Unsupervised learning to cluster the disease stages in parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder (after Alzheimer's disease) and directly affects upto 5 million people worldwide. The stages (Hoehn and Yaar) of disease has been predicted by many methods which will be helpful for the doctors to give the dosage according to it. So these methods were brought up based on the data set which includes about seventy patients at nine clinics in Sweden. The purpose of the work is to analyze unsupervised technique with supervised neural network techniques in order to make sure the collected data sets are reliable to make decisions. The data which is available was preprocessed before calculating the features of it. One of the complex and efficient feature called wavelets has been calculated to present the data set to the network. The dimension of the final feature set has been reduced using principle component analysis. For unsupervised learning k-means gives the closer result around 76% while comparing with supervised techniques. Back propagation and J4 has been used as supervised model to classify the stages of Parkinson's disease where back propagation gives the variance percentage of 76-82%. The results of both these models have been analyzed. This proves that the data which are collected are reliable to predict the disease stages in Parkinson's disease.

Simulation and optimisation techniques for sawmill yard operation : A literature review

Increasing costs and competitive business strategies are pushing sawmill enterprises to make an effort for optimization of their process management. Organizational decisions mainly concentrate on performance and reduction of operational costs in order to maintain profit margins. Although many efforts have been made, effective utilization of resources, optimal planning and maximum productivity in sawmill are still challenging to sawmill industries. Many researchers proposed the simulation models in combination with optimization techniques to address problems of integrated logistics optimization. The combination of simulation and optimization technique identifies the optimal strategy by simulating all complex behaviours of the system under consideration including objectives and constraints. During the past decade, an enormous number of studies were conducted to simulate operational inefficiencies in order to find optimal solutions. This paper gives a review on recent developments and challenges associated with simulation and optimization techniques. It was believed that the review would provide a perfect ground to the authors in pursuing further work in optimizing sawmill yard operations.

The kidney in different stages of the cardiovascular continuum

Patients with chronic kidney disease are at higher risk of developing cardiovascular disease. The complex, interaction between the kidney and the cardiovascular system is incompletely understood, particularly at the early stages of the cardiovascular continuum. The overall aim of this thesis was to clarify novel aspects of the interplay between the kidney and the cardiovascular system at different stages of the cardiovascular continuum; from risk factors such as insulin resistance, inflammation and oxidative stress, via sub-clinical cardiovascular damage such as endothelial dysfunction and left ventricular dysfunction, to overt cardiovascular death. This thesis is based on two community-based cohorts of elderly, Uppsala Longitudinal Study of Adult Men (ULSAM) and Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS). The first study, show that higher insulin sensitivity, measured with euglycemic-hyperinsulinemic clamp technique was associated to improve estimated glomerular filtration rate (eGFR) in participants with normal fasting plasma glucose, normal glucose tolerance and normal eGFR. In longitudinal analyses, higher insulin sensitivity at baseline was associated with lower risk of impaired renal function during follow-up. In the second study, eGFR was inversely associated with different inflammatory markers (C-reactive protein, interleukin-6, serum amyloid A) and positively associated with a marker of oxidative stress (urinary F2-isoprostanes). In line with this, the urinary albumin/creatinine ratio was positively associated with these inflammatory markers, and negatively associated with oxidative stress. In study three, higher eGFR was associated with better endothelial function as assessed by the invasive forearm model. Further, in study four, higher eGFR was significantly associated with higher left ventricular systolic function (ejection fraction). The 5th study of the thesis shows that higher urinary albumin excretion rate (UAER) and lower eGFR was independently associated with an increased risk for cardiovascular mortality. Analyses of global model fit, discrimination, calibration, and reclassification suggest that UAER and eGFR add relevant prognostic information beyond established cardiovascular risk factors in participants without prevalent cardiovascular disease. Conclusion: this thesis show that the interaction between the kidney and the cardiovascular system plays an important role in the development of cardiovascular disease and that this interplay begins at an early asymptomatic stage of the disease process.

Nurses' research utilization two years after graduation : a national survey ofassociated individual, organizational, and educational factors

Background. Nurses' research utilization (RU) as part of evidence-based practice is strongly emphasized in today's nursing education and clinical practice. The primary aim of RU is to provide high-quality nursing care to patients. Data on newly graduated nurses' RU are scarce, but a predominance of low use has been reported in recent studies. Factors associated with nurses' RU have previously been identified among individual and organizational/contextual factors, but there is a lack of knowledge about how these factors, including educational ones, interact with each other and with RU, particularly in nurses during the first years after graduation. The purpose of this study was therefore to identify factors that predict the probability for low RU among registered nurses two years after graduation. Methods. Data were collected as part of the LANE study (Longitudinal Analysis of Nursing Education), a Swedish national survey of nursing students and registered nurses. Data on nurses' instrumental, conceptual, and persuasive RU were collected two years after graduation (2007, n = 845), together with data on work contextual factors. Data on individual and educational factors were collected in the first year (2002) and last term of education (2004). Guided by an analytic schedule, bivariate analyses, followed by logistic regression modeling, were applied. Results. Of the variables associated with RU in the bivariate analyses, six were found to be significantly related to low RU in the final logistic regression model: work in the psychiatric setting, role ambiguity, sufficient staffing, low work challenge, being male, and low student activity. Conclusions. A number of factors associated with nurses' low extent of RU two years postgraduation were found, most of them potentially modifiable. These findings illustrate the multitude of factors related to low RU extent and take their interrelationships into account. This knowledge might serve as useful input in planning future studies aiming to improve nurses', specifically newly graduated nurses', RU.