bluuebunny/crossref_metadata_2025 huggingface dataset:
CL-SR: Boosting Imbalanced Image Classification with Contrastive Learning and Synthetic Minority Oversampling Technique Based on Rough Set Theory Integration
Authors: Gao Xiaoling , Jamil Nursuriati , Ramli Muhammad Izzad
Published: November 2024

Image recognition models often struggle with class imbalance, which can impede their performance. To overcome this issue, researchers have extensively used resampling methods, traditionally focused on tabular datasets. In contrast to the original method, which generates data at the data level, this paper introduces a novel strategy that combines contrastive learning with the Synthetic Minority Oversampling Technique based on Rough Set Theory (SMOTE-RSB) specifically tailored for imbalanced image datasets. Our method leverages contrastive learning to refine representation learning and balance features, thus effectively mitigating the challenges of imbalanced image classification. We begin by extracting features using a pre-trained contrastive learning encoder. Subsequently, SMOTE-RSB is applied to these features to augment underrepresented classes and reduce irrelevant features. We evaluated our approach on several modified benchmark datasets, including CIFAR-10, SVHN, and ImageNet-LT, achieving notable improvements: an F1 score of 72.43% and a Gmean of 82.53% on the CIFAR-10 long-tailed dataset, F1 scores up to 79.57% and Gmean of 88.20% on various SVHN datasets, and a Top-1 accuracy of 68.67% on ImageNet-LT. Both qualitative and quantitative results confirm the effectiveness of our method in managing imbalances in image datasets. Additional ablation studies exploring various contrastive learning models and oversampling techniques highlight the flexibility and efficiency of our approach across different settings, underscoring its significant potential for enhancing imbalanced image classification.
Advanced Spectroscopic Characterization, Antioxidant and Antibacterial Activity Evaluation, and Trace Metal Analyses of Essential Oils from Star Anise, Nutmeg, Clove, Oregano, Bay Leaves, and Lemon Peel
Authors: Sander Aleksandra , Bival Štefan Maja , Radetić Antonela , Petračić Ana , Kučić Grgić Dajana , Cvetnić Matija , Parlov Vuković Jelena
Published: November 2024

Essential oils from star anise, nutmeg, clove buds, oregano, bay leaves, and lemon peel were extracted via hydrodistillation. GC-MS, UV–Vis, FTIR, and 1H NMR spectroscopy were used to identify the major compounds (trans-anethole, sabinene, eugenol, carvacrol, eucalyptol and limonene, for star anise, nutmeg, clove buds, oregano, bay leaves, and lemon peel essential oil, respectively), revealing that the spectra were dominated by the oils’ primary constituents. Antioxidant activity was assessed using DPPH and ABTS assays, demonstrating high radical scavenging ability, especially for bay leaf and oregano oils. Despite phenolic content being correlated with antioxidant activity, discrepancies were found, suggesting that non-phenolic compounds and synergism also play a role. Antibacterial evaluation showed significant activity for bay leaf and oregano oils, particularly against Klebsiella pneumoniae and Pseudomonas aeruginosa, due to phenolic and terpene compounds. The presence of trace metals in the oils, including those with antimicrobial and antioxidant properties such as Cu, and Zn, was also analyzed. The risk assessment showed that toxic metals were below harmful thresholds.
A New Approach to 3D Facilities Management in Buildings Using GIS and BIM Integration: A Case Study Application
Authors: Carrasco César A. , Lombillo Ignacio , Sánchez-Espeso Javier M. , Balbás Francisco Javier
Published: November 2024

This research seeks to advance the technological process of 3D digitization in built environments and streamline management processes in the construction sector through digital methodologies. To this end, an integration framework is proposed that combines geographic information systems (GISs) and building information modeling (BIM) digital models, specifically for simulating building facilities maintenance management. Although the proposed methodology is applicable across various geographical contexts and building typologies, to ensure clarity in its development, it was applied to a specific case study. For this purpose, a 3D GIS model was created for one of the campuses of the University of Cantabria in Santander, Spain, along with a BIM model for one of its university buildings. Using these integrated models, facility management was simulated within a 3D environment via a computerized maintenance management system (CMMS). The findings indicated that GIS and BIM digital models could indeed be integrated through straightforward linking mechanisms without compromising the efficiency of information synchronization and management. When comparing 2D facility management approaches with 3D formats, the advantages of 3D visualization became clear. This three-dimensional representation allowed for a more intuitive understanding of spatial dynamics and interactions, facilitating quicker identification of potential issues and more efficient maintenance operations. Consequently, integrating these advanced digital models not only optimizes operational efficiency but also fosters a collaborative environment, fundamentally transforming building facilities management.
Simultaneous Vibration and Temperature Real-Time Monitoring Using Single Fiber Bragg Grating and Free Space Optics
Authors: Yao Cheng-Kai , Kumar Pradeep , Liu Bing-Xian , Dehnaw Amare Mulatie , Peng Peng-Chun
Published: November 2024

Simultaneous monitoring of temperature and vibration of electromechanical systems, public buildings, and volcanic terrain is an important indicator of preventing accidents. This work showcases the simultaneous temperature and vibration measurement using a single-fiber Bragg grating (FBG) sensor. The concurrent interrogation of vibration and temperature by the FBG sensing system can be integrated with free space optics (FSO), which saves on the costs associated with fiber optic cables and overcomes terrain barriers. Furthermore, the real-time measured vibration frequencies and different temperature levels can be recognized by a deep neural network (DNN) sequential model. In addition to the FSO support, the sensing system can be arranged in multiple sensing locations to form a wide range of measurements, offering a highly cost-effective solution.
Development of a Multi-Source Satellite Fusion Method for XCH4 Product Generation in Oil and Gas Production Areas
Authors: Fan Lu , Wan Yong , Dai Yongshou
Published: November 2024

Methane (CH4) is the second-largest greenhouse gas contributing to global climate warming. As of 2022, methane emissions from the oil and gas industry amounted to 3.586 million tons, representing 13.24% of total methane emissions and ranking second among all methane emission sources. To effectively control methane emissions in oilfield regions, this study proposes a multi-source remote sensing data fusion method based on the concept of data fusion, targeting high-emission areas such as oil and gas fields. The aim is to construct an XCH4 remote sensing dataset that meets the requirements for high resolution, wide coverage, and high accuracy. Initially, XCH4 data products from the GOSAT satellite and the TROPOMI sensor are matched both spatially and temporally. Subsequently, variables such as longitude, latitude, aerosol optical depth, surface albedo, digital elevation model (DEM), and month are incorporated. Using a local random forest (LRF) model for fusion, the resulting product combines the high accuracy of GOSAT data with the wide coverage of TROPOMI data. On this basis, ΔXCH4 is derived using GF-5. Combined with the GFEI prior emission inventory, the high-precision fusion dataset output by the LRF model is redistributed grid by grid in oilfield areas, producing a 1 km resolution XCH4 grid product, thereby constructing a high-precision, high-resolution dataset for oilfield regions. Finally, the challenges that emerged from the study were discussed and summarized, and it was envisioned that, in the future, with the advancement of satellite technology and algorithms, it would be possible to obtain more accurate and high-resolution datasets of methane concentration and apply such datasets to a wide range of fields, with the expectation that significant contributions could be made to reducing methane emissions and combating climate change.
Stability of Feature Selection in Multi-Omics Data Analysis
Authors: Łukaszuk Tomasz , Krawczuk Jerzy , Żyła Kamil , Kęsik Jacek
Published: November 2024

In the rapidly evolving field of multi-omics data analysis, understanding the stability of feature selection is critical for reliable biomarker discovery and clinical applications. This study investigates the stability of feature-selection methods across various cancer types by utilizing 15 datasets from The Cancer Genome Atlas (TCGA). We employed classifiers with embedded feature selection, including Support Vector Machines (SVM), Logistic Regression (LR), and Lasso regression, each incorporating L1 regularization. Through a comprehensive evaluation using five-fold cross-validation, we measured feature-selection stability and assessed the accuracy of predictions regarding TP53 mutations, a known indicator of poor clinical outcomes in cancer patients. All three classifiers demonstrated optimal feature-selection stability, measured by the Nogueira metric, with higher regularization (fewer selected features), while lower regularization generally resulted in decreased stability across all omics layers. Our findings indicate differences in feature stability across the various omics layers; mirna consistently exhibited the highest stability across classifiers, while the mutation and rna layers were generally less stable, particularly with lower regularization. This work highlights the importance of careful feature selection and validation in high-dimensional datasets to enhance the robustness and reliability of multi-omics analyses.
Improved Remote Photoplethysmography Using Machine Learning-Based Filter Bank
Authors: Lee Jukyung , Joo Hyosung , Woo Jihwan
Published: November 2024

Remote photoplethysmography (rPPG) is a non-contact technology that monitors heart activity by detecting subtle color changes within the facial blood vessels. It provides an unconstrained and unconscious approach that can be widely applied to health monitoring systems. In recent years, research has been actively conducted to improve rPPG signals and to extract significant information from facial videos. However, rPPG can be vulnerable to degradation due to changes in the illumination and motion of a subject, and overcoming these challenges remains difficult. In this study, we propose a machine learning-based filter bank (MLFB) noise reduction algorithm to improve the quality of rPPG signals. The MLFB algorithm determines the optimal spectral band for extracting information on cardiovascular activity and reconstructing an rPPG signal using a support vector machine. The proposed approach was validated with an open dataset, achieving a 35.5% (i.e., resulting in a mean absolute error of 2.5 beats per minute) higher accuracy than those of conventional methods. The proposed algorithm can be integrated into various rPPG algorithms for the pre-processing of RGB signals. Moreover, its computational efficiency is expected to enable straightforward implementation in system development, making it broadly applicable across the healthcare field.
Influence of Particulate Matter and Carbon Dioxide on Students’ Emotions in a Smart Classroom
Authors: Fretes Gabriela , Llurba Cèlia , Palau Ramon , Rosell-Llompart Joan
Published: November 2024

The effects of air quality on health and cognition are well documented, but few studies have focused on its impact on emotions, leaving this area underexplored. This study investigates the influence of environmental factors—specifically particulate matter (PM1, PM2.5, and PM10) and carbon dioxide (CO2)—on students’ basic emotions in secondary school classrooms. For the collection of environmental data, we used low-cost sensors, which were carefully calibrated to ensure acceptable accuracy for monitoring air quality variables, despite inherent precision limitations compared to traditional sensors. Emotions were recorded via camera and analyzed using a custom-developed code. Based on these data, we found significant but modest correlations, such as the negative correlation between PM levels and happiness, and positive correlations of CO2 concentrations with fear and disgust. The regression models explained between 36% and 62% of the variance in emotions like neutrality, sadness, fear, and happiness, highlighting nonlinear relationships in some cases. These findings underscore the need for improved classroom environmental management, including the implementation of real-time air quality monitoring systems. Such systems would enable schools to mitigate the negative emotional effects of poor air quality, contributing to healthier and more conducive learning environments. Future research should explore the combined effects of multiple environmental factors to further understand their impact on student well-being.
A New Approach to Characterize Superplastic Materials from Free-Forming Test and Inverse Analysis
Authors: Giuliano Gillo , Polini Wilma
Published: November 2024

For about 60 years, the aerospace industry has been strongly interested in superplastic forming processes to produce extremely light and complex-shaped components. Superplastic characteristics are found in lightweight metallic materials such as titanium-based, aluminum-based, and, more recently, magnesium-based alloys. Since the high ductility exhibited by superplastic materials is two orders of magnitude higher than that of conventional materials, complex-shaped components can be obtained. If made with conventional materials, they require expensive assembly operations. The behaviour of superplastic materials is summarized by a constitutive equation commonly obtained via tensile testing that subjects the tested material to a one-dimensional stress state. On the contrary, free-forming tests allows us to test the material by subjecting it to a stress state similar to that determined during a real superplastic-forming process. The aim of this work is to define the characteristic parameters of superplastic materials by free-forming tests. The behaviour of superplastic materials is commonly modelled using a power law which puts the material into a stress-to-strain-rate relationship. This law needs to identify two parameters characterizing superplastic materials: the strain rate sensitivity index and the strength coefficient. In this work, a new procedure is presented that implies the two material parameters vary with strain. It allows for a reduction in the number of constants needed to determine the material constitutive equation, thus requiring low simulation time compared to models that adopt the multiple-objective optimization based on genetic algorithms (GAs). It is more suitable to be used in the industrial field. Furthermore, the proposed procedure is compared with a conventional procedure which is also based on the inverse analysis carried out through the use of a finite element analysis. The results of the conventional procedure, based on the inverse analysis, which is conducted through the use of a finite element analysis, are used to calculate the material constants, and are compared with those coming from the procedure proposed in this work. The proposed procedure appears equally simple and gives more accurate results compared to the conventional procedure. In fact, the maximum percentage error, regarding the prediction of the forming times of a free-forming process, was reduced from 20% to 8%. The development of the proposed procedure, as well as the comparison of the results with a conventional procedure, required the development of an experimental activity. This activity consists of free-forming tests conducted at a constant pressure (the pressures employed vary from 0.2 to 0.4 MPa), at a temperature of 753 K, and on circular sheets (thickness 1.0 mm and radius 40 mm) in superplastic magnesium alloy AZ31.
Mutual Neutralization in Collisions of Li+ with O−
Authors: Larson Åsa , Orel Ann E.
Published: November 2024

The total and differential cross-sections and final state distribution for mutual neutralization in collisions of Li+ with O− were calculated using an ab initio quantum mechanical approach based on potential energy curves and non-adiabatic coupling elements computed with the multi-reference configuration interaction method. The final state distributions favored channels with excited oxygen states, indicating a strong effect of electron correlation, and the electron transfer could not be described by a simple one-electron exchange process.
Critical Impact of Isospin Asymmetry in Elucidating Magicity Across Isotonic Chains of Different Mass Regions Using Relativistic Energy Density Functional
Authors: Yadav Praveen K. , Biswal N. , Panda R. N. , Mishra S. , Kumar Raj , Bhuyan M.
Published: November 2024

This study provides a comprehensive examination of the surface properties—particularly the symmetry energy and its contributing components—of isotonic chains across various mass ranges, including light, medium, heavy, and superheavy nuclei. We establish a correlation between nuclear symmetry energy and isospin asymmetry in different mass regions along isotonic chains with magic and semi-magic neutron numbers of N = 20, 40, 82, 126, and 172. Our approach integrates the coherent density fluctuation model within the relativistic mean-field (RMF) framework, utilizing both the non-linear NL3 and density-dependent DD-ME2 parameter sets. The methodology employs the Brueckner energy density functional in conjunction with our recently developed relativistic energy density functional (relativistic-EDF). The relativistic parameterization of the EDF at local density facilitates a consistent exploration of isospin-dependent surface properties across the nuclear landscape. In the present work, we successfully reproduce established shell closures and demonstrate that the relativistic approach yields significantly improved predictions for recognized magic numbers, particularly Z = 28 and 50. Additionally, we present compelling evidence for the presence of novel shell and sub-shell closures, specifically at Z = 34, 58, 92, and 118. These findings contribute to a nuanced understanding of nuclear surface properties while serving as a benchmark for future investigations and validations of nuclear models.
Simultaneous Method for Solving Certain Systems of Matrix Equations with Two Unknowns
Authors: Stanimirović Predrag S. , Ćirić Miroslav , Mourtas Spyridon D. , Milovanović Gradimir V. , Petrović Milena J.
Published: November 2024

Quantitative bisimulations between weighted finite automata are defined as solutions of certain systems of matrix-vector inequalities and equations. In the context of fuzzy automata and max-plus automata, testing the existence of bisimulations and their computing are performed through a sequence of matrices that is built member by member, whereby the next member of the sequence is obtained by solving a particular system of linear matrix-vector inequalities and equations in which the previously computed member appears. By modifying the systems that define bisimulations, systems of matrix-vector inequalities and equations with k unknowns are obtained. Solutions of such systems, in the case of existence, witness to the existence of a certain type of partial equivalence, where it is not required that the word functions computed by two WFAs match on all input words, but only on all input words whose lengths do not exceed k. Solutions of these new systems represent finite sequences of matrices which, in the context of fuzzy automata and max-plus automata, are also computed sequentially, member by member. Here we deal with those systems in the context of WFAs over the field of real numbers and propose a different approach, where all members of the sequence are computed simultaneously. More precisely, we apply a simultaneous approach in solving the corresponding systems of matrix-vector equations with two unknowns. Zeroing neural network (ZNN) neuro-dynamical systems for approximating solutions of heterotypic bisimulations are proposed. Numerical simulations are performed for various random initial states and comparison with the Matlab, linear programming solver linprog, and the pseudoinverse solution generated by the standard function pinv is given.
On Schur Forms for Matrices with Simple Eigenvalues
Authors: Konstantinov Mihail Mihaylov , Petkov Petko Hristov
Published: November 2024

In this paper, we consider various aspects of the Schur problem for a square complex matrix A, namely the similarity unitary transformation of A into upper triangular form containing the eigenvalues of A on its diagonal. Since the profound work of I. Schur published in 1909, this has become a fundamental issue in the theory and applications of matrices. Nevertheless, certain details concerning the Schur problem need further clarification, especially in connection with the perturbation analysis of the Schur decomposition relative to perturbations in the matrix A. We consider both canonical and condensed Schur forms. Special attention is paid to matrices with simple eigenvalues. Some new concepts, such as quasi-Schur forms and diagonally spectral matrices, are also introduced and studied.
Understanding Wood Polysaccharide Depolymerization and Denaturation Under Different Toasting Conditions Through Analysis of Sugars Extracted from French Oak Chips
Authors: Kainuma Genki , Mochizuki Ayano , Watanabe-Saito Fumie , Hisamoto Masashi , Kusumoto Norihisa , de Revel Gilles , Okuda Tohru
Published: November 2024

By analyzing the sugars extracted from oak chips toasted at various temperatures (180 to 280 °C) for various durations (10 to 30 min) in a model wine, we examined how wood polysaccharides are affected by toasting. The responses induced by toasting significantly differed among the major sugars constituting the wood. The main components of wood polysaccharides—glucose, arabinose, galactose, and xylose—were analyzed, and the results showed that galactose had the highest extraction amounts at around 220 °C of toasting, xylose at around 240 °C, and glucose at around 280 °C. On the other hand, the extraction amounts decreased with longer toasting durations. These results suggest that wood polysaccharides undergo temperature-dependent depolymerization while simultaneously undergoing denaturation. In addition, these depolymerization reactions tended to shift towards lower temperatures with longer toasting durations. The results of this study elucidate the chemical changes that occur within the wood during the toasting of oak chips and highlight the importance of the relationship between toasting temperature and duration. Additionally, this study demonstrated that by using the sugars extracted from oak chips as indicators, it is possible to partially visualize the reactions that occur within oak chips during toasting.
A Comparison of Contractile Properties and Acute Muscle Fatigue Response in Adult Females with Non-Specific Chronic Low Back Pain
Authors: Lee Hyungwoo , Lee Seungwon , Kim Chanki , Jeon Kyoungkyu
Published: November 2024

This study examined the erector spinae contractile properties, trunk isokinetic strength, and differences in acute muscle fatigue response after exercise in young females with and without non-specific chronic low back pain (NSCLBP). This study evaluated participants using tensiomyography and isokinetic trunk strength tests. An independent t-test compared the control group and the NSCLBP group, while a two-way mixed ANOVA analyzed differences in the erector spinae’s acute muscle fatigue response before and after exercise within and between groups. The results of the tensiomyography indicated that the NSCLBP group exhibited significantly lower Dm and Vc (p < 0.05) compared to the control group, while Tc showed no significant difference between groups. Significant differences in all variables were observed between the groups in the isokinetic trunk strength test (p < 0.05). Furthermore, the two-way mixed ANOVA revealed significant group main effects in Dm and Vc of the erector spinae (p < 0.05). This study found that non-specific chronic low back pain is linked to a decrease in Dm, Vc, and trunk isokinetic strength in both extensor and flexor muscles. It suggests that future research should further investigate the acute muscle fatigue response in individuals with and without NSCLBP.
From Green Chemistry to Healthy Environments: Silver Nanoparticles as a Dual Antioxidant and Antibacterial Agents for Advancing Biomedicine and Sustainable Wastewater Treatment
Authors: Moussa Hamza , Hamid Sarah , Mameri Amal , Lekmine Sabrina , Tahraoui Hichem , Kebir Mohammed , Touzout Nabil , Dahmoune Farid , Ola Mohammad Shamsul , Zhang Jie , Amrane Abdeltif
Published: November 2024

The green synthesis of silver nanoparticles (AgNPs) using plant extracts is an eco-friendly method with potential for biomedical and environmental applications. This study aims to synthesize silver nanoparticles (SO-AgNPs) using Salvia officinalis L. extract and evaluate their antioxidant and antibacterial properties, positioning them as candidates for applications in sustainable biomedicine and wastewater treatment. S. officinalis L. extract was used to synthesize AgNPs under optimized conditions, with a 10% extract/AgNO₃ ratio and a reaction time of 180 min. The SO-AgNPs were characterized using ATR-FTIR, XRD, SEM, DLS, and Zeta potential analysis. The antioxidant activity of the extract and SO-AgNPs was evaluated using ABTS+• and DPPH• radical scavenging assays. Antibacterial activity was tested against 11 bacterial strains and bacteria isolated from industrial effluent, with minimal inhibitory concentrations (MIC) determined for both the extract and SO-AgNPs. The SO-AgNPs demonstrated potent antioxidant activity, with IC₅₀ values of 0.233 mg/mL and 0.305 mg/mL in the ABTS+• assay, and 0.173 mg/mL and 0.185 mg/mL in the DPPH• assay for the extract and SO-AgNPs, respectively. Antibacterial testing showed MIC values of 0.25 mg/mL for SO-AgNPs and between 3.12 and 6.25 mg/mL for S. officinalis L. extract against E. coli, P. aeruginosa, A. baumannii, MRSA, B. cereus, and S. epidermidis. For bacteria isolated from industrial effluent, the MIC values were 0.125 mg/mL for SO-AgNPs and 0.5 mg/mL for the extract. This study highlights the dual antioxidant and antibacterial capabilities of S. officinalis L. extract and SO-AgNPs, demonstrating their potential for use in both biomedical and environmental applications, including wastewater treatment.
Isoliquiritigenin Prevents the Development of Nephropathy by an HFD in Rats Through the Induction of Antioxidant Production and Inhibition of the MD-2/TLR4/NF-κB Pathway
Authors: Yahya Mohammed Abdo , Alshammari Ghedeir M. , Osman Magdi A. , Al-Harbi Laila Naif , Alotaibi Setah Naif
Published: November 2024

This study tested the ISL against renal damage induced by a high-fat diet (HFD) and explored its underlying mechanisms. Adult male rats were assigned to four groups: (1) control on a standard diet (STD), (2) ISL on STD (30 mg/kg), (3) HFD, and (4) HFD + ISL (30 mg/kg). After 12 weeks of dietary intervention, ISL treatment led to significant reductions in body weight gain, visceral fat, and glucose and insulin levels in HFD-fed rats. Notably, ISL decreased serum urea and creatinine, increased serum albumin, and improved urinary profiles by lowering the urinary albumin and the albumin/creatinine ratio. Histological analyses revealed that ISL enhanced the glomerular structure and mitigated tubular damage, as evidenced by reduced urinary excretion of the kidney injury markers NGAL and KIM-1. Additionally, ISL significantly lowered cholesterol, triglycerides, and free fatty acids in both the control and HFD groups while also decreasing oxidized low-density lipoproteins (ox-LDLs) and malondialdehyde (MDA). Importantly, ISL enhanced renal antioxidant levels, increasing glutathione (GSH), superoxide dismutase (SOD), and catalase (CAT). Moreover, ISL downregulated mRNA levels of MD-2, Toll-like receptor-4 (TLR-4), and NF-κB, leading to reduced NF-κB p65 levels in renal tissues. In conclusion, ISL offers substantial protection against HFD-induced renal toxicity through mechanisms that attenuate metabolic stress, enhance antioxidant defenses, and inhibit the MD-2/TLR4/NF-κB inflammatory pathway.
Diagnosis and Management of Mitochondrial Encephalopathy, Lactic Acidosis, and Stroke-like Episodes Syndrome
Authors: Na Ji-Hoon , Lee Young-Mock
Published: November 2024

Mitochondrial encephalopathy, lactic acidosis, and stroke-like episodes (MELAS) syndrome is a complex mitochondrial disorder characterized by a wide range of systemic manifestations. Key clinical features include recurrent stroke-like episodes, seizures, lactic acidosis, muscle weakness, exercise intolerance, sensorineural hearing loss, diabetes, and progressive neurological decline. MELAS is most commonly associated with mutations in mitochondrial DNA, particularly the m.3243A>G mutation in the MT-TL1 gene, which encodes tRNALeu (CUR). These mutations impair mitochondrial protein synthesis, leading to defective oxidative phosphorylation and energy failure at the cellular level. The clinical presentation and severity vary widely among patients, but the syndrome often results in significant morbidity and reduced life expectancy because of progressive neurological deterioration. Current management is largely focused on conservative care, including anti-seizure medications, arginine or citrulline supplementation, high-dose taurine, and dietary therapies. However, these therapies do not address the underlying genetic mutations, leaving many patients with substantial disease burden. Emerging experimental treatments, such as gene therapy and mitochondrial replacement techniques, aim to correct the underlying genetic defects and offer potential curative strategies. Further research is essential to understand the pathophysiology of MELAS, optimize current therapies, and develop novel treatments that may significantly improve patient outcomes and extend survival.
D-Dimers and MPO Are No Suitable Biomarkers for Application in Abdominal Aortic Aneurysm (AAA) Surveillance in a Real-World Setting of Vascular Surgery Patients
Authors: Siegrist Hans , Spieler Anja , Peters Andreas S. , Passek Karola H. , Böckler Dittmar , Dihlmann Susanne
Published: November 2024

There is currently no clinically valid biomarker for predicting the growth and prognosis of abdominal aortic aneurysms (AAA). The most promising candidates with the highest diagnostic values are plasma D-dimers and markers of activated neutrophils, i.e., myeloperoxidase (MPO) or cell-free DNA. So far, case-control studies on these markers have been performed almost exclusively using healthy individuals as controls. To validate the value of these markers in the clinical setting of a vascular surgery department, we analysed the diagnostic and prognostic potential of plasma D-dimers and MPO in 177 AAA patients versus 138 non-AAA patients with different vascular diseases. Significantly elevated levels of D-dimers were recorded for AAA patients compared with non-AAA patients, although the difference between the two groups was significantly smaller than that in other studies comparing AAA patients with healthy controls. Surprisingly, MPO levels were significantly higher in non-AAA patients than in those with AAA. After adjusting for the confounding factors of sex, peripheral artery disease (PAD) and internal carotid stenosis in multivariate regression models, neither D-dimers nor MPO remained independent correlates of AAA. In contrast, D-dimer plasma levels correlated well with the maximal aortic diameter. Combined analysis of D-dimers and circulating cell-free DNA levels derived from a previous study failed to improve the predictive values for the maximal aortic diameter. In conclusion, our data show that D-dimers and MPO are not suitable biomarkers for monitoring AAA in a real-world setting of mixed vascular surgery patients.
Progressive Cachexia: Tuberculosis, Cancer, or Thyrotoxicosis? Disease-Directed Therapy and Atypical Courses of Autoimmune and Malignant Thyroid Diseases in a High Specialization Era: Case-Control Study with a Critical Literature Review
Authors: Zdziarski Przemyslaw , Sroka Zbigniew
Published: November 2024

Background. Critical and progressive cachexia may be observed in numerous medical disciplines, but in patients with various diseases, several pathways overlap (endocrine, inflammatory and kidney diseases, heart failure, cancer). Methods. Unlike numerous cohort studies that examine thyroid cancer and risk factors, a different method was used to avoid bias and analyze the sequence of events, i.e., the pathway. A case-control analysis is presented on patients with initial immune-mediated thyroiditis complicated by cachexia, presenting pulmonary pathology coexisting with opportunistic infection, and ultimately diagnosed with cancer (TC—thyroid cancer, misdiagnosed as lung cancer). Results. Contrary to other patients with lung cancer, the presented patients were not active smokers and exclusively women who developed cachexia with existing autoimmune processes in the first phase. Furthermore, the coexistence of short overall survival without cancer progression in the most seriously ill patients, as well as correlation with sex (contrary to history of smoking) and predisposition to mycobacterial disease, are very suggestive. Although we describe three different autoimmune conditions (de Quervain’s, Graves’, and atrophic thyroiditis), disturbances in calcium and metabolic homeostasis, under the influence of hormonal and inflammatory changes, are crucial factors of cachexia and prognosis. Conclusions. The unique sequence sheds light on immune-mediated thyroid disease as a subclinical paraneoplastic process modified by various therapeutic regimens. However, it is also associated with cachexia, systemic consequences, and atypical sequelae, which require a holistic approach. The differential diagnosis of severe cachexia, adenocarcinoma with pulmonary localization, and tuberculosis reactivation requires an analysis of immunological and genetic backgrounds. Contrary to highly specialized teams (e.g., lung cancer units), immunotherapy and general medicine in aging populations require a multidisciplinary, holistic, and inquiring approach. The lack of differentiation, confusing biases, and discrepancies in the literature are the main obstacles to statistical research, limiting findings to correlations of common factors only. Time-lapse case studies such as this one may be among the first to build evidence of a pathway and an association between inflammatory and endocrine imbalances in cancer cachexia.
The Effect of Physical Activity Interventions on Executive Function in Overweight and Obese Adults: A Systematic Review
Authors: Chávez-Hernández María Elena , De La Torre Lizbeth , Rodríguez-Serrano Luis Miguel , Wöbbeking-Sánchez Marina
Published: November 2024

Background/objectives: Overweight and obesity are global public health problems associated with chronic disease and mental health. Physical activity (PA) is essential throughout a person’s life; an active lifestyle helps people to live healthier lives and improve their functional and mental abilities, such as executive function (EF). This systematic review aimed to analyze the evidence on the effects of PA on EF in overweight and/or obese adults (≥18 years old). Methods: Records from the PubMed, ScienceDirect, and JSTOR databases were searched and, following the PRISMA guidelines, seven studies were included in the present systematic review. Risk of bias was assessed using the National Institute of Health Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Results from the studies included indicate that acute, short-term, and long-term PA interventions are an effective strategy to improve inhibitory control, working memory, and processing speed in overweight and obese adults. Furthermore, evidence indicates that EF can be effective as a measure to predict adherence to PA programs and weight loss. Conclusions: Exercise and physical activity interventions are a promising therapeutic strategy to promote weight loss and improve EF in adults with overweight and obesity. Additionally, EF may be further explored as a predictor of healthy aging due to the choices made throughout life and the long-term benefits that result.
Arrested Coalescence: A Tool to Explore Tissue Rheology
Authors: Samatas Sotiris , Planasdemunt-Hospital Martí , Oriola David
Published: November 2024

Tissue spheroids are self-organised 3D cellular aggregates that serve as a versatile platform in tissue engineering. While numerous high-throughput methods exist to characterise the cellular function of tissue spheroids, equivalent techniques for the mechanical characterisation are still lacking. In this review, we focus on tissue fusion— a simple, fast, and inexpensive method to characterise the rheology of tissue spheroids. We begin by discussing the implications of tissue rheology in development and disease, followed by a detailed explanation of how the phenomenon of arrested coalescence can be used to explore the rheology of tissue spheroids. Finally, we present different theoretical models that, when combined with experimental data, allow us to extract rheological information.
Overview of Gas-Generating-Reaction-Based Immunoassays
Authors: Yu Zhao-Jiang , Deng De-Hua , Liang Si-Rui , Huang Ya-Liang , Yi Xin-Yao
Published: November 2024

Point-of-care (POC) immunoassays have become convincing alternatives to traditional immunosensing methods for the sensitive and real-time detection of targets. Immunoassays based on gas-generating reactions were recently developed and have been used in various fields due to their advantages, such as rapid measurement, direct reading, simple operation, and low cost. Enzymes or nanoparticles modified with antibodies can effectively catalyze gas-generating reactions and convert immunorecognition events into gas pressure signals, which can be easily recorded by multifunctional portable devices. This article summarizes the advances in gas-generating-reaction-based immunoassays, according to different types of signal output systems, including distance-based readout, pressure differential, visualized detection, and thermal measurement. The review mainly focuses on the role of photothermal materials and the working principle of immunoassays. In addition, the challenges and prospects for the future development of gas-generating-reaction-based immunoassays are briefly discussed.
Gender Dysphoria and Related Symptoms in Autism Spectrum Disorder: A Bilingual Review of the Literature
Authors: Tateno Masaru , Shimomura Ryotaro , Shiraishi Eri , Nanba Kotaro , Tateno Yukie
Published: November 2024

The association between autism spectrum disorder (ASD) and gender dysphoria (GD) has attracted a great deal of interest among child and adolescent psychiatrists in Japan. In clinical settings, it is common to hear complaints or concerns related to GD from adolescents with ASD. In the past few years, several review articles have been published on ASD and GD. The Initial Clinical Guidelines for co-occurring ASD and GD in adolescents were published in 2018, suggesting the increasing need of intervention for these conditions worldwide. Although a large amount of evidence has been accumulated regarding the co-occurrence of ASD and GD, all review articles were based solely on case reports and articles published in English. In this article, we performed a bilingual literature review using English- and Japanese-language literature databases. We found 13 case reports in English and 11 case reports in Japanese. The Japanese literature included articles on gender-related symptoms in ASD, but not limited to ASD with comorbid GD. Wattel and her colleagues proposed 15 theories on the link between ASD and GD. We classified the reported cases into one or more of the fifteen theories proposed by Wattel. These theories seemed useful in understanding the co-occurrence of ASD and GD, especially in AMAB cases. Wattel’s 15 theories are categorized into biological, psychological, and social factors, respectively. With regard to the social factors, we discussed Japanese school culture and psychological burden among gender-dysphoric students. Further studies are awaited.
Navigating Uncertainty: The Role of Mood and Confidence in Decision-Making Flexibility and Performance
Authors: Lavín Claudio , García Roberto , Fuentes Miguel
Published: November 2024

Dealing with uncertainty is a pivotal skill for adaptive decision-making across various real-life contexts. Cognitive models suggest that individuals continuously update their knowledge based on past choices and outcomes. Traditionally, uncertainty has been linked to negative states such as fear and anxiety. Recent evidence, however, highlights that uncertainty can also evoke positive emotions, such as surprise, interest, excitement, and enthusiasm, depending on one’s task expectations. Despite this, the interplay between mood, confidence, and learning remains underexplored. Some studies indicate that self-reported mood does not always align with confidence, as these constructs evolve on different timescales. We propose that mood influences confidence, thereby enhancing decision flexibility—defined as the ability to switch effectively between exploration and exploitation. This increased flexibility is expected to improve task performance by increasing accuracy. Our findings support this hypothesis, revealing that confidence modulates exploration/exploitation strategies and learning rates, while mood affects reward perception and confidence levels. These findings indicate that metacognition entails a dynamic balance between exploration and exploitation, integrating mood states with high-level cognitive processes.
Energy Efficiency in Biophilic Architecture: A Systematic Literature Review and Visual Analysis Using CiteSpace and VOSviewer
Authors: Ding Xin , Cui Yanqiu , Chen Zhengshu , Zhang Hangyue
Published: November 2024

The advent and application of biophilic architecture bring numerous environmental, economic, and energy-efficiency benefits, playing a crucial role in advancing low-carbon, energy-saving, healthy, comfortable, and sustainable development within the construction industry. Thanks to its many advantages—such as aesthetic enhancement, improved microclimates, and negative carbon potential—biophilic architecture has been widely adopted in building design, particularly as a response to the escalating environmental crisis. Integrating plants with various architectural forms can optimize building performance, especially by reducing operational energy consumption. This study uses knowledge mapping tools like CiteSpace 6.1.R3 and VOSviewer 1.6.19 to analyze 2309 research papers from the Web of Science (WoS) published over the past decade on the topic of “energy efficiency in biophilic architecture”. It conducts visual analyses of publication trends, collaborative networks, and key themes. The research categorizes plant–architecture integration methods, focusing on three primary areas: green roofs, vertical green systems, and green photovoltaic systems. Additionally, it reviews the ways in which biophilic architecture contributes to energy savings, the research methodologies employed, energy-saving rates, and the factors influencing these outcomes. Finally, a SWOT framework is constructed to assess the strengths, weaknesses, opportunities, and potential threats of biophilic architecture, as well as its future development prospects. The findings indicate that integrating plants with building roofs is an effective energy-saving strategy, achieving energy savings of up to 70%. Furthermore, combining biophilic elements with photovoltaic systems can enhance the efficiency of solar energy generation. This study offers valuable insights for architects and researchers in designing more energy-efficient and sustainable buildings.
Study on Damage Constitutive Model of Reactive Powder Concrete in Uniaxial Tension
Authors: Zhang Hongji , Lu Hang , Wang Ziheng , Gao Siming , Wen Bo , Ju Yanzhong
Published: November 2024

In this paper, the damage constitutive model of reactive powder concrete (RPC) in uniaxial tension is investigated. The relationship between the uniaxial tensile strength of RPC and the steel fiber admixture was analyzed by preparing RPC specimens with different steel fiber volume admixtures for uniaxial tensile tests, and the stress–strain curves were recorded. The test results show that the uniaxial tensile strength of RPC is significantly enhanced with an increase in steel fiber doping, especially after the doping amount is greater than 2%, showing a linear increase. Based on the classical damage mechanics and Weibull distribution, the damage evolution equation and the constitutive model of RPC uniaxial tension were established. The validation shows that the model can effectively describe the damage process of RPC in uniaxial tension, which provides a theoretical basis for the application of RPC in engineering practice.
Analytical Study of Stud Shear Connector Behavior in Steel–UHPC Composite Structures
Authors: Du Wei , Hu Zhijian , Zhou Zhi
Published: November 2024

Ultra-high performance concrete (UHPC) combined with shorter stud shear connectors (h/d < 4) presents challenges that existing analytical models for stud connectors cannot adequately address. This study enhances the elastic foundation beam model to better accommodate these material and dimensional changes. Key improvements include the analytical calculation of equivalent foundation stiffness, which incorporates the rotation of the stud head—an aspect often neglected in previous research—and considers the post-yield plastic hinge at the stud weld. The proposed analytical model effectively captures variations in stud diameter and concrete elastic modulus, providing a load–slip curve with broader applicability than traditional empirical formulas. Validation against experimental data from 21 push-out specimens of varying diameters shows strong agreement, confirming the accuracy of the method. Moreover, a parametric study based on the analytical model reveals the sequential relationship between the formation of plastic hinges at the stud weld and the development of plastic regions in the concrete. This relationship is influenced by factors such as stud diameter, yield strength, and concrete strength. Notably, an increase in concrete strength significantly enhances the shear force at the stud root at the point when the concrete reaches its compressive strength. This explains why high-strength concrete specimens exhibit lower ultimate slip. These findings provide a crucial basis for understanding the behavior of stud shear connectors in composite structures.