Introduction to the wheelchair training's influence on the rehabilitation of patients

目的  通过轮椅训练提高患者掌握轮椅的技巧，保证患者乘坐轮椅时的安全，提高患者日常生活能力及社会参与能力。方法  通过轮椅基本技术动作练习、轮椅技巧动作训练、轮椅体育项目训练、社会实践检测。结果  患者轮椅训练前后对照，躯干的控制能力较前好转，ADL能力明显提高，社会参与能力增强。结论  轮椅训练可以使残疾人参与康复体育和社会活动的机会明显增加。Objective: Training to improve patient’s master of wheelchair technology to ensure the safety of patients in wheelchairs things to improve patients' daily living skills and social participation skills. Methods: By practicing basic techniques wheelchair, wheelchair technology movement training, wheelchair sports training, social practice test. Results: Wheelchair patients before and after control technology, the ability to control the trunk before it gets better, ADL ability as well as social participation improved significantly. Conclusion: Wheelchair training increased opportunities for people with disabilities to participate in the rehabilitation of sports and social activities.

Zero-shot Domain-sensitive Speech Recognition with Prompt-conditioning Fine-tuning

In this work, we propose a method to create domain-sensitive speech recognition models that utilize textual domain information by conditioning its generation on a given text prompt. This is accomplished by fine-tuning a pre-trained, end-to-end model (Whisper) to learn from demonstrations with prompt examples. We show that this ability can be generalized to different domains and even various prompt contexts, with our model gaining a Word Error Rate (WER) reduction of up to 33% on unseen datasets from various domains, such as medical conversation, air traffic control communication, and financial meetings. Considering the limited availability of audio-transcript pair data, we further extend our method to text-only fine-tuning to achieve domain sensitivity as well as domain adaptation. We demonstrate that our text-only fine-tuned model can also attend to various prompt contexts, with the model reaching the most WER reduction of 29% on the medical conversation dataset.Comment: F-T Liao and Y-C Chan contributed equall

Advanced glycation end products (AGEs) in relation to atherosclerotic lipid profiles in middle-aged and elderly diabetic patients

<p>Abstract</p> <p>Objectives</p> <p>To evaluate the association between AGEs and atherosclerotic lipid profiles among aging diabetic patients in Taiwan.</p> <p>Design and Methods</p> <p>After age and gender matching, we selected 207 diabetic subjects and 174 diabetic subjects with proteinuria. Lipid profiles, including total cholesterol (TC), triglycerides (TG), high density cholesterol-lipoprotein (HDL-C) and low density lipoprotein-cholesterol (LDL-C) were measured using standard methods. AGEs were measured with the immunoassay method.</p> <p>Results</p> <p>In general, males were heavier; however, females had higher AGEs, fasting glucose (GLU), TC, HDL-C and LDL-C levels than males, and had higher TC/HDL-C, LDL-C/HDL-C, and TG/HDL-C ratios compared to males. AGEs were more strongly correlated with TG levels and TCL/LDL-C, LDL-C/HDL-C and TG/HDL-C ratios when compared to glucose or hemoglobin A1c. Subjects had higher AGEs levels (≧ 2.0 AU) with more adverse lipid profiles.</p> <p>Conclusion</p> <p>AGEs seem to be a good biomarker to evaluate the association between diabetes and atherosclerotic disorders in aging diabetes.</p

A PEDICTION METHOD FOR THERMAL CONDUCTIVITY AND ELECTRIC CONDUCTIVITY OF NANOFLUIDS BASED ON PARTICLES AGGREGATION THEORY

ABSTRACT Nanoparticles in nanofluids are in the form of nanoparticle clusters caused by aggregation. In order to calculate the thermal and electric conductivities of the nanofluids, the growth process and three-dimensional space structure of the nanoparticle cluster in the host fluid was simulated, and then the thermal and electric conductivities of the cluster were calculated with the resistance network method. The thermal and electric conductivities of the nanofluid were calculated based on the simulated thermal and electric conductivities of nanoparticle clusters, the volume fraction of nanoparticle clusters to the nanofluid as well as the liquid molecule adsorption layer of the nanoparticle. The simulation method was validated by experimental data