Sensitivity analysis, dominant factors, and robustness of the ECETOC TRA v3, Stoffenmanager 4.5, and ART 1.5 occupational exposure models

Occupational exposure modeling is widely used in the context of the E.U. regulation on the registration, evaluation, authorization, and restriction of chemicals (REACH). First tier tools, such as European Centre for Ecotoxicology and TOxicology of Chemicals (ECETOC) targeted risk assessment (TRA) or Stoffenmanager, are used to screen a wide range of substances. Those of concern are investigated further using second tier tools, e.g., Advanced REACH Tool (ART). Local sensitivity analysis (SA) methods are used here to determine dominant factors for three models commonly used within the REACH framework: ECETOC TRA v3, Stoffenmanager 4.5, and ART 1.5. Based on the results of the SA, the robustness of the models is assessed. For ECETOC, the process category (PROC) is the most important factor. A failure to identify the correct PROC has severe consequences for the exposure estimate. Stoffenmanager is the most balanced model and decision making uncertainties in one modifying factor are less severe in Stoffenmanager. ART requires a careful evaluation of the decisions in the source compartment since it constitutes ∼75% of the total exposure range, which corresponds to an exposure estimate of 20-22 orders of magnitude. Our results indicate that there is a trade off between accuracy and precision of the models. Previous studies suggested that ART may lead to more accurate results in well-documented exposure situations. However, the choice of the adequate model should ultimately be determined by the quality of the available exposure data: if the practitioner is uncertain concerning two or more decisions in the entry parameters, Stoffenmanager may be more robust than ART.

When gas analysis assists with postmortem imaging to diagnose causes of death.

Postmortem imaging consists in the non-invasive examination of bodies using medical imaging techniques. However, gas volume quantification and the interpretation of the gas collection results from cadavers remain difficult. We used whole-body postmortem multi-detector computed tomography (MDCT) followed by a full autopsy or external examination to detect the gaseous volumes in bodies. Gases were sampled from cardiac cavities, and the sample compositions were analyzed by headspace gas chromatography-mass spectrometry/thermal conductivity detection (HS-GC-MS/TCD). Three categories were defined according to the presumed origin of the gas: alteration/putrefaction, high-magnitude vital gas embolism (e.g., from scuba diving accident) and gas embolism of lower magnitude (e.g., following a traumatic injury). Cadaveric alteration gas was diagnosed even if only one gas from among hydrogen, hydrogen sulfide or methane was detected. In alteration cases, the carbon dioxide/nitrogen ratio was often >0.2, except in the case of advanced alteration, when methane presence was the best indicator. In the gas embolism cases (vital or not), hydrogen, hydrogen sulfide and methane were absent. Moreover, with high-magnitude vital gas embolisms, carbon dioxide content was >20%, and the carbon dioxide/nitrogen ratio was >0.2. With gas embolisms of lower magnitude (gas presence consecutive to a traumatic injury), carbon dioxide content was <20% and the carbon dioxide/nitrogen ratio was often <0.2. We found that gas analysis provided useful assistance to the postmortem imaging diagnosis of causes of death. Based on the quantifications of gaseous cardiac samples, reliable indicators were determined to document causes of death. MDCT examination of the body must be performed as quickly as possible, as does gas sampling, to avoid generating any artifactual alteration gases. Because of cardiac gas composition analysis, it is possible to distinguish alteration gases and gas embolisms of different magnitudes.

Chemotherapy and radiotherapy in nasopharyngeal carcinoma: an update of the MAC-NPC meta-analysis.

BACKGROUND: A previous individual patient data meta-analysis by the Meta-Analysis of Chemotherapy in Nasopharynx Carcinoma (MAC-NPC) collaborative group to assess the addition of chemotherapy to radiotherapy showed that it improves overall survival in nasopharyngeal carcinoma. This benefit was restricted to patients receiving concomitant chemotherapy and radiotherapy. The aim of this study was to update the meta-analysis, include recent trials, and to analyse separately the benefit of concomitant plus adjuvant chemotherapy. METHODS: We searched PubMed, Web of Science, Cochrane Controlled Trials meta-register, ClinicalTrials.gov, and meeting proceedings to identify published or unpublished randomised trials assessing radiotherapy with or without chemotherapy in patients with non-metastatic nasopharyngeal carcinoma and obtained updated data for previously analysed studies. The primary endpoint of interest was overall survival. All trial results were combined and analysed using a fixed-effects model. The statistical analysis plan was pre-specified in a protocol. All data were analysed on an intention-to-treat basis. FINDINGS: We analysed data from 19 trials and 4806 patients. Median follow-up was 7·7 years (IQR 6·2-11·9). We found that the addition of chemotherapy to radiotherapy significantly improved overall survival (hazard ratio [HR] 0·79, 95% CI 0·73-0·86, p<0·0001; absolute benefit at 5 years 6·3%, 95% CI 3·5-9·1). The interaction between treatment effect (benefit of chemotherapy) on overall survival and the timing of chemotherapy was significant (p=0·01) in favour of concomitant plus adjuvant chemotherapy (HR 0·65, 0·56-0·76) and concomitant without adjuvant chemotherapy (0·80, 0·70-0·93) but not adjuvant chemotherapy alone (0·87, 0·68-1·12) or induction chemotherapy alone (0·96, 0·80-1·16). The benefit of the addition of chemotherapy was consistent for all endpoints analysed (all p<0·0001): progression-free survival (HR 0·75, 95% CI 0·69-0·81), locoregional control (0·73, 0·64-0·83), distant control (0·67, 0·59-0·75), and cancer mortality (0·76, 0·69-0·84). INTERPRETATION: Our results confirm that the addition of concomitant chemotherapy to radiotherapy significantly improves survival in patients with locoregionally advanced nasopharyngeal carcinoma. To our knowledge, this is the first analysis that examines the effect of concomitant chemotherapy with and without adjuvant chemotherapy as distinct groups. Further studies on the specific benefits of adjuvant chemotherapy after concomitant chemoradiotherapy are needed. FUNDING: French Ministry of Health (Programme d'actions intégrées de recherche VADS), Ligue Nationale Contre le Cancer, and Sanofi-Aventis.

Prognostic factors for progression-free and overall survival in advanced biliary tract cancer.

BACKGROUND: Biliary tract cancer is an uncommon cancer with a poor outcome. We assembled data from the National Cancer Research Institute (UK) ABC-02 study and 10 international studies to determine prognostic outcome characteristics for patients with advanced disease. METHODS: Multivariable analyses of the final dataset from the ABC-02 study were carried out. All variables were simultaneously included in a Cox proportional hazards model, and backward elimination was used to produce the final model (using a significance level of 10%), in which the selected variables were associated independently with outcome. This score was validated externally by receiver operating curve (ROC) analysis using the independent international dataset. RESULTS: A total of 410 patients were included from the ABC-02 study and 753 from the international dataset. An overall survival (OS) and progression-free survival (PFS) Cox model was derived from the ABC-02 study. White blood cells, haemoglobin, disease status, bilirubin, neutrophils, gender, and performance status were considered prognostic for survival (all with P < 0.10). Patients with metastatic disease {hazard ratio (HR) 1.56 [95% confidence interval (CI) 1.20-2.02]} and Eastern Cooperative Oncology Group performance status (ECOG PS) 2 had worse survival [HR 2.24 (95% CI 1.53-3.28)]. In a dataset restricted to patients who received cisplatin and gemcitabine with ECOG PS 0 and 1, only haemoglobin, disease status, bilirubin, and neutrophils were associated with PFS and OS. ROC analysis suggested the models generated from the ABC-02 study had a limited prognostic value [6-month PFS: area under the curve (AUC) 62% (95% CI 57-68); 1-year OS: AUC 64% (95% CI 58-69)]. CONCLUSION: These data propose a set of prognostic criteria for outcome in advanced biliary tract cancer derived from the ABC-02 study that are validated in an international dataset. Although these findings establish the benchmark for the prognostic evaluation of patients with ABC and confirm the value of longheld clinical observations, the ability of the model to correctly predict prognosis is limited and needs to be improved through identification of additional clinical and molecular markers.

Helping formulate propositions in forensic DNA analysis

The Bayesian paradigm is the preferred approach to evidence interpretation. It requires the evaluation of the probability of the evidence under at least two propositions. The value of the findings (i.e., our LR) will depend on these propositions and the case information, so it is crucial to identify which propositions are useful for the case at hand. Previously, a number of principles have been advanced and largely accepted for the evaluation of evidence. In the evaluation of traces involving DNA mixtures there may be more than two propositions possible. We apply these principles to some exemplar situations. We also show that in some cases, when there are no clear propositions or no defendant, a forensic scientist may be able to generate explanations to account for observations. In that case, the scientist plays a role of investigator, rather than evaluator. We believe that it is helpful for the scientist to distinguish those two roles.

Advanced chemometric methods: Applicability on industrial data

Recent years have produced great advances in the instrumentation technology. The amount of available data has been increasing due to the simplicity, speed and accuracy of current spectroscopic instruments. Most of these data are, however, meaningless without a proper analysis. This has been one of the reasons for the overgrowing success of multivariate handling of such data. Industrial data is commonly not designed data; in other words, there is no exact experimental design, but rather the data have been collected as a routine procedure during an industrial process. This makes certain demands on the multivariate modeling, as the selection of samples and variables can have an enormous effect. Common approaches in the modeling of industrial data are PCA (principal component analysis) and PLS (projection to latent structures or partial least squares) but there are also other methods that should be considered. The more advanced methods include multi block modeling and nonlinear modeling. In this thesis it is shown that the results of data analysis vary according to the modeling approach used, thus making the selection of the modeling approach dependent on the purpose of the model. If the model is intended to provide accurate predictions, the approach should be different than in the case where the purpose of modeling is mostly to obtain information about the variables and the process. For industrial applicability it is essential that the methods are robust and sufficiently simple to apply. In this way the methods and the results can be compared and an approach selected that is suitable for the intended purpose. Differences in data analysis methods are compared with data from different fields of industry in this thesis. In the first two papers, the multi block method is considered for data originating from the oil and fertilizer industries. The results are compared to those from PLS and priority PLS. The third paper considers applicability of multivariate models to process control for a reactive crystallization process. In the fourth paper, nonlinear modeling is examined with a data set from the oil industry. The response has a nonlinear relation to the descriptor matrix, and the results are compared between linear modeling, polynomial PLS and nonlinear modeling using nonlinear score vectors.

Estimation of lung cancer diagnosis and treatment costs based on a patient-level analysis in Catalonia (Spain)

Background: Assessing of the costs of treating disease is necessary to demonstrate cost-effectiveness and to estimate the budget impact of new interventions and therapeutic innovations. However, there are few comprehensive studies on resource use and costs associated with lung cancer patients in clinical practice in Spain or internationally. The aim of this paper was to assess the hospital cost associated with lung cancer diagnosis and treatment by histology, type of cost and stage at diagnosis in the Spanish National Health Service. Methods: A retrospective, descriptive analysis on resource use and a direct medical cost analysis were performed. Resource utilisation data were collected by means of patient files from nine teaching hospitals. From a hospital budget impact perspective, the aggregate and mean costs per patient were calculated over the first three years following diagnosis or up to death. Both aggregate and mean costs per patient were analysed by histology, stage at diagnosis and cost type. Results: A total of 232 cases of lung cancer were analysed, of which 74.1% corresponded to non-small cell lung cancer (NSCLC) and 11.2% to small cell lung cancer (SCLC); 14.7% had no cytohistologic confirmation. The mean cost per patient in NSCLC ranged from 13,218 Euros in Stage III to 16,120 Euros in Stage II. The main cost components were chemotherapy (29.5%) and surgery (22.8%). Advanced disease stages were associated with a decrease in the relative weight of surgical and inpatient care costs but an increase in chemotherapy costs. In SCLC patients, the mean cost per patient was 15,418 Euros for limited disease and 12,482 Euros for extensive disease. The main cost components were chemotherapy (36.1%) and other inpatient costs (28.7%). In both groups, the Kruskall-Wallis test did not show statistically significant differences in mean cost per patient between stages. Conclusions: This study provides the costs of lung cancer treatment based on patient file reviews, with chemotherapy and surgery accounting for the major components of costs. This cost analysis is a baseline study that will provide a useful source of information for future studies on cost-effectiveness and on the budget impact of different therapeutic innovations in Spain.

Evaluation of sample processing methods for the polar contaminant analysis of sewage sludge using liquid chromatography - mass spectrometry (LC/MS)

Monitoring of sewage sludge has proved the presence of many polar anthropogenic pollutants since LC/MS techniques came into routine use. While advanced techniques may improve characterizations, flawed sample processing procedures, however, may disturb or disguise the presence and fate of many target compounds present in this type of complex matrix before analytical process starts. Freeze-drying or oven-drying, in combination with centrifugation or filtration as sample processing techniques were performed followed by visual pattern recognition of target compounds for assessment of pretreatment processes. The results shown that oven-drying affected the sludge characterization, while freeze-drying led to less analytical misinterpretations.

Comparison Structure Analysis

This study presents an automatic, computer-aided analytical method called Comparison Structure Analysis (CSA), which can be applied to different dimensions of music. The aim of CSA is first and foremost practical: to produce dynamic and understandable representations of musical properties by evaluating the prevalence of a chosen musical data structure through a musical piece. Such a comparison structure may refer to a mathematical vector, a set, a matrix or another type of data structure and even a combination of data structures. CSA depends on an abstract systematic segmentation that allows for a statistical or mathematical survey of the data. To choose a comparison structure is to tune the apparatus to be sensitive to an exclusive set of musical properties. CSA settles somewhere between traditional music analysis and computer aided music information retrieval (MIR). Theoretically defined musical entities, such as pitch-class sets, set-classes and particular rhythm patterns are detected in compositions using pattern extraction and pattern comparison algorithms that are typical within the field of MIR. In principle, the idea of comparison structure analysis can be applied to any time-series type data and, in the music analytical context, to polyphonic as well as homophonic music. Tonal trends, set-class similarities, invertible counterpoints, voice-leading similarities, short-term modulations, rhythmic similarities and multiparametric changes in musical texture were studied. Since CSA allows for a highly accurate classification of compositions, its methods may be applicable to symbolic music information retrieval as well. The strength of CSA relies especially on the possibility to make comparisons between the observations concerning different musical parameters and to combine it with statistical and perhaps other music analytical methods. The results of CSA are dependent on the competence of the similarity measure. New similarity measures for tonal stability, rhythmic and set-class similarity measurements were proposed. The most advanced results were attained by employing the automated function generation – comparable with the so-called genetic programming – to search for an optimal model for set-class similarity measurements. However, the results of CSA seem to agree strongly, independent of the type of similarity function employed in the analysis.

Application of morphometry, static DNA ploidy analysis, and steroid receptor expression in diagnosis and prognosis of Libyan breast cancer

The aim of this study was to describe the demographic, clinicopathological, biological and morphometric features of Libyan breast cancer patients. The supporting value of nuclear morphometry and static image cytometry in the sensitivity for detecting breast cancer in conventional fine-needle aspiration biopsies were estimated. The findings were compared with findings in breast cancer in Finland and Nigeria. In addation, the value of ER and PR were evaluated. There were 131 histological samples, 41 cytological samples, and demographic and clinicopathological data from 234 Libyan patients. The Libyan breast cancer is dominantly premenopausal and in this feature it is similar to breast cancer in sub-Saharan Africans, but clearly different from breast cancer in Europeans, whose cancers are dominantly postmenopausal in character. At presention most Libyan patients have locally advanced disease, which is associated with poor survival rates. Nuclear morphometry and image DNA cytometry agree with earlier published data in the Finnish population and indicate that nuclear size and DNA analysis of nuclear content can be used to increase the cytological sensitivity and specificity in doubtful breast lesions, particularly when free cell sampling method is used. Combination of the morphometric data with earlier free cell data gave the following diagnostic guidelines: Range of overlap in free cell samples: 55 μm2 -71 μm2. Cut-off values for diagnostic purposes: Mean nuclear area (MNA) >54 μm2 for 100% detection of malignant cases (specificity 84 %), MNA < 72 μm2 for 100% detection of benign cases (sensitivity 91%). Histomorphometry showed a significant correlation between the MNA and most clinicopathological features, with the strongest association observed for histological grade (p <0.0001). MNA seems to be a prognosticator in Libyan breast cancer (Pearson’s test r = - 0.29, p = 0.019), but at lower level of significance than in the European material. A corresponding relationship was not found in shape-related morphometric features. ER and PR staining scores were in correlation with the clinical stage (p= 0.017, and 0.015, respectively), and also associated with lymph node negative patients (p=0.03, p=0.05, respectively). Receptor-positive (HR+) patients had a better survival. The fraction of HR+ cases among Libyan breast cancers is about the same as the fraction of positive cases in European breast cancer. The study suggests that also weak staining (corresponding to as few as 1% positive cells) has prognostic value. The prognostic significance may be associated with the practice to use antihormonal therapy in HR+ cases. The low survival and advanced presentation is associated with active cell proliferation, atypical nuclear morphology and aneuploid nuclear DNA content in Libyan breast cancer patients. The findings support the idea that breast cancer is not one type of disease, but should probably be classified into premenopausal and post menopausal types.

Advanced ceramics: evaluation of the mechanism of stock removal and ground surface quality

The aim of this work is to evaluate the mechanism of stock removal and the ground surface quality of advanced ceramics machined by a surface grinding process using diamond grinding wheels. The analysis of the grinding performance was done regarding the cutting surface wear behavior of the grinding wheel for ceramic workpieces. The ground surface was evaluated using Scanning Electron Microscopy (SEM). As a result it can be said that the mechanism of material removal in the grinding of ceramic is largely one of brittle fracture. The increase of the h max can reduce the tangential force required by the process. Although, it results in an increase in the surface damage, reducing the mechanical properties of the ground component.

Validation and Selection of Transportation Cost Drivers with Advanced Methods

In today's logistics environment, there is a tremendous need for accurate cost information and cost allocation. Companies searching for the proper solution often come across with activity-based costing (ABC) or one of its variations which utilizes cost drivers to allocate the costs of activities to cost objects. In order to allocate the costs accurately and reliably, the selection of appropriate cost drivers is essential in order to get the benefits of the costing system. The purpose of this study is to validate the transportation cost drivers of a Finnish wholesaler company and ultimately select the best possible driver alternatives for the company. The use of cost driver combinations as an alternative is also studied. The study is conducted as a part of case company's applied ABC-project using the statistical research as the main research method supported by a theoretical, literature based method. The main research tools featured in the study include simple and multiple regression analyses, which together with the literature and observations based practicality analysis forms the basis for the advanced methods. The results suggest that the most appropriate cost driver alternatives are the delivery drops and internal delivery weight. The possibility of using cost driver combinations is not suggested as their use doesn't provide substantially better results while increasing the measurement costs, complexity and load of use at the same time. The use of internal freight cost drivers is also questionable as the results indicate weakening trend in the cost allocation capabilities towards the end of the period. Therefore more research towards internal freight cost drivers should be conducted before taking them in use.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

A mathematical framework for group analysis of von Willebrand factor multimeric composition following luminography

The objective of the present study was to establish a method for quantitative analysis of von Willebrand factor (vWF) multimeric composition using a mathematical framework based on curve fitting. Plasma vWF multimers from 15 healthy subjects and 13 patients with advanced pulmonary vascular disease were analyzed by Western immunoblotting followed by luminography. Quantitative analysis of luminographs was carried out by calculating the relative densities of low, intermediate and high molecular weight fractions using laser densitometry. For each densitometric peak (representing a given fraction of vWF multimers) a mean area value was obtained using data from all group subjects (patients and normal individuals) and plotted against the distance between the peak and IgM (950 kDa). Curves were constructed for each group using nonlinear fitting. Results indicated that highly accurate curves could be obtained for healthy controls and patients, with respective coefficients of determination (r²) of 0.9898 and 0.9778. Differences were observed between patients and normal subjects regarding curve shape, coefficients and the region of highest protein concentration. We conclude that the method provides accurate quantitative information on the composition of vWF multimers and may be useful for comparisons between groups and possibly treatments.

Productizing of advanced service for power plants

Työn tavoitteena on kehittää ABB:lle palvelutuote, jota voidaan tarjota voimalaitosasiakkaille. Uuden palvelutuotteen tulee vastata ABB:n uuden strategian linjauksiin. Palvelulla tarjotaan asiakkaille 1.1.2015 voimaan tulleen energiatehokkuuslain määrittelemien pakollisten toimenpiteiden suoritusta. Työssä kerätään, käsitellään ja analysoidaan tietoa voimalaitosasiakkaille suunnatun palvelun tuotteistamisprosessin päätöksenteon tueksi. Palvelutuotteen kehittämistä varten tutkitaan ABB:n nykyisiä palvelutuotteita, osaamista ja referenssi projekteja, energiatehokkuuslakia, voimalaitosten energiatehokkuus-potentiaalia ja erilaisia energiakatselmusmalleja. Päätöksenteon tueksi tehdään referenssiprojektina energia-analyysi voimalaitokselle, jossa voimalaitoksesta tehdään ipsePRO simulointiohjelmalla mallinnus. Mallinnuksen ja koeajojen avulla tutkitaan voimalaitoksen minimikuorman optimointia. Markkinatutkimuksessa selvitetään lainsäädännön vaikutusta, nykyistä markkinatilannetta, potentiaalisia asiakkaita, kilpailijoita ja ABB:n mahdollisuuksia toimia alalla SWOT–analyysin avulla. Tutkimuksen tulosten perusteella tehdään päätös tuotteistaa voimalaitoksille palvelutuote, joka sisältää kaikki toimet energiatehokkuuslain asettamien vaatimusten täyttämiseen yrityksen energiakatselmuksen vastuuhenkilön, energiakatselmuksen ja kohdekatselmuksien teon osalta. Lisäksi työn aikana Energiavirasto myönsi ABB:lle pätevyyden toimia yrityksen energiakatselmuksen vastuuhenkilönä, mikä on edellytyksenä palvelun tarjoamiselle.