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Cyber-Threat Landscape in Healthcare Industry and Legal Framework Governing Personal Health Information in India
2021 and 2022 have been the years of frequent cyberattacks. India remains in the top 25 countries severely affected by the continuous cyber-attacks and tops the list. The healthcare department is amongst the most affected area. In 2020, the healthcare department suffered a severe impact with around 348K cyber-attacks alone on Indian healthcare infrastructure. The recent occurrence of cyber-attack on AIIMS hospital in December 2022 followed by several other incidences of data breaches have made the concerned authorities pro-active on exercising vigilance and reforming the legal and technical system to protect the health infrastructure. This paper has been developed on extensive literature and focuses on describing the nature of electronic health records, the risks they are exposed to along with as to why they are so susceptible to these cyber-risks. Furthermore, the paper also deals with different kinds of threats affecting the privacy and security of electronic health records specifically. The paper analyzes Indian legal framework, briefly compares it with international legal framework (specifically US & EU) and highlights the shortcomings in Indian legislative framework followed by laying down certain recommendations primarily highlighting the possible changes required in Indian legal framework and practices that can be adopted at organizational level to overcome and mitigate such risks. N. Raizada, P. Srivastava, 2024. -
Managing coworker conflict: investigating the effect of workplace phubbing and mindfulness on employee deviant and negligent behavior
Purpose: This study aims to examine the influence of workplace phubbing on employee deviant behavior and negligence, while also investigating the mediating role of coworker conflict. Additionally, the study explores the moderating effect of workplace mindfulness on the relationship between workplace phubbing, the mediators and employee deviant behavior and negligence. Design/methodology/approach: Data were gathered from employees in the service sector in the UAE using an online survey questionnaire. A total of 374 participants submitted complete responses. The studys hypotheses were tested through regression-based moderated path analysis, incorporating conditional process modeling and nonlinear bootstrapping. Findings: The study indicates that experiencing phubbing at work contributes to feelings of coworker conflict, which subsequently leads to increased interpersonal deviance and employee negligence. Moreover, workplace mindfulness weakens the positive influence of being phubbed on coworker conflict, interpersonal deviance and employee negligence. Originality/value: To the best of the authors knowledge, no previous studies have examined the negative impact of being phubbed at the individual employee level within the service industry. This study aims to contribute to both theory and practice by elucidating the mediating mechanism of coworker conflict and exploring the moderating effects of workplace mindfulness. 2024, Emerald Publishing Limited. -
REMEMBERING PLACE: The Temporality of Trauma in Rudraprayag after the 2013 Flash Floods
The 2013 flash floods reproduced an everyday that was textural, the returning past of the event combined with gestures from within the everyday, to disorient survivors of the event. I attempt in this essay to analyze the return of the event as producing psycho-spatial affects, drawn from the psyches own propensity to return while repressing the event that causes the return, described within psycho-analytic literature as afterwardsness. Such afterwardsness is conditioned by the sheer incomprehensibility of environmental change that took place in just three days in the Mandakini Valley between June 15 and June 17, 2013. Following the flood, delays with the recovery process, and particularly with the process of compensation, exacerbate this trauma, leading to an extension of the temporality of trauma infinitely forward. (2024), (American Anthropological Association). All rights reserved. -
Efficient Mitosis Segmentation and Detection in Breast Cancer Histopathological Images Using YOLOv5 Model
Mitosis count serves as a critical biomarker in breast cancer research, aiding in the prediction of aggressiveness, prognosis, and grade of the disease. However, accurately identifying mitotic cells amidst shape and stain variations, while distinguishing them from similar objects like lymphocytes and cells with dense nuclei, presents a significant challenge. Traditional machine learning methods have struggled with this task, particularly in detecting small mitotic cells, leading to high inter-rater variability among pathologists. In recent years, the rise in deep learning has reduced the subjectivity of mitosis detection. However, Deep Learning models face challenges with segmenting and classifying mitosis due to its intricate morphological variations, cellular heterogeneity, and overlapping structures. In response to these challenges, this study presents an Intelligent Mitosis Segmentation and Detection in Breast Cancer Histopathological Images Using Deep Learning (IMSD-BCHIDL) Model. The purpose of the IMSD-BCHIDL technique is to segment and classify mitosis in the histopathological images. To accomplish this, the IMSD-BCHIDL technique mainly employs YOLO-v5 model, which proficiently segments and classifies the mitosis cells. In addition, InceptionV3 is applied as a backbone network for the YOLO-v5 model, which helps in capturing extensive contextual details from the input image and results in improved detection tasks. For demonstrating the greater solution of the IMSD-BCHIDL method of the IMSD-BCHIDL technique, a wide range of experimental analyses is made. The simulation values portrayed the improved solution of the IMSD-BCHIDL system with other recent DL models. 2024 by the authors. -
Breeding distrust during artificial intelligence (AI) era: howtechnological advancements, jobinsecurity and job stress fuel organizational cynicism?
Purpose: This study examines how technological advancements and psychological capital contribute to job stress. Furthermore, the paper examines how job insecurity, job stress and job involvement influence the cynicism of recently laid-off employees. Despite various research studies, there is a lack of understanding of employees views on their work future and its probable influence on their job behaviors in this era of technology. Design/methodology/approach: A quantitative method was used to collect a sample of 403 recently laid-off employees. The research tool of this study was a questionnaire, and the sampling technique was stratified random sampling. IBM SPSS and AMOS software were utilized to ensure the trustworthiness and accuracy of constructs via factor analysis. The proposed hypotheses were tested using structural equation modeling. Findings: The analysis showed that technological advancements, specifically in job-related stress, job involvement and job insecurity, significantly affect organizational cynicism. Job involvement is negatively associated with employees cynicism. Practical implications: The current study adds to the comprehension of shifts in the perceived behavior of employees toward their organizations due to factors like the adoption of new technology in the organization, job stress, job insecurity and job involvement. Accordingly, there will be a need to form a favorable working atmosphere so that employees can perform their jobs with positive psychology and without any insecurity or stress. Originality/value: The study is thought to contribute to the literature in terms of measuring organizational cynicism while layoffs continue due to AI advancements. 2024, Emerald Publishing Limited. -
Employee experience, well-being and turnover intentions in the workplace
Purpose: This study aims to examine the role of employee experience in influencing employee well-being and turnover intentions within organizations. The mediating role of well-being will also be investigated, along with an exploration of whether these relationships differ across genders, specifically in the Indian corporate context. Design/methodology/approach: A descriptive, quantitative study was conducted using structured questionnaires to gather data from 111 employees in the Indian corporate sector. The study used a non-probability judgment sampling method. Data was analyzed through SPSS for descriptive and inferential statistics, and partial least squares was used to explore mediation and model fit. Findings: The study found a significant impact of employee experience on well-being, as well as a negative correlation between both employee experience and turnover intention and well-being and turnover intention. Well-being was found to partially mediate the relationship between employee experience and turnover intention. Gender-based analysis revealed no significant differences in the relationships between these variables for men and women. Originality/value: This research highlights the universal applicability of employee experience as a predictor of well-being and turnover intention, irrespective of gender. By establishing that gender does not moderate these relationships, this study provides new insights challenging traditional assumptions about gender disparities in workplace outcomes. 2024, Emerald Publishing Limited. -
Machine learningbased approaches for enhancing human resource management using automated employee performance prediction systems
Purpose: This study focuses on enhancing the accuracy and efficiency of employee performance prediction to enhance decision making and improve organisational productivity. By introducing advance machine learning (ML) techniques, this study aims to create a more reliable and data-driven approach to evaluate employee performance. Design/methodology/approach: In this study, nine machine learning (ML) models were used for forecasting employee performance: Random Forest, AdaBoost, CatBoost, LGB Classifier, SVM, KNN, XGBoost, Decision Tree and one Hybrid model (SVM + XGBoost). Each ML model is trained on an HR data set covering various features such as employee demographics, job-related factors and past performance records, ensuring reliable performance predictions. Feature scaling techniques, namely, min-max scaling, Standard Scaler and PCA, have been used to enhance the effectiveness of employee performance prediction. The models are trained to classify data, predicting whether an employees performance meets expectations or needs improvement. Findings: All proposed models used in the study can correctly categorize data with an average accuracy of 94%. Notably, the Random Forest model demonstrates the highest accuracy across all three scaling techniques, achieving optimise accuracy, respectively. The results presented have significant implications for HR procedures, providing businesses with the opportunity to make data-driven decisions, improve personnel management and foster a more effective and productive workforce. Research limitations/implications: The scope of the used data set limits the study, despite our models delivering high accuracy. Further research could extend to different data sets or more diverse organisational settings to validate the models effectiveness across various contexts. Practical implications: The proposed ML models in the study provide essential tools for HR departments, enabling them to make more informed data driven decisions with regard to employee performance. This approach can enhance personnel management, improve workforce productivity and fostering a more effective organisational environment. Social implications: Although AI models have shown promising outcomes, it is crucial to recognise the constraints and difficulties involved in their use. To ensure the fair and responsible use of AI in employee performance prediction, ethical considerations, privacy problems and any biases in the data should be properly addressed. Future work will be required to improve and broaden the capabilities of AI models in predicting employee performance. Originality/value: This study introduces an exclusive combination of ML models for accurately predicting employee performance. By employing these advanced techniques, the study offers novel insight into how organisations might transition from a conventional evaluation method to a more advanced and objective, data-backed approach. 2024, Emerald Publishing Limited. -
Antecedents and Trajectories of the Child and Adolescent Mental Health Crisis: Assimilating Empirically Guided Pathways for Stakeholders
Importance: Amid and following the COVID-19 pandemic, there has been a growing focus on understanding the underlying etiology of the mental health crisis in children and youth. However, there remains a dearth of empirically driven literature to comprehensively explore these issues. This narrative review delves into current mental health challenges among children and youth, examining perspectives from both pre-pandemic and pandemic periods. Observations: Research highlights reveal concerning statistics, such as 1 in 5 children experience mental health disorders. The pandemic exacerbated these issues, introducing stressors such as job losses and heightened anticipatory anxiety. Race relations have emerged as a significant public health concern, with biases impacting students, particularly affecting Asian, black, and multiracial individuals. Substance use trends indicate a rise in overdose deaths, particularly among adolescents, with cannabis use linked to adverse outcomes. Increased screen time and income disparities further compound mental health challenges. Conclusions and Relevance: Proposed public health mitigation strategies include improving access to evidence-based treatments, implementing legislative measures for early identification and treatment of developmental disorders, and enhancing suicide prevention efforts. School-based interventions and vocational-technical education are crucial, alongside initiatives targeting sleep hygiene, social media usage, nutrition, and physical activity. Educating health care professionals about both physical and mental health is essential to address workforce burnout and effectively manage clinical complexities. 2024 Physicians Postgraduate Press, Inc. -
Beyond Binary: Exploring the Dynamics of Bi-Curiosity Propulsion and Persistence Among Young Women
Sexual identity fails to adhere to the dichotomous models, transcending to a more fluid quality than normative compulsory heterosexuality. The present study investigates the experience of bi-curiosity, focusing on its initiation among young women residing in urban India. Bi-curiosity, a sexual orientation questioning marked by exploratory experiences, is a possible but not a necessary precursor to bisexuality. This qualitative study explores on the psychological and social factors contributing to a bi-curious orientation. It focuses on the subjective processes of development and maintenance of sexual identity questioning. Three organizing themes emerged from the Reflective Thematic Analysis: (a.) Affective Indicators, (b.) Social Experiences, and (c.) Intimacy in friendships. While sexual identity questioning was propelled by more psychological factors, like physical attraction, fantasy, experienced jealousy toward men, and comfort with the same sex, social and environmental factors contribute significantly. Individual experiences with patriarchy, social attitudes toward same-sex relationships, and their representation on media platforms often reinforce the process. Another important contributor was womens close friendships with the same sex, which are sites for physical closeness, emotional intimacy, and personal growth, and share these characteristics with romantic relationships. These factors emerged as important reinforcers to the development and maintenance of sexual identity questioning. 2024 Taylor & Francis Group, LLC. -
We are Treated as Outsiders in Our Own City: Lived Experiences of Intersectional Stigma Against Sex Workers in Kolkata, India
Introduction: Sex workers in India experience intersectional stigma related to their gender identity, sexuality, and profession. The objective of the present study is to analyze the lived experiences of intersectional stigma against sex workers in Kolkata. Methods: We interviewed 30 cisgender female sex workers in March 2023 in Kolkata, India. Interviews were digitally audio recorded, translated from Bengali into English, and transcribed and coded using thematic analysis. Results: We identified five main themes regarding intersectional stigma: (1) internalized stigma regarding the shame associated with being a female sex worker, (2) perceived stigma of sex work as a dirty profession, associated with lower caste status, (3) enacted stigma against sex workers who are mothers, (4) enacted stigma against the children of sex workers, and (5) reduction of stigma through unionization/labor organizing. Conclusions: Intersectional stigma against sex workersis impacted by negative attitudes regarding gender, caste status, single motherhood, and occupation. We identified internalized stigma as a source of shame for sex workers. Sex workers also were perceived to beengaged in afilthy profession, associated with lower caste status. Those sex workers who were mothers experienced discrimination, as did their children. Respondents reported how collectivization has helped to address these experiences of stigma anddiscrimination. Policy Implications: Addressing the intersectional stigma against sex workers in Kolkata necessitates a shift in social attitudes.Findings underscore the urgent need for stigma reduction interventions and socialpolicies, including (1) labor protections for sex workers, (2) individual/community-level interventions for sex workers, and (3) media campaigns to address stigma reduction. By understanding the lived experiences of sex workers, we may develop better interventions to reduce stigma in the lives of sex workers in Kolkata and throughout India. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Machine Learning Based Optimal Feature Selection for Pediatric Ultrasound Kidney Images Using Binary Coati Optimization
Chronic kidney disease (CKD) one of the most dangerous illnesses. Early detection is vital for improving survival rates and underscoring the need for an intelligent classifier to differentiate between normal and abnormal kidney ultrasound images. Features extracted from an image have a significant impact on classification accuracy. In this study, we present a Binary Coati optimization algorithm (BCOA) for feature selection in CKD, which focuses on reducing the high dimensionality features extracted from ultrasound images, including GLCM, GLRLM, GLSZM, GLDM, NGTDM, and first order, by employing BCOA-S shaped and BCOA-V shaped transfer functions that convert BCOA from a continuous search space to a binary form, which helps in the selection of optimal features to improve the classification performance while reducing the feature dimensionality. The reduced feature was evaluated using six machine-learning classifiers: Random Forest, Support Vector Machine, Decision tree, K-nearest Neighbor, XG-boost, and Nae Bayes. The efficiency of the proposed framework was assessed based on accuracy, precision, recall, specificity, f1 score and AUC curve. BCOA-V outperformed in terms of accuracy, precision, recall, specificity, F1 score and AUC curve by 99%,100%,97%,100%, 98%, and 98%, respectively. This makes it a superior choice for CKD diagnosis and is a valuable tool for feature selection in medical diagnosis. (2024), (Intelligent Network and Systems Society). All rights reserved. -
DISTANCE SPECTRUM OF TWO FAMILIES OF GRAPHS
Let H1 and H2 be two copies of the complete graph Kn, n ? 3 with vertex sets V(H1) = {v1,v2...,vn} and V(H2) = {u1,u2,...,un}. Graph ?(n,p), 1 ? p ? n-1, is obtained from the union of graphs H1 and H2 by adding edges {uivi)|i ? {1, 2...,p}}. Graph ?(n) is obtained from the union of graphs H1 and H2 by joining each vertex vi of H1 to every vertex in {u1, u2, ..., un} \ {ui}, i = 1, 2, ..., n. The adjacency spectrum of ?(n, p) and ?(n) were determined in [9]. An open problem posed in [7] was to find families of graphs of diameter greater than two, for which the adjacency and distance spectrum are both integral. To answer the open problem, the distance spectrum of the above family of graphs is calculated, and new distance equienergetic graphs are constructed in this paper. 2024 Jangjeon Research Institute for Mathematical Sciences and Physics. All rights reserved. -
Development of Biocompatible Barium peroxide/Pluronic F127/L-ornithine Composite for Enriched Antimicrobial, Antioxidant and Anticancer Potential: An in vitro Study
Osteosarcoma (MG-63) is a type of bone cancer affects mostly adolescents and young adults. Disease-causing microorganisms like Bacillus subtilis, Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae and Candida albicans pose serious illness in humans. There is a need to develop multifunctional composite to combat cancer and other most common disease caused by disease causing microorganisms. In this context, BaO2 and pluronic F127, L-Ornithine coated BaO2 (BaO2-PF127-LO) composite have been prepared and characterized by XRD, FTIR, UV-Vis, SEM, HRTEM, EDAX, and XPS analytical techniques. BaO2 and BaO2-PF127-LO were orthorhombic crystalline structure and the crystallite size was found as 32nm for BaO2 and 26nm for modified BaO2 PL studies revealed the green emission observed at 506nm for BaO2-PF127-LO composite which is absent in the case of bare BaO2. Antimicrobial activity of BaO2 and BaO2-PF127-LO was investigated. MTT assay was performed to determine the anticancer potential while the DPPH free radical scavenging assay was carried out to determine the antioxidant potential. The experiment study revealed that the BaO2-PF127-LO exhibited enhanced antimicrobial, antioxidant, and anticancer activity and low toxicity when compared to pristine BaO2. The experimental results revealed that the BaO2-PF127-LO composite holds promising potential for biomedical applications. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Development and Analysis of Current Collectors for Proton Exchange Membrane Fuel Cells
Hydrogen fuel cells are gaining popularity in power-consuming devices due to their zero-emission characteristics. However, ohmic resistance, which arises from the resistance to electron flow through the electrodes and external circuit, can cause reduced efficiency and voltage drops in a fuel cell. This research aims to develop current collector plates for proton exchange membrane fuel cells with optimal design, high electrical conductivity, and thermal conductivity to mitigate ohmic resistance. Six different designs and five different materials-copper, brass, aluminum, stainless steel 316, and stainless steel 304 were considered for this purpose. The study involved experimental electrical conductivity and fuel cell performance tests to identify the best material and design for the current collector. Results indicated that brass and copper exhibited the least resistivity and favorable material characteristics. Consequently, all six current collector plate designs were developed using brass and copper with various machining and finishing processes. Performance testing on a fuel cell test station revealed that brass current collector plate design 5, featuring open ratios, demonstrated superior performance. Ultimately, the optimum design and material selection of the current collector plates have led to the development of fuel cells with reduced ohmic resistance and improved overall performance. 2024, Politechnika Lubelska. All rights reserved. -
A hybrid deep learning and quantum computing approach for optimized encryption algorithms in secure communications
As online dangers get worse, there is a greater need for strong encryption methods to protect private conversations. Utilizing the strengths of both deep learning and quantum computing, this study suggests a new mixed method for improving the security of communication systems by making encryption algorithms work better. When it comes to keeping up with new online threats, traditional security methods often fall behind. Deep learning techniques could be a good way to improve encryption algorithms because they let the system learn and change to new attack methods. In the meantime, quantum computing offers unmatched computing power that can completely change how cryptography works by using quantum events like superposition and entanglement. Our suggested method combines the flexibility of deep learning with the computing power of quantum computing to get around the problems with current encryption methods. This will make safe communication systems more resistant to attacks from smart people. Through tests and models, we show that our mixed approach works better and more effectively than current encryption methods. This shows that it has the ability to solve the growing safety problems in a world that is becoming more and more linked. 2024, Taru Publications. All rights reserved. -
Development vs. Rights A Case for Sustainable Development of Onge Tribes of Little Andaman
Human rights and environmental protections are often violated as a consequence of development activities. In addition to harming the environment, this increases the marginalisation of those who are already marginalised. The development paradigm that is based on the interests of the majority not only tends to retard the indigenous people but also renders them incapable of competing with the majority. For the indigenous people, development has always been a problem rather than a solution. Development initiatives under the umbrella of globalisation with a label of monotony, ignore the aspects of the diverse livelihoods of many indigenous peoples. The Niti Aayog proposed in its vision document, the Sustainable Development of Little Andaman, in 2021, that the island should be developed into a megacity by utilising its natural features and strategic location. The long-term objective is to develop the island into a major financial tourism hub that can rival Hong Kong and Singapore. This plan will, on the one hand, advance commerce, employment, and economic growth; on the other hand, environmental conservation issues will also arise. Concerns over this vision document have indeed been voiced by several academics, environmentalists, and conservationists due to issues with Onge indigenous rights, ecological fragility, and earthquake and tsunami susceptibility. In this context, the research article aims to study and analyse the proposed megacity project and its impact on the rights of Onge tribes and the environment. Sahana Florence and Achyutananda Mishra, 2024. -
Energy-efficient and secure routing strategy for opportunistic data transmission in WSNs
Driven by the critical importance of routing in Wireless Sensor Networks (WSNs) and the security vulnerabilities present in existing protocols, this research aims to address the key challenges in securing WSNs. Many current routing protocols focus on computational efficiency but fall short of providing strong security measures, leaving them vulnerable to malicious attacks. Reactive protocols, often preferred for their reduced bandwidth usage, heighten security concerns due to their limited resources for maintaining network routes, while proactive alternatives require more resources. Additionally, the ad hoc nature and energy limitations of WSNs make traditional security models, designed for wired and wireless networks, impractical. To overcome these limitations, this paper introduces the Secured Energy-Efficient Opportunistic Routing Scheme for sustainable WSNs. The proposed protocol is designed to enhance security by continuously updating neighbor information and verifying the validity of routing parameters, while also being power-aware, a critical factor given the energy constraints of WSNs. The protocol has been evaluated through simulation experiments, measuring key performance indicators such as throughput, average end-to-end delay (E2 delay), energy consumption, and network lifetime. The results demonstrate that the proposed protocol effectively strengthens WSN security while addressing the unique operational constraints of these networks. 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
A novel approach for integrating cryptography and blockchain into IoT system
The quick advancement of Internet of Things (IoT) emphasizes the significance of cryptography and blockchain ensuring the security of sensitive data and connected devices. Blockchain technology and encryption play key roles in ensuring the security of the expansive IoT network. Blockchain offers decentralized trust, immutability, and transparency to IoT networks and transactions, while encryption serves to protect IoT data from unauthorized access. It is a novel approach for integrating cryptography and blockchain into IoT System, cryptography and blockchain stand out as robust technologies that enhance the security of IoT systems. The implementation of an integrated architecture, along with a strategic integration approach, further strengthens the security measures. This methodology proves valuable for managing and validating digital transactions on decentralized, immutable networks. This work also explores the potential significance of integrating cryptography and blockchain into IoT System, this functions and applications in enhancing IoT security. This methodology introduces encryption techniques tailored for resource-constrained IoT devices, which are essential for ensuring end-to-end security. 2024, Taru Publications. All rights reserved. -
GLOBAL POVERTY AND HUMAN SECURITY: A VASUDHAIVA KU?U?BAKA? PERSPECTIVE
Poverty has been a persistent issue throughout human history, affecting societies worldwide. In the major industrialized nations, social welfare policies served as the primary approach to poverty alleviation until the late 20th century. In 1994, the United Nations Development Programme (UNDP) introduced a human-centred sustainable development model, emphasizing human security as a means to eradicate poverty and other forms of insecurity. Despite these efforts, data from the World Bank and other international organizations indicate that a significant portion of the global population remains impoverished, highlighting the ongoing need for development and inclusivity. The ancient Indian concept of vasudhaiva ku?u?baka?, which promotes open-mindedness, interconnectedness, brotherhood, and fairness, offers a universal vision rooted in a family model. Interpreted in a contemporary context, vasudhaiva ku?u?baka? presents a global perspective that resonates with the principles of human security. Integrating this concept with the human security framework holds the potential to address global poverty and promote the universality of human rights. This article seeks to reconstruct the human security paradigm through the perspective of vasudhaiva ku?u?baka? in order to eradicate poverty and promote global well-being. 2024 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore). -
Photoisomerization Dynamics of 2-[(E)-(4-fluorophenyl)diazenyl]-1 H -imidazole: A Theoretical and Experimental Insight
This study investigates the photoresponsive behavior of substituted azobenzenes with a specific focus on their nonlinear optical response. This study suggests that azoimidazole substitution is a better alternative to azobenzene derivatives for nonlinear optical responses. The synthesis, characterization, photophysical property and isomerization pathway of 2-[(E)-(4-fluorophenyl)diazenyl]-1H-imidazole (E-2g) are presented as an optical limiter through a comprehensive blend of experimental and theoretical approaches. Notably, E-2g exhibited a lower energy barrier than reported azobenzenes. The trans-to-cis photostationary state was reached in 75 min, while the cis-to-trans state was achieved in 60 min at 354 nm. The study further explores the photoisomerization pathway of E-2g, highlighting its nonlinear absorption, which has a nonlinear absorption coefficient (?eff) of 8.8 10-11 m/W at 20 ?J, as determined by Z-scan measurements. The results suggest that E-2g exhibits significant nonlinear absorption characteristics, which helps in applications requiring protection from intense light sources. 2024 World Scientific Publishing Company.