A Proposed Course for High Risk Students Using Mediated Learning Units

No abstract provided by author

A Proposed Course for High Risk Students Using Mediated Learning Units

No abstract provided by author

Pressure Ulcer Risk and Prevention: Examining the Inter-Rater Reliability of the National Database of Nursing Quality Indicators® (NDNQI)

ABSTRACT Measuring and reporting performance have become the norm. The purpose of this descriptive multi-site (N = 36 NDNQI-participating hospitals) study was to examine the reliability of the National Database of Nursing Quality Indicators® (NDNQI®) pressure ulcer (PrU) risk and prevention measures. This is the first known study to examine the inter-rater reliability of these measures. Data for Part 1 of this two-part study were extracted from 1,637 patient records by 120 raters. One rater at each hospital was considered the "expert". Agreement between the expert and non-expert raters was calculated for the risk measures. Among the patients, 530 were "at risk" for PrU, and included in calculations of agreement for the prevention measures. In Part 2, raters completed an online survey about the methods they use to collect these data. Cohen's kappa values varied widely within and across hospitals. Because most patients were assessed for PrU risk, and those at risk received prevention, the prevalence of a "Yes" response was high suggesting prevalence-adjusted kappa (PAK) may be a better estimate of inter-rater reliability than Cohen's kappa. PAK values for: Skin assessment, PAK = .977, 95% CI [.966 - .989]; Risk assessment, PAK = .978, 95% CI [.964 -.993]; Time since last risk assessment, PAK = .790, 95% CI [.729 - .852]; Risk assessment scale, PAK = .997, 95% CI [.991 - 1.0]; Risk status, PAK = .877, 95% CI [.838 - .917]; Any prevention, PAK = .856, 95% [.769 - .943]; Skin assessment documented, PAK = .956, 95% CI [.904 - 1.0]; and Pressure-redistribution surface use, PAK = .839, 95% CI [.763 - .916] indicated substantial to near perfect agreement. PAK values for: Routine repositioning, PAK = .577, 95% CI [.494 - .661]; Nutritional support, PAK = .500, 95% CI [.418 - .581]; and Moisture management, PAK = .556, 95% CI [.469 - .643] indicated moderate agreement. Results provide support for the reliability of all (5) PrU risk measures, and three of six prevention measures. Areas of disagreement between the expert and non-expert raters should direct education to improve reliability. Results of the online survey suggest raters need further training on the NDNQI guidelines for PrU data collection

Capturing and Analyzing the Execution Control Flow of OpenMP Applications

An important aspect of understanding the behavior of applications with respect to their performance, overhead, and scalability characteristics is knowledge of their execution control flow. High level knowledge of which functions or constructs were executed after which other constructs allows reasoning about temporal application characteristics such as cache reuse. This paper describes an approach to capture and visualize the execution control flow of OpenMP applications in a compact way. Our approach does not require a full trace of program execution events but is instead based on a straightforward extension to the summary data already collected by an existing profiling tool. In multithreaded applications each thread may define its own independent flow of control, complicating both the recording as well as the visualization of the execution dynamics. Our approach allows for the full flexibility with respect to independent threads. However, the most common usage models of OpenMP have threads operate in a largely uniform way, synchronizing frequently at sequence points and diverging only to operate on different data items in worksharing constructs. Our approach accounts for this by offering a simplified representation of the execution control flow for threads with similar behavior

Condition monitoring and anomaly detection in cyber-physical systems

The modern industrial environment is equipping myriads of smart manufacturing machines where the state of each device can be monitored continuously. Such monitoring can help identify possible future failures and develop a cost-effective maintenance plan. However, it is a daunting task to perform early detection with low false positives and negatives from the huge volume of collected data. This requires developing a holistic machine learning framework to address the issues in condition monitoring of high-priority components and develop efficient techniques to detect anomalies that can detect and possibly localize the faulty components. This paper presents a comparative analysis of recent machine learning approaches for robust, cost-effective anomaly detection in cyber-physical systems. While detection has been extensively studied, very few researchers have analyzed the localization of the anomalies. We show that supervised learning outperforms unsupervised algorithms. For supervised cases, we achieve near-perfect accuracy of 98 percent (specifically for tree-based algorithms). In contrast, the best-case accuracy in the unsupervised cases was 63 percent :the area under the receiver operating characteristic curve (AUC) exhibits similar outcomes as an additional metric.Comment: 6 page

Formation problems of consolidated budget income in the Russian Federation in terms of Tomsk region

The article highlights the problems of increasing pressure on budgets in the territorial entity of the Russian Federation and therefore, the ability to mobilize financial resources to regional budgets of executive authorities. Industrial analysis of revenues got from the territory of Tomsk region is carried out, as well as the dynamics of income distribution due to the budget levels is examined. It is obvious that most of the revenues incoming from Tomsk Region, are credited to the federal budget. It can be explained by the development of oil and gas industry and high level of tax liabilities at such enterprises. The paper analyzes the structure of consolidated budget in Tomsk region to identify the basic sources of income. Furthermore, the dependence of revenues of regional and local budgets from the implemented federal fiscal policy is examined, the examples of the decisions that led to the falling revenues of the regional and local budgets are given

Factors Influencing the Impact of Depressive Symptoms on Physical Functional Capacity After Cardiac Rehabilitation

Purpose This study aims to determine (1) if depressive symptoms in the year following completion of cardiac rehabilitation impact physical functional capacity and (2) if exercise, perceived benefits and barriers, self-efficacy, and social support moderate this relationship. Design This longitudinal correlational secondary data analysis included 379 cardiovascular rehabilitation patients. Methods Participants completed measures of depression and potential moderating variables at baseline, 2 months, 6 months, and 12 months and 6-minute work test at baseline and 12 months and wore heart rate monitors to measure exercise for 12 months. Findings Poorer physical functional capacity was predicted by depressed mood score. This relationship was moderated by the percentage of time exercising in target heart rate zone and family support of exercise, but not by perceived benefits and barriers or self-efficacy for exercise. Conclusions Depressive symptoms negatively impact physical functional capacity, and this relationship is moderated by family support and the percentage of time exercising in target heart rate zone