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The increasing age of humans leads to reduced strength and muscle mass. Increasing age can also cause a decrease in the function of other organs, such as the urinary tract so that some elderly people have difficulty moving places to urinate and need to use diapers. The types of urinary catheters on the market are intermittent catheters, suprapubic catheters, and external catheters. The purpose of this study was to design a special external catheter for women with the name Ecable. Ecable is designed according to the needs of users both the elderly themselves and people who care for the elderly. The method used in this design is design thinking. ecable consists of five major components: a urine bag, an alarm, a hose, special underwear, and a urine funnel. The advantages offered by this product are easy to install and remove, comfortable to use, minimize unpleasant odors, there is a full urine bag detection alarm, minimize the cause of irritation, and are cost-effective because they can be used repeatedly. This catheter is expected to help the elderly and caregivers to overcome existing needs.

The 5-year project 'Breeding roots, tubers and banana products for end user preferences' (RTBfoods) focused on collecting consumers' preferences on 12 food products to guide breeding programmes. It involved multidisciplinary teams from Africa, Latin America, and Europe. Diverse data types were generated on preferred qualities of users (farmers, family and entrepreneurial processors, traders or retailers, and consumers). Country-based target product profiles were produced with a comprehensive market analysis, disaggregating gender's role and preferences, providing prioritised lists of traits for the development of new plant varieties. We describe the approach taken to create, in the roots, tubers, and banana breeding databases, a centralised and meaningful open access to sensory information on food products and genotypes. Biochemical, instrumental textural, and sensory analysis data are then directly connected to the specific plant record while user survey data, bearing personal information, were analysed, anonymised, and uploaded in a repository. Names and descriptions of food quality traits were added into the Crop Ontology for labelling data in the databases, along with the various methods of measurement used by the project. The development and application of standard operating procedures, data templates, and adapted trait ontologies improved the data quality and its format, enabling the linking of these to the plant material studied when uploaded in the breeding databases or in repositories. Some modifications to the database model were necessary to accommodate the food sensory traits and sensory panel trials. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry., (© 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.)

Applying an equity lens to quality improvement (QI) by collecting, reviewing, and using data that measure health disparities helps identify whether QI interventions improve outcomes evenly and equally across the population or have a greater impact in an advantaged or disadvantaged group. Methodological issues inherent in measuring disparities include appropriately selecting data sources; ensuring reliability and validity of equity data; choosing a suitable comparison group; and understanding between-group variation. The integration and utilization of QI techniques to promote equity is dependent on meaningful measurement to develop targeted interventions and provide a means of ongoing real-time assessment., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Modern breeding methods integrate next-generation sequencing and phenomics to identify plants with the best characteristics and greatest genetic merit for use as parents in subsequent breeding cycles to ultimately create improved cultivars able to sustain high adoption rates by farmers. This data-driven approach hinges on strong foundations in data management, quality control, and analytics. Of crucial importance is a central database able to (1) track breeding materials, (2) store experimental evaluations, (3) record phenotypic measurements using consistent ontologies, (4) store genotypic information, and (5) implement algorithms for analysis, prediction, and selection decisions. Because of the complexity of the breeding process, breeding databases also tend to be complex, difficult, and expensive to implement and maintain. Here, we present a breeding database system, Breedbase (https://breedbase.org/, last accessed 4/18/2022). Originally initiated as Cassavabase (https://cassavabase.org/, last accessed 4/18/2022) with the NextGen Cassava project (https://www.nextgencassava.org/, last accessed 4/18/2022), and later developed into a crop-agnostic system, it is presently used by dozens of different crops and projects. The system is web based and is available as open source software. It is available on GitHub (https://github.com/solgenomics/, last accessed 4/18/2022) and packaged in a Docker image for deployment (https://hub.docker.com/u/breedbase, last accessed 4/18/2022). The Breedbase system enables breeding programs to better manage and leverage their data for decision making within a fully integrated digital ecosystem., (© The Author(s) 2022. Published by Oxford University Press on behalf of Genetics Society of America.)