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Play development in children with disabilties

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ISBN: 9783110522143 9783110522112 Year: Pages: 228 DOI: 10.1515/9783110522143 Language: English
Publisher: De Gruyter
Subject: Social Sciences --- Psychology
Added to DOAB on : 2017-12-21 18:30:20
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This book is the result of the first two-year work of Working Group 1 of the network “LUDI – Play for children with disabilities”. LUDI is an Action (2014-2018) financed by COST; it is a multidisciplinary network of more than 30 countries and almost 100 researchers and practitioners belonging to the humanistic and technological fields to study the topic of play for children with disabilities within the framework of the International Classification of Functioning Disability and Health (WHO, 2001).The principal objective of this book is to bring the LUDI contribution to the important topic of play in children with disabilities, because today an international consensus on the definition of play and disabilities is still lacking. The process of ensuring equity in the exercise of the right to play for children with disabilites requests three actions: to approach this topic through a “common language”, at least all over Europe; to put play at the centre of the multidisciplinary research and intervention regarding the children with disabilities; to grant this topic the status of a scientific and social theme of full visibility and recognized authority. Children with disabilities face several limitations in play, due to several reasons: impairments; playgrounds, toys and other play tools that are not accessible and usable; environments and contexts that are not accessible nor inclusive; lack of educational awareness and intentionality; lack of specific psycho-pedagogical and rehabilitative competence; lack of effective intervention methodologies. Moreover, disabled children’s lives are dominated by medical and rehabilitative practices in which play is always an activity aiming to reach an objective or to provoke an improvement; play for the sake of play is considered a waste of time. The concept of play for the sake of play strongly refers to the distinction between play activities and play-like activities. Play activities are initiated and carried out by the player (alone, with peers, with adults, etc.) for the only purpose of play itself (fun and joy, interest and challenge, love of race and competition, ilinx and dizziness, etc.). They have of course consequences on growth and development, but these consequences are not intentionally pursued. Play-like activities are initiated and conducted by an adult (with one or more children), in educational, clinical, social contexts; they are playful and pleasant, but their main objective is other than play: e.g., cognitive learning, social learning, functional rehabilitation, child's observation and assessment, psychological support, psychotherapy, etc. This book, then, contributes to a clear distinction between play and play-like activities that, hopefully, will bring to new developments in play studies.

Guidelines for supporting children with disabilities' play. Methodologies, tools, and contexts

Authors: --- ---
ISBN: 9783110613445 Year: Pages: 172 DOI: 10.1515/9783110613445 Language: English
Publisher: De Gruyter
Subject: Education
Added to DOAB on : 2018-09-11 11:41:35
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Play for the sake of play, without any secondary goals, if of utmost importance for children’s wellbeing and development. In this book you’ll find guidelines to support children with disabilities’ play. Providing ready-to-use information in a lay-person language, this book is for parents, teachers, rehabilitation professionals, toy manufacturers, policy makers and all persons interested in the topic of play for children with disabilities.

Application of Bioinformatics in Cancers

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ISBN: 9783039217885 9783039217892 Year: Pages: 418 DOI: 10.3390/books978-3-03921-789-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Biotechnology
Added to DOAB on : 2019-12-09 11:49:16
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This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible.

Keywords

comorbidity score --- mortality --- locoregionally advanced --- HNSCC --- curative surgery --- traditional Chinese medicine --- health strengthening herb --- cancer treatment --- network pharmacology --- network target --- high-throughput analysis --- brain metastases --- colorectal cancer --- KRAS mutation --- PD-L1 --- tumor infiltrating lymphocytes --- drug resistance --- gefitinib --- erlotinib --- biostatistics --- bioinformatics --- Bufadienolide-like chemicals --- molecular mechanism --- anti-cancer --- bioinformatics --- cancer --- brain --- pathophysiology --- imaging --- machine learning --- extreme learning --- deep learning --- neurological disorders --- pancreatic cancer --- TCGA --- curation --- DNA --- RNA --- protein --- single-biomarkers --- multiple-biomarkers --- cancer-related pathways --- colorectal cancer --- DNA sequence profile --- Monte Carlo --- mixture of normal distributions --- somatic mutation --- tumor --- mutable motif --- activation induced deaminase --- AID/APOBEC --- transcriptional signatures --- copy number variation --- copy number aberration --- TCGA mining --- cancer CRISPR --- firehose --- gene signature extraction --- gene loss biomarkers --- gene inactivation biomarkers --- biomarker discovery --- chemotherapy --- microarray --- ovarian cancer --- predictive model --- machine learning --- overall survival --- observed survival interval --- skin cutaneous melanoma --- The Cancer Genome Atlas --- omics --- breast cancer prognosis --- artificial intelligence --- machine learning --- decision support systems --- cancer prognosis --- independent prognostic power --- omics profiles --- histopathological imaging features --- cancer --- intratumor heterogeneity --- genomic instability --- epigenetics --- mitochondrial metabolism --- miRNAs --- cancer biomarkers --- breast cancer detection --- machine learning --- feature selection --- classification --- denoising autoencoders --- breast cancer --- feature extraction and interpretation --- concatenated deep feature --- cancer modeling --- interaction --- histopathological imaging --- clinical/environmental factors --- oral cancer --- miRNA --- bioinformatics --- datasets --- biomarkers --- TCGA --- GEO DataSets --- hormone sensitive cancers --- breast cancer --- StAR --- estrogen --- steroidogenic enzymes --- hTERT --- telomerase --- telomeres --- alternative splicing --- network analysis --- hierarchical clustering analysis --- differential gene expression analysis --- cancer biomarker --- diseases genes --- variable selection --- false discovery rate --- knockoffs --- bioinformatics --- copy number variation --- cell-free DNA --- methylation --- mutation --- next generation sequencing --- self-organizing map --- head and neck cancer --- treatment de-escalation --- HP --- molecular subtypes --- tumor microenvironment --- Bioinformatics tool --- R package --- machine learning --- meta-analysis --- biomarker signature --- gene expression analysis --- survival analysis --- functional analysis --- bioinformatics --- machine learning --- artificial intelligence --- Network Analysis --- single-cell sequencing --- circulating tumor DNA (ctDNA) --- Neoantigen Prediction --- precision medicine --- Computational Immunology

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