bluuebunny/crossref_metadata_2025 huggingface dataset:
Horizontal Rates of Wetland Migration Appear Unlikely to Keep Pace with Shoreline Transgression under Conditions of 21st Century Accelerating Sea Level Rise along the Mid-Atlantic and Southeastern USA
Authors: Parkinson Randall W.
Published: March 2024

This investigation evaluated two fundamental assumptions of wetland inundation models designed to emulate landscape evolution and resiliency under conditions of sea level rise: that they can (1) migrate landward at the same rate as the transgressing shoreline and (2) immediately replace the plant community into which they are onlapping. Rates of wetland (e.g., marsh, mangrove) migration were culled from 11 study areas located in five regions of focus: Delaware Bay, Chesapeake Bay, Pamlico Sound, South Florida, and Northwest Florida. The average rate of marsh migration (n = 14) was 3.7 m yr−1. The average rate of South Florida mangrove migration (n = 4) was 38.0 m yr−1. The average rate of upland forest retreat (n = 4) was 3.4 m yr−1. Theoretical rates of shoreline transgression were calculated using site-specific landscape slope and scenario-based NOAA sea level rise elevations in 2050. Rates of shoreline transgression over the marsh landscape averaged 94 m yr−1. The average rate of shoreline transgression in the mangrove-dominated areas of South Florida was 153.2 m yr−1. The calculated rates of shoreline transgression were much faster than the observed horizontal marsh migration, and by 2050, the offset or gap between them averaged 2700 m and ranged between 292 and 5531 m. In South Florida, the gap average was 3516 m and ranged between 2766 m and 4563 m. At sites where both horizontal marsh migration and forest retreat rates were available, the distance or gap between them in 2050 averaged 47 m. Therefore, the results of this study are inconsistent with the two fundamental assumptions of many wetland inundation models and suggest that they may overestimate their resilience under conditions of 21st century accelerating sea level rise.
A Case Study of Consumer’s Attitudes towards Agro-Food Markets in Danube Microregion in COVID-19 Pandemic
Authors: Iljkić Dario , Klepač Olgica , Užar Dubravka , Samfira Ionel , Dunđerski Dušan , Haman Daniel , Zoican Catalin , Majić Ivana , Varga Ivana
Published: March 2024

The COVID-19 pandemic affected many aspects of human life including consumer behavior. The main aim of this paper was to identify basic patterns of changes in consumer attitudes towards agri-food products under the influence of the 2020 pandemic and to better understand to what extent and what kind of food market problems appeared for the inhabitants of the Danube microregion. For this purpose, an explorative study was elaborated. Assuming that the experience of COVID-19 affected consumer attitudes and sense of food security, a hybrid survey was conducted in the Danube microregion (Croatia, Serbia and Romania) during 2022. Data collected from a total of 903 respondents were statistically analyzed in SPSS. Descriptive statistics, PCA, ANOVA and t-Test were employed. The main results have shown that although the surveyed population of the Danube microregion during the pandemic in 2020 was generally not afraid of food shortages, food was in most part available for their families and their shopping habits have not changed to a large degree, the experience of the pandemic has raised the level of awareness about some issues related to food and specifically the prices of food products. Also, three different patterns of attitude and behavior towards food and agriculture, which emerged as a result of the experience of the pandemic in 2020, were identified. These patterns also proved to be different for different segments of the population. The findings suggest the need for stronger support for the development of locally affordable food systems with the use of ICT as a coping mechanism in crises.
Examining Model Similarity for Exercise Self-Efficacy among Adults Recovering from a Stroke: A Community-Based Exercise Program
Authors: Pastore Olivia L. , Jarry François , Zou Jammy , Tomasone Jennifer R. , Martin Luc J. , Pagé Véronique , Sweet Shane N.
Published: March 2024

We used a single-case experimental research design to examine the effect of modelling (peer versus non-peer) on exercise self-efficacy in stroke survivors who participated in a community-based exercise program. Data were obtained using an ABCA design: (A1) no model/baseline 1 (3 weeks); (B) peer model (6 weeks); (C) non-peer model (6 weeks); and (A2) no model/baseline 2 (3 weeks). Four participants completed self-efficacy questionnaires after each weekly session. Overall, participants reported higher exercise self-efficacy in the model conditions (Cohen’s d range from −0.37 to 4.22), with ratings appearing highest for the non-peer model. Modelling in general may help stroke survivors increase their exercise self-efficacy. Lastly, we provide our reflections on the pragmatics of completing a study within a community setting.
Wheelchair Dance: Exploring a Novel Approach to Enhance Wheelchair Skills, Belongingness and Inclusion among Children with Mobility Limitations
Authors: Berthiaume Jade , Cherriere Claire , Ouellet Béatrice , Éthier Laurence , Rushton Paula W. , Lemay Martin , Best Krista L.
Published: March 2024

Playful approaches are recommended to enhance wheelchair skills training with young people. Inclusive dance allows participants to discover motor skills and improve social participation. Integrating wheelchair skills training into dance has not been evaluated. This study aimed to explore participants’ experiences in dance while integrating wheelchair skills, and the influence of dance on wheelchair skills and wheelchair use confidence in young people. A convergent mixed-methods design was used during a one-week dance camp. Data collection combined observations, two focus groups (with young dancers who used manual wheelchairs and with professional dancers without disabilities), and evaluation of wheelchair skills and confidence. Data analyses included deductive thematic analysis guided by the Quality Parasport Participation Framework, merged with pre–post comparisons in wheelchair skills and confidence. Three young female dancers were 11, 12 and 15 years of age and three professional female dancers were 22, 27 and 27 years of age. Emergent themes included skill mastery, belongingness, and supportive environments. There were improvements in wheelchair skills and confidence (16.7%, 19.4%, 16.7%; 0.8%, 11.4%, 4.5%, respectively). Participants described overall positive experiences with the dance camp and perceived enhanced skills and confidence. This study advances knowledge about innovative approaches to integrate wheelchair skills training for young people. Future larger-scale controlled studies are needed to determine efficacy.
The Assessment of SF-36 Survey for Quality-of-Life Measurement after Radical Cystectomy for Muscle-Invasive Bladder Cancer: A Systematic Review
Authors: Barbos Vlad , Feciche Bogdan , Latcu Silviu , Croitor Alexei , Dema Vlad , Bardan Razvan , Faur Flaviu Ionut , Mateescu Tudor , Novacescu Dorin , Bogdan Gherle , Cumpanas Alin Adrian
Published: March 2024

This study presents a systematic review of the literature on individuals’ health-related quality of life (HRQoL) following radical cystectomy for muscle-invasive bladder cancer (MIBC), utilizing the Short Form-36 Health Survey (SF-36) as a primary assessment tool. The review was designed as an exhaustive literature search across three major databases including PubMed, Scopus, and Embase up to December 2023, using the PRISMA guidelines. The selection process refined 2281 identified articles down to 11 studies meeting our inclusion criteria. These studies encompassed a diverse demographic and clinical profile of 774 participants, with follow-up durations ranging from 3 to 130 months, thereby offering insights into both short-term and long-term HRQoL outcomes. The results highlighted significant alterations in individuals’ HRQoL across various domains post-radical cystectomy. Notably, the Physical Functioning (PF) and Bodily Pain (BP) domains generally scored higher, indicating a moderate to high perceived physical health status. However, the Role Physical (RP) and Role Emotional (RE) domains showed variability, reflecting the challenges in daily role fulfillment and emotional adjustment post-surgery. A marked variability in physical recovery was observed, with studies reporting significant differences in PF and RP scores between patient groups. The General Health (GH) and Vitality (VT) domains sometimes reflected perceived deteriorations, whereas the Mental Health (MH) scores suggested that many patients maintained or achieved high levels of well-being post-operatively. The conclusions drawn from this systematic review underscore the profound and multi-faceted impact of radical cystectomy on HRQoL, varying widely between studies, being influenced by geographic factors, surgical methods, and the time of evaluation. The findings emphasize the necessity for holistic patient care approaches that address both physical and emotional rehabilitation, aiming to improve HRQoL outcomes.
Group Structure as a Foundation for Entropies
Authors: Jensen Henrik Jeldtoft , Tempesta Piergiulio
Published: March 2024

Entropy can signify different things. For instance, heat transfer in thermodynamics or a measure of information in data analysis. Many entropies have been introduced, and it can be difficult to ascertain their respective importance and merits. Here, we consider entropy in an abstract sense, as a functional on a probability space, and we review how being able to handle the trivial case of non-interacting systems, together with the subtle requirement of extensivity, allows for a systematic classification of the functional form.
(Re)Construction of Quantum Space-Time: Transcribing Hilbert into Configuration Space
Authors: Svozil Karl
Published: March 2024

Space-time in quantum mechanics is about bridging Hilbert and configuration space. Thereby, an entirely new perspective is obtained by replacing the Newtonian space-time theater with the image of a presumably high-dimensional Hilbert space, through which space-time becomes an epiphenomenon construed by internal observers.
Duration Perception and Reading in Typically Developing Adults and Adults with Developmental Dyslexia: Implications for Assessment and Intervention
Authors: Liapi Aikaterini , Silva Susana , Folia Vasiliki
Published: March 2024

While the link between beat perception and reading skills is attributed to a general improvement in neural entrainment to speech units, duration perception (DP) is primarily linked to a specific aspect of speech perception, specifially discriminating phonemes of varying lengths. Our previous study found a significant correlation between DP and pseudoword reading in both typically developing (TD) individuals and adults with dyslexia (DD). This suggests that, like beat, DP may also enhance overall speech perception. However, our previous study employed a composite measure that did not discriminate speed from accuracy. In this study, we sought to replicate the link between DP and pseudoword reading in a new sample and explore how it might vary depending on the reading parameter being measured. We analyzed the performance of 60 TD vs. 20 DD adults in DP, word reading and pseudoword reading tasks, analyzing the latter for both speed and accuracy. Indeed, duration skills correlated positively with pseudoword reading accuracy. In TD adults, there was no association between DP and reading speed, whereas DD individuals exhibited slower reading speed alongside improved duration skills. We emphasize the potential usefulness of DP tasks in assessment and early intervention and raise new questions about compensatory strategies adopted by DD adults.
Examining Students’ Acceptance and Use of ChatGPT in Saudi Arabian Higher Education
Authors: Sobaih Abu Elnasr E. , Elshaer Ibrahim A. , Hasanein Ahmed M.
Published: March 2024

This study examines students’ acceptance and use of ChatGPT in Saudi Arabian (SA) higher education, where there is growing interest in the use of this tool since its inauguration in 2022. Quantitative research data, through a self-reporting survey drawing on the “Unified Theory of Acceptance and Use of Technology” (UTAUT2), were collected from 520 students in one of the public universities in SA at the start of the first semester of the study year 2023–2024. The findings of structural equation modeling partially supported the UTAUT and previous research in relation to the significant direct effect of performance expectancy (PE), social influence (SI), and effort expectancy (EE) on behavioral intention (BI) on the use of ChatGPT and the significant direct effect of PE, SI, and BI on actual use of ChatGPT. Nonetheless, the results did not support earlier research in relation to the direct relationship between facilitating conditions (FCs) and both BI and actual use of ChatGPT, which was found to be negative in the first relationship and insignificant in the second one. These findings were because of the absence of resources, support, and aid from external sources in relation to the use of ChatGPT. The results showed partial mediation of BI in the link between PE, SI, and FC and actual use of ChatGPT in education and a full mediation in the link of BI between EE and actual use of ChatGPT in education. The findings provide numerous implications for scholars and higher education institutions in SA, which are also of interest to other institutions in similar contexts.
Decentralized Exchange Transaction Analysis and Maximal Extractable Value Attack Identification: Focusing on Uniswap USDC3
Authors: Choi Nakhoon , Kim Heeyoul
Published: March 2024

With the advancement of blockchain technology and growing concerns about the vulnerabilities and mistrust in centralized financial services, decentralized finance (DeFi) and decentralized exchanges (DEXs) have emerged as promising alternatives. This paper delves into the challenges and issues within DeFi, with a particular focus on Uniswap. We highlight the susceptibility to Maximal Extractable Value (MEV) attacks, providing a background on the current state of DeFi and DEXs. Our approach includes a detailed transaction analysis on Uniswap to identify and analyze MEV attack patterns, alongside a method for detecting bots. The results offer critical insights into the nature of various attacks in DEXs and the correlation between internal and external blockchain events and MEV attack patterns. This research provides valuable guidelines for enhancing DEX security and mitigating MEV risks, serving as an essential resource for stakeholders in the DeFi ecosystem.
Advancing Temporal Action Localization with a Boundary Awareness Network
Authors: Gu Jialiang , Yi Yang , Wang Min
Published: March 2024

Temporal action localization (TAL) is crucial in video analysis, yet presents notable challenges. This process focuses on the precise identification and categorization of action instances within lengthy, raw videos. A key difficulty in TAL lies in determining the exact start and end points of actions, owing to the often unclear boundaries of these actions in real-world footage. Existing methods tend to take insufficient account of changes in action boundary features. To tackle these issues, we propose a boundary awareness network (BAN) for TAL. Specifically, the BAN mainly consists of a feature encoding network, coarse pyramidal detection to obtain preliminary proposals and action categories, and fine-grained detection with a Gaussian boundary module (GBM) to get more valuable boundary information. The GBM contains a novel Gaussian boundary pooling, which serves to aggregate the relevant features of the action boundaries and to capture discriminative boundary and actionness features. Furthermore, we introduce a novel approach named Boundary Differentiated Learning (BDL) to ensure our model’s capability in accurately identifying action boundaries across diverse proposals. Comprehensive experiments on both the THUMOS14 and ActivityNet v1.3 datasets, where our BAN model achieved an increase in mean Average Precision (mAP) by 1.6% and 0.2%, respectively, over existing state-of-the-art methods, illustrate that our approach not only improves upon the current state of the art but also achieves outstanding performance.
Implementation of EnDat Interface Master Using Configurable Logic Block in MCU
Authors: Kim Kyungah , Tran Duc M. , Choi Joon-Young
Published: March 2024

In this study, we propose an implementation method of the Encoder Data (EnDat) interface master for slave encoders using only a configurable logic block (CLB) and a serial peripheral interface (SPI) integrated into microcontroller units. By programming the CLB device to execute logic functions and finite state machines designed for the EnDat interface master operation, we realize the EnDat and SPI clocks that are required for the EnDat interface master operation. This approach is cost-efficient because additional hardware components, such as a field-programmable gate array or a complex programmable logic device, are unnecessary for the master implementation. We build a one-axis feed drive system that is powered by an AC motor and equipped with an EnDat linear encoder for measuring table speed and position. By performing various experiments for table position and speed control based on the built feed drive system, we verify the performance and practical usefulness of the implemented EnDat interface master. The maximum EnDat clock frequency without the propagation delay compensation is achieved by 2 MHz, which can cope with 16 kHz control cycle frequency. The usefulness is demonstrated by showing the table speed and position control performance that are acceptable in real applications.
A Space-Borne SAR Azimuth Multi-Channel Quantization Method
Authors: Xu Wei , Bai Lu , Huang Pingping , Tan Weixian , Dong Yifan
Published: March 2024

The space-borne synthetic aperture radar (SAR) azimuth multi-channel system has extensive applications because it can achieve high-resolution and wide-swath radar imaging. The thermal noise generated by the radar receiver of each channel during operation will cause an imbalance between channels. If the echoes of each channel are quantized with the same number of bits without considering the influence of thermal noise, false targets will appear in the imaging consequences. Considering that the thermal noise generated in the receiver will affect the quantization process of the space-borne SAR azimuth multi-channel system, a new space-borne SAR azimuth multi-channel quantization method is proposed to improve this problem. Firstly, the pure noise power of the receiver is calculated without transmitting the radar signal. The signal power is estimated by subtracting the pure noise power from the total power. Then, the average value of the radar echo signal minus k times the standard deviation is used as the left endpoint of the original data amplitude range, and the average value of the radar echo signal plus k times the standard deviation is used as the right endpoint of the original data amplitude range. The original echo data after adjusting the amplitude range is quantified. This method can effectively reduce the influence of thermal noise and random outliers in the receiver on quantization and suppress the appearance of false targets. Finally, simulation is used to confirm the viability of the suggested quantization approach.
Advancing Borehole Imaging: A Classification Database Developed via Adaptive Ring Segmentation
Authors: Deng Zhaopeng , Han Shuangyang , Liu Zeqi , Wang Jian , Zhao Haoran
Published: March 2024

The use of in-hole imaging to investigate geological structure characteristics is one of the crucial methods for the study of rock mass stability and rock engineering design. The in-hole images are usually influenced by the lighting and imaging characteristics, resulting in the presence of interference noise regions in the images and consequently impacting the classification accuracy. To enhance the analytical efficacy of in-hole images, this paper employs the proposed optimal non-concentric ring segmentation method to establish a new database. This method establishes the transformation function based on the Ansel Adams Zone System and the fluctuation values of the grayscale mean, adjusting the gray-level distribution of images to extract two visual blind spots of different scales. Thus, the inner and outer circles are located with these blind spots to achieve the adaptive acquisition of the optimal ring. Finally, we use the optimal non-concentric ring segmentation method to traverse all original images to obtain the borehole image classification database. To validate the effectiveness of this method, we conduct experiments using various segmentation and classification evaluation metrics. The results show that the Jaccard and Dice of the optimal non-concentric ring segmentation approach are 88.43% and 98.55%, respectively, indicating superior segmentation performance compared to other methods. Furthermore, after employing four commonly used classification models to validate the performance of the new classification database, the results demonstrate a significant improvement in accuracy and macro-average compared to the original database, with the highest increase in accuracy reaching 4.2%. These results fully demonstrate the effectiveness of the proposed optimal non-concentric ring segmentation method.
Combined K-Means Clustering with Neural Networks Methods for PV Short-Term Generation Load Forecasting in Electric Utilities
Authors: Sleiman Alex , Su Wencong
Published: March 2024

The power system has undergone significant growth and faced considerable challenges in recent decades, marked by the surge in energy demand and advancements in smart grid technologies, including solar and wind energies, as well as the widespread adoption of electric vehicles. These developments have introduced a level of complexity for utilities, compounded by the rapid expansion of behind-the-meter (BTM) photovoltaic (PV) systems, each with its own unique design and characteristics, thereby impacting power grid stability and reliability. In response to these intricate challenges, this research focused on the development of a robust forecasting model for load generation. This precision forecasting is crucial for optimal planning, mitigating the adverse effects of PV systems, and reducing operational and maintenance costs. By addressing these key aspects, the goal is to enhance the overall resilience and efficiency of the power grid amidst the evolving landscape of energy and technological advancements. The authors propose a solution leveraging LSTM (long short-term memory) model for a forecasting horizon up to 168 hours. This approach incorporates combinations of K-means clustering, automated meter infrastructure (AMI) real-world PV load generation, weather data, and calculated solar positions to forecast the generation load at customer locations to achieve a 5.7% mean absolute error between the actual and the predicted generation load.
Sustainability and Resilience Assessment Methods: A Literature Review to Support the Decarbonization Target for the Construction Sector
Authors: Sesana Marta Maria , Dell’Oro Paolo
Published: March 2024

It is a well-known issue that the 2050 target of carbon emissions neutrality will be reached only with the co-operation of all the interested sectors, and the construction sector could be one of the main contributors to this change. With the built environment globally responsible for about 40% of annual global energy-related CO2 emissions, the construction sector offers an important opportunity to drive transformative change and presents the most challenging mitigation potential among all industrial sectors, which also brings opportunities for adopting sustainability practices and increasing resilience. This paper presents a systematic literature review of those two pivotal concepts to reach the decarbonization goal: sustainability and resilience. Starting from an extensive literature review (2536 scientific documents) based on the PRISMA statement, the definitions and assessment methodologies of those concepts for the construction sector have been studied. The methodological approach followed for their analysis has been conducted on a first selection of 42 documents, further reduced to 12 by using clear inclusion criteria to identify the integrated assessment procedures. The main goal of this study is to clarify the correlation between sustainability and resilience concepts for constructions and their integrated assessment, in line with the latest regulations and market needs. The results show that, currently, sustainability and resilience are mainly evaluated in a distinct way to obtain building energy performance certificates, as well as to quantify the building market value and its complementary contribution to the ‘energy efficiency first’ principle and energy-saving targets towards the emergent issue of climate change. Few works focus on the integrated assessment of both concepts considering the construction industries’ point of view about materials and/or systems for buildings. The novelty of this study is the critical review of the current sustainability and resilience integrated assessment methods used for the construction value chain, declined for four main target groups. Researchers, policymakers, industries, and professionals could gain dedicated insights and practical suggestions to put in practice the elements of circular economy, ecological innovation, and cleaner production, which are essential in order to drive the decarbonization of the built environment.
The Interaction between Short- and Long-Term Energy Storage in an nZEB Office Building
Authors: Stamatellos George , Stamatellou Antiopi-Malvina
Published: March 2024

The establishment of near-autonomous micro-grids in commercial or public building complexes is gaining increasing popularity. Short-term storage capacity is provided by means of large battery installations, or, more often, by the employees’ increasing use of electric vehicle batteries, which are allowed to operate in bi-directional charging mode. In addition to the above short-term storage means, a long-term storage medium is considered essential to the optimal operation of the building’s micro-grid. The most promising long-term energy storage carrier is hydrogen, which is produced by standard electrolyzer units by exploiting the surplus electricity produced by photovoltaic installation, due to the seasonal or weekly variation in a building’s electricity consumption. To this end, a novel concept is studied in this paper. The details of the proposed concept are described in the context of a nearly Zero Energy Building (nZEB) and the associated micro-grid. The hydrogen produced is stored in a high-pressure tank to be used occasionally as fuel in an advanced technology hydrogen spark ignition engine, which moves a synchronous generator. A size optimization study is carried out to determine the genset’s rating, the electrolyzer units’ capacity and the tilt angle of the rooftop’s photovoltaic panels, which minimize the building’s interaction with the external grid. The hydrogen-fueled genset engine is optimally sized to 40 kW (0.18 kW/kWp PV). The optimal tilt angle of the rooftop PV panels is 39°. The maximum capacity of the electrolyzer units is optimized to 72 kW (0.33 kWmax/kWp PV). The resulting system is tacitly assumed to integrate to an external hydrogen network to make up for the expected mismatches between hydrogen production and consumption. The significance of technology in addressing the current challenges in the field of energy storage and micro-grid optimization is discussed, with an emphasis on its potential benefits. Moreover, areas for further research are highlighted, aiming to further advance sustainable energy solutions.
Scalable and Quench-Free Processing of Metal Halide Perovskites in Ambient Conditions
Authors: Cartledge Carsen , Penukula Saivineeth , Giuri Antonella , Bakshi Kayshavi , Ahmad Muneeza , Mahaffey Mason , Li Muzhi , Zhang Rui , Rizzo Aurora , Rolston Nicholas
Published: March 2024

With the rise of global warming and the growing energy crisis, scientists have pivoted from typical resources to look for new materials and technologies. Perovskite materials hold the potential for making high-efficiency, low-cost solar cells through solution processing of Earth-abundant materials; however, scalability, stability, and durability remain key challenges. In order to transition from small-scale processing in inert environments to higher throughput processing in ambient conditions, the fundamentals of perovskite crystallization must be understood. Classical nucleation theory, the LaMer relation, and nonclassical crystallization considerations are discussed to provide a mechanism by which a gellan gum (GG) additive—a nontoxic polymeric saccharide—has enabled researchers to produce quality halide perovskite thin-film blade coated in ambient conditions without a quench step. Furthermore, we report on the improved stability and durability properties inherent to these films, which feature improved morphologies and optoelectronic properties compared to films spin-coated in a glovebox with antisolvent. We tune the amount of GG in the perovskite precursor and study the interplay between GG concentration and processability, morphological control, and increased stability under humidity, heat, and mechanical testing. The simplicity of this approach and insensitivity to environmental conditions enable a wide process window for the production of low-defect, mechanically robust, and operationally stable perovskites with fracture energies among the highest obtained for perovskites.
Climate Change Challenges in Temperate and Sub-Tropical Fruit Tree Cultivation
Authors: Roussos Petros A.
Published: March 2024

In the last few years, the world has experienced the impacts of climate change, such as elevated mean annual temperature, extreme weather events, drought, etc. Among living organisms, perennial plant species are the ones mostly exposed to climate change impacts, as they may experience different extreme events within the same year, such as flooding during some periods and drought in summer months, extremely low temperatures in winter but excessively high temperatures in summer, etc. Climate change affects a range of physiological functions of temperate fruit and nut tree species, such as their phenophases, bud dormancy release and vernalization, pollination and fruit set, fruit growth and quality, as well as bud sprouting and growth initiation. Besides these, the impact of climate change on pests, diseases, and weeds may generate significant negative interactions with tree physiology, threatening food production, food safety, and human welfare. In the present manuscript, a general aspect of climate change impacts on fruits’ and nut trees’ physiological functions is described and commented on.
Edge and Fog Computing for the Internet of Things
Authors: Pozzebon Alessandro
Published: March 2024

Over the last years few years, the number of interconnected devices within the context of Internet of Things (IoT) has rapidly grown; some statistics state that the total number of IoT-connected devices in 2023 has reached the groundbreaking number of 17 billion [...]
UP-SDCG: A Method of Sensitive Data Classification for Collaborative Edge Computing in Financial Cloud Environment
Authors: Zu Lijun , Qi Wenyu , Li Hongyi , Men Xiaohua , Lu Zhihui , Ye Jiawei , Zhang Liang
Published: March 2024

The digital transformation of banks has led to a paradigm shift, promoting the open sharing of data and services with third-party providers through APIs, SDKs, and other technological means. While data sharing brings personalized, convenient, and enriched services to users, it also introduces security risks, including sensitive data leakage and misuse, highlighting the importance of data classification and grading as the foundational pillar of security. This paper presents a cloud-edge collaborative banking data open application scenario, focusing on the critical need for an accurate and automated sensitive data classification and categorization method. The regulatory outpost module addresses this requirement, aiming to enhance the precision and efficiency of data classification. Firstly, regulatory policies impose strict requirements concerning data protection. Secondly, the sheer volume of business and the complexity of the work situation make it impractical to rely on manual experts, as they incur high labor costs and are unable to guarantee significant accuracy. Therefore, we propose a scheme UP-SDCG for automatically classifying and grading financially sensitive structured data. We developed a financial data hierarchical classification library. Additionally, we employed library augmentation technology and implemented a synonym discrimination model. We conducted an experimental analysis using simulation datasets, where UP-SDCG achieved precision surpassing 95%, outperforming the other three comparison models. Moreover, we performed real-world testing in financial institutions, achieving good detection results in customer data, supervision, and additional in personally sensitive information, aligning with application goals. Our ongoing work will extend the model’s capabilities to encompass unstructured data classification and grading, broadening the scope of application.
FFYOLO: A Lightweight Forest Fire Detection Model Based on YOLOv8
Authors: Yun Bensheng , Zheng Yanan , Lin Zhenyu , Li Tao
Published: March 2024

Forest is an important resource for human survival, and forest fires are a serious threat to forest protection. Therefore, the early detection of fire and smoke is particularly important. Based on the manually set feature extraction method, the detection accuracy of the machine learning forest fire detection method is limited, and it is unable to deal with complex scenes. Meanwhile, most deep learning methods are difficult to deploy due to high computational costs. To address these issues, this paper proposes a lightweight forest fire detection model based on YOLOv8 (FFYOLO). Firstly, in order to better extract the features of fire and smoke, a channel prior dilatation attention module (CPDA) is proposed. Secondly, the mixed-classification detection head (MCDH), a new detection head, is designed. Furthermore, MPDIoU is introduced to enhance the regression and classification accuracy of the model. Then, in the Neck section, a lightweight GSConv module is applied to reduce parameters while maintaining model accuracy. Finally, the knowledge distillation strategy is used during training stage to enhance the generalization ability of the model and reduce the false detection. Experimental outcomes demonstrate that, in comparison to the original model, FFYOLO realizes an mAP0.5 of 88.8% on a custom forest fire dataset, which is 3.4% better than the original model, with 25.3% lower parameters and 9.3% higher frames per second (FPS).
Decolonising Fire Science by Reexamining Fire Management across Contested Landscapes: A Workshop Approach
Authors: Croker Abigail Rose , Ford Adriana E. S. , Kountouris Yiannis , Mistry Jayalaxshmi , Muthiuru Amos Chege , Smith Cathy , Praise Elijah , Chiawo David , Muniu Veronica
Published: March 2024

In many landscapes worldwide, fire regimes and human–fire interactions were reorganised by colonialism and continue to be shaped by neo-colonial processes. The introduction of fire suppression policies and state-centric property-rights systems across conservation areas and the intentional erasure of Indigenous governance systems and knowledge have served to decouple Indigenous fire-dependent communities from culturally mediated fire regimes and fire-adapted landscapes. This has driven a decline in anthropogenic fires while simultaneously increasing wildfire risk where Indigenous people have been excluded, resulting in widespread social–ecological vulnerabilities. Much contemporary fire research also bears colonial legacies in its epistemological traditions, in the global geographical distribution of research institutions, and the accessibility of research outputs. We report on a two-day workshop titled ‘Fire Management Across Contested Landscapes’ convened concurrently in Nairobi, Kenya, and London, UK. The workshop formed part of a series of workshops on ‘Decolonising Fire Science’ held by the Leverhulme Centre for Wildfires, Environment and Society, UK. The workshop in Nairobi invited diverse Kenyan stakeholders to engage in participatory activities that facilitate knowledge sharing, aiming to establish an inclusive working fire network. Activities included rich pictures, world café discussions, participatory art, and the co-development of a declaration to guide fire management in Kenya. Meanwhile, in London, Leverhulme Wildfires researchers explored participatory research methodologies including rich pictures and participatory video, and developed a declaration to guide more equitable research. There were opportunities throughout the workshop for participants in Nairobi and London to engage in dialogue with one another, sharing their experiences and understandings of complex fire challenges in Kenya and globally.
Research on the Inhibitory Effect of Hydrated Phase Change Materials on Spontaneous Combustion in Coal
Authors: Wu Fanghua , Shi Shiliang , Shao Shuzhen , Lu Yi , Gu Wangxin , Wang Youliang , Yuan Xindi
Published: March 2024

In order to study the effect of hydrated phase change materials on the suppression of spontaneous combustion in coal, a thermogravimetric experiment and a reaction activation energy analysis experiment were conducted to explore the changes in the combustion characteristic parameters, characteristic temperature, and activating energy of gas coal, long-flame coal, meagre coal, and lean coal before and after adding hydrated phase change materials. The research results indicated that hydrated phase change materials increased the characteristic temperature point of the coal samples and had effective inhibitory effects on different stages of the oxidation process. However, the effect was best at low temperatures, as hydrated phase change materials undergo phase change and absorb heat when heated at low temperatures, isolating coal from contact with oxygen. The activating energy increased by 1.138–23.048 KJ·mol−1 and the mass loss was reduced by 1.6%–9.3% after inhibition of the coal samples, indicating that the oxidation rate of the various coal samples was slowed down and, thus, spontaneous combustion can be suppressed through the use of hydrated phase change materials. At the same time, this material reduced the combustibility indices of meagre coal and lean coal, as well as the comprehensive combustion indices of long-flame coal and gas coal.
Experimental Analysis of the Effect of Limescale on the Wettability of Indirect Evaporative Cooling System Plates
Authors: Caruana Roberta , Marocco Luca , Liberati Paolo , Guilizzoni Manfredo
Published: March 2024

Indirect evaporative cooling systems have attracted much interest in recent years as they guarantee good cooling effectiveness, with lower energy demand with respect to traditional systems, thus helping to address the issue of climate change. Many studies have shown that an increase in the wettability of recuperator plates results in an improvement in the system performance. However, if the water injected into the system comes from the city water supply, it will contain calcium carbonate residuals, which will form limescale layers on the plates, thus possibly changing their wetting behavior. Therefore, the wettability of three surfaces (an aluminum uncoated surface, AL, a standard epoxy coating, STD, and a hydrophilic lacquer, HPHI) was analyzed in the presence of limescale formations, and compared with that obtained in a previous study for corresponding clean surfaces. The results showed that the HPHI contact angle was reduced in the presence of limescale (median: 50°), that for STD was slightly increased (median: 81°), and that for AL was again reduced (median: 75°). Consequently, HPHI was confirmed to be the most wettable surface in both clean and limescale conditions. Finally, an analysis was undertaken evaluating the spreading factor and the reversible work of adhesion, which were in good agreement with the qualitative visual observations of the plates covered with limescale.
Comparison of Gas Treatments of High Oxygen, Carbon Monoxide, and Nitric Oxide on Ground Beef Color in Modified Atmosphere Packaging
Authors: Carpenter Benjamin J. , Dobbins Thomas W. , Hernandez Manuel Sebastian , Barker Samantha N. , Loomas Kaitlyn R. , Osburn Wesley N. , Legako Jerrad F.
Published: March 2024

The objective of this study was to evaluate the viability and performance of nitric oxide modified-atmosphere packaging (MAP) as a novel alternative to high oxygen and carbon monoxide MAP for ground beef. Packages of ground beef under high oxygen (HI-OX), carbon monoxide (CO), and nitric oxide (NO) atmospheres were evaluated for descriptive and instrumental color every 12 h during a 120 h display period. Surface myoglobin percentages, internal cooked color, thiobarbituric acid reactive substances (TBARS), and residual nitrite and nitrate were also evaluated. There were gas × time interactions for descriptive color, discoloration, a* values, b* values, deoxymyoglobin percentages, and metmyoglobin percentages (p < 0.05). There were also gas-type main effects for cooked color and TBARS (p < 0.05). Carbon monoxide maintained the most redness and least discoloration throughout the display period, while HI-OX started with a bright red color but rapidly browned (p < 0.05). Nitric oxide started as dark red to tannish-red but transitioned to a dull red (p < 0.05). However, NO had increased redness and a* values for internal cooked color (p < 0.05). Although CO outperformed NO packages, NO exhibited a unique color cycle warranting further research to optimize its use.
Assessing Starch Retrogradation from the Perspective of Particle Order
Authors: Lu Hao , Zhan Jinling , Shen Wangyang , Ma Rongrong , Tian Yaoqi
Published: March 2024

Starch retrogradation is a complex process involving changes in the multi-scale structure. In particular, the particle order of retrograded starch is unclear. In this study, we measured the radius of gyration (Rg) and radius of particles (R) of retrograded starch using small-angle X-ray scattering. Retrograded starch included various Rg, and the values of Rg depended on the length and state of the starch chains. With time, the standard deviations of R decreased due to the increase in particle uniformity. Based on these results, a new method for assessing the degree of starch retrogradation was established from the perspective of the particle order. The accuracy of the new method was verified through differential scanning calorimetry and scanning electron microscopy. The microstructures of the samples indicated that the retrograded starch granules contained substructures (primary particles) of different sizes. This study provides a new perspective for analyzing the structure of retrograded starch.
Assessment of Hygiene Management Practices and Comparative Analysis of Regulatory Frameworks for Shared Kitchens across Different Countries
Authors: Na Yu Jin , Baek Jin Young , Gwon So Young , Yoon Ki Sun
Published: March 2024

Shared kitchens, where users share kitchen space, are becoming popular worldwide due to the economic cost savings of startup businesses. This study conducted monitoring of microbial and chemical hazards from prepared foods and the environment of shared kitchen facilities, surveyed shared kitchen operators, and compared shared kitchen regulations between Korea and other countries. The monitoring results indicate that the hygiene status of the facilities and the microbial and chemical hazards in the prepared foods were all within the standard specifications, showing significantly lower levels compared to regular restaurants (p < 0.05). In particular, concurrent-use and time-division types of open shared kitchens showed significantly lower levels of both hazards than separated-individual kitchens. Survey results of hygiene inspection also confirmed better hygiene management in concurrent-use and time-division types of open shared kitchens in Korea. However, more frequent cleaning and disinfection, hygiene inspections, and training are high economic burdens in the operation of shared kitchens compared to regular restaurants. Moreover, mandatory insurance subscriptions, the operator’s responsibility in hygiene-related incidents, and high operational costs collectively challenge shared kitchens’ competitiveness in the food service market. Critical reassessments of regulations utilizing the benefits of shared kitchens are needed to promote a safe dining culture and the growth of shared kitchen startup businesses.
Fractional Fuzzy Neural System: Fractional Differential-Based Compensation Prediction for Reputation Infringement Cases
Authors: Zhang Ni , Zhu Wu-Yang , Jin Peng , Huang Guo , Pu Yi-Fei
Published: March 2024

With the rise of social media and the internet, the rapid dissemination of information has increased the likelihood of reputation infringement. This study utilizes judicial big data and AI to analyze intrinsic connections in reputation infringement cases, aiding judges in delivering consistent rulings. The challenge lies in balancing freedom of speech with the right to reputation and addressing the ambiguity and subjectivity in infringement cases. This research constructs a structured reputation infringement case dataset from Chinese Judgments Online. It introduces a Fractional Fuzzy Neural System (FFNS) to tackle the vagueness in reputation infringement acts and judicial language, enhancing prediction accuracy for case outcomes. The FFNS, integrating fractional calculus, fuzzy logic, and neural networks, excels in adaptability and nonlinear modeling. It uses fractional order fuzzy membership functions to depict the extent and severity of reputation infringement accurately, combining these outputs with neural networks for predictive analysis. The result is a more precise adjudication tool, demonstrating significant potential for judicial application.
Fabrication and Characterization of Quad-Component Bioinspired Hydrogels to Model Elevated Fibrin Levels in Central Nervous Tissue Scaffolds
Authors: Diaz-Lasprilla Ana M. , McKee Meagan , Jimenez-Vergara Andrea C. , Ravi Swathisri , Bellamy Devon , Ortega Wendy , Crosby Cody O. , Steele Jennifer , Plascencia-Villa Germán , Perry George , Munoz-Pinto Dany J.
Published: March 2024

Multicomponent interpenetrating polymer network (mIPN) hydrogels are promising tissue-engineering scaffolds that could closely resemble key characteristics of native tissues. The mechanical and biochemical properties of mIPNs can be finely controlled to mimic key features of target cellular microenvironments, regulating cell-matrix interactions. In this work, we fabricated hydrogels made of collagen type I (Col I), fibrin, hyaluronic acid (HA), and poly (ethylene glycol) diacrylate (PEGDA) using a network-by-network fabrication approach. With these mIPNs, we aimed to develop a biomaterial platform that supports the in vitro culture of human astrocytes and potentially serves to assess the effects of the abnormal deposition of fibrin in cortex tissue and simulate key aspects in the progression of neuroinflammation typically found in human pathologies such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and tissue trauma. Our resulting hydrogels closely resembled the complex modulus of AD human brain cortex tissue (~7.35 kPa), promoting cell spreading while allowing for the modulation of fibrin and hyaluronic acid levels. The individual networks and their microarchitecture were evaluated using confocal laser scanning microscopy (CLSM) and scanning electron microscopy (SEM). Human astrocytes were encapsulated in mIPNs, and negligible cytotoxicity was observed 24 h after the cell encapsulation.