Effects of Tamoxifen and oestrogen on histology and radiographic density in high and low mammographic density human breast tissues maintained in murine tissue engineering chambers

Mammographic density (MD) is a strong risk factor for breast cancer. It is altered by exogenous endocrine treatments, including hormone replacement therapy and Tamoxifen. Such agents also modify breast cancer (BC) risk. However, the biomolecular basis of how systemic endocrine therapy modifies MD and MD-associated BC risk is poorly understood. This study aims to determine whether our xenograft biochamber model can be used to study the effectiveness of therapies aimed at modulating MD, by examine the effects of Tamoxifen and oestrogen on histologic and radiographic changes in high and low MD tissues maintained within the biochamber model. High and low MD human tissues were precisely sampled under radiographic guidance from prophylactic mastectomy fresh specimens of high-risk women, then inserted into separate vascularized murine biochambers. The murine hosts were concurrently implanted with Tamoxifen, oestrogen or placebo pellets, and the high and low MD biochamber tissues maintained in the murine host environment for 3 months, before the high and low MD biochamber tissues were harvested for histologic and radiographic analyses. The radiographic density of high MD tissue maintained in murine biochambers was decreased in Tamoxifen-treated mice compared to oestrogen-treated mice (p = 0.02). Tamoxifen treatment of high MD tissue in SCID mice led to a decrease in stromal (p = 0.009), and an increase in adipose (p = 0.023) percent areas, compared to placebo-treated mice. No histologic or radiographic differences were observed in low MD biochamber tissue with any treatment. High MD biochamber tissues maintained in mice implanted with Tamoxifen, oestrogen or placebo pellets had dynamic and measurable histologic compositional and radiographic changes. This further validates the dynamic nature of the MD xenograft model, and suggests the biochamber model may be useful for assessing the underlying molecular pathways of Tamoxifen-reduced MD, and in testing of other pharmacologic interventions in a preclinical model of high MD.

Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

Towards development of a rapid and effective non-destructive testing strategy to identify brominated flame retardants in the plastics of consumer products

Polybrominated diphenyl ethers (PBDEs) are a class of brominated flame retardants (BFRs) once extensively used in the plastics of a wide range of consumer products. The listing of certain congeners that are constituents of commercial PBDE mixtures (including c-octaBDE) in the Stockholm Convention and tightening regulation of many other BFRs in recent years have created the need for a rapid and effective method of identifying BFR-containing plastics. A three-tiered testing strategy comparing results from non-destructive testing (X-ray fluorescence (XRF)) (n = 1714), a surface wipe test (n = 137) and destructive chemical analysis (n = 48) was undertaken to systematically identify BFRs in a wide range of consumer products. XRF rapidly identified bromine in 92% of products later confirmed to contain BFRs. Surface wipes of products identified tetrabromobisphenol A (TBBPA), c-octaBDE congeners and BDE-209 with relatively high accuracy (> 75%) when confirmed by destructive chemical analysis. A relationship between the amounts of BFRs detected in surface wipes and subsequent destructive testing shows promise in predicting not only the types of BFRs present but also estimating the concentrations present. Information about the types of products that may contain persistent BFRs will assist regulators in implementing policies to further reduce the occurrence of these chemicals in consumer products.

ISPCAN child abuse screening tool children's version (ICAST-C): Instrument development and multi-national pilot testing

Objective To develop a child victimization survey among a diverse group of child protection experts and examine the performance of the instrument through a set of international pilot studies. Methods The initial draft of the instrument was developed after input from scientists and practitioners representing 40 countries. Volunteers from the larger group of scientists participating in the Delphi review of the ICAST P and R reviewed the ICAST C by email in 2 rounds resulting in a final instrument. The ICAST C was then translated and back translated into six languages and field tested in four countries using a convenience sample of 571 children 12–17 years of age selected from schools and classrooms to which the investigators had easy access. Results The final ICAST C Home has 38 items and the ICAST C Institution has 44 items. These items serve as screeners and positive endorsements are followed by queries for frequency and perpetrator. Half of respondents were boys (49%). Endorsement for various forms of victimization ranged from 0 to 51%. Many children report violence exposure (51%), physical victimization (55%), psychological victimization (66%), sexual victimization (18%), and neglect in their homes (37%) in the last year. High rates of physical victimization (57%), psychological victimization (59%), and sexual victimization (22%) were also reported in schools in the last year. Internal consistency was moderate to high (alpha between .685 and .855) and missing data low (less than 1.5% for all but one item). Conclusions In pilot testing, the ICAST C identifies high rates of child victimization in all domains. Rates of missing data are low, and internal consistency is moderate to high. Pilot testing demonstrated the feasibility of using child self-report as one strategy to assess child victimization. Practice implications The ICAST C is a multi-national, multi-lingual, consensus-based survey instrument. It is available in six languages for international research to estimate child victimization. Assessing the prevalence of child victimization is critical in understanding the scope of the problem, setting national and local priorities, and garnering support for program and policy development aimed at child protection.

Design and flight testing of an integrated solar powered UAV and WSN for greenhouse gas monitoring emissions in agricultural farms

There is an increased interest in measuring the amount of greenhouse gases produced by farming practices . This paper describes an integrated solar powered Unmanned Air Vehicles (UAV) and Wireless Sensor Network (WSN) gas sensing system for greenhouse gas emissions in agricultural lands. The system uses a generic gas sensing system for CH4 and CO2 concentrations using metal oxide (MoX) and non-dispersive infrared sensors, and a new solar cell encapsulation method to power the unmanned aerial system (UAS)as well as a data management platform to store, analyze and share the information with operators and external users. The system was successfully field tested at ground and low altitudes, collecting, storing and transmitting data in real time to a central node for analysis and 3D mapping. The system can be used in a wide range of outdoor applications at a relatively low operational cost. In particular, agricultural environments are increasingly subject to emissions mitigation policies. Accurate measurements of CH4 and CO2 with its temporal and spatial variability can provide farm managers key information to plan agricultural practices. A video of the bench and flight test performed can be seen in the following link: https://www.youtube.com/watch?v=Bwas7stYIxQ

Complex crystallization dynamics in amorphous germanium observed with dynamic transmission electron microscopy

Crystallization of amorphous germanium (a-Ge) by laser or electron beam heating is a remarkably complex process that involves several distinct modes of crystal growth and the development of intricate microstructural patterns on the nanosecond to ten microsecond time scales. Here we use dynamic transmission electron microscopy (DTEM) to study the fast, complex crystallization dynamics with 10 nm spatial and 15 ns temporal resolution. We have obtained time-resolved real-space images of nanosecond laser-induced crystallization in a-Ge with unprecedentedly high spatial resolution. Direct visualization of the crystallization front allows for time-resolved snapshots of the initiation and roughening of the dendrites on submicrosecond time scales. This growth is followed by a rapid transition to a ledgelike growth mechanism that produces a layered microstructure on a time scale of several microseconds. This study provides insights into the mechanisms governing this complex crystallization process and is a dramatic demonstration of the power of DTEM for studying time-dependent material processes far from equilibrium.

In situ investigation of explosive crystallization in a-Ge: Experimental determination of the interface response function using dynamic transmission electron microscopy

The crystallization of amorphous semiconductors is a strongly exothermic process. Once initiated the release of latent heat can be sufficient to drive a self-sustaining crystallization front through the material in a manner that has been described as explosive. Here, we perform a quantitative in situ study of explosive crystallization in amorphous germanium using dynamic transmission electron microscopy. Direct observations of the speed of the explosive crystallization front as it evolves along a laser-imprinted temperature gradient are used to experimentally determine the complete interface response function (i.e., the temperature-dependent front propagation speed) for this process, which reaches a peak of 16 m/s. Fitting to the Frenkel-Wilson kinetic law demonstrates that the diffusivity of the material locally/immediately in advance of the explosive crystallization front is inconsistent with those of a liquid phase. This result suggests a modification to the liquid-mediated mechanism commonly used to describe this process that replaces the phase change at the leading amorphous-liquid interface with a change in bonding character (from covalent to metallic) occurring in the hot amorphous material.

A critical evaluation of literature on robot path planning in dynamic environment

Robot Path Planning (RPP) in dynamic environments is a search problem based on the examination of collision-free paths in the presence of dynamic and static obstacles. Many techniques have been developed to solve this problem. Trapping in a local minima and maintaining a Real-Time performance are known as the two most important challenges that these techniques face to solve such problem. This study presents a comprehensive survey of the various techniques that have been proposed in this domain. As part of this survey, we include a classification of the approaches and identify their methods.

Boarding Control System - for Improved Accessibility to Offshore Wind Turbines

This paper considers the dynamic modelling and motion control of a Surface Effect Ship (SES) for safer transfer of personnel and equipment from vessel to-and-from an offshore wind-turbine. Such a vessel is a key enabling factor for operation and maintenance (O&M) of offshore wind-energy infrastructure. The control system designed is referred to as Boarding Control System (BCS). We investigate the performance of this system for a specific wind-farm service vessel–The Wave Craft. A two-modality vessel model is presented to account for the vessel free motion and motion whilst in contact with a wind-turbine. On a SES, the pressurized air cushion carries the majority of the vessel mass. The control problem considered relates to the actuation of the pressure such that wave-induced vessel motions are minimized. This leads to a safer personnel transfer in developed sea-states than what is possible today. Results for the BCS is presented through simulation and model-scale craft testing.

Initial prototype testing of Ray's Night Out: A new mobile app targeting risky drinking in young people

Background Risky single occasion drinking (RSOD; 4 or more drinks in <6 h) more than doubles the risk of injury in young people (15 - 25 years). The potential role of smartphone apps in reducing RSOD in young people is yet to be explored. Objective: To describe the initial prototype testing of ‘Ray's Night Out’, a new iPhone app targeting RSOD in young people. Method Quantitative and qualitative methods were used to evaluate the quality, perceived utility, and acceptability of the app among nine young people (19e23 years). Results Participants reported Ray's Night Out had good to excellent levels of functionality and visual appeal, acceptable to good levels of entertainment, interest and information, and acceptable levels of customization and interactivity. Young people thought the app had high levels of youth appeal, would prompt users to think about their alcohol use limits, but was unlikely to motivate a change in alcohol use in its current form. Qualitative data provided several suggestions for improving the app. Conclusion Following revision, Ray's Night Out could provide an effective intervention for RSOD in non help-seeking young people. A randomized controlled trial is currently underway to test the final prototype of the app.

An optimal design for screening trials

Yao, Begg, and Livingston (1996, Biometrics 52, 992-1001) considered the optimal group size for testing a series of potentially therapeutic agents to identify a promising one as soon as possible for given error rates. The number of patients to be tested with each agent was fixed as the group size. We consider a sequential design that allows early acceptance and rejection, and we provide an optimal strategy to minimize the sample sizes (patients) required using Markov decision processes. The minimization is under the constraints of the two types (false positive and false negative) of error probabilities, with the Lagrangian multipliers corresponding to the cost parameters for the two types of errors. Numerical studies indicate that there can be a substantial reduction in the number of patients required.

The Learning Component of Dynamic Allocation Indices

For a multiarmed bandit problem with exponential discounting the optimal allocation rule is defined by a dynamic allocation index defined for each arm on its space. The index for an arm is equal to the expected immediate reward from the arm, with an upward adjustment reflecting any uncertainty about the prospects of obtaining rewards from the arm, and the possibilities of resolving those uncertainties by selecting that arm. Thus the learning component of the index is defined to be the difference between the index and the expected immediate reward. For two arms with the same expected immediate reward the learning component should be larger for the arm for which the reward rate is more uncertain. This is shown to be true for arms based on independent samples from a fixed distribution with an unknown parameter in the cases of Bernoulli and normal distributions, and similar results are obtained in other cases.

A robust approach to design a single facility layout plan in dynamic manufacturing environments using a permutation-based genetic algorithm

During the past few decades, developing efficient methods to solve dynamic facility layout problems has been focused on significantly by practitioners and researchers. More specifically meta-heuristic algorithms, especially genetic algorithm, have been proven to be increasingly helpful to generate sub-optimal solutions for large-scale dynamic facility layout problems. Nevertheless, the uncertainty of the manufacturing factors in addition to the scale of the layout problem calls for a mixed genetic algorithm–robust approach that could provide a single unlimited layout design. The present research aims to devise a customized permutation-based robust genetic algorithm in dynamic manufacturing environments that is expected to be generating a unique robust layout for all the manufacturing periods. The numerical outcomes of the proposed robust genetic algorithm indicate significant cost improvements compared to the conventional genetic algorithm methods and a selective number of other heuristic and meta-heuristic techniques.

Direct shear testing on unsaturated silty soils to investigate the effects of drying and wetting on shear strength parameters at low suction

A modified conventional direct shear device was used to measure unsaturated shear strength of two silty soils at low suction values (0 ~ 50 kPa) that were achieved by following drying and wetting paths of soil water characteristic curves (SWCCs). The results revealed that the internal friction angle of the soils was not significantly affected by either the suction or the drying wetting SWCCs. The apparent cohesion of soil increased with a decreasing rate as suction increased. Shear stress-shear displacement curves obtained from soil specimens subjected to the same net normal stress and different suction values showed a higher initial stiffness and a greater peak stress as suction increased. A soil in wetting exhibited slightly higher peak shear stress and more contractive volume change behavior than that of soil in drying at the same net normal stress and suction.

Random Breath Testing Operation and Effectiveness in 1987

• In December 1986 funds were approved to double the intensity of random breath testing (RBT) and provide publicity support for police efforts. These changes were considered necessary to make RBT effective. • RBT methods were changed in the metropolitan area to enable block testing (pulling over a block of traffic rather than one or two cars), deployment of police to cut off escape routes, and testing by traffic patrols in all police subdivisions. Additional operators were trained for country RBT. • A publicity campaign was developed, aimed mainly at male drivers aged 18-50. The campaign consisted of the “cardsharp” television commercials, radio commercials, newspaper articles, posters and pamphlets. • Increased testing and the publicity campaigns were launched on 10 April 1987. • Police tests increased by 92.5% in May – December 1987, compared with the same period in the previous four years. • The detection rate for drinking drivers picked up by police who were cutting off escape routes was comparatively high, indicating that drivers were attempting to avoid RBT, and that this police method was effective at detecting these drivers. • A telephone survey indicated that drivers were aware of the messages of the publicity campaign. • The telephone survey also indicated that the target group had been exposed to high levels of RBT, as planned, and that fear of apprehension was the major factor deterring them from drink driving. • A roadside survey of driver blood alcohol concentrations (BACs) by the University of Adelaide’s Road Accident Research Unit (RARU) showed that, between 10p.m. and 3a.m., the proportion of drivers in Adelaide with a BAC greater than or equal to 0/08 decreased by 42%. • Drivers under 21 were identified as a possible problem area. • Fatalities in the twelve month period commencing May 1987 decreased by 18% in comparison with the previous twelve month period, and by 13% in comparison with the average of the previous two twelve month periods (commencing May 1985 and May 1986). There are indications that this trend is continuing. • It is concluded that the increase in RBT, plus publicity, was successful in achieving its aims of reductions in drink driving and accidents.