Search Results (129)

Due to the strong electronegativity of oxygen ions, the valence band maximum (VBM) that is derived from the O 2p orbital leads to strong localization, as well as further heavy hole mass and low hole mobility, which makes it extremely difficult to obtain high-conductivity p-type transparent conductive materials. Herein, we propose the strategy of multiple anions through the introduction of weaker electronegative nitrogen, in consideration of the delocalization on VBM, as well as the stability of octahedral anion cages. As such, first-principles calculations in the framework of density functional theory (DFT) are used for this work. Crystal structure prediction software USPEX (version 2023.0) was adopted to investigate the N-O appropriate ratio in CaTiO_3−xN_x (0 ≤ x ≤ 1) to balance the high transmission of light and highly favorable dispersion at the VBM. Furthermore, the p-type TCO performance of CaTiO_3-xN_x was evaluated based on the hole effective mass, hole mobility, and conductivity. The effectiveness of modulating p-type TCO through N-O multiple anions was also evaluated through defect formation energy and ionization energy. Ultimately, the construction of a CaTiO_3-xN_x/Si heterojunction and band alignment were considered for practical application. This approach attempts to boost the diversity of p-type perovskite-based TCOs and opens a new perspective for engineering and innovative material design for sustainable TCOs demand. Full article

Five-axis precision dispensing machines are employed for semiconductor packaging. The dispensing accuracy is significantly affected by multiple geometric errors among the five axes. This paper proposes a vision-based measurement (VBM) system for identifying geometric errors and calibrating kinematics. The VBM system is also employed to complete the detection of the workpiece. A kinematic model of the machine was established using a local product-of-exponential formulation of screw theory. A geometric error identification algorithm was designed. Eight position-independent geometric errors (PIGEs) and position-dependent geometric errors (PDGEs) were involved. The system of overdetermined equations was solved. Combining the singular value decomposition and regularization, eight PIGEs in the A and C axes were identified. Comprehensive error measurement results verified the proposed approach. The VBM system measured a mean spatial position error of approximately 59.9 μm and a mean orientation error of about 160 arcsec for the end-effector, reflecting the geometric error level of the prototype machine. The proposed approach provides a feasible and automated calibration solution for five-axis precision dispensing machines. Full article

This contribution illustrates the research focused on the process of securing and the transportation prior to the conservation treatment of a wooden Crucifix—severely damaged in 2016 during the earthquake of Central Italy—through the application of menthyl lactate. The preparatory and paint layers of the polychrome sculpture are extremely fragile due to decohesion issues and the presence of unstable cleavages and losses linked to severe thermo-hygrometric variations. Many scientific and application tests were carried out in the laboratory and then, later, on a fragment of the Crucifix in order to identify the volatile binder best-suited to this case study: menthyl lactate was selected among six binders as the most appropriate compound due to its effective consolidation, lower sublimation rate, negligible residue, and non-hazardousness. Lastly, a very specific transportation system was designed and realised to move the work, without further loss and damage, from the storage building where it was kept in Spoleto to the conservation department of the Opificio delle Pietre Dure in Florence. The volatile binder will continue to be locally applied to allow the mechanical cleaning, in order to remove the thick deposits of debris without damaging the colour. The conservation treatment will be carried out in the future, in parallel with further scientific tests. Full article

Background: The voxel-based specific regional analysis system for Alzheimer’s disease (VSRAD) allows quantitative evaluation of the degree of an individual’s brain atrophy through statistical comparison of brain magnetic resonance imaging (MRI) of their brain to a normative database of healthy Japanese individuals. Currently, the VSRAD is used in routine clinical practice in the diagnosis of Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB). Recent studies using VSRAD have explored its utility in the assessment of brain atrophy associated with various conditions, including diabetes, oral health status, and olfactory dysfunction. This review summarizes the principles of the VSRAD and its foundational method, voxel-based morphometry (VBM), and their clinical and research applications. Methods: This narrative review was conducted by performing a literature search of PubMed to identify articles regarding VBM and the VSRAD that were published between 2005 and 2025. Results: VSRAD yields four indices for quantifying the severity and extent of gray matter atrophy, especially in the medial temporal lobe. Studies have demonstrated its high diagnostic accuracy in distinguishing among AD, mild cognitive impairment (MCI), and DLB. Furthermore, it is correlated with neuropsychological test scores and has been applied to evaluate brain changes associated with diabetes, olfactory dysfunction, and physical inactivity. Motion-corrected MR images, which utilize AI techniques, have also been validated using VSRAD-derived metrics. Conclusions: Quantifying brain atrophy using the VSRAD allows objective evaluation and facilitates the investigation of its association with various diseases. Specifically, VSRAD can be considered a useful adjunctive tool for diagnosing AD and DLB. Full article

Background/Objectives: Previous magnetic resonance imaging (MRI) investigations reported brain alterations in anorexia nervosa restricting type (AN-R); however, the number of existing structural neuroimaging studies in the developmental age is limited. Here, we analyzed the volumetric brain differences between adolescent patients with AN-R and control peers, and possible correlations between brain volumes and clinical features. Methods: The sample comprised 47 adolescent females with AN-R (mean age: 15.0 years, SD = 1.4) who underwent structural MRI within one month of admission to a tertiary care university hospital, and 39 typically developing controls matched for sex and age. The patients were clinically characterized by standardized interviews/questionnaires. Using the voxel-based morphometry (VBM) technique, possible significant volumetric brain differences between the two groups were analyzed. Moreover, correlations between altered brain regions and clinical (i.e., body mass index (BMI) and disease duration) or psychopathological variables were investigated. Results: An overall reduction in gray matter (GM) volume with a concomitant increase in cerebrospinal fluid (CSF) is observed in AN-R patients; these alterations correlate with a lower BMI. The reduction in GM volume affects the frontal and parietal regions involved in the cognitive processes that underlie and sustain the AN-R clinical features. Conclusions: These results add to the current knowledge of the AN-R pathophysiology and pave the way for the development of brain imaging biomarkers for AN in the developmental age. Full article

In rotating machines, any faults in anti-friction bearings occurring during operation can lead to failures that are unacceptable due to considerable downtime losses and maintenance costs. Hence, early fault detection is essential, and different vibration-based methods (VBMs) are explored to recognise incipient fault signatures. Based on rotordynamics, if a bearing defect causes metal-to-metal (MtM) impacts during shaft rotation, the impacts excite high-frequency resonance responses of the bearing assembly. The defect-related frequencies are modulated with the resonance responses and rely on signal demodulation for fault detection. However, the current study highlights that the bearing fault/faults may not be detected if the defect in a bearing is not causing MtM impacts nor exciting the high-frequency resonance of the bearing assembly. In a roller bearing, a localised defect may maintain persistent contact between rolling elements and raceways, thereby preventing the occurrence of impulse vibration responses. Due to contact persistence, such defects may not generate impact and may not be detected by existing VBMs, and the bearing could behave as healthy. This paper investigates such specific cases by exploring the relationship between roller-bearing defect characteristics and their potential to generate impact loads during operation. Using an experimental bearing rig, different roller and inner-race defects are presented while their fault characteristic frequencies remain undetected by the envelope analysis, fast Kurtogram, cyclic spectral coherence, and tensor decomposition methods. This study highlights the significance of both the dimension and location of defects within bearings on their detectability based on the rotordynamics concept. Further, simple roller-beam experiments are carried out to visualise and validate the reliability of the experimental observations made on the roller bearing dynamics. Full article

As a key insulating material in power equipment, epoxy resins (EP) are often limited in practical applications due to space charge accumulation and mechanical degradation. This study systematically investigates the effects of SiO₂ nanoparticle doping on the electrical and mechanical properties of SiO₂/EP composites through molecular dynamics simulations and first-principles calculations. The results demonstrate that SiO₂ doping enhances the mechanical properties of EP, with notable improvements in Young’s modulus, bulk modulus, and shear modulus, while maintaining excellent thermal stability across different temperatures. Further investigations reveal that SiO₂ doping effectively modulates the interfacial charge behavior between EP and metals (Cu/Fe) by introducing shallow defect states and reconstructing interfacial dipoles. Density of states analysis indicates the formation of localized defect states at the interface in doped systems, which dominate the defect-assisted hopping mechanism for charge transport and suppress space charge accumulation. Potential distribution calculations show that doping reduces the average potential of EP (1 eV for Cu layer and 1.09 eV for Fe layer) while simultaneously influencing the potential distribution near the polymer–metal interface, thereby optimizing the interfacial charge injection barrier. Specifically, the hole barrier at the maximum valence band (VBM) after doping significantly increased, rising from the initial values of 0.448 eV (Cu interface) and 0.349 eV (Fe interface) to 104.02% and 209.46%, respectively. These findings provide a theoretical foundation for designing high-performance epoxy-based composites with both enhanced mechanical properties and controllable interfacial charge behavior. Full article

As renewable energy technologies advance, identifying efficient photocatalytic materials for water splitting to produce hydrogen has become an important research focus in materials science. This study presents a multi-task regression model (MTRM) designed to predict the conduction band minimum (CBM), valence band maximum (VBM), and solar-to-hydrogen efficiency (STH) of inorganic materials. Utilizing crystallographic and band gap data from over 15,000 materials in the SNUMAT database, machine-learning methods are applied to predict CBM and VBM, which are subsequently used as additional features to estimate STH. A deep neural network framework with a multi-branch, multi-task regression structure is employed to address the issue of error propagation in traditional cascading models by enabling feature sharing and joint optimization of the tasks. The calculated results show that, while traditional tree-based models perform well in single-task predictions, MTRM achieves superior performance in the multi-task setting, particularly for STH prediction, with an MSE of 0.0001 and an R² of 0.8265, significantly outperforming cascading approaches. This research provides a new approach to predicting photocatalytic material performance and demonstrates the potential of multi-task learning in materials science. Full article

Background/Objectives: T1-weighted magnetic resonance imaging (MRI) and the Montreal Cognitive Assessment are standard, efficient, and swift clinical and research tools used when interrogating cognitively impairing (CI) conditions, such as Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD). However, the associations between gross cognitive impairment (CI) as compared to domain-specific functioning and underlying neuroanatomical correlates have not been investigated among individuals with early-onset Mild Cognitive Impairment (MCI) or Alzheimer’s disease (EOAD), who can benefit greatly from early diagnosis and intervention strategies. Methods: We analyzed T1-weighted MRIs and Montreal Cognitive Assessment (MoCA) scores from the ADNI database in individuals < 65 years old who were either cognitively normal (CN) or had MCI or EOAD. Gray matter volume (GMV) was estimated in voxel-based morphometry (VBM) and ROI-parcellation general linear models examining associations with individual MoCA scores after adjusting for demographic covariates. Results: Results from 120 subjects (44 CN, 62 MCI, and 14 EOAD), identified significant global but also individually distinct domain-specific topographical signatures spanning the temporal, parietal, limbic, occipital, frontal lobes, and cingulate gyri. Conclusions: The results highlight neural correlates of cognitive functioning in a sample of young patients representative of the AD continuum, in addition to studying the structural MRI and functional cognitive difference. Full article

Background/Objective: The Trail Making Test (TMT) is a widely used neuropsychological tool to assess processing speed (Part A) and executive function (Part B). However, the neuroanatomical substrates underlying its Black & White variant (TMT-B&W) and the influence of demographic factors remain poorly understood. This study aimed to identify gray matter (GM) correlates of TMT-B&W performance across unadjusted and covariate-adjusted models in cognitively healthy adults. Methods: In this cross-sectional study, 87 participants (40–80 years) underwent structural magnetic resonance imaging (MRI) and completed TMT-B&W. Whole-brain voxel-based morphometry (VBM) was conducted using FreeSurfer for preprocessing and Computational Anatomy Toolbox (CAT12)/Statistical Parametric Mapping (SPM12) for analysis. Two voxel-wise regression models (unadjusted and adjusted for age, education, gender, and total intracranial volume (TICV)) assessed GM associations with TMT-B&W-A-B performance. Statistical thresholds were voxel-level p < 0.001 (uncorrected) and cluster-level Family-Wise Error (FWE) correction (p < 0.001). Results: In unadjusted models, TMT-B&W-A performance correlated with GM reductions in the right orbitofrontal cortex (T = 42.64, equivk = 515.60, representing peak voxel level T-statistic and cluster size in voxels), while TMT-B&W-B linked to the right insular cortex (T = 50.65, equivk = 515.50). After adjustment, both tasks converged on the left thalamus (TMT-A: T = 8.05, equivk = 594; TMT-B: T = 8.11, equivk = 621), with TMT-B&W-B showing a denser thalamic cluster. Demographic covariates attenuated cortical associations, revealing thalamic integration as a shared mechanism. Conclusions: The thalamus emerges as a critical hub for TMT-B&W performance when accounting for demographic variation, while distinct cortical regions mediate task-specific demands in unadjusted models. These findings support the TMT-B&W as a practical, low-cost neurobehavioral marker of brain integrity in older populations. Full article

The aim of this study is to examine the impact of VBM success on the corporate sustainability of Thai listed firms. The effects of successful VBM on decision-making effectiveness, business value creation, and corporate competency are also investigated. Both contingency theory and the relevant literature are utilized to aid in effectively comprehending the consequences of successful VBM. Thai listed companies were selected as the sample for this study, and data collected from 101 accounting directors through questionnaires were used as the research instrument. PLS-SEM was employed to test the hypothesized relationships. The results found that successful VBM has a considerable impact on company sustainability, owing primarily to indirect effects through mediating variables, such as business value generation and corporate competence, rather than direct effects, which are not significant. As a result, it is possible to conclude that good VBM implementation will increase business sustainability through processes or mediating variables, rather than directly affecting it. In addition, the success of VBM significantly improves the business value creation and corporate competency. Lastly, effective decision-making, the creation of company value, and corporate competency all significantly enhance corporate sustainability. Contributions from management and theoretical perspectives are openly provided. Recommendations, conclusions, and future study directions are also highlighted and discussed herein. Full article

An interpretable machine learning framework was constructed to predict the bandgap of silicon oxide materials used for electric furnace refractories. Among seven machine learning models compared, the AdaBoost ensemble model performed the best with an R² of 0.80 and MAE of 0.5, indicating high accuracy. Breaking through the traditional limitation of directly correlating features such as the conduction-band minimum (CBM) and valence-band maximum (VBM), this study utilized SHapley Additive exPlanations (SHAP) analysis to uncover deeper relationships between critical features like ‘energy above hull’, ‘num of unique magnetic sites’, and ‘formation energy per atom ‘ with the bandgap. These features significantly influence the thermal stability and erosion resistance of the material. This research provides a theoretical basis for optimizing the performance of silicon oxide materials and green metallurgical processes, thereby promoting sustainable development in the steel industry. Full article

Background/Objectives: Breast cancer chemotherapy patients and survivors face cognitive side effects that are not fully understood. Neuroimaging can provide a unique way to study these effects; however, it can be difficult to recruit large numbers of subjects. Our meta-analysis aims to synthesize volumetric neuroimaging data to highlight consistent findings in regional brain volume changes to further advance our understanding of the chemotherapy-related cognitive impairments faced by breast cancer patients and survivors. Methods: An Activation Likelihood Estimation analysis was conducted across the data from eight voxel-based morphometry experiments examining changes in the brains of breast cancer patients and survivors exposed to chemotherapy over time and three voxel-based morphometry experiments comparing chemotherapy-exposed subjects to controls with and without breast cancer. Results: There were consistent volume reductions across the whole brain in both experiment groups. The subjects’ over-time analysis showed peak consistency among the studies in the right inferior frontal gyrus and the left insula. Conclusions: Chemotherapy for non-central nervous system cancers such as breast cancer can cause physical changes throughout the brain that can be quantitatively measured by neuroimaging methodologies and may underlie persistent cognitive deficits in some individuals. Full article

The current work determines the physical properties of Cs₂HfCl₆ photovoltaic compounds including their structural, electronic, and optical behavior, utilizing the DFT approach. The simulated Cs₂HfCl₆ lattice constants, cell volumes, and bond lengths decrease as the pressure increases from 0 to 20 GPa. The band structure analysis reveals that the calculated under-pressure (0–20 GPa) of Cs₂HfCl₆ is semiconducting with a flexible indirect bandgap (5.44, 2.76, 2.02, 1.45, and 0.99) eV. The electronic bandgap diminishes (0–20 GPa), transitioning the compound from the UV to the visible spectra. This alteration improves the transition from the VBM to the CBM, hence augmenting the optical effectiveness. Concurrently, the dielectric function escalates, enhancing the absorption and conductivity, and causing a red shift in the optical spectra, while diminishing the reflection in the visible spectra. Our findings on the hydraulic pressure (0–20 GPa) and the electrical and optical properties indicate that Cs₂HfCl₆ may be utilized in the development of next-generation solar cells, LEDs, UV sensors, and high-pressure optical instruments. Full article

Introduction: Neurodegenerative diseases like progressive supranuclear palsy (PSP) present challenges concerning their diagnosis. Neuroimaging using magnetic resonance (MRI) may add diagnostic value. However, modern techniques such as volumetric assessment using Voxel-Based Morphometry (VBM), although proven to be more accurate and superior compared to MRI, have not gained popularity among scientists in the investigation of neurological disorders due to their higher cost and time-consuming applications. Conventional brain MRI methods may present a quick, practical, and easy-to-use imaging rating tool for the differential diagnosis of PSP. The purpose of this study is to evaluate a string of existing visual MRI rating scales and signs regarding their impact for the diagnosis of PSP. Materials and Methods: The population study consisted of 30 patients suffering from PSP and 72 healthy controls. Each study participant underwent a brain MRI, which was subsequently examined by two independent researchers in a double-blinded fashion. Fifteen visual rating scales and signs were evaluated, including pontine atrophy, cerebellar atrophy, midbrain atrophy, aqueduct of Sylvius enlargement, cerebellar peduncle hyperintensities, enlargement of the fourth ventricle (100% sensitivity and 71% specificity) and left temporal lobe atrophy (97% sensitivity and 78% specificity). Conclusions: Enlargement of the Sylvius aqueduct, enlargement of the fourth ventricle and atrophy of both temporal lobes together with the presence of morning glory and hummingbird signs can be easily and quickly distinguished and identified by an experienced radiologist without involving any complex analysis, making them useful tools for PSP diagnosis. MRI visual scale measurements could be added to the diagnostic criteria of PSP and may serve as an alternative to highly technical and more sophisticated quantification methods. Full article