Algorithm creation and optimization for the crew pairing problem

Algoritmo que optimiza y crea pairings para tripulaciones de líneas aéreas mediante la posterior programación en Java.

A genetic algorithm to ensemble feature selection

We are going to implement the "GA-SEFS" by Tsymbal and analyse experimentally its performance depending on the classifier algorithms used in the fitness function (NB, MNge, SMO). We are also going to study the effect of adding to the fitness function a measure to control complexity of the base classifiers.

Risk assessment of recurrence in sporadic retinoblastoma using a molecular-based algorithm.

PURPOSE: Most RB1 mutations are unique and distributed throughout the RB1 gene. Their detection can be time-consuming and the yield especially low in cases of conservatively-treated sporadic unilateral retinoblastoma (Rb) patients. In order to identify patients with true risk of developing Rb, and to reduce the number of unnecessary examinations under anesthesia in all other cases, we developed a universal sensitive, efficient and cost-effective strategy based on intragenic haplotype analysis. METHODS: This algorithm allows the calculation of the a posteriori risk of developing Rb and takes into account (a) RB1 loss of heterozygosity in tumors, (b) preferential paternal origin of new germline mutations, (c) a priori risk derived from empirical data by Vogel, and (d) disease penetrance of 90% in most cases. We report the occurrence of Rb in first degree relatives of patients with sporadic Rb who visited the Jules Gonin Eye Hospital, Lausanne, Switzerland, from January 1994 to December 2006 compared to expected new cases of Rb using our algorithm. RESULTS: A total of 134 families with sporadic Rb were enrolled; testing was performed in 570 individuals and 99 patients younger than 4 years old were identified. We observed one new case of Rb. Using our algorithm, the cumulated total a posteriori risk of recurrence was 1.77. CONCLUSIONS: This is the first time that linkage analysis has been validated to monitor the risk of recurrence in sporadic Rb. This should be a useful tool in genetic counseling, especially when direct RB1 screening for mutations leaves a negative result or is unavailable.

Treatment algorithm for moderate to severe ulcerative colitis.

The care for a patient with ulcerative colitis (UC) remains challenging despite the fact that morbidity and mortality rates have been considerably reduced during the last 30 years. The traditional management with intravenous corticosteroids was modified by the introduction of ciclosporin and infliximab. In this review, we focus on the treatment of patients with moderate to severe UC. Four typical clinical scenarios are defined and discussed in detail. The treatment recommendations are based on current literature, published guidelines and reviews, and were discussed at a consensus meeting of Swiss experts in the field. Comprehensive treatment algorithms were developed, aimed for daily clinical practice.

Algorithm optimization for solving crew scheduling problems

In this paper, we are proposing a methodology to determine the most efficient and least costly way of crew pairing optimization. We are developing a methodology based on algorithm optimization on Eclipse opensource IDE using the Java programming language to solve the crew scheduling problems.

Age above 60 years is not a negative predictive factor for combined antiviral therapy with pegylated interferon alpha and ribavirin in hepatitis C patients

Background: Age is frequently discussed as negative host factor to achieve a sustained virological response (SVR) to antiviral hepatitis C therapy. However, elderly patients often show relevant fibrosis or cirrhosis which is a known negative predictive factor, making it difficult to interpret age as an independent predictive factor. Methods: From the framework of the Swiss hepatitis C cohort (SCCS), we collected data from 545 antiviral hepatitis C therapies, including data from 67 hepatitis C patients ≥ 60 y who had been treated with PEG-interferon and ribavirin. We analyzed host factors (age, gender, fibrosis, haemoglobin, depression, earlier hepatitis C treatment), viral factors (genotype, viral load) and treatment course (early virological response, end of treatment response, SVR). Generalised estimating equations (GEE) regression modelling was used for the primary end point (SVR), with age ≥ 60 y and < 60 y as independent variable and gender, presence of cirrhosis, genotype, earlier treatment and viral load as confounders. SVR was analysed in young and elderly patients after matching for these confounders. Additionally, classification tree analysis was done in elderly patients using these confounders. Results: SVR analyzed in 545 patients was 55%. In genotype 1/4, SVR was 42.9% in 259 patients < 60 y and 26.1% in 46 patients ≥ 60 y. In genotype 2/3, SVR was 74.4% in 215 patients < 60 y and 84% in 25 patients ≥ 60 y. However, GEE model showed that age had no influence on achieving SVR (Odds ratio 0.91). Confounders influenced SVR as known from previous studies (cirrhosis, genotype 1/4, previous treatment and viral load >600'000 IE/ml as negative predictive factors). When young and elderly patients were matched (analysis in 59 elderly patients), SVR was not different in these patient groups (54.2% and 55.9%, resp.; p=0.795 in binomial test). The classification tree-derived best criterion for SVR in elderly patients was genotype, with no further criteria relevant for predicting SVR in genotype 2/3. In patients with genotype 1/4, further criteria were presence of cirrhosis and low viral load <600'000 IE/ml in non-cirrhotic patients. Conclusions: Age is not a relevant predictive factor for achieving SVR, when confounders were taken into account. In terms of effectiveness of antiviral therapy, age does not play a major role and should not be regarded as relevant negative predictive factor. Since life expectancy in Switzerland at age 60 is more than 22 y, hepatitis C therapy is reasonable in elderly patients with known relevant fibrosis or cirrhosis, because interferon-based hepatitis C therapy improves survival and reduces carcinogenesis.

Development and validation of AMANDA, a new algorithm for selecting highly relevant regions in Molecular Interaction Fields

Descriptors based on Molecular Interaction Fields (MIF) are highly suitable for drug discovery, but their size (thousands of variables) often limits their application in practice. Here we describe a simple and fast computational method that extracts from a MIF a handful of highly informative points (hot spots) which summarize the most relevant information. The method was specifically developed for drug discovery, is fast, and does not require human supervision, being suitable for its application on very large series of compounds. The quality of the results has been tested by running the method on the ligand structure of a large number of ligand-receptor complexes and then comparing the position of the selected hot spots with actual atoms of the receptor. As an additional test, the hot spots obtained with the novel method were used to obtain GRIND-like molecular descriptors which were compared with the original GRIND. In both cases the results show that the novel method is highly suitable for describing ligand-receptor interactions and compares favorably with other state-of-the-art methods.

A systolic array for linear MIMO detection based on an all-swap lattice reduction algorithm

A systolic array to implement lattice-reduction-aided lineardetection is proposed for a MIMO receiver. The lattice reductionalgorithm and the ensuing linear detections are operated in the same array, which can be hardware-efficient. All-swap lattice reduction algorithm (ASLR) is considered for the systolic design.ASLR is a variant of the LLL algorithm, which processes all lattice basis vectors within one iteration. Lattice-reduction-aided linear detection based on ASLR and LLL algorithms have very similarbit-error-rate performance, while ASLR is more time efficient inthe systolic array, especially for systems with a large number ofantennas.

Valeur prédictive de la surexpression/ amplification de Her2/neu pour un traitement ciblé du cancer du sein [Predictive value of Her2/neu expression/amplification for the targeted treatment of breast cancer]

Her2/neu is a tyrosine kinase receptor which stimulates cell growth. The receptor is overexpressed in about 20% of breast cancers. Her2/neu expression is an indicator of poor prognosis but also the target of the treatment of breast cancer using humanised anti-Her2/ neu antibodies. Only cancers overexpressing the protein will respond to this therapy, but which has significant (cardiac) side effects and is expensive. It is therefore important to test for the overexpression of the protein on breast cancer cells. This paper discusses how this can be done and ongoing research into new therapeutic options targeting the involved signaling pathways.

ILS-ESP An efficient, simple, and parameter-free algorithm for solving the permutation flow-shop problem

From a managerial point of view, the more effcient, simple, and parameter-free (ESP) an algorithm is, the more likely it will be used in practice for solving real-life problems. Following this principle, an ESP algorithm for solving the Permutation Flowshop Sequencing Problem (PFSP) is proposed in this article. Using an Iterated Local Search (ILS) framework, the so-called ILS-ESP algorithm is able to compete in performance with other well-known ILS-based approaches, which are considered among the most effcient algorithms for the PFSP. However, while other similar approaches still employ several parameters that can affect their performance if not properly chosen, our algorithm does not require any particular fine-tuning process since it uses basic "common sense" rules for the local search, perturbation, and acceptance criterion stages of the ILS metaheuristic. Our approach defines a new operator for the ILS perturbation process, a new acceptance criterion based on extremely simple and transparent rules, and a biased randomization process of the initial solution to randomly generate different alternative initial solutions of similar quality -which is attained by applying a biased randomization to a classical PFSP heuristic. This diversification of the initial solution aims at avoiding poorly designed starting points and, thus, allows the methodology to take advantage of current trends in parallel and distributed computing. A set of extensive tests, based on literature benchmarks, has been carried out in order to validate our algorithm and compare it against other approaches. These tests show that our parameter-free algorithm is able to compete with state-of-the-art metaheuristics for the PFSP. Also, the experiments show that, when using parallel computing, it is possible to improve the top ILS-based metaheuristic by just incorporating to it our biased randomization process with a high-quality pseudo-random number generator.

Testing the predictive adaptive response in a host-parasite system

1. Harsh environmental conditions experienced during development can reduce the performance of the same individuals in adulthood. However, the 'predictive adaptive response' hypothesis postulates that if individuals adapt their phenotype during development to the environments where they are likely to live in the future, individuals exposed to harsh conditions in early life perform better when encountering the same harsh conditions in adulthood compared to those never exposed to these conditions before. 2. Using the common vole (Microtus arvalis) as study organism, we tested how exposure to flea parasitism during the juvenile stage affects the physiology (haematocrit, resistance to oxidative stress, resting metabolism, spleen mass, and testosterone), morphology (body mass, testis mass) and motor performance (open field activity and swimming speed) of the same individuals when infested with fleas in adulthood. According to the 'predictive adaptive response' hypothesis, we predicted that voles parasitized at the adult stage would perform better if they had already been parasitized with fleas at the juvenile stage. 3. We found that voles exposed to fleas in adulthood had a higher metabolic rate if already exposed to fleas when juvenile, compared to voles free of fleas when juvenile and voles free of fleas in adulthood. Independently of juvenile parasitism, adult parasitism impaired adult haematocrit and motor performances. Independently of adult parasitism, juvenile parasitism slowed down crawling speed in adult female voles. 4. Our results suggest that juvenile parasitism has long-term effects that do not protect from the detrimental effects of adult parasitism. On the contrary, experiencing parasitism in early-life incurs additional costs upon adult parasitism measured in terms of higher energy expenditure, rather than inducing an adaptive shift in the developmental trajectory. 5. Hence, our study provides experimental evidence for long term costs of parasitism. We found no support for a predictive adaptive response in this host-parasite system.

Validation of the potentially avoidable hospital readmission rate as a routine indicator of the quality of hospital care

BACKGROUND: The hospital readmission rate has been proposed as an important outcome indicator computable from routine statistics. However, most commonly used measures raise conceptual issues. OBJECTIVES: We sought to evaluate the usefulness of the computerized algorithm for identifying avoidable readmissions on the basis of minimum bias, criterion validity, and measurement precision. RESEARCH DESIGN AND SUBJECTS: A total of 131,809 hospitalizations of patients discharged alive from 49 hospitals were used to compare the predictive performance of risk adjustment methods. A subset of a random sample of 570 medical records of discharge/readmission pairs in 12 hospitals were reviewed to estimate the predictive value of the screening of potentially avoidable readmissions. MEASURES: Potentially avoidable readmissions, defined as readmissions related to a condition of the previous hospitalization and not expected as part of a program of care and occurring within 30 days after the previous discharge, were identified by a computerized algorithm. Unavoidable readmissions were considered as censored events. RESULTS: A total of 5.2% of hospitalizations were followed by a potentially avoidable readmission, 17% of them in a different hospital. The predictive value of the screen was 78%; 27% of screened readmissions were judged clearly avoidable. The correlation between the hospital rate of clearly avoidable readmission and all readmissions rate, potentially avoidable readmissions rate or the ratio of observed to expected readmissions were respectively 0.42, 0.56 and 0.66. Adjustment models using clinical information performed better. CONCLUSION: Adjusted rates of potentially avoidable readmissions are scientifically sound enough to warrant their inclusion in hospital quality surveillance.

Bioclimatic constraints to Andean cat distribution: a modelling application for rare species

AimTo identify the bioclimatic niche of the endangered Andean cat (Leopardus jacobita), one of the rarest and least known felids in the world, by developing a species distribution model.LocationSouth America, High Andes and Patagonian steppe. Peru, Bolivia, Chile, Argentina.MethodsWe used 108 Andean cat records to build the models, and 27 to test them, applying the Maxent algorithm to sets of uncorrelated bioclimatic variables from global databases, including elevation. We based our biogeographical interpretations on the examination of the predicted geographic range, the modelled response curves and latitudinal variations in climatic variables associated with the locality data.ResultsSimple bioclimatic models for Andean cats were highly predictive with only 3-4 explanatory variables. The climatic niche of the species was defined by extreme diurnal variations in temperature, cold minimum and moderate maximum temperatures, and aridity, characteristic not only of the Andean highlands but also of the Patagonian steppe. Argentina had the highest representation of suitable climates, and Chile the lowest. The most favourable conditions were centrally located and spanned across international boundaries. Discontinuities in suitable climatic conditions coincided with three biogeographical barriers associated with climatic or topographic transitions.Main conclusionsSimple bioclimatic models can produce useful predictions of suitable climatic conditions for rare species, including major biogeographical constraints. In our study case, these constraints are also known to affect the distribution of other Andean species and the genetic structure of Andean cat populations. We recommend surveys of areas with suitable climates and no Andean cat records, including the corridor connecting two core populations. The inclusion of landscape variables at finer scales, crucially the distribution of Andean cat prey, would contribute to refine our predictions for conservation applications.

Predictive factors of adrenal insufficiency in patients admitted to acute medical wards: a case control study.

BACKGROUND: Adrenal insufficiency is a rare and potentially lethal disease if untreated. Several clinical signs and biological markers are associated with glucocorticoid failure but the importance of these factors for diagnosing adrenal insufficiency is not known. In this study, we aimed to assess the prevalence of and the factors associated with adrenal insufficiency among patients admitted to an acute internal medicine ward. METHODS: Retrospective, case-control study including all patients with high-dose (250 μg) ACTH-stimulation tests for suspected adrenal insufficiency performed between 2008 and 2010 in an acute internal medicine ward (n = 281). Cortisol values <550 nmol/l upon ACTH-stimulation test were considered diagnostic for adrenal insufficiency. Area under the ROC curve (AROC), sensitivity, specificity, negative and positive predictive values for adrenal insufficiency were assessed for thirteen symptoms, signs and biological variables. RESULTS: 32 patients (11.4%) presented adrenal insufficiency; the others served as controls. Among all clinical and biological parameters studied, history of glucocorticoid withdrawal was the only independent factor significantly associated with patients with adrenal insufficiency (Odds Ratio: 6.71, 95% CI: 3.08 -14.62). Using a logistic regression, a model with four significant and independent variable was obtained, regrouping history of glucocorticoid withdrawal (OR 7.38, 95% CI [3.18 ; 17.11], p-value <0.001), nausea (OR 3.37, 95% CI [1.03 ; 11.00], p-value 0.044), eosinophilia (OR 17.6, 95% CI [1.02; 302.3], p-value 0.048) and hyperkalemia (OR 2.41, 95% CI [0.87; 6.69], p-value 0.092). The AROC (95% CI) was 0.75 (0.70; 0.80) for this model, with 6.3 (0.8 - 20.8) for sensitivity and 99.2 (97.1 - 99.9) for specificity. CONCLUSIONS: 11.4% of patients with suspected adrenal insufficient admitted to acute medical ward actually do present with adrenal insufficiency, defined by an abnormal response to high-dose (250 μg) ACTH-stimulation test. A history of glucocorticoid withdrawal was the strongest factor predicting the potential adrenal failure. The combination of a history of glucocorticoid withdrawal, nausea, eosinophilia and hyperkaliemia might be of interest to suspect adrenal insufficiency.