THE EFFECTS OF DISTRIBUTOR DESIGN ON THE SOLIDS DISTRIBUTION IN A CFB RISER

The influence of gas distributor design on the gas-solids flow structure was investigated in a rectangular CFB riser. The gas distributor was altered five different ways. The results show that the distributor design had significant effects on the solids distribution. The changed flow structure was maintained from the entrance to the riser top. Altering the gas distributor was an effective and practical method to change the flow structure. This study may be beneficial to CFB design and operation

TwinTex: Geometry-aware Texture Generation for Abstracted 3D Architectural Models

Coarse architectural models are often generated at scales ranging from individual buildings to scenes for downstream applications such as Digital Twin City, Metaverse, LODs, etc. Such piece-wise planar models can be abstracted as twins from 3D dense reconstructions. However, these models typically lack realistic texture relative to the real building or scene, making them unsuitable for vivid display or direct reference. In this paper, we present TwinTex, the first automatic texture mapping framework to generate a photo-realistic texture for a piece-wise planar proxy. Our method addresses most challenges occurring in such twin texture generation. Specifically, for each primitive plane, we first select a small set of photos with greedy heuristics considering photometric quality, perspective quality and facade texture completeness. Then, different levels of line features (LoLs) are extracted from the set of selected photos to generate guidance for later steps. With LoLs, we employ optimization algorithms to align texture with geometry from local to global. Finally, we fine-tune a diffusion model with a multi-mask initialization component and a new dataset to inpaint the missing region. Experimental results on many buildings, indoor scenes and man-made objects of varying complexity demonstrate the generalization ability of our algorithm. Our approach surpasses state-of-the-art texture mapping methods in terms of high-fidelity quality and reaches a human-expert production level with much less effort. Project page: https://vcc.tech/research/2023/TwinTex.Comment: Accepted to SIGGRAPH ASIA 202

The effects of psychiatric disorders on the risk of chronic heart failure: a univariable and multivariable Mendelian randomization study

BackgroundSubstantial evidence suggests an association between psychiatric disorders and chronic heart failure. However, further investigation is needed to confirm the causal relationship between these psychiatric disorders and chronic heart failure. To address this, we evaluated the potential effects of five psychiatric disorders on chronic heart failure using two-sample Mendelian Randomization (MR).MethodsWe selected single nucleotide polymorphisms (SNPs) associated with chronic heart failure and five psychiatric disorders (Attention-Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), Major Depression, Bipolar Disorder and Schizophrenia (SCZ)). Univariable (UVMR) and multivariable two-sample Mendelian Randomization (MVMR) were employed to assess causality between these conditions. Ever smoked and alcohol consumption were controlled for mediating effects in the multivariable MR. The inverse variance weighting (IVW) and Wald ratio estimator methods served as the primary analytical methods for estimating potential causal effects. MR-Egger and weighted median analyses were also conducted to validate the results. Sensitivity analyses included the funnel plot, leave-one-out, and MR-Egger intercept tests. Additionally, potential mediators were investigated through risk factor analyses.ResultsGenetically predicted heart failure was significantly associated with ADHD (odds ratio (OR), 1.12; 95% CI, 1.04–1.20; p = 0.001), ASD (OR, 1.29; 95% CI, 1.07–1.56; p = 0.008), bipolar disorder (OR, 0.89; 95% CI, 0.83–0.96; p = 0.001), major depression (OR, 1.15; 95% CI, 1.03–1.29; p = 0.015), SCZ (OR, 1.04; 95% CI, 1.00–1.07; p = 0.024). Several risk factors for heart failure are implicated in the above cause-and-effect relationship, including ever smoked and alcohol consumption.ConclusionOur study demonstrated ADHD, ASD, SCZ and major depression may have a causal relationship with an increased risk of heart failure. In contrast, bipolar disorder was associated with a reduced risk of heart failure, which could potentially be mediated by ever smoked and alcohol consumption. Therefore, prevention strategies for heart failure should also incorporate mental health considerations, and vice versa

Deciphering the contributions of cuproptosis in the development of hypertrophic scar using single-cell analysis and machine learning techniques

Hypertrophic scar (HS) is a chronic inflammatory skin disease characterized by excessive deposition of extracellular matrix, but the exact mechanisms related to its formation remain unclear, making it difficult to treat. This study aimed to investigate the potential role of cuproptosis in the information of HS. To this end, we used single-cell sequencing and bulk transcriptome data, and screened for cuproptosis-related genes (CRGs) using differential gene analysis and machine learning algorithms (random forest and support vector machine). Through this process, we identified a group of genes, including ATP7A, ULK1, and MTF1, as novel therapeutic targets for HS. Furthermore, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to confirm the mRNA expression of ATP7A, ULK1, and MTF1 in both HS and normal skin (NS) tissues. We also constructed a diagnostic model for HS and analyzed the immune infiltration characteristics. Additionally, we used the expression profiles of CRGs to perform subgroup analysis of HS. We focused mainly on fibroblasts in the transcriptional profile at single-cell resolution. By calculating the cuproptosis activity of each fibroblast, we found that cuproptosis activity of normal skin fibroblasts increased, providing further insights into the pathogenesis of HS. We also analyzed the cell communication network and transcription factor regulatory network activity, and found the existence of a fibroblast-centered communication regulation network in HS, where cuproptosis activity in fibroblasts affects intercellular communication. Using transcription factor regulatory activity network analysis, we obtained highly active transcription factors, and correlation analysis with CRGs suggested that CRGs may serve as potential target genes for transcription factors. Overall, our study provides new insights into the pathophysiological mechanisms of HS, which may inspire new ideas for the diagnosis and treatment

Discovery of BRAF/HDAC Dual Inhibitors Suppressing Proliferation of Human Colorectal Cancer Cells

The combination of histone deacetylase inhibitor and BRAF inhibitor (BRAFi) has been shown to enhance the antineoplastic effect and reduce the progress of BRAFi resistance. In this study, a series of (thiazol-5-yl)pyrimidin-2-yl)amino)-N-hydroxyalkanamide derivatives were designed and synthesized as novel dual inhibitors of BRAF and HDACs using a pharmacophore hybrid strategy. In particular, compound 14b possessed potent activities against BRAF, HDAC1, and HDAC6 enzymes. It potently suppressed the proliferation of HT-29 cells harboring BRAFV600E mutation as well as HCT116 cells with wild-type BRAF. The dual inhibition against BRAF and HDAC downstream proteins was validated in both cells. Collectively, the results support 14b as a promising lead molecule for further development and a useful tool for studying the effects of BRAF/HDAC dual inhibitors

Moderating Effect of Mindfulness on the Relationships Between Perceived Stress and Mental Health Outcomes Among Chinese Intensive Care Nurses

This study aimed to explore the potential moderating effect of mindfulness and its facets on the relationships among perceived stress and mental health outcomes (burnout, depression, anxiety, and subjective well-being) among Chinese intensive care nurses. A total of 500 Chinese intensive care nurses completed self-report measures of mindfulness, burnout syndromes, perceived stress, depression, anxiety, and subjective well-being. Correlation and hierarchical multiple regressions were applied for data analysis. Mindfulness moderated the effects of perceived stress on emotional exhaustion (the core component of burnout syndrome), depression, anxiety, positive affect, and negative affect but not on the other two dimensions of burnout and life satisfaction. Further analyses indicated that the ability to act with awareness was particularly crucial in improving the effects of perceived stress on depression. These results further broaden our understanding of the relationships between perceived stress and burnout, depression, anxiety, and subjective well-being by demonstrating that mindfulness may serve as a protective factor that alleviates or eliminates the negative effects of perceived stress on depression, anxiety, burnout syndrome, and subjective well-being and may instigate further research into targeted mindfulness interventions for Chinese intensive care nurses

L'indexation parallèle de séries de données et la recherche de similarité sur du matériel moderne

La recherche de similarité de séries de données est une opération essentielle pour plusieurs applications dans de nombreux domaines. Cependant, les techniques de pointe ne parviennent pas à fournir les performances temporelles requises, que ce soit pour réaliser une exploration interactive des séries de données, ou simplement une analyse de grandes collections de données. Au cours de ma thèse, nous présentons les premières solutions d'indexation de séries de données conçues pour tirer parti intrinsèquement du matériel moderne, afin d'accélérer les temps de traitement de la recherche de similarité pour les données sur disque et en mémoire. En particulier, nous développons de nouveaux algorithmes utilisant les architectures SIMD (multi-core, multi-socket et Single Instruction Multiple Data), ainsi que des algorithmes adaptés pour l’utilisation des unités de traitement graphique (GPU). Nos expériences réalisées sur un panel de données synthétiques et réelles démontrent que nos approches sont d’ordres de grandeur plus rapides que les solutions de pointe utilisant les données enregistrées sur disque et en mémoire. Plus précisément, notre solution sur disque peut répondre à des requêtes de recherche de similitude exacte sur des ensembles de données de 100 Go en 15 secondes, et pour notre solution en mémoire en moins de 36 millisecondes, ce qui permet pour la première fois une exploration interactive de données en temps réel sur des grandes collections de séries de données.Data series similarity search is a core operation for several data series analysis applications across many different domains. However, the state-of-the-art techniques fail to deliver the time performance required for interactive exploration, or analysis of large data series collections. In this Ph.D. work, we present the first data series indexing solutions that are designed to inherently take advantage of modern hardware, in order to accelerate similarity search processing times for both on-disk and in-memory data. In particular, we develop novel algorithms for multi-core, multi-socket, and Single Instruction Multiple Data (SIMD) architectures, as well as algorithms for Graphics Processing Units (GPUs). Our experiments on a variety of synthetic and real data demonstrate that our approaches are up to orders of magnitude faster than the state-of-the-art solutions for both disk-resident and in-memory data. More specifically, our on-disk solution can answer exact similarity search queries on 100GB datasets in ∼ 15 seconds, and our in-memory solution in as low as 36 milliseconds, which enables for the first time real-time, interactive data exploration on very large data series collections