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13 pages, 2802 KiB

Open AccessArticle

Potentially Pathogenic Free-Living Amoebae Isolated from Soil Samples from Warsaw Parks and Squares

by Edyta Beata Hendiger-Rizo, Magdalena Chmielewska-Jeznach, Katarzyna Poreda, Aitor Rizo Liendo, Anna Koryszewska-Bagińska, Gabriela Olędzka and Marcin Padzik

Pathogens 2024, 13(10), 895; https://doi.org/10.3390/pathogens13100895 (registering DOI) - 12 Oct 2024

Abstract

Free-living amoebae (FLA) are prevalent in diverse environments, representing various genera and species with different pathogenicity. FLA-induced infections, such as the highly fatal amoebic encephalitis, with a mortality rate of 99%, primarily affect immunocompromised individuals while others such as Acanthamoeba keratitis (AK) and [...] Read more.

Free-living amoebae (FLA) are prevalent in diverse environments, representing various genera and species with different pathogenicity. FLA-induced infections, such as the highly fatal amoebic encephalitis, with a mortality rate of 99%, primarily affect immunocompromised individuals while others such as Acanthamoeba keratitis (AK) and cutaneous amebiasis may affect immunocompetent individuals. Despite the prevalence of FLA, there is a lack of standardized guidelines for their detection near human habitats. To date, no studies on the isolation and identification of FLA in environmental soil samples in Warsaw have been published. The aim of this study was to determine the presence of amoebae in soil samples collected from Warsaw parks and squares frequented by humans. The isolated protozoa were genotyped. Additionally, their pathogenic potential was determined through thermophilicity tests. A total of 23 soil samples were seeded on non-nutrient agar plates (NNA) at 26 °C and monitored daily for FLA presence. From the total of 23 samples, 18 were positive for FLA growth in NNA and PCR (78.2%). Acanthamoeba spp. was the most frequently isolated genus, with a total of 13 positive samples (13/18; 72.2%), and the T4 genotype being the most common. Moreover, Platyamoeba placida (3/18; 16.7%), Stenamoeba berchidia (1/18; 5.6%) and Allovahlkampfia sp. (1/18; 5.6%), also potentially pathogenic amoebae, were isolated. To our knowledge, this is the first report of FLA presence and characterization in the Warsaw area. Full article

(This article belongs to the Special Issue Opportunistic and Rare Parasitic Infections)

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19 pages, 985 KiB

Open AccessArticle

On the Energy Behaviors of the Bellman–Ford and Dijkstra Algorithms: A Detailed Empirical Study

by Othman Alamoudi and Muhammad Al-Hashimi

J. Sens. Actuator Netw. 2024, 13(5), 67; https://doi.org/10.3390/jsan13050067 (registering DOI) - 12 Oct 2024

Abstract

The Single-Source Shortest Paths (SSSP) graph problem is a fundamental computation. This study attempted to characterize concretely the energy behaviors of the two primary methods to solve it, the Bellman–Ford and Dijkstra algorithms. The very different interactions of the algorithms with the hardware [...] Read more.

The Single-Source Shortest Paths (SSSP) graph problem is a fundamental computation. This study attempted to characterize concretely the energy behaviors of the two primary methods to solve it, the Bellman–Ford and Dijkstra algorithms. The very different interactions of the algorithms with the hardware may have significant implications for energy. The study was motivated by the multidisciplinary nature of the problem. Gaining better insights should help vital applications in many domains. The work used reliable embedded sensors in an HPC-class CPU to collect empirical data for a wide range of sizes for two graph cases: complete as an upper-bound case and moderately dense. The findings confirmed that Dijkstra’s algorithm is drastically more energy efficient, as expected from its decisive time complexity advantage. In terms of power draw, however, Bellman–Ford had an advantage for sizes that fit in the upper parts of the memory hierarchy (up to 2.36 W on average), with a region of near parity in both power draw and total energy budgets. This result correlated with the interaction of lighter logic and graph footprint in memory with the Level 2 cache. It should be significant for applications that rely on solving a lot of small instances since Bellman–Ford is more general and is easier to implement. It also suggests implications for the design and parallelization of the algorithms when efficiency in power draw is in mind. Full article

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18 pages, 614 KiB

Open AccessReview

An Evaluation on the Potential of Large Language Models for Use in Trauma Triage

by Kelvin Le, Jiahang Chen, Deon Mai and Khang Duy Ricky Le

Emerg. Care Med. 2024, 1(4), 350-367; https://doi.org/10.3390/ecm1040035 (registering DOI) - 12 Oct 2024

Abstract

Large Language Models (LLMs) are becoming increasingly adopted in various industries worldwide. In particular, there is emerging research assessing the reliability of LLMs, such as ChatGPT, in performing triaging decisions in emergent settings. A unique aspect of emergency triaging is the process of [...] Read more.

Large Language Models (LLMs) are becoming increasingly adopted in various industries worldwide. In particular, there is emerging research assessing the reliability of LLMs, such as ChatGPT, in performing triaging decisions in emergent settings. A unique aspect of emergency triaging is the process of trauma triaging. This process requires judicious consideration of mechanism of injury, severity of injury, patient stability, logistics of location and type of transport in order to ensure trauma patients have access to appropriate and timely trauma care. Current issues of overtriage and undertriage highlight the potential for the use of LLMs as a complementary tool to assist in more accurate triaging of the trauma patient. Despite this, there remains a gap in the literature surrounding the utility of LLMs in the trauma triaging process. This narrative review explores the current evidence for the potential for implementation of LLMs in trauma triaging. Overall, the literature highlights multifaceted applications of LLMs, especially in emergency trauma settings, albeit with clear limitations and ethical considerations, such as artificial hallucinations, biased outputs and data privacy issues. There remains room for more rigorous research into refining the consistency and capabilities of LLMs, ensuring their effective integration in real-world trauma triaging to improve patient outcomes and resource utilisation. Full article

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11 pages, 888 KiB

Open AccessArticle

The Effect of Extreme Alkalemia upon Presentation to the Emergency Department on Patient Outcomes

by Ivan Gur, Amichai Gutgold, Gai Milo and Asaf Miller

J. Clin. Med. 2024, 13(20), 6077; https://doi.org/10.3390/jcm13206077 (registering DOI) - 12 Oct 2024

Abstract

Background/Objectives: The prognostic significance of alkalemia found in an initial emergency department (ED) evaluation has not been described thus far. Methods: We retrospectively reviewed the records of all patients aged 18 years or older evaluated in the ED of one large academic referral [...] Read more.

Background/Objectives: The prognostic significance of alkalemia found in an initial emergency department (ED) evaluation has not been described thus far. Methods: We retrospectively reviewed the records of all patients aged 18 years or older evaluated in the ED of one large academic referral center during 2000–2023. Included patients were those with at least one measurement of pH ≥ 7.55 upon initial ED presentation. Alkalemia was deemed primarily metabolic (PM) if PCO₂ was ≥35 mmHg and primarily respiratory (PR) if bicarbonate levels were ≤24 mEq/L. The primary outcome was survival 30 days from ED presentation. Results: Of 2440 patients included, 199 (8.1%) had PM and 1494 (61.2%) had PR. Alkalemia severity was not correlated with prognosis. Survival at 30 days was significantly (p < 0.001) lower in the PM group (78.9%) compared with that of either the PR (95.3%) or the combined etiology (92.2%) groups. Multivariate survival analysis after balancing potential observed confounders using propensity score matching revealed the type of alkalemia (PM vs. PR) to be a significant predictor of 30-day mortality (aHR 1.73; 95% C.I. = [1.07 to 2.82]; p = 0.026), irrespective of age, other laboratory values obtained on ED evaluation (including pH), past medical history, or vital signs on presentation. Conclusions: In patients presenting to the ED with significant alkalemia, the mechanism of alkalemia, i.e., primarily metabolic versus primarily respiratory, rather than the absolute degree of alkalemia, is associated with increased mortality. Full article

(This article belongs to the Section Emergency Medicine)

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27 pages, 12606 KiB

Open AccessArticle

Dynamic Wireless Charging of Electric Vehicles Using PV Units in Highways

by Tamer F. Megahed, Diaa-Eldin A. Mansour, Donart Nayebare, Mohamed F. Kotb, Ahmed Fares, Ibrahim A. Hameed and Haitham El-Hussieny

World Electr. Veh. J. 2024, 15(10), 463; https://doi.org/10.3390/wevj15100463 (registering DOI) - 12 Oct 2024

Abstract

Transitioning from petrol or gas vehicles to electric vehicles (EVs) poses significant challenges in reducing emissions, lowering operational costs, and improving energy storage. Wireless charging EVs offer promising solutions to wired charging limitations such as restricted travel range and lengthy charging times. This [...] Read more.

Transitioning from petrol or gas vehicles to electric vehicles (EVs) poses significant challenges in reducing emissions, lowering operational costs, and improving energy storage. Wireless charging EVs offer promising solutions to wired charging limitations such as restricted travel range and lengthy charging times. This paper presents a comprehensive approach to address the challenges of wireless power transfer (WPT) for EVs by optimizing coupling frequency and coil design to enhance efficiency while minimizing electromagnetic interference (EMI) and heat generation. A novel coil design and adaptive hardware are proposed to improve power transfer efficiency (PTE) by defining the optimal magnetic resonant coupling WPT and mitigating coil misalignment, which is considered a significant barrier to the widespread adoption of WPT for EVs. A new methodology for designing and arranging roadside lanes and facilities for dynamic wireless charging (DWC) of EVs is introduced. This includes the optimization of transmitter coils (TCs), receiving coils (RCs), compensation circuits, and high-frequency inverters/converters using the partial differential equation toolbox (pdetool). The integration of wireless charging systems with smart grid technology is explored to enhance energy distribution and reduce peak load issues. The paper proposes a DWC system with multiple segmented transmitters integrated with adaptive renewable photovoltaic (PV) units and a battery system using the utility main grid as a backup. The design process includes the determination of the required PV array capacity, station battery sizing, and inverters/converters to ensure maximum power point tracking (MPPT). To validate the proposed system, it was tested in two scenarios: charging a single EV at different speeds and simultaneously charging two EVs over a 1 km stretch with a 50 kW system, achieving a total range of 500 km. Experimental validation was performed through real-time simulation and hardware tests using an OPAL-RT platform, demonstrating a power transfer efficiency of 90.7%, thus confirming the scalability and feasibility of the system for future EV infrastructure. Full article

(This article belongs to the Special Issue Wireless Power Transfer Technology for Electric Vehicles)

20 pages, 352 KiB

Open AccessReview

Advances in Finite Element Modeling of Fatigue Crack Propagation

by Abdulnaser M. Alshoaibi and Yahya Ali Fageehi

Appl. Sci. 2024, 14(20), 9297; https://doi.org/10.3390/app14209297 (registering DOI) - 12 Oct 2024

Abstract

Fatigue crack propagation is a critical phenomenon that affects the structural integrity and lifetime of various engineering components. Over the years, finite element modeling (FEM) has emerged as a powerful tool for studying fatigue crack propagation and predicting crack growth behavior. This study [...] Read more.

Fatigue crack propagation is a critical phenomenon that affects the structural integrity and lifetime of various engineering components. Over the years, finite element modeling (FEM) has emerged as a powerful tool for studying fatigue crack propagation and predicting crack growth behavior. This study offers a thorough overview of recent advancements in finite element modeling (FEM) of fatigue crack propagation. It highlights cutting-edge techniques, methodologies, and developments, focusing on their strengths and limitations. Key topics include crack initiation and propagation modeling, the fundamentals of finite element modeling, and advanced techniques specifically for fatigue crack propagation. This study discusses the latest developments in FEM, including the Extended Finite Element Method, Cohesive Zone Modeling, Virtual Crack Closure Technique, Adaptive Mesh Refinement, Dual Boundary Element Method, Phase Field Modeling, Multi-Scale Modeling, Probabilistic Approaches, and Moving Mesh Techniques. Challenges in FEM are also addressed, such as computational complexity, material characterization, meshing issues, and model validation. Additionally, the article underscores the successful application of FEM in various industries, including aerospace, automotive, civil engineering, and biomechanics. Full article

(This article belongs to the Special Issue Recent Advances in Fatigue and Fracture of Engineering Materials)

19 pages, 517 KiB

Open AccessArticle

“This Is Me” an Awareness-Raising and Anti-Stigma Program for Undergraduate Nursing Students: A Pre-Post Intervention Study

by Olga Valentim, Tânia Correia, Lídia Moutinho, Paulo Seabra, Ana Querido and Carlos Laranjeira

Nurs. Rep. 2024, 14(4), 2956-2974; https://doi.org/10.3390/nursrep14040216 (registering DOI) - 12 Oct 2024

Abstract

Background: Stigma education for nursing students has focused solely on stigma reduction, with studies showing temporary improvements in attitudes. However, nursing education research should also emphasize the importance of critical reflection and self-reflection to enhance attitudes, beliefs, topic comprehension, and learning satisfaction. This [...] Read more.

Background: Stigma education for nursing students has focused solely on stigma reduction, with studies showing temporary improvements in attitudes. However, nursing education research should also emphasize the importance of critical reflection and self-reflection to enhance attitudes, beliefs, topic comprehension, and learning satisfaction. This study aimed to evaluate the effectiveness of the “This is me” intervention regarding knowledge, attitudes, and communication skills of senior undergraduate nursing students in responding to mental illness-related stigma. Methods: This study employed a psychoeducational intervention for reducing mental illness stigma, using a questionnaire survey to assess pre- and post-intervention effects, with 37 eligible nursing students undergoing clinical training in psychiatric services between 16 May and 15 July 2022. Instruments included sociodemographic and health questions, the MICA-4 scale to evaluate students’ attitudes toward mental illness, the MAKS to measure mental health knowledge, the Empathy Scale (JSPE-S), the Intergroup Anxiety Scale (SS-12), and the Attribution Questionnaire (AQ-27). Results: Most students were female (73.0%) and single (70.3%), with a mean age of around 29 years. After implementing the psychoeducational program, there was a statistically significant increase in overall stigma-related knowledge (MAKS: Z = −1.99, p < 0.05), a decrease in intergroup anxiety (IAS: Z = −3.42, p < 0.05), and reductions in the perceptions of patients as dangerous (AQ27—Dangerousness: Z = −2.399, p < 0.05) and fear (AQ27—Fear: Z = −2.415, p < 0.05). Additionally, there was an improvement in empathy, specifically in Perspective Taking (JSPE: Z = −2.555, p < 0.05). Conclusions: This program may contribute to mental health literacy related to stigma, positively impacting therapeutic relationships and communication with people with mental illness and resulting in more effective care practices. Full article

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16 pages, 6694 KiB

Open AccessArticle

Metal–Polymer Joining by Additive Manufacturing: Effect of Printing Parameters and Interlocking Design

by Teresa Abreu, Rui M. Leal, Carlos Leitão and Ivan Galvão

J. Manuf. Mater. Process. 2024, 8(5), 228; https://doi.org/10.3390/jmmp8050228 (registering DOI) - 12 Oct 2024

Abstract

Additive manufacturing has a strong potential to produce sound metal–polymer joints using controlled polymer deposition on a metallic substrate. In this way, this study aimed to explore the morphological and mechanical properties of metal–polymer joints produced through material-extrusion-based AM using a pin-based macro-mechanical [...] Read more.

Additive manufacturing has a strong potential to produce sound metal–polymer joints using controlled polymer deposition on a metallic substrate. In this way, this study aimed to explore the morphological and mechanical properties of metal–polymer joints produced through material-extrusion-based AM using a pin-based macro-mechanical interlocking mechanism. Joints were fabricated with polylactic acid deposited onto a heated aluminium alloy substrate to form the connection. The optimisation process was focused on improving the printing parameters and pin geometries to reduce voids and enhance joint integrity. The results indicate that optimised samples exhibit superior mechanical resistance, achieving a maximum load improvement with an overall strength increase of 368.97% compared to non-optimised joints. A combined pin geometry (50% cylindrical, 50% conical) was found to be the most effective. Morphological analysis confirmed uniform polymer deposition, ensuring reliable joint performance. These findings underscore the critical role of geometric optimisation in enhancing the strength and durability of metal–polymer joints in AM applications. Full article

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21 pages, 1550 KiB

Open AccessArticle

Using 3D Hand Pose Data in Recognizing Human–Object Interaction and User Identification for Extended Reality Systems

by Danish Hamid, Muhammad Ehatisham Ul Haq, Amanullah Yasin, Fiza Murtaza and Muhammad Awais Azam

Information 2024, 15(10), 629; https://doi.org/10.3390/info15100629 (registering DOI) - 12 Oct 2024

Abstract

Object detection and action/gesture recognition have become imperative in security and surveillance fields, finding extensive applications in everyday life. Advancement in such technologies will help in furthering cybersecurity and extended reality systems through the accurate identification of users and their interactions, which plays [...] Read more.

Object detection and action/gesture recognition have become imperative in security and surveillance fields, finding extensive applications in everyday life. Advancement in such technologies will help in furthering cybersecurity and extended reality systems through the accurate identification of users and their interactions, which plays a pivotal role in the security management of an entity and providing an immersive experience. Essentially, it enables the identification of human–object interaction to track actions and behaviors along with user identification. Yet, it is performed by traditional camera-based methods with high difficulties and challenges since occlusion, different camera viewpoints, and background noise lead to significant appearance variation. Deep learning techniques also demand large and labeled datasets and a large amount of computational power. In this paper, a novel approach to the recognition of human–object interactions and the identification of interacting users is proposed, based on three-dimensional hand pose data from an egocentric camera view. A multistage approach that integrates object detection with interaction recognition and user identification using the data from hand joints and vertices is proposed. Our approach uses a statistical attribute-based model for feature extraction and representation. The proposed technique is tested on the HOI4D dataset using the XGBoost classifier, achieving an average F1-score of 81% for human–object interaction and an average F1-score of 80% for user identification, hence proving to be effective. This technique is mostly targeted for extended reality systems, as proper interaction recognition and users identification are the keys to keeping systems secure and personalized. Its relevance extends into cybersecurity, augmented reality, virtual reality, and human–robot interactions, offering a potent solution for security enhancement along with enhancing interactivity in such systems. Full article

(This article belongs to the Special Issue Extended Reality and Cybersecurity)

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30 pages, 1907 KiB

Open AccessReview

Molecular Signaling Pathways and MicroRNAs in Bone Remodeling: A Narrative Review

by Monica Singh, Puneetpal Singh, Baani Singh, Kirti Sharma, Nitin Kumar, Deepinder Singh and Sarabjit Mastana

Diseases 2024, 12(10), 252; https://doi.org/10.3390/diseases12100252 (registering DOI) - 12 Oct 2024

Abstract

Bone remodeling is an intricate process executed throughout one’s whole life via the cross-talk of several cellular events, progenitor cells and signaling pathways. It is an imperative mechanism for regaining bone loss, recovering damaged tissue and repairing fractures. To achieve this, molecular signaling [...] Read more.

Bone remodeling is an intricate process executed throughout one’s whole life via the cross-talk of several cellular events, progenitor cells and signaling pathways. It is an imperative mechanism for regaining bone loss, recovering damaged tissue and repairing fractures. To achieve this, molecular signaling pathways play a central role in regulating pathological and causal mechanisms in different diseases. Similarly, microRNAs (miRNAs) have shown promising results in disease management by mediating mRNA targeted gene expression and post-transcriptional gene function. However, the role and relevance of these miRNAs in signaling processes, which regulate the delicate balance between bone formation and bone resorption, are unclear. This review aims to summarize current knowledge of bone remodeling from two perspectives: firstly, we outline the modus operandi of five major molecular signaling pathways, i.e.,the receptor activator of nuclear factor kappa-B (RANK)-osteoprotegrin (OPG) and RANK ligand (RANK-OPG-RANKL), macrophage colony-stimulating factor (M-CSF), Wnt/β-catenin, Jagged/Notch and bone morphogenetic protein (BMP) pathways in regards to bone cell formation and function; and secondly, the miRNAs that participate in these pathways are introduced. Probing the miRNA-mediated regulation of these pathways may help in preparing the foundation for developing targeted strategies in bone remodeling, repair and regeneration. Full article

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17 pages, 2804 KiB

Open AccessArticle

Quantitation of Copper Tripeptide in Cosmetics via Fabric Phase Sorptive Extraction Combined with Zwitterionic Hydrophilic Interaction Liquid Chromatography and UV/Vis Detection

by Pantelitsa Pingou, Anthi Parla, Abuzar Kabir, Kenneth G. Furton, Victoria Samanidou, Spyridon Papageorgiou, Efthimios Tsirivas, Athanasia Varvaresou and Irene Panderi

Separations 2024, 11(10), 293; https://doi.org/10.3390/separations11100293 (registering DOI) - 12 Oct 2024

Abstract

The increasing demand for effective cosmetics has driven the development of innovative analytical techniques to ensure product quality. This work presents the development and validation of a zwitterionic hydrophilic interaction liquid chromatography method, coupled with ultraviolet detection, for the quantification of copper tripeptide [...] Read more.

The increasing demand for effective cosmetics has driven the development of innovative analytical techniques to ensure product quality. This work presents the development and validation of a zwitterionic hydrophilic interaction liquid chromatography method, coupled with ultraviolet detection, for the quantification of copper tripeptide in cosmetics. A novel protocol for sample preparation was developed using fabric phase sorptive extraction to extract the targeted analyte from the complex cosmetic cream matrix, followed by chromatographic separation on a ZIC^®-pHILIC analytical column. A thorough investigation of the chromatographic behavior of the copper tripeptide on the HILIC column was performed during method development. The mobile phase consisted of 133 mM ammonium formate (pH 9, adjusted with ammonium hydroxide) and acetonitrile at a 40:60 (v/v) ratio, with a flow rate of 0.2 mL/min. A design of experiments (DOE) approach allowed precise adjustments to various factors influencing the extraction process, leading to the optimization of the fabric phase sorptive extraction protocol for copper tripeptide analysis. The method demonstrated excellent linearity over a concentration range of 0.002 to 0.005% w/w for copper tripeptide, with a correlation coefficient exceeding 0.998. The limits of detection and quantitation were 5.3 × 10⁻⁴% w/w and 2.0 × 10⁻³% w/w, respectively. The selectivity of the method was verified through successful separation of copper tripeptide from other cream components within 10 min, establishing its suitability for high-throughput quality control of cosmetic formulations. Full article

(This article belongs to the Special Issue Analysis and Bioanalysis of Pharmaceuticals: Sample Preparation and Chromatography)

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16 pages, 4416 KiB

Open AccessArticle

Quantitative Evaluation of Soil Erosion in Loess Hilly Area of Western Henan Based on Sampling Approach

by Zhijia Gu, Keke Ji, Qiang Yi, Shaomin Cao, Panying Li and Detai Feng

Water 2024, 16(20), 2895; https://doi.org/10.3390/w16202895 (registering DOI) - 12 Oct 2024

Abstract

The terrain in the loess hilly area of western Henan is fragmented, with steep slopes and weak soil erosion resistance. The substantial soil erosion in this region results in plenty of problems, including decreased soil productivity and ecological degradation. These problems significantly hinder [...] Read more.

The terrain in the loess hilly area of western Henan is fragmented, with steep slopes and weak soil erosion resistance. The substantial soil erosion in this region results in plenty of problems, including decreased soil productivity and ecological degradation. These problems significantly hinder the social and economic development in the region. Soil conservation planning and ecological development require accurate soil erosion surveys. However, the studies of spatio-temporal patterns, evolution, and the driving force of soil erosion in this region are insufficient. Therefore, based on a multi-stage, unequal probability, systematic area sampling method and field investigation, the soil erosion of the loess hilly area of western Henan was quantitatively evaluated by the Chinese Soil Loss Equation (CSLE) in 2022. The impact forces of soil erosion were analyzed by means of a geographic detector and multiple linear regression analysis, and the key driving factors of the spatio-temporal evolution of soil erosion in this region were revealed. The results were as follows. (1) The average soil erosion rate of the loess hilly area in western Henan in 2022 was 5.94 t⋅ha⁻¹⋅a⁻¹, with a percentage of soil erosion area of 29.10%. (2) High soil erosion rates mainly appeared in the west of Shangjie, Xingyang, and Jiyuan, which are related to the development of production and construction projects in these areas. The areas with a high percentage of soil erosion area were in the north (Xinan and Yima), west (Lushi), and southeast (Songxian and Ruyang) of the study area. Moreover, areas with the most erosion were found in forest land, cultivated land, and areas with a slope above 25°. (3) At the landscape level, the number and density of patches of all land types, except orchard land, increased significantly, and the boundary perimeter, landscape pattern segmentation, and degree of fragmentation increased. (4) The geographical detector and multiple linear regression analysis indicated that the driving forces of soil erosion are mainly topographic and climatic (slope length, elevation, precipitation, and temperature). Soil erosion was significantly influenced by the density of landscape patches. These maps and factors influencing soil erosion can serve as valuable sources of information for regional soil conservation plans and ecological environment improvements. Full article

(This article belongs to the Special Issue Soil Erosion and Soil and Water Conservation)

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43 pages, 1980 KiB

Open AccessReview

A Bibliometric Analysis Exploring the Acceptance of Virtual Reality among Older Adults: A Review

by Pei-Gang Wang, Nazlena Mohamad Ali and Mahidur R. Sarker

Computers 2024, 13(10), 262; https://doi.org/10.3390/computers13100262 (registering DOI) - 12 Oct 2024

Abstract

In recent years, there has been a widespread integration of virtual reality (VR) technology across various sectors including healthcare, education, and entertainment, marking a significant rise in its societal importance. However, with the ongoing trend of population ageing, understanding the elderly’s acceptance of [...] Read more.

In recent years, there has been a widespread integration of virtual reality (VR) technology across various sectors including healthcare, education, and entertainment, marking a significant rise in its societal importance. However, with the ongoing trend of population ageing, understanding the elderly’s acceptance of such new technologies has become a focal point in both academic and industrial discourse. Despite the attention it garners, there exists a gap in understanding the attitudes of older adults towards VR adoption, along with evident needs and barriers within this demographic. Hence, gaining an in-depth comprehension of the factors influencing the acceptance of VR technology among older adults becomes imperative to enhance its utility and efficacy within this group. This study employs renowned databases such as WoS and Scopus to scrutinize and analyze the utilization of VR among the elderly population. Utilizing VOSviewer software (version 1.6.20), statistical analysis is conducted on the pertinent literature to delve into research lacunae, obstacles, and recommendations in this domain. The findings unveil a notable surge in literature studies concerning VR usage among older adults, particularly evident since 2019. This study documents significant journals, authors, citations, countries, and research domains contributing to this area. Furthermore, it highlights pertinent issues and challenges surrounding the adoption of VR by older users, aiming to identify prevailing constraints, research voids, and future technological trajectories. Simultaneously, this study furnishes guidelines and suggestions tailored towards enhancing VR acceptance among the elderly, thereby fostering a more inclusive technological milieu. Ultimately, this research aspires to establish an encompassing technological ecosystem empowering older adults to harness VR technology for enriched engagement, learning, and social interactions. Full article

(This article belongs to the Special Issue Xtended or Mixed Reality (AR+VR) for Education 2024)

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12 pages, 2249 KiB

Open AccessArticle

Combining Activated Carbon Adsorption and CO₂ Carbonation to Treat Fly Ash Washing Wastewater and Recover High-Purity Calcium Carbonate

by Weifang Chen, Yifan Chen, Yegui Wang and Na Zhao

Water 2024, 16(20), 2896; https://doi.org/10.3390/w16202896 (registering DOI) - 12 Oct 2024

Abstract

Fly ash washing wastewater was carbonated with carbon dioxide (CO₂) to remove calcium (Ca) by forming a calcium carbonate (CaCO₃) precipitate. An investigation of the factors affecting carbonation showed that Ca removal was highly dependent on the initial pH [...] Read more.

Fly ash washing wastewater was carbonated with carbon dioxide (CO₂) to remove calcium (Ca) by forming a calcium carbonate (CaCO₃) precipitate. An investigation of the factors affecting carbonation showed that Ca removal was highly dependent on the initial pH of the wastewater. The Ca removal was 10%, 61%, 91% and more than 99% at initial wastewater pH levels of 11.8, 12.0, 12.5 and 13.0, respectively. The optimal conditions for carbonation were initial pH of 13.0, carbonation time of 30 min and CO₂ flow rate of 30 mL/min. The Ca concentration in the wastewater decreased to <40 mg/L, while 73 g of CaCO₃ precipitate was produced per liter of wastewater. However, heavy metals, specifically Pb and Zn, co-precipitated during carbonation, which resulted in a CaCO₃ product that contained as much as 0.61 wt% of Pb and 0.02 wt% of Zn. Activated carbon modified by a quaternary ammonium salt was used to selectively adsorb the Pb and Zn first. The Pb- and Zn-free water was then carbonated. By combining adsorption with carbonation, the Ca concentration in the treated wastewater was decreased to about 28 mg/L, while the Na, Cl and K were retained. The wastewater thus treated was ready for NaCl and KCl recovery. In addition, the precipitate had a Ca content of more than 38 wt% and almost no heavy metals. The average particle size of the precipitate was 47 μm, with a uniform cubic shape. The quality of the precipitate met the requirements for the industrial reuse of CaCO₃. In summary, adsorption and carbonation combined were able to remove pollutants from wastewater while recovering useful resources. Full article

(This article belongs to the Section Wastewater Treatment and Reuse)

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14 pages, 2519 KiB

Open AccessCommunication

Alternative Splicing of the Last TKFC Intron Yields Transcripts Differentially Expressed in Human Tissues That Code In Vitro for a Protein Devoid of Triokinase and FMN Cyclase Activity

by María Jesús Costas, Ana Couto, Alicia Cabezas, Rosa María Pinto, João Meireles Ribeiro and José Carlos Cameselle

Biomolecules 2024, 14(10), 1288; https://doi.org/10.3390/biom14101288 (registering DOI) - 12 Oct 2024

Abstract

The 18-exon human TKFC gene codes for dual-activity triokinase and FMN cyclase (TKFC) in an ORF, spanning from exon 2 to exon 18. In addition to TKFC-coding transcripts (classified as tkfc type by their intron-17 splice), databases contain evidence for alternative TKFC transcripts, [...] Read more.

The 18-exon human TKFC gene codes for dual-activity triokinase and FMN cyclase (TKFC) in an ORF, spanning from exon 2 to exon 18. In addition to TKFC-coding transcripts (classified as tkfc type by their intron-17 splice), databases contain evidence for alternative TKFC transcripts, but none of them has been expressed, studied, and reported in the literature. A novel full-ORF transcript was cloned from brain cDNA and sequenced (accession no. DQ344550). It results from an alternative 3′ splice-site in intron 17. The cloned cDNA contains an ORF also spanning from exon 2 to exon 18 of the TKFC gene but with a 56-nt insertion between exons 17 and 18 (classified as tkfc_ins56 type). This insertion introduces an in-frame stop, and the resulting ORF codes for a shorter TKFC variant, which, after expression, is enzymatically inactive. TKFC intron-17 splicing was found to be differentially expressed in human tissues. In a multiple-tissue northern blot using oligonucleotide probes, the liver showed a strong expression of the tkfc-like splice of intron 17, and the heart preferentially expressed the tkfc_ins56-like splice. Through a comparison to global expression data from massive-expression studies of human tissues, it was inferred that the intestine preferentially expresses TKFC transcripts that contain neither of those splices. An analysis of transcript levels quantified by RNA-Seq in the GTEX database revealed an exception to this picture due to the occurrence of a non-coding short transcript with a tkfc-like splice. Altogether, the results support the occurrence of potentially relevant transcript variants of the TKFC gene, differentially expressed in human tissues. (This work is dedicated in memoriam to Professor Antonio Sillero, 1938–2024, for his lifelong mentoring and his pioneering work on triokinase). Full article

(This article belongs to the Special Issue Unraveling the Complexity of the Human Spliceosome and RNA Splicing)

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21 pages, 3236 KiB

Open AccessArticle

Model Optimization and Application of Straw Mulch Quantity Using Remote Sensing

by Yuanyuan Liu, Yu Sun, Yueyong Wang, Jun Wang, Xuebing Gao, Libin Wang and Mengqi Liu

Agronomy 2024, 14(10), 2352; https://doi.org/10.3390/agronomy14102352 (registering DOI) - 12 Oct 2024

Abstract

Straw mulch quantity is an important indicator in the detection of straw returned to the field in conservation tillage, but there is a lack of large-scale automated measurement methods. In this study, we estimated global straw mulch quantity and completed the detection of [...] Read more.

Straw mulch quantity is an important indicator in the detection of straw returned to the field in conservation tillage, but there is a lack of large-scale automated measurement methods. In this study, we estimated global straw mulch quantity and completed the detection of straw returned to the field. We used an unmanned aerial vehicle (UAV) carrying a multispectral camera to acquire remote sensing images of straw in the field. First, the spectral index was selected using the Elastic-net (ENET) algorithm. Then, we used the Genetic Algorithm Hybrid Particle Swarm Optimization (GA-HPSO) algorithm, which embeds crossover and mutation operators from the Genetic Algorithm (GA) into the improved Particle Swarm Optimization (PSO) algorithm to solve the problem of machine learning model prediction performance being greatly affected by parameters. Finally, we used the Monte Carlo method to achieve a global estimation of straw mulch quantity and complete the rapid detection of field plots. The results indicate that the inversion model optimized using the GA-HPSO algorithm performed the best, with the coefficient of determination (R²) reaching 0.75 and the root mean square error (RMSE) only being 0.044. At the same time, the Monte Carlo estimation method achieved an average accuracy of 88.69% for the estimation of global straw mulch quantity, which was effective and applicable in the detection of global mulch quantity. This study provides a scientific reference for the detection of straw mulch quantity in conservation tillage and also provides a reliable model inversion estimation method for the estimation of straw mulch quantity in other crops. Full article

(This article belongs to the Special Issue Imaging Technology for Detecting Crops and Agricultural Products—3rd Edition)

15 pages, 3752 KiB

Open AccessArticle

Camellia oleifera Tree Detection and Counting Based on UAV RGB Image and YOLOv8

by Renxu Yang, Debao Yuan, Maochen Zhao, Zhao Zhao, Liuya Zhang, Yuqing Fan, Guangyu Liang and Yifei Zhou

Agriculture 2024, 14(10), 1789; https://doi.org/10.3390/agriculture14101789 (registering DOI) - 12 Oct 2024

Abstract

The detection and counting of Camellia oleifera trees are important parts of the yield estimation of Camellia oleifera. The ability to identify and count Camellia oleifera trees quickly has always been important in the context of research on the yield estimation of [...] Read more.

The detection and counting of Camellia oleifera trees are important parts of the yield estimation of Camellia oleifera. The ability to identify and count Camellia oleifera trees quickly has always been important in the context of research on the yield estimation of Camellia oleifera. Because of their specific growing environment, it is a difficult task to identify and count Camellia oleifera trees with high efficiency. In this paper, based on a UAV RGB image, three different types of datasets, i.e., a DOM dataset, an original image dataset, and a cropped original image dataset, were designed. Combined with the YOLOv8 model, the detection and counting of Camellia oleifera trees were carried out. By comparing YOLOv9 and YOLOv10 in four evaluation indexes, including precision, recall, mAP, and F1 score, Camellia oleifera trees in two areas were selected for prediction and compared with the real values. The experimental results show that the cropped original image dataset was better for the recognition and counting of Camellia oleifera, and the mAP values were 8% and 11% higher than those of the DOM dataset and the original image dataset, respectively. Compared to YOLOv5, YOLOv7, YOLOv9, and YOLOv10, YOLOv8 performed better in terms of the accuracy and recall rate, and the mAP improved by 3–8%, reaching 0.82. Regression analysis was performed on the predicted and measured values, and the average R² reached 0.94. This research shows that a UAV RGB image combined with YOLOv8 provides an effective solution for the detection and counting of Camellia oleifera trees, which is of great significance for Camellia oleifera yield estimation and orchard management. Full article

(This article belongs to the Section Digital Agriculture)

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27 pages, 946 KiB

Open AccessArticle

AI-Generated Spam Review Detection Framework with Deep Learning Algorithms and Natural Language Processing

by Mudasir Ahmad Wani, Mohammed ElAffendi and Kashish Ara Shakil

Computers 2024, 13(10), 264; https://doi.org/10.3390/computers13100264 (registering DOI) - 12 Oct 2024

Abstract

Spam reviews pose a significant challenge to the integrity of online platforms, misleading consumers and undermining the credibility of genuine feedback. This paper introduces an innovative AI-generated spam review detection framework that leverages Deep Learning algorithms and Natural Language Processing (NLP) techniques to [...] Read more.

Spam reviews pose a significant challenge to the integrity of online platforms, misleading consumers and undermining the credibility of genuine feedback. This paper introduces an innovative AI-generated spam review detection framework that leverages Deep Learning algorithms and Natural Language Processing (NLP) techniques to identify and mitigate spam reviews effectively. Our framework utilizes multiple Deep Learning models, including Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, Gated Recurrent Unit (GRU), and Bidirectional LSTM (BiLSTM), to capture intricate patterns in textual data. The system processes and analyzes large volumes of review content to detect deceptive patterns by utilizing advanced NLP and text embedding techniques such as One-Hot Encoding, Word2Vec, and Term Frequency-Inverse Document Frequency (TF-IDF). By combining three embedding techniques with four Deep Learning algorithms, a total of twelve exhaustive experiments were conducted to detect AI-generated spam reviews. The experimental results demonstrate that our approach outperforms the traditional machine learning models, offering a robust solution for ensuring the authenticity of online reviews. Among the models evaluated, those employing Word2Vec embeddings, particularly the BiLSTM_Word2Vec model, exhibited the strongest performance. The BiLSTM model with Word2Vec achieved the highest performance, with an exceptional accuracy of 98.46%, a precision of 0.98, a recall of 0.97, and an F1-score of 0.98, reflecting a near-perfect balance between precision and recall. Its high F2-score (0.9810) and F0.5-score (0.9857) further highlight its effectiveness in accurately detecting AI-generated spam while minimizing false positives, making it the most reliable option for this task. Similarly, the Word2Vec-based LSTM model also performed exceptionally well, with an accuracy of 97.58%, a precision of 0.97, a recall of 0.96, and an F1-score of 0.97. The CNN model with Word2Vec similarly delivered strong results, achieving an accuracy of 97.61%, a precision of 0.97, a recall of 0.96, and an F1-score of 0.97. This study is unique in its focus on detecting spam reviews specifically generated by AI-based tools rather than solely detecting spam reviews or AI-generated text. This research contributes to the field of spam detection by offering a scalable, efficient, and accurate framework that can be integrated into various online platforms, enhancing user trust and the decision-making processes. Full article

(This article belongs to the Special Issue When Natural Language Processing Meets Machine Learning—Opportunities, Challenges and Solutions)

26 pages, 5695 KiB

Open AccessArticle

Polyurethanes Synthesized with Blends of Polyester and Polycarbonate Polyols—New Evidence Supporting the Dynamic Non-Covalent Exchange Mechanism of Intrinsic Self-Healing at 20 °C

by Yuliet Paez-Amieva, Noemí Mateo-Oliveras and José Miguel Martín-Martínez

Polymers 2024, 16(20), 2881; https://doi.org/10.3390/polym16202881 (registering DOI) - 12 Oct 2024

Abstract

Polyurethanes (PUs) synthesized with blends of polycarbonate and polyester polyols (CD+PEs) showed intrinsic self-healing at 20 °C. The decrease in the polycarbonate soft segments content increased the self-healing time and reduced the kinetics of self-healing of the PUs. The percentage of C-O species [...] Read more.

Polyurethanes (PUs) synthesized with blends of polycarbonate and polyester polyols (CD+PEs) showed intrinsic self-healing at 20 °C. The decrease in the polycarbonate soft segments content increased the self-healing time and reduced the kinetics of self-healing of the PUs. The percentage of C-O species decreased and the ones of C-N and C=O species increased by increasing the polyester soft segments in the PUs, due to higher micro-phase separation. All PUs synthetized with CD+PE blends exhibited free carbonate species and interactions between the polycarbonate and polyester soft segments to a somewhat similar extent in all PUs. By increasing the polyester soft segments content, the storage moduli of the PUs decreased and the tan delta values increased, which resulted in favored polycarbonate soft segments interactions, and this was related to slower kinetics of self-healing at 20 °C. Although the PU made with a mixture of 20 wt.% CD and 80 wt.% PE showed cold crystallization and important crystallinity of the soft segments, as well as high storage moduli, the intercalation of a small amount of polycarbonate soft segments disturbed the interactions between the polyester soft segments, so it exhibited self-healing at 20 °C. The self-healing of the PUs was attributed to the physical interactions between polycarbonate soft segments themselves and with polyester soft segments, and, to a minor extent, to the mobility of the polymeric chains. Finally, the PUs made with 40 wt.% or more polyester polyol showed acceptable mechanical properties. Full article

(This article belongs to the Special Issue Advances in Polyurethane and Composites)

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14 pages, 5623 KiB

Open AccessArticle

Ultrasonic Guided Wave Health Monitoring of High-Temperature Aircraft Structures Based on Variational Mode Decomposition and Fuzzy Entropy

by Feiting Zhang, Kaifu Zhang, Hui Cheng, Dongyue Gao and Keyi Cai

Actuators 2024, 13(10), 411; https://doi.org/10.3390/act13100411 (registering DOI) - 12 Oct 2024

Abstract

This paper presents an innovative approach to high-temperature health monitoring of aircraft structures utilizing an ultrasonic guided wave transmission and reception system integrated with a zirconia heat buffer layer. Aiming to address the challenges posed by environmental thermal noise and the installation of [...] Read more.

This paper presents an innovative approach to high-temperature health monitoring of aircraft structures utilizing an ultrasonic guided wave transmission and reception system integrated with a zirconia heat buffer layer. Aiming to address the challenges posed by environmental thermal noise and the installation of heat buffers, which can introduce structural nonlinearities into guided wave signals, a composite guided wave consisting of longitudinal and Lamb waves was proposed for online damage detection within thermal protection systems. To effectively analyze these complex signals, a hybrid damage monitoring technique combining variational mode decomposition (VMD) and fuzzy entropy (FEN) was introduced. The VMD was employed to isolate the principal components of the guided wave signals, while the fuzzy entropy of these components served as a quantitative damage factor, characterizing the extent of the structural damage. Furthermore, this study validated the feasibility of piezoelectric probes equipped with heat buffer layers for both exciting and receiving ultrasonic guided wave signals in a dual heat buffer layer, a one-transmit-one-receive configuration. The experimental results demonstrated the efficacy of the proposed VMD-FEN damage factor for real-time monitoring of damage in aircraft thermal protection systems, both at ambient and elevated temperatures (up to 150 °C), showcasing its potential for enhancing the safety and reliability of aerospace structures operating under extreme thermal conditions. Full article

(This article belongs to the Section Aircraft Actuators)

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26 pages, 4212 KiB

Open AccessArticle

Texture-Image-Oriented Coverless Data Hiding Based on Two-Dimensional Fractional Brownian Motion

by Yen-Ching Chang, Jui-Chuan Liu, Ching-Chun Chang and Chin-Chen Chang

Electronics 2024, 13(20), 4013; https://doi.org/10.3390/electronics13204013 (registering DOI) - 12 Oct 2024

Abstract

In an AI-immersing age, scholars look for new possibilities of employing AI technology to their fields, and how to strengthen security and protect privacy is no exception. In a coverless data hiding domain, the embedding capacity of an image generally depends on the [...] Read more.

In an AI-immersing age, scholars look for new possibilities of employing AI technology to their fields, and how to strengthen security and protect privacy is no exception. In a coverless data hiding domain, the embedding capacity of an image generally depends on the size of a chosen database. Therefore, choosing a suitable database is a critical issue in coverless data hiding. A novel coverless data hiding approach is proposed by applying deep learning models to generate texture-like cover images or code images. These code images are then used to construct steganographic images to transmit covert messages. Effective mapping tables between code images in the database and hash sequences are established during the process. The cover images generated by a two-dimensional fractional Brownian motion (2D FBM) are simply called fractional Brownian images (FBIs). The only parameter, the Hurst exponent, of the 2D FBM determines the patterns of these cover images, and the seeds of a random number generator determine the various appearances of a pattern. Through the 2D FBM, we can easily generate as many FBIs of multifarious sizes, patterns, and appearances as possible whenever and wherever. In the paper, a deep learning model is treated as a secret key selecting qualified FBIs as code images to encode corresponding hash sequences. Both different seeds and different deep learning models can pick out diverse qualified FBIs. The proposed coverless data hiding scheme is effective when the amount of secret data is limited. The experimental results show that our proposed approach is more reliable, efficient, and of higher embedding capacity, compared to other coverless data hiding methods. Full article

(This article belongs to the Special Issue Novel Methods Applied to Security and Privacy Problems in Future Networking Technologies)

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16 pages, 2486 KiB

Open AccessArticle

Targeting KDM1A in Neuroblastoma with NCL-1 Induces a Less Aggressive Phenotype and Suppresses Angiogenesis

by Annika Sprüssel, Takayoshi Suzuki, Naoki Miyata, Kathy Astrahantseff, Annabell Szymansky, Joern Toedling, Theresa M. Thole-Kliesch, Annika Ballagee, Marco Lodrini, Annette Künkele, Matthias Truss, Lukas C. Heukamp, Susanne Mathia, Falk Hertwig, Christian Rosenberger, Angelika Eggert, Hedwig E. Deubzer and Johannes H. Schulte

J. Clin. Med. 2024, 13(20), 6081; https://doi.org/10.3390/jcm13206081 (registering DOI) - 12 Oct 2024

Abstract

Background: The KDM1A histone demethylase regulates the cellular balance between proliferation and differentiation, and is often deregulated in human cancers including the childhood tumor neuroblastoma. We previously showed that KDM1A is strongly expressed in undifferentiated neuroblastomas and correlates with poor patient prognosis, suggesting [...] Read more.

Background: The KDM1A histone demethylase regulates the cellular balance between proliferation and differentiation, and is often deregulated in human cancers including the childhood tumor neuroblastoma. We previously showed that KDM1A is strongly expressed in undifferentiated neuroblastomas and correlates with poor patient prognosis, suggesting a possible clinical benefit from targeting KDM1A. Methods: Here, we tested the efficacy of NCL-1, a small molecule specifically inhibiting KDM1A in preclinical models for neuroblastoma. Results: NCL-1 mimicked the effects of siRNA-mediated KDM1A knockdown and effectively inhibited KDM1A activity in four neuroblastoma cell lines and a patient-representative cell model. KDM1A inhibition shifted the aggressive tumor cell phenotypes towards less aggressive phenotypes. The proliferation and cell viability was reduced, accompanied by the induction of markers of neuronal differentiation. Interventional NCL-1 treatment of nude mice harboring established neuroblastoma xenograft tumors reduced tumor growth and inhibited cell proliferation. Reduced vessel density and defects in blood vessel construction also resulted, and NCL-1 inhibited the growth and tube formation of HUVEC-C cells in vitro. Conclusions: Inhibiting KDM1A could attack aggressive neuroblastomas two-fold, by re-directing tumor cells toward a less aggressive, slower-growing phenotype and by preventing or reducing the vascular support of large tumors. Full article

(This article belongs to the Special Issue High-Risk Neuroblastoma: New Clinical Insights and Challenges)

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15 pages, 1795 KiB

Open AccessArticle

Enhancing Sewage Sludge Stabilization, Pathogen Removal, and Biomass Production through Indigenous Microalgae Promoting Growth: A Sustainable Approach for Sewage Sludge Treatment

by Hajer Ben Hamed, Antoine Debuigne, Hetty Kleinjan, Dominique Toye and Angélique Léonard

Recycling 2024, 9(5), 97; https://doi.org/10.3390/recycling9050097 (registering DOI) - 12 Oct 2024

Abstract

Sewage sludge (SS), a byproduct of wastewater treatment plants, poses significant environmental and health risks if not properly handled. Conventional approaches for SS stabilization often involve costly and energy-consuming processes. This study investigated the effect of promoting native microalgae growth in SS on [...] Read more.

Sewage sludge (SS), a byproduct of wastewater treatment plants, poses significant environmental and health risks if not properly handled. Conventional approaches for SS stabilization often involve costly and energy-consuming processes. This study investigated the effect of promoting native microalgae growth in SS on its stabilization, pathogen bacteria removal, and valuable biomass production. The effect on settleability, filterability, and extracellular polymeric substances (EPSs) was examined as well. Experiments were conducted in photobioreactors (PBRs) without O₂ supply and CO₂ release under controlled parameters. The results show a significant improvement in SS stabilization, with a reduction of volatile solids (VSs) by 47.55%. Additionally, fecal coliforms and E. coli were efficiently removed by 2.25 log and 6.72 log, respectively. Moreover, Salmonella spp. was not detected after 15 days of treatment. The settleability was improved by 71.42%. However, a worsening of the sludge filterability properties was observed, likely due to a decrease in floc size following the reduction of protein content in the tightly bound EPS fraction. Microalgae biomass production was 16.56 mg/L/day, with a mean biomass of 0.35 g/L at the end of the batch treatment, representing 10.35% of the total final biomass. These findings suggest that promoting native microalgal growth in SS could be sustainable and cost-effective for SS stabilization, microalgal biomass production, and the enhancement of sludge-settling characteristics, notwithstanding potential filtration-related considerations. Full article

(This article belongs to the Topic Sustainable Recycling and Reuse of Industrial By-Products or Waste from Geo-Resource Exploitation)

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40 pages, 467 KiB

Open AccessArticle

Decision Analysis Algorithm Using Frank Aggregation in the SWARA Framework with ^p,qRung Orthopair Fuzzy Information

by Jawad Ali, Suhad Ali Osman Abdallah and N. S. Abd EL-Gawaad

Symmetry 2024, 16(10), 1352; https://doi.org/10.3390/sym16101352 (registering DOI) - 12 Oct 2024

Abstract

The present study introduces an innovative approach to multi-criteria decision making (MCDM) aimed at handling decision analysis involving

^{p, q}

rung orthopair fuzzy (

^{p, q}

ROF) data, where the criteria weights are completely unknown. To achieve this objective, we formulate [...] Read more.

The present study introduces an innovative approach to multi-criteria decision making (MCDM) aimed at handling decision analysis involving

^{p, q}

rung orthopair fuzzy (

^{p, q}

ROF) data, where the criteria weights are completely unknown. To achieve this objective, we formulate generalized operational rules referred to as Frank operational rules, tailored for

^{p, q}

ROF numbers (

^{p, q}

ROFNs) utilizing the Frank t-norm and t-conorm. With these newly devised operations as a foundation, we create a variety of

^{p, q}

ROF aggregation operators (AOs) to effectively aggregate

^{p, q}

ROF information. Furthermore, we examine specific instances of these operators and rigorously establish their desirable properties, including idempotency, monotonicity, boundedness, and symmetry. Subsequently, we adapt the SWARA technique to the realm of

^{p, q}

ROF fuzzy data and this adapted technique becomes instrumental in determining criteria weights within the proposed MCDM framework centered around proposed AOs. We furnish a descriptive example to exemplify the practicality of the developed approach. Lastly, the effectiveness and soundness of our approach are underscored through both parameter analysis and a comparative evaluation. Full article

(This article belongs to the Section Engineering and Materials)

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