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GutBrain Axis: Role in Hunger and Satiety
The human gastrointestinal tract consists of nearly 100 trillion microorganisms, referred as gut microbiota or gut microbiome. The microbial colonization in the human gut begins at the time of birth and its colonization increases with age which is influenced by factors like age, diet, and antibiotic treatment. Gut microbiota is believed to play a major role in human health as well as various physiological activities like metabolism, nutrition, physiology, etc. Imbalance of the normal gut microbiota has been linked with gastrointestinal conditions such as inflammatory bowel disease (IBD), irritable bowel syndrome (IBS) as well as wider systemic manifestations of disease such as obesity, type 2 diabetes, and atopy. Gutbrain axis, a two-way (bi-directional) connection and communication between the gut and the brain has potentially huge influence over our health which integrates neural, hormonal, and immunological signaling between the gut and the brain. There is growing evidence on the influence of gastrointestinal (GI) microbiota that modulates appetite, feeding, and metabolism as well as regulates the mechanisms of digestion. Gut hormones like Ghrelin, Cholecystokinin (CCK), Pancreatic Polypeptide (PP), Peptide YY (PYY), Glucagon-Like Peptide 1 (GLP-1), Oxyntomodulin (OXM), Glucagon, Gastric Inhibitory Polypeptide (GIP), and Amylin have been identified in the gastrointestinal system which have a fundamental role in coordinating digestive process within the gastrointestinal system, thus regulating feeding behavior and energy balance. Studies have indicated that the modulation in gut microbiota regulates the production of ghrelin and PYY in overweight and obese patients and helps in promoting weight loss and improves glucose regulation. Considering the importance of the role of gut microbiota on hunger and satiety, this chapter was written where we have discussed the gutbrain axis and its role in hunger and satiety. Further, mechanism of appetite regulation by gut microbiota and their role in obesity control have also been discussed. Finally, future perspectives on application of gut microbiota as potential probiotic solutions for obesity and related metabolic disorders will be discussed. Springer Nature Singapore Pte Ltd. 2022. -
GWebPositionRank: Unsupervised Graph and Web-based Keyphrase Extraction form BERT Embeddings
Automatic keyphrase extraction is considered a preliminary task in many Natural Language Processing (NLP) applications that attempt to extract the descriptive phrases representing the main content of a document. Owing to the need for a large amount of labelled training data, an unsupervised approach is highly appropriate for keyphrase extraction and ranking. Keyphrase Extraction with BERT Transformers (KeyBERT) leverages the BERT embeddings that utilize the cosine similarity to rank the candidate keyphrases. However, extracting keyphrases based on the fundamental cosine similarity measure does not consider the spatial dimension locally and globally. Hence, this work focuses on enhancing the KeyBERT-based method with a Graph-based WebPositionRank (GWebPositionRank) design. The proposed unsupervised GWebPositionRank is the composition of graph-based ranking, referring to local analysis and web-based ranking, referring to the global analysis. To spatially examine the keyphrases, the proposed approach conducts the keyphrase position analysis at the document level through graph-based ranking and the web level using the WebPositionRank algorithm. Initially, the proposed approach extracts the coarse-grained keyphrases from the KeyBERT model and ranks the extracted keyphrases, the modelling of quality and fine-tuned keyphrases. In the GWebPositionRank method, the quality keyphrase ranking involves the document-level position analysis and four different graph centrality measures in a constructed textual graph for each text document, whereas the fine-tuned keyphrase ranking involves the web-level position analysis and diversity computation for the quality keyphrases extracted from the graph-based ranking method. Thus, the proposed approach extracts a set of potential keyphrases for each document through the advantage of the GWebPositionRank algorithm. The experimental results illustrate that the proposed unsupervised algorithm yielded superior results than the comparative baseline models while testing on the SemEval2017 dataset. 2024 IEEE. -
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. -
h-almost Ricci Solitons on Generalized Sasakian-space-forms
The aim of this article is to study the h-almost Ricci solitons and h-almost gradient Ricci solitons on generalized Sasakian-space-forms. First, we consider h-almost Ricci soliton with the potential vector field V as a contact vector field on generalized Sasakian-space-form of dimension greater than three. Next, we study h-almost gradient Ricci solitons on a three-dimensional quasi-Sasakian generalized Sasakian-space-form. In both the cases, several interesting results are obtained Kyungpook Mathematical Journal -
Hairy Root Engineering for Enhanced Production of Secondary Metabolites
[No abstract available] -
HALC: An AI-Driven Legal Decision-Making Framework - A Qualitative NVivo Case Study on Tribal Rights
This study proposes a structured human-AI collaboration framework for legal and ethical decision-making, integrating artificial intelligence with human expertise. Unlike fully automated AI systems, it prioritizes transparency, accountability, and ethical oversight. Through expert interviews with legal professionals and AI technologists, we identified key challenges, including bias, lack of explainability, and the need for human validation. Using thematic analysis in NVivo, we developed a stepwise framework that ethically collects data, applies AI-driven analysis, ensures human oversight, and informs policy decisions. This approach enhances human judgment rather than replacing it, with potential applications in law, governance, and public policy. Future research will test and refine this framework. 2025 IEEE. -
Hall effect on two-phase radiated flow of magneto-dusty-nanoliquid with irregular heat generation/consumption
Impacts of Hall current and irregular heat generation/consumption on two-phase flow of dusty-nanofluid are scrutinized. Particulate nanofluid saturates the stretched surface. Heat transfer mechanism is studied via radiative heating and viscous dissipation aspects. The nanoliquid is a carrier fluid and dust (micro-sized fine particles) particles are suspended in it. Governed equations are remodeled in the form of ordinary differential system using stretching transformations. Numeric solutions are developed via Runge-Kutta-Fehlberg scheme. The influence of pertinent parameters on both nanofluid and particle phase flow fields are studied through graphs. The friction factor and Nusselt number are also studied. It is established that the Hall current has a significant impact on thermal flow fields. The irregular heat generation/consumption aspect is constructive for the heating process. 2017 -
Hall effects on dusty nanofluid two-phase transient flow past a stretching sheet using KVL model
The influence of Hall current on the time-dependent flow of nanofluid in the presence of dust particles is investigated. The water-based copper nanoliquid containing fine dust particles occupies a stretching surface. The effective thermal conductivity and the viscosity of the nanoliquid are estimated by KVL (Khanafer-Vafai-Lightstone) model. The notion of boundary layer approximation is employed to model the governing equations for both nanofluid and dust phases. Similarity transformations are employed to obtain ordinary differential equations from the governed partial differential equations. The numeric solutions are developed via Runge-Kutta-Fehlberg integration scheme. The graphical illustrations are to explain the impacts of the governing parameters on flow fields. It is established that the nanofluid's Nusselt number increases due to the suspension of dust particles. An enhancement of heat transfer rate has a direct relationship with Hall current and unsteadiness. 2018 Elsevier B.V. -
Hand ability and practice in congenitally blind children
The assumption that blind children will improve in ability with practice in spatial tasks was tested in a group of 90 congenitally blind and blindfolded sighted children between the ages of 5 and 15 years. All the children were tested for hand preference. The children were then pre-tested and post-tested on four tasks that measured various hand skills with their left and right hands. The period of practice between the pre and post-test was four months. Results indicated a percentage gain with practice during development for the left and the right hands of the blind children. The left and right hands of both groups of children did not differ in percentage gain, indicating little or no relationship between hand preference and hand ability. The effects of practice showed gains for the blind children compared to the sighted blindfolded children in the post-test. Results are discussed with a view that use of self- referent cues can improve spatial ability in blind children. Springer Science+Business Media, LLC 2009. -
Hand Sign Recognition to Structured Sentences
Computer vision is not just a concept of deep learning; it has wide applications such as motion recognition, object recognition, video indexing, video media understanding, and recognition-based intelligence. -However, vision-based systems are a challenging field for research and accurate results. Recent areas of interest are human action recognition or human hands gesture recognition techniques using video data set, still, an image data set, spatiotemporal methods, features in RGB, deep learning methods. Hand action recognition has applications such as communication systems to shorten the bridge gap for people with speech disabilities by using a vision-based system to recognize hand sign language and convert it to text, forming structured sentences which will be easy to understand and communicate. 2023 IEEE. -
Handbook of Nutraceuticals: Science, Technology and Engineering
This book explores the complete development cycle of nutraceuticals and nano-nutraceuticals, with particular focus on manufacturing techniques and formulation strategies. It discusses their physicochemical behavior and presents innovative analytical characterization methods. The text also includes a variety of formulation approaches along with pharmacologic and pharmacokinetic evaluations. Several chapters address the controlled delivery of nutraceutical components, and the use of natural and biodegradable polymers in delivery systems is thoroughly reviewed. In vitro evaluation techniques for assessing nutrient delivery effectiveness are covered in detail, along with discussions on bioavailability, food additives, and encapsulation technologies. A dedicated chapter on the future of controlled-release technologies rounds out the volume. Springer Nature Switzerland AG 2026. -
Handloom weavers and lockdown in Sualkuchi Cluster of Assam
After demonetisation in 2016, followed by imposition of the goods and services tax in the subsequent year, the COVID-19 lockdown has turned out to be a final nail in the coffin for the handloom sector in Assam. It has special importance in the informal economy of Assam since it is next to agriculture in creating employment opportunities. An examination of the Sualkuchi weaving cluster in Assam shows the many challenges the weavers, most of them women, face. 2020 Economic and Political Weekly. All rights reserved. -
Handoff schemes in mobile environments a comparative study
Vehicular ad-hoc networks are one of the most popular applications of Ad-hoc networks, where networks are formed without any sort of physical connecting medium and can be formed whenever required. It is an area in networks that has enjoyed a considerable amount of attention for quite some time. Due to the highly mobile environment where these networks find their usability, it can be understood that there are a lot of problems with respect to maintaining the communication links between the moving vehicular nodes and the static infrastructures which act as the access points (AP) for these moving vehicular mobile nodes (MN). The coverage area of each AP is limited and as such, the connections need to be re-established time and again between the MNs and the closest accessible AP. Handoff is the process involved here, which deals with selecting the optimal APs as well as the best network available for data transmission. In this article, the authors compare various handoff methods and categorize them based on the different approaches they follow. Copyright 2020 IGI Global. -
Handwritten Character Recognition of MODI Script using Convolutional Neural Network Based Feature Extraction Method and Support Vector Machine Classifier
Deep learning based algorithms are used in various pattern recognition tasks, including character recognition. Convolutional Neural Network (CNN) is effectively implemented for character recognition and is one of the best performing deep learning models. CNN can be used for character recognition directly or it can be used for extracting features in the character recognition process. Implementation of a feature extraction method using CNN autoencoder for MODI script character recognition is discussed in the paper. The extracted features are then subjected to Support Vector Machine (SVM) for the purpose of classification. The On-the-fly data augmentation method is used to add variability and generalization of the data set. MODI Script is an ancient Indian script and was used for writing Marathi until 1950. Various libraries and temples in India and abroad have a large collection of MODI documents. Character recognition related research of MODI script is still in infancy and research and development is necessary to extract the information from MODI manuscripts stored in various libraries. The performance of the proposed method, which uses CNN autoencoder as a feature extractor and an SVM based classifier gives very high accuracy and is better compared to the most accurate MODI character recognition method reported so far. 2020 IEEE. -
Handwritten digit recognition using convolutional neural networks
Optical character recognition (OCR) systems have been used for extraction of text contained in scanned documents or images. This system consists of two steps: character detection and recognition. One classification algorithm is required for character recognition by their features. Character can be recognized using neural networks. The multilayer perceptron (MLP) provides acceptable recognition accuracy for character classification. Moreover, the convolutional neural network (CNN) and the recurrent neural network (RNN) are providing character recognition with high accuracy. MLP, RNN, and CNN may suffer from the large amount of computation in the training phase. MLP solves different types of problems with good accuracy but it takes huge amount of time due to its dense network connection. RNNs are suitable for sequence data, while CNNs are suitable for spatial data. In this chapter, a CNN is implemented for recognition of digits from MNIST database and a comparative study is established between MLP, RNN, and CNN. The CNN provides the higher accuracy for digit recognition and takes lowest amount of time for training the system with respect to MLP and RNN. The CNN gives better result with accuracy up to 98.92% as the MNIST digit dataset is used, which is spatial data. 2020 Walter de Gruyter GmbH, Berlin/Boston. All rights reserved. -
Handwritten Telugu Character Recognition Using Machine Learning
The Telugu language is the most prominent representative within the Dravidian language family, predominantly spoken in the southeastern regions of India. Handwritten character recognition in Telugu has significant applications across diverse fields such as healthcare, administration, education, and paleography. Despite its importance, the Telugu script differs significantly from English, presenting distinct challenges in recognizing characters due to its complexity and diverse character shapes. This study explores the application of machine learning, particularly delving into deep learning techniques, to improve the accuracy of Telugu character recognition. This paper proposes a model to recognize handwritten Telugu characters using Convolutional Neural Network (CNN). The proposed study demonstrates the accuracy in identifying diverse handwritten Telugu characters. We assess the system's performance against conventional and machine learning methodologies and preprocess an extensive dataset to guarantee strong model training. The proposed model excels in accurately predicting visually similar but distinct characters, achieving an impressive accuracy rate of 96.96%. 2024 IEEE. -
Handwritten tibetan character recognition using hidden markov model
The Tibetan language which is one of the four oldest and most original languages of Asia is elemental to Tibetan identity, culture and religion and it convey very specific social and cultural behaviors, and ways of thinking. The annihilation of the Tibetan language will have tremendous consequences for the Tibetan culture and hence it is important to preserve it. Tibetan language is mainly used in Tibet, Bhutan, and also in parts of Nepal and India. Tibetan script is devised based on the Devanagari model and Sanskrit based grammars. In this paper, a method for Tibetan handwritten character recognition based on density and distance feature detection is presents. To get a better classification result, images are converted into binary and noise removal is done by using Otzsos method. Features are extracted by normalizing the image based on distance and density of the pixel in the image. Finally, Hidden Markov Model is used for character classification. BEIESP. -
Happiness and resilience among young physically disadvantaged employees in India: A pilot study
Purpose: The study aimed to examine and compare the happiness and resilience of disadvantaged employees and non-disadvantaged employees. Method: The study sample included 37 young employees, between 20 and 30 years of age. Among them, 17 were with physical disadvantages of one type or the other, and 20 had no physical disadvantages. Results: Mann-Whitney U test showed that there is no difference in resilience and happiness between disadvantaged and non-disadvantaged employees. Among the non-disadvantaged employees, there is a relationship between happiness and resilience. However, among the disadvantaged employees, this relationship is not there. Conclusions: Disadvantaged employees in the present sample do not differ from the non-disadvantaged in their happiness and resilience. However, it cannot be assumed that happiness is a contributing factor to the resilience of the disadvantaged employees. Also, it is not possible to generalize the results of the study due to the small sample size. 2019, Action for Disability Regional Rehabilitation Centre. All rights reserved. -
Happiness at Work: Flow as an Aid in Achieving Workplace Excellence
The volume provides a comprehensive understanding of the conceptual and practical implications of happiness. It is a synthesis of cutting-edge research and real-world strategies by authors from diverse disciplines, including psychology, sociology, philosophy, neuroscience, spirituality, education, literature, arts, and music. It offers a glimpse into the science and practice of happiness by exploring positive psychological variables such as mindfulness, emotional intelligence, physical rest, flow, bliss, psychological well-being, spiritual happiness, and workplace happiness. This volume is a valuable resource for anyone interested in the pursuit of happiness, combining rigorous scientific inquiry with practical wisdom to guide readers on their journey toward a joyful and meaningful existence. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
HAPPINESS INDEX OF HIGHER EDUCATION STUDENTS TOWARDS ONLINE LEARNING IN INDIA
World Happiness Index generally indicates the level of happiness and satisfaction among the residents in a given country. Since we all know that worldwide new ecosystem of online education has evolved there are many countries which have done pretty well with respect to adopting of technology in the education others have been lacking behind and hence causing more inequality in the online education space. To understand the students' perception and satisfaction regarding the online learning this study was conducted to assess the relationships of the happiness index (HI) and related parameters which were retrieved from existing literatures and self-prepared parameters. Accordingly, the world happiness index signifies a direct relationship with the social economic development factors leading to the general well-being of individuals and societies that include the full development of healthcare, politics, and higher employment. The question arises has the online learning lived up to its potential? The Indian Education System is heterogeneous comprising of private and public universities. The study was on conducted in the National Capital Region of India, (NCR). The data was collected from various types of universities' students irrespective of the gender, caste, creed and religion. The study aims to understand the perception of the students and challenges faced by them during the online learning. It is very important to know the views of the students along with teachers to get the true ground reality of online learning in India. Since the pandemic have hit overall the world education sector was hit too. All the educational institutions were closed for about nearly 1.5 years. There was drastic shift in the paradigm from traditional learning to the online learning. To understand the students' perception data is being collected from around 268 students of the Delhi NCR region. The study is quantitative. The questionnaire was distributed to the both Government and Private Universities to understand students' satisfaction regarding online learning. The data was being analyzed in the graph form. The study says the future of online learning is possible provided students have access to devices and better connectivity. 2022 Zeitschrift fur Psychologie / Journal of Psychology.All rights reserved.