Interface pour le pilotage et l'analyse des robots basée sur un générateur de cinématiques

In robotics we depend on software tools during design, modeling, programming and testing. These tools are essentials, often indispensable aids for developing and operating sophisticated robotic systems. At the same time, these tools are complex and usually too difficult to be used by non specialists. For example tools used for simulation or off-line programming require significant knowledge and skill. The goal of this thesis is to provide novice users with an intuitive tool (CINEGEN) for designing, studying and controlling robot manipulators without programming. In particular the tool addresses two main problems: 1) modeling a new robot requires an significant amount of time; 2) robot tasks (motion, actions, etc.) are generally difficult for novice users to specify. CINEGEN is a novel tool for kinematic simulation of robot manipulators in a virtual environment. It is easy to use and is capable of handling generic kinematic structures. With CINEGEN the description of robots is easy to perform and enables rapid prototyping. Additionally, CINEGEN's capability for real-time interactive simulation allows novice users to quickly specify and evaluate robot tasks. A new simulation can be created very rapidly by describing the robot in a simple text based configuration file. In this file, robots are defined by the properties of each link and their relationships. Robots are defined as a tree structure from the base to the end-effector. For robots with kinematic loops, each loop is represented with two open sub-chains which are closed using a simple constraint. This same type of constraint is used to define which part of the robot must follow movements generated by input devices to the simulation. Once defined, this file is parsed by CINEGEN which automatically constructs the robot structure and its numerical kinematic model to satisfy all the constraints. Then the kinematic solver computes the robot movements regarding the user inputs and the internal constraints. This allows the user to interactively control the robot in two modes: direct kinematics (independent control of each joint) or inverse kinematics (control of the end effector). This constraint solver scheme provides the user with a unified interface to control robots without requiring thought about direct or inverse kinematics. The user interacts with the model of the robot using a virtual reality based interface. This interface gives the user a direct and intuitive means to study a robot's behavior. The virtual reality based interface implies three fundamentals needs: a visualization of 3-dimensional world, appropriate input devices and real-time simulation. The visualization of the robot in a three dimensional space allows the user to understand the robot and the world in which it moves without any symbolic representation. The design of a new haptic input device extends the use of commercial devices employed, making it easier to generate control inputs as well as to "feel" the robot response. Real-time performance (refresh at more than 25Hz) of the complete simulation (graphics as well as kinematics) is obtained via efficient numerical tools and a constraint solver dedicated to robot kinematics. In short, the project developed in this thesis answer to two principal needs: rapid prototyping and analysis of robot manipulators with general kinematic structure, an intuitive interface for teleoperation (task definition) of new robots without programming

A comparison of statistical and machine-learning approaches for spatiotemporal modeling of nitrogen dioxide across Switzerland

Land use regression modeling has commonly been used to model ambient air pollutant concentrations in environmental epidemiological studies. Recently, other statistical and machine-learning methods have also been applied to model air pollution, but their relative strengths and limitations have not been extensively investigated. In this study, we developed and compared land-use statistical and machine-learning models at annual, monthly and daily scales estimating ground-level NO2 concentrations across Switzerland (at high spatial resolution 100 × 100 m). Our study showed that the best model type varies with context, particularly with temporal resolution and training data size. Linear-regression-based models were useful in predicting long-term (annual, monthly) spatial distribution of NO2 and outperformed machine-learning models. However, linear-regression-based models were limited in representing short-term temporal variation even when predictor variables with temporal variability were provided. Machine-learning models showed high capability in predicting short-term temporal variation and outperformed linear-regression-based models for modeling NO2 variation at high temporal resolution (daily). However, the best performing models, XGBoost and LightGBM, constantly overfit on training data and may result in erratic patterns in the model-estimated concentration surfaces. Therefore, the temporal and spatial scale of the study is an important factor on which the choice of the suitable model type should be based and validation is required whatever approach is used

Secular Trend and Risk Factors for Antimicrobial Resistance in Escherichia coli Isolates in Switzerland 1997-2007

Abstract : Background: : Antibacterial resistance in Escherichia coli isolates of urinary infections, mainly to fluoroquinolones, is emerging. The aim of our study was to identify the secular trend of resistant E. coli isolates and to characterize the population at risk for colonization or infections with these organisms. Patients and Methods: : Retrospective analysis of 3,430 E.coli first isolates of urine specimens from patients admitted to the University Hospital Basel in 1997, 2000, 2003, and 2007. Results: : Resistance to ciprofloxacin, trimethoprim/sulfamethoxazole, and amoxicillin/clavulanate has increased over the 10-year study period (from 1.8% to 15.9%, 17.4% to 21.3%, and 9.5% to 14.5%, respectively). A detailed analysis of the 2007 data revealed that independent risk factors for ciprofloxacin resistance were age (5.3% 75 years; odds ratio [OR] 1.29 per 10 years, 95% confidence interval [CI] 1.15-1.45, p < 0.001) and male gender (OR 1.59, 95% CI 1.05-2.41, p = 0.04). In contrast, nosocomial E. coli isolates were associated with lower odds of ciprofloxacin resistance (OR 0.51, 95% CI 0.28-0.67, p < 0.001). The frequency of resistant isolate rates was not influenced by the clinical significance (i.e., colonization vs urinary tract infection, UTI) or by whether the urine was taken from a urinary catheter. Importantly, the increase in ciprofloxacin resistance paralleled the increase in ciprofloxacin consumption in Switzerland (Pearson's correlation test R2= 0.998, p = 0.002). Of note, resistance was less frequent in isolates sent in by general practitioners. However, after adjustment for age and gender, only resistance against amoxicillin/clavulanate was found to be less frequent (OR 0.34, 95% CI 0.16-0.92, p = 0.03). Conclusion: : Our study reveals that resistance rates have been increasing during the last decade. Published resistance rates may lack information due to important differences regarding age, gender, and probable origin of the isolates. Empirical therapy for UTI should be guided more on individual risk profile and local resistance data than on resistance data bank

Lymphogranuloma venereum: Eine alte Krankheit in neuem Kleid

Zusammenfassung: Lymphogranuloma venereum ist eine sexuell übertragene Erkrankung verursacht durch Chlamydia trachomatis der Serotypen L1, L2 und L3. Die klassische Manifestation ist eine schmerzhafte inguinale Lymphadenopathie, welche ohne Behandlung zu schwerwiegenden Komplikationen führt. Daneben wird seit einigen Jahren gehäuft eine ulzerierende Proktitis beschrieben, speziell bei Männern, die Sex mit Männern haben. Da die klinischen Beschwerden unspezifisch sind, muss bei Proktitis aktiv nach Chlamydia trachomatis gesucht werden. Die Diagnostik des Lymphogranuloma venereum erfolgt heute hauptsächlich mit molekularen Testverfahren. Zur Therapie wird Tetracyclin über 3Wochen empfohlen. Die Erkrankung wird anhand von 5 aktuellen klinischen Fallbeispielen dargestell

Serial monitoring of pancreatic stone protein for the detection of sepsis in intensive care unit patients with complicated abdominal surgery: A prospective, longitudinal cohort study.

The objective of this study was to assess the performance of pancreatic stone protein (PSP) monitoring for the detection of sepsis, prediction of outcome and distinction between bacterial and fungal infections in intensive care unit (ICU) patients with complicated abdominal surgery. In this prospective multicenter cohort study, patients with complicated abdominal surgery had serial PSP measurements during their ICU stay. Infectious episodes were classified as bacterial, fungal or mixed. PSPmax (maximal PSP value within 48 h of the diagnosis of infection) and ΔPSP (difference between PSPmax and the preceding PSP value) were used for analyses. PSPmax was obtained for 118 infectious episodes (68 patients). ΔPSP was available for 73 episodes (48 patients). Both PSPmax and ΔPSP were significantly higher in patients with sepsis and in patients with a fatal outcome. A PSPmax ≥124 ng/ml and a ΔPSP ≥34 ng/ml could detect sepsis with a sensitivity/specificity of 84%/54% and 69%/76%, respectively. There was no significant difference of PSPmax or ΔPSP between patients with bacterial/mixed versus fungal infections. Serial PSP monitoring may be an additional tool for the early detection of sepsis in patients with complicated abdominal surgery who are at high risk of severe infections