Risk of cardiovascular disease in Chinese patients with rheumatoid arthritis: a cross sectional study based on hospital medical records in 10 years

Objective: Though the risk of cardiovascular disease (CVD) in rheumatoid arthritis (RA) has been established in Western population, little is known about the risk in Chinese people with RA. Our objective was to estimate the risk of CVD in Chinese people with RA using hospital medical records data. Methods The inpatients medical record database 2005‐2015 of Sichuan provincial people’s hospital was examined. All individuals with a primary diagnosis of RA were included as cases, and those of osteoarthritis (OA) were included as controls, which consisted of the unmatched dataset. Then, RA cases and OA controls were matched by sex and age at 1:1 ratio, forming the matched dataset. The morbidity of CVD (including ischemia heart disease (IHD), congestive heart failure (CHF), et al), stroke and arthrosclerosis were extracted from the database, so as the demographic data and comorbidities related to CVD. Multiple logistic regression analysis was used to estimate the risk of CVD in RA adjusted for demographics and comorbidities using the unmatched dataset. Sensitivity analysis was conducted 1) considering interaction terms between RA and comorbidities, and 2) using multivariable conditional logistic regression for the matched dataset. Results: The unmatched data set comprised of 1824RA cases and 1995 OA controls and the matched dataset comprised of 1022 pairs of sex and age matched RA and OA patients. RA exhibited increased odds of prevalent CVD compared with OA, and the adjusted ORs (95%CIs) for CVD, stroke, IHD, CHF, and atherosclerosis were1.86(1.42‐2.43), 1.11(0.71‐1.74), 1.47(0.97‐2.24), 2.09(1.03‐4.22), and 2.49 (1.97‐3.13), respectively, and was 2.26 (1.29‐3.96) for IHD further adjusted for interaction term. The matched dataset analysis found similar results. Conclusions: Chinese people with RA were approximated 2 times more 1 likely to have CVD, IHD, CHF and atherosclerosis compared with those with OA. The findings justified the need of further longitudinal study to establish the causal‐relationship between RA and CVD and to estimate the precise risk in this population

Integrating high dimensional bi-directional parsing models for gene mention tagging

Motivation: Tagging gene and gene product mentions in scientific text is an important initial step of literature mining. In this article, we describe in detail our gene mention tagger participated in BioCreative 2 challenge and analyze what contributes to its good performance. Our tagger is based on the conditional random fields model (CRF), the most prevailing method for the gene mention tagging task in BioCreative 2. Our tagger is interesting because it accomplished the highest F-scores among CRF-based methods and second over all. Moreover, we obtained our results by mostly applying open source packages, making it easy to duplicate our results

Multiple Iteration of Weight Updates for Least Mean Square Adaptive Filter in Active Noise Control Application

The method of least mean square (LMS) is the commonly used algorithm in Adaptive filter due to its simplicity and robustness in implementation. In Active Noise Control application, a filtered reference signal is used prior to LMS algorithm to overcome the constraint on stability and convergence performance of the system due to the existence of the auxiliary path. This is known as Filtered-X LMS algorithm. In conventional Filtered-X LMS algorithm, each filter weight is updated once on every audio sample. This paper proposes the improved version of Filtered-X LMS algorithm with the use of multiple iteration of filter weight on every sample of audio signal. The proposed work uses field programmable gate arrays to realize real-time simulation on hardware for the noise signal of 500 Hz. Results from the real-time hardware simulations have shown much faster error convergence and better adaptation performance for different selections of learning constant μ, as compared with the conventional method

Nonlinear THF-FXLMS algorithm for active noise control with loudspeaker nonlinearity

Adaptive algorithms are prevalently applied in the design of nonlinear active noise control (ANC) systems. The most important nonlinearity in ANC is the saturation effect produced by the electro-acoustical sensors and transducers. The dominant saturation nonlinearity is in the transducers, which can be represented by a Wiener model. An effective solution to mitigate such nonlinear distortion is to employ the Nonlinear Filtered-X Least Mean Square (NLFXLMS) algorithm. The controller compensates the nonlinearity using a model of the saturation effect represented by the scaled error function (SEF). However, the NLFXLMS is limited by two practical issues such that the degree of nonlinearity has to be known in advance and the SEF cannot be evaluated in real time. In this work, the NLFXLMS algorithm is modified by incorporating the tangential hyperbolic function (THF) to model the saturation effect of the loudspeaker. The proposed THF-NLFXLMS algorithm, models the nonlinear secondary path and applies the estimated degree of nonlinearity in the control algorithm design. The results show that the Wiener secondary path, with saturation nonlinearity represented by SEF, can be modelled by THF with a certain degree of accuracy and can yield a reasonable estimate of the degree of nonlinearity. The performance of the proposed algorithm is comparable with the benchmark NLFXLMS and is superior to the conventional FXLMS as well as the second order Volterra algorithm of similar computational complexity with the proposed algorithm

Study on IoT and Big Data Analysis of 12” 7 nm Advanced Furnace Process Exhaust Gas Leakage

Modern FAB uses a large number of high-energy processes, including plasma, CVD, and ion implantation. Furnaces are one of the important tools for semiconductor manufacturing. According to the requirements of conversion production management, FAB installed a set of IoT-based research based on 12″ 7 nm-level furnaces chip process. Two furnace processing tool measurement points were set up in a 12-inch 7 nm-level factory in Hsinchu Science Park, Taiwan, this is a 24-hour continuous monitoring system, the data obtained every second is sequentially send and stored in the cloud system. This study will be set in the cloud database for big data analysis and decision-making. The lower limit of TEOS, C2H4, CO is 0.4, 1.5, 1 ppm. Semiconductor process, so that IoT integration and big data operations can be performed in all processes, this is an important step to promote FAB intelligent production, and also an important contribution to this research

Preparation of TiO2 Nanocrystallite Powders Coated with 9 mol% ZnO for Cosmetic Applications in Sunscreens

The preparation of TiO2 nanocrystallite powders coated with and without 9 mol% ZnO has been studied for cosmetic applications in sunscreens by a co-precipitation process using TiCl4 and Zn(NO3)2·6H2O as starting materials. XRD results show that the phases of anatase TiO2 and rutile TiO2 coexist for precursor powders without added ZnO (T-0Z) and calcined at 523 to 973 K for 2 h. When the T-0Z precursor powders are calcined at 1273 K for 2 h, only the rutile TiO2 appears. In addition, when the TiO2 precursor powders contain 9 mol% ZnO (T-9Z) are calcined at 873 to 973 K for 2 h, the crystallized samples are composed of the major phase of rutile TiO2 and the minor phases of anatase TiO2 and Zn2Ti3O8. The analyses of UV/VIS/NIR spectra reveal that the absorption of the T-9Z precursor powders after being calcined has a red-shift effect in the UV range with increasing calcination temperature. Therefore, the TiO2 nanocrystallite powders coated with 9 mol% ZnO can be used as the attenuate agent in the UV-A region for cosmetic applications in sunscreens

Risk of cardiovascular disease in Chinese patients with rheumatoid arthritis: a cross sectional study based on hospital medical records in 10 years

Objective: Though the risk of cardiovascular disease (CVD) in rheumatoid arthritis (RA) has been established in Western population, little is known about the risk in Chinese people with RA. Our objective was to estimate the risk of CVD in Chinese people with RA using hospital medical records data.MethodsThe inpatients medical record database 2005‐2015 of Sichuan provincial people’s hospital was examined. All individuals with a primary diagnosis of RA were included as cases, and those of osteoarthritis (OA) were included as controls, which consisted of the unmatched dataset. Then, RA cases and OA controls were matched by sex and age at 1:1 ratio, forming the matched dataset. The morbidity of CVD (including ischemia heart disease (IHD), congestive heart failure (CHF), et al), stroke and arthrosclerosis were extracted from the database, so as the demographic data and comorbidities related to CVD. Multiple logistic regression analysis was used to estimate the risk of CVD in RA adjusted for demographics and comorbidities using the unmatched dataset. Sensitivity analysis was conducted 1) considering interaction terms between RA and comorbidities, and 2) using multivariable conditional logistic regression for the matched dataset.Results: The unmatched data set comprised of 1824RA cases and 1995 OA controls and the matched dataset comprised of 1022 pairs of sex and age matched RA and OA patients. RA exhibited increased odds of prevalent CVD compared with OA, and the adjusted ORs (95%CIs) for CVD, stroke, IHD, CHF, and atherosclerosis were1.86(1.42‐2.43), 1.11(0.71‐1.74), 1.47(0.97‐2.24), 2.09(1.03‐4.22), and 2.49 (1.97‐3.13), respectively, and was 2.26 (1.29‐3.96) for IHD further adjusted for interaction term. The matched dataset analysis found similar results.Conclusions: Chinese people with RA were approximated 2 times more 1 likely to have CVD, IHD, CHF and atherosclerosis compared with those with OA. The findings justified the need of further longitudinal study to establish the causal‐relationship between RA and CVD and to estimate the precise risk in this population