Tell Me What Air You Breath, I Tell You Where You Are

International audienceWide spread use of sensors and mobile devices along with the new paradigm of Mobile Crowd-Sensing (MCS), allows monitoring air pollution in urban areas. Several measurements are collected, such as Particulate Matters, Nitrogen dioxide, and others. Mining the context of MCS data in such domains is a key factor for identifying the individuals' exposure to air pollution, but it is challenging due to the lack or the weakness of predictors. We have previously developed a multi-view learning approach which learns the context solely from the sensor measurements. In this demonstration, we propose a visualization tool (COMIC) showing the different recognized contexts using an improved version of our algorithm. We also demonstrate the change points detected by a multi-dimensional CPD model. We leverage real data from a MCS campaign, and compare different methods

Micro-environment recognition in the context of environmental crowdsensing

International audienceWith the rapid advancements of sensor technologies and mobile computing, Mobile Crowd-Sensing (MCS) has emerged as a new paradigm to collect massive-scale rich trajectory data. Nomadic sensors empower people and objects with the capability of reporting and sharing observations on their state, their behavior and/or their surrounding environments. Processing and mining multi-source sensor data in MCS raise several challenges due to their multi-dimensional nature where the measured parameters (i.e., dimensions) may differ in terms of quality, variabilty, and time scale. We consider the context of air quality MCS, and focus on the task of mining the context from the MCS data. Relating the measures to their context is crucial to interpret them and analyse the participant's exposure. This paper investigates the feasibility of recognizing the human's context (called herein micro-environment) in an environmental MCS scenario. We put forward a multi-view learning approach, that we adapt to our context, and implement it along with other time series classification approaches. The experimental results, applied to real MCS data, not only confirm the power of MCS data in characterizing the micro-environment, but also show a moderate impact of the integration of mobility data in this recognition. Furthermore, multi-view learning shows similar performance as the reference deep learning algorithm, without requiring specific hardware

Place de la fronde trans ligamentaire sacro-épineuse ou IVS postérieure modifiée dans la prise en charge des prolapsus génitaux

ST ETIENNE-BU Médecine (422182102) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Learning the micro-environment from rich trajectories in the context of mobile crowd sensing

International audienceWith the rapid advancements of sensor technologies and mobile computing, Mobile Crowd Sensing (MCS) has emerged as a new paradigm to collect massive-scale rich trajectory data. Nomadic sensors empower people and objects with the capability of reporting and sharing observations on their state, their behavior and/or their surrounding environments. Processing and mining multi-source sensor data in MCS raise several challenges due to their multi-dimensional nature where the measured parameters (i.e., dimensions) may differ in terms of quality, variability, and time scale. We consider the context of air quality MCS and focus on the task of mining the micro-environment from the MCS data. Relating the measures to their micro-environment is crucial to interpret them and analyse the participant’s exposure properly. In this paper, we focus on the problem of investigating the feasibility of recognizing the human’s micro-environment in an environmental MCS scenario. We propose a novel approach for learning and predicting the micro-environment of users from their trajectories enriched with environmental data represented as multidimensional time series plus GPS tracks. We put forward a multi-view learning approach that we adapt to our context, and implement it along with other time series classification approaches. We extend the proposed approach to a hybrid method that employs trajectory segmentation to bring the best of both methods. We optimise the proposed approaches either by analysing the exact geolocation (which is privacy invasive), or simply applying some a priori rules (which is privacy friendly). The experimental results, applied to real MCS data, not only confirm the power of MCS and air quality (AQ) data in characterizing the micro-environment, but also show a moderate impact of the integration of mobility data in this recognition. Furthermore, and during the training phase, multi-view learning shows similar performance as the reference deep learning algorithm, without requiring specific hardware. However, during the application of models on new data, the deep learning algorithm fails to outperform our proposed models

Perforated diverticulitis of the sigmoid colon causing a subcutaneous emphysema

INTRODUCTION: Although diverticular disease of the colon is frequent, perforated diverticulitis causing subcutaneous emphysema is a uncommon entity. We wish to present this extremely rare case of perforated colonic diverticulum in the subcutaneous tissue, which is the first one that we have encountered in our practice, along with the accompanying diagnostic and therapeutic issues and a review of the literature. PRESENTATION OF CASE: We report the case of an 83-year-old man who admitted to the emergency room due to an abdominal subcutaneous emphysema. Physical examination revealed a severe subcutaneous emphysema especially in the left iliac fossa and abdominal pain. An urgent contrast enhanced abdominal CT scan showed multiple diverticula in the sigmoid colon and multiple air bubbles in the subcutaneous tissue. The exploratory laparotomy identified a perforation of diverticular in subcutaneous tissue. Forty centimeters of colon were resected. The subcutaneous emphysema resolved without specific treatment. The postoperative period was uncomplicated. DISCUSSION: Subcutaneous emphysema of anterior abdomen wall is an obvious physical sign but its etiology is complex to determine and may be potentially lethal. The pathophysiological mechanism involved is the emergence of a pressure gradient between the peritoneum and surrounding structures, causing rupture of the anterior abdominal wall, allowing gas from a perforation to diffuse along tissue planes. CONCLUSION: This physical sign may be of especial value in elderly patient groups amongst whom perforation may be less clinically obvious. General surgeons should bear in mind this rare complication of colonic diverticulosis

Seasonal Variation of Aerosol Size Distribution Data at the Puy de Dôme Station with Emphasis on the Boundary Layer/Free Troposphere Segregation

International audienceAerosol particles are important due to their direct and indirect impacts on climate. Within the planetary boundary layer (BL), these particles have a relatively short lifetime due to their frequent removal process by wet deposition. When aerosols are transported into the free troposphere (FT), their atmospheric lifetime increases significantly, making them representative of large spatial areas. In this work, we use a combination of in situ measurements performed at the high altitude PUY (Puy de Dôme, 45 • 46 N, 2 • 57 E, 1465 m a.s.l) station, together with LIDAR profiles at Clermont-Ferrand for characterizing FT conditions, and further characterize the physical properties of aerosol in this poorly documented area of the atmosphere. First, a combination of four criteria was used to identify whether the PUY station lies within the FT or within the BL. Results show that the PUY station is located in BL with frequencies ranging from 50% during the winter, up to 97% during the summer. Then, the classification is applied to a year-long dataset (2015) of particle size distribution data to study the differences in particle physical characteristics (size distribution) and black carbon (BC) concentrations between the FT and the BL. Although BC, Aitken, and the accumulation mode particles concentrations were higher in the BL than in the FT in winter and autumn, they were measured to be higher in the FT compared to BL in spring. No significant difference between the BL and the FT concentrations was observed for the nucleation mode particles for all seasons, suggesting a continuous additional source of nucleation mode particles in the FT during winter and autumn. Coarse mode particle concentrations were found higher in the FT than in the BL for all seasons and especially during summer. This indicates an efficient long-range transport of large particles in the FT from distant sources (marine and desert) due to higher wind speeds in the FT compared to BL. For FT air masses, we used 204-h air mass back-trajectories combined with boundary layer height estimations from ECMWF ERA-Interim to assess the time they spent in the FT since their last contact with the BL and to evaluate the impact of this parameter on the aerosol properties. We observed that even after 75 h without any contact with the BL, FT aerosols preserve specific properties of their air mass type

Peritoneal Carcinomatosis of Rare Ovarian Origin Treated by Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy: A Multi-Institutional Cohort from PSOGI and BIG-RENAPE

International audiencePURPOSE:Ovarian cancer is the most common deadly cancer of gynecologic origin. Patients often are diagnosed at advanced stage with peritoneal metastasis. There are many rare histologies of ovarian cancer; some have outcomes worse than serous ovarian cancer. Cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) can be considered for patients with recurrence. This study was designed to assess the impact of CRS and HIPEC on survival of patient with peritoneal metastasis from rare ovarian malignancy.METHODS:A prospective, multicentric, international database was retrospectively searched to identify all patients with rare ovarian tumor (mucinous, clear cells, endometrioid, small cell hypercalcemic, and other) and peritoneal metastasis who underwent CRS and HIPEC through the Peritoneal Surface Oncology Group International (PSOGI) and BIG-RENAPE working group. The postoperative complications, long-term results, and principal prognostic factors were analyzed.RESULTS:The analysis included 210 patients with a median follow-up of 43.5 months. Median overall survival (OS) was 69.3 months, and the 5-year OS was 57.7%. For mucinous tumors, median OS and DFS were not reached at 5 years. For granulosa tumors, median overall survival was not reached at 5 years, and median DFS was 34.6 months. Teratoma or germinal tumor showed median overall survival and DFS that were not reached at 5 years. Differences in OS were not statistically significant between histologies (p = 0.383), whereas differences in DFS were (p < 0.001).CONCLUSIONS:CRS and HIPEC may increases long-term survival in selected patients with peritoneal metastasis from rare ovarian tumors especially in mucinous, granulosa, or teratoma histological subtypes

Jejuno–ileal diverticulitis: Etiopathogenicity, diagnosis and management

Introduction: Although diverticular disease of the duodenum and colon is frequent, the jejuno–ileal diverticulosis (JOD) is an uncommon entity. The perforation of the small bowel diverticula can be fatal due to the delay in diagnosis. Presentation of case: We report the case of a 79-year-old man presenting with generalized abdominal pain and altered bowel habits. Physical examination revealed a severe diffuse abdominal pain. A CT scan of the abdomen and pelvis with oral contrast showed thickening of the distal jejunal loop and thickening and infiltration of the mesenteric fat and the presence of free air in the mesentery suggesting a possible perforation adjacent to the diverticula. A midline laparotomy was performed. The jejunal diverticula were found along the mesenteric border. Forty centimeters of the jejunum were resected. Histopathology report confirmed the presence of multiple jejunual diverticula, and one of them was perforated. The patient tolerated the procedure and the postoperative period was uncomplicated. Discussion: The prevalence of small intestinal diverticula ranges from 0.06% to 1.3%. The etiopathogenesis of JOD is unclear, although the current hypothesis focuses on abnormalities in the smooth muscle or myenteric plexus, on intestinal dyskinesis and on high intraluminal pressures. Diagnosis is often difficult and delayed because clinical symptoms are not specific and mainly imaging studies performs the diagnosis. Conclusion: Because of the relative rarity of acquired jejuno–ileal diverticulosis, the perforation of small bowel diverticulitis poses technical dilemmas

ASO Visual Abstract: Role of Hyperthermic Intraperitoneal Chemotherapy Combined with Cytoreductive Surgery as Consolidation Therapy for Advanced Epithelial Ovarian Cancer

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NO2, BC and PM Exposure of Participants in the Polluscope Autumn 2019 Campaign in the Paris Region

The Polluscope project aims to better understand the personal exposure to air pollutants in the Paris region. This article is based on one campaign from the project, which was conducted in the autumn of 2019 and involved 63 participants equipped with portable sensors (i.e., NO2, BC and PM) for one week. After a phase of data curation, analyses were performed on the results from all participants, as well as on individual participants’ data for case studies. A machine learning algorithm was used to allocate the data to different environments (e.g., transportation, indoor, home, office, and outdoor). The results of the campaign showed that the participants’ exposure to air pollutants depended very much on their lifestyle and the sources of pollution that may be present in the vicinity. Individuals’ use of transportation was found to be associated with higher levels of pollutants, even when the time spent on transport was relatively short. In contrast, homes and offices were environments with the lowest concentrations of pollutants. However, some activities performed in indoor air (e.g., cooking) also showed a high levels of pollution over a relatively short period