Self-Organising Maps: A new way to screen the level of satisfaction of dialysis patients

Evaluation of patient satisfaction has become an important indicator for assessing health care quality. Fresenius Medical Care (FME) as a global provider of dialysis services through its NephroCare network has a strong interest in monitoring patient satisfaction.The aim of the paper is to test and validate a methodology for detecting a residual area of low satisfaction in dialysis patients.The FME Patient Satisfaction Programme questionnaire was distributed to haemodialysis (HD) patients treated in 335 centers of its network. It contained 79 questions covering various satisfaction aspects regarding Dialysis Unit, Dialysis Arrangement, Nurses, Doctors, etc.To analyse the data provided by the questionnaire, the Self-Organising Map (SOM) method was used. SOM is a neural network model for clustering and projecting high-dimensional data into a low-dimensional space, preserving topological relationships of original high-dimensional data spaces.10,632 HD patients completed the questionnaire. Mean age was 63.05 ± 14.93 years with 56.69% males. Response rate was 66%. Overall level of satisfaction was 1.99 (range from ?3 to +3). On average patients were very satisfied with all issues. Nevertheless, a group of patients, around 60 years old, balanced gender ratio, whose level of satisfaction was lower than 1, were highlighted.In the NephroCare clinics patient satisfaction with service is rather high. While traditional analysis usually stops here, the SOM method allows identification of areas of potential improvement for specific patient groups.     

On the differential benchmarking of promotional efficiency with machine learning modelling (II): Practical applications

The assessment of promotional sales with models constructed by machine learning techniques is arousing interest due, among other reasons, to the current economic situation leading to a more complex environment of simultaneous and concurrent promotional activities. An operative model diagnosis procedure was previously proposed in the companion paper, which can be readily used both for agile decision making on the architecture and implementation details of the machine learning algorithms, and for differential benchmarking among models. In this paper, a detailed example of model analysis is presented for two representative databases with different promotional behaviour, namely, a non-seasonal category (milk) and a heavily seasonal category (beer). The performance of four well-known machine learning techniques with increasing complexity is analyzed in detail here. In particular, k-Nearest Neighbours, General Regression Neural Networks, Multilayer Perceptron (MLP), and Support Vector Machines (SVM), are differentially compared. Present paper evaluates these techniques along the experiments described for both categories when applying the methodological findings obtained in the companion paper. We conclude that some elements included in the architecture are not essential for a good performance of the machine learning promotional models, such as the semiparametric nature of the kernel in SVM models, whereas other can be strongly dependent of the database, such as the convenience of multiple output models in MLP regression schemes. Additionally, the specificity of the behaviour of certain categories and product ranges determines the need to establish suitable and specific procedures for a better prediction and feature extraction.     

Linking Organizational Resources and Work Engagement to Employee Performance and Customer Loyalty: The Mediation of Service Climate.

This study examined the mediating role of service climate in the prediction of employee performance and customer loyalty. Contact employees (N=342) from 114 service units (58 hotel front desks and 56 restaurants) provided information about organizational resources, engagement, and service climate. Furthermore, customers (N=1,140) from these units provided information on employee performance and customer loyalty. Structural equation modeling analyses were consistent with a full mediation model in which organizational resources and work engagement predict service climate, which in turn predicts employee performance and then customer loyalty. Further analyses revealed a potential reciprocal effect between service climate and customer loyalty. Implications of the study are discussed, together with limitations and suggestions for future research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Stress and Coping Model of Medication Adherence and Viral Load in HIV-Positive Men and Women on Highly Active Antiretroviral Therapy (HAART).

The authors tested a structural model that incorporated age, time since diagnosis, social support, coping, and negative mood as predictors of medication adherence and HIV viral load on 188 men and 134 women on highly active antiretroviral therapy (HAART). The authors used psychosocial latent factors formed from baseline measures to predict latent factors of adherence, as assessed by electronic monitoring and self-report, and viral load defined by indicators assessed over a 15-month period. Results from the model indicate that greater negative mood and lower social support are related to greater use of avoidance-oriented coping strategies. Use of these coping strategies by patients on HAART is related to poorer medication adherence and, subsequently, higher viral load. This model advances researchers' understanding of the contribution of psychosocial variables in predicting treatment adherence and disease progression in HIV-positive men and women. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

High Performance Air Pollution Simulation Using OpenMP

The aim of this work is to provide a high performance air quality simulation using the sulphur transport Eulerian model 2 (STEM-II) program. First of all we optimize the sequential program with the aim of increasing data locality. Then, the optimized program is parallelized using OpenMP shared-memory directives. Experimental results on a 32-processor SGI Origin 2000 show that the parallel program achieves important reductions in the execution times.     

A Mixed Closure-CSP Method for Solving Scheduling Problems

Scheduling problems can be viewed as a set of temporal metric and disjunctive constraints and so they can be formulated in terms of CSP techniques. In the literature, there are CSP-based methods which sequentially interleave search efforts with the application of consistency enforcing mechanisms and variable/ordering heuristics. Therefore, the number of backtrackings needed to obtain a solution is reduced. In this paper, we propose a new method that effectively integrates the CSP process into a limited closure process: not by interleaving them but rather as a part of the same process. Such an integration allows us to define more informed heuristics. These heuristics are used to limit the complete closure process to a maximum number of disjunctions, thereby reducing its complexity while at the same time reducing the search space. Some open disjunctive solutions can be maintained in the CSP process, limiting the number of backtrackings necessary, and avoiding having to know all the problem constraints in advance. Our experiments with flow-shop and job-shop instances show that this approach obtains a feasible solution/optimal solution without having to use backtracking in most cases. We also analyze the behaviour of our algorithm when some constraints are known dynamically and we demonstrate that it can provide better results than a pure CSP process.     

Immunohistochemistry of neuronal nitric oxide synthase and protein nitration in the striatum of the aged rat

To ascertain the possible implications of the nitric oxide (NO*) producing system in striatal senescence, and by using immunohistochemistry and image-processing approaches, we describe the presence of the enzyme nitric oxide synthase (NOS), the NADPH-diaphorase (NADPH-d) histochemical marker, and nitrotyrosine-derived complexes (N-Tyr) in the striatum of adult and aged rats. The results showed neuronal NOS immunoreactive (nNOS-IR) aspiny medium-sized neurons and nervous fibres in both age groups, with no variation in the percentage of immunoreactive area but a significant decrease in the intensity and in the number of somata with age, which were not related to the observed increase with age of the striatal bundles of the white matter. In addition, NADPH-d activity was detected in neurons with morphology similar to that of the nNOS-IR cells; a decrease in the percentage of area per field and in the number of cells, but an increase in the intensity of staining for the NADPH-d histochemical marker, were detected with age. The number of neuronal NADPH-d somata was higher than for the nNOS-IR ones in both age groups. Moreover, N-Tyr-IR complexes were observed in cells (neurons and glia) and fibres, with a significant increase in the percentage of the area of immunoreaction, related to the increase of white matter, but a decrease in intensity for the aged group. On the other hand, we did not detect the inducible isoform (iNOS) either in adult or in aged rats. Taken together, these results support the contention that NADPH-d staining is not such an unambiguous marker for nNOS, and that increased protein nitration may participate in striatal aging.     

Characterisation of chickpea flour‐based gluten‐free batters and muffins with added biopolymers: rheological,physical and sensory properties

Chickpea flour (CF)‐based muffin formulations were made with CF alone and with added biopolymers [whey protein (WP), xanthan gum (XG) and inulin (INL)] to evaluate their suitability to be a wheat flour (WF) substitute in muffins. Structural characteristics of the batters and muffins were studied by means of rheometry, microscopy, physicochemical properties, and texture and sensory analysis. Partial replacement of CF with XG, alone (at 0.5 and 1%) or blended with either WP or INL, significantly increased the batter viscoelasticity as denser matrices developed; moreover, the muffins with XG added at 1% had similar hardness to wheat gluten muffins. The replacement of WF decreased the springiness, cohesiveness, chewiness, resilience and specific volume of the muffin. However, baked muffins with added XG also showed higher sensory sponginess and moisture associated with numerous air bubbles in the batter and were perceived to be easier to swallow and to have better general appearance.     

Recycled Polyolefin Blends: Effect of Modified Natural Zeolite on their Properties and Morphology

The purpose of this study is to investigate the effect of treated natural zeolite on the flow behavior, morphology, thermal, and mechanical properties in recycled polyolefin blends. A model polymer blend consisting of 95 wt% polyolefines and 5 wt% polystyrene was studied. Compositions from this recycled blend and dehydrated zeolite in a narrow concentration range (0–5 wt%) were treated with maleic anhydride-grafted polypropylene and initiator dicumyl peroxide. The compositions were characterized by capillary rheometry, wide-angle X-ray scattering, differential scanning calorimetry, scanning electron microscopy, and mechanical tests. The results show a compatibilizing effect of treated zeolite expressed by increase of shear viscosity and improvement of interfacial interactions and impact strength. The results can open wide possibilities for utilization of treated zeolite in recycling of unsorted polymer wastes.