bluuebunny/crossref_metadata_2025 huggingface dataset:
Response of Crop Yield and Productivity Contribution Rate to Long-Term Different Fertilization in Northeast of China
Authors: Ma Xingzhu , Hao Xiaoyu , Zhao Yue , Peng Xinhua , Ji Jinghong , Liu Shuangquan , Zheng Yu , Sun Lei , Zhou Baoku
Published: January 2025

To reveal the changes in crop yield and contribution rate of black soil productivity under long-term different fertilization conditions in black soil areas and to find the important significance of fertilization for sustainable and stable crop yield, high yield, and improving the contribution rate of black soil nutrients. Based on the long-term experiment of black soil fertility in Harbin, the Ministry of Agriculture and Rural Affairs, under the maize–wheat–soybean rotation system, crop yield, sustainability and stability of yield, the contribution rate of black soil productivity, and natural nutrient supply capacity under 10 fertilization treatments (CK, NP, NK, PK, NPK, M, MNP, MNK, MPK, and MNPK) were analyzed. Results showed that, compared with the treatment of chemical fertilizer, yields of maize, wheat, and soybeans increased under treatment of organic fertilizer combined with chemical fertilizer, among which the yields of maize and wheat changed the most. As the rotation period lengthened, the sustainable yield index (SYI) values of chemical fertilizer treatment and its combination with organic fertilizer treatment gradually decreased. During the rotation period, the SYI value follows: chemical fertilizer combined with organic fertilizer > chemical fertilizer > organic fertilizer. The coefficient of variation (CV) of yield stability showed an overall trend of increasing first and then decreasing, with individual treatments showing a gradual increasing trend (NP and NPK; MNP and MNPK). Under different rotation periods, the overall contribution rate of soil productivity of long-term organic fertilizer combined with chemical fertilizer treatment was higher than that of single chemical fertilizer treatment. With the extension of the rotation period, the contribution rate of soil productivity of NPK treatment was higher and slightly increased, while other treatments showed a downward trend. Although the contribution rate of soil productivity of organic–inorganic fertilizer combined treatment (MNP and MNK) showed a downward trend, it still remained at a high level (97.2% and 95.9%). In addition, the black soil has strong phosphorus and potassium supply capacity; nitrogen was lower than those two elements, with an average natural potassium supply capacity of 94.0–97.1%. Therefore, the combination of organic and inorganic fertilizers is one of the most effective fertilization measures to stabilize crop yield in the black soil region. Nitrogen fertilizer, as a limiting factor for crop growth in the black soil region, should be emphasized in its application.
Development and Validation of Multiplex-PCR Assay for β-Carotene hydroxylase and γ-Tocopherol methyl transferase Genes Governing Enhanced Multivitamins in Maize for Its Application in Genomics-Assisted Breeding
Authors: Gowda Munegowda Manoj , Muthusamy Vignesh , Chhabra Rashmi , Duo Hriipulou , Pal Saikat , Gain Nisrita , Katral Ashvinkumar , Kasana Ravindra K. , Zunjare Rajkumar U. , Hossain Firoz
Published: January 2025

Traditional maize possesses low concentrations of provitamin-A and vitamin-E, leading to various health concerns. Mutant alleles of crtRB1 and vte4 that enhance β-carotene (provitamin-A) and α-tocopherol (vitamin-E), respectively, in maize kernels have been explored in several biofortification programs. For genetic improvement of these target nutrients, uniplex-PCR assays are routinely used in marker-assisted selection. However, due to back-to-back breeding seasons, the time required for genotyping individually for each target gene in large backcross populations becomes a constraint for advancing the generations. Additionally, multiple PCR assays for various genes increase the required costs and resources. Here, we aimed to develop a multiplex-PCR assay to simultaneously identify different allelic forms of crtRB1 and vte4 genes and validate them in a backcross-based segregating population. The PCR assay was carried out using newly developed primers for crtRB1 and a gene-specific primer for vte4. The uniplex-PCR assay was standardized for selected primer pairs in the BC1F1 population segregating for crtRB1 and vte4 genes. Subsequently, a multiplex-PCR assay for crtRB1 and vte4 genes was developed and employed for genotyping in the BC1F1 population. The assay differentiated among four possible genotypic classes, namely crtRB1+crtRB1/vte4+vte4, crtRB1crtRB1/vte4+vte4, crtRB1+crtRB1/vte4+vte4+, and crtRB1crtRB1/vte4+vte4+. This newly developed multiplex-PCR assay saved 41.7% of the cost and 35.6% of the time compared to two individual uniplex-PCR assays. The developed assay could accelerate maize nutritional quality breeding programs through rapid and cost-effective genotyping for the target genes. This is the first report of a multiplex-PCR assay specific to crtRB1 and vte4 genes for its use in genomics-assisted breeding in maize.
Assessing Vegetation Canopy Growth Variations in Northeast China
Authors: Lu Lijie , Yu Lingxue , Li Xuan , Gao Li , Bao Lun , Chang Xinyue , Gao Xiaohong , Cai Zhongquan
Published: January 2025

Studying climate change’s impact on vegetation canopy growth and senescence is significant for understanding and predicting vegetation dynamics. However, there is a lack of adequate research on canopy changes across the lifecycles of different vegetation types. Using GLASS LAI (leaf area index) data (2001–2020), we investigated canopy development (April–June), maturity (July–August), and senescence (September–October) rates in Northeast China, focusing on their responses to preseason climatic factors. We identified that early stages saw canopy development acceleration, with over 71% of areas experiencing such acceleration in April and May. As the vegetation grew, the accelerating canopy development slowed down, and the canopy reached its maturation earlier. By analyzing the partial correlation between canopy growth and preseason climatic factors, it was identified that changes in canopy growth were most significantly affected by preseason air temperature. A positive correlation was observed in the early stages, which shifted to a negative correlation during canopy maturation and senescence. Notably, the transition timing varied among different vegetation types, with grasslands (June) occurring earlier than forests (July) and farmlands (August). Additionally, grassland canopy growth showed a stronger response to precipitation than forests and farmlands, with a lagged effect of 2.50 months. Our findings improve understanding of vegetation canopy growth across different stages, holding significant importance for ecological environmental monitoring, land-use planning, and sustainable development.
Representing Structural Isomer Effects in a Coarse-Grain Model of Poly(Ether Ketone Ketone)
Authors: Jones Chris D. , Fothergill Jenny W. , Barrett Rainier , Ghanbari Lina N. , Enos Nicholas R. , McNair Olivia , Wiggins Jeffrey , Jankowski Eric
Published: January 2025

To improve the computational accessibility of the time and length scales required for studying fusion welding of thermoplastic interfaces via molecular dynamics, we develop a coarse-grained (CG) model of poly(etherketoneketone) (PEKK), a high-performance thermoplastic whose use in aerospace composites offers advantages over thermosets, including the ability to weld parts and reduce reliance on mechanical fasteners and adhesives. PEKK can be synthesized with varying para (T) and meta (I) linkages—described by the T/I ratio—which affect backbone structure and influence properties such as melting, crystallization kinetics, and stress relaxation times, while leaving the glass transition temperature unaffected. Our CG model accurately replicates the bulk morphology and polymer chain structure of an underlying united atom model, and captures key T/I-dependent effects, including the observed trends in stress relaxation and the invariance of the glass transition temperature. This model achieves the computational efficiency necessary to explore polymer diffusion and entanglement in welded interfaces, providing a valuable tool for advancing the use of thermoplastics in aerospace applications.
Carbon Nanotube/Polymer Composites for Functional Applications
Authors: Yim Yoon-Ji , Yoon Young-Hoon , Kim Seong-Hwang , Lee Jeong-Hoon , Chung Dong-Chul , Kim Byung-Joo
Published: January 2025

Carbon nanotubes (CNTs) have garnered significant interest in the field of nanotechnology owing to their unique structure and exceptional properties. These materials find applications across a diverse array of fields, including electronics, environmental science, energy, and biotechnology. CNTs serve as potent reinforcing agents in polymer composites; even minimal additions can significantly improve the mechanical, electrical, and thermal properties of polymers. With the growing demand for polymer composites across various industries, there is an anticipation for CNT/polymer composites to evolve in increasingly diverse directions. This paper reviews recent advancements in the manufacturing techniques of various CNT/polymer composites and discusses the enhancements in their mechanical, electrical, and thermal properties. Furthermore, it explores the potential applications of these composites.
Artificial Intelligence-Driven Modeling for Hydrogel Three-Dimensional Printing: Computational and Experimental Cases of Study
Authors: Bediaga-Bañeres Harbil , Moreno-Benítez Isabel , Arrasate Sonia , Pérez-Álvarez Leyre , Halder Amit K. , Cordeiro M. Natalia D. S. , González-Díaz Humberto , Vilas-Vilela José Luis
Published: January 2025

Determining the values of various properties for new bio-inks for 3D printing is a very important task in the design of new materials. For this purpose, a large number of experimental works have been consulted, and a database with more than 1200 bioprinting tests has been created. These tests cover different combinations of conditions in terms of print pressure, temperature, and needle values, for example. These data are difficult to deal with in terms of determining combinations of conditions to optimize the tests and analyze new options. The best model demonstrated a specificity (Sp) of 88.4% and a sensitivity (Sn) of 86.2% in the training series while achieving an Sp of 85.9% and an Sn of 80.3% in the external validation series. This model utilizes operators based on perturbation theory to analyze the complexity of the data. For comparative purposes, neural networks have been used, and very similar results have been obtained. The developed tool could easily be applied to predict the properties of bioprinting assays in silico. These findings could significantly improve the efficiency and accuracy of predictive models in bioprinting without resorting to trial-and-error tests, thereby saving time and funds. Ultimately, this tool may help pave the way for advances in personalized medicine and tissue engineering.
Fine-Tuning the Physicochemical Properties of Poly(lactic Acid) Nanoparticles for the Controlled Release of the BET Inhibitor JQ1: Influence of PVA Concentration
Authors: Kedjar Nedjla , Iannuzzi Eleonora , Kreuzer Martin , Alonso-Moreno Carlos , Moya-Lopez Carmen
Published: January 2025

The compounds targeting the bromo and extra terminal domain proteins (BET), such as the JQ1, present potent anti-cancer activity in preclinical models, however, the application of JQ1 at the clinical level is limited by its short half-life, rapid clearance, and non-selective inhibition of BET family proteins, leading to off-target effects and resistance. To address these challenges, the optimization of JQ1 delivery has been accomplished through polylactide (PLA) nanoparticles. PLA derivatives with varying molecular weights were synthesized via ring-opening polymerization using a zinc-based initiator and characterized using thermogravimetric analysis, differential scanning calorimetry, and infrared spectroscopy. PLA nanoparticles (NPs) were subsequently formulated, and the effects of key parameters—including PLA molecular weight, organic phase concentration, and surfactant concentration—on particle size, polydispersity index (PDI), and encapsulation efficiency were systematically investigated. PLA molecular weight and organic phase concentration mainly influenced the NPs size whilst the thermodynamic state of the NPs was unaffected by these two parameters. The surfactant concentration is correlated to the encapsulation efficacy of JQ1 as well as the release profile, suggesting the potential tool that the variation of these parameters represent for customizing the release of JQ1 according to specific needs.
CFD Simulation of Fluid Flow and Combustion Characteristics in Aero-Engine Combustion Chambers with Single and Double Fuel Inlets
Authors: Agarwal Abhishek , Kalenga Michel Kalenga Wa , Ilunga Masengo
Published: January 2025

Gas turbine engines are used in many applications such as power plants and aircrafts. The energy generated through fuel combustion has a significant impact on fluid flow characteristics and thrust force produced by gas turbine engines. This energy generation is based on the precise mixing of fuel and air with known proportions. The present research work attempts to examine the characteristics of fluid flow for aero-engine combustion in a chamber with either a single fuel inlet or multiple fuel inlets using the computational fluid dynamics (CFD) technique. Developed in Creo-6.0 parametric design software, the combustion chamber was modeled and simulated using the ANSYS CFX simulation platform to determine the pressure and other fluid flow-induced characteristics. The analysis was performed for both single fuel inlet and multiple fuel inlet combustion chamber designs. The outlet pressure of the combustion chamber is a key parameter in determining the combustion characteristics and subsequent gas expansion in gas turbine performance. Our results indicated that the outlet pressure from the double fuel inlet design was 49.04% higher than the single fuel inlet design. The thrust force (propulsion) in gas turbine engines is a result of the mass flow rate of exhaust gasses, as quantified by the gas exit velocity. Induced thrust on a combustor with double fuel inlet was 48.3% higher than the induced thrust in the single fuel inlet design, making the double fuel inlet design a more viable option. The higher outlet pressure obtained in the double fuel inlet design showed higher enthalpy generation and greater energy conversion into thrust. The cause of this higher enthalpy is attributed to better fuel combustion in the primary zone. It appears that the double fuel inlet design could improve total turbine efficiency, reduce fuel consumption, and lower emissions.
Execute Justice and Charity for Your People: Jewish Divorce Mediation as a Model for Intrareligious Peacekeeping
Authors: Nissel Sarah M.
Published: January 2025

This article explores the complex issue of disharmony within religious marriages, focusing on Jewish approaches to divorce. Contrasting Jewish divorce mediation with other religions’ approaches to marital conflict, this article examines two Judaic models: one viewing divorce as a severe remedy permissible only under certain circumstances, and the other allowing for divorce when a marriage is irreparably broken. The author highlights the positive Jewish commandment to peacefully divorce, discussing how mediation integrates compassion and justice, in line with Jewish legal and ethical traditions. This work emphasizes the benefits of community-based divorce mediation, including lower costs, shorter timelines, and increased communal acceptance. Jewish divorce mediation, the author argues, is particularly effective in maintaining child-centeredness and co-parenting relationships post-divorce. This article calls for a broader adoption of Jewish divorce mediation through charitable organizations to effectuate Jewish family values and provide amicable resolutions within the Jewish community.
Advancements in Vision–Language Models for Remote Sensing: Datasets, Capabilities, and Enhancement Techniques
Authors: Tao Lijie , Zhang Haokui , Jing Haizhao , Liu Yu , Yan Dawei , Wei Guoting , Xue Xizhe
Published: January 2025

Recently, the remarkable success of ChatGPT has sparked a renewed wave of interest in artificial intelligence (AI), and the advancements in Vision–Language Models (VLMs) have pushed this enthusiasm to new heights. Differing from previous AI approaches that generally formulated different tasks as discriminative models, VLMs frame tasks as generative models and align language with visual information, enabling the handling of more challenging problems. The remote sensing (RS) field, a highly practical domain, has also embraced this new trend and introduced several VLM-based RS methods that have demonstrated promising performance and enormous potential. In this paper, we first review the fundamental theories related to VLM, then summarize the datasets constructed for VLMs in remote sensing and the various tasks they address. Finally, we categorize the improvement methods into three main parts according to the core components of VLMs and provide a detailed introduction and comparison of these methods.
Validation of an AMSR2 Thin-Ice Thickness Algorithm for Global Sea-Ice-Covered Oceans Using Satellite and In Situ Observations
Authors: Nakata Kazuki , Kachi Misako , Shimada Rigen , Yoshizawa Eri , Ito Masato , Ohshima Kay I.
Published: January 2025

The detection of thin-ice thickness using satellite microwave radiometers is a strong tool for estimating sea-ice production in coastal polynyas, which leads to dense water formation driving ocean thermohaline circulation. Thin-ice areas are classified into two ice types: active frazil, comprising frazil ice and open water, and thin solid ice, areas of relatively uniform thin ice. A thin-ice algorithm for AMSR-E has been developed to classify these two ice types and estimate ice thickness of <20 cm. In this study, we validate the applicability of the algorithm to the successor, AMSR2, using validation data of ice types identified from Sentinel-1 and ice thickness derived from MODIS. The validation results show an ice-type misclassification rate of ~3% and mean absolute errors in ice thickness of 2.0 cm and 5.0 cm for active frazil and thin solid ice, respectively. These values are similar to those for AMSR-E, indicating that the thin-ice algorithm can be applied to AMSR2. Further validations with the moored ADCP backscattering data capturing underwater frazil ice signals demonstrate that the algorithm can accurately distinguish between two ice types and effectively detect deep-penetrating frazil ice. The AMSR2 thin-ice thickness data has been released as a JAXA research product.
Deep BiLSTM Attention Model for Spatial and Temporal Anomaly Detection in Video Surveillance
Authors: Natha Sarfaraz , Ahmed Fareed , Siraj Mohammad , Lagari Mehwish , Altamimi Majid , Chandio Asghar Ali
Published: January 2025

Detection of anomalies in video surveillance plays a key role in ensuring the safety and security of public spaces. The number of surveillance cameras is growing, making it harder to monitor them manually. So, automated systems are needed. This change increases the demand for automated systems that detect abnormal events or anomalies, such as road accidents, fighting, snatching, car fires, and explosions in real-time. These systems improve detection accuracy, minimize human error, and make security operations more efficient. In this study, we proposed the Composite Recurrent Bi-Attention (CRBA) model for detecting anomalies in surveillance videos. The CRBA model combines DenseNet201 for robust spatial feature extraction with BiLSTM networks that capture temporal dependencies across video frames. A multi-attention mechanism was also incorporated to direct the model’s focus to critical spatiotemporal regions. This improves the system’s ability to distinguish between normal and abnormal behaviors. By integrating these methodologies, the CRBA model improves the detection and classification of anomalies in surveillance videos, effectively addressing both spatial and temporal challenges. Experimental assessments demonstrate that the CRBA model achieves high accuracy on both the University of Central Florida (UCF) and the newly developed Road Anomaly Dataset (RAD). This model enhances detection accuracy while also improving resource efficiency and minimizing response times in critical situations. These advantages make it an invaluable tool for public safety and security operations, where rapid and accurate responses are needed for maintaining safety.
Validity Identification and Rectification of Water Surface Fast Fourier Transform-Based Space-Time Image Velocimetry (FFT-STIV) Results
Authors: Zhang Zhen , Chen Lin , Yuan Zhang , Gao Ling
Published: January 2025

Fast Fourier Transform-based Space-Time Image Velocimetry (FFT-STIV) has gained considerable attention due to its accuracy and efficiency. However, issues such as false detection of MOT and blind areas lead to significant errors in complex environments. This paper analyzes the causes of FFT-STIV gross errors and then proposes a method for validity identification and rectification of FFT-STIV results. Three evaluation indicators—symmetry, SNR, and spectral width—are introduced to filter out invalid results. Thresholds for these indicators are established based on diverse and complex datasets, enabling the elimination of all erroneous velocities while retaining 99.83% of valid velocities. The valid velocities are then combined with the distribution law of section velocity to fit the velocity curve, rectifying invalid results and velocities in blind areas. The proposed method was tested under various water levels, weather conditions, and lighting scenarios at the Panzhihua Hydrological Station. Results demonstrate that the method effectively identifies FFT-STIV results and rectifies velocities in diverse environments, outperforming FFT-STIV and achieving a mean relative error (MRE) of less than 8.832% within 150 m. Notably, at night with numerous invalid STIs at a distance, the proposed method yields an MRE of 4.383% after rectification, outperforming manual labeling.
Spectral Content Effects Study in Non-Contact Resonance Ultrasound Spectroscopy
Authors: Tayyib Muhammad , Svilainis Linas
Published: January 2025

The application of spread-spectrum signals (arbitrary pulse width and position (APWP) sequences) in air-coupled resonant ultrasound spectroscopy is studied. It was hypothesized that spread-spectrum signal optimization should be based on te signal to noise ratio (SNR). Six APWP signal optimization criteria were proposed for this purpose. Experimental measurements were conducted using a thin polycarbonate sample using two standard spread-spectrum signals, linear and nonlinear frequency modulation, together with six optimized APWP signals. It was found that the performance of APWP signals derived from linear frequency modulation was better. The two best performing optimization criteria are SNR improvement on a linear scale with the SNR as an additional weight and energy improvement on a dB scale. The influence of spectral coverage on measurement errors was evaluated. It was found that it is sufficient to cover the sample resonance peak and the valley. The lowest error rates for density, 3%, and for thickness, 3.5%, were achieved when the upper valley was covered. For velocity, the best result, 5%, was achieved when the lower valley was covered. The lowest error rate for attenuation, 3.8%, was achieved in the case when both valleys were covered. Yet no significant performance degradation was noted when a whole −30 dB passband was covered.
Movement Disorders and Smart Wrist Devices: A Comprehensive Study
Authors: Caroppo Andrea , Manni Andrea , Rescio Gabriele , Carluccio Anna Maria , Siciliano Pietro Aleardo , Leone Alessandro
Published: January 2025

In the medical field, there are several very different movement disorders, such as tremors, Parkinson’s disease, or Huntington’s disease. A wide range of motor and non-motor symptoms characterizes them. It is evident that in the modern era, the use of smart wrist devices, such as smartwatches, wristbands, and smart bracelets is spreading among all categories of people. This diffusion is justified by the limited costs, ease of use, and less invasiveness (and consequently greater acceptability) than other types of sensors used for health status monitoring. This systematic review aims to synthesize research studies using smart wrist devices for a specific class of movement disorders. Following PRISMA-S guidelines, 130 studies were selected and analyzed. For each selected study, information is provided relating to the smartwatch/wristband/bracelet model used (whether it is commercial or not), the number of end-users involved in the experimentation stage, and finally the characteristics of the benchmark dataset possibly used for testing. Moreover, some articles also reported the type of raw data extracted from the smart wrist device, the implemented designed algorithmic pipeline, and the data classification methodology. It turned out that most of the studies have been published in the last ten years, showing a growing interest in the scientific community. The selected articles mainly investigate the relationship between smart wrist devices and Parkinson’s disease. Epilepsy and seizure detection are also research topics of interest, while there are few papers analyzing gait disorders, Huntington’s Disease, ataxia, or Tourette Syndrome. However, the results of this review highlight the difficulties still present in the use of the smartwatch/wristband/bracelet for the identified categories of movement disorders, despite the advantages these technologies could bring in the dissemination of low-cost solutions usable directly within living environments and without the need for caregivers or medical personnel.
Multi-Objective Optimization for Resource Allocation in Space–Air–Ground Network with Diverse IoT Devices
Authors: Xu Yongnan , Tang Xiangrong , Huang Linyu , Ullah Hamid , Ning Qian
Published: January 2025

As the Internet of Things (IoT) expands globally, the challenge of signal transmission in remote regions without traditional communication infrastructure becomes prominent. An effective solution involves integrating aerial, terrestrial, and space components to form a Space–Air–Ground Integrated Network (SAGIN). This paper discusses an uplink signal scenario in which various types of data collection sensors as IoT devices use Unmanned Aerial Vehicles (UAVs) as relays to forward signals to low-Earth-orbit satellites. Considering the fairness of resource allocation among IoT devices of the same category, our goal is to maximize the minimum uplink channel capacity for each category of IoT devices, which is a multi-objective optimization problem. Specifically, the variables include the deployment locations of UAVs, bandwidth allocation ratios, and the association between UAVs and IoT devices. To address this problem, we propose a multi-objective evolutionary algorithm that ensures fair resource distribution among multiple parties. The algorithm is validated in eight different scenario settings and compared with various traditional multi-objective optimization algorithms. The experimental results demonstrate that the proposed algorithm can achieve higher-quality Pareto fronts (PFs) and better convergence, indicating more equitable resource allocation and improved algorithmic effectiveness in addressing this issue. Moreover, these pre-prepared, high-quality solutions from PFs provide adaptability to varying requirements in signal collection scenarios.
Energy-Efficient and Trust-Based Autonomous Underwater Vehicle Scheme for 6G-Enabled Internet of Underwater Things
Authors: Hussain Altaf , Li Shuaiyong , Hussain Tariq , Attar Razaz Waheeb , Alhomoud Ahmed , Alsagri Reem , Zaman Khalid
Published: January 2025

This paper introduces a novel energy-efficient lightweight, void hole avoidance, localization, and trust-based scheme, termed as Energy-Efficient and Trust-based Autonomous Underwater Vehicle (EETAUV) protocol designed for 6G-enabled underwater acoustic sensor networks (UASNs). The proposed scheme addresses key challenges in UASNs, such as energy consumption, network stability, and data security. It integrates a trust management framework that enhances communication security through node identification and verification mechanisms utilizing normal and phantom nodes. Furthermore, a 6G communication module is deployed to reduce network delay and enhance packet delivery, contributing to more efficient data transmission. Leveraging Autonomous Underwater Vehicles (AUVs), the EETAUV protocol offers a lightweight approach for node discovery, identification, and verification while ensuring a high data transmission rate through a risk-aware strategy including at low computational cost. The protocol’s performance is evaluated through extensive simulations and compared against state-of-the-art methods across various metrics, including network lifetime, throughput, residual energy, packet delivery ratio, mean square error, routing overhead, path loss, network delay, trust, distance, velocity, Computational Cost of Routing, and data security. The results demonstrate the superior cumulative performance of the proposed EETAUV scheme, making it a robust solution for secure, efficient, and reliable communication in UASNs.
Review of Energy Communities: Definitions, Regulations, Topologies, and Technologies
Authors: Lazaroiu Alexandra Catalina , Roscia Mariacristina , Lazaroiu George Cristian , Siano Pierluigi
Published: January 2025

The Clean Energy package recognizes and offers a favorable regulatory framework for citizens and energy communities with renewable energy sources. However, various countries’ national regulations will be highly important for the successful development of energy communities in existing cities and surrounding areas. Energy communities represent a way in which citizens and local authorities can invest in clean energy sources and energy efficiency, with several benefits in addition to the financial ones, like strengthening the concept of community and individual contributions to reductions in the overall carbon footprint. In this paper, an overview of recent developments in financial incentives in energy communities, their organization, and typologies, as well as benefits shared among the participants, is performed. The overview reveals the potential of energy communities in contributing to the economic, energetic, and social development of cities towards sustainable and smart cities.
How Minimalism Drives Green Purchase Intention in Collectivist Cultures
Authors: Nguyen Khanh Huy , Tran Mai Dong
Published: January 2025

This study investigates the mediating role of pro-environmental behaviours (PEBs) in the relationship between minimalism, collectivist culture, environmental concern, and green purchase intention (GPI) in emerging economies. This study aims to fill a gap in our understanding of how lifestyle choices, cultural values, and environmental consciousness influence sustainable consumption in collectivist settings. The study presents a new viewpoint on minimalism as an antecedent of pro-environmental behaviours, addressing deficiencies in the current literature regarding sustainability and consumer behaviour. The study utilises data from 385 participants across emerging economies and employs Partial Least Squares Structural Equation Modelling (PLS-SEM) to examine the links between components. Moreover, stringent validation methods, such as the heterotrait–monotrait ratio (HTMT), guarantee the trustworthiness and validity of the results. The findings indicate that minimalism, collectivist culture, and environmental concern favourably affect pro-environmental behaviours, which considerably mediate their influence on green purchase intention. Private PEBs exert a more significant impact on GPI than public PEBs, underscoring the significance of individual-level sustainable behaviours. These findings enhance the theoretical discussion on sustainability in emerging economies and provide practical insights for fostering sustainable consumer behaviours through culturally adapted techniques.
A Systematic Review of Factors Contributing to Ineffective Cultural Heritage Management
Authors: Seila Fatma , Selim Gehan , Newisar May
Published: January 2025

Ineffective management increasingly threatens cultural heritage conservation, resulting in the mismanagement of tangible heritage assets and reducing the efficacy of conservation efforts. Although much of the literature examines the relationship between heritage management, tourism, and economic development, a notable gap exists in comprehending the interrelated elements that undermine the efficacy of conservation initiatives. This paper argues that administrative, financial, legal, and stakeholder-related factors are intricately connected in causing ineffective heritage management. These factors must be examined in interrelation to improve cultural heritage conservation efforts. A systematic review of the academic and grey literature on conserving tangible cultural assets is carried out to contribute to this goal. This literature review identifies 29 factors that contribute to the inefficacy of cultural heritage management plans. These factors are classified into several categories, including administrative institutions, stakeholders, financial resources, natural and human risks, laws and legislation, and political issues. This study presents a theoretical framework that connects governments, stakeholders, legislation, and administrative performance as crucial components in the success of heritage management. It highlights the need for transparent procedures for the successful implementation of heritage management strategies. The findings contribute to assessing cultural heritage management plans and propose directions for further research, including addressing local heritage concerns and methods to enhance the management performance. By identifying key factors that impede effective management, this paper contributes to the broader sustainability challenges of preserving cultural heritage while promoting social and economic stability. Enhanced heritage management practices can significantly contribute to the development of inclusive and sustainable communities.
Enhanced Photocatalytic Degradation of Cyanide in Mining Wastewater Using a ZnO-BiOI Heterojunction Catalyst
Authors: Ashiegbu Darlington C. , Pilane Paballo , Moma John , Potgieter Herman
Published: January 2025

The mining industry often relies on the natural degradation of tailings dams to break down cyanide in wastewater. However, this method has drawbacks, including high costs due to significant water demand and variable effectiveness dependent on environmental conditions, and it is a time-consuming process. To address this issue, this study focused on preparing, characterizing, and applying a ZnO-BiOI heterostructure for cyanide removal in water. The heterojunction was thoroughly characterized using techniques such as SEM-EDX, X-ray diffraction, nitrogen adsorption–desorption isotherms, photoluminescence, and XPS scans. The photocatalytic efficacy was evaluated by degrading CN−-containing solutions across varying photocatalyst masses, temperatures, and initial cyanide concentrations. The results showed that 5 mg of the heterostructure completely eliminated 40 ppm of cyanide in 35 min. Increasing the catalyst mass to 15 mg significantly reduced the time for the complete degradation of 40 ppm cyanide, while 25 mg of the photocatalyst achieved cyanide removal in 35 min. The optimal temperature was found to be 50 °C, with complete cyanide removal occurring in 20 min within the temperature range of 25 °C to 70 °C. Moreover, when the cyanide concentration ranged from 40 ppm to 100 ppm, 15 mg of heterojunction catalyst achieved a 97% destruction efficiency in removing a 100 ppm cyanide solution within 35 min. These results strongly indicate that the synthesized heterojunction has the potential to serve as an effective and efficient photocatalyst for cyanide degradation in process effluents and wastewater.
Information Security Risk Framework for Digital Transformation Technologies
Authors: Stefani Eduardo , Costa Ivanir , Gaspar Marcos Antonio , Goes Roberto de Souza , Monteiro Rogerio Carlos , Petrili Breno Ribeiro , Pereira Alexandre de Paula
Published: January 2025

The increasing impact of digital technologies on society is marked by rapid and disruptive changes, including more efficient and modern processes, and is pushing companies to adopt digital solutions. However, companies have limited options, and can rarely avoid being affected by the speed and challenges introduced by digital technologies. Researchers have observed that, despite the advantages they bring, the cybersecurity risks associated with these technologies are not fully apparent. In this context, the present study aims to uncover the risks associated with using digital transformation technologies, which may lead to outcomes that fall short of initial expectations. As the research methodology, a systematic literature review was conducted involving a search for scientific articles in bibliographic databases in order to identify, organize, and classify these risks. This review offered visibility into the risks companies face when adopting digital technologies and provided a framework that highlights the most relevant risks. IT specialists validated these risks through a consistent questionnaire followed by application of the Cronbach’s alpha coefficient applied, aligning our systematic literature review with market realities regarding the risks that companies are exposed to when using digital technologies. As a contribution to both industry and academia, this work offers a framework that can support companies in their digital transformation journey by helping them to recognize and manage the cybersecurity risks associated with digital technologies. Future studies could expand on this framework by developing a model for risk prioritization and mitigation.
Blockchain Applications in the Military Domain: A Systematic Review
Authors: Kostopoulos Nikos , Stamatiou Yannis C. , Halkiopoulos Constantinos , Antonopoulou Hera
Published: January 2025

Background: Blockchain technology can transform military operations, increasing security and transparency and gaining efficiency. It addresses many problems related to data security, privacy, communication, and supply chain management. The most researched aspects are its integration with emerging technologies, such as artificial intelligence, the IoT, application in uncrewed aerial vehicles, and secure communications. Methods: A systematic review of 43 peer-reviewed articles was performed to discover the applications of blockchain in defense. Key areas analyzed include the role of blockchain in securing communications, fostering transparency, promoting real-time data sharing, and using smart contracts for maintenance management. Challenges were assessed, including scalability, interoperability, and integration with the legacy system, alongside possible solutions, such as sharding and optimized consensus mechanisms. Results: In the case of blockchain, great potential benefits were shown in enhancing military operations, including secure communication, immutable record keeping, and real-time integration of data with the IoT and AI. Smart contracts optimized resource allocation and reduced maintenance procedures. However, challenges remain, such as scalability, interoperability, and high energy requirements. Proposed solutions, like sharding and hybrid architecture, show promise to address these issues. Conclusions: Blockchain is set to revolutionize the efficiency and security of the military. Its potential is enormous, but it must overcome scalability, interoperability, and integration issues. Further research and strategic adoption will thus allow blockchain to become one of the cornerstones of future military operations.
A Proof-of-Concept for Safety Evaluation of Inhalation Exposure to Known Respiratory Irritants Using In Vitro and In Silico Methods
Authors: Sadekar Nikaeta , Behrsing Holger Peter , Hansen Tanja , Patel Vivek , Paulo Hazel , Rae Alex , Ritter Detlef , Schwarz Katharina , Api Anne Marie
Published: January 2025

There is increased interest in developing non-animal test systems for inhalation exposure safety assessments. However, defined methodologies are absent for predicting local respiratory effects from inhalation exposure to irritants. The current study introduces a concept for applying in vitro and in silico methods for inhalation exposure safety assessment. Three in vitro systems, representing the upper (MucilAir™—nasal epithelial tissue) and lower (A549 cells and human precision-cut lung slices) human respiratory regions, were exposed to six respiratory irritants. These irritant exposures were conducted as liquid droplets, aerosol, or vapors, and samples were collected over 24 h. Cytotoxicity, cytokine release, epithelial resistance, oxidative stress, and mitochondrial membrane potential were measured. To determine the human relevance of in vitro exposures, airway surface depositions were predicted by simulating airborne concentrations equivalent to the Cramer class III inhalation threshold of toxicological concern limit of 0.47 mg/person/day using an in silico model. A > 100-fold margin of exposure was calculated comparing lowest concentrations showing in vitro effects to in silico simulated values. While further studies are needed, this manuscript presents a basic requirement for employing non-animal methods to inform inhalation exposure safety assessments by combining in vitro and in silico assays.
Tourism-Induced Land Use Transformations, Urbanisation, and Habitat Degradation in the Phu Quoc Special Economic Zone
Authors: Nguyen Can Trong , Downes Nigel K. , Sitthi Asamaporn , Losiri Chudech
Published: January 2025

Dynamic development of tourism activities and rapid urbanisation in Special Economic Zones (SEZs) can lead to significant land use and land cover changes (LULCCs) and environmental degradation, particularly in ecologically sensitive areas. This study examines the transformation of land use and its associated impacts on habitat quality and thermal environment in Phu Quoc Island (Vietnam) over a 20-year period (2003–2023). Using multi-temporal Landsat satellite imagery and random forest classification, we quantify LULCCs and assess the environmental consequences of urban expansion on habitat degradation and intensification of the island’s thermal environment, focusing on land surface temperature (LST) changes. Our analysis reveals that rapid urbanisation, driven by large-scale tourism and infrastructure developments, has led to a significant loss of forest and farmland, leading to a 5.6% decline in habitat quality and a marked increase in LST. The study also highlights the uneven distribution of urban growth, with the majority of expansion occurring in the southern and central regions of the island. By applying the InVEST Habitat Quality Model, we identify key zones of habitat degradation and offer insights into the spatial patterns of environmental sensitivity and changes. Our findings underscore the need for integrated land use planning and sustainable development strategies to mitigate the negative environmental impacts of SEZ-driven urbanisation on island ecosystems. This research provides critical guidance for policymakers, planners, and environmental managers to balance economic growth with environmental conservation in fragile island environments.
Two Years of SARS-CoV-2 Omicron Genomic Evolution in Brazil (2022–2024): Subvariant Tracking and Assessment of Regional Sequencing Efforts
Authors: Souza Ueric José Borges de , Spilki Fernando Rosado , Tanuri Amilcar , Roehe Paulo Michel , Campos Fabrício Souza
Published: January 2025

SARS-CoV-2, the virus responsible for COVID-19, has undergone significant genetic evolution since its emergence in 2019. This study examines the genomic diversity of SARS-CoV-2 in Brazil after the worst phase of the pandemic, the wider adoption of routine vaccination, and the abolishment of other non-pharmacological preventive measures from July 2022 to July 2024 using 55,951 sequences retrieved from the GISAID database. The analysis focuses on the correlation between confirmed COVID-19 cases, sequencing efforts across Brazilian states, and the distribution and evolution of viral lineages. Our findings reveal significant regional disparities in genomic surveillance, with São Paulo and Rio de Janeiro recovering the largest number of genomes, while Tocantins and Amazonas showed higher sequencing rates relative to their reported case numbers, indicating proactive surveillance efforts. We identified 626 distinct SARS-CoV-2 lineages circulating in Brazil, with dominant subvariants shifting over time from BA.5 in 2022 to XBB and JN.1 in 2023–2024. The emergence of new subvariants in this new epidemiological scenario underscores the importance of ongoing genomic surveillance to track viral evolution and inform public health strategies, providing valuable information to update vaccines and implement other measures, such as lockdowns, mask usage, social distancing, health education, and self-testing.
Evaluating Forelimb and Hindlimb Joint Conformation of Morna Racehorses (Equus caballus)
Authors: Ahmad Israr , Ijaz Sahar , Usman Mirza M. , Safdar Ayesha , Khan Imdad U. , Zeeshan Muhammad , Bukhari Syed S. U. H.
Published: January 2025

Measuring limb joint angles is crucial for understanding horse conformation, performance, injury diagnosis, and prevention. While Thoroughbred horses have been extensively studied, local Pakistani breeds (e.g., Morna racehorse) have not received scientific attention. This study aimed to quantify normal angles of limb joints in the Morna breed. Limb joint angles of standing horses (n = 50) were quantified using a measuring tape, height stick, protractor scale, and goniometer. The mean and standard deviation (Mean ± SD) values for the forelimb joint angles were 123.02 ± 3.46° for elbow, 171.52 ± 2.39° for knee, and 147.68 ± 5.11° for fetlock. The mean ± SD values for the hindlimb joint angles were 128.62 ± 4.08° for stifle, 160.40 ± 3.89° for hock, and 155.48 ± 2.68° for fetlock. There was a non-significant (p > 0.05) correlation between horse joint angles and, age, body weight, and body condition score (BCS). The elbow and stifle joint angles of Morna align well with characteristics associated with optimal racing performance. However, the hock and fetlock angles differ from jumping Thoroughbred and French trotters. We recommend further research to examine the conformation of the Morna breed, particularly by measuring the lengths of limb segments and correlating it with joint angles. This may provide valuable insights into individual variations within the breed.