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Recent trends in hierarchical electrode materials in supercapacitor: Synthesis, electrochemical measurements, performance and their charge-storage mechanism
Supercapacitors are energy storage devices that getting significant research interest among global researchers due to their features such as high specific capacitance, quick charge/discharge, high power density, prolonged cycle life, and safety that contribute to applications in portable electronic devices. Electrode materials are key constituents of supercapacitors and they control their electrochemical performances. There are various structures of electrode materials have been developed for supercapacitors such as core-shell structures, hetero-structures, and hierarchical structures. Among the structures, hierarchical electrode materials (HEMs) are low-cost, easy to synthesize, have high surface area, high active sites, and high electrochemical performances. Thus, this review focuses on the recent synthesis of hierarchical-type electrode materials, electrochemical setup, and characterization, analyses three- and two-electrode system performances in the use of supercapacitors, and charge-storage mechanisms, and summarizes critical viewpoints for future research. The performance of HEMs-based supercapacitors is shown to be high when compared to a single type of electrode. In supercapacitors, porous carbons, metal-organic frameworks, and transition metal sulfides-based HEMs have exceptional electrochemical capabilities across all parameters, including specific capacitance, cycle stability, energy density, and capacitance retention, as found in this review. This review may be helpful to the primary researchers who are working on the preparation and measurement of HEMs for supercapacitor applications. Further, the hierarchical structure-based electrode material is promising for future research in advanced supercapacitor research and could be of interest in technology transfer. 2024 Elsevier Ltd -
Recent trends in photocatalytic water splitting using titania based ternary photocatalysts-A review
Hydrogen is considered as an ideal fuel, and its use has several advantages. While several methods are available for producing hydrogen, photocatalytic water splitting using semiconductor-based photocatalysts is one of the better methods. Among the various semiconductors, titania, having many desirable properties, is a widely explored photocatalyst material to fabricate ternary heterojunctions. Preventing the recombination of photoexcited charge carriers, reducing the band gap, and enhancing the migration of charges are steps needed to improve the efficiency of the photocatalysts. Various modifications have been made to the structural and chemical properties of the photocatalysts. While innovative synthetic protocols can bring about the desired changes, incorporating metal oxides and noble metals with varied morphologies into titania leads to multijunction photocatalysts. Structural modifications to titania include incorporation of various nanostructured materials, noble metal nanoparticles, transition metal chalcogenides, polymer materials, semiconductors like g-C3N4, quantum dots, etc. 2022 Hydrogen Energy Publications LLC -
Recent trends in the electrochemical sensors on ?- and calcium channel blockers for hypertension and angina pectoris: A comprehensive review
Stress, ingrained human behaviors, an inactive lifestyle, and poor dietary decisions are the primary causes of hypertension and the related coronary artery disease (CAD), which is also commonly referred to as angina pectoris. Effective high blood pressure (BP) treatment represents a substantial approach to reducing the burden of hypertension-related cardiovascular and renal diseases. A group of drugs known as ?-blockers and calcium channel blockers (CCBs) are frequently used to treat diseases like hypertension (high blood pressure), cardiac arrhythmias and heart failure. For efficient therapeutic use and to reduce potential side effects, ?-blocker concentration monitoring is essential. Chromatographic techniques are employed in a wide range to detect ?-blockers and CCBs without interference, among other analytical methods that have been described. For the detection of ?-blockers and CCBs, electrochemical sensors provide numerous benefits including sensitivity, selectivity, rapidity, and cost-effectiveness. These sensors can help with patient monitoring in clinical settings, ensuring that the prescription ?-blocker dosage is within the therapeutic range. Since ?-blockers are frequently consumed by people, the contamination can be occurred through discharge of wastewater. The presence and measurement of ?-blockers in water samples enables researchers to evaluate potential risks to aquatic life and public health. In this regard, this review addresses recently developed electrochemical (voltammetric) methodologies and measurement protocols for the determination of both ?-blockers and CCBs in pharmaceuticals, biological fluids, and environmental samples. Additionally, this review also provides an overview of the various advanced nanomaterials such as carbon nanotubes, graphene oxide, metal and metal oxide nanoparticles, polymeric structures, zeolite materials, ionic liquids, perovskite semiconductor-based materials, MXenes, Quantum dots, Nano MIPs and various dimensional materials applied to fabricate chemically modified electrodes/electrochemical sensors to determine the ?-blockers and CCBs. Moreover supplied are tables listing the analyte, modified electrode, measurement method, measuring medium pH, linear detection range (LDR), limit of detection (LOD) and sensitivity as they are cited in the original research. Furthermore, important conclusions are made from the published reports in the last decade and some future perspectives are also suggested. 2023 Elsevier B.V. -
Recent Trends in the Synthesis and Mechanistic Implications of Phenanthridines
Phenanthridine derivatives are one of the most intensively studied families of biologically active compounds. There has been considerable scientific interest in the turn of this century in the synthesis of these N-containing heterocycles as they are prevalent in many alkaloids and also possess striking biological activities including antibacterial, antifungal, antitumor activities. In this regard, a number of synthetic approaches toward the construction of phenanthridine moieties with various substituents, and to increase their yield have been developed by the synthetic organic community. Even though many researchers have developed various innovative methods for the synthesis of phenanthridine derivatives for the past few years, still there is substantial scope for the discovery of novel synthetic methods. In this review, the latest developments in the diverse synthetic strategies of phenanthridine derivatives in the presence and absence of metals were described. The present review also enlightens the use of different reagents, the diversity of the substrates identified, and the plausible mechanisms unravelled towards the construction of these biologically relevant scaffolds. (Figure presented.). 2021 Wiley-VCH GmbH -
Recent trends in the transformative impact of biomass-derived carbon dots in biomedical science
Carbon dots (CDs) have gained significant attention from researchers due to their unique properties, which make them a promising option among nanomaterials for biomedical use. From recent trends, it is confirmed that CDs are the best candidates available among nanomaterials for the treatment of various diseases, including Ulcer, Diabetes, Gout, Wound healing and other syndromes. Semiconductor dots, which dominated in the early days, have been replaced by biomass-derived CDs (BCDs) due to their low toxicity, biocompatibility, and ease of synthesis. Although extensive research has been carried out on the applications of CDs in the biomedical field, the use of biomass as a precursor for CDs in therapeutic and clinical applications remains least explored and has not been systematically reviewed. This review primarily focuses on synthesis strategies, factors influencing the biomedical use of CDs, and recent research in therapeutic and clinical applications. In addition, the earlier trend of employing BCDs in bioimaging, biosensing, and molecular detection is also discussed. By examining the latest research developments, we provide a comprehensive overview of the progress and future prospects of BCDs in healthcare. This exploration highlights not only the potential of these sustainable nanomaterials but also their promise in enabling new breakthroughs in disease treatment. 2025 Elsevier Ltd. -
Recentring Personal Development in Counsellor Education: Integrating Self-compassion, Meaning and Self-care in Training
Personal development (PD) was once the cornerstone of counsellor preparation. However, competency-driven reforms of the late-20th century relegated introspective work to the curricular margins. This chapter argues for a systematic reintegration of PD within counsellor education, contending that self-compassion, meaning in life and holistic self-care are pedagogically indispensable for fostering counselling self-efficacy and sustaining the professional quality of life (ProQOL). After tracing the historical displacement of reflective practice, we differentiate PD from the broader notion of personal growth and technically oriented professional development. Synthesising evidence from counselling, health and educational psychology, we demonstrate that trainees who cultivate self-compassion, meaning-making in life and intentional holistic self-care show greater empathic resonance, lower burnout indicators and more ethical decision-making. The chapter offers concrete strategies such as reflective writing, development labs, mindfulness exercises and scaffolded peer-support structures, which educators can embed within diverse regulatory contexts. By restoring PD to the centre of counsellor training, programmes can prepare practitioners who work competently and congruently, safeguarding client welfare and well-being. 2026 by John Wiley & Sons, Ltd. All rights reserved. -
Reclaiming Selfhood: Transfeminine Identity in the Poetry of Justice Ameer and Golden
Despite increased visibility of trans identities in contemporary US discourse, Black transfeminine individuals remain subjected to systemic violence, societal misrecognition, and cultural erasure, exacerbated by the fraught political climate under administrations that alternately advance and restrict transgender rights. This paper explores the transformative potential of Black transfeminine poetry as a site of self-representation and resistance against hegemonic frameworks of gender, race, and identity. Through a close reading of select poems by Justice Ameer and Golden, the analysis highlights how their works challenge cisnormative and patriarchal narratives, reclaim authority over gender representation and illuminate the fluidity of identity as a process of resilience and resistance. Drawing on themes of memory, trauma, community, and agency, this paper situates their poetry as both a critique of systemic marginalisation and a radical act of reimagination. By positioning their works within the broader socio-political context of the United States, the paper underscores how Black transfeminine poetics not only confront societal erasure but also construct spaces of affirmation and liberation. Through these explorations, the paper demonstrates the capacity of poetry to subvert oppressive narratives, assert the multiplicity of identity, and envision transformative possibilities for transfeminine existence. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
Reclaiming the Ethical Foundations of Mindfulness: Toward a Dharma-Guided Clinical Paradigm
Mindfulness-based interventions (MBIs) have gained clinical prominence yet often omit the ethical and ontological dimensions central to Buddhist traditions. Building on the public health analysis by Oman (2025) of mindfulness along 14 axes (A1A14), which finds alignment on prevention, stress/mental health, resilience, and multisectoral collaboration but identifies gaps in epidemiologic foundations, multilevel intervention design, cultural/religious adaptation, equity, and attention to the collective attentional environment, we propose a Dharma-guided model that directly addresses these implementation challenges (A6A13). Specifically, we outline: (a) culturally responsive adaptations that preserve ethical integrity; (b) multilevel delivery (individual, group, institution, and community) through stepped-care and community-owned pathways; (c) clinician competencies in intercultural/interreligious literacy; (d) metrics and study designs that build the missing epidemiologic base; and (e) interventions responsive to societys attentional environment. This public health-oriented translation repositions MBIs as vehicles for existential insight, moral development, and culturally grounded healing with population-level relevance, complementing the agenda of Oman (2025) and advancing an implementation-ready framework for diverse settings. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025. -
Recognition and Understanding of Emotions in Persons with Mild to Moderate Mental Retardation
Deficits in intellectual ability have been linked to deficits in emotion understanding and consequently social competence. Research suggests that individuals with mental retardation exhibit deficits in their ability to identify emotional states in themselves and others, relative to normal mental age matched controls and peers and display an inability to decode facial expressions of emotion. Emotional experience is elicited in part by a cognitive appraisal of a situation toward a goal. However, the ecological validity of previous studies is limited. In this study we developed new materials to investigate the emotion understanding skills of persons with mild to moderate mental retardation. Six tasks included faces displaying emotion in context, comic strips, audio, video and audio-visual material of individuals expressing emotions in context. Results indicated that the mentally retarded were able to identify emotions in context than expressions without context and emotion understanding improved with increasing contextual cues and dynamic content. 2014, Springer India Pvt. Ltd. -
Recognition of Green Colour Vegetables' Images Using an Artificial Neural Network
Image processing is used in all the domains including agriculture. In this paper, we have introduced a computationally simple and small feature vector, as a tool for the recognition of green colour vegetable images. The RGB colour system is used and the feature set is computationally economic and performs well on locally available vegetable images. For recognition of vegetable images, an ANN-based classifier is deployed. The recognition percentage is in the scale of 74-100 for 15 vegetable types. This work finds application in the packing of vegetables, food processing, automatic vending. 2019 IEEE. -
Recognition of Signature Using Neural Network and Euclidean Distance for Bank Cheque Automation
Handwritten signature recognition plays significant role in automatic document verification system in particularly bank cheque authorization. The proposed method focuses on A novel technique for offline signature recognition approach for bank cheque based on zonal features and regional features. These combined features are used to find genuinety of signature using Euclidean distance as a metric. Extensive experiments are carried out to exhibit the success of the recommended approach. 2019, Springer Nature Singapore Pte Ltd. -
Recommendation Framework for Diet and Exercise Based on Clinical Data: A Systematic Review
Nowadays, diet and exercise recommender frameworks have gaining expanding consideration because of their importance for living healthy lifestyle. Due of the expanded utilization of the web, people obtain the applicable wellbeing data with respect to their medicinal problem and available medications. Since diseases have a strong relationship with food and exercise, it is especially essential for the patients to focus on adopting good food habits and normal exercise routine. Most existing systems on the diet concentrate on proposals that recommend legitimate food items by considering their food choices or medical issues. These frameworks provide functionalities to monitor nutritional requirement and additionally suggest the clients to change their eating conduct in an interactive way. We present a review of diet and physical activity recommendation frameworks for people suffering from specific diseases in this paper. We demonstrate the advancement made towards recommendation frameworks helping clients to find customized, complex medical facilities or make them available some preventive services measures. We recognize few challenges for diet and exercise recommendation frameworks which are required to be addressed in sensitive areas like health care. 2019, Springer Nature Singapore Pte Ltd. -
Recommendation of diet using hybrid collaborative filtering learning methods
These days, various recommender systems exist for online advertisement services which recommend the products considering users interests. Similarly, health recommendation systems are becoming most important component in individuals life. Due to the modernization and busy schedule, people give less concern to their eating patterns. This leads to various health issues like obesity, thyroid disorder, diabetes and others. Every individual has different health issues and food habits. Therefore, diet recommendations should be suggested by considering their personal health profile and food preferences. So, it becomes essential to analyze individuals health concerns before recommending the diet with required nutrient values. Thus, it helps people to minimize the further risks associated with the current health conditions. The proposed diet and exercise recommender framework suggests a balanced diet for thyroid patients. It takes care of the food intake with necessary nutrients requirement based on thyroid disorders. This paper applies K-nearest neighbor collaborative filtering models using various similarity measures. The paper assessed two-hybrid learning methods, KNN with alternating least squares: KNN-ALS and KNN with stochastic gradient decent: KNN-SGD. The experimental setup analyzed and evaluated the performances of all algorithms using mean absolute error (MAE) and root mean squared error (RMSE) values. Springer Nature Singapore Pte Ltd 2020. -
Recommendation of food items for thyroid patients using content-based knn method
Food recommendation system has become a recent topic of research due to increase use of web services. A balanced food intake is significant to maintain individuals physical health. Due to unhealthy eating patterns, it results in various diseases like diabetes, thyroid disorder, and even cancer. The choice of food items with proper nutritional values depends on individuals health conditions and food preferences. Therefore, personalized food recommendations are provided based on personal requirements. People can easily access a huge amount of food details from online sources like healthcare forums, dietitian blogs, and social media websites. Personal food preferences, health conditions, and reviews or ratings of food items are required to recommend diet for thyroid patients. We propose a unified food recommendation framework to identify food items by incorporating various content-based features. The framework uses the domain knowledge to build the private model to analyze unique food characteristics. The proposed recommender model generates diet recommendation list for thyroid patients using food items rating patterns and similarity scores. The experimental setup validated the proposed food recommender system with various evaluation criteria, and the proposed framework provides better results than conventional food recommender systems. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. -
Recommendation System using Clustering and Comparing Clustering and Topic Modelling Techniques
In this paper, we have used a technique called clustering to recommend the products to the customer and also tried to compare clustering and Topic modelling to find out which technique is better for our purpose. From all the papers that have been reviewed, we observed that the greater part of the proposal approaches applied content-based filtering (55%). Collaborative-based filtering was applied by just 18% of the looked into approaches, and hybrid based by 16%. Other suggestion ideas included generalizing, thing driven proposals, and crossover suggestions. The content-based filtering approaches overwhelmingly utilized papers that the clients had made, marked, examined, or downloaded [1]. To begin with, it stays muddled which suggestion ideas and approaches are the most encouraging. For instance, analysts demonstrated different results on the presentation of content based and collaborative filtering. A portion of the time content-based filtering performed better contrasted with collaborative filtering sand a portion of the time it performed all the more regrettable. 2022 IEEE. -
Recommendations from teachers on schools' roles in identifying problems and building awareness among students
Students develop skills, gain knowledge, and achieve greater wellbeing by creating a positive school environment. Through the years, schools have realized the importance of mental health services for adolescents. Research on the role of schools in mental health awareness building and preventing mental health problems is meager, and focuses on students in the western context. This chapter focuses on the recommendations given by teachers on what role schools can play in identifying, preventing, and building awareness among adolescents. These recommendations are based on the themes obtained through semi-structured interviews with 24 teachers teaching 10th, 11th, and 12th graders in private high schools and colleges in Bangalore. Consequently, it aims to provide an overview of incorporating techniques and strategies to enhance mental health among school students in the Indian Scenario. 2024, IGI Global. All rights reserved. -
Recommender system for personalised travel itinerary
A recommender system is an approach to give an appropriate solution to a particular problem. This helps in recognising the pattern or behaviour of a user to suggest future possible likes of the user. Nowadays people like to travel during their spare time, it has become a rigid task to decide where to go. This paper represents a customised recommender system to help users in destining their itinerary. A model is designed to suggest the best places to visit in Rome. A questionnaire was prepared to get information about user's interest during their travel. The model generates the best five places to visit with respect to the choice picked by the user. The top five places for each category will be displayed to the user and the user was asked to pick a starting point for the itinerary. Then the model generates another set off a filtered list of places to enhance their travel experience. It includes displaying the top 5 restaurants to visit during their travel. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
Recommender system for surplus stock clearance
Accumulation of the stock had been a major concern for retail shop owners. Surplus stock could be minimized if the system could continuously monitor the accumulated stock and recommend those which require clearance. Recommender Systems computes the data, shadowing the manual work and give efficient recommendations to overcome stock accumulation, creating space for new stock for sale to enhance the profit in business. An intelligent recommender system was built that could work with the data and help the shop owners to overcome the issue of surplus stock in a remarkable way. An item-item collaborative filtering technique with Pearson similarity metric was used to draw the similarity between the items and accordingly give recommendations. The results obtained on the dataset highlighted the top-N items using the Pearson similarity and the Cosine similarity. The items having the highest rank had the highest accumulation and required attention to be cleared. The comparison is drawn for the precision and recall obtained by the similarity metrics used. The evaluation of the existing work was done using precision and recall, where the precision obtained was remarkable, while the recall has the scope of increment but in turn, it would reduce the value of precision. Thus, there lies a scope of reducing the stock accumulation with the help of a recommender system and overcome losses to maximize profit. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
Reconceptualizing Empowerment And Autonomy: Ethnographic Narratives From A Self Help Group In South India
The paper revisits academics' conceptualizations of women empowerment as stopping short of autonomy. It departs from the general observation that women empowerment movements by and large have failed to translate the new agency of women outside the domains of socio economy; that women empowerment movements' capacity to re-engage with patriarchal structures and ideologies is seriously contained. Through an ethnography of Kudumbashree, an SHG in the South Indian state of Keralam, we question the neat distinctions between empowerment and autonomy that prevail in the academic common sense. The transition of agency from the economic to the political domain is a subtle enterprise and is mediated by a number of factors including the economic independence, decision making capability and political participation. Socio -economic - political implications of women empowerment could be the first step in challenging and overcoming the relations of oppression in any society. The stereotypical assumptions can be negotiated by solely apportioning responsibilities and re-engaging with the system through everyday practices. The nuances of empowered women's re-engagement with local gender/power regimes lead to changes at the conceptual level that cuts beyond the individual and group level material transformations. The Electrochemical Society -
Reconciling Privacy Rights With Digital Investigations: Legal-Ethical Challenges in Cyber Forensics
The advancement of cyber forensics-through Al-driven profiling, metadata analysis, and real-time surveillance has enhanced digital investigations but raised significant legal and ethical concerns. This chapter explores the growing tension between state surveillance and individual privacy, focusing on the Indian legal framework, includ-ing the Justice K.S. Putaswamy decision, and comparing it with global standards such as the GDPR, ECHR, and Budapest Convention. Key issues addressed include algorithmic bias, lack of consert, cross-border data sharing, and misuse of forensic tools against vulnerable groups. The chapter argues for a balanced, rights-based framework grounded in privacy-by-design, proportionality, and judicial oversight. It offers policy recommendations to ensure cyber forensic practices remain effective while upholding constitutional protections and international human rights norms. 2026 by IGI Global Scientific Publishing. All rights reserved.