bluuebunny/crossref_metadata_2025 huggingface dataset:
Plants of Conservation Interest in a Protected Area: A Case Study of the Gran Sasso and Monti Della Laga National Park (Central Italy)
Authors: Conti Fabio , Tinti Daniela , Bartolucci Fabrizio
Published: June 2024

The National Park of Gran Sasso and Monti della Laga (PNGSL) is located in Central Italy and covers an area of 143.311 ha across three administrative regions (Abruzzo, Marche, and Lazio). It is the protected area hosting the highest number of vascular plants in both Europe and the Mediterranean basin. The plan of the park recognizes the need to establish a list of plants of conservation interest to prioritize for protection. The aim of this study is to identify plants (vascular and bryophytes) for inclusion on a protection list, taking into account their phytogeographic importance as well as the threat of extinction, and subsequently propose an original categorization (protection classes) suggesting specific conservation actions and measures. We used original criteria to select plants of conservation interest among the 2678 plant taxa listed in the national park. We identified 564 vascular plant species and subspecies (including nine hybrids) and one bryophyte to be included in the proposed protection list. The case study of the PNGSL could be a model for other protected areas.
Frequency-Dependent Dielectric Permittivity and Water Permeability in Ordered Mesoporous Silica-Grafted Fluorinated Polyimides
Authors: Son Jaemin , Park Hwon , Kim Minju , Park Jae Hui , Nam Ki-Ho , Bae Jin-Seok
Published: June 2024

Polymers with a low dielectric constant (Dk) are promising materials for high-speed communication networks, which demand exceptional thermal stability, ultralow Dk and dissipation factor, and minimum moisture absorption. In this paper, we prepared a series of novel low-Dk polyimide films containing an MCM-41-type amino-functionalized mesoporous silica (AMS) via in situ polymerization and subsequent thermal imidization and investigated their morphologies, thermal properties, frequency-dependent dielectric behaviors, and water permeabilities. Incorporating 6 wt.% AMS reduced the Dk at 1 MHz from 2.91 of the pristine fluorinated polyimide (FPI) to 2.67 of the AMS-grafted FPI (FPI-g-AMS), attributed to the free volume and low polarizability of fluorine moieties in the backbone and the incorporation of air voids within the mesoporous AMS particles. The FPI-g-AMS films presented a stable dissipation factor across a wide frequency range. Introducing a silane coupling agent increased the hydrophobicity of AMS surfaces, which inhibited the approaching of the water molecules, avoiding the hydrolysis of Si–O–Si bonds of the AMS pore walls. The increased tortuosity caused by the AMS particles also reduced water permeability. All the FPI-g-AMS films displayed excellent thermooxidative/thermomechanical stability, including a high 5% weight loss temperature (>531 °C), char residue at 800 °C (>51%), and glass transition temperature (>300 °C).
Influence of Yarn and Fabric Properties on Mechanical Behavior of Polymer Materials and Its Retention over Time
Authors: Salopek Čubrić Ivana , Čubrić Goran
Published: June 2024

The mechanical properties of textile materials play a crucial role in determining their comfort, functionality, performance, safety, and aesthetics. Understanding and optimizing these properties is essential to meet consumer demands. Key aspects of mechanical properties, such as surface roughness, abrasion resistance, and compression, have a significant impact on the touch and durability of the material, as demonstrated by various research studies. This study focuses on analyzing the mechanical properties of materials produced of different polymer yarns and their changes under combined aging factors. The findings emphasize the significance of textile abrasion resistance and surface roughness measurement, particularly for aged materials. Although the use of recycled polyester yarn is sustainable and offers advantages such as higher tensile strength, the results have shown that the use of conventional polyester yarn is more advantageous overall as it has higher abrasion resistance, a smoother surface texture, and better elasticity retention after aging. The insights presented are vital for designing high-performance sportswear, which is crucial in today’s competitive environment.
Advances in Functional Rubber and Elastomer Composites
Authors: Alam Md Najib
Published: June 2024

Two crucial innovations—mastication and vulcanization—have revolutionized the use of rubber in our daily lives [...]
Whoever I Am: On the Quality of Life
Authors: Masciandaro Nicola
Published: June 2024

What is the relation between quantification and the mysterious question of identity? What order of quality is proper to the inexplicable fact that one is oneself? Starting with an examination of the ontological blind spots of counting, this essay investigates the priority of quality over quantity, in connection with the spiritual nature of life understood as the spontaneous and infinitely evolving question of itself. It argues, in face of the forces of quantophrenia and numerocracy, for the importance of recognizing the essentially serial and apophatic structure of identity, the existential sense that all entities are the living question of themselves. As such, no individual may be considered as merely a part of reality. Each is, no less, the totality.
Dependence Modelling for Heavy-Tailed Multi-Peril Insurance Losses
Authors: Yan Tianxing , Lu Yi , Jeong Himchan
Published: June 2024

The Danish fire loss dataset records commercial fire losses under three insurance coverages: building, contents, and profits. Existing research has primarily focused on the heavy-tail behaviour of the losses but ignored the relationship among different insurance coverages. In this paper, we aim to model the aggregate loss for all three coverages. To study the pairwise dependence of claims from all types of coverage, an independent model, a hierarchical model, and some copula-based models are proposed for the frequency component. Meanwhile, we applied composite distributions to capture the heavy-tailed severity component. It is shown that consideration of dependence for the multi-peril frequencies (i) significantly enhances model goodness-of-fit and (ii) provides more accurate risk measures of the aggregated losses for all types of coverage in total.
Using Geostationary Satellite Observations to Improve the Monitoring of Vegetation Phenology
Authors: Lu Jun , He Tao , Song Dan-Xia , Wang Cai-Qun
Published: June 2024

Geostationary satellite data enable frequent observations of the Earth’s surface, facilitating the rapid monitoring of land covers and changes. However, optical signals over vegetation, represented by the vegetation index (VI), exhibit an anisotropic effect due to the diurnal variation in the solar angle during data acquisition by geostationary satellites. This effect, typically characterized by the bi-directional reflectance distribution function (BRDF), can introduce uncertainties in vegetation monitoring and the estimation of phenological transition dates (PTDs). To address this, we investigated the diurnal variation in the normalized difference vegetation index (NDVI) with solar angles obtained from geostationary satellites since the image had fixed observation angles. By establishing a temporal conversion relationship between instantaneous NDVI and daily NDVI at the local solar noon (LSNVI), we successfully converted NDVIs obtained at any time during the day to LSNVI, increasing cloud-free observations of NDVI by 34%. Using different statistics of the time series vegetation index, including LSNVI, daily averaged NDVI (DAVI), and angular corrected NDVI (ACVI), we extracted PTD at five typical sites in China. The results showed a difference of up to 41.5 days in PTD estimation, with the highest accuracy achieved using LSNVI. The use of the proposed conversion approach, utilizing time series LSNVI, reduced the root mean square error (RMSE) of PTD estimation by 9 days compared with the use of actual LSNVI. In conclusion, this study highlights the importance of eliminating BRDF effects in geostationary satellite observations and demonstrates that the proposed angular normalization method can enhance the accuracy of time series NDVI in vegetation monitoring.
LUFFD-YOLO: A Lightweight Model for UAV Remote Sensing Forest Fire Detection Based on Attention Mechanism and Multi-Level Feature Fusion
Authors: Han Yuhang , Duan Bingchen , Guan Renxiang , Yang Guang , Zhen Zhen
Published: June 2024

The timely and precise detection of forest fires is critical for halting the spread of wildfires and minimizing ecological and economic damage. However, the large variation in target size and the complexity of the background in UAV remote sensing images increase the difficulty of real-time forest fire detection. To address this challenge, this study proposes a lightweight YOLO model for UAV remote sensing forest fire detection (LUFFD-YOLO) based on attention mechanism and multi-level feature fusion techniques: (1) GhostNetV2 was employed to enhance the conventional convolution in YOLOv8n for decreasing the number of parameters in the model; (2) a plug-and-play enhanced small-object forest fire detection C2f (ESDC2f) structure was proposed to enhance the detection capability for small forest fires; (3) an innovative hierarchical feature-integrated C2f (HFIC2f) structure was proposed to improve the model’s ability to extract information from complex backgrounds and the capability of feature fusion. The LUFFD-YOLO model surpasses the YOLOv8n, achieving a 5.1% enhancement in mAP and a 13% reduction in parameter count and obtaining desirable generalization on different datasets, indicating a good balance between high accuracy and model efficiency. This work would provide significant technical support for real-time forest fire detection using UAV remote-sensing images.
Spatial Spectrum Estimation of Weak Scattering Wave Signal in Range-Doppler Domain
Authors: Xu Hang , Ma Hong , Wang Li , Jin Jiang , Zhang Hua , Liu Xiaodong
Published: June 2024

How to enhance the desired signal with low signal-to-noise ratio (SNR) is a difficult problem in the estimation process of the direction-of-arrival (DOA) of the target scattering wave signal. In this paper, the feasibility of spatial spectrum estimation in the Range-Doppler (RD) domain is analyzed in principle, and the SNR gain expression of weak scattering wave signal is derived when constructing multi-snapshots virtual array data. On this basis, the mutual eigenvector singular value decomposition (MESVD) method based on RD domain mode excitation is proposed, which can robustly and effectively estimate the direction of the coherent weak signals. Simulation experiments verify that the RD domain spectral estimation method has the ability to simultaneously obtain the direction of multiple weak target scattering waves, and the direction-finding accuracy can reach the Cramer–Rao bound (CRB) of conventional spectral estimation method. The results of Monte Carlo experiments show that the root-mean-square-error (RMSE) of azimuth estimation of RD domain spatial spectrum estimation method is 5.76° lower than that of a conventional multiple signal classification (MUSIC) method. In addition, the practicability of the proposed method is demonstrated by comparing the DOA estimation results of a set of real data with Automatic Dependent Surveillance-Broadcast (ADS-B) data.
IfCMD: A Novel Method for Radar Target Detection under Complex Clutter Backgrounds
Authors: Zhang Chenxi , Xu Yishi , Chen Wenchao , Chen Bo , Gao Chang , Liu Hongwei
Published: June 2024

Traditional radar target detectors, which are model-driven, often suffer remarkable performance degradation in complex clutter environments due to the weakness in modeling the unpredictable clutter. Deep learning (DL) methods, which are data-driven, have been introduced into the field of radar target detection (RTD) since their intrinsic non-linear feature extraction ability can enhance the separability between targets and the clutter. However, existing DL-based detectors are unattractive since they require a large amount of independent and identically distributed (i.i.d.) training samples of target tasks and fail to be generalized to the other new tasks. Given this issue, incorporating the strategy of meta-learning, we reformulate the RTD task as a few-shot classification problem and develop the Inter-frame Contrastive Learning-Based Meta Detector (IfCMD) to generalize to the new task efficiently with only a few samples. Moreover, to further separate targets from the clutter, we equip our model with Siamese architecture and introduce the supervised contrastive loss into the proposed model to explore hard negative samples, which have the targets overwhelmed by the clutter in the Doppler domain. Experimental results on simulated data demonstrate competitive detection performance for moving targets and superior generalization ability for new tasks of the proposed method.
Dual-Polarized Dipole Antenna with Wideband Stable Radiation Patterns Using Artificial Magnetic Conductor Reflector
Authors: Lin Xianjing , Mai Jielin , He Hongjun , Zhang Yao
Published: June 2024

This paper presents a wideband dual-polarized dipole antenna structure operating at 1.7–3.8 GHz (76.4%). For a traditional 4G dipole antenna that covers the band 1.71–2.69 GHz, it is difficult to maintain the satisfactory impedance matching and normal stable radiation patterns within the 5G sub-6 GHz band 3.3–3.8 GHz, mainly due to the fixed antenna height no longer being a quarter-wavelength. To solve this, a connected-ring-shaped metasurface structure is proposed and deployed to operate as an artificial magnetic conductor (AMC). As a result, stable antenna radiation patterns are obtained within the whole band 1.7–3.8 GHz. For verification, this wideband dipole antenna using AMC is implemented and tested. The measured results show that the proposed antenna has an impedance bandwidth of 80.7% (1.7–4.0 GHz). It has an average measured in-band realized gain of 7.0±1.0 dBi and a stable 70±5 half power beam width (HPBW) within the 4G/5G-sub 6GHz bands 1.71–2.69 GHz and 3.3–3.8 GHz.
The Impact of the COVID-19 Pandemic on the Immobilized Lifestyle of Institutionalized Older Persons: An Empirical Study
Authors: Coman Claudiu , Bărbat Carmen , Goian Cosmin , Bularca Maria Cristina , Andrioni Felicia , Popp Lavinia , Netedu Adrian , Burlacu Mihai , Bălăuță Dănuț , Talpă Nicolae , Popa Bogdan
Published: June 2024

Our study aimed to examine how care centers for older persons acted and adapted during the COVID-19 pandemic period by considering the opinions of the beneficiaries, employees, and managers of such centers. The research was conducted between February and June 2022, and we used a mixed-methods approach. For the quantitative research, we applied a questionnaire to 430 institutionalized older persons from Timis County, Romania. For the qualitative analysis, we conducted interviews with 31 institutionalized older persons, 7 employees, and 4 managers. Most institutionalized older persons were mainly satisfied with their lives in the care centers. The main difficulties they faced were the impossibility of being close to loved ones and the difficulty of adapting to the living conditions within the center. Additionally, the older persons were satisfied with their interactions with the staff of the care centers. The conducted research provides a view of the lifestyle of older persons in care centers during the pandemic. It highlights their struggles and can be used as a reference point for further improvement of the lifestyle of older persons within care centers.
Glutamic-N,N-Diacetic Acid as an Innovative Chelating Agent in Microfertilizer Development: Biodegradability, Lettuce Growth Promotion, and Impact on Endospheric Bacterial Communities
Authors: Galieva Gulnaz , Kuryntseva Polina , Selivanovskaya Svetlana , Brusko Vasiliy , Garifullin Bulat , Dimiev Ayrat , Galitskaya Polina
Published: June 2024

The search for new biodegradable fertilizers to increase the productivity of agricultural plants is an urgent task. In this study, a complex microfertilizer was developed based on a chelating agent—glutamic-N,N-diacetic acid (GLDA). The evaluation encompassed assessments of biodegradability and effectiveness in fostering lettuce plant growth in hydroponic and conventional soil settings. The impact on endospheric bacteria, a sensitive indicator, was also examined. Results indicated a 59.8% degradation rate of the GLDA complex on the 28th day. The most notable positive effects were observed in above-ground plant biomass, with a 4.6-fold increase for hydroponics and 1.5 to 1.8-fold increases for root and foliar treatments in soil. In hydroponics, GLDA-treated plants showed 24 and 45 operational taxonomic units (OTUs) for leaves and 272 and 258 for roots (GLDA-treated and control plants). In soil, the OTU counts were 270 and 101, 221 and 111, and 198 and 116 in the leaves and roots of GLDA-treated and control plants (under root and foliar treatments), respectively. Non-metric multidimensional scaling (NMDS) and Indicator Species Analysis (ISA) demonstrated significant distinctions in endospheric communities between substrates (hydroponics and soil) in the presence of GLDA. Importantly, GLDA use simplified the composition of endospheric bacterial communities.
Integration of Smart City Technology and Business Model Innovation
Authors: Liu Zhen , Liu Yixin , Osmani Mohamed
Published: June 2024

At present, the progress of business model stages supported by a variety of technology categories may unclear, and the integration of technology application and business model innovation (BMI) is hard due to operational practices in various industries and research areas, which block the view of the integration of smart city technology (SCT) and BMI for further development. Thus, this paper aims to explore the current research on the integration of SCT and BMI and identify the current research status and hotspots, assisting in indicating the status of these technologies in the business model stages in order to determine future trends, and adopts a mixed research methodology including a macro-quantitative method based on bibliometrics and a micro-qualitative method using content analysis. The results reveal a 17-year (2007 to 2023) integration of SCT and BMI enhanced by cloud computing, big data, Internet of Things, and artificial intelligence in recent years, with the most current studies focusing on the ideation and design stages of the business model stages with an emphasis on using digital capabilities to refine, formulate, and design the corresponding business model while defining the strategy through internal and external factors. Interestingly, Industry 4.0 and digital servitization are currently the key trends.
How to Leverage Digital Sustainability Orientation to Promote Environmentally Sustainable Practices of Manufacturing Enterprises in China
Authors: Zhang Jinshan , Liu Man
Published: June 2024

The promotion of high-quality, environmentally sustainable practices in enterprises in the digital age has become an important topic in business and academic circles. In this study, by employing a perspective combining digital orientation (DO) and sustainability commitment orientation (SCO), the concept of digital sustainability orientation (DSO) is presented, and digital green capability (DGC) is introduced as the mediating variable. Moreover, the driving mechanism model of corporate environmental sustainability practice (ESP) is constructed, and the moderating role of environmental scanning (ES) is taken into consideration. Using two sets of research data from 353 manufacturing enterprises in China, the empirical test results show that DSO has a significant role in improving ESP, and DGC is important in mediating between DSO and ESP. ES acts as a moderating variable between DSO and DGC and further moderates the mediating role of DGC between DSO and EPS; that is, the stronger the ES, the more significant the mediating effect of DGC. The conclusion of this study broadens the application scope of strategic orientation theory in the study of digital sustainability and has theoretical and practical implications for exploring the development of DGC and the dynamic mechanism of ESP.
Tripartite Social Roles of Urban Underground Pipeline Informatization in China
Authors: Xie Zhiqiang , Liu Yun , Feng Yuyun , Zhao Lei , Fu Xingfeng , Jiang Fengshan , Zhai Zhengang , Zheng Daoyang , Lian Junyu
Published: June 2024

Urban underground pipelines (UUPs) are critical infrastructure, and their safe operation has become a key concern in Chinese society. Currently, the tripartite social roles of the local people’s government, pipeline management departments, and the public are crucial in the informatization of urban underground pipelines. In this study, a survey was conducted among 126 professionals and technical personnel involved in underground pipeline informatization across eight cities in different regions of China. A quantitative weighted evaluation model was established using the Project Quantitative Index (PQI) and principal component analysis (PCA) to investigate the value of the tripartite aforementioned social groups in UUP informatization. The results indicate: (1) There is a significant positive correlation between the tripartite social roles and the promotion of UUP informatization. Moreover, the indicators with the highest PQI value are “Establishment of UUP informatization management departments” and “Support the work of the UUP informatization industry association” under the role of the local people’s government. (2) The informatization work of underground pipelines in different cities is affected differently by the tripartite social roles. This suggests that the local people’s government and professional management departments in different cities can proactively leverage their unique advantages in UUP informatization based on their specific circumstances. (3) PCA results showed that the indicators related to the public carried significant weight, indicating that the public also played an important role in UUP informatization. The degree of UUP informatization in the eight studied cities is ranked as follows: Guangzhou > Beijing > Qingdao > Kunming > Shanghai > Chengdu > Wuhan > Sian. This paper further discusses the unique roles and contributions of the tripartite social groups in UUP informatization, aiming to provide decision support for the future construction, management, and safe operation and maintenance of urban underground pipelines in China.
Decoding the Fashion Quotient: An Empirical Study of Key Factors Influencing U.S. Generation Z’s Purchase Intention toward Fast Fashion
Authors: Wojdyla Weronika , Chi Ting
Published: June 2024

With a reputation for offering stylish and on-trend clothing at pocket-friendly prices, fast fashion brands resonate with the economic realities faced by many Gen Z consumers. Gen Z consumers are not just a target consumer market but also a driving force shaping the future of the fashion industry. Their preferences, values, and behaviors impact trends, reshape retail practices, and influence the overall trajectory of the fashion landscape. The evolving discourse surrounding sustainability and conscious consumerism suggests that the future may see a recalibration of the fashion landscape, with Gen Z at the forefront of demanding more responsible and transparent practices from the fashion industry. Therefore, this study aimed to identify the factors significantly influencing U.S. Gen Z consumers’ intentions to purchase fast fashion. Building on the theory of planned behavior, a research model for understanding Gen Z consumers’ intentions to buy fast fashion is proposed. Attitude, subjective norms, perceived behavioral control, environmental knowledge, need for uniqueness, materialism, and fashion leadership are investigated as predictors. Moreover, we examined how environmental knowledge, need for uniqueness, materialism, and fashion leadership affect Gen Z consumers’ attitudes toward fast fashion products. A total of 528 eligible responses were collected for analysis through a Qualtrics online survey. The proposed model’s psychometric properties were evaluated, and the hypotheses were tested using the multiple regression method. It was found that attitude, perceived consumer effectiveness, environmental knowledge, and fashion leadership significantly influenced Gen Z consumers’ intentions to shop fast fashion. Additionally, Gen Z consumers’ environmental knowledge, need for uniqueness, and fashion leadership significantly affect their attitudes toward fast fashion. The research model demonstrated strong explanatory power, explaining 68.9% of the variance in Gen Z consumers’ purchase intention toward fast fashion.
Return Migration and Reintegration in Serbia: Are All Returnees the Same?
Authors: Langović Milica , Djurkin Danica , Krstić Filip , Petrović Marko , Ljakoska Marija , Kovjanić Aleksandar , Vukašinović Sandra
Published: June 2024

The Republic of Serbia is traditionally a country of emigration, especially since the 1960s. As a result of this emigration, return migration has become an increasingly intensive migratory process in the 21st century. This study aims to examine the factors behind return migration, as well as to explore the characteristics of the reintegration process in Serbia, including the sustainability of return. This paper is based on a survey (N = 172) and interviews (N = 20) conducted with return migrants in Serbia. The research findings point to the diversity of the return migration factors, among which a longing for the country of origin is singled out as the most important. Regarding the reintegration process, this study highlights several differences that are apparent between retired returnees on the one hand and other returnees (students, employed, unemployed) on the other. The results show that the satisfaction with quality of life upon return is higher among older returnees and that the satisfaction with quality of life decreases as the respondents’ level of education increases. It is also found that the sustainability of return is connected to the life satisfaction and that respondents who plan to migrate again are the least satisfied with the quality of life compared to those who plan to stay and those who have not decided yet. This paper provides insights into some of the critical elements of the return migration and reintegration process in Serbia. Since return migrants can contribute to sustainable socio-economic development due to their human, social and financial capital, this study may be of relevance to the development of strategies and the implementation of policies in the domain of migration governance.
Spatio-Temporal Evolution and Driving Factors of Tourism Economic Resilience in the Yili River Valley
Authors: Zhao Pengkai , Sun Haojie , Zhao Xinyu , Song Changying , Xu Xueting
Published: June 2024

The tourism economy plays an essential role in supporting and driving tourism development. Therefore, studying its resilience is crucial for promoting sustainable and high-quality tourism development. The purpose of this study is to construct a tourism economic resilience evaluation index system and assess the tourism economic resilience of 10 counties and cities in the Ili River Valley from 2010 to 2019 using the entropy weight TOPSIS method. The results show that (1) the tourism economic resilience shows a “W”-shaped time-series dynamic development trend, especially a decline in 2012–2013 and 2015–2016; (2) the spatial pattern shows a non-equilibrium characteristic, with the northwestern part of the valley represented by Yining City showing a high level of resilience, and the central to southeastern counties and cities showing a lower level of resilience; (3) the spatio-temporal evolution steadily points to “northwest–southeast”, and there are five toughness convergence clubs, with obvious stability and neighborhood effects; (4) and the analysis of the driving factors shows that the number of employees in the tertiary industry, especially the input of high-quality talents, is crucial to improving the quality of services, strengthening the ability to withstand risks and the potential for development, and its impact is significant. These results provide an important reference for the formulation of tourism development strategies and promote the sustainable development of tourism.
The Resilience of the Built Environment to Flooding: The Case of Alappuzha District in the South Indian State of Kerala
Authors: Choorapulakkal Afeef Abdurahman , Madandola Muhammed Gbolahan , Al-Kandari Amina , Furlan Raffaello , Bayram Goze , Mohamed Hassan Abdelgadir Ahmed
Published: June 2024

In recent years, floods and climate-induced cataclysms have caused significant annual damage to livelihoods worldwide, with limited research on their vulnerability, impact, resilience, and long-term adaptation strategies in developing countries. In the South Indian State of Kerala, the major flood in 2018 caused immense economic losses in the low-lying and densely populated Alappuzha District. While the region has a heightened risk of periodic flooding, the considerable destruction of buildings and infrastructure highlights the need for effective solutions for flood resilience in the existing housing stock and new construction. In this context, this study examines flood resilience in the built environment of Alappuzha, focusing on flood vulnerability, building practices, and potential approaches suitable for the region that the current literature does not address. This study employs a qualitative research approach to understand current trends in adaptation strategies and the influencing socioeconomic and cultural factors. The study employs various data collection methods, including interviews, site observations, and content analyses of existing government reports, journal articles, and popular media sources. The findings indicate that although there are three types of established flood resilience techniques (static elevated, floating, and amphibious structures), their suitability for the low-lying areas of Alappuzha depends on the geographic, climatic, socioeconomic, and cultural contexts. Stilted houses have become the most common construction method, in response to climatic and socioeconomic conditions. In addition, the findings highlight the bounce-forth resilience quality of amphibious building techniques and suggest further exploration by integrating them with local technologies and materials. The study concludes that a comprehensive approach is needed that integrates traditional and modern knowledge and practices in disaster risk reduction and management to enhance the resilience of the built environment to flooding.
Toward Sustainable Biomanufacturing: A Feasibility Index for Silicon Carbide Production from Rice Waste
Authors: Gualandri Fabio , Kuzior Aleksandra
Published: June 2024

Silicon carbide, known for its distinct chemical and physical properties, is increasingly recognized as a critical material in sectors such as energy, space, and defense. Traditional production methods like the Acheson process are energy-intensive and costly, both in terms of investment and maintenance. Additionally, the concentrated nature of its manufacturing can lead to supply bottlenecks, hindering technological progress in key areas. To address these issues, this paper proposes a circular economy approach to silicon carbide production, leveraging the ecological challenge of rice waste disposal to create a new source of silica materials. It includes an evaluation of the economic and technological feasibility of this method and introduces a multidimensional composite index to identify potential early adopters for large-scale implementation. This innovative approach not only reduces reliance on critical minerals but also offers a solution to managing agricultural waste.
Big Data Infrastructure and Corporate ESG Performance: Evidence from Listed Chinese Manufacturing Companies
Authors: Wang Minjuan , Zhang Dingsheng
Published: June 2024

This paper investigates the impact of big data on firms’ environmental, social, and governance (ESG) performance. We provide quasi-experimental estimates using a unique quasi-natural experiment: the national policy of introducing Big Data Pilot Zones (BDPZs) in Chinese cities. Our analysis exploits data on firm-level ESG performance with a standard difference-in-differences empirical strategy. We find that big data has a significant positive impact on corporate ESG performance. The effect is more prominent for companies in non-heavily polluting industries, with a lower level of digital transformation, and those not rigorously audited. Analysis of the mechanisms shows that big data enhances the transparency of corporate information. Facing external supervisory pressure, companies tend to enhance their ESG performance to mitigate reputational risks.
Study on the Particle Strength and Crushing Patterns of Coal Gangue Coarse-Grained Subgrade Fillers
Authors: Zhang Zong-Tang , Xu Yang-Xun , Liao Ji-Biao , Liu Shun-Kai , Liu Ze , Gao Wen-Hua , Yi Li-Wei
Published: June 2024

Coal gangue, as a subgrade filler, is of great significance for the sustainable development of the economy, society, and environment. Particle crushing tests were conducted on coal gangue coarse-grained subgrade filler (CGSF) under uniaxial compression conditions, and the relationships between load and displacement, crushing strength, failure pattern, and gradation after crushing were analyzed. A new visual analysis method for the crushing patterns of particles was provided through image analysis, and a new gradation equation based on the traditional fractal model was proposed to describe the crushed particles. The results indicate that as the particles are gradually compressed the sharp corners of particles are gradually crushed and fall off, causing the relationship curve between load and displacement to fluctuate and grow, and particle splitting failure leads to the approximately linear growth curve. Moreover, the distribution of particle crushing strength for coal gangue is between 3.02 and 11.11 MPa, and the crushing probability and the applied load well satisfy the Weibull distribution function. Furthermore, as the particle size decreases, the shapes of crushed coal gangue particles are block, flaky, acicular, and powder, and the particles with a size greater than 5 mm are mainly flaky. In addition, comparative analysis shows that the new gradation equation can better describe the gradation of coal gangue fragments after crushing.
Advancements in Soil Organic Carbon Mapping and Interpolation Techniques: A Case Study from Lithuania’s Moraine Plains
Authors: Volungevicius Jonas , Žydelis Renaldas , Amaleviciute-Volunge Kristina
Published: June 2024

Monitoring soil organic carbon (SOC) is essential for assessing the sustainability of soil usage. This study explores the spatial variability and mapping of SOC in Lithuania’s Nevėžis Plain using various interpolation methods, with an emphasis on understanding the impacts of soil typological units, moisture regimes, and erosion on SOC distribution. A total of 275 soil samples were collected from agricultural croplands at depths of 0–10 cm, supplemented by 38 samples from previous studies. The SOC map was created based on the contours of the Lithuanian soil geodatabase. Statistical analysis revealed that the distribution of SOC in the studied area was significantly influenced by soil moisture and the degree of erosion. Based on these findings, SOC mapping was conducted according to the contours of Lithuanian soils. Comparing the interpolation methods that were analyzed, it was found that the kriging, RBF, and EBK methods fail to adequately capture the minimum and maximum values of SOC, while the IDW fails to adequately capture only the minimum values. In summary, the integrated geographical approach is complex but applicable to SOC mapping. This method facilitates the creation of adaptable SOC maps that are both geographically and pedologically informed. Key principles to apply this approach for future research and practical application should include establishing a statistically reliable data foundation, categorizing samples based on contrasting soil moisture regime, degrees of erosion, and land use patterns, and developing contouring principles along with a criteria algorithm that enables accurate spatial interpolation of average SOC values.
Assessing the Role of HRM and HRD in Enhancing Sustainable Job Performance and Innovative Work Behaviors through Digital Transformation in ICT Companies
Authors: Lou Yuanyuan , Hong Ahreum , Li Yannan
Published: June 2024

In the era of Industry 4.0, digital transformation has become a cornerstone for modern organizations, fundamentally altering how businesses operate and compete. This study delves into the impact of digital transformation on human resource management (HRM), human resource development (HRD), and employees’ innovative work behaviors and job performance in a rapidly evolving business environment. In conducting a survey among 391 employees from information and communication technology (ICT) companies in China, structural equation modeling was employed to analyze the data. The findings reveal a correlation between digital transformation and innovative work behaviors and job performance, with HRM and HRD playing partial mediating roles. Digital transformation not only optimizes work processes and enhances productivity but also fosters the innovation of business models and processes. Moreover, the research indicates the critical importance of implementing efficient digital systems and processes in promoting an organizational culture of innovation and enhancing employees’ innovative capabilities. Thus, digital transformation is seen as a pivotal strategic tool, altering not just the modus operandi of organizations but also influencing employee behavior and performance.
Design and Optimization of a Mid-Field Wireless Power Transfer System for Enhanced Energy Transfer Efficiency
Authors: Khan Daud , Ahmad Ashfaq , Choi Dong-you
Published: June 2024

Mid-field wireless power transfer (WPT) offers a compelling solution for delivering power to miniature implantable medical devices deep within the human body. Despite its potential, the current power delivery levels remain constrained, and the design of a compact source structure to focus the transmitter field on such implants presents significant challenges. In this paper, a novel miniaturized transmitter antenna operating at 1.71 GHz is proposed. Leveraging the antenna proximity-coupled feeding technique, we achieve optimal current distribution for efficient power transfer. Additionally, a receiver integrated within the human body is proposed, comprising a slotted ground and a meandering slotted radiating element. This receiver is excited via a coaxial feedline with a truncated ground. Our findings demonstrate wireless power transfer of −23 dB (0.501%) at a distance of 30 mm between the transmitter and receiver, alongside a peak gain of −20 dB with an impedance bandwidth of 39.61%. These results highlight promising advancements in enhancing energy transfer efficiency for deep-implant applications.
Fixed Point Method for Nonlinear Fractional Differential Equations with Integral Boundary Conditions on Tetramethyl-Butane Graph
Authors: Nieto Juan J. , Yadav Ashish , Mathur Trilok , Agarwal Shivi
Published: June 2024

Until now, little investigation has been done to examine the existence and uniqueness of solutions for fractional differential equations on star graphs. In the published articles on the subject, the authors used a star graph with one junction node that has edges with the other nodes, although there are no edges between them. These graph structures do not cover more generic non-star graph structures; they are specific examples. The purpose of this study is to prove the existence and uniqueness of solutions to a new family of fractional boundary value problems on the tetramethylbutane graph that have more than one junction node after presenting a labeling mechanism for graph vertices. The chemical compound tetramethylbutane has a highly symmetrical structure, due to which it has a very high melting point and a short liquid range; in fact, it is the smallest saturated acyclic hydrocarbon that appears as a solid at a room temperature of 25 °C. With vertices designated by 0 or 1, we propose a fractional-order differential equation on each edge of tetramethylbutane graph. Employing the fixed-point theorems of Schaefer and Banach, we demonstrate the existence and uniqueness of solutions for the suggested fractional differential equation satisfying the integral boundary conditions. In addition, we examine the stability of the system. Lastly, we present examples that illustrate our findings.
Multilevel Algorithm for Large-Scale Gravity Inversion
Authors: Cao Shujin , Chen Peng , Lu Guangyin , Mao Yajing , Zhang Dongxin , Deng Yihuai , Chen Xinyue
Published: June 2024

Surface gravity inversion attempts to recover the density contrast distribution in the 3D Earth model for geological interpretation. Since airborne gravity is characterized by large data volumes, large-scale 3D inversion exceeds the capacity of desktop computing resources, making it difficult to achieve the appropriate depth/lateral resolution for geological interpretation. In addition, gravity data are finite and noisy, and their inversion is ill posed. Especially in the absence of a priori geological information, regularization must be introduced to overcome the difficulty of the non-uniqueness of the solutions to recover the most geologically plausible ones. Because the use of Haar wavelet operators has an edge-preserving property and can preserve the sensitivity matrix structure at each level of the multilevel method to obtain faster solvers, we present a multilevel algorithm for large-scale gravity inversion solved by the re-weighted regularized conjugate gradient (RRCG) algorithm to reduce the inversion computational resources and improve the depth/lateral resolution of the inversion results. The RRCG-based multilevel inversion was then applied to synthetic cases and airborne gravity data from the Quest-South project in British Columbia, Canada. Results from synthetic models and field data show that the RRCG-based multilevel inversion is suitable for obtaining density contrast distributions with appropriate horizontal and vertical resolution, especially for large-scale gravity inversions compared to Occam’s inversion.
Modeling a Multimodal Routing Problem with Flexible Time Window in a Multi-Uncertainty Environment
Authors: Ge Yan , Sun Yan , Zhang Chen
Published: June 2024

In this study, we extend the research on the multimodal routing problem by considering flexible time window and multi-uncertainty environment. A multi-uncertainty environment includes uncertainty regarding the demand for goods, the travel speed of the transportation mode, and the transfer time between different transportation modes. This environment further results in uncertainty regarding the delivery time of goods at their destination and the earliness and lateness caused by time window violations. This study adopts triangular fuzzy numbers to model the uncertain parameters and the resulting uncertain variables. Then, a fuzzy mixed integer nonlinear programming model is established to formulate the specific problem, including both fuzzy parameters and fuzzy variables. To make the problem easily solvable, this study employs chance-constrained programming and linearization to process the proposed model to obtain an equivalent credibilistic chance-constrained linear programming reformulation with an attainable global optimum solution. A numerical case study based on a commonly used multimodal network structure is presented to demonstrate the feasibility of the proposed method. Compared to hard and soft time windows, the numerical case analysis reveals the advantages of the flexible time window in reducing the total costs, avoiding low reliability regarding timeliness, and providing confidence level-sensitive route schemes to achieve flexible routing decision-making under uncertainty. Furthermore, the numerical case analysis verifies that it is necessary to model the multi-uncertainty environment to satisfy the improved customer requirements for timeliness and enhance the flexibility of the routing, and multimodal transportation is better than unimodal transportation when routing goods in an uncertain environment. The sensitivity analysis in the numerical case study shows the conflicting relationship between the economic objective and the reliability regarding the timeliness of the routing, and the result provides a reference for the customer to find a balance between them.
Does Digital Village Construction Empower the Green Allocation of Agricultural Water Resources?
Authors: Zhao Li , Chen Haining , Ding Xuhui , Chen Yifan
Published: June 2024

The development of digital villages plays a critical role in advancing green agriculture steadily and with high quality. This study measures the efficiency of agricultural water resource allocation using provincial-level rural data from 2011 to 2022 and a super Slacks-Based Measure model accounting for non-desirable outputs. Using the ArcGIS tool, this study illustrates the spatiotemporal patterns and provincial clustering of the green allocation of agricultural water resources. A spatial Durbin model further examines interactions between digital villages and water resource efficiency. Findings indicate the following: (1) The green water resource efficiency in China’s 30 provinces showed a gradual, steady increase, albeit with notable regional differences, particularly a “northwestern depression” in spatial distribution. (2) Moran’s I index indicates a strong positive spatial correlation between digital villages and green water resource efficiency, manifested as either “high–high” or “low–low” clustering. (3) The spatial Durbin model results demonstrate that digital villages enhance the green water resource efficiency of neighboring areas, a phenomenon referred to as the “Matthew effect”. (4) Different aspects of digital village construction, operation, and lifestyle positively influence green water resource efficiency, while digital loops have a negative impact. Aligning resource allocation efficiency with the establishment of digital village infrastructure is paramount. This symbiotic relationship bolsters the structural foundation of agricultural production, optimizing resource utilization and fostering technological advancements in rural settings.
Grass–Endophyte Interactions and Their Associated Alkaloids as a Potential Management Strategy for Plant Parasitic Nematodes
Authors: Mwangi Nyambura G. , Stevens Mark , Wright Alistair J. D. , Edwards Simon G. , Hare Martin C. , Back Matthew A.
Published: June 2024

Claviceptaceous endophytic fungi in the genus Epichloë mostly form a symbiotic relationship with cool-season grasses. Epichloë spp. are capable of producing bioactive alkaloids such as peramines, lolines, ergot alkaloids, and indole-diterpenes, which protect the host plant from herbivory by animals, insects, and nematodes. The host also benefits from enhanced tolerance to abiotic stresses, such as salt, drought, waterlogging, cold, heavy metals, and low nitrogen stress. The bioactive alkaloids produced can have both direct and indirect effects towards plant parasitic nematodes. Direct interaction with nematodes’ motile stages can cause paralysis (nematostatic effect) or death (nematicidal effect). Indirectly, the metabolites may induce host immunity which inhibits feeding and subsequent nematode development. This review highlights the different mechanisms through which this interaction and the metabolites produced have been explored in the suppression of plant parasitic nematodes and also how the specific interactions between different grass genotypes and endophyte strains result in variable suppression of different nematode species. An understanding of the different grass–endophyte interactions and their successes and failures in suppressing various nematode species is essential to enable the proper selection of grass–endophyte combinations to identify the alkaloids produced, concentrations required, and determine which nematodes are sensitive to which specific alkaloids.