Dynamic changes in high and low mammographic density human breast tissues maintained in murine tissue engineering chambers during various murine peripartum states and over time

Mammographic density (MD) is a strong heritable risk factor for breast cancer, and may decrease with increasing parity. However, the biomolecular basis for MD-associated breast cancer remains unclear, and systemic hormonal effects on MD-associated risk is poorly understood. This study assessed the effect of murine peripartum states on high and low MD tissue maintained in a xenograft model of human MD. Method High and low MD human breast tissues were precisely sampled under radiographic guidance from prophylactic mastectomy specimens of women. The high and low MD tissues were maintained in separate vascularised biochambers in nulliparous or pregnant SCID mice for 4 weeks, or mice undergoing postpartum involution or lactation for three additional weeks. High and low MD biochamber material was harvested for histologic and radiographic comparisons during various murine peripartum states. High and low MD biochamber tissues in nulliparous mice were harvested at different timepoints for histologic and radiographic comparisons. Results High MD biochamber tissues had decreased stromal (p = 0.0027), increased adipose (p = 0.0003) and a trend to increased glandular tissue areas (p = 0.076) after murine postpartum involution. Stromal areas decreased (p = 0.042), while glandular (p = 0.001) and adipose areas (p = 0.009) increased in high MD biochamber tissues during lactation. A difference in radiographic density was observed in high (p = 0.0021) or low MD biochamber tissues (p = 0.004) between nulliparous, pregnant and involution groups. No differences in tissue composition were observed in high or low MD biochamber tissues maintained for different durations, although radiographic density increased over time. Conclusion High MD biochamber tissues had measurable histologic changes after postpartum involution or lactation. Alterations in radiographic density occurred in biochamber tissues between different peripartum states and over time. These findings demonstrate the dynamic nature of the human MD xenograft model, providing a platform for studying the biomolecular basis of MD-associated cancer risk. © 2013 Springer Science+Business Media New York.

Aircraft dynamic navigation for unmanned aerial vehicles

This thesis describes the investigation of an Aircraft Dynamic Navigation (ADN) approach, which incorporates an Aircraft Dynamic Model (ADM) directly into the navigation filter of a fixed-wing aircraft or UAV. The result is a novel approach that offers both performance improvements and increased reliability during short-term GPS outages. This is important in allowing future UAVs to achieve routine, unconstrained, and safe operations in commercial environments. The primary contribution of this research is the formulation Unscented Kalman Filter (UKF) which incorporates a complex, non-linear, laterally and longitudinally coupled, ADM, and sensor suite consisting of a Global Positioning System (GPS) receiver, Inertial Measurement Unit (IMU), Electronic Compass (EC), and Air Data (AD) Pitot Static System.

Effect of vertical misalignment of adjacent sleepers on the increase in dynamic loads around rail joints

In spite of the extensive usage of continuous welded rails, a number of rail joints still exist in the track. Although a number of them exist as part of turnouts in the yards where the speed is not of concern, the Insultated Rail Joints (IRJs) that exist in ballasted tracks remain a source of significant impact loading. A portion of the dynamic load generated at the rail joints due to wheel passage is transmitted to the support system which leads to permanent settlements of the ballast layer with subsequent vertical misalignment of the sleepers around the rail joints. The vertical misalignment of the adjacent sleepers forms a source of high frequency dynamic load raisers causing significant maintenance work including localised grinding of railhead around the joint, re-alignment of the sleepers and/or ballast tamping or track component renewals/repairs. These localised maintenance activities often require manual inspections and disruptions to the train traffic loading to significant costs to the rail industry. Whilst a number of studies have modelled the effect of joints as dips, none have specifically attended to the effect of vertical misalignment of the sleepers on the dynamic response of rail joints. This paper presents a coupled finite element track model and rigid body track-vehicle interaction model through which the effects of vertical of sleepers on the increase in dynamic loads around the IRJ are studied. The finite element track model is employed to determine the generated dip from elastic deformations as well as the vertical displacement of sleepers around the joint. These data (dip and vertical misalignments) are then imported into the rigid body vehicle-track interaction model to calculate the dynamic loads.

Anti-wind-up designs for dynamic positioning of marine vehicles with control allocation

This paper presents a framework for the design of a joint motion controller and a control allocation strategy for dynamic positioning of marine vehicles. The key aspects of the proposed designs are a systematic approach to deal with actuator saturation and to inform the motion controller about saturation. The proposed system uses a mapping that translates the actuator constraint sets into constraint sets at the motion controller level. Hence, while the motion controller addresses the constraints, the control allocation algorithm can solve an unconstrained optimisation problem. The constrained control design is approached using a multivariable anti-wind-up strategy for strictly proper controllers. This is applicable to the implementation of PI and PID type of motion controllers.

The effect of multiplayer dynamic difficulty adjustment on the player experience of video games

Multiplayer Dynamic Difficulty Adjustment (mDDA) is a method of reducing the difference in player performance and subsequent challenge in competitive multiplayer video games. As a balance of between player skill and challenge experienced is necessary for optimal player experience, this experimental study investigates the effects of mDDA and awareness of its presence on player performance and experience using subjective and biometric measures. Early analysis indicates that mDDA normalizes performance and challenge as expected, but awareness of its presence can reduce its effectiveness.

A dynamic in vivo model of epithelial-to-mesenchymal transitions in circulating tumor cells and metastases of breast cancer

Epithelial-to-mesenchymal transition (EMT) processes endow epithelial cells with enhanced migratory/invasive properties and are therefore likely to contribute to tumor invasion and metastatic spread. Because of the difficulty in following EMT processes in human tumors, we have developed and characterized an animal model with transplantable human breast tumor cells (MDA-MB-468) uniquely showing spontaneous EMT events to occur. Using vimentin as a marker of EMT, heterogeneity was revealed in the primary MDA-MB-468 xenografts with vimentin-negative and vimentin-positive areas, as also observed on clinical human invasive breast tumor specimens. Reverse transcriptase-PCR after microdissection of these populations from the xenografts revealed EMT traits in the vimentin-positive zones characterized by enhanced 'mesenchymal gene' expression (Snail, Slug and fibroblast-specific protein-1) and diminished expression of epithelial molecules (E-cadherin, ZO-3 and JAM-A). Circulating tumor cells (CTCs) were detected in the blood as soon as 8 days after s.c. injection, and lung metastases developed in all animals injected as examined by in vivo imaging analyses and histology. High levels of vimentin RNA were detected in CTCs by reverse transcriptase-quantitative PCR as well as, to a lesser extent, Snail and Slug RNA. Von Willebrand Factor/vimentin double immunostainings further showed that tumor cells in vascular tumoral emboli all expressed vimentin. Tumoral emboli in the lungs also expressed vimentin whereas macrometastases displayed heterogenous vimentin expression, as seen in the primary xenografts. In conclusion, our data uniquely demonstrate in an in vivo context that EMT occurs in the primary tumors, and associates with an enhanced ability to intravasate and generate CTCs. They further suggest that mesenchymal-to-epithelial phenomena occur in secondary organs, facilitating the metastatic growth.

Dynamic modelling of long-term care decisions

This paper describes and analyzes research on the dynamics of long-term care and the policy relevance of identifying the sources of persistence in caregiving arrangements (including the effect of dynamics on parameter estimates, implications for family welfare, parent welfare, child welfare, and cost of government programs). We discuss sources and causes of observed persistence in caregiving arrangements including inertia/state dependence (confounded by unobserved heterogeneity) and costs of changing caregivers. We comment on causes of dynamics including learning/human capital accumulation; burnout; and game-playing. We suggest how to deal with endogenous geography; dynamics in discrete and continuous choices; and equilibrium issues (multiple equilibria, dynamic equilibria). We also present an overview of commonly used longitudinal data sets and evaluate their relative advantages/disadvantages. We also discuss other data issues related to noisy measures of wealth and family structure. Finally, we suggest some methods to handle econometric problems such as endogeneous geography. © 2014 Springer Science+Business Media New York.

Two dynamic discrete choice estimation problems and simulation method solutions

This paper considers two problems that frequently arise in dynamic discrete choice problems but have not received much attention with regard to simulation methods. The first problem is how to simulate unbiased simulators of probabilities conditional on past history. The second is simulating a discrete transition probability model when the underlying dependent variable is really continuous. Both methods work well relative to reasonable alternatives in the application discussed. However, in both cases, for this application, simpler methods also provide reasonably good results.

Approximate solutions to stochastic dynamic programs

This paper examines the properties of various approximation methods for solving stochastic dynamic programs in structural estimation problems. The problem addressed is evaluating the expected value of the maximum of available choices. The paper shows that approximating this by the maximum of expected values frequently has poor properties. It also shows that choosing a convenient distributional assumptions for the errors and then solving exactly conditional on the distributional assumption leads to small approximation errors even if the distribution is misspecified. © 1997 Cambridge University Press.

A dynamic Web agent for verifying the security and integrity of a Web site's contents

To harness safe operation of Web-based systems in Web environments, we propose an SSPA (Server-based SHA-1 Page-digest Algorithm) to verify the integrity of Web contents before the server issues an HTTP response to a user request. In addition to standard security measures, our Java implementation of the SSPA, which is called the Dynamic Security Surveillance Agent (DSSA), provides further security in terms of content integrity to Web-based systems. Its function is to prevent the display of Web contents that have been altered through the malicious acts of attackers and intruders on client machines. This is to protect the reputation of organisations from cyber-attacks and to ensure the safe operation of Web systems by dynamically monitoring the integrity of a Web site's content on demand. We discuss our findings in terms of the applicability and practicality of the proposed system. We also discuss its time metrics, specifically in relation to its computational overhead at the Web server, as well as the overall latency from the clients' point of view, using different Internet access methods. The SSPA, our DSSA implementation, some experimental results and related work are all discussed

Improvement of a dynamic accumulator at ICICS 07 and its application in multi-user keyword-based retrieval on encrypted data

A dynamic accumulator is an algorithm, which merges a large set of elements into a constant-size value such that for an element accumulated, there is a witness confirming that the element was included into the value, with a property that accumulated elements can be dynamically added and deleted into/from the original set. Recently Wang et al. presented a dynamic accumulator for batch updates at ICICS 2007. However, their construction suffers from two serious problems. We analyze them and propose a way to repair their scheme. We use the accumulator to construct a new scheme for common secure indices with conjunctive keyword-based retrieval.

Dynamic self-organization phenomena in complex ionized gas systems : new paradigms and technological aspects

An overview of dynamic self-organization phenomena in complex ionized gas systems, associated physical phenomena, and industrial applications is presented. The most recent experimental, theoretical, and modeling efforts to understand the growth mechanisms and dynamics of nano- and micron-sized particles, as well as the unique properties of the plasma-particle systems (colloidal, or complex plasmas) and the associated physical phenomena are reviewed and the major technological applications of micro- and nanoparticles are discussed. Until recently, such particles were considered mostly as a potential hazard for the microelectronic manufacturing and significant efforts were applied to remove them from the processing volume or suppress the gas-phase coagulation. Nowadays, fine clusters and particulates find numerous challenging applications in fundamental science as well as in nanotechnology and other leading high-tech industries.

Keyword field-free conjunctive keyword searches on encrypted data and extension for dynamic groups

We consider the following problem: a user stores encrypted documents on an untrusted server, and wishes to retrieve all documents containing some keywords without any loss of data confidentiality. Conjunctive keyword searches on encrypted data have been studied by numerous researchers over the past few years, and all existing schemes use keyword fields as compulsory information. This however is impractical for many applications. In this paper, we propose a scheme of keyword field-free conjunctive keyword searches on encrypted data, which affirmatively answers an open problem asked by Golle et al. at ACNS 2004. Furthermore, the proposed scheme is extended to the dynamic group setting. Security analysis of our constructions is given in the paper.

Lower partial moment and information entropy-based dynamic electricity purchasing strategy

In the electricity market environment, load-serving entities (LSEs) will inevitably face risks in purchasing electricity because there are a plethora of uncertainties involved. To maximize profits and minimize risks, LSEs need to develop an optimal strategy to reasonably allocate the purchased electricity amount in different electricity markets such as the spot market, bilateral contract market, and options market. Because risks originate from uncertainties, an approach is presented to address the risk evaluation problem by the combined use of the lower partial moment and information entropy (LPME). The lower partial moment is used to measure the amount and probability of the loss, whereas the information entropy is used to represent the uncertainty of the loss. Electricity purchasing is a repeated procedure; therefore, the model presented represents a dynamic strategy. Under the chance-constrained programming framework, the developed optimization model minimizes the risk of the electricity purchasing portfolio in different markets because the actual profit of the LSE concerned is not less than the specified target under a required confidence level. Then, the particle swarm optimization (PSO) algorithm is employed to solve the optimization model. Finally, a sample example is used to illustrate the basic features of the developed model and method.

Detection of dynamic primary user with cooperative spectrum sensing

In this paper we demonstrate that existing cooperative spectrum sensing formulated for static primary users cannot accurately detect dynamic primary users regardless of the information fusion method. Performance error occurs as the sensing parameters calculated by the conventional detector result in sensing performance that violates the sensing requirements. Furthermore, the error is accumulated and compounded by the number of cooperating nodes. To address this limitation, we design and implement the duty cycle detection model for the context of cooperative spectrum sensing to accurately calculate the sensing parameters that satisfy the sensing requirements. We show that longer sensing duration is required to compensate for dynamic primary user traffic.