Dyslipidaemia Associated with Type 2 Diabetics with Micro and Macrovascular Complications among Ghanaians

In this study, differences in lipid levels amongst diabetics with and without complications were assessed to determine lipid disorders that are associated with diabetic complications other than cardiovascular diseases. A Cross sectional study design was employed. The study included 288 diabetics and 108 non diabetics with different types of complications such as hypertension, nephropathy, neuropathy, and retinopathy. The mean serum total cholesterol was higher in patients with complications compared to those without complications and the non-diabetic controls. The normotensive diabetic patients had the lowest total cholesterol among the diabetic patients’ groups (4.65 ± 0.17 mmol/l) compared to the diabetics with hypertension (6.051 ± 0.20 mmol/l), retinopathy (6.26 ± 0.29 mmol/l), neuropathy (5.80 ± 0.17 mmol/l) and nephropathy patients 5.74 ± 0.26 mmol/l (P < 0.05). The prevalence of dyslipidaemia among diabetic subjects was between 19.2 and 84.0%. The study shows that, in addition to macrovascular complications, dyslipidaemia is common in type 2 diabetes mellitus patients with microvascular complications.     

Markers of isometric training intensity and reductions in resting blood pressure

In this study, we examined the correlations between selected markers of isometric training intensity and subsequent reductions in resting blood pressure. Thirteen participants performed a discontinuous incremental isometric exercise test to volitional exhaustion at which point mean torque for the final 2-min stage (2min-torque(peak)) and peak heart rate peak (HR(peak)) were identified. Also, during 4 weeks of training (3 sessions per week, comprising 4?×?2?min bilateral leg isometric exercise at 95% HR(peak)), heart rate (HR(train)), torque (Torque(train)), and changes in EMG amplitude (ΔEMG(amp)) and frequency (ΔEMG(freq)) were determined. The markers of training intensity were: Torque(train) relative to the 2min-torque(peak) (%2min-torque(peak)), EMG relative to EMG(peak) (%EMG(peak)), HR(train) ΔEMG(amp), ΔEMG(freq), and %MVC. Mean systolic (-4.9 mmHg) and arterial blood pressure (-2.7mmHg) reductions correlated with %2min-torque(peak) (r?=?-0.65, P?=?0.02 and r?=?-0.59, P?=?0.03), ΔEMG(amp) (r?=?0.66, P?=?0.01 and r?=?0.59, P?=?0.03), ΔEMG(freq) (r?=?-0.67, P?=?0.01 and r?=?-0.64, P?=?0.02), and %EMG(peak) (systolic blood pressure only; r?=?-0.63, P?=?0.02). These markers best reflect the association between isometric training intensity and reduction in resting blood pressure observed after bilateral leg isometric exercise training.     

健身锻炼心理预测因素与运动损伤的相关性研究

目的:从运动心理学角度探讨大众健身人群风险认知、风险承担、运动能力判断、运动损伤经历等心理预测因素与运动损伤的相关性,同时测定以上因素对实际健身锻炼中运动损伤的预测效度,并探究其间的性别差异,旨在为进一步有效减少和预防运动损伤提供理论依据.方法:从健身俱乐部新入会的学员中,随机选取300名(男性150人,女性150人)年龄在26～35岁之间的健康成年志愿者组成实验组,进行为期12周,每周3～4次的健身锻炼.要求受试者在俱乐部每次锻炼前及时记录并提供风险认知、风险承担、运动能力判断及运动损伤经历等信息.利用运动损伤风险量表(RISSc)、风险承担行为量表(RTB)和李克特五级评分法(Likert-Type Scale)等对以上因素进行测试与评价.之后,对实验数据进行相关性分析、多元Logistic回归分析和多元方差分析等统计学处理.结果:1)“风险认知”并不与“风险承担”或“运动损伤”呈负相关;2)低水平的“风险认知”和“运动能力判断”使锻炼者受伤风险显著增加,其比值比( ORs)区间为:3.79～7.95;3)“运动能力高估”与“运动损伤”呈正相关;4)“运动能力判断”与“风险承担”呈正相关;5)“风险承担”与“运动能力高估”、“运动损伤”或“运动损伤经历”之间不存在相关性;6)“运动损伤经历”与运动损伤之间也不存在相关性;7)女性的“风险认知”水平比男性高,“风险承担”水平比男性低;但在“运动能力判断”和“运动能力高估”上,并无性别差异,且随后男性和女性在健身锻炼中发生的运动损伤量较为接近.结论:1)健身锻炼心理预测因素中,“风险认知”不与运动损伤呈负相关;“运动能力高估”与运动损伤呈正相关;“风险承担”与运动损伤之间无相关性.2)低水平的“风险认知”和“运动能力判断”是健身锻炼者发生运动损伤的重要心理危险因素;3)女性风险认知力比男性高,运动能力判断(高估)与男性相似,风险承担行为比男性少,且易受过去运动损伤经历的影响.     

Using automated analysis to assess middle school students' competence with scientific argumentation

Argumentation is fundamental to science education, both as a prominent feature of scientific reasoning and as an effective mode of learning—a perspective reflected in contemporary frameworks and standards. The successful implementation of argumentation in school science, however, requires a paradigm shift in science assessment from the measurement of knowledge and understanding to the measurement of performance and knowledge in use. Performance tasks requiring argumentation must capture the many ways students can construct and evaluate arguments in science, yet such tasks are both expensive and resource-intensive to score. In this study we explore how machine learning text classification techniques can be applied to develop efficient, valid, and accurate constructed-response measures of students' competency with written scientific argumentation that are aligned with a validated argumentation learning progression. Data come from 933 middle school students in the San Francisco Bay Area and are based on three sets of argumentation items in three different science contexts. The findings demonstrate that we have been able to develop computer scoring models that can achieve substantial to almost perfect agreement between human-assigned and computer-predicted scores. Model performance was slightly weaker for harder items targeting higher levels of the learning progression, largely due to the linguistic complexity of these responses and the sparsity of higher-level responses in the training data set. Comparing the efficacy of different scoring approaches revealed that breaking down students' arguments into multiple components (e.g., the presence of an accurate claim or providing sufficient evidence), developing computer models for each component, and combining scores from these analytic components into a holistic score produced better results than holistic scoring approaches. However, this analytical approach was found to be differentially biased when scoring responses from English learners (EL) students as compared to responses from non-EL students on some items. Differences in the severity between human and computer scores for EL between these approaches are explored, and potential sources of bias in automated scoring are discussed.     

Digital Museums and Diverse Cultural Knowledges: Moving Past the Traditional Catalog

Web 2.0 technologies have introduced increasingly participatory practices to creating content, and museums are becoming interested in the potentials of “Museum 2.0” for reaching and engaging with new audiences. As technological advances are opening up the ways in which museums share information about the objects in their collections, the means by which museums create, handle, process, and transmit knowledge has become more transparent. For this to be done effectively, however, some underlying contradictions must be resolved between museum practices, which privilege the account of the “expert,” and distributed social technology practices, whose strengths lie in allowing for many, sometimes contradictory, perspectives. This article presents a theoretical position and framework for the adaptation of Web 2.0 technologies within the traditional work of the museum, in ways that support the generation and representation of knowledge in, by, and for diverse communities. We then expand on this theoretical perspective by discussing several case studies of exploratory work in this area, and close the article by presenting a few tactical, bottom-up initiatives that museums and distributed communities can take to facilitate the diffusion of this new conceptual framework. Though the subject of this article is online museums, the issues are relevant to all online collections, in particular portals, online public access catalogs (OPAC), and content management systems.