From big smartphone data to worldwide research: The Mobile Data Challenge

This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC), an initiative to collect unique longitudinal smartphone dataset for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC, describe the specific datasets used in each of them, discuss the key design and implementation aspects introduced in order to generate privacy-preserving and scientifically relevant mobile data resources for wider use by the research community, and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.

Camp For All Connection: a community health information outreach project

Purpose: The purpose of the Camp For All Connection project is to facilitate access to electronic health information resources at the Camp For All facility. Setting/Participants/Resources: Camp For All is a barrier-free camp working in partnership with organizations to enrich the lives of children and adults with chronic illnesses and disabilities and their families by providing camping and retreat experiences. The camp facility is located on 206 acres in Burton, Texas. The project partners are Texas Woman's University, Houston Academy of Medicine-Texas Medical Center Library, and Camp For All. Brief Description: The Camp For All Connection project placed Internet-connected workstations at the camp's health center in the main lodge and provided training in the use of electronic health information resources. A train-the-trainer approach was used to provide training to Camp For All staff. Results/Outcome: Project workstations are being used by health care providers and camp staff for communication purposes and to make better informed health care decisions for Camp For All campers. Evaluation Method: A post-training evaluation was administered at the end of the train-the-trainer session. In addition, a series of site visits and interviews was conducted with camp staff members involved in the project. The site visits and interviews allowed for ongoing dialog between project staff and project participants.

Multi-Environment Model Estimation for Motility Analysis of Caernorhabditis elegans

The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them quantitatively. Over the past years, C. elegans' motility has been studied across a wide range of environments, including crawling on substrates, swimming in fluids, and locomoting through microfluidic substrates. However, each environment often requires customized image processing tools relying on heuristic parameter tuning. In the present study, we propose a novel Multi-Environment Model Estimation (MEME) framework for automated image segmentation that is versatile across various environments. The MEME platform is constructed around the concept of Mixture of Gaussian (MOG) models, where statistical models for both the background environment and the nematode appearance are explicitly learned and used to accurately segment a target nematode. Our method is designed to simplify the burden often imposed on users; here, only a single image which includes a nematode in its environment must be provided for model learning. In addition, our platform enables the extraction of nematode ‘skeletons’ for straightforward motility quantification. We test our algorithm on various locomotive environments and compare performances with an intensity-based thresholding method. Overall, MEME outperforms the threshold-based approach for the overwhelming majority of cases examined. Ultimately, MEME provides researchers with an attractive platform for C. elegans' segmentation and ‘skeletonizing’ across a wide range of motility assays.

Allele-specific polymerase chain reaction diagnostic test for the functional MDR1 polymorphism in dogs

The major multidrug transporter P-glycoprotein (Pgp) contributes to the barrier function of several tissues and organs, including the brain. In a subpopulation of Collies and seven further dog breeds, a 4 base pair deletion has been described in the Pgp-encoding MDR1 gene. This deletion results in the absence of a functional form of Pgp and loss of its protective function. Severe intoxication with the Pgp substrate ivermectin has been attributed to the genetically determined lack of Pgp. An allele-specific polymerase chain reaction (PCR)-based screening method has been developed to detect the mutant allele and to determine if a dog is homozygous or heterozygous for the mutation. Based on this validation, the allele-specific PCR proved to be a robust, reproducible and specific tool, allowing rapid determination of the MDR1 genotype of dogs of at risk breeds using blood samples or buccal swabs.

A 1.8-kb insertion in the 3'-UTR of RXFP2 is associated with polledness in sheep

Sheep breeds show a broad spectrum of different horn phenotypes. In most modern production breeds, sheep are polled (absence of horns), whereas horns occur mainly in indigenous breeds. Previous studies mapped the responsible locus to the region of the RXFP2 gene on ovine chromosome 10. A 4-kb region of the 3'-end of RXFP2 was amplified in horned and polled animals from seven Swiss sheep breeds. Sequence analysis identified a 1833-bp genomic insertion located in the 3'-UTR region of RXFP2 present in polled animals only. An efficient PCR-based genotyping method to determine the polled genotype of individual sheep is presented. Comparative sequence analyses revealed evidence that the polled-associated insertion adds a potential antisense RNA sequence of EEF1A1 to the 3'-end of RXFP2 transcripts.

Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features.

Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. MRI sets of 109 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA). Spearman's correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Auto-segmented sub-volumes showed moderate to high agreement with manually delineated volumes (range (r): 0.4 - 0.86). Also, the auto and manual volumes showed similar correlation with VASARI features (auto r = 0.35, 0.43 and 0.36; manual r = 0.17, 0.67, 0.41, for contrast-enhancing, necrosis and edema, respectively). The auto-segmented contrast-enhancing volume and post-contrast abnormal volume showed the highest AUC (0.66, CI: 0.55-0.77 and 0.65, CI: 0.54-0.76), comparable to manually defined volumes (0.64, CI: 0.53-0.75 and 0.63, CI: 0.52-0.74, respectively). BraTumIA and manual tumor sub-compartments showed comparable performance in terms of prognosis and correlation with VASARI features. This method can enable more reproducible definition and quantification of imaging based biomarkers and has potential in high-throughput medical imaging research.

Prevalence of HIV risk-related behaviors among undocumented Central American immigrant women in Houston, Texas, 2010

The primary aim of this dissertation research is to provide epidemiological data on HIV risk-related behaviors among undocumented Central American immigrant women living in Houston, Texas. Between February and May 2010, we used respondent driven sampling (RDS) to recruit 230 Guatemalan, Honduran, and El Salvadoran women, ages 18 to 50 years, living in Houston without a valid United States visa or residency papers. RDS is a probability-based sampling method that utilizes social networks to access members of hidden populations that lack a sampling frame. Participants completed an interview regarding their demographics, access to and utilization of healthcare services, HIV testing, and sexual behaviors. Data from this study were used 1) to describe the prevalence of sexual HIV risk-related behaviors among undocumented Central American immigrant women, comparing those who recently immigrated to the U.S. (within the past five years) to those with more established residency (of over five years); 2) to describe the prevalence of lifetime HIV testing and evaluate its associated factors in this target population; and 3) to describe the effectiveness of RDS to access members of this target population. ^ As described in Paper 1, there was a generally low prevalence of individual HIV risk-related behaviors (i.e., multiple, concurrent, convenience, and casual sexual partnerships) among the undocumented Central American immigrant women in this study. However, there was evidence of HIV risk due to unprotected sex with male partners who have concurrent sexual partnerships. We identified recent immigrants as the subpopulation at greatest risk, as they were significantly more likely than established immigrants to have multiple and/or concurrent sexual partners. As described in Paper 2, the lifetime prevalence of HIV testing was almost 70%. After adjusting for age, number of years living in the U.S., income security, and resource barriers, lifetime HIV testing was significantly associated with being from Honduras, having more than a sixth grade education, having a regular healthcare provider, and having knowledge of available healthcare resources. Finally, as described in Paper 3, RDS was an effective method for obtaining a diverse sample of Central American immigrant women in Houston. ^ This project is the first to use RDS to conduct an HIV behavioral survey among undocumented Central American immigrant women. Our results will inform the design of future research studies and the implementation of HIV prevention activities among undocumented Central American immigrants in the U.S.^

DEVELOPMENT OF A BEAM-SPECIFIC PLANNING TARGET VOLUME AND A ROBUST PLAN ANALYSIS TOOL FOR PROTON THERAPY

Proton therapy is growing increasingly popular due to its superior dose characteristics compared to conventional photon therapy. Protons travel a finite range in the patient body and stop, thereby delivering no dose beyond their range. However, because the range of a proton beam is heavily dependent on the tissue density along its beam path, uncertainties in patient setup position and inherent range calculation can degrade thedose distribution significantly. Despite these challenges that are unique to proton therapy, current management of the uncertainties during treatment planning of proton therapy has been similar to that of conventional photon therapy. The goal of this dissertation research was to develop a treatment planning method and a planevaluation method that address proton-specific issues regarding setup and range uncertainties. Treatment plan designing method adapted to proton therapy: Currently, for proton therapy using a scanning beam delivery system, setup uncertainties are largely accounted for by geometrically expanding a clinical target volume (CTV) to a planning target volume (PTV). However, a PTV alone cannot adequately account for range uncertainties coupled to misaligned patient anatomy in the beam path since it does not account for the change in tissue density. In order to remedy this problem, we proposed a beam-specific PTV (bsPTV) that accounts for the change in tissue density along the beam path due to the uncertainties. Our proposed method was successfully implemented, and its superiority over the conventional PTV was shown through a controlled experiment.. Furthermore, we have shown that the bsPTV concept can be incorporated into beam angle optimization for better target coverage and normal tissue sparing for a selected lung cancer patient. Treatment plan evaluation method adapted to proton therapy: The dose-volume histogram of the clinical target volume (CTV) or any other volumes of interest at the time of planning does not represent the most probable dosimetric outcome of a given plan as it does not include the uncertainties mentioned earlier. Currently, the PTV is used as a surrogate of the CTV’s worst case scenario for target dose estimation. However, because proton dose distributions are subject to change under these uncertainties, the validity of the PTV analysis method is questionable. In order to remedy this problem, we proposed the use of statistical parameters to quantify uncertainties on both the dose-volume histogram and dose distribution directly. The robust plan analysis tool was successfully implemented to compute both the expectation value and its standard deviation of dosimetric parameters of a treatment plan under the uncertainties. For 15 lung cancer patients, the proposed method was used to quantify the dosimetric difference between the nominal situation and its expected value under the uncertainties.

Método de evaluación a campo de la resistencia al moho azul en clones de ajo tipo colorado

Con el objeto de ajustar un método de evaluación a campo para facilitar la selección de clones de ajo (Allium sativum L.) con resistencia a Penicillium allii, se realizó un ensayo replicado en el cual se midió la respuesta de tres clones experimentales a la infección, en dos épocas de plantación. Los tratamientos incluyeron combinaciones de presencia o ausencia de: a) desinfección de la "semilla", b) heridas artificiales en los bulbillos, c) inoculación artificial. Los bulbillos con la hoja envolvente se desinfectaron con una solución diluida de hipoclorito de sodio. La inoculación se realizó mediante la inmersión en una solución de 106 esporas•ml-1. Las heridas se realizaron con una lanceta (blood lancet). Los bulbillos se incubaron en cámara húmeda durante 24 horas a 20 °C, antes de plantación. Las variables respuestas computadas fueron las siguientes: número de plantas muertas, y vivas con síntomas y sin síntomas, a los 152 días de plantación en la primera época y 118 días en la segunda; número de bulbos por calibres y rendimiento a cosecha. La información obtenida se analizó a través de correspondencia simple, diferencia de proporciones y análisis paramétricos. Se detectaron mayores diferencias entre los tratamientos en la tasa de sobrevivencia y en la proporción de calibres comerciales en la época tardía. No se observaron diferencias (p < 0,05) del rendimiento en la plantación temprana. La herida fue determinante en el ingreso del patógeno. Los tratamientos quedaron limitados a un testigo: desinfectado, no inoculado y sin herida, y a un tratamiento: desinfectado, con inoculación y herida. Con respecto a la época, resultó conveniente la evaluación en plantaciones tardías porque se expresan mejor las diferencias entre los tratamientos.

Table 1 Microorganisms, identified with DOGE analysis. 16S rDNA sequences, obtained from sequencing of DOGE bands, were assigned to the corresponding microorganisms

Microorganisms play an important role in the transformation of material within the earth's crust. The storage of CO2 could affect the composition of inorganic and organic components in the reservoir, consequently influencing microbial activities. To study the microbial induced processes together with geochemical, petrophysical and mineralogical changes, occurring during CO2 storage, long-term laboratory experiments under simulated reservoir P-T conditions were carried out. Clean inner core sections, obtained from the reservoir region at the CO2 storage site in Ketzin (Germany) from a depth of about 650 m, were incubated in high pressure vessels together with sterile synthetic formation brine under in situ P-T conditions of 5.5 MPa and 40°C. A 16S rDNA based fingerprinting method was used to identify the dominant species in DNA extracts of pristine sandstone samples. Members of the alpha- and beta-subdivisions of Proteobacteria and the Actinobacteria were identified. So far sequences belonging to facultative anaerobic, chemoheterotrophic bacteria (Burkholderia fungorum, Agrobacterium tumefaciens) gaining their energy from the oxidation of organic molecules and a genus also capable of chemolithoautotrophic growth (Hydrogenophaga) was identified. During CO2 incubation minor changes in the microbial community composition were observed. The majority of microbes were able to adapt to the changed conditions. During CO2 exposure increased concentrations of Ca**2+, K**+, Mg**2+ and SO4**2- were observed. Partially, concentration rises are (i) due to equilibration between rock pore water and synthetic brine, and (ii) between rock and brine, and are thus independent on CO2 exposure. However, observed concentrations of Ca**2+, K**+, Mg**2+ are even higher than in the original reservoir fluid and therefore indicate mineral dissolution due to CO2 exposure.

Using a causal smoothing to improve the performance of an on-line neural network glucose prediction algorithm

This work evaluates a spline-based smoothing method applied to the output of a glucose predictor. Methods:Our on-line prediction algorithm is based on a neural network model (NNM). We trained/validated the NNM with a prediction horizon of 30 minutes using 39/54 profiles of patients monitored with the Guardian® Real-Time continuous glucose monitoring system The NNM output is smoothed by fitting a causal cubic spline. The assessment parameters are the error (RMSE), mean delay (MD) and the high-frequency noise (HFCrms). The HFCrms is the root-mean-square values of the high-frequency components isolated with a zero-delay non-causal filter. HFCrms is 2.90±1.37 (mg/dl) for the original profiles.

A systematic mapping study on the open source software development process.

Abstract?Background: There is no globally accepted open source software development process to define how open source software is developed in practice. A process description is important for coordinating all the software development activities involving both people and technology. Aim: The research question that this study sets out to answer is: What activities do open source software process models contain? The activity groups on which it focuses are Concept Exploration, Software Requirements, Design, Maintenance and Evaluation. Method: We conduct a systematic mapping study (SMS). A SMS is a form of systematic literature review that aims to identify and classify available research papers concerning a particular issue. Results: We located a total of 29 primary studies, which we categorized by the open source software project that they examine and by activity types (Concept Exploration, Software Requirements, Design, Maintenance and Evaluation). The activities present in most of the open source software development processes were Execute Tests and Conduct Reviews, which belong to the Evaluation activities group. Maintenance is the only group that has primary studies addressing all the activities that it contains. Conclusions: The primary studies located by the SMS are the starting point for analyzing the open source software development process and proposing a process model for this community. The papers in our paper pool that describe a specific open source software project provide more regarding our research question than the papers that talk about open source software development without referring to a specific open source software project.

Improved heuristic drift elimination with magnetically-aided dominant directions (MiHDE) for pedestrian navigation in complex buildings

The main problem of pedestrian dead-reckoning (PDR) using only a body-attached inertial measurement unit is the accumulation of heading errors. The heading provided by magnetometers in indoor buildings is in general not reliable and therefore it is commonly not used. Recently, a new method was proposed called heuristic drift elimination (HDE) that minimises the heading error when navigating in buildings. It assumes that the majority of buildings have their corridors parallel to each other, or they intersect at right angles, and consequently most of the time the person walks along a straight path with a heading constrained to one of the four possible directions. In this article we study the performance of HDE-based methods in complex buildings, i.e. with pathways also oriented at 45°, long curved corridors, and wide areas where non-oriented motion is possible. We explain how the performance of the original HDE method can be deteriorated in complex buildings, and also, how severe errors can appear in the case of false matches with the building's dominant directions. Although magnetic compassing indoors has a chaotic behaviour, in this article we analyse large data-sets in order to study the potential use that magnetic compassing has to estimate the absolute yaw angle of a walking person. Apart from these analysis, this article also proposes an improved HDE method called Magnetically-aided Improved Heuristic Drift Elimination (MiHDE), that is implemented over a PDR framework that uses foot-mounted inertial navigation with an extended Kalman filter (EKF). The EKF is fed with the MiHDE-estimated orientation error, gyro bias corrections, as well as the confidence over that corrections. We experimentally evaluated the performance of the proposed MiHDE-based PDR method, comparing it with the original HDE implementation. Results show that both methods perform very well in ideal orthogonal narrow-corridor buildings, and MiHDE outperforms HDE for non-ideal trajectories (e.g. curved paths) and also makes it robust against potential false dominant direction matchings.

De los proyectos al programa en el ámbito público: nuevo modelo de evaluación del empleo en la Comunidad de Madrid.

Regarding different programmes belonging to the public sphere, it is essential to have proper tools able to quickly provide accurate data related to impacts generated by its projects. This aspect, along with the actual use of this data is essential for proper planning. This communication presents the system designed for project-based evaluation of the employment programs in the Community of Madrid. This system aims to provide fast and reliable information by relying on a combination of qualitative and quantitative methods from existing information and structures. Another contribution of the designed system is the implementation of the Empowerment Evaluation as a tool to encourage the incorporation of evaluation results to the planning processes in a systematic way.

Variable structure control with chattering elimination and guaranteed stability for a generalized T-S model

In this paper, a fuzzy based Variable Structure Control (VSC) with guaranteed stability is presented. The main objective is to obtain an improved performance of highly non-linear unstable systems. The main contribution of this work is that, firstly, new functions for chattering reduction and error convergence without sacrificing invariant properties are proposed, which is considered the main drawback of the VSC control. Secondly, the global stability of the controlled system is guaranteed.The well known weighting parameters approach, is used in this paper to optimize local and global approximation and modeling capability of T-S fuzzy model.A one link robot is chosen as a nonlinear unstable system to evaluate the robustness, effectiveness and remarkable performance of optimization approach and the high accuracy obtained in approximating nonlinear systems in comparison with the original T-S model. Simulation results indicate the potential and generality of the algorithm. The application of the proposed FLC-VSC shows that both alleviation of chattering and robust performance are achieved with the proposed FLC-VSC controller. The effectiveness of the proposed controller is proven in front of disturbances and noise effects.