MicroRNAs may mediate the down-regulation of neurokinin-1 receptor in chronic bladder pain syndrome

Bladder pain syndrome (BPS) is a clinical syndrome of pelvic pain and urinary urgency-frequency in the absence of a specific cause. Investigating the expression levels of genes involved in the regulation of epithelial permeability, bladder contractility, and inflammation, we show that neurokinin (NK)1 and NK2 tachykinin receptors were significantly down-regulated in BPS patients. Tight junction proteins zona occludens-1, junctional adherins molecule -1, and occludin were similarly down-regulated, implicating increased urothelial permeability, whereas bradykinin B(1) receptor, cannabinoid receptor CB1 and muscarinic receptors M3-M5 were up-regulated. Using cell-based models, we show that prolonged exposure of NK1R to substance P caused a decrease of NK1R mRNA levels and a concomitant increase of regulatory micro(mi)RNAs miR-449b and miR-500. In the biopsies of BPS patients, the same miRNAs were significantly increased, suggesting that BPS promotes an attenuation of NK1R synthesis via activation of specific miRNAs. We confirm this hypothesis by identifying 31 differentially expressed miRNAs in BPS patients and demonstrate a direct correlation between miR-449b, miR-500, miR-328, and miR-320 and a down-regulation of NK1R mRNA and/or protein levels. Our findings further the knowledge of the molecular mechanisms of BPS, and have relevance for other clinical conditions involving the NK1 receptor.

Towards Energy Consumption Measurement in a Cloud Computing Wireless Testbed

The evolution of the Next Generation Networks, especially the wireless broadband access technologies such as Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX), have increased the number of "all-IP" networks across the world. The enhanced capabilities of these access networks has spearheaded the cloud computing paradigm, where the end-users aim at having the services accessible anytime and anywhere. The services availability is also related with the end-user device, where one of the major constraints is the battery lifetime. Therefore, it is necessary to assess and minimize the energy consumed by the end-user devices, given its significance for the user perceived quality of the cloud computing services. In this paper, an empirical methodology to measure network interfaces energy consumption is proposed. By employing this methodology, an experimental evaluation of energy consumption in three different cloud computing access scenarios (including WiMAX) were performed. The empirical results obtained show the impact of accurate network interface states management and application network level design in the energy consumption. Additionally, the achieved outcomes can be used in further software-based models to optimized energy consumption, and increase the Quality of Experience (QoE) perceived by the end-users.

A unified approach to modeling multivariate binary data using copulas over partitions

Many seemingly disparate approaches for marginal modeling have been developed in recent years. We demonstrate that many current approaches for marginal modeling of correlated binary outcomes produce likelihoods that are equivalent to the proposed copula-based models herein. These general copula models of underlying latent threshold random variables yield likelihood based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalized models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts.

Human and embodied energy analysis applied to water source protection and household water treatment interventions used in Mali, West Africa

As water quality interventions are scaled up to meet the Millennium Development Goal of halving the proportion of the population without access to safe drinking water by 2015 there has been much discussion on the merits of household- and source-level interventions. This study furthers the discussion by examining specific interventions through the use of embodied human and material energy. Embodied energy quantifies the total energy required to produce and use an intervention, including all upstream energy transactions. This model uses material quantities and prices to calculate embodied energy using national economic input/output-based models from China, the United States and Mali. Embodied energy is a measure of aggregate environmental impacts of the interventions. Human energy quantifies the caloric expenditure associated with the installation and operation of an intervention is calculated using the physical activity ratios (PARs) and basal metabolic rates (BMRs). Human energy is a measure of aggregate social impacts of an intervention. A total of four household treatment interventions – biosand filtration, chlorination, ceramic filtration and boiling – and four water source-level interventions – an improved well, a rope pump, a hand pump and a solar pump – are evaluated in the context of Mali, West Africa. Source-level interventions slightly out-perform household-level interventions in terms of having less total embodied energy. Human energy, typically assumed to be a negligible portion of total embodied energy, is shown to be significant to all eight interventions, and contributing over half of total embodied energy in four of the interventions. Traditional gender roles in Mali dictate the types of work performed by men and women. When the human energy is disaggregated by gender, it is seen that women perform over 99% of the work associated with seven of the eight interventions. This has profound implications for gender equality in the context of water quality interventions, and may justify investment in interventions that reduce human energy burdens.

Parameter estimation for transformer modeling

Large Power transformers, an aging and vulnerable part of our energy infrastructure, are at choke points in the grid and are key to reliability and security. Damage or destruction due to vandalism, misoperation, or other unexpected events is of great concern, given replacement costs upward of $2M and lead time of 12 months. Transient overvoltages can cause great damage and there is much interest in improving computer simulation models to correctly predict and avoid the consequences. EMTP (the Electromagnetic Transients Program) has been developed for computer simulation of power system transients. Component models for most equipment have been developed and benchmarked. Power transformers would appear to be simple. However, due to their nonlinear and frequency-dependent behaviors, they can be one of the most complex system components to model. It is imperative that the applied models be appropriate for the range of frequencies and excitation levels that the system experiences. Thus, transformer modeling is not a mature field and newer improved models must be made available. In this work, improved topologically-correct duality-based models are developed for three-phase autotransformers having five-legged, three-legged, and shell-form cores. The main problem in the implementation of detailed models is the lack of complete and reliable data, as no international standard suggests how to measure and calculate parameters. Therefore, parameter estimation methods are developed here to determine the parameters of a given model in cases where available information is incomplete. The transformer nameplate data is required and relative physical dimensions of the core are estimated. The models include a separate representation of each segment of the core, including hysteresis of the core, λ-i saturation characteristic, capacitive effects, and frequency dependency of winding resistance and core loss. Steady-state excitation, and de-energization and re-energization transients are simulated and compared with an earlier-developed BCTRAN-based model. Black start energization cases are also simulated as a means of model evaluation and compared with actual event records. The simulated results using the model developed here are reasonable and more correct than those of the BCTRAN-based model. Simulation accuracy is dependent on the accuracy of the equipment model and its parameters. This work is significant in that it advances existing parameter estimation methods in cases where the available data and measurements are incomplete. The accuracy of EMTP simulation for power systems including three-phase autotransformers is thus enhanced. Theoretical results obtained from this work provide a sound foundation for development of transformer parameter estimation methods using engineering optimization. In addition, it should be possible to refine which information and measurement data are necessary for complete duality-based transformer models. To further refine and develop the models and transformer parameter estimation methods developed here, iterative full-scale laboratory tests using high-voltage and high-power three-phase transformer would be helpful.

Energy and conductance state modeling of power electronic converters for DC microgrids

This document will demonstrate the methodology used to create an energy and conductance based model for power electronic converters. The work is intended to be a replacement for voltage and current based models which have limited applicability to the network nodal equations. Using conductance-based modeling allows direct application of load differential equations to the bus admittance matrix (Y-bus) with a unified approach. When applied directly to the Y-bus, the system becomes much easier to simulate since the state variables do not need to be transformed. The proposed transformation applies to loads, sources, and energy storage systems and is useful for DC microgrids. Transformed state models of a complete microgrid are compared to experimental results and show the models accurately reflect the system dynamic behavior.

A Calculus of Evolving Objects

The demands of developing modern, highly dynamic applications have led to an increasing interest in dynamic programming languages and mechanisms. Not only applications must evolve over time, but the object models themselves may need to be adapted to the requirements of different run-time contexts. Class-based models and prototype-based models, for example, may need to co-exist to meet the demands of dynamically evolving applications. Multi-dimensional dispatch, fine-grained and dynamic software composition, and run-time evolution of behaviour are further examples of diverse mechanisms which may need to co-exist in a dynamically evolving run-time environment How can we model the semantics of these highly dynamic features, yet still offer some reasonable safety guarantees? To this end we present an original calculus in which objects can adapt their behaviour at run-time to changing contexts. Both objects and environments are represented by first-class mappings between variables and values. Message sends are dynamically resolved to method calls. Variables may be dynamically bound, making it possible to model a variety of dynamic mechanisms within the same calculus. Despite the highly dynamic nature of the calculus, safety properties are assured by a type assignment system.

A Calculus of Evolving Objects

The demands of developing modern, highly dynamic applications have led to an increasing interest in dynamic programming languages and mechanisms. Not only must applications evolve over time, but the object models themselves may need to be adapted to the requirements of different run-time contexts. Class-based models and prototype-based models, for example, may need to co-exist to meet the demands of dynamically evolving applications. Multi-dimensional dispatch, fine-grained and dynamic software composition, and run-time evolution of behaviour are further examples of diverse mechanisms which may need to co-exist in a dynamically evolving run-time environment. How can we model the semantics of these highly dynamic features, yet still offer some reasonable safety guarantees? To this end we present an original calculus in which objects can adapt their behaviour at run-time. Both objects and environments are represented by first-class mappings between variables and values. Message sends are dynamically resolved to method calls. Variables may be dynamically bound, making it possible to model a variety of dynamic mechanisms within the same calculus. Despite the highly dynamic nature of the calculus, safety properties are assured by a type assignment system.

Retention in care under universal antiretroviral therapy for HIV-infected pregnant and breastfeeding women ('Option B+') in Malawi

OBJECTIVE To explore the levels and determinants of loss to follow-up (LTF) under universal lifelong antiretroviral therapy (ART) for pregnant and breastfeeding women ('Option B+') in Malawi. DESIGN, SETTING, AND PARTICIPANTS We examined retention in care, from the date of ART initiation up to 6 months, for women in the Option B+ program. We analysed nationwide facility-level data on women who started ART at 540 facilities (n = 21 939), as well as individual-level data on patients who started ART at 19 large facilities (n = 11 534). RESULTS Of the women who started ART under Option B+ (n = 21 939), 17% appeared to be lost to follow-up 6 months after ART initiation. Most losses occurred in the first 3 months of therapy. Option B+ patients who started therapy during pregnancy were five times more likely than women who started ART in WHO stage 3/4 or with a CD4 cell count 350 cells/μl or less, to never return after their initial clinic visit [odds ratio (OR) 5.0, 95% confidence interval (CI) 4.2-6.1]. Option B+ patients who started therapy while breastfeeding were twice as likely to miss their first follow-up visit (OR 2.2, 95% CI 1.8-2.8). LTF was highest in pregnant Option B+ patients who began ART at large clinics on the day they were diagnosed with HIV. LTF varied considerably between facilities, ranging from 0 to 58%. CONCLUSION Decreasing LTF will improve the effectiveness of the Option B+ approach. Tailored interventions, like community or family-based models of care could improve its effectiveness.

Gründungsausbildung und Gründungsabsicht: eine empirische Untersuchung an der TU Dortmund

Für das wirtschaftliche Wachstum und die Innovationskraft einer Volkswirtschaft sind junge Unternehmen von herausragender Bedeutung. Ein wichtiges Ziel von Politik und Wirtschaft muss folglich die Sensibilisierung und Förderung potenzieller Gründer sein. Die vorliegende Untersuchung geht der Frage nach, ob eine universitäre Gründungsausbildung die Gründungsabsicht von Studierenden positiv beeinflussen kann. Aufbauend auf dem intentionsbasierten Modell von Krueger /Carsrud (1993) wurden im Rahmen einer Befragung an der TU Dortmund 111 Studierende der Wirtschaftswissenschaften zu ihren Gründungsabsichten befragt. Es zeigte sich, dass die Gründungsabsicht durch den Besuch von Veranstaltungen zum Gründungsmanagement deutlich gesteigert werden kann. Für die deutsche Wirtschafts- und Bildungspolitik ergibt sich aus den Ergebnissen die Handlungsempfehlung, die universitäre Gründungsausbildung auszubauen und intensiv zu fördern.

Spike timing dependent plasticity: a consequence of more fundamental learning rules.

Spike timing dependent plasticity (STDP) is a phenomenon in which the precise timing of spikes affects the sign and magnitude of changes in synaptic strength. STDP is often interpreted as the comprehensive learning rule for a synapse - the "first law" of synaptic plasticity. This interpretation is made explicit in theoretical models in which the total plasticity produced by complex spike patterns results from a superposition of the effects of all spike pairs. Although such models are appealing for their simplicity, they can fail dramatically. For example, the measured single-spike learning rule between hippocampal CA3 and CA1 pyramidal neurons does not predict the existence of long-term potentiation one of the best-known forms of synaptic plasticity. Layers of complexity have been added to the basic STDP model to repair predictive failures, but they have been outstripped by experimental data. We propose an alternate first law: neural activity triggers changes in key biochemical intermediates, which act as a more direct trigger of plasticity mechanisms. One particularly successful model uses intracellular calcium as the intermediate and can account for many observed properties of bidirectional plasticity. In this formulation, STDP is not itself the basis for explaining other forms of plasticity, but is instead a consequence of changes in the biochemical intermediate, calcium. Eventually a mechanism-based framework for learning rules should include other messengers, discrete change at individual synapses, spread of plasticity among neighboring synapses, and priming of hidden processes that change a synapse's susceptibility to future change. Mechanism-based models provide a rich framework for the computational representation of synaptic plasticity.

Modeled Interaction of Comet 67P/Churyumov-Gerasimenko with the Solar Wind Inside 2 AU

Periodic comets move around the Sun on elliptical orbits. As such comet 67P/Churyumov-Gerasimenko (hereafter 67P) spends a portion of time in the inner solar system where it is exposed to increased solar insolation. Therefore given the change in heliocentric distance, in case of 67P from aphelion at 5.68 AU to perihelion at ~1.24 AU, the comet’s activity—the production of neutral gas and dust—undergoes significant variations. As a consequence, during the inbound portion, the mass loading of the solar wind increases and extends to larger spatial scales. This paper investigates how this interaction changes the character of the plasma environment of the comet by means of multifluid MHD simulations. The multifluid MHD model is capable of separating the dynamics of the solar wind ions and the pick-up ions created through photoionization and electron impact ionization in the coma of the comet. We show how two of the major boundaries, the bow shock and the diamagnetic cavity, form and develop as the comet moves through the inner solar system. Likewise for 67P, although most likely shifted back in time with respect to perihelion passage, this process is reversed on the outbound portion of the orbit. The presented model herein is able to reproduce some of the key features previously only accessible to particle-based models that take full account of the ions’ gyration. The results shown herein are in decent agreement to these hybrid-type kinetic simulations.

A Mathematical Model for Simplifying Representations of Objects in a Geographic Information System

The study of operations on representations of objects is well documented in the realm of spatial engineering. However, the mathematical structure and formal proof of these operational phenomena are not thoroughly explored. Other works have often focused on query-based models that seek to order classes and instances of objects in the form of semantic hierarchies or graphs. In some models, nodes of graphs represent objects and are connected by edges that represent different types of coarsening operators. This work, however, studies how the coarsening operator "simplification" can manipulate partitions of finite sets, independent from objects and their attributes. Partitions that are "simplified first have a collection of elements filtered (removed), and then the remaining partition is amalgamated (some sub-collections are unified). Simplification has many interesting mathematical properties. A finite composition of simplifications can also be accomplished with some single simplification. Also, if one partition is a simplification of the other, the simplified partition is defined to be less than the other partition according to the simp relation. This relation is shown to be a partial-order relation based on simplification. Collections of partitions can not only be proven to have a partial- order structure, but also have a lattice structure and are complete. In regard to a geographic information system (GIs), partitions related to subsets of attribute domains for objects are called views. Objects belong to different views based whether or not their attribute values lie in the underlying view domain. Given a particular view, objects with their attribute n-tuple codings contained in the view are part of the actualization set on views, and objects are labeled according to the particular subset of the view in which their coding lies. Though the scope of the work does not mainly focus on queries related directly to geographic objects, it provides verification for the existence of particular views in a system with this underlying structure. Given a finite attribute domain, one can say with mathematical certainty that different views of objects are partially ordered by simplification, and every collection of views has a greatest lower bound and least upper bound, which provides the validity for exploring queries in this regard.

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

The Study of International Cultural Relations of Postwar Japan

The paper examines policies and activities of cultural exchange carried out by Japanese national, local and private agents since the end of WWII. Methodologically, we distinctively use the notion culture as a tool and as an object of study, and to synthesize the two in full intention, based on the debate among IR students about so called Cultural Turn in IR theories. As case studies, the Japanese experiences are examined from two points. Firstly, it is compared with the German experiences in Europe, with special attention to the construction of national identity.In both countries, the peoples tried to make use of cultural exchange activities in the management of international relations. The actual developments of cultural relations by the two countries, however, were in striking contrast to each other. Secondly, our study focuses on the explosive expansion of private sector's international cultural exchange in the 1980s in association with so called "emerging civil society" phenomenon observed worldwide throughout 1970s and 1980s. By using our original approach mentioned in the Chapter 1, the paper tries to sketch out that the increase of the private organizations is largely the response of the Japanese society to outside influences, not something genuinely outgrown from within the society itself due to mainly domestic causes.