A prognostic assessment method for power electronics modules

This paper describes a prognostic method which combines the physics of failure models with probability reasoning algorithm. The measured real time data (temperature vs. time) was used as the loading profile for the PoF simulations. The response surface equation of the accumulated plastic strain in the solder interconnect in terms of two variables (average temperature, and temperature amplitude) was constructed. This response surface equation was incorporated into the lifetime model of solder interconnect, and therefore the remaining life time of the solder component under current loading condition was predicted. The predictions from PoF models were also used to calculate the conditional probability table for a Bayesian Network, which was used to take into account of the impacts of the health observations of each product in lifetime prediction. The prognostic prediction in the end was expressed as the probability for the product to survive the expected future usage. As a demonstration, this method was applied to an IGBT power module used for aircraft applications.

Probabilistic approach in weighted Markov branching processes

This note provides a new probabilistic approach in discussing the weighted Markov branching process (WMBP) which is a natural generalisation of the ordinary Markov branching process. Using this approach, some important characteristics regarding the hitting times of such processes can be easily obtained. In particular, the closed forms for the mean extinction time and conditional mean extinction time are presented. The explosion behaviour of the process is investigated and the mean explosion time is derived. The mean global holding time and the mean total survival time are also obtained. The close link between these newly developed processes and the well-known compound Poisson processes is investigated. It is revealed that any weighted Markov branching process (WMBP) is a random time change of a compound Poisson process.

Iron organic speciation determination in rainwater using cathodic stripping voltammetry

A sensitive method using Competitive Ligand Exchange-Adsorptive Cathodic Stripping Voltammetry (CLE-ACSV) has been developed to determine for the first time iron (Fe) organic speciation in rainwater over the typical natural range of pH. We have adapted techniques previously developed in other natural waters to rainwater samples, using the competing ligand 1-nitroso-2-naphthol (NN). The blank was equal to 0.17 ± 0.05 nM (n = 14) and the detection limit (DL) for labile Fe was 0.15 nM which is 10–70 times lower than that of previously published methods. The conditional stability constant for NN under rainwater conditions was calibrated over the pH range 5.52–6.20 through competition with ethylenediaminetetraacetic acid (EDTA). The calculated value of the logarithm of β′Fe3+3(NN)β′Fe3+(NN)3 increased linearly with increasing pH according to log β′Fe3+3(NN)=2.4±0.6×pH+11.9±3.5log β′Fe3+(NN)3=2.4±0.6×pH+11.9±3.5 (salinity = 2.9, T = 20 °C). The validation of the method was carried out using desferrioxamine mesylate B (DFOB) as a natural model ligand for Fe. Adequate detection windows were defined to detect this class of ligands in rainwater with 40 μM of NN from pH 5.52 to 6.20. The concentration of Fe-complexing natural ligands was determined for the first time in three unfiltered and one filtered rainwater samples. Organic Fe-complexing ligand concentrations varied from 104.2 ± 4.1 nM equivalent of Fe(III) to 336.2 ± 19.0 nM equivalent of Fe(III) and the logarithm of the conditional stability constants, with respect to Fe3+, varied from 21.1 ± 0.2 to 22.8 ± 0.3. This method will provide important data for improving our understanding of the role of wet deposition in the biogeochemical cycling of iron.

Joint distributions of waves and rain

The transfer of gases between the atmosphere and ocean is affected by a number of processes, of which wave action and rainfall are two of potential significance. Efforts have been made to quantify separately their contributions; however such assessments neglect the interaction of these phenomena. Here we look at the correlation statistics of waves and rain to note which regions display a strong association between rainfall and the local sea state. The conditional probability of rain varies from ~0.5% to ~15%, with most of the equatorial belt (which contains the ITCZ) showing a greater likelihood of rain at the lowest sea states. In contrast the occurrence of rain is independent of wave height in the Southern Ocean. The 1997/98 El Niño enhances the frequency of rain in some Pacific regions, with this change showing some association with wave conditions.

Improving the performance of a Mediterranean demersal fishery towards societal objectives beyond MSY

Mediterranean demersal fisheries are highly multispecific and many of their target stocks are overexploited. In addition, rocketing fuel costs and low market prices of traditionally high-value species are challenging the viability of fisheries. Here, based on the numeric results of a simulation model, we conclude that this situation can be remedied by reducing both fishing mortality and fishing costs. According to our model results, fishing effort reductions of 48–71% would improve the health of fish stocks while increasing the economic profits of Mallorca islands bottom trawl fishery to as much as 1.9 M€ (146% higher than current profits). If all fish stocks were exploited at their MSY (or below) level, the reduction in fishing effort would have to be of 71% from current values. If equilibrium profits from the fishery were to be maximized (MEY), fishing effort would need to be reduced by 48%. These results must be taken with caution due the many sources of uncertainty of our analysis. The modeling tools used to estimate these values are conditional to the adequate treatment of two sources of uncertainty that are particularly problematic in Mediterranean fisheries: insufficiently known recruitment variability and lack of periodic evaluations of the state of many species. Our results show that fishing effort reductions would produce economic yield gains after a period of transition. Further studies on the benefits of changing the size-selection pattern of fisheries, on better estimation of stock–recruitment relationships and on better quantifications of the contribution of secondary species to these fisheries, are expected to improve the scientific recommendations for Mediterranean demersal fisheries toward sustainability principles.

Improving the performance of a Mediterranean demersal fishery toward economic objectives beyond MSY

Mediterranean demersal fisheries are highly multispecific and many of their target stocks are overexploited. In addition, rocketing fuel costs and low market prices of traditionally high-value species are challenging the viability of fisheries. Here, based on the numeric results of a simulation model, we conclude that this situation can be remedied by reducing both fishing mortality and fishing costs. According to our model results, fishing effort reductions of 48-71% would improve the health of fish stocks while increasing the economic profits of Mallorca islands bottom trawl fishery to as much as 1.9 M(sic) (146% higher than current profits). If all fish stocks were exploited at their MSY (or below) level, the reduction in fishing effort would have to be of 71% from current values. If equilibrium profits from the fishery were to be maximized (MEY), fishing effort would need to be reduced by 48%. These results must be taken with caution due the many sources of uncertainty of our analysis. The modeling tools used to estimate these values are conditional to the adequate treatment of two sources of uncertainty that are particularly problematic in Mediterranean fisheries: insufficiently known recruitment variability and lack of periodic evaluations of the state of many species. Our results show that fishing effort reductions would produce economic yield gains after a period of transition. Further studies on the benefits of changing the size-selection pattern of fisheries, on better estimation of stock recruitment relationships and on better quantifications of the contribution of secondary species to these fisheries, are expected to improve the scientific recommendations for Mediterranean demersal fisheries toward sustainability principles.

Generic, disease-specific and individualised approaches to measuring health-related quality of life among people with heart disease - a comparative analysis.

Increasing emphasis is being placed on the evaluation of health-related quality of life. However, there is no consensus on the definition of this concept and as a result there are a plethora of existing measurement instruments. Head-to-head comparisons of the psychometric properties of existing instruments are necessary to facilitate evidence-based decisions about which instrument should be chosen for routine use. Therefore, an individualised instrument (the modified Patient Generated Index), a generic instrument (the Short Form 36) and a disease-specific instrument (the Quality of Life after Myocardial Infarction questionnaire) were administered to patients with ischaemic heart disease (n=117) and the evidence for the validity, reliability and sensitivity of each instrument was examined and compared. The modified Patient Generated Index compared favourably with the other instruments but none of the instruments examined provided sound evidence for sensitivity to change. Therefore, any recommendation for the use of the individualised approach in the routine collection of health-related quality of life data in clinical practice must be conditional upon the submission of further evidence to support the sensitivity of such instruments.

Addressing Bed Costs for the Elderly: A New Methodology for Modelling Patient Outcomes and Length of Stay

The proportion of elderly in the population has dramatically increased and will continue to do so for at least the next 50 years. Medical resources throughout the world are feeling the added strain of the increasing proportion of elderly in the population. The effective care of elderly patients in hospitals may be enhanced by accurately modelling the length of stay of the patients in hospital and the associated costs involved. This paper examines previously developed models for patient length of stay in hospital and describes the recently developed conditional phase-type distribution (C-Ph) to model patient duration of stay in relation to explanatory patient variables. The Clinics data set was used to demonstrate the C-Ph methodology. The resulting model highlighted a strong relationship between Barthel grade, patient outcome and length of stay showing various groups of patient behaviour. The patients who stay in hospital for a very long time are usually those that consume the largest amount of hospital resources. These have been identified as the patients whose resulting outcome is transfer. Overall, the majority of transfer patients spend a considerably longer period of time in hospital compared to patients who die or are discharged home. The C-Ph model has the potential for considering costs where different costs are attached to the various phases or subgroups of patients and the anticipated cost of care estimated in advance. It is hoped that such a method will lead to the successful identification of the most cost effective case-mix management of the hospital ward.

Learning Bayesian networks from data: An information-theory based approach

This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop efficient algorithms that can effectively learn Bayesian networks, requiring only polynomial numbers of conditional independence (CI) tests in typical cases. We provide precise conditions that specify when these algorithms are guaranteed to be correct as well as empirical evidence (from real world applications and simulation tests) that demonstrates that these systems work efficiently and reliably in practice.

Bolsa Familia Program and school enrolment: An analysis of the 2010 Brazilian demographic census

The Bolsa Família Program goal is to promote social development and poverty reduction, through the direct transfer of conditional cash, in association with other social programs. This study aims to analyze whether Bolsa Família had an association with children’s school attendance, which is one of the educational conditions of the program. Our main hypothesis is that children living in households receiving Bolsa Família had greater chances of attending school. Data from the Ministry of Social Development and Combating Famine indicated that children living in households with Bolsa Família had greater school enrolment levels. By using data from the 2010 Demographic Census, collected by the Brazilian Institute of Geography and Statistics (IBGE), some descriptive analyzes and binary logistic regression models were performed for different thresholds of household per capita income. These estimates were made by comparing children who lived in households receiving Bolsa Família to those children not receiving the program. We took into consideration characteristics about the household, mothers, and children. The results were clustered by the municipality of residence of the child. In all income thresholds, children benefi ting from Bolsa Família were more likely to be enrolled in school, compared to children not receiving the benefi t.

Computerised Diagnostic Decision Support System for the Classification of Pre-Invasive Cervical Squamous Lesions.

Previous studies have revealed considerable interobserver and intraobserver variation in the histological classification of preinvasive cervical squamous lesions. The aim of the present study was to develop a decision support system (DSS) for the histological interpretation of these lesions. Knowledge and uncertainty were represented in the form of a Bayesian belief network that permitted the storage of diagnostic knowledge and, for a given case, the collection of evidence in a cumulative manner that provided a final probability for the possible diagnostic outcomes. The network comprised 8 diagnostic histological features (evidence nodes) that were each independently linked to the diagnosis (decision node) by a conditional probability matrix. Diagnostic outcomes comprised normal; koilocytosis; and cervical intraepithelial neoplasia (CIN) 1, CIN II, and CIN M. For each evidence feature, a set of images was recorded that represented the full spectrum of change for that feature. The system was designed to be interactive in that the histopathologist was prompted to enter evidence into the network via a specifically designed graphical user interface (i-Path Diagnostics, Belfast, Northern Ireland). Membership functions were used to derive the relative likelihoods for the alternative feature outcomes, the likelihood vector was entered into the network, and the updated diagnostic belief was computed for the diagnostic outcomes and displayed. A cumulative probability graph was generated throughout the diagnostic process and presented on screen. The network was tested on 50 cervical colposcopic biopsy specimens, comprising 10 cases each of normal, koilocytosis, CIN 1, CIN H, and CIN III. These had been preselected by a consultant gynecological pathologist. Using conventional morphological assessment, the cases were classified on 2 separate occasions by 2 consultant and 2 junior pathologists. The cases were also then classified using the DSS on 2 occasions by the 4 pathologists and by 2 medical students with no experience in cervical histology. Interobserver and intraobserver agreement using morphology and using the DSS was calculated with K statistics. Intraobserver reproducibility using conventional unaided diagnosis was reasonably good (kappa range, 0.688 to 0.861), but interobserver agreement was poor (kappa range, 0.347 to 0.747). Using the DSS improved overall reproducibility between individuals. Using the DSS, however, did not enhance the diagnostic performance of junior pathologists when comparing their DSS-based diagnosis against an experienced consultant. However, the generation of a cumulative probability graph also allowed a comparison of individual performance, how individual features were assessed in the same case, and how this contributed to diagnostic disagreement between individuals. Diagnostic features such as nuclear pleomorphism were shown to be particularly problematic and poorly reproducible. DSSs such as this therefore not only have a role to play in enhancing decision making but also in the study of diagnostic protocol, education, self-assessment, and quality control. (C) 2003 Elsevier Inc. All rights reserved.

Power-law behaviour, heterogeneity, and trend chasing

Long-range dependence in volatility is one of the most prominent examples in financial market research involving universal power laws. Its characterization has recently spurred attempts to provide some explanations of the underlying mechanism. This paper contributes to this recent line of research by analyzing a simple market fraction asset pricing model with two types of traders---fundamentalists who trade on the price deviation from estimated fundamental value and trend followers whose conditional mean and variance of the trend are updated through a geometric learning process. Our analysis shows that agent heterogeneity, risk-adjusted trend chasing through the geometric learning process, and the interplay of noisy fundamental and demand processes and the underlying deterministic dynamics can be the source of power-law distributed fluctuations. In particular, the noisy demand plays an important role in the generation of insignificant autocorrelations (ACs) on returns, while the significant decaying AC patterns of the absolute returns and squared returns are more influenced by the noisy fundamental process. A statistical analysis based on Monte Carlo simulations is conducted to characterize the decay rate. Realistic estimates of the power-law decay indices and the (FI)GARCH parameters are presented.

Blood-derived dermal langerin+ dendritic cells survey the skin in the steady state.

Langerin is a C-type lectin receptor that recognizes glycosylated patterns on pathogens. Langerin is used to identify human and mouse epidermal Langerhans cells (LCs), as well as migratory LCs in the dermis and the skin draining lymph nodes (DLNs). Using a mouse model that allows conditional ablation of langerin(+) cells in vivo, together with congenic bone marrow chimeras and parabiotic mice as tools to differentiate LC- and blood-derived dendritic cells (DCs), we have revisited the origin of langerin(+) DCs in the skin DLNs. Our results show that in contrast to the current view, langerin(+)CD8(-) DCs in the skin DLNs do not derive exclusively from migratory LCs, but also include blood-borne langerin(+) DCs that transit through the dermis before reaching the DLN. The recruitment of circulating langerin(+) DCs to the skin is dependent on endothelial selectins and CCR2, whereas their recruitment to the skin DLNs requires CCR7 and is independent of CD62L. We also show that circulating langerin(+) DCs patrol the dermis in the steady state and migrate to the skin DLNs charged with skin antigens. We propose that this is an important and previously unappreciated element of immunosurveillance that needs to be taken into account in the design of novel vaccine strategies.

The Macroeconomic Factors Conditioning the Impact of Identity on Attitudes towards the EU

Factors relating to identity and to economics have been shown to be important predictors of attitudes towards the European Union (EU). In this article, we show that the impact of identity is conditional on economic context. First, living in a member state that receives relatively high levels of EU funding acts as a 'buffer', diluting the impact of an exclusive national identity on Euroscepticism. Second, living in a relatively wealthy member state, with its associated attractiveness for economic migrants, increases the salience of economic xenophobia as a driver of sceptical attitudes. These results highlight the importance of seeing theories of attitude formation (such as economic and identity theories) not as competitors but rather as complementary, with the predictive strength of one theoretical approach (identity) being a function of system-level variation in factors relating to the other theoretical approach (macro-level economic conditions).

Semifactual: Byrne's account of even-if

Byrne's approach to the semifactual conditional captures the reasoning data. However, we argue that it does not account for the processes or Principles by which people arrive at representations of even-if conditionals, upon which their reasoning is said to be based. Drawing upon recent work on the suppositional conditional we present such an account.