bluuebunny/crossref_metadata_2025 huggingface dataset:
Terrestrial Animal Source Foods and Health Outcomes for Those with Special Nutrient Needs in the Life Course
Authors: Iannotti Lora , Rueda García Ana María , Palma Giulia , Fontaine Fanette , Scherf Beate , Neufeld Lynnette M. , Zimmerman Rachel , Fracassi Patrizia
Published: September 2024

Background. Animal source foods are under scrutiny for their role in human health, yet some nutritionally vulnerable populations are largely absent from consideration. Methods. Applying a Population Intervention/Exposure Comparator Outcome (PICO/PECO) framework and prioritizing systematic review and meta-analyses, we reviewed the literature on terrestrial animal source foods (TASFs) and human health, by life course phase. Results. There were consistent findings for milk and dairy products on positive health outcomes during pregnancy and lactation, childhood, and among older adults. Eggs were found to promote early childhood growth, depending on context. Unprocessed meat consumption was associated with a reduced risk for anemia during pregnancy, improved cognition among school-age children, and muscle health in older adults. Milk and eggs represent a risk for food sensitivities/allergies, though prevalence is low, and individuals tend to outgrow the allergies. TASFs affect the human microbiome and associated metabolites with both positive and negative health repercussions, varying by type and quantity. Conclusions. There were substantial gaps in the evidence base for studies limiting our review, specifically for studies in populations outside high-income countries and for several TASF types (pig, poultry, less common livestock species, wild animals, and insects). Nonetheless, sufficient evidence supports an important role for TASFs in health during certain periods of the life course.
Effects of 12-Week Supplementation with Coffee Diterpene Cafestol in Healthy Subjects with Increased Waist Circumference: A Randomized, Placebo-Controlled Trial
Authors: Mellbye Fredrik D. , Nguyen Mi D. , Hermansen Kjeld , Jeppesen Per B. , Al-Mashhadi Zheer K. , Ringgaard Steffen , Gregersen Søren
Published: September 2024

Background: Coffee consumption is inversely associated with type 2 diabetes. Cafestol, a bioactive compound in coffee, has demonstrated glucose-lowering and insulin-secretory properties in cell and animal studies. The acute effects of cafestol on glucose metabolism in humans have only been briefly investigated, and longer-term effects have not been explored. This study aimed to assess the effects of purified cafestol on insulin sensitivity and other metabolic parameters in healthy individuals with increased waist circumference at risk of developing type 2 diabetes. Methods: A 12-week randomized, placebo-controlled, parallel trial was conducted with 40 participants. Insulin suppression tests, mixed meal tests, and MRI scans were performed before and after the intervention. Results: Administering 6 mg of cafestol twice daily did not alter insulin sensitivity or glucose tolerance but led to significant reductions in body weight (2%), visceral fat volume (5%), and gamma-glutamyl transferase levels (15%) compared to the placebo. Conclusions: Cafestol may hold promise for weight and visceral fat reduction. Cafestol did not improve insulin sensitivity or glucose tolerance in this study but might still contribute to the observed inverse association between coffee consumption and type 2 diabetes. Future research should explore higher dosages and longer treatment durations, particularly in individuals with impaired glucose metabolism and type 2 diabetes.
Pyrimidines: A New Versatile Molecule in the Drug Development Field, Scope, and Future Aspects
Authors: Venugopala Katharigatta N. , Kamat Vinuta
Published: September 2024

Pyrimidine is a moiety that occurs in living organisms and has a variety of significant biological properties in pharmacology. Due to the easy handling of synthesis, easily available precursor, and less duration for the reaction, for the synthesis, not many technical skills are needed. All these factors attract chemists to focus more on pyrimidines. Apart from the synthesis of biological applications of pyrimidines, medicinal chemists have gathered to explore more pyrimidine scaffolds due to their interesting medicinal properties and easy targeting of various binding sites. This review delves into the diverse biological activities of compounds derived from pyrimidine during the year 2024. We have attempted to explore the growing significance of pyrimidine derivatives and provide a new path for designing new potent molecules.
Synthesis, Absolute Configuration, Biological Profile and Antiproliferative Activity of New 3,5-Disubstituted Hydantoins
Authors: Jurin Mladenka , Čikoš Ana , Stepanić Višnja , Górecki Marcin , Pescitelli Gennaro , Kontrec Darko , Jakas Andreja , Dražić Tonko , Roje Marin
Published: September 2024

Hydantoins, a class of five-membered heterocyclic compounds, exhibit diverse biological activities. The aim of this study was to synthesize and characterize a series of novel 3,5-disubstituted hydantoins and to investigate their antiproliferative activity against human cancer cell lines. The new hydantoin derivatives 5a–i were prepared as racemic mixtures of syn- and anti-isomers via a base-assisted intramolecular amidolysis of C-3 functionalized β-lactams. The enantiomers of syn-5a and anti-hydantoins 5b were separated by preparative high-performance liquid chromatography (HPLC) using n-hexane/2-propanol (90/10, v/v) as the mobile phase. The absolute configuration of the four allyl hydantoin enantiomers 5a was assigned based on a comparison of the experimental electronic circular dichroism (ECD) and vibrational circular dichroism (VCD) spectra with those calculated using density functional theory (DFT). The antiproliferative activity evaluated in vitro against three different human cancer cell lines: HepG2 (liver hepatocellular carcinoma), A2780 (ovarian carcinoma), and MCF7 (breast adenocarcinoma), and on the non-tumor cell line HFF1 (normal human foreskin fibroblasts) using the MTT cell proliferation assay. In silico drug-like properties and ADMET profiles were estimated using the ADMET Predictor ver. 9.5 and the online server admetSAR. Eighteen new 3,5-disubstituted hydantoins were synthesized and characterized. The compound anti-5c showed potent cytotoxic activity against the human tumor cell line MCF7 (IC50 = 4.5 µmol/L) and the non-tumor cell line HFF1 (IC50 = 12.0 µmol/L). In silico analyzes revealed that the compounds exhibited moderate water solubility and membrane permeability and are likely substrates for CYP3A4 and P-glycoprotein and have a high probability of antiarthritic activity.
Combination Therapy and Phytochemical-Loaded Nanosytems for the Treatment of Neglected Tropical Diseases
Authors: Soto-Sánchez Jacqueline , Garza-Treviño Gilberto
Published: September 2024

Background: Neglected tropical diseases (NTDs), including leishmaniasis, trypanosomiasis, and schistosomiasis, impose a significant public health burden, especially in developing countries. Despite control efforts, treatment remains challenging due to drug resistance and lack of effective therapies. Objective: This study aimed to synthesize the current research on the combination therapy and phytochemical-loaded nanosystems, which have emerged as promising strategies to enhance treatment efficacy and safety. Methods/Results: In the present review, we conducted a systematic search of the literature and identified several phytochemicals that have been employed in this way, with the notable efficacy of reducing the parasite load in the liver and spleen in cases of visceral leishmaniasis, as well as lesion size in cutaneous leishmaniasis. Furthermore, they have a synergistic effect against Trypanosoma brucei rhodesiense rhodesain; reduce inflammation, parasitic load in the myocardium, cardiac hypertrophy, and IL-15 production in Chagas disease; and affect both mature and immature stages of Schistosoma mansoni, resulting in improved outcomes compared to the administration of phytochemicals alone or with conventional drugs. Moreover, the majority of the combinations studied demonstrated enhanced solubility, efficacy, and selectivity, as well as increased immune response and reduced cytotoxicity. Conclusions: These formulations appear to offer significant therapeutic benefits, although further research is required to validate their clinical efficacy in humans and their potential to improve treatment outcomes in affected populations.
Development of Gastroretentive Floating Combination Tablets Containing Amoxicillin Trihydrate 500 mg and Levofloxacin 125 mg for Eradicating Resistant Helicobacter pylori
Authors: Kim Da Hun , Lee Sa-Won , Lee Jun Hak , Park Jin Woo , Park Sung Mo , Maeng Han-Joo , Koo Tae-Sung , Cho Kwan Hyung
Published: September 2024

Background/Objectives: The aim of this work was to prepare and characterize gastroretentive floating combination tablets (GRCTs) containing 500 mg of amoxicillin trihydrate (AMX) and 125 mg of levofloxacin (LVX) that provide sustained drug release and stability at gastric pH levels for the eradication of resistant Helicobacter pylori. Method: GRCTs were prepared with low-density excipients and hydrophilic swellable polymers, including hydroxypropyl methylcellulose (HPMC) of various viscosities, polyethylene oxide (PEO), and carboxymethylcellulose (CMC), by the direct compression method. The prepared GRCTs were investigated and optimized in terms of pH stability, tablet hardness, floating lag time and total floating time, drug release rate, gel strength. Results: AMX and LVX in GRCT were stable at the HP eradication target pH above 4.0. The effervescent GRCT composition (AMX/LVX/HPMC [4000 cP]/CMC/microcrystalline cellulose/citric acid/sodium bicarbonate/calcium silicate/silicon dioxide/magnesium stearate = 500/125/50/50/125/40/60/30/10/10, w/w) yielded acceptable hardness (>6 kp), reduced floating lag time (<5 s), a long floating duration (>12 h), and sustained release rates of AMX and LVX (>90% until 12 h). This optimized GRCT had a gel strength of 107.33 ± 10.69 g and pH > 4.0, which maintained the tablets’ shape and AMX stability for 12 h. Conclusions: Collectively, the formulated effervescent GRCTs combining AMX and LVX represented a promising candidate dosage form for eradicating resistant H. pylori.
Harnessing the Potential of Hollow Graphitic Carbon Nanocages for Enhanced Methanol Oxidation Using PtRu Nanoparticles
Authors: Ramli Zatil Amali Che , Pasupuleti Jagadeesh , Kamarudin Siti Kartom , Zainoodin Azran Mohd , Isahak Wan Nor Roslam Wan , Koh S. P. , Kiong Sieh Tiong
Published: September 2024

Direct Methanol Fuel Cell (DMFC) is a powerful system for generating electrical energy for various applications. However, there are several limitations that hinder the commercialization of DMFCs, such as the expense of platinum (Pt) at market price, sluggish methanol oxidation reaction (MOR) due to carbon monoxide (CO) formation, and slow electrooxidation kinetics. This work introduces carbon nanocages (CNCs) that were obtained through the pyrolysis of polypyrrole (Ppy) as the carbon source. The CNCs were characterized using BET, XRD, HRTEM, TEM, SEM, and FTIR techniques. The CNCs derived from the Ppy source, pyrolyzed at 750 °C, exhibited the best morphologies with a high specific surface area of 416 m2g−1, allowing for good metal dispersion. Subsequently, PtRu catalyst was doped onto the CNC-Ppy750 support using chemical reduction and microwave-assisted methods. In electrochemical tests, the PtRu/CNC-Ppy750 electrocatalyst demonstrated improved CO tolerance and higher performance in MOR compared to PtRu-supported commercial carbon black (CB), with values of 427 mA mg−1 and 248 mA mg−1, respectively. The superior MOR performance of PtRu/CNC-Ppy750 was attributed to its high surface area of CNC support, uniform dispersion of PtRu catalyst, and small PtRu nanoparticles on the CNC. In DMFC single-cell tests, the PtRu/CNC-Ppy750 exhibited higher performance, approximately 1.7 times higher than PtRu/CB. In conclusion, the PtRu/CNC-PPy750 represents a promising electrocatalyst candidate for MOR and anodic DMFC applications.
Evaluation of the Flexural Behavior of One-Way Slabs by the Amount of Carbon Grid Manufactured by Adhesive Bonding
Authors: Kim Kyung-Min , Park Sung-Woo , Song Bhum-Keun , Yoon Seon-Hee
Published: September 2024

Fiber-reinforced polymers (FRPs), which are resistant to corrosion, are used as reinforcement material for concrete. However, the flexural behavior of concrete members reinforced with FRPs can vary depending on the properties of FRPs. In this study, the flexural behavior of one-way concrete slab specimens reinforced with a new grid-type carbon-fiber-reinforced polymer (CFRP) (carbon grid) manufactured by bonding pultruded CFRP strands to an adhesive was investigated. The experimental results indicated differences in the load–deflection relationships of the specimens depending on the carbon grid reinforcement amount. Specimens in which the carbon grids were over-reinforced or reinforced close to the balanced reinforcement ratio reached the maximum load due to concrete crushing and exhibited ductile failure. The specimen under-reinforced with the carbon grid exhibited brittle failure. Specimens with carbon grid reinforcement close to a balanced reinforcement ratio exhibited maximum loads ranging from 0.43 to 0.61 times the calculated flexural strength, which resulted in becoming 0.86–1.00 lower in the specimens with a wider width of the CFRP strands. This study proposes coefficients to estimate the stiffness of carbon-grid-reinforced concrete flexural members after cracking. Applying these coefficients resulted in stiffness calculations that reasonably simulated the behavior of the specimens reinforced with carbon grids after crack formation.
Smart Carbon Fiber-Reinforced Polymer Composites for Damage Sensing and On-Line Structural Health Monitoring Applications
Authors: Lopes Cláudia , Araújo Andreia , Silva Fernando , Pappas Panagiotis-Nektarios , Termine Stefania , Trompeta Aikaterini-Flora A. , Charitidis Costas A. , Martins Carla , Mould Sacha T. , Santos Raquel M.
Published: September 2024

High electrical conductivity, along with high piezoresistive sensitivity and stretchability, are crucial for designing and developing nanocomposite strain sensors for damage sensing and on-line structural health monitoring of smart carbon fiber-reinforced polymer (CFRP) composites. In this study, the influence of the geometric features and loadings of carbon-based nanomaterials, including reduced graphene oxide (rGO) or carbon nanofibers (CNFs), on the tunable strain-sensing capabilities of epoxy-based nanocomposites was investigated. This work revealed distinct strain-sensing behavior and sensitivities (gauge factor, GF) depending on both factors. The highest GF values were attained with 0.13 wt.% of rGO at various strains. The stability and reproducibility of the most promising self-sensing nanocomposites were also evaluated through ten stretching/relaxing cycles, and a distinct behavior was observed. While the deformation of the conductive network formed by rGO proved to be predominantly elastic and reversible, nanocomposite sensors containing 0.714 wt.% of CNFs showed that new conductive pathways were established between neighboring CNFs. Based on the best results, formulations were selected for the manufacturing of pre-impregnated materials and related smart CFRP composites. Digital image correlation was synchronized with electrical resistance variation to study the strain-sensing capabilities of modified CFRP composites (at 90° orientation). Promising results were achieved through the incorporation of CNFs since they are able to form new conductive pathways and penetrate between micrometer-sized fibers.
A New Defence against the Problem of Evil
Authors: Molto Daniel
Published: September 2024

In this paper, I propose a defence against the problem of evil. This defence does not involve either free will or soul-making, but, rather, is intended as a replacement for the traditional theodicies. The defence will have two components: firstly, a proposal for why a good God would not intervene to eliminate the evil (natural or moral) in the world; and second, a proposal for why a good God would need to allow evil to exist in the world in the first place. I identify four desiderata for defences against the problem of evil and I argue that this new defence achieves all of these at least as well as traditional defences involving free will and/or soul-making.
On the Consistency of Stochastic Noise Properties and Velocity Estimations from Different Analysis Strategies and Centers with Environmental Loading and CME Corrections
Authors: Lv Hongli , He Xiaoxing , Hu Shunqiang , Sun Xiwen , Huang Jiahui , Fernandes Rui , Xie Wen , Xiong Huajiang
Published: September 2024

The analysis of the Global Navigation Satellite System (GNSS) time series provides valuable information for geodesy and geodynamics research. Precise data analysis strategies are crucial for accurately obtaining the linear velocity of GNSS stations, enabling high-precision applications of GNSS time series. This study investigates the impact of different stochastic noise models on velocity estimations derived from GNSS time series, specifically under conditions of environmental loading correction and common mode error (CME) removal. By comparing data from various data centers, we find that post-correction, different analysis strategies exhibit high consistency in their noise characteristics and velocity estimation results. Across various analysis strategies, the optimal noise models were predominantly Power Law with White Noise (PLWN) and Flicker Noise with White Noise (FNWN), with the optimal noise models including COMB/JPL, COMB/SOPAC, and COMB/NGL for approximately 50% of the datasets. Most of the stations (approximately 80%) showed velocity differences below 0.3 mm/year and velocity estimation uncertainties below 0.1 mm/year. Nonetheless, variations in amplitudes and periodic signals persisted due to differences in the processing of raw GNSS observations. For instance, the NGL and JPL datasets, which were processed using GipsyX 2.1 software, showed higher amplitudes of the 5.5-day periodic signal. These findings provide a solid empirical foundation for advancing data analysis methods and enhancing the reliability of GNSS time series results in future research.
ACDF-YOLO: Attentive and Cross-Differential Fusion Network for Multimodal Remote Sensing Object Detection
Authors: Fei Xuan , Guo Mengyao , Li Yan , Yu Renping , Sun Le
Published: September 2024

Object detection in remote sensing images has received significant attention for a wide range of applications. However, traditional unimodal remote sensing images, whether based on visible light or infrared, have limitations that cannot be ignored. Visible light images are susceptible to ambient lighting conditions, and their detection accuracy can be greatly reduced. Infrared images often lack rich texture information, resulting in a high false-detection rate during target identification and classification. To address these challenges, we propose a novel multimodal fusion network detection model, named ACDF-YOLO, basedon the lightweight and efficient YOLOv5 structure, which aims to amalgamate synergistic data from both visible and infrared imagery, thereby enhancing the efficiency of target identification in remote sensing imagery. Firstly, a novel efficient shuffle attention module is designed to assist in extracting the features of various modalities. Secondly, deeper multimodal information fusion is achieved by introducing a new cross-modal difference module to fuse the features that have been acquired. Finally, we combine the two modules mentioned above in an effective manner to achieve ACDF. The ACDF not only enhances the characterization ability for the fused features but also further refines the capture and reinforcement of important channel features. Experimental validation was performed using several publicly available multimodal real-world and remote sensing datasets. Compared with other advanced unimodal and multimodal methods, ACDF-YOLO separately achieved a 95.87% and 78.10% mAP0.5 on the LLVIP and VEDAI datasets, demonstrating that the deep fusion of different modal information can effectively improve the accuracy of object detection.
Multispectral UAV Image Classification of Jimson Weed (Datura stramonium L.) in Common Bean (Phaseolus vulgaris L.)
Authors: Lauwers Marlies , De Cauwer Benny , Nuyttens David , Maes Wouter H. , Pieters Jan G.
Published: September 2024

Jimson weed (Datura stramonium L.) is a toxic weed that is occasionally found in fields with common bean (Phaseolus vulgaris L.) for the processing industry. Common bean growers are required to manually remove toxic weeds. If toxic weed plants remain, the standing crop will be rejected. Hence, the implementation of an automatic weed detection system aiding the farmers is badly needed. The overall goal of this study was to investigate if D. stramonium can be located in common bean fields using an unmanned aerial vehicle (UAV)-based ten-band multispectral camera. Therefore four objectives were defined: (I) assessing the spectral discriminative capacity between common bean and D. stramonium by the development and application of logistic regression models; (II) examining the influence of ground sampling distance (GSD) on model performance; and improving model generalization by (III) incorporating the use of vegetation indices and cumulative distribution function (CDF) matching and by (IV) combining spectral data from multiple common bean fields with the use of leave-one-group-out cross-validation (LOGO CV). Logistic regression models were created using data from fields at four different locations in Belgium. Based on the results, it was concluded that common bean and D. stramonium are separable based on multispectral information. A model trained and tested on the data of one location obtained a validation true positive rate and true negative rate of 99% and 95%, respectively. In this study, where D. stramonium had a mean plant size of 0.038 m2 (σ = 0.020), a GSD of 2.1 cm was found to be appropriate. However, the results proved to be location dependent as the model was not able to reliably distinguish D. stramonium in two other datasets. Finally, the use of a LOGO CV obtained the best results. Although small D. stramonium plants were still systematically overlooked and classified as common bean, the model was capable of detecting large D. stramonium plants on three of the four fields. This study emphasizes the variability in reflectance data among different common bean fields and the importance of an independent dataset to test model generalization.
Machine Learning Modelling for Soil Moisture Retrieval from Simulated NASA-ISRO SAR (NISAR) L-Band Data
Authors: Dinesh Dev , Kumar Shashi , Saran Sameer
Published: September 2024

Soil moisture is a critical factor that supports plant growth, improves crop yields, and reduces erosion. Therefore, obtaining accurate and timely information about soil moisture across large regions is crucial. Remote sensing techniques, such as microwave remote sensing, have emerged as powerful tools for monitoring and mapping soil moisture. Synthetic aperture radar (SAR) is beneficial for estimating soil moisture at both global and local levels. This study aimed to assess soil moisture and dielectric constant retrieval over agricultural land using machine learning (ML) algorithms and decomposition techniques. Three polarimetric decomposition models were used to extract features from simulated NASA-ISRO SAR (NISAR) L-Band radar images. Machine learning techniques such as random forest regression, decision tree regression, stochastic gradient descent (SGD), XGBoost, K-nearest neighbors (KNN) regression, neural network regression, and multilinear regression were used to retrieve soil moisture from three different crop fields: wheat, soybean, and corn. The study found that the random forest regression technique produced the most precise soil moisture estimations for soybean fields, with an R2 of 0.89 and RMSE of 0.050 without considering vegetation effects and an R2 of 0.92 and RMSE of 0.042 considering vegetation effects. The results for real dielectric constant retrieval for the soybean field were an R2 of 0.89 and RMSE of 6.79 without considering vegetation effects and an R2 of 0.89 and RMSE of 6.78 with considering vegetation effects. These findings suggest that machine learning algorithms and decomposition techniques, along with a semi-empirical technique like Water Cloud Model (WCM), can be effective tools for estimating soil moisture and dielectric constant values precisely. The methodology applied in the current research contributes essential insights that could benefit upcoming missions, such as the Radar Observing System for Europe in L-band (ROSE-L) and the collaborative NASA-ISRO SAR (NISAR) mission, for future data analysis in soil moisture applications.
Two-Dimensional Direction Finding for L-Shaped Coprime Array via Minimization of the Ratio of the Nuclear Norm and the Frobenius Norm
Authors: Zhou Lang , Ye Kun , Zhang Xuebo
Published: September 2024

More recently, the ability of the coprime array to yield large array apertures and high degrees of freedom in comparison with the uniform linear array (ULA) has drawn an enormous amount of attention. In light of this, we propose a low-rank matrix completion algorithm via minimization of the ratio of the nuclear norm and the Frobenius norm (N/F) to solve the two-dimensional (2D) direction finding problem for the L-shaped coprime array (LsCA). Specifically, we first interpolate the virtual co-array signal related to the cross-correlation matrix (CCM) and utilize the interpolated virtual signal for Toeplitz matrix reconstruction. Then, the N/F method is employed to perform low-rank matrix completion on the reconstructed matrix. Finally, exploiting the conjugate symmetry characteristics of the completed matrix, we further develop a direction-finding algorithm that enables 2D angle estimation. Remarkably, the 2D angles are able to be automatically paired by the proposed algorithm. Numerical simulation findings demonstrate that the proposed N/F algorithm generates excellent angular resolution and computational complexity. Furthermore, this algorithm yields better estimation accuracy compared to the competing algorithms.
Contested Borderlands: Experimental Governance and Statecraft in the Laos Golden Triangle Special Economic Zone
Authors: Luzzu Josto
Published: September 2024

The Golden Triangle Special Economic Zone (GTSEZ) in northwest Laos exemplifies an experimental governance model, where sovereign powers are partially privatized to drive economic development. Established in 2007 through a 99-year concession with the Kings Romans Group (KRG), a Chinese gaming company, the GTSEZ is integral to Laos’s strategy of leveraging Special Economic Zones (SEZs) for modernization. This paper examines the complex dynamics between the Lao state and non-state actors within the GTSEZ, highlighting its fragmented yet pragmatic statecraft. Drawing on extensive fieldwork from 2014 to 2018, the study examines the GTSEZ’s historical connections to the opium trade and its contemporary socio-political and economic roles. The zone’s creation has generated both enthusiasm and criticism, particularly concerning sovereignty, local impacts, and controversial activities. The paper also discusses the broader implications of SEZs in Laos’s nation-building efforts, and the GTSEZ’s balance of economic openness with regulatory oversight, enhancing the understanding of experimental governance in Southeast Asia.
Research on the Identification, Network Construction, and Optimization of Ecological Spaces in Metropolitan Areas Based on the Concept of Production-Living-Ecological Space
Authors: Zhang Ping , Zhang Jingfang , Yu Hanwu , Jiang Xiujuan , Zhang Nan
Published: September 2024

In the strategic orientation of promoting high-quality development of metropolitan areas, ecological space is not only the core carrier for maintaining regional ecological balance and harmony but also a key element in shaping the scientific layout of metropolitan areas and promoting harmonious coexistence between cities and nature. This paper takes the Chang-Zhu-Tan metropolitan area as the research object and identifies and classifies ecological space based on the “Production-Life-Ecology” concept, extracts core ecological source areas through the minimum resistance model, and generates ecological resistance surfaces. Then, three types of ecological space corridors are constructed by using the MCR gravity model. This study finds that the ecological space in the Chang-Zhu-Tan metropolitan area is seriously fragmented, the number of corridors is insufficient, and the spatial configuration of the “Production-Life-Ecology” is imbalanced in the region and proposes optimization models and strategies in combination with the spatial network approach to identify and classify ecological space patterns for the metropolitan area. Accordingly, the study proposes optimization models and strategies based on the spatial network approach to provide theoretical support and practical guidance for the ecological spatial pattern and sustainable development of the metropolitan area.
A Review of Sustainable Indices Relevant to the Agri-Food Industry
Authors: Nakelse Tebila , Dennis Elliott
Published: September 2024

In recent years, sustainable practices have become increasingly important in global food production, with a growing emphasis on monitoring and verifying environmentally friendly and socially responsible processes. This paper reviews a comprehensive list of 331 sustainability indices, certifications, and standards used worldwide. We categorized each metric, assessed their key attributes, and compared the focus and measurement practices between food and non-food sustainability metrics. Our comparative analysis highlights significant differences between agricultural and non-agricultural sectors, particularly emphasizing the need for improved measurement frameworks in the beef industry regarding GHG emissions, water use, soil health, and animal welfare. We then demonstrate how these metrics can be applied to the beef production system, identifying potential gaps in existing indices that could be more comprehensive in encompassing environmental, social, and economic aspects. By synthesizing existing knowledge and pinpointing areas for further research, this review aims to contribute to the ongoing efforts to promote sustainable agricultural production and consumption.
The Impact of Supply Chain Finance on the Investment Efficiency of Publicly Listed Companies in China Based on Sustainable Development
Authors: Dou Yixin , Zhao Jiaxin
Published: September 2024

The development and utilization of supply chain finance play a pivotal role in both enhancing financial structures and delivering substantial support for the sustainable progress of the real economy. This assistance is essential for promoting high-quality economic growth and ensuring stable, long-term development. This study empirically examines the effects of supply chain finance on investment efficiency, exploring the underlying mechanisms involved. Additionally, it assesses whether financing constraints and information asymmetry serve as mediating variables in the relationship between supply chain finance and investment efficiency among enterprises. The analysis is based on data from publicly listed companies in China covering the period from 2013 to 2022. The results indicate that supply chain finance effectively addresses both overinvestment and underinvestment issues, leading to a notable improvement in overall investment efficiency. Utilizing a two-way fixed effects model to analyze the role of financing constraints and information asymmetry as mediating variables, the study demonstrates that both factors significantly mediate the relationship between supply chain finance and investment efficiency within enterprises. Supply chain finance improves investment efficiency by mitigating financing constraints and lessening information asymmetry between enterprises and external stakeholders. The heterogeneity analysis reveals that the positive impact of supply chain finance on investment efficiency is notably greater in non-state-owned enterprises and in regions with more advanced development.
Does the Concept of Green Development Promote High-Quality Urban Development?—An Empirical Analysis Based on the Pilot Policy of the “Zero-Waste City” in China
Authors: Zhou Yifei
Published: September 2024

Since 2019, eighteen major ministries and commissions, including the National Development and Reform Commission, have launched trials for a “zero-waste city”. Shenzhen, Baotou, Tongling, and 16 other cities and regions have entered the practical operation stage, and the significance of the economic effect of the policy pilot needs to be tested through empirical evaluation. This study systematically gathers time series data from 281 prefecture-level cities in China from 2005 to 2022 and constructs an innovative experimental framework for the construction of a zero-waste city. It implements a series of rigorous robustness testing procedures using the difference-in-differences (DID) method to scientifically and objectively measure the actual effects of waste-free city construction strategies in promoting the city’s social development along a high-quality development path. This study provides deep insights into the zero-waste city construction strategy as a strong driving force. Our results indicate that the high-quality development stage has a positive impact on the city as a whole that cannot be ignored. At the same time, in-depth analysis shows that this strategy exhibits strong regional differences in the process of promoting high-quality urban development. For the two core regions of eastern and central China, the implementation of zero-waste city policies has significantly accelerated the pace of high-quality development, and further analysis reveals that, compared with the developed eastern region, the implementation of this policy in the central region has achieved superior results in terms of high-quality development. Third, the benefits of waste-free city policies are related to the economic bases of cities, the number of green patents granted, national policies, geographical location, and other factors.
Relationship between Physical Activity Levels, Quality of Life, and Sociodemographic Attributes among Adults in Tabuk, Saudi Arabia: A Direction toward Sustainable Health
Authors: Algamdi Maaidah M. , Al Amer Hamad S.
Published: September 2024

Physical activity (PA) improves quality of life (QOL), yet the relationship between PA, QOL, and sociodemographic factors in Saudi Arabia remains underexplored. This study examined this relationship among 369 adults from Tabuk City, Saudi Arabia. The questionnaire measured PA levels and QOL using the Arabic versions of the International Physical Activity Questionnaire and the 36-item Short-Form Health Survey (SF-36), respectively. Data analyses included chi-square, Mann–Whitney U, and Kruskal–Wallis H tests alongside a multivariate regression analysis. Among the SF-36 scores, marital status (p = 0.005), history of chronic diseases (p = 0.004), and medication use (p = 0.001) showed significant differences; pain (80.6 ± 21.5) and energy/fatigue (63.0 ± 18.5) scored highest and lowest, respectively; and sex was significantly associated with PA levels (p = 0.001). The average total SF-36 score was 69.5 ± 15.7, and 42.5% of participants reported low PA. Participants with moderate PA had significantly higher SF-36 scores (p = 0.003), energy/fatigue (p < 0.0001), emotional wellbeing (p = 0.009), and general health (p = 0.004) scores compared with those with low PA. The significant association between PA and QOL underscores the need for sustainable health programs to enhance and maintain PA in alignment with the Saudi Vision 2030 QOL program. It can also inform the development of targeted interventions to enhance PA levels and improve QOL aspects within communities, considering specific sociodemographic attributes to ensure effectiveness and inclusivity.
A Novel Framework for Identifying Major Fishing Vessel Accidents and Their Key Influencing Factors
Authors: Zhou Hongxia , Wang Fang , Hu Weili , Grifoll Manel , Liu Jiao , Du Weijie , Zheng Pengjun
Published: September 2024

This research addresses the critical issue of major fishing vessel accidents, which traditionally suffer from a lack of focused analysis due to their rarity and the subjective nature of their classification. We propose an innovative methodology of Peaks Over Threshold to overcome subjectivity in accident classification. This approach ensures a more representative and accurate analysis of major accidents, distinguishing them from more common, less severe incidents. Employing a Bayesian network model, we further explore the most influential factors contributing to these major accidents. The key innovation lies in our novel approach to data handling and analysis, enabling us to uncover hidden patterns and causal relationships that traditional methods often overlook. The results show that the approach proposed in this study can effectively capture the key factors of major fishing vessel accidents. This study identifies accident type, vessel-related factors, and accident location as the key influential factors leading to major accidents. The findings from our research are intended to inform sustainable fisheries management practices, promoting interventions that aim to decrease the occurrence and impact of severe maritime accidents while balancing economic, safety, and sustainable development considerations.
A Cybernetics Approach and Autoregressive Distributed Lag Econometric Exploration of Romania’s Circular Economy
Authors: Georgescu Irina , Nica Ionuț , Delcea Camelia , Ciurea Cristian , Chiriță Nora
Published: September 2024

The purpose of this study, which adopts a cybernetics systems approach, is to analyze the circular economy landscape in Romania. It investigates the role of circular economy practices in the country’s endeavors to combat climate change and minimize its environmental footprint. Using data spanning from 2000 to 2022, we applied the autoregressive distributed lag (ARDL) model to examine the interdependence between CO2 emissions and key factors, such as GDP per capita, the recycling rate of municipal waste, and the generation of municipal waste per capita. Our findings suggest that the implementation of sustainable development strategies in Romania has successfully decoupled economic growth from environmental sustainability. This study introduces novelty by approaching the ARDL analysis through the integration of circular economy principles into a cybernetics system. This perspective contributes to informed decision making and the establishment of efficient tactical, operational, and strategic directions. Our results indicate that, in the long run, both the recycling rate of municipal waste and the generation of municipal waste per capita positively influence CO2 emissions, while GDP per capita has a negative impact. Variance decomposition and impulse response functions were employed to assess the explanatory variables’ influence on CO2 emissions and their effectiveness in explaining temporal fluctuations.
Sustainable Entrepreneurship: Interval Analysis in Risk Management and Uncertain Economies
Authors: Chupin Alexander , Chupina Zhanna , Bolsunovskaya Marina , Shirokova Svetlana , Kulyashova Zinaida , Vorotinceva Tatyana
Published: September 2024

Sustainable management in high-tech enterprises is a key aspect of successfully operating modern companies, especially under conditions of risk and uncertainty. This study reviews the field of sustainable management and interval analysis and identifies the main trends and challenges facing high-tech enterprises in the modern world. This study emphasizes the importance of applying interval analysis in making strategic decisions and developing sustainable business models that can adapt to variable environments. This paper presents empirical data, illustrating the practical application of interval analysis tools in the management in high-tech enterprises. It analyzes the effectiveness and potential of this approach to increase the levels of sustainability and competitiveness of organizations in constantly changing business environments. In general, this article is a valuable contribution to the development of sustainable management theory and practice for high-tech enterprises, enriching the existing knowledge in this area and offering new perspectives for research and practical application. Our research has been validated and is presented in the results section. The purpose of this study is to present current developments in methodologies and tools for risk measurement within the probabilistic paradigm of uncertainty, which are supposed to be used in relation to the economic evaluation of real investment projects. The methodological directions or approaches to risk measurement formed in this context are (1) based on quantile measures, within which the quantitative aspect of risk is modeled using quantile quantiles of the distribution of a random variable describing the possible (predicted) results of economic activity; (2) the Monte Carlo method, which is a tool for evaluating the indicators of economic efficiency and risk in justifying real investments, taking into account different distribution laws and mutual relations for the financial and economic parameters of the investment project, as well as its computational and instrumental elaboration.
The Impact of United Nations Sustainable Development Goals on Customers’ Perceptions and Loyalty in the Banking Sector: A Multi-Mediation Approach
Authors: Elansari Hussin , Alzubi Ahmad , Khadem Amir
Published: September 2024

The pursuit of sustainable development has become a global priority, with the United Nations Sustainable Development Goals (UN SDGs) serving as a comprehensive framework for addressing various social, economic, and environmental challenges. Employing the stimulus–organization–response (SOR) model, this study examines the impact of customer’s perceptions of the firm’s compliance with the SDGs on customers’ perceptions and loyalty through the mediation roles of image, trust, and reputation in the customer’s evaluation of the firm in the banking sector in Turkey. To achieve these objectives, a quantitative research approach was used, and 455 valid responses were collected from retail banking customers through an online survey. Data from the study were statistically analyzed using partial least-squares–structural equation modeling (PLS-SEM). The findings reveal significant positive relationships between SDG implementation and customers’ perceptions of banking institutions’ image, trust, and reputation. Furthermore, favorable image, trust, and favorable reputation are found to positively influence customer loyalty in the banking sector. The mediation analyses confirm that each of the mediating variables partially mediates the relationships between SDG implementation and customer loyalty, underscoring the significance of these intermediate variables in shaping customers’ loyalty behaviors. This research contributes to both theoretical and practical domains by providing insights into the role of SDG implementation in enhancing customer perceptions and loyalty in the banking sector. Managerial implications are discussed, and recommendations are provided for banking institutions seeking to leverage the SDGs to strengthen customer relationships and achieve sustainable growth.
Teleworking and Mental Well-Being: A Systematic Review on Health Effects and Preventive Measures
Authors: Shaholli David , Manai Maria Vittoria , Iantorno Francesco , Di Giampaolo Luca , Nieto Hector Alberto , Greco Emilio , La Torre Giuseppe , De Sio Simone
Published: September 2024

Background: In the aftermath of the Coronavirus pandemic and the resulting lockdown and social distancing policies, a new form of work, already existing in the past, has been further enlarged. Teleworking is “full- or part-time electronic work, on-line or off-line, performed at home by self-employed or office workers” and today represents an important lever for companies, including for sustainability, allowing employees to work flexibly, efficiently and remotely. The relationship between telework and sustainability in economic, social, and environmental aspects is also being questioned. The aim of this systematic review is to investigate the effects this has had on workers’ mental health. Methods: PRISMA guidelines were followed. The research was performed on Pubmed and Scopus without restrictions on study type and time limits. The methodological quality of the studies included was assessed using AMSTAR-2, INSA and NOS scales. A meta-analysis of the main adverse effects found in observational studies was also carried out. Results: A total of 38 articles were included in the systematic review. A large proportion of the studies examined showed a correlation between teleworking and worsening mental health. The meta-analysis showed increased levels of mental ill-health (38.8%), stress (28.4%), isolation (6.3%), anxiety (23%), depression (22.6%), work–family conflicts (19.5%), poor sleep quality (56.4%), fatigue (16.1%) and irritability (39.6%). Conclusions: Although most of the works analyzed show a deterioration in the mental health of workers, positive effects were noted in some. There is the need for more studies to optimally investigate the cause–effect relationship between teleworking and mental health deterioration.
The Paradox of Progress towards SDG7: Governance Quality and Energy Poverty Dynamics in Pakistan
Authors: Liu Rongbing , Qadeer Afifa , Liu Junqi , Sarwar Suleman , Hussan Muhammad Wasim
Published: September 2024

This study investigates the multidimensional aspects of energy poverty in Pakistan from 2000 to 2022, specifically evaluating the direct, indirect, and total effects of socioeconomic and environmental factors. We employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the impacts of income, population, governance quality, energy intensity, fuel prices, and renewable energy consumption on energy poverty. The study further contributes by examining the mediating role of governance quality and developing the World Governance Indicators (WGI) Index. The findings indicate significant negative effects of energy intensity and renewable energy consumption on energy poverty. Conversely, population growth and income levels demonstrate positive effects, contradicting conventional economic development and energy access assumptions. Governance quality establishes direct and indirect effects that mediate most relationships between independent variables and energy poverty. Bootstrapping analysis confirms the significance of governance quality as a mediator. The model describes significant energy poverty variance with robust predictive relevance. This study emphasizes the need to adopt a comprehensive strategy to decrease Pakistan’s energy poverty by articulating socioeconomic, environmental, and governance factors. Our findings offer valuable information for policymakers to achieve UN Sustainable Development Goal 7, embarking on governance reforms, promoting sustainable growth, and enforcing investments in energy efficiency and renewable sources as Pakistan approaches the 2030 SDG 7 deadline.