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Integrated Approaches for the Delivery of Maternal and Child Health Services with Childhood Immunization Programs in Low- and Middle-Income Countries: Systematic Review Update 2011-2020.
Vaccines (Basel)
November 2024
Global Immunization Division, Global Health Center, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA.
: The integration of maternal and child health services (MCH) with routine immunization is an important global health strategy, particularly in low- and middle-income countries (LMICs). However, evidence is lacking regarding the best practices for service integration and the effect of integration on immunization and linked health service outcomes. : We searched publication databases and gray literature for articles published between 2011 and 2020 that include approaches to integrating MCH services with immunizations during the first two years of life in LMICs.
View Article and Find Full Text PDFDesign and Evaluation of a Cloud Computing System for Real-Time Measurements in Polarization-Independent Long-Range DAS Based on Coherent Detection.
Sensors (Basel)
December 2024
Institute of Mechanical Intelligence, Scuola Superiore Sant'Anna, Via G. Moruzzi 1, 56124 Pisa, Italy.
CloudSim is a versatile simulation framework for modeling cloud infrastructure components that supports customizable and extensible application provisioning strategies, allowing for the simulation of cloud services. On the other hand, Distributed Acoustic Sensing (DAS) is a ubiquitous technique used for measuring vibrations over an extended region. Data handling in DAS remains an open issue, as many applications need continuous monitoring of a volume of samples whose storage and processing in real time require high-capacity memory and computing resources.
View Article and Find Full Text PDFComparison of Methods to Assess Adherence to Infant and Young Child Feeding Practices and Provision of Low-Aflatoxin Porridge Flours in a Community-Based Intervention Trial.
Nutrients
December 2024
Office of the President, Goshen College, Goshen, IN 46526, USA.
Background: Levels of adherence to recommended protocols in an intervention trial can affect outcomes and confound the results. To broaden the evidence about the selection and utility of adherence measures in varying contexts, we describe the level of adherence to the Mycotoxin Mitigation Trial (MMT) randomized intervention using caregiver-reported survey questions and compare inferences of adherence between multi-module surveys and interactive 24 h dietary recalls based on our program theory.
Methods: The MMT was a two-arm cluster-randomized trial conducted in 52 health facilities (clusters) in central Tanzania.
Optimizing Swine Oral Fluid Sampling Procedures for Growing Pigs in Commercial Settings.
Pathogens
December 2024
Department of Veterinary Diagnostic and Production Animal Medicine, College of Veterinary Medicine, Iowa State University, Ames, IA 50011, USA.
Pen-based oral fluids are used extensively for surveillance and disease detection in swine, but there is sparse information on the sampling process itself. To address this shortcoming, we documented the pen-based oral fluid sampling process with the aim of optimizing the number of pigs in a pen that contributed to the sample. We quantified the effects of (1) previous experience with rope sampling (training), (2) the number of ropes suspended in the pen, and (3) sampling time on pig participation and pig-rope contact.
View Article and Find Full Text PDFAdvancements in Artificial Intelligence-Enhanced Imaging Diagnostics for the Management of Liver Disease-Applications and Challenges in Personalized Care.
Bioengineering (Basel)
December 2024
Department of Gastroenterology and Hepatology, Faculty of Medicine, Kindai University, 377-2 Ohno-Higashi, Osakasayama 589-8511, Japan.
Liver disease can significantly impact life expectancy, making early diagnosis and therapeutic intervention critical challenges in medical care. Imaging diagnostics play a crucial role in diagnosing and managing liver diseases. Recently, the application of artificial intelligence (AI) in medical imaging analysis has become indispensable in healthcare.
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