Load-sharing with degradation management in a compressor station

Management of compressor degradation is often considered from the perspective of maintenance of the compressor, but most frameworks for the operation of compressors do not take degradation into account. This paper proposes a method for operation of compressors that takes into account the current level of degradation in order to manage further degradation. The algorithm can be used in maintenance planning frameworks, in particular if the timings of maintenance activities are fixed. The algorithm can extend the lifetime of a compressor by mitigating its degradation, or, conversely, can intensify the degradation to reach the maximum level in time for planned maintenance. The performance of the algorithm has been demonstrated in a case study for five compressors. A comparison with equal load approach shows that the new algorithm improves the operation of the system by managing the degradation of selected compressors. Explicit management of degradation allows an extension of the lifetime of selected compressors before maintenance must be performed. Conversely, by ensuring that the desired level of degradation is attained before pre-planned maintenance actions, it contributes to increased efficacy of maintenance actions. Note to Practitioners —The paper presents a new framework for load-sharing in a compressor station with compressors subject to degradation. The main innovation of the framework is the use of relationships between custom degradation indicators to manage degradation of the compressors. The results in the paper prove that it is possible to manage degradation in an industrial setting by adjusting the load of each compressor. From a practical perspective, the framework allows more degraded compressors to follow the less degraded compressors (called leaders). The simplicity of the proposed framework enables an intuitive choice of leaders, in particular in compressor stations with more than two compressors. Focused directly on the load sharing, the framework al..

Updates on polyurethane and its multifunctional applications in biomedical engineering

Polyurethanes (PUs) have properties that make them promising in biomedical applications. PU is recognized as one of the main families of blood and biocompatible materials. PU plays a vital role in the design of medical devices in various medical fields. The structure of PU contains two segments: soft and hard. Its elastomeric feature is due to its soft segment, and its excellent and high mechanical property is because of its hard segment. It is possible to achieve specific desirable and targeted properties by changing the soft and hard chemical structures and the ratio between them. The many properties of PU each draw the attention of different medical fields. This work reviews PU highlighted properties, such as biodegradability, biostability, shape memory, and improved antibacterial activity. Also, because PU has a variety of applications, this review restricts its focus to PU's prominent applications in tissue engineering, cardiovascular medicine, drug delivery, and wound healing. In addition, it contains a brief review of PU's applications in biosensors and oral administration

The Aharonov-Bohm effect in graphene rings

This is a review of electronic quantum interference in mesoscopic ring structures based on graphene, with a focus on the interplay between the Aharonov-Bohm effect and the peculiar electronic and transport properties of this material. We first present an overview on recent developments of this topic, both from the experimental as well as the theoretical side. We then review our recent work on signatures of two prominent graphene-specific features in the Aharonov-Bohm conductance oscillations, namely Klein tunneling and specular Andreev reflection. We close with an assessment of experimental and theoretical development in the field and highlight open questions as well as potential directions of the developments in future work.Comment: review article for "Special Issue on Graphene", to appear in "Solid State Communications

Nurses' experiences of delirium and how to identify delirium - A qualitative study

Aim: Delirium is a serious, acute medical condition which places a heavy burden on the patient, his or her family and healthcare professionals. There have been only a limited number of studies to explore nurses' experiences of delirium and how delirium is identified in community care. The research questions of the study are as follows: “How do community care nurses' experience delirium?” and “How is delirium identified?”. Design: This study has been designed as an explorative and descriptive study. Methods: A topic-based interview guide was developed containing questions associated with the Registered Nurses' experiences of their meetings with people with delirium and their identification of delirium. Results: Nurses working in the community care need to know more about delirium as they play a key role in treatment. Our results also show that the participants have difficulty in establishing whether a patient is suffering from acute confusion/delirium, depression or dementia.publishedVersio

Natural and Orthogonal Interaction framework for modeling gene-environment interactions with application to lung cancer

Objectives: We aimed at extending the Natural and Orthogonal Interaction (NOIA) framework, developed for modeling gene-gene interactions in the analysis of quantitative traits, to allow for reduced genetic models, dichotomous traits, and gene-environment interactions. We evaluate the performance of the NOIA statistical models using simulated data and lung cancer data. Methods: The NOIA statistical models are developed for additive, dominant, and recessive genetic models as well as for a binary environmental exposure. Using the Kronecker product rule, a NOIA statistical model is built to model gene-environment interactions. By treating the genotypic values as the logarithm of odds, the NOIA statistical models are extended to the analysis of case-control data. Results: Our simulations showed that power for testing associations while allowing for interaction using the NOIA statistical model is much higher than using functional models for most of the scenarios we simulated. When applied to lung cancer data, much smaller p values were obtained using the NOIA statistical model for either the main effects or the SNP-smoking interactions for some of the SNPs tested. Conclusion: The NOIA statistical models are usually more powerful than the functional models in detecting main effects and interaction effects for both quantitative traits and binary traits. Copyright (C) 2012 S. Karger AG, Base

Synovitis in osteoarthritis: current understanding with therapeutic implications

Modern concepts of osteoarthritis (OA) have been forever changed by modern imaging phenotypes demonstrating complex and multi-tissue pathologies involving cartilage, subchondral bone and (increasingly recognized) inflammation of the synovium. The synovium may show significant changes, even before visible cartilage degeneration has occurred, with infiltration of mononuclear cells, thickening of the synovial lining layer and production of inflammatory cytokines. The combination of sensitive imaging modalities and tissue examination has confirmed a high prevalence of synovial inflammation in all stages of OA, with a number of studies demonstrating that synovitis is related to pain, poor function and may even be an independent driver of radiographic OA onset and structural progression. Treating key aspects of synovial inflammation therefore holds great promise for analgesia and also for structure modification. This article will review current knowledge on the prevalence of synovitis in OA and its role in symptoms and structural progression, and explore lessons learnt from targeting synovitis therapeutically

Breast-feeding and risk of epithelial ovarian cancer.

Among women who have had the opportunity to breast-feed, ever breast-feeding and increasing durations of episodes of breast-feeding for each breast-fed child are associated with a decrease in the risk of ovarian cancer independent of numbers of births, which may be strongest for the endometrioid subtype