16 research outputs found

    Flight and Analytical Methods for Determining the Coupled Vibration Response of Tandem Helicopters

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    Chapter one presents a discussion of flight-test and analysis methods for some selected helicopter vibration studies. The use of a mechanical shaker in flight to determine the structural response is reported. A method for the analytical determination of the natural coupled frequencies and mode shapes of vibrations in the vertical plane of tandem helicopters is presented in Chapter two. The coupled mode shapes and frequencies are then used to calculate the response of the helicopter to applied oscillating forces

    Depression care management for late-life depression in China primary care: Protocol for a randomized controlled trial

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    <p>Abstract</p> <p>Background</p> <p>As a major public health issue in China and worldwide, late-life depression is associated with physical limitations, greater functional impairment, increased utilization and cost of health care, and suicide. Like other chronic diseases in elders such as hypertension and diabetes, depression is a chronic disease that the new National Health Policy of China indicates should be managed in primary care settings. Collaborative care, linking primary and mental health specialty care, has been shown to be effective for the treatment of late-life depression in primary care settings in Western countries. The primary aim of this project is to implement a depression care management (DCM) intervention, and examine its effectiveness on the depressive symptoms of older patients in Chinese primary care settings.</p> <p>Methods/Design</p> <p>The trial is a multi-site, primary clinic based randomized controlled trial design in Hangzhou, China. Sixteen primary care clinics will be enrolled in and randomly assigned to deliver either DCM or care as usual (CAU) (8 clinics each) to 320 patients (aged ≄ 60 years) with major depression (20/clinic; n = 160 in each treatment condition). In the DCM arm, primary care physicians (PCPs) will prescribe 16 weeks of antidepressant medication according to the treatment guideline protocol. Care managers monitor the progress of treatment and side effects, educate patients/family, and facilitate communication between providers; psychiatrists will provide weekly group psychiatric consultation and CM supervision. Patients in both DCM and CAU arms will be assessed by clinical research coordinators at baseline, 4, 8, 12, 18, and 24 months. Depressive symptoms, functional status, treatment stigma and clients' satisfaction will be used to assess patients' outcomes; and clinic practices, attitudes/knowledge, and satisfaction will be providers' outcomes.</p> <p>Discussion</p> <p>This will be the first trial of the effectiveness of a collaborative care intervention aiming to the management of late-life depression in China primary care. If effective, its finding will have relevance to policy makers who wish to scale up DCM treatments for late-life depression in national wide primary care across China.</p> <p>Study Registration</p> <p>The DCM project is registered through the National Institutes of Health sponsored by clinical trials registry and has been assigned the identifier: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01287494">NCT01287494</a></p

    Linking Symptom Inventories using Semantic Textual Similarity

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    An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment
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