Application of preventive maintenance planning in a parquet enterprise

In this study, the process of a parquet enterprise’s transition to preventive maintenance which has been implementing maintenance technique in case of breakdown was investigated. During that transition process, follow up forms for maintenance–repair, breakdown and spare parts were prepared and the implementation processes were followed. At the end of the implementation, it was identified that breakdowns have declined, anxiety and turmoil brought about by breakdowns have been prevented, thelife span of the machines soared, labour-borne accidents declined and production quality increased

Computational study of droplets rising using Lattice Boltzmann Model

Paper presented to the 10th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Florida, 14-16 July 2014.Multi relaxation time lattice Boltzmann method is implemented to study unsteady multiphase flows of two immiscible fluids. D2Q9 lattice arrangement for two dimensional flows is employed to investigate lighter fluid droplets rising in heavier fluid. Density distribution functions for each fluid and distribution functions for the coloring step identifying the location of interface separating each immiscible fluid will be used to simulate the dynamics of the droplets and the velocity field of each phase. Buoyancy and other interactive forces between phases are modeled to predict the evolution of droplets as they are rising. No-slip no penetration boundary conditions and periodic boundary conditions are considered in transient flow simulations of multi-phase immiscible fluid for a range of various arrangements of droplets. The effect of the boundaries on the droplets dynamics will be presented.dc201

Elastic instability in stratified core annular flow

We study experimentally the interfacial instability between a layer of dilute polymer solution and water flowing in a thin capillary. The use of microfluidic devices allows us to observe and quantify in great detail the features of the flow. At low velocities, the flow takes the form of a straight jet, while at high velocities, steady or advected wavy jets are produced. We demonstrate that the transition between these flow regimes is purely elastic -- it is caused by viscoelasticity of the polymer solution only. The linear stability analysis of the flow in the short-wave approximation captures quantitatively the flow diagram. Surprisingly, unstable flows are observed for strong velocities, whereas convected flows are observed for low velocities. We demonstrate that this instability can be used to measure rheological properties of dilute polymer solutions that are difficult to assess otherwise.Comment: 4 pages, 4 figure

Ammonium and nitrate status of the first crop corn fields at Cukurova region

The ammonium (NH4) and nitrate (NO3) are the available nitrogen (N) forms that plants need in large quantities. Their existence in the soil is limited, and concentrations are kept low due to the losses by leaching in the soil profile and microbial consumptions. Sustainability of the plant available nitrogen forms in soil profile is important for plant growth and crop production. In this research, our main objective was to evaluate mineral nitrogen (Nmin) status of the first crop corn soils and plants in Akarsu Irrigation District of Cukurova Region in 2007. Soil samples prior to sowing and after harvest were taken from 0-30, 30-60 and 60-90 cm soil depths, and analyzed for ammonium and nitrate concentrations. Plant samples were also taken during harvest, and analyzed for N content for determination of total N uptake. There was considerable amount of ammonium and nitrate in the soil profile during preplanting and postharvest. Since the soils were mostly heavy texture, there is tendency to have ammonium also in the soil solution. However, ammonium concentration was far below the nitrate concentration throughout the profile. Plant nitrogen uptake in the irrigation district was very close to the amount that was applied by the local farmers. The results indicated that soil mineral nitrogen level is an important criteria for fertilization practices, especially the preplant Nmin values need to be considered to decrease the amount of N fertilizer that will be applied

Searching for serial refreshing in working memory:Using response times to track the content of the focus of attention over time

One popular idea is that, to support maintenance of a set of elements over brief periods of time, the focus of attention rotates among the different elements thereby serially refreshing the content of Working Memory (WM). In the research reported here, probe letters were presented between to-be-remembered letters. Response times to these probes were used to infer the status of the different items in WM. If the focus of attention cycles from one item to the next, its content should be different at different points in time and this should be reflected in a change in the response time patterns over time. Across a set of four experiments, we demonstrate a striking pattern of invariance in the response time patterns over time, suggesting that either the content of the focus of attention did not change over time or that response times cannot be used to infer the content of the focus of attention. We discuss how this pattern constrains models of WM, attention, and human information processing

MRI-based radiomics for prognosis of pediatric diffuse intrinsic pontine glioma: an international study.

Background: Diffuse intrinsic pontine gliomas (DIPGs) are lethal pediatric brain tumors. Presently, MRI is the mainstay of disease diagnosis and surveillance. We identify clinically significant computational features from MRI and create a prognostic machine learning model. Methods: We isolated tumor volumes of T1-post-contrast (T1) and T2-weighted (T2) MRIs from 177 treatment-naïve DIPG patients from an international cohort for model training and testing. The Quantitative Image Feature Pipeline and PyRadiomics was used for feature extraction. Ten-fold cross-validation of least absolute shrinkage and selection operator Cox regression selected optimal features to predict overall survival in the training dataset and tested in the independent testing dataset. We analyzed model performance using clinical variables (age at diagnosis and sex) only, radiomics only, and radiomics plus clinical variables. Results: All selected features were intensity and texture-based on the wavelet-filtered images (3 T1 gray-level co-occurrence matrix (GLCM) texture features, T2 GLCM texture feature, and T2 first-order mean). This multivariable Cox model demonstrated a concordance of 0.68 (95% CI: 0.61-0.74) in the training dataset, significantly outperforming the clinical-only model (C = 0.57 [95% CI: 0.49-0.64]). Adding clinical features to radiomics slightly improved performance (C = 0.70 [95% CI: 0.64-0.77]). The combined radiomics and clinical model was validated in the independent testing dataset (C = 0.59 [95% CI: 0.51-0.67], Noether's test P = .02). Conclusions: In this international study, we demonstrate the use of radiomic signatures to create a machine learning model for DIPG prognostication. Standardized, quantitative approaches that objectively measure DIPG changes, including computational MRI evaluation, could offer new approaches to assessing tumor phenotype and serve a future role for optimizing clinical trial eligibility and tumor surveillance

Pretransplant Prediction of Posttransplant Survival for Liver Recipients with Benign End-Stage Liver Diseases: A Nonlinear Model

Background: The scarcity of grafts available necessitates a system that considers expected posttransplant survival, in addition to pretransplant mortality as estimated by the MELD. So far, however, conventional linear techniques have failed to achieve sufficient accuracy in posttransplant outcome prediction. In this study, we aim to develop a pretransplant predictive model for liver recipients ’ survival with benign end-stage liver diseases (BESLD) by a nonlinear method based on pretransplant characteristics, and compare its performance with a BESLD-specific prognostic model (MELD) and a generalillness severity model (the sequential organ failure assessment score, or SOFA score). Methodology/Principal Findings: With retrospectively collected data on 360 recipients receiving deceased-donor transplantation for BESLD between February 1999 and August 2009 in the west China hospital of Sichuan university, we developed a multi-layer perceptron (MLP) network to predict one-year and two-year survival probability after transplantation. The performances of the MLP, SOFA, and MELD were assessed by measuring both calibration ability and discriminative power, with Hosmer-Lemeshow test and receiver operating characteristic analysis, respectively. By the forward stepwise selection, donor age and BMI; serum concentration of HB, Crea, ALB, TB, ALT, INR, Na +; presence of pretransplant diabetes; dialysis prior to transplantation, and microbiologically proven sepsis were identified to be the optimal input features. The MLP, employing 18 input neurons and 12 hidden neurons, yielded high predictive accuracy, wit