bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-Scale and Multi-Network Deep Feature Fusion for Discriminative Scene Classification of High-Resolution Remote Sensing Images
Authors: Yuan Baohua , Sehra Sukhjit Singh , Chiu Bernard
Published: October 2024

The advancement in satellite image sensors has enabled the acquisition of high-resolution remote sensing (HRRS) images. However, interpreting these images accurately and obtaining the computational power needed to do so is challenging due to the complexity involved. This manuscript proposed a multi-stream convolutional neural network (CNN) fusion framework that involves multi-scale and multi-CNN integration for HRRS image recognition. The pre-trained CNNs were used to learn and extract semantic features from multi-scale HRRS images. Feature extraction using pre-trained CNNs is more efficient than training a CNN from scratch or fine-tuning a CNN. Discriminative canonical correlation analysis (DCCA) was used to fuse deep features extracted across CNNs and image scales. DCCA reduced the dimension of the features extracted from CNNs while providing a discriminative representation by maximizing the within-class correlation and minimizing the between-class correlation. The proposed model has been evaluated on NWPU-RESISC45 and UC Merced datasets. The accuracy associated with DCCA was 10% and 6% higher than discriminant correlation analysis (DCA) in the NWPU-RESISC45 and UC Merced datasets. The advantage of DCCA was better demonstrated in the NWPU-RESISC45 dataset due to the incorporation of richer within-class variability in this dataset. While both DCA and DCCA minimize between-class correlation, only DCCA maximizes the within-class correlation and, therefore, attains better accuracy. The proposed framework achieved higher accuracy than all state-of-the-art frameworks involving unsupervised learning and pre-trained CNNs and 2–3% higher than the majority of fine-tuned CNNs. The proposed framework offers computational time advantages, requiring only 13 s for training in NWPU-RESISC45, compared to a day for fine-tuning the existing CNNs. Thus, the proposed framework achieves a favourable balance between efficiency and accuracy in HRRS image recognition.
A Multi-Tiered Collaborative Network for Optical Remote Sensing Fine-Grained Ship Detection in Foggy Conditions
Authors: Zhou Wenbo , Li Ligang , Liu Bo , Cao Yuan , Ni Wei
Published: October 2024

Ship target detection faces the challenges of complex and changing environments combined with the varied characteristics of ship targets. In practical applications, the complexity of meteorological conditions, uncertainty of lighting, and the diversity of ship target characteristics can affect the accuracy and efficiency of ship target detection algorithms. Most existing target detection methods perform well in conditions of a general scenario but underperform in complex conditions. In this study, a collaborative network for target detection under foggy weather conditions is proposed, aiming to achieve improved accuracy while satisfying the need for real-time detection. First, a collaborative block was designed and SCConv and PCA modules were introduced to enhance the detection of low-quality images. Second, the PAN + FPN structure was adopted to take full advantage of its lightweight and efficient features. Finally, four detection heads were used to enhance the performance. In addition to this, a dataset for foggy ship detection was constructed based on ShipRSImageNet, and the mAP on the dataset reached 48.7%. The detection speed reached 33.3 frames per second (FPS), which is ultimately comparable to YOLOF. It shows that the model proposed has good detection effectiveness for remote sensing ship images during low-contrast foggy days.
National-Scale Detection of New Forest Roads in Sentinel-2 Time Series
Authors: Trier Øivind Due , Salberg Arnt-Børre
Published: October 2024

The Norwegian Environment Agency is responsible for updating a map of undisturbed nature, which is performed every five years based on aerial photos. Some of the aerial photos are already up to five years old when a new version of the map of undisturbed nature is published. Thus, several new nature interventions may have been missed. To address this issue, the timeliness and mapping accuracy were improved by integrating Sentinel-2 satellite imagery for the detection of new roads across Norway. The focus on new roads was due to the fact that most new nature interventions include the construction of new roads. The proposed methodology is based on applying U-Net on all the available summer images with less than 10% cloud cover over a five-year period, with an aggregation step to summarize the predictions. The observed detection rate was 98%. Post-processing steps reduced the false positive rate to 46%. However, as the false positive rate was still substantial, the manual verification of the predicted new roads was needed. The false negative rate was low, except in areas without vegetation.
Fusion Attention for Action Recognition: Integrating Sparse-Dense and Global Attention for Video Action Recognition
Authors: Kim Hyun-Woo , Choi Yong-Suk
Published: October 2024

Conventional approaches to video action recognition perform global attention over the entire video patches, which may be ineffective due to the temporal redundancy of video frames. Recent works on masked video modeling adopt a high-ratio tube masking and reconstruction strategy as a pre-training method to mitigate the problem of focusing on spatial features well but not on temporal features. Inspired by this pre-training method, we propose Fusion Attention for Action Recognition (FAR), which fuses the sparse-dense attention patterns specialized for temporal features with global attention during fine-tuning. FAR has three main components: head-split sparse-dense attention (HSDA), token–group interaction, and group-averaged classifier. First, HSDA splits the head of multi-head self-attention to fuse global and sparse-dense attention. The sparse-dense attention is divided into groups of tube-shaped patches to focus on temporal features. Second, token–group interaction is used to improve information exchange between divided patch groups. Finally, the group-averaged classifier uses spatio-temporal features from different patch groups to improve performance. The proposed method uses the weight parameters that are pre-trained with VideoMAE and MVD, and achieves higher performance (+0.1–0.4%) with less computation than models fine-tuned with global attention on Something-Something V2 and Kinetics-400. Moreover, qualitative comparisons show that FAR captures temporal features quite well in highly redundant video frames. The FAR approach demonstrates improved action recognition with efficient computation, and exploring its adaptability across different pre-training methods presents an interesting direction for future research.
An Efficient Pairing-Free Ciphertext-Policy Attribute-Based Encryption Scheme for Internet of Things
Authors: Guo Chong , Gong Bei , Waqas Muhammad , Alasmary Hisham , Tu Shanshan , Chen Sheng
Published: October 2024

The Internet of Things (IoT) is a heterogeneous network composed of numerous dynamically connected devices. While it brings convenience, the IoT also faces serious challenges in data security. Ciphertext-policy attribute-based encryption (CP-ABE) is a promising cryptography method that supports fine-grained access control, offering a solution to the IoT’s security issues. However, existing CP-ABE schemes are inefficient and unsuitable for IoT devices with limited computing resources. To address this problem, this paper proposes an efficient pairing-free CP-ABE scheme for the IoT. The scheme is based on lightweight elliptic curve scalar multiplication and supports multi-authority and verifiable outsourced decryption. The proposed scheme satisfies indistinguishability against chosen-plaintext attacks (CPA) under the elliptic curve decisional Diffie–Hellman (ECDDH) problem. Performance analysis shows that our proposed scheme is more efficient and better suited to the IoT environment compared to existing schemes.
Age-Related Changes in Postural Stability in Response to Varying Surface Instability in Young and Middle-Aged Adults
Authors: Promsri Arunee , Pitiwattanakulchai Punnakan , Saodan Siwaporn , Thiwan Salinrat
Published: October 2024

As individuals transition into middle age, subtle declines in postural control may occur due to gradual reductions in neuromuscular control. The current study aimed to examine the effect of age on bipedal postural control across three support surfaces with varying degrees of instability: a firm surface, a foam pad, and a multiaxial balance board. The effect of surface stability was also assessed. Postural accelerations were recorded using a tri-axial accelerometer placed over the lumbar spine (L5) in 24 young female adults (23.9 ± 5.3 years) and 24 middle-aged female adults (51.4 ± 5.9 years). Sample entropy (SampEn) was used to analyze the complexity of postural control by measuring the regularity of postural acceleration. The main results show significant age-related differences in the mediolateral and anteroposterior acceleration directions (p ≤ 0.012). Young adults exhibit more irregular fluctuations in postural acceleration (high SampEn), reflecting greater efficiency or automaticity in postural control compared to middle-aged adults. Increased surface instability also progressively decreases SampEn in the mediolateral direction (p < 0.001), reflecting less automaticity with increased instability. However, no interaction effects are observed. These findings imply that incorporating balance training on unstable surfaces might help middle-aged adults maintain postural control and prevent future falls.
Flowrate Sensing and Measurement in Portable Smart Inhalers
Authors: Mysovskikh Ivan , Legg Mathew , Demidenko Serge
Published: October 2024

This review discusses approaches and implementations of flowrate sensing and measurement in smart inhalers for effective respiratory disease management. It highlights the importance of compliance with proper inhaling techniques and consistent adherence for managing respiratory conditions. Methods and relevant commercial and prototype research-type devices for sensing and measuring inhalation flowrate in smart inhalers are studied and compared. The study argues that the utilisation of acoustic analysis and air-pressure sensing is a promising approach to detect and evaluate the inhaling action, ultimately allowing improvement in the treatment outcomes and life quality of patients with respiratory diseases.
Enhanced Wavelet-Based Medical Image Denoising with Bayesian-Optimized Bilateral Filtering
Authors: Taassori Mehdi
Published: October 2024

Medical image denoising is essential for improving the clarity and accuracy of diagnostic images. In this paper, we present an enhanced wavelet-based method for medical image denoising, aiming to effectively remove noise while preserving critical image details. After applying wavelet denoising, a bilateral filter is utilized as a post-processing step to further enhance image quality by reducing noise while maintaining edge sharpness. The bilateral filter’s effectiveness heavily depends on its parameters, which must be carefully optimized. To achieve this, we employ Bayesian optimization, a powerful technique that efficiently identifies the optimal filter parameters, ensuring the best balance between noise reduction and detail preservation. The experimental results demonstrate a significant improvement in image denoising performance, validating the effectiveness of our approach.
0.5 V, Low-Power Bulk-Driven Current Differencing Transconductance Amplifier
Authors: Kumngern Montree , Khateb Fabian , Kulej Tomasz
Published: October 2024

This paper presents a novel low-power low-voltage current differencing transconductance amplifier (CDTA). To achieve a low-voltage low-power CDTA, the BD-MOST (bulk-driven MOS transistor) technique operating in a subthreshold region is used. The proposed CDTA is designed in 0.18 µm CMOS technology, can operate with a supply voltage of 0.5 V, and consumes 1.05 μW of power. The proposed CDTA is used to realize a current-mode universal filter. The filter can realize five standard transfer functions of low-pass, band-pass, high-pass and band-stop, and all-pass from the same circuit. Neither component-matching conditions nor input signals of the inverse type are required to realize these filter functions. The current-mode filter offers low-input and high-output impedance and uses grounded capacitors. The natural frequency and quality factor of the filters can be orthogonally controlled. The proposed CDTA and its applications are simulated using SPICE to confirm the feasibility and functionality of the new circuits.
A 2.4 GHz High-Efficiency Rectifier Circuit for Ambient Low Electromagnetic Power Harvesting
Authors: Du Jinxin , Wang Ruimeng , Zheng Pingyi
Published: October 2024

A novel 2.4 GHz high-efficiency rectifier circuit suitable for working under very-low-input electromagnetic (EM) power conditions (−20 to −10 dBm) is proposed for typical indoor power harvesting. The circuit features a SMS7630 Schottky diode in a series with a voltage booster circuit at the front end and a direct-current (DC)-pass filter at the back end. The voltage booster circuit consists of an asymmetric coupled transmission line (CTL) and a high-impedance microstrip line (of 100 Ω instead of 50 Ω) to significantly increase the potential at the diode’s input, thereby enabling the diode to operate effectively even in very-low-power environments. The experimental measurements show that the microwave direct-current (MW-DC) conversion efficiency of the rectifier circuit reaches 31.1% at a −20 dBm input power and 62.4% at a −10 dBm input power, representing a 7.4% improvement compared to that of the state of the art. Furthermore, the rectifier circuit successfully shifts the input power level corresponding to the peak rectification efficiency from 0 dBm down to −10 dBm. This design is a promising candidate for powering low-energy wireless sensors in typical indoor environments (e.g., the home or office) with low EM energy density.
Enhancing Activity Recognition After Stroke: Generative Adversarial Networks for Kinematic Data Augmentation
Authors: Hadley Aaron J. , Pulliam Christopher L.
Published: October 2024

The generalizability of machine learning (ML) models for wearable monitoring in stroke rehabilitation is often constrained by the limited scale and heterogeneity of available data. Data augmentation addresses this challenge by adding computationally derived data to real data to enrich the variability represented in the training set. Traditional augmentation methods, such as rotation, permutation, and time-warping, have shown some benefits in improving classifier performance, but often fail to produce realistic training examples. This study employs Conditional Generative Adversarial Networks (cGANs) to create synthetic kinematic data from a publicly available dataset, closely mimicking the experimentally measured reaching movements of stroke survivors. This approach not only captures the complex temporal dynamics and common movement patterns after stroke, but also significantly enhances the training dataset. By training deep learning models on both synthetic and experimental data, we enhanced task classification accuracy: models incorporating synthetic data attained an overall accuracy of 80.0%, significantly higher than the 66.1% seen in models trained solely with real data. These improvements allow for more precise task classification, offering clinicians the potential to monitor patient progress more accurately and tailor rehabilitation interventions more effectively.
Recent Developments in Luteolin-Loaded Nanoformulations for Enhanced Anti-Carcinogenic Activities: Insights from In Vitro and In Vivo Studies
Authors: Mod Razif Muhammad Redza Fahmi , Chan Siok Yee , Chew Yik-Ling , Hassan Masriana , Ahmad Hisham Shairyzah , Abdul Rahman Shamima , Mai Chun-Wai , Teo Michelle Yee Mun , Kee Phei Er , Khoo Kuan Shiong , Lee Siew-Keah , Liew Kai Bin
Published: October 2024

With approximately 18 million people affected by cancer in 2020 globally, scientists are exploring innovative approaches to develop effective treatments for various types of cancer. Traditional chemotherapy drugs, although effective against cancer cells, often lead to significant side effects on healthy tissues, such as hair loss, anemia, and nausea. To discover safer alternatives, researchers are investigating natural bioactive compounds found abundantly in plants. Luteolin, a flavonoid found in celery and artichokes, stands out due to its diverse anti-carcinogenic properties, including inhibiting proliferation, inducing apoptosis, activating autophagy, and inhibiting angiogenesis and metastasis. However, the therapeutic potential of luteolin is hindered by challenges related to its bioavailability and solubility. This critical review explores the specific anti-carcinogenic properties of luteolin while analyzing the impact of its limited bioavailability and solubility on effectiveness. Additionally, it investigates the outcomes of encapsulating luteolin in nanoformulations, providing insights into potential strategies for enhancing its anti-carcinogenic effects. Finally, the review compares the efficacy of luteolin with and without nanoformulations. This review provides valuable insights into the potential of utilizing luteolin-loaded nanoformulations as a safer and more effective method for treating cancer, contributing to the ongoing efforts in improving cancer care and outcomes worldwide.
A Retrieval-Augmented Generation Approach for Data-Driven Energy Infrastructure Digital Twins
Authors: Ieva Saverio , Loconte Davide , Loseto Giuseppe , Ruta Michele , Scioscia Floriano , Marche Davide , Notarnicola Marianna
Published: October 2024

Digital-twin platforms are increasingly adopted in energy infrastructure management for smart grids. Novel opportunities arise from emerging artificial intelligence technologies to increase user trust by enhancing predictive and prescriptive analytics capabilities and by improving user interaction paradigms. This paper presents a novel data-driven and knowledge-based energy digital-twin framework and architecture. Data integration and mining based on machine learning are integrated into a knowledge graph annotating asset status data, prediction outcomes, and background domain knowledge in order to support a retrieval-augmented generation approach, which enhances a conversational virtual assistant based on a large language model to provide user decision support in asset management and maintenance. Components of the proposed architecture have been mapped to commercial-off-the-shelf tools to implement a prototype framework, exploited in a case study on the management of a section of the high-voltage energy infrastructure in central Italy.
Young Europeans’ Geo-Political Identities: A Poststructural Analysis
Authors: Ross Alistair
Published: October 2024

This study analyses the way young Europeans, aged between 10 and 20, construct their sense of identity with geo-political entities such as the nation, the state and the European Union; how these are expressed; and how young people manage the potential multiplicity of identities. It re-analyses earlier data, some 224 transcripts of young Europeans discussing their identities and sense of attachment to the geo-political entities of the state and the nation. This study looks specifically at how they discuss affiliations to a country or nation and does so within the historical context of the development of European nations in the 19th and 20th centuries and the ‘strict definition’ of nationality, as based on either birthplace or parentage. The young people’s discussions identify a wide range of reasons for attachment (or not) to one or more states: these include parentage, birthplace, passports, culture, language, residence, etc., many of which are incompatible with each other. Their response to this is often to profess multiple identities, switching to use that is most appropriate to a particular context or contingency. How does this behaviour meet the various models of identity formation, such as the psychosocial, the socio-cultural, and the poststructuralist? These young people also offer a range of qualities or values that they expect a state to uphold and deliver and are sometimes critical of states’ behaviour in this area. The combination of these attributes and qualities leads to a range of attitudes towards a polity or polities, ranging from acceptance of their status to indifference. The explanations suggested in this paper are that globalisation and migration have led to the realisation that the ‘strict definitions’ of nationality are no longer appropriate, and there are new potential attributes for identity, and secondly, that the development of supranational codification and the implementation of human rights are weakening the sovereignty of states. Together, these two factors reduce the perception of the requirement to develop a single overriding national identity. This combination of multiple identities and recognising the importance of human rights values is most commonly found amongst young people who have grown up in multicultural societies, often urban, and the corollary of this is that combination is least likely to be found among the older population in more rural, monocultural settlements.
Soil Physical Properties, Root Distribution, and “Ponkan” Tangerine Yield Across Different Rootstocks in a Deep Tillage Ultisol
Authors: Benevenute Pedro Antônio Namorato , Melo Laura Beatriz Batista , Barbosa Samara Martins , Domingues Mariany Isabela Soares , Vasques Isabela Cristina Filardi , Morais Everton Geraldo de , Castro Lucas Roberto de , Oliveira Geraldo César de , Ferreira Ester Alice , Silva Bruno Montoani
Published: October 2024

Deep soil tillage and proper rootstock selection mitigate the root development limitations in Ultisol’s Bt horizon, enhancing the citrus yield potential. This study evaluates the root spatial distribution of three Ponkan tangerine rootstocks in Ultisol under deep tillage alongside the physical-hydric attributes and plant measurements. The experimental area underwent furrow creation, subsoiling, and hole opening for planting. The treatments included three rootstocks: “Cravo Santa Cruz” (CSC), “Sunki Tropical” (ST), and “Citrandarin Índio” (CI). Under the Ultisol preparation, these rootstocks were compared to a native forest area (FA). Three years post-initial tillage, soil samples were collected at depths of 0–0.05, 0.35–0.40, and 0.45–0.50 m from the pre-established positions. The evaluation encompassed soil dispersive clay, available water, crop water use, plant measurement, and crop yield. The root evaluation utilized the crop profile method and 2D images, with subsequent surface mapping of the root variables, number (NR), and diameter (RD) analyzed via kriging geostatistical analysis. The Ultisol showed significant changes in its physical-hydric attributes regarding structural change and more excellent clay dispersion, with a considerable contribution to the micropore volume. Deep tillage effectively improved the root spatial distribution, especially concerning the number and diameter of roots, and enhanced the water use, reflected in the vegetative growth and yield, with the rootstock CSC standing out.
The Effect of Green Entrepreneurship Education on Green Entrepreneurial Intentions: A Case Study of the Guangxi Zhuang Autonomous Region, China
Authors: Yu Changliang , Yan Siqi , Zhang Xuelong
Published: October 2024

This study integrates the concept of green entrepreneurship into the entrepreneurship education system, and grasps the correct way to promote the green entrepreneurship intention of college students. The model of promoting college students’ green entrepreneurship intention with policy support is constructed to answer the following research questions: what is the internal mechanism of green entrepreneurship education in promoting green entrepreneurship intention of college students in Guangxi, and how does green entrepreneurship policy affect its internal mechanism? Through a questionnaire survey of 304 college students from major cities in Guangxi, China, this paper investigates how college green entrepreneurship education affects college students’ green entrepreneurship intention through the desirability and feasibility of green entrepreneurship and actively explores the regulatory role of the institutional environment. The results show that the desirability and feasibility of green entrepreneurship play a mediating role between green entrepreneurship education and the promotion of college students’ green entrepreneurship intention, and the regulatory environment positively moderates the positive effect of desirability and feasibility of green entrepreneurship on green entrepreneurship intention. This study contributes to the literature on green entrepreneurship. On the one hand, by studying the mediating mechanism of green entrepreneurship desirability and feasibility, this study has added empirical evidence on the promotion effect of green entrepreneurship education on the green entrepreneurship intention of college students. On the other hand, this study emphasizes the impact of policy regulation on the strengthening process of college students’ green entrepreneurial intention. This study will help to build a characteristic and effective green entrepreneurship education system in colleges and universities, enhance college students’ green entrepreneurship intention and green core competitiveness, and drive them to enhance their sense of social responsibility and build “green development” values.
Has the Policy of National Agricultural Green Development Pilot Zones Enhanced the Agricultural Eco-Efficiency? Observation Based on the County-Level Data from Hubei Province of China
Authors: Li Songbiao , Shangguan Lina
Published: October 2024

China’s agricultural green development is of great significance to protecting the ecological environment, ensuring food security, and promoting rural revitalization. This study considers China’s agricultural green development pilot zones policy as a natural experiment to examine its impact on regional agricultural eco-efficiency. Based on county-level data in Hubei Province from 2013 to 2021, the EBM-Undesirable model was employed to measure regional agricultural eco-efficiency. Then, the staggered DID model was conducted to estimate the policy impact. The results indicate that the pilot zones policy significantly enhances the agricultural eco-efficiency in the designated areas. The results from heterogeneity and mechanism analysis indicate that the pilot zones policy has a more substantial effect on the western region and less-affluent counties, and rural innovation serves as an intermediary variable for the policy to exert the “green” effect. Therefore, it is crucial for the government to consider regional disparities and the role of rural innovation when advancing policy implementation. Tailoring measures to suit specific local circumstances and consistently enhancing agricultural eco-efficiency in different regions is essential.
Textual Attributes of Corporate Sustainability Reports and ESG Ratings
Authors: Huang Jie , Wang Derek D. , Wang Yiying
Published: October 2024

While the textual attributes of corporate financial documents, such as annual reports, have been extensively analyzed in the academic literature, those of corporate sustainability reports, which serve as a critical channel for nonfinancial disclosure, are relatively under-explored. Given the increasing importance of Environmental, Social, and Governance (ESG) factors in corporate strategy and stakeholder evaluation, understanding the role of textual attributes in sustainability reporting is crucial. This study examines 10,021 hand-collected sustainability reports from Chinese firms between 2009 and 2021, focusing on six key textual attributes: length, readability, tone, boilerplate language, redundancy, and completeness. Using computational linguistics, we analyze how these attributes evolve over time and their impact on ESG ratings provided by both international (MSCI, FTSE) and domestic (SNSI) agencies. Our findings reveal that the length and completeness of sustainability reports significantly influence ESG scores across agencies, demonstrating a shared appreciation for detailed and transparent disclosures. However, international and domestic rating agencies exhibit differing responses to attributes like tone, boilerplate language, and redundancy. These differences highlight variations in evaluation standards, methodologies, and value orientations between global and local stakeholders. The results emphasize the need for firms to tailor their sustainability disclosures to meet diverse stakeholder expectations. This study contributes to the growing body of literature on nonfinancial reporting by providing empirical evidence on how specific textual characteristics of sustainability reports can shape ESG evaluations, offering insights for both corporate communicators and policymakers.
Promoting Sustainable Transportation: Factors Influencing Battery Electric Vehicle Adoption Across Age Groups in Thailand
Authors: Limpasirisuwan Natcha , Champahom Thanapong , Jomnonkwao Sajjakaj , Ratanavaraha Vatanavongs
Published: October 2024

Battery Electric Vehicles (BEVs) are a crucial innovation for achieving sustainable transportation and reducing greenhouse gas emissions, which are major contributors to global warming and climate change. While previous studies have explored attitudes towards BEV technology acceptance, few have examined the interplay of external factors such as government measures and adoption barriers in promoting sustainable mobility. This study addresses this gap by investigating the roles of government policies, usage obstacles and innovation diffusion in stimulating BEV purchase intentions, while applying the Innovative Diffusion Theory (IDT). Data from 3632 respondents in Thailand were analyzed using structural equation modeling (SEM) to examine causal relationships between factors. The results indicate that government policies supporting BEV users enhance innovation diffusion in society, leading to increased adoption intentions. Furthermore, effective policies help mitigate barriers to BEV usage, further encouraging adoption. The study also reveals that causal relationships of BEV usage intentions vary across age groups, highlighting the need for targeted approaches in promoting sustainable transportation. These findings contribute to the development of evidence-based policy recommendations to accelerate BEV adoption, supporting Thailand’s Carbon Neutrality goals and broader sustainable development objectives. By elucidating the complex dynamics of BEV adoption, this research provides valuable insights for policymakers and stakeholders working towards a more sustainable and environmentally friendly transportation sector.
Advances in Nanotechnology for Sustainable Agriculture: A Review of Climate Change Mitigation
Authors: Quintarelli Valentina , Ben Hassine Mortadha , Radicetti Emanuele , Stazi Silvia Rita , Bratti Alessandro , Allevato Enrica , Mancinelli Roberto , Jamal Aftab , Ahsan Muhammad , Mirzaei Morad , Borgatti Daniele
Published: October 2024

Currently, one of the main challenges is the mitigation of the effects of climate change on the agricultural sector. Conventional agriculture, with the intensive use of herbicides and pesticides to control weeds and pests, and the improper use of mineral fertilizers, contributes to climate change by causing increased greenhouse gases and groundwater pollution. Therefore, more innovative technologies must be used to overcome these problems. One possible solution is nanotechnology, which has the potential to revolutionize the conventional agricultural system. Active nanoparticles can be used both as a direct source of micronutrients and as a delivery platform for bioactive agrochemicals to improve crop growth, yield, and quality. The use of nanoparticle formulations, including nano-pesticides, nano-herbicides, nano-fertilizers, and nano-emulsions, has been extensively studied to improve crop health and shelf-life of agricultural products. Comprehensive knowledge of the interactions between plants and nanoparticles opens up new opportunities to improve cropping practices through the enhancement of properties such as disease resistance, crop yield, and nutrient use. The main objective of this review is to analyze the main effects of climate change on conventional agricultural practices, such as the use of pesticides, herbicides, and fertilizers. It also focuses on how the introduction of nanoparticles into conventional practices can improve the efficiency of chemical pest control and crop nutrition. Finally, this review examines in depth the last 10 years (2014–2024) of scientific literature regarding the use of nanoparticles in agriculture to mitigate the effects of climate change.
Integrating Management Strategy and Porter’s Five Forces Model for the Sustainable Recycling of Textile Waste
Authors: Šimonová Timea , Malindzakova Marcela , Malindzak Dusan
Published: October 2024

The purpose of this paper was to address the compatibility of management strategies with the competitive needs of textile waste recycling companies by applying Porter’s model. In conjunction with Porter’s model, it is appropriate to assess the attractiveness of the industry based on the balance of opportunities and threats, which determines whether the industry is attractive or less attractive. From this assessment, it is possible to decide whether to remain in the given industry and to identify strategies that indicate success. In terms of the European Green Agreement, it is necessary to ensure the faster and more efficient development of the circular economy, with a focus on resource-intensive sectors, including the textile industry. Given the adoption of the EU Strategy for Sustainable and Circular Textiles in June 2023, it is essential to address the issue of sustainable textile waste recycling. The importance of this strategy lies in strengthening the industry through reuse and repairs, as well as addressing the problem of textile waste. The prioritization of textile waste recycling has gained even greater importance with the arrival of the new automotive company, Volvo Cars, in eastern Slovakia. This development underscores the need for enhanced recycling efforts to manage the expected increase in industrial textile waste associated with the automotive sector’s expansion in the region. In Slovakia, four companies are involved in textile waste recycling: SK-TEX s.r.o., PR Krajné s.r.o., HOVEBA s.r.o., and LYKOTEX Slovakia s.r.o. This paper provides information on the possibility of expanding textile waste recycling capacities in eastern Slovakia. The quadratic graph method was used to identify an optimal location for textile waste recycling. The results of this analysis will help determine which enterprise in eastern Slovakia can enhance its competitiveness by leveraging this strategic location.
Sustainable Utilization of Waste Pumice Powder in Slag-Based Geopolymer Concretes: Fresh and Mechanical Properties
Authors: Safari Zrar , Younis Khaleel H. , Kamal Ibtisam
Published: October 2024

In societies worldwide, there is significant pressure on the construction industry to employ waste/recycled materials instead of natural-sourced materials to develop infrastructures to mitigate negative environmental consequences. This study investigated the feasibility of using waste pumice powder as a binder in place of granular blast-furnace slag to manufacture geopolymer concrete. Three sets of GC mixes were developed with three ratios of alkaline activator/binder (A/B) of 0.45, 0.5, and 0.55. Eight GC mixes were prepared for each set, with eight replacement ratios of GGBFS with WPP (0%, 30%, 50%, 60%, 70%, 80%, 90%, and 100%). The influence of WPP addition as a substitute source of aluminosilicate precursors on the fresh (workability and setting time), mechanical (compressive strength and flexural strength), physical characteristics (density and water absorption), and microstructure morphology of WPP/slag-based geopolymers were studied. A linear correlation between UPV and compressive strength was found. The results revealed that setting times and workability are affected by the A/B ratio and content of WPP. WPP reduces the workability and increases setting time (both initial and final). There was a drop in compressive and flexural strengths as the percentage of WPP in the GC increased. The maximum compressive (60 MPa) and flexural strength (4.96 MPa) at an A/B ratio of 0.45 for a 100% slag content mix were obtained. However, a GC mix containing 50% WPP and 50% slag with a compressive strength of 28 MPa after 28 days of curing at ambient temperature was achieved, which is acceptable for structural applications.
A Survey of Dynamical and Gravitational Lensing Tests in Scale Invariance: The Fall of Dark Matter?
Authors: Maeder André , Courbin Frédéric
Published: October 2024

We first briefly review the adventure of scale invariance in physics, from Galileo Galilei, Weyl, Einstein, and Feynman to the revival by Dirac (1973) and Canuto et al. (1977). In the way that the geometry of space–time can be described by the coefficients gμν, a gauging condition given by a scale factor λ(xμ) is needed to express the scaling. In general relativity (GR), λ=1. The “Large Number Hypothesis” was taken by Dirac and by Canuto et al. to fix λ. The condition that the macroscopic empty space is scale-invariant was further preferred (Maeder 2017a), the resulting gauge is also supported by an action principle. Cosmological equations and a modified Newton equation were then derived. In short, except in extremely low density regions, the scale-invariant effects are largely dominated by Newtonian effects. However, their cumulative effects may still play a significant role in cosmic evolution. The theory contains no “adjustment parameter”. In this work, we gather concrete observational evidence that scale-invariant effects are present and measurable in astronomical objects spanning a vast range of masses (0.5 M⊙< M <1014M⊙) and an equally impressive range of spatial scales (0.01 pc < r < 1 Gpc). Scale invariance accounts for the observed excess in velocity in galaxy clusters with respect to the visible mass, the relatively flat/small slope of rotation curves in local galaxies, the observed steep rotation curves of high-redshift galaxies, and the excess of velocity in wide binary stars with separations above 3000 kau found in Gaia DR3. Last but not least, we investigate the effect of scale invariance on gravitational lensing. We show that scale invariance does not affect the geodesics of light rays as they pass in the vicinity of a massive galaxy. However, scale-invariant effects do change the inferred mass-to-light ratio of lens galaxies as compared to GR. As a result, the discrepancies seen in GR between the total lensing mass of galaxies and their stellar mass from photometry may be accounted for. This holds true both for lenses at high redshift like JWST-ER1 and at low redshift like in the SLACS sample. Of note is that none of the above observational tests require dark matter or any adjustable parameter to tweak the theory at any given mass or spatial scale.
Associations Between Inter-Limb Asymmetry in Lower Limb Strength and Jump Performance in 14–15-Year-Old Basketball Players
Authors: Ding Ling , Lyu Mengde , Chen Zhili , Wu Junyu , Wang Yufei , Bishop Chris , Li Youqiang
Published: October 2024

This study aims to (1) assess the inter-limb asymmetry in hip, knee, and ankle strength and countermovement jump (CMJ) performance among adolescent basketball players and (2) examine the relationship between inter-limb asymmetry and CMJ performance. Moreover, 30 adolescent basketball players (15 boys and 15 girls) aged 14 to 15 years participated in this study. The strength of the lower limb joints was measured using an isokinetic dynamometer at a speed of 60 degrees per second. Three maximal CMJs were performed, and the highest jump was used for the final analysis. The subjects were median-split into high-asymmetry (n = 15) and low-asymmetry (n = 15) groups based on the calculated strength asymmetry scores. The asymmetry scores were calculated using the formula: (dominant–non-dominant)/dominant* 100%. The inter-limb asymmetry data ranged from 12.2% to 21.6%. A Spearman correlation analysis showed that only the inter-limb asymmetry of the ankle plantar flexor was significantly correlated with the CMJ heights (ρ = −0.56, p = 0.001). An independent t-test revealed no significant differences in strength asymmetry between boys and girls (all p > 0.05). The low-asymmetry group demonstrated significantly greater CMJ performance compared to the high-asymmetry group (ES = 1.11, 95% CI = 0.34–1.87, p = 0.007), indicating that inter-limb asymmetry of the ankle plantar flexor has a significant negative impact on CMJ performance. Coaches should focus on enhancing both the strength and symmetry of the ankle joints to improve athletic performance and prevent injuries in sports, where jumping is a common movement.
Evolution of Self-Gravitating Fluid Spheres Involving Ghost Stars
Authors: Herrera Luis , Di Prisco Alicia , Ospino Justo
Published: October 2024

Exact solutions are presented which describe, either the evolution of fluid distributions corresponding to a ghost star (vanishing total mass), or describing the evolution of fluid distributions which attain the ghost star status at some point of their lives. The first two solutions correspond to the former case, they admit a conformal Killing vector (CKV) and describe the adiabatic evolution of a ghost star. Other two solutions corresponding to the latter case are found, which describe evolving fluid spheres absorbing energy from the outside, leading to a vanishing total mass at some point of their evolution. In this case the fluid is assumed to be expansion–free. In all four solutions the condition of vanishing complexity factor was imposed. The physical implications of the results, are discussed.
Exploring the Role of Top Management Team Diversity and Absorptive Capacity in the Relationship Between Corporate Environmental, Social, and Governance Performance and Firm Value
Authors: Li Qianru , Zhang Yuhao , Yan Jinzhe
Published: October 2024

Environmental, social, and governance (ESG) performance is a key indicator of a firm’s long-term value and competitiveness. This study combined internal management dynamics (TMT diversity and absorptive capacity) and external social responsibility (ESG) to provide a more holistic perspective that explores the relationship between ESG performance and corporate value at multiple levels. In this study, Chinese A-share listed companies from 2011 to 2022 were selected and analyzed using a quantitative approach. The findings are as follows: (1) There is a positive correlation between ESG performance and firm value. (2) This relationship is particularly accentuated within non-high-polluting industries, the eastern and middle region, and non-state-owned firms. (3) The age, gender, financial background, and absorptive capacity of TMTs significantly moderate the relationship between corporate ESG performance and firm value. These findings will help business leaders and policymakers understand how effective management and responsibility practices can drive long-term business success and social impact. These findings not only help academics deepen their theoretical constructs but also provide operational guidance for business practices.
Exploring Human Misuse and Abuse of Veterinary Drugs: A Descriptive Pharmacovigilance Analysis Utilising the Food and Drug Administration’s Adverse Events Reporting System (FAERS)
Authors: Dunn Josie , Schifano Fabrizio , Dudley Ed , Guirguis Amira
Published: October 2024

Introduction: Evidence suggests an increasing misuse of veterinary medicines by humans. This study aims to analyse Adverse Events (AEs) associated with selected veterinary products using the Food and Drug Administration Adverse Events Reporting System (FAERS). Methods: A descriptive pharmacovigilance analysis was conducted on AEs related to 21 drugs approved for human and/or animal use. Results: A total of 38,756 AEs, including 9566 fatalities, were identified. The United States reported the highest number of cases (13,532), followed by Canada (2869) and the United Kingdom (1400). Among the eight drugs licenced exclusively for animals, levamisole, pentobarbital, and xylazine were most frequently reported. Reports predominantly involved males (57%) from the 18–64 age group, with incidents related mainly to overdose, dependence, and multi-agent toxicities. Unmasking techniques revealed ‘intentional overdose’ as the primary reaction. Polysubstance use was evident in 90% of the drugs, with benzodiazepines/Z-drugs and opioids as common co-used classes. Conclusions: Veterinary medications are increasingly infiltrating the illicit drug market due to their pharmacological properties. This trend highlights the need for heightened vigilance and awareness to prevent further public health risks associated with the adulteration of illicit substances with veterinary products like xylazine and pentobarbital.
Assessing the Arsenic Contents and Associated Risks in Groundwater of Vehari and Lodhran Districts, Pakistan
Authors: Khalid Sana , Shahid Muhammad , Bibi Irshad , Nadeem Hafiz Muhammad , Younis Muhammad , Natasha Natasha , Murtaza Behzad , Niazi Nabeel Khan
Published: October 2024

Exposure to arsenic (As) can induce numerous lethal diseases, such as cancer, cardiovascular issues, skin diseases, and diabetes in humans. The major route of human and animal exposure to As is through drinking As-rich groundwater. This study assessed As occurrence in the groundwater of two districts in the Punjab (Vehari and Lodhran) provinces of Pakistan. Groundwater analysis revealed an average As concentration of 7.7 µg/L (n = 79) in the study area, with a maximum As concentration up to 41.4 µg/L (33% of samples exceeding the WHO limit of 10 µg/L). Arsenic traces were found in animal milk (n = 15, mean: 0.79 µg/L, 17% exceeding 2.0 µg/L), human hair (n = 12, mean: 0.36 µg/g, 17% exceeding 1.0 µg/g), and human nails (n = 8, mean: 0.03 µg/g, none of the samples exceeded 1.0 µg/g). Health risk assessment indices revealed that about 33% of the hazard quotient and 54% of the cancer risk factor exceeded their thresholds. Despite the low–moderate As concentration in groundwater and the accumulation of As in a few biological samples, there is a possibility of potential As poisoning via the long-term and continuous use of groundwater for drinking. Monitoring and blanket testing of wells for As in well water can provide baseline data to minimize the threat of As-mediated arsenicosis in As-affected areas of Pakistan. Moreover, a detailed study of potential As accumulation in biological samples with a higher number of samples is recommended in the area.