bluuebunny/crossref_metadata_2025 huggingface dataset:
Review of Gasification of Thermoplastics and Thermosets
Authors: Busto Mariana , Nardi Franco , Dosso Liza , Badano Juan Manuel , Tarifa Enrique Eduardo , Vera Carlos Román
Published: February 2025

The end-of-life management of plastic represents a significant environmental challenge, largely due to its limited use, low biodegradability, and high volume of disposed material, in the order of 400 million tonnes by 2019. Several types of polymers can be recycled by mechanical means, but some others, like plastics, sometimes require chemical methods for their reuse. In this context, gasification is one of the most promising chemical recycling techniques. Gasification is a thermochemical process performed at moderate temperatures of work (800–1100 °C) that converts carbonaceous materials into rich hydrogen gas, which can be used for energy obtention or the Fisher–Tropsch process. However, this procedure can also produce undesirable by-products like tar and char. The products’ composition and relative quantities are highly dependent on the overall process configuration and the input fuel. The current study evaluates the catalytic gasification of the most common plastic waste, seeking to obtain higher gas yields and syngas with high energy. The text focuses on the current state of development and recent advances in various publications over the last fifteen years, with emphasis on thermoplastics and thermosets. The search showed that temperatures, the type of fluidizing gas, and the catalyst have a major influence on the quality of the obtained gas. Optimal gasification conditions, such as temperatures between 600 and 900 °C, depending on the plastic feedstock, steam-to-feedstock ratios > 1, the appropriate selection of a gasifying agent according to gas requirements and energy optimization, and the composition and location of the catalyst in the system (in situ, in the reactor, or ex situ), are identified as critical for maximizing H2 and CO production and minimizing tar. Finally, we provide summaries of the last advanced patent in the field, where the main focus appears to be feedstock pretreatment intended to ensure handling feasibility due to the variety of plastic wastes.
Clinicians’ Perspectives on Managing Medical Emergencies in Eating Disorders (MEED) in Adolescence—A Reflexive Thematic Analysis
Authors: Brennan Cliona , Illingworth Sarah , Cini Erica , Simic Mima , Baudinet Julian , McAdams Ellen , Bhakta Dee
Published: February 2025

Objective: Despite the UK national guidance for Managing Emergencies in Eating Disorders (MEED) being widely used, little is known about how the guidance has been embedded into clinical practice or implemented across services. Methods: Clinicians (n = 13) working in community child and adolescent eating disorder services and medical wards were interviewed about their experience of using the MEED guidance in their clinical practice. Open-ended questions were used. Reflexive thematic analysis was used to analyse interview data. Results: Reflexive thematic analysis of responses identified three main themes. These were the following: (1) a common language, (2) looking beneath the surface, and (3) refeeding syndrome—a rare event in youth. These themes evidenced the important role of the MEED guidance in child and adolescent eating disorders and highlighted both the benefits and limitations of the current guidance. Conclusions: This study demonstrated that MEED was most helpful as a tool to clearly communicate acuity of medical risks between services, aiding multi-agency working required to manage both physical and mental health risks of young people with AN. The absence of parameter risk stratification and the lack of consistency on refeeding guidance across adolescent and adult guidance were highlighted as areas that future research should focus on.
Migration of Korean Daejonggyo Believers to Manchuria in the Early 20th Century and Their Consciousness of Ancient Territory
Authors: Yoon Seokmin , Kim Youngjin , Yang Yi
Published: February 2025

In the late Joseon dynasty, many Koreans crossed the border between Joseon and Qing for survival. They then migrated to Manchuria, in the Qing territory, around Mt. Baekdu. In the late 1900s, Japan seized diplomatic and military control of Korea, and in 1910, Korea was annexed by Japan. Many Koreans then moved to the Manchurian region of China. Religion played an important role in the large Korean community formed in Manchuria after the 1910s. During this period, Korean immigrant communities that were centered on religion were established in Manchuria. Among the many religions, Daejonggyo (大倧敎) places great emphasis on national consciousness, and it was an active component of the anti-Japanese armed independence movement to restore national sovereignty. In particular, Daejonggyo claimed that Dangun (檀君), the founder of the Korean people, came down from heaven, established the first nation of the Korean people on Mt. Baekdu, and governed the surrounding area. Accordingly, Daejonggyo considered the Manchurian region to be the ancient territory of the Korean people. In addition, Daejonggyo presented the concept of the Baedal nation as a Dangun lineage and included not only the Korean people but also various northern ethnic groups, such as the Manchurian people. By doing so, Daejonggyo converged not only the Korean Peninsula and the Joseon nation (minjok, 民族) but also the Manchurian region and various ethnic groups in Manchuria into its own territory and people. Through this, Daejonggyo believers not only secured the legitimacy of residing in Manchuria but also gained the justification to drive out the Japanese and restore the Korean peninsular ancient territory.
Correction Method for Thermal Deformation Line-of-Sight Errors of Low-Orbit Optical Payloads Under Unstable Illumination Conditions
Authors: Li Yao , Chen Xin , Liu Guangsen , Rao Peng
Published: February 2025

Accurate optical axis pointing of optical payloads in low orbits is essential for sustained indication and high-precision positioning of motion targets. Owing to the short orbital period in low orbits and the influence of the sun, the incident light on the optical payloads and the space thermal environment undergo drastic and irregular changes over a short period. These changes cause optical distortions within the camera and variations in the installation matrix referenced for the satellite. Ultimately, these changes affect the imaging process of the camera and the line-of-sight (LOS) accuracy, greatly disadvantaging the high-precision pointing and positioning of space targets. In this paper, a correction method based on stellar observation data is proposed to address the LOS deviation issue of low-orbit optical payloads caused by space thermal deformation (STD). The proposed method innovatively utilizes the angle relationship between the solar vector, the satellite position vector, and the camera LOS vector as the correction parameters to characterize the thermal environment in which the payload operates. This method overcomes the irregularity and frequent correction requirements of LOS errors in low-orbit payloads. Experimental results showed that the mean absolute error of the camera LOS after the correction was 0.001096 rad, representing an 80.28% improvement over previous measurements, even reaching 99% improvement in the final mission. At a 95% confidence level, the correction errors for the final mission were consistently below 10−4 (2σ) rad in the right ascension and declination directions.
An Adaptive Feature Enhanced Gaussian Weighted Network for Hyperspectral Image Classification
Authors: Zhu Fei , Shi Cuiping , Wang Liguo , Pan Haizhu
Published: February 2025

Recently, research on hyperspectral image classification (HSIC) methods has made significant progress. However, current models commonly only focus on the primary features, overlooking the valuable information contained in secondary features that can enhance the model’s learning capabilities. To address this issue, an adaptive feature enhanced gaussian weighted network (AFGNet) is proposed in this paper. Firstly, an adaptive feature enhancement module (AFEM) was designed to evaluate the effectiveness of different features and enhance those that are more conducive to model learning. Secondly, a gaussian weighted feature fusion module (GWF2) was constructed to integrate local and global feature information effectively. Finally, a multi-head collaborative attention (MHCA) mechanism was proposed. MHCA enhances the feature extraction capability of the model for sequence data through direct interaction and global modeling. Extensive experiments were conducted on five challenging datasets. The experimental results demonstrate that the proposed method outperforms several SOTA methods.
A Multi-Scale Spatio-Temporal Fusion Network for Occluded Small Object Detection in Geiger-Mode Avalanche Photodiode LiDAR Systems
Authors: Ding Yuanxue , Du Dakuan , Sun Jianfeng , Ma Le , Yang Xianhui , He Rui , Lu Jie , Qu Yanchen
Published: February 2025

The Geiger-Mode Avalanche Photodiode (Gm-APD) LiDAR system demonstrates high-precision detection capabilities over long distances. However, the detection of occluded small objects at long distances poses significant challenges, limiting its practical application. To address this issue, we propose a multi-scale spatio-temporal object detection network (MSTOD-Net), designed to associate object information across different spatio-temporal scales for the effective detection of occluded small objects. Specifically, in the encoding stage, a dual-channel feature fusion framework is employed to process range and intensity images from consecutive time frames, facilitating the detection of occluded objects. Considering the significant differences between range and intensity images, a multi-scale context-aware (MSCA) module and a feature fusion (FF) module are incorporated to enable efficient cross-scale feature interaction and enhance small object detection. Additionally, an edge perception (EDGP) module is integrated into the network’s shallow layers to refine the edge details and enhance the information in unoccluded regions. In the decoding stage, feature maps from the encoder are upsampled and combined with multi-level fused features, and four prediction heads are employed to decode the object categories, confidence, widths and heights, and displacement offsets. The experimental results demonstrate that the MSTOD-Net achieves mAP50 and mAR50 scores of 96.4% and 96.9%, respectively, outperforming the state-of-the-art methods.
AI-Driven Real-Time Monitoring of Ground-Nesting Birds: A Case Study on Curlew Detection Using YOLOv10
Authors: Chalmers Carl , Fergus Paul , Wich Serge , Longmore Steven N. , Walsh Naomi Davies , Oliver Lee , Warrington James , Quinlan Julieanne , Appleby Katie
Published: February 2025

Effective monitoring of wildlife is critical for assessing biodiversity and ecosystem health as declines in key species often signal significant environmental changes. Birds, particularly ground-nesting species, serve as important ecological indicators due to their sensitivity to environmental pressures. Camera traps have become indispensable tools for monitoring nesting bird populations, enabling data collection across diverse habitats. However, the manual processing and analysis of such data are resource-intensive, often delaying the delivery of actionable conservation insights. This study presents an AI-driven approach for real-time species detection, focusing on the curlew (Numenius arquata), a ground-nesting bird experiencing significant population declines. A custom-trained YOLOv10 model was developed to detect and classify curlews and their chicks using 3/4G-enabled cameras linked to the Conservation AI platform. The system processes camera trap data in real time, significantly enhancing monitoring efficiency. Across 11 nesting sites in Wales, the model achieved high performance, with a sensitivity of 90.56%, specificity of 100%, and F1-score of 95.05% for curlew detections and a sensitivity of 92.35%, specificity of 100%, and F1-score of 96.03% for curlew chick detections. These results demonstrate the capability of AI-driven monitoring systems to deliver accurate, timely data for biodiversity assessments, facilitating early conservation interventions and advancing the use of technology in ecological research.
The Influence of Parameter Estimation Bounds on Velocity Estimation in PSInSAR
Authors: Balz Timo , Ewais Mostafa
Published: February 2025

Permanent scatterer interferometric synthetic aperture radar (PSInSAR) processing requires parameter selection that can significantly impact results, yet these parameters are often not fully disclosed in scientific publications. To demonstrate how different parameter settings in PSInSAR processing affect results, our study analyzed PSInSAR processing results using varying parameters. Results were evaluated both with and without temporal coherence filtering (threshold ≥ 0.8). Parameter variations produced differences that exceeded previously stated accuracy ranges for PSInSAR methods, while overall deformation trends remained similar across parameter sets. This shows that even seemingly minor parameter variations can lead to significant differences in PSInSAR results, exceeding what would be considered acceptable with respect to previously published accuracies. These findings emphasize the need for complete parameter disclosure in scientific publications and suggest more careful interpretation of small velocity differences in PSInSAR results.
Application of Improved Fault Detection and Robust Adaptive Algorithm in GNSS/INS Integrated Navigation
Authors: Wang Qinghai , Liu Jianghua , Jiang Jinguang , Pang Xianrui , Ge Zhimin
Published: February 2025

In vehicle GNSS/INS integrated navigation, robust and adaptive algorithms have become one of the key technologies for achieving a comprehensive PNT due to their ability to control the gross errors of the observation model and dynamic model. The Sage–Husa algorithm is widely used in optimizing the Kalman filter due to its ability to estimate the observation or state covariance without prior information. However, the quality of observations in complex environments is prone to large fluctuations, so the averaging method is not suitable for dynamic navigation. To solve this problem, this article designs a double window structure and introduces a time-dependent fading weighted factor. At the same time, a logarithmic form factor constructor is proposed in order to avoid anomalies in the robust and adaptive factor. The traditional innovation adaptive filter is improved and turned into a multi-factor adaptive filter. In this paper, an improved fault detection algorithm is used to combine a robust algorithm with an adaptive algorithm to adapt to different gross errors in different scenarios. The experimental results of complex scenarios show that the position RMSE of the improved algorithm in the east, north, and height directions is 0.68 m, 0.71 m, and 1.05 m, respectively, which are reduced by 39.3%, 39.3%, and 70.3% compared to the EKF.
Real-Time Monitoring of Energy Contributions in Renewable Energy Communities Through an IoT Measurement System
Authors: Bonavolontà Francesco , Liccardo Annalisa , Mottola Fabio , Proto Daniela
Published: February 2025

This paper presents an IoT-based monitoring system designed to measure energy exchanges within Renewable Energy Communities. The proposed system utilizes embedded devices functioning as IoT power meters, which communicate via LoRaWAN technology and employ the MQTT protocol. Members of the energy community can monitor energy flows in real time, enabling them to remain constantly informed about potential penalties and adopt behaviors that optimize incentives linked to the self-consumption of generated energy. Moreover, in the case of Renewable Energy Communities, incentive schemes can be adopted which allow exploiting the advantages of using storage units. In this context, it is important to correctly measure the energy terms which can be incentivized. This is not an easy task, especially when dealing with storage units for which the concept of negative energy input is used to identify the energy absorbed from the network to be fed back into the network when needed. This paper aims to propose the use of distributed power meters to identify the various energy contributions relevant for incentive calculations, such as negative energy input, produced and withdrawn energy, and self-consumed energy. A case study, involving some resources of a Renewable Energy Community, is presented, evidencing the advantages of the proposal.
Doing Visibility: Understanding Gender and Discipline Differences in Science Communication on Social Media and in the Press
Authors: Spagert Lina , Wolf Elke
Published: February 2025

Nowadays, visibility is playing an increasingly important role in science communication. The topic is particularly significant for female experts, as their visibility not only inspires other women but also challenges gender stereotypes in academia. This article provides the first insights into the actual public visibility of scientific experts in Germany and presents potential factors that influence visibility. The analysis is based on the theoretical concept of doing visibility and identifies factors that influence the decision to increase visibility via social media. Our complex dataset comprises 139 experts (59 from computer science and 80 from social sciences), who took part in our online survey about visibility and personal information. Additionally, we tracked the respondent’s online footprint to ascertain their actual visibility in social media and press. The study reveals significant differences in creating visibility and the perception of visibility by sex and discipline. Computer scientists are more active on social media, while male social scientists are more visible in the press. Male computer scientists (57%) post their work on social media most frequently, followed by female computer scientists (35%), female social scientists (24%), and male social scientists (17%). Furthermore, the engagement on social media depends on the discipline, age, and media affinity of the experts. Overall, female experts gain less visibility on LinkedIn and in the press, although the gender differences in IT are smaller in this respect. Based on the results, we discuss potential reasons for the unequal distribution of visibility and suggest targeted interventions to close the gender visibility gap, such as (social) media or interview training. In addition, organisations and media representatives should be trained to actively contribute to breaking down gender stereotypes.
Palynology for Sustainability: A Classical and Versatile Tool for New Challenges: Editorial
Authors: Florenzano Assunta , Clò Eleonora , Servera-Vives Gabriel , Mercuri Anna Maria
Published: February 2025

This Special Issue presents interdisciplinary studies in applied palynology, highlighting the use of pollen as a tool for understanding environmental conditions across various contexts. Contributions include applications of pollen as a bioindicator for chemical pollution, human impact, and other variables. Several articles focus on the use of pollen in archaeological research, environmental health, and air quality monitoring, such as in Rome and Bologna, analysing long-term trends in allergenic pollen concentrations and airborne allergens. Additionally, studies of modern analogues in Mediterranean landscapes and in Southern Oman illustrate how modern pollen helps reconstruct vegetation history and land uses, and assess ecological changes. Overall, the contributions underscore the importance of pollen in environmental monitoring, sustainability research, and human health protection.
Analysis of the Interrelationships and Drivers of Ecosystem Services in the Heihe River Basin
Authors: Yan Yuxiang , Liu Xiaohuang , Lin Tao , Li Peng , Min Jie , Zhu Ping , Liu Xiaotong , Wang Chao
Published: February 2025

The preservation and enhancement of ecosystem services are essential for maintaining ecological balance and sustainable growth. The Heihe River Basin (HRB) is important for ecological security in Northwest China, yet is a fragile ecological environment. Understanding the dynamics and evolution of ESs is vital for balancing resource exploitation, socioeconomic development, and ecological protection. Using the InVEST model, we calculated water yield, habitat quality, and carbon stock in the HRB during 2000–2020 and examined shifts in ecosystem services. Trade-offs and synergies among ESs were assessed using GeoDa and key drivers were identified through the geodetector model. The spatial distribution of water yield, habitat quality, and carbon storage varied significantly, with high values concentrated in the upstream Qilian Mountains and low values in the downstream desert areas. High carbon storage clusters were stable, high water yield clusters increased and subsequently decreased, and high habitat quality clusters fluctuated. Carbon storage, water yield, and habitat quality exhibited a synergistic relationship. Climate and topography, particularly vapor emissions and elevation, were the primary factors influencing ESs, while socioeconomic factors had a lesser impact. These findings provide valuable insights for sustainable ecosystem management and conservation in the HRB and other arid inland watershed regions.
Educational Aspects Affecting Paramedic Preparedness and Sustainability of Crisis Management: Insights from V4 Countries and the Role of Innovative Technologies
Authors: Titko Michal , Slemenský Miroslav
Published: February 2025

Recent major disasters, including the COVID-19 pandemic and floods in Europe, highlight the unpredictability of crises and the necessity for systemic preparedness at all levels of crisis management, including pre-hospital emergency medical services. Paramedics observed, under these challenging conditions (but not exclusively during them), cases of insufficient knowledge and skills in providing pre-hospital medical care, which lead to inadequate or prolonged decision making in delivering assistance. For this reason, the authors aimed to determine the extent to which such situations occur and to examine their causes, focusing on potential gaps and shortcomings in the education of paramedics. This study examines the impact of educational systems on the professional preparedness of paramedics in V4 European countries (the Slovak Republic, the Czech Republic, Hungary, and Poland) during pre-hospital care through a questionnaire survey. A survey involving over 1600 respondents revealed significant disparities in perceived knowledge and skill gaps, with Poland demonstrating the highest deficiencies (78%) and the Slovak Republic the lowest (57%). Key factors influencing these gaps included the frequency of external educational and training activities, years of experience, and expertise in managing critical conditions. The findings underscore the importance of innovative technologies, such as simulations and virtual reality, in enhancing paramedic training, along with integrating digital solutions across all phases of disaster management. Recommendations focus on strengthening system resilience, fostering interdisciplinary approaches, and improving system sustainability and adaptability. By using the results obtained and leveraging technological advances, the study aims to contribute to more effective crisis preparedness, population protection, and sustainable development goals (SDGs), namely (3, 4, 9, and 11), especially in the field of crisis management. This reinforces the broader role of SDGs in building more robust, future-ready disaster management frameworks.
New Strategies for Sustainable Biofuel Production: Pyrolytic Poly-Generation of Biomass
Authors: Meng Fanbin , Wang Donghai
Published: February 2025

Biomass serves as a promising renewable and sustainable feedstock for energy production through thermochemical conversion. It can be transformed into sustainable biofuels by means of pyrolysis. Among these methods, the pyrolytic poly-generation of biomass, a novel biomass thermal conversion technology, can concurrently produce three valuable products, namely biochar, bio-oil, and combustible gas, without generating any byproducts. In contrast, conventional thermal conversion processes, such as carbonization for biochar, liquefaction for bio-oil, gasification for syngas, and combustion for heat, only yield single products, have limited efficiency, and give rise to byproducts. Clearly, pyrolytic poly-generation holds significant advantages over conventional thermal conversion processes. Nevertheless, the pyrolytic poly-generation process and its products are remarkably influenced by numerous factors, including the raw biomass properties, pretreatment methods, operating parameters, and catalysts. This article reviews the processing parameters and technology for biomass pyrolytic poly-generation, and also explores future research areas, with the aim of identifying research gaps and promoting its industrial implementation.
Navigating Environmental Uncertainty: The Role of ESG Performance in Driving Firm-Level High-Quality Development
Authors: Zhang Yatao , Ban Qi , Li Jialing
Published: February 2025

Total factor productivity serves as a critical indicator of high-quality corporate development. This study systematically examines the impact of ESG performance on TFP using panel data from Shanghai and Shenzhen A-share listed firms spanning 2009 to 2023. The findings reveal three key insights: first, corporate ESG performance significantly enhances TFP, with regression analysis demonstrating a statistically robust positive correlation (1% significance level) and high explanatory power (R2 > 0.8). Second, under environmental uncertainty, ESG-driven total factor productivity improvements operate through dual mechanisms: energy conservation and resource allocation optimisation. Third, heterogeneity analysis highlights that non-state-owned enterprises exhibit a more pronounced relationship compared to state-owned counterparts, particularly in high-environmental-uncertainty scenarios. Beyond enriching academic discourse on ESG metrics, this research elucidates the intrinsic linkage between ESG practices and TFP under dynamic environmental conditions, offering actionable strategies for firms to align sustainability goals with productivity growth. For international stakeholders, this study provides empirical evidence from China—the world’s second-largest economy—to inform global ESG policy design and cross-border investment decisions, emphasising the role of institutional contexts in sustainability-driven value creation. The insights are pivotal for investors, policymakers, and multinational corporations seeking to navigate ESG complexities while advancing sustainable development goals in emerging markets.
Present and Projected Suitability of Olive Trees in a Currently Marginal Territory in the Face of Climate Change: A Case Study from N-Italy
Authors: Bordoni Massimiliano , Gambarani Antonio , Giganti Matteo , Vivaldi Valerio , Rossi Graziano , Bazzano Paolo , Meisina Claudia
Published: February 2025

Expected climate change will impact the environmental suitability of different territories. This will be of particular importance for crop sustainability in agriculture, especially in territories that are currently marginal in the biogeographic distribution of cultivated crops; in some cases, the growing conditions may become more suitable due to the projected modified climatic conditions. This paper aims to reconstruct different scenarios of environmental suitability of olive trees under current and future climatic scenarios, considering for the first time a marginal area for this tree plant in Europe. This study represents a first attempt to assess the possible evolution of the suitability of one of the most important Mediterranean crop trees in a current marginal area. This area corresponds to a territory (Oltrepò Pavese, South Lombardy) located at northern edge of the typical geographical distribution. The results of the suitability scenarios, obtained by applying a data-driven method based on predictors representative of the main geological, geomorphological, climatic, and plant cover variables influencing olive tree presence in a territory, show that the future projections at different periods (short-term at 2050; medium-term at 2070; long-term at 2100) suggest an increase in the suitable areas for olive tree cultivation. The increased suitability in this geographical area is related to an increase in air temperature and a parallel decrease in the number of frost days projected for the future scenarios, guaranteeing an increase in suitable areas for olive trees especially in those sectors located at higher latitudes and altitudes than the ones currently more suitable to olive trees. This study could represent a useful basis to implement effective and sustainable strategies of land planning and of mitigation measures to limit the impacts of the climate change effects on cultivation, making the developed method a potential operational tool for the evaluation of the territories that are and will be more adapted to this cultivation according to actual and future climatic scenarios.
Research on the Measurement and Improvement in Fresh Product Supply Chain Resilience Based on Blockchain Technology
Authors: Zhao Zhong , Zhu Ziwen
Published: February 2025

Fresh product faces intrinsic vulnerabilities to supply disruptions, given its perishable nature and seasonal dependencies. This underscores the critical importance of supply chain resilience in sustaining a steady and dependable flow of these goods and is a key factor in promoting the sustainable development of the supply chain. By employing well-established resilience metrics, specifically time to recovery, recovery level, and lost performance during recovery (with profit adopted as the performance indicator for this study), this study explores the resilience of the fresh product supply chain and examines the impact of blockchain technology on resilience enhancement. The findings indicate that when resilience is prioritized, optimal recovery efforts and supply recovery levels exceed those targeted solely for profit maximization. A negative correlation emerges between supply chain resilience and recovery delay, while an optimal supply recovery level is positively associated with recovery delay. Numerical evaluations further demonstrate that blockchain technology has a marked effect on elevating supply recovery levels, thus significantly strengthening resilience. Moreover, recovery levels display a positive correlation with the degree of blockchain adoption, while profit loss initially decreases before ascending alongside increased blockchain investments. Resilience also inversely correlates with fresh-keeping efforts, with blockchain applications accelerating this downward trend. Collectively, this study not only provides important references for recovery decision-making in the fresh agricultural product supply chain but also emphasizes the significant potential of blockchain technology (BT) in enhancing supply chain resilience and promoting sustainable development.
Vapor Pressure Deficit as an Indicator of Condensation in a Greenhouse with Natural Ventilation Using Numerical Simulation Techniques
Authors: Acevedo-Romero Mirka Maily , Hernández-Bocanegra Constantin Alberto , Aguilar-Rodríguez Cruz Ernesto , Ramos-Banderas José Ángel , Solorio-Díaz Gildardo
Published: February 2025

The relationship between Vapor Pressure Deficit (VPD) and condensation in a naturally ventilated Gothic greenhouse in northeastern Mexico was analyzed using numerical simulation techniques. This study was carried out in 3D in a steady state, considering the presence of crops. The model was validated with experimental data on temperature and relative humidity. Custom Field Functions (CFFs) were implemented to calculate VPD and dew point temperature (Tdp). The conditions that cause condensation inside the greenhouse were analyzed by evaluating days with and without the presence of condensation, with 100 and 50% window opening configurations, and the relationship between condensation and VPD levels was established as an indicator of this phenomenon. The simulation results showed that condensation conditions can be prevented by opening the ventilation at its maximum capacity in a timely manner. In the simulation with a 50% opening, VPD values of zero were reached and coincided with zero and negative values in the subtraction of ambient temperature and dew point temperature. However, when opening the windows to 100%, the VPD maintained values between 0.15 and 0.25, and the dew point temperature remained below ambient temperature by up to 2 °C. It is concluded that the VPD can indicate the risk or presence of condensation inside the greenhouse.
Enhancing Inland River Shore Power Utilization: A Game Theory and Prospect Theory Approach to Optimizing Incentive Mechanisms
Authors: Cai Wenxue , Xie Cailian , Gu Yimiao
Published: February 2025

The development of the shipping and port industry has significantly driven both the Chinese and global economies. However, the environmental impact of their carbon footprint cannot be overlooked. Recently, the industry has made strides in implementing various environmental protection measures, with the promotion and adoption of shore power technology in inland port areas emerging as promising avenues for sustainable development. Despite widespread promotion and the establishment of shore power facilities in inland river areas, the utilization rate remains low. This is primarily due to the minimal benefits that inland river ships gain from using shore power that often fail to meet their expectations. The traditional income function based on rational agent theory is inadequate, leading to existing incentive measures that do not effectively encourage shore power usage by inland river ships. Therefore, it is essential to analyze this issue from the perspective of behavioral economics. This paper introduces the reference point effect from prospect theory and designs an incentive mechanism for inland river shore power based on game theory principles. The goal is to explore how government subsidies and penalties can be adjusted to create effective incentives for shore power usage, ultimately seeking to improve the adoption rate of shore power among inland river ships and enhance the overall environmental quality of inland river ports.
Automating KPI Measurement: A Sustainable Solution for Educational Accreditation
Authors: Mondal Saiful R.
Published: February 2025

This paper examines the use of interactive Google Sheets for the automatic measurement of key performance indicators (KPIs) in higher education, particularly in the context of academic accreditation. As institutions face increasing pressure to demonstrate quality and effectiveness, reliable data tracking and reporting have become essential. Traditional methods of managing academic records and performance metrics can be cumbersome and error-prone, underscoring the need for an automated solution. By leveraging Google Sheets’ dynamic capabilities, institutions can efficiently monitor KPIs related to student performance, curriculum effectiveness, and faculty qualifications. This approach allows for real-time data updates, facilitating timely insights that support accreditation processes and continuous improvement initiatives. The study outlines the design and implementation of a dynamic Google Sheets framework tailored to higher education KPIs, highlighting its benefits in enhancing data accuracy, reducing administrative burden, and fostering collaboration among faculty and administration. Through illustrative case studies, we demonstrate how this tool empowers institutions to meet accreditation standards and drive educational excellence. Ultimately, the research emphasizes the potential of automation to transform academic record management and enhance institutional accountability in higher education.
Sustainable Food Festival Tourism: Integrating the Bio-Circular-Green (BCG) Model for Cultural and Environmental Resilience in Thailand
Authors: Suvittawat Adisak , Janchai Napaporn , Seepho Sirinthorn , Nonthachai Jaruwat , Nonthachai Intira
Published: February 2025

The Bio-Circular-Green (BCG) model presents a transformative framework for advancing sustainability in food festival tourism, particularly in Thailand. Food festivals serve as dynamic platforms for celebrating local culinary heritage while fostering environmental responsibility and economic resilience. This study examined the integration of the BCG model with critical success factors and community identity to assess its impact on sustainable food festival management. Employing a quantitative research approach and structural equation modeling, data were collected from 503 festival attendees to analyze key relationships among event management, community identity, and sustainability practices. The findings underscore the effectiveness of the BCG model in enhancing resource efficiency, minimizing waste, and promoting local sourcing, thus strengthening the sustainability and attractiveness of food festivals. Notably, while the role of community identity was found to be less significant than anticipated, this suggests evolving tourist preferences favoring sustainability and quality over traditional cultural attributes. These insights offer valuable implications for policymakers, event organizers, and stakeholders in designing eco-conscious, culturally enriching festivals that align with the global sustainability goals. This study contributes to the theoretical discourse on sustainable tourism and provides practical strategies to foster environmentally responsible and economically viable food festivals.
Enhanced Recovery After Surgery Protocols in Cesarean Delivery in International Settings: A Clinical Review of Implementation in Turkey and Croatia
Authors: Filipović Biljana , Höbek Rukiye Akarsu , Čukljek Snježana , Kovačević Irena , Ristić Jadranka , Şahin Akboğa Özlem , Friganović Adriano
Published: February 2025

Background: Enhanced Recovery After Surgery (ERAS) protocols have become integral in improving postoperative outcomes in cesarean deliveries. Variations in protocol adherence and implementation practices can significantly impact maternal and neonatal health across different healthcare systems. Objective: To evaluate the implementation of ERAS protocols in cesarean deliveries across two countries—Croatia and Turkey—and highlight differences in the level of adherence to ERAS recommendations. Design: A comparative clinical review was conducted. The study employed qualitative assessments carried out by medical professionals at two hospitals: one in central Anatolia, Turkey, and the Clinical Hospital “Sveti Duh” in Zagreb, Croatia. Methods: Twenty perioperative ERAS recommendations were evaluated based on implementation levels, rated using a five-point Likert scale (from very low to very high implementation). Qualitative insights were also collected to understand challenges and adaptations in the implementation process. Results: In Croatia, 13 recommendations were implemented at a very high level, compared to 8 in Turkey. Conclusions: Croatia demonstrates higher and more consistent adherence to ERAS protocols compared to Turkey, which faces greater challenges in consistent implementation, particularly in preoperative and postoperative care.
MOSSNet: A Lightweight Dual-Branch Multiscale Attention Neural Network for Bryophyte Identification
Authors: Luo Haixia , Zhang Xiangfen , Yuan Feiniu , Yu Jing , Ding Hao , Xu Haoyu , Hong Shitao
Published: February 2025

Bryophytes, including liverworts, mosses, and hornworts, play an irreplaceable role in soil moisture retention, erosion prevention, and pollution monitoring. The precise identification of bryophyte species enhances our understanding and utilization of their ecological functions. However, their complex morphology and structural symmetry make identification difficult. Although deep learning improves classification efficiency, challenges remain due to limited datasets and the inadequate adaptation of existing methods to multi-scale features, causing poor performance in fine-grained multi-classification. Thus, we propose MOSSNet, a lightweight neural network for bryophyte feature detection. It has a four-stage architecture that efficiently extracts multi-scale features using a modular design with symmetry consideration in feature representation. At the input stage, the Convolutional Patch Embedding (CPE) module captures representative features through a two-layer convolutional structure. In each subsequent stage, Dual-Branch Multi-scale (DBMS) modules are employed, with one branch utilizing convolutional operations and the other utilizing the Dilated Convolution Enhanced Attention (DCEA) module for multi-scale feature fusion. The DBMS module extracts fine-grained and coarse-grained features by a weighted fusion of the outputs from two branches. Evaluating MOSSNet on the self-constructed dataset BryophyteFine reveals a Top-1 accuracy of 99.02% in classifying 26 bryophyte species, 7.13% higher than the best existing model, while using only 1.58 M parameters, 0.07 G FLOPs.
Research on Regional Collaborative Governance Between Central and Local Governments Under the Background of Green Innovation
Authors: Huang Xiaotong , Zhan Wentao , Qi Tianjiao , Guo Yu , Bai Rui , Hong Tao
Published: February 2025

In the current context of increasingly severe global environmental problems, green innovation policies have attracted much attention as an important means to promote sustainable economic development, achieve efficient resource utilization, and be environmentally friendly. Since green innovation involves various factors such as technology research and development and policy support, active cooperation and coordination among governments at all levels are required. Therefore, the theoretical analysis of the game strategy of green innovation among regional governments is particularly important. This paper focuses on inter-governmental collaboration, constructs a tripartite evolutionary game model between the central government and different local governments, analyzes the revenue situation of each party under different policy tendencies, and studies the impact of changes in different factors such as local government green innovation revenue and central government tax revenue on the stability of green innovation policy through simulation analysis. The results show that the adoption of punitive policies by the central government is more conducive to the formation of a stable collaborative governance mechanism. In addition to direct governance costs and benefits, the tax coefficient of local governments and the reduction in local enterprise profits are also key factors affecting regional collaborative governance. On this basis, this paper discusses the game strategies of different regional governments in promoting green innovation from the perspectives of the central government and local governments and puts forward policy recommendations to promote regional collaborative green innovation at the mechanism construction and specific operational levels, providing theoretical guidance for inter-governmental green innovation cooperation.
Development of a Method to Evaluate the Dynamic Fit of Face Masks
Authors: Goodge Katarina E. , Brown Drew E. , Frey Margaret , Baytar Fatma
Published: February 2025

Evaluating designed objects in real-world use cases enables usability optimization. For functional objects such as face masks, the mask must fit the user initially and continue to fit during movements such as talking. This paper describes methodology development for dynamic fit analysis of face masks using 3D head scans. Participants were scanned while wearing Basic, Cup, and Petal model masks before and after reading a passage aloud and completed surveys across eight fit dimensions. Face and mask measurements were virtually extracted from the head scans for quantitative fit analysis, and mask overlays were inspected for qualitative fit analysis. Four of eleven facial measurements changed significantly from closed to open-mouth posture while the nasal dorsum was identified as a stable landmark and served as a reference to define a mask shift metric. The mask shift was compared to the survey results for the model masks, with the Cup design fitting best and the Petal design rated as most comfortable. Poor fit modes identified from mask overlays were fabric buckling, compressed nose and ears, and gapping between the mask and facial features. This methodology can be implemented during the analysis stage of the iterative design process and complements static fit analyses.
Past, Current and Future Techniques for Monitoring Paralytic Shellfish Toxins in Bivalve Molluscs
Authors: Finch Sarah C. , Harwood D. Tim
Published: February 2025

Paralytic shellfish poisoning is a threat to human health caused by the consumption of shellfish contaminated with toxins of the saxitoxin class. Human health is protected by the setting of regulatory limits and the analysis of shellfish prior to sale. Both robust toxicity data, generated from experiments fitting into the ethical 3R framework, and appropriate analysis methods are required to ensure the success of this approach. A literature review of in vivo animal bioassays and in vitro and analytical methods showed that in vitro methods are the best option to screen shellfish for non-regulatory purposes. However, since neither the receptor nor antibody binding of paralytic shellfish toxin analogues correlate with toxicity, these assays cannot accurately quantify toxicity in shellfish nor be used to calculate toxicity equivalence factors. Fully replacing animals in testing is rightfully the ultimate goal, but this cannot be at a cost to human health. More modern technology, such as organ-on-a-chip, represent an exciting development, but animal bioassays cannot currently be replaced in the determination of toxicity. Analytical methods that employ toxicity equivalence factors calculated using oral animal toxicity data result in an accurate assessment of the food safety risk posed by paralytic shellfish toxin contamination in bivalve molluscs.
Sex-Specific Immune Responses Mediate Host Specificity in Hookworm Infections
Authors: Langeland Andrea , Jackson Catherine A. , McKean Elise L. , Errahmani Hajar , O’Halloran Damien M. , Hawdon John M.
Published: February 2025

Hookworm infections affect 500–700 million people worldwide and can lead to chronic conditions, such as malnutrition and anemia. The challenge of managing these infections is heightened by the absence of effective vaccines and the potential for anthelmintic resistance to develop. A comprehensive understanding of the molecular interactions between the parasite and host is vital for unraveling the complexities of infection dynamics. This study aimed to identify the immune system components responsible for host specificity in hookworms by infecting immunodeficient mouse models. Findings herein indicate that innate immunity is essential in protecting against Ancylostoma ceylanicum establishment in mice. Significant differences in parasite development were noted in mice lacking the signal transducer and activator of transcription 6 (Stat6−), with female mice reliant on this Th2 pathway for protection. Secondary infections in female Stat6− mice and an immunodeficient NSG mouse reached patency, demonstrating that immunodeficient mice fail to develop protective immunity against subsequent infections, similar to human hookworm infections. In contrast, no parasite development was observed in mice infected with A. caninum, highlighting that the survival strategies of this species are independent of the host immune landscape. These results underscore the complexity of host–parasite interactions and point to new directions for therapeutic strategies, which may differ between sex.