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Perspectives Envisaging Employee Loyalty : A Case Analysis
Journal of Management Research Vol. 12, No. 2, pp 100-112, ISSN No. 0974-455X -
Perspectives on the Intersection of Gender, Customary Laws and Land Rights in India
For centuries, tribal communities in India have maintained distinct social and cultural identities, often with communal land ownership practices that were inclusive of women. The struggle of tribal women in India for land rights is a poignant manifestation of their fight against intersecting forms of oppression rooted in patriarchy, traditional power structures, and historical marginalisation. Given the existing background, this article discusses the intersection of property rights and gender relations in India, making a case for independent property rights for tribal women. It analyses the role of customary laws of inheritance in a legal pluralistic India and its conflict with positive law. The article also focuses on the role of the Indian judiciary in remedying the systemic discrimination against tribal women in India. It analyses the approach of the Indian courts in maintaining a balance between the autonomy granted to the tribes by the Indian Constitution and ensuring justice to women who are victims of such self-governance. 2024 Jyoti Singh and Kajori Bhatnagar. -
Persuasive techniques used by advertisers in television commercials /
The purpose of this research is to observe the persuasive techniques used by advertisers in television commercials focussing on eight different advertisements belonging to four different categories. The researcher concentrates on the different components utilized by promoters to summon passionate reaction on the viewers/consumers. The commercials chosen by the researcher depict essential connections that are esteemed and kept up in the society. -
Pertaining analysis of fracture risk in Osteoporotic patients using Machine Learning Techniques
Bone fractures in the spine or hip are the most severe complications of Osteoporosis. Older subjects with Osteoporosis are vulnerable to falls. This paper aims to review the breakthrough in machine learning methods over the past four years in assessing fracture risk in osteoporotic patients. Machine learning is applied in the healthcare and medical field. Machine learning professionals can accurately predict disease onset by analyzing a large amount of data. Osteoporosis is one of the healthcare domains in which new Machine learning and Artificial Intelligence techniques can be implemented. The objective of this research is to give an overview of the recent advancements in machine learning methods in finding out the risk factors for fractures or predicting the onset of disease. A systematic search was conducted in PubMed to get research papers published on Machine learning methods to detect, classify, or predict osteoporosis-related fracture risk. The articles belonging to Fracture prediction and risks (n=14), Osteoporosis classification(n=3), Diagnosis of fracture(n=3), and Predicting length of stay (n=1) were identified. The quality of the articles is assessed. Most articles described the efforts to create the model and showcased excellent results in predicting the risks. Significant limitations were in the form of inadequate data splitting and data validations. More validation studies are needed in various large groups to improve the model. Most of the participants in significant studies were in their initial stage of the disease, and the reproducibility analysis was done with major disease issues. 2023 IEEE. -
Perusal of flexoelectric effect with deformed interface in distinct (PZT-7A, PZT-5A, PZT-6B, PZT-4, PZT-2) piezoelectric materials
The present research article aims to describe that the flexoelectric affects the propagation of Love-type in various piezoelectric (PE) materials bars (PZT-7A, PZT-5A, PZT-6B, PZT-4, PZT-2) that rest over a silicon oxide plate under the presence of a deformed interface. With the help of material properties of these various piezoelectric, this article elucidates the impact of flexoelectric (FE) and piezoelectric (PE) on propagation characteristics of Love-type waves. Before this, the desire dispersion relation in the form of a complex, for both electrically unlocked/locked conditions, have been obtained by using mechanical as well as electrical quantities for the respective medium under suitable boundary and interface conditions. The complex dispersion relation is separated into real and imaginary terms which give Real(c) and Imag(c). Further, the effect of flexoelectric (FE) and piezoelectric (PE) on Real(c) and Imag(c) have been observed. In addition, a comparative study among various types of piezoelectric materials is also performed which serve as a major highlight of the present research work. The outcomes of this study may be very helpful in the specific problems of monitoring structural health system design with the help of simulation and alesser number of elaborate trials. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Pester power and advertisements influence on purchase of food products in a convenience store /
Asian Journal Of Management, Vol.8, Issue 2, pp.204-214, ISSN: 2321-5763 (Online) 0976-9495X (Print). -
PEVRM: Probabilistic Evolution Based Version Recommendation Model for Mobile Applications
Traditional recommendation approaches for the mobile Apps basically depend on the Apps related features. Now a days many users are in quench of Apps recommendation based on the version description. Earlier mobile Apps recommendation system do not handle the cold start problem and also lacks in time for recommending the related and latest version of Apps. To overcome this issues, a hybrid Apps recommendation framework which is considering the version of the mobile Apps is proposed. This novel framework named 'Probabilistic Evolution based Version Recommendation Model (PEVRM)' integrates the principles of Probabilistic Matrix Factorization (PMF) with Version Evolution Progress Model (VEPM). With the help this novel recommendation algorithm, the mobile users easily identify the specific Apps for particular task based on its version progression. At same time, this framework helps in resolving cold start problems of new users. Evaluations of this framework utilize a benchmark dataset, i.e., Apple's iTunes App Store3, for revealing its promising performance. 2013 IEEE. -
pH-dependent water permeability switching and its memory in MoS2 membranes
Intelligent transport of molecular species across different barriers is critical for various biological functions and is achieved through the unique properties of biological membranes14. Two essential features of intelligent transport are the ability to (1) adapt to different external and internal conditions and (2) memorize the previous state5. In biological systems, the most common form of such intelligence is expressed as hysteresis6. Despite numerous advances made over previous decades on smart membranes, it remains a challenge to create a synthetic membrane with stable hysteretic behaviour for molecular transport711. Here we demonstrate the memory effects and stimuli-regulated transport of molecules through an intelligent, phase-changing MoS2 membrane in response to external pH. We show that water and ion permeation through 1T? MoS2 membranes follows a pH-dependent hysteresis with a permeation rate that switches by a few orders of magnitude. We establish that this phenomenon is unique to the 1T? phase of MoS2, due to the presence of surface charge and exchangeable ions on the surface. We further demonstrate the potential application of this phenomenon in autonomous wound infection monitoring and pH-dependent nanofiltration. Our work deepens understanding of the mechanism of water transport at the nanoscale and opens an avenue for the development of intelligent membranes. 2023, The Author(s), under exclusive licence to Springer Nature Limited. -
pH-indicator based on delignified jute fiber and red cabbage anthocyanins for monitoring fish spoilage using a smartphone application
Halochromic materials that show visible color changes in response to changes in pH are suitable for the real-time monitoring of fish spoilage. In this study, an easy-to-use, simple, inexpensive, and non-toxic fish freshness indicator was fabricated by combining delignified jute (Corchorus olitorius) fibers and anthocyanins (halochromic materials) from red cabbage (DFA: Delignified jute fibers incorporated with anthocyanins). A single-step decolorization/delignification using solar irradiation along with NaOH and H2O2 treatment was used for modifying the jute fibers. This method helps to overcome the self-color, mitigates the lack of affinity of jute fibers towards anthocyanins and preserves the lignin so that the strength of the fiber is not impacted. A smartphone-based color analysis was used for real-time fish quality monitoring using DFA. To the best of our knowledge, there are no reports on the use of jute fibers as substrates to incorporate anthocyanins for food spoilage monitoring. The indicator displayed an observable color response to the pH and varying concentrations of amine compounds. During the storage of fish (mackerel), the colorimetric indicator showed a visible color change from pink (for fresh fish) to blue (for spoiling fish) and then to green (for spoiled fish), corresponding to changes in pH and total volatile basic nitrogen. To offer a straightforward quantitative assessment of color changes, we utilized the freely available Android application Color Grab to measure the color using RGB and L*, a*, and b* indices. The DFA indicator providing naked-eye analysis has the potential to be an effective tool for real-time monitoring of on-site food spoilage by non-specialized personnel in resource-limited areas. 2024 Elsevier B.V. -
Pharmaceutical Tablet Uniformity Prediction Using Spectroscopy-Based Data Fusion and Machine Learning Approaches
The pharmaceutical industry is highly regulated, and every manufacturer must demonstrate the drug product's quality, safety, and efficacy before market release. Quality control plays a vital role in ensuring drug products' consistency, purity, and potency through rigorous testing of raw materials in the process and the finished stages of manufacturing. Quality risk management and process understanding are critical to maintaining quality throughout manufacturing. Quality by Design (QbD) offers a structured approach, while Process Analytical Technology (PAT) facilitates real-time monitoring to control risk of product quality. Process analyzers, multivariate methods, process control, and continuous improvement tools are part of the PAT framework that enhances process understanding and aids risk mitigation strategies. Near-infrared (NIR) spectroscopy is a commonly used analytical technique in PAT environments for both qualitative and quantitative measurements; these are real-time and non-destructive process analyzers. Chemometrics helps extract information from this chemical data using mathematical and statistical methods. With the advent of Industry 4.0, machine learning models have gained popularity in spectroscopy due to their ability to handle complex, high-dimensional data and adapt to various applications. This research introduces a systematic approach to implementing machine learning models as an alternative to traditional chemical testing in predicting the content uniformity of pharmaceutical tablets. The objective is to improve the quality of data analysis and its predictive performance. This study also outlines the importance of using manufacturing information as stratified variables in predictive modeling and spectroscopic data, or sensor fusion data. To demonstrate the effectiveness of this approach, a real-world NIR dataset developed based on various characteristics such as manufacturing scale, tablet strength, dose proportion, and coating is utilized. This real-world application of the research makes the content more relatable and interesting to the reader. This allows the seamless use of the model across different known environments as the model is trained using sensor data fusion. A comparison of Partial Least Squares regression models and machine learning Neural Network models is evaluated for the model predictability. The work also delves into selecting and optimizing appropriate hyperparameters for a chosen optimal model. It explores the impact of model performance to ensure successful implementation in the production environment and discusses various approaches in monitoring during life cycle management. -
Phenolic composition and antioxidant potential of Cosmostigma cordatum
Cosmostigma cordatum (Poir.) M.R. Almeida, a plant belonging to the family Apocynaceae, has not been explored for its phytochemistry and antioxidant properties. Dried samples of leaves were used to estimate the proximate and mineral composition. Distilled water, methanol, and ethanol extracts were analyzed for the quantification of phenolic compounds and antioxidant potential. EC50 values were determined to estimate the antioxidant potential. Leaves of C. cordatum were found to be a good source of proximate contents and minerals. The total phenols, flavonoids, minerals, and antioxidant activity were determined from methanolic, ethanolic, and aqueous extracts of leaves. Extracts showed a higher concentration of phenols (2.29 0.06 mg GAE g-1) in methanolic extracts and these extracts had higher antioxidant activity when compared to ethanol and aqueous extracts. The flavonoid content was higher in ethanolic extracts (51.94 0.89 mg QE g-1) than in other extracts. In addition, gas chromatography-mass spectroscopy analysis of the hexane extract of leaves identified (E,E)-7,11,15-trimethyl-3-methylene-hexadeca-1,6,10,14-tetraene, 1H-cycloprop[e]azulene, decahydro-1,1,7-trimethyl-4-methylene-, n-hexadecanoic acid, 1-naphthalenepropanol,.alpha-ethenyldecahydro-2-hydroxy-.alpha.2,5,5,8a-pentamethyl [1R[1.alpha.(R*).beta.4a.beta.8a.alpha.]]-,cis-3,14-clerodadien-13-ol, squalene and octacosane. Our results suggest that the leaves can become a potential source of food supplements, nutraceuticals, and photo-therapeutics. 2022, Indian journals. All rights reserved. -
Philanthropic and Functional Motivation of DREAMS Afterschool Intervention Programme Volunteers: A Correlational Study
Rapid increase in access to information and communication technology among youths have changed their approach towards life. Present study aims to find the relationship between philanthropy and functional motivation among fresh DREAMS volunteers. Study adopted two standardized tool to measure philanthropy and functional motivation. Study selected all the fresh 255 volunteers who just joined DREAMS afterschool intervention programme (AIP), which included 25 boys and 230 girls. Study employed descriptive correlational design and administered the survey questionnaire to participants of the study. Statistical analysis of the data revealed a significant positive moderate correlation between philanthropy and functional motivation. Philanthropy could explain 11.8% variation in functional motivation of fresh volunteers. Quartile points explains almost 74% of the participants fared high on functional motivation than philanthropy. Thus, present day youths have high functional motivation to volunteer than philanthropy. Future researchers may delve into the root cause for lack of philanthropic mindset among gen Zs. 2024 Asian Journal of Human Services, All rights reserved. -
PHILOSOPHICAL POSTHUMANISM: A RENEWED WORLDVIEW AND A METHODOLOGICAL FRAMEWORK FOR CRITICAL ANALYSIS
Exponential technological advances capture the zeitgeist of contemporary society. Machines are increasingly gaining agency, which helps in the deconstruction of the humanist notion of humans. Society takes a posthuman turn with large-scale humanmachine imbrication and nonhuman agency. The posthuman turn is also reflected in the academic world, which is seriously contemplating the integration of posthumanities. The philosophical posthumanism of Francisca Ferrando is a posthuman theory with three constituent elements: post-humanism, post-anthropocentrism, and post-dualism. Post-humanism revisits the definition of human that has given rise to marginalization within the human species. Post-anthropocentrism critiques the human superiority and exceptionalism that have led to the marginalization of other species. Post-dualism revisits the dualistic mindset that allows hierarchical sociopolitical constructions. Ferrando presents a vision of a posthuman utopian society that recognizes pluralistic voices within the human species on egalitarian terms, accepts and values the agency of nonhuman actors, and sheds the dualistic view of life that keeps humans and nonhumans on either side of the binary system. Philosophical posthumanism can be suitable as a methodological framework to analyze the posthuman discourses in literary works, specifically in science fiction. 2024 The Pennsylvania State University, University Park, PA. -
Phishfort - Anti-phishing framework
Phishing attack is one of the most common form of attack used to get unauthorized access to users' credentials or any other sensitive information. It is classified under social engineering attack, which means it is not a technical vulnerability. The attacker exploits the human nature to make mistake by fooling the user to think that a given web page is genuine and submitting confidential data into an embedded form, which is harvested by the attacker. A phishing page is often an exact replica of the legitimate page, the only noticeable difference is the URL. Normal users do not pay close attention to the URL every time, hence they are exploited by the attacker. This paper suggests a login framework which can be used independently or along with a browser extension which will act as a line of defense against such phishing attacks. The semi-automated login mechanism suggested in this paper eliminates the need for the user to be alert at all time, and it also provides a personalized login screen so that the user can to distinguish between a genuine and fake login page quite easily. 2018 Authors. -
Phishing attack detection using Machine Learning
Phishing is a type of digital assault, which adversely affects people where the client is coordinated to counterfeit sites and hoodwinked to screen their touchy and private data which integrates watchwords of records, monetary data, ATM pin-card data, etc. Recently safeguarding touchy records, it's fragile to cover yourself from malware or web phishing. AI is an investigation of information examination and logical investigation of calculations has demonstrated outcomes. Contradicting phishing sprinters with remarkable perception and felonious outcomes comparable as care shops, and custom against phishing approaches. This paper examines the association of Machine Literacy routes in identifying phishing assaults and records their advantages and drawbacks. There are countless Machine Learning calculations that have been dug to proclaim the relevant decision that act as against phishing apparatuses. We made a phishing section framework that extracts capacities that are expected to descry phishing. We likewise utilize numeric outline, as well as an overall investigation of customary Machine Learning methodologies comparable as Decision Tree, Random Forest, Multi-layer Perceptron's, XG Boost Classifier, SVM, Light BGM Classifier, Cat Boost Classifier, and covering grounded highlights choice, which contains the metadata of URLs and assists with deciding if a site is licit or not. 2022 The Authors -
Phonon limited diffusion thermopower in phosphorene
A theoretical investigation of diffusion thermopower, Sd, of phosphorene employing Boltzmann transport formalism is presented. We assume carriers in phosphorene to be scattered by in-plane single and flexural two-phonon processes via deformation potential coupling. Our calculations of Sd in phosphorene show that, at low temperatures (T?< 20 K) Sd increases linearly with temperature and for the range of temperatures considered single phonon contribution to Sd dominates. As function of carrier concentration, ns, considered (1016?1018 m-2), at T = 300K, Sd decreases from 189?V/K to 9.9 ?V/K. 2017 Author(s). -
Phosphorus-doped molybdenum disulfide as counter electrode catalyst for efficient bifacial dye-sensitized solar cells
MoS2 is a promising counter electrode material for dye-sensitized solar cell owing to its optical and electrical properties and two-dimensional layered structure. However, it still suffers from minimal conductivity, poor charge transport and less active sites. The present study offers a promising method for enhancing catalytic and fast charge transfer in MoS2 through heteroatom doping of phosphorus. A facile one-step hydrothermal treatment was acquired to do the phosphorus doping. The spin-coated P-doped MoS2 (MSP2) counter electrode (CE) shows a superior power conversion efficiency of 7.93% for front illumination and 5.34% for rear illumination, outperforming Pt-based (7.41% and 5.75%) CE. Thus, phosphorous incorporation increases the number of active sites and improves the catalytic property of the material. The P-doped MoS2 (MSP2) CE film also shows high transmittance, making it a suitable choice for bifacial type of solar cell. 2023 Elsevier Ltd -
Photoaligned Liquid Crystalline Structures for Photonic Applications
With the advancement of information display technologies, research on liquid crystals is undergoing a tremendous shift to photonic devices. For example, devices and configurations based on liquid crystal materials are being developed for various applications, such as spectroscopy, imaging, and fiber optics. One of the problems behind the development of photonic devices lies in the preparation of patterned surfaces that can provide high resolution. Among all liquid crystal alignment techniques, photoalignment represents a promising non-contact method for the fabrication of patterned surfaces. In this review, we discuss the original research findings on electro-optic effects, which were mainly achieved at the Department of Electronic and Computer Engineering of the Hong Kong University of Science and Technology and the collaborating research laboratories. 2023 by the authors. -
Photocatalytic activity of bismuth silicate heterostructures synthesized via surfactant mediated sol-gel method
A surfactant mediated sol-gel method is employed to synthesize bismuth silicate heterostructures with tunable morphologies and properties. The synthesized nanoparticle samples were characterized by XRD, FTIR Spectroscopy, SEM-EDAX and UV-DRS. The synthesized bismuth silicates exhibit excellent photodegradation against malachite green and rhodamine B dyes in the aqueous medium. Bismuth silicates (10% SiO2-Bi2O3) show superior photocatalytic property and outstanding reusability compared to pure bismuth oxide. The kinetics of the photodegradation of the dyes shows that the reaction follows first-order kinetics with the regression coefficient of 0.99. Thus, enabling Bismuth silicates heterostructures practical application as a photocatalyst for clean water. 2019 Elsevier Ltd -
Photocatalytic and antioxidant potential of silver nanoparticles biosynthesized using Artemisia stelleriana leaf extracts
The antioxidant and photocatalytic activity of Artemisia stelleriana-based silver nanoparticles (AS-AgNPs) was investigated in this study. Microscopic, X-ray diffraction and spectroscopic studies were used to characterize the synthesized AS-AgNPs. UVvisible spectrophotometric examination revealed a peak at 425 nm. The phytocompounds involved in the transformation of silver ions into AS-AgNPs were confirmed using Fourier-transform infrared spectroscopy analysis. The crystalline nature of the AS-AgNPs was verified using the X-ray powder diffraction technique. Spherical-shaped AS-AgNPs with a size of 22.7 nm were proved using field emission scanning electron microscopy. The AS-AgNPs were top-notch photocatalysts for the degradation of Reactive Blue-222A (RB-222A) and Reactive Blue-220 (RB-220) dyes. After 80 min of UV light exposure, AS-AgNPs degraded RB-222A and RB-220 dyes by 94.6 and 90.8%, respectively. The phytotoxicity investigation in Vigna radiata and Arte-mia salina indicated that the hazardous dye can be degraded into innocuous chemicals by AS-AgNPs. The results suggest that AS-AgNPs are an excellent antioxidant and photocatalyst for the degradation of synthetic dyes. 2023 The Authors.