No evidence for large differences in genomic methylation between wild and hatchery steelhead (Oncorhynchus mykiss)

When salmonid fish that have been raised in hatcheries spawn in the wild, they often produce fewer surviving adult offspring than wild fish. Recent data from steelhead (Oncorhynchus mykiss) in the Hood River (Oregon, USA) show that even one or two generations of hatchery culture can result in dramatic declines in fitness. Although intense domestication selection could cause such declines, it is worth considering alternative explanations. One possibility is heritable epigenetic changes induced by the hatchery environment. Here, we show, using methylation-sensitive amplified fragment length polymorphism, that hatchery and wild adult steelhead from the Hood River do not appear to differ substantially in overall levels of genomic methylation. Thus, although altered methylation of specific DNA sites or other epigenetic processes could still be important, the hatchery environment does not appear to cause a global hypo- or hypermethylation of the genome or create a large number of sites that are differentially methylated.

Increasing Utilization of US Electric Grids via Smart Technologies: Integration of Load Management, Real Time Pricing, Renewables, EVs and Smart Grid Sensors

Electric power grids throughout the world suffer from serious inefficiencies associated with under-utilization due to demand patterns, engineering design and load following approaches in use today. These grids consume much of the world’s energy and represent a large carbon footprint. From material utilization perspectives significant hardware is manufactured and installed for this infrastructure often to be used at less than 20-40% of its operational capacity for most of its lifetime. These inefficiencies lead engineers to require additional grid support and conventional generation capacity additions when renewable technologies (such as solar and wind) and electric vehicles are to be added to the utility demand/supply mix. Using actual data from the PJM [PJM 2009] the work shows that consumer load management, real time price signals, sensors and intelligent demand/supply control offer a compelling path forward to increase the efficient utilization and carbon footprint reduction of the world’s grids. Underutilization factors from many distribution companies indicate that distribution feeders are often operated at only 70-80% of their peak capacity for a few hours per year, and on average are loaded to less than 30-40% of their capability. By creating strong societal connections between consumers and energy providers technology can radically change this situation. Intelligent deployment of smart sensors, smart electric vehicles, consumer-based load management technology very high saturations of intermittent renewable energy supplies can be effectively controlled and dispatched to increase the levels of utilization of existing utility distribution, substation, transmission, and generation equipment. The strengthening of these technology, society and consumer relationships requires rapid dissemination of knowledge (real time prices, costs & benefit sharing, demand response requirements) in order to incentivize behaviors that can increase the effective use of technological equipment that represents one of the largest capital assets modern society has created.

Evaluation of a portable image overlay projector for the visualisation of surgical navigation data: phantom studies

Presenting visual feedback for image-guided surgery on a monitor requires the surgeon to perform time-consuming comparisons and diversion of sight and attention away from the patient. Deficiencies in previously developed augmented reality systems for image-guided surgery have, however, prevented the general acceptance of any one technique as a viable alternative to monitor displays. This work presents an evaluation of the feasibility and versatility of a novel augmented reality approach for the visualisation of surgical planning and navigation data. The approach, which utilises a portable image overlay device, was evaluated during integration into existing surgical navigation systems and during application within simulated navigated surgery scenarios.

Antimicrobial use in Swiss dairy farms: quantification and evaluation of data quality

Data on antimicrobial use play a key role in the development of policies for the containment of antimicrobial resistance. On-farm data could provide a detailed overview of the antimicrobial use, but technical and methodological aspects of data collection and interpretation, as well as data quality need to be further assessed. The aims of this study were (1) to quantify antimicrobial use in the study population using different units of measurement and contrast the results obtained, (2) to evaluate data quality of farm records on antimicrobial use, and (3) to compare data quality of different recording systems. During 1 year, data on antimicrobial use were collected from 97 dairy farms. Antimicrobial consumption was quantified using: (1) the incidence density of antimicrobial treatments; (2) the weight of active substance; (3) the used daily dose and (4) the used course dose for antimicrobials for intestinal, intrauterine and systemic use; and (5) the used unit dose, for antimicrobials for intramammary use. Data quality was evaluated by describing completeness and accuracy of the recorded information, and by comparing farmers' and veterinarians' records. Relative consumption of antimicrobials depended on the unit of measurement: used doses reflected the treatment intensity better than weight of active substance. The use of antimicrobials classified as high priority was low, although under- and overdosing were frequently observed. Electronic recording systems allowed better traceability of the animals treated. Recording drug name or dosage often resulted in incomplete or inaccurate information. Veterinarians tended to record more drugs than farmers. The integration of veterinarian and farm data would improve data quality.

INTEGRATION D’UN OBSERVATOIRE URBAIN SUR GOOGLE MAPS : Cas des infrastructures de la santé de la ville de Douala Cameroun

The spectacular advances computer science applied to geographic information systems (GIS) in recent times has favored the emergence of several technological solutions. These developments have given rise to enormous opportunities for digital management of the territory. Among the technological solutions, the most famous Google Maps offers free online mapping dynamic exhaustive of the Maps. In addition to meet the enormous needs of urban indicators geotagged information, we did work on this project “Integration of an urban observatory on Google Maps.” The problem of geolocation in the urban observatory is particularly relevant in the sense that there is currently no data (descriptive and geographical) reliable on the urban sector; we must stick to extrapolate from data old and obsolete. This helps to curb the effectiveness of urban management to make difficult investment programming and to prevent the acquisition of knowledge to make cities engines of growth. The use of a geolocation tool coupled to the data would allow better monitoring of indicators Our project's objective is to develop an interactive map server (WebMapping) which map layer is formed from the resources of the Google Maps servers and match information from the field to produce maps of urban equipment and infrastructure of a city data to the client's request To achieve this goal, we will participate in a study of a GPS location of strategic sites in our core sector (health facilities), on the other hand, using information from the field, we will build a postgresql database that will link the information from the field to map from Google Maps via KML scripts and PHP appropriate. We will limit ourselves in our work to the city of Douala Cameroon with the sectors of health facilities with the possibility of extension to other areas and other cities. Keywords: Geographic Information System (GIS), Thematic Mapping, Web Mapping, data mining, Google API.

Service Descriptions and Linked Data for Integrating WSNs into Enterprise IT

This paper presents our ongoing work on enterprise IT integration of sensor networks based on the idea of service descriptions and applying linked data principles to them. We argue that using linked service descriptions facilitates a better integration of sensor nodes into enterprise IT systems and allows SOA principles to be used within the enterprise IT and within the sensor network itself.

Bayesian Hidden Markov Modeling of Array CGH Data

Genomic alterations have been linked to the development and progression of cancer. The technique of Comparative Genomic Hybridization (CGH) yields data consisting of fluorescence intensity ratios of test and reference DNA samples. The intensity ratios provide information about the number of copies in DNA. Practical issues such as the contamination of tumor cells in tissue specimens and normalization errors necessitate the use of statistics for learning about the genomic alterations from array-CGH data. As increasing amounts of array CGH data become available, there is a growing need for automated algorithms for characterizing genomic profiles. Specifically, there is a need for algorithms that can identify gains and losses in the number of copies based on statistical considerations, rather than merely detect trends in the data. We adopt a Bayesian approach, relying on the hidden Markov model to account for the inherent dependence in the intensity ratios. Posterior inferences are made about gains and losses in copy number. Localized amplifications (associated with oncogene mutations) and deletions (associated with mutations of tumor suppressors) are identified using posterior probabilities. Global trends such as extended regions of altered copy number are detected. Since the posterior distribution is analytically intractable, we implement a Metropolis-within-Gibbs algorithm for efficient simulation-based inference. Publicly available data on pancreatic adenocarcinoma, glioblastoma multiforme and breast cancer are analyzed, and comparisons are made with some widely-used algorithms to illustrate the reliability and success of the technique.

A Pseudolikelihood Approach for Simultaneous Analysis of Array Comparative Genomic Hybridizations (aCGH)

DNA sequence copy number has been shown to be associated with cancer development and progression. Array-based Comparative Genomic Hybridization (aCGH) is a recent development that seeks to identify the copy number ratio at large numbers of markers across the genome. Due to experimental and biological variations across chromosomes and across hybridizations, current methods are limited to analyses of single chromosomes. We propose a more powerful approach that borrows strength across chromosomes and across hybridizations. We assume a Gaussian mixture model, with a hidden Markov dependence structure, and with random effects to allow for intertumoral variation, as well as intratumoral clonal variation. For ease of computation, we base estimation on a pseudolikelihood function. The method produces quantitative assessments of the likelihood of genetic alterations at each clone, along with a graphical display for simple visual interpretation. We assess the characteristics of the method through simulation studies and through analysis of a brain tumor aCGH data set. We show that the pseudolikelihood approach is superior to existing methods both in detecting small regions of copy number alteration and in accurately classifying regions of change when intratumoral clonal variation is present.

Semiparametric Normal Transformation Models for Spatially Correlated Survival Data

There is an emerging interest in modeling spatially correlated survival data in biomedical and epidemiological studies. In this paper, we propose a new class of semiparametric normal transformation models for right censored spatially correlated survival data. This class of models assumes that survival outcomes marginally follow a Cox proportional hazard model with unspecified baseline hazard, and their joint distribution is obtained by transforming survival outcomes to normal random variables, whose joint distribution is assumed to be multivariate normal with a spatial correlation structure. A key feature of the class of semiparametric normal transformation models is that it provides a rich class of spatial survival models where regression coefficients have population average interpretation and the spatial dependence of survival times is conveniently modeled using the transformed variables by flexible normal random fields. We study the relationship of the spatial correlation structure of the transformed normal variables and the dependence measures of the original survival times. Direct nonparametric maximum likelihood estimation in such models is practically prohibited due to the high dimensional intractable integration of the likelihood function and the infinite dimensional nuisance baseline hazard parameter. We hence develop a class of spatial semiparametric estimating equations, which conveniently estimate the population-level regression coefficients and the dependence parameters simultaneously. We study the asymptotic properties of the proposed estimators, and show that they are consistent and asymptotically normal. The proposed method is illustrated with an analysis of data from the East Boston Ashma Study and its performance is evaluated using simulations.

Cervical soft tissue imaging using a mobile CBCT scanner with a flat panel detector in comparison with corresponding CT and MRI data sets

OBJECTIVE: The aim of this study was to evaluate soft tissue image quality of a mobile cone-beam computed tomography (CBCT) scanner with an integrated flat-panel detector. STUDY DESIGN: Eight fresh human cadavers were used in this study. For evaluation of soft tissue visualization, CBCT data sets and corresponding computed tomography (CT) and magnetic resonance imaging (MRI) data sets were acquired. Evaluation was performed with the help of 10 defined cervical anatomical structures. RESULTS: The statistical analysis of the scoring results of 3 examiners revealed the CBCT images to be of inferior quality regarding the visualization of most of the predefined structures. Visualization without a significant difference was found regarding the demarcation of the vertebral bodies and the pyramidal cartilages, the arteriosclerosis of the carotids (compared with CT), and the laryngeal skeleton (compared with MRI). Regarding arteriosclerosis of the carotids compared with MRI, CBCT proved to be superior. CONCLUSIONS: The integration of a flat-panel detector improves soft tissue visualization using a mobile CBCT scanner.

Potential of chemically modified hydrophilic surface characteristics to support tissue integration of titanium dental implants

In the past, several modifications of specific surface properties such as topography, structure, chemistry, surface charge, and wettability have been investigated to predictably improve the osseointegration of titanium implants. The aim of the present review was to evaluate, based on the currently available evidence, the impact of hydrophilic surface modifications of titanium for dental implants. A surface treatment was performed to produce hydroxylated/hydrated titanium surfaces with identical microstructure to either acid-etched, or sand-blasted, large grit and acid-etched substrates, but with hydrophilic character. Preliminary in vitro studies have indicated that the specific properties noted for hydrophilic titanium surfaces have a significant influence on cell differentiation and growth factor production. Animal experiments have pointed out that hydrophilic surfaces improve early stages of soft tissue and hard tissue integration of either nonsubmerged or submerged titanium implants. This data was also corroborated by the results from preliminary clinical studies. In conclusion, the present review has pointed to a potential of hydrophilic surface modifications to support tissue integration of titanium dental implants.

The exchange of radiotherapy data as part of an electronic patient-referral system

PURPOSE: To describe the implementation and use of an electronic patient-referral system as an aid to the efficient referral of patients to a remote and specialized treatment center. METHODS AND MATERIALS: A system for the exchange of radiotherapy data between different commercial planning systems and a specially developed planning system for proton therapy has been developed through the use of the PAPYRUS diagnostic image standard as an intermediate format. To ensure the cooperation of the different TPS manufacturers, the number of data sets defined for transfer has been restricted to the three core data sets of CT, VOIs, and three-dimensional dose distributions. As a complement to the exchange of data, network-wide application-sharing (video-conferencing) technologies have been adopted to provide methods for the interactive discussion and assessment of treatments plans with one or more partner clinics. RESULTS: Through the use of evaluation plans based on the exchanged data, referring clinics can accurately assess the advantages offered by proton therapy on a patient-by-patient basis, while the practicality or otherwise of the proposed treatments can simultaneously be assessed by the proton therapy center. Such a system, along with the interactive capabilities provided by video-conferencing methods, has been found to be an efficient solution to the problem of patient assessment and selection at a specialized treatment center, and is a necessary first step toward the full electronic integration of such centers with their remotely situated referral centers.

Information integration and management through the design and construction phases of a project life cycle

Information management is a key aspect of successful construction projects. Having inaccurate measurements and conflicting data can lead to costly mistakes, and vague quantities can ruin estimates and schedules. Building information modeling (BIM) augments a 3D model with a wide variety of information, which reduces many sources of error and can detect conflicts before they occur. Because new technology is often more complex, it can be difficult to effectively integrate it with existing business practices. In this paper, we will answer two questions: How can BIM add value to construction projects? and What lessons can be learned from other companies that use BIM or other similar technology? Previous research focused on the technology as if it were simply a tool, observing problems that occurred while integrating new technology into existing practices. Our research instead looks at the flow of information through a company and its network, seeing all the actors as part of an ecosystem. Building upon this idea, we proposed the metaphor of an information supply chain to illustrate how BIM can add value to a construction project. This paper then concludes with two case studies. The first case study illustrates a failure in the flow of information that could have prevented by using BIM. The second case study profiles a leading design firm that has used BIM products for many years and shows the real benefits of using this program.

VISUAL-INERTIAL INTEGRATION FOR HUMAN MOTION TRACKING AND NAVIGATION IN FREE-LIVING ENVIRONMENTS

The aging population has become a burning issue for all modern societies around the world recently. There are two important issues existing now to be solved. One is how to continuously monitor the movements of those people having suffered a stroke in natural living environment for providing more valuable feedback to guide clinical interventions. The other one is how to guide those old people effectively when they are at home or inside other buildings and to make their life easier and convenient. Therefore, human motion tracking and navigation have been active research fields with the increasing number of elderly people. However, motion capture has been extremely challenging to go beyond laboratory environments and obtain accurate measurements of human physical activity especially in free-living environments, and navigation in free-living environments also poses some problems such as the denied GPS signal and the moving objects commonly presented in free-living environments. This thesis seeks to develop new technologies to enable accurate motion tracking and positioning in free-living environments. This thesis comprises three specific goals using our developed IMU board and the camera from the imaging source company: (1) to develop a robust and real-time orientation algorithm using only the measurements from IMU; (2) to develop a robust distance estimation in static free-living environments to estimate people’s position and navigate people in static free-living environments and simultaneously the scale ambiguity problem, usually appearing in the monocular camera tracking, is solved by integrating the data from the visual and inertial sensors; (3) in case of moving objects viewed by the camera existing in free-living environments, to firstly design a robust scene segmentation algorithm and then respectively estimate the motion of the vIMU system and moving objects. To achieve real-time orientation tracking, an Adaptive-Gain Orientation Filter (AGOF) is proposed in this thesis based on the basic theory of deterministic approach and frequency-based approach using only measurements from the newly developed MARG (Magnet, Angular Rate, and Gravity) sensors. To further obtain robust positioning, an adaptive frame-rate vision-aided IMU system is proposed to develop and implement fast vIMU ego-motion estimation algorithms, where the orientation is estimated in real time from MARG sensors in the first step and then used to estimate the position based on the data from visual and inertial sensors. In case of the moving objects viewed by the camera existing in free-living environments, a robust scene segmentation algorithm is firstly proposed to obtain position estimation and simultaneously the 3D motion of moving objects. Finally, corresponding simulations and experiments have been carried out.

Integration of QUAL2Kw and ArcGIS for Silver Bow Creek, Montana

The purpose of this project is to take preliminary steps towards the development of a QUAL2Kw model for Silver Bow Creek, MT. These preliminary steps include initial research and familiarization with QUAL2Kw, use of ArcGIS to fill in geospatial data gaps, and integration of QUAL2Kw and ArcGIS. The integration involves improvement of the QUAL2Kw model output through adding functionality to the model itself, and development of a QUAL2Kw specific tool in ArcGIS. These improvements are designed to help expedite and simplify the viewing of QUAL2Kw output data spatially in ArcGIS as opposed to graphically within QUAL2Kw. These improvements will allow users to quickly and easily view the many output parameters of each model run geographically within ArcGIS. This will make locating potential problem areas or “hot spots” much quicker and easier than interpreting the QUAL2Kw output data from a graph alone. The added functionality of QUAL2KW was achieved through the development of an excel Macro, and the tool in ArcGIS was developed using python scripting and the model builder feature in ArcGIS.