Information Analysis and Databases

Means to automate the fact replace the man in their job functions for a man and machines automatic mechanism, ie documentary specialists in computer and computers are the cornerstone of any modern system of documentation and information. From this point of view immediately raises the problem of deciding what resources should be applied to solve the specific problem in each specific case. We will not let alone to propose quick fixes or recipes in order to decide what to do in any case. The solution depends on repeat for each particular problem. What we want is to move some points that can serve as a basis for reflection to help find the best solution possible, once the problem is defined correctly. The first thing to do before starting any automated system project is to define exactly the domain you want to cover and assess with greater precision possible importance.

A Fuzzy Decision Strategy for Topic Identification and Dynamic Selection of Language Models

International audience

Different Aspects of General Anesthesia in Pediatric Dentistry: A Review

Context:Most child population is able to undergo dental treatment in the conventional setting. However, some children fail to cope with in-office conscious state and cannot respond to usual management modalities. This review aims to discuss the topic further. Evidence Acquisition: A computerized search in databases PubMed, MEDLINE, EMBASE, Google Scholar and Google were performed using dental general anesthesia related keywords. Original and review English-written articles that were limited to child population were retrieved without any limitation of publication date. The suitable papers were selected and carefully studied. A data form designed by author was used to write relevant findings. Results: Preoperative oral examination and comprehensive evaluation of treatment needs is only possible after clinical and radiographic oral examination. Effective collaboration in dental GA team should be made to minimize psychological trauma of children who undergo dental GA. Before conducting comprehensive dental treatment under GA, the general health of the child and the success rate of procedures provided needs to be accurately evaluated. It is noteworthy that determination of the optimal timing for GA dental operation is of great importance. Providing safety with pediatric dental rehabilitation under GA is critical. Conclusions: Besides criteria for case selection of dental GA, some degree of dental practitioner’s judgment is required to make decision. Pre- and post-operative instructions to parents or caregiver decrease the risk of complications. However, trained resuscitation providers, careful monitoring and advanced equipment minimize adverse outcomes.

An investigation of imputation methods for discrete databases and multi-variate time series

When it comes to information sets in real life, often pieces of the whole set may not be available. This problem can find its origin in various reasons, describing therefore different patterns. In the literature, this problem is known as Missing Data. This issue can be fixed in various ways, from not taking into consideration incomplete observations, to guessing what those values originally were, or just ignoring the fact that some values are missing. The methods used to estimate missing data are called Imputation Methods. The work presented in this thesis has two main goals. The first one is to determine whether any kind of interactions exists between Missing Data, Imputation Methods and Supervised Classification algorithms, when they are applied together. For this first problem we consider a scenario in which the databases used are discrete, understanding discrete as that it is assumed that there is no relation between observations. These datasets underwent processes involving different combina- tions of the three components mentioned. The outcome showed that the missing data pattern strongly influences the outcome produced by a classifier. Also, in some of the cases, the complex imputation techniques investigated in the thesis were able to obtain better results than simple ones. The second goal of this work is to propose a new imputation strategy, but this time we constrain the specifications of the previous problem to a special kind of datasets, the multivariate Time Series. We designed new imputation techniques for this particular domain, and combined them with some of the contrasted strategies tested in the pre- vious chapter of this thesis. The time series also were subjected to processes involving missing data and imputation to finally propose an overall better imputation method. In the final chapter of this work, a real-world example is presented, describing a wa- ter quality prediction problem. The databases that characterized this problem had their own original latent values, which provides a real-world benchmark to test the algorithms developed in this thesis.

Implementazione e benchmarking dell'algoritmo QDANet PRO per l'analisi di big data genomici

Dato il recente avvento delle tecnologie NGS, in grado di sequenziare interi genomi umani in tempi e costi ridotti, la capacità di estrarre informazioni dai dati ha un ruolo fondamentale per lo sviluppo della ricerca. Attualmente i problemi computazionali connessi a tali analisi rientrano nel topic dei Big Data, con databases contenenti svariati tipi di dati sperimentali di dimensione sempre più ampia. Questo lavoro di tesi si occupa dell'implementazione e del benchmarking dell'algoritmo QDANet PRO, sviluppato dal gruppo di Biofisica dell'Università di Bologna: il metodo consente l'elaborazione di dati ad alta dimensionalità per l'estrazione di una Signature a bassa dimensionalità di features con un'elevata performance di classificazione, mediante una pipeline d'analisi che comprende algoritmi di dimensionality reduction. Il metodo è generalizzabile anche all'analisi di dati non biologici, ma caratterizzati comunque da un elevato volume e complessità, fattori tipici dei Big Data. L'algoritmo QDANet PRO, valutando la performance di tutte le possibili coppie di features, ne stima il potere discriminante utilizzando un Naive Bayes Quadratic Classifier per poi determinarne il ranking. Una volta selezionata una soglia di performance, viene costruito un network delle features, da cui vengono determinate le componenti connesse. Ogni sottografo viene analizzato separatamente e ridotto mediante metodi basati sulla teoria dei networks fino all'estrapolazione della Signature finale. Il metodo, già precedentemente testato su alcuni datasets disponibili al gruppo di ricerca con riscontri positivi, è stato messo a confronto con i risultati ottenuti su databases omici disponibili in letteratura, i quali costituiscono un riferimento nel settore, e con algoritmi già esistenti che svolgono simili compiti. Per la riduzione dei tempi computazionali l'algoritmo è stato implementato in linguaggio C++ su HPC, con la parallelizzazione mediante librerie OpenMP delle parti più critiche.

Topic extraction from microblog posts using conversation structures

Conventional topic models are ineffective for topic extraction from microblog messages since the lack of structure and context among the posts renders poor message-level word co-occurrence patterns. In this work, we organize microblog posts as conversation trees based on reposting and replying relations, which enrich context information to alleviate data sparseness. Our model generates words according to topic dependencies derived from the conversation structures. In specific, we differentiate messages as leader messages, which initiate key aspects of previously focused topics or shift the focus to different topics, and follower messages that do not introduce any new information but simply echo topics from the messages that they repost or reply. Our model captures the different extents that leader and follower messages may contain the key topical words, thus further enhances the quality of the induced topics. The results of thorough experiments demonstrate the effectiveness of our proposed model.

Databases for quantitative history

This paper will propose that, rather than sitting on silos of data, historians that utilise quantitative methods should endeavour to make their data accessible through databases, and treat this as a new form of bibliographic entry. Of course in many instances historical data does not lend itself easily to the creation of such data sets. With this in mind some of the issues regarding normalising raw historical data will be looked at with reference to current work on nineteenth century Irish trade. These issues encompass (but are not limited to) measurement systems, geographic locations, and potential problems that may arise in attempting to unify disaggregated sources. It will discuss the need for a concerted effort by historians to define what is required from digital resources for them to be considered accurate, and to what extent the normalisation requirements for database systems may conflict with the desire for accuracy. Many of the issues that the historian may encounter engaging with databases will be common to all historians, and there would be merit in having defined standards for referencing items, such as people, places, locations, and measurements.

A multiagent based strategy for detecting attacks in databases in a distributed mode

This paper presents a distributed hierarchical multiagent architecture for detecting SQL injection attacks against databases. It uses a novel strategy, which is supported by a Case-Based Reasoning mechanism, which provides to the classifier agents with a great capacity of learning and adaptation to face this type of attack. The architecture combines strategies of intrusion detection systems such as misuse detection and anomaly detection. It has been tested and the results are presented in this paper.

Depresión en pacientes con epilepsia: Revisión sistemática de la literatura

Esta revisión sistemática de la literatura tuvo como objetivo investigar sobre la depresión en personas con epilepsia en la última década (2005-2015), enfocándose en identificar en el paciente con epilepsia: características sociodemográficas, prevalencia de la depresión, tipos de intervención para el manejo de la depresión, factores asociados con la aparición y el mantenimiento de la depresión y por último, identificar las tendencias en investigación en el estudio de la depresión en pacientes con epilepsia. Se revisaron 103 artículos publicados entre 2005 y 2015 en bases de datos especializadas. Los resultados revelaron que la prevalencia de depresión en pacientes con epilepsia es diversa y oscila en un rango amplio entre 3 y 70 %, por otro lado, que las principales características sociodemográficas asociadas a la depresión está el ser mujer, tener un estado civil soltero y tener una edad comprendida entre los 25 y los 45 años. A esto se añade, que los tratamientos conformados por terapia psicológica y fármacos, son la mejor opción para garantizar la eficacia en los resultados del manejo de la depresión en los pacientes con epilepsia. Con respecto a los factores asociados a la aparición de la depresión en pacientes con epilepsia, se identificaron causas tanto neurobiológicas como psicosociales, asimismo los factores principales asociados al mantenimiento fueron una percepción de baja calidad de vida y una baja auto-eficacia. Y finalmente los tipos de investigación más comunes son de tipo aplicado, de carácter descriptivo, transversales y de medición cuantitativa.

Trastornos musculoesqueléticos en trabajadores de la industria automotriz: revisión de la literatura 2000 a 2016.

Los trastornos musculoesqueléticos (TME) tienen alta relación con la industria automotriz afectando a los trabajadores en quienes se puede encontrar varias patologías como Síndrome Del Túnel Del Carpo, Epicondilitis, Síndrome del Manguito Rotador, discopatía lumbar y lumbalgias, entre otros. Entre los factores de riesgo asociados a estos trastornos están los movimientos repetitivos, posturas inadecuadas, vibración, uso manual de herramientas, tareas físicas demandantes y el mal levantamiento de pesos. Todas estas patologías son causa de ausentismo laboral en todo el mundo, lo que conlleva a un aumento en el costo económico por incapacidades, ayudas diagnósticas y tratamientos. Se realizó una revisión de la literatura científica de artículos publicados del año 2000 a 2016 con relación a los trastornos musculoesqueléticos en la industria automotriz en las bases de datos de Pubmed, Ebsco Host, ScienceDirect y Embase. La evidencia encontrada sugiere que la patología lumbar es la que presenta mayor prevalencia en la industria, con 65% en la población Europea, 42% en Asia, Norteamérica en un 20% y en América Latina en un 46%. A pesar que en la industria automotriz predominan como fuerza laboral los hombres, se reportó que las mujeres eran las que tenían mayores factores de riesgo para desarrollar un TME y dentro de estos las posturas inadecuadas, movimientos repetitivos, sobrecarga laboral y levantamiento de pesos, sumado al tiempo de exposición que fue un común denominador en cada uno de los estudios analizados. Las conclusiones fueron que la prevalencia de TME en esta industria es elevada y esto amerita la implementación de programas de prevención más enfocados en este tema. Además no se encontró en la literatura la existencia de un método eficiente para análisis postural y de sobrecarga física, lo que habla de una necesidad urgente de realizar más investigaciones enfocadas en este tipo de población.

The Value Of The 2005 International Society Of Urological Pathology (isup) Modified Gleason Grading System As A Predictor Of Biochemical Recurrence After Radical Prostatectomy.

To compare time and risk to biochemical recurrence (BR) after radical prostatectomy of two chronologically different groups of patients using the standard and the modified Gleason system (MGS). Cohort 1 comprised biopsies of 197 patients graded according to the standard Gleason system (SGS) in the period 1997/2004, and cohort 2, 176 biopsies graded according to the modified system in the period 2005/2011. Time to BR was analyzed with the Kaplan-Meier product-limit analysis and prediction of shorter time to recurrence using univariate and multivariate Cox proportional hazards model. Patients in cohort 2 reflected time-related changes: striking increase in clinical stage T1c, systematic use of extended biopsies, and lower percentage of total length of cancer in millimeter in all cores. The MGS used in cohort 2 showed fewer biopsies with Gleason score ≤ 6 and more biopsies of the intermediate Gleason score 7. Time to BR using the Kaplan-Meier curves showed statistical significance using the MGS in cohort 2, but not the SGS in cohort 1. Only the MGS predicted shorter time to BR on univariate analysis and on multivariate analysis was an independent predictor. The results favor that the 2005 International Society of Urological Pathology modified system is a refinement of the Gleason grading and valuable for contemporary clinical practice.

Growth Curves For Girls With Turner Syndrome.

The objective of this study was to review the growth curves for Turner syndrome, evaluate the methodological and statistical quality, and suggest potential growth curves for clinical practice guidelines. The search was carried out in the databases Medline and Embase. Of 1006 references identified, 15 were included. Studies constructed curves for weight, height, weight/height, body mass index, head circumference, height velocity, leg length, and sitting height. The sample ranged between 47 and 1,565 (total = 6,273) girls aged 0 to 24 y, born between 1950 and 2006. The number of measures ranged from 580 to 9,011 (total = 28,915). Most studies showed strengths such as sample size, exclusion of the use of growth hormone and androgen, and analysis of confounding variables. However, the growth curves were restricted to height, lack of information about selection bias, limited distributional properties, and smoothing aspects. In conclusion, we observe the need to construct an international growth reference for girls with Turner syndrome, in order to provide support for clinical practice guidelines.

Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

De Novo Assembly And Transcriptome Analysis Of The Rubber Tree (hevea Brasiliensis) And Snp Markers Development For Rubber Biosynthesis Pathways.

Hevea brasiliensis (Willd. Ex Adr. Juss.) Muell.-Arg. is the primary source of natural rubber that is native to the Amazon rainforest. The singular properties of natural rubber make it superior to and competitive with synthetic rubber for use in several applications. Here, we performed RNA sequencing (RNA-seq) of H. brasiliensis bark on the Illumina GAIIx platform, which generated 179,326,804 raw reads on the Illumina GAIIx platform. A total of 50,384 contigs that were over 400 bp in size were obtained and subjected to further analyses. A similarity search against the non-redundant (nr) protein database returned 32,018 (63%) positive BLASTx hits. The transcriptome analysis was annotated using the clusters of orthologous groups (COG), gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Pfam databases. A search for putative molecular marker was performed to identify simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). In total, 17,927 SSRs and 404,114 SNPs were detected. Finally, we selected sequences that were identified as belonging to the mevalonate (MVA) and 2-C-methyl-D-erythritol 4-phosphate (MEP) pathways, which are involved in rubber biosynthesis, to validate the SNP markers. A total of 78 SNPs were validated in 36 genotypes of H. brasiliensis. This new dataset represents a powerful information source for rubber tree bark genes and will be an important tool for the development of microsatellites and SNP markers for use in future genetic analyses such as genetic linkage mapping, quantitative trait loci identification, investigations of linkage disequilibrium and marker-assisted selection.

Exploring Iris Colour Prediction And Ancestry Inference In Admixed Populations Of South America.

New DNA-based predictive tests for physical characteristics and inference of ancestry are highly informative tools that are being increasingly used in forensic genetic analysis. Two eye colour prediction models: a Bayesian classifier - Snipper and a multinomial logistic regression (MLR) system for the Irisplex assay, have been described for the analysis of unadmixed European populations. Since multiple SNPs in combination contribute in varying degrees to eye colour predictability in Europeans, it is likely that these predictive tests will perform in different ways amongst admixed populations that have European co-ancestry, compared to unadmixed Europeans. In this study we examined 99 individuals from two admixed South American populations comparing eye colour versus ancestry in order to reveal a direct correlation of light eye colour phenotypes with European co-ancestry in admixed individuals. Additionally, eye colour prediction following six prediction models, using varying numbers of SNPs and based on Snipper and MLR, were applied to the study populations. Furthermore, patterns of eye colour prediction have been inferred for a set of publicly available admixed and globally distributed populations from the HGDP-CEPH panel and 1000 Genomes databases with a special emphasis on admixed American populations similar to those of the study samples.