Local model predictive control experiences with differential driven wheeled mobile robots

This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields

Mobile Robot Local Predictive Control under Perception Constraints

This research extends a previously developed work concerning about the use of local model predictive control in mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The platformused is a differential driven robot with a free rotating wheel. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are also introduced. In this sense, monocular image data provide an occupancy grid where safety trajectories are computed by using goal attraction potential fields

Color differences among feral pigeons (Columba livia) are not attributable to sequence variation in the coding region of the melanocortin-1 receptor gene (MC1R)

Genetic variation at the melanocortin-1 receptor (MC1R) gene is correlated with melanin color variation in many birds. Feral pigeons (Columba livia) show two major melanin-based colorations: a red coloration due to pheomelanic pigment and a black coloration due to eumelanic pigment. Furthermore, within each color type, feral pigeons display continuous variation in the amount of melanin pigment present in the feathers, with individuals varying from pure white to a full dark melanic color. Coloration is highly heritable and it has been suggested that it is under natural or sexual selection, or both. Our objective was to investigate whether MC1R allelic variants are associated with plumage color in feral pigeons.We sequenced 888 bp of the coding sequence of MC1R among pigeons varying both in the type, eumelanin or pheomelanin, and the amount of melanin in their feathers. We detected 10 non-synonymous substitutions and 2 synonymous substitution but none of them were associated with a plumage type. It remains possible that non-synonymous substitutions that influence coloration are present in the short MC1R fragment that we did not sequence but this seems unlikely because we analyzed the entire functionally important region of the gene.Our results show that color differences among feral pigeons are probably not attributable to amino acid variation at the MC1R locus. Therefore, variation in regulatory regions of MC1R or variation in other genes may be responsible for the color polymorphism of feral pigeons.

Measuring potentially avoidable hospital readmissions.

The objectives of this study were to develop a computerized method to screen for potentially avoidable hospital readmissions using routinely collected data and a prediction model to adjust rates for case mix. We studied hospital information system data of a random sample of 3,474 inpatients discharged alive in 1997 from a university hospital and medical records of those (1,115) readmitted within 1 year. The gold standard was set on the basis of the hospital data and medical records: all readmissions were classified as foreseen readmissions, unforeseen readmissions for a new affection, or unforeseen readmissions for a previously known affection. The latter category was submitted to a systematic medical record review to identify the main cause of readmission. Potentially avoidable readmissions were defined as a subgroup of unforeseen readmissions for a previously known affection occurring within an appropriate interval, set to maximize the chance of detecting avoidable readmissions. The computerized screening algorithm was strictly based on routine statistics: diagnosis and procedures coding and admission mode. The prediction was based on a Poisson regression model. There were 454 (13.1%) unforeseen readmissions for a previously known affection within 1 year. Fifty-nine readmissions (1.7%) were judged avoidable, most of them occurring within 1 month, which was the interval used to define potentially avoidable readmissions (n = 174, 5.0%). The intra-sample sensitivity and specificity of the screening algorithm both reached approximately 96%. Higher risk for potentially avoidable readmission was associated with previous hospitalizations, high comorbidity index, and long length of stay; lower risk was associated with surgery and delivery. The model offers satisfactory predictive performance and a good medical plausibility. The proposed measure could be used as an indicator of inpatient care outcome. However, the instrument should be validated using other sets of data from various hospitals.

A Gain Scheduling Model Predictive Controller for Blood Glucose Control in Type 1 Diabetes

This paper presents a control strategy for blood glucose(BG) level regulation in type 1 diabetic patients. To design the controller, model-based predictive control scheme has been applied to a newly developed diabetic patient model. The controller is provided with a feedforward loop to improve meal compensation, a gain-scheduling scheme to account for different BG levels, and an asymmetric cost function to reduce hypoglycemic risk. A simulation environment that has been approved for testing of artificial pancreas control algorithms has been used to test thecontroller. The simulation results show a good controller performance in fasting conditions and meal disturbance rejection, and robustness against model–patient mismatch and errors in mealestimation

On the tractability of the piecewise-linear approximation for general discrete-choice network revenue management

The choice network revenue management (RM) model incorporates customer purchase behavioras customers purchasing products with certain probabilities that are a function of the offeredassortment of products, and is the appropriate model for airline and hotel network revenuemanagement, dynamic sales of bundles, and dynamic assortment optimization. The underlyingstochastic dynamic program is intractable and even its certainty-equivalence approximation, inthe form of a linear program called Choice Deterministic Linear Program (CDLP) is difficultto solve in most cases. The separation problem for CDLP is NP-complete for MNL with justtwo segments when their consideration sets overlap; the affine approximation of the dynamicprogram is NP-complete for even a single-segment MNL. This is in contrast to the independentclass(perfect-segmentation) case where even the piecewise-linear approximation has been shownto be tractable. In this paper we investigate the piecewise-linear approximation for network RMunder a general discrete-choice model of demand. We show that the gap between the CDLP andthe piecewise-linear bounds is within a factor of at most 2. We then show that the piecewiselinearapproximation is polynomially-time solvable for a fixed consideration set size, bringing itinto the realm of tractability for small consideration sets; small consideration sets are a reasonablemodeling tradeoff in many practical applications. Our solution relies on showing that forany discrete-choice model the separation problem for the linear program of the piecewise-linearapproximation can be solved exactly by a Lagrangian relaxation. We give modeling extensionsand show by numerical experiments the improvements from using piecewise-linear approximationfunctions.

Vertebrate and nematode genes coding for yolk proteins are derived from a common ancestor.

One of the most obvious characteristics of the egg cells of oviparous animals is their large size resulting to a major extent from the deposition of nutritional reserves, mainly constituted of yolk proteins. In general, these are derived from a precursor called vitellogenin, which undergoes posttranslational modifications during secretion and during transport into and storage within the oocytes. Comparative analysis of the structural organization of the vitellogenin gene and of its product in different species shows that the vitellogenin gene is very ancient and that in vertebrates the gene may have more resemblance to the earliest gene than in invertebrates.

Success of referral for alcohol dependent patients from a general hospital : predictive value of patient and process characteristics

RESUME: Introduction L'objectif de cette étude prospective de cohorte était d'estimer l'efficacité d'un processus de prise en charge standardisé de patients dépendants de l'alcool dans le contexte d'un hôpital universitaire de soins généraux. Ce modèle de prise en charge comprenait une évaluation multidisciplinaire puis des propositions de traitements individualisées et spécifiques (« projet thérapeutique »). Patients et méthode 165 patients alcoolo-dépendants furent recrutés dans différents services de l'hôpital universitaire, y compris la policlinique de médecine. Ils furent dans un premier temps évalués par une équipe multidisciplinaire (médecin interniste, psychiatre, assistant social), puis un projet thérapeutique spécialisé et individualisé leur fut proposé lors d'une rencontre réunissant le patient et l'équipe. Tous les patients éligibles acceptant de participer à l'étude (n=68) furent interrogés au moment de l'inclusion puis 2 et 6 mois plus tard par une psychologue. Des informations standardisées furent recueillies sur les caractéristiques des patients, le processus de prise en charge et l'évolution à 6 mois. Les critères de succès utilisés à 6 mois furent: l'adhérence au traitement proposé et l'abstinence d'alcool. Résultats Lors de l'évaluation à 6 mois, 43% des patients étaient toujours en traitement et 28% étaient abstinents. Les variables prédictrices de succès parmi les caractéristiques des patients étaient un âge de plus de 45 ans, ne pas vivre seul, avoir un travail et être motivé pour un traitement (RAATE-A <18). Pour les variables dépendantes du processus de prise en charge, un sevrage complet de l'alcool lors de la rencontre multidisciplinaire ainsi que la présence de tous les membres de l'équipe à cette réunion étaient des facteurs associés au succès. Conclusion L'efficacité de ce modèle d'intervention pour patients dépendants de l'alcool en hôpital de soins généraux s'est montrée satisfaisante, en particulier pour le critère de succès adhérence au traitement. Des variables associées au succès ou à l'échec à 6 mois ont pu être mises en évidence, permettant d'identifier des populations de patients évoluant différemment. Des stratégies de prise en charge tenant compte de ces éléments pourraient donc être développées, permettant de proposer des traitements plus adaptés ainsi qu'une meilleure rétention des patients alcooliques dans les programmes thérapeutiques. ABSTRACT. To assess the effectiveness of a multidisciplinary evaluation and referral process in a prospective cohort of general hospital patients with alcohol dependence, alcohol-dependent patients were identified in the wards of the general hospital and its primary care center. They were evaluated and then referred to treatment by a multidisciplinary team; those patients who accepted to participate in this cohort study were consecutively included and followed for 6 months. Not included patients were lost for follow-up, whereas all included patients were assessed at time of inclusion, 2 and 6 months later by a research psychologist in order to collect standardized baseline patients' characteristics, process salient features and patients outcomes (defined as treatment adherence and abstinence). Multidisciplinary evaluation and therapeutic referral was feasible and effective, with a success rate of 43% for treatment adherence and 28% for abstinence at 6 months. Among patients' characteristics, predictors of success were an age over 45, not living alone, being employed and being motivated to treatment (RAATE-A score < 18), whereas successful process characteristics included detoxification of the patient at time of referral and a full multidisciplinary referral meeting. This multidisciplinary model of evaluation and referral of alcohol dependent patients of a general hospital had a satisfactory level of effectiveness. Predictors of success and failure allow the identification of subsets of patients for whom new strategies of motivation and treatment referral should be designed.

Use of the Cognitive Performance Scale (CPS) to detect cognitive impairment in the acute care setting: concurrent and predictive validity.

The Cognitive Performance Scale (CPS) was initially designed to assess cognition in long term care residents. Subsequently, the CPS has also been used among in-home, post-acute, and acute care populations even though CPS' clinimetric performance has not been studied in these settings. This study aimed to determine CPS agreement with the Mini Mental Status Exam (MMSE) and its predictive validity for institutionalization and death in a cohort (N=401) of elderly medical inpatients aged 75 years and over. Medical, physical and mental status were assessed upon admission. The same day, the patient's nurse completed the CPS by interview. Follow-up data were gathered from the central billing system (nursing home stay) and proxies (death). Cognitive impairment was present in 92 (23%) patients according to CPS (score >or= 2). Agreement with MMSE was moderate (kappa 0.52, P<.001). Analysis of discordant results suggested that cognitive impairment was overestimated by the CPS in dependent patients with comorbidities and depressive symptoms, and underestimated in older ones. During follow-up, subjects with abnormal CPS had increased risks of death (adjusted hazard ratio (adjHR) 1.7, 95% CI 1.0-2.8, P=.035) and institutionalization (adjHR 2.7, 95% CI 1.3-5.3, P=.006), independent of demographic, health and functional status. Interestingly, subjects with abnormal CPS were at increased risk of death only if they also had abnormal MMSE. The CPS predicted death and institutionalization during follow-up, but correlated moderately well with the MMSE. Combining CPS and MMSE provided additional predictive information, suggesting that domains other than cognition are assessed by professionals when using the CPS in elderly medical inpatients.

Les biomarqueurs prédictifs dans le cancer colorectal [Predictive biomarkers in colorectal cancer]

While for many years the diagnosis and therapy of colon cancer did not change drastically, recently new drugs (irinotecan and oxaliplatin, used in adjuvant or neo-adjuvant approaches) and even more recently the introduction of therapies targeting the epidermal growth factor receptor (EGFR) through the monoclonal antibodies cetuximab and panitumumab, are revolutionizing the field. The finding that only patients with a tumor with a wild type (non mutated) KRAS gene respond to anti-EGFR therapy has also affected the way pathologists address colorectal cancer. Molecular analysis of the KRAS gene has become almost a routine in a very short period of time. Pathologists will have to be prepared for a new era: from standard morphology based diagnostic procedures to the prediction of response to therapy using molecular tools.

SAT Modulo Linear Arithmetic for Solving Polynomial

Polynomial constraint solving plays a prominent role in several areas of hardware and software analysis and verification, e.g., termination proving, program invariant generation and hybrid system verification, to name a few. In this paper we propose a new method for solving non-linear constraints based on encoding the problem into an SMT problem considering only linear arithmetic. Unlike other existing methods, our method focuses on proving satisfiability of the constraints rather than on proving unsatisfiability, which is more relevant in several applications as we illustrate with several examples. Nevertheless, we also present new techniques based on the analysis of unsatisfiable cores that allow one to efficiently prove unsatisfiability too for a broad class of problems. The power of our approach is demonstrated by means of extensive experiments comparing our prototype with state-of-the-art tools on benchmarks taken both from the academic and the industrial world.

Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

Non-Linear and Non-Conventional Speech Processing: Alternative Techniques

This special issue aims to cover some problems related to non-linear and nonconventional speech processing. The origin of this volume is in the ISCA Tutorial and Research Workshop on Non-Linear Speech Processing, NOLISP’09, held at the Universitat de Vic (Catalonia, Spain) on June 25–27, 2009. The series of NOLISP workshops started in 2003 has become a biannual event whose aim is to discuss alternative techniques for speech processing that, in a sense, do not fit into mainstream approaches. A selected choice of papers based on the presentations delivered at NOLISP’09 has given rise to this issue of Cognitive Computation.

A Canonical Genetic Algorithm for Blind Inversion of Linear Channels

It is well known the relationship between source separation and blind deconvolution: If a filtered version of an unknown i.i.d. signal is observed, temporal independence between samples can be used to retrieve the original signal, in the same manner as spatial independence is used for source separation. In this paper we propose the use of a Genetic Algorithm (GA) to blindly invert linear channels. The use of GA is justified in the case of small number of samples, where other gradient-like methods fails because of poor estimation of statistics.

Predictive analysis and mapping of indoor radon concentrations in a complex environment using kernel estimation: an application to Switzerland.

PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.