66 research outputs found
SweepNet: Unsupervised Learning Shape Abstraction via Neural Sweepers
No full textShape abstraction is an important task for simplifying complex geometric structures while retaining essential features. Sweep surfaces, commonly found in human-made objects, aid in this process by effectively capturing and representing object geometry, thereby facilitating abstraction. In this paper, we introduce \papername, a novel approach to shape abstraction through sweep surfaces. We propose an effective parameterization for sweep surfaces, utilizing superellipses for profile representation and B-spline curves for the axis. This compact representation, requiring as few as 14 float numbers, facilitates intuitive and interactive editing while preserving shape details effectively. Additionally, by introducing a differentiable neural sweeper and an encoder-decoder architecture, we demonstrate the ability to predict sweep surface representations without supervision. We show the superiority of our model through several quantitative and qualitative experiments throughout the paper. Our code is available at https://mingrui-zhao.github.io/SweepNet/14 pages,20 figures, ECCV 202
Novel Protein Biomarkers and Therapeutic Targets for Type 1 Diabetes and Its Complications: Insights from Summary-Data-Based Mendelian Randomization and Colocalization Analysis
No full textMillions of patients suffer from type 1 diabetes (T1D) and its associated complications. Nevertheless, the pursuit of a cure for T1D has encountered significant challenges, with a crucial impediment being the lack of biomarkers that can accurately predict the progression of T1D and reliable therapeutic targets for T1D. Hence, there is an urgent need to discover novel protein biomarkers and therapeutic targets, which holds promise for targeted therapy for T1D. In this study, we extracted summary-level data on 4907 plasma proteins from 35,559 Icelanders and 2923 plasma proteins from 54,219 UK participants as exposures. The genome-wide association study (GWAS) summary statistics on T1D and T1D with complications were obtained from the R9 release results from the FinnGen consortium. Summary-data-based Mendelian randomization (SMR) analysis was employed to evaluate the causal associations between the genetically predicted levels of plasma proteins and T1D-associated outcomes. Colocalization analysis was utilized to investigate the shared genetic variants between the exposure and outcome. Moreover, transcriptome analysis and a protein–protein interaction (PPI) network further illustrated the expression patterns of the identified protein targets and their interactions with the established targets of T1D. Finally, a Mendelian randomization phenome-wide association study evaluated the potential side effects of the identified core protein targets. In the primary SMR analysis, we identified 72 potential protein targets for T1D and its complications, and nine of them were considered crucial protein targets. Within the group were five risk targets and four protective targets. Backed by evidence from the colocalization analysis, the protein targets were classified into four tiers, with MANSC4, CTRB1, SIGLEC5 and MST1 being categorized as tier 1 targets. Delving into the DrugBank database, we retrieved 11 existing medications for T1D along with their therapeutic targets. The PPI network clarified the interactions among the identified potential protein targets and established ones. Finally, the Mendelian randomization phenome-wide association study corroborated MANSC4 as a reliable target capable of mitigating the risk of various forms of diabetes, and it revealed the absence of adverse effects linked to CTRB1, SIGLEC5 and MST1. This study unveiled many protein biomarkers and therapeutic targets for T1D and its complications. Such advancements hold great promise for the progression of drug development and targeted therapy for T1D
Proteome-Wide Mendelian Randomization and Colocalization Analysis Identify Therapeutic Targets for Knee and Hip Osteoarthritis
No full textOsteoarthritis (OA) is a common degenerative disease. Although some biomarkers and drug targets of OA have been discovered and employed, limitations and challenges still exist in the targeted therapy of OA. Mendelian randomization (MR) analysis has been regarded as a reliable analytic method to identify effective therapeutic targets. Thus, we aimed to identify novel therapeutic targets for OA and investigate their potential side effects based on MR analysis. In this study, two-sample MR, colocalization analysis, summary-data-based Mendelian randomization (SMR) and Mendelian randomization phenome-wide association study (MR-PheWAS) were conducted. We firstly analyzed data from 4907 plasma proteins to identify potential therapeutic targets associated with OA. In addition, blood expression quantitative trait loci (eQTLs) data sources were used to perform additional validation. A protein–protein interaction (PPI) network was also constructed to delve into the interactions among identified proteins. Then, MR-PheWASs were utilized to assess the potential side effects of core therapeutic targets. After MR analysis and FDR correction, we identified twelve proteins as potential therapeutic targets for knee OA or hip OA. Colocalization analysis and additional validation supported our findings, and PPI networks revealed the interactions among identified proteins. Finally, we identified MAPK3 (OR = 0.855, 95% CI: 0.791–0.923, p = 6.88 × 10−5) and GZMK (OR = 1.278, 95% CI: 1.131–1.444, p = 8.58 × 10−5) as the core therapeutic targets for knee OA, and ITIH1 (OR = 0.847, 95% CI: 0.784–0.915, p = 2.44 × 10−5) for hip OA. A further MR phenome-wide association study revealed the potential side effects of treatments targeting MAPK3, GZMK, and ITIH1. This comprehensive study indicates twelve plasma proteins with potential roles in knee and hip OA as therapeutic targets. This advancement holds promise for the progression of OA drug development, and paves the way for more efficacious treatments of OA
Hybrid CFRP light alloy wheel
No full textLAUREA MAGISTRALENel processo di sviluppo di una nuova ruota per una moto, è necessario aggiungere 4 carbon-fiber dischi al cerchione.
Vogliamo vedere che, nelle condizioni di carico reali, è possibile o no i carbon-fiber dischi essere staccata dal cerchio di magnesio. Simuliamo il sistema ruota in Abaqus e analizzare il risultato, otteniamo la distribuzione della forza e discutiamo il peeling off.In the process of the development of a new light alloy wheel for a motor bike, we need to add 4 carbon-fiber discs to the wheel rim.
We want to see that under the real load conditions, the carbon-fiber discs will or not be peeled off from the magnesium wheel rim. By simulating the wheel system in Abaqus and analyzing the result, we get the force distribution and discuss the peeling off
Macro Analysis on Apple Stock In order to determine investment value of Apple
No full textThe purpose of this article is to address the question of whether Apple is worth investing in by analyzing investment data on Apple’s stock and Apple’s own data. In this article, the author assumes 10,000 shares of Apple Inc stock from January 1, 2020, until August 2, 2022, and uses Yahoo Finance’s historical data to calculate past earnings levels, combined with the author’s macro analysis of Apple’s economic conditions and market conditions to conclude that Apple is well worth investing in over the next 3-5 years
Application of Seasonal ARIMA Model in Forecasting the Exchange Rate: Taking RMB to USD as an Example
No full textForecasting exchange rate is very profitable and crucial. Realizing the forecasting of the exchange rate means that personal investors can do arbitrage; For the policy makers, it means that they can optimize their fiscal policy and monetary policy. The article has used seasonal ARIMA model in terms of forecasting the RMB to USD exchange rate, and captures the seasonal factors of the RMB to USD exchange rate which is a time series better. First, the author deals with the data by using first-order seasonal difference；then,the author applies the auto ARIMA model in Rstudio to fit the model with the data, receiving the ARIMA(4,2,1)(0,1,0)(365). After that, the author forecasts the RMB to USD exchange rate in the next 90 days. Finally, the author does the residual test, and discusses the autocorrelation,fitting degree, and whether or not it is overfitted of the model. The conclusion of the writer is that the RMB to USD exchange rate will fall in the next 90 days
Multi-way Theta-Join Based on CMD Storage Method
No full textIn the era of the Big Data, how to analyze such a vast quantity of data is a challenging problem, and conducting a multi-way theta-join query is one of the most time consuming operations. MapReduce has been mentioned most in the massive data processing area and some join algorithms based on it have been raised in recent years. However, MapReduce paradigm itself may not be suitable to some scenarios and multi-way theta-join seems to be one of them. Many multi- way theta-join algorithms on traditional parallel database have been raised for many years, but no algorithm has been mentioned on the CMD (coordinate modulo distribution) storage method, although some algorithms on equal-join have been proposed. In this paper, we proposed a multi-way theta-join method based on CMD, which takes the advantage of the CMD storage method. Experiments suggest that it's a valid and efficient method which achieves significant improvement compared to those applied on the MapReduce
Therapeutic Potential of Exosomes in Tendon and Tendon–Bone Healing: A Systematic Review of Preclinical Studies
No full textExosomes have been proven to play a positive role in tendon and tendon–bone healing. Here, we systematically review the literature to evaluate the efficacy of exosomes in tendon and tendon–bone healing. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a systematic and comprehensive review of the literature was performed on 21 January 2023. The electronic databases searched included Medline (through PubMed), Web of Science, Embase, Scopus, Cochrane Library and Ovid. In the end, a total of 1794 articles were systematically reviewed. Furthermore, a “snowball” search was also carried out. Finally, forty-six studies were included for analysis, with the total sample size being 1481 rats, 416 mice, 330 rabbits, 48 dogs, and 12 sheep. In these studies, exosomes promoted tendon and tendon–bone healing and displayed improved histological, biomechanical and morphological outcomes. Some studies also suggested the mechanism of exosomes in promoting tendon and tendon–bone healing, mainly through the following aspects: (1) suppressing inflammatory response and regulating macrophage polarization; (2) regulating gene expression, reshaping cell microenvironment and reconstructing extracellular matrix; (3) promoting angiogenesis. The risk of bias in the included studies was low on the whole. This systematic review provides evidence of the positive effect of exosomes on tendon and tendon–bone healing in preclinical studies. The unclear-to-low risk of bias highlights the significance of standardization of outcome reporting. It should be noted that the most suitable source, isolation methods, concentration and administration frequency of exosomes are still unknown. Additionally, few studies have used large animals as subjects. Further studies may be required on comparing the safety and efficacy of different treatment parameters in large animal models, which would be conducive to the design of clinical trials
Targeting and Modeling Immune Resistance in Lung Cancer
No full textThe general metadata -- e.g., title, author, abstract, subject headings, etc. -- is publicly available, but access to the submitted files is restricted to UT Southwestern campus access and/or authorized UT Southwestern users.Lung cancer causes most cancer-associated death both in U.S. and worldwide. Immune checkpoint blockade has achieved durable therapeutic effects in some lung cancer patients. The mechanism of immune escape in lung cancer merits further investigation to improve the efficacy of immune checkpoint blockade and other treatments. This thesis is focused on targeting innate immune resistance in small cell lung cancer (SCLC) and modeling human non-small cell lung cancer (NSCLC) in genetically engineered mouse models (GEMMs). I observed that SCLC escapes from innate immune surveillance by down-regulating NK cell-activating ligands. Histone deacetylase (HDAC) inhibitor could restore expression of NK cell-activating ligands and trigger anti-tumor immunity in vivo. HDAC inhibitors can be potential therapeutics for SCLC. Besides, I generated a NSCLC GEMM with high tumor mutational burden (TMB) by incorporating PoleP286R. PoleP286R GEMM with wildtype p53 is sensitive to immune checkpoint blockade (ICB). Loss of p53 and tumor heterogeneity contributed to immune escape in this high TMB mouse model. This ICB-sensitive, high TMB model can be utilized to explore novel immunotherapy and study novel mechanism of immune resistance of NSCLC
Dependability and Security in Medical Information System
No full textThis article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Medical Information Systems (MIS) help medical practice and health care significantly. Security and dependability are two increasingly important factors for MIS nowadays. In one hand, people would be willing to step into the MIS age only when their privacy and integrity can be protected and guaranteed with MIS systems. On the other hand, only secure and reliable MIS systems would provide safe and solid medical and health care service to people. In this paper, we discuss some new security and reliability technologies which are necessary for and can be integrated with existing MISs and make the systems highly secure and dependable. We also present an implemented Middleware architecture which has been integrated with the existing VISTA/CPRS system in the U.S. Department of Veterans Affairs seamlessly and transparently
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