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关键词： activities of daily living   cognitive function   glycemic control   mortality   older diabetes  

摘要： Aim Although the glycemic target in older diabetes patients is based on cognition, activities of daily living and multimorbidity in the Japanese guideline, evidence of the relationships is limited. Thus, we aimed to assess the relationship between functional category and mortality in older people with diabetes. Methods We evaluated the data of 843 older diabetes patients in a 6-year prospective study, and the association between functional categories and all-cause mortality. The patients were divided into three functional categories based on cognition, instrumental activities of daily living and basic activities of daily living using the Mini-Mental State Examination, Tokyo Metropolitan Institute of Gerontology Index of Competence and Barthel Index at baseline, respectively (model 1). Those with multimorbidity (>= 4 of 8 morbidities) were classified into category III (model 2). The functional category assessed using eight items from the Tokyo Metropolitan Institute of Gerontology Index of Competence and Barthel Index was also constructed (model 3). Hazard ratios and 95% confidence intervals were calculated in the Cox regression analysis using age, sex, body mass index, glycated hemoglobin level, total cholesterol level, estimated glomerular filtration rate and frequency of severe hypoglycemia as covariates. Results During the 6-year follow up, 64 incident mortalities occurred. The hazard ratios for mortality in categories II and III (as the reference of category I) were 1.83 (95% confidence interval 1.06-3.14, P = 0.030) and 3.05 (95% confidence interval 1.12-8.26, P = 0.029) after adjustment for covariates, respectively (model 1). Models 2 and 3 showed similar associations between functional category and mortality. Conclusions The functional categories predicted all-cause mortality in older adults with diabetes. Geriatr Gerontol Int 2021;center dot center dot: center dot center dot-center dot center dot.

摘要： We prove that every finite symmetric integral tensor category C with the Chevalley property over an algebraically closed field k of characteristic p > 2 admits a symmetric fiber functor to the category of supervector spaces. This proves Ostrik's conjecture [25, Conjecture 1.3] in this case. Equivalently, we prove that there exists a unique finite supergroup scheme G over k and a grouplike element epsilon is an element of kG of order <= 2, whose action by conjugation on G coincides with the parity automorphism of G, such that C is symmetric tensor equivalent to Rep(G, epsilon). In particular, when C is unipotent, the functor lands in Vec, so C is symmetric tensor equivalent to Rep(U) for a unique finite unipotent group scheme U over k. We apply our result and the results of [17] to classify certain finite dimensional triangular Hopf algebras with the Chevalley property over k (e.g., local), in group scheme-theoretical terms. Finally, we compute the Sweedler cohomology of restricted enveloping algebras over an algebraically closed field k of characteristic p > 0, classify associators for their duals, and study finite dimensional (not necessarily triangular) local quasi-Hopf algebras and finite (not necessarily symmetric) unipotent tensor categories over an algebraically closed field k of characteristic p > 0. The appendix by K. Coulembier and P. Etingof gives another proof of the above classification results using the recent paper [4], and more generally, shows that the maximal Tannakian and super-Tannakian subcategory of a symmetric tensor category over a field of characteristic not equal 2 is always a Serre subcategory.

关键词： Exact category   Divisible object   Flat object   Cotorsion pair   Finitely accessible additive category   Module category   Pure short exact sequence   Simple module   Jacobson radical  

摘要： For a Quillen exact category C endowed with two exact structures D and E such that E subset of D an object X of C is called E-divisible (respectively E-flat) if every short exact sequence from 7, starting (respectively ending) with X belongs to E. We continue our study of relatively divisible and relatively flat objects in Quillen exact categories with applications to finitely accessible additive categories and module categories. We derive consequences for exact structures generated by the simple modules and the modules with zero Jacobson radical.

关键词： Bayesian modeling   latent variable   multivariate longitudinal data analysis   Ornstein-Uhlenbeck process   oscillating and nonoscillating processes  

摘要： We propose a Bayesian latent Ornstein-Uhlenbeck (OU) model to analyze unbalanced longitudinal data of binary and ordinal variables, which are manifestations of fewer continuous latent variables. We focus on the evolution of such latent variables when they continuously change over time. Existing approaches are limited to data collected at regular time intervals. Our proposal makes use of an OU process for the latent variables to overcome this limitation. We show that assuming real eigenvalues for the drift matrix of the OU process, as is frequently done in practice, can lead to biased estimates and/or misleading inference when the true process is oscillating. In contrast, our proposal allows for both real and complex eigenvalues. We illustrate our proposed model with a motivating dataset, containing patients with amyotrophic lateral sclerosis disease. We were interested in how bulbar, cervical, and lumbar functions evolve over time.

关键词： Extraction  

摘要： Extraction of pattern class associated discriminative subspace is critical to many pattern classification problems. Traditionally, pattern class labels are regarded as indicators to discriminate between pattern classes. In this work, a novel indicator model is proposed to extract discriminant subspace by projecting samples onto a space where the projected categories are mutually orthogonal and in-category normalized. Category orthonormal property and its connections to discriminative subspace extraction are derived. It is shown that the proposed method has a strong connection with the existing Fukunaga-Koontz Transformation but extends the category number from two to multiple. For applications with a large dimension size but limited number of samples, an analytic least-norm solver is developed for calculating the projection function. A discriminative subspace extraction method for multiple classes is proposed and is evaluated by a combination with classifiers. Experiments demonstrate a promising result of using the extracted category orthonormal subspace for multi-class subspace extraction when sample number is small. (c) 2021 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

关键词： Sentiment analysis   Attention mechanism   Convolutional neural network   Text classification  

摘要： The aspect-category sentiment analysis can provide more and deeper information than the document-level sentiment analysis, because it aims to predict the sentiment polarities of different aspect categories in the same text. The main challenge of aspect-category sentiment analysis is that different aspect categories may present different polarities in the same text. Previous studies combine the Long Short-Term Memory (LSTM) and attention mechanism to predict the sentiment polarity of the given aspect category, but the LSTM-based methods are not really bidirectional text feature extraction methods. In this paper, we propose a multi-task aspect-category sentiment analysis model based on RoBERTa (Robustly Optimized BERT Pre-training Approach). Treating each aspect category as a subtask, we employ the RoBERTa based on deep bidirectional Transformer to extract features from both text and aspect tokens, and apply the cross-attention mechanism to guide the model to focus on the features most relevant to the given aspect category. According to the experimental results, the proposed model outperforms other models for comparison in aspect-category sentiment analysis. Furthermore, the influencing factors of our proposed model are also analyzed.

关键词： Radioactive   Waste tracking system   Low and intermediate level radioactive waste   Waste classification   Re-establishment waste classification  

摘要： Entities generating low and intermediate-level radioactive waste, including the nuclear power plant (KHNP), Korea Atomic Energy Research Institute, and KEPCO Nuclear Fuel Company, are currently managing the established waste classification criteria and waste tracking system (WTS). However, management thereof remains inefficient;thus, an integrated approach is required. This study examined the establishment of an integrated WTS in Korea based on an analysis of domestic and overseas systems to consolidate the classification criteria of the different entities. Furthermore, codes were assigned to locations where waste is processed and stored to offer scenarios based on movements between these locations.

关键词： Head-related transfer function   Individualization   Spectral notch   Pinna   Median plane   Virtual reality  

摘要： An authentic approach to present three-dimensional acoustical sensation to everyone is to provide head-related transfer functions (HRTFs) that are exactly adapted to each listener. This approach is called the individualization of HRTFs. In order to generate individualized HRTFs, the present study proposes a modeling method of HRTFs that extracts the frequency bins in which spectral notches (N1 and N2) are included. The frequency bins for N1 and N2 were classified into two categories based on the just noticeable difference in notch frequency with regard to the vertical angle perception of a sound image. Then, discriminant analyses were carried out as objective variables of the category of each of the N1 and N2 frequency bins and as explanatory variables of ten anthropometric parameters of pinnae. The results show that the categories of N1 and N2 frequency bins for the front direction can be estimated with accuracies of 83.1% and 77.8%, respectively. For the rear direction, the accuracies of the category estimation of N1 and N2 were 74.3% and 77.1%, respectively. (C) 2021 Elsevier Ltd. All rights reserved.