Identical Blocks Research Articles

Moving mirrors, OTOCs and scrambling

We explore the physics of scrambling in the moving mirror models, in which a two-dimensional CFT is subjected to a time-dependent boundary condition. It is well-known that by choosing an appropriate mirror profile, one can model quantum aspects of black holes in two dimensions, ranging from Hawking radiation in an eternal black hole (for an “escaping mirror”) to the recent realization of Page curve in evaporating black holes (for a “kink mirror”). We explore a class of OTOCs in the presence of such a boundary and explicitly demonstrate the following primary aspects: First, we show that the dynamical CFT data directly affect an OTOC and maximally chaotic scrambling occurs for the escaping mirror for a large-c CFT with identity block dominance. We further show that the exponential growth of OTOC associated with the physics of scrambling yields a power-law growth in the model for evaporating black holes which demonstrates unitary dynamics in terms of a Page curve. We also demonstrate that, by tuning a parameter, one can naturally interpolate between an exponential growth associated with scrambling and a power-law growth in unitary dynamics. Our work explicitly exhibits the role of higher-point functions in CFT dynamics as well as the distinction between scrambling and Page curve. We also discuss several future possibilities based on this class of models.

Histological and photoacoustic evaluation of rectal cancer after neoadjuvant therapy using microvascular density.

As non-operative management of rectal cancer proliferates, re-staging and surveillance methods are critical in selecting appropriate patients for organ preservation versus proctectomy. In previous work, the authors have shown that transrectal acoustic resolution photoacoustic microscopy (ARPAM) co-registered with ultrasound can differentiate residual cancer from complete tumoural response to neoadjuvant therapy. We hypothesize that these findings are due to changes in microvascular density (MVD). Patients with rectal adenocarcinoma who underwent neoadjuvant therapy, transrectal photoacoustic imaging and resection were included. We first compared immunohistochemical staining with erythroblast transformation-specific-related gene (ERG) immunostain to standard CD31 to confirm adequate identification of endothelium. Tissue sections from identical blocks were stained with CD31 and ERG, and then a correlation was calculated between manually labelled CD31-stained vessels and ERG nuclei density. Second, representative tissue blocks from responders, partial responders and non-responders were stained with ERG. ERG nuclei density was quantified as a proxy for MVD. CD31 MVD and ERG nuclei density were strongly correlated (R2 = 0.87; P < 0.01). In the tumour bed of patients after neoadjuvant therapy, MVD of complete responders (599 nuclei/mm2; 95% CI 434-764) is significantly higher (P < 0.01) than that of partial responders (185 nuclei/mm2; 95% CI 64-306) and non-responders (117 nuclei/mm2; 95% CI 42-192). No significant difference was found between the partial responders and non-responders (P = 0.60). Microvascular density appears highest in cases of complete tumour response to neoadjuvant therapy, similar to normal rectal tissue. The histological microvascular patterns seen in treated tissue may explain the imaging patterns seen in photoacoustic microscopy.

A novel 8-connected Pixel Identity GAN with Neutrosophic (ECP-IGANN) for missing imputation

Missing pixel imputation presents a critical challenge in image processing and computer vision, particularly in applications such as image restoration and inpainting. The primary objective of this paper is to accurately estimate and reconstruct missing pixel values to restore complete visual information. This paper introduces a novel model called the Enhanced Connected Pixel Identity GAN with Neutrosophic (ECP-IGANN), which is designed to address two fundamental issues inherent in existing GAN architectures for missing pixel generation: (1) mode collapse, which leads to a lack of diversity in generated pixels, and (2) the preservation of pixel integrity within the reconstructed images. ECP-IGANN incorporates two key innovations to improve missing pixel imputation. First, an identity block is integrated into the generation process to facilitate the retention of existing pixel values and ensure consistency. Second, the model calculates the values of the 8-connected neighbouring pixels around each missing pixel, thereby enhancing the coherence and integrity of the imputed pixels. The efficacy of ECP-IGANN was rigorously evaluated through extensive experimentation across five diverse datasets: BigGAN-ImageNet, the 2024 Medical Imaging Challenge Dataset, the Autonomous Vehicles Dataset, the 2024 Satellite Imagery Dataset, and the Fashion and Apparel Dataset 2024. These experiments assessed the model’s performance in terms of diversity, pixel imputation accuracy, and mode collapse mitigation, with results demonstrating significant improvements in the Inception Score (IS) and Fréchet Inception Distance (FID). ECP-IGANN markedly enhanced image segmentation performance in the validation phase across all datasets. Key metrics, such as Dice Score, Accuracy, Precision, and Recall, were improved substantially for various segmentation models, including Spatial Attention U-Net, Dense U-Net, and Residual Attention U-Net. For example, in the 2024 Medical Imaging Challenge Dataset, the Residual Attention U-Net’s Dice Score increased from 0.84 to 0.90, while accuracy improved from 0.88 to 0.93 following the application of ECP-IGANN. Similar performance enhancements were observed with the other datasets, highlighting the model’s robust generalizability across diverse imaging domains.

Stochastic stability of random stacking of blocks

The paper explores the stability of a tower obtained by stacking identical rectangular blocks on top of each other with an inherent randomness due to slight positional offsets between successive blocks. With probabilistic modeling techniques, the diffusive behavior of the stacking process is studied and the collapse is seen as a first passage time problem. In the considered model, alignment errors are idealized as independent Gaussian random variables with zero mean and given standard deviation. We derive expressions for the joint probability density functions of block positions, and analyze their correlation. The study extends to the stochastic stability of a stack of given height, by exploring the statistical characteristics of the center of gravity of the part of tower above each block. Eventually, the probabilistic analysis of collapse is developed to quantify the statistics of the number of blocks that can be heaped up before the tower topples. Although this problem may initially appear playful, it offers an illustrated introduction to first passage problems on a non homogenous process. From a practical standpoint, this analysis offers a simple understanding of the influence of alignment errors on the overall stability of a stack, which may find several fields of application.

Effects of sea-land breeze on air pollutant dispersion in street networks with different distances from coast using WRF-CFD coupling method

A WRF-CFD coupled model with high-temporal resolution is employed to investigate pollutant dispersions during a sea-land breeze (SLB) day in an identical building block configuration at three locations in Shanghai, China, and the blocks are set at the coast (L1), downtown (L2) and inland (L3). The results show that the localized wind speed drops below 1 m/s during the sea-land-breeze collision period (SLBCP), which leads to pollutant accumulation. The closer the block is to the coast, the earlier occurrence and longer duration of SLBCP, and Blocks L1, L2, and L3 experience SLBCPs during the morning peak traffic period (MPTP), low-traffic-volume period (at midday), and evening peak traffic period (EPTP), with durations of 2.5 h, 2 h, and 1 h, respectively. Due to the low wind speeds of both land breezes and sea breezes during the overlap of MPTP and SLBCP, the pollutant concentration in Block L1 is significantly elevated, and the peak concentration is two times higher than that in the non-coastal blocks (L2 and L3). Block L2 shows a peak concentration during the midday low-traffic-volume period, while no evident peak concentration is found in L3 in EPTP. The mean concentrations in Blocks L1, L2, and L3 during EPTP are 72 %, 57 %, and 31 % lower than those during MPTP, respectively. This suggests that SLB has significantly different effects on wind fields and pollutant dispersion in building blocks with different distances from the coast and can provide reference data for transport planning in coastal cities.

WISNet: A deep neural network based human activity recognition system

Nowadays, Human Activity Recognition (HAR) is a key research area with many ubiquitous innovative solutions, where both accelerometer and gyroscope data provide information about an observed person’s physical activity. HAR offers a diverse variety of important applications, including healthcare, burglary detection, workplace monitoring, and emergency identification. Traditional recognition approaches rely on extracting handmade features from the obtained data to identify the typeof human action. Additionally, the efficacy of these works is dependent upon the specific customized features that are chosen. One potential approach to tackle this issue is to utilize Convolutional Neural Networks (CNN) to automatically learn the relevant features. In this paper, we propose a deep learning model, WISNet, a custom 1D-CNN approach to recognize six complex human activities: Jogging, Walking Downstairs, Sitting, Standing, Walking and Climbing Upstairs. The model includes a Convolved Normalized Pooled (CNPM) Block to generate significant features from the initial layers. An Identity and Basic (IDBN) Block is incorporated to extract residual progressive features for capturing complex sequential data dependencies. Channel and Spatial attention (CASb) Block is integrated with the network to prioritize or minimize essential features based on relative weights. The proposed WISNet model achieved an enhanced accuracy and F1-score of 96.41 % and 0.95 for the HAR dataset by surpassing the existing transfer learning architectures such as Gated Recurrent Units (GRU), Long Short-Term Memory (LSTM), and Recurrent Neural Network (SimpleRNN). By strategically integrating the CNPM, IDBN, and CASb blocks, this study aims to tackle distinct challenges encountered in the classification process by enhancing the discernment of features essential for the precise identification of multi-class human activity recognition. The seamless integration of these blocks within the model plays a pivotal role in elevating the overall performance of the WISNet architecture. The work also validates WISNet with similar open-source datasets (UCI-HAR and KU-HAR) and dissimilar open-source datasets (Sleep state detection, Fall detection, and ECG Heartbeat).

The Effects of Intra-Articular Triamcinolone and Autologous Protein Solution on Metabolic Parameters in Horses.

Intra-articular corticosteroids are a popular treatment choice for joint-associated pain and inflammation in horses despite recent work on the metabolic effects of these drugs. The goal of this project was to compare metabolic effects between intra-articular (IA) triamcinolone acetonide (TA) and an autologous protein solution (APS). Five mixed-breed geldings (4-9 years) were utilized for this project. Three identical and consecutive 28-day treatment blocks were used, with metacarpophalangeal IA treatments consisting of equal volumes of saline, a commercially available APS, or 9 mg of TA. Regular plasma and serum samples were collected for ACTH, cortisol, glucose, insulin, and thyroid hormone analysis, in addition to thyrotropin-releasing hormone (TRH) and oral sugar tests (OSTs). Significant treatment effects of IA TA were present at 48 h post-injection in both the TRH and the OST. There was also significant suppression by IA TA of baseline ACTH and cortisol between 2 h and 96 h post-treatment, hyperglycemia between 12 h and 48 h, and hyperinsulinemia at 32 h post-treatment. There were no treatment effects with respect to any measured thyroid hormones, nor were there any significant treatment effects of APS noted. Results suggest at least 2 days and up to 7 days should elapse between a single 9 mg IA TA treatment and OST and/or TRH testing. This study found that TA exhibits significant effects on ACTH, cortisol, glucose, and insulin, while the APS does not.

Nondestructive testing method of Si3N4 ceramic bearing cylindrical roller surface defects based on depthwise separable convolution coupled with identity block ASPP

Nondestructive testing method of Si3N4 ceramic bearing cylindrical roller surface defects based on depthwise separable convolution coupled with identity block ASPP

Improving the homogeneity of Halbach arrays by optimizing magnet combinations using a genetic algorithm.

The purpose of this study was to test the effectiveness of using a genetic algorithm to find the optimal combination of permutations of permanent magnets in a Halbach magnet array in order to achieve the best magnetic field homogeneity in this work area. The test took place on a simple Halbach magnet array of 32 cubic permanent magnets. The magnetization of these magnets was preliminary assessed. Our calculations demonstrate that it is possible to achieve homogeneity of the magnetic field within the working area comparable to that of ideal identical magnetic blocks. Therefore, our study shows that combinatorics can be used to optimize homogeneity without selecting magnetic blocks, which can significantly reduce the cost of manufacturing the final structure.

Cyclic and Linear Tetrablock Copolymers Synthesized at Speed and Scale by Lewis Pair Polymerization of a One-Pot (Meth)acrylic Mixture and Characterized at Multiple Levels.

Cyclic block copolymers (cBCP) are fundamentally intriguing materials, but their synthetic challenges that demand precision in controlling both the monomer sequence and polymer topology limit access to AB and ABC block architectures. Here, we show that cyclic ABAB tetra-BCPs (cABAB) and their linear counterpart (lABAB) can be readily obtained at a speed and scale from one-pot (meth)acrylic monomer mixtures, through coupling the Lewis pair polymerization's unique compounded-sequence control with its precision in topology control. This approach achieves fast (<15 min) and quantitative (>99%) conversion to tetra-BCPs of predesignated linear or cyclic topology at scale (40 g) in a one-pot procedure, precluding the needs for repeated chain extensions, stoichiometric addition steps, dilute conditions, and postsynthetic modifications, and/or postsynthetic ring-closure steps. The resulting lABAB and cABAB have essentially identical molecular weights (Mn = 165-168 kg mol-1) and block degrees/symmetry, allowing for direct behavioral comparisons in solution (hydrodynamic volume, intrinsic viscosity, elution time, and refractive indices), bulk (thermal transitions), and film (thermomechanical and rheometric properties and X-ray scattering patterns) states. To further the morphological characterizations, allylic side-chain functionality is exploited via the thiol-ene click chemistry to install crystalline octadecane side chains and promote phase separation between the A and B blocks, allowing visualization of microdomain formation.

Electron Delocalization and Transfer Across Polyoxometalates-Based Subnanomaterials in Catalytic Reactions.

Due to their identical building blocks and high surface-to-volume ratio, subnanomaterials exhibit significant properties compared to their bulk nanomaterial counterparts. The interactions between these building blocks can result in either equal or unequal sharing of electrons, leading to electron transfer in heterojunctions or electron delocalization within symmetric structures. Clusters, possessing electronic properties akin to atoms, can serve as reservoirs of electrons to stabilize crucial intermediates in catalytic reactions. This perspective provides a novel understanding of well-defined subnanomaterials with distinct architectures, such as cluster-based constructions and co-assembled heterojunctions, emphasizing the relationship between electronic structures and catalytic properties. The objective is to provide novel perspectives on the realm of subnanomaterials and cluster-based architectures.

Cultivating a Civic Identity using a Feminist Cohort Model: An Analysis of Tulane’s Newcomb Scholars Program

Analysis of the Newcomb Scholars program at Tulane University offers a case study in the development of civic identity through participation in a four-year curricular program with community engagement and service-learning grounded in feminist pedagogies and theories. Each year, twenty intellectually curious and ambitious undergraduates are selected to participate in an academically rigorous interdisciplinary learning experience centering feminist leadership. Using data from a recently completed 10-year evaluation of the Newcomb Scholars program, this article considers how these students’ civic identity is forged because of curricular and co-curricular experiences and persists in post-graduation settings. Evaluation data includes longitudinal survey responses, participant grade data, and demographic information of program participants. Our analysis examines how the components of the Scholars program adhere to the five building blocks for developing a healthy civic identity and shares results from the program’s 10-year assessment (Schnaubelt, et al 2022). Special focus is placed on participants' commitment to feminism as a political issue, a defining element of a healthy civic identity. Significantly, the study found nearly 77% of respondents to the alumnae survey agreeing that they are currently engaged in some level of feminist work and 95% of respondents identifying as a feminist. The cohort structure is also a focus. It keeps the Newcomb Scholars together for curricular and co-curricular experiences across four years, allowing them to practice the building blocks of a healthy civic identity in the context of an enduring community. Further, we discuss the challenges the program has experienced due to institutional and organizational constraints. Finally, we offer thoughts on how to address these concerns within a context of national democratic threat and decreased trust in higher education.

Cardiorespiratory and Neuromuscular Improvements Plateau after 2 wk of Sprint Interval Training in Sedentary Individuals.

Previous studies ranging from 2 to 12 wk of sprint interval training (SIT) have reported improvements in maximal oxygen uptake (V̇O 2max ) and neuromuscular function in sedentary populations. However, whether the time course of the changes in these variables correlates with greater training volumes is unclear. Thirteen sedentary participants performed three all-out training weekly sessions involving 15-s sprints interspersed with 2 min of recovery on a cycle ergometer. The 6-wk training program was composed of three identical blocks of 2 wk in which training volume was increased from 10 to 14 repetitions over the first four sessions and reduced to 8 in the last session. The power output and the heart rate (HR) were monitored during the sessions. The V̇O 2max , the power-force-velocity profile, and the isometric force were assessed every 2 wk from baseline. A significant increase in V̇O 2max was observed from the second week plateauing thereafter despite four additional weeks of training. The dynamic force production increased from the second week, and the speed production decreased by the end of the protocol. The isometric force and the maximal power output from the power-force-velocity profile did not change. Importantly, the time spent at high percentages of the maximal HR during the training sessions was lower in the second and third training block compared with the first. SIT resulted in an effective approach for rapidly increasing V̇O 2max , and no change in the isometric force was found; cycling-specific neuromuscular adaptations were observed from the second week of training. SIT may be useful in the short term, but further improvement of overall physical fitness might need other training modalities like endurance and/or resistance training.

Ultrafine Graphite Scrap and Carbon Blocks Prepared by High-Solid-Loading Bead Milling and Conventional Ball Milling: A Comparative Assessment.

A comparison between the physical characteristics of graphite ultrafine particles and the properties of graphite blocks prepared from graphite scrap using bead and conventional ball milling techniques is presented. Industrial-scale bead milling was used to prepare graphite scrap with an initial particle size d50 of 24 μm in the ultrafine range of <10 μm. Bead milling can significantly reduce the production time of ultrafine graphite from graphite scrap from 72 h by ball milling to 10 min. Ultrafine graphite scrap prepared from both ball milling and bead milling yields particles with a similar morphology, with a minor difference in crystalline size La and stacking height Lc observed. Carbon blocks were fabricated from both techniques, yielding carbon blocks with an almost identical microstructure and block density. Blocks from bead milling have slightly higher flexural strength as well as comparable hardness and resistivity. The block's flexural strength, hardness, and resistivity were 68.37 MPa, 99, and 36.9 μΩ·m, respectively, in a bead-milled carbon block and 61.86 MPa, 95.5, and 38.6 μΩ·m, respectively, for a ball-milled carbon block. Bead milling can be applied for the preparation of ultrafine graphite particles and graphite blocks with production that is 9 times faster for the same ultrafine graphite particle output and final product quality.

Strongly Proper Connected Coloring of Graphs

We study a new variant of connected coloring of graphs based on the concept of strong edge coloring (every color class forms an induced matching). In particular, an edge-colored path is strongly proper if its color sequence does not contain identical terms within a distance of at most two. A strong proper connected coloring of G is the one in which every pair of vertices is joined by at least one strongly proper path. Let spc(G)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\\,\ extrm{spc}\\,}}(G)$$\\end{document} denote the least number of colors needed for such coloring of a graph G. We prove that the upper bound spc(G)≤5\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\\,\ extrm{spc}\\,}}(G)\\le 5$$\\end{document} holds for any 2-connected graph G. On the other hand, we demonstrate that there are 2-connected graphs with arbitrarily large girth satisfying spc(G)≥4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\\,\ extrm{spc}\\,}}(G)\\ge 4$$\\end{document}. Additionally, we prove that graphs whose cycle lengths are divisible by 3 satisfy spc(G)≤3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\\,\ extrm{spc}\\,}}(G)\\le 3$$\\end{document}. We also consider briefly other connected colorings defined by various restrictions on color sequences of connecting paths. For instance, in a nonrepetitive connected coloring of G, every pair of vertices should be joined by a path whose color sequence is nonrepetitive, that is, it does not contain two adjacent identical blocks. We demonstrate that 2-connected graphs are 15-colorable, while 4-connected graphs are 6-colorable, in the connected nonrepetitive sense. A similar conclusion with a finite upper bound on the number of colors holds for a much wider variety of connected colorings corresponding to fairly general properties of sequences. We end the paper with some open problems of concrete and general nature.

Shape-Anisotropic Assembly of Protein Nanocages with Identical Building Blocks by Designed Intermolecular π-π Interactions.

Protein lattices that shift the structure and shape anisotropy in response to environmental cues are closely coupled to potential functionality. However, to design and construct shape-anisotropic protein arrays from the same building blocks in response to different external stimuli remains challenging. Here, by a combination of the multiple, symmetric interaction sites on the outer surface of protein nanocages and the tunable features of phenylalanine-phenylalanine interactions, a protein engineering approach is reported to construct a variety of superstructures with shape anisotropy, including 3D cubic, 2D hexagonal layered, and 1D rod-like crystalline protein nanocage arrays by using one single protein building block. Notably, the assembly of these crystalline protein arrays is reversible, which can be tuned by external stimuli (pH and ionic strength). The anisotropic morphologies of the fabricated macroscopic crystals can be correlated with the Å-to-nm scale protein arrangement details by crystallographic elucidation. These results enhance the understanding of the freedom offered by an object's symmetry and inter-object π-π stacking interactions for protein building blocks to assemble into direction- and shape-anisotropic biomaterials.

Breast Ultrasound Images Augmentation and Segmentation Using GAN with Identity Block and Modified U-Net 3.

One of the most prevalent diseases affecting women in recent years is breast cancer. Early breast cancer detection can help in the treatment, lower the infection risk, and worsen the results. This paper presents a hybrid approach for augmentation and segmenting breast cancer. The framework contains two main stages: augmentation and segmentation of ultrasound images. The augmentation of the ultrasounds is applied using generative adversarial networks (GAN) with nonlinear identity block, label smoothing, and a new loss function. The segmentation of the ultrasounds applied a modified U-Net 3+. The hybrid approach achieves efficient results in the segmentation and augmentation steps compared with the other available methods for the same task. The modified version of the GAN with the nonlinear identity block overcomes different types of modified GAN in the ultrasound augmentation process, such as speckle GAN, UltraGAN, and deep convolutional GAN. The modified U-Net 3+ also overcomes the different architectures of U-Nets in the segmentation process. The GAN with nonlinear identity blocks achieved an inception score of 14.32 and a Fréchet inception distance of 41.86 in the augmenting process. The GAN with identity achieves a smaller value in Fréchet inception distance (FID) and a bigger value in inception score; these results prove the model's efficiency compared with other versions of GAN in the augmentation process. The modified U-Net 3+ architecture achieved a Dice Score of 95.49% and an Accuracy of 95.67%.

Coil-Helix Block Copolymers Can Exhibit Divergent Thermodynamics in the Disordered Phase.

Chiral building blocks have the ability to self-assemble and transfer chirality to larger hierarchical length scales, which can be leveraged for the development of novel nanomaterials. Chiral block copolymers, where one block is made completely chiral, are prime candidates for studying this phenomenon, but fundamental questions regarding the self-assembly are still unanswered. For one, experimental studies using different chemistries have shown unexplained diverging shifts in the order-disorder transition temperature. In this study, particle-based molecular simulations of chiral block copolymers in the disordered melt were performed to uncover the thermodynamic behavior of these systems. A wide range of helical models were selected, and several free energy calculations were performed. Specifically, we aimed to understand (1) the thermodynamic impact of changing the conformation of one block in chemically identical block copolymers and (2) the effect of the conformation on the Flory-Huggins interaction parameter, χ, when chemical disparity was introduced. We found that the effective block repulsion exhibits diverging behavior, depending on the specific conformational details of the helical block. Commonly used conformational metrics for flexible or stiff block copolymers do not capture the effective block repulsion because helical blocks are semiflexible and aspherical. Instead, pitch can quantitatively capture the effective block repulsion. Quite remarkably, the shift in χ for chemically dissimilar block copolymers can switch sign with small changes in the pitch of the helix.

Denoised encoder-based residual U-net for precise teeth image segmentation and damage prediction on panoramic radiographs

ObjectivesThis research focuses on performing teeth segmentation with panoramic radiograph images using a denoised encoder-based residual U-Net model, which enhances segmentation techniques and has the capacity to adapt to predictions with different and new data in the dataset, making the proposed model more robust and assisting in the accurate identification of damages in individual teeth. MethodsThe effective segmentation starts with pre-processing the Tufts dataset to resize images to avoid computational complexities. Subsequently, the prediction of the defect in teeth is performed with the denoised encoder block in the residual U-Net model, in which a modified identity block is provided in the encoder section for finer segmentation on specific regions in images, and features are identified optimally. The denoised block aids in handling noisy ground truth images effectively. ResultsProposed module achieved greater values of mean dice and mean IoU with 98.90075 and 98.74147 ConclusionsProposed AI enabled model permitted a precise approach to segment the teeth on Tuffs dental dataset in spite of the existence of densed dental filling and the kind of tooth. Clinical SignificanceThe proposed model is pivotal for improved dental diagnostics, offering precise identification of dental anomalies. This could revolutionize clinical dental settings by facilitating more accurate treatments and safer examination processes with lower radiation exposure, thus enhancing overall patient care.

A Region-Folding Electromagnetic Transient Simulation Approach for Large-Scale Power Electronics System

This paper proposes a region-folding electromagnetic transient simulation approach for large-scale power electronics systems to boost simulation speed. In the region-folding approach, the loop tear method is proposed to decouple the connections among power electronics blocks, the grouping and pre-calculating method of identical structural blocks is proposed to avoid computing the inverse of matrices repeatedly, and the global simultaneous response procedure is proposed to handle the simultaneous and multiple switching events. The implementation of the proposed approach is combined with high-performance parallelization technology to shorten the simulation time. The Modular Multilevel Converter (MMC)-based High Voltage Direct Current (HVDC) model and DC photovoltaic power station model are simulated respectively to validate the accuracy and efficiency. Simulation results indicate that the proposed approach has the same accuracy as other Electromagnetic Transients (EMT) commercial software with better efficiency.