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Life Skills Development for Adolescent Girls at Risk with Special Reference to Rescued Devadasi Girls: An Intervention Study
Devadasi means to servant of God. The word is derived from Sanskrit language. It is originated from two words ??deva and ??dasi which mean God and servant respectively. The devadasi is attributed to girls dedicated to a Goddess called Yellama through the marriage to the deity. There are some important psycho social implications of devadasi system. The system of devadasi is a form of slave trade. In this system the young girls are exploited in the name of religious practices. A major disadvantage of this system is that it disintegrates an individual especially an adolescent girl in context of her overall development and social development in particular. Intervention has always been the essence of social work. Life skills education can be given prime importance and adolescent girls especially in situations such as rescued devadasi can be trained to apply life skills to redress their mental health problems. Teaching life skills to adolescents would help them to transform knowledge, skills, attitudes and values into real abilities. The aim of the current study was to assess the level of Life skills among the rescued devadasi adolescent girls and provide life skills training and evaluation of the overall effectiveness of the Programme. The design used was a pre experimental research design without a control group. 25 adolescent girls who are rescued from the devadasi system were part of the study from northern Karnataka. Based on the need assessment carried in the initial phase of the study, an intervention Programme was developed for the participants based on the 10 life skills laid out by the World Health Organization. A standardized Life skills assessment scale developed by Vranda (2009) was used in pre assessment and post assessments. The results indicate that the Programme was effective and displayed statistical significance in rendering the participants with Life skills. The implication of the study reiterates the importance of developing tailor made life skills Programme for vulnerable groups and girls at risk. KEY WORDS: Life skills, rescued devadasi girls -
Life skills for personal well-being
This investigation examines the integrative and transformative qualities of service learning in higher education, specifically focusing on its contribution to developing personal well-being-related life skills. By integrating significant community service with academic goals, service learning provides a comprehensive educational experience. Its defined components, theoretical framework, and real-world applications underscore the subject's significance. Student experiences and case studies illustrate its influence on empathy, resiliency, and communication. Strategic implementation approaches serve as a compass for purposeful undertakings. Service learning connects theoretical concepts with practical application, cultivating globally literate and socially conscious individuals who can navigate the everchanging realm of higher education. 2024, IGI Global. -
Lifestyle Diseases Prevalent in Urban Slums of South India
Lifestyle diseases have always been considered to be a malady of the middle and upper classes of society. Recent findings indicate that these chronic non-communicable diseases are common among the lower socioeconomic classes as well. The objective of this study was to assess the prevalence of lifestyle diseases in three cohorts of urban slums, namely, waste pickers living in non-notified slums, communities living in notified slums, and BBMP Pourakarmikas, and to identify the risk factors among the three cohorts contributing to the common lifestyle diseases including hypertension, diabetes, and cardiovascular diseases. In this study, the data was collected by conducting health camps, followed by analysis of the data using logistic regression, HosmerLemeshow test and ROC Curve Analysis. The prevalence of hypertension was found 13.35%, diabetes-8.53% and cardiovascular disease-3.59%. These were significantly associated with substance abuse, high BMI, and age. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Light as an elicitor for enhanced production of secondary metabolites in plant cell, tissue, and organ cultures
Currently, in vitro cell, tissue, and organ cultures are used to produce plant secondary metabolites that are used as natural coloring agents, nutraceuticals, and medications. Various strategies have been applied for the hyperaccumulation of biomass and bioactive secondary compounds in vitro. The elicitation of cultured cells and organs with biotic and abiotic elicitors is an excellent strategy that has yielded promising results. Among various abiotic elicitors, light parameters such as light quality, intensity, and photoperiod have evolved as biotechnological tools to elicit cultures. Of the various light sources tested, ultraviolet (UV) lights, particularly UV-B, red, blue, and a mixture of light emitted by fluorescent light or light-emitting diodes, have yielded outstanding results and boosted the accumulation of bioactive compounds in cultured cells and organs. The objective of the current study was to evaluate light as an elicitor source and summarize the advantages and limitations of various light sources as elicitors for the bioaccumulation of secondary metabolites in vitro. The mechanism of the elicitation of secondary metabolism by UV and spectral light is discussed in this review. The Author(s), under exclusive licence to Springer Nature B.V. 2024. -
Light Tracking Bot Endorsing Futuristic Underground Transportation
Controlling a bot machine that uses non-conventional energy form, i.e. light is said to have an upper hand in pioneering transportation system. The expanding request of making the streets more secure has persuaded a ton of organizations to create finest autonomous vehicles. This paper will concentrate on the potential outcomes of utilizing just light-sensing gadgets alone for the light tracking bot using advanced color detection algorithm. The algorithm would help the bot in sensing the color of light and act accordingly, for instance green color to proceed, red color to stop. This particular requisition has high scope in real time application over the emergent underground transportation system; speculating on how the emerging innovative advances fit to the fiddle urban areas of the 21st century. 2020, Springer Nature Switzerland AG. -
Light weight authentication protocol for WSN using ECC and hexagonal numbers
Wireless Sensor Network (WSN) is a spatially distributed network. It contains many numbers of distributed, self-directed, small, battery powered devices called sensor nodes or motes. In recent years the deployment of WSN in various application domains are growing in a rapid pace as with the upcoming boom of Internet of Things (IoT) and Internet of Everything (IoE). However, the effectiveness of the WSN deployment is restricted due to the constrained computation and power source. Hence, many researchers have been proposing new approaches and models to improve the efficiency of the domain specific WSN deployment procedures. Though, many research communities addressing various issues in WSN deployment, still the privacy and security of such networks are susceptible to various network attacks. Thus, it is necessary to practice different models for authentication and privacy preservation in a highly dynamic resource constrained WSN environment to realize the effectiveness and efficiency of the deployment. Hence, this paper addressing an authentication scheme that can reduce energy consumption without compromising on security and privacy. In order to provide a light weight authentication mechanism, this paper proposing an authentication mechanism for WSN deployment by combining the features of Elliptic Curve Cryptography (ECC) and Hexagonal numbers. The feature of ECC is used to reduce the key size and the effectiveness of generating hexagonal numbers is used for minimizing the energy consumption in a resource constrained WSN environment. The results of the proposed approach are evaluated with the different authentication models and the results were indicating that the proposed approach can perform better than the other approaches. 2019 Institute of Advanced Engineering and Science. -
Light-induced advanced oxidation processes as pfas remediation methods: A review
PFAS substances, which have been under investigation in recent years, are certainly some of the most critical emerging contaminants. Their presence in drinking water, correlated with diseases, is consistently being confirmed by scientific studies in the academic and health sectors. With the aim of developing new technologies to mitigate the water contamination problem, research activity based on advanced oxidation processes for PFAS dealkylation and subsequent mineralization is active. While UV radiation could be directly employed for decontamination, there are nevertheless considerable problems regarding its use, even from a large-scale perspective. In contrast, the use of cheap, robust, and green photocatalytic materials active under near UV-visible radiation shows interesting prospects. In this paper we take stock of the health problems related to PFAS, and then provide an update on strategies based on the use of photocatalysts and the latest findings regarding reaction mechanisms. Finally, we detail some brief considerations in relation to the economic aspects of possible solutions. 2021 by the authors. Licensee MDPI, Basel, Switzerland. -
Lightning Cards! /
Patent Number: 202141060863, Applicant: Bundela Disha Hitenbhai.
The present system or invention, Lightning Cards, is an online multiplayer card game that utilises computer vision and machine learning techniques in order to deliver a fast-paced reactions card game unheard of not only online, but also as a physical card game. The present system is enabled by way of ML tools to recognise the hand keypoint landmarks and other algorithms for recognising the actual hand gesture. -
Lightning Cards! /
Patent Number: 202141060863, Applicant: Bundela Disha Hitenbhai.
The present system or invention, Lightning Cards, is an online multiplayer card game that utilises computer vision and machine learning techniques in order to deliver a fast-paced reactions card game unheard of not only online, but also as a physical card game. The present system is enabled by way of ML tools to recognise the hand keypoint landmarks and other algorithms for recognising the actual hand gesture. -
Lights and Shadows in Autodesk 3ds Max: Methods and Features
Using the 3ds Max software, this paper describes the intricate modelling process of implying shadows onto various objects to make it look more realistic. In this article, Various Shadow types and controls are used in order to demonstrate the functions of shadows in Autodesk 3ds Max. The paper helps the reader understand the nature of the lights and shadows in a computer-generated environment and its implementation in the real-world situations. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Lightweight Anti DDoS Security Tool: Edge Level Filtering in SDN using P4
Software Defined Network (SDN) which has a promising future in satellite communication was first introduced as the solution to solve problems existing in the traditional network architecture. So far in SDN, mitigation strategies employed hardware installation or software solution which is heavily dependent on SDN controllers. The disadvantage of these approaches is the a) cost for implementation, b) intensive resource usage, and 3) costly optimization strategy necessary to enhance SDN performance. This research aims to fill the gap of the previously seen defense mechanism by enabling edge-level filtering without involving the control plane. By implementing filtering functions in edge switches, it can provide an efficient and effective defense layer in SDN network systems so that SDN switch can become the first line of defense against packet injection attacks. The proposed solution, Lightweight Anti-DDoS Software (LADS) focuses on lightweight workloads and provisioning of effective filtering mechanism to allow SDN switches to drop and block malicious packets sent by attackers. It utilizes Programming Protocol-independent Packet Processors (P4) programming language to create custom functionalities in SDN switches. P4 allows SDN switches to conduct host authentication and malicious packet filtering as well as blacklisting to isolate attackers. Simulation result proves that LADS efficiently manages malicious activities and maintains network performance during attacks at the data plane independent of SDN controller. 2023 IEEE. -
Lightweight Model for Occlusion Removal from Face Images
In the realm of deep learning, the prevalence of models with large number of parameters poses a significant challenge for low computation device. Critical influence of model size, primarily governed by weight parameters in shaping the computational demands of the occlusion removal process. Recognizing the computational burdens associated with existing occlusion removal algorithms, characterized by their propensity for substantial computational resources and large model sizes, we advocate for a paradigm shift towards solutions conducive to low-computation environments. Existing occlusion riddance techniques typically demand substantial computational resources and storage capacity. To support real-time applications, it's imperative to deploy trained models on resource-constrained devices like handheld devices and internet of things (IoT) devices possess limited memory and computational capabilities. There arises a critical need to compress and accelerate these models for deployment on resource-constrained devices, without compromising significantly on model accuracy. Our study introduces a significant contribution in the form of a compressed model designed specifically for addressing occlusion in face images for low computation devices. We perform dynamic quantization technique by reducing the weights of the Pix2pix generator model. The trained model is then compressed, which significantly reduces its size and execution time. The proposed model, is lightweight, due to storage space requirement reduced drastically with significant improvement in the execution time. The performance of the proposed method has been compared with other state of the art methods in terms of PSNR and SSIM. Hence the proposed lightweight model is more suitable for the real time applications with less computational cost. 2024 by the author(s). -
Lightweight Spectral-Spatial Squeeze-and- Excitation Residual Bag-of-Features Learning for Hyperspectral Classification
Of late, convolutional neural networks (CNNs) find great attention in hyperspectral image (HSI) classification since deep CNNs exhibit commendable performance for computer vision-related areas. CNNs have already proved to be very effective feature extractors, especially for the classification of large data sets composed of 2-D images. However, due to the existence of noisy or correlated spectral bands in the spectral domain and nonuniform pixels in the spatial neighborhood, HSI classification results are often degraded and unacceptable. However, the elementary CNN models often find intrinsic representation of pattern directly when employed to explore the HSI in the spectral-spatial domain. In this article, we design an end-to-end spectral-spatial squeeze-and-excitation (SE) residual bag-of-feature (S3EResBoF) learning framework for HSI classification that takes as input raw 3-D image cubes without engineering and builds a codebook representation of transform feature by motivating the feature maps facilitating classification by suppressing useless feature maps based on patterns present in the feature maps. To boost the classification performance and learn the joint spatial-spectral features, every residual block is connected to every other 3-D convolutional layer through an identity mapping followed by an SE block, thereby facilitating the rich gradients through backpropagation. Additionally, we introduce batch normalization on every convolutional layer (ConvBN) to regularize the convergence of the network and scale invariant BoF quantization for the measure of classification. The experiments conducted using three well-known HSI data sets and compared with the state-of-the-art classification methods reveal that S3EResBoF provides competitive performance in terms of both classification and computation time. 1980-2012 IEEE. -
Lightweight Sybil attack detection framework for wireless sensor network with cluster topology
The development of communication and networking technology has made it possible for wireless sensor networks to play a significant role in many fields. Wireless sensor networks are vulnerable to a variety of security threats because of their remote hostile features. The Sybil attack, which generates several identities to gain access to wireless sensor networks, is one such devastating but simple to spread exploit. This Paper proposes a novel identity and trust-based system to ensure protection against Sybil attacks. Analysis of the RSSI and location parameter increases the accuracy. It recognises the attackers and broadcasts information about them to all adjacent sensor nodes. Additionally, it offers other crucial security features. 2025 Author(s). -
Lightweight Sybil attack detection framework for wireless sensor network with cluster topology
The development of communication and networking technology has made it possible for wireless sensor networks to play a significant role in many fields. Wireless sensor networks are vulnerable to a variety of security threats because of their remote hostile features. The Sybil attack, which generates several identities to gain access to wireless sensor networks, is one such devastating but simple to spread exploit. This Paper proposes a novel identity and trust-based system to ensure protection against Sybil attacks. Analysis of the RSSI and location parameter increases the accuracy. It recognises the attackers and broadcasts information about them to all adjacent sensor nodes. Additionally, it offers other crucial security features. 2025 Author(s). -
Lightweight Zero Trust Access Control with Behavior-Based Anomaly Detection in Cloud
As cloud services become more popular, static security models must give way to dynamic, identity-centric ones. This paper introduces a serverless AWS architecturebased Lightweight Zero Trust Access (LZTA) framework with Behavior-Based Anomaly Detection (BBAD) designed for the cloud. Through the use of AWS Lambda to process CloudTrail logs and DynamoDB to store profiles, our system automatically learns user behavior. Using this profile, a Lambda Authorizer at the API Gateway determines a risk score in real time for every access request, preventing unusual activity such as attempts from unidentified IP addresses. This scalable, reasonably priced frame- work proved to be an effective modern cloud security solution by successfully blocking simulated credential theft attacks with a latency of less than 150 ms while running at no cost within the AWS Free Tier. 2025 IEEE. -
Lignin nanoparticles from Ayurvedic industry spent materials: Applications in Pickering emulsions for curcumin and vitamin D3 encapsulation
Lignin nanoparticles (LNP), extracted from spent materials of Dashamoola Arishta (Ayurvedic formulation), shared a molecular weight of 14.42 kDa with commercial lignin. Processed into LNPs (496.43 0.54 nm) via planetary ball milling, they demonstrated stability at pH 8.0 with a zeta potential of ?32 0.27 mV. Operating as Pickering particles, LNP encapsulated curcumin and vitamin D3 in sunflower oil, forming LnE + Cu + vD3 nanoemulsions (particle size: 347.40 0.71 nm, zeta potential: ?42.27 0.72 mV) with high encapsulation efficiencies (curcumin: 87.95 0.21%, vitamin D3: 72.66 0.11%). The LnE + Cu + vD3 emulsion exhibited stability without phase separation over 90 days at room (27 2 C) and refrigeration (4 1 C) temperatures. Remarkably, LnE + Cu + vD3 exhibited reduced toxicity, causing 29.32% and 34.99% cell death in L6 and RAW264.7 cells respectively, at the highest concentration (50 ?g/mL). This underscores the potential valorization of Ayurvedic industry spent materials for diverse industrial applications. 2024 Elsevier Ltd -
Lignin-based nanomaterials for food and pharmaceutical applications: Recent trends and future outlook
Small particles of size ranging from 1 to 100 nm are referred to as nanoparticles. Nanoparticles have tremendous applications in various sectors, including the areas of food and pharmaceutics. They are being prepared from multiple natural sources widely. Lignin is one such source that deserves special mention due to its ecological compatibility, accessibility, abundance, and low cost. This amorphous heterogeneous phenolic polymer is the second most abundant molecule in nature after cellulose. Apart from being used as a biofuel source, lignin is less explored for its potential at a nano-level. In plants, lignin exhibits cross-linking structures with cellulose and hemicellulose. Numerous advancements have taken place in synthesizing nanolignins for manufacturing lignin-based materials to benefit from the untapped potential of lignin in high-value-added applications. Lignin and lignin-based nanoparticles have numerous applications, but in this review, we are mainly focusing on the applications in the food and pharmaceutical sectors. The exercise we undertake has great relevance as it helps scientists and industries gain valuable insights into lignin's capabilities and exploit its physical and chemical properties to facilitate the development of future lignin-based materials. We have summarized the available lignin resources and their potential in the food and pharmaceutical industries at various levels. This review attempts to understand various methods adopted for the preparation of nanolignin. Furthermore, the unique properties of nano-lignin-based materials and their applications in fields including the packaging industry, emulsions, nutrient delivery, drug delivery hydrogels, tissue engineering, and biomedical applications were well-discussed. 2023 Elsevier B.V. -
Lignite-derived nanocarbon as surface passivator and cosensitizer in dye-sensitized solar cell
Interfacial exciton recombination and narrow absorption region are two bottlenecks that limit the performance of a dye-sensitized solar cell (DSSC). The present study focuses on improving the solar cell's efficiency by utilizing a lignite-derived nanocarbon that behaves as a surface passivator and cosensitizer. Incorporating nanocarbon enhanced the spectral absorption region of the N719 dye with a bathochromic shift and played the role of a cosensitizer. In addition, the quenched photoluminescence spectra revealed that nanocarbon also aids in the swift transfer of electrons to the conduction band of TiO2 by reducing the exciton recombination and acting as a surface passivator. On measuring the fabricated DSSC under AM 1.5G irradiation with the intensity of 100 mW/cm2, the nanocarbon-based device exhibited an efficiency (?) of 9.02% with a photocurrent density of 20.45 mA/cm2, outperforming the pristine device (? = 6.21%). An enhancement of 45% in the power conversion efficiency was achieved. Thus, the results unveiled that nanocarbons derived from pollution-causing fuel synergistically aided in enhancing the performance of DSSC. 2024 Elsevier Ltd