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Beyond Bollywood and Hindi: making a case for other language films in India
[No abstract available] -
Romance and Hitchcock? Viewing master of suspense as master of romance
This essay through literature and textual analysis argues that romance or romantic love is a dominant theme in Alfred Hitchcocks films alongside suspense. Romance in Hitchcocks films is highlighted in limited studies in the past and the findings are not conclusive. This study analysed a selected sample of 19 prominent films of Hitchcock. It argues that romantic content in Hitchcocks films is similar to classic Hollywood romantic films. However, unique features of romance specific to Hitchcocks films such as working together to solve a mystery, and complicated love were also found as recurring themes. Hitchcock employs his auteur style in the portrayal of romantic love to an extent that the romantic content in his films can be characterised as having a distinct style lending itself to term it as Hitchcock romance. Hitchcock romance is the amalgamation of suspense and romance that support each other to drive the narrative forward. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Immortality and beyond: review of the film Seo Bok
[No abstract available] -
Media in everyday life: review of the series Reply 1988
[No abstract available] -
Reimagining North Korea in a new frame: review of the series Crash Landing on You (2019)
[No abstract available] -
Contemplating hair: Many shades of hair oppression in India
What is it like to be a woman with wavy/curly hair in a country like India? Although hair stories are different for different women, one common hair story for all Indian women with wavy/curly hair is moments of insecurity regarding the normalcy and beauty appeal of their hair. Aside from the discrimination faced due to the texture of hair, Indian women also face restrictions and suffocations in terms of creative self-expression of hair. This chapter presents an overview of the hair culture in India from a historical perspective along with religious narratives. The nature of hair discrimination of women in India is discussed and the chapter also shed light on institutionalised illogical restrictions. The author's personal hair stories will serve as an example to underline the complexity of hair discrimination in India. 2024, IGI Global. All rights reserved. -
Do Koreans hate Indians? Fact checking viral online videos calling out Korean racism
[No abstract available] -
Acid functionalized Arachis hypogaea skin based carbon nanosphere as efficacious material for enhanced energy storage
The present introduces a single step approach for enhancing supercapacitor performance by utilizing acid-functionalized porous carbon derived from the inner skin of Arachis hypogaea as a sustainable biomass precursor. Through pyrolysis at 800 C in a nitrogen atmosphere, the resulting porous carbon material demonstrates unique structural and electrochemical behavior as confirmed by FTIR, XRD, Raman spectroscopy, FE-SEM, HR-TEM,EDS,BET analyses. The acid functionalized variant (FAH8) significantly outperformed the non-functionalized carbon (AH8), showing a fourfold increase in specific capacitance. Electrochemical evaluations revealed that FAH8 achieved a high specific capacitance of 273 Fg?1 at 0.25 Ag?1 in 3 M KOH, with an energy density of 22.5 Wh kg?1 and a power density of 125 W kg?1 in a three-electrode setup. The symmetrical CR2032 device of FAH8 exhibited a maximum capacitance of 98 Fg?1 and displayed excellent stability, with 98.5 % efficiency and 97.4 % capacitance retention after 7500 cycles. Notably, the device also delivered a high energy density of 23.17 Wh kg?1 and power density of 325.0 W kg?1. The enhanced performance attributed by the simple acid functionalization highlights the potential of this material in energy storage. Thus, the study not only emphasizes the effective use of low-cost biomass precursors but also provides a straightforward functionalization strategy to boost energy storage capabilities, paving the way for sustainable high-performance supercapacitors. 2025 Elsevier Ltd -
Molecularly imprinted graphene based biosensor as effective tool for electrochemical sensing of uric acid
Graphene oxide based molecularly imprinted polymer was designed by incorporating vinyltrimethoxysilane into the layers of graphene oxide, which was copolymerized with functional monomers such as Itaconic acid (IA) and methyl methacrylate (MMA) was developed via bulk imprinting technique. The prepared polymer was studied for selective sensing the uric acid (UA) in blood serum. The electrode was constructed by modifying bare glassy carbon electrodes with the prepared molecularly imprinted polymer (MIP) via drop cast method. Electrochemical measurements were made by Cyclic voltammetric (CV) and Differential Pulse Voltammetric (DPV) response of the sensor. The physical and chemical properties of the resultant material will be characterized by FTIR spectroscopy, XRD and FESEM. The constructed sensor showed a regression coefficient (R2) of 0.9302 with limit of detection (LOD) of about 0.565 ??M. The developed sensor is reusable without any compromise in its selectivity. All the results confirm that the constructed biosensor requires no pre-treatment of samples and is suitable for real sample analysis. 2023 The Authors -
Temperature and pressure dependent luminescence mechanism of a zinc blende structured ZnS:Mn nanophosphor under UV excitation
A comprehensive photoluminescence and mechanoluminescence analysis of a ZnS:Mn2+ nano-phosphor with a zinc blende structure is presented. The sample containing quantum dot-sized nanocrystallites was synthesized by the chemical precipitation method and shows excellent orange luminescence at ambient conditions related to the 4T1 ? 6A1 transition. The sample shows stable and identical luminescence behavior under both UV and X-ray excitation at ambient conditions and also exhibits excellent self-powered mechanoluminescence properties. The pressure and temperature-induced luminescence mechanism of the phosphor is also established. The shift of the 4T1 ? 6A1 luminescence band of Mn2+ with both pressure and temperature and the luminescence mechanism is explained via the d5 Tanabe Sugano diagram. The broad luminescence band of the 4T1 ? 6A1 transition shifts from the visible to near-infrared range at a rate of ?35.8 meV GPa?1 with the increase of the pressure and it is subsequently quenched completely at a pressure of 16.41 GPa due to a reversible phase transition from zinc blende (F4?3m) to rocksalt (Fm3?m) phase. The high-pressure and temperature-dependent decay kinetics measurements of the sample luminescence are also reported. 2024 The Royal Society of Chemistry. -
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Evaluation of Social Media Marketing Literature in the Tourism Industry Using PRISMA
Social media is an effective communication and information-sharing tool for tourism enterprises and organisations. Tourism marketing shall tap the growing popularity of social media and internet users, embracing a technological shift by optimising the potential of social media. This research study evaluates the academic journal articles related to social media in the tourism industry published on EBSCOhost, ScienceDirect and Google Scholar academic databases from 2005 to 2022. The article adopts a content analysis approach to review the articles and to evaluate the present state of knowledge of social media marketing in academic literature. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) is used for reporting and screening the review papers. The articles were coded and categorised under six major themes: Marketing, Destination experience/image, Tourism recovery, Smart tourism, Communication and Promotion. The research analysis has identified two major areas: (a) Travellers/tourists Perspective which has a focus on their behavioural attitude and (b) Tourism Agencies Perspective which has a functional approach. Based on the review of the literature to give direction for further research, an improvised version of the definition for the term social media with the inclusion of more specific terms in it has been proposed with theoretical and practical implications. 2023 MICA-The School of Ideas. -
A Prompt Study on Recent Advances in the Development Of Colorimetric and Fluorescent Chemosensors for Nanomolar Detection of Biologically Important Analytes
Fluorescent and colorimetric chemosensors for selective detection of various biologically important analytes have been widely applied in different areas such as biology, physiology, pharmacology, and environmental sciences. The research area based on fluorescent chemosensors has been in existence for about 150years with the development of large number of fluorescent chemosensors for selective detection of cations as metal ions, anions, reactive species, neutral molecules and different gases etc. Despite the progress made in this field, several problems and challenges still exist. The most important part of sensing is limit of detection (LOD) which is the lowest concentration that can be measured (detected) with statistical significance by means of a given analytical procedure. Although there are so many reports available for detection of millimolar to micromolar range but the development of chemosensors for the detection of analytes in nanomolar range is still a challenging task. Therefore, in our current review we have focused the history and a general overview of the development in the research of fluorescent sensors for selective detection of various analytes at nanomolar level only. The basic principles involved in the design of chemosensors for specific analytes, binding mode, photophysical properties and various directions are also covered here. Summary of physiochemical properties, mechanistic view and type of different chemosensors has been demonstrated concisely in the tabular forms. Graphical Abstract: In our current review we have focused the history and a general overview of the development in the research of fluorescent sensors for selective detection of various analytes at nanomolar level only. [Figure not available: see fulltext.] 2024, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Gym-Goers Self-Identification with Physically Attractive Fitness Trainers and Intention to Exercise
Gym-goers often socially compare themselves with their trainers as they strive to look as attractive as their fitness trainers. The aim of this study was to better understand this phenomenon in the fitness industry. Relying on social comparison theory and social identity theory, self-identification with a physically attractive fitness trainer was posited to have a strong mediating effect on the relationship between appearance motive, weight management motive and gym-goers intention to exercise. The moderation effects of gym-goers age and gender in the direct relationships between appearance motive, weight management motive and exercise intention were also examined. The primary outcome of this study revealed that gym-goers who were influenced by appearance and weight management motives are more likely to identify with physically attractive fitness trainers. Additionally, gender significantly moderates the relationships between appearance motive, weight management motive and exercise intention. Appearance and weight management motives are the primary factors that influence the exercise intention of female gym-goers as compared to their male counterparts. This study sheds new insights into understanding the influence of the physical attractiveness of fitness trainers and its impact on gym-goers exercise intentions via self and social identification process. 2022 by the authors. Licensee MDPI, Basel, Switzerland. -
FITNESS TRAINERS PHYSICAL ATTRACTIVENESS AND GYM GOERS EXERCISE INTENTION
In line with the law of attraction, physical attractiveness has been widely used in marketing as well as advertising due to its potency in persuading consumers to take action. However, would physical attractiveness of a fitness trainer influence gym goers intention to exercise? This question motivated this research. Based on recent literature reviews, several research constructs were identified to form a research framework to investigate the physical attractiveness phenomena in the fitness industry. Hypothetically, the impact of the physical attractiveness of a fitness trainer on gym goers exercise intention is postulated to be mediated by trainers perceived expertise, trustworthiness, likeability and perceived health. Questionnaires were administered among gym-goers from 10 randomly selected fitness centres across three districts of Melaka State in Malaysia, and 192 final sample data were obtained. Data analysis reveals fitness trainers perceived expertise and likeability significantly mediates the relationship between the physical attractiveness of fitness trainers and gym goers exercise intention. Physical attractiveness of fitness trainers does impact the exercise intention of gym goers indirectly. Implications of the findings to theory and practice are also discussed in this paper, as well as suggestions for future studies. 2022, Universiti Malaysia Sarawak. All rights reserved. -
A new framework for contour tracing using Euclidean distance mapping
In this paper, a new fast, efficient and accurate contour extraction method, using eight sequential Euclidean distance map and connectivity criteria based on maximal disk, is proposed. The connectivity criterion is based on a set of point pairs along the image boundary pixels. The proposed algorithm generates a contour of an image with less number of iterations compared to many of the existing methods. The performance of the proposed algorithm is tested with a database of handwritten character images. In comparison to two standard contour tracing algorithms (the Moore method and the Canny edge detection method), the proposed algorithm found to give good quality contour images and require less computing time. Further, features extracted from contours of handwritten character images, generated using the proposed algorithm, resulted in better recognition accuracy. Copyright 2021 Inderscience Enterprises Ltd. -
Exploring the Adaptability of Attention U-Net for Post-operative Brain Tumor Segmentation in MRI Scans
This study explores the adaptability of a segmentation model, originally trained on pre-operative MRI data, in post-operative recurrent brain tumor segmentation. We utilized the Attention U-Net model for this study. In pre-operative training, the model achieved a Dice Coefficient of 0.92 and an IOU of 0.86 for brain tumor MRI segmentation. Due to the surgical artifacts in post-operative data, performance reduced with Dice Coefficient of 0.54 and an IOU of 0. To improve the performance, the model's architecture is fine-tuned by introducing dilated convolutions and residual connections. This refinement yielded improvements in results, with a Dice Coefficient of 0.68 and an IOU of 0.62 in the post-operative context. This improvement underscores the need for further research to select and adapt efficient models, retrain specific layers with an extensive collection of post-operative images, and fine-tune model parameters to enhance feature extraction during the encoding phase. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Advancing Brain Tumor Segmentation in MRI Scans: Hybrid Attention-Residual UNET with Transformer Blocks
Accurate segmentation of brain tumors is vital for effective treatment planning, disease diagnosis, and monitoring treatment outcomes. Post-surgical monitoring, particularly for recurring tumors, relies on MRI scans, presenting challenges in segmenting small residual tumors due to surgical artifacts. This emphasizes the need for a robust model with superior feature extraction capabilities for precise segmentation in both pre-and post-operative scenarios. The study introduces the Hybrid Attention-Residual UNET with Transformer Blocks (HART-UNet), enhancing the U-Net architecture with a spatial self-attention module, deep residual connections, and RESNET50 weights. Trained on BRATS20 and validated on Kaggle LGG and BTC_ postop datasets, HART-UNet outperforms established models (UNET, Attention UNET, UNET++, and RESNET 50), achieving Dice Coefficients of 0.96, 0.97, and 0.88, respectively. These results underscore the models superior segmentation performance, marking a significant advancement in brain tumor analysis across pre-and post-operative MRI scans. 2024 by the authors of this article. -
Enhanced Postoperative Brain MRI Segmentation with Automated Skull Removal and Resection Cavity Analysis
Brain tumors present a significant medical challenge, often necessitating surgical intervention for treatment. In the context of postoperative brain MRI, the primary focus is on the resection cavity, the void that remains in the brain following tumor removal surgery. Precise segmentation of this resection cavity is crucial for a comprehensive assessment of surgical efficacy, aiding healthcare professionals in evaluating the success of tumor removal. Automatically segmenting surgical cavities in post-operative brain MRI images is a complex task due to challenges such as image artifacts, tissue reorganization, and variations in appearance. Existing state-of-the-art techniques, mainly based on Convolutional Neural Networks (CNNs), particularly U-Net models, encounter difficulties when handling these complexities. The intricate nature of these images, coupled with limited annotated data, highlights the need for advanced automated segmentation models to accurately assess resection cavities and improve patient care. In this context, this study introduces a two-stage architecture for resection cavity segmentation, featuring two innovative models. The first is an automatic skull removal model that separates brain tissue from the skull image before input into the cavity segmentation model. The second is an automated postoperative resection cavity segmentation model customized for resected brain areas. The proposed resection cavity segmentation model is an enhanced U-Net model with a pre-trained VGG16 backbone. Trained on publicly available post-operative datasets, it undergoes preprocessing by the proposed skull removal model to enhance precision and accuracy. This segmentation model achieves a Dice coefficient value of 0.96, surpassing state-of-the-art techniques like ResUNet, Attention U-Net, U-Net++, and U-Net. (2024) Sobha Xavier P., Sathish P. K. and Raju G. -
Addressing the complexities of postoperative brain MRI cavity segmentationa comprehensive review
Postoperative brain magnetic resonance images (MRI) is pivotal for evaluating tumor resection and monitoring post-surgical changes. The segmentation of surgical cavities in these images poses challenges due to artifacts, tissue reorganization, and heterogeneous appearances. This study explores challenges and advancements in postoperative brain MRI segmentation, examining publicly accessible datasets and the efficacy of various deep learning models. The analysis focuses on different U-Net models (U-Net, V-Net, ResU-Net, attention U-Net, dense U-Net, and dilated U-Net) using the EPISURG dataset. The training dice scores are as follows: U-Net 0.8150, attention U-Net 0.8534, V-Net 0.7602, ResU-Net 0.7945, dense U-Net 0.83, dilated U-Net 0.80. The study thoroughly assesses existing postoperative cavity segmentation models and proposes a fine-tuning approach to enhance the performance further, particularly for the best-performing model, attention U-Net. This fine-tuning involves introducing dilated convolutions and residual connections to the existing attention U-Net model, resulting in improved results. These improvements underscore the necessity for ongoing research to select and adapt efficient models, retrain specific layers with a comprehensive collection of postoperative images, and fine-tune model parameters to enhance feature extraction during the encoding phase. 2024, Institute of Advanced Engineering and Science. All rights reserved.