bluuebunny/crossref_metadata_2025 huggingface dataset:
Responses of Vehicular Occupants During Emergency Braking and Aggressive Lane-Change Maneuvers
Authors: Hwang Hyeonho , Kim Taewung
Published: October 2024

To validate active human body models for investigating occupant safety in autonomous cars, it is crucial to comprehend the responses of vehicle occupants during evasive maneuvers. This study sought to quantify the behavior of midsize male and small female passenger seat occupants in both upright and reclined postures during three types of vehicle maneuvers. Volunteer tests were conducted using a minivan, where vehicle kinematics were measured with a DGPS sensor and occupant kinematics were captured with a stereo-vision motion capture system. Seatbelt loads, belt pull-out, and footrest reaction forces were also documented. The interior of the vehicle was 3D-scanned for modeling purposes. Results indicated that seatback angles significantly affected occupant kinematics, with small female volunteers displaying reduced head and torso movements, except during emergency braking with a upright posture seatback. Lane-change maneuvers revealed that maximum lateral head excursions varied depending on the maneuver’s direction. The study concluded that seatback angles were crucial in determining the extent of occupant movement, with notable variations in head and torso excursions observed. The collected data assist in understanding occupant behavior during evasive maneuvers and contribute to the validation of human body models, offering essential insights for enhancing safety systems in autonomous vehicles.
An Overview of Software Sensor Applications in Biosystem Monitoring and Control
Authors: Badreldin Nasem , Cheng Xiaodong , Youssef Ali
Published: October 2024

This review highlights the critical role of software sensors in advancing biosystem monitoring and control by addressing the unique challenges biological systems pose. Biosystems—from cellular interactions to ecological dynamics—are characterized by intrinsic nonlinearity, temporal variability, and uncertainty, posing significant challenges for traditional monitoring approaches. A critical challenge highlighted is that what is typically measurable may not align with what needs to be monitored. Software sensors offer a transformative approach by integrating hardware sensor data with advanced computational models, enabling the indirect estimation of hard-to-measure variables, such as stress indicators, health metrics in animals and humans, and key soil properties. This article outlines advancements in sensor technologies and their integration into model-based monitoring and control systems, leveraging the capabilities of Internet of Things (IoT) devices, wearables, remote sensing, and smart sensors. It provides an overview of common methodologies for designing software sensors, focusing on the modelling process. The discussion contrasts hypothetico-deductive (mechanistic) models with inductive (data-driven) models, illustrating the trade-offs between model accuracy and interpretability. Specific case studies are presented, showcasing software sensor applications such as the use of a Kalman filter in greenhouse control, the remote detection of soil organic matter, and sound recognition algorithms for the early detection of respiratory infections in animals. Key challenges in designing software sensors, including the complexity of biological systems, inherent temporal and individual variabilities, and the trade-offs between model simplicity and predictive performance, are also discussed. This review emphasizes the potential of software sensors to enhance decision-making and promote sustainability in agriculture, healthcare, and environmental monitoring.
Sensing and Perception in Robotic Weeding: Innovations and Limitations for Digital Agriculture
Authors: Shamshiri Redmond R. , Rad Abdullah Kaviani , Behjati Maryam , Balasundram Siva K.
Published: October 2024

The challenges and drawbacks of manual weeding and herbicide usage, such as inefficiency, high costs, time-consuming tasks, and environmental pollution, have led to a shift in the agricultural industry toward digital agriculture. The utilization of advanced robotic technologies in the process of weeding serves as prominent and symbolic proof of innovations under the umbrella of digital agriculture. Typically, robotic weeding consists of three primary phases: sensing, thinking, and acting. Among these stages, sensing has considerable significance, which has resulted in the development of sophisticated sensing technology. The present study specifically examines a variety of image-based sensing systems, such as RGB, NIR, spectral, and thermal cameras. Furthermore, it discusses non-imaging systems, including lasers, seed mapping, LIDAR, ToF, and ultrasonic systems. Regarding the benefits, we can highlight the reduced expenses and zero water and soil pollution. As for the obstacles, we can point out the significant initial investment, limited precision, unfavorable environmental circumstances, as well as the scarcity of professionals and subject knowledge. This study intends to address the advantages and challenges associated with each of these sensing technologies. Moreover, the technical remarks and solutions explored in this investigation provide a straightforward framework for future studies by both scholars and administrators in the context of robotic weeding.
Decorated Electrode Surfaces with Nanostructures and Metal-Organic Frameworks as Transducers for Sensing
Authors: Caruncho-Pérez Sara , Díez Aida M. , Prado-Comesaña Ana , Pazos Marta , Sanromán María Ángeles , González-Romero Elisa
Published: October 2024

In this study, several materials are presented as modifiers of the screen-printed carbon electrodes with the aim of developing new sensing platforms for the voltammetric analysis of drugs. Specifically, Clotiapine and Sulfamethoxazole were selected as models for antipsychotics and antibiotics, respectively. Different nanostructures were studied as modifiers, including both transition metals and carbon-based materials. Moreover, biochar and two metal-organic frameworks (MOFs) were tested as well. The NH2-MIL-125(Ti) MOF showed an 80% improvement in the analytical signal of Sulfamethoxazole, but it partially overlapped with an additional signal associated with the loss of the MOF ligand. For this reason, several immobilization strategies were tested, but none of them met the requirements for the development of a sensor for this analyte. Conversely, carbon nanotubes and the NH2-MIL-101(Fe) MOF were successfully applied for the analysis of Clotiapine in the medicine Etumine®, with RSD below 2% and relative errors that did not exceed 9% in any case, which demonstrates the precision and accuracy achieved with the tested modifications. Despite these promising results, it was not possible to lower the limits of detection and quantification, so in this sense further investigation must be performed to increase the sensitivity of the developed sensors.
A Method for Compensating Hemoglobin Interference in Total Serum Bilirubin Measurement Using a Simple Two-Wavelength Reflectance Photometer
Authors: Zucchini Lorenzo , Coda Zabetta Carlos Daniel , Ajčević Miloš , Accardo Agostino
Published: October 2024

Neonatal hyperbilirubinemia (NH) is a common condition in newborns, with elevated bilirubin levels potentially causing neurological damage or death. Accurate and timely measurements of total serum bilirubin are essential to prevent these outcomes. Direct spectrophotometry, a reliable method for measuring bilirubin, is particularly useful in constrained settings due to its potential for portable low-cost instrumentation. However, this method is susceptible to interference from hemoglobin, often present due to hemolysis. Typically, this interference is reduced using complex optical filters, reagents, multiple wavelengths, or combinations thereof, which increase costs and complexity while reducing usability. This study presents a hemoglobin compensation algorithm applied to a simple, portable, two-wavelength (465 and 590 nm) reflectance photometer designed to receive 30 µL of plasma or whole blood samples and perform the measurement without any reagents. Testing across five bilirubin and hemoglobin levels (4.96 to 28 mg/dL and 0.06 to 0.99 g/dL, respectively) demonstrated that the algorithm effectively reduces hemoglobin interference and overestimation errors. The overall root mean square error was reduced from 4.86 to 1.45 mg/dL, while the measurement bias decreased from −4.46 to −0.10 mg/dL. This substantial reduction in overestimation errors supports future clinical trials with neonatal blood samples.
Concatenated CNN-Based Pneumonia Detection Using a Fuzzy-Enhanced Dataset
Authors: Buriboev Abror Shavkatovich , Muhamediyeva Dilnoz , Primova Holida , Sultanov Djamshid , Tashev Komil , Jeon Heung Seok
Published: October 2024

Pneumonia is a form of acute respiratory infection affecting the lungs. Symptoms of viral and bacterial pneumonia are similar. Rapid diagnosis of the disease is difficult, since polymerase chain reaction-based methods, which have the greatest reliability, provide results in a few hours, while ensuring high requirements for compliance with the analysis technology and professionalism of the personnel. This study proposed a Concatenated CNN model for pneumonia detection combined with a fuzzy logic-based image improvement method. The fuzzy logic-based image enhancement process is based on a new fuzzification refinement algorithm, with significantly improved image quality and feature extraction for the CCNN model. Four datasets, original and upgraded images utilizing fuzzy entropy, standard deviation, and histogram equalization, were utilized to train the algorithm. The CCNN’s performance was demonstrated to be significantly improved by the upgraded datasets, with the fuzzy entropy-added dataset producing the best results. The suggested CCNN attained remarkable classification metrics, including 98.9% accuracy, 99.3% precision, 99.8% F1-score, and 99.6% recall. Experimental comparisons showed that the fuzzy logic-based enhancement worked significantly better than traditional image enhancement methods, resulting in higher diagnostic precision. This study demonstrates how well deep learning models and sophisticated image enhancement techniques work together to analyze medical images.
Hand Gesture Recognition Using Ultrasonic Array with Machine Learning
Authors: Joo Jaewoo , Koh Jinhwan , Lee Hyungkeun
Published: October 2024

In the field of gesture recognition technology, accurately detecting human gestures is crucial. In this research, ultrasonic transducers were utilized for gesture recognition. Due to the wide beamwidth of ultrasonic transducers, it is difficult to effectively distinguish between multiple objects within a single beam. However, they are effective at accurately identifying individual objects. To leverage this characteristic of the ultrasonic transducer as an advantage, this research involved constructing an ultrasonic array. This array was created by arranging eight transmitting transducers in a circular formation and placing a single receiving transducer at the center. Through this, a wide beam area was formed extensively, enabling the measurement of unrestricted movement of a single hand in the X, Y, and Z axes. Hand gesture data were collected at distances of 10 cm, 30 cm, 50 cm, 70 cm, and 90 cm from the array. The collected data were trained and tested using a customized Convolutional Neural Network (CNN) model, demonstrating high accuracy on raw data, which is most suitable for immediate interaction with computers. The proposed system achieved over 98% accuracy.
Presence of Soya in Industrial and Homemade Sausage Production in Kosovo and Its Reflection on Fatty Acid Profile
Authors: Mehmetukaj Dafina , Bytyçi Xhavit , Cana Armend , Gashi-Zogëjani Vlora , Shandro-Zeqiri Malbora , Bajraktari Drita , Jankuloski Dean , Hajrulai-Musliu Zehra
Published: October 2024

In the present study, we investigated to what extent soybean was used in industrial and homemade sausage produced in Kosovo, as well as its potential impact on the fatty acid profile. In total, 63 samples, 42 industrial and 21 traditional sausages, were collected either from the market or the production site. All samples were tested by means of real-time PCR for the detection and quantification of soy content, as well as the GC-FID to determine the potential reflection in the fatty acid profile. The presence of soy DNA was detected in 54 out of 63 samples. In total, 41 out of 42 industrial sausage samples were positive for soy DNA, with an average ct value of 22.60 and a standard deviation (SD) of 4.28, whereas 13 out of 21 traditional sausage samples were positive for soy DNA, with a mean ct value of 23.36 and a standard deviation (SD) of 4.56. There was a statistically significant difference in means between industrial sausage and traditional sausage, with p ≤ 0.001 based on CT values (ANOVA test). We investigated the correlation between ct values in real-time PCR for soy DNA with each fatty acid content. There is a moderate correlation of soy DNA ct values with C16:0 palmitin (decrease), C18:0 stearic acid (decrease), C18:1 oleic acid (increase), and overall saturated fatty acids (decrease). With the exception of C14:0 Myristin, C18:1 oleic, and C20:0 Arachin acids and monosaturated fats, the ANOVA test reveals a significant difference in means between groups for the majority of the fatty acids between industrial sausages and traditional sausages. The current study demonstrates that the fatty acid composition of sausages is influenced by the amount of soy present in them. The extent to which other components affect the fatty acid profile is unknown. However, an increase in oleic acid and a decrease in stearic and overall saturated fatty acids are expected.
What Is the (Lack Of) Integration? An Intergroup Perspective Using the Photovoice Methodology
Authors: Crapolicchio Eleonora , Marzana Daniela , Gaboardi Marta , Giuliani Cristina , Regalia Camillo
Published: October 2024

Photovoice is a participatory action research (PAR) method that employes photographic language to explore individuals’ stories and living contexts. This study explores the representations of young participants, both immigrants and non-immigrants, concerning integration—defined within Berry’s (1997) framework as a bidirectional process of cultural and social adaptation between migrants and host communities—and the lack of integration within their neighborhood in Reggio Emilia, Italy. The participants included 12 young individuals (6 migrants and 6 locals) aged 19 to 29, two peer researchers, and one researcher. Over the course of two weekly three-hour meetings, participants captured and discussed photos depicting their perspectives on integration. The findings highlighted diverse conceptualizations of integration. Participants emphasized the reciprocal relationship between migrants and locals, illustrating how positive interactions with schools, workplaces, and public spaces facilitate integration. Additionally, successful migrants were seen as models of empowerment. Conversely, themes such as poverty, loneliness, discrimination, and the impact of war emerged as significant barriers to integration. This study underscores the dynamic and interactive nature of integration, as experienced by young people in multicultural settings. It highlights how Photovoice methodology can effectively capture nuanced perspectives on integration, foster mutual understanding, and facilitate intergroup relationships. The method fosters personal and community reflection, actively engaging its audience in critical discussions about integration.
Social Representations of the War in Italy during the Russia/Ukraine Conflict
Authors: Melotti Giannino , Villano Paola , Pivetti Monica
Published: October 2024

Social representations of the war, anchored in historical experience and cultural values, play a motivational role in justifying collective behavior. Following Russia’s 2022 invasion of Ukraine, the research delves into the meanings associated with war through a social representation approach. Employing Doise’s sociodynamic approach, researchers identify the semantic field linked with war and analyze its organizing principles, revealing the variability of representations. In total, 313 Italian participants (female = 241, 75.4%; age range = 18–74) completed a questionnaire featuring a free association task with the word “war”, providing demographic and political and religious orientation data. Lexical correspondence analysis, utilizing Spad-t software, highlights three polarized themes: the emotional dimension aroused by war, media-conveyed imagery, and the underlying causes of conflict. The social anchoring analysis projects variables such as gender and political orientation onto a factorial plane. Finally, cluster analysis dissects psychological anchoring, identifying four distinct groups characterized by their descriptions of war: effects, reasons, emotions, and images. Theoretical and practical implications are discussed.
Looking Back When Moving Forward: Researching Sites of Former Disability Institutions
Authors: Kelly Jack , Creighton Leigh , Carnemolla Phillippa , Steele Linda
Published: October 2024

This article discusses an inclusive research program where colleagues and co-researchers (with intellectual disability) guide and inform future research practice to ensure research is targeted to areas of significance and relevance to them. The research program is about sites of former disability institutions. Many people with intellectual disability in Australia were segregated and forced to live in disability institutions until deinstitutionalisation efforts became mainstream in the late 20th Century. We are a team of four people based in New South Wales, Australia. Our team includes disability advocates and researchers who have contributed to a program of research exploring connections between sites of former disability institutions and contemporary disability rights. In this article, we reflect on conversations about our research undertaken so far and where the research goes from here. We explore five pillars of action informing how research relating to disability institutions can progress: 1. Current use: research exploring erasure of experiences of institutionalisation communicated through educational resources and maps about current use of sites of former disability institutions; 2. Reparative planning processes: research developing frameworks for alternative approaches to planning and heritage processes supporting alternative uses of former sites of disability institutions; 3. Official recognition and redress: research exploring perspectives on governments formally recognising and remedying experiences of people with disability who were institutionalised; 4. Community-led repair and remembrance: research identifying practices for both celebrating advocates with disability and reckoning with and repairing familial and social bonds broken through institutionalisation; 5. Community-inclusive practices: research exploring endurance of institutional practices in disability accommodation in community settings. These five pillars are underpinned by three foundational layers: advancing disability human rights; reckoning with intersections between disability institutions and settler colonialism, other dynamics of oppression, and eugenics; and using inclusive practices.
Spanish Healthcare Institutions and Their Role in Social Media-Driven Influenza Vaccination Campaigns: A Comprehensive Analysis of X
Authors: Jiménez-Hidalgo Pedro Jesús , Ruiz-Núñez Carlos , Jiménez-Gómez Beatriz , Segado-Fernández Sergio , Romero-Magdalena Carlos Santiago , López-Espuela Fidel , Herrera-Peco Ivan
Published: October 2024

Social media plays a crucial role in health information dissemination, yet it also raises concerns about misinformation. This study examines the role of Spanish health centers in promoting influenza vaccination on social networks, particularly X (formerly Twitter), during the 2023–2024 campaign. An observational, retrospective study analyzed the activity of 832 Spanish health centers on X. Data collection focused on the existence of official accounts, follower engagement and the nature of messages posted. Metrics were obtained using X Analytics, and statistical analysis was performed using JAMOVI v2.4 software. Of the 832 centers, 607 had readable X accounts. Collective accounts were more prevalent (351) than individual ones (239). Collective accounts had significantly more followers and posts but showed less engagement compared to individual accounts. The most followed accounts belonged to public entities, like the Community of Madrid and private organizations, such as Sanitas. An analysis of the vaccination campaign revealed that most posts had a political focus with limited health information, resulting in minimal interaction with the public. As a conclusion, the study highlights the fragmented nature of health communication through social networks in Spain. Despite the higher visibility of collective accounts, their engagement with the public is low, often due to the political nature of posts. A unified national strategy is essential for enhancing public health communication, focusing on interactive and relevant content.
The Internal Socio-Economic Polarization of Urban Neighborhoods: The Case of the Municipality of Nice
Authors: Gripsiou Argyro
Published: October 2024

In continuity with the research on social segregation and the phenomenon of urban gentrification, this article examines the cohabitation patterns of populations with diametrically opposed incomes within the same neighborhood, typically observed in the city center. This phenomenon is defined here as internal socio-economic polarization. It is measured through the combination of two original indexes (poverty and wealth indexes) constructed based on income deciles per consumption unit for the year of 2017. The analysis focuses on the municipality of Nice, characterized by a low demographic dynamic, a relative concentration of seniors, and a strong tourist attractiveness, particularly in the highly polarized neighborhoods that occupy almost the entire city center. This study is complemented by a principal component analysis summarizing the characteristics of the population and housing stock in the neighborhoods of Nice. The main objective of this research is to identify and locate polarized neighborhoods within the urban context of Nice, to analyze the distinctive traits of their population and housing stock, and, finally, to highlight potential trends in the population’s socio-economic status. Moreover, the economic trajectories of polarized neighborhoods, in connection with their population and housing characteristics (such as the secondary use of a portion of the housing stock, often low-quality old buildings, social housing, and the overrepresentation of retirees), help explain the forms of socio-economic polarization observed in these neighborhoods (such as the indications of gentrification, unfinished gentrification, and sustainable cohabitation).
On the Strategies and Efficiency of Care and Support Systems for Elderly Across Cantons in Switzerland
Authors: Huggenberger Yashka , Wagner Joël , Wanzenried Gabrielle
Published: October 2024

The Swiss Federal Council has formulated a policy requiring each canton to establish housing conducive to independent living during old age. Maintaining the independence of older adults at home rather than transitioning to more expensive institutional care has gained traction. This study investigates the heterogeneity of strategies arising from the autonomy granted to each canton. Using mandatory statistics from the Swiss Federal Statistical Office for 2020 on 1550 institutions for the elderly and 2546 at-home care providers, we rank the 26 cantons by permanent and temporary care and support, distinguishing between at-home and institutional care. We use univariate regressions to explain differences and perform efficiency analyses of the respective systems. We find that the French- and Italian-speaking cantons prioritise at-home care, while the German-speaking regions rely more on institutional care. The analyses reveal an inefficient stationary approach in German-speaking cantons, which often places elderly individuals with minimal care needs in institutions. Conversely, with an ambulatory approach favouring independence, cantons like Vaud and Valais prioritize counselling and at-home services, deferring entry into institutions and allowing for short convalescence stays. Our findings are relevant for governmental infrastructure planning and the property owners, investors, and property managers involved in senior housing decisions.
Anthropometric Profile and Position-Specific Changes in Segmental Body Composition of Professional Football Players Throughout a Training Period
Authors: Staśkiewicz-Bartecka Wiktoria , Krupa-Kotara Karolina , Rozmiarek Mateusz , Malchrowicz-Mośko Ewa , Grajek Mateusz , Elordui Saioa Agirre , Urriolabeitia Razkin Jokin , Babarro Arkaitz Castañeda
Published: October 2024

Body and anthropometric profiles of football players vary depending on the physiological and technical demands imposed by different positions. The aim of this study was to evaluate the body composition of professional soccer players in relation to their position on the field during a training macrocycle. The Direct Segmental Multi-Frequency Bioelectrical Impedance Analysis method was used to analyze 58 players at six key moments of the macrocycle. The results show that body profiles are adjusted to the specific demands of each position. Midfielders showed the lowest muscle mass, while defenders showed many notable changes. In general, as the season progressed, all field players experienced an increase in trunk body fat. Fat and lean mass values of goalkeepers differed greatly from the rest. The greatest variations in body composition were observed during pre-season and transition in relation to variations in training load and competitive intensity. The results suggest that the phase of the macrocycle has a greater influence on these variations, although the physical characteristics of each position are relevant. Understanding these dynamics allows for the design of more personalized and efficient training programs to optimize the performance of footballers according to their roles and each stage of the season.
Constituents over Correlation: Indicators and Arctic Urban Decision-Making
Authors: Tafrate Jacob D. , Nyland Kelsey E. , Orttung Robert W.
Published: October 2024

Arctic city mayors influence municipal sustainability outcomes, navigating decisions on waste management, social service funding, and economic development. How do mayors make these decisions and to what extent do they integrate sustainability indicator data? Interviews with the mayors of Fairbanks, Alaska, Yellowknife, Canada, and Luleå, Sweden, revealed indicators are used on a case-by-case basis to track trends but lack systematic integration into decision-making. Constituent concerns drive agendas rather than indicator trends. Based on International Organization for Standardization (ISO) guidelines, 128 indicators grouped into 19 sustainability themes were compiled from 2000 to 2019 for the study cities. Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied to examine the utility of ISO indicators as a guiding factor for sustainability trend tracking, identifying key themes for each city. Results show that indicator trends are too inconsistent and interconnected to be useful as an independent form of guidance for mayors. For Arctic municipalities, sustainability indicator datasets are useful in specific circumstances, but they do not provide the same kind of decision-making heuristic that mayors receive from direct constituent interaction. Findings emphasize the importance of more robust data collection and the development of management frameworks that support sustainability decision-making in Arctic cities.
Potential Identification of Root System Architecture Using GPR for Tree Translocation as a Sustainable Forestry Task: A Case Study of the Wild Service Tree
Authors: Kurowska Ewa E. , Czerniak Andrzej , Bańkowski Janusz , Kasztelan Adrian
Published: October 2024

Sustainable economic development serves society but requires taking over space, often at the expense of areas occupied by single trees or even parts of forest areas. Techniques for transplanting adult trees used in various conflict situations at the interface of economy and nature work as a tool for sustainable management of urbanized and industrial areas, as well as, in certain circumstances, forest or naturally valuable areas. This study aimed to evaluate the effectiveness of ground-penetrating radar (GPR) in determining the horizontal and vertical extent of tree root systems before transplantation. Employing this non-invasive method to map root system architecture aids in the appropriate equipment selection and helps define the dimensions and depth of trenches to minimize root damage during excavation. This study specifically focused on the root systems of wild service trees (Sorbus torminalis (L.) Crantz) found in a limestone mine area, where some specimens were planned to be transplanted, as the species is protected under law in Poland. The root systems were scanned with a ground-penetrating radar equipped with a 750 MHz antenna. Then, the root balls were dug out, and the root parameters and other dendrometric parameters were measured. The GPR survey and manual root analyses provided rich comparative graphic material. The number of the main roots detected by the GPR was comparable to those inventoried after extracting the stump. The research was carried out in problematic soil, causing non-standard deformations of the root systems. Especially in such conditions, identifying unusually arranged roots using the GPR method is valuable because it helps in a detailed planning of the transplanting process, minimizing root breakage during the activities carried out, which increases the survival chances of the transplanted tree in a new location.
Catalytic Effects of Potassium Concentration on Steam Gasification of Biofuels Blended from Olive Mill Solid Wastes and Pine Sawdust for a Sustainable Energy of Syngas
Authors: Nsibi Chafaa , Pozzobon Victor , Escudero-Sanz Javier , Lajili Marzouk
Published: October 2024

The effect of potassium impregnation at different concentrations during gasification, under nitrogen/water steam atmosphere, of char produced via pyrolysis of olive mill residues blended or not with pine sawdust was investigated. Three concentrations (0.1 M, 0.5 M, and 1.5 M) of potassium carbonate solution (K2CO3) were selected to impregnate samples. First, four types of pellets were prepared; one using exhausted olive mill solid waste (G) noted (100G) and three using G blended with pine sawdust (S) in different percentages (50%S–50%G (50S50G); 60%S–40%G (60S40G); 80%S–20%G (80S20G)). Investigations showed that when isothermal temperature increases during the gasification conducted with two water steam percentages of 10% and 30%, the reactivity increases with potassium concentration up to 0.5 M, especially for 100G. Still, higher catalyst concentration (1.5 M) showed adverse effects attributable to silicon release and char pore fouling. Moreover, the effect of the steam concentration on the gasification reactivity was significant with the non-impregnated sample 100G. Finally, a kinetic study was carried out to determine the different kinetic parameters corresponding to the Arrhenius law.
Balancing Efficiency and Environmental Impacts in Greek Viticultural Management Systems: An Integrated Life Cycle and Data Envelopment Approach
Authors: Tziolas Emmanouil , Karampatea Aikaterini , Karapatzak Eleftherios , Banias George F.
Published: October 2024

Greek wines excel in quality and exports, but the viticultural sector faces significant challenges from complex supply chains, shifting European policies, and the growing need for sustainability amidst climate change and economic pressures. External environmental costs could affect significantly the decision-making process of farmers, reflecting a broader evaluation of sustainability in viticulture. This study evaluates the economic and environmental impacts of organic, integrated, and conventional viticulture management systems in Drama, Greece using a life cycle (LC) approach and data envelopment analysis (DEA) to determine efficiency, quantify environmental impacts in monetary terms, and incorporate these costs into the analysis. Organic management systems have lower energy consumption and emissions compared to integrated and conventional systems, with organic systems ranging from 4546 to 6573 kWh/ha in energy use and 1358 to 1795 kg CO2 eq./ha in emissions, while integrated and conventional systems range from 9157 to 12,109 kWh/ha and 2961 to 3661 kg CO2 eq./ha. The DEA analysis reveals that most organic systems perform efficiently when accounting for environmental costs, whereas conventional systems face significant efficiency declines, with only a few maintaining optimal performance. Policy-supported transitions based on the provider gets principle are crucial for balancing economic and environmental goals in viticulture, as the integration of shadow prices significantly impacts efficiency.
Multi-Scale Risk-Informed Comprehensive Assessment Methodology for Lithium-Ion Battery Energy Storage System
Authors: Wang Lingzhi , Bu Yang , Wu Yichun
Published: October 2024

Lithium-ion batteries (LIB) are prone to thermal runaway, which can potentially result in serious incidents. These challenges are more prominent in large-scale lithium-ion battery energy storage system (Li-BESS) infrastructures. The conventional risk assessment method has a limited perspective, resulting in inadequately comprehensive evaluation outcomes, which impedes the provision of dependable technical support for the scientific appraisal of intricate large-scale Li-BESS systems. This study presents a novel Li-BESS-oriented multi-scale risk-informed comprehensive assessment framework, realizing the seamless transmission of assessment information across various scales. The findings from a previous smaller-scale analysis serve as inputs for a larger scale. The evaluation process of this method is more scientifically rigorous and yields more comprehensive results compared to assessment technologies just relying on a single perspective. By utilizing the proposed comprehensive assessment methodology, this study utilized the emergency power supply of nuclear power plants (NPPs) as an application scenario, demonstrating the complete implementation process of the framework and conducting a comprehensive assessment of Li-BESS feasibility as an emergency power source for NPPs. Our findings propose a novel paradigm for the comprehensive assessment of Li-BESS, which is expected to serve as a scientific foundation for decision-making and technical guidance in practical applications.
Measuring the Digital Maturity of Organisations in the People Care Sector
Authors: Kadoić Nikola , Monllau Jaques Teresa , Lacueva Rueda Jaime
Published: October 2024

This study focuses on the organisations in the people care sector (OPCs), encompassing a broad spectrum of activities ranging from essential healthcare services to various aspects of daily living support. Sustainability in OPCs encompasses multiple dimensions aimed at ensuring the long-term viability, efficiency, and effectiveness of services provided to vulnerable populations. Given the critical role of digital technologies in enhancing the operational efficiency within such organisations and their sustainability, it becomes imperative to gauge their digital maturity levels. To establish a robust framework for assessing the digital maturity of OPCs, we identified 29 factors grouped into five clusters that encapsulate various dimensions of digital readiness that directly influence the sustainability of OPCs. We employed the SNAP methodology to ascertain the relative significance of these factors and clusters. Furthermore, each factor was articulated through the lens of digital maturity using the rubrics approach, offering a nuanced understanding of the OPCs’ digital readiness across four distinct levels. Experts from the people care sector, IT, and multi-criteria decision-making contributed invaluable input during the instrument’s development phase. Theoretical validation of the instrument involved focus group discussions with domain experts, while practical validation entailed applying the instrument to real-world case studies. The instrument enables OPCs to assess their digital maturity levels, providing valuable strategic planning and decision-making insights. Furthermore, the instrument can serve as a roadmap for identifying areas ripe for digital transformation and weak points, facilitating continuous improvement and future readiness. The quantification of the digital maturity of the OPC enables the OPCs to rank at the cluster maturity level and overall maturity level. Overall, this instrument represents a significant step towards enhancing digital maturity assessment within the OPC sector, contributing to its evolution and adaptation in the digital age, and enabling the OPCs’ sustainability.
Study on the Coupling Coordination Degree and Driving Mechanism of “Production-Living-Ecological” Space in Ecologically Fragile Areas: A Case Study of the Turpan–Hami Basin
Authors: Gao Yue , Bai Linyan , Zhou Kefa , Kou Yanfei , Yuan Weiting , Zhou Xiaozhen , Qiu Ziyun , Zhao Dequan , Lv Zhihong , Wu Qiulan , Zhang Feng , Zhang Qing
Published: October 2024

One of the key conditions for achieving superior regional growth is ensuring the harmonious development of both the layout and functions of territorial space. Territorial space, which includes production space, living space, and ecological space, serves as a critical system and venue for economic, cultural, and social activities in a region. The harmonized growth of production–living–ecological space (PLES) is essential for attaining sustainable development goals. Research on PLES offers a fresh perspective on promoting sustainable development of the spatial domain and the sustainable use of resources. However, studies on PLE functions in ecologically fragile areas are lacking. Therefore, in this study, which adopts a PLES perspective, land-use data are used to classify land according to the dominant functions of production, ecology, and living. Integration of point-of-interest (POI) data with socio-economic data was established to spatially describe indicators at the grid level and create a scoring system for PLES indicators in ecologically fragile areas. Finally, the entropy weight method, holistic assessment methods, coupling coordination degree model (CCDM), and geodetector were employed to explore the coupling coordination relationships and factors influencing PLESs in the Turpan–Hami Basin from 2010 to 2020. The results indicate that the Turpan–Hami Basin consists predominantly of potential ecological space, mainly in the central and northern regions, which are characterized by the Gobi Desert and bare rock landforms. Over the past decade, the PLES framework has seen a notable rise in the allocation of residential and ecological areas, whereas the portion dedicated to production spaces has diminished. The overall coupling coordination degree (CCD) of PLES in the Turpan–Hami Basin is at a coordinated level and gradually increasing. The most significant impact on the degree of PLES coupling coordination is exerted by population and natural factors. The research findings provide theoretical support for the sustainable utilization of resources in the Turpan–Hami Basin and other ecologically fragile areas while also offering scientific evidence to promote the coupling coordination of PLES, thereby contributing to high-quality regional development.
Demand Forecast Information Sharing in Low-Carbon Supply Chains
Authors: Wang Yanjie , Wang Qinpeng , Shi Jingao
Published: October 2024

In view of the crucial role of consumer data concerning low-carbon preferences, a low-carbon supply chain was established, encompassing one manufacturer and one retailer. Both entities employed technological tools to predict consumer demand. This study assessed the profitability of supply chain participants under two strategies, “make-to-order” and “make-to-stock”, considering scenarios with and without demand forecast sharing information. Furthermore, we investigated how factors such as demand variability, forecast biases from the manufacturer and the retailer, and the forecast correlation coefficient affect the performance of the supply chain and the benefits of sharing information. Our findings indicate that the strategies of supply chain members remain unaffected by the chosen production models and that information sharing proves advantageous for the manufacturer and the retailer. Especially for manufacturers, profits in a “make-to-order” scenario surpass those in a “make-to-stock” scenario. Our numerical analysis showed that profits for the manufacturer and the retailer were consistently higher in scenarios where information was shared than in cases where it was not for “make-to-order” and “make-to-stock” strategies.
Effects of Offshore Wind Farms: Environmental and Social Perspectives from Uruguay
Authors: Forastiero Milagros , Gutiérrez Rodrigo , Weschenfelder Franciele , de Almeida Everton , Hernandez Jesus C.
Published: October 2024

The installation of offshore wind farms is rising, driven by the goal of changing the global energy matrix. However, many of their possible impacts are still unknown. Increased noise levels, disruptions to food chains, pollution due to traffic, and impacts on fishing communities and tourism are all potential effects to consider. Marine habitats are essential carbon dioxide sinks. Therefore, losing marine biodiversity due to offshore wind farms can be counterproductive in mitigating climate change. Balancing biodiversity conservation, wind potential, and political interests is challenging. Today, Uruguay has significantly decreased the fossil share in its electricity generation, incorporating electricity generation from wind, solar, and biomass energy alongside hydroelectricity. In line with this, the country’s Hydrogen Roadmap highlights green hydrogen as relevant, potentially serving as a fuel for both domestic and export transportation. Combining the country’s strong base of wind energy production experience with its sustainable policy, it plans to implement offshore wind farms to produce green hydrogen, making studies of its impacts crucial. This paper reviews the current social and environmental information on the Uruguayan coastal habitat, analyzes onshore wind farms’ ecological studies, and examines offshore wind farms’ global environmental and social impacts. Finally, it proposes studies for environmental approval of offshore wind farms.
A Computer Vision Model for Seaweed Foreign Object Detection Using Deep Learning
Authors: Zhang Xiang , Alhendi Omar , Hamid Siti Hafizah Ab , Japar Nurul , Nor Adibi M.
Published: October 2024

Seaweed foreign object detection has become crucial for food consumption and industrial use. This process not only can prevent potential health issues, but also maintain the overall marketability of seaweed production in the food industry. Traditional methods of inspecting seaweed foreign objects heavily rely on human judgment, which deals with large volumes with diverse impurities and can be inconsistent and inefficient. An automation system for real-time seaweed foreign object detection in the inspection process should be adopted. However, automated seaweed foreign object detection has several challenges due to its dependency on visual input inspection, such as an uneven surface and undistinguishable impurities. In fact, limited access to advanced technologies and high-cost equipment would also influence visual input acquisition, thereby hindering the advancement of seaweed foreign object detection in this field. Therefore, we introduce a computer vision model utilizing a deep learning-based algorithm to detect seaweed impurities and classify the samples into ‘clean’ and ‘unclean’ categories. In this study, we managed to identify six types of seaweed impurities including sand sticks, shells, discolored seaweed, grass, worm shells, and mixed impurities. We collected 1204 images and our model’s performance was thoroughly evaluated based on comparisons with three pre-trained models, i.e., Yolov8, ResNet, and MobileNet. Our experiment shows that Yolov8 outperforms the other two models with an accuracy of 98.86%. This study also included the development of an Android application to validate the deep learning engine to ensure its optimal performance. Based on our experiments, the mobile application managed to classify 50 pieces of seaweed samples within 0.2 s each, showcasing its potential use in large-scale production lines and factories. This research demonstrates the impact of Artificial Intelligence on food safety by offering a scalable and efficient solution that can be deployed in other food production processes facing similar challenges. Our approach paves the way for broader industry adoption and advancements in automated foreign object detection systems by optimizing detection accuracy and speed.
Insect Production: A Circular Economy Strategy in Iceland
Authors: Safavi Aysan , Thrastardottir Runa , Thorarinsdottir Ragnheidur I. , Unnthorsson Runar
Published: October 2024

In this review, the multifaceted issue of food security is addressed, emphasizing the need for innovative and culturally appropriate solutions. Exploring insect livestock farming emerges as a potential remedy, offering a pathway to alleviate food insecurity and promote food sovereignty, particularly when integrated with social acceptability. Stakeholder engagement on both production and consumption fronts, coupled with sustained support, is vital for successful implementation. The expanding landscape of commercial insect farming in the West prompts questions about its broader scalability and equitable deployment, especially for vulnerable populations. Existing research gaps underscore the need for a coordinated effort across international, national, and legal frameworks to effectively integrate insect farming into existing agricultural systems. In this review, we have delved into the industrial-scale production processes of mealworms and black soldier flies (BSFs), known for their high protein content and organic waste conversion, covering small and industrial cultivation methods, offering insights into mealworm production life cycles, innovative rearing systems, and harvesting techniques. This review concludes with climate-specific recommendations for insect facilities, stressing the importance of sustainable practices, continuous research and development, effective market strategies and economic feasibilities in Iceland. In the context of escalating demand for sustainable protein sources, industrial-scale insect production emerges as a pivotal player in addressing global food security challenges.