Change points detection in crime-related time series: an on-line fuzzy approach based on a shape space representation

The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.

Microbiological diagnosis of community-acquired respiratory tract infections by nucleic acid detection.

Background: Microbiological diagnostic procedures have changed significantly over the last decade. Initially the implementation of the polymerase chain reaction (PCR) resulted in improved detection tests for microbes that were difficult or even impossible to detect by conventional methods such as culture and serology, especially in community-acquired respiratory tract infections (CA-RTI). A further improvement was the development of real-time PCR, which allows end point detection and quantification, and many diagnostic laboratories have now implemented this powerful method. Objective: At present, new performant and convenient molecular tests have emerged targeting in parallel many viruses and bacteria responsible for lower and/or upper respiratory tract infections. The range of test formats and microbial agents detected is evolving very quickly and the added value of these new tests needs to be studied in terms of better use of antibiotics, better patient management, duration of hospitalization and overall costs. Conclusions: Molecular tools for a better microbial documentation of CA-RTI are now available. Controlled studies are now required to address the relevance issue of these new methods, such as, for example, the role of some newly detected respiratory viruses or of the microbial DNA load in a particular patient at a particular time. The future challenge for molecular diagnosis will be to become easy to handle, highly efficient and cost-effective, delivering rapid results with a direct impact on clinical management.

Choline-PET in prostate cancer management: The point of view of the radiation oncologist.

Among PET radiotracers, FDG seems to be quite accepted as an accurate oncology diagnostic tool, frequently helpful also in the evaluation of treatment response and in radiation therapy treatment planning for several cancer sites. To the contrary, the reliability of Choline as a tracer for prostate cancer (PC) still remains an object of debate for clinicians, including radiation oncologists. This review focuses on the available data about the potential impact of Choline-PET in the daily clinical practice of radiation oncologists managing PC patients. In summary, routine Choline-PET is not indicated for initial local T staging, but it seems better than conventional imaging for nodal staging and for all patients with suspected metastases. In these settings, Choline-PET showed the potential to change patient management. A critical limit remains spatial resolution, limiting the accuracy and reliability for small lesions. After a PSA rise, the problem of the trigger PSA value remains crucial. Indeed, the overall detection rate of Choline-PET is significantly increased when the trigger PSA, or the doubling time, increases, but higher PSA levels are often a sign of metastatic spread, a contraindication for potentially curable local treatments such as radiation therapy. Even if several published data seem to be promising, the current role of PET in treatment planning in PC patients to be irradiated still remains under investigation. Based on available literature data, all these issues are addressed and discussed in this review.

Multi-modal Change Detection, Application to the Detection of Flooded Areas: Outcome of the 2009-2010 data fusion contest

The 2009-2010 Data Fusion Contest organized by the Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society was focused on the detection of flooded areas using multi-temporal and multi-modal images. Both high spatial resolution optical and synthetic aperture radar data were provided. The goal was not only to identify the best algorithms (in terms of accuracy), but also to investigate the further improvement derived from decision fusion. This paper presents the four awarded algorithms and the conclusions of the contest, investigating both supervised and unsupervised methods and the use of multi-modal data for flood detection. Interestingly, a simple unsupervised change detection method provided similar accuracy as supervised approaches, and a digital elevation model-based predictive method yielded a comparable projected change detection map without using post-event data.

Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.

Multisensor change detection with nonlinear canonical correlation

The analysis of multi-modal and multi-sensor images is nowadays of paramount importance for Earth Observation (EO) applications. There exist a variety of methods that aim at fusing the different sources of information to obtain a compact representation of such datasets. However, for change detection existing methods are often unable to deal with heterogeneous image sources and very few consider possible nonlinearities in the data. Additionally, the availability of labeled information is very limited in change detection applications. For these reasons, we present the use of a semi-supervised kernel-based feature extraction technique. It incorporates a manifold regularization accounting for the geometric distribution and jointly addressing the small sample problem. An exhaustive example using Landsat 5 data illustrates the potential of the method for multi-sensor change detection.

Rockfall detection from LIDAR point clouds: A clustering approach using R

The analysis of rockfall characteristics and spatial distribution is fundamental to understand and model the main factors that predispose to failure. In our study we analysed LiDAR point clouds aiming to: (1) detect and characterise single rockfalls; (2) investigate their spatial distribution. To this end, different cluster algorithms were applied: 1a) Nearest Neighbour Clutter Removal (NNCR) in combination with the Expectation?Maximization (EM) in order to separate feature points from clutter; 1b) a density based algorithm (DBSCAN) was applied to isolate the single clusters (i.e. the rockfall events); 2) finally we computed the Ripley's K-function to investigate the global spatial pattern of the extracted rockfalls. The method allowed proper identification and characterization of more than 600 rockfalls occurred on a cliff located in Puigcercos (Catalonia, Spain) during a time span of six months. The spatial distribution of these events proved that rockfall were clustered distributed at a welldefined distance-range. Computations were carried out using R free software for statistical computing and graphics. The understanding of the spatial distribution of precursory rockfalls may shed light on the forecasting of future failures.

Landslide detection and monitoring capability of boat-based mobile laser scanning along Dieppe coastal cliffs, Normandy

Integrated in a wide research assessing destabilizing and triggering factors to model cliff dynamic along the Dieppe's shoreline in High Normandy, this study aims at testing boat-based mobile LiDAR capabilities by scanning 3D point clouds of the unstable coastal cliffs. Two acquisition campaigns were performed in September 2012 and September 2013, scanning (1) a 30-km-long shoreline and (2) the same test cliffs in different environmental conditions and device settings. The potentials of collected data for 3D modelling, change detection and landslide monitoring were afterward assessed. By scanning during favourable meteorological and marine conditions and close to the coast, mobile LiDAR devices are able to quickly scan a long shoreline with median point spacing up to 10cm. The acquired data are then sufficiently detailed to map geomorphological features smaller than 0.5m2. Furthermore, our capability to detect rockfalls and erosion deposits (>m3) is confirmed, since using the classical approach of computing differences between sequential acquisitions reveals many cliff collapses between Pourville and Quiberville and only sparse changes between Dieppe and Belleville-sur-Mer. These different change rates result from different rockfall susceptibilities. Finally, we also confirmed the capability of the boat-based mobile LiDAR technique to monitor single large changes, characterizing the Dieppe landslide geometry with two main active scarps, retrogression up to 40m and about 100,000m3 of eroded materials.

Routine use of point-of-care tests: usefulness and application in clinical microbiology.

Point-of-care (POC) tests offer potentially substantial benefits for the management of infectious diseases, mainly by shortening the time to result and by making the test available at the bedside or at remote care centres. Commercial POC tests are already widely available for the diagnosis of bacterial and viral infections and for parasitic diseases, including malaria. Infectious diseases specialists and clinical microbiologists should be aware of the indications and limitations of each rapid test, so that they can use them appropriately and correctly interpret their results. The clinical applications and performance of the most relevant and commonly used POC tests are reviewed. Some of these tests exhibit insufficient sensitivity, and should therefore be coupled to confirmatory tests when the results are negative (e.g. Streptococcus pyogenes rapid antigen detection test), whereas the results of others need to be confirmed when positive (e.g. malaria). New molecular-based tests exhibit better sensitivity and specificity than former immunochromatographic assays (e.g. Streptococcus agalactiae detection). In the coming years, further evolution of POC tests may lead to new diagnostic approaches, such as panel testing, targeting not just a single pathogen, but all possible agents suspected in a specific clinical setting. To reach this goal, the development of serology-based and/or molecular-based microarrays/multiplexed tests will be needed. The availability of modern technology and new microfluidic devices will provide clinical microbiologists with the opportunity to be back at the bedside, proposing a large variety of POC tests that will allow quicker diagnosis and improved patient care.

NEW METHODS FOR DETECTION, SUSCEPTIBILITY TESTING AND BIOFILM ERADICATION OF DIFFICULT ORGANISMS

Aujourd'hui, les problèmes des maladies infectieuses concernent l'émergence d'infections difficiles à traiter, telles que les infections associées aux implants et les infections fongiques invasives chez les patients immunodéprimés. L'objectif de cette thèse était de développer des stratégies pour l'éradication des biofilms bactériens (partie 1), ainsi que d'étudier des méthodes innovantes pour la détection microbienne, pour l'établissement de nouveaux tests de sensibilité (partie 2). Le traitement des infections associées aux implants est difficile car les biofilms bactériens peuvent résister à des niveaux élevés d'antibiotiques. A ce jour, il n'y a pas de traitement optimal défini contre des infections causées par des bactéries de prévalence moindre telles que Enterococcus faecalis ou Propionibacterium acnés. Dans un premier temps, nous avons démontré une excellente activité in vitro de la gentamicine sur une souche de E. faecalis en phase stationnaire de croissance Nous avons ensuite confirmé l'activité de la gentamicine sur un biofilm précoce en modèle expérimental animal à corps étranger avec un taux de guérison de 50%. De plus, les courbes de bactéricidie ainsi que les résultats de calorimétrie ont prouvé que l'ajout de gentamicine améliorait l'activité in vitro de la daptomycine, ainsi que celle de la vancomycine. In vivo, le schéma thérapeutique le plus efficace était l'association daptomycine/gentamicine avec un taux de guérison de 55%. En établissant une nouvelle méthode pour l'évaluation de l'activité des antimicrobiens vis-à-vis de micro-organismes en biofilm, nous avons démontré que le meilleur antibiotique actif sur les biofilms à P. acnés était la rifampicine, suivi par la penicilline G, la daptomycine et la ceftriaxone. Les études conduites en modèle expérimental animal ont confirmé l'activité de la rifampicine seule avec un taux de guérison 36%. Le meilleur schéma thérapeutique était au final l'association rifampicine/daptomycine avec un taux de guérison 63%. Les associations de rifampicine avec la vancomycine ou la levofloxacine présentaient des taux de guérisons respectivement de 46% et 25%. Nous avons ensuite étudié l'émergence in vitro de la résistance à la rifampicine chez P. acnés. Nous avons observé un taux de mutations de 10"9. La caractérisation moléculaire de la résistance chez les mutant-résistants a mis en évidence l'implication de 5 mutations ponctuelles dans les domaines I et II du gène rpoB. Ce type de mutations a déjà été décrit au préalable chez d'autres espèces bactériennes, corroborant ainsi la validité de nos résultats. La deuxième partie de cette thèse décrit une nouvelle méthode d'évaluation de l'efficacité des antifongiques basée sur des mesures de microcalorimétrie isotherme. En utilisant un microcalorimètre, la chaleur produite par la croissance microbienne peut être-mesurée en temps réel, très précisément. Nous avons évalué l'activité de l'amphotéricine B, des triazolés et des échinocandines sur différentes souches de Aspergillus spp. par microcalorimétrie. La présence d'amphotéricine Β ou de triazole retardait la production de chaleur de manière concentration-dépendante. En revanche, pour les échinochandines, seule une diminution le pic de « flux de chaleur » a été observé. La concordance entre la concentration minimale inhibitrice de chaleur (CMIC) et la CMI ou CEM (définie par CLSI M38A), avec une marge de 2 dilutions, était de 90% pour l'amphotéricine B, 100% pour le voriconazole, 90% pour le pozoconazole et 70% pour la caspofongine. La méthode a été utilisée pour définir la sensibilité aux antifongiques pour d'autres types de champignons filamenteux. Par détermination microcalorimétrique, l'amphotéricine B s'est avéré être l'agent le plus actif contre les Mucorales et les Fusarium spp.. et le voriconazole le plus actif contre les Scedosporium spp. Finalement, nous avons évalué l'activité d'associations d'antifongiques vis-à-vis de Aspergillus spp. Une meilleure activité antifongique était retrouvée avec l'amphotéricine B ou le voriconazole lorsque ces derniers étaient associés aux échinocandines vis-à-vis de A. fumigatus. L'association échinocandine/amphotéricine B a démontré une activité antifongique synergique vis-à-vis de A. terreus, contrairement à l'association échinocandine/voriconazole qui ne démontrait aucune amélioration significative de l'activité antifongique. - The diagnosis and treatment of infectious diseases are today increasingly challenged by the emergence of difficult-to-manage situations, such as infections associated with medical devices and invasive fungal infections, especially in immunocompromised patients. The aim of this thesis was to address these challenges by developing new strategies for eradication of biofilms of difficult-to-treat microorganisms (treatment, part 1) and investigating innovative methods for microbial detection and antimicrobial susceptibility testing (diagnosis, part 2). The first part of the thesis investigates antimicrobial treatment strategies for infections caused by two less investigated microorganisms, Enterococcus faecalis and Propionibacterium acnes, which are important pathogens causing implant-associated infections. The treatment of implant-associated infections is difficult in general due to reduced susceptibility of bacteria when present in biofilms. We demonstrated an excellent in vitro activity of gentamicin against E. faecalis in stationary growth- phase and were able to confirm the activity against "young" biofilms (3 hours) in an experimental foreign-body infection model (cure rate 50%). The addition of gentamicin improved the activity of daptomycin and vancomycin in vitro, as determined by time-kill curves and microcalorimetry. In vivo, the most efficient combination regimen was daptomycin plus gentamicin (cure rate 55%). Despite a short duration of infection, the cure rates were low, highlighting that enterococcal biofilms remain difficult to treat despite administration of newer antibiotics, such as daptomycin. By establishing a novel in vitro assay for evaluation of anti-biofilm activity (microcalorimetry), we demonstrated that rifampin was the most active antimicrobial against P. acnes biofilms, followed by penicillin G, daptomycin and ceftriaxone. In animal studies we confirmed the anti-biofilm activity of rifampin (cure rate 36% when administered alone), as well as in combination with daptomycin (cure rate 63%), whereas in combination with vancomycin or levofloxacin it showed lower cure rates (46% and 25%, respectively). We further investigated the emergence of rifampin resistance in P. acnes in vitro. Rifampin resistance progressively emerged during exposure to rifampin, if the bacterial concentration was high (108 cfu/ml) with a mutation rate of 10"9. In resistant isolates, five point mutations of the rpoB gene were found in cluster I and II, as previously described for staphylococci and other bacterial species. The second part of the thesis describes a novel real-time method for evaluation of antifungals against molds, based on measurements of the growth-related heat production by isothermal microcalorimetry. Current methods for evaluation of antifungal agents against molds, have several limitations, especially when combinations of antifungals are investigated. We evaluated the activity of amphotericin B, triazoles (voriconazole, posaconazole) and echinocandins (caspofungin and anidulafungin) against Aspergillus spp. by microcalorimetry. The presence of amphotericin Β or a triazole delayed the heat production in a concentration-dependent manner and the minimal heat inhibition concentration (MHIC) was determined as the lowest concentration inhibiting 50% of the heat produced at 48 h. Due to the different mechanism of action echinocandins, the MHIC for this antifungal class was determined as the lowest concentration lowering the heat-flow peak with 50%. Agreement within two 2-fold dilutions between MHIC and MIC or MEC (determined by CLSI M38A) was 90% for amphotericin B, 100% for voriconazole, 90% for posaconazole and 70% for caspofungin. We further evaluated our assay for antifungal susceptibility testing of non-Aspergillus molds. As determined by microcalorimetry, amphotericin Β was the most active agent against Mucorales and Fusarium spp., whereas voriconazole was the most active agent against Scedosporium spp. Finally, we evaluated the activity of antifungal combinations against Aspergillus spp. Against A. jumigatus, an improved activity of amphotericin Β and voriconazole was observed when combined with an echinocandin. Against A. terreus, an echinocandin showed a synergistic activity with amphotericin B, whereas in combination with voriconazole, no considerable improved activity was observed.

Automatic front-crawl temporal phase detection using adaptive filtering of inertial signals

This study introduces a novel approach for automatic temporal phase detection and inter-arm coordination estimation in front-crawl swimming using inertial measurement units (IMUs). We examined the validity of our method by comparison against a video-based system. Three waterproofed IMUs (composed of 3D accelerometer, 3D gyroscope) were placed on both forearms and the sacrum of the swimmer. We used two underwater video cameras in side and frontal views as our reference system. Two independent operators performed the video analysis. To test our methodology, seven well-trained swimmers performed three 300 m trials in a 50 m indoor pool. Each trial was in a different coordination mode quantified by the index of coordination. We detected different phases of the arm stroke by employing orientation estimation techniques and a new adaptive change detection algorithm on inertial signals. The difference of 0.2 +/- 3.9% between our estimation and video-based system in assessment of the index of coordination was comparable to experienced operators' difference (1.1 +/- 3.6%). The 95% limits of agreement of the difference between the two systems in estimation of the temporal phases were always less than 7.9% of the cycle duration. The inertial system offers an automatic easy-to-use system with timely feedback for the study of swimming.