The Autism Treatment Network and Autism Intervention Research Network on Physical Health were established in 2008 with goals of improving understanding of the medical aspects of autism spectrum disorders. Over the past decade, the combined network has conducted >2 dozen clinical studies, established clinical pathways for best practice, developed tool kits for professionals and families to support better care, and disseminated these works through numerous presentations at scientific meetings and publications in medical journals. As the joint network enters its second decade continuing this work, it is undergoing a transformation to increase these activities and accelerate their incorporation into clinical care at the primary care and specialty care levels. In this article, we describe the past accomplishments and present activities. We also outline planned undertakings such as the establishment of the Autism Learning Health Network, the increasing role of family members as co-producers of the work of the network, the growth of clinical trials activities with funding from foundations and industry, and expansion of work with primary care practices and autism specialty centers. We also discuss the challenges of supporting network activities and potential solutions to sustain the network.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1542/2019-1895D | DOI Listing |
Sci Rep
December 2024
College of Economics and Management, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
In light of the Chinese government's dual carbon goals, achieving cleaner production activities has become a central focus, with regional environmental collaborative governance, including the management of agricultural carbon reduction, emerging as a mainstream approach. This study examines 268 prefecture-level cities in China, measuring the carbon emission efficiency of city agriculture from 2001 to 2022. By integrating social network analysis and a modified gravity model, the study reveals the characteristics of the spatial association network of city agricultural carbon emission efficiency in China.
View Article and Find Full Text PDFSci Rep
December 2024
Merchant Marine College, Shanghai Maritime University, Shanghai, 201306, China.
The intelligent identification of wear particles in ferrography is a critical bottleneck that hampers the development and widespread adoption of ferrography technology. To address challenges such as false detection, missed detection of small wear particles, difficulty in distinguishing overlapping and similar abrasions, and handling complex image backgrounds, this paper proposes an algorithm called TCBGY-Net for detecting wear particles in ferrography images. The proposed TCBGY-Net uses YOLOv5s as the backbone network, which is enhanced with several advanced modules to improve detection performance.
View Article and Find Full Text PDFSci Rep
December 2024
College of Information Engineering, SuQian University, SuQian, 223800, China.
The safety and reliability of rotating machinery hinge significantly on the proper functioning of rolling bearings. In the last few years, there have been significant advances in the algorithms for intelligent fault diagnosis of bearings. However, the vibration signals collected by machines are inevitably affected by irrelevant noise because of the complex working environments of bearings.
View Article and Find Full Text PDFSci Rep
December 2024
Health Services Research and Pharmacoepidemiology Unit, Foundation for the Promotion of Health and Biomedical Research of Valencia Region (FISABIO), Avenida Cataluña, 21, 46020, Valencia, Spain.
Improvement of post-stroke outcomes relies on patient adherence and appropriate therapy maintenance by physicians. However, comprehensive evaluation of these factors is often overlooked. This study assesses secondary stroke prevention by differentiating patient adherence to antithrombotic treatments (ATT) from physician-initiated interruptions or switches.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Internal Medicine, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, Busan, 48108, Republic of Korea.
This study aimed to investigate alterations in a multilayer network combining structural and functional layers in patients with end-stage kidney disease (ESKD) compared with healthy controls. In all, 38 ESKD patients and 43 healthy participants were prospectively enrolled. They exhibited normal brain magnetic resonance imaging (MRI) without any structural lesions.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!