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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.

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).

Describes the importance of selenium (Se) for human health. Outlines the sources of Se in the environment and food. Gives UK recommended intakes. Calls for further research into the nutritional significance of Se.

In certain industrial operations, workers are required to stand for a prolonged duration. This leads to muscular fatigue in the legs, posing a threat to the productivity and well-being of the workers. This paper aims to address this problem of women in the clothing industry with an exoskeleton designed for lower extremities and improve productivity.

Ulrich’s product design approach has been followed with suitable modifications. The methodology involves a study to justify the need for this product and terminating at the physical and virtual evaluations of the product. Required anthropometric parameters are considered along the design process.

The exoskeleton discussed in this paper is an innovative product made of Aluminium 6061 alloy. During the simulation phase of the product, total von-mises stresses to a part bearing 1 leg were 31.5 MPa, 94.7 MPa and 284 MPa for aluminium, SS308 and springs, respectively. These values are below the yield limit by a great margin. Based on a user survey of this product, 72% of the targeted customers were interested in buying. Also, comparing electromyography (EMG) mean value of the voltage between workers’ leg with and without exoskeleton revealed that there was an improvement in the voltage by 2.5% when exoskeleton was used.

This paper emphasizes, for the first time – the necessity of an exoskeleton indigenized for the Indian population and the process of realizing it by designing an exoskeleton.

Earthquake usually causes death, injury, disability and destruction of buildings and infrastructure, and people with disabilities are usually affected more than healthy people. As undesirable experiences may also have positive outcomes, this study aims to investigate the experiences of PWD and identify the positive effects of earthquakes on them in Iran, as an earthquake-prone country.

In this qualitative study, 20 participants were selected purposively among those having physical disability, aged 23-55 years and with experience of an earthquake. Their opinions were collected using semi-structured interviews. Analysis was performed using thematic approach and MAXQDA software was used to organize the data.

The positive effects of earthquake were categorized into five main themes: promotion of preparedness, knowledge enhancement, improvement of structures, socio-economic improvement (economic situation enhancement and social cohesion promotion) and outstanding role of national and international non-governmental organizations.

Although disasters are generally unpleasant, in the long term, they can result in positive effects and may be considered as opportunities to improve the situation and eliminate certain limitations. It is also important to learn from experiences of people with disabilities and apply the lessons learned, for enhancing preparedness and providing better services in the response phase of disaster management. Additionally, paying attention to the positive attitudes of such people, with special conditions and limitations, indicates their enhanced resilience to cope with disasters and emergencies, including COVID-19, which should be taken into consideration by policymakers and planners in future programs.