bluuebunny/crossref_metadata_2025 huggingface dataset:
Coastal Vulnerability Index (CVI) Assessment: Evaluating Risks Associated with Human-Made Activities along the Limassol Coastline, Cyprus
Authors: Theocharidis Christos , Doukanari Marina , Kalogirou Eleftheria , Christofi Demetris , Mettas Christodoulos , Kontoes Charalampos , Hadjimitsis Diofantos , Argyriou Athanasios V. , Eliades Marinos
Published: October 2024

Coastal risk assessment is crucial for coastal management and decision making, especially in areas already experiencing the negative impacts of climate change. This study aims to investigate the coastal vulnerability due to climate change and human activities in an area west of the Limassol district’s coastline, in Cyprus, on which there have been limited studies. Furthermore, an analysis is conducted utilising the Coastal Vulnerability Index (CVI) by exploiting eight key parameters: land cover, coastal slope, shoreline erosion rates, tidal range, significant wave height, coastal elevation, sea-level rise, and coastal geomorphology. These parameters were assessed utilising remote sensing (RS) data and Geographical Information Systems (GISs) along a 36.1 km stretch of coastline. The results exhibited varying risk levels of coastal vulnerability, mainly highlighting a coastal area where the Kouris River estuary is highly vulnerable. The study underscores the need for targeted coastal management strategies to address the risks associated with coastal erosion. Additionally, the CVI developed in this study can be exploited as a tool for decision makers, empowering them to prioritise areas for intervention and bolster the resilience of coastal areas in the face of environmental changes.
The First Validation of Aerosol Optical Parameters Retrieved from the Terrestrial Ecosystem Carbon Inventory Satellite (TECIS) and Its Application
Authors: Ren Yijie , Chen Binglong , Bu Lingbing , Hu Gen , Fang Jingyi , Liyanage Pasindu
Published: October 2024

In August 2022, China successfully launched the Terrestrial Ecosystem Carbon Inventory Satellite (TECIS). The primary payload of this satellite is an onboard multi-beam lidar system, which is capable of observing aerosol optical parameters on a global scale. This pioneering study used the Fernald forward integration method to retrieve aerosol optical parameters based on the Level 2 data of the TECIS, including the aerosol depolarization ratio, aerosol backscatter coefficient, aerosol extinction coefficient, and aerosol optical depth (AOD). The validation of the TECIS-retrieved aerosol optical parameters was conducted using CALIPSO Level 1 and Level 2 data, with relative errors within 30%. A comparison of the AOD retrieved from the TECIS with the AERONET and MODIS AOD products yielded correlation coefficients greater than 0.7 and 0.6, respectively. The relative error of aerosol optical parameter profiles compared with ground-based measurements for CALIPSO was within 40%. Additionally, the correlation coefficients R2 with MODIS and AERONET AOD were approximately between 0.5 and 0.7, indicating the high accuracy of TECIS retrievals. Utilizing the TECIS retrieval results, combined with ground air quality monitoring data and HYSPLIT outcomes, a typical dust transport event was analyzed from 2 to 7 April 2023. The results indicate that dust was transported from the Taklamakan Desert in Xinjiang, China, to Henan and Anhui provinces, with a gradual decrease in the aerosol depolarization ratio and backscatter coefficient during the transport process, causing varying degrees of pollution in the downstream regions. This research verifies the accuracy of the retrieval algorithm through multi-source data comparison and demonstrates the potential application of the TECIS in the field of aerosol science for the first time. It enables the fine-scale regional monitoring of atmospheric aerosols and provides reliable data support for the three-dimensional distribution of global aerosols and related scientific applications.
Enhanced Impacts of Extreme Weather Events on Forest: The Upper Valtellina (Italy) Case Study
Authors: Barbagallo Blanka , Rocca Nicolò , Cresi Lorenzo , Diolaiuti Guglielmina Adele , Senese Antonella
Published: October 2024

Extreme weather events are increasingly recognized as major stress factors for forest ecosystems, causing both immediate and long-term effects. This study focuses on the impacts experienced by the forests of Valdisotto, Valfurva, and Sondalo (28% of the total area is covered by forests) in Upper Valtellina (Italy) due to the Vaia storm that occurred in October 2018. To define the immediate impacts of Vaia, we assess the economic value of forest ecosystem services (ESs), particularly those provided by timber production and carbon sequestration, pre- and post-Vaia and during the emergency period. We used the market price method to assess the economic values of timber production and carbon sequestration, as these are considered to be marketable goods. Based on data processed from Sentinel-2 satellite images (with a spatial resolution of 10 m), our results show that, despite the reduction in forest area (−2.02%) and timber stock (−2.38%), the economic value of the timber production increased after Vaia due to higher timber prices (i.e., from a total of €124.97 million to €130.72 million). However, considering the whole emergency period (2019–2020), the total losses are equal to €5.10 million for Valdisotto, €0.32 million for Valfurva, and €0.43 million for Sondalo. Instead, an economic loss of 2.88% is experienced for carbon sequestration, with Valdisotto being the more affected municipality (−4.48% of the pre-Vaia economic value). In terms of long-term impacts, we discuss the enhanced impacts due to the spread of the bark beetle Ips typopgraphus.
Ego-Vehicle Speed Correction for Automotive Radar Systems Using Convolutional Neural Networks
Authors: Moon Sunghoon , Kim Daehyun , Kim Younglok
Published: October 2024

The development of autonomous driving vehicles has increased the global demand for robust and efficient automotive radar systems. This study proposes an automotive radar-based ego-vehicle speed detection network (AVSD Net) model using convolutional neural networks for estimating the speed of the ego vehicle. The preprocessing and postprocessing methods used for vehicle speed correction are presented in detail. The AVSD Net model exhibits characteristics that are independent of the angular performance of the radar system and its mounting angle on the vehicle, thereby reducing the loss of the maximum detection range without requiring a downward or wide beam for the elevation angle. The ego-vehicle speed is effectively estimated when the range–velocity spectrum data are input into the model. Moreover, preprocessing and postprocessing facilitate an accurate correction of the ego-vehicle speed while reducing the complexity of the model, enabling its application to embedded systems. The proposed ego-vehicle speed correction method can improve safety in various applications, such as autonomous emergency braking systems, forward collision avoidance assist, adaptive cruise control, rear cross-traffic alert, and blind spot detection systems.
Investigating Transfer Learning in Noisy Environments: A Study of Predecessor and Successor Features in Spatial Learning Using a T-Maze
Authors: Seo Incheol , Lee Hyunsu
Published: October 2024

In this study, we investigate the adaptability of artificial agents within a noisy T-maze that use Markov decision processes (MDPs) and successor feature (SF) and predecessor feature (PF) learning algorithms. Our focus is on quantifying how varying the hyperparameters, specifically the reward learning rate (αr) and the eligibility trace decay rate (λ), can enhance their adaptability. Adaptation is evaluated by analyzing the hyperparameters of cumulative reward, step length, adaptation rate, and adaptation step length and the relationships between them using Spearman’s correlation tests and linear regression. Our findings reveal that an αr of 0.9 consistently yields superior adaptation across all metrics at a noise level of 0.05. However, the optimal setting for λ varies by metric and context. In discussing these results, we emphasize the critical role of hyperparameter optimization in refining the performance and transfer learning efficacy of learning algorithms. This research advances our understanding of the functionality of PF and SF algorithms, particularly in navigating the inherent uncertainty of transfer learning tasks. By offering insights into the optimal hyperparameter configurations, this study contributes to the development of more adaptive and robust learning algorithms, paving the way for future explorations in artificial intelligence and neuroscience.
Trauma-Informed Photovoice for Adolescents and Young Adults with Child Welfare Involvement
Authors: Katz Colleen C. , Banya Moiyattu , Augsberger Astraea , Collins David , Kilgore LaShawnda , Moles Kerry , Deopersaud Cheyanne , Munson Michelle R.
Published: October 2024

Youth who age out of foster care face a constellation of challenges associated with navigating the transition to adulthood and often do not have opportunities to express their perspectives. The purpose of this project was to partner with these youth to develop a trauma-informed photovoice program that can be freely utilized in child welfare programming. This youth participatory action research (yPAR) project engaged youth and young adults with child welfare experience in a long-term partnership to co-develop and pilot test a trauma-informed photovoice program called Photovoice for Change (P4C). P4C evolved into a three-meeting structure: (1) orientation and launch; (2) preparation for sharing; and (3) share back. Youth participants revealed photographs of “places and spaces” that impacted their lives, sharing their meaning with other youth and supportive adults in a group setting. The project concluded with a gallery showing, featuring a video highlighting the program participants’ experiences. Trauma-informed photovoice may be an important program to embed within the child welfare system, as it can provide youth with an opportunity to: (a) strengthen within-group relationships and (b) express important aspects of their lives in a supportive and safe environment.
Fast Fashion, Sustainability, and Nudge Theory: Examining the Effects of Choice Architecture on Consumption of Sustainable Fashion over Fast Fashion
Authors: Peleg Mizrachi Meital , Tal Alon
Published: October 2024

This study considers ways to increase the consumption of sustainable fashion given the significant environmental and social damages associated with the industry. A series of experiments were conducted examining the impacts of choice architecture (nudges) under field conditions in collaboration with one of Israel’s largest shopping centers. This study sought to identify which interventions at the retail level successfully motivate sustainable fashion behavioral change regarding purchases and willingness to pay more, along with agreement with several statements regarding the climate crisis and sustainable fashion. Among the types of nudges examined in this field study were providing information, increasing accessibility to sustainable alternatives and appealing to social identity in relation to demographics and green self-image. This study found that offering alternatives to consumers constituted the most effective way to “nudge” consumers toward more sustainable purchasing behavior. Nonetheless, this does not negate the contribution of providing information and strengthening social norms regarding sustainable fashion. Additionally, in all groups, most participants reported that they did not know how to distinguish between sustainable and non-sustainable fashion, nor did they believe that the clothes they purchased were actually sustainable. The findings emphasize the need for policies that will increase the accessibility of sustainable fashion.
What Is the Value of an Environmental Certification Label in Tourism Industry? Is It Worth the Effort?
Authors: Dias Francisco , Lavaredas Alexandra Meira , Esteves Patrícia
Published: October 2024

The increasing awareness of environmental, social and cultural issues has highlighted the concept of sustainable certification. The aim of this study is to understand the main drivers and constraints for companies to join certification schemes and compare possible changes between the years 2021 and 2024 among tourism companies. A total of 417 online questionnaires were collected, and a comparative study was conducted. The findings show that the drivers for implementing certification schemes are improving the company’s image and customer-based brand equity, strengthening competitiveness, achieving eco-efficiency, cost reduction, and competitive advantage. On the side of the obstacles that discourage the adoption of certification schemes, there are difficulties in meeting the criteria of the certifications, adapting working methods, higher costs, and lower price competitiveness. The results also show that there was a significant increase in the number of certified companies and that women and young entrepreneurs are more sensitive to the implementation of good practices. It has been concluded that although there is greater demand and interest in implementing good tourism practices, people who know less about certification schemes and companies that are not certified have a weaker opinion regarding this topic.
Towards Sustainable Mobility: Determinants of Intention to Purchase Used Electric Vehicles in China
Authors: Zou Jinzhi , Kamarudin Khairul Manami , Liu Jing , Zhang Jiaqi
Published: October 2024

A thriving electric vehicles (EVs) market serves as a pivotal embodiment of the global push towards sustainable mobility. As one of the leading global EV sellers, China owns a huge used EV market, which should be spotlighted. While most studies focus on the mechanism of new EV purchases, few put their insight into the trade of used EVs. To fill this gap, this paper aims to clarify the mechanism of consumption behaviour towards used EVs. First, we identified 11 variables that have a direct or indirect impact on consumers’ purchase intention and constructed a conceptual framework. Then, we checked the structural relationships of the model through an empirical study (n = 431). The results showed that purchase intention was determined by two variables: perceived risk and attitude. We also observed an association between income and purchase intention. Functional risk had a direct and significant impact on perceived risk. Economic value, brand trust, and after-sales service were crucial predictors of attitude. Education could moderate the relationship between attitudes and purchase intention. Based on theoretical findings, we present the design strategies to enhance consumers’ purchase willingness from car companies’ and policymakers’ viewpoints. In practical situations, this article offers valuable insights for stakeholders related to the used EV industry, providing a critical reference for advancing sustainable mobility.
Zooplankton Structure and Ecological Niche Differentiation of Dominant Species in Tahe Bay, Lushun, China
Authors: Zhang Yanrong , Yin Zengqiang , Wang Yan , Li Guoxing , Zhang Dawang , Yang Jun , Chen Lei , Gu Haifeng , Qin Yuxue , Tian Tao
Published: October 2024

Zooplankton are important food organisms in the marine ecosystem, and their community structure and distribution reflect the productivity of the waters. To investigate the zooplankton structure and the environmental factors affecting ecological niche differentiation in the waters of Tahe Bay, Lushun, a survey was conducted in September 2021 and March, April, and November 2022 in the waters of Tahe Bay. The results showed that there are 31 species representing four phyla, with an annual mean abundance of 12.42 × 103 ind/m3, dominated by Copepoda (13 species, 41.94%), with zooplankton richness indices ranging from 0.83 to 2.44, diversity indices ranging from 0.84 to 2.42, and evenness indices ranging from 0.14 to 0.84. Pearson’s correlation of zooplankton abundance and community diversity with environmental factors, such as water temperature, salinity, dissolved oxygen, NH3-N, and NO3-N, was significant in the waters of Tahe Bay. There were 13 dominant species, mainly consisting of broad-niche species, among which Oithona similis was the dominant species in all four seasons; the degree of niche overlap of the dominant species was related to the seasons, with a serious niche overlap accounting for 81.0% in September 2021, and there was no niche overlap in March 2022; 33.3% of the species had a severe ecological niche overlap in April 2022, with a serious niche overlap accounting for 86.7% in November 2022. The results of redundancy analysis (RDA) indicated that water temperature, salinity, DO, and DIP are the main environmental factors affecting the ecological niche differentiation of the dominant species of zooplankton.
The Optimization of a Slow-Walking System in a Higher Education Campus—Taking the Huangjiahu Campus of Wuhan University of Science and Technology as an Example
Authors: Xia Xiaotang , Yan Hong , Qin Yuting , Li Tingyang
Published: October 2024

The design of slow-moving systems in colleges and universities is a critical factor in ensuring the safety, convenience, and comfort of campus transportation. This study focuses on the Huangjiahu Campus of Wuhan University of Science and Technology, conducting an in-depth analysis of the current shortcomings in the campus’s slow-moving system with respect to safety, convenience, and comfort. The analysis employs the PLPS research method and statistical analysis, while the satisfaction with the slow-moving transportation system is further assessed using the IPA method. The study identifies key factors affecting the performance of the slow-moving system and proposes improvement measures based on the evaluation results. These measures aim to enhance campus transportation efficiency, improve environmental quality, and increase the vitality and attractiveness of campus spaces. This study offers a theoretical basis and practical strategies for optimizing the slow-moving transportation system at the Huangjiahu Campus of Wuhan University of Science and Technology and other institutions of higher education. It also provides guidance for planning and improving slow-moving transportation systems in urban planning, contributing significant academic and practical value.
Enhancing Autonomous Driving Safety: A Robust Stacking Ensemble Model for Traffic Sign Detection and Recognition
Authors: Wang Yichen , Wang Jie , Wang Qianjin
Published: October 2024

Accurate detection and classification of traffic signs play a vital role in ensuring driver safety and supporting advancements in autonomous driving technology. This paper introduces a novel approach for traffic sign detection and recognition by integrating the Faster RCNN and YOLOX-Tiny models using a stacking ensemble technique. The innovative ensemble methodology creatively merges the strengths of both models, surpassing the limitations of individual algorithms and achieving superior performance in challenging real-world scenarios. The proposed model was evaluated on the CCTSDB dataset and the MTSD dataset, demonstrating competitive performance compared to traditional algorithms. All experiments were conducted using Python 3.8 on the same system equipped with an NVIDIA GTX 3060 12G graphics card. Our results show improved accuracy and efficiency in recognizing traffic signs in various real-world scenarios, including distant, close, complex, moderate, and simple settings, achieving a 4.78% increase in mean Average Precision (mAP) compared to Faster RCNN and improving Frames Per Second (FPS) by 8.1% and mAP by 6.18% compared to YOLOX-Tiny. Moreover, the proposed model exhibited notable precision in challenging scenarios such as ultra-long-distance detections, shadow occlusions, motion blur, and complex environments with diverse sign categories. These findings not only showcase the model’s robustness but also serve as a cornerstone in propelling the evolution of autonomous driving technology and sustainable development of future transportation. The results presented in this paper could potentially be integrated into advanced driver-assistance systems and autonomous vehicles, offering a significant step forward in enhancing road safety and traffic management.
Comparative Life Cycle Assessment and Life Cycle Cost Analysis of Bonded Nd-Fe-B Magnets: Virgin Production versus Recycling
Authors: Yang Yaxuan , Liu Min , Zhu Peihong , Gao Ke , Xuan Yueheng , Lu Qingmei , Ding Yue , Zhang Baoguo , Yue Ming
Published: October 2024

Conducting a comprehensive analysis of life cycle assessment and life cycle cost is critical for quantifying environmental impacts and estimating production costs associated with new production methods. Therefore, the life cycle assessment and life cycle cost of 1 kg bonded Nd-Fe-B magnetic powder produced by different production methods from “cradle to gate” are studied in this study. The results indicate that recycling is more advantageous than direct production in both environmental and economic terms. Specifically, the endpoint impact categories for 1 kg of bonded Nd-Fe-B powder produced by various methods reveal that recycling and regeneration reduce the environmental impact by 42%, 41%, and 42% compared to direct production in the categories of Human Health, Ecosystem Diversity, and Resource Availability, respectively. Additionally, in terms of life cycle cost, recycling yields savings of 47% and 32% compared to direct production in the internal and external life cycle cost, respectively. The results demonstrate that the environmentally friendly and cost-reducing method of recycling and regeneration points out a pathway for transforming the industrial structure of bonded Nd-Fe-B magnetic powder.
Farmers Preferentially Allocate More Land to Cultivation of Conventional White Maize Compared to Weevil-Resistant Biofortified Orange Maize
Authors: Nkhata Smith G. , Watson Finason , Chimbaza Monica , Namaumbo Sydney , Kammwamba Kondwani , Chisapo Gift , Ngoma Theresa Nakoma , Chilembo Madalitso , Matumba Limbikani
Published: October 2024

The successful translation of biofortified orange maize (BOM) to a staple household food is dependent on farmers’ ability to cultivate and subsequently utilize it. In this study, we assessed farmers’ allocation of their land to the cultivation of BOM and conventional white maize (CWM) varieties in districts where the AFIKEPO Nutrition Program is implemented in Malawi. The results showed that farmers were skeptical of allocating more land to the cultivation of BOM. CWM was allocated significantly more land (1.75 ± 0.51 acres) than BOM (1.12 ± 0.32 acres) (p < 0.001) in all districts. More farmers (87.9%) allocated less than 1 acre to BOM cultivation. The cost of seeds did not explain the preference for CWM, as the price of seeds in Malawi Kwacha was similar for both maize types (p = 0.742). Consequently, the average number of bags (50 kg maize grains/bag) harvested was significantly lower (mean: 6.48 ± 8.27 bags; median: 4 bags) for BOM than for CWM (mean: 23.11 ± 20.54 bags; median: 17 bags). Interestingly, BOM was found to be more resistant to weevils during post-harvest storage, suggesting the potential for improved food and nutrition security for households. The knowledge of high grain resistance to weevils did not influence farmers to cultivate more BOM. This has the potential to negatively affect maize biofortification as an effective strategy to alleviate vitamin A deficiency (VAD) in developing countries. Farmers should be sensitized to identify the benefits of BOM so that they are willing to purchase seeds and grow BOM on a larger scale. Coupled with its higher resistance to storage weevils, superior taste, and nutrient content, the continued cultivation and consumption of BOM has the potential to contribute to the achievement of both food and nutrition security within communities.
Sustainability of Gulf of Mexico Coastal Estuaries and Lagoons: Interactions with Hydrocarbon Production—A Review with a Look to the Future
Authors: Day John W. , Rivera-Arriaga Evelia , del Carmen Peña-Puch Angelina , Hunter Rachael G.
Published: October 2024

Here, we review the functioning and importance of deltaic coastal systems in the northern and southern Gulf of Mexico and how petroleum activities have impacted these two important systems. The Mississippi and Usumacinta-Grijalva Deltas are areas of high biological productivity and biodiversity that support the two largest fisheries in the Gulf. The north central Gulf receives inflow from the Mississippi river, the largest discharge in North America. The Mississippi Delta covers about 10,000 km2. The Usumacinta-Grijalva River is the second highest freshwater input to the Gulf and discharges to the Usumacinta-Grijalva/Laguna de Terminos deltaic complex. These two areas are the largest petroleum producing regions in the Gulf, involving both inshore and offshore production. Petroleum activities impact coastal ecosystems in two important ways. In inshore areas dominated by coastal wetlands, there has been enormous physical disruption of the natural environment that affected hydrology and system functioning. In both inshore and offshore areas, spilled oil and release of high salinity produced water has led to widespread toxic pollution. Documentation of petroleum activity impacts on coastal marine ecosystems is much more advanced in the Mississippi Delta. Here, we describe how petroleum production impacts coastal ecosystems and discuss how restoration and management can restore the functioning of impacted coastal ecosystems.
Unconventional Ingredients from the Industrial Oilseed By-Products in Dairy Goat Feeding: Effects on the Nutritional Quality of Milk and on Human Health
Authors: Tristan Asensi Marta , Pagliai Giuditta , Napoletano Antonia , Lotti Sofia , Dinu Monica , Mannelli Federica , Invernizzi Guido , Sofi Francesco , Colombini Barbara , Buccioni Arianna
Published: October 2024

Oilseed by-products (Cynara cardunculus and Camelina sativa) (CCCS) are rich in bioactive compounds. This study aimed to evaluate the health effects of consuming yogurt made from goat milk fed with CCCS industrial residues in adults. In this randomized, crossover clinical trial, 20 healthy adults (14F; 37.7 ± 14.2 years) consumed either yogurt made from goat milk fed with CCCS or regular goat yogurt (C) daily for 1 month in each phase. Anthropometric parameters and blood samples were collected at the beginning and end of each phase. CCCS yogurt consumption resulted in a significant fat mass reduction (−1.8% and −1.1 kg) and fat-free mass increase (+1.5% and +0.9 kg). Regarding blood parameters, a non-significant decrease in triglycerides, total cholesterol, and LDL cholesterol was observed, particularly after the CCCS intervention. Moreover, creatinine levels exhibited an opposite trend (p = 0.023) after CCCS, decreasing in subjects aged ≤30 years (−0.03 mg/dL) and increasing in older subjects (+0.05 mg/dL). Regarding inflammatory parameters, a non-significant trend in increased IL-1ra levels was observed especially after CCCS yogurt consumption compared to the C yogurt (+56.9 vs. +19.1 pg/mL, respectively). The use of unconventional feed derived from oilseed by-products for dairy goat feeding may have potential possible beneficial effects on human health.
Moving beyond the Framing Impasse in the Aral Sea Delta: Vernacular Knowledge of Salinization and Its Potential for Social Learning towards Sustainability
Authors: Féaux de la Croix Jeanne , Samakov Aibek
Published: October 2024

The Food and Agriculture Organization estimates that close to 9% of the world’s soils are affected by salinity. The purpose of this article is to discuss qualitative social science findings on alternative ways of conceptualizing salinization in Kazakhstan and how these findings could be leveraged for transformative knowledge towards sustainability. We highlight dimensions of land degradation that are doubly obscured: the under-represented issue of salinization, and vernacular knowledge on salinization. The article draws on qualitative data collection methods, including eighteen months of participant observation, workshop transcripts and archival records. Three research findings are presented. First, there is an analysis of the framing of environmental issues common among policymakers in the region. Second, these frameworks are contrasted with novel data on how local farming communities understand and deal with salinization. These two research results enable extrapolating a third finding: how such locally based knowledge could be harnessed towards solving salinization issues. Beyond the specific issue of salinization, the results of this research suggest potentially valuable design principles relating to specific ways that the environmental knowledge of expert farmers and scientific experts could be paired. In the case of Central Asia, models based on the local culture can be adapted, such as hosting and apprenticeship relationships. This example suggests transferable lessons on how to forge social learning towards sustainability that start from imperfect local tools (bottom-up) rather than from internationally promoted but socially distant blueprints (top-down).
Has the Development of Broadband Infrastructure Improved Household Energy Consumption in Rural China?
Authors: He Zongyue , Zhang Yanhong , Wang Xiqian
Published: October 2024

Digital infrastructure plays a crucial role in shaping household energy consumption behaviors, especially in the context of achieving carbon peaking and carbon neutrality goals in China. In this study, we explored the impact of broadband infrastructure on household energy consumption and clean fuel choices, using data from the China Health and Retirement Longitudinal Study (CHARLS). In a difference-in-differences (DID) framework, our findings indicate that the promotion of broadband infrastructure significantly increases rural household energy consumption and facilitates a transition to cleaner energy sources. Notably, households with better socioeconomic status, particularly those with higher education and income levels, benefit more from enhanced broadband internet access. Mechanism analysis reveals that the “Broadband China” policy can positively influence household consumption through several potential channels: fostering technological innovation, enhancing energy efficiency in cities, and improving overall environmental awareness. These findings contribute to our understanding of the role of broadband infrastructure in shaping household energy consumption patterns and have important implications for policymakers, particularly in the context of sustainable development and energy transition efforts.
The Dynamics of Vegetation Evapotranspiration and Its Response to Surface Meteorological Factors in the Altay Mountains, Northwest China
Authors: Aili Aishajiang , Hailiang Xu , Waheed Abdul , Wanyu Zhao , Qiao Xu , Xinfeng Zhao , Peng Zhang
Published: October 2024

The Altay Mountains’ forests are vital to Xinjiang’s terrestrial ecosystem, especially water regulation and conservation. This study evaluates vegetation evapotranspiration (ET) from 2000 to 2017 using temperature, precipitation, and ET data from the China Meteorological Data Sharing Service. The dataset underwent quality control and was interpolated using the inverse distance weighted (IDW) method. Correlation analysis and climate trend methodologies were applied to assess the impacts of temperature, precipitation, drought, and extreme weather events on ET. The results indicate that air temperature had a minimal effect on ET, with 68.34% of the region showing weak correlations (coefficients between −0.2 and 0.2). Conversely, precipitation exhibited a strong positive correlation with ET across 98.91% of the area. Drought analysis, using the standardized precipitation evapotranspiration index (SPEI) and the Temperature Vegetation Dryness Index (TVDI), showed that ET was significantly correlated with the SPEI in 96.47% of the region, while the TVDI displayed both positive and negative correlations. Extreme weather events also significantly influenced ET, with reductions in the Simple Daily Intensity Index (SDII), heavy precipitation days (R95p, R10), and increases in indicators like growing season length (GSL) and warm spell duration index (WSDI) leading to variations in ET. Based on the correlation coefficients and their significance, it was confirmed that the SII (precipitation intensity) and R95p (heavy precipitation) are the main factors causing vegetation ET increases. These findings offer crucial insights into the interactions between meteorological variables and ET, essential information for sustainable forest management, by highlighting the importance of optimizing water regulation strategies, such as adjusting species composition and forest density to enhance resilience against drought and extreme weather, thereby ensuring long-term forest health and productivity in response to climate change.
Unlocking Customer Happiness and Enhancing Quality of Life: The Potential of Small and Medium-Sized Enterprise ICT Initiatives in Stress-Inducing Environments
Authors: Shava Herring
Published: October 2024

Customers in resource-poor communities still grapple with many information and communication technology (ICT) failures as they strive to access goods and services in small and medium enterprises near them. From a customer perspective, these challenges often lead to stress-related issues such as frustrations and anxiety, which can even result in transaction abandonment. Extended ICT failures result in SMEs failing to achieve sustainable e-commerce. This study delves into the impact of ICT initiatives by SMEs in stress-inducing environments on customers’ quality of life. The study further examines whether customer stress and happiness play a role in this association. Quantitative data were acquired using the mall intercept method, while the developed hypotheses were examined using structural equation modeling (SEM) in SMART-PLS 4. The results shed light on how customers navigate daily ICT-related failures experienced by SMEs operating in poor resource communities as they strive for happiness and stress-free lives, ultimately leading to an improved quality of life. The study recommends that the government, through its agencies, the Department of Communications and Digital Technologies and the Department of Science and Technology, among others, not only create an environment supporting SME ICT initiatives but also find strategies for sustaining SME ICT adoption for improved human well-being and socio-economic development within resource-constrained communities.
Relative Fluctuating Asymmetry and Predictive Metrics of Cast Antler Pairs in White-Tailed Deer (Odocoileus virginianus)
Authors: Peterson Brian C. , Farrell Patrick D. , Schoenebeck Casey W.
Published: October 2024

Antlers are genetically coded to have bilateral symmetry. However, environmental stressors cause asymmetries between antlers. Previous studies have investigated fluctuating asymmetries on harvested white-tailed deer (Odocoileus virginianus Zimmermann, 1780). Cast antlers provide underutilized metrics that are not available prior to shedding. The objectives of this study were to quantify relative fluctuating asymmetry (RFA) between age groups and identify the best age-specific pre- and post-cast antler metrics to confirm an antler pair. We hypothesized lower RFA values for post-cast measurements than pre-cast measurements due to a lessened chance for damage when atop the head. Additionally, younger individuals were hypothesized to have higher RFA values due to greater susceptibility to environmental stressors. Cast antler pairs from 196 white-tailed deer were collected in Nebraska. We measured 14 available antler metrics per cast antler side classified by age group. The most symmetric measurements between antler sides included pedicle seal area, main beam length, and circumference. Antlers of older deer were consistently more symmetric than younger deer. When combining the top metrics and testing against random antler pairs, we found an 81.9–92.3% match rate for 1.5 and ≥2.5-year-olds, respectively. Our findings provided a quantifiable method to assign antler pair classifications more confidently while documenting decreased symmetry in younger individuals.
Comprehensive Analysis of Pelvic Asymmetries in Low Back Pain, Scoliosis, Post-Traumatic Pelvic Dysfunctions and Obstetric Changes: A Narrative Review Focused on Clinical Relevance
Authors: Cruz-Medel Inés , Rodrigues-de-Souza Daiana Priscila , Alburquerque-Sendín Francisco
Published: October 2024

The human pelvis is a complex structure, which participates in the biomechanical functioning of the musculoskeletal system. Although it is considered a symmetrical entity, the morphology of the pelvis is subject to different factors that alter its anatomy, function or biomechanics, such as age, bipedal locomotion, obstetric changes and sexual dimorphism. However, how these factors influence pelvic asymmetry is unknown. Some evidence suggests that this condition leads to different pathological states, such as chronic low back pain, scoliosis, post-traumatic pelvic dysfunctions and obstetric changes. Therefore, pelvic asymmetries present a significant challenge in clinical practice due to their multifactorial nature and their potential impact on quality of life. Multidisciplinary research and collaboration are essential to improve understanding and develop more effective and specific identification and treatment approaches in the presence of pelvic asymmetries.
Schwinger–Keldysh Path Integral Formalism for a Quenched Quantum Inverted Oscillator
Authors: Choudhury Sayantan , Dey Suman , Gharat Rakshit Mandish , Mandal Saptarshi , Pandey Nilesh
Published: October 2024

In this work, we study the time-dependent behavior of quantum correlations of a system of an inverted oscillator governed by out-of-equilibrium dynamics using the well-known Schwinger–Keldysh formalism in the presence of quantum mechanical quench. Considering a generalized structure of a time-dependent Hamiltonian for an inverted oscillator system, we use the invariant operator method to obtain its eigenstate and continuous energy eigenvalues. Using the expression for the eigenstate, we further derive the most general expression for the generating function as well as the out-of-time-ordered correlators (OTOCs) for the given system using this formalism. Further, considering the time-dependent coupling and frequency of the quantum inverted oscillator characterized by quench parameters, we comment on the dynamical behavior, specifically the early, intermediate and late time-dependent features of the OTOC for the quenched quantum inverted oscillator. Next, we study a specific case, where the system of an inverted oscillator exhibits chaotic behavior by computing the quantum Lyapunov exponent from the time-dependent behavior of OTOCs in the presence of the given quench profile.
Advancing Nanopulsed Plasma Bubbles for the Degradation of Organic Pollutants in Water: From Lab to Pilot Scale
Authors: Meropoulis Stauros , Aggelopoulos Christos A.
Published: October 2024

The transition from lab-scale studies to pilot-scale applications is a critical step in advancing water remediation technologies. While laboratory experiments provide valuable insights into the underlying mechanisms and method effectiveness, pilot-scale studies are essential for evaluating their practical feasibility and scalability. This progression addresses challenges related to operational conditions, effectiveness and energy requirements in real-world scenarios. In this study, the potential of nanopulsed plasma bubbles, when scaled up from a lab environment, was explored by investigating critical experimental parameters, such as plasma gas, pulse voltage, and pulse repetition rate, while also analyzing plasma-treated water composition. To validate the broad effectiveness of this method, various classes of highly toxic organic pollutants were examined in terms of pollutant degradation efficiency and energy requirements. The pilot-scale plasma bubble reactor generated a high concentration of short-lived reactive species with minimal production of long-lived species. Additionally, successful degradation of all pollutants was achieved in both lab- and pilot-scale setups, with even lower electrical energy-per-order (EEO) values at the pilot scale, 2–3 orders of magnitude lower compared to other advanced oxidation processes. This study aimed to bridge the gap between lab-scale plasma bubbles and upscaled systems, supporting the rapid, effective, and energy-efficient destruction of organic pollutants in water.
A Hybrid Trio-Deep Feature Fusion Model for Improved Skin Cancer Classification: Merging Dermoscopic and DCT Images
Authors: Attallah Omneya
Published: October 2024

The precise and prompt identification of skin cancer is essential for efficient treatment. Variations in colour within skin lesions are critical signs of malignancy; however, discrepancies in imaging conditions may inhibit the efficacy of deep learning models. Numerous previous investigations have neglected this problem, frequently depending on deep features from a singular layer of an individual deep learning model. This study presents a new hybrid deep learning model that integrates discrete cosine transform (DCT) with multi-convolutional neural network (CNN) structures to improve the classification of skin cancer. Initially, DCT is applied to dermoscopic images to enhance and correct colour distortions in these images. After that, several CNNs are trained separately with the dermoscopic images and the DCT images. Next, deep features are obtained from two deep layers of each CNN. The proposed hybrid model consists of triple deep feature fusion. The initial phase involves employing the discrete wavelet transform (DWT) to merge multidimensional attributes obtained from the first layer of each CNN, which lowers their dimension and provides time–frequency representation. In addition, for each CNN, the deep features of the second deep layer are concatenated. Afterward, in the subsequent deep feature fusion stage, for each CNN, the merged first-layer features are combined with the second-layer features to create an effective feature vector. Finally, in the third deep feature fusion stage, these bi-layer features of the various CNNs are integrated. Through the process of training multiple CNNs on both the original dermoscopic photos and the DCT-enhanced images, retrieving attributes from two separate layers, and incorporating attributes from the multiple CNNs, a comprehensive representation of attributes is generated. Experimental results showed 96.40% accuracy after trio-deep feature fusion. This shows that merging DCT-enhanced images and dermoscopic photos can improve diagnostic accuracy. The hybrid trio-deep feature fusion model outperforms individual CNN models and most recent studies, thus proving its superiority.
Optical Particle Tracking in the Pneumatic Conveying of Metal Powders through a Thin Capillary Pipe
Authors: Pedrolli Lorenzo , Fraccarollo Luigi , Achiaga Beatriz , Lopez Alejandro
Published: October 2024

Directed Energy Deposition (DED) processes necessitate a consistent material flow to the melt pool, typically achieved through pneumatic conveying of metal powder via thin pipes. This study aims to record and analyze the multiphase fluid–solid flow. An experimental setup utilizing a high-speed camera and specialized optics was constructed, and the flow through thin transparent pipes was recorded. The resulting information was analyzed and compared with coupled Computational Fluid Dynamics-Discrete Element Modeling (CFD-DEM) simulations, with special attention to the solids flow fluctuations. The proposed methodology shows a significant improvement in accuracy and reliability over existing approaches, particularly in capturing flow rate fluctuations and particle velocity distributions in small-scale systems. Moreover, it allows for accurately analyzing Particle Size Distribution (PSD) in the same setup. This paper details the experimental design, video analysis using particle tracking, and a novel method for deriving volumetric concentrations and flow rate from flat images. The findings confirm the accuracy of the CFD-DEM simulations and provide insights into the dynamics of pneumatic conveying and individual particle movement, with the potential to improve DED efficiency by reducing variability in material deposition rates.
Exploring Neutrino Masses (g − 2)μ,e in Type I+II Seesaw in Le–Lα-Gauge Extended Model
Authors: Panda Papia , Mishra Priya , Behera Mitesh Kumar , Singirala Shivaramakrishna , Mohanta Rukmani
Published: October 2024

This paper aims to explore the implications of U(1)Le−Lα gauge symmetries, where α=τ,μ, in the neutrino sector through type-(I+II) seesaw mechanisms. To achieve such a hybrid framework, we include a scalar triplet and three right-handed neutrinos. The model can successfully account for the active neutrino masses, mixing angles, mass squared differences, and the CP-violating phase within the 3σ bounds of NuFit v5.2 neutrino oscillation data. The presence of a new gauge boson at the MeV scale provides an explanation for the muon and electron (g−2) within the confines of their experimental limits. Furthermore, we scrutinize the proposed models in the context of upcoming long-baseline neutrino experiments such as DUNE, P2SO, T2HK, and T2HKK. The findings reveal that P2SO and T2HK have the ability to probe both models in their 5σ-allowed oscillation parameter region, whereas DUNE and T2HKK can conclusively test only the model with U(1)Le−Lμ-symmetry within the 5σ parameter space if the true values of the oscillation parameters remain consistent with NuFit v5.2.
Universes Emerging from Nothing and Disappearing into Nothing as an Endless Cosmological Process
Authors: Marochnik Leonid
Published: October 2024

The equation of state of quantum fluctuations of the gravitational field of the universe depends on H4, where H is the Hubble constant. This means that it is invariant with respect to the Wick rotation, i.e., the transition from Lorentzian space-time to Euclidean space-time and vice versa. It is shown that the quantum birth of universes from Euclidean space-time, i.e., from nothing, and their quantum disappearance to nothing (return to Euclidean space-time) by the time the density of the matter filling the universe becomes negligible could be a likely cosmological scenario. On an infinite time axis, this is an endless process of birth and death of universes appearing and disappearing and replacing each other. Within this scenario, our current universe is going to disappear into nothing at z≤−0.68, i.e., after 18.37 billion years, and the lifetime of our universe and similar universes is about 32 billion years.