Mathematical modelling of patient risks in a hospital environment, using multiple regression analysis

The aim of this research work was primarily to examine the relevance of patient parameters, ward structures, procedures and practices, in respect of the potential hazards of wound cross-infection and nasal colonisation with multiple resistant strains of Staphylococcus aureus, which it is thought might provide a useful indication of a patient's general susceptibility to wound infection. Information from a large cross-sectional survey involving 12,000 patients from some 41 hospitals and 375 wards was collected over a five-year period from 1967-72, and its validity checked before any subsequent analysis was carried out. Many environmental factors and procedures which had previously been thought (but never conclusively proved) to have an influence on wound infection or nasal colonisation rates, were assessed, and subsequently dismissed as not being significant, provided that the standard of the current range of practices and procedures is maintained and not allowed to deteriorate. Retrospective analysis revealed that the probability of wound infection was influenced by the patient's age, duration of pre-operative hospitalisation, sex, type of wound, presence and type of drain, number of patients in ward, and other special risk factors, whilst nasal colonisation was found to be influenced by the patient's age, total duration of hospitalisation, sex, antibiotics, proportion of occupied beds in the ward, average distance between bed centres and special risk factors. A multi-variate regression analysis technique was used to develop statistical models, consisting of variable patient and environmental factors which were found to have a significant influence on the risks pertaining to wound infection and nasal colonisation. A relationship between wound infection and nasal colonisation was then established and this led to the development of a more advanced model for predicting wound infections, taking advantage of the additional knowledge of the patient's state of nasal colonisation prior to operation.

The steady state performance of converter type reactive power compensators

As a source or sink of reactive power, compensators can be made from a voltage sourced inverter circuit with the a.c. terminals of the inverter connected to the system through an inductive link and with a capacitor connected across the d.c. terminals. Theoretical calculations on linearised models of the compensators have shown that the parameters characterising the performance are the reduced firing angle and the resonance ratio. The resonance ratio is the ratio of the natural frequency of oscillation of the energy storage components in the circuit to the system frequency. The reduced firing angle of the inverter divided by the damping coefficient, β, where β is half the R to X ratio of the link between the inverter and the system. The theoretical results have been verified by computer simulation and experiment. There is a narrow range of values for the resonance ratio below which there is no appreciable improvement in performance, despite an increase in the cost of the energy storage components, and above which the performance of the equipment is poor with the current being dominated by harmonics. The harmonic performance of the equipment is improved by using multiple inverters and phase shifting transformers to increase the pulse number. The optimum value of the resonance ratio increases pulse number, indicating a reduction in the energy storage components needed at high pulse numbers. The reactive power output from the compensator varies linearly with the reduced firing angle while the losses vary as the square of it.

A review of multi-factor capacity expansion models for manufacturing plants:searching for a holistic decision aid

Investment in capacity expansion remains one of the most critical decisions for a manufacturing organisation with global production facilities. Multiple factors need to be considered making the decision process very complex. The purpose of this paper is to establish the state-of-the-art in multi-factor models for capacity expansion of manufacturing plants within a corporation. The research programme consisting of an extensive literature review and a structured assessment of the strengths and weaknesses of the current research is presented. The study found that there is a wealth of mathematical multi-factor models for evaluating capacity expansion decisions however no single contribution captures all the different facets of the problem.

Living with uncertainty in the age of runtime models

Uncertainty can be defined as the difference between information that is represented in an executing system and the information that is both measurable and available about the system at a certain point in its life-time. A software system can be exposed to multiple sources of uncertainty produced by, for example, ambiguous requirements and unpredictable execution environments. A runtime model is a dynamic knowledge base that abstracts useful information about the system, its operational context and the extent to which the system meets its stakeholders' needs. A software system can successfully operate in multiple dynamic contexts by using runtime models that augment information available at design-time with information monitored at runtime. This chapter explores the role of runtime models as a means to cope with uncertainty. To this end, we introduce a well-suited terminology about models, runtime models and uncertainty and present a state-of-the-art summary on model-based techniques for addressing uncertainty both at development- and runtime. Using a case study about robot systems we discuss how current techniques and the MAPE-K loop can be used together to tackle uncertainty. Furthermore, we propose possible extensions of the MAPE-K loop architecture with runtime models to further handle uncertainty at runtime. The chapter concludes by identifying key challenges, and enabling technologies for using runtime models to address uncertainty, and also identifies closely related research communities that can foster ideas for resolving the challenges raised. © 2014 Springer International Publishing.

Multiple Dipole Source Models for Scalp-Recorded Event-Related Potentials: Example from Complex Visual Processing in the Human Brain

2000 Mathematics Subject Classification: 62P10, 92C20

The eye of the beholder: The impact of a district implementation plan of state mandates as perceived by the implementers

The purpose of this inquiry was to investigate the impact of a large, urban school district's experience in implementing a mandated school improvement plan and to examine how that plan was perceived, interpreted, and executed by those charged with the task. The research addressed the following questions: First, by whom was the district implementation plan designed, and what factors were considered in its construction? Second, what impact did the district implementation plan have on those charged with its implementation? Third, what impact did the district plan have on the teaching and learning practices of a particular school? Fourth, what aspects of the implemention plan were perceived as most and least helpful by school personnel in achieving stated goals? Last, what were the intended and unintended consequences of an externally mandated and directed plan for improving student achievement? The implementation process was measured against Fullan's model as expounded upon in The Meaning of Educational Change (1982) and The New Meaning of Educational Change (1990). The Banya implementation model (1993), because it added a dimension not adequately addressed by Fullan, was also considered.^ A case study was used as the methodological framework of this qualitative study. Sources of data used in this inquiry included document analysis, participant observations in situ, follow-up interviews, the "long" interview, and triangulation. The study was conducted over a twelve-month period. Findings were obtained from the content analysis of interview transcripts of multiple participants. Results were described and interpreted using the Fullan and Banya models as the descriptive framework. A cross-case comparison of the multiple perspectives of the same phenomena by various participants was constructed.^ The study concluded that the school district's implementation plan to improve student achievement was closely aligned to Fullan's model, although not intentionally. The research also showed that where there was common understanding at all levels of the organization as to the expectations for teachers, level of support to be provided, and availability of resources, successful implementation occured. The areas where successful implementation did not occur were those where the complexity of the changes were underestimated and processes for dealing with unintended consequences were not considered or adequately addressed. The unique perspectives of the various participants, from the superintendent to the classroom teacher, are described. Finally, recommendations for enhancement of implementation are offered and possible topics for further research studies are postulated. ^

Changes in Brain Resting-state Functional Connectivity Associated with Peripheral Nerve Block: A Pilot Study.

BACKGROUND: Limited information exists on the effects of temporary functional deafferentation (TFD) on brain activity after peripheral nerve block (PNB) in healthy humans. Increasingly, resting-state functional connectivity (RSFC) is being used to study brain activity and organization. The purpose of this study was to test the hypothesis that TFD through PNB will influence changes in RSFC plasticity in central sensorimotor functional brain networks in healthy human participants. METHODS: The authors achieved TFD using a supraclavicular PNB model with 10 healthy human participants undergoing functional connectivity magnetic resonance imaging before PNB, during active PNB, and during PNB recovery. RSFC differences among study conditions were determined by multiple-comparison-corrected (false discovery rate-corrected P value less than 0.05) random-effects, between-condition, and seed-to-voxel analyses using the left and right manual motor regions. RESULTS: The results of this pilot study demonstrated disruption of interhemispheric left-to-right manual motor region RSFC (e.g., mean Fisher-transformed z [effect size] at pre-PNB 1.05 vs. 0.55 during PNB) but preservation of intrahemispheric RSFC of these regions during PNB. Additionally, there was increased RSFC between the left motor region of interest (PNB-affected area) and bilateral higher order visual cortex regions after clinical PNB resolution (e.g., Fisher z between left motor region of interest and right and left lingual gyrus regions during PNB, -0.1 and -0.6 vs. 0.22 and 0.18 after PNB resolution, respectively). CONCLUSIONS: This pilot study provides evidence that PNB has features consistent with other models of deafferentation, making it a potentially useful approach to investigate brain plasticity. The findings provide insight into RSFC of sensorimotor functional brain networks during PNB and PNB recovery and support modulation of the sensory-motor integration feedback loop as a mechanism for explaining the behavioral correlates of peripherally induced TFD through PNB.

Joint Analysis of Multiple Algorithms and Performance Measures

There has been an increasing interest in the development of new methods using Pareto optimality to deal with multi-objective criteria (for example, accuracy and time complexity). Once one has developed an approach to a problem of interest, the problem is then how to compare it with the state of art. In machine learning, algorithms are typically evaluated by comparing their performance on different data sets by means of statistical tests. Standard tests used for this purpose are able to consider jointly neither performance measures nor multiple competitors at once. The aim of this paper is to resolve these issues by developing statistical procedures that are able to account for multiple competing measures at the same time and to compare multiple algorithms altogether. In particular, we develop two tests: a frequentist procedure based on the generalized likelihood-ratio test and a Bayesian procedure based on a multinomial-Dirichlet conjugate model. We further extend them by discovering conditional independences among measures to reduce the number of parameters of such models, as usually the number of studied cases is very reduced in such comparisons. Data from a comparison among general purpose classifiers is used to show a practical application of our tests.

Economic Evaluations of State Policies

Thesis (Ph.D.)--University of Washington, 2016-08

State sum models for quantum gravity

This paper reviews the construction of quantum field theory on a 4-dimensional spacetime by combinatorial methods, and discusses the recent developments in the direction of a combinatorial construction of quantum gravity.

A path-based framework for analyzing large markov models

Reliability and dependability modeling can be employed during many stages of analysis of a computing system to gain insights into its critical behaviors. To provide useful results, realistic models of systems are often necessarily large and complex. Numerical analysis of these models presents a formidable challenge because the sizes of their state-space descriptions grow exponentially in proportion to the sizes of the models. On the other hand, simulation of the models requires analysis of many trajectories in order to compute statistically correct solutions. This dissertation presents a novel framework for performing both numerical analysis and simulation. The new numerical approach computes bounds on the solutions of transient measures in large continuous-time Markov chains (CTMCs). It extends existing path-based and uniformization-based methods by identifying sets of paths that are equivalent with respect to a reward measure and related to one another via a simple structural relationship. This relationship makes it possible for the approach to explore multiple paths at the same time,· thus significantly increasing the number of paths that can be explored in a given amount of time. Furthermore, the use of a structured representation for the state space and the direct computation of the desired reward measure (without ever storing the solution vector) allow it to analyze very large models using a very small amount of storage. Often, path-based techniques must compute many paths to obtain tight bounds. In addition to presenting the basic path-based approach, we also present algorithms for computing more paths and tighter bounds quickly. One resulting approach is based on the concept of path composition whereby precomputed subpaths are composed to compute the whole paths efficiently. Another approach is based on selecting important paths (among a set of many paths) for evaluation. Many path-based techniques suffer from having to evaluate many (unimportant) paths. Evaluating the important ones helps to compute tight bounds efficiently and quickly.

The use of animal models in multiple myeloma

International audience

Contributions to gait recognition using multiple views

Esta tesis se centra en la identificación de personas a través de la forma de caminar. El problema del reconocimiento del paso ha sido tratado mediante diferentes enfoques, en los dominios 2D y 3D, y usando una o varias vistas. Sin embargo, la dependencia con respecto al punto de vista, y por tanto de la trayectoria del sujeto al caminar sigue siendo aún un problema abierto. Se propone hacer frente al problema de la dependencia con respecto a la trayectoria por medio de reconstrucciones 3D de sujetos caminando. El uso de reconstrucciones varias ventajas que cabe destacar. En primer lugar, permite explotar una mayor cantidad de información en contraste con los métodos que extraen los descriptores de la marcha a partir de imágenes, en el dominio 2D. En segundo lugar, las reconstrucciones 3D pueden ser alineadas a lo largo de la marcha como si el sujeto hubiera caminado en una cinta andadora, proporcionando así una forma de analizar el paso independientemente de la trayectoria seguida. Este trabajo propone tres enfoques para resolver el problema de la dependencia a la vista: 1. Mediante la utilización de reconstrucciones volumétricas alineadas. 2. Mediante el uso de reconstrucciones volumétricas no alineadas. 3. Sin usar reconstrucciones. Se proponen además tres tipos de descriptores. El primero se centra en describir el paso mediante análisis morfológico de los volúmenes 3D alineados. El segundo hace uso del concepto de entropa de la información para describir la dinámica del paso humano. El tercero persigue capturar la dinámica de una forma invariante a rotación, lo cual lo hace especialmente interesante para ser aplicado tanto en trayectorias curvas como rectas, incluyendo cambios de dirección. Estos enfoques han sido probados sobre dos bases de datos públicas. Ambas están especialmente diseñadas para tratar el problema de la dependencia con respecto al punto de vista, y por tanto de la dependencia con respecto a la trayectoria. Los resultados experimentales muestran que para el enfoque basado en reconstrucciones volumétricas alineadas, el descriptor del paso basado en entropa consigue los mejores resultados, en comparación con métodos estrechamente relacionados del Estado del Arte actual. No obstante, el descriptor invariante a rotación consigue una tasa de reconocimiento que supera a los métodos actuales sin requerir la etapa previa de alineamiento de las reconstrucciones 3D.

Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM projects (Chapter 3). Returns from implemented ECM projects are used to fund additional ECM projects. In these cases, fluctuations in energy costs and uncertainty in the estimated savings severely influence ECM project selection and the amount of the appropriation requested. A risk aversion method proposed imposes a minimum on the number of “of projects completed in each stage. A comparative method using Conditional Value at Risk is analyzed. Time consistency was addressed in this chapter. This work demonstrates how a risk-based, stochastic, multi-stage model with binary decision variables at each stage provides a much more accurate estimate for planning than the agency’s traditional approach and deterministic models. Finally, in Chapter 4, a rolling-horizon model allows for subadditivity and superadditivity of the energy savings to simulate interactive effects between ECM projects. The approach makes use of inequalities (McCormick, 1976) to re-express constraints that involve the product of binary variables with an exact linearization (related to the convex hull of those constraints). This model additionally shows the benefits of learning between stages while remaining consistent with the single congressional appropriations framework.

Multiple sulfur isotope fractionations in inorganic aqueous systems

New constraints on isotope fractionation factors in inorganic aqueous sulfur systems based on theoretical and experimental techniques relevant to studies of the sulfur cycle in modern environments and the geologic rock record are presented in this dissertation. These include theoretical estimations of equilibrium isotope fractionation factors utilizing quantum mechanical software and a water cluster model approach for aqueous sulfur compounds that span the entire range of oxidation state for sulfur. These theoretical calculations generally reproduce the available experimental determinations from the literature and provide new constraints where no others are available. These theoretical calculations illustrate in detail the relationship between sulfur bonding environment and the mass dependence associated with equilibrium isotope exchange reactions involving all four isotopes of sulfur. I additionally highlight the effect of isomers of protonated compounds (compounds with the same chemical formula but different structure, where protons are bound to either sulfur or oxygen atoms) on isotope partitioning in the sulfite (S4+) and sulfoxylate (S2+) systems, both of which are key intermediates in oxidation-reduction processes in the sulfur cycle. I demonstrate that isomers containing the highest degree of coordination around sulfur (where protonation occurs on the sulfur atom) have a strong influence on isotopic fractionation factors, and argue that isomerization phenomenon should be considered in models of the sulfur cycle. Additionally, experimental results of the reaction rates and isotope fractionations associated with the chemical oxidation of aqueous sulfide are presented. Sulfide oxidation is a major process in the global sulfur cycle due largely to the sulfide-producing activity of anaerobic microorganisms in organic-rich marine sediments. These experiments reveal relationships between isotope fractionations and reaction rate as a function of both temperature and trace metal (ferrous iron) catalysis that I interpret in the context of the complex mechanism of sulfide oxidation. I also demonstrate that sulfide oxidation is a process associated with a mass dependence that can be described as not conforming to the mass dependence typically associated with equilibrium isotope exchange. This observation has implications for the inclusion of oxidative processes in environmental- and global-scale models of the sulfur cycle based on the mass balance of all four isotopes of sulfur. The contents of this dissertation provide key reference information on isotopic fractionation factors in aqueous sulfur systems that will have far-reaching applicability to studies of the sulfur cycle in a wide variety of natural settings.