Antarctica Sea-Ice Oscillation and Its Possible Impact on Monsoon of South Sea

Antarctic sea-ice oscillation index with a seesaw pattern is defined using NCEP/NCAR reanalysis girds data of monthly Antarctica sea-ice concentration from 1979 to 2002. The relationships between the index of winter and the summer precipitations in China as well as the onset date of the summer East Asia monsoon are presented. The study result shows that the grids of correlation coefficients passed 5% confidence level between Antarctic sea-ice oscillation index and Antarctic sea-ice concentration are more than 1/3 of all grids of Antarctica sea-ice, that means the index can represent 1/3 sea-ice area. The winter index has a significant correlation with abnormal summer (June-August) precipitation in China. The area of positive correlation lies in the Yangtze River basin and its south, and that of negative correlation lies mainly in the north of Yangtze River basin. While the winter index is positive(negative), the onset date of South China Sea monsoon is earlier(later), with a probability of 79% (80%). Consequently, a conceptual modelis given in term of discussing the possible process between the winter Antarctic sea ice and the monsoon precipitation in China

Glucocorticoid-Induced Autophagy in Osteocytes

Glucocorticoid (GC) therapy is the most frequent cause of secondary osteoporosis. In this study we have demonstrated that GC treatment induced the development of autophagy, preserving osteocyte viability. GC treatment resulted in an increase in autophagy markers and the accumulation of autophagosome vacuoles in vitro and in vivo promoted the onset of the osteocyte autophagy, as determined by expression of autophagy markers in an animal model of GC-induced osteoporosis. An autophagy inhibitor reversed the protective effects of GCs. The effects of GCs on osteocytes were in contrast to tumor necrosis factor α (TNF-α), which induced apoptosis but not autophagy. Together this study reveals a novel mechanism for the effect of GC on osteocytes, shedding new insight into mechanisms responsible for bone loss in patients receiving GC therapy. © 2010 American Society for Bone and Mineral Research

An approach to construct Bayesian networks for use in living environment field, taking Chinese CCRCs as the example

Motivation: Fast population aging has been considered one of the most challenging demographic transitions globally. The influence of older adults’ living environment on their well-being cannot be ignored.Knowledge gap: Although the importance of living environment factors on the well-being of people has been widely recognized, the interaction between these factors and their interactive influence on the well-being of older people have not been quantified. Aim and objectives: This paper presents a detailed approach to develop a Bayesian network (Bns), focusing on constructing, parameterizing and quantitatively evaluating the Bns, with the ultimate purpose of revealing the impact of living environment on residents' well-being in Chinese Continuing Care Retirement Communities (CCRCs).Research method: Living environment variables that may affect well-being were first identified via comprehensive literature review. Two contextually appropriate scales were then selected to measure well-being. Based on this, we further developed the construction process of Bns for the CCRCs, including qualitative and quantitative parts.Preliminary findings: Fifteen living environment variables were identified, comprising community daily life service, urban infrastructure accessibility, community management and operation, greening space, safety, connection with family, social engagement, community daily support facilities, social connection within the community, walkability, community social activities engagement, community barrier-free infrastructure, health services, and age-friendly indoor environment. The Ryff Scale and the Short Form-36 Scale were considered appropriate for measuring well-being. Combining these findings, the process of developing a definite whole Bns approach for the CCRCs is proposed. Experts' viewpoints and Dempster-Shafer Theory (DST) are utilized to construct Bns. Knowledge Engineering Bayesian Networks (KBEN) are adopted to combine expert and data sources to parameterize and evaluate the Bns.Research significance: This research promotes the innovative application of Bns in environmental research, involving the elements and methods of constructing the model. Researchers can refer to the guidance and use it as a feasible instrument to apply to their research, which advances future investigations in the field

An Overview of Naturally Occurring Retirement Communities (NORCs) for Ageing in Place

As an alternative to ageing at home in the community, naturally occurring retirement communities (NORCs) have great potential to facilitate ageing in place; however, they have not attracted much research attention. This study conducts an overview of NORCs, aiming to examine the previous research in a comprehensive manner in order to explore how NORCs impact ageing in place, with the goal of guiding future research. The research presented here employs the content analysis method to review prior NORC-related studies and categorise research themes and findings following top-down coding principles. A total of 49 articles were selected from the Scopus and Web of Science databases, and the results show that the “social environment”, which was the most discussed topic (n = 24), provides the necessary mental support and physical motivation for older adults to live actively in NORCs, and that NORCs play a positive role in preserving public resources and promoting individual health. The limitations of this study include the fact that there is little public information on NORC programs and the subjective classification of themes, among others. This study acts as a foundation for future research on NORCs, which serve as a perfect model for healthy ageing in place

Enhanced Dual–Vector Model Predictive Control for PMSM Drives Using the Optimal Vector Selection Principle

The Dual–Vector model predictive control (DV–MPC) method can improve the steady–state control performance of motor drives compared to using the single–vector method in one switching cycle. However, this performance enhancement generally increases the computational burden due to the exponential increase in the number of vector selections, lowering the system’s dynamic response. Alternatively, limiting the vector combinations will sacrifice system steady–state performance. To address this issue, this paper proposes an enhanced DV–MPC method that can determine the optimal vector combinations along with their duration time within minimized calculation times. Compared to the existing DV–MPC methods, the proposed enhanced technique can achieve excellent steady–state performance while maintaining a low computational burden. These benefits have been demonstrated in the results from a 2.5k rpm permanent magnet synchronous motor drive

Diabetic kidney disease screening status and related factors: a cross-sectional study of patients with type 2 diabetes in six provinces in China

Abstract Objective To understand the awareness and practice of diabetic kidney disease (DKD) or nephropathy screening among community-based patients with type 2 diabetes in six provinces and cities in China, and to analyse the related factors affecting screening practices. Methods From December 2021 to March 2022, a cross-sectional survey was conducted using a structured questionnaire in 6230 patients with type 2 diabetes aged 18 years and older. The content of the questionnaire includes three parts: the general situation of diabetic patients (gender, age, ethnicity, marriage, education, occupation, etc.), DKD screening practices, and the evaluation of DKD screening services. Results 89.70% of the patients had their fasting blood glucose measured every six months, 21.12% of the patients had their glycosylated hemoglobin measured every six months, and only 13.11% and 9.34% of the patients had a urine protein-creatinine ratio test and estimated glomerular filtration rate test every 12 months. The proportions of glycosylated hemoglobin, urine protein-creatinine ratio, and estimated glomerular filtration rate were relatively high in young, northern, highly educated, and long-duration type 2 diabetic patients. Conclusion The results of this survey found that the proportion of urine protein-creatinine ratio testing, estimated glomerular filtration rate testing, and glycosylated hemoglobin testing in Chinese patients with type 2 diabetes was very low. Patients with type 2 diabetes in rural areas, southern areas, with low education level, and short course of disease have lower detection rates for DKD, and hence lower rates of prevention and treatment