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Many aspects of the self are lost as a consequence of having multiple sclerosis (MS). A person's identity can be altered by negative self-concepts, which are associated with poor psychological wellbeing and can lead individuals to reconstruct their sense of self. The Social Identity Model of Identity Change argues that previously established identities form a basis of continued social support, by providing grounding and connectedness to others to facilitate the establishment of new identities. Family support is a salient factor in adjustment to MS and may enable the establishment of new identities. The purpose of this paper is to investigate identity reconstruction following a diagnosis of MS.

A meta-synthesis of the qualitative literature was conducted to examine the relationship between identity change and family identity of people with MS and other family members.

In all, 16 studies were identified that examined identity change and the family following a diagnosis of MS. Coping strategies used by people with MS and their wider family groups, affect the reconstruction of people's identity and the adjustment to MS. Receiving support from the family whilst a new identity is constructed can buffer against the negative effects of identity loss.

The family base is strengthened if MS-related problems in daily life are adapted into the individual and family identity using positive coping styles.

This review provides an interpretation and explanation for results of previous qualitative studies in this area.

The purpose of this study is to examine the advancement of cultural transformation over time demands certain alterations in human perceptions. It also aims to examine the 21st century’s many radical changes in India, the constant legal battles to decriminalize homosexuality, and challenges to the rigid dichotomy between heterosexuality and homosexuality. Besides, it influences popular culture among the masses, which has turned out to create a more visible space for the lesbian community. In India, lesbian literature begins synchronously under the shades of women’s writing and feminism that wires new hopes for their identity.

This paper examines a primary text as Indian writer Abha Dawesar’s Babyji (2005). There comes the iconic work of Abha Dawesar’s Babyji (2005), which creates a turning point by introducing the life, inner conflict and turbulence of a teenage girl. In addition, a textual analysis of this novel brings forth an analysis of attributes such as sexuality, gender and the interplay of caste and class that meld lesbian childhood and adolescence. This paper also examines how a lesbian girl adapts to and negotiates her maturation amidst vivid social scenarios and cultural conditioning.

A few studies (Hidalgo, et al., 2013; Bem, 1989; Pyne, 2016) show many children have reached or crossed their teenage life without accurate or affirmative knowledge of sexuality and gender. Parents, teachers and even other intellectuals of the adult world fail to transfer their knowledge effectively to children. Definitely, the relevance of sex education is paramount, but more important is what implementation tactics should be used for the same cause. The point is that sex education should not be condensed into a certain gender or perpetuate parochial discrimination. It needs to adapt an age-appropriate curriculum for the cognitive and emotional development of the individuals. Considering these factors, understanding comprehensive sex education is what is most likely to find sustainable remedies for this matter. Gerald writes about a socialization process and gays and lesbians hiding their identity from family and society; a fear of rejection; there is a social gap in peer and family spheres. These fears prevent lesbian or gay young persons from fully developing their identities (1999). Rao and Mason tested a model derived from minority stress theory in which the perceived impact of Section 377 increases depressive symptoms of sexual minorities by increasing concealment stress, leading to a diminished sense of belonging. Because of their minority status, they are more vulnerable to and have a higher prevalence of mental illness than heterosexual individuals (2018).

Babyji has created a discourse to perpetuate normativity and gives importance to the mental health of the excluded lesbian group. It opens a door to studying teenage groups’ issues and their challenges to understanding social and mental issues regarding their identity. A study on this untouched area is required to highlight their issues and mental health problems. This research is an initiative step to create and provide a platform to raise awareness in society.

This work aims to develop a novel fuzzy associator rule-based fuzzified deep convolutional neural network (FDCNN) architecture for the classification of smartphone sensor-based human activity recognition. This work mainly focuses on fusing the λ_max method for weight initialization, as a data normalization technique, to achieve high accuracy of classification.

The major contributions of this work are modeled as FDCNN architecture, which is initially fused with a fuzzy logic based data aggregator. This work significantly focuses on normalizing the University of California, Irvine data set’s statistical parameters before feeding that to convolutional neural network layers. This FDCNN model with λ_max method is instrumental in ensuring the faster convergence with improved performance accuracy in sensor based human activity recognition. Impact analysis is carried out to validate the appropriateness of the results with hyper-parameter tuning on the proposed FDCNN model with λ_max method.

The effectiveness of the proposed FDCNN model with λ_max method was outperformed than state-of-the-art models and attained with overall accuracy of 97.89% with overall F1 score as 0.9795.

The proposed fuzzy associate rule layer (FAL) layer is responsible for feature association based on fuzzy rules and regulates the uncertainty in the sensor data because of signal inferences and noises. Also, the normalized data is subjectively grouped based on the FAL kernel structure weights assigned with the λ_max method.

Contributed a novel FDCNN architecture that can support those who are keen in advancing human activity recognition (HAR) recognition.

A novel FDCNN architecture is implemented with appropriate FAL kernel structures.