bluuebunny/crossref_metadata_2025 huggingface dataset:
Phytochemical Characterization and Biological Activity of Two Anacardiaceae Species from Guinea-Bissau
Authors: Malú Quintino , Malmir Maryam , Infante Caldeira Gonçalo , Encarnação Sofia , Lima Katelene , Catarino Luís , Silva Lima Beatriz , Rocha João , Silva Olga
Published: December 2024

The dried leaves of Lannea velutina A.Rich. and Sorindeia juglandifolia Planch. ex Oliv. are commonly used in traditional medicine throughout West Africa to treat inflammatory diseases. The aim of the present study was to evaluate the anti-inflammatory activity of the standardized hydroethanolic (70%) extracts of these plants and to investigate the underlying mechanisms, with a focus on their antioxidant properties. The anti-inflammatory effects were evaluated using a rat model of induced paw edema, while the antioxidant activity was evaluated by DPPH• radical scavenging and iron-reducing antioxidant power assays. Chemical fingerprint was achieved by LC-UV/DAD-ESI/MS and the main classes of secondary metabolites were quantified by colorimetric analysis. The results showed that Sorindeia juglandifolia extract significantly inhibited the increase in paw edema volume, with the maximum effect observed at doses of 100 and 200 mg/kg (20.51 ± 1.07% and 35.50 ± 6.90%, respectively). For L. velutina, the strongest inhibition was observed at 200 and 400 mg/kg (47.48 ± 11.37% and 35.40 ± 1.70%, respectively). Both extracts also showed remarkable antioxidant activity. Phenol derivatives were identified as the main classes of secondary metabolites, with L. velutina containing 350.1 ± 20.6 mg GAE/g DE and S. juglandifolia containing 463.4 ± 29.4 mg GAE/g DE. Ten phenolic markers were identified in L. velutina and six in S. juglandifolia extracts. The main components of L. velutina include myricetin-3-O-glucuronide, quercetin-3-O-glucuronide, catechin, and gallic acid, while S. juglandifolia contains gallic acid, isoquercitrin, and ethyl gallate. These results confirm the anti-inflammatory potential of L. velutina and S. juglandifolia and highlight their prospects as candidates for the development of standardized anti-inflammatory herbal medicines based on their chemical and biological properties.
Changes in Metabolites Produced in Wheat Plants Against Water-Deficit Stress
Authors: Spanic Valentina , Duvnjak Jurica , Hefer Dubravka , D’Auria John C.
Published: December 2024

Drought stress can adversely affect the seed germination and seedling growth of wheat plants. This study analyzed the effect of drought on seed germination and the morphological parameters of seedlings from ten winter wheat genotypes. The primary focus was to elucidate the effects of two drought intensities on metabolic status in wheat seedlings. The findings suggest that most wheat genotypes exhibited a significant reduction in germination and growth traits under severe drought, while the genotype Srpanjka exhibited less reduction under both drought conditions. Out of 668 metabolic features, 54 were altered under 10% PEG stress and 140 under 20% PEG stress, with 48 commonly shared between these two stress intensities. This study demonstrated that the metabolic response of shoots to 10% PEG stress contrasts with that of 20% PEG stress. Some growth metabolites, such as oxalic acid, sophorose, and turanose, showed the highest positive increase under both stresses, while butanoic acid, tropic acid, glycine, propionic acid, and phosphonoacetic acid decreased. It is suggested that the accumulation of amino acids, such as proline, contributed to the drought tolerance of the plants. Among all organic acids, succinic and aspartic acids particularly increased the plant response to mild and severe drought stress, respectively. Our results suggest that different metabolites in wheat seedlings enhance the potential ability of wheat to cope with drought stress in the early growth stages by activating a rapid and comprehensive tolerance mechanism. This discovery presents a new approach for enhancing wheat tolerance to abiotic stress, including water deficit.
Characterizing Curing Efficiency of EGCG-Encapsulated Halloysite Nanotube Modified Adhesives for Durable Dentin–Resin Interfaces
Authors: Alhijji Saleh , Platt Jeffrey A. , Al-Maflehi Nassr , Alhotan Abdulaziz , Haider Julfikar , Bottino Marco C. , Windsor L. Jack
Published: December 2024

Matrix metalloproteinase (MMP)-induced collagen degradation at the resin-dentin interface remains a significant challenge for maintaining the longevity of dental restorations. This study investigated the effects of epigallocatechin-3-gallate (EGCG), a potent MMP inhibitor, on dental adhesive curing efficiency when encapsulated in halloysite nanotubes (HNTs). EGCG-loaded HNTs were incorporated into a commercial dental adhesive (Adper Scotchbond Multi-Purpose) at 7.5% and 15% w/v concentrations. To isolate the effects of each component, the study included three control groups: unmodified adhesive (negative control), adhesive containing only HNTs, and adhesive containing only EGCG (0.16% and 0.32%, equivalent to the EGCG content in EGCG–HNT groups). Degree of conversion (DC), polymerization conversion (PC), and Vickers micro-hardness (VHN) were assessed to evaluate curing efficiency. The addition of 7.5% EGCG-encapsulated HNTs maintained curing properties similar to the control, showing no significant differences in DC (80.97% vs. 81.15%), PC (86.59% vs. 85.81%), and VHN (23.55 vs. 24.12) (p > 0.05). In contrast, direct incorporation of EGCG at 0.32% significantly decreased DC (73.59%), PC (80.63%), and VHN (20.56) values compared to both control and EGCG–HNT groups (p < 0.05). Notably, HNT encapsulation mitigated these negative effects on polymerization, even at higher EGCG concentrations. These findings demonstrate that EGCG encapsulation in HNTs can maintain the curing efficiency of dental adhesives while potentially preserving the MMP-inhibitory benefits of EGCG.
Effects of Polyol Types on Underwater Curing Properties of Polyurethane
Authors: Zhang Cheng , Zhang Yixuan , Liu Yao , Cui Yiming , Zhao Ming , Peng Shuai , Wang Hecong , Song Zuobao , Zhang Qunchao , Shi Dean , Zhu Yuxue
Published: December 2024

This study aims to develop castable polyurethane suitable for applications on wet substrates or underwater construction. Polyurethanes were synthesized using various polyols with similar hydroxyl values, including poly(tetrahydrofuran) polyol, polyester polyol, castor oil-modified polyol, soybean oil-modified polyol, and cashew nut shell oil-modified polyol. The corresponding polyurethane curing products were evaluated for their underwater curing characteristics by volume expansion ratios and adhesion strength on dry and wet substrates, combined with analyses of reaction exothermic behavior, wetting properties on dry and wet substrates, interfacial tension, and microstructure characterization from the perspectives of reaction activity and water solubility. The results indicate that polyols with higher hydrophobicity and reactivity to isocyanates lead to reduced side reactions during underwater curing, making them more suitable for underwater applications. Soybean oil-based and cashew nut shell oil-based polyurethanes exhibited fast curing (gel times of 1.15 and 1.35 min, respectively), minimal volume change (within 2.5% after 7 days underwater), and strong wet adhesion (1.95 MPa and 2.38 MPa with minimal loss, respectively). The two polyols showed different mechanical properties, providing tailored options for specific underwater engineering applications.
Fertility, Hatchability, and Prediction of Egg Weight from Egg Quality Indices of Nigerian Indigenous and Exotic Helmeted Guinea Fowls
Authors: Jegede Praise , Yakubu Abdulmojeed , Musa Ibrahim S. , Vincent Samuel T. , Shoyombo Ayoola J. , Alabi Olayinka O. , Wheto Mathew , Adebambo Ayotunde O. , Popoola Mustapha A.
Published: December 2024

This study was conducted to compare the fertility and hatchability performance of the Nigerian indigenous and exotic helmeted guinea fowls and predict egg weight from egg indices in Nigeria. A total of 300 randomly selected 8-month-old guinea fowls, comprising 150 indigenous (30 males and 120 females) and 150 exotic birds (30 males and 120 females), were utilized in this study. Consequently, a total of 240 randomly selected eggs (120 per genotype) were used separately for the reproductive and egg quality assessments. The fertility and hatchability parameters were subjected to descriptive statistics (numbers and percentages), while the 17 egg quality parameters were analyzed using a T-test, phenotypic correlation, principal component analysis, multiple linear regression, and a CHAID decision tree. Percentages of fertility (90.0 and 73.3%) and hatchability (66.7 and 56.8%) were higher in the exotic birds compared to their indigenous counterparts. The egg quality parameters of the exotic birds were higher (p < 0.05) than those of the indigenous birds, with the exception of egg shell index (18.88 ± 0.79 versus 16.41 ± 0.69) and Haugh unit (92.37 ± 3.13 versus 91.09 ± 3.22). However, the mean yolk/albumen ratio was similar (p > 0.05). The phenotypic correlation coefficients between egg weight and egg quality indices in both genetic groups ranged from low to high values [−0.05–0.95 (indigenous); −0.19–0.96 (exotic birds)]. Three principal components sufficiently accounted for the variations in the egg quality traits of both genetic groups. The CHAID algorithm was more consistent in egg weight prediction, with egg width as the primary explanatory variable. The present information may guide breeding and management strategies geared towards the improvement of the reproductive and egg quality traits of the helmeted guinea fowls.
Prediction of a Hydrogen Vapor Cloud Explosion with a Barrier Wall Using Various Machine Learning Methods
Authors: Min Hyunseok , Kang Hyungseok
Published: December 2024

Hydrogen is considered the next energy to replace fossil fuels, but it must be handled with care given that it is a flammable gas. A barrier wall is an effective way to mitigate the effect of an explosion, and to build a safe barrier wall, research on hydrogen explosions is necessary. Experiments and CFD (computational fluid dynamics) are two commonly used methods, but both are costly to use under any condition. Machine learning can be used to enhance the data from experiments and CFD as the trained model can predict explosion pressure levels very rapidly under various conditions. We propose the prediction of a hydrogen VCE (vapor cloud explosion) with a barrier wall using various machine learning methods. This research uses CFD simulation data from KAERI (Korea Atomic Energy Research Institute) as training data. MLP (multi-layer perceptron), LSTM (long short-term memory), and the Transformer architectures are used to train the hydrogen VCE and are compared. In our research, MLP produces the best score among all learning processes, with an R2 value exceeding 0.97, outperforming both LSTM and Transformer in terms of accuracy and speed. The trained machine learning model can be used to build safe barrier walls in hydrogen refueling stations. Evaluating the safe distance from the barrier wall and evaluating the optimal position of the barrier wall are possible usages.
A Series Arc Fault Diagnosis Method Based on an Extreme Learning Machine Model
Authors: Qi Lichun , Kawaguchi Takahiro , Hashimoto Seiji
Published: December 2024

In this study, we address the critical issue of accurately detecting series AC arc faults, which are often challenging to identify due to their small fault currents and can lead to devastating electrical fires. We propose an intelligent diagnosis method based on the extreme learning machine (ELM) model to enhance detection accuracy and real-time monitoring capabilities. Our approach involves collecting high-frequency current signals from 23 types of loads using a self-developed AC series arc fault data acquisition device. We then extract 14 features from both the time and frequency domains as candidates for arc fault diagnosis, employing a random forest to select the most significantly changed features. Finally, we design an ELM classifier for series arc fault diagnosis, achieving an identification accuracy of 99.00% ± 0.26%. Compared to existing series arc fault diagnosis methods, our ELM-based method demonstrates superior recognition performance. This study contributes to the field by providing a more accurate and efficient diagnostic tool for series AC arc faults, with broad implications for electrical safety and fire prevention.
The Development of a Method for NVH Prediction in Electrical Driving Systems Using a Quasi-Transient Excitation Force
Authors: Kim Myunggyu , Lee Sangwoo , Kim Hyunsu
Published: December 2024

Most motor vibrations are generated by excitation forces such as torque and switching ripples that are amplified at the mechanical resonance frequency. Both electromagnetic and structural vibration analyses should be used to accurately predict these vibrations. In this study, an analysis method that can simultaneously consider the excitation forces and vibration characteristics is proposed. The switching ripple was obtained from a 1D analysis model that included inverter and motor elements, while the motor torque ripple was extracted from a 2D electromagnetic analysis. To express the transient characteristics as the frequency of the excitation force increase when the vehicle accelerates, the excitation forces obtained in a steady state were converted into quasi-transient excitation forces using a sine sweep function which is newly suggested in this paper. For the vibration response characteristics of the motor, the transfer function between the excitation position and the response point of the motor was derived through structural analysis using the 3D finite element method. Using the quasi-transient excitation force and the transfer function obtained in the frequency domain, it was possible to establish a method for simultaneously representing the vibration characteristics due to resonance and excitation forces such as torque and switching ripples.
Research on the Production of Hydrogen Fluoride from Silicon Tetrafluoride Using 2.45 GHz Microwave Plasma
Authors: Liu Songlin , Shi Lianjun , Liu Guilan , Xiao Wei , Zhu Huacheng
Published: December 2024

Silicon tetrafluoride (SiF4), being a toxic gas, contains abundant fluorine and silicon resources. However, at present, the extraction of these resources from SiF4 remains a significant challenge for current technologies. Microwave plasma emerges as a promising technology with considerable potential in this area. Nevertheless, the majority of research endeavors concentrate on the silicon production through microwave plasma treatment of SiF4, while the resultant tail gas, rich in fluorine resources, is neglected and subsequently wasted. In this paper, a low-pressure microwave plasma is employed to process SiF4 and H2 for the one-step synthesis of hydrogen fluoride (HF). The microwave power reflection ratio, electron density, SF4 conversion rate, and produced HF concentration in varying microwave power levels and gas flow rates are obtained. The results demonstrate that all the processing parameters have a direct impact on the HF concentration. The maximum HF concentration of 11,200 ppm is achieved under the specific condition: an H2 flow rate of 2.5 sccm, a SiF4 flow rate of 2 sccm, and a microwave power level of 1100 W. Notably, this condition also results in the lowest energy cost. Moreover, the underlying reaction mechanism of the conversion from SiF4 to HF is thoroughly analyzed. This work presents fundamental process guidance for the production of HF using microwave plasma, facilitating the scalability of this technology in industry.
Numerical Simulation of the Interaction Between Hydraulic Fracture and the Bedding Plane in Shale Formation
Authors: Zheng Heng , Wang Haibo , Li Fengxia , Li Ning
Published: December 2024

Hydraulic fracturing was the primary technology for shale oil and gas development. Creating a huge stimulated reservoir volume was essential to improving shale oil and gas production. Based on the CDEM, a 3D hydraulic fracturing numerical model was proposed to simulate the interaction between hydraulic fracture and natural fracture. The simulation indicated that net pressure decrease was the main factor affecting fracture propagation in the vertical direction. Under a high stress difference, when the stress difference is over 9.0 MPa, the propagation resistance of rock matrix is higher than that of the bedding plane, thus the bedding plane has a huge opening, and the hydraulic fracture was arrested by the bedding plane. For high formation permeability, increasing the viscosity of the fracturing fluid can effectively improve the fracture height, which can accelerate the hydraulic fracture across the bedding plane. Improving the injection rate also benefitted crossing the bedding plane. This research has great significance in improving the stimulated reservoir volume.
Resistance and Christian Ethics in Africa
Authors: Orbih William I.
Published: December 2024

Colonialism in Africa rewarded individuals who offered no resistance to its ideology and demonized those who did. An effect this continues to have on the African moral imagination is the tendency to idealize compliance over resistance, especially to Western hegemony. Given Africa’s sociopolitical struggles and the consequence of the continent’s ongoing entrapment in the colonial power matrix, I explore ways ethical discourses on the continent can contribute to the ongoing interdisciplinary process of decolonization. In engagement with African literature and decolonial studies on the one hand and liberation ethics on the other, this article proposes a Christian ethics for Africa, discussing resistance as both a moral imperative in postcolonial contexts and a constitutive of the Christian identity.
Bathing Practices as a Religious and Medical Encounter: Water, Climate and Health Across Monsoon Asia
Authors: Bianchini Francesco
Published: December 2024

This study explores the intersection between religious and medical bathing practices across Monsoon Asia, with particularly reference to āyurvedic and Buddhist traditions. While previous scholarship has emphasised the ritualistic and social dimensions of bathing in Brahmanical and Buddhist contexts, this article complements it with discussions of its medicinal and healing functions, as outlined in classical texts and displayed in material culture. The research highlights how bathing was considered essential for maintaining bodily balance—a concept analogous to humoral theory in Galenic medicine—across different climatic and environmental conditions, particularly during the monsoon season. The article further examines the transregional circulation and localisation of these practices, considering how diverse Asian cultures adapted Indic bathing traditions to their unique climatic and cultural contexts. Notably, the study addresses the complex interplay between religious doctrines, health and environmental factors, drawing connections between āyurvedic principles and Buddhist medical discourses. The findings suggest that while the notion of balance in bathing practices was widespread, its interpretation and implementation varied significantly across regions, reflecting local environmental and cultural influences. Through a comparative analysis of sources from South Asia, China and Southeast Asia, this article provides a nuanced understanding of how religio-medical bathing practices were shaped by and responded to the diverse climatic realities of Monsoon Asia.
Multilingual Singing in Nigeria: Examining Roles, Meaning, and Function in Wazobia Gospel Music
Authors: Oyeniyi Adekunle
Published: December 2024

This article presents an introductory historical, sociolinguistic, and ethnographic study of “Wazobia gospel music”, a twenty-first-century Nigerian congregational musical genre. The term ‘Wazobia’ signifies a fusion of the three regionally recognized local languages in Nigeria: Wa (Yorùbá), Zo (Hausa), and Bia (Igbo)—words that mean ‘come’ in the respective languages. In the Nigerian context, the Wazobia concept could also symbolize the inclusion of more than one ethnicity or language. By dissecting three multilingual Nigerian congregational songs, I unveil the diverse perceptions of Wazobia gospel music and the associations of the musical genre in line with the influencing agencies, text, and performance practices. Furthermore, I provide a detailed description and analysis of the textual and sonic contents of Wazobia gospel music, emphasizing its roles, meanings, and functions in the Lagos congregations context. I argue that Wazobia gospel music—multilingual singing in Nigerian churches—embodies multilayered roles in negotiating identity and creating hospitality. The complexity of studying congregational singing in cosmopolitan cities (like Lagos, Nigeria) due to multiple ethnolinguistic and musical expressions within local and transnational links is also addressed. To tackle this complexity, this article adopts an interdisciplinary approach, combining historical research, oral history, and hybrid ethnography. This approach ensures a thorough and in-depth understanding of Wazobia gospel music, a topic of significant importance in the study of Nigerian music, linguistics, and cultural studies. By employing frameworks of musical localization and signification, I incorporate the results of my ethnographic studies of three Protestant churches in Lagos, Nigeria, to illustrate Wazobia gospel music’s continued importance. The article conceptualizes multilingual singing and offers fresh perspectives on studying Nigerian Christian congregational music in the twenty-first century.
Sensitivity Analysis of Gas Retrieval from FS MAX-DOAS Measurements
Authors: Xu Jiangman , Li Ang , Hu Zhaokun , Ren Hongmei
Published: December 2024

Multi-axis differential absorption spectroscopy (MAX-DOAS) has become an important tool for detecting trace gases in optical remote sensing. At present, the temporal resolution of the system using the traditional motor-rotated elevation telescope is extremely low. We focus on studying the atmospheric radiation transmission of fast synchronous MAX-DOAS (FS MAX-DOAS), which has greatly improved the temporal resolution on the ground and on mobile platforms and the influence of related parameters on the atmospheric mass factor (AMF), which is used to guide the design and experiments of the new system. The optimal elevation angle combination, the spectral resolution, and the specific effects of relevant parameters on the AMF during profile inversion by the new system were analyzed, and the feasibility of the new system for mobile MAX-DOAS was evaluated. The inversion results of the measured spectra collected by the system show that FS MAX-DOAS can meet the requirements of both ground and mobile platform observation scenarios. The results of our sensitivity study are of great significance for guiding experiments.
Spatial Pattern Evolution and Influencing Factors of Foreign Star-Rated Hotels in Chinese Cities
Authors: Zhang Xiang , Han Dongxiao , Zhang Chunfeng , Feng Wenyi , Wu Jinsong , Xie Yan , He Yating
Published: December 2024

Spatial distribution is a critical factor influencing the success or failure of hotel management. This study examines the spatial distribution patterns of foreign star-rated hotels in China from 2000 to 2015 based on 27 typical city cases, using global and local spatial autocorrelation methods within GIS spatial analysis. The research explores the evolution of these patterns, analyzes key characteristics, and combines these insights with a stepwise regression method. Pearson correlation analysis is used to identify factors that influence the evolution of the spatial pattern. This study reveals that, first, the Z-value of global spatial autocorrelation of foreign star-rated hotels in China decreases from 2.38 to 1.63, indicating that the spatial distribution of foreign star-rated hotels in China has shifted from imbalanced to balanced, transitioning from economically developed regions such as areas with overseas Chinese populations, provincial capitals, and municipalities directly under central government control, toward tourist cities. Second, star-rated hotels hold a critical position within the spatial pattern, highlighting their central role in shaping the hospitality landscape. Third, the spatial distribution of foreign star-rated hotels is primarily influenced by the number of inbound tourists, followed by the presence of scenic spots rated 4A and above. The influence of other factors is found to be less significant. Fourth, the correlation coefficient between tourism demand and foreign star-rated hotels increased by 0.004, whereas the correlation coefficient between tourism supply and foreign star-rated hotels decreased by 0.036, indicating that market factors are playing an increasingly important role in shaping the evolution of foreign star-rated hotels in China, reflecting broader market dynamics. This study provides practical guidance for local Chinese hotels facing competition from foreign-funded establishments and offers theoretical insight into the strategic implementation of transnational operations. It points out the expansion direction of local Chinese hotels across different developmental stages.
FP-YOLOv8: Surface Defect Detection Algorithm for Brake Pipe Ends Based on Improved YOLOv8n
Authors: Rao Ke , Zhao Fengxia , Shi Tianyu
Published: December 2024

To address the limitations of existing deep learning-based algorithms in detecting surface defects on brake pipe ends, a novel lightweight detection algorithm, FP-YOLOv8, is proposed. This algorithm is developed based on the YOLOv8n framework with the aim of improving accuracy and model lightweight design. First, the C2f_GhostV2 module has been designed to replace the original C2f module. It reduces the model’s parameter count through its unique design. It achieves improved feature representation by adopting specific technique within its structure. Additionally, it incorporates the decoupled fully connected (DFC) attention mechanism, which minimizes information loss during long-range feature transmission by separately capturing pixel information along horizontal and vertical axes via convolution. Second, the Dynamic ATSS label allocation strategy is applied, which dynamically adjusts label assignments by integrating Anchor IoUs and predicted IoUs, effectively reducing the misclassification of high-quality prediction samples as negative samples. Thus, it improves the detection accuracy of the model. Lastly, an asymmetric small-target detection head, FADH, is proposed to utilize depth-separable convolution to accomplish classification and regression tasks, enabling more precise capture of detailed information across scales and improving the detection of small-target defects. The experimental results show that FP-YOLOv8 achieves a mAP50 of 89.5% and an F1-score of 87% on the ends surface defects dataset, representing improvements of 3.3% and 6.0%, respectively, over the YOLOv8n algorithm, Meanwhile, it reduces model parameters and computational costs by 14.3% and 21.0%. Additionally, compared to the baseline model, the AP50 values for cracks, scratches, and flash defects rise by 5.5%, 5.6%, and 2.3%, respectively. These results validate the efficacy of FP-YOLOv8 in enhancing defect detection accuracy, reducing missed detection rates, and decreasing model parameter counts and computational demands, thus meeting the requirements of online defect detection for brake pipe ends surfaces.
Prediction and Fitting of Nonlinear Dynamic Grip Force of the Human Upper Limb Based on Surface Electromyographic Signals
Authors: Cai Zixiang , Qu Mengyao , Han Mingyang , Wu Zhijing , Wu Tong , Liu Mengtong , Yu Hailong
Published: December 2024

This study aimed to predict and fit the nonlinear dynamic grip force of the human upper limb using surface electromyographic (sEMG) signals. The research employed a time-series-based neural network, NARX, to establish a mapping relationship between the electromyographic signals of the forearm muscle groups and dynamic grip force. Three-channel electromyographic signal acquisition equipment and a grip force sensor were used to record muscle signals and grip force data of the subjects under specific dynamic force conditions. After preprocessing the data, including outlier removal, wavelet denoising, and baseline drift correction, the NARX model was used for fitting analysis. The model compares two different training strategies: regularized stochastic gradient descent (BRSGD) and conjugate gradient (CG). The results show that the CG greatly shortened the training time, and performance did not decline. NARX demonstrated good accuracy and stability in dynamic grip force prediction, with the model with 10 layers and 20 time delays performing the best. The results demonstrate that the proposed method has potential practical significance for force control applications in smart prosthetics and virtual reality.
Square Root Unscented Kalman Filter-Based Multiple-Model Fault Diagnosis of PEM Fuel Cells
Authors: Allam Abdulrahman , Mangold Michael , Zhang Ping
Published: December 2024

Harsh operating conditions imposed by vehicular applications significantly limit the utilization of proton exchange membrane fuel cells (PEMFCs) in electric propulsion systems. Improper/poor management and supervision of rapidly varying current demands can lead to undesired electrochemical reactions and critical cell failures. Among other failures, flooding and catalytic degradation are failure mechanisms that directly impact the composition of the membrane electrode assembly and can cause irreversible cell performance deterioration. Due to the functional significance and high manufacturing costs of the catalyst layer, monitoring internal fuel cell states is crucial. For this purpose, a diagnostic-oriented multi-scale PEMFC catalytic degradation model is developed which incorporates the failure effects of catalytic degradation on cell dynamics and global stack performance. Embedded to the multi-scale model is a square root unscented Kalman filter (SRUKF)-based multiple-model fault diagnosis scheme. In this approach, multiple models are used to estimate specific internal PEMFC system parameters, such as the mass transfer coefficient of the gas diffusion layer or the exchange current density, which are treated as additional system states. Online state estimates are provided by the SRUKF, which additionally propagates model-conditioned statistical information to update a Bayesian framework for model selection. The Bayesian model selection method carries fault indication signals that are interpreted by a derived decision logic to obtain reliable information on the current-operating system regime. The proposed diagnosis scheme is evaluated through simulations using the LA 92 and NEDC driving cycles.
Consistent Condom and Lubricant Use and Associated Factors Amongst Men Who Have Sex with Men in Sub-Saharan Africa: A Systematic Review
Authors: Abdulai Ratif , Phalane Edith , Atuahene Kyeremeh , Phaswana-Mafuya Refilwe Nancy
Published: December 2024

Men who have sex with men (MSM) in sub-Saharan Africa (SSA) are disproportionately affected by the human immunodeficiency virus (HIV) compared to adult men in the general population. Unprotected anal sexual intercourse is a high-risk behavior for HIV infection. This makes the correct and consistent use of condoms with condom-compatible lubricants crucial in reducing further HIV acquisition amongst the MSM population in SSA. However, consolidated data on the scope of the consistency of condom use with lubricants among MSM in SSA is lacking. In this regard, it was necessary to consolidate existing evidence on consistent condom usage with lubricants, as well as associated context-specific factors among the MSM population in SSA. A systematic review was conceptualized and registered with the International Prospective Register of Systematic Reviews (registration number: CRD42023437904). It was compiled following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) principles and guidelines between July 2023 and June 2024. We searched PubMed, Scopus, ScienceDirect, Google Scholar, and governmental and non-governmental institutions to find published and gray literature relevant to the review objectives from 2005 to June 2024. Studies conducted in SSA, published in English, focusing on MSM aged ≥15 years and also reported condom and lubricant use were considered for this review. Following the removal of duplicates and ineligible articles, 40 studies out of 202 reviewed were selected for the study. The most common study designs were cross-sectional surveys (n = 32) followed by prospective cohorts (n = 4), integrated bio-behavioral surveillance surveys (n = 3), and intervention studies (n = 1). Of the 40 eligible studies included in this review, half (n = 20) reported consistent use of condoms but without lubricants, three reported consistent use of condoms with lubricants but did not specify the lubricant type, six reported consistent condom use with water-based condom-compatible lubricants, and 11 reported only condom use but not consistent usage. Factors linked to consistent condom use with lubricants among MSM from various studies included higher educational level, knowing one’s HIV status, accessibility challenges, and older age. Having a high level of self-worth and HIV risk-reduction counseling was also associated with a consistency of condom use amongst MSM who engaged in receptive anal sex. This review indicates that only a few studies reported consistent condom use with lubricants and water-based compatible lubricants.
Perspectives on Sustainable Construction in the Middle East: A Comparative Analysis of Industry and Academia
Authors: Elnaklah Rana , Alotaibi Badr Saad , Elbellahy Shukri , Abuhussain Mohammed Awad
Published: December 2024

Existing research has primarily focused on investigating barriers in developed countries, emphasising economic, technical, and governmental factors which impede the diffusion of green building practices. However, developing regions, including the Middle East, often must be represented in green building research. Understanding these region-specific barriers is important for developing tailored solutions. In addition, existing identified green building barriers have primarily been obtained from the industry sector, while perspectives from other stakeholders, such as academia, have less attention. Hence, this study compares the perspectives of academic and industry professionals regarding the possible barriers which may impede the adoption of green buildings, with a particular focus on cultural, educational, and social factors. A mixed-method approach was employed, including a large-scale survey (n = 1112) with 54% of the participants being from the industrial sector and 46% being from the academic sector, as well as 17 semi-structured interviews to triangulate the data obtained from the survey. The study was conducted in Saudi Arabia as a representative case of the Middle East. Participants reported 23 barriers, which were themed into six groups: economic, technical, governmental, market demand, educational, and cultural barriers. Notably, seven of these barriers were reported for the first time in this study, including a lack of integrating green building concepts into university curricula, cultural preferences for traditional construction practices, resistance to change, prioritisation of economic factors over environmental and social considerations, a limited number of completed green building projects, delays in the permit and approval processes, and a lack of leadership and coordination. The statistical analysis revealed significant differences between the industry and academic perspectives (p < 0.05, d = 0.61) regarding the barriers to adopting green buildings, with academics over-reporting the educational, cultural, and technical barriers compared with the industry sector. Based on the identified barriers, five strategies were suggested which could help promote the widespread adoption and long-term sustainability of green buildings in the Middle East.
A Systematic Literature Review of Privacy Information Disclosure in AI-Integrated Internet of Things (IoT) Technologies
Authors: Amin M A Shariful , Kim Seongjin , Rishat Md Al Samiul Amin , Tang Zhenya , Ahn Hyunchul
Published: December 2024

The rapid advancement and integration of Artificial Intelligence (AI) in Internet of Things (IoT) technologies have raised significant concerns regarding privacy information disclosure. As AI-enabled IoT devices collect, process, and share vast amounts of personal data, it is crucial to understand the current state of research on this topic and identify areas for future investigation. This research systematically analyzed 38 peer-reviewed articles on privacy information disclosure in the AI-enabled IoT context. The analysis yielded pivotal themes pertinent to information disclosure in the IoT realm, encompassing facets such as consumer IoT adoption, personalized service, the commodification of information, external threats, vulnerability, innovation, regulation, behavioral patterns, trust, demographic considerations, user satisfaction, strategic marketing plans, and institutional reputation. This paper posits a combined summary research framework explaining user-centric information disclosure behavior in the IoT sphere in light of these disclosures. The insights presented cater to diverse stakeholders, including researchers, policymakers, and businesses, aiming for optimized AI-integrated IoT engagement while prioritizing privacy.
Mapping Urban Changes Through the Spatio-Temporal Analysis of Vegetation and Built-Up Areas in Iași, Romania
Authors: Foșalău Cristian-Manuel , Roșu Lucian , Iațu Corneliu , Dinter Oliver-Valentin , Cristodulo Petru-Mihai
Published: December 2024

Vegetation cover in urban and peri-urban areas is threatened by urban sprawl, through habitat fragmentation, loss of green space, biodiversity reduction, and the urban heat island effect intensifying. The intrusion of cities into natural landscapes reduces vital ecosystem services provided by vegetation. Hence, sustainable and integrated urban planning practices are required. Our study aims to investigate the dynamics of the urban and peri-urban fabric by exploring the relationship between the green fabric distribution and recent trends in urban expansion, focusing specifically on the peri-urban areas of Iași Municipality, Romania. We designed a mixed-method approach combining a multivariate analysis of four critical indicators (vegetation cover, built-up space, land surface temperature, and population density), emerging hot-spots, and space-time cubes in a GIS environment to achieve our research aims. Our results demonstrate that uncontrolled urban expansion has manifested in diverse patterns, impacting territories next to road transport networks and with construction-suitable topography. Concurrently, the development of green spaces prevails in forests and unexpected locations such as brownfields, railway corridors, and old industrial zones, through the growth of urban greenery. This approach provides a comprehensive understanding of how urban sprawl impacts the environment and how different land types are prone to this transformation, creating a path towards sustainability, resilience, and equitable development.
Integrating Remote Sensing and Community Perceptions for Sustainable Climate Adaptation Strategies in Mountain Ecosystems
Authors: Pokhrel Ankita , Fang Ping , Bastola Gaurav
Published: December 2024

Mountain ecosystems, such as Nepal’s Annapurna Conservation Area (ACA), are highly vulnerable to climate change, which threatens biodiversity, water resources, and livelihoods. This study examines Land Use Land Cover (LULC) changes, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Snow Index (NDSI), climate variability, and community perception and adaptations over a 35-year period (1988–2023) using remote sensing, meteorological data, and community surveys. Vegetation expanded by 19,800 hectares, while barren land declined, reflecting afforestation and land reclamation efforts. NDVI showed improved vegetation health, while NDSI revealed significant snow cover losses, particularly after 1996. Meteorological analysis highlighted intensifying monsoonal rainfall and rising extreme precipitation events at lower elevations. Communities reported increased flooding, unpredictable rainfall, and reduced snowfall, driving adaptive responses such as water conservation, crop diversification, and rainwater harvesting. These findings demonstrate the value of integrating scientific data with local knowledge to inform sustainable adaptation strategies. Contributing to Sustainable Development Goals (SDGs) 6 and 13, the findings emphasize the importance of adaptive water management, resilient agriculture, and participatory conservation to enhance climate resilience in mountain ecosystems.
The Antecedents of the Willingness to Adopt and Pay for Climate-Smart Agricultural Technology Among Cooperatives in China
Authors: Feng Xiaoxue , Zailani Suhaiza
Published: December 2024

Climate-smart agricultural technology (CSAT) has been recognized as an effective agricultural technology for mitigating or eliminating climate change damages to agricultural production. The adoption of CSAT by Chinese farmers has also increased significantly, driven by the government. However, the range of technologies adopted is very limited to several types, such as piped irrigation, high-yielding seeds, and organic fertilizers. In this study, four reasons for the adoption of CSAT were summarized through a literature review and semi-structured interviews, and antecedents and outcomes were conceptualized through the Behavioral Reasoning Theory (BRT) model and the concept of willingness to pay (WTP). The data from 308 farmers’ cooperatives were analyzed and it was found that three reasons—policy/government support, recommendations from opinion leaders, and extension services—have positive significant impacts on the willingness of farmers’ cooperatives to adopt CSAT. However, perceived usefulness was also observed to have no significant impact on the willingness of farmers’ cooperatives to adopt CSAT because the significant level of the t-value was only 1.767. In addition, the value of openness to change was proved to have significant positive effects on policy/government support, recommendations from opinion leaders, extension services, and perceived usefulness, whereas it had no impact on willingness to adopt CSAT. However, reasons for the adoption (policy/government support, recommendations from opinion leaders, and extension services) were confirmed to have a mediating effect between the value of openness to change and willingness to adopt CSAT, which means that the value of openness to change can indirectly affect the willingness to adopt CSAT by influencing the views of farmers’ cooperatives on the variables of reasons for the adoption of CSAT. More widespread, diverse, and multi-level CSAT adoption requires in-depth publicity and promotion and multi-channel recommendations, both at the government level and at the technology company level.
Investigating Surface Settlements During Shield Tunneling Using Numerical Analysis
Authors: He Ruixia , Zhou Ziwen , Li Shuai , Vanapalli Sai
Published: December 2024

The development of the subway system in Shenyang City, China, plays a vital role in alleviating traffic congestion and promoting sustainable societal growth. However, the deformation of the surface caused by the tunneling of the shield presents a significant threat to the structural integrity of Shenyang Subway Line 2 and adjacent geotechnical structures. To tackle this challenge, a set of FEA (finite element analysis) simulations were carried out to examine surface deformation under various construction scenarios for Line 2. These simulations were compared with empirical formulas and numerical analyses conducted using Midas GTS NX 2019 software, in addition to actual site measurements. The outcomes of the finite element analysis (FEA) demonstrated a closer alignment with the empirical data than with traditional formulas. The maximum deformation was observed to be approximately twice as large as the equivalent diameter at the back of the excavation face. The analysis indicated that surface deformation is inversely correlated with overburden thickness (H), soil elasticity (E), and the grout filling rate of the shield tail (ψ), while it is directly proportional to the shield’s outer diameter (D). This study provides important methods used in the shield tunneling process employed in the Shenyang subway and suggests that the developed methodologies may be applicable to similar subway projects.
On Local Fractional Topological Indices and Entropies for Hyper-Chordal Ring Networks Using Local Fractional Metric Dimension
Authors: Ali Shahzad , Ashraf Shahzaib , Ali Shahbaz , Afzal Abdullah , Alali Amal S.
Published: December 2024

An algebraic graph is defined in terms of graph theory as a graph with related algebraic structures or characteristics. If the vertex set of a graph G is a group, a ring, or a field, then G is called an algebraic structure graph. This work uses an algebraic structure graph based on the modular ring Zn, known as a hyper-chordal ring network. The lower and upper bounds of the local fractional metric dimension are computed for certain families of hyper-chordal ring networks. Utilizing the cardinalities of local fractional resolving sets, local fractional resolving (LFR)M-polynomials are computed for hyper-chordal ring networks. Further, new topological indices based on (LFR)M-polynomials are established for the proposed networks. The local fraction entropies are developed by modifying the first three kinds of Zagreb entropies, which are calculated for the chosen hyper-chordal ring networks. Furthermore, numerical and graphical comparisons are discussed to observe the order between newly computed topological indices.
ChatBlock: A Block-Based Chatbot Framework for Supporting Young Learners and the Classroom Authoring for Teachers
Authors: Anutariya Chutiporn , Chawmungkrung Hathaichanok , Jearanaiwongkul Watanee , Racharak Teeradaj
Published: December 2024

Chatbots have been used as a digital interactive learning tool in education. Designing a chatbot for young students has challenges in their capability to formulate sentences by typing. Teachers have a challenge to develop a chatbot for desired purposes as well as to suit their classes. This research proposes a ChatBlock framework that provides ChatBlock Tutor and ChatBlock Classroom interfaces to serve the target users. ChatBlock Tutor is designed as a block-based interface to support young students to connect various types of blocks for creating sentences. The formulated block-based sentences are used to make a conversation with the chatbot. On the other hand, the ChatBlock Classroom is developed to support teachers in preparing customizable content for a classroom in various formats, i.e., Q&As, learning materials, exercises, and quizzes. Finally, the design and development of ChatBlock is discussed and two case studies in primary schools are elaborated. We conduct a preliminary evaluation with a selected primary school and report the lessons learned from our study.