Office of Naval Research

I read with interest “[Association between family physician gender and patient service times. Evidence from Ontario][1]”[1][2] by Kralj et al in the January 2026 issue of Canadian Family Physician . The article examined associations between family physician gender, patient encounter duration,

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This article presents the development of an ecosystem for creating and updating maps in real time using data obtained from dashcam devices based on an SDK provided by Navmii. The proposed solution makes it possible to automatically recognize road sign

The UK Institute of Naval Medicine operates a Heat Illness Clinic (HIC) to assess service personnel for heat tolerance following Exertional Heat Illness (EHI). This study aims to identify employment outcomes and EHI recurrence rates for those assessed. A retrospective cohort study of patients seen in the HIC in 2019. Heat Tolerance Assessment (HTA) data were collected. Information on employment status and EHI recurrence were gathered from the clinical record. Data from 99 personnel were included; 78% were unrestricted at one year and 9% had been, or were likely to be, medically discharged due to EHI susceptibility. The remaining 13% had some level of ongoing limitation. Of the 84 personnel who were initially assessed as heat tolerant, 6 (7%) went on to have another episode of EHI and 3 of these (4%) were medically discharged. Of the 15 personnel who were initially assessed as heat intolerant, none have gone on to have a further EHI episode after 2 years and 6 were medically discharged. Eleven of the 99 personnel (11%) had their initial EHI on arduous selection activities for elite military units, and all these personnel were assessed as heat tolerant. Most of those referred to the HIC are assessed and returned to unrestricted duty within 4 months. A minority of personnel have ongoing employment restrictions at 1 year. Arduous selection activities are high risk for EHI, regardless of HTA outcome. Those who are found to be heat tolerant on assessment remain at risk of EHI recurrence.

In order to solve that problems of few ammunition support personnel, low support efficiency and repeated statistics, the classification model of emergency ammunition material support task is studied, the application of PPSVM in the classification of emergency ammunition material support task is analyzed, the probability output model of multi- classification support vector machine is established, and then the classification process is completed by selecting the class number with the largest posterior probability as the class output of test samples The experimental results show that the method can solve the classification problem of emergency ammunition material support task.