Un modelo de predicción de la insolvencia empresarial basado en variables financieras. Su aplicación al caso textil catalán (1994-1997)

En este documento se formula un modelo de predicción de la insolvencia a través de la combinación de diferentes variables cuantitativas extraídas de los estados contables de una muestra de empresas para los años 1994-1997. Partiendo del modelo de flexibilidad financiera de Donaldson, que es adaptado por Van Frederikslust a la predicción de la insolvencia, lo que aquí se expone es una aplicación a una muestra de empresas de los sectores textil y confección. Aunque los resultados no son alentadores, lo más importante es destacar cómo a través de una modelización de este tipo, probamos una formulación teórica del problema.

Prediction of preeclampsia by means of Doppler flowmetry of uterine artery and flow-mediated dilation of brachial artery

Objective To evaluate the association of Doppler of uterine artery and flow-mediated dilation of brachial artery (FMD) in the assessment of placental perfusion and endothelial function to predict preeclampsia. Materials and Methods A total of 91 patients considered as at risk for developing preeclampsia were recruited at the prenatal unit of the authors' institution. All the patients underwent FMD and Doppler of uterine arteries between their 24th and 28th gestational weeks. Calculations of sensitivity and specificity for both isolated and associated methods were performed. Results Nineteen out of the 91 patients developed preeclampsia, while the rest remained normotensive. Doppler flowmetry of uterine arteries with presence of bilateral protodiastolic notch had sensitivity of 63.1% and specificity of 87.5% for the prediction of preeclampsia. Considering a cutoff value of 6.5%, FMD showed sensitivity of 84.2% and specificity of 73.6%. In a parallel analysis, as the two methods were associated, sensitivity was 94.2% and specificity, 64.4%. Conclusion The association of Doppler study of uterine arteries and FMD has proved to be an interesting clinical strategy for the prediction of preeclampsia, which may represent a positive impact on prenatal care of patients considered as at high-risk for developing such a condition.

A Meta-Analysis of Trabecular Bone Score in Fracture Risk Prediction and Its Relationship to FRAX.

Trabecular bone score (TBS) is a gray-level textural index of bone microarchitecture derived from lumbar spine dual-energy X-ray absorptiometry (DXA) images. TBS is a bone mineral density (BMD)-independent predictor of fracture risk. The objective of this meta-analysis was to determine whether TBS predicted fracture risk independently of FRAX probability and to examine their combined performance by adjusting the FRAX probability for TBS. We utilized individual-level data from 17,809 men and women in 14 prospective population-based cohorts. Baseline evaluation included TBS and the FRAX risk variables, and outcomes during follow-up (mean 6.7 years) comprised major osteoporotic fractures. The association between TBS, FRAX probabilities, and the risk of fracture was examined using an extension of the Poisson regression model in each cohort and for each sex and expressed as the gradient of risk (GR; hazard ratio per 1 SD change in risk variable in direction of increased risk). FRAX probabilities were adjusted for TBS using an adjustment factor derived from an independent cohort (the Manitoba Bone Density Cohort). Overall, the GR of TBS for major osteoporotic fracture was 1.44 (95% confidence interval [CI] 1.35-1.53) when adjusted for age and time since baseline and was similar in men and women (p > 0.10). When additionally adjusted for FRAX 10-year probability of major osteoporotic fracture, TBS remained a significant, independent predictor for fracture (GR = 1.32, 95% CI 1.24-1.41). The adjustment of FRAX probability for TBS resulted in a small increase in the GR (1.76, 95% CI 1.65-1.87 versus 1.70, 95% CI 1.60-1.81). A smaller change in GR for hip fracture was observed (FRAX hip fracture probability GR 2.25 vs. 2.22). TBS is a significant predictor of fracture risk independently of FRAX. The findings support the use of TBS as a potential adjustment for FRAX probability, though the impact of the adjustment remains to be determined in the context of clinical assessment guidelines. © 2015 American Society for Bone and Mineral Research.

Prediction of Antibacterial Activity from Physicochemical Properties of Antimicrobial Peptides

Consensus is gathering that antimicrobial peptides that exert their antibacterial action at the membrane level must reach a local concentration threshold to become active. Studies of peptide interaction with model membranes do identify such disruptive thresholds but demonstrations of the possible correlation of these with the in vivo onset of activity have only recently been proposed. In addition, such thresholds observed in model membranes occur at local peptide concentrations close to full membrane coverage. In this work we fully develop an interaction model of antimicrobial peptides with biological membranes; by exploring the consequences of the underlying partition formalism we arrive at a relationship that provides antibacterial activity prediction from two biophysical parameters: the affinity of the peptide to the membrane and the critical bound peptide to lipid ratio. A straightforward and robust method to implement this relationship, with potential application to high-throughput screening approaches, is presented and tested. In addition, disruptive thresholds in model membranes and the onset of antibacterial peptide activity are shown to occur over the same range of locally bound peptide concentrations (10 to 100 mM), which conciliates the two types of observations

Reduced ceria nanofilms from structure prediction

Experimentally, Ce2O3 films are used to study cerium oxide in its fully or partially reduced state, as present in many applications. We have explored the space of low energy Ce2O3 nanofilms using structure prediction and density functional calculations, yielding more than 30 distinct nanofilm structures. First, our results help to rationalize the roles of thermodynamics and kinetics in the preparation of reduced ceria nanofilms with different bulk crystalline structures (e.g. A-type or bixbyite) depending on the support used. Second, we predict a novel, as yet experimentally unresolved, nanofilm which has a structure that does not correspond to any previously reported bulk A2B3 phase and which has an energetic stability between that of A-type and bixbyite. To assist identification and fabrication of this new Ce2O3 nanofilm we calculate some observable properties and propose supports for its epitaxial growth.

Virus Infections in Early Childhood, Cow’s Milk Formula Exposure and Genetic Predisposition in the Development of Diabetes-Associated Autoimmunity

Varhaislapsuuden virusinfektioiden, lehmänmaitopohjaisen äidinmaitovastikeen ja geneettisen alttiuden merkitys diabetekseen liittyvän autoimmuniteetin kehittymisessä Tyypin 1 diabetes on autoimmuunisairaus, joka syntyy haiman insuliinia tuottavien beta-solujen tuhouduttua elimistön oman immuunipuolustusjärjestelmän hyökkäyksen seurauksena. Sekä perimän että ympäristötekijöiden arvellaan vaikuttavan tautiprosessiin, mutta taudin tarkkaa syntymekanismia ei tunneta. Tutkimuksen tarkoituksena oli selvittää varhaislapsuuden ympäristötekijöiden vaikutusta beta-soluautoimmuniteetin syntyyn, erityispaino tutkimuksessa oli ympäristötekijöiden yhteisvaikutuksessa sekä geneettisten riskitekijöiden ja ympäristötekijöiden vuorovaikutuksessa. Varhaislapsuudessa sairastettu sytomegalovirus- tai enterovirusinfektio ei lisännyt beta-soluautoimmuniteetin riskiä lapsilla, joilla on geneettisesti kohonnut riski sairastua tyypin 1 diabetekseen. Ennen puolen vuoden ikää sairastettu rotavirusinfektio lisäsi hieman tyypin 1 diabetekseen liittyvän autoimmuniteetin riskiä. Tarkemmassa analyysissa varhaislapsuuden enterovirusinfektio osoittautui kuitenkin autovasta-aineiden muodostumisen riskitekijäksi niiden lasten joukossa, jotka olivat saaneet lehmänmaitopohjaista äidinmaidon vastiketta ensimmäisten elinkuukausien aikana. Tämä löydös viittaa enterovirusinfektion ja lehmänmaitopohjaisen vastikkeen yhteisvaikutukseen tyypin 1 diabetekseen liittyvän autoimmuniteetin synnyssä. Löydösten mukaan PTPN22 geenin C1858T polymorfismi vaikuttaa CD4+ T solujen aktivaatioon ja proliferaatiovasteeseen, 1858T alleeliin liittyy alentunut T-soluresepto-rivälitteinen aktivaatio. 1858T alleelin kantajuuteen liittyy lisäksi lisääntynyt autovasta-aineiden ja kliinisen diabeteksen ilmaantuvuus. Tämä yhteys rajoittui yksilöihin, jotka olivat altistuneet lehmänmaitopohjaiselle vastikkeelle ennen kuuden kuukauden ikää. Tulosten mukaan sekä ympäristötekijöiden väliset yhteisvaikutukset että perimä vaikuttavat yksittäisen ympäristötekijän merkitykseen tyypin 1 diabetekseen liittyvän autoimmuniteetin synnyssä. Nämä yhteisvaikutukset ympäristötekijöiden kesken ja perimän ja ympäristötekijöiden välillä selittävät aiemmin julkaistujen tulosten ristiriittaisuutta tutkimuksissa, joissa on analysoitu vain yhden ympäristötekijän vaikutusta diabeteksen ilmaantuvuuteen.

Prediction of individual automobile RBNS claim reserves in the context of Solvency II

Automobile bodily injury (BI) claims remain unsettled for a long time after the accident. The estimation of an accurate reserve for Reported But Not Settled (RBNS) claims is therefore vital for insurers. In accordance with the recommendation included in the Solvency II project (CEIOPS, 2007) a statistical model is here implemented for RBNS reserve estimation. Lognormality on empirical compensation cost data is observed for different levels of BI severity. The individual claim provision is estimated by allocating the expected mean compensation for the predicted severity of the victim’s injury, for which the upper bound is also computed. The BI severity is predicted by means of a heteroscedastic multiple choice model, because empirical evidence has found that the variability in the latent severity of injured individuals travelling by car is not constant. It is shown that this methodology can improve the accuracy of RBNS reserve estimation at all stages, as compared to the subjective assessment that has traditionally been made by practitioners.

Minimization of the experimental workload for the prediction of pollutants propagation in rivers. Mathematical modelling and knowledge re-use

The present thesis in focused on the minimization of experimental efforts for the prediction of pollutant propagation in rivers by mathematical modelling and knowledge re-use. Mathematical modelling is based on the well known advection-dispersion equation, while the knowledge re-use approach employs the methods of case based reasoning, graphical analysis and text mining. The thesis contribution to the pollutant transport research field consists of: (1) analytical and numerical models for pollutant transport prediction; (2) two novel techniques which enable the use of variable parameters along rivers in analytical models; (3) models for the estimation of pollutant transport characteristic parameters (velocity, dispersion coefficient and nutrient transformation rates) as functions of water flow, channel characteristics and/or seasonality; (4) the graphical analysis method to be used for the identification of pollution sources along rivers; (5) a case based reasoning tool for the identification of crucial information related to the pollutant transport modelling; (6) and the application of a software tool for the reuse of information during pollutants transport modelling research. These support tools are applicable in the water quality research field and in practice as well, as they can be involved in multiple activities. The models are capable of predicting pollutant propagation along rivers in case of both ordinary pollution and accidents. They can also be applied for other similar rivers in modelling of pollutant transport in rivers with low availability of experimental data concerning concentration. This is because models for parameter estimation developed in the present thesis enable the calculation of transport characteristic parameters as functions of river hydraulic parameters and/or seasonality. The similarity between rivers is assessed using case based reasoning tools, and additional necessary information can be identified by using the software for the information reuse. Such systems represent support for users and open up possibilities for new modelling methods, monitoring facilities and for better river water quality management tools. They are useful also for the estimation of environmental impact of possible technological changes and can be applied in the pre-design stage or/and in the practical use of processes as well.

De formula: Dei gratia, principum titulis adjici solita

Invocatio: I.N.D.O.M.

Application of GA-PLS and GA-KPLS calculations for the prediction of the retention indices of essential oils

Genetic algorithm and partial least square (GA-PLS) and kernel PLS (GA-KPLS) techniques were used to investigate the correlation between retention indices (RI) and descriptors for 117 diverse compounds in essential oils from 5 Pimpinella species gathered from central Turkey which were obtained by gas chromatography and gas chromatography-mass spectrometry. The square correlation coefficient leave-group-out cross validation (LGO-CV) (Q²) between experimental and predicted RI for training set by GA-PLS and GA-KPLS was 0.940 and 0.963, respectively. This indicates that GA-KPLS can be used as an alternative modeling tool for quantitative structure-retention relationship (QSRR) studies.

Models and applications for risk assessment and prediction of Asian soybean rust epidemics

Asian rust of soybean [Glycine max (L.) Merril] is one of the most important fungal diseases of this crop worldwide. The recent introduction of Phakopsora pachyrhizi Syd. & P. Syd in the Americas represents a major threat to soybean production in the main growing regions, and significant losses have already been reported. P. pachyrhizi is extremely aggressive under favorable weather conditions, causing rapid plant defoliation. Epidemiological studies, under both controlled and natural environmental conditions, have been done for several decades with the aim of elucidating factors that affect the disease cycle as a basis for disease modeling. The recent spread of Asian soybean rust to major production regions in the world has promoted new development, testing and application of mathematical models to assess the risk and predict the disease. These efforts have included the integration of new data, epidemiological knowledge, statistical methods, and advances in computer simulation to develop models and systems with different spatial and temporal scales, objectives and audience. In this review, we present a comprehensive discussion on the models and systems that have been tested to predict and assess the risk of Asian soybean rust. Limitations, uncertainties and challenges for modelers are also discussed.

Ohutlevytuotteen valmistuskustannusten määrittely suunnitteluvaiheessa

Diplomityössä kehitetään ABB Oy Drives:lle menetelmää, jolla voidaan ennustaa ohutlevyosien ja niistä koostuvien kokoonpanojen hintaa ilman tarkkaa valmistuksellista geometriatietoa. Työ on osa Tekesin rahoittamaa Piirre 2.0 -projektia. Työn teoriaosa määrittelee lyhyesti ohutlevytuotteet ja niiden valmistusmenetelmät. Laajemmassa teoriatarkastelussa ovat erilaiset ohutlevytuotteiden valmistuskustannusten ennustamismenetelmät regressioanalyysin käyttöön painottuen. Käytännön osiossa määritetään Finn-Power LP6 -levytyökeskuksen suorituskyky ja muodostetaan työaikalaskuri kerättyyn tietoon perustuen. Lisäksi muodostetaan regressioanalyysit kahden eri alihankkijan valmistamien ohutlevytuotteiden pohjalta. Regressiotekniikoiden avulla etsitään kustannuksiin voimakkaasti vaikuttavat parametrit ja muodostetaan laskukaava valmistuskustannusten ennustamiseen. Lopuksi vertaillaan teorian ja käytännön osien yhteensopivuutta ja etsitään syitä havaittuihin eroihin. Tutkimustulosten hyödyntämismahdollisuuksien ohella esitetään myös eräitä jatkokehitysehdotuksia.

Comparação de taxas de erosão em estradas florestais estimadas pelo modelo WEPP (Water Erosion Prediction Project) modificado em relção a medições experimentais

O objetivo do trabalho foi testar o modelo WEPP (Water Erosion Prediction Project), através de comparações entre volume de enxurrada e perda de solo observados experimentalmente, provenientes dos segmentos de estradas florestais submetidas à chuva natural com inclinações de 1 e 7% e comprimentos de rampa de 20 e 40 m, e aqueles preditos pelo aplicativo, visando o desenvolvimento de um modelo brasileiro de predição de erosão em estradas florestais. Na determinação da quantidade do material erodido foram instalados tambores coletores, com capacidade de 209,25 litros, localizados na parte inferior das estradas, onde foram inseridas tubulações de PVC de 2 polegadas para coleta dos sedimentos provenientes da estrada propriamente dita. Nos tambores coletores foram feitos orifícios nivelados e perfeitamente iguais, posicionados a 0,65 m do fundo do primeiro e a 0,60 m do fundo do segundo, que funcionaram como um divisor Geib. Nas parcelas de 20 e 40 m de comprimento foram feitos cinco e sete orifícios, respectivamente, no primeiro e segundo tambores. O terceiro tambor foi utilizado para coletar o excedente da enxurrada proveniente do segundo tambor. Os tambores foram ligados em série, através de cano PVC de 2 polegadas. Os dados de volume e intensidade de precipitação diária foram obtidos com a instalação de pluviômetro e pluviógrafo no local. O período de coleta de dados foi de um ano, concentrando-se na época das chuvas. Posteriormente, os arquivos de clima, precipitação, solo, inclinação e comprimento do segmento foram introduzidos e adaptados ao modelo de predição de erosão WEPP com o propósito de testá-lo, visando a confecção de um modelo apropriado às condições brasileiras.