Women with endometriosis have higher comorbidities: Analysis of domestic data in Taiwan

AbstractEndometriosis, defined by the presence of viable extrauterine endometrial glands and stroma, can grow or bleed cyclically, and possesses characteristics including a destructive, invasive, and metastatic nature. Since endometriosis may result in pelvic inflammation, adhesion, chronic pain, and infertility, and can progress to biologically malignant tumors, it is a long-term major health issue in women of reproductive age. In this review, we analyze the Taiwan domestic research addressing associations between endometriosis and other diseases. Concerning malignant tumors, we identified four studies on the links between endometriosis and ovarian cancer, one on breast cancer, two on endometrial cancer, one on colorectal cancer, and one on other malignancies, as well as one on associations between endometriosis and irritable bowel syndrome, one on links with migraine headache, three on links with pelvic inflammatory diseases, four on links with infertility, four on links with obesity, four on links with chronic liver disease, four on links with rheumatoid arthritis, four on links with chronic renal disease, five on links with diabetes mellitus, and five on links with cardiovascular diseases (hypertension, hyperlipidemia, etc.). The data available to date support that women with endometriosis might be at risk of some chronic illnesses and certain malignancies, although we consider the evidence for some comorbidities to be of low quality, for example, the association between colon cancer and adenomyosis/endometriosis. We still believe that the risk of comorbidity might be higher in women with endometriosis than that we supposed before. More research is needed to determine whether women with endometriosis are really at risk of these comorbidities

An exploratory study of the adjustment of Chinese immigrants in temporary housing areas

published_or_final_versionSocial WorkMasterMaster of Social Wor

A Context Aware Smart Classroom Architecture for Smart Campuses

The Smart campus is a concept of an education institute using technologies, such as information systems, internet of things (IoT), and context-aware computing, to support learning, teaching, and administrative activities. Classrooms are important building blocks of a school campus. Therefore, a feasible architecture for building and running smart classrooms is essential for a smart campus. However, most studies related to the smart classroom are focused on studying or addressing particular technical or educational issues, such as networking, AI applications, lecture quality, and user responses to technology. In this study, an architecture for building and running context-aware smart classrooms is proposed. The proposed architecture consists of three parts including a prototype of a context-aware smart classroom, a model for technology integration, and supporting measures for the operation of smart classrooms in this architecture. The classroom prototype was designed based on our study results and a smart classroom project in Ming Chuan University (MCU). The integration model was a layered model uses Raspberry Pi in the bottom layer of the model to integrate underlying technologies and provide application interfaces to the higher layer applications for the ease of building context-aware smart classroom applications. As a result, application interfaces were implemented using Raspberry Pi based on the proposed technology integration model, and a context-aware energy-saving smart classroom application was implemented based on the proposed classroom prototype and the implemented web application interface. The result shows that, in terms of technology, the proposed architecture is feasible for building context-aware smart classrooms in smart campuses

An ARM-Based Q-Learning Algorithm

Abstract. This article presents an algorithm that combines a FAST-based algorithm (Flexible Adaptable-Size Topology), called ARM, and Q-learning algorithm. The ARM is a self organizing architecture. Dynamically adjusting the size of sensitivity regions of each neuron and adaptively pruning one of the redundant neurons, the ARM can preserve resources (available neurons) to accommodate more categories. The Q-learning is a dynamic programming-based reinforcement learning method, in which the learned action-value function, Q, directly approximates Q*, the optimal action-value function, independent of the policy being followed. In the proposed method, the ARM acts as a cluster to categorize input vectors from the outside world. Clustered results are then sent to the Q-learning architecture in order that it learns to present the best actions to the outside world. The effect of the algorithm is shown through computer simulations of the well-known control of balancing an inverted pendulum on a cart.

Biodegradable Polymeric Membranes for Organic Solvent/Water Pervaporation Applications

Biodegradable polymers are a green alternative to apply as the base membrane materials in versatile processes. In this study, two dense membranes were made from biodegradable PGS (poly(glycerol sebacate)) and APS (poly(1,3-diamino-2-hydroxypropane-co-polyol sebacate)), respectively. The prepared membranes were characterized by FE-SEM, AFM, ATR-FTIR, TGA, DSC, water contact angle, and degree of swelling, in comparison with the PDMS (polydimethylpolysiloxane) membrane. In the pervaporation process for five organic solvent/water systems at 37 °C, both biodegradable membranes exhibited higher separation factors for ethanol/water and acetic acid/water separations, while the PDMS membrane attained better effectiveness in the other three systems. In particular, a positive relationship between the separation factor and the swelling ratio of organic solvent to water (DSo/DSw) was noticed. In spite of their biodegradability, the stability of both PGS and APS membranes was not deteriorated on ethanol/water pervaporation for one month. Furthermore, these two biodegradable membranes were applied in the pervaporation of simulated ABE (acetone-butanol-ethanol) fermentation solution, and the results were comparable with those reported in the literature