Tracking filter and multi-sensor data fusion

In this paper factorization filtering, fusion filtering strategy and related algorithms are presented. Some results of implementation and validation using realistic data are given

Multi-target Tracking in a Test Range Scenario

Integrated Test Range (ITR) handles various types of multiple-target flight trials. To facilitatetarget tracking and estimation in such multi-target scenario, nearest neighbourhood (NN)technique-based data association algorithm has been adopted at ITR. The present paper discussesthe NN-based data association algorithm and its performance in a real flight trial situation byusing multiple-target track data from a multi-target tracking radar

METABOLISM OF INTRAVENOUS METHYLNALTREXONE IN MICE, RATS, DOGS AND HUMANS

were observed in rats. Dogs produced only one metabolite, MNTX-3-glucuronide (M9). In conclusion, MNTX was not extensively metabolized in humans. Conversion to methyl-6-naltrexol isomers (M4 and M5) and MNTX-3-sulfate (M2) were the primary pathways of metabolism in humans. MNTX was metabolized to a higher extent in mice than in rats, dogs, and humans. Glucuronidation was a major metabolic pathway in mice, rats and dogs, but not in humans. Overall, the data suggested species differences in the metabolism of MNTX

Prevalence and Risk Factors of Neurologic Manifestations in Hospitalized Children Diagnosed with Acute SARS-CoV-2 or MIS-C

Background: Our objective was to characterize the frequency, early impact, and risk factors for neurological manifestations in hospitalized children with acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or multisystem inflammatory syndrome in children (MIS-C). Methods: Multicenter, cross-sectional study of neurological manifestations in children aged <18 years hospitalized with positive SARS-CoV-2 test or clinical diagnosis of a SARS-CoV-2-related condition between January 2020 and April 2021. Multivariable logistic regression to identify risk factors for neurological manifestations was performed. Results: Of 1493 children, 1278 (86%) were diagnosed with acute SARS-CoV-2 and 215 (14%) with MIS-C. Overall, 44% of the cohort (40% acute SARS-CoV-2 and 66% MIS-C) had at least one neurological manifestation. The most common neurological findings in children with acute SARS-CoV-2 and MIS-C diagnosis were headache (16% and 47%) and acute encephalopathy (15% and 22%), both P < 0.05. Children with neurological manifestations were more likely to require intensive care unit (ICU) care (51% vs 22%), P < 0.001. In multivariable logistic regression, children with neurological manifestations were older (odds ratio [OR] 1.1 and 95% confidence interval [CI] 1.07 to 1.13) and more likely to have MIS-C versus acute SARS-CoV-2 (OR 2.16, 95% CI 1.45 to 3.24), pre-existing neurological and metabolic conditions (OR 3.48, 95% CI 2.37 to 5.15; and OR 1.65, 95% CI 1.04 to 2.66, respectively), and pharyngeal (OR 1.74, 95% CI 1.16 to 2.64) or abdominal pain (OR 1.43, 95% CI 1.03 to 2.00); all P < 0.05. Conclusions: In this multicenter study, 44% of children hospitalized with SARS-CoV-2-related conditions experienced neurological manifestations, which were associated with ICU admission and pre-existing neurological condition. Posthospital assessment for, and support of, functional impairment and neuroprotective strategies are vitally needed

Data association and tracking for a multi-senor multi-target scenario

Tracking in multi senor multi target (MSMT)scenario is a complex problem due to the uncertainties in the origin of observations.Solution to this problem requires appropriate gating and data association procedures to associate measurements with targets. A PC MATLAB program has been developed based on gating and data association using nearest neighborhood approach to track multiple targets with multiple ground based radars.In this paper the details of the procedure followed and the results of the performance of the algorithm for a typical(MSMT)situation are presented

Tracking filter and multi-sensor data fusion13;

In this paper factorization filtering, fusion filtering strategy and related algorithms are presented. Some results of implementation and validation using realistic data are give

Data association and fusion algorithms for tracking in presence of measurement loss

Tracking on multi-sensor multi-target (MSMT) scenario is a complex and difficult tasks due to the uncertainties in the origin of observations. This requires appropriate gating and data association procedures to associate measurements with targets. A PC MATLAB program, based on track oriented approach, is evaluated which uses Nearest Neighbour kalman filter (NNKF) and Probabilities Data association filter (PDAF)for tracking multiple targets from data of multiple sensors