Dental Implants Success Prediction: Tomography Based and Data Mining Based Approach.

There are a number of factors that contribute to the success of dental implant operations. Among others, is the choice of location in which the prosthetic tooth is to be implanted. This project offers a new approach to analyse jaw tissue for the purpose of selecting suitable locations for teeth implant operations. The application developed takes as input jaw computed tomography stack of slices and trims data outside the jaw area, which is the point of interest. It then reconstructs a three dimensional model of the jaw highlighting points of interest on the reconstructed model. On another hand, data mining techniques have been utilised in order to construct a prediction model based on an information dataset of previous dental implant operations with observed stability values. The goal is to find patterns within the dataset that would help predicting the success likelihood of an implant.

Patients' prediction of extubation success.

The spontaneous breathing trial (SBT)-relying on objective criteria assessed by the clinician-is the major diagnostic tool to determine if patients can be successfully extubated. However, little is known regarding the patient's subjective perception of autonomous breathing. We performed a prospective observational study in 211 mechanically ventilated adult patients successfully completing a SBT. Patients were randomly assigned to be interviewed during this trial regarding their prediction of extubation success. We compared post-extubation outcomes in three patient groups: patients confident (confidents; n = 115) or not (non-confidents; n = 38) of their extubation success and patients not subjected to interview (control group; n = 58). Extubation success was more frequent in confidents than in non-confidents (90 vs. 45%; p < 0.001/positive likelihood ratio = 2.00) or in the control group (90 vs. 78%; p = 0.04). On the contrary, extubation failure was more common in non-confidents than in confidents (55 vs. 10%; p < 0.001/negative likelihood ratio = 0.19). Logistic regression analysis showed that extubation success was associated with patient's prediction [OR (95% CI): 9.2 (3.74-22.42) for confidents vs.non-confidents] as well as to age [0.72 (0.66-0.78) for age 75 vs. 65 and 1.31 (1.28-1.51) for age 55 vs. 65]. Our data suggest that at the end of a sustained SBT, extubation success might be correlated to the patients' subjective perception of autonomous breathing. The results of this study should be confirmed by a large multicenter trial.

Evaluating the success of software development projects in Russia, Ukraine, and Belarus

The size and complexity of projects in the software development are growing very fast. At the same time, the proportion of successful projects is still quite low according to the previous research. Although almost every project's team knows main areas of responsibility which would help to finish project on time and on budget, this knowledge is rarely used in practice. So it is important to evaluate the success of existing software development projects and to suggest a method for evaluating success chances which can be used in the software development projects. The main aim of this study is to evaluate the success of projects in the selected geographical region (Russia-Ukraine-Belarus). The second aim is to compare existing models of success prediction and to determine their strengths and weaknesses. Research was done as an empirical study. A survey with structured forms and theme-based interviews were used as the data collection methods. The information gathering was done in two stages. At the first stage, project manager or someone with similar responsibilities answered the questions over Internet. At the second stage, the participant was interviewed; his or her answers were discussed and refined. It made possible to get accurate information about each project and to avoid errors. It was found out that there are many problems in the software development projects. These problems are widely known and were discussed in literature many times. The research showed that most of the projects have problems with schedule, requirements, architecture, quality, and budget. Comparison of two models of success prediction presented that The Standish Group overestimates problems in project. At the same time, McConnell's model can help to identify problems in time and avoid troubles in future. A framework for evaluating success chances in distributed projects was suggested. The framework is similar to The Standish Group model but it was customized for distributed projects.

Prediction and understanding of the effect of children's interest upon school performance;

Mode of access: Internet.

Previsione del Successo di Prodotti di Moda Prima della Commercializzazione: un Nuovo Dataset e Modello di Vision-Language Transformer

A differenza di quanto avviene nel commercio tradizionale, in quello online il cliente non ha la possibilità di toccare con mano o provare il prodotto. La decisione di acquisto viene maturata in base ai dati messi a disposizione dal venditore attraverso titolo, descrizioni, immagini e alle recensioni di clienti precedenti. É quindi possibile prevedere quanto un prodotto venderà sulla base di queste informazioni. La maggior parte delle soluzioni attualmente presenti in letteratura effettua previsioni basandosi sulle recensioni, oppure analizzando il linguaggio usato nelle descrizioni per capire come questo influenzi le vendite. Le recensioni, tuttavia, non sono informazioni note ai venditori prima della commercializzazione del prodotto; usando solo dati testuali, inoltre, si tralascia l’influenza delle immagini. L'obiettivo di questa tesi è usare modelli di machine learning per prevedere il successo di vendita di un prodotto a partire dalle informazioni disponibili al venditore prima della commercializzazione. Si fa questo introducendo un modello cross-modale basato su Vision-Language Transformer in grado di effettuare classificazione. Un modello di questo tipo può aiutare i venditori a massimizzare il successo di vendita dei prodotti. A causa della mancanza, in letteratura, di dataset contenenti informazioni relative a prodotti venduti online che includono l’indicazione del successo di vendita, il lavoro svolto comprende la realizzazione di un dataset adatto a testare la soluzione sviluppata. Il dataset contiene un elenco di 78300 prodotti di Moda venduti su Amazon, per ognuno dei quali vengono riportate le principali informazioni messe a disposizione dal venditore e una misura di successo sul mercato. Questa viene ricavata a partire dal gradimento espresso dagli acquirenti e dal posizionamento del prodotto in una graduatoria basata sul numero di esemplari venduti.

Prediction of Golgi Type II membrane proteins based on their transmembrane domains

Motivation: A major issue in cell biology today is how distinct intracellular regions of the cell, like the Golgi Apparatus, maintain their unique composition of proteins and lipids. The cell differentially separates Golgi resident proteins from proteins that move through the organelle to other subcellular destinations. We set out to determine if we could distinguish these two types of transmembrane proteins using computational approaches. Results: A new method has been developed to predict Golgi membrane proteins based on their transmembrane domains. To establish the prediction procedure, we took the hydrophobicity values and frequencies of different residues within the transmembrane domains into consideration. A simple linear discriminant function was developed with a small number of parameters derived from a dataset of Type II transmembrane proteins of known localization. This can discriminate between proteins destined for Golgi apparatus or other locations (post-Golgi) with a success rate of 89.3% or 85.2%, respectively on our redundancy-reduced data sets.

Structural prediction of peptides bound to MHC class I.

An ab initio structure prediction approach adapted to the peptide-major histocompatibility complex (MHC) class I system is presented. Based on structure comparisons of a large set of peptide-MHC class I complexes, a molecular dynamics protocol is proposed using simulated annealing (SA) cycles to sample the conformational space of the peptide in its fixed MHC environment. A set of 14 peptide-human leukocyte antigen (HLA) A0201 and 27 peptide-non-HLA A0201 complexes for which X-ray structures are available is used to test the accuracy of the prediction method. For each complex, 1000 peptide conformers are obtained from the SA sampling. A graph theory clustering algorithm based on heavy atom root-mean-square deviation (RMSD) values is applied to the sampled conformers. The clusters are ranked using cluster size, mean effective or conformational free energies, with solvation free energies computed using Generalized Born MV 2 (GB-MV2) and Poisson-Boltzmann (PB) continuum models. The final conformation is chosen as the center of the best-ranked cluster. With conformational free energies, the overall prediction success is 83% using a 1.00 Angstroms crystal RMSD criterion for main-chain atoms, and 76% using a 1.50 Angstroms RMSD criterion for heavy atoms. The prediction success is even higher for the set of 14 peptide-HLA A0201 complexes: 100% of the peptides have main-chain RMSD values &lt; or =1.00 Angstroms and 93% of the peptides have heavy atom RMSD values &lt; or =1.50 Angstroms. This structure prediction method can be applied to complexes of natural or modified antigenic peptides in their MHC environment with the aim to perform rational structure-based optimizations of tumor vaccines.

Détermination de l'antigène HLA-G soluble dans le liquide folliculaire et dans le milieu de culture d'embryons comme indicateur du succès d'un traitement par FIV-ICSI [Soluble human leukocyte antigen-G (sHLA-G) in follicular fluid and embryo culture medium and its impact on pregnancy prediction in IVF-ICSI treatment]

In IVF around 70% of embryos fail to implant. Often more than one embryo is transferred in order to enhance the chances of pregnancy, but this is at the price of an increased multiple pregnancy risk. In the aim to increase the success rate with a single embryo, research projects on prognostic factors of embryo viability have been initiated, but no marker has found a routine clinical application to date. Effects of soluble human leukocyte antigen-G (sHLA-G) on both NK cell activity and on Th1/Th2 cytokine balance suggest a role in the embryo implantation process, but the relevance of sHLA-G measurements in embryo culture medium and in follicular fluid (FF) are inconsistent to date. In this study, we have investigated the potential of sHLA-G in predicting the achievement of a pregnancy after IVF-ICSI in a large number of patients (n = 221). sHLA-G was determined in media and in FF by ELISA. In both FF and embryo medium, no significant differences in sHLA-G concentrations were observed between the groups "pregnancy" and "implantation failure", or between the groups "ongoing" versus "miscarried pregnancies". Our results do not favour routine sHLA-G determinations in the FF nor in embryo conditioned media, with the current assay technology available.

The Role of a firm’s mindset in international success - case study of Finnish marine industry firms

This thesis investigates the influence of a firm’s mindset on international success in the context of the Finnish marine industry. The study draws theoretical wisdom from organisational behaviour and strategic management literatures. The research aim set for this study was to identify and categorise existing strategic types based on mindsets found in the marine industry SMEs, and to link the influence of mindsets with success by examining the role of mindsets in a firm’s performance. Mindsets of firms were conceptualised as aggregate collections of perceptions that influence how the surrounding environment is discerned by the members of the firm. Mindsets are idiosyncratic to firms and therefore important firm-specific resources which influence decision-making and can be observed through the strategic behaviour of firms. Qualitative case study method was applied which was further supported by quantitative data on the financial performance of the ten case firms. Taxonomy based on the dimension of mindsets and prediction was developed to demonstrate four ideal types of firms identified within the marine industry. It was found that all of the case firms emphasised adaptation in their strategy while planning was emphasised to a varying degree. Moreover, two different methods of adapting were found; proactive and reactive. Firms which plan in the long-term and adapt proactively constantly investigate whether their plans are synchronous with the realities of the market; by having an open mindset, a firm’s perception of the reality of the market is enabling the firm to develop value creating strategies which are superiorly informed.This finding was supported by the financial data and led to the proposition that having an open mindset and placing a high level of emphasis on prediction may have a positive influence on international success. Also, it was proposed that concentrating only on exploiting business opportunities in the present time and not exploring any addition opportunities can have a negative influence on the firm’s performance, even if the mindset of the firm is open.

The examination of predictors of success in two programmes requiring self-direction /

The new Physiotherapy and Occupational Therapy programmes, based in the Faculty of Health Sciences, McMaster University (Hamilton, Ontario) are unique. The teaching and learning philosophies utilized are based on learner-centred and selfdirected learning theories. The 1991 admissions process of these programmes attempted to select individuals who would make highly qualified professionals and who would have the necessary skills to complete such unique programmes. In order to: 1 . learn more about the concept of self-directed learning and its related characteristics in health care professionals; 2. examine the relationship between various student characteristics - personal, learner and those assessed during the admissions process - and final course grades, and 3. determine which, if any, smdent characteristics could be considered predictors for success in learner-centred programmes requiring self-directed learning skills, a correlational research design was developed and carried out. Thirty Occupational Therapy and thirty Physiotherapy smdents were asked to complete 2 instruments - a questionnaire developed by the author and the Oddi Continuing Learning Inventory (Oddi, 1986). Course grades and ratings of students during the admissions process were also obtained. Both questionnaires were examined for reliability, and factor analyses were conducted to determine construct validity. Data obtained from the questionnaires, course grades and student ratings (from the admissions process) were analyzed and compared using the Contingency Co-efficient, the Pearson's product-moment correlation co-efficient, and the multiple regression analysis model. The research findings demonstrated a positive relationship (as identified by Contingency Coefficient or Pearson r values) between various course grades and the following personal and learner characteristics: field of smdy of highest level of education achieved, level of education achieved, sex, marital stams, motivation for completing the programmes, reasons for eru-oling in the programmes, decision to enrol in the programmes, employment history, preferred learning style, strong selfconcept and the identification of various components of the concept of self-directed learning. In most cases, the relationships were significant to the 0.01 or 0.(X)1 levels. Results of the multiple regression analyses demonstrated that several learner and admissions characteristic variables had R^ values that accounted for the largest proportion of the variance in several dependent variables. Thus, these variables could be considered predictors for success. The learner characteristics included: level of education and strong self-concept. The admissions characteristics included: ability to evaluate strengths, ability to give feedback, curiosity and creativity, and communication skills. It is recommended that research continue to be conducted to substantiate the relationships found between course grades and characteristic variables in more diverse populations. "Success in self-directed programmes" from the learner's perspective should also be investigated. The Oddi Continuing Learning Inventory should continue to be researched. Further research may lead to refinement or further development of the instrument, and may provide further insight into self-directed learner attributes. The concept of self-directed learning continues to be incorporated into educational programmes, and thus should continue to be explored.

Development of a multi-gene PCR assay for the prediction of the response to hormone therapy in breast cancer

Deux tiers des cancers du sein expriment des récepteurs hormonaux ostrogéniques (tumeur ER-positive) et la croissance de ces tumeurs est stimulée par l’estrogène. Des traitements adjuvant avec des anti-estrogènes, tel que le Tamoxifen et les Inhibiteurs de l’Aromatase peuvent améliorer la survie des patientes atteinte de cancer du sein. Toutefois la thérapie hormonale n’est pas efficace dans toutes les tumeurs mammaires ER-positives. Les tumeurs peuvent présenter avec une résistance intrinsèque ou acquise au Tamoxifen. Présentement, c’est impossible de prédire quelle patiente va bénéficier ou non du Tamoxifen. Des études préliminaires du laboratoire de Dr. Mader, ont identifié le niveau d’expression de 20 gènes, qui peuvent prédire la réponse thérapeutique au Tamoxifen (survie sans récidive). Ces marqueurs, identifié en utilisant une analyse bioinformatique de bases de données publiques de profils d’expression des gènes, sont capables de discriminer quelles patientes vont mieux répondre au Tamoxifen. Le but principal de cette étude est de développer un outil de PCR qui peut évaluer le niveau d’expression de ces 20 gènes prédictif et de tester cette signature de 20 gènes dans une étude rétrospective, en utilisant des tumeurs de cancer du sein en bloc de paraffine, de patients avec une histoire médicale connue. Cet outil aurait donc un impact direct dans la pratique clinique. Des traitements futiles pourraient être éviter et l’indentification de tumeurs ER+ avec peu de chance de répondre à un traitement anti-estrogène amélioré. En conséquence, de la recherche plus appropriée pour les tumeurs résistantes au Tamoxifen, pourront se faire.

Prediction of global and local model quality in CASP8 using the ModFOLD server

The development of effective methods for predicting the quality of three-dimensional (3D) models is fundamentally important for the success of tertiary structure (TS) prediction strategies. Since CASP7, the Quality Assessment (QA) category has existed to gauge the ability of various model quality assessment programs (MQAPs) at predicting the relative quality of individual 3D models. For the CASP8 experiment, automated predictions were submitted in the QA category using two methods from the ModFOLD server-ModFOLD version 1.1 and ModFOLDclust. ModFOLD version 1.1 is a single-model machine learning based method, which was used for automated predictions of global model quality (QMODE1). ModFOLDclust is a simple clustering based method, which was used for automated predictions of both global and local quality (QMODE2). In addition, manual predictions of model quality were made using ModFOLD version 2.0-an experimental method that combines the scores from ModFOLDclust and ModFOLD v1.1. Predictions from the ModFOLDclust method were the most successful of the three in terms of the global model quality, whilst the ModFOLD v1.1 method was comparable in performance to other single-model based methods. In addition, the ModFOLDclust method performed well at predicting the per-residue, or local, model quality scores. Predictions of the per-residue errors in our own 3D models, selected using the ModFOLD v2.0 method, were also the most accurate compared with those from other methods. All of the MQAPs described are publicly accessible via the ModFOLD server at: http://www.reading.ac.uk/bioinf/ModFOLD/. The methods are also freely available to download from: http://www.reading.ac.uk/bioinf/downloads/.

Strategies: Revolution in climate prediction is both necessary and possible: A declaration at the World Modelling Summit for Climate Prediction

The impending threat of global climate change and its regional manifestations is among the most important and urgent problems facing humanity. Society needs accurate and reliable estimates of changes in the probability of regional weather variations to develop science-based adaptation and mitigation strategies. Recent advances in weather prediction and in our understanding and ability to model the climate system suggest that it is both necessary and possible to revolutionize climate prediction to meet these societal needs. However, the scientific workforce and the computational capability required to bring about such a revolution is not available in any single nation. Motivated by the success of internationally funded infrastructure in other areas of science, this paper argues that, because of the complexity of the climate system, and because the regional manifestations of climate change are mainly through changes in the statistics of regional weather variations, the scientific and computational requirements to predict its behavior reliably are so enormous that the nations of the world should create a small number of multinational high-performance computing facilities dedicated to the grand challenges of developing the capabilities to predict climate variability and change on both global and regional scales over the coming decades. Such facilities will play a key role in the development of next-generation climate models, build global capacity in climate research, nurture a highly trained workforce, and engage the global user community, policy-makers, and stakeholders. We recommend the creation of a small number of multinational facilities with computer capability at each facility of about 20 peta-flops in the near term, about 200 petaflops within five years, and 1 exaflop by the end of the next decade. Each facility should have sufficient scientific workforce to develop and maintain the software and data analysis infrastructure. Such facilities will enable questions of what resolution, both horizontal and vertical, in atmospheric and ocean models, is necessary for more confident predictions at the regional and local level. Current limitations in computing power have placed severe limitations on such an investigation, which is now badly needed. These facilities will also provide the world's scientists with the computational laboratories for fundamental research on weather–climate interactions using 1-km resolution models and on atmospheric, terrestrial, cryospheric, and oceanic processes at even finer scales. Each facility should have enabling infrastructure including hardware, software, and data analysis support, and scientific capacity to interact with the national centers and other visitors. This will accelerate our understanding of how the climate system works and how to model it. It will ultimately enable the climate community to provide society with climate predictions, which are based on our best knowledge of science and the most advanced technology.

Application of data assimilation to ocean and climate prediction

Ocean prediction systems are now able to analyse and predict temperature, salinity and velocity structures within the ocean by assimilating measurements of the ocean’s temperature and salinity into physically based ocean models. Data assimilation combines current estimates of state variables, such as temperature and salinity, from a computational model with measurements of the ocean and atmosphere in order to improve forecasts and reduce uncertainty in the forecast accuracy. Data assimilation generally works well with ocean models away from the equator but has been found to induce vigorous and unrealistic overturning circulations near the equator. A pressure correction method was developed at the University of Reading and the Met Office to control these circulations using ideas from control theory and an understanding of equatorial dynamics. The method has been used for the last 10 years in seasonal forecasting and ocean prediction systems at the Met Office and European Center for Medium-range Weather Forecasting (ECMWF). It has been an important element in recent re-analyses of the ocean heat uptake that mitigates climate change.