded devices. The sensors generate high-fidelity 3D point clouds, which are automatically stitched using a point could segmentation approach through deep learning. The deep learner combines raw RGB and depth data to identify correspondences between the multiple 3D point clouds, thus creating a single and accurate mesh that reconstructs the cattle geometry on the fly. In order to evaluate the performance of our system, we implemented a two-fold validation process. Initially, we quantitatively tested the scanner for its ability to determine accurate volume and surface area measurements in a controlled environment featuring known objects. Next, we explored the impact and need for multi-device synchronization when scanning moving targets (cattle). Finally, we performed qualitative and quantitative measurements on cattle. The experimental results demonstrate that the proposed system is capable of producing high-quality meshes of untamed cattle with accurate volume and surface area measurements for livestock studies.
A Cyber Risk Assessment Approach to Federated Identity Management Framework-Based Digital Healthcare System
Authors: Huda Shamsul , Islam Md. Rezaul , Abawajy Jemal , Kottala Vinay Naga Vamsi , Ahmad Shafiq
Published: August 2024

This paper presents a comprehensive and evidence-based cyber-risk assessment approach specifically designed for Medical Cyber Physical Systems (MCPS)- and Internet-of-Medical Devices (IoMT)-based collaborative digital healthcare systems, which leverage Federated Identity Management (FIM) solutions to manage user identities within this complex environment. While these systems offer advantages like easy data collection and improved collaboration, they also introduce new security challenges due to the interconnected nature of devices and data, as well as vulnerabilities within the FIM and the lack of robust security in IoMT devices. To proactively safeguard the digital healthcare system from cyber attacks with potentially life-threatening consequences, a comprehensive and evidence-based cyber-risk assessment is crucial for mitigating these risks. To this end, this paper proposes a novel cyber-risk assessment approach that leverages a three-dimensional attack landscape analysis, encompassing existing IT infrastructure, medical devices, and Federated Identity Management protocols. By considering their interconnected vulnerabilities, the approach recommends tailored security controls to prioritize and mitigate critical risks, ultimately enhancing system resilience. The proposed approach combines established industry standards like Cyber Resilience Review (CRR) asset management and NIST SP 800-30 for a comprehensive assessment. We have validated our approach using threat modeling with attack trees and detailed attack sequence diagrams on a diverse range of IoMT and MCPS devices from various vendors. The resulting evidence-based cyber-risk assessments and corresponding security control recommendations will significantly support healthcare professionals and providers in improving both patient and medical device safety management within the FIM-enabled healthcare ecosystem.
Comparative Study of Polymer-Modified Copper Oxide Electrochemical Sensors: Stability and Performance Analysis
Authors: Baziak Andrzej , Kusior Anna
Published: August 2024

The effectiveness of copper oxide-modified electrochemical sensors using different polymers is being studied. The commercial powder was sonicated in an isopropyl alcohol solution and distilled water with 5 wt% polymers (chitosan, Nafion, PVP, HPC, α-terpineol). It was observed that the chitosan and Nafion caused degradation of CuO, but Nafion formed a stable mixture when diluted. The modified electrodes were drop-casted and analyzed using cyclic voltammetry in 0.1 M KCl + 3 mM [Fe(CN)6]3−/4− solution to determine the electrochemically active surface area (EASA). The results showed that α-terpineol formed agglomerates, while HPC created uneven distributions, resulting in poor stability. On the other hand, Nafion and PVP formed homogeneous layers, with PVP showing the highest EASA of 0.317 cm2. In phosphate-buffered saline (PBS), HPC and PVP demonstrated stable signals. Nafion remained the most stable in various electrolytes, making it suitable for sensing applications. Testing in 0.1 M NaOH revealed HPC instability, partial dissolution of PVP, and Cu ion reduction. The type of polymer used significantly impacts the performance of CuO sensors. Nafion and PVP show the most promise due to their stability and effective dispersion of CuO. Further optimization of polymer–CuO combinations is necessary for enhanced sensor functionality.
Ultra-Wideband Circular Polarized Implantable Patch Antenna for Implantable Blood Glucose Detection System Applications
Authors: Song Zhiwei , Li Mengke
Published: August 2024

To address the current demands for antenna miniaturization, ultra-bandwidth, and circular polarization in advanced medical devices, a novel ISM band implantable antenna for blood glucose monitoring has been developed. This antenna achieves miniaturization by incorporating slots in the radiation patch and adding symmetric short-circuit probes, resulting in a compact size of only 0.054λ0 × 0.054λ0 × 0.005λ0 (λ0 is the wavelength in free space in respect of the lowest working frequency). By combining two resonance points and utilizing a differential feed structure, the antenna achieves ultra-broadband and circular polarization. Simulations indicate a |S11| bandwidth of 1.1 GHz (1.65–2.75 GHz) and an effective axial ratio (based on 3 dB axis ratio) bandwidth of 590 MHz (1.89–2.48 GHz), able to cover both the ISM frequency band (2.45 GHz) and the mid-field frequency band (1.9 GHz). The antenna exhibits CP gains of −20.04 dBi at a frequency of 2.45 GHz, while it shows gains of −24.64 dBi at 1.9 GHz. Furthermore, a superstrate layer on the antenna’s radiating surface enhances its biocompatibility and minimizes its impact on the human body. Simulation and experimental results indicate that the antenna can establish a stable wireless communication link for implantable continuous blood glucose monitoring systems.
Analysis of Wheat-Yield Prediction Using Machine Learning Models under Climate Change Scenarios
Authors: Iqbal Nida , Shahzad Muhammad Umair , Sherif El-Sayed M. , Tariq Muhammad Usman , Rashid Javed , Le Tuan-Vinh , Ghani Anwar
Published: August 2024

Climate change has emerged as one of the most significant challenges in modern agriculture, with potential implications for global food security. The impact of changing climatic conditions on crop yield, particularly for staple crops like wheat, has raised concerns about future food production. By integrating historical climate data, GCM (CMIP3) projections, and wheat-yield records, our analysis aims to provide significant insights into how climate change may affect wheat output. This research uses advanced machine learning models to explore the intricate relationship between climate change and wheat-yield prediction. Machine learning models used include multiple linear regression (MLR), boosted tree, random forest, ensemble models, and several types of ANNs: ANN (multi-layer perceptron), ANN (probabilistic neural network), ANN (generalized feed-forward), and ANN (linear regression). The model was evaluated and validated against yield and weather data from three Punjab, Pakistan, regions (1991–2021). The calibrated yield response model used downscaled global climate model (GCM) outputs for the SRA2, B1, and A1B average collective CO2 emissions scenarios to anticipate yield changes through 2052. Results showed that maximum temperature (R = 0.116) was the primary climate factor affecting wheat yield in Punjab, preceding the Tmin (R = 0.114), while rainfall had a negligible impact (R = 0.000). The ensemble model (R = 0.988, nRMSE= 8.0%, MAE = 0.090) demonstrated outstanding yield performance, outperforming Random Forest Regression (R = 0.909, nRMSE = 18%, MAE = 0.182), ANN(MLP) (R = 0.902, MAE = 0.238, nRMSE = 17.0%), and boosting tree (R = 0.902, nRMSE = 20%, MAE = 0.198). ANN(PNN) performed inadequately. The ensemble model and RF showed better yield results with R2 = 0.953, 0.791. The expected yield is 5.5% lower than the greatest average yield reported at the site in 2052. The study predicts that site-specific wheat output will experience a significant loss due to climate change. This decrease, which is anticipated to be 5.5% lower than the highest yield ever recorded, points to a potential future loss in wheat output that might worsen food insecurity. Additionally, our findings highlighted that ensemble approaches leveraging multiple model strengths could offer more accurate and reliable predictions under varying climate scenarios. This suggests a significant potential for integrating machine learning in developing climate-resilient agricultural practices, paving the way for future sustainable food security solutions.
The Urban–Rural Transformation and Its Influencing Mechanisms on Air Pollution in the Yellow River Basin
Authors: Xu Chen , Yin Zhenzhen , Sun Wei , Cao Zhi , Cheng Mingyang
Published: August 2024

Air pollution has recently gained much attention from the general population. Despite pollution control being an issue in both urban and rural regions, most of the available research has concentrated on urban districts. Hence, investigations into how urban–rural transition affects PM2.5 are warranted within the framework of urban–rural integration. Using the Yellow River Basin as a case study, this study employed the entropy method and Analytic Hierarchy Process (AHP) to uncover the extent of urban–rural transformation. It then used the spatial autocorrelation method to investigate the spatiotemporal features of PM2.5 and the spatial econometric model to investigate the mechanisms that influence the relationship between urban–rural transformation and PM2.5. The results are as follows: (1) The level of urban–rural transformation shows an obvious upward trend with time. The development has progressed from asymmetrical north-east and south-west elevations to a more balanced pattern of north-east, middle-east, and west-west elevations. (2) The PM2.5 concentration increased steadily, then fluctuated, and finally decreased. Notably, the general pattern has not changed much, and it is high in the east and low in the west. (3) Different subsystems of the urban–rural transformation have different impacts on air pollution at different stages. The influence of industrial transformation (IT) on PM2.5 showed an inverted “N-shaped” curve of negative–negative–changes, and the industrial structure played a leading role in the spatiotemporal evolution of PM2.5. An inverted “U-shaped” curve forms the left side of the impact of population transition (PT) on PM2.5. Land transformation (LT) has a “U-shaped” curve for its effect on PM2.5. This study provides a new perspective on the topic of PM2.5 and its connection to urban–rural integration, which is crucial to understanding the dynamics of this shift. To achieve the goal of high-quality development, this study supports regional initiatives to reduce PM2.5 emissions in the Yellow River Basin. Moreover, the results of this study can provide a reference for decision-makers in the world’s densely populated areas that suffer from serious air pollution.
A Novel Stacked Generalization Ensemble-Based Hybrid SGM-BRR Model for ESG Score Prediction
Authors: Wang Zhie , Wang Xiaoyong , Liu Xuexin , Zhang Jun , Xu Jingde , Ma Jun
Published: August 2024

Recently, financial institutions and investors have placed an increasing emphasis on ESG (environmental, social, and governance) as a principal indicator for the evaluation of companies. However, the current ESG scoring systems lack uniformity and are often subjective. It is of great importance to be able to make accurate predictions regarding the ESG scores of corporations. A Stacked Generalization Model that employs Random Forest (RF), Gradient Boosting Decision Tree (GBDT), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM) as base learners, with Bayesian Ridge Regression (BRR) as the meta-model for integrating the predictions of these diverse models is proposed. The goal is to develop an ESG score prediction model for Chinese companies. The experimental data set encompasses Chinese A-share listed companies from 2012 to 2020. The Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and coefficient of determination (R2) are employed for model evaluation and are compared with seven benchmark models. The results demonstrate that SGM-BRR reduces the RMSE by 18.4%, 17.3%, 13.7%, and 76.1%, the MAE by 15.4%, 18.4%, 15.8%, and 68.4%, and increases the R2 by 2%, 1.4%, 2%, and 6% for ESG, E, S, and G scores, respectively. Furthermore, the model’s performance is validated across different industries, with SGM-BRR exhibiting the most optimal performance of RMSE, MAE, and R2 in 27, 25, and 27 groups, respectively. Consequently, the model demonstrates broad applicability and stability performance in ESG score prediction.
Two Decades of Advancements in Cold Supply Chain Logistics for Reducing Food Waste: A Review with Focus on the Meat Industry
Authors: Davoudi Sina , Stasinopoulos Peter , Shiwakoti Nirajan
Published: August 2024

The current study focuses on the critical role of efficient cold supply chain logistics (CSCL) within the beef meat supply chain (SC), ensuring the timely delivery of premium products. Despite its significance, substantial food loss and waste (FLW) in CSCL pose multifaceted challenges across economic, social, and environmental dimensions. This comprehensive literature review aims to identify state-of-the-art CSCL for reducing food waste, key research themes, and their potential roles in red meat waste reduction, as well as identify future research directions. It explores four pivotal themes—management, sustainability, network design (ND), and new information technologies (IT)—each contributing uniquely to mitigating FLW. A review of papers published in the last two decades reveals management as the predominant theme, followed by sustainability, ND, and IT. The study underscores the interconnectedness of these themes and highlights gaps in current research, particularly the need for multi-objective optimisation models. These models should integrate uncertainties, sustainability dimensions, and technological advancements, while aligning strategic, tactical, and operational decisions to enhance CSCL sustainability and reduce FLW in the beef meat industry. This review informs stakeholders—researchers, policymakers, practitioners, the government, and the public—about emerging trends and opportunities in addressing food waste, thereby fostering more efficient and sustainable CSCL practices.
The Effect of Distance between Jet Fans on Gas Transport, Energy Conservation, and Emission Reduction in Long Highway Tunnels
Authors: Suo Liang , Li Shugang , Wu Fengliang , Zhao Pengxiang , Wen Jian , Qi Peng , Diao Zongbo
Published: August 2024

With the rapid development of the national economy, China’s transportation industry is experiencing accelerated development, and, at the same time, the number of long tunnels is constantly increasing. In order to examine the influence of jet fan spacing on gas transport law during the construction of long highway tunnels, this study used the Baima Highway Tunnel in Sichuan as an engineering prototype and established a numerical tunnel ventilation model based on Fluent numerical simulation software. The gas transport characteristics of jet fans in tunnels at different spacings (200 m, 400 m, 600 m, and 800 m) were studied. The results showed that with the increase in jet fan spacing (200 m, 400 m, 600 m, and 800 m), the gas concentration at the tunnel face showed a trend of decreasing and then increasing. Moreover, by analyzing the gas distribution cloud map and the wind flow line diagram, it was determined that the ventilation system effect was the best when the jet fan spacing was 600 m, which met the requirements of a gas concentration of less than 0.5% at the tunnel face and a minimum wind speed of 0.25 m/s. At the same time, according to the optimal spacing for the optimization of the site ventilation system, it was observed that after the ventilation was stabilized (after 600 s), the minimum value of the gas concentration in the left and right tunnel holes diminished from 0.38% to 0.31% and from 0.41% to 0.31%, with rates of reduction of 18.42% and 24.39%, respectively. This indicated that after optimizing the ventilation system at the tunnel site, the concentration significantly decreased compared with before the optimization. Moreover, when the jet fan spacing was 600 m compared with 200 m and 400 m, the annual energy savings were 1900.8 MW·h and 950.4 MW·h, respectively. The research results clarified the optimal layout parameters of jet fans in the Baima Highway Tunnel, providing a reference for the rational layout of jet fans in long-distance tunnels. In addition, the results of this study provide an important theoretical basis for the gas prevention and safe construction of long highway tunnels. Furthermore, this study contributes to research in energy conservation, emission reduction, and sustainable development of energy in the ventilation process during tunnel construction.
The Role of Digital Transformation and Digital Competencies in Organizational Sustainability: A Study of SMEs in Lima, Peru
Authors: Espina-Romero Lorena , Ríos Parra Doile , Gutiérrez Hurtado Humberto , Peixoto Rodriguez Egidio , Arias-Montoya Francisco , Noroño-Sánchez José Gregorio , Talavera-Aguirre Rosa , Ramírez Corzo Javier , Vilchez Pirela Rafael Alberto
Published: August 2024

Digitalization has significantly transformed businesses in the 21st century, but there are gaps in understanding how it affects human resource management and organizational culture in SMEs in Lima, Peru. This study aims to fill this gap by analyzing the influence of digital transformation, digital competencies, and digital HR management on the organizational culture of SMEs in Lima and how these factors contribute to organizational sustainability. Using a quantitative approach and structural equation modeling (SEM), 307 business leaders were surveyed between January and March 2024. The results show that digital transformation and digital competencies significantly influence digital HR management, which positively impacts organizational culture and promotes sustainable practices. Additionally, it was found that digital HR management mediates the relationship between digital transformation and organizational culture, as well as between digital competencies and organizational culture. It is crucial to invest in digital technologies and foster digital competencies to improve HR management and promote a sustainable organizational culture. In conclusion, digitalization redefines organizational culture and reinforces sustainability, especially in SMEs in Lima, Peru, providing new scientific value by demonstrating these mechanisms of change.
Sustainable Technological Incorporation in Aquaculture: Attitudinal and Motivational Perceptions of Entrepreneurs in the Northwest Region of Mexico
Authors: Urías-Camacho Alejandro , Peinado Guevara Héctor José , Rodríguez-Montes de Oca Gustavo Alejandro , Peinado-Guevara Víctor Manuel , Herrera Barrientos Jaime , Sánchez Alcalde Mary Cruz , González-Félix Griselda Karina , Cuadras-Berrelleza Aldo Alan
Published: August 2024

The northwest region of Mexico stands out as one of the areas with the greatest contribution to the national aquaculture industry, which has led its producers to reconsider the need to innovate in the processes of technological incorporation in sustainable ways. Thus, the aim of this study was to determine the attitudinal and motivational context perceived in aquaculture companies in the region, related to the innovation, competitiveness and support programmes. By means of Likert scaling, it was possible to identify aspects of both domains that would facilitate the development of technological innovation within aquaculture. Such an escalation also showed the need to intensify efforts, with the participation of the state, public and private universities, as well as non-governmental organisations, to develop strategies and policies that facilitate the incorporation of innovative technologies. The research design is structured under a descriptive-explanatory approach, with a cross-sectional format, in which 108 surveys were applied. These surveys were designed using the Likert scale and validated with the McDonald’s Omega method, with ω = 0.773. Cronbach’s α and exploratory factor analysis (EFA) were employed, showing a correlation between the items of the construct and its subcategories. The values of the covariance of the items obtained through the exploratory analysis show that 56% of the items have a correlation greater than 0.05. This indicates that there is a positive attitude and motivation towards the implementation of technological innovation in aquaculture in the study region, with participation from all three levels of government.
Turning Apple Pomace into Value: Sustainable Recycling in Food Production—A Narrative Review
Authors: Zaky Ahmed A. , Witrowa-Rajchert Dorota , Nowacka Małgorzata
Published: August 2024

Apple pomace is a significant by-product generated during the making of apple juice. It is frequently discarded as waste, harming the environment and making it risky for people’s health. The primary goals of this narrative review are to discuss the composition, functional bioactives, extraction techniques, and current food applications of apple pomace. Given the immediate positive economic effects, higher yields from novel extraction techniques were determined to be paramount. In addition to bioactive substances, apple pomace has a high dietary fiber content that could be utilized in newly created formulations. Additionally, this pomace can be added to food products to increase their nutritional content and marketability. For example, adding apple pomace to bread, confectionery, dairy, and meat products has increased their nutritional value and phytochemical and health-promoting qualities. Furthermore, the limitations associated with using this by-product in those products are addressed in this investigation. It is expected that the data presented in this work will serve as a helpful reference for food industry professionals in proposing an economical and sustainable extraction method that will convert apple waste into a functional product with added value. Along with validating potential bioactivity, additional research is required to determine the stability of bioactive substances and the mechanisms that regulate them.
Modeling of Soil Cation Exchange Capacity Based on Chemometrics, Various Spectral Transformations, and Multivariate Approaches in Some Soils of Arid Zones
Authors: Mustafa Abdel-rahman A. , Abdelsamie Elsayed A. , Mohamed Elsayed Said , Rebouh Nazih Y. , Shokr Mohamed S.
Published: August 2024

Cation exchange capacity is a crucial metric for managing soil fertility and promoting agricultural sustainability. An alternative technique for the non-destructive assessment of important soil parameters is reflectance spectroscopy. The main focus of this paper is on how to analyze and predict the content of various soil cation exchange capacities (CEC) in arid conditions (Sohag governorate, Egypt) at a low cost using laboratory analysis of CEC, visible near-infrared and shortwave infrared (Vis-NIR) spectroscopy, partial least-squares regression (PLSR), and Ordinary Kriging (OK). Utilizing reflectance spectroscopy with a spectral resolution of 10 nm and laboratory studies with a spectral range of 350 to 2500 nm, 104 surface soil samples were collected to a depth of 30 cm in the Sohag governorate, Egypt (which is part of the dry region of North Africa), in order to accomplish this goal. The association between the spectroradiometer and CEC averaged values was modeled using PLSR in order to map the predicted value using Ordinary Kriging (OK). Thirty-one soil samples were selected for validation. The predictive validity of the cross-validated models was evaluated using the coefficient of determination (R2), root mean square error (RMSE), residual prediction deviation (RPD), and ratio of performance to interquartile distance (RPIQ). The results indicate that ten transformation methods yielded calibration models that met the study’s requirements, with R2 > 0.6, RPQ > 2.5, and RIQP > 4.05. For evaluating CEC in Vis-NIR spectra, the most efficient transformation and calibration model was the reciprocal of Log R transformation (R2 = 0.98, RMSE = 0.40, RPD = 6.99, and RIQP = 9.22). This implies that combining the reciprocal of Log R with PLSR yields the optimal model for predicting CEC values. The CEC values were best fitted by four models: spherical, exponential, Gaussian, and circular. The methodology used here does offer a “quick”, inexpensive tool that can be broadly and quickly used, and it can be readily implemented again in comparable conditions in arid regions.
Spatial and Temporal Changes in Land Use and Landscape Pattern Evolution in the Economic Belt of the Northern Slope of the Tianshan Mountains in China
Authors: Li Xiaolong , Qin Da , He Xinlin , Wang Chunxia , Yang Guang , Li Pengfei , Liu Bing , Gong Ping , Yang Yuefa
Published: August 2024

The economic belt on the north slope of the Tianshan Mountains is a highly productive area in Xinjiang, but with the rapid development of the economy and industry and the acceleration of urbanization in recent years, the fragile ecological environment in the region has further deteriorated. Exploring shifts in land utilization across different eras and regions, along with the transformation of terrain configurations, provides key perspectives that can propel sustainable societal and environmental growth within this particular area. The research analyzed four periods (1990, 2000, 2010, 2020) of remote sensing image data combined with field monitoring data using methods such as land use variability, landscape pattern index, and grey relational model. Focusing on investigating the dynamics of the ecological environment in high-intensity human activity areas, examining alterations in land use patterns over time and space, transitions in land use types, and trends in landscape pattern indices. (1) The dominant land environments situated in the economic zone adjacent to the northern base of the Tianshan mountain range encompass extensive expanses of grassy plains and unexploited landscapes, making up 45% and 38% of the area, correspondingly. The single dynamic change degree of construction land was the largest due to the implementation of long-term land development and urbanization policies. Land use transfer change mainly occurred among cultivated land, grassland, forestland, and unused land. With strong human activities, the construction land area has expanded by 145.16% (2089.7 km2), and this number is still increasing. (2) The spatial landscape structure on the north slope of Tianshan Mountain is becoming more complicated and diversified; the cities with the highest degree of fragmentation were concentrated in the middle and western sections. Grassland is the most dominant patch type in the landscape. The shape of patches tends to be irregular and complex in general, and the fragmentation degree and dispersion degree of landscape patches are enhanced as the proportion of different landscape types increases. (3) Grey correlation analysis indicates that grasslands, cultivated land, and unused land are key elements in the landscape pattern changes on the northern slope of the Tianshan Mountains. Central urban agglomeration is an area with strong landscape pattern changes, and ecological protection should be emphasized while promoting economic development.