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The sixteenth century
Published in Michael J. O’Dowd, The History of Medications for Women, 2020
The ‘river of stars’ which forms the Milky Way was understood by the ancients to be a river of life-giving goddess milk. Egyptians believed that the milk came from the udder of the heavenly cow, Hathor, or Isis in her bovine form. The word ‘galaxy’ itself came from the Greek gala, which means ‘milk’. The Milky Way was also known as the ‘river of the divine lady’ and also ‘mother of the sky’, the ‘moonway’ or the ‘track of the white cow’. In one well-known European nursery rhyme, the white cow jumped over the moon, leaving a trail of her ‘star-milk’ across the sky.
Technology Solutions and Programs to Promote Leisure and Communication Activities with People with Intellectual and other Disabilities
Published in Christopher M. Hayre, Dave J. Muller, Marcia J. Scherer, Everyday Technologies in Healthcare, 2019
Giulio E. Lancioni, Nirbhay N. Singh, Mark F. O’Reilly, Jeff Sigafoos
The second study involved a man who was considered to have a mild to moderate intellectual disability, presented with blindness and possessed clear, easily discriminable speech. He was provided with a Galaxy S3 smartphone with the S-voice module. The names and telephone numbers of the 14 persons available for the man’s telephone calls had been recorded in the device’s database. Specifically, the man had been guided to record those names in the device. Before the first telephone call of each session, the man was required to provide an access word (i.e. a greeting word) to activate the device. Thereafter, he was to use the word ‘Call’, followed by the name of the person with whom he wanted to get in touch to start a telephone call. He had to use the word ‘Stop’ to end a call when it was completed or if there was no answer from the person called. Data showed that the man was highly successful in performing his telephone calls independently throughout the intervention phases and the post-intervention check.
The World Wide Web
Published in David Coady, James Chase, The Routledge Handbook of Applied Epistemology, 2018
This vision of socio-technical integration lies at the heart of an important concept that has emerged in the context of the Web science literature. This is the concept of social machines (Palermos 2017; Smart and Shadbolt 2014). Social machines are systems in which human and (Web-based) machine elements are jointly involved in the mechanistic realization of phenomena that subtend the computational, cognitive, and social domains (Smart and Shadbolt 2014). From an epistemological perspective, a particular category of social machines is of particular interest. These are known as knowledge machines (Smart et al. 2017). A knowledge machine is a social machine that participates in some form of knowledge-relevant process, such as the acquisition, discovery, and representation of knowledge. Citizen science systems, such as Galaxy Zoo (Lintott et al. 2008), are one kind of knowledge machine that has been the focus of considerable research attention. These have grown in prominence over recent years, to the point where they play an important role in many forms of scientific practice (see Meyer and Schroeder 2015). Such characterizations are sufficient to make citizen science systems worthy of applied epistemological analysis, and this is especially so given the interest in applying epistemological theory to the understanding and analysis of scientific processes (e.g., Palermos 2015).
Deciphering cross-species reactivity of LAMP-1 antibodies using deep mutational epitope mapping and AlphaFold
Published in mAbs, 2023
Tiphanie Pruvost, Magali Mathieu, Steven Dubois, Bernard Maillère, Emmanuelle Vigne, Hervé Nozach
The Zymoprep Yeast Plasmid Miniprep II kit (Zymo Research, Irvine, USA) was used to extract plasmids from the sorted population. Regions of interest were amplified in a first PCR step and then adapters and barcodes needed for Illumina sequencing were added in a second PCR step. NGS was performed with an Illumina MiSeq (Illumina, San Diego, USA) device (2x300bp, v3 kit 600 cycles) with at least one million reads per population. The first steps of data analysis were performed on the Galaxy platform. Reads were first paired using the Pear function. Then, the reads with an unexpected length were eliminated using Filter FASTQ function. The following analysis steps were performed using RStudio software and eliminated sequences containing more than one mutation compared to the parental antigen sequence. Reads presenting a quality under 30 were also eliminated. After DNA translation, identical sequences were grouped and counted in order to calculate the mono-mutant enrichment ratio in each sorted population compared to the initial population.
Galaxy for open-source computational drug discovery solutions
Published in Expert Opinion on Drug Discovery, 2023
Anamika Singh Gaur, Selvaraman Nagamani, Lipsa Priyadarsinee, Hridoy J. Mahanta, Ramakrishnan Parthasarathi, G. Narahari Sastry
Drug discovery in academia and industry poses quite contrasting challenges where understanding the mechanism of action is key for the former, success in clinical development appears to be of prime importance in the later. In the 21st century, open-source software packages are available for a wide range of bioinformatics and chemoinformatics applications that include downloading, manipulating, and processing of small and macromolecules along with their properties [1–5]. In general, drug discovery software and tools are commonly developed for all the diseases, although different types of diseases demand contrasting requirements. In recent times, with the advancement in computational fields, it is warranted to develop customized computational tools for a given disease. Galaxy is an ideally suited web-based open-source computational workbench to analyze large datasets. The Galaxy can be customized to integrate analysis and visualization tools in a single framework. Galaxy is an open-source web-based platform that helps researchers to overcome accessibility, reproducibility, and transparency challenges in data-driven biomedical research [6–9]. The users required a minimal level of programming skills and the ability to use the command line and handle unique file formats. Some tools have complicated source code and it is very difficult for the computationally inexperienced scientists to compile them and reproduce the analysis in a different environment.