MAPI: towards the integrated exploitation of bioinformatics Web Services.

BACKGROUND. Bioinformatics is commonly featured as a well assorted list of available web resources. Although diversity of services is positive in general, the proliferation of tools, their dispersion and heterogeneity complicate the integrated exploitation of such data processing capacity. RESULTS. To facilitate the construction of software clients and make integrated use of this variety of tools, we present a modular programmatic application interface (MAPI) that provides the necessary functionality for uniform representation of Web Services metadata descriptors including their management and invocation protocols of the services which they represent. This document describes the main functionality of the framework and how it can be used to facilitate the deployment of new software under a unified structure of bioinformatics Web Services. A notable feature of MAPI is the modular organization of the functionality into different modules associated with specific tasks. This means that only the modules needed for the client have to be installed, and that the module functionality can be extended without the need for re-writing the software client. CONCLUSIONS. The potential utility and versatility of the software library has been demonstrated by the implementation of several currently available clients that cover different aspects of integrated data processing, ranging from service discovery to service invocation with advanced features such as workflows composition and asynchronous services calls to multiple types of Web Services including those registered in repositories (e.g. GRID-based, SOAP, BioMOBY, R-bioconductor, and others).

Expectations, experiences and attitudes of patients and primary care health professionals regarding online psychotherapeutic interventions for depression: protocol for a qualitative study.

BACKGROUND In the year 2020, depression will cause the second highest amount of disability worldwide. One quarter of the population will suffer from depression symptoms at some point in their lives. Mental health services in Western countries are overburdened. Therefore, cost-effective interventions that do not involve mental health services, such as online psychotherapy programs, have been proposed. These programs demonstrate satisfactory outcomes, but the completion rate for patients is low. Health professionals' attitudes towards this type of psychotherapy are more negative than the attitudes of depressed patients themselves. The aim of this study is to describe the profile of depressed patients who would benefit most from online psychotherapy and to identify expectations, experiences, and attitudes about online psychotherapy among both patients and health professionals that can facilitate or hinder its effects. METHODS A parallel qualitative design will be used in a randomised controlled trial on the efficiency of online psychotherapeutic treatment for depression. Through interviews and focus groups, the experiences of treated patients, their reasons for abandoning the program, the expectations of untreated patients, and the attitudes of health professionals will be examined. Questions will be asked about training in new technologies, opinions of online psychotherapy, adjustment to therapy within the daily routine, the virtual and anonymous relationship with the therapist, the process of online communication, information necessary to make progress in therapy, process of working with the program, motivations and attitudes about treatment, expected consequences, normalisation of this type of therapy in primary care, changes in the physician-patient relationship, and resources and risks. A thematic content analysis from the grounded theory for interviews and an analysis of the discursive positions of participants based on the sociological model for focus groups will be performed. DISCUSSION Knowledge of the expectations, experiences, and attitudes of both patients and medical personnel regarding online interventions for depression can facilitate the implementation of this new psychotherapeutic tool. This qualitative investigation will provide thorough knowledge of the perceptions, beliefs, and values of patients and clinicians, which will be very useful for understanding how to implement this intervention method for depression.

"I don't know how you are" or indirect questioning in oncology interviews: an ongoing exploratory study

Background: The exploratory study is part of an evaluation of the pre-graduate teaching of communication skills (Lausanne Medical School). It is based on the data of a project highlighting the impact of individualized vs. group training for medicine students in breaking bad news to simulated patients who are diagnosed with cancer. The analysis of the video-taped interviews of the students (N=63) with the RIAS has shown a current usage of utterances such as I don't know if -you have any plans for the future / you have already heard about chemotherapy / ... or I don't know how -you are feeling today after this surgery / you like that all this stuff takes place / ...Aim: The present study questions the specificity of these assertive utterances used as questions (indirect), the specificity of their content, and their intentionality - specific vs. exploratory.Methods: The mentioned utterances are qualitatively analyzed (content analysis, intentionality analysis, etc).Results: 26 students (41%) used 1 to 6 times I don't know utterances during the interviews that contain 53 of such utterances in total. In contrast, they are atypical in an oncologist sample who conducted similar interviews (N=31; 4 oncologist used them 1 to 2 times). In more than half of the cases (29/53), simulated patients interpret I don't know questions as giving them a space to speak (open responses). Conclusions: The atypicality of the I don't know utterances in the oncologist sample may have linguistic explanations in terms of generational marker, but the specificity of the content suggests psychological explanations in terms of defense mechanism as well (marker of "toning down" or insecurity as regards the discussed topic).Keywords: Breaking bad news, communication skills, oncology, pre-graduate medical education, indirect questioning

Diagnosing Patients Combining Principal Components Analysis and Case Based Reasoning

This paper addresses the application of a PCA analysis on categorical data prior to diagnose a patients data set using a Case-Based Reasoning (CBR) system. The particularity is that the standard PCA techniques are designed to deal with numerical attributes, but our medical data set contains many categorical data and alternative methods as RS-PCA are required. Thus, we propose to hybridize RS-PCA (Regular Simplex PCA) and a simple CBR. Results show how the hybrid system produces similar results when diagnosing a medical data set, that the ones obtained when using the original attributes. These results are quite promising since they allow to diagnose with less computation effort and memory storage

International nursing : cultivating a culture of empowerment

International nursing has been a growing phenomenon throughout the globe. International nurses have been found to be an asset to healthcare organizations and an important part of the health care team. However, growing concern for the plight of international nurses facing obstacles such as professional stagnation and exploitation has spurred the development of strategies to mitigate and ameliorate the experiences of nurses working abroad. In this respect, the purpose of this study was to explore the management-influenced factors and the nurse team-influenced factors that promote the empowerment of the international nurse in the health care setting. The methodology used in this study was a systemic review. After a rigorous search for relevant empirical studies using OVID database, eight empirical research studies were selected using systematic review methodology to collect, analyze and synthesize data. The selected eight empirical studies were then subjected to a content analysis. The results suggested that the empowerment of an international nurse is inseparable from the empowerment of the health care organization. Based on the findings in this study, strategies to promote international nurses were found to mirror strategies evidenced to empower the nursing organization. Some of the management-influenced factors which were found to facilitate empowerment included a diversity rich work culture, transformational leadership at the management level, and a responsibility to foster the values of the organization. The team-influenced factors which were found to contribute to the empowerment of the international nurse included a united mutually-interdependent nurse team, shared accountability among the members of the nurse team, and the building of trust in work relationships. To conlude, this study indicates that efforts to empower international nurses without considering the work culture and the organization as a whole are futile because empowerment cannot take place in an environment that lacks antecedent conditions. Strategies to empower the international nurse should not focus on the deficits and special needs of the international nurse, but should focus on the similarities and commonalities of the nursing body. Empowerment of the international nurse mean open honest communication, supportive work environment, and a firm policy to quell disruptive elements that threaten the organization's values, mission, and philosophy of care.

Violence against adolescents: an analysis based on the categories gender and generation

Exploratory and descriptive study based on quantitative and qualitative methods that analyze the phenomenon of violence against adolescents based on gender and generational categories. The data source was reports of violence from the Curitiba Protection Network from 2010 to 2012 and semi-structured interviews with 16 sheltered adolescents. Quantitative data were analyzed using SPSS software version 20.0 and the qualitative data were subjected to content analysis. The adolescents were victims of violence in the household and outside of the family environment, as victims or viewers of violence. The violence was experienced at home, mostly toward girls, with marked overtones of gender violence. More than indicating the magnitude of the issue, this study can give information to help qualify the assistance given to victimized people and address how to face this issue.

Needs of psychopedagogical training for the care of children with chronic disease: perceptions of hospital nursing

OBJECTIVE To identify the psychopedagogical training needs of the pediatric nurses in the largest public hospital of the Balearic Islands, Spain. METHOD This study was developed with a quantitative and qualitative design, where 78 nurses (97.5% of the service) answered a questionnaire, and 15 participated in interviews that were analyzed via content analysis. RESULTS The quantitative results show gaps in the knowledge and psychopedagogical skills of the staff. These aspects could facilitate the development of tasks tailored to the personality and the psychoevolutional time of children with chronic diseases, as well as to the emotional state of families. The qualitative data was organized into four categories: family support; hospital and education; psychopedagogical training and difficulties in practice. The little communication between nurses and teachers is evident. CONCLUSION The data reinforces the need to implement training strategies and interdisciplinary work among health professionals, educators and families.

Mapping of Environmental Data Using Kernel-Based Methods

Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

Analysis of digestive tract content of the larvae of Polybia scutellaris (White) (Hymenoptera, Vespidae)

Polybia scutellaris (White, 1841) is a social wasp of biological interest for its role as pollinator and maybe as biological control agent of sanitary and agricultural pests. This study examines the digestive tract contents of the larvae of P. scutellaris from four nests in Magdalena (Buenos Aires province, Argentina). Contents included both animal (arthropod parts) and plant (pollen, leaf and fruit epidermis) parts. The pollen content analysis showed that the wasps visited 19 different taxa of plants during the last active period of the colony before the nests had been collected. The range of sources used by P. scutellaris allows us characterizing the species as a generalist flower visitor. Wasps visited both native and exotic plants located nearby the nest. Most of the epidermal plant remains found in the larval digestive tract belonged to Malvaceae, a family not exploited by the studied colonies as pollen source.

A note on the dual scaling of dominance data and its relationship to correspondence analysis

Dual scaling of a subjects-by-objects table of dominance data (preferences,paired comparisons and successive categories data) has been contrasted with correspondence analysis, as if the two techniques were somehow different. In this note we show that dual scaling of dominance data is equivalent to the correspondence analysis of a table which is doubled with respect to subjects. We also show that the results of both methods can be recovered from a principal components analysis of the undoubled dominance table which is centred with respect to subject means.

Reconeixement de gestos de la mà amb el sensor Kinect

El reconeixement dels gestos de la mà (HGR, Hand Gesture Recognition) és actualment un camp important de recerca degut a la varietat de situacions en les quals és necessari comunicar-se mitjançant signes, com pot ser la comunicació entre persones que utilitzen la llengua de signes i les que no. En aquest projecte es presenta un mètode de reconeixement de gestos de la mà a temps real utilitzant el sensor Kinect per Microsoft Xbox, implementat en un entorn Linux (Ubuntu) amb llenguatge de programació Python i utilitzant la llibreria de visió artifical OpenCV per a processar les dades sobre un ordinador portàtil convencional. Gràcies a la capacitat del sensor Kinect de capturar dades de profunditat d’una escena es poden determinar les posicions i trajectòries dels objectes en 3 dimensions, el que implica poder realitzar una anàlisi complerta a temps real d’una imatge o d’una seqüencia d’imatges. El procediment de reconeixement que es planteja es basa en la segmentació de la imatge per poder treballar únicament amb la mà, en la detecció dels contorns, per després obtenir l’envolupant convexa i els defectes convexos, que finalment han de servir per determinar el nombre de dits i concloure en la interpretació del gest; el resultat final és la transcripció del seu significat en una finestra que serveix d’interfície amb l’interlocutor. L’aplicació permet reconèixer els números del 0 al 5, ja que s’analitza únicament una mà, alguns gestos populars i algunes de les lletres de l’alfabet dactilològic de la llengua de signes catalana. El projecte és doncs, la porta d’entrada al camp del reconeixement de gestos i la base d’un futur sistema de reconeixement de la llengua de signes capaç de transcriure tant els signes dinàmics com l’alfabet dactilològic.

Brief DISCERN, six questions for the evaluation of evidence-based content of health-related websites.

OBJECTIVE: To extract and to validate a brief version of the DISCERN which could identify mental health-related websites with good content quality. METHOD: The present study is based on the analysis of data issued from six previous studies which used DISCERN and a standardized tool for the evaluation of content quality (evidence-based health information) of 388 mental health-related websites. After extracting the Brief DISCERN, several psychometric properties (content validity through a Factor analysis, internal consistency by the Cronbach's alpha index, predictive validity through the diagnostic tests, concurrent validity by the strength of association between the Brief DISCERN and the original DISCERN scores) were investigated to ascertain its general applicability. RESULTS: A Brief DISCERN composed of two factors and six items was extracted from the original 16 items version of the DISCERN. Cronbach's alpha coefficients were more than acceptable for the complete questionnaire (alpha=0.74) and for the two distinct domains: treatments information (alpha=0.87) and reliability (alpha=0.83). Sensibility and specificity of the Brief DISCERN cut-off score > or =16 in the detection of good content quality websites were 0.357 and 0.945, respectively. Its predictive positive and negative values were 0.98 and 0.83, respectively. A statistically significant linear correlation was found between the total scores of the Brief DISCERN and those of the original DISCERN (r=0.84 and p<0.0005). CONCLUSION: The Brief DISCERN seems to be a reliable and valid instrument able to discriminate between websites with good and poor content quality. PRACTICE IMPLICATIONS: The Brief DISCERN is a simple tool which could facilitate the identification of good information on the web by patients and general consumers.

Integrative molecular bioinformatics study of human adrenocortical tumors : microRNA, tissue-specific target prediction, and pathway analysis.

MicroRNAs (miRs) are involved in the pathogenesis of several neoplasms; however, there are no data on their expression patterns and possible roles in adrenocortical tumors. Our objective was to study adrenocortical tumors by an integrative bioinformatics analysis involving miR and transcriptomics profiling, pathway analysis, and a novel, tissue-specific miR target prediction approach. Thirty-six tissue samples including normal adrenocortical tissues, benign adenomas, and adrenocortical carcinomas (ACC) were studied by simultaneous miR and mRNA profiling. A novel data-processing software was used to identify all predicted miR-mRNA interactions retrieved from PicTar, TargetScan, and miRBase. Tissue-specific target prediction was achieved by filtering out mRNAs with undetectable expression and searching for mRNA targets with inverse expression alterations as their regulatory miRs. Target sets and significant microarray data were subjected to Ingenuity Pathway Analysis. Six miRs with significantly different expression were found. miR-184 and miR-503 showed significantly higher, whereas miR-511 and miR-214 showed significantly lower expression in ACCs than in other groups. Expression of miR-210 was significantly lower in cortisol-secreting adenomas than in ACCs. By calculating the difference between dCT(miR-511) and dCT(miR-503) (delta cycle threshold), ACCs could be distinguished from benign adenomas with high sensitivity and specificity. Pathway analysis revealed the possible involvement of G2/M checkpoint damage in ACC pathogenesis. To our knowledge, this is the first report describing miR expression patterns and pathway analysis in sporadic adrenocortical tumors. miR biomarkers may be helpful for the diagnosis of adrenocortical malignancy. This tissue-specific target prediction approach may be used in other tumors too.

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

Evaluation of Steel Bridges, Volumes I & II, TR-493, 2007

This report is divided into two volumes. This volume (Volume I) summarizes a structural health monitoring (SHM) system that was developed for the Iowa DOT to remotely and continuously monitor fatigue critical bridges (FCB) to aid in the detection of crack formation. The developed FCB SHM system enables bridge owners to remotely monitor FCB for gradual or sudden damage formation. The SHM system utilizes fiber bragg grating (FBG) fiber optic sensors (FOSs) to measure strains at critical locations. The strain-based SHM system is trained with measured performance data to identify typical bridge response when subjected to ambient traffic loads, and that knowledge is used to evaluate newly collected data. At specified intervals, the SHM system autonomously generates evaluation reports that summarize the current behavior of the bridge. The evaluation reports are collected and distributed to the bridge owner for interpretation and decision making. Volume II summarizes the development and demonstration of an autonomous, continuous SHM system that can be used to monitor typical girder bridges. The developed SHM system can be grouped into two main categories: an office component and a field component. The office component is a structural analysis software program that can be used to generate thresholds which are used for identifying isolated events. The field component includes hardware and field monitoring software which performs data processing and evaluation. The hardware system consists of sensors, data acquisition equipment, and a communication system backbone. The field monitoring software has been developed such that, once started, it will operate autonomously with minimal user interaction. In general, the SHM system features two key uses. First, the system can be integrated into an active bridge management system that tracks usage and structural changes. Second, the system helps owners to identify damage and deterioration.