bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization of a Major Quantitative Trait Locus for the Whiteness of Rice Grain Using Chromosome Segment Substitution Lines
Authors: Chen Lulu , Leng Yujia , Zhang Caiyun , Li Xixu , Ye Zhihui , Lu Yan , Huang Lichun , Liu Qing , Gao Jiping , Zhang Changquan , Liu Qiaoquan
Published: December 2024

The whiteness of rice grains (WRG) is a key indicator of appearance quality, directly impacting its commercial value. The trait is quantitative, influenced by multiple factors, and no specific genes have been cloned to date. In this study, we first examined the correlation between the whiteness of polished rice, cooked rice, and rice flour, finding that the whiteness of rice flour significantly correlated with both polished and cooked rice. Thus, the whiteness of rice flour was chosen as the indicator of WRG in our QTL analysis. Using a set of chromosome segment substitution lines (CSSL) with japonica rice Koshihikari as the recipient and indica rice Nona Bokra as the donor, we analyzed QTLs for WRG across two growth environments and identified six WRG QTLs. Notably, qWRG9 on chromosome 9 displayed stable genetic effects in both environments. Through chromosomal segment overlapping mapping, qWRG9 was narrowed to a 1.2 Mb region. Additionally, a BC4F2 segregating population confirmed that low WRG was a dominant trait governed by the major QTL qWRG9, with a segregation ratio of low to high WRG approximating 3:1, consistent with Mendelian inheritance. Further grain quality analysis on the BC4F2 population revealed that rice grains carrying the Indica-type qWRG9 allele not only exhibited lower WRG but also had significantly higher protein content. These findings support the fine mapping of the candidate gene and provide an important QTL for improving rice grain quality through genetic improvement.
In-Depth LC-ESI/HRMS-Guided Phytochemical Analysis and Antioxidant Activity Analysis of Eco-Sustainable Extracts of Cynara cardunculus (Carciofo di Paestum PGI) Leaves
Authors: Cerulli Antonietta , Cuozzo Roberta , Melis Maria Paola , Serreli Gabriele , Deiana Monica , Masullo Milena , Piacente Sonia
Published: December 2024

The Italian Carciofo di Paestum (C. scolymus) PGI, an artichoke variety from the Campania region, was investigated for its potential to reuse by-products for food supplements. EtOH:H2O 50:50 and 75:25 extracts of its leaves were analyzed for phenolic and flavonoid content and antioxidant activity (TEAC: 1.90 and 1.81 mM of Trolox; DPPH IC50: 106.31 µg/mL and 128.21 µg/mL; FRAP: 1.68 and 1.58 mM FeSO₄/g extract). To further investigate the antioxidant potential, the ability of the two extracts to scavenge reactive species was assessed in Caco-2 cell cultures, showing a dose-dependent antioxidant capacity. To highlight metabolites responsible for the activity, LC-ESI/HRMSMS analysis was achieved, revealing 28 compounds (sesquiterpenes, megastigmanes, quinic acid and hydroxycinnamic acid derivatives, flavonoids, lignans, triterpenoid saponins, and polar fatty acids), of which structures were determined using 1D- and 2D-NMR analysis. In addition, quantitative determination of caffeoyl, dicaffeoyl, and quinic acid derivatives (CQAs) was performed through LC-ESI/QTrap/MS/MS, highlighting that the most abundant compound was 5-caffeoylquinic acid (6), with values of 9.310 and 7.603 mg/g extract in EtOH:H2O (75:25) and EtOH:H2O (50:50), respectively. The analysis showed that extracts were rich in bioactive compounds, suggesting their potential for development into antioxidant-based food supplements that may protect cells from oxidative stress and support overall wellness.
Patterns of Genetic and Morphological Variability of Teucrium montanum sensu lato (Lamiaceae) on the Balkan Peninsula
Authors: Zbiljić Miloš , Lakušić Dmitar , Šatović Zlatko , Liber Zlatko , Kuzmanović Nevena
Published: December 2024

The Balkan Peninsula represents an important center of plant diversity, exhibiting remarkable ecological heterogeneity that renders it an optimal region for studying the diversification patterns of complex taxa such as Teucrium montanum. In the Balkan Peninsula, T. montanum is a highly plastic and morphologically variable species with unresolved taxonomic status. To ascertain the patterns of genetic and morphological diversification, a comparative genetic and morphological analysis was conducted. In total, 57 populations were subjected to analysis using AFLP and a multivariate morphometric approach. A Bayesian analysis of population structure distinguished two main genetic clusters, labelled A and B. Cluster B was found to be geographically restricted to the northwestern Dinarides, while cluster A occurred in the rest of the Balkans. Genetic cluster A was further subdivided into four subclusters that were spatially separated from each other. The contact populations between the subclusters exhibited a mixed genetic structure. There was a partial correlation between genetic and morphological diversification. The peripheral populations of the genetic clusters displayed morphological differences, while both genetic and morphological differences decreased in the contact zones. The observed genetic structure can be attributed to the reproductive biology of this species and the complex geological history of the Balkan Peninsula.
Dynamic Boronic Ester Cross-Linked Polymers with Tunable Properties via Side-Group Engineering
Authors: Wang Linlin , Wang Xiao , Feng Shengyu , Li Lei
Published: December 2024

The development of dynamic covalent materials with repairability, reprocessability, and recyclability is crucial for sustainable development. In this work, we report a new strategy to adjust the thermomechanical properties of boronic ester cross-linked poly(β-hydroxyl amine)s through side-group engineering. By tuning the side groups of the poly(β-hydroxyl amine)s, we have developed self-healable, reprocessable, and shape-programmable materials. By tuning the side groups of the poly(β-hydroxyl amine)s, the thermomechanical properties can be readily adjusted. Notably, the 3-amino-1,2-propanediol-derived polymer exhibits enhanced thermal (Tg = 95 °C) and mechanical (tensile strength = 34.2 MPa) performance due to increased hydrogen bonding. Benefiting from the dynamic reversibility of the boronic esters, these materials demonstrate solvent-assisted healing, reprocessing, chemical recycling, and shape programming capabilities. Given their straightforward synthesis, tunable properties, and robust dynamic features, the boronic ester cross-linked poly(β-hydroxyl amine)s hold great promise for various applications, including flexible electronic and biomedical materials.
Design, Analysis, and Testing of a Type V Composite Pressure Vessel for Hydrogen Storage
Authors: Mikroni Maria , Koutsoukis Grigorios , Vlachos Dimitrios , Kostopoulos Vassilis , Vavouliotis Antonios , Trakakis George , Athinaios Dimitrios , Nikolakea Chrysavgi , Zacharakis Dimitrios
Published: December 2024

Hydrogen, as a zero-emission fuel, produces only water when used in fuel cells, making it a vital contributor to reducing greenhouse gas emissions across industries like transportation, energy, and manufacturing. Efficient hydrogen storage requires lightweight, high-strength vessels capable of withstanding high pressures to ensure the safe and reliable delivery of clean energy for various applications. Type V composite pressure vessels (CPVs) have emerged as a preferred solution due to their superior properties, thus this study aims to predict the performance of a Type V CPV by developing its numerical model and calculating numerical burst pressure (NBP). For the validation of the numerical model, a Hydraulic Burst Pressure test is conducted to determine the experimental burst pressure (EBP). The comparative study between NBP and EBP shows that the numerical model provides an accurate prediction of the vessel’s performance under pressure, including the identification of failure locations. These findings highlight the potential of the numerical model to streamline the development process, reduce costs, and accelerate the production of CPVs that are manufactured by prepreg hand layup process (PHLP), using carbon fiber/epoxy resin prepreg material.
RETRACTED: Ahmed et al. Thermal Analysis of a Metal–Organic Framework ZnxCo1-X-ZIF-8 for Recent Applications. Polymers 2021, 13, 4051
Authors: Ahmed Moustafa , Al-Hadeethi Yas M. , Alshahrie Ahmed , Kutbee Arwa T , Shaaban Essam R. , Al-Hossainy Ahmed F.
Published: December 2024

The journal retracts the article “Thermal Analysis of a Metal–Organic Framework ZnxCo1-X-ZIF-8 for Recent Applications” [...]
The Influence of Fresh Latex Coagulation on the Parameter Characteristics of the Yeoh Hyperelastic Constitutive Model for Natural Rubber
Authors: Ding Li , Huang Honghai , Wang Yuekun , Li Jianwei , Gui Hongxing , Chen Yongping
Published: December 2024

The coagulation of fresh latex is one of the critical processes that impacts rubber quality during natural rubber processing. Constitutive relationships are the basis for the study of the mechanical properties of rubber materials and serve as a prerequisite for material simulation studies. However, studies on the effect of different coagulation methods on natural rubber constitutive relationships have yet to be carried out, and the current models used for natural rubber constitutive relationships need to be improved. In order to investigate the effects of different coagulation methods on the hyperelastic properties of natural rubber, the impact of natural coagulation, enzyme coagulation, acid coagulation, microbial coagulation, and enzyme-assisted microbial coagulation on the hyperelastic constitutive relationship of natural rubber were analyzed in detail based on tensile experiments and the Yeoh model. The results show that after introducing a strain rate-related factor, the Yeoh model can describe well the mechanical behavior of natural rubber carbon black composites in different deformation regions, and the rubber, studied with varying coagulation methods, exhibits different mechanical properties in different deformation regions. This study provides new evidence for the study of high-performance natural rubber and serves as a reference for process selection in the primary processing of natural rubber.
Extraction of Natural-Based Raw Materials Towards the Production of Sustainable Man-Made Organic Fibres
Authors: Vale Ana Catarina , Leite Liliana , Pais Vânia , Bessa João , Cunha Fernando , Fangueiro Raul
Published: December 2024

Bioresources have been gaining popularity due to their abundance, renewability, and recyclability. Nevertheless, given their diverse composition and complex hierarchical structures, these bio-based sources must be carefully processed to effectively extract valuable raw polymeric materials suitable for producing man-made organic fibres. This review will first highlight the most relevant bio-based sources, with a particular focus on promising unconventional biomass sources (terrestrial vegetables, aquatic vegetables, fungi, and insects), as well as agroforestry and industrial biowaste (food, paper/wood, and textile). For each source, typical applications and the biopolymers usually extracted will also be outlined. Furthermore, acknowledging the challenging lignocellulosic structure and composition of these sources, an overview of conventional and emerging pre-treatments and extraction methods, namely physical, chemical, physicochemical, and biological methodologies, will also be presented. Additionally, this review aims to explore the applications of the compounds obtained in the production of man-made organic fibres (MMOFs). A brief description of their evolution and their distinct properties will be described, as well as the most prominent commercial MMOFs currently available. Ultimately, this review concludes with future perspectives concerning the pursuit of greener and sustainable polymeric sources, as well as effective extraction processes. The potential and main challenges of implementing these sources in the production of alternative man-made organic fibres for diverse applications will also be highlighted.
3D-Printed Acrylated Soybean Oil Scaffolds with Vitrimeric Properties Reinforced by Tellurium-Doped Bioactive Glass
Authors: Bergoglio Matteo , Kriehuber Matthias , Sölle Bernhard , Rossegger Elisabeth , Schlögl Sandra , Najmi Ziba , Cochis Andrea , Ferla Federica , Miola Marta , Vernè Enrica , Sangermano Marco
Published: December 2024

In this study, we present novel, vitrimeric and biobased scaffolds that are designed for hard tissue applications, composed of acrylated, epoxidized soybean oil (AESO) and reinforced with bioactive glass that is Tellurium doped (BG-Te) and BG-Te silanized, to tune the mechanical and antibacterial properties. The manufacture’s method consisted of a DLP 3D-printing method, enabling precise resolution and the possibility to manufacture a hollow and complex structure. The resin formulation was optimized with a biobased, reactive diluent to adjust the viscosity for an optimal 3D-printing process. The in vitro biological evaluation of the 3D-printed scaffolds, combined with BG-Te and BG-Te-Sil, showed that the sample’s surfaces remained safe for hBMSCs’ attachment and proliferation. The number of S. aureus that adhered to the BG-Te was 87% and 54% lower than on the pristine (control) and BG-Te-Sil, respectively, with the eradication of microbiofilm aggregates. This work highlights the effect of the vitrimeric polymer matrix and doped, bioactive glass in manufacturing biocompatible, biobased, and antibacterial scaffold used in hard tissue application.
Application of the Hydrocarbon Generation Potential Method in Resource Potential Evaluation: A Case Study of the Qiongzhusi Formation in the Sichuan Basin, China
Authors: Yang Hanxuan , Geng Chao , Zheng Majia , Zheng Zhiwei , Long Hui , Chang Zijing , Li Jieke , Pang Hong , Yang Jian
Published: December 2024

Global recoverable shale gas reserves are estimated to be 214.5 × 1012 m3. Estimation methods for shale gas resources, such as volumetric, analog, and genetic approaches, have been widely used in previous studies. However, these approaches have notable limitations, including the substantial effect of rock heterogeneity, difficulties in determining the similarity of analog accumulations, and unsuitability for evaluating high-mature–overmature source rocks. In the Qiongzhusi Formation (Є1q) of the Sichuan Basin, China, extensive development of high-mature–overmature shales has led to significant advancements in conventional and unconventional shale gas exploration. This progress highlights the need for the development of an integrated evaluation system for conventional and unconventional resources. Hence, this study uses the whole petroleum system theory and an improved hydrocarbon generation potential method to analyze the distribution patterns of hydrocarbon generation, retention, and expulsion during various stages of oil and gas accumulation in the Є1q. In addition, it assesses the resource potential of conventional and shale oil and gas. Hydrocarbon generation and expulsion centers are favorable exploration targets for conventional oil and gas, primarily located in the central and northern regions of the Mianyang—Changning rift trough, with an estimated resource potential of 6560 × 1012 m3. Hydrocarbon retention centers represent promising targets for shale oil and gas exploration, concentrated in the central Mianyang—Changning rift trough, with a resource potential of 287 × 1012 m3. This study provides strategic guidance for future oil and gas exploration in the Є1q and offers a methodological reference for integrated resource assessments of conventional and unconventional oil and gas systems of high-mature–overmature source rocks in similar basins worldwide.
An Improved Prediction Method for Failure Probability of Natural Gas Pipeline Based on Multi-Layer Bayesian Network
Authors: Weng Yueyue , Sun Xu , Yang Yufeng , Tao Mengmeng , Liu Xiaoben , Zhang Hong , Zhang Qiang
Published: December 2024

The failure probability of a pipeline is a quantification of the likelihood of an accident occurring in the pipeline, which is an indispensable part of the pipeline risk assessment process. To solve the problems of strong subjectivity, low feasibility, and low accuracy in the existing pipeline failure probability calculation methods, a three-layer Bayesian network topology model of “pipeline failure–failure cause–influencing factor” is proposed, with the pipeline failure as the subnode, the type of pipeline failure as the intermediate node, and the factors affecting the pipeline failure as the parent node of the network. Based on data fitting and fuzzy theory analysis methods, the functional relationship between the impact factor and the failure frequency of various pipelines is quantified. Using the mean value theorems for definite integrals and the analytic hierarchy process, the conditional probability of the directed edge in the network is calculated. The proposed function relationship provides a method to calculate the prior probability according to the parameters of the pipeline and its surroundings and a new idea to train the network model even without sufficient data.
Propagation Law of Hydraulic Fractures in Continental Shale Reservoirs with Sandstone–Shale Interaction
Authors: Gao Yuan , Qin Qiuping , Bian Xiaobing , Wang Xiaoyang , Xu Wenjun , Zhao Yanxin
Published: December 2024

There are significant lithological and stress differences between continental shale layers, posing challenges for hydraulic fractures (HFs) to propagate through the formations, leading to weak fracture effects. To address this, this article adopts the finite element and cohesive force element methods to formulate a three-dimensional numerical model for hydraulic fracture (HF) propagation through layers, considering interlayer lithology and stress variations. The accuracy of the model was verified by physical experiments, and the one-factor analysis method was used to creatively reveal the complex mechanism of the effect of geological and engineering variables on the diffusion of HFs in continental shale reservoirs. The results show that high interlayer stress difference, high interlayer tensile strength difference, low interlayer Young’s modulus difference and large interlayer thickness are not conducive to the penetration of HFs, but increasing the injection rate and the viscosity of fracturing fluid can effectively improve the penetration of HFs. The influence ranking of each factor was determined using the grey relational degree analysis method: interlayer stress difference > interlayer Young’s modulus difference > interlayer tensile strength difference > interlayer thickness > injection rate > fracturing fluid viscosity.
Corrosion State Monitoring Based on Multi-Granularity Synergistic Learning of Acoustic Emission and Electrochemical Noise Signals
Authors: Wang Rui , Shan Guangbin , Qiu Feng , Zhu Linqi , Wang Kang , Meng Xianglong , Li Ruiqin , Song Kai , Chen Xu
Published: December 2024

Corrosion monitoring is crucial for ensuring the structural integrity of equipment. Acoustic emission (AE) and electrochemical noise (EN) have been proven to be highly effective for the detection of corrosion. Due to the complementary nature of these two techniques, previous studies have demonstrated that combining both signals can facilitate research on corrosion monitoring. However, current machine learning models have not yet been able to effectively integrate these two different modal types of signals. Therefore, a new deep learning framework, CorroNet, is designed to synergistically integrate AE and EN signals at the algorithmic level for the first time. The CorroNet leverages multimodal learning, enhances accuracy, and automates the monitoring process. During training, paired AE-EN data and unpaired EN data are used, with AE signals serving as anchors to help the model better align EN signals with the same corrosion stage. A new feature alignment loss function and a probability distribution consistency loss function are designed to facilitate more effective feature learning to improve classification performance. Experimental results demonstrate that CorroNet achieves superior accuracy in corrosion stage classification compared to other state-of-the-art models, with an overall accuracy of 97.01%. Importantly, CorroNet requires only EN signals during the testing phase, making it suitable for stable and continuous monitoring applications. This framework offers a promising solution for real-time corrosion detection and structural health monitoring.
From Microalgae to Biofuels: Investigating Valorization Pathways Towards Biorefinery Integration
Authors: Chatzimaliakas Panagiotis Fotios , Koutsaftis-Fragkos Ermis , Mai Sofia , Malamis Dimitris , Barampouti Elli Maria
Published: December 2024

The rapid growth of the world population led to an exponential growth in industrial activity all around the world. Consequently, CO2 emissions have risen almost 400% since 1950 due to human activities. In this context, microalgae biomass has emerged as a renewable and sustainable feedstock for producing third-generation biofuels. This study explores the laboratory-scale production of bioethanol and biomethane from dried algal biomass. The first step was to evaluate and optimize the production of glucose from the biomass. Thus, three different techniques with three different solvents were tested to identify the most effective and efficient in terms of saccharification yield. With the assistance of an autoclave or a high-temperature water bath and 0.2 M NaOH as a solvent, yields of 79.16 ± 3.03% and 85.73 ± 3.23% were achieved which correspond to 9.24 and 9.80 g/L of glucose, respectively. Furthermore, the most efficient method from the pretreatment step was chosen to carry out a factorial design to produce bioethanol. The experiments showed that the loading of cellulase was of crucial importance to the optimization of the process. Optimized ethanolic fermentation yielded ethanol concentrations up to 4.40 ± 0.28 g/L (76.12 ± 4.90%) (0.3 Μ NaOH, 750 μL/gcellulose and 65 μL/gstarch), demonstrating the critical role of cellulase loading. Biomethane potential (BMP) assays on fermentation residues showed increased yields compared to untreated feedstock, with a maximum methane yield of 217.88 ± 10.40 mL/gVS. Combined energy production from bioethanol and biomethane was calculated at up to 1044.48 kWh/tn of algae feedstock, with biomethane contributing 75.26% to the total output. These findings highlight the potential of integrated algae-based biorefineries to provide scalable and sustainable biofuel solutions, aligning with circular economy principles.
Modeling and Predicting Self-Organization in Dynamic Systems out of Thermodynamic Equilibrium: Part 1: Attractor, Mechanism and Power Law Scaling
Authors: Brouillet Matthew , Georgiev Georgi Yordanov
Published: December 2024

Self-organization in complex systems is a process associated with reduced internal entropy and the emergence of structures that may enable the system to function more effectively and robustly in its environment and in a more competitive way with other states of the system or with other systems. This phenomenon typically occurs in the presence of energy gradients, facilitating energy transfer and entropy production. As a dynamic process, self-organization is best studied using dynamic measures and principles. The principles of minimizing unit action, entropy, and information while maximizing their total values are proposed as some of the dynamic variational principles guiding self-organization. The least action principle (LAP) is the proposed driver for self-organization; however, it cannot operate in isolation; it requires the mechanism of feedback loops with the rest of the system’s characteristics to drive the process. Average action efficiency (AAE) is introduced as a potential quantitative measure of self-organization, reflecting the system’s efficiency as the ratio of events to total action per unit of time. Positive feedback loops link AAE to other system characteristics, potentially explaining power–law relationships, quantity–AAE transitions, and exponential growth patterns observed in complex systems. To explore this framework, we apply it to agent-based simulations of ants navigating between two locations on a 2D grid. The principles align with observed self-organization dynamics, and the results and comparisons with real-world data appear to support the model. By analyzing AAE, this study seeks to address fundamental questions about the nature of self-organization and system organization, such as “Why and how do complex systems self-organize? What is organization and how organized is a system?”. We present AAE for the discussed simulation and whenever no external forces act on the system. Given so many specific cases in nature, the method will need to be adapted to reflect their specific interactions. These findings suggest that the proposed models offer a useful perspective for understanding and potentially improving the design of complex systems.
Performance Evaluation of Modified Biochar as a Polycyclic Aromatic Hydrocarbon Adsorbent and Microbial-Immobilized Carrier
Authors: Geng Shuying , Mao Shushuai , Xu Guangming , Ding Aizhong , Chen Feiyong , Dou Junfeng , Fan Fuqiang
Published: December 2024

Herein, biochars derived from corn stalks, rice husks, and bamboo powder were modified by nitric acid oxidation and sodium hydroxide alkali activation to identify efficient and cost-effective polycyclic aromatic hydrocarbon-adsorbent and microbial-immobilized carriers. The surface characterization and adsorption investigation results suggested that acid/alkali modification promoted the phenanthrene removal ability in an aqueous solution of biochars via facilitating π–π/n–π electron donor–acceptor interactions, electrostatic interactions, hydrogen bonds, and hydrophobic interactions. Subsequently, the degrading bacteria Rhodococcus sp. DG1 was successfully immobilized on the rice husk-derived biochar with nitric acid oxidation (RBO), which exhibited the maximum phenanthrene adsorption efficiency (3818.99 µg·g−1), abundant surface functional groups, and a larger specific surface area (182.6 m2·g−1) and pore volume (0.141 m3·g−1). Degradation studies revealed that the microorganisms immobilized on RBO by the adsorption method yielded a significant phenanthrene removal rate of 80.15% after 30 days, which was 38.78% higher than that of the control. Conversely, the polymer gel network-based microenvironment in the microorganism-immobilized RBO by the combined adsorption–embedding method restricted the migration and diffusion of nutrients and pollutants in the reaction system. This study thus introduces an innovative modified biochar-based microbial immobilization technology characterized by a simple design, convenient operation, and high adsorption efficiency, offering valuable insights into material selection for PAH contamination bioremediation.
High-Precision Recognition Algorithm for Equipment Defects Based on Mask R-CNN Algorithm Framework in Power System
Authors: Xin Mingyong , Xu Changbao , Gao Jipu , Wang Yu , Wang Bo
Published: December 2024

In current engineering applications, target detection based on power vision neural networks has problems with low accuracy and difficult defect recognition. Thus, this paper proposes a high-precision substation equipment defect recognition algorithm based on the Mask R-CNN algorithm framework to achieve high-precision substation equipment defect monitoring. The effectiveness of the Mask R-CNN algorithm is compared and analyzed in substation equipment defect recognition and the applicability of the Mask R-CNN algorithm in edge computing. According to different types of substation equipment defect characteristics, substation equipment defect recognition guidelines were developed. The guideline helps to calibrate the existing training set and build defect recognition models for substation equipment based on different algorithms. In the end, the system based on a power edge vision neural network was built. The feasibility and accuracy of the algorithm was verified by model training and actual target detection results.
Redefining Leadership: The Role of Spirituality and Motherhood in Muslim Women’s Educational Leadership
Authors: Lahmar Fella
Published: December 2024

This study explores the perspectives and experiences of three Muslim female headteachers in Islamic schools in England, each with over twenty years of experience, to understand how they perceive and negotiate their leadership roles. Using Allama Muhammad Iqbal’s theory of agency and structure, nine semi-structured interviews were conducted in three phases: 2010–2012, and 2018–2020. The rich longitudinal data, despite the limited sample size, provided an in-depth understanding of emerging themes around Muslim women’s leadership in British Islamic schooling. Analysis reveals that these headteachers conceptualise leadership through the Islamic principles of imāmah (spiritual leadership), qiwāmah (guardianship), and amānah (trusteeship), emphasising ethical responsibility, continuous learning, and service-oriented leadership. Their leadership within this framework is neither submissive to men’s authority nor rivalling it but acts as an autonomous agency through the Tawḥīdi (Oneness of God) theological framework and akhlāq (ethical framework), defending chosen values within the Ibādah (worship; acts of devotion to God alone) context. Motherhood is seen as intrinsic to their leadership, with nurturing, guiding, and supporting roles extending from home to school, challenging the dichotomy between private and public spheres. This paper contends that the current educational leadership models are predominantly Western, failing to capture the unique experiences and perspectives of female Muslim leaders who reject framing their perspectives within feminist parameters. Advocating a decolonised approach, centring these women’s coherent religious conceptual frameworks, the study suggests that these leaders’ practices offer a unique perspective on educational leadership, blending spiritual, ethical, and communal responsibilities, and calls for further research to explore the identified themes in broader contexts.
Wittgenstein on the “Alien Will”: A Study of Compatibilism and Divine Influence
Authors: Mácha Jakub
Published: December 2024

In this article, I delve into Wittgenstein’s early manuscripts to examine the idea of an “alien will”, which may have been inspired by Schopenhauer and Weininger. By contrast with other interpretations, I treat this notion not as a metaphor but as the fundamental idea that the world is independent of an individual’s will and appears instead to be influenced by a quasi-divine, alien will. This alien will, distinct from personal will, could either coincide or conflict with an individual subject’s will, affecting their happiness. I argue that this (dis)agreement involves the modal properties of objects rather than being a matter of factual consistency. Ultimately, I position Wittgenstein’s views as a form of pre-emptive compatibilism, according to which divine will shapes human conditions without compromising free will. This contributes a significant perspective to debates in the philosophy of religion.
Influenza Virus-Associated Acute Necrotizing Encephalopathy in Two Young Children: Case Report
Authors: Largo Prisca , Arnone Olivia C. , Sacco Francesco , Cantalupo Gaetano , Biban Paolo
Published: December 2024

Background and Clinical Significance: Acute necrotizing encephalopathy (ANE) represents a severe complication, mainly described in children, of influenza virus infection. We report the cases of two young girls with ANE associated with influenza virus infection who were diagnosed by MRI cerebral scan. Case Presentation: A 7-year-old girl with a history of a previous episode of ANE presented with a worsening drowsy state and seizures. In the second case, an otherwise healthy 5-year-old girl presented with fever, seizures, and marked neurological deterioration. In both cases, nasopharyngeal swab testing was positive for influenza virus A, while cerebral MRI indicated ANE. Despite aggressive treatment with high-dose corticosteroids and a five-day course ofimmunoglobulins, the ultimate prognosis was poor in both patients. ANE is a serious complication of viral infections in children, with a high mortality rate and a broad spectrum of neurological sequelae. To date, the pathophysiology and management of influenza virus-induced ANE remain uncertain. Although ANE is usually sporadic, familial and recurrent cases have been reported, and anRAN-binding protein (RANBP2) mutation has occasionally been associated with its occurrence.Conclusions: Rapid recognition of neurological symptoms and suspicion of a viral trigger, especially in influenza-like illnesses, are both essential for the timely administration of effective therapy. Further research is needed to clarify the pathophysiology of ANE and establish the best therapeutic strategies to fight such a deadly disease.
Calibration and Performance Evaluation of Cost-Effective Capacitive Moisture Sensor in Slope Model Experiments
Authors: Hidayat Muhammad Nurjati , Hazarika Hemanta , Kanaya Haruichi
Published: December 2024

Understanding the factors that contribute to slope failures, such as soil saturation, is essential for mitigating rainfall-induced landslides. Cost-effective capacitive soil moisture sensors have the potential to be widely implemented across multiple sites for landslide early warning systems. However, these sensors need to be calibrated for specific applications to ensure high accuracy in readings. In this study, a soil-specific calibration was performed in a laboratory setting to integrate the soil moisture sensor with an automatic monitoring system using the Internet of Things (IoT). This research aims to evaluate a low-cost soil moisture sensor (SKU:SEN0193) and develop calibration equations for the purpose of slope model experiment under artificial rainfall condition using silica sand. The results indicate that a polynomial function is the best fit, with a coefficient of determination (R2) ranging from 0.918 to 0.983 and a root mean square error (RMSE) ranging from 1.171 to 2.488. The calibration equation was validated through slope model experiments, with soil samples taken from the models after the experiment finished. Overall, the moisture content readings from the sensors showed approximately a 12% deviation from the actual moisture content. The findings suggest that the cost-effective capacitive soil moisture sensor has the potential to be used for the development of landslide early warning system.
A Lightweight and Small Sample Bearing Fault Diagnosis Algorithm Based on Probabilistic Decoupling Knowledge Distillation and Meta-Learning
Authors: Luo Hao , Ren Tongli , Zhang Ying , Zhang Li
Published: December 2024

Rolling bearings play a crucial role in industrial equipment, and their failure is highly likely to cause a series of serious consequences. Traditional deep learning-based bearing fault diagnosis algorithms rely on large amounts of training data; training and inference processes consume significant computational resources. Thus, developing a lightweight and suitable fault diagnosis algorithm for small samples is particularly crucial. In this paper, we propose a bearing fault diagnosis algorithm based on probabilistic decoupling knowledge distillation and meta-learning (MIX-MPDKD). This algorithm is lightweight and deployable, performing well in small sample scenarios and effectively solving the deployment problem of large networks in resource-constrained environments. Firstly, our model utilizes the Model-Agnostic Meta-Learning algorithm to initialize the parameters of the teacher model and conduct efficient training. Subsequently, by employing the proposed probability-based decoupled knowledge distillation approach, the outstanding performance of the teacher model was imparted to the student model, enabling the student model to converge rapidly in the context of a small sample size. Finally, the Paderborn University dataset was used for meta-training, while the bearing dataset from Case Western Reserve University, along with our laboratory dataset, was used to validate the results. The experimental results demonstrate that the algorithm achieved satisfactory accuracy performance.
Enhancing Time Series Anomaly Detection: A Knowledge Distillation Approach with Image Transformation
Authors: Park Haiwoong , Jang Hyeryung
Published: December 2024

Anomaly detection is critical in safety-sensitive fields, but faces challenges from scarce abnormal data and costly expert labeling. Time series anomaly detection is relatively challenging due to its reliance on sequential data, which imposes high computational and memory costs. In particular, it is often composed of real-time collected data that tends to be noisy, making preprocessing an essential step. In contrast, image anomaly detection has leveraged advancements in technologies for analyzing spatial patterns and visual features, achieving high accuracy and promoting research aimed at improving efficiency. We propose a novel framework that bridges image anomaly detection with time series data. Using Gramian Angular Field (GAF) transformations, we convert time series into images and apply state-of-the-art techniques, Reverse Distillation (RD) and EfficientAD (EAD), for efficient and accurate anomaly detection. Tailored preprocessing and transformations further enhance performance and interoperability. When evaluated on the multivariate time series anomaly detection dataset Secure Water Treatment (SWaT) and the univariate datasets University of California, Riverside (UCR) and Numenta Anomaly Benchmark (NAB), our approach demonstrated high recall overall and achieved approximately 99% F1 scores on some univariate datasets, proving its effectiveness as a novel solution for time series anomaly detection.
A NIRS-Based Technique for Monitoring Brain Tissue Oxygenation in Stroke Patients
Authors: Gutierrez-Martinez Josefina , Vega-Martinez Gabriel , Toledo-Peral Cinthya Lourdes , Mercado-Gutierrez Jorge Airy , Quinzaños-Fresnedo Jimena
Published: December 2024

Stroke is a global health issue caused by reduced blood flow to the brain, which leads to severe motor disabilities. Measuring oxygen levels in the brain tissue is crucial for understanding the severity and evolution of stroke. While CT or fMRI scans are preferred for confirming a stroke due to their high sensitivity, Near-Infrared Spectroscopy (NIRS)-based systems could be an alternative for monitoring stroke evolution. This study explores the potential of fNIRS signals to assess brain tissue in chronic stroke patients along with rehabilitation therapy. To study the feasibility of this proposal, ten healthy subjects and three stroke patients participated. For signal acquisition, two NIRS sensors were placed on the forehead of the subjects, who were asked to remain in a resting state for 5 min, followed by a 30 s motor task for each hand, which consists of opening and closing the hand at a steady pace, with a 1 min rest period in between. Acomplete protocol for placing sensors and a signal processing algorithm are proposed. In healthy subjects, a measurable change in oxygen saturation was found, with statistically significant differences (females p = 0.016, males p = 0.005) between the resting-state and the hand movement conditions. This work showed the feasibility of the complete proposal, including the NIRS sensor, the placement, the tasks protocol, and signal processing, for monitoring the state of the brain tissue cerebral oxygenation in stroke patients undergoing rehabilitation therapy. Thus this is a non-invasive barin assessment test based on fNIRS with the potential to be implemented in non-controlled clinical environments.
Game-Theoretic Motion Planning with Perception Uncertainty and Right-of-Way Constraints
Authors: Panahandeh Pouya , Alghooneh Ahmad Reza , Pirani Mohammad , Fidan Baris , Khajepour Amir
Published: December 2024

This paper addresses two challenges in AV motion planning: adherence to right-of-way and handling uncertainties, using two game-theoretic frameworks, namely Stackelberg and Nash Bayesian (Bayesian). By modeling the interactions between road users as a hierarchical relationship, the proposed approach enables the AV to strategically optimize its trajectory while considering the actions and priorities of other road users. Additionally, the Bayesian equilibrium aspect of the framework incorporates probabilistic beliefs and updates them based on sensor measurements, allowing the AV to make informed decisions in the presence of uncertainty in the sensory system. Experimental assessments demonstrate the efficacy of the approach, emphasizing its ability to improve the reliability and adaptability of AV motion planning.
Analysis of Stability and Variability in Sensor Readings from a Vehicle Weigh-in-Motion Station
Authors: Ryguła Artur , Brzozowski Krzysztof , Grygierek Marcin , Socha Agnieszka
Published: December 2024

This study presents a detailed analysis of the stability of weigh-in-motion sensors used at vehicle weighing stations. The objective of this research was a long-term assessment of reading variability, with a particular focus on the sensors’ application in automated measurement stations. These investigations constitute a critical component of modern traffic management systems and vehicle overload control. The analysis covered the period from 2022 to 2024, incorporating data from vehicles participating in regular traffic as well as dedicated control runs using vehicles with known wheel and axle load distributions. The study also considered changes in road surface conditions, particularly rut depth, and their variations over the examined period. The findings revealed that, despite the lack of station calibration over the three-year period, the observed parameters exhibited only minor changes. These results confirm the high stability of the applied measurement system and its ability to maintain measurement accuracy over extended operational periods, which is essential for its practical application in real-world traffic conditions.
Safety of Immersive Virtual Reality for the Management of Parkinson’s Disease
Authors: Pimenta Silva Daniela , Pona-Ferreira Filipa , Santos Beatriz , Campo-Prieto Pablo , Bouça-Machado Raquel , Ferreira Joaquim J.
Published: December 2024

Virtual reality (VR) has been used in research and clinical practice in the management of Parkinson’s disease (PD), potentially enhancing physiotherapy. Adverse events (AEs) associated with VR applications in PD have been poorly explored. We conducted a randomized controlled trial to compare two 12-week interventions using physiotherapy and immersive VR, and analyzed the frequency and type of AEs occurring in 30 people with PD. We reported 144 AEs (8.4% of the sessions), predominantly classified as mild and unrelated to the interventions. Two were serious AEs, one leading to study discontinuation. Notably, discomfort/pain, motor fluctuations, and falls were the most frequently reported, accounting for 63% of the total AEs. Five falls were definitely associated with the ‘sense of presence’ provided by the fully immersive VR system, which underscores the necessity for careful game selection when designing interventions for PD. Motor fluctuations may have been associated with various factors, which merit further investigation. We also explored the role of SSQ as a measure of cybersickness in PD. In conclusion, it is important to closely monitor and characterize AEs to ensure safety and efficacy in clinical practice as AEs may be more common than previously recognized in VR interventions in PD.
A User Association and Resource Allocation Algorithm for UAV-Assisted Smart Grid
Authors: Wei Jianwei , Lei Yuzhu , Wen Zhiyi , Xiao Yongqing , Ma Pengcheng , Sun Lingtao , Su Lin
Published: December 2024

Recently, massive intelligent applications have emerged for the smart grid (SG), such as inspection and sensing. To support these applications, there have been high requirements on wireless communication for the SG, especially in remote areas. To tackle these challenges, a UAV-assisted heterogeneous wireless network is proposed in this paper for the SG, where multiple UAVs and a macro base station collaboratively provide a wide range of communication services. To further improve the communication capacity of this system, a joint user association and resource allocation algorithm is developed to maximize the total system throughput. To solve this problem, a matching algorithm is first proposed to solve the user association and subchannel assignment optimization problem. Then, the Lagrangian dual method is utilized to solve the power allocation problem. Finally, extensive simulations show that the proposed algorithm can effectively increase the user communication rate and enhance the capacity of the heterogeneous network for the SG.
p-CuO/n-ZnO Heterojunction Pyro-Phototronic Photodetector Controlled by CuO Preparation Parameters
Authors: Zhang Zhen , Li Fangpei , Peng Wenbo , Zhu Quanzhe , He Yongning
Published: December 2024

The combination of ZnO with narrow bandgap materials such as CuO is now a common method to synthesize high-performance optoelectronic devices. This study focuses on optimizing the performance of p-CuO/n-ZnO heterojunction pyroelectric photodetectors, fabricated through magnetron sputtering, by leveraging the pyro-phototronic effect. The devices’ photoresponse to UV (365 nm) and visible (405 nm) lasers is thoroughly examined. The results show that when the device performance is regulated by adjusting the three parameters—sputtering power, sputtering time, and sputtering oxygen–argon ratio—the optimal sputtering parameters should be as follows: sputtering power of 120 W, sputtering time of 15 min, and sputtering oxygen–argon ratio of 1:3. With the optimal sputtering parameters, the maximum responsivity of the pyroelectric effect and the traditional photovoltaic effect Rpyro+photo of the detector is 4.7 times that under the basic parameters, and the maximum responsivity of the traditional photovoltaic effect Rphoto is also 5.9 times that under the basic parameters. This study not only showcases the extensive potential of the pyro-phototronic effect in enhancing heterojunction photodetectors for high-performance photodetection but also provides some ideas for fabricating high-performance photodetectors.
Comparative Analysis of Physiological Vergence Angle Calculations from Objective Measurements of Gaze Position
Authors: Krauze Linda , Panke Karola , Krumina Gunta , Pladere Tatjana
Published: December 2024

Eccentric photorefractometry is widely used to measure eye refraction, accommodation, gaze position, and pupil size. While the individual calibration of refraction and accommodation data has been extensively studied, gaze measurements have received less attention. PowerRef 3 does not incorporate individual calibration for gaze measurements, resulting in a divergent offset between the measured and expected gaze positions. To address this, we proposed two methods to calculate the physiological vergence angle based on the visual vergence data obtained from PowerRef 3. Twenty-three participants aged 25 ± 4 years viewed Maltese cross stimuli at distances of 25, 30, 50, 70, and 600 cm. The expected vergence angles were calculated considering the individual interpupillary distance at far. Our results demonstrate that the PowerRef 3 gaze data deviated from the expected vergence angles by 9.64 ± 2.73° at 25 cm and 9.25 ± 3.52° at 6 m. The kappa angle calibration method reduced the discrepancy to 3.93 ± 1.19° at 25 cm and 3.70 ± 0.36° at 600 cm, whereas the linear regression method further improved the accuracy to 3.30 ± 0.86° at 25 cm and 0.26 ± 0.01° at 600 cm. Both methods improved the gaze results, with the linear regression calibration method showing greater overall accuracy.