bluuebunny/crossref_metadata_2025 huggingface dataset:
Revocable and Traceable Undeniable Attribute-Based Encryption in Cloud-Enabled E-Health Systems
Authors: He Zhongxiang , Chen Yuling , Luo Yun , Zhang Lingyun , Tang Yingying
Published: December 2023

The emerging cloud storage technology has significantly improved efficiency and productivity in the traditional electronic healthcare field. However, it has also brought about many security concerns. Ciphertext policy attribute-based encryption (CP-ABE) holds immense potential in achieving fine-grained access control, providing robust security for electronic healthcare data in the cloud. However, current CP-ABE schemes still face issues such as inflexible attribute revocation, relatively lower computational capabilities, and key management. To address these issues, this paper introduces a revocable and traceable undeniable ciphertext policy attribute-based encryption scheme (MA-RUABE). MA-RUABE not only enables fast and accurate data traceability, effectively preventing malicious user key leakage, but also includes a direct revocation feature, significantly enhancing computational efficiency. Furthermore, the introduction of a multi-permission mechanism resolves the issue of centralization of power caused by single-attribute permissions. Furthermore, a security analysis demonstrates that our system ensures resilience against chosen plaintext attacks. Experimental results demonstrate that MA-RUABE incurs lower computational overhead, effectively enhancing system performance and ensuring data-sharing security in cloud-based electronic healthcare systems.
Social Justice in Scottish Education? Revisiting the Question
Authors: Brown Jonathan , Mercieca Duncan
Published: December 2023

Social justice is a key value within Scottish education and is listed as one of four professional values within the General Teaching Council for Scotland’s (GTCS) professional standards. This paper uses the work of Nancy Fraser to question what is meant by social justice within Scottish education. Parallels are drawn between the conception of social justice as presented within the Standard for Registration and the work of Fraser, highlighting the relevance of a professional standard that seeks to orientate professionals towards social justice rather than codify the practice in reference to a single scale on which all matters of justice should be weighed. Following this, the Getting it Right for Every Child policy (GIRFEC) is problematized to demonstrate the dangers of mis-framing. This paper ends by connecting the concept of professional orientation towards justice as indicated within the Standard for Registration to Aristotle’s idea of sensibilities and phronêsis.
Entrepreneurship as a Career Option within Education: A Critical Review of Psychological Constructs
Authors: Kakouris Alexandros , Tampouri Sofia , Kaliris Andronikos , Mastrokoukou Sofia , Georgopoulos Nikolaos
Published: December 2023

Entrepreneurship is now suggested as a competence not only for starting new businesses but for employability and well-being as well. Envisaged as a career option, entrepreneurship is now a new concern in the field of career counseling psychology. Traditionally, entrepreneurship is about starting new businesses or being self-employed, but nowadays, it is also considered a competence for employability and well-being. Systematically nurtured in educational settings for more than two decades, the entrepreneurial intention of students has become a specific construct for educators to assess the impact of entrepreneurial courses. The present article seeks to critically review the psychological constructs, models, and approaches that have been used in educational settings to explain the formation of entrepreneurial intention. The majority of relevant studies has been found to be quantitative, reproducing in a positivist manner the construct of self-efficacy and the theory of reasoned action. Some constructs and approaches that have been extensively used in the career counseling discipline seem to be under-researched in the entrepreneurship education field. In this line of research, the potential contribution of sources on self-efficacy and dysfunctional career beliefs or motives should be examined. Additionally, theoretical paradigms like constructionist-narrative-based career counseling or positive psychology and other newer theories (e.g., happenstance learning theory) might be useful in investigating several influences on career decision making for entrepreneurship. Based on the current findings from the literature, a research agenda is proposed for future research in the field in order to achieve better connections between entrepreneurship and career theories and to shed light on the complex process of students’ entrepreneurial career decisions.
Artificial Intelligence in Higher Education: An Analysis of Existing Bibliometrics
Authors: López-Chila Roberto , Llerena-Izquierdo Joe , Sumba-Nacipucha Nicolás , Cueva-Estrada Jorge
Published: December 2023

Since its origin in the 1950s, artificial intelligence (AI) has evolved from technological to educational applications. AI is emerging as an essential tool in education. Its integration into education promises the personalization and the globalization of learning. Despite its potential, it is crucial to consider its ethical challenges and uses. This bibliometric study sought to understand the current state of AI in higher education in order to provide a basis for future research. A bibliometric analysis was conducted between 2017 and 2023, using the Scopus database. The query was performed on 23 October 2023 and focused on titles, keywords, and abstracts. A total of 870 articles were found, and their metadata were analyzed after removing incorrect data. VOSviewer software was used to visualize the similarities, and the publications were studied by country, authors, and collaborations. A steady growth in AI studies in higher education was found, highlighting areas such as computer science and social sciences. China and the United States led in production and citations. Keywords such as “artificial intelligence”, “chatgpt”, and “machine learning” indicated trends and areas of interest.
Physical Education Teachers’ Representations of Their Training to Promote the Inclusion of Students with Disabilities
Authors: Celestino Tadeu , Ribeiro Esperança , Morgado Elsa Gabriel , Leonido Levi , Pereira Antonino
Published: December 2023

School inclusion is based on the need to adopt and implement a holistic view of education, training, and human development embodied in the idea of everyone, for everyone. In the context of Physical Education (PE), there are still several constraints to the realization of this universal desideratum. Among these, teacher training and qualification for the inclusion of students with Specific Health Needs (SHNs) stands out. That is, students with physical and mental health problems whose impact is significantly manifested in the learning process. Thus, the objective of this study was to identify the representations of PE teachers about their training to develop inclusive processes with students with SES. Participants in this study were 151 PE teachers from different regions and districts of Portugal (Algarve, Aveiro, Castelo Branco, Lisbon, Porto, and Viseu) who had 23.6 ± 8.1 years of teaching service. Teachers answered an online questionnaire, on the Google Forms platform, with open and closed questions about their education and training to develop inclusive processes in PE. The results indicate two significant dimensions: (1) initial training for teaching inclusive PE and (2) continuous training for inclusion. Regarding initial training, a large majority of the teachers under study, at the end of their initial training, did not have the essential skills to teach PE to students with SES. It was also identified that a large majority reported not having had any contact with students with SES throughout their training process for teaching. It was also recognized that this training was not adjusted to the development of intervention skills with students with SHN. Regarding continuous training, it was identified that attendance at this training increased their skills to teach PE to students with SHN. Workshops/actions/training courses are the main training models adopted. However, it is recognized that the training provided does not respond concretely to their training needs to intervene with students with SHN, since teachers essentially seek to improve intervention in the context of inclusive physical education. We conclude that teacher training for inclusion is not yet fully adjusted to the reality of the inclusive school paradigm. In this sense, in practical terms, the following are suggested: (1) the need for reinforcement in study plans with specific and long-term curricular units; (2) the introduction of real practice components in context; and (3) supervised pedagogical practice in diverse contexts.
Transfer of Learning of New Nursing Professionals: Exploring Patterns and the Effect of Previous Work Experience
Authors: Roig-Ester Helena , Robalino Guerra Paulina Elizabeth , Quesada-Pallarès Carla , Gegenfurtner Andreas
Published: December 2023

While numerous studies have focused on the learning transfer of in-company training in past decades, relatively few have explored the transfer of knowledge from university studies to the workplace, particularly in the context of nursing. Moreover, profile variables tend to be used to describe the sample but not to explore its effect on learning transfer. This article explores the effect of previous work experience—in health—on the learning transfer factors model among new nurses during their first year of work. A total of 196 nurses with six months to one year of experience, representing various healthcare services in Catalonia, participated in this study. We administered a 53-item questionnaire based on the Model to Evaluate Transfer in Nursing Professionals. Using cluster analysis, we identified three distinct groups: Cluster #1 (Academically unprepared with low self-competence), Cluster #2 (Academically unprepared but moderately self-competent), and Cluster #3 (Highly academically prepared and highly self-competent). Nurses in Cluster #3 exhibited a higher degree of learning transfer. However, we also found an interaction between previous work experience and learning transfer. To analyse these interactions, we applied non-traditional analysis techniques, including network analysis, which revealed significant differences between the models with and without work experience. This study highlights the importance of exploring transfer beyond the traditional in-company training context and identifies previous work experiences as one of the key variables that needs to be carefully examined.
The Design and Application of a Polarization 3D Imager for Land Object Imaging
Authors: Zhang Yue , Jiao Jianchao , Zhang Xuemin , Liu Yi , Li Xuan , Su Yun
Published: December 2023

Polarization 3D imaging is a passive, monocular, long-distance 3D imaging technology. Compared with traditional 3D imaging methods, it has many advantages, such as its lack of need for a light source, lack of need for image matching, and ability to achieve 3D imaging using only a single image. In this study, the principle of polarization 3D imaging was introduced. In the design process of a polarization 3D imager, the acquisition method for obtaining polarization information, the extinction ratio, the spatial resolution, and the refractive index of objects was introduced in detail. The influence of these key factors on the accuracy of polarization 3D imaging was analyzed. Taking the limitations of a small satellite payload into account, specific indicators such as multi-aperture polarized imaging, a 10,000:1 extinction ratio, and a spatial resolution of 30 m were designed. The implementation and functions of the polarization 3D imager were elaborated upon, and optical systems and polarizing devices were developed. Finally, by utilizing the image data obtained by the polarization 3D imager, polarization 3D imaging of real ground objects was obtained. The accuracy of the polarization 3D imaging inversion was approximately twice the spatial resolution. These research results lay the technical foundations for the development and practical application of polarization 3D imaging technology and instruments.
A Computationally Efficient Method for Increasing Confidentiality in Smart Electricity Networks
Authors: Larijani Ata , Dehghani Farbod
Published: December 2023

Safeguarding the data collected by smart meters is essential because the disclosure of this information may threaten the privacy of the consumer. By obtaining them, hackers can find out the behavior of the person and use that information for malicious purposes. Therefore, the anonymity of such information can prevent the occurrence of risks. Given the paramount significance of user privacy and data integrity, this paper primarily investigates the confidentiality, integrity, and anonymity of messages. This paper aims to develop a platform for determining dynamic pricing to coordinate supply and demand, thereby maximizing the efficiency of facilities. In the previous research, the operation center was not authenticated for the customer in the first step, and they also had a heavy computational cost. But this paper has endeavored to develop an efficient and comprehensive privacy-preserving solution for the smart electricity network. Also, it has tried to cover all the required security objectives by dealing with authenticity, confidentiality, and irrefutability. The method of the research is that two entities mutually authenticate each other and reach a key agreement so that if the operation center wants to send a control command, it can send control commands directly to the meter with less time complexity. The power company sends control commands and requests to the smart meters until the analyzed and collected energy consumption data are transmitted. The data aggregator node gathers the data from the meters. The results showed that the proposed method reduced the computational complexity and communication overhead to a satisfactory level and is also resistant to various attacks.
A Data-Driven Approach to Team Formation in Software Engineering Based on Personality Traits
Authors: Vasiljević Jan , Lavbič Dejan
Published: December 2023

Collaboration among individuals with diverse skills and personalities is crucial to producing high-quality software. The success of any software project depends on the team’s cohesive functionality and mutual complementation. This study introduces a data-centric methodology for forming Software Engineering (SE) teams centred around personality traits. Our study analysed data from an SE course where 157 students in 31 teams worked through four project phases and were evaluated based on deliverables and instructor feedback. Using the Five-Factor Model (FFM) and a variety of statistical tests, we determined that teams with higher levels of extraversion and conscientiousness, and lower neuroticism, consistently performed better. We examined team members’ interactions and developed a predictive model using extreme gradient boosting. The model achieved a 74% accuracy rate in predicting inter-member satisfaction rankings. Through graphical explainability, the model underscored incompatibilities among members, notably those with differing levels of extraversion. Based on our findings, we introduce a team formation algorithm using Simulated Annealing (SA) built upon the insights derived from our predictive model and additional heuristics.
Identification of Critical Nodes in Power Grid Based on Improved PageRank Algorithm and Power Flow Transfer Entropy
Authors: Zeng Jinhui , Wu Yisong , Liu Jie , He Dong , Lan Zheng
Published: December 2023

Identifying critical nodes in the power grid is a crucial aspect of power system security and stability analysis. However, the current methods for identification fall short in fully accounting for the power transfer characteristics between nodes and the consequences of node removal on the security and stability of power grid operation. To enhance the effective and accurate identification of critical nodes in the power grid, a method is proposed. This method is based on improved PageRank algorithm and node-weighted power flow transfer entropy, referred to as IPRA-PFTE. Firstly, based on the power flow and equivalent impedance between nodes, and the introduction of virtual nodes, an improved PageRank algorithm is obtained. Then the node-weighted power flow transfer entropy is derived by considering the uniformity of the transfer power flow distribution in the system following the removal of a node. Finally, the importance of nodes is obtained by combining the improved PageRank algorithm with the node-weighted power flow transfer entropy. The method’s effectiveness and accuracy are validated through simulation using the IEEE 39-bus example and subsequent comparison with existing methods.
Integrating Sensor Systems and Signal Processing for Sustainable Production: Analysis of Cutting Tool Condition
Authors: Kozłowski Edward , Antosz Katarzyna , Sęp Jarosław , Prucnal Sławomir
Published: December 2023

This research focuses on the crucial role of monitoring tool conditions in milling to improve workpiece quality, increase production efficiency, and reduce costs and environmental impact. The goal was to develop predictive models for detecting tool condition changes. Data from a sensor-equipped research setup were used for signal analysis during different machining stages. The study applied logistic regression and a gradient boosting classifier for material layer identification, with the latter achieving an impressive 97.46% accuracy. Additionally, the effectiveness of the classifiers was further confirmed through the analysis of ROC (Receiver Operating Characteristic) curves and AUC (Area Under the Curve) values, demonstrating their high quality and precise identification capabilities. These findings support the classifiers’ utility in predicting the condition of cutting tools, potentially reducing raw material consumption and environmental impact, thus promoting sustainable production practices.
The Role of the Energy Sector in Contributing to Sustainability Development Goals: A Text Mining Analysis of Literature
Authors: Carvalho Luísa , Santos Márcia R. C.
Published: December 2023

This text mining study delves into the multifaceted contributions of the energy sector to Sustainable Development Goals (SDGs). By analyzing 363 papers, we uncover key themes, trends, and challenges shaping the intersection of energy and sustainability. The findings reveal that the energy sector plays a pivotal role in achieving SDGs such as affordable and clean energy (SDG 7) and climate action (SDG 13). Critical issues encompass governance, policy frameworks, and technological innovations. This research underscores the need for interdisciplinary collaboration and holistic approaches in addressing complex energy-related sustainability challenges. The insights derived here provide guidance to policymakers, researchers, and stakeholders seeking to harness the energy sector’s potential for a more sustainable and equitable future.
Storage Sites for Carbon Dioxide in the North Sea and Their Particular Characteristics
Authors: Rigby Sean P. , Alsayah Ali
Published: December 2023

This paper reviews and evaluates work on the structural complexity of the potential carbon dioxide storage sites in the North Sea, including the nature of the reservoir structures, the reservoir rocks, the presence of inter-layers, faults, and fractures, and how these factors influence carbon dioxide capacity. In particular, the review emphasises the significance of studying caprocks in detail, not just the reservoir rock’s carbon dioxide storage capacity. This work also particularly considers reservoir simulation work on North Sea sites and illustrates the importance of using fully coupled flow–geomechanical–geochemical modelling to ensure that complex feedback and synergistic effects are not missed. It includes comparisons with other sites where relevant. It also discusses recent challenges and controversies that have arisen from simulations of sequestration in North Sea reservoirs and the need for comprehensive field data to resolve these issues.
Application of Fuzzy Neural Networks in Combustion Process Diagnostics
Authors: Grądz Żaklin , Wójcik Waldemar , Gromaszek Konrad , Kotyra Andrzej , Smailova Saule , Iskakova Aigul , Yeraliyeva Bakhyt , Kumargazhanova Saule , Imanbek Baglan
Published: December 2023

Coal remains one of the key raw materials used in the energy industry to generate electricity and heat. As a result, diagnostics of the combustion process is still an important topic of scientific research. Correct implementation of the process allows the emission of pollutants into the atmosphere to be kept at a compliant level. Therefore, it is important to conduct the process in a manner that will not exceed these standards. A preliminary analysis of the measurement signals was carried out, and signal predictions of flame intensity changes were determined using the autoregressive moving average (ARMA) model. Different fuzzy neural network architectures have been investigated. Binary and multi-class classifications of flame states were conducted. The best results were obtained from the ANFIS_grid partition model, producing an accuracy of 95.46% for binary classification and 79.08% for multi-class classification. The accuracy of the recognition of flame states and the high convergence of the determined predictions with measurement signals validate the application of the proposed approach in diagnosing or controlling the combustion process of pulverized coal and its mixtures with biomass. Expert decisions determine the range of acceptable states.
The Potential of Green Hydrogen and Power-to-X Utilization in Jordanian Industries: Opportunities and Future Prospects
Authors: Muhsen Hani , Al-Mahmodi Mohammed , Tarawneh Rashed , Alkhraibat Asma , Al-Halhouli Ala’aldeen
Published: December 2023

Green hydrogen and power-to-X technologies hold significant potential in the global energy transition towards net-zero emissions. This is attributed to the premise that these technologies can decarbonize numerous sectors worldwide by providing versatile and sustainable energy carriers and industrial feedstocks to replace fossil-based fuels and chemicals. To this end, the qualitative benefits of green hydrogen and power-to-X technologies have been thoroughly examined for various applications in past years. In contrast, quantifying the potential penetration of such technologies on national and global levels still requires extensive research. Therefore, this paper investigates the prospective integration of green hydrogen and power-to-X technologies within Jordanian industries, considering their quantitative utilization potential for current and future capacities. The findings showed that the Jordanian food processing and heavy industries emerged as major sectors with substantial potential for incorporating green hydrogen and power-to-X products as alternative fuels or chemical feedstocks. In detail, the total potential utilization capacity for these sectors stood at around 57 thousand tons per year. Specifically, fertilizers production, cement industry, steel reforming, and oil refinery possess an annual potential capacity of around 6.8, 11.8, 12.7, and 25.8 thousand tons, respectively. It is also worth mentioning that the current utilization capacity of hydrogen in Jordanian industries was found to be around 8.9 thousand tons per annum, which is completely covered by fossil-based hydrogen to date. These results imply that there will be a promising market for green hydrogen and power-to-X utilization in Jordanian industries, which will play a significant role in integrated energy transition efforts in the future.
The Colourimetric Method for Mixing Time Measurement in Single-Use and Multi-Use Bioreactors—Methodology Overview and Practical Recommendations
Authors: Bartczak Mateusz , Pilarek Maciej
Published: December 2023

Mixing time is an important parameter for quantifying the mixing efficiency of a bioreactor system, essential for successful bioprocess development in various branches of the bioengineering sector (e.g., biopharma, biorefineries, food industry and bioreactor design). The colourimetric method is one of the ways of obtaining valuable quantitative data about the mixing process and the liquid flow inside a vessel. This review consists of a catalogue and a discussion of previously published data in which the colourimetric method has been utilised; a critical comparison between the colourimetric and other mixing time measurement methods; an explanation of practical considerations regarding the bioreactor setup and the choice of reagents; a practical guide for requirements for the acquisition of high-quality images of the mixing process; a thorough discussion of aspects connected to the computer image processing of the video material. This review is intended to thoroughly present the versatility of the colourimetric method for mixing time measurement in miscellaneous bioreactor systems, i.e., in classical tanks and modern single-use (disposable) plastic film-based bag-like containers, and to facilitate the implementation of the colourimetric method in new research setups by providing complete and valuable recommendations about each step of the methodology.
Review of Energy-Related Machine Learning Applications in Drying Processes
Authors: Đaković Damir , Kljajić Miroslav , Milivojević Nikola , Doder Đorđije , Anđelković Aleksandar S.
Published: December 2023

Drying processes are among the most energy-intensive industrial processes. There is a need for development of the efficient methods needed for estimating, measuring, and reducing energy use. Different machine learning algorithms might provide some of the answers to these issues in a faster and less costly way, without the need for time-consuming and expensive experiments done at different scales of the dryers. The aim of this paper was to provide a comprehensive overview of machine learning applications for addressing energy-related challenges by exploration of different energy types and energy reduction opportunities. Also, the analysis of the applied algorithms, their specific applications and a critical evaluation of the obtained results are provided. The paper is based on the necessity of the improvements in energy use needed for drying related on the existing data. The overview of the ways for such achievements, and a general classification of machine learning algorithm are the background of the paper. The methods used are the machine learning techniques employed in different energy-related issues for drying processes. The paper focuses on the applications of artificial neural networks and other machine learning algorithms and models for different energy-related issues, including different energy types applications, challenges associated with energy consumption, and opportunities for energy reduction. Not only the applied algorithms, but also their specific applications, and the statistical analysis of the obtained results are also overviewed. Finally, a critical evaluation of the findings highlighting the potentials of machine learning algorithms in addressing energy-related challenges (such as estimation of energy consumption, opportunities for energy reduction, and use of different energy sources) is provided. The presented analysis underscored the effectiveness of machine learning applications for these purposes.
Wind Turbine Geometrical and Operation Variables Reconstruction from Blade Acceleration Measurements
Authors: Pimenta Francisco , Moutinho Carlos , Magalhães Filipe
Published: December 2023

To develop reliable numerical models and better interpret monitoring campaigns experimental data of wind turbines, knowing the structure operation conditions, in particular the rotor angular velocity and blades’ pitch angle, is of paramount importance, but often not known due to confidentiality restrictions, or known with low time resolution (typically 10 min average values). In this work, it is shown analytically that blades accelerations measurements contain valuable information that allow for a better characterisation of the effective rotor shaft tilt and blades cone angle for different operating conditions. It is also shown that these measurements can be used to reconstruct the time history of the rotor angular velocity and blades’ pitch angle. After presented in an analytical framework, the methodology is validated with experimental data of two full scale wind turbines. The successful reconstruction of the rotor operating conditions shows that the method presented can be used to provide further insight into the dynamics of the structure that aids monitoring data analysis and provides an alternative method to monitor the SCADA systems themselves. The paper combines quite unique experimental data collected at two operating rotors with original data processing strategies that provide very valuable information to researchers and wind turbine operators.
Current Collapse Phenomena Investigation in Automotive-Grade Power GaN Transistors
Authors: Basile Alfio , Scrimizzi Filippo , Rizzo Santi Agatino
Published: December 2023

This work analyzes the impact of working conditions on the current collapse (CC) phenomenon for an automotive GaN device. For this purpose, some sensing circuits have been compared to find the most suitable for the considered GaN family. Simulations of the testing schematic have been performed, a prototype board has been created, and some measurements have been taken. Finally, the work has investigated the effect on the CC of the input voltage, current level, switching frequency, and duty cycle. The key outcome is that the temperature increment mitigates the CC phenomenon, which implies that the on-state resistance worsening (dynamic/static ratio), which is due to the CC, reduces with increasing temperature. Therefore, the typical increment of the dynamic on-resistance (RDSON) with increasing temperature is ascribable to the increment of the static one with temperature, while it is not at all an exacerbation of the current collapse phenomenon.
The Preparation and Performance of Bamboo Waste Bio-Oil Phenolic Resin Adhesives for Bamboo Scrimber
Authors: Li Chunmiao , Ren Xueyong , Han Shanyu , Li Yongxia , Chen Fuming
Published: December 2023

Bamboo is a fast-growing plant with properties such as low cost, abundant resources, and good carbon sequestration effect. However, the swift growth of bamboo resources generates an immense quantity of processing waste, which is necessary to effectively utilize bamboo processing waste. The leftovers from bamboo processing can be reutilized by fast pyrolysis to prepare renewable bio-oil. In this study, bamboo bio-oil was partially substituted for phenol to synthesize phenolic resin with different substitution rates under the action of an alkaline catalyst, and then to serve as the adhesive to produce bamboo scrimber. Bamboo bundles were impregnated with synthetic bio-oil phenolic resin to create bamboo scrimber, which was subsequently hot-pressed. The research shows that modified phenolic resins with a bio-oil substitution rate of under 30% have good physical and chemical properties, while the free aldehyde content of phenolic resin with 40% bio-oil substitution exceeds the limit value (0.3%) specified in the Chinese National Standard. The thermal stability of phenolic resins was also increased after bio-oil modification, indicated by the movement of the TG curve to higher temperature ranges. It was found that the bamboo scrimber prepared with 20% BPF resin adhesive had the best comprehensive properties of a good mechanical strength, hydrophobicity, and mildew resistance, particularly with an elastic modulus of 9269 MPa and a static bending strength of 143 MPa. The microscopic morphology showed that the BPF resin was well impregnated into the interior of the bamboo bundle and had a compact bonding structure within the bamboo scrimber. The anti-mold performance experiment found that the bio-oil-modified resin increased the anti-mold level of the bamboo scrimber from slightly corrosion-resistant to strong corrosion-resistant. The conclusions obtained from this study have a good reference value for achieving the comprehensive utilization of bamboo, helping to promote the use of all components, reduce the production cost of bamboo scrimber, and improve its mildew resistance performance. This provides new ideas for the development of low-cost mildew resistant bamboo scrimber novel materials.
Analysis of Spatial and Temporal Changes in Vegetation Cover and Driving Forces in the Wuding River Basin, Loess Plateau
Authors: Zhang Hao , He Zhilin , Xu Junkui , Mu Weichen , Chen Yanglong , Wang Guangxia
Published: December 2023

Vegetation cover in the Loess Plateau region is an important component of ecological protection in the Yellow River Basin, and this study provides a scientific reference for further vegetation restoration. Based on Landsat images and related data, we utilized the dimidiate pixel model and Geodetector method to study the vegetation cover in the Wuding River Basin from 2000 to 2022. The results indicated the spatial and temporal distribution of the vegetation cover and its changes over the study period. Additionally, the driving factors influencing its spatial changes were also uncovered. We also propose a land use shift vegetation cover contribution formula to quantify the effect of land type change on the FVC. The study showed that (1) the overall vegetation cover of the watershed increased significantly, and the FVC showed an increasing trend from 2000 to 2013 and a slow decline from 2013 to 2022, with the gradual transformation of low-graded FVC into a higher graded one. (2) The FVC increased spatially from northwest to southeast, and the trend of future changes is mainly decreasing. (3) The strongest explanatory power for the FVC change is the land use type and its interactive combination with rainfall. (4) The conversion of grassland to cropland contributes the most to the vegetation cover at 1.52%, and the increase in the cropland area is more conducive to the increase in the vegetation cover.
Complementarity with Real Forests: A Conceptual Framework and Narrative Review of Multidimensional Effects in Virtual Forests
Authors: Jia Xingxing , Xu Jingcheng , Xu Yucheng , Li Hongyi , Peng Siqi , Zhao Bing
Published: December 2023

Numerous studies have confirmed the positive impacts of real forests in areas such as stress relief. However, not everyone can visit forests easily. Virtual technologies offer new ways of experiencing forests for people who are hindered by real-life conditions and provide researchers with a manageable mode of study. Recently, there has been an influx of relevant research; however, themes within the overall perspective of the field remain unclear. This study aimed to review the literature and provide an overview of the potential health benefits of virtual forests. Research themes were extracted, and a conceptual framework for the multidimensional effects of virtual forest exposure was proposed from a holistic perspective. We analyzed studies using descriptive analytical methods through the Scopus, Web of Science, and PubMed databases and snowball searches. In total, 58 studies were included. This review identified four themes and segments throughout the virtual forest exposure process: core elements, experiences, effects, and circulation. We propose a new conceptual framework for a holistic perspective that incorporates technological features that are specific to virtual environments and makes connections to real forests. Finally, perspectives for future research in virtual forest therapy and its practical implications are discussed.
Resource Indexing and Querying in Large Connected Environments
Authors: Achkouty Fouad , Chbeir Richard , Gallon Laurent , Mansour Elio , Corral Antonio
Published: December 2023

The proliferation of sensor and actuator devices in Internet of things (IoT) networks has garnered significant attention in recent years. However, the increasing number of IoT devices, and the corresponding resources, has introduced various challenges, particularly in indexing and querying. In essence, resource management has become more complex due to the non-uniform distribution of related devices and their limited capacity. Additionally, the diverse demands of users have further complicated resource indexing. This paper proposes a distributed resource indexing and querying algorithm for large connected environments, specifically designed to address the challenges posed by IoT networks. The algorithm considers both the limited device capacity and the non-uniform distribution of devices, acknowledging that devices cannot store information about the entire environment. Furthermore, it places special emphasis on uncovered zones, to reduce the response time of queries related to these areas. Moreover, the algorithm introduces different types of queries, to cater to various user needs, including fast queries and urgent queries suitable for different scenarios. The effectiveness of the proposed approach was evaluated through extensive experiments covering index creation, coverage, and query execution, yielding promising and insightful results.
Acetylcholinesterase- and Butyrylcholinesterase-Based Biosensors for the Detection of Quaternary Ammonium Biocides in Food Industry
Authors: Mouawad Lynn , Istamboulie Georges , Catanante Gaëlle , Noguer Thierry
Published: December 2023

A sensitive and robust electrochemical cholinesterase-based sensor was developed to detect the quaternary ammonium (QAs) biocides most frequently found in agri-food industry wash waters: benzalkonium chloride (BAC) and didecyldimethylammonium chloride (DDAC). To reach the maximum residue limit of 28 nM imposed by the European Union (EU), two types of cholinesterases were tested, acetylcholinesterase (AChE, from Drosophila melanogaster) and butyrylcholinesterase (BChE, from horse serum). The sensors were designed by entrapping AChE or BChE on cobalt phthalocyanine-modified screen-printed carbon electrodes. The limits of detection (LOD) of the resulting biosensors were 38 nM for DDAC and 320 nM for BAC, using, respectively, AChE and BChE. A simple solid-phase extraction step was used to concentrate the samples before biosensor analysis, allowing for the accurate determination of DDAC and BAC in tap water with limits of quantification (LOQ) as low as 2.7 nM and 5.3 nM, respectively. Additional assays demonstrated that the use of a phosphotriesterase enzyme allows for the total removal of interferences due to the possible presence of organophosphate insecticides in the sample. The developed biosensors were shown to be stable during 3 months storage at 4 °C.
Variations in Ecuadorian Cocoa Fermentation and Drying at Two Locations: Implications for Quality and Sensory
Authors: Streule Stefanie , Freimüller Leischtfeld Susette , Galler Martina , Motzer Dominik , Poulose-Züst Monja , Miescher Schwenninger Susanne
Published: December 2023

In Ecuador, various processes are applied during cocoa post-harvesting. This study, therefore, explored fermentation parameters across two locations with 2–7 independent runs, focusing on temperature, microbial counts, pH during fermentation and drying, and their impact on cocoa bean quality. Factors including fermentation devices (jute bags, plastic bags, and wooden boxes), pre-drying, turning during fermentation, fermentation duration, and drying temperature were investigated. Fermenting in plastic bags without pre-drying or turning and fermenting in jute bags for only 40 ± 2.0 h yielded low maximal fermentation temperatures Tmax (31.1 ± 0.4 °C and 37.6 ± 1.8 °C), leading to bitter, astringent, woody, and earthy cocoa liquor. Longer fermentation (63 ± 6 h) in wooden boxes with turning (Wt) and in jute bags with pre-drying and turning (Jpt) achieved the highest Tmax of 46.5 ± 2.0 °C, and a more acidic cocoa liquor, particularly in Wt (both locations) and Jpt (location E). Therefore, it is recommended to ferment for a minimum duration from day 1 to 4 (63 ± 6 h), whether using plastic bags (with mandatory pre-drying) or jute bags (with or without pre-drying or turning). Furthermore, this study underscores the risks associated with excessively high drying temperatures (up to 95.2 ± 13.7 °C) and specific dryer types, which can falsify cut-tests and introduce unwanted burnt-roasted off-flavors in the cocoa liquor.
Optimization and In Vitro Digestion of a Guava (Psidium guajava), Mamey (Pouteria sapota) and Stevia (Stevia rebaudiana) Functional Beverage
Authors: Belmonte-Herrera Beatriz Haydee , Domínguez-Avila J. Abraham , Ayala-Zavala J. Fernando , Valenzuela-Melendres Martín , Tortoledo-Ortiz Orlando , González-Aguilar Gustavo A.
Published: December 2023

Guava and mamey are phenolic- and carotenoid-rich fruits with potential health benefits, but are minimally used as ingredients in functional beverages. The objectives of the present work are to optimize the content of guava and mamey pulps and a stevia solution in the formulation of a functional beverage with high content of bioactive compounds and sensory acceptability using a mixture design analysis, and to analyze its composition after in vitro digestion. The optimized formulation (17.77 and 19.23 g of guava and mamey pulps, respectively; 1% stevia solution) yielded a beverage with 418.21 mg gallic acid equivalents (GAE)/100 mL and 0.20 mg β-carotene/100 mL, and an antioxidant capacity of 213.58, 78.90 and 234.03 mg Trolox equivalents (TE)/100 mL using three methodologies. The mathematical model developed was significant (p < 0.05), according to R2 values between 0.70 and 0.75. α- and β-carotene were quantified during the oral phase of in vitro digestion. Gallic, p-coumaric, ferulic and chlorogenic acids were also identified. The beverage had a general acceptability of 6.72. We conclude that the mathematical model developed was a good predictor of the experimental data and that the optimized beverage contained high bioactive concentrations (phenolics and carotenoids) and was well-accepted by potential consumers.
Insights into the Structure, Metabolism, Biological Functions and Molecular Mechanisms of Sialic Acid: A Review
Authors: Li Dan , Lin Qinlu , Luo Feijun , Wang Hanqing
Published: December 2023

Sialic acid (SA) is a kind of functional monosaccharide which exists widely in edible bird’s nest (EBN), milk, meat, mucous membrane surface, etc. SA is an important functional component in promoting brain development, anti-oxidation, anti-inflammation, anti-virus, anti-tumor and immune regulation. The intestinal mucosa covers the microbial community that has a significant impact on health. In the gut, SA can also regulate gut microbiota and metabolites, participating in different biological functions. The structure, source and physiological functions of SA were reviewed in this paper. The biological functions of SA through regulating key signaling pathways and target genes were discussed. In summary, SA can modulate gut microbiota and metabolites, which affect gene expressions and exert its biological activities. It is helpful to provide scientific reference for the further investigation of SA in the functional foods.
Eigenfemora—Age-at-Death Estimation in the Proximal Femur through an Image Processing Approach
Authors: Navega David , Ferreira Maria Teresa , Curate Francisco
Published: December 2023

Estimating age at death is essential to establish biological profiles from human skeletal remains in both forensic and archeological settings. Imaging studies of skeletal age changes in adults have described the metamorphosis of trabecular bone structure and bone loss in the proximal femur as well as changes in morphology during different stages of life. This study aims to assess the utility of a digital representation of conventional X-ray films of the proximal femur for the estimation of age at death in a sample of 91 adult individuals (47 females and 44 males) of the Coimbra Identified Skeletal Collection. The proposed approach showed a root mean squared error (RMSE) of 17.32 years (and mean absolute error of 13.47 years) for females and an RMSE of 14.06 years (mean absolute error of 11.08 years) for males. The main advantage of this approach is consistency in feature detection and extraction, as X-ray images projected on the femora space will always produce the same set features to be analyzed for age estimation, while more traditional methods rely heavily on operator experience that can lead to inconsistent age estimates among experts.
Bio-Based Aerogels for the Removal of Heavy Metal Ions and Oils from Water: Novel Solutions for Environmental Remediation
Authors: Boccia Antonella Caterina , Neagu Monica , Pulvirenti Alfio
Published: December 2023

Contamination of the aqueous environment caused by the presence of heavy metal ions and oils is a growing concern that must be addressed to reduce their detrimental impact on living organisms and safeguard the environment. Recent efficient and environmentally friendly remediation methods for the treatment of water are based on third-generation bioaerogels as emerging applications for the removal of heavy metal ions and oils from aqueous systems. The peculiarities of these materials are various, considering their high specific surface area and low density, together with a highly porous three-dimensional structure and tunable surface chemistry. This review illustrates the recent progress in aerogels developed from cellulose and chitosan as emerging materials in water treatment. The potential of aerogel-based adsorbents for wastewater treatment is reported in terms of adsorption efficacy and reusability. Despite various gaps affecting the manufacturing and production costs of aerogels that actually limit their successful implementation in the market, the research progress suggests that bio-based aerogels are ready to be used in water-treatment applications in the near future.
Influence of the Oil Structuring System on Lipid Hydrolysis and Bioaccessibility of Healthy Fatty Acids and Curcumin
Authors: Cofrades Susana , Gómez-Estaca Joaquín , Álvarez María Dolores , Garcimartín Alba , Macho-González Adrián , Benedí Juana , Pintado Tatiana
Published: December 2023

Oleogels (OG) and gelled emulsions (GE) were elaborated with a mixture of olive and chia oils (80:20 ratio) without and with the incorporation of the health-related compound curcumin. These were studied to evaluate the influence of the oil structuring system on the lipid hydrolysis and bioaccessibility of three healthy fatty acids (FA) (palmitic, oleic, and α-linolenic acids) and of curcumin, compared to the oil mixture (bulk oil, BO). The oil structuring system influenced the firmness and texture, and the presence of curcumin significantly altered the color parameters. GE showed higher lipid digestibility, with a greater proportion of absorbable fraction (higher content of free FA and monoacylglycerides) than OG, which behaved similarly to BO. The presence of curcumin affected the degree of lipolysis, reducing lipid digestibility in OG and increasing it in GE. As for FA bioaccessibility, although GE presented higher percentages overall, curcumin significantly increased and decreased FA bioaccessibility in OG and GE, respectively. The oil structuring system also influenced the bioaccessibility of curcumin, which was higher in GE. Therefore, when selecting an oil structuring system, their physicochemical properties, the degree of lipid hydrolysis, and the bioaccessibility of both curcumin and the FA studied should all be considered.