970 resultados para Univariate Analysis box-jenkins methodology


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A study of tin deposits from Priamurye (Russia) is performed to analyze the differencesbetween them based on their origin and also on commercial criteria. A particularanalysis based on their vertical zonality is also given for samples from Solnechnoedeposit. All the statistical analysis are made on the subcomposition formed by seventrace elements in cassiterite (In, Sc, Be, W, Nb, Ti and V) using the Aitchison’methodology of analysis of compositional data

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Isotopic data are currently becoming an important source of information regardingsources, evolution and mixing processes of water in hydrogeologic systems. However, itis not clear how to treat with statistics the geochemical data and the isotopic datatogether. We propose to introduce the isotopic information as new parts, and applycompositional data analysis with the resulting increased composition. Results areequivalent to downscale the classical isotopic delta variables, because they are alreadyrelative (as needed in the compositional framework) and isotopic variations are almostalways very small. This methodology is illustrated and tested with the study of theLlobregat River Basin (Barcelona, NE Spain), where it is shown that, though verysmall, isotopic variations comp lement geochemical principal components, and help inthe better identification of pollution sources

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A compositional time series is obtained when a compositional data vector is observed atdifferent points in time. Inherently, then, a compositional time series is a multivariatetime series with important constraints on the variables observed at any instance in time.Although this type of data frequently occurs in situations of real practical interest, atrawl through the statistical literature reveals that research in the field is very much in itsinfancy and that many theoretical and empirical issues still remain to be addressed. Anyappropriate statistical methodology for the analysis of compositional time series musttake into account the constraints which are not allowed for by the usual statisticaltechniques available for analysing multivariate time series. One general approach toanalyzing compositional time series consists in the application of an initial transform tobreak the positive and unit sum constraints, followed by the analysis of the transformedtime series using multivariate ARIMA models. In this paper we discuss the use of theadditive log-ratio, centred log-ratio and isometric log-ratio transforms. We also presentresults from an empirical study designed to explore how the selection of the initialtransform affects subsequent multivariate ARIMA modelling as well as the quality ofthe forecasts

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BACKGROUND Only multifaceted hospital wide interventions have been successful in achieving sustained improvements in hand hygiene (HH) compliance. METHODOLOGY/PRINCIPAL FINDINGS Pre-post intervention study of HH performance at baseline (October 2007-December 2009) and during intervention, which included two phases. Phase 1 (2010) included multimodal WHO approach. Phase 2 (2011) added Continuous Quality Improvement (CQI) tools and was based on: a) Increase of alcohol hand rub (AHR) solution placement (from 0.57 dispensers/bed to 1.56); b) Increase in frequency of audits (three days every three weeks: "3/3 strategy"); c) Implementation of a standardized register form of HH corrective actions; d) Statistical Process Control (SPC) as time series analysis methodology through appropriate control charts. During the intervention period we performed 819 scheduled direct observation audits which provided data from 11,714 HH opportunities. The most remarkable findings were: a) significant improvements in HH compliance with respect to baseline (25% mean increase); b) sustained high level (82%) of HH compliance during intervention; c) significant increase in AHRs consumption over time; c) significant decrease in the rate of healthcare-acquired MRSA; d) small but significant improvements in HH compliance when comparing phase 2 to phase 1 [79.5% (95% CI: 78.2-80.7) vs 84.6% (95% CI:83.8-85.4), p<0.05]; e) successful use of control charts to identify significant negative and positive deviations (special causes) related to the HH compliance process over time ("positive": 90.1% as highest HH compliance coinciding with the "World hygiene day"; and "negative":73.7% as lowest HH compliance coinciding with a statutory lay-off proceeding). CONCLUSIONS/SIGNIFICANCE CQI tools may be a key addition to WHO strategy to maintain a good HH performance over time. In addition, SPC has shown to be a powerful methodology to detect special causes in HH performance (positive and negative) and to help establishing adequate feedback to healthcare workers.

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Morphogens of the Wnt protein family are the secreted lipoglycoprotein ligands which initiate several pathways heavily involved in the coordination of various developmental stages of organisms in the majority of animal species. Deregulation of these pathways in the adult leads to formation and sustaining of multiple types of cancer. The latter notion is reinforced by the fact that the very discovery of the first Wnt ligand was due to its role as the causative factor of carcinogenic transformation (Nusse and Varmus, 1982). Nowadays our knowledge on Wnt signaling has "moved with the times" and these pathways were identified to be often crucial for tumor formation, its interactions with the microenvironment, and promotion of the metastases (Huang and Du, 2008; Zerlin et al., 2008; Jessen, 2009). Thus the relevance of the pathway as the target for drug development has further increased in the light of modern paradigms of the complex cancer treatments which target also spreading and growth- promoting factors of tumors by specific and highly efficient substances (Pavet et al., 2010). Presently the field of the Wnt-targeting drug research is almost solely dominated by assays based on transcriptional activation induced by the signaling. This approach resulted in development of a number of promising substances (Lee et al., 2011). Despite its effectiveness, the method nevertheless suffers from several drawbacks. Among the major ones is the fact that this approach is prone to identify compounds targeting rather downstream effectors of the pathway, which are indiscriminately used by all the subtypes of the Wnt signaling. Additionally, proteins which are involved in several signaling cascades and not just the Wnt pathway turn out as targets of the new compounds. These issues increase risks of side effects due to off-target interactions and blockade of the pathway in healthy cells. In the present work we put forward a novel biochemical approach for drug development on the Wnt pathway. It targets Frizzleds (Fzs) - a family of 7-transmbembrane proteins which serve as receptors for Wnt ligands. They offer unique properties for the development of highly specific and effective drugs as they control all branches of the Wnt signaling. Recent advances in the understanding of the roles of heterotrimeric G proteins downstream from Fzs (Katanaev et al., 2005; Liu et al., 2005; Jernigan et al., 2010) suggest application of enzymatic properties of these effectors to monitor the receptor-mediated events. We have applied this knowledge in practice and established a specific and efficient method based on utilization of a novel high-throughput format of the GTP-binding assay to follow the activation of Fzs. This type of assay is a robust and well-established technology for the research and screenings on the GPCRs (Harrison and Traynor, 2003). The conventional method of detection involves the radioactively labeled non-hydrolysable GTP analog [35S]GTPyS. Its application in the large-scale screenings is however problematic which promoted development of the novel non-radioactive GTP analog GTP-Eu. The new molecule employs phenomenon of the time-resolved fluorescence to provide sensitivity comparable to the conventional radioactive substance. Initially GTP-Eu was tested only in one of many possible types of GTP-binding assays (Frang et al., 2003). In the present work we expand these limits by demonstrating the general comparability of the novel label with the radioactive method in various types of assays. We provide a biochemical characterization of GTP-Eu interactions with heterotrimeric and small GTPases and a comparative analysis of the behavior of the new label in the assays involving heterotrimeric G protein effectors. These developments in the GTP-binding assay were then applied to monitor G protein activation by the Fz receptors. The data obtained in mammalian cultured cell lines provides for the first time an unambiguous biochemical proof for direct coupling of Fzs with G proteins. The specificity of this interaction has been confirmed by the experiments with the antagonists of Fz and by the pertussis toxin-mediated deactivation. Additionally we have identified the specificity of Wnt3a towards several members of the Fz family and analyzed the properties of human Fz-1 which was found to be the receptor coupled to the Gi/o family of G proteins. Another process playing significant role in the functioning of every GPCR is endocytosis. This phenomenon can also be employed for drug screenings on GPCRs (Bickle, 2010). In the present work we have demonstrated that Drosophila Fz receptors are involved in an unusual for many GPCRs manifestation of the receptor-mediated internalization. Through combination of biochemical approaches and studies on Drosophila as the model organism we have shown that direct interactions of the Fzs and the α-subunit of the heterotrimeric G protein Go with the small GTPase Rab5 regulate internalization of the receptor in early endosomes. We provide data uncovering the decisive role of this self-promoted endocytosis in formation of a proper signaling output in the canonical as well as planar cell polarity (PCP) pathways regulated by Fz. The results of this work thus establish a platform for the high-throughput screening to identify substances active in the cancer-related Wnt pathways. This methodology has been adjusted and applied to provide the important insights in Fz functioning and will be instrumental for further investigations on the Wnt-mediated pathways.

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En aquest treball, es proposa un nou mètode per estimar en temps real la qualitat del producte final en processos per lot. Aquest mètode permet reduir el temps necessari per obtenir els resultats de qualitat de les anàlisi de laboratori. S'utiliza un model de anàlisi de componentes principals (PCA) construït amb dades històriques en condicions normals de funcionament per discernir si un lot finalizat és normal o no. Es calcula una signatura de falla pels lots anormals i es passa a través d'un model de classificació per la seva estimació. L'estudi proposa un mètode per utilitzar la informació de les gràfiques de contribució basat en les signatures de falla, on els indicadors representen el comportament de les variables al llarg del procés en les diferentes etapes. Un conjunt de dades compost per la signatura de falla dels lots anormals històrics es construeix per cercar els patrons i entrenar els models de classifcació per estimar els resultas dels lots futurs. La metodologia proposada s'ha aplicat a un reactor seqüencial per lots (SBR). Diversos algoritmes de classificació es proven per demostrar les possibilitats de la metodologia proposada.

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The BTAF1 transcription factor interacts with TATA-binding protein (TBP) to form the B-TFIID complex, which is involved in RNA polymerase II transcription. Here, we present an extensive mapping study of TBP residues involved in BTAF1 interaction. This shows that residues in the concave, DNA-binding surface of TBP are important for BTAF1 binding. In addition, BTAF1 interacts with residues in helix 2 on the convex side of TBP as assayed in protein-protein and in DNA-binding assays. BTAF1 drastically changes the TATA-box binding specificity of TBP, as it is able to recruit DNA-binding defective TBP mutants to both TATA-containing and TATA-less DNA. Interestingly, other helix 2 interacting factors, such as TFIIA and NC2, can also stabilize mutant TBP binding to DNA. In contrast, TFIIB which interacts with a distinct surface of TBP does not display this activity. Since many proteins contact helix 2 of TBP, this provides a molecular basis for mutually exclusive TBP interactions and stresses the importance of this structural element for eukaryotic transcription.

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BACKGROUND In the MACRO study, patients with metastatic colorectal cancer (mCRC) were randomised to first-line treatment with 6 cycles of capecitabine and oxaliplatin (XELOX) plus bevacizumab followed by either single-agent bevacizumab or XELOX plus bevacizumab until disease progression. An additional retrospective analysis was performed to define the prognostic value of tumour KRAS status on progression-free survival (PFS), overall survival (OS) and response rates. METHODOLOGY/PRINCIPAL FINDINGS KRAS data (tumour KRAS status and type of mutation) were collected by questionnaire from participating centres that performed KRAS analyses. These data were then cross-referenced with efficacy data for relevant patients in the MACRO study database. KRAS status was analysed in 394 of the 480 patients (82.1%) in the MACRO study. Wild-type (WT) KRAS tumours were found in 219 patients (56%) and mutant (MT) KRAS in 175 patients (44%). Median PFS was 10.9 months for patients with WT KRAS and 9.4 months for patients with MT KRAS tumours (p=0.0038; HR: 1.40; 95% CI:1.12-1.77). The difference in OS was also significant: 26.7 months versus 18.0 months for WT versus MT KRAS, respectively (p=0.0002; HR: 1.55; 95% CI: 1.23-1.96). Univariate and multivariate analyses showed that KRAS was an independent variable for both PFS and OS. Responses were observed in 126 patients (57.5%) with WT KRAS tumours and 76 patients (43.4%) with MT KRAS tumours (p=0.0054; OR: 1.77; 95% CI: 1.18-2.64). CONCLUSIONS/SIGNIFICANCE This analysis of the MACRO study suggests a prognostic role for tumour KRAS status in patients with mCRC treated with XELOX plus bevacizumab. For both PFS and OS, KRAS status was an independent factor in univariate and multivariate analyses.

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BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

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The disintegration of the USSR brought the emergence of a new geo-energy space in Central Asia. This space arose in the context of a global energy transition, which began in the late 1970s. Therefore, this new space in a changing energy world requires both new conceptual frameworks of analysis and the creation of new analytical tools. Taking into account this fact, our paper attempts to apply the theoretical framework of the Global Commodity Chain (GCC) to the case of natural resources in Central Asia. The aim of the paper is to check if there could be any Central Asia’s geo-energy space, assuming that this space would exist if natural resources were managed with regional criteria. The paper is divided into four sections. First an introduction that describes the new global energy context within natural resources of Central Asia would be integrated. Secondly, the paper justifies why the GCC methodology is suitable for the study of the value chains of energy products. Thirdly, we build up three cases studies (oil and uranium from Kazakhstan and gas from Turkmenistan) which reveal a high degree of uncertainty over the direction these chains will take. Finally, we present the conclusions of this study that state that the most plausible scenario would be the integration of energy resources of these countries in GCC where the core of the decision-making process will be far away from the region of Central Asia. Key words: Energy transition, geo-energy space, Global Commodity Chains, Central Asia

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The diagnosis of mucocutaneous leishmaniasis (MCL) is hampered by the absence of a gold standard. An accurate diagnosis is essential because of the high toxicity of the medications for the disease. This study aimed to assess the ability of polymerase chain reaction (PCR) to identify MCL and to compare these results with clinical research recently published by the authors. A systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA Statement was performed using comprehensive search criteria and communication with the authors. A meta-analysis considering the estimates of the univariate and bivariate models was performed. Specificity near 100% was common among the papers. The primary reason for accuracy differences was sensitivity. The meta-analysis, which was only possible for PCR samples of lesion fragments, revealed a sensitivity of 71% [95% confidence interval (CI) = 0.59; 0.81] and a specificity of 93% (95% CI = 0.83; 0.98) in the bivariate model. The search for measures that could increase the sensitivity of PCR should be encouraged. The quality of the collected material and the optimisation of the amplification of genetic material should be prioritised.

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In the eighties, John Aitchison (1986) developed a new methodological approach for the statistical analysis of compositional data. This new methodology was implemented in Basic routines grouped under the name CODA and later NEWCODA inMatlab (Aitchison, 1997). After that, several other authors have published extensions to this methodology: Marín-Fernández and others (2000), Barceló-Vidal and others (2001), Pawlowsky-Glahn and Egozcue (2001, 2002) and Egozcue and others (2003). (...)

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One of the tantalising remaining problems in compositional data analysis lies in how to deal with data sets in which there are components which are essential zeros. By anessential zero we mean a component which is truly zero, not something recorded as zero simply because the experimental design or the measuring instrument has not been sufficiently sensitive to detect a trace of the part. Such essential zeros occur inmany compositional situations, such as household budget patterns, time budgets,palaeontological zonation studies, ecological abundance studies. Devices such as nonzero replacement and amalgamation are almost invariably ad hoc and unsuccessful insuch situations. From consideration of such examples it seems sensible to build up amodel in two stages, the first determining where the zeros will occur and the secondhow the unit available is distributed among the non-zero parts. In this paper we suggest two such models, an independent binomial conditional logistic normal model and a hierarchical dependent binomial conditional logistic normal model. The compositional data in such modelling consist of an incidence matrix and a conditional compositional matrix. Interesting statistical problems arise, such as the question of estimability of parameters, the nature of the computational process for the estimation of both the incidence and compositional parameters caused by the complexity of the subcompositional structure, the formation of meaningful hypotheses, and the devising of suitable testing methodology within a lattice of such essential zero-compositional hypotheses. The methodology is illustrated by application to both simulated and real compositional data

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The application of Discriminant function analysis (DFA) is not a new idea in the studyof tephrochrology. In this paper, DFA is applied to compositional datasets of twodifferent types of tephras from Mountain Ruapehu in New Zealand and MountainRainier in USA. The canonical variables from the analysis are further investigated witha statistical methodology of change-point problems in order to gain a betterunderstanding of the change in compositional pattern over time. Finally, a special caseof segmented regression has been proposed to model both the time of change and thechange in pattern. This model can be used to estimate the age for the unknown tephrasusing Bayesian statistical calibration

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BACKGROUND: The aim of this study is to determine whether statistical associations can be demonstrated in ocular syphilis between baseline clinical and laboratory parameters with visual acuity at presentation and with any change in visual acuity after treatment. METHODS: Charts of 26 patients (42 eyes) with ocular syphilis presenting to the Uveitis clinic of the Jules-Gonin Eye Hospital were reviewed. A baseline cross-sectional analysis was performed in order to identify any association between visual acuity at presentation and demographic, clinical or laboratory parameters. After treatment, any analogy between these parameters and a change in visual acuity was subsequently assessed in a series of univariate comparisons. RESULTS: The following factors were associated with worse initial visual acuity: severity of visual field impairment at presentation (p=0.012), macular oedema (p=0.004) and optic neuropathy (p=0.031). There was a borderline association with the presence of vasculitis on fluroangiography (p=0.072). Improvement in best corrected visual acuity after treatment was significantly associated with the presence of vasculitis on fluroangiography (p=0.005), neurosyphilis, according to lumbar puncture findings (p=0.037) and marginally with anterior uveitis (p=0.070). Inflammation relapse was associated with the coexistence of pain as presenting sign (p<0.001) and with a longer duration of symptoms prior to the initial visit (p=0.023). CONCLUSIONS: Severe ocular inflammation associated with vasculitis, vitritis or anterior uveitis in ocular syphilis would appear to be a reversible phenomenon that responds well to appropriate antibiotic treatment, resulting in improvement in visual acuity. Prompt treatment enables a good visual prognosis, while any delay in therapy increases the risk of subsequent relapse.