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This study presents a pioneering investigation into the wide array of coping mechanisms employed by individuals in the year 2023, with a focus on data collected through the popular social media platform TikTok. Coping mechanisms are essential strategies that people adopt to navigate the challenges and stressors of everyday life, yet little research has been conducted on their comprehensive compilation across different backgrounds, countries, and experiences. Using TikTok as a data collection tool allowed us to access a diverse and extensive pool of participants, representing various cultural, social, and demographic backgrounds. Our study collates coping mechanisms reported by users from different parts of the world, facilitating the identification of both universal and culture-specific strategies. This research contributes to the existing literature by providing a holistic view of coping mechanisms without being limited to specific fields or populations. By analyzing the coping methods shared on TikTok, we reveal a comprehensive list of strategies employed by people from diverse walks of life. The findings of this study not only shed light on how individuals cope with challenges in the modern era but also offer insights into the evolving coping trends and the role of social media in disseminating coping strategies. Understanding these coping mechanisms can have implications for mental health professionals, practitioners, and policymakers seeking to provide support and resources to individuals facing different stressors and hardships.

This paper focuses on enhancing Bengali Document Layout Analysis (DLA) using the YOLOv8 model and innovative post-processing techniques. We tackle challenges unique to the complex Bengali script by employing data augmentation for model robustness. After meticulous validation set evaluation, we fine-tune our approach on the complete dataset, leading to a two-stage prediction strategy for accurate element segmentation. Our ensemble model, combined with post-processing, outperforms individual base architectures, addressing issues identified in the BaDLAD dataset. By leveraging this approach, we aim to advance Bengali document analysis, contributing to improved OCR and document comprehension and BaDLAD serves as a foundational resource for this endeavor, aiding future research in the field. Furthermore, our experiments provided key insights to incorporate new strategies into the established solution.

During laser and ultrasound thermotherapy it is always desirable to have a precise necrosis of deeply seated tumor preserving the adjoining healthy tissue with minimum thermally induced nociceptive pain sensation to the patient. The aim of the present study is to determine the effects of nanoparticle mixed tissues under pulsed and continuous heating during high intensity focused ultrasound (HIFU) and laser interstitial thermal therapy (LITT). The present problem incorporating the tissue thermal relaxation times ( ) was solved in a 3-dimensional multilayered vasculature breast tumor model signifying the complex inhomogeneous tissue structure. The coupled Radiative transfer, Helmontz, momentum, dual phase lag (DPL) and equilibrium equations for optic, acoustic, fluid, temperature and mechanical fields respectively were solved simultaneously using COMSOL Multiphysics (Bangalore, India) software. An in-vitro study on agar based tissue phantom was also performed to validate the present numerical results of focused ultrasound heating. The thermal relaxation times of tissue causes significant changes of thermal and damage history under focused ultrasound heating compared to unfocused laser heating. With limited rise in tissue temperature, the pulsed mode of heating for longer period with lower duty cycle (16.6%) shows a target specific necrotic damage with reduced nociceptive pain in contrast to continuous mode of heating. Further, the presence of nanoparticles and multilevel artery and vein affect both the thermal and mechanical response under external heating. Thus, the present findings could help to understand the role of different external heating modes and sources on tumor necrosis during clinical practice of thermo-therapy.

High Intensity Focused Ultrasound (HIFU) is a promising therapy for thermal ablation and hyperthermia, characterised by it noninvasiveness, high penetration depth. Effective HIFU thermo-therapy requires the ability to accurately predict temperature elevation and corresponding thermal dose distribution in target tissues. We report a parametric numerical study of the thermal response and corresponding of thermal dose in a bio-tissue in response to ultrasound. We compared the predictions of tissue models with two, three and seven layers, to ultrasound induced heating at duty cycles ranging from 0.6 and 0.9. Further, two tumor sizes and transducer powers (10 W and 15 W) were considered. Inhomogeneous Helmholtz equation was coupled with Penne's bioheat equation to predict heating in response to pulsed ultrasound. Necrotic lesion size was calculated using the cumulative equivalent minute (CEM) thermal dose function. In-vitro experiments were performed with agar-based tissue phantoms as a preliminary validation of the numerical results. The simulations conducted with the seven layered model predicted up to 33.5% lower peak pressure amplitude than the three-layered model. As the ultrasound pulse width decreased with the equivalent sonication time fixed, the corresponding magnitude of the peak temperature and the rate of temperature rise decreased. Pulsed ultrasound resulted in increased the volume of necrotic lesions for equivalent time of sonication. The findings of this study highlight the dependence of HIFU-induced heating on target geometry and acoustic properties, and could help guide the choice of suitable ultrasound exposure parameters for further studies., Comment: 11 figures, journal