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Flexible Nanogenerators Based on Enhanced Flexoelectricity in Mn3O4 Membranes
Atomically thin, few-layered membranes of oxides show unique physical and chemical properties compared to their bulk forms. Manganese oxide (Mn3O4) membranes are exfoliated from the naturally occurring mineral Hausmannite and used to make flexible, high-performance nanogenerators (NGs). An enhanced power density in the membrane NG is observed with the best-performing device showing a power density of 7.99mWm?2 compared to 1.04Wm?2 in bulk Mn3O4. A sensitivity of 108mVkPa?1 for applied forces <10N in the membrane NG is observed. The improved performance of these NGs is attributed to enhanced flexoelectric response in a few layers of Mn3O4. Using first-principles calculations, the flexoelectric coefficients of monolayer and bilayer Mn3O4 are found to be 50100 times larger than other 2D transition metal dichalcogenides (TMDCs). Using a model based on classical beam theory, an increasing activation of the bending mode with decreasing thickness of the oxide membranes is observed, which in turn leads to a large flexoelectric response. As a proof-of-concept, flexible NGs using exfoliated Mn3O4 membranes are made and used in self-powered paper-based devices. This research paves the way for the exploration of few-layered membranes of other centrosymmetric oxides for application as energy harvesters. 2023 Wiley-VCH GmbH. -
Clinical hypnosis and Patanjali yoga sutras
The trance states in yoga and hypnosis are associated with similar phenomena like relaxation, disinclination to talk, unreality, misrepresentation, alterations in perception, increased concentration, suspension of normal reality testing, and the temporary nature of the phenomena. While some researchers consider yoga to be a form of hypnosis, others note that there are many similarities between the trance in yoga and the hypnotic trance. The present study aimed to find similarities between the trance states of hypnosis and Patanjali?s yoga sutras. The trance states were compared with the understanding of the phenomena of trance, and the therapeutic techniques and benefits of both. An understanding of the concept of trance in Patanjali?s yoga sutras was gained through a thematic analysis of the book Four Chapters on Freedom by Swami Satyananda Saraswati. This led to an understanding of the concept of trance in the yoga sutras. The obtained concepts were compared to the concepts of trance in hypnosis (obtained through the literature on hypnosis) to investigate whether or not there exist similarities. The findings of the study show that there are similarities between the trance in hypnosis and the trance in Patanjali?s yoga sutras in the induction and deepening of the trance states in hypnosis and that of Samadhi, the phenomena present in hypnosis and the kinds of siddhis that are obtained through Samadhi, and the therapeutic techniques and the therapeutic process in Patanjali?s yoga sutra and hypnosis. -
A study of pulsation & rotation in a sample of A-K type stars in the Kepler field
We present the results of time-series photometric analysis of 15106 A-K type stars observed by the Kepler space mission. We identified 513 new rotational variables and measured their starspot rotation periods as a function of spectral type and discuss the distribution of their amplitudes. We examined the well-established period-color relationship that applies to stars of spectral types F5-K for all of these rotational variables and, interestingly, found that a similar period-color relationship appears to extend to stars of spectral types A7 to early-F too. This result is not consistent with the very foundation of the period-color relationship. We have characterized 350 new non-radial pulsating variables such as A- and F-type candidate ? Scuti, ? Doradus and hybrid stars, which increases the known candidate non-radial pulsators in the Kepler field significantly, by ?20%. The relationship between two recently constructed observables, Energy and Efficiency, was also studied for the large sample of non-radial pulsators, which shows that the distribution in the logarithm of Energy (log (En)) can be used as a potential tool to distinguish between the non-radial pulsators, to some extent. Through visual inspection of the light curves and their corresponding frequency spectra, we found 23 new candidate red giant solar-like oscillators not previously reported in the literature. The basic physical parameters such as masses, radii and luminosities of these solar-like oscillators were also derived using asteroseismic relations. 2018, The Author(s). -
Effect of pH on the structural and optical properties of cobalt oxide nanoparticles synthesized by hydrothermal method
The paper focuses on the synthesis and characterization of cobalt oxide nanoparticles synthesized under different alkaline pH of the precursor solution by hydrothermal method. Cubic spinel Co3O4 crystallites were observed by X-ray diffraction pattern (XRD) and Raman spectrum. The crystallite size decreases as the pH value increases. The absorption spectrum exhibited two broad bands which are in good agreement with the cobalt oxide band structure. The change in bandgap was observed with pH of the precursor solution in agreement with size effects. Photoluminescence (PL) spectra consist of a broad emission with different peaks which are due to point defects. 2022 -
A review on the electrochemical behavior of graphenetransition metal oxide nanocomposites for energy storage applications
Electrochemical energy storage devices like supercapacitors and rechargeable batteries require an improvement in their performance at the commercial level. Among them, supercapacitors are beneficial in sustainable nanotechnologies for energy conversion and storage systems and have high power rates compared to batteries. High chemical and mechanical stability, huge electrical conductivity, and high specific surface area have been beneficial for selecting graphene as a supercapacitor electrode material. The excellent properties of transition metal oxides are accountable for the application in the field of energy storage. The synergistic effects of the composites of graphene derivatives with transition metal oxides will boost the performance of the devices. Recently, several studies have been done for developing supercapacitor electrodes with these nanocomposites. This review article presents an analysis of the performance of these nanocomposites with an overview of their specific capacitance, energy density, and cycling stability for supercapacitor electrode application. A brief introduction of the theory and experimental analysis of supercapacitors is also given. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Amorphous versus crystalline Al2O3nanoparticles: A comparative study in photocatalytic dye degradation
This study focuses on the synthesis of aluminum oxide (Al2O3) nanoparticles and compares their amorphous and crystalline phases, emphasizing their suitability for photocatalytic dye degradation. The as-prepared Al2O3, synthesized using the sol-gel technique, is found to have an amorphous nature, which is later annealed at 1200C to obtain its ? phase of crystalline nature. Despite the widespread applications of aluminum oxide in various fields, the differences between its amorphous and crystalline phases are not well understood. This work bridges this gap by evaluating the amorphous and crystalline phases of Al2O3, particularly for dye degradation. As technologies advance to enhance aluminum-containing photocatalytic materials by doping, composites, and hybrids, understanding the impact of material phase on photocatalytic capabilities becomes crucial. The research comprehensively assesses structural, functional, morphological, optical, and dye degradation characteristics. Remarkably, amorphous Al2O3 demonstrates superior dye degradation efficacy compared with its crystalline counterpart, achieving an enhanced degradation efficiency of 87.2% for rhodamine B, a commonly used azo dye in the printing and textile industries. 2024 Emerald Publishing Limited: All rights reserved. -
A Deep Ensemble Framework for DDoS Attack Recognition and Mitigation in Cloud SDN Environment
Much research has been done in the recent past on the absolute shift of Internet infrastructure in order to make it more significantly programmable, configurable and make it more conveniently feasible. Software Defined Networking (SDN) forms the basis for this absolute shift in Internet infrastructure. When you look at the benefits of an SDN-based cloud environment they are monumental. Namely, network traffic control and elastic resource management. The SDN-based cloud environment becomes susceptible to cyber threats, especially like that of Distributed Denial of Service (DDoS) attacks and other cyber-attacks that perturb the SDN-based cloud environment. Hence, automated Machine Learning (ML) models are an efficient way to protect against these cyber-attacks. This research will develop a deep learning-based ensemble model for DDoS attack detection and classification (DLEM-DDoS) in a cloud environment. Long Short-Term Memory (LSTM), 1-D Convolutional Neural Networks (1D-CNN) and Gated Recurrent Unit (GRU) are the three DL models integrated into an ensemble model that classifies the incoming packet by majority voting classifiers. Network traffic data including source and destination IP addresses, packet and byte counts, packet and byte rates, flow duration, protocol types and port numbers are fed into the DLEM-DDoS model. This model preprocesses this data by converting categorical values (like protocol types) into numerical values and removing any missing values. Once collected and preprocessed, the data is fed into deep learning models (LSTM, 1D-CNN, GRU) within the framework for analysis. Finally, in this research using the DLEM-DDoS technique an efficient DDoS attack mitigation scheme in an SDN-based cloud environment is demonstrated. The report shows comprehensive stimulations as well as a superiority into the current approaches in terms of several measures. 2024 S. Annie Christila and R. Sivakumar. This open-access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
Multi-Layer Ensemble Deep Reinforcement Learning based DDoS Attack Detection and Mitigation in Cloud-SDN Environment
Cloud computing (CC) remains as a promising environment which offers scalable and cost effectual computing facilities. The combination of the SDN technique with the CC platform simplifies the complexities of cloud networking and considerably enhances the scalability, manageability, programmability, and dynamism of the cloud. This study introduces a novel Multi-Layer Ensemble Deep Reinforcement Learning based DDoS Attack Detection and Mitigation (MEDR-DDoSAD) technique in Cloud-SDN Environment. The major aim of the presented technique lies in the recognition of DDoS attacks from the cloud-SDN platform. The MEDR-DDoSAD technique transforms the input data into images and the features are derived via deep convolutional neural network based Xception model. 2022 IEEE. -
Nanomaterials for A431 Epidermoid Carcinoma Treatment
Malignancy is the ancient sickness that causes an increased rate of mortality worldwide. Traditional malignant growth treatments that are clinically utilized comprise chemotherapy, radiotherapy, and medical procedure. Despite the fact that there have been motivating enhancements in the nanotechnology and biomedical field, malignant growth remains the most urgent condition to treat, as the central reason for mortality. Nanotechnology has the possibility to improve medication transport and delivery by modifying pharmacokinetics and conveyance, resulting in reduced negative reactions and in this manner improving precision. Some issues exist regarding destinations and the difficulties that occur, and the potential for success becomes closer with every discovery. Nanomaterials are smaller in size than organic macromolecules. More correctly, they as a rule have a width of many nanometers (nm), which makes them from 100 up to multiple times smaller than even one malignancy cell. Nanoparticles can occur in sizes running from 10 up to 400nm, and can likewise be used with a simple set up or a blend of pharmacologically dynamic medications, depending on a superficial level of properties. The various aspect of nanotechnology for malignant growth treatment include exact targeting of the lively segments in cell/tissues, producing upgrades responsive medication discharge, defeating natural obstructions, interfacing against disease dynamic system with imaging atoms, improving disease examination, and imaging. For the most part, nanoparticles burdened with mending operators are conveyed experimentally for firm malignancy treatment. Todays nanotechnology is a magnificent platform for the treatment of differing malignant growths. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Comparative Analysis of Predictive Models for Customer Churn Prediction in the Telecommunication Industry
To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. The results indicate that the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition. 2024 IEEE. -
The Role of Gratitude as a Moderator of the Relationship Between Belief in a Just World and Forgiveness Among Middle-Aged Adults in India
This research explores the relationship between personal belief in a just world (PBJW), gratitude, and forgiveness within the context of middle-aged adults in India. While prior research has established links between PBJW and forgiveness, this investigation delves deeper, examining how gratitude moderates these relationships. The primary objective is to unveil how gratitude moderates the connection between PBJW and forgiveness, filling a significant research gap within the Indian context. The researchers collected data from 386 middle-aged Indian adults through online and offline surveys. The study reveals a positive but weak correlation between PBJW and forgiveness. Gratitude significantly moderates this relationship, amplifying the impact of PBJW on forgiveness. These discoveries offer fresh insights into the complex dynamics underlying forgiveness processes among middle-aged adults in India, addressing a critical gap in the existing research landscape within this cultural context. Practical implications are drawn for counselors and formators that support efforts to promote forgiveness and enhance interpersonal harmony and psychological health. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Presence or absence of Dunning-Kruger effect: Differences in narcissism, general self-efficacy and decision-making styles in young adults
The Dunning-Kruger effect is a cognitive bias in which individuals who are unskilled in certain domains overestimate their ability and are unaware of it. Past studies have focused on establishing the effect but have not looked into associated factors. This study aimed to see if the Dunning-Kruger effect has any influence on an individuals narcissism, general self-efficacy and decision making styles especially in young adults in the Indian population. The Dunning- Kruger effect was established using scores from the Cognitive Reflection Task and the Rationality scale from Rational Experiential Inventory, keeping the Unskilled and Unaware phrase under consideration, while establishing cut-offs. The participants were also divided into three groups - the group that was able to estimate their performance, the group that over-estimated their performance and the group that underestimated their performance. The dependent variables were measured using the NPI-16, General Self-Efficacy Scale and Flinders Decision-Making Styles Questionnaire. The Kruskal-Wallis H results showed that there is a significant difference between the group with Dunning-Kruger effect, without Dunning-Kruger effect and the group that underestimated their performance with reference to Narcissism, General Self-Efficacy, Vigilance and Hypervigilance decision-making styles. The Mann-Whitney U results further indicated a significant difference in Narcissism and Vigilance, between the groups that overestimated their performance and the group that accurately estimated their performance. However, there was no correlation between the CRT discrepancy scores of the individuals with Dunning-Kruger effect and the dependent variables. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature. -
Spider Monkey Crow Optimization Algorithm with Deep Learning for Sentiment Classification and Information Retrieval
The epidemic increase in online reviews' growth made the sentiment classification a fascinating domain in academic and industrial research. The reviews assist several domains, which is complicated to gather annotated training data. Several sentiment classification methodologies are devised for performing the sentiment analysis, but retrieval of information is not accurately performed, less effective, and less convergence speed. In this paper, we propose a sentiment paper proposes a sentiment classification model, namely Spider Monkey Crow Optimization algorithm (SMCA), for training the deep recurrent neural network (DeepRNN). In this method, the telecom review is employed to remove stop words and stemming to eliminate inappropriate data to minimize user's seeking time. Meanwhile, the feature extraction is performed using SentiWordNet to derive the sentiments from the reviews. The extracted SentiWordNet features and other features, like elongated words, punctuation, hashtag, and numerical values, are employed in the DeepRNN for classifying sentiments. To retrieve the required review, the Fuzzy K-Nearest neighbor (Fuzzy-KNN) is employed to retrieve the review based on a distance measure. With rigorous assessments and experimentation, it is observed that the proposed SMCA-based DeepRNN performs better in terms of accuracy of 97.7%, precision of 95.5%, recall of 94.6%, and F1-score 96.7%, respectively. 2013 IEEE. -
Fungal Mushrooms: A Natural Compound With Therapeutic Applications
Fungi are extremely diverse in terms of morphology, ecology, metabolism, and phylogeny. Approximately, 130 medicinal activities like antitumor, immunomodulation, antioxidant, radical scavenging, cardioprotective and antiviral actions are assumed to be produced by the various varieties of medicinal mushrooms. The polysaccharides, present in mushrooms like ?-glucans, micronutrients, antioxidants like glycoproteins, triterpenoids, flavonoids, and ergosterols can help establish natural resistance against infections and toxins. Clinical trials have been performed on mushrooms like Agaricus blazei Murrill Kyowa for their anticancer effect, A. blazei Murrill for its antihypertensive and cardioprotective effects, and some other mushrooms had also been evaluated for their neurological effects. The human evaluation dose studies had been also performed and the toxicity dose was evaluated from the literature for number of mushrooms. All the mushrooms were found to be safe at a dose of 2000mg/kg but some with mild side effects. The safety and therapeutic effectiveness of the fungal mushrooms had shifted the interest of biotechnologists toward fungal nanobiotechnology as the drug delivery system due to the vast advantages of nanotechnology systems. In complement to the vital nutritional significance of medicinal mushrooms, numerous species have been identified as sources of bioactive chemicals. Moreover, there are unanswered queries regarding its safety, efficacy, critical issues that affect the future mushroom medicine development, that could jeopardize its usage in the twenty-first century. Copyright 2022 Chugh, Mittal, MP, Arora, Bhattacharya, Chopra, Cavalu and Gautam. -
Development and validation of superstitious beliefs scale
Superstitions though considered as irrational beliefs are widely prevalent in all cultures. Most of the existing work on superstitions are predominantly based on traditional western beliefs. The relevance of established superstition scales which are developed in western societies in collective societies need to explored. Interdependent nature of self which is a characteristic of collectivistic culture also has a role in belief formation. The present study aims at developing a new self-report measure of superstitious beliefs scale. Study 1, focused on exploring the factor structure and establishing reliability over a sample of 338 undergraduate students. The 17-item Superstitious Belief Scale (SBS) developed distinguishes a six-factor structure namely, Popular Beliefs, Belief in Good Luck, Belief in Bad Luck, Personal Superstitions and Social Superstitions. The six-factor structure was evaluated on a new sample (N = 483) using confirmatory factor analysis in Study 2. The internal consistency values of the new SBS over Studies 1 and 2 indicated high reliability. The findings have important implications for existing theory on superstitions. The new framework proposes and demonstrates the need to base the understanding of measurement of superstitious beliefs relevant in India. AesthetixMS 2020. -
Measures of superstitious beliefs: A meta-analytic review of research
Superstition is a term which is widely used across the globe but, is understood differently by people from different cultures. Superstitious beliefs are challenged by emerging scientific knowledge, and they continue to persist even among advanced societies. In recent years, superstitions are viewed as a belief in luck. The instruments that are available to assess this phenomenon are few and have insufficient psychometric properties. There is a need for developing new standardised measures which explore the complex, conceptual nature of superstitions. A meta-analysis of existing literature was done to explore the existing measures of superstitious beliefs and to examine the relationship between reliability of scales and the various attributes of scales. A literature search was conducted in relevant databases. Suitable transformation procedures for coefficient alpha were used. Meta-regression analysis was done to explore the heterogeneity of data. 41 scales measuring superstitions were analysed. Results indicate that reliability coefficients were from heterogeneous samples. Regression analysis revealed that few characteristics of scales predicted reliability. Journal of the Indian Academy of Applied Psychology. -
Young Adults Consumption Patterns and Attitude towards Minimalist Lifestyle during COVID-19 Pandemic- An Exploratory Study
Purpose The COVID-19 pandemic disrupted the consumption patterns of people the world over. The patterns and trends of consumption that drive markets were no longer relevant during the pandemic. Newer factors drove the consumption decisions and consumers have changed their patterns. COVID pandemic enforced citizens globally to adopt minimalism. This research is aimed at qualitatively understanding the consumer experiences during the lockdown period and their future orientation towards a minimalist lifestyle. Method Participants were young adults of 18 to 25 years of age from India. A constructivist paradigm was adopted to understand the subjective meaning of their choices. Data was collected through Focused group discussions and content analysis was used to arrive at the themes. Findings Data revealed that priority was given to buying essential items during times of crisis. Stockpiling, conscious buying and simple living were the cornerstones of the consumption patterns. Practical implications Findings have implications for sustainable consumption practices with a minimalist approach. Understanding the future orientation of consumers towards adopting a minimalist lifestyle could help market researchers better understand sustainable consumption patterns, thereby helping them in tailoring their product marketing. The far-reaching implications of the results focus on green consumption values and ecological responsibility. Value This paper seeks to explore attitudes and beliefs on sustainable consumption in a young adult population during the Covid-19 outbreak and has implications for sustainable consumption practices using a minimalistic approach in the future. 2022 RESTORATIVE JUSTICE FOR ALL. -
Air Quality Index, Personality Traits and Their Impact on the Residential Satisfaction and Quality of Life: An Exploratory Path Analysis Model
The environment directly influences the behaviour, experiences, and also the well-being of people. It is not only the outside environment but the indoor environmental quality (IEQ) that also affects the well-being of its residents (Arif et al., 2016). The objective of the present study is to study the relationship between Air Quality Index (AQI), Personality traits, Residential Satisfaction, and quality of life among participants living in Bengaluru, Chennai, and Delhi NCR. A total of 685 residents aged 18-65, living in Bengaluru, Chennai, and Delhi NCR for over 2 years, who responded to the call for participation were selected for the study. Data was collected through online Google forms. Correlation and regression analysis were carried out to understand the strength and direction of the relationship between study variables. SPSS AMOS was used to estimate the measurement model and capture mediation paths. The results present an exploratory model which identifies air quality index and personality traits and their contribution towards the perceptions of residential satisfaction. The study also establishes a link between residential satisfaction and quality of life, the new ecological paradigm, and the dominant social paradigm. The present study highlights the necessity to adopt a pro-environmental approach to improve the quality of life. 2024 - IOS Press. All rights reserved. -
Impact of Urban Environmental Quality, Residential Satisfaction, and Personality on Quality of Life among Residents of Delhi/NCR
Environmental quality and Sustainability seek to preserve, enhance and protect our environmental resources that directly aim at providing an amicable quality of life and sustainable development for the upcoming generations. Considering the hazardous environmental urban quality in Delhi NCR, air pollution is the topmost factor deteriorating health of the population in general. The urban air database by WHO reports Delhi exceeding the maximum PM10 limit by almost 10-times at 292 ?g/m3. Noticing that an individual's surroundings have an enormous value in human lives, the study aimed at understanding the impact of urban environmental quality, residential satisfaction, and personality on the quality of life among residents of Delhi NCR. In addition, we also track the environmental worldviews to attitudes on pro-environmental behavior in understanding sustainability. The results from the SEM model indicated that one index rise in RESS lead to a fall in quality of life by 0.029-point value whereas one index rise in personality could enhance the quality of life by 0.15-point value. Pro-Environmental Behaviors and Urban Environmental factors did not showcase any significant impact on the quality of life. The Electrochemical Society.