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Mental health treatment: Exploring the potential of augmented reality and virtual reality

By producing immersive, individualized, and captivating therapeutic experiences, augmented reality (AR) and virtual reality (VR) may significantly transform mental health treatment. These technologies provide efficacious resolutions for exposure therapy, augmenting conventional methodologies, mitigating social disapproval, and fortifying the therapeutic alliance. Virtual and augmented reality increase the accessibility and convenience of therapy by enabling highly individualized interventions. Training for mental health professionals, rigorous research, compliance with data privacy regulations, and adherence to ethical standards are essential for responsible use. Augmented reality (AR) and virtual reality (VR) can expand the accessibility of mental health services as costs decrease, thereby ultimately enhancing the welfare of those in search of assistance and recovery. Incorporating augmented reality and virtual reality into clinical practice may make mental health treatment more engaging, effective, and individualized. 2024, IGI Global. All rights reserved.

Conference Paper

Mental Workload Estimation Using EEG

Mental workload contributes considerably to the outcome or the performance of any task. The concern of human workload increases during a human-machine collaboration task or in a multitasking environment. This paper presents a comparative study of machine learning algorithms used to estimate workload using Electroencephalography (EEG) data. An open-access EEG dataset acquired during a 'simultaneous capacity (SIMKAP) experiment' and 'no task' is used to create and validate models for binary classification of workload as present and absent respectively. The paper presents an implementation of various classification models that use EEG data to predict the workload. In this paper, implementation for KNN classifier (57.3%), Random Forest classifier (57.19%), MLP network classifier (58.2%), CNN+ LSTM network classifier (58.68%), and LSTM network classifier (61.08%) has been reported. The paper can be further extended to study operator workload in real-time using a brain-computer interface paradigm for any kind of task in a real-world application. The workload classification can be further used in human-machine tasks to decide task allocation between the system to achieve optimal performance in a complex critical system. 2020 IEEE.

Article

Mentha spicata assisted AgCuO nanocomposite enables anti-diabetic and vitamin-C sensing activities

Diabetes mellitus (DM), a multifactorial chronic health condition, affects a sizable portion of the global population, and more people are expected to contract it in the future, according to the World Health Organisation (WHO). Diabetes mellitus can be treated with conventional drugs, but most of the medications have a variety of side effects. The use of nanocomposites (NCs) to treat diabetes has been prioritized in this scenario. In this study, AgCuO NCs were synthesized using a green method using Mentha spicata leaf extract and their physicochemical properties were investigated with a variety of analytical techniques. According to an extensive in vivo and in vitro analysis of the biological activities of as-synthesized AgCuO NCs, AgCuO NCs possess effective antibacterial, anti-diabetic, and anti-hyperlipidemic characteristics. When AgCuO NCs are administered to STZ-induced animals in a concentration-based manner, the blood levels of inflammatory and liver marker enzymes are reduced and antioxidant enzyme levels are increased. Besides, AgCuO NCs exhibit excellent sensing activity with a limit of detection of 86 nM against Vitamin-C. This study reveals that AgCuO NCs derived from Mentha spicata may, therefore, prove to be a very successful anti-diabetic and biosensor candidate in the future. 2024 Elsevier B.V.

Article

Mentors perceived interest, motivation, and volunteering intention at DREAMS after school intervention programme

DREAMS stands for Desire, Readiness, Empowerment, Action, and Mastery for Success. Dreams afterschool intervention programme (ASIP) is to empower children who are weak in psychosocial skills to realize their full potential and to plan for a successful life with the help of college student mentors and senior community mentors. The present study explored the college student mentors interest and motivation to serve at DREAMS and the volunteering intention to stay or discontinue as mentors. The study bases its investigation purely on the mentors revelation of their experiences of DREAMS ASIP. Study followed phenomenological inquiry method and conducted semi-structured interview with 10 college-student mentors, which included 6 active mentors and 4 dropouts. A face-to-face interview conducted by the researchers recorded all the unique points diligently and conducted the data analysis using thematic analysis. Study found 3 main themes and 12 subordinate themes out of thematic analysis. The master themes are mentors interest, mentors motivation, and mentors volunteering experiences. The results section of the article presents the details of themes and sub-themes along with few excerpts of interviewees. Implications of the study might help other ASPs to understand the nature of their volunteers interest and motivation. Future researchers may study factors affecting the mentors strengths and weaknesses within the organisation. 2023 RESTORATIVE JUSTICE FOR ALL.

Article

Mergers and acquisitions in India Information Technology Industry and its impact on shareholders wealth

International Journal of Research in Commerce, IT & Management Vol. 2, Issue 4, pp. 118-121 ISSN No. 2231-5756

Article

Mesoporous Iron Aluminophosphate: An efficient Catalyst for One Pot Synthesis of Amides By Ester-Amide Exchange Reaction

Volume 233

Conference Paper

Mesoporous iron aluminophosphate: An efficient catalyst for one pot synthesis of amides by ester-amide exchange reaction

A series of metal aluminophosphates (MAlP: M = V, Fe, Co, Ni & Cu) were prepared by co-precipitation method. All the materials were characterized by various physico-chemical techniques. The materials were found to be mesoporous and moderately acidic. The catalytic activity of the materials was investigated in the synthesis of benzamides in a single pot reaction under solvent free refluxing conditions from methyl benzoate and different amines. Iron aluminophosphate was found to be the most effective catalyst for the synthesis of benzamides with 100% selectivity. The isolated yield of benzamide varied from 46% to 100% depending on the nature of amine. A possible reaction mechanism has been proposed which correlates the surface acidity and catalytic activity of the catalyst. The catalyst could be recycled for about three times without any appreciable loss in activity, thus making the method ecofriendly and economical.

Article

Mesoporous onion-like carbon nanostructures from natural oil for high-performance supercapacitor and electrochemical sensing applications: Insights into the post-synthesis sonochemical treatment on the electrochemical performance

Although onion-like carbon nanostructures (OLCs) are attractive materials for energy storage, their commercialization is hampered by the absence of a simple, cost-effective, large-scale synthesis route and binder-free electrode processing. The present study employs a scalable and straightforward technique to fabricate sonochemically tailored OLCs-based high-performance supercapacitor electrode material. An enhanced supercapacitive performance was demonstrated by the OLCs when sonicated in DMF at 60 C for 15 min, with a specific capacitance of 647 F/g, capacitance retention of 97% for 5000 cycles, and a charge transfer resistance of 3 ?. Furthermore, the OLCs were employed in the electrochemical quantification of methylene blue, a potential COVID-19 drug. The sensor demonstrated excellent analytical characteristics, including a linear range of 100 pM to 1000 pM, an ultralow sensitivity of 64.23 pM, and a high selectivity. When used to identify and quantify methylene blue in its pharmaceutical formulation, the sensor demonstrated excellent reproducibility, high stability, and satisfactory recovery. 2021 The Author(s)

Conference Paper

Message efficient ring leader election in distributed systems

Leader Election Algorithm, not only in distributed systems but in any communication network, is an essential matter for discussion. Tremendous amount of work are happening in the research community on election as network protocols are in need of co-ordinator process for the smooth running of the system. These so called Coordinator processes are responsible for the synchronization of the system otherwise, the system loses its reliability. Furthermore, if the leader process crashes, the new leader process should take the charge as early as possible. New leader is one among the currently running processes with the highest process id. In this paper we have presented a modified version of ring algorithm. Our work involves substantial modifications of the existing ring election algorithm and the comparison of message complexity with the original algorithm. Simulation results show that our algorithm minimizes the number of messages even in worst case scenario. 2013 Springer Science+Business Media.

Article

Message framing and COVID-19 vaccine acceptance among millennials in South India

Vaccine hesitancy and refusal remain a major concern for healthcare professionals and policymakers. Hence, it is necessary to ascertain the underlying factors that promote or hinder the uptake of vaccines. Authorities and policy makers are experimenting with vaccine promotion messages to communities using loss and gain-framed messages. However, the effectiveness of message framing in influencing the intention to be vaccinated is unclear. Based on the Theory of Planned Behaviour (TPB), this study analysed the impact of individual attitude towards COVID-19 vaccination, direct and indirect social norms, perceived behavioural control and perceived threat towards South Indian millennials intention to get vaccinated. The study also assessed the effect of framing vaccine communication messages with gain and loss framing. Data was collected from 228 Millennials from South India during the COVID-19 pandemic from September to October 2021 and analysed using PLS path modelling and Necessary Condition Analysis (NCA). The findings reveal that attitudes towards vaccination, perceived threat and indirect social norms positively impact millennials intention to take up vaccines in both message frames. Further, independent sample t-test between the framing groups indicate that negative (loss framed message) leads to higher vaccination intention compared to positive (gain framed message). A loss-framed message is thus recommended for message framing to promote vaccine uptake among millennials. These findings provide useful information in understanding the impact of message framing on behavioural intentions, especially in the context of vaccine uptake intentions of Millennials in South India. Copyright: 2022 Prakash et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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