A planning model for needs analysis for subacute care

The purpose of this study is to produce a model to be used by state regulating agencies to assess demand for subacute care. In accomplishing this goal, the study refines the definition of subacute care, demonstrates a method for bed need assessment, and measures the effectiveness of this new level of care. This was the largest study of subacute care to date. Research focused on 19 subacute units in 16 states, each of which provides high-intensity rehabilitative and/or restorative care carried out in a high-tech unit. Each of the facilities was based in a nursing home, but utilized separate staff, equipment, and services. Because these facilities are under local control, it was possible to study regional differences in subacute care demand. Using this data, a model for predicting demand for subacute care services was created, building on earlier models submitted by John Whitman for the American Hospital Association and Robin E. MacStravic. The Broderick model uses the "bootstrapping" method and takes advantage of high technology: computers and software, databases in business and government, publicly available databases from providers or commercial vendors, professional organizations, and other information sources. Using newly available sources of information, this new model addresses the problems and needs of health care planners as they approach the challenges of the 21st century.

Proposta de válvula bypass para controle de velocidade de PIGs instrumentados: protótipo e simulação em bancada

In the Oil industry, oil and gas pipelines are commonly utilized to perform the transportation of production fluids to longer distances. The maintenance of the pipelines passes through the analysis of several tools, in which the most currently used are the pipelines inspection cells, popularly knowing as PIG. Among the variants existing in the market, the instrumented PIG has a significant relevance; acknowledging that through the numerous sensors existing in the equipment, it can detect faults or potential failure along the inspected line. Despite its versatility, the instrumented PIG suffers from speed variations, impairing the reading of sensors embedded in it. Considering that PIG moves depending on the speed of the production fluid, a way to control his speed is to control the flow of the fluid through the pressure control, reducing the flow rate of the produced flow, resulting in reduction of overall production the fluid in the ducts own or with the use of a restrictive element (valve) installed on it. The characteristic of the flow rate/pressure drop from restrictive elements of the orifice plate is deducted usually from the ideal energy equation (Bernoulli’s equation) and later, the losses are corrected normally through experimental tests. Thus, with the objective of controlling the fluids flow passing through the PIG, a valve shutter actuated by solenoid has been developed. This configuration allows an ease control and stabilization of the flow adjustment, with a consequent response in the pressure drops between upstream and downstream of the restriction. It was assembled a test bench for better definition of flow coefficients; composed by a duct with intern diameter of four inches, one set of shutters arranged in a plate and pressure gauges for checking the pressure drop in the test. The line was pressurized and based on the pressure drop it was possible to draw a curve able to characterize the flow coefficient of the control valve prototype and simulate in mockup the functioning, resulting in PIG speed reduction of approximately 68%.

Análise de confiabilidade de um moto-ventilador centrífugo: aplicação no sistema de pressurização de subestação industrial para garantia da segurança operacional na indústria petroquímica

The need of the oil industry to ensure the safety of the facilities, employees and the environment, not to mention the search for maximum efficiency of its facilities, makes it seeks to achieve a high level of excellence in all stages of its production processes in order to obtain the required quality of the final product. Know the reliability of equipment and what it stands for a system is of fundamental importance for ensuring the operational safety. The reliability analysis technique has been increasingly applied in the oil industry as fault prediction tool and undesirable events that can affect business continuity. It is an applied scientific methodology that involves knowledge in engineering and statistics to meet and or analyze the performance of components, equipment and systems in order to ensure that they perform their function without fail, for a period of time and under a specific condition. The results of reliability analyzes help in making decisions about the best maintenance strategy of petrochemical plants. Reliability analysis was applied on equipment (bike-centrifugal fan) between the period 2010-2014 at the Polo Petrobras Guamaré Industrial, situated in rural Guamaré municipality in the state of Rio Grande do Norte, where he collected data field, analyzed historical equipment and observing the behavior of faults and their impacts. The data were processed in commercial software reliability ReliaSoft BlockSim 9. The results were compared with a study conducted by the experts in the field in order to get the best maintenance strategy for the studied system. With the results obtained from the reliability analysis tools was possible to determine the availability of the centrifugal motor-fan and what will be its impact on the security of process units if it will fail. A new maintenance strategy was established to improve the reliability, availability, maintainability and decreased likelihood of Moto-Centrifugal Fan failures, it is a series of actions to promote the increased system reliability and consequent increase in cycle life of the asset. Thus, this strategy sets out preventive measures to reduce the probability of failure and mitigating aimed at minimizing the consequences.

Dynamic fault tree analysis with PEWMA modeling of event rates and Bayesian updating of material balance parameters using MCMC

This research explores Bayesian updating as a tool for estimating parameters probabilistically by dynamic analysis of data sequences. Two distinct Bayesian updating methodologies are assessed. The first approach focuses on Bayesian updating of failure rates for primary events in fault trees. A Poisson Exponentially Moving Average (PEWMA) model is implemnented to carry out Bayesian updating of failure rates for individual primary events in the fault tree. To provide a basis for testing of the PEWMA model, a fault tree is developed based on the Texas City Refinery incident which occurred in 2005. A qualitative fault tree analysis is then carried out to obtain a logical expression for the top event. A dynamic Fault Tree analysis is carried out by evaluating the top event probability at each Bayesian updating step by Monte Carlo sampling from posterior failure rate distributions. It is demonstrated that PEWMA modeling is advantageous over conventional conjugate Poisson-Gamma updating techniques when failure data is collected over long time spans. The second approach focuses on Bayesian updating of parameters in non-linear forward models. Specifically, the technique is applied to the hydrocarbon material balance equation. In order to test the accuracy of the implemented Bayesian updating models, a synthetic data set is developed using the Eclipse reservoir simulator. Both structured grid and MCMC sampling based solution techniques are implemented and are shown to model the synthetic data set with good accuracy. Furthermore, a graphical analysis shows that the implemented MCMC model displays good convergence properties. A case study demonstrates that Likelihood variance affects the rate at which the posterior assimilates information from the measured data sequence. Error in the measured data significantly affects the accuracy of the posterior parameter distributions. Increasing the likelihood variance mitigates random measurement errors, but casuses the overall variance of the posterior to increase. Bayesian updating is shown to be advantageous over deterministic regression techniques as it allows for incorporation of prior belief and full modeling uncertainty over the parameter ranges. As such, the Bayesian approach to estimation of parameters in the material balance equation shows utility for incorporation into reservoir engineering workflows.

Dynamic safety analysis of managed pressure drilling operations

The exploration and development of oil and gas reserves located in harsh offshore environments are characterized with high risk. Some of these reserves would be uneconomical if produced using conventional drilling technology due to increased drilling problems and prolonged non-productive time. Seeking new ways to reduce drilling cost and minimize risks has led to the development of Managed Pressure Drilling techniques. Managed pressure drilling methods address the drawbacks of conventional overbalanced and underbalanced drilling techniques. As managed pressure drilling techniques are evolving, there are many unanswered questions related to safety and operating pressure regimes. Quantitative risk assessment techniques are often used to answer these questions. Quantitative risk assessment is conducted for the various stages of drilling operations – drilling ahead, tripping operation, casing and cementing. A diagnostic model for analyzing the rotating control device, the main component of managed pressure drilling techniques, is also studied. The logic concept of Noisy-OR is explored to capture the unique relationship between casing and cementing operations in leading to well integrity failure as well as its usage to model the critical components of constant bottom-hole pressure drilling technique of managed pressure drilling during tripping operation. Relevant safety functions and inherent safety principles are utilized to improve well integrity operations. Loss function modelling approach to enable dynamic consequence analysis is adopted to study blowout risk for real-time decision making. The aggregation of the blowout loss categories, comprising: production, asset, human health, environmental response and reputation losses leads to risk estimation using dynamically determined probability of occurrence. Lastly, various sub-models developed for the stages/sub-operations of drilling operations and the consequence modelling approach are integrated for a holistic risk analysis of drilling operations.

Structural Analysis and Form-Finding of Mycelium-Based Monolithic Domes

As sustainability becomes an integral design driver for current civil structures, new materials and forms are investigated. The aim of this study is to investigate analytically and numerically the mechanical behavior of monolithic domes composed of mycological fungi. The study focuses on hemispherical and elliptical forms, as the most typical solution for domes. The influence of different types of loading, geometrical parameters, material properties and boundary conditions is investigated in this study. For the cases covered by the classical shell theory, a comparison between the analytical and the finite element solution is given. Two case studies regarding the dome of basilica of “San Luca” (Bologna, Italy) and the dome of sanctuary of “Vicoforte” (Vicoforte, Italy) are included. After the linear analysis under loading, buckling is also investigated as a critical type of failure through a parametric study using finite elements model. Since shells rely on their shape, form-found domes are also investigated and a comparison between the behavior of the form-found domes and the hemispherical domes under the linear and buckling analysis is conducted. From the analysis it emerges that form-finding can enhance the structural response of mycelium-based domes, although buckling becomes even more critical for their design. Furthermore, an optimal height to span ratio for the buckling of form-found domes is identified. This study highlights the importance of investigating appropriate forms for the design of novel biomaterial-based structures.

The Impact of Carbonate Texture on the Quantification of Total Porosity by Image Analysis

Date of Acceptance: 31/08/2015 The authors would like to thank Total E&P and BG Group for project funding and support and the Industry Technology Facilitator for enabling the collaborative development (grant number 3322PSD). The authors would also like to thank Aberdeen Formation Evaluation Society and the College of Physical Sciences at the University of Aberdeen for partial financial support. Dougal Jerram, Raymi Castilla, Claude Gout, Frances Abbots and an anonymous reviewer are thanked for their constructive comments and suggestions to improve the standard of this manuscript. The authors would also like to express their gratitude toJohn Still and Colin Taylor for technical assistance in the laboratory and Nick Timms (Curtin University) and Angela Halfpenny (CSIRO) for their assistance with the full thin section scanning equipment.

The Impact of Carbonate Texture on the Quantification of Total Porosity by Image Analysis

Date of Acceptance: 31/08/2015 The authors would like to thank Total E&P and BG Group for project funding and support and the Industry Technology Facilitator for enabling the collaborative development (grant number 3322PSD). The authors would also like to thank Aberdeen Formation Evaluation Society and the College of Physical Sciences at the University of Aberdeen for partial financial support. Dougal Jerram, Raymi Castilla, Claude Gout, Frances Abbots and an anonymous reviewer are thanked for their constructive comments and suggestions to improve the standard of this manuscript. The authors would also like to express their gratitude toJohn Still and Colin Taylor for technical assistance in the laboratory and Nick Timms (Curtin University) and Angela Halfpenny (CSIRO) for their assistance with the full thin section scanning equipment.

Habitual chocolate consumption and the risk of incident heart failure among healthy men and women

Acknowledgments The authors would like to thank the participants of the EPIC-Norfolk cohort. We thank the nutritionist team and data management team of the EPIC-Norfolk cohort. The EPIC-Norfolk study was supported by grants from the Medical Research Council and Cancer Research UK. Funders had no role in study design or interpretation of the findings.

Habitual chocolate consumption and the risk of incident heart failure among healthy men and women

Acknowledgments The authors would like to thank the participants of the EPIC-Norfolk cohort. We thank the nutritionist team and data management team of the EPIC-Norfolk cohort. The EPIC-Norfolk study was supported by grants from the Medical Research Council and Cancer Research UK. Funders had no role in study design or interpretation of the findings.

The Policy Dystopia Model:an interpretive analysis of tobacco industry political activity

BACKGROUND: Tobacco industry interference has been identified as the greatest obstacle to the implementation of evidence-based measures to reduce tobacco use. Understanding and addressing industry interference in public health policy-making is therefore crucial. Existing conceptualisations of corporate political activity (CPA) are embedded in a business perspective and do not attend to CPA's social and public health costs; most have not drawn on the unique resource represented by internal tobacco industry documents. Building on this literature, including systematic reviews, we develop a critically informed conceptual model of tobacco industry political activity. METHODS AND FINDINGS: We thematically analysed published papers included in two systematic reviews examining tobacco industry influence on taxation and marketing of tobacco; we included 45 of 46 papers in the former category and 20 of 48 papers in the latter (n = 65). We used a grounded theory approach to build taxonomies of "discursive" (argument-based) and "instrumental" (action-based) industry strategies and from these devised the Policy Dystopia Model, which shows that the industry, working through different constituencies, constructs a metanarrative to argue that proposed policies will lead to a dysfunctional future of policy failure and widely dispersed adverse social and economic consequences. Simultaneously, it uses diverse, interlocking insider and outsider instrumental strategies to disseminate this narrative and enhance its persuasiveness in order to secure its preferred policy outcomes. Limitations are that many papers were historical (some dating back to the 1970s) and focused on high-income regions. CONCLUSIONS: The model provides an evidence-based, accessible way of understanding diverse corporate political strategies. It should enable public health actors and officials to preempt these strategies and develop realistic assessments of the industry's claims.

Single-cell functional analysis of parathyroid adenomas reveals distinct classes of calcium sensing behaviour in primary hyperparathyroidism.

Primary hyperparathyroidism (PHPT) is a common endocrine neoplastic disorder caused by a failure of calcium sensing secondary to tumour development in one or more of the parathyroid glands. Parathyroid adenomas are comprised of distinct cellular subpopulations of variable clonal status that exhibit differing degrees of calcium responsiveness. To gain a clearer understanding of the relationship among cellular identity, tumour composition and clinical biochemistry in PHPT, we developed a novel single cell platform for quantitative evaluation of calcium sensing behaviour in freshly resected human parathyroid tumour cells. Live-cell intracellular calcium flux was visualized through Fluo-4-AM epifluorescence, followed by in situ immunofluorescence detection of the calcium sensing receptor (CASR), a central component in the extracellular calcium signalling pathway. The reactivity of individual parathyroid tumour cells to extracellular calcium stimulus was highly variable, with discrete kinetic response patterns observed both between and among parathyroid tumour samples. CASR abundance was not an obligate determinant of calcium responsiveness. Calcium EC50 values from a series of parathyroid adenomas revealed that the tumours segregated into two distinct categories. One group manifested a mean EC50 of 2.40 mM (95% CI: 2.37-2.41), closely aligned to the established normal range. The second group was less responsive to calcium stimulus, with a mean EC50 of 3.61 mM (95% CI: 3.45-3.95). This binary distribution indicates the existence of a previously unappreciated biochemical sub-classification of PHPT tumours, possibly reflecting distinct etiological mechanisms. Recognition of quantitative differences in calcium sensing could have important implications for the clinical management of PHPT.

Single-Cell Transcriptome Analysis of Olfactory Sensory Neurons

Olfactory sensory neurons (OSNs), which detect a myriad of odorants, are known to express one allele of one olfactory receptor (OR) gene (Olfr) from the largest gene family in the mammalian genome. The OSNs expressing the same OR project their axons to the main olfactory bulb where they converge to form glomeruli. This “One neuron-one receptor rule” makes the olfactory epithelium (OE), which consists of a vast number of OSNs expressing unique ORs, one of the most heterogeneous cell populations. However, the mechanism of how the single OR allele is chosen remains unclear along with the question of whether one OSN only expresses a single OR gene, a hypothesis that has not been rigorously verified while we performed the experiments. Moreover, failure of axonal targeting to single glomerulus was observed in MeCP2 deficient OSNs where delayed development was proposed as an explanation for the phenotype. How Mecp2 mutation caused this aberrant targeting is not entirely understood.

In this dissertation, we explored the transcriptomes of single and mature OSNs by single-cell RNA-Seq to reveal their heterogeneity and further studied the OR gene expression from these isolated OSNs. The singularity of sequenced OSNs was ensured by the observation of monoallelic expression of X-linked genes from the hybrid samples from crosses between mice of different strains where strain-specific polymorphisms could be used to track the allelic origins of SNP-containing reads. The clustering of expression profiles from triplicates that originated from the same cell assured that the transcriptomic identities of OSNs were maintained through the experimental process. The average gene expression profiles of sequenced OSNs correlated well to the conventional transcriptome data of FACS-sorted Omp-positive cells, and the top-ranked expression of OR was conceded in the single-OSN transcriptomes. While exploring cellular diversity, in addition to OR genes, we revealed nearly 200 differentially expressed genes among the sequenced OSNs in this study. Among the 36 sequenced OSNs, eight cells (22.2%) showed multiple OR gene expression and the presences of additional ORs were not restricted to the neighbor loci that shared the transcriptional effect of the primary OR expression, suggesting that the “One neuron-one receptor rule” might not be strictly true at the transcription level. All of the inferable ORs, including additional co-expressed ORs, were shown to be monoallelic. Our sequencing of 21 Mecp2308 mutant OSNs, of which 62% expressed more than one OR genes, and the expression levels of the additional ORs were significantly higher than those in the wild-type, suggested that MeCP2 plays a role in the regulation of singular OR gene expression. Dual label in situ hybridization along with the sequence data revealed that dorsal and ventral ORs were co-expressed in the same Mecp2 mutant OSN, further implying that MeCP2 might be involved in regulation of OR territories in the OE. Our results suggested a new role of MeCP2 in OR gene choice and ratified that this multiple-OR expression caused by Mecp2 mutation did not accompany delayed OSN development that has been observed in the previous studies on the Mecp2 mutants.

Acoustic and Magnetic Techniques for the Isolation and Analysis of Cells in Microfluidic Platforms

Cancer comprises a collection of diseases, all of which begin with abnormal tissue growth from various stimuli, including (but not limited to): heredity, genetic mutation, exposure to harmful substances, radiation as well as poor dieting and lack of exercise. The early detection of cancer is vital to providing life-saving, therapeutic intervention. However, current methods for detection (e.g., tissue biopsy, endoscopy and medical imaging) often suffer from low patient compliance and an elevated risk of complications in elderly patients. As such, many are looking to “liquid biopsies” for clues into presence and status of cancer due to its minimal invasiveness and ability to provide rich information about the native tumor. In such liquid biopsies, peripheral blood is drawn from patients and is screened for key biomarkers, chiefly circulating tumor cells (CTCs). Capturing, enumerating and analyzing the genetic and metabolomic characteristics of these CTCs may hold the key for guiding doctors to better understand the source of cancer at an earlier stage for more efficacious disease management.

The isolation of CTCs from whole blood, however, remains a significant challenge due to their (i) low abundance, (ii) lack of a universal surface marker and (iii) epithelial-mesenchymal transition that down-regulates common surface markers (e.g., EpCAM), reducing their likelihood of detection via positive selection assays. These factors potentiate the need for an improved cell isolation strategy that can collect CTCs via both positive and negative selection modalities as to avoid the reliance on a single marker, or set of markers, for more accurate enumeration and diagnosis.

The technologies proposed herein offer a unique set of strategies to focus, sort and template cells in three independent microfluidic modules. The first module exploits ultrasonic standing waves and a class of elastomeric particles for the rapid and discriminate sequestration of cells. This type of cell handling holds promise not only in sorting, but also in the isolation of soluble markers from biofluids. The second module contains components to focus (i.e., arrange) cells via forces from acoustic standing waves and separate cells in a high throughput fashion via free-flow magnetophoresis. The third module uses a printed array of micromagnets to capture magnetically labeled cells into well-defined compartments, enabling on-chip staining and single cell analysis. These technologies can operate in standalone formats, or can be adapted to operate with established analytical technologies, such as flow cytometry. A key advantage of these innovations is their ability to process erythrocyte-lysed blood in a rapid (and thus high throughput) fashion. They can process fluids at a variety of concentrations and flow rates, target cells with various immunophenotypes and sort cells via positive (and potentially negative) selection. These technologies are chip-based, fabricated using standard clean room equipment, towards a disposable clinical tool. With further optimization in design and performance, these technologies might aid in the early detection, and potentially treatment, of cancer and various other physical ailments.

A facilities maintenance management process based on degradation prediction using sensed data

Energy efficiency and user comfort have recently become priorities in the Facility Management (FM) sector. This has resulted in the use of innovative building components, such as thermal solar panels, heat pumps, etc., as they have potential to provide better performance, energy savings and increased user comfort. However, as the complexity of components increases, the requirement for maintenance management also increases. The standard routine for building maintenance is inspection which results in repairs or replacement when a fault is found. This routine leads to unnecessary inspections which have a cost with respect to downtime of a component and work hours. This research proposes an alternative routine: performing building maintenance at the point in time when the component is degrading and requires maintenance, thus reducing the frequency of unnecessary inspections. This thesis demonstrates that statistical techniques can be used as part of a maintenance management methodology to invoke maintenance before failure occurs. The proposed FM process is presented through a scenario utilising current Building Information Modelling (BIM) technology and innovative contractual and organisational models. This FM scenario supports a Degradation based Maintenance (DbM) scheduling methodology, implemented using two statistical techniques, Particle Filters (PFs) and Gaussian Processes (GPs). DbM consists of extracting and tracking a degradation metric for a component. Limits for the degradation metric are identified based on one of a number of proposed processes. These processes determine the limits based on the maturity of the historical information available. DbM is implemented for three case study components: a heat exchanger; a heat pump; and a set of bearings. The identified degradation points for each case study, from a PF, a GP and a hybrid (PF and GP combined) DbM implementation are assessed against known degradation points. The GP implementations are successful for all components. For the PF implementations, the results presented in this thesis find that the extracted metrics and limits identify degradation occurrences accurately for components which are in continuous operation. For components which have seasonal operational periods, the PF may wrongly identify degradation. The GP performs more robustly than the PF, but the PF, on average, results in fewer false positives. The hybrid implementations, which are a combination of GP and PF results, are successful for 2 of 3 case studies and are not affected by seasonal data. Overall, DbM is effectively applied for the three case study components. The accuracy of the implementations is dependant on the relationships modelled by the PF and GP, and on the type and quantity of data available. This novel maintenance process can improve equipment performance and reduce energy wastage from BSCs operation.