849 resultados para Multi-camera system


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The multi-target screening method described in this work allows the simultaneous detection and identification of 700 drugs and metabolites in biological fluids using a hybrid triple-quadrupole linear ion trap mass spectrometer in a single analytical run. After standardization of the method, the retention times of 700 compounds were determined and transitions for each compound were selected by a "scheduled" survey MRM scan, followed by an information-dependent acquisition using the sensitive enhanced product ion scan of a Q TRAP hybrid instrument. The identification of the compounds in the samples analyzed was accomplished by searching the tandem mass spectrometry (MS/MS) spectra against the library we developed, which contains electrospray ionization-MS/MS spectra of over 1,250 compounds. The multi-target screening method together with the library was included in a software program for routine screening and quantitation to achieve automated acquisition and library searching. With the help of this software application, the time for evaluation and interpretation of the results could be drastically reduced. This new multi-target screening method has been successfully applied for the analysis of postmortem and traffic offense samples as well as proficiency testing, and complements screening with immunoassays, gas chromatography-mass spectrometry, and liquid chromatography-diode-array detection. Other possible applications are analysis in clinical toxicology (for intoxication cases), in psychiatry (antidepressants and other psychoactive drugs), and in forensic toxicology (drugs and driving, workplace drug testing, oral fluid analysis, drug-facilitated sexual assault).

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OBJECTIVES: To assess perioperative outcomes and blood pressure (BP) responses to an implantable carotid sinus baroreflex activating system being investigated for the treatment of resistant hypertension. METHODS: We report on the first seventeen patients enrolled in a multicenter study. Bilateral perivascular carotid sinus electrodes (CSL) and a pulse generator (IPG) are permanently implanted. Optimal placement of the CSL is determined by intraoperative BP responses to test activations. Acute BP responses were tested postoperatively and during the first four months of follow-up. RESULTS: Prior to implant, BP was 189.6+/-27.5/110.7+/-15.3 mmHg despite stable therapy (5.2+/-1.8 antihypertensive drugs). The mean procedure time was 202+/-43 minutes. No perioperative strokes or deaths occurred. System tests performed 1 or up to 3 days postoperatively resulted in significant (all p < or = 0.0001) mean maximum reduction, with standard deviations and 95% confidence limits for systolic BP, diastolic BP and heart rate of 28+/-22 (17, 39) mmHg, 16+/-11 (10, 22) mmHg and 8+/-4 (6, 11) BPM, respectively. Repeated testing during 3 months of therapeutic electrical activation demonstrated a durable response. CONCLUSIONS: These preliminary data suggest an acceptable safety of the procedure with a low rate of adverse events and support further clinical development of baroreflex activation as a new concept to treat resistant hypertension.

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Obesity is becoming an epidemic phenomenon in most developed countries. The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended. It is essential to monitor everyday food intake for obesity prevention and management. Existing dietary assessment methods usually require manually recording and recall of food types and portions. Accuracy of the results largely relies on many uncertain factors such as user's memory, food knowledge, and portion estimations. As a result, the accuracy is often compromised. Accurate and convenient dietary assessment methods are still blank and needed in both population and research societies. In this thesis, an automatic food intake assessment method using cameras, inertial measurement units (IMUs) on smart phones was developed to help people foster a healthy life style. With this method, users use their smart phones before and after a meal to capture images or videos around the meal. The smart phone will recognize food items and calculate the volume of the food consumed and provide the results to users. The technical objective is to explore the feasibility of image based food recognition and image based volume estimation. This thesis comprises five publications that address four specific goals of this work: (1) to develop a prototype system with existing methods to review the literature methods, find their drawbacks and explore the feasibility to develop novel methods; (2) based on the prototype system, to investigate new food classification methods to improve the recognition accuracy to a field application level; (3) to design indexing methods for large-scale image database to facilitate the development of new food image recognition and retrieval algorithms; (4) to develop novel convenient and accurate food volume estimation methods using only smart phones with cameras and IMUs. A prototype system was implemented to review existing methods. Image feature detector and descriptor were developed and a nearest neighbor classifier were implemented to classify food items. A reedit card marker method was introduced for metric scale 3D reconstruction and volume calculation. To increase recognition accuracy, novel multi-view food recognition algorithms were developed to recognize regular shape food items. To further increase the accuracy and make the algorithm applicable to arbitrary food items, new food features, new classifiers were designed. The efficiency of the algorithm was increased by means of developing novel image indexing method in large-scale image database. Finally, the volume calculation was enhanced through reducing the marker and introducing IMUs. Sensor fusion technique to combine measurements from cameras and IMUs were explored to infer the metric scale of the 3D model as well as reduce noises from these sensors.

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Adding virtual objects to real environments plays an important role in todays computer graphics: Typical examples are virtual furniture in a real room and virtual characters in real movies. For a believable appearance, consistent lighting of the virtual objects is required. We present an augmented reality system that displays virtual objects with consistent illumination and shadows in the image of a simple webcam. We use two high dynamic range video cameras with fisheye lenses permanently recording the environment illumination. A sampling algorithm selects a few bright parts in one of the wide angle images and the corresponding points in the second camera image. The 3D position can then be calculated using epipolar geometry. Finally, the selected point lights are used in a multi pass algorithm to draw the virtual object with shadows. To validate our approach, we compare the appearance and shadows of the synthetic objects with real objects.

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For broadcasting purposes MIXED REALITY, the combination of real and virtual scene content, has become ubiquitous nowadays. Mixed Reality recording still requires expensive studio setups and is often limited to simple color keying. We present a system for Mixed Reality applications which uses depth keying and provides threedimensional mixing of real and artificial content. It features enhanced realism through automatic shadow computation which we consider a core issue to obtain realism and a convincing visual perception, besides the correct alignment of the two modalities and correct occlusion handling. Furthermore we present a possibility to support placement of virtual content in the scene. Core feature of our system is the incorporation of a TIME-OF-FLIGHT (TOF)-camera device. This device delivers real-time depth images of the environment at a reasonable resolution and quality. This camera is used to build a static environment model and it also allows correct handling of mutual occlusions between real and virtual content, shadow computation and enhanced content planning. The presented system is inexpensive, compact, mobile, flexible and provides convenient calibration procedures. Chroma-keying is replaced by depth-keying which is efficiently performed on the GRAPHICS PROCESSING UNIT (GPU) by the usage of an environment model and the current ToF-camera image. Automatic extraction and tracking of dynamic scene content is herewith performed and this information is used for planning and alignment of virtual content. An additional sustainable feature is that depth maps of the mixed content are available in real-time, which makes the approach suitable for future 3DTV productions. The presented paper gives an overview of the whole system approach including camera calibration, environment model generation, real-time keying and mixing of virtual and real content, shadowing for virtual content and dynamic object tracking for content planning.

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The study assessed the economic efficiency of different strategies for the control of post-weaning multi-systemic wasting syndrome (PMWS) and porcine circovirus type 2 subclinical infection (PCV2SI), which have a major economic impact on the pig farming industry worldwide. The control strategies investigated consisted on the combination of up to 5 different control measures. The control measures considered were: (1) PCV2 vaccination of piglets (vac); (2) ensuring age adjusted diet for growers (diets); (3) reduction of stocking density (stock); (4) improvement of biosecurity measures (bios); and (5) total depopulation and repopulation of the farm for the elimination of other major pathogens (DPRP). A model was developed to simulate 5 years production of a pig farm with a 3-weekly batch system and with 100 sows. A PMWS/PCV2SI disease and economic model, based on PMWS severity scores, was linked to the production model in order to assess disease losses. This PMWS severity scores depends on the combination post-weaning mortality, PMWS morbidity in younger pigs and proportion of PCV2 infected pigs observed on farms. The economic analysis investigated eleven different farm scenarios, depending on the number of risk factors present before the intervention. For each strategy, an investment appraisal assessed the extra costs and benefits of reducing a given PMWS severity score to the average score of a slightly affected farm. The net present value obtained for each strategy was then multiplied by the corresponding probability of success to obtain an expected value. A stochastic simulation was performed to account for uncertainty and variability. For moderately affected farms PCV2 vaccination alone was the most cost-efficient strategy, but for highly affected farms it was either PCV2 vaccination alone or in combination with biosecurity measures, with the marginal profitability between 'vac' and 'vac+bios' being small. Other strategies such as 'diets', 'vac+diets' and 'bios+diets' were frequently identified as the second or third best strategy. The mean expected values of the best strategy for a moderately and a highly affected farm were £14,739 and £57,648 after 5 years, respectively. This is the first study to compare economic efficiency of control strategies for PMWS and PCV2SI. The results demonstrate the economic value of PCV2 vaccination, and highlight that on highly affected farms biosecurity measures are required to achieve optimal profitability. The model developed has potential as a farm-level decision support tool for the control of this economically important syndrome.

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BACKGROUND & AIMS: Refractory ascites (RA) affects 10% of patients with advanced cirrhosis and ascites. Usual therapy includes large volume paracentesis, and in selected patients, a transjugular portosystemic shunt (TIPS). These therapies may be associated with increased morbidity: paracentesis may induce circulatory dysfunction and impair quality of life and TIPS may induce encephalopathy and is associated with increased mortality in patients with severe liver dysfunction. We present the results of a multicenter, non-randomized trial to assess the safety and efficacy of a new automated pump system for treatment of RA. METHODS: Forty patients at 9 centers (February 2010-June 2011) received an implanted pump for the automated removal of ascites from the peritoneal cavity into the bladder, from where it was eliminated through normal urination. Patients were followed-up for 6months. The primary study outcome was safety. Secondary outcomes included recurrence of tense ascites and pump performance. RESULTS: Surgical complications occurred early in the study and became less frequent. The pump system removed 90% of the ascites and significantly reduced the median number of large volume paracentesis per month [3.4 (range 1-6) vs. 0.2 (range 0-4); p <0.01]. Cirrhosis-related adverse events decreased along follow-up. CONCLUSIONS: The automated pump seems an efficacious tool to move out ascites from the peritoneal cavity to the bladder. Its safety is still moderate, but a broad use in different countries will improve the surgical technique as well as the medical surveillance. A prospective randomized clinical trial vs. large volume paracentesis is underway to confirm these preliminary results.

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The poster demonstrates the preparatory steps of a digital multi-text edition that are abstracted from the experiences made in the Parzival Project, based at the University of Bern, the Berlin-Brandenburg Academy of Sciences and the University of Erlangen. This edition of Wolfram von Eschenbach’s German Grail novel, written shortly after 1200 and transmitted during several centuries in ca. hundred witnesses, has now been completed by more than a half of the textual corpus.

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BACKGROUND Stroke is a major cause of morbidity and mortality during open-heart surgery. Up to 60% of intraoperative cerebral events are emboli induced. This randomized, controlled, multicenter trial is the first human study evaluating the safety and efficacy of a novel aortic cannula producing simultaneous forward flow and backward suction for extracting solid and gaseous emboli from the ascending aorta and aortic arch upon their intraoperative release. METHODS Sixty-six patients (25 females; 68±10 years) undergoing elective aortic valve replacement surgery, with or without coronary artery bypass graft surgery, were randomized to the use of the CardioGard (CardioGard Medical, Or-Yehuda, Israel) Emboli Protection cannula ("treatment") or a standard ("control") aortic cannula. The primary endpoint was the volume of new brain lesions measured by diffusion-weighted magnetic resonance imaging (DW-MRI), performed preoperatively and postoperatively. Device safety was investigated by comparisons of complications rate, namely neurologic events, stroke, renal insufficiency and death. RESULTS Of 66 patients (34 in the treatment group), 51 completed the presurgery and postsurgery MRI (27 in the treatment group). The volume of new brain lesion for the treatment group was (mean±standard error of the mean) 44.00±64.00 versus 126.56±28.74 mm3 in the control group (p=0.004). Of the treatment group, 41% demonstrated new postoperative lesions versus 66% in the control group (p=0.03). The complication rate was comparable in both groups. CONCLUSIONS The CardioGard cannula is safe and efficient in use during open-heart surgery. Efficacy was demonstrated by the removal of a substantial amount of emboli, a significant reduction in the volume of new brain lesions, and the percentage of patients experiencing new brain lesions.

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Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.