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Exercising is a key approach adopted by muscular dystrophy patients to halt the weakening of muscles as it can eventually lead to serious immobility issues. Though it is essential to exercise on a daily basis for healthy living, there is no mention of any research effort in the current literature regarding the development of an apparel product for these mobility-affected patients that might assist them both in meeting their exercising needs and providing them some comfort in their daily living. Thus, this paper aims to focus on identifying the specific needs of muscular dystrophy victims and proposing special adaptive clothing solutions to support their daily exercise and mobility needs.

To achieve the objectives of this study, attention was focused on the muscular dystrophy afflicted women in Sri Lanka. Semi-structured interviews were conducted with the female victims of muscular dystrophy and their lifestyles were observed carefully; additional data were gathered by holding semi-structured interviews with their physiotherapists. Further, interviews were conducted with both garment technologists and fabric technologists too. Data gathered through these methods were analyzed qualitatively using the principles of thematic analysis and then aggregate conclusions were drawn.

It was observed that the patients were engaged in special activities such as exercising three times a day besides following their normal day-to-day activities to maintain and develop muscle strength. It soon became evident that these women found it difficult to perform their daily exercise routines with their regular clothing and were looking for custom made clothing they could wear all day long in comfort and avoid the problems that arose while exercising. The study specifies the requirements that must be met to satisfy both generic and specific needs. Considering all these aspects some adaptive clothing solutions were proposed to support daily exercising activity with respect to comfort, convenience, health and safety, as well as socio-cultural and psychological needs.

The area of fusing generic and specific features to support the daily exercising needs of muscular dystrophy victims is an untouched field of experimentation and being a need of the disabled, the present study marks a milestone on the way to a novel area of apparel design, besides exploring a new field of research.

Diagnosing genetic neuromuscular disorder such as muscular dystrophy is complicated when the imperfection occurs while splicing. This paper aims in predicting the type of muscular dystrophy from the gene sequences by extracting the well-defined descriptors related to splicing mutations. An automatic model is built to classify the disease through pattern recognition techniques coded in python using scikit-learn framework.

In this paper, the cloned gene sequences are synthesized based on the mutation position and its location on the chromosome by using the positional cloning approach. For instance, in the human gene mutational database (HGMD), the mutational information for splicing mutation is specified as IVS1-5 T > G indicates (IVS - intervening sequence or introns), first intron and five nucleotides before the consensus intron site AG, where the variant occurs in nucleotide G altered to T. IVS (+ve) denotes forward strand 3′– positive numbers from G of donor site invariant and IVS (−ve) denotes backward strand 5′ – negative numbers starting from G of acceptor site. The key idea in this paper is to spot out discriminative descriptors from diseased gene sequences based on splicing variants and to provide an effective machine learning solution for predicting the type of muscular dystrophy disease with the splicing mutations. Multi-class classification is worked out through data modeling of gene sequences. The synthetic mutational gene sequences are created, as the diseased gene sequences are not readily obtainable for this intricate disease. Positional cloning approach supports in generating disease gene sequences based on mutational information acquired from HGMD. SNP-, gene- and exon-based discriminative features are identified and used to train the model. An eminent muscular dystrophy disease prediction model is built using supervised learning techniques in scikit-learn environment. The data frame is built with the extracted features as numpy array. The data are normalized by transforming the feature values into the range between 0 and 1 aid in scaling the input attributes for a model. Naïve Bayes, decision tree, K-nearest neighbor and SVM learned models are developed using python library framework in scikit-learn.

To the best knowledge of authors, this is the foremost pattern recognition model, to classify muscular dystrophy disease pertaining to splicing mutations. Certain essential SNP-, gene- and exon-based descriptors related to splicing mutations are proposed and extracted from the cloned gene sequences. An eminent model is built using statistical learning technique through scikit-learn in the anaconda framework. This paper also deliberates the results of statistical learning carried out with the same set of gene sequences with synonymous and non-synonymous mutational descriptors.

The data frame is built with the Numpy array. Normalizing the data by transforming the feature values into the range between 0 and 1 aid in scaling the input attributes for a model. Naïve Bayes, decision tree, K-nearest neighbor and SVM learned models are developed using python library framework in scikit-learn. While learning the SVM model, the cost, gamma and kernel parameters are tuned to attain good results. Scoring parameters of the classifiers are evaluated using tenfold cross-validation using metric functions of scikit-learn library. Results of the disease identification model based on non-synonymous, synonymous and splicing mutations were analyzed.

Certain essential SNP-, gene- and exon-based descriptors related to splicing mutations are proposed and extracted from the cloned gene sequences. An eminent model is built using statistical learning technique through scikit-learn in the anaconda framework. The performance of the classifiers are increased by using different estimators from the scikit-learn library. Several types of mutations such as missense, non-sense and silent mutations are also considered to build models through statistical learning technique and their results are analyzed.

To the best knowledge of authors, this is the foremost pattern recognition model, to classify muscular dystrophy disease pertaining to splicing mutations.

Impairment of intelligence in Duchenne muscular dystrophy (DMD) patients was described by Duchenne de Boulogne himself in 1868. Further studies report intelligence disorders with mayor impairment of memory. The aim of the present study was to assess the presence of affective and personality disorders in a group of children affected by DMD. Twenty six male DMD patients, mean age eleven and four months years old, were assessed for their affective and personality disorder. Only eight subjects had a total IQ below average with major difficulties in verbal and visual-spatial memory, comprehension, arithmetic and vocabulary. All the subjects presented some disorders: tendency to marginalization and isolation, self-depreciation, sense of insecurity, hypochondriac thoughts and marked state of anxiety. These disorders are often a dynamic prolongation of a psychological process which starts when the diagnosis is made and continues, in a slow and latent fashion, throughout the evolution of the disease.

The treatment and care of persons with a disability should and must be all encompassing. With the expansion of the knowledge that proper dieting can make a difference in the individual’s development and quality of life, attention must be focused on using proper food intake to remediate the negative impact of a disability. Food is related to proper healthcare; therefore, we must include proper nutrition in working with learners with exceptionalities. We must add to the list of treatments not only educational intervention, social interaction, and independent living, but also food intake. This chapter looks at the dietary needs of several disabling conditions, and addresses how particular dietary food selections help in their development and their ability to learn integration, playing skills with others, and working independently when called on to do so. Therefore, for the purposes of this chapter, we focus on exceptionalities such as cognitive disability, autism spectrum disorder (ASD), Down syndrome, attention deficit hyperactivity disorder (ADHD), muscular dystrophy, and cystic fibrosis.

Students with physical and health impairments represent a small but growing group of individuals with diverse educational needs. They are those students whose physical limitations or health problems interfere with school attendance or learning to such an extent that special services, training, equipment, materials, or facilities are required. Therefore, the purpose of this chapter is to discuss some of these impairments and acquaint both general and special educators with interventions for helping students with physical and health impairments succeed.

Research was conducted on parents’ experience of caring for a child living with Duchenne muscular dystrophy (DMD). The focus of this research was on the key psychological aspects of the process of adjustment to the illness of their child (family and spousal relationship, daily life, emotions, career, spirituality, and coping strategies). There was evidence throughout the study of gender‐specific differences in constructing the different aspects of the shared experience. The main findings included major differences in the initial reaction and coping styles between mothers and fathers. These differences could be perceived as a threat or could serve as a source of isolation between parents. Additional findings included the unequal sharing of caregiving tasks between partners: the primary caregiving role usually being assumed by the mother, with the father playing a supportive role. The unique contribution of this study in further describing the lived experience of parents of a child with DMD is its attention to the internal dynamic of the relationship between mothers and fathers. This dynamic is highly dependent on the respective roles of primary and secondary caregiver. This research has implications for the design and implementation of intervention strategies aimed at couples caring for a child with DMD, or with other severe, chronic, and uniformly fatal illnesses.

This study aims to analyse the nature and forms of digital content that may influence e-participation for persons with disabilities (PWDs) during a flood disaster.

This paper undertakes a case study of the 2019 and 2020’s flood in Kerala, India. In-depth interviews with rehab workers during the flood are used in the study. Topic modelling and sentiment analysis are carried out using Twitter data. The native language responses from Facebook forums related to PWDs are analysed manually to construct taxonomy of problematic content

The results show that problematic content toward PWDs in the social media occurs during a flood. The extreme and exploitative content results in disability exclusion. Thus, e-participants fail to address the actual disability-specific requirements through social media during a disaster.

The paper explores social media content toward PWDs. Implications of findings on citizens’ e-participation competency are delineated. Existing e-participation literature reports a low degree of disability e-participation in social media. Exploring disability e-participation helps to design more inclusive participation platforms. Further studies can explore the disability consciousness among e-participants for a more inclusive space.

The development of problematic content in the social media environment is alarming. Regulatory frameworks are also less adequate. Hence, policies for enabling inclusive participation that is not limited to the information technology infrastructure is needed.

First, the citizens will get more insights for meaningful disability e-participation. Second, inclusive e-participation platform designs will help to reduce problematic content generation.

Disability e-participation requires regional studies. But there are fewer studies on disability e-participation from developing nations. The current study considered the regional context and complexities of disability e-participation. This paper gives policy recommendations for an inclusive e-participation.

Professor H. M. Evans, when making a study of the reproductive capacity of rats at the University of California in 1922, found that animals given a diet containing all the then known vitamins failed to produce normal litters. This observation indicated that another vitamin was required for fertility and subsequently led to the recognition of vitamin E. The vitamin was known to be present in lettuce and wheat germ, since when either of these were added to the rats' feed their fertility was restored. Subsequently, in 1936, by a lengthy procedure for concentrating the vitamin, Evans was successful in isolating the pure substance from wheat germ oil. It was identified as an alcohol with the chemical formula G29H50O2 and found to be fat soluble. At the suggestion of Professor G. Calhoun, Evans introduced the name “a‐toco‐pherol” for the pure compound (from the Greek tokos = childbirth, phero = to bear, and “‐ol” indicating that the substance is an alcohol).

Theories of platform strategy and adoption have been largely derived from studies of their application in the information and communications technology (ICT) sector. These platforms vary in openness, with the model of open source software providing the best-known exemplar for open platforms.

This exploratory field study examines the degree to which nine attributes of ICT platforms are applicable to open platforms in biotechnology. Using a combination of interview and secondary data, it identifies three patterns of such biotechnology platforms – IP commons, hackerspaces, and crowdsourced patient registries – and the degree to which these nine attributes apply. It shows the impact of ICT platforms and open source software on open source approaches to biotechnology, and how the latter are affected by the technical, legal, and institutional differences between information technology and biotechnology.

Instead of open source software platforms organized around modular interfaces, complements, ecosystems, and two-sided markets, this study instead suggests a model of open source knowledge platforms which benefits from economies of scale but not indirect network effects. From this, it discusses the generalizability of the ICT-derived models of open source platforms and offers suggestions for future research.