bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of Bilayer Resistive Random Access Memory Based on Ti/HfO2/ZrO2/Pt
Authors: Sun Zhendong , Wang Pengfei , Li Xuemei , Chen Lijia , Yang Ying , Wang Chunxia
Published: April 2024

In this paper, the electrothermal coupling model of metal oxide resistive random access memory (RRAM) is analyzed by using a 2D axisymmetrical structure in COMSOL Multiphysics simulation software. The RRAM structure is a Ti/HfO2/ZrO2/Pt bilayer structure, and the SET and RESET processes of Ti/HfO2/ZrO2/Pt are verified and analyzed. It is found that the width and thickness of CF1 (the conductive filament of the HfO2 layer), CF2 (the conductive filament of the ZrO2 layer), and resistive dielectric layers affect the electrical performance of the device. Under the condition of the width ratio of conductive filament to transition layer (6:14) and the thickness ratio of HfO2 to ZrO2 (7.5:7.5), Ti/HfO2/ZrO2/Pt has stable high and low resistance states. On this basis, the comparison of three commonly used RRAM metal top electrode materials (Ti, Pt, and Al) shows that the resistance switching ratio of the Ti electrode is the highest at about 11.67. Finally, combining the optimal conductive filament size and the optimal top electrode material, the I-V hysteresis loop was obtained, and the switching ratio Roff/Ron = 10.46 was calculated. Therefore, in this paper, a perfect RRAM model is established, the resistance mechanism is explained and analyzed, and the optimal geometrical size and electrode material for the hysteresis characteristics of the Ti/HfO2/ZrO2/Pt structure are found.
Bond Formation at C8 in the Nucleoside and Nucleotide Purine Scaffold: An Informative Selection
Authors: Undheim Kjell
Published: April 2024

This paper presents methods for the introduction and exchange of substituents in a nucleobase and its nucleosides and nucleotides with emphasis on the C8-position in the purine skeleton. The nucleobase is open for electrophilic and nucleophilic chemistry. The nucleophilic chemistry consists mainly of displacement reactions when the C8-substituent is a good leaving group such as a halogen atom. The heteroatom in amines, sulfides, or oxides is a good nucleophile. Halides are good reaction partners. Metal-promoted cross-coupling reactions are important for carbylations. Direct oxidative metalation reactions using sterically hindered metal amides offer chemo- and regio-selectivity besides functional tolerance and simplicity. The carbon site is highly nucleophilic after metalation and adds electrophiles resulting in chemical bond formation. Conditions for metal-assisted reactions are described for nucleobases and their glycosides.
Neurocognitive Impairment and Social Cognition in Parkinson’s Disease Patients
Authors: Doskas Triantafyllos , Vadikolias Konstantinos , Ntoskas Konstantinos , Vavougios George D. , Tsiptsios Dimitrios , Stamati Polyxeni , Liampas Ioannis , Siokas Vasileios , Messinis Lambros , Nasios Grigorios , Dardiotis Efthimios
Published: April 2024

In addition to motor symptoms, neurocognitive impairment (NCI) affects patients with prodromal Parkinson’s disease (PD). NCI in PD ranges from subjective cognitive complaints to dementia. The purpose of this review is to present the available evidence of NCI in PD and highlight the heterogeneity of NCI phenotypes as well as the range of factors that contribute to NCI onset and progression. A review of publications related to NCI in PD up to March 2023 was performed using PubMed/Medline. There is an interconnection between the neurocognitive and motor symptoms of the disease, suggesting a common underlying pathophysiology as well as an interconnection between NCI and non-motor symptoms, such as mood disorders, which may contribute to confounding NCI. Motor and non-motor symptom evaluation could be used prognostically for NCI onset and progression in combination with imaging, laboratory, and genetic data. Additionally, the implications of NCI on the social cognition of afflicted patients warrant its prompt management. The etiology of NCI onset and its progression in PD is multifactorial and its effects are equally grave as the motor effects. This review highlights the importance of the prompt identification of subjective cognitive complaints in PD patients and NCI management.
Evaluation of Menopausal Syndrome Relief and Anti-Obesity Efficacy of the Korean Fermented Food Doenjang: A Randomized, Double-Blind Clinical Trial
Authors: Han A Lum , Ryu Myeong Seon , Yang Hee-Jong , Jeong Do-Youn , Choi Keum Ha
Published: April 2024

Foods that help improve menopausal syndrome are being studied worldwide. Doenjang is a traditional Korean fermented soybean food with potential health benefits for menopausal women. In this clinical trial using Doenjang, we aimed to compare the effectiveness of traditional Doenjang and commercial Doenjang in menopausal women. Furthermore, we compared whether Doenjang has a better effect if the number of beneficial microbes is higher. The analyses included the following groups: traditional Doenjang containing either a high dose (HDC; n = 18) or low dose (LDC; n = 18) of beneficial microbes and commercial Doenjang (CD; n = 20). The Kupperman index and hematological changes were examined before and after the use of Doenjang pills. The effects of Doenjang on obesity and body composition were studied before and after ingestion. Lastly, the microorganisms and short-chain fatty acid changes in the stool were compared. The Kupperman index decreased after Doenjang consumption in all three groups, with the greatest decrease in the LDC group. Only the groups that took traditional Doenjang pills exhibited reduced LDL cholesterol. No changes in obesity and inflammation-related indicators were observed. The number of Firmicutes, associated with obesity, decreased in the CD group but the numbers of Bacteroidetes increased in the HDC and CD groups. Thus, traditional Doenjang is more effective in alleviating menopausal syndrome than commercial Doenjang. Further research on the anti-obesity effect or changes in microbiomes and short-chain fatty acids in feces is needed.
Biomarkers in Detection of Hepatitis C Virus Infection
Authors: Woo Jungreem , Choi Youkyung
Published: April 2024

The hepatitis C virus (HCV) infection affects 58 million people worldwide. In the United States, the incidence rate of acute hepatitis C has doubled since 2014; during 2021, this increased to 5% from 2020. Acute hepatitis C is defined by any symptom of acute viral hepatitis plus either jaundice or elevated serum alanine aminotransferase (ALT) activity with the detection of HCV RNA, the anti-HCV antibody, or hepatitis C virus antigen(s). However, most patients with acute infection are asymptomatic. In addition, ALT activity and HCV RNA levels can fluctuate, and a delayed detection of the anti-HCV antibody can occur among some immunocompromised persons with HCV infection. The detection of specific biomarkers can be of great value in the early detection of HCV infection at an asymptomatic stage. The high rate of HCV replication (which is approximately 1010 to 1012 virions per day) and the lack of proofreading by the viral RNA polymerase leads to enormous genetic diversity, creating a major challenge for the host immune response. This broad genetic diversity contributes to the likelihood of developing chronic infection, thus leading to the development of cirrhosis and liver cancer. Direct-acting antiviral (DAA) therapies for HCV infection are highly effective with a cure rate of up to 99%. At the same time, many patients with HCV infection are unaware of their infection status because of the mostly asymptomatic nature of hepatitis C, so they remain undiagnosed until the liver damage has advanced. Molecular mechanisms induced by HCV have been intensely investigated to find biomarkers for diagnosing the acute and chronic phases of the infection. However, there are no clinically verified biomarkers for patients with hepatitis C. In this review, we discuss the biomarkers that can differentiate acute from chronic hepatitis C, and we summarize the current state of the literature on the useful biomarkers that are detectable during acute and chronic HCV infection, liver fibrosis/cirrhosis, and hepatocellular carcinoma (HCC).
LDLR-Mediated Targeting and Productive Uptake of siRNA-Peptide Ligand Conjugates In Vitro and In Vivo
Authors: Broc Baptiste , Varini Karine , Sonnette Rose , Pecqueux Belinda , Benoist Florian , Masse Maxime , Mechioukhi Yasmine , Ferracci Géraldine , Temsamani Jamal , Khrestchatisky Michel , Jacquot Guillaume , Lécorché Pascaline
Published: April 2024

Small RNA molecules such as microRNA and small interfering RNA (siRNA) have become promising therapeutic agents because of their specificity and their potential to modulate gene expression. Any gene of interest can be potentially up- or down-regulated, making RNA-based technology the healthcare breakthrough of our era. However, the functional and specific delivery of siRNAs into tissues of interest and into the cytosol of target cells remains highly challenging, mainly due to the lack of efficient and selective delivery systems. Among the variety of carriers for siRNA delivery, peptides have become essential candidates because of their high selectivity, stability, and conjugation versatility. Here, we describe the development of molecules encompassing siRNAs against SOD1, conjugated to peptides that target the low-density lipoprotein receptor (LDLR), and their biological evaluation both in vitro and in vivo.
Interlaminar Shear Strength Change and Storage Life Prediction of Carbon Fiber/Epoxy Composites with Hygrothermal Accelerated Aging
Authors: Fan Jinjuan , Zhang Qin , Chen Xinwen , He Yuhuai
Published: April 2024

In order to investigate the durability of fiber-reinforced polymer composites in hygrothermal environments, hygrothermal accelerate aging tests, for 360 days at 70 °C, RH70%; 70 °C, RH85%; 85 °C, RH70%; and 85 °C, RH85% and natural storage for 2 years in Guangzhou, China, were carried out for composite laminates. Then, the moisture absorption and interlaminar shear strength were measured. The hygrothermal damage mechanism of the composite was studied by Fourier transform infrared (FTIR), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and field emission scanning electron microscopy (FSEM). A dual stress storage life prediction model and the equivalent relationship between natural storage and hygrothermal acceleration were established. The results show that the order of moisture absorption rates, moisture absorption contents, and the severity effect order on the interlaminar shear strength is RH85%; 85 °C > 70 °C; RH85% > 85 °C; RH70% > 70 °C; and RH70%. The time to achieve an effective moisture absorption balance is opposite to this. The moisture absorption rate meets Fick’s law before the effective moisture absorption balance, and then shows a linear trend. The interlayer shear strength still decreases exponentially with aging, which is mainly caused by the resin plasticization and interface weakening. Hygrothermal accelerated aging for 13.4831 days at 85 °C; RH85% is equivalent to that for one-year actual storage in Guangzhou. According to the failure criterion of shear strength decreasing to 77%, the storage life of T700/epoxy in Guangzhou is 14.4661 years.
Influences of Polyphenols on the Properties of Crosslinked Acellular Fish Swim Bladders: Experiments and Molecular Dynamic Simulations
Authors: Han Yuqing , Jiang Jie , Li Jinjin , Zhao Ling , Xi Zhenhao
Published: April 2024

Acellular fish swim bladders (AFSBs) are a promising biomaterial in tissue engineering, however, they may suffer from rapid degradation due to enzyme invasion. In this work, natural polyphenols, including epigallocatechin gallate (EGCG), proanthocyanidin (PC), tannic acid (TA) and protocatechuic acid (PCA), were utilized to improve the properties of AFSBs through crosslinking modifications. Fourier transform infrared (FTIR) results indicate that the triple helix of the collagen in AFSBs is well preserved after crosslinking. The differential scanning calorimetry (DSC), water contact angle (WCA) and in vitro degradation tests indicate that the polyphenol-crosslinked AFSBs exhibit improved thermal stability, enzymatic stability, hydrophilicity and mechanical properties. Among them, EGCG with multiple phenolic hydroxyl groups and low potential resistance is more favorable for the improvement of the mechanical properties and enzymatic stability of AFSBs, as well as their biocompatibility and integrity with the collagen triple helix. Moreover, the crosslinking mechanism was demonstrated to be due to the hydrogen bonds between polyphenols and AFSBs, and was affected by the molecular size, molecular weight and the hydroxyl groups activity of polyphenol molecules, as clarified by molecular dynamic (MD) simulations. The approach presented in this work paves a path for improving the properties of collagen materials.
Ethylene Vinyl Alcohol Copolymer Nanofibrous Cation Exchange Chromatographic Membranes with a Gradient Porous Structure for Lysozyme Separation
Authors: Tang Tianzhi , Gan Jinping , Cao Zhanrui , Cheng Pan , Cheng Qin , Mei Tao , Zhu Liping , Zhou Feng , Liu Ke , Wang Dong
Published: April 2024

Lysozyme, a common antimicrobial agent, is widely used in the food, biopharmaceutical, chemical, and medicine fields. Rapid and effective isolation of lysozymes is an everlasting topic. In this work, ethylene vinyl alcohol (EVOH) copolymer nanofibrous membranes with a gradient porous structure used for lysozyme adsorption were prepared through layer-by-layer nanofiber wet-laying and a cost-efficient ultraviolet (UV)-assisted graft-modification method, where benzophenone was used as an initiator and 2-acrylamide-2-methylpropanesulfonic acid as a modifying monomer. As indicated in the Fourier Transform Infrared (FTIR) and X-ray photoelectric energy spectrometer (XPS) investigation, sulfonic acid groups were introduced on the surface of the modified nanofibrous membrane, which possessed the ability to adsorb lysozyme. Compared with membranes with homogenous porous structures, membranes with a gradient porous structure present higher static (335 mg/g) and dynamic adsorption capacities (216.3 mg/g). Meanwhile, the adsorption capacity remained high after five cycles of the adsorption–desorption process. The results can be attributed to the gradient porous structure rather than the highest porosity and specific surface area. This suggests that the membrane with comprehensive separation performance can be designed from the view of the transmembrane porous structure, which is of significance for the development of next-generation advanced chromatographic membranes.
Asymptotic Performance of GNSS Positioning Approaches under Cross-Correlation Effects
Authors: Duan Yuze , Wei Jiaolong , Tang Zuping
Published: April 2024

Conventional global navigation satellite system receivers typically employ a two-step positioning procedure (2SP) by first independently estimating the synchronization parameters and then using these parameters to solve a system of superdeterministic equations derived from multilateration to accomplish positioning. Direct position estimation (DPE) has emerged as a promising alternative that utilizes a single-step procedure to obtain the maximum likelihood estimate of a position. This approach has been shown to effectively mitigate biases incurred by the second estimation step in 2SP. However, for code-division multiple-access systems, the pseudo-orthogonality of the spreading codes causes the estimation problem not to be mapped to a perfectly orthogonal space. Additionally, the cross-correlation interference between satellites renders the maximum likelihood invariant theory untenable in the first estimation step of the 2SP. This study presents the derivation of the Cramér–Rao bound constraint for both the 2SP and DPE, evaluating the performance degradation of the 2SP compared to that of the DPE with the consideration of cross-correlation. Furthermore, a more stringent result is proven, indicating that the 2SP is not as asymptotically efficient as the DPE in all scenarios. The derived bounds are validated using realistic scenarios, and the root-mean-square error performance of the respective maximum likelihood estimators is compared.
A Novel Flood Risk Analysis Framework Based on Earth Observation Data to Retrieve Historical Inundations and Future Scenarios
Authors: Yao Kezhen , Yang Saini , Wang Zhihao , Liu Weihang , Han Jichong , Liu Yimeng , Zhou Ziying , Gariano Stefano Luigi , Shi Yongguo , Jaeger Carlo
Published: April 2024

Global warming is exacerbating flood hazards, making the robustness of flood risk management a critical issue. Without considering future scenarios, flood risk analysis built only on historical knowledge may not adequately address the coming challenges posed by climate change. A comprehensive risk analysis framework based on both historical inundations and future projections to tackle uncertainty is still lacking. In this view, a scenario-based, data-driven risk analysis framework that for the first time integrates recent historical floods and future risk trends is here presented, consisting of flood inundation-prone and high-risk zones. Considering the Poyang Lake Eco-Economic Zone (PLEEZ) in China as the study area, we reproduced historical inundation scenarios of major flood events by using Sentinel-1 imagery from 2015 to 2021, and used them to build the risk baseline model. The results show that 11.7% of the PLEEZ is currently exposed to the high-risk zone. In the SSP2-RCP4.5 scenario, the risk would gradually decrease after peaking around 2040 (with a 19.3% increase in high-risk areas), while under the traditional fossil fuel-dominated development pathway (SSP5-RCP8.5), the risk peak would occur with a higher intensity about a decade earlier. The attribution analysis results reveal that the intensification of heavy rainfall is the dominant driver of future risk increase and that the exploitation of unused land such as wetlands induces a significant increase in risk. Finally, a hierarchical panel of recommended management measures was developed. We hope that our risk analysis framework inspires newfound risk awareness and provides the basis for more effective flood risk management in river basins.
Methane Retrieval from Hyperspectral Infrared Atmospheric Sounder on FY3D
Authors: Zhang Xinxin , Zhang Ying , Meng Fan , Tao Jinhua , Wang Hongmei , Wang Yapeng , Chen Liangfu
Published: April 2024

This study utilized an infrared spotlight Hyperspectral infrared Atmospheric Sounder (HIRAS) and the Medium Resolution Spectral Imager (MERSI) mounted on FY3D cloud products from the National Satellite Meteorological Center of China to obtain methane profile information. Methane inversion channels near 7.7 μm were selected based on the different distribution of methane weighting functions across different seasons and latitudes, and the selected retrieval channels had a great sensitivity to methane but not to other parameters. The optimization method was employed to retrieve methane profiles using these channels. The ozone profiles, temperature, and water vapor of the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation reanalysis data (ERA5) were applied to the retrieval process. After validating the methane profile concentrations retrieved by HIRAS, the following conclusions were drawn: (1) compared with Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrument Container (CARIBIC) flight data, the average correlation coefficient, relative difference, and root mean square error were 0.73, 0.0491, and 18.9 ppbv, respectively, with lower relative differences and root mean square errors in low-latitude regions than in mid-latitude regions. (2) The methane profiles retrieved from May 2019 to September 2021 showed an average error within 60 ppbv compared with the Fourier transform infrared spectrometer (FTIR) station observations of the Infrared Working Group (IRWG) of the Network for the Detection of Atmospheric Composition Change (NDACC). The errors between the a priori and retrieved values, as well as between the retrieved and smoothed values, were larger by around 400–500 hPa. Apart from Toronto and Alzomoni, which had larger peak values in autumn and spring respectively, the mean column averaging kernels typically has a larger peak in summer.
Road Extraction and Distress Assessment by Spaceborne, Airborne, and Terrestrial Platforms
Authors: Baiocchi Valerio , Zhang Xianfeng , Mei Alessandro
Published: April 2024

The road systems connecting villages, cities, and countries stand as a pivotal transportation infrastructure in modern society [...]
Robot-Assisted Surgery in Poland: The Past, the Present, and the Perspectives for the Future
Authors: Sosnowski Roman , Jakubiak Krzysztof , Kamecki Hubert , Kade Grzegorz , Drewa Tomasz , Szydełko Tomasz , Chłosta Piotr , Kania Piotr , Jarzemski Piotr
Published: April 2024

In recent decades, we have been witnessing a technological revolution in the area of minimally invasive urologic surgery, with robot-assisted surgery being one of the most game-changing inventions [...]
A Review of Solar and Wind Energy Resource Projection Based on the Earth System Model
Authors: Chen Guanying , Ji Zhenming
Published: April 2024

Many countries around the world are rapidly advancing sustainable development (SD) through the exploitation of clean energy sources such as solar and wind energy, which are becoming the core of the sustainable energy transition. In recent years, the continuous advancement of Earth system models (ESMs) has facilitated numerous studies utilizing them to predict long-term and large-scale meteorological elements, consequently enabling forecasts of wind and solar energy. These forecasts provide critical guidance for formulating national renewable energy policies. Nevertheless, the current literature on ESMs predicting wind and solar energy lacks sufficient integration. Hence, to comprehend the focal points and future research prospects, we conducted this systematic review, employing four academic search tools to comprehensively analyze the relevant literature from the past five years. We summarized the general analytical process and compared the content and conclusions of the literature. The study reveals that future photovoltaic (PV) potential for electricity generation may increase in certain regions but decrease in others, while the global potential for concentrated solar power (CSP) may diminish, influenced by diverse factors and displaying significant regional disparities. In addition, wind resource trends vary in different regions, and forecasts exhibit considerable uncertainty. Therefore, many studies have corrected wind speeds prior to predicting wind energy. Subsequent research endeavors should concentrate on optimizing ESMs, investigating the impacts of technological innovation, and enhancing the prediction and analysis of extreme weather events.
Intragenerational Dynamics in the Indonesian Oil Palm Growth Zone: The Resolution between Circular Dimensions and Human Capital
Authors: Herdiansyah Herdis , Mamola Randi , Ernawati Ninin
Published: April 2024

The community in the oil palm planting zone experiences intragenerational disappointment, due to feelings of alienation that add to the complexity of conflict resolution. We employed an experimental conflict resolution approach utilising Latent Class Analysis and ANOVA hypothesis testing to summarise research findings, a method which involves selecting descriptions of conflict classes and member variables, in order to depict intragenerational community characteristics that concern the perceptions and experiences of conflict within oil palm planting zones. The results indicate that groups categorised as “aggressive habitat threats” reflected concerns about environmental degradation and the potential eviction of small landholders. Meanwhile, the “job transition” group presented a potential for conflict in proportion to their aspirations for a decent life. However, conflicts do not always result in direct clashes. Conversely, community empowerment, including circular dimensions and human resources, acts as a catalyst that motivates intragenerational individuals to actively accelerate efforts to increase their capacity.
Using Ensemble Learning for Remote Sensing Inversion of Water Quality Parameters in Poyang Lake
Authors: Peng Changchun , Xie Zhijun , Jin Xing
Published: April 2024

Inland bodies of water, such as lakes, play a crucial role in sustaining life and supporting ecosystems. However, with the rapid development of socio-economics, water resources are facing serious pollution problems, such as the eutrophication of water bodies and degradation of wetlands. Therefore, the monitoring, management, and protection of inland water resources are particularly important. In past research, empirical models and machine learning models have been widely used for the water quality assessment of inland lakes. Due to the complexity of the optical properties of inland lake water bodies, the performance of these models is often limited. To overcome the limitations of these models, this study uses in situ water quality data from 2017 to 2018 and multispectral (MS) remote sensing data from Sentinel-2 to construct experimental samples of Poyang Lake. Based on these experimental samples, we constructed a spatio-temporal ensemble model (STE) to evaluate four common water quality parameters: chlorophyll-a (Chl-a), total phosphorus (TP), total nitrogen (TN), and chemical oxygen demand (COD). The model adopts an ensemble learning strategy, improving the model’s performance by merging multiple advanced machine learning algorithms. We introduced several indices related to water quality parameters as auxiliary variables, such as NDCI and Enhanced Three, and used band data and these auxiliary variables as predictive variables, thereby greatly enhancing the predictive potential of the model.The results show that the inversion accuracy of these four inversion models is high (R2 of 0.94, 0.88, 0.92, and 0.93; RMSE of 1.15, 0.01, 0.02, and 0.02; MAE of 0.81, 0.01, 0.09, and 0.10), indicating that the STE model has good evaluation accuracy. Meanwhile, we used the STE model to reveal the spatio-temporal distribution of Chl-a, TP, TN, and COD from 2017 to 2018, and analyzed their seasonal and spatial variation rules. The results of this study not only provide an effective and practical method for monitoring and managing water quality parameters in inland lakes, but also provide water security for socio-economic and ecological environmental safety.
Research on Sustainable Urban–Rural Integration Development: Measuring Levels, Influencing Factors, and Exploring Driving Mechanisms—Taking Eight Cities in the Greater Bay Area as Examples
Authors: Xu Jing , Zeng Zhenjian , Xi Zhenhua , Peng Zhencong , Chen Gangheng , Zhu Xiting , Chen Xinjia
Published: April 2024

Urban–rural integration is a top priority in social development and an urgent requirement for vigorously promoting rural revitalization. However, the current development of urban–rural integration in China still faces issues such as an unreasonable urban–rural industrial structure, unidirectional flow of rural population, and low sense of belonging among rural residents. Based on this, this paper selects eight cities from the Greater Bay Area as examples, organizing urban–rural integration development data from 1986 to 2022. It employs principal component analysis to quantitatively evaluate the evolutionary trend of urban–rural integration, constructs a fixed-effect panel quantile regression model to explore the factors influencing urban–rural integration and its spatiotemporal evolution, and uses threshold effects and interaction effects to test the threshold and application requirements for maximizing the benefits of urban–rural integration driving mechanisms, drawing empirical insights from comparisons with other bay areas around the world. The research found the following: First, between 1986 and 2022, the development of urban–rural integration in the Greater Bay Area steadily progressed, with gradually emerging effects, and industrial integration and population integration made significant contributions to the development of urban–rural integration. Second, the driving mechanisms of market economics, government intervention, and social fusion significantly impact urban–rural integration, with the influence of market economics being the most significant. Third, the impacts of the three driving mechanisms on urban–rural integration show temporal and spatial differences. In terms of time, market economics and government intervention always have a positive impact, while social fusion shows a “suppressing-promoting” trend, with a lower impact coefficient. Spatially, there are differences in strategies and priorities for promoting urban–rural integration in each region. Fourth, all three driving mechanisms exhibit threshold effects, and the explanatory power of any two interacting driving mechanisms for urban–rural integration development is stronger than that of any single mechanism. Notably, the combined interaction effect of the three driving mechanisms has the highest impact coefficient. The driving mechanisms should be implemented according to the principles of “synchronization, heterogeneity, and categorization”.
Sustainability and Productivity of Village Tank Cascade Systems: A Bibliometric Analysis and Knowledge Mapping
Authors: Ratnayake Sujith S. , Reid Michael , Larder Nicolette , Kariyawasam Champika S. , Hunter Callum , Hunter Danny , Dharmasena Punchi B. , Pushpakumara Gamini , Kogo Benjamin
Published: April 2024

Research on social–ecological systems is rapidly expanding globally in response to human-induced climate change, biodiversity loss, and ecosystem degradation. Safeguarding these traditional agroecosystems is vital according to the 2030 Agenda for Sustainable Development. In the last decade, there has been a growing research interest in the Village Tank Cascade Systems (VTCSs) of Sri Lanka, recognised as social–ecological systems. However, few studies have systematically analysed VTCS research in Sri Lanka. To examine this apparent knowledge gap in more detail, a bibliometric analysis and knowledge mapping were conducted to systematically analyse and interpret the state, trends, clusters, and emerging fields of VTCS research. In total, 159 peer-reviewed research publications between 1985 and 2023 were obtained from the Web of Science Core Collection, Scopus databases, Google Scholar, and ResearchGate to perform this analysis. Furthermore, this study employed the Sustainability Assessment of Food and Agriculture systems (SAFA) tool, developed by the Food and Agriculture Organization of the United Nations, to map the inclusion of sustainability and productivity dimensions in VTCS research, in alignment with the objectives set forth by the 2030 Agenda for Sustainable Development. The study provides insight into dominant and neglected areas of future VTCS research.
From E-Waste to Eco-Wonder: Resurrecting Computers for a Sustainable Future
Authors: Reyna Jorge , Hanham Jose , Orlando Joanne
Published: April 2024

Educational institutions are massive consumers of computing technologies, often replacing their computing infrastructure in a 3-to-5-year timeframe. Once decommissioned, many components of computing technologies are no longer useable and become electronic waste. Replacing computer infrastructure within these short timeframes is a significant e-waste sustainability issue that educational institutions need to address. This article aims to introduce and provoke new thinking regarding e-waste management and its implications for education. The authors introduce the term sustainable device literacy to conceptualise how educators and educational institutions can take an educative approach to refreshing computing technologies beyond their presumed obsolescence. Two example case studies that demonstrate the upgrade of a laptop from 2012 and a desktop computer from 2015 are included to provoke new discussions regarding e-waste and education. Using benchmarking tools, the findings from the case studies show that computing technologies that may be considered obsolete can be upgraded to include much of the functionality of current computers. The broader implications for sustainability are discussed.
System Dynamics Simulation and Influencing Factors of the Interaction between Urbanization and Eco-Environment in Hebei Province, China
Authors: Wang Hefeng , Zhao Jinshan , Zhao Ao , Cao Yuan , Wei Kaihao
Published: April 2024

Searching for an urbanization development model that is suitable for the eco-environment can provide important references for regional sustainable development. By comprehensively using models such as system dynamics (SD), distance coordination coupling degree, symbiosis degree, and grey correlation degree, the interaction between urbanization and eco-environment in Hebei Province from 2020 to 2035 was dynamically simulated based on the historical data from 2000 to 2019. In addition, the key bidirectional influence factors of urbanization and eco-environment were identified. The entire process analysis from model construction, scenario simulation, and preferred scenarios to factor identification was achieved. The results showed the following. (1) The constructed SD model was reliable and effective, and could be used to simulate future strategies. (2) Three evaluation methods could effectively reveal the advantages and disadvantages of the phased scenario schemes during the simulation period, and the obtained results had strong consistency. The urbanization priority development scenario was more suitable for short-term and medium-term planning, while the friendly development scenario was more suitable for the entire simulation period. (3) Five indicators of urbanization and seven indicators of the eco-environment were highly relevant to the evaluation levels of the eco-environment and urbanization, respectively. The study extended the application of the symbiosis theory and the evaluation methods of scenario simulation schemes for urbanization and eco-environment systems.
Restoring a Degraded Riparian Forested Buffer While Balancing Phosphorus Remediation, Biodiversity, and Indigenous Land Access
Authors: Rubin Jessica , McGranaghan Carol , Kolba Luca , Görres Josef
Published: April 2024

This research tested whether mycorrhizae can rejuvenate the water quality and pollinator functions of degraded riparian forested buffers (RFBs) in agricultural landscapes while facilitating indigenous Abenaki access to ancestral lands. Two plots within a degraded RFB were restored with a multi-functional plant community, one plot inoculated with commercial mycorrhizae and the other without. A control plot remained in a degraded state dominated by the invasive shrub Rhamnus cathartica. The restoration palette of 32 plants included 28 species useful to the Abenaki, representing opportunities for phosphorus removal through harvesting. Monitoring data from 2020 to 2023 indicated consistently greater plant diversity in the restored plots, with 58 newcomers appearing. Although the total phosphorus (P) decreased over time in all the treatments, the greatest decrease was in the uninoculated plot, likely due to pathogenicity from the commercial inoculant or the spatial variability of soil and light. The biomass P of five plant species differed among the species but not among the treatment plots. Nonetheless, Abenaki harvesting removed P and can be an effective form of phytoremediation, phytoextraction. However, this research revealed trade-offs between P mitigation, indigenous use, and pollinator functions of the RFB. Fostering higher biodiversity, Indigenous land access, and P mitigation are important solution-oriented aims to balance when restoring degraded RFBs.
Spatiotemporal Dynamics and Mainstreaming Strategies of Ecosystem-Based Adaptation to Urban Climate Change
Authors: Liu Zhimin , Xiu Chunliang , Han Gang , Yuan Lina
Published: April 2024

Cities worldwide are facing varying degrees of ongoing threats closely tied to climate change. Research is emerging that addresses climate risks as a pressing issue, especially for vulnerable cities in the Global South; however, there is a significant lack of systematic and application-oriented research on ecosystem-based adaptation to urban climate change. This study uses Shenyang in Northeast China as a case study, employing multisource data and integrated methods to examine and depict the dynamics of urban ecosystem-based adaptation to climate change amid rapid urbanization. The results indicate a decline in capacity for climate change adaptation during the study period. A framework for mainstreaming ecosystem-based adaptation is proposed, identifying specific strategies for climate change mitigation and adaptation in urban policy and planning processes in Shenyang. It also has significance for other cities to draw lessons from. By linking urban ecosystem dynamics, the capacity for urban climate adaptation, and sustainable urban governance, this study bridges the gap between research and practice in urban climate change adaptation, and expands the contribution of geography-based interdisciplinary integration to urban resilience. More practically, it provides references for Shenyang in adapting to climate change and transitioning to sustainable development.
Evaluation Research on the Spatial Vitality of Huaihe Road Commercial Block in Hefei City Based on Multi-Source Data Correlation
Authors: Zhou Qinghua , Zheng Yiran
Published: April 2024

This article takes the spatial vitality of Huaihe Road Commercial Block in Hefei city as the research object and defines two evaluation dimensions, including external characteristic elements and constituent elements of spatial vitality. The external characteristic elements are reflected by the data of heat maps. As for the constituent elements, this article presents the corresponding influencing factor indicators in the aspects of the road network configuration, functional commercial form and spatial quality of the commercial block. In addition, it conducts a quantitative study on the multi-source data of the influencing factor indicators relating to the spatial vitality of this commercial block by means of heat maps, block POI, street view images and urban space. In the process of this quantitative study, some tools, such as the ArcGIS platform, space syntax Depthmap modeling and street view semantic analysis, are employed. A quantitative study is further carried out using the correlation analysis method to analyze the relationship between the external characteristic elements and internal constituent elements of spatial vitality of commercial blocks and explore the effects of different factors on the spatial vitality of commercial blocks when these factors are interacting with each other.
Balancing Wellbeing and Responsibility: CSR’s Role in Mitigating Burnout in Hospitality under UN-SDGs
Authors: Ma Wei , Li Rita Yi Man , Manta Otilia , Alzuman Abad
Published: April 2024

This study investigates the effect of Corporate Social Responsibility (CSR) on burnout among employees in China’s hospitality industry, highlighting wellness as an essential driver of success and its correlation to the United Nations Sustainable Development Goals. It looks at CSR’s impact on stress, with employee happiness and resilience acting as mediators, whereas altruism is supposed to act as a moderator. This study collected data from various hospitality organizations across major cities in China over three phases through well-known scales. The findings of structural equation modeling show a negative relationship between CSR and burnout with the mediating effects of happiness and resilience moderated by altruism. The above findings highlight how CSR can reduce worker fatigue while creating a positive work environment within the hospitality sector. This study enriches theoretical knowledge and practical strategies for enhancing employee wellbeing, emphasizing the role of strategic CSR in creating a more sustainable and productive hospitality sector.
Evaluation of Symmetrical Face Pressure of EPB
Authors: Yaman Hasan Eray , Aksoy Cemalettin Okay
Published: April 2024

The content of this study combines city safety, optimum excavation situation, mining, geology, and civil engineering principles. Tunnel boring machines (TBM) are the most commonly used machines in the excavation of urban tunnels. These machines prevent the inward movement of the tunnel face and control the amount of settlement formed on the ground by applying pressure to the tunnel face. The most important question here is to determine the amount of pressure to be applied to the tunnel face. There are many widely accepted formulas used in the calculation of the face pressure and these formulas generally attempt to limit the settlements on the ground by using parameters such as groundwater level, overburden thickness, physical and mechanical properties of the surrounding rocks, etc. In this study, a new formula was developed. This new formula calculates the face pressure required to be applied by EPB to the tunnel face in order to prevent damage to a structure located on the route and within the area to be affected by tunnel excavation, instead of only preventing settlements on the surface. In the formula, produced within the scope of this study, in addition to other studies, 3D distances of the structure to which the deformation limitation will be made to prevent damage is also one of the parameters.
Removable Singularities of Harmonic Functions on Stratified Sets
Authors: Dairbekov Nurlan S. , Penkin Oleg M. , Savasteev Denis V.
Published: April 2024

There are deep historical connections between symmetry, harmonic functions, and stratified sets. In this article, we prove an analog of the removable singularity theorem for bounded harmonic functions on stratified sets. The harmonic functions are understood in the sense of the soft Laplacian. The result can become one of the main technical components for extending the well-known Poincaré–Perron’s method of proving the solvability of the Dirichlet problem for the soft Laplacian.
A Research on Multi-Index Intelligent Integrated Prediction Model of Catchment Pollutant Load under Data Scarcity
Authors: Miao Donghao , Gu Wenquan , Li Wenhui , Liu Jie , Hu Wentong , Feng Jinping , Shao Dongguo
Published: April 2024

Within a river catchment, the relationship between pollutant load migration and its related factors is nonlinear generally. When neural network models are used to identify the nonlinear relationship, data scarcity and random weight initialization might result in overfitting and instability. In this paper, we propose an averaged weight initialization neural network (AWINN) to realize the multi-index integrated prediction of a pollutant load under data scarcity. The results show that (1) compared with the particle swarm optimization neural network (PSONN) and AdaboostR models that prevent overfitting, AWINN improved simulation accuracy significantly. The R2 in test sets of different pollutant load models reached 0.51–0.80. (2) AWINN is effective in overcoming instability. With more hidden layers, the stability of the models’ outputs was stronger. (3) Sobol sensitivity analysis explained that the main influencing factors of the whole process were the flows of the catchment inlet and outlet, and main factors changed across seasons. The algorithm proposed in this paper can realize stably integrated prediction of pollutant load in the catchment under data scarcity and help to understand the mechanism that influences pollutant load migration.
Research on the Impact of Using a Combination of Rigid and Flexible Vegetation on Slope Hydrological Properties in Loess Regions
Authors: Tao Hu , Wang Fucui , Shi Xi , Bu Shilong , Bao Ziming , Zhang Dezhi , Xiong Lifeng
Published: April 2024

Slope vegetation is a key component of soil erosion control. Rigid vegetation improves slope stability, while flexible vegetation reduces water velocity, and the combination of both improves erosion resistance; however, there are few studies on how the combination of rigid and flexible vegetation affects the hydraulic characteristics of slope flow. In order to investigate the effect of this combination on the hydraulic characteristics of slopes, a mathematical model of the coefficient of resistance under the cover of rigid–flexible vegetation was established by using theoretical analysis and indoor tests, and the indoor tests were conducted with different rigid–flexible vegetation combinations (single-row interlocking (IS), double-row interlocking (IT), upstream rigid–downstream flexible (RF), and bare slope (BS)). The results showed that the rigid–flexible vegetation combination had a significant effect on the slope water flow. With the increase in flow, the water depth and flow velocity of slope flow showed an increasing trend, the flow velocity of the bare slope was significantly larger than that of the vegetation-covered slope, and the value of the water depth increment of the vegetation-covered slope was 0.086~0.22 times that of the bare slope. The Reynolds number showed a good linear increasing relationship with flow rate, and with the gradual increase in flow rate and slope, the flow pattern gradually changed from slow flow to fast flow. When the slope was 2°, the drag coefficient increased and then decreased. The pattern of erosion reduction capacity was IS > RF > IT > BS. The results of this study provide strong theoretical support for understanding the mechanism of vegetation-controlled erosion and provide scientific guidance for optimizing vegetation design in the Loess Plateau region.
Deep Learning Methods of Satellite Image Processing for Monitoring of Flood Dynamics in the Ganges Delta, Bangladesh
Authors: Lemenkova Polina
Published: April 2024

Mapping spatial data is essential for the monitoring of flooded areas, prognosis of hazards and prevention of flood risks. The Ganges River Delta, Bangladesh, is the world’s largest river delta and is prone to floods that impact social–natural systems through losses of lives and damage to infrastructure and landscapes. Millions of people living in this region are vulnerable to repetitive floods due to exposure, high susceptibility and low resilience. Cumulative effects of the monsoon climate, repetitive rainfall, tropical cyclones and the hydrogeologic setting of the Ganges River Delta increase probability of floods. While engineering methods of flood mitigation include practical solutions (technical construction of dams, bridges and hydraulic drains), regulation of traffic and land planning support systems, geoinformation methods rely on the modelling of remote sensing (RS) data to evaluate the dynamics of flood hazards. Geoinformation is indispensable for mapping catchments of flooded areas and visualization of affected regions in real-time flood monitoring, in addition to implementing and developing emergency plans and vulnerability assessment through warning systems supported by RS data. In this regard, this study used RS data to monitor the southern segment of the Ganges River Delta. Multispectral Landsat 8-9 OLI/TIRS satellite images were evaluated in flood (March) and post-flood (November) periods for analysis of flood extent and landscape changes. Deep Learning (DL) algorithms of GRASS GIS and modules of qualitative and quantitative analysis were used as advanced methods of satellite image processing. The results constitute a series of maps based on the classified images for the monitoring of floods in the Ganges River Delta.