Identifying factors influencing reservoir eutrophication using interpretable machine learning combined with shoreline morphology and landscape hydrological features: A case study of Danjiangkou Reservoir, China.

Reservoir nearshore areas are influenced by both terrestrial and aquatic ecosystems, making them sensitive regions to water quality changes. The analysis of basin landscape hydrological features provides limited insight into the spatial heterogeneity of eutrophication in these areas. The complex characteristics of shoreline morphology and their impact on eutrophication are often overlooked. To comprehensively analyze the complex relationships between shoreline morphology and landscape hydrological features, with eutrophication, this study uses Danjiangkou Reservoir as a case study. Utilizing Landsat 8 OLI remote sensing data from 2013 to 2022, combined with a semi-analytical approach, the spatial distribution of the Trophic State Index (TSI) during flood discharge periods (FDPs) and water storage periods (WSPs) was obtained. Using Extreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP), explained the relationships between landscape composition, landscape configuration, hydrological topography, shoreline morphology, and TSI, identified key factors at different spatial scales and validated their reliability. The results showed that: (1) There is significant spatial heterogeneity in the TSI distribution of Danjiangkou Reservoir. The eutrophication levels are significant in the shoreline and bay areas, with a tendency to extend inward only during the WSPs. (2) The importance of landscape composition, landscape configuration, hydrological topography, and shoreline morphology to TSI variations during the FDPs are 25.12 %, 29.6 %, 23.09 %, and 22.19 % respectively. Besides shoreline distance, the Landscape Shape Index (LSI) and Hypsometric Integral (HI) are the two most significant environmental variables overall during the FDPs. Forest and grassland areas become the most influential factors during the WSPs. The influence of landscape patterns and hydrological topography on TSI varies at different spatial scales. At the 200 m riparian buffer zone, the increase in cropland and impervious areas significantly elevates eutrophication levels. (3) Morphology complexity, shows a noticeable threshold effect on TSI, with complex shoreline morphology increasing the risk of eutrophication.

Mandibular Interincisor and Intercanine Width at Three Different Stages of Dentition: A Cross-sectional Study.

Background and objective: Malocclusion is a manifestation of normal biological variability, defined as a misalignment of the teeth or an incorrect occlusion between the upper and lower dental arches. This study aimed to evaluate the mandibular intercanine primary, mixed, and permanent dentition in school children of Shimla, Himachal Pradesh. Materials and methods: This cross-sectional study was conducted on 1,392 children between the ages of 4 and 18 years from schools that fulfilled the inclusion criteria. The dental casts were poured and further divided based on the dentition stage, i.e., primary, mixed, and permanent dentition stages. Mandibular arch widths-interincisor and intercanine were measured on the casts by a digital vernier caliper. Results: The statistically significant difference was found as the interincisor width increased from primary to mixed dentition and between males and females for permanent dentition. Intercanine width significantly increases from primary to mixed dentition and gradually from mixed to permanent dentition stages. Conclusion: The present study found that there is a significant increase in interincisor and intercanine width in the lower dental arch from primary dentition to permanent dentition. How to cite this article: Singhal P, Jaswal O, Thakur S. Mandibular Interincisor and Intercanine Width at Three Different Stages of Dentition: A Cross-sectional Study. Int J Clin Pediatr Dent 2024;17(4):417-424.

Left atrial appendage thrombus is associated with a higher fractal dimension in patients with atrial fibrillation.

PURPOSE: To assess the anatomical complexity of the left atrial appendage (LAA) using fractal dimension (FD) based on cardiac computed tomography angiography (CTA) and the association between LAA FD and LAA thrombosis. MATERIALS AND METHODS: Patients with atrial fibrillation (AF) who underwent both cardiac CTA and transesophageal echocardiography (TEE) between December 2018 and December 2022 were retrospectively analyzed. Patients were categorized into normal (n = 925), circulatory stasis (n = 82), and thrombus groups (n = 76) based on TEE results and propensity score matching (PSM) was performed for subsequent analysis. FD was calculated to quantify the morphological heterogeneity of LAA. Independent risk factors for thrombus were screened using logistic regression. The diagnostic performance of FD and CHA2DS2-VaSc score for predicting thrombus was evaluated using the area under the receiver operating characteristics curve (AUC). RESULTS: LAA FD was higher in the thrombus group (1.61 [1.49, 1.70], P < 0.001) than in the circulatory stasis (1.33 [1.18, 1.47]) and normal groups (1.30 [1.18, 1.42]) both before and after PSM. LAA FD was also an independent risk factor in the thrombus (OR [odds ratio] = 570,861.15 compared to normal, 41,122.87 compared to circulatory stasis; all P < 0.001) and circulatory stasis group (OR = 98.87, P = 0.001) after PSM. The diagnostic performance of LAA FD was significantly better than the CHA2DS2-VaSc score in identifying thrombus. CONCLUSIONS: Patients with high LAA FD are more likely to develop LAA thrombus, and the use of FD provides an effective method for assessing the risk of thrombosis in AF patients, thereby guiding individualized clinical treatment.

Multi-dimensional microfluidic paper-based analytical devices (µPADs) for noninvasive testing: A review of structural design and applications.

The rapid emergence of microfluidic paper-based devices as point-of-care testing (POCT) tools for early disease diagnosis and health monitoring, particularly in resource-limited areas, holds immense potential for enhancing healthcare accessibility. Leveraging the numerous advantages of paper, such as capillary-driven flow, porous structure, hydrophilic functional groups, biodegradability, cost-effectiveness, and flexibility, it has become a pivotal choice for microfluidic substrates. The repertoire of microfluidic paper-based devices includes one-dimensional lateral flow assays (1D LFAs), two-dimensional microfluidic paper-based analytical devices (2D µPADs), and three-dimensional (3D) µPADs. In this comprehensive review, we provide and examine crucial information related to paper substrates, design strategies, and detection methods in multi-dimensional microfluidic paper-based devices. We also investigate potential applications of microfluidic paper-based devices for detecting viruses, metabolites and hormones in non-invasive samples such as human saliva, sweat and urine. Additionally, we delve into capillary-driven flow alternative theoretical models of fluids within the paper to provide guidance. Finally, we critically examine the potential for future developments and address challenges for multi-dimensional microfluidic paper-based devices in advancing noninvasive early diagnosis and health monitoring. This article showcases their transformative impact on healthcare, paving the way for enhanced medical services worldwide.

Impact of pharmacist-led pharmaceutical care on health-related and pharmaceutical therapy-related quality of life in patients with heart failure: A randomized controlled trial.

BACKGROUND: Data on the impact of pharmacist-led pharmaceutical care (PC) on pharmaceutical therapy-related and health-related quality of life (HRQoL) and their sensitivities to PC provision in patients with heart failure (HF) are scarce. OBJECTIVES: This study aimed to assess the impact of pharmacist-led PC on HRQoL employing the Minnesota Living with Heart Failure Questionnaire (MLHFQ) and 5-level EuroQol 5 dimension (EQ-5D-5L) and on pharmaceutical therapy-related quality of life using the Patient-Reported Outcomes Measure of Pharmaceutical Therapy (PROMPT) in HF patients and compare sensitivities to the PC provision of these three tools. METHODS: A single-blinded randomized controlled trial was conducted at a tertiary public hospital in Thailand between November 2022 and May 2023. Overall, 250 patients were randomly divided into the usual care (UC) (N = 124) and PC (N = 126) groups. Mixed effects models were used to investigate the differences in the mean change scores of PROMPT, EQ-5D-5L, and MLHFQ between the UC and PC groups. The sensitivities to PC provision of the three measures were evaluated using standardized effect sizes (SESs). RESULTS: Significant differences were found in five of eight domains and the total score of the PROMPT between the PC and UC groups (all p < 0.05). However, no significant differences were found in the EQ-5D-5L and MLHFQ between the two groups (both p > 0.05). The SESs of the five domains and total score of PROMPT ranged from 0.29 to 1.65, considered small-to-large effect sizes, whereas the SESs of EQ-5D-5L and MLHFQ were -0.4 to 0, considered small effect sizes. CONCLUSIONS: Pharmacist-led PC can positively affect pharmaceutical therapy-related quality of life using PROMPT in HF patients. Additionally, PROMPT is more sensitive to PC provision than EQ-5D-5L and MLHFQ.

Retinal Microvasculature Causally Affects the Brain Cortical Structure: A Mendelian Randomization Study.

Purpose: To reveal the causality between retinal vascular density (VD), fractal dimension (FD), and brain cortex structure using Mendelian randomization (MR). Design: Cross-sectional study. Participants: Genome-wide association studies of VD and FD involving 54 813 participants from the United Kingdom Biobank were used. The brain cortical features, including the cortical thickness (TH) and surface area (SA), were extracted from 51 665 patients across 60 cohorts. Surface area and TH were measured globally and in 34 functional regions using magnetic resonance imaging. Methods: Bidirectional univariable MR (UVMR) was used to detect the causality between FD, VD, and brain cortex structure. Multivariable MR (MVMR) was used to adjust for confounding factors, including body mass index and blood pressure. Main Outcome Measures: The global and regional measurements of brain cortical SA and TH. Results: At the global level, higher VD is related to decreased TH (ß = -0.0140 mm, 95% confidence interval: -0.0269 mm to -0.0011 mm, P = 0.0339). At the functional level, retinal FD is related to the TH of banks of the superior temporal sulcus and transverse temporal region without global weighted, as well as the SA of the posterior cingulate after adjustment. Vascular density is correlated with the SA of subregions of the frontal lobe and temporal lobe, in addition to the TH of the inferior temporal, entorhinal, and pars opercularis regions in both UVMR and MVMR. Bidirectional MR studies showed a causation between the SA of the parahippocampal and cauda middle frontal gyrus and retinal VD. No pleiotropy was detected. Conclusions: Fractal dimension and VD causally influence the cortical structure and vice versa, indicating that the retinal microvasculature may serve as a biomarker for cortex structural changes. Our study provides insights into utilizing noninvasive fundus images to predict cortical structural deteriorations and neuropsychiatric disorders. Financial Disclosures: The author(s) have no proprietary or commercial interest in any materials discussed in this article.

A New Paradigm for High-dimensional Data: Distance-Based Semiparametric Feature Aggregation Framework via Between-Subject Attributes.

This article proposes a distance-based framework incentivized by the paradigm shift towards feature aggregation for high-dimensional data, which does not rely on the sparse-feature assumption or the permutation-based inference. Focusing on distance-based outcomes that preserve information without truncating any features, a class of semiparametric regression has been developed, which encapsulates multiple sources of high-dimensional variables using pairwise outcomes of between-subject attributes. Further, we propose a strategy to address the interlocking correlations among pairs via the U-statistics-based estimating equations (UGEE), which correspond to their unique efficient influence function (EIF). Hence, the resulting semiparametric estimators are robust to distributional misspecification while enjoying root-n consistency and asymptotic optimality to facilitate inference. In essence, the proposed approach not only circumvents information loss due to feature selection but also improves the model's interpretability and computational feasibility. Simulation studies and applications to the human microbiome and wearables data are provided, where the feature dimensions are tens of thousands.

Particle shape analysis of calcareous sand based on digital images.

Particle geometric is a key parameter that defines the eometric attributes of calcareous sand particles and is intricately related to their mechanical traits, such as compression and shear. The scanning electron microscopy and digital imaging were applied to capture the microscopic properties and geometric projections of calcareous sand. The qualitative analysis, conventional statistical methods and fractal theory were employed to describe the geometric morphology of sand particles. Additionally, we analyzed the structural and physical traits of calcareous sand based on its unique biological genesis. We developed a hypothetical structural-physical model for calcareous sand. Our findings revealed the interwoven reticulation on the surface of calcareous gravel particles, along with an uneven distribution of pores on the external surface. As the particle size increased, the global profile factor decreased and the angularity increased. The critical threshold for the variations in flatness, surface roughness, and circularity was observed at a particle size of 5 mm, with the particle size having a relatively minor effect on these characteristics for particles smaller than 5 mm. The shape of the calcareous sand particles exhibited fractal characteristics, with fractal dimension serving as a measure of surface smoothness, particle breakage, and strength. These experimental results could significantly enhance our understanding of the mechanical behavior of calcareous sand.

Enhancing spatio-temporal environmental analyses: A machine learning superpixel-based approach.

The progressive evolution of the spatial and temporal resolutions of Earth observation satellites has brought multiple benefits to scientific research. The increasing volume of data with higher frequencies and spatial resolutions offers precise and timely information, making it an invaluable tool for environmental analysis and enhanced decision-making. However, this presents a formidable challenge for large-scale environmental analyses and socioeconomic applications based on spatial time series, often compelling researchers to resort to lower-resolution imagery, which can introduce uncertainty and impact results. In response to this, our key contribution is a novel machine learning approach for dense geospatial time series rooted in superpixel segmentation, which serves as a preliminary step in mitigating the high dimensionality of data in large-scale applications. This approach, while effectively reducing dimensionality, preserves valuable information to the maximum extent, thereby substantially enhancing data accuracy and subsequent environmental analyses. This method was empirically applied within the context of a comprehensive case study encompassing the 2002-2022 period with 8-d-frequency-normalized difference vegetation index data at 250-m resolution in an area spanning 43,470 km2. The efficacy of this methodology was assessed through a comparative analysis, comparing our results with those derived from 1000-m-resolution satellite data and an existing superpixel algorithm for time series data. An evaluation of the time-series deviations revealed that using coarser-resolution pixels introduced an error that exceeded that of the proposed algorithm by 25 % and that the proposed methodology outperformed other algorithms by more than 9 %. Notably, this methodological innovation concurrently facilitates the aggregation of pixels sharing similar land-cover classifications, thus mitigating subpixel heterogeneity within the dataset. Further, the proposed methodology, which is used as a preprocessing step, improves the clustering of pixels according to their time series and can enhance large-scale environmental analyses across a wide range of applications.

Quantitative Assessment of Intervertebral Disc Degeneration Using the Disc Signal Intensity Index in Patients With Spine-Related Pain.

Objective This is a retrospective observational study that aims to investigate the association between disc signal intensity index (DSI2) scores and patient-reported outcome measures in patients with lumbar spine disorders. Methods We introduced DSI2 to quantitatively assess disc degeneration. MRI records of patients with lumbar spine-related pain between 2019 and 2022 were analyzed retrospectively. Patient demographics and outcomes were collected, including the Numerical Rating Scale of Pain and EuroQol Group 5 Dimension 5-Level Quality of Life (EQ-5D-5L) scores. The DSI2 was calculated by dividing the mean signal intensity of the L1-S1 discs by that of the CSF on midsagittal T2-weighted MRI images. Results Each DSI2 level corresponded to a Pfirrmann grade score at the respective lumbar level. Multivariable linear regression analysis using the EQ-5D-5L as the objective variable identified BMI (p = 0.007) and average DSI2 (p = 0.018) as independent risk factors for EQ-5D-5L deterioration. However, the mean Pfirrmann grade score was not an independent risk factor (p = 0.58). Conclusion Our study using DSI2 showed the relationship between disc degeneration and EQ-5D-5L deterioration. Distinct from the Pfirrmann grading system, the DSI2 method is a promising alternative for future disc research that excellently detects the subtle progression of degeneration.

Performance Limits and Advancements in Single 2D Transition Metal Dichalcogenide Transistor.

Two-dimensional (2D) transition metal dichalcogenides (TMDs) allow for atomic-scale manipulation, challenging the conventional limitations of semiconductor materials. This capability may overcome the short-channel effect, sparking significant advancements in electronic devices that utilize 2D TMDs. Exploring the dimension and performance limits of transistors based on 2D TMDs has gained substantial importance. This review provides a comprehensive investigation into these limits of the single 2D-TMD transistor. It delves into the impacts of miniaturization, including the reduction of channel length, gate length, source/drain contact length, and dielectric thickness on transistor operation and performance. In addition, this review provides a detailed analysis of performance parameters such as source/drain contact resistance, subthreshold swing, hysteresis loop, carrier mobility, on/off ratio, and the development of p-type and single logic transistors. This review details the two logical expressions of the single 2D-TMD logic transistor, including current and voltage. It also emphasizes the role of 2D TMD-based transistors as memory devices, focusing on enhancing memory operation speed, endurance, data retention, and extinction ratio, as well as reducing energy consumption in memory devices functioning as artificial synapses. This review demonstrates the two calculating methods for dynamic energy consumption of 2D synaptic devices. This review not only summarizes the current state of the art in this field but also highlights potential future research directions and applications. It underscores the anticipated challenges, opportunities, and potential solutions in navigating the dimension and performance boundaries of 2D transistors.

Musculoskeletal Dimension and Brightness Reference Values in Lumbar Magnetic Resonance Imaging-A Radio-Anatomic Investigation in 80 Healthy Adult Individuals.

Background/Objectives: Magnetic resonance imaging (MRI) is the preferred diagnostic means to visualize spinal pathologies, and offers the possibility of precise structural tissue analysis. However, knowledge about MRI-based measurements of physiological cross-sectional musculoskeletal dimensions and associated tissue-specific average structural brightness in the lumbar spine of healthy young women and men is scarce. The current study was planned to investigate characteristic intersexual differences and to provide MRI-related musculoskeletal baseline values before the onset of biological aging. Methods: At a single medical center, lumbar MRI scans of 40 women and 40 men aged 20-40 years who presented with moderate nonspecific low back pain were retrospectively evaluated for sex-specific differences in cross-sectional sizes of the fifth lumbar vertebrae, psoas and posterior paravertebral muscles, and respective sex- and age-dependent average brightness alterations on T2-weighted axial sections in the L5-level. Results: In women (mean age 33.5 years ± 5.0 (standard deviation)), the investigated musculoskeletal cross-sectional area sizes were significantly smaller (p < 0.001) compared to those in men (mean age 33.0 years ± 5.7). Respective average musculoskeletal brightness values were higher in women compared to those in men, and most pronounced in posterior paravertebral muscles (p < 0.001). By correlating brightness results to those of subcutaneous fat tissue, all intersexual differences, including those between fifth lumbar vertebrae and psoas muscles, turned out to be statistically significant. This phenomenon was least pronounced in psoas muscles. Conclusions: Lumbar musculoskeletal parameters showed significantly larger dimensions of investigated anatomical structures in men compared to those in women aged 20-40 years, and an earlier onset and faster progress of bone loss and muscle degradation in women.

A novel formula for estimating the vertical dimension of occlusion using panoramic radiography.

BACKGROUND: This study aimed to develop a new formula to easily estimate the vertical dimension of occlusion (VDO) by using the distance between the mental foramen on a panoramic radiograph. SUBJECTS AND METHODS: A total of 508 dentulous subjects were selected from outpatient dental clinics at the College of Dental Medicine, Al-Azhar University. The vertical dimension of the occlusion was measured using a single calibrated calliper. For each subject, a digital panoramic radiograph was taken with fixed exposure parameters. The intermental foramina distance (IMFD) was measured. The data were collected and then analysed using the IBM SPSS version 20.0 software package. (Armonk, NY: IBM Corp.). Linear regression was used to determine the relationship between the intermental foramina distance (IMFD) and the vertical dimension at occlusion (VDO). RESULTS: Pearson's correlation analysis revealed that there was a strong correlation between the intermental foramina distance (IMFD) and the VDO. Thus, a novel formula was developed for determining the VDO using panoramic radiography. CONCLUSION: The novel formula developed herein facilitated the determination of the VDO among prosthetic rehabilitation for subjects who lost vertical dimension due to loss of posterior teeth or severe wear of natural posterior teeth. Further studies are needed to determine the clinical applicability of the derived formulae for edentulous subjects.

Relevance of farm-scale indicators and tools for farmers to assess sustainability of their mixed crop-ruminant livestock systems.

Ensuring the sustainability and circularity of mixed crop-ruminant livestock systems is essential if they are to deliver on the enhancement of long-term productivity and profitability with a smaller footprint. The objectives of this study were to select indicators in the environmental, economic and social dimensions of sustainability of crop-livestock systems, to assess if these indicators are relevant in the operational schedule of farmers, and to score the indicators in these farm systems. The scoring system was based on relevance to farmers, data availability, frequency of use, and policy. The study was successful in the assemblage of a suite of indicators comprising three dimensions of sustainability and the development of criteria to assess the usefulness of these indicators in crop-ruminant livestock systems in distinct agro-climatic regions across the globe. Except for ammonia emissions, indicators within the Emissions to air theme obtained high scores, as expected from mixed crop-ruminant systems in countries transitioning towards low emission production systems. Despite the inherent association between nutrient losses and water quality, the sum of scores was numerically greater for the former, attributed to a mix of economic and policy incentives. The sum of indicator scores within the Profitability theme (farm net income, expenditure and revenue) received the highest scores in the economic dimension. The Workforce theme (diversity, education, succession) stood out within the social dimension, reflecting the need for an engaged labor force that requires knowledge and skills in both crop and livestock husbandry. The development of surveys with farmers/stakeholders to assess the relevance of farm-scale indicators and tools is important to support direct actions and policies in support of sustainable mixed crop-ruminant livestock farm systems.

Linear fractal evolution characteristics of rock crack distributions during loading process.

To investigate the fractal characteristics of rock crack distributions during the loading process, discrete element method was used to make rock samples with joints and record the crack propagation. The Box-counting method was used to quantitatively analyze the fractal dimension of the crack distribution at each moment, and the relationship between the crack fractal dimension and strain ratio was established based on fractal theory. The results indicated that the relationship between the fractal dimension of the crack distribution and strain ratio showed a strong linear characteristic. By transforming this linear relationship into a linear function, the slope of the function was found to be linked to the failure patterns of the sample, and a refinement coefficient (damage-fracture reduction factor) was identified from the slope as an effective basis for determining the degree of sample damage and fracture. The damage-fracture reduction factor can be categorized: 0.25-0.5 (spilt and fracture), 0.5-0.9 (synergy between fracture and damage), 0.9-1 (microcrack asymptotic damage). Owing to the linear fractal characteristics, an expression for the damage variables influenced by failure patterns can be established from the geometric aspect. In addition, the linear fractal characteristics of the cracks were verified in other acoustic emission and crack extension experiments.

Riemannian geometry for efficient analysis of protein dynamics data.

An increasingly common viewpoint is that protein dynamics datasets reside in a nonlinear subspace of low conformational energy. Ideal data analysis tools should therefore account for such nonlinear geometry. The Riemannian geometry setting can be suitable for a variety of reasons. First, it comes with a rich mathematical structure to account for a wide range of geometries that can be modeled after an energy landscape. Second, many standard data analysis tools developed for data in Euclidean space can be generalized to Riemannian manifolds. In the context of protein dynamics, a conceptual challenge comes from the lack of guidelines for constructing a smooth Riemannian structure based on an energy landscape. In addition, computational feasibility in computing geodesics and related mappings poses a major challenge. This work considers these challenges. The first part of the paper develops a local approximation technique for computing geodesics and related mappings on Riemannian manifolds in a computationally feasible manner. The second part constructs a smooth manifold and a Riemannian structure that is based on an energy landscape for protein conformations. The resulting Riemannian geometry is tested on several data analysis tasks relevant for protein dynamics data. In particular, the geodesics with given start- and end-points approximately recover corresponding molecular dynamics trajectories for proteins that undergo relatively ordered transitions with medium-sized deformations. The Riemannian protein geometry also gives physically realistic summary statistics and retrieves the underlying dimension even for large-sized deformations within seconds on a laptop.

The Impact Message Inventory-Circumplex (IMI-C): Exploring the Aversiveness Component of Therapists' Covert Reactions to Patients' Interpersonal Communications.

The Impact Message Inventory-Circumplex (IMI-C) is a two-dimensional measure of patient-induced countertransference. Surprisingly, in a replication study of its circumplex structure, Hafkenscheid and Timmerman could retrieve a third dimension, in addition to the basic dimensions of Affiliation and Control. They tentatively interpreted this preliminary third dimension as representing 'reactance' (oppositional and uncooperative patient behaviours), with 'active' and 'passive' as polarities. This provisional interpretation was no more than plausible and was partly speculative. Therefore, a more systematic empirical approach to the meaning embedded in the third dimension is required. The present empirical study tests the hypothesis that the preliminary third dimension might represent aversiveness rather than reactance. A panel of IMI-C users (N = 100) independently judged all 56 items of the instrument in terms of the general (i.e., without taking a specific patient in mind) emotional undertone enclosed in the item formulations using a forced choice three point scale format: 'positive emotional undertone' (+), 'neutral' (o) and negative (aversive) undertone (-). Overall, IMI-C users appeared to evaluate the formulations of items constituting the preliminary third dimension as intrinsically more aversive (negative emotional connotation), compared to the group of IMI-C items not included in this preliminary third dimension. However, the original octants of the IMI-C could be discriminated in terms of aversiveness as well. Anyhow, clinical interpretations of IMI-C profiles may benefit from an examination of the aversiveness component, enclosed within the items and octants themselves, irrespective of the specific patients judged with the instrument.

Fractal evolution characteristics of fracture meso-damage in uniaxial compression rock masses using bonded block model.

With regard to deep mining in metal mines, an investigation into the failure mode of deep fractured rock masses and their corresponding acoustic emission signal characteristics is conducted via uniaxial compression tests. Subsequently, a fractal damage renormalization group mechanical model is developed to explain the behavior of those fractured rock masses. Employing the bonded block model (BBM) numerical simulation method, fracture process in synthetic rock samples is analyzed, thereby validating the efficacy of the mechanical model. The numerical simulations highlight the critical role of fractures expansion in underlying the deterioration of rock mass strength. As the peak load decreases, the fracture fractal dimension increases, leading to a significant 14.2% reduction in compressive strength accompanied by an approximate 8.7% rise in average fracture fractal dimension. A comparative analysis of tetrahedral and voronoi block synthetic rock samples reveals the tetrahedral block samples exhibit a superior ability to depict the fracture behavior of fractured rock masses. Specifically, they offer a more accurate simulation of acoustic emission characteristics and failure modes. Furthermore, variations in the fracture fractal dimension with respect to the hole defect's position are observed, with the maximum value occurring along the vertical axis of the hole defect. This observation underscores the potential utility of visually monitoring deep rock fracture dynamics as an effective mean for quantitatively evaluating fracture damage and strength degradation in deep rock formations.

Dimension-Controlled VO2 Film for Optoelectronic Logic Gates and Information Encryption.

As the fields of photonics and information technology develop, a lot of novel applications based on VO2 material, such as optoelectronic computing and information encryption, have been developed. While the performance of these devices was not only closely associated with the VO2 phase transition properties but also depended on their dimensional characteristics. In the current study, we conducted the dimension-controlled vanadium dioxide (VO2) film growth, resulting in the epitaxial 2-dimensional (2D) VO2 film and well-distributed 3-dimensional (3D) VO2 crystal film deposition, respectively. It was revealed that, unlike the 2D film, the pronounced localized surface plasmon resonance dominated the near-infrared spectrum across the phase transition for the 3D VO2 film due to the naturally formed meta-surface structure, which showed a transmittance valley in the infrared spectrum after metallization. Based on this distinct infrared spectrum feature in the 3D VO2 film, we proposed an optoelectronic logic gate controlled by the input voltage and the probing Vis/IR light. By detecting the transmittance states of the probing light with different wavelengths, we achieved multistate encoding functions and demonstrated the information encryption application. This new conception device also showed great potential for some other applications such as optoelectronic coupled computing, information encryption, and optical near-field sensing computing.