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Short term effects of brief need based psychoeducation on knowledge, self-stigma, and burden among siblings of persons with schizophrenia: A prospective controlled trial
Siblings of persons with schizophrenia are important in providing long-term social support to the patients. Interventions addressing their needs are very sparse. Hence, this study aimed at testing the short-term effects of brief need based psychoeducation on knowledge, self-stigma, and burden among siblings of persons with schizophrenia. In this prospective controlled open label trial, 80 siblings of persons with schizophrenia were allocated in equal numbers to the brief need based psychoeducation group and the treatment-as-usual group. The outcomes were measured at baseline, and after the first and third month post-intervention. RM-ANCOVA was conducted to test the effect of the brief psychoeducation on outcome scores. The groups were similar with respect to socio-demographic, clinical, and outcome scores at the baseline. There was a significant group time interaction effect on knowledge (F = 8.71; p < 0.01; ?p 2 = 0.14) and self-stigma scores (F = 14.47; p < 0.001; ?p 2 = 0.21), wherein the brief psychoeducation group showed a significant increase in knowledge and reduction in self-stigma with medium effect size through baseline to the third month follow-up as compared to the treatment as usual group. We also observed a significant main effect of time; irrespective of the group allocation, there was a significant increase in the knowledge through baseline to third month follow-up (F = 5.69; p = 0.02; ?p 2 = 0.09). No main or interaction effects of group and time were observed on burden. The findings suggest that brief need based psychoeducation may increase knowledge about the illness and reduce self-stigma. Further systematic studies are warranted to test this intervention for long-term effects. 2017 Elsevier B.V. -
Short term effects of brief need based psychoeducation on knowledge, self-stigma, and burden among siblings of persons with schizophrenia: A prospective controlled trial /
Asian Journal of Psychiatry, Vol.7, pp.59-66, ISSN: 2211-3797. -
Personality and Psychological Predictors of Instagram Personalized Ad Avoidance
The purpose of this paper is to apply the meta-theoretical model of motivation and personality (3M) of Mowen to study consumers ad avoidance in the context of online personalized advertisements on Instagram. The current study developed a theoretical framework that links personality traits with reactance arousal and ad avoidance behaviours. Based on the data analysis, it was found that consumers with higher general self-efficacy tend to have more reactance arousal (situational level trait) compared to ad irritation, ad skepticism (surface traits), and ad avoidance behaviours towards personalized advertising on Instagram. The findings will help advertisers and marketers in segmenting the market better based on young users efficacy levels, navigational habits, personality traits, functional motives, and demographic variables to effectively reach the targeted consumers. 2023 IGI Global. All rights reserved. -
Adoption Laws in India : A critical Analysis through a Sociological Lens
Golden Research Thoughts Vol.2, Issue 6, pp.1-7 ISSN No. 2231-5063 -
Role of mixed nanofluids on fluid flow and intensify energy transfer in a boundary layer region driven by a free convective force
This research study explores boundary layer flow and intensification of heat transfer through a porous medium accompanied by buoyant forces with the support of appended mixed nanofluids. The generated partial differentiation model is altered to a couple of the highly complicated nonlinear differentiation model by support of the similarity conversion. The resultant model is then resolved by the shooting method for finding the initial approximation and thereafter the Runge-Kutta-Fehlberg 45th-order method is used to get the desired result. The energy transfer and the flow of mixed nanofluids are analyzed by considering vital factors, like convection, porous and volume fraction. The acquired results fairly agree with erstwhile published articles. The major finding is that for greater values of the volume fraction, both fluid flow and energy transfer of a mixed nanofluid will be greater when compared with a regular nanofluid. 2019 Wiley Periodicals, Inc. -
Effect of variable viscosity on marangoni convective boundary layer flow of nanofluid in the presence of mixed convection
The effect of variable viscosity on Marangoni convection in immediate vicinity of the plate is discussed. The mathematical model of the problem is highly nonlinear partial differential equations transforms into two nonlinear ordinary differential equations by applying suitable similarity transformations. The reduced similarity equivalences are then solved numerically by RungeKutta Fehlberg-45 order method. The consequences of pertinent parameters like variable viscosity parameter, convection parameter and volume fraction are analyzed on various flow fields. The results acquired are on par with erstwhile published results. The results of the present study shows that for greater values of angular momentum the buoyancy effects dominate, augmentation in mixed convection carries away the free convection currents from the plate, increase in volume fraction of solid enhances the thermal conductivity of the fluid and it is important to note that Marangoni effect is constructive for cooling processes. 2019 by American Scientific Publishers All rights reserved. -
Non-inverse signed graph of a group
Let G be a group with binary operation *. The non-inverse graph (in short, i*-graph) of G, denoted by ?, is a simple graph with vertex set consisting of elements of G and two vertices x, y ? ? are adjacent if x and y are not inverses of each other. That is, x ? y if and only if x * y ?= iG ?= y*x, where iG is the identity element of G. In this paper, we extend the study of i*-graphs to signed graphs by defining i*-signed graphs. We characterize the graphs for which the i*-signed graphs and negated i*-signed graphs are balanced, sign-compatible, consistent and k-clusterable. We also obtain the frustration index of the i*-signed graph. Further, we characterize the homogeneous non-inverse signed graphs and study the properties like net-regularity and switching equivalence. Amreen J., Naduvath S., 2024. -
Coset component signed graph of a group
In this paper, the notion of a newly derived signed graph called a coset component graph, based on cosets of subgroups of a group is introduced. Let G be a group and H be its subgroup. Then, the coset component graph of H in G, denoted by ?cc, is a simple graph with the vertex set consisting of elements of G and two vertices say, a, b ? ?cc are adjacent if either aH = bH or Ha = Hb. A coset component signed graph of H in G is a signed graph whose edges get the sign in accordance with their inclusion in the edge set of the corresponding coset component graph. The structure and important properties of the coset component signed graphs are determined in this paper. 2024 World Scientific Publishing Company. -
Order Sum Graph of a Group
The concept of the order sum graph associated with a finite group based on the order of the group and order of group elements is introduced. Some of the properties and characteristics such as size, chromatic number, domination number, diameter, circumference, independence number, clique number, vertex connectivity, spectra, and Laplacian spectra of the order sum graph are determined. Characterizations of the order sum graph to be complete, perfect, etc. are also obtained. 2023 University of Baghdad. All rights reserved. -
On the Non-Inverse Graph of a Group
Let (G, ?) be a finite group and S = {u G|u u-1}, then the inverse graph is defined as a graph whose vertices coincide with G such that two distinct vertices u and v are adjacent if and only if either u ? v S or v ? u S. In this paper, we introduce a modified version of the inverse graph, called i?-graph associated with a group G. The i?-graph is a simple graph with vertex set consisting of elements of G and two vertices x, y ? are adjacent if x and y are not inverses of each other. We study certain properties and characteristics of this graph. Some parameters of the i?-graph are also determined. 2022 Javeria Amreen et al., published by Sciendo. -
Dynamic route scheduler in vehicular ad hoc network for smart crowd control
Revenue generated by tourism is positively correlated with the development of any city. In recent years, tourism is getting peak focus among the government, local bodies, and researchers. This has led to increase in initiatives to grow tourism in and across the country. Being one of the most flourishing sectors, tourism in India shows bold signals of emerging as a strong participant in the world of tourism. In addition to safeguarding its culture and deep-rooted traditional values, tourism provides a way to increase employment opportunities as well as increase the foreign exchange within the country. There are many open research problems arising in the domain, which need the attention of researchers. City traffic management is one among the major concern for cities around the world. Scheduling dynamic travel plans for tourists with crowd and traffic awareness has high scope for research. In this paper, a system is proposed which connects the vehicles to a centralized sink for getting the optimal routes. Route scheduling is done based on a prediction model. Different parameters were collected from the environment that includes crowd, traffic, and schedule of other vehicles. The system has modules like static nodes, mobile nodes, host nodes, and sink node for the control and management. Selection of path and protocol is a primary strategy to design any VANET systems. Hence, performance analysis of routing protocols for the proposed system is done as a major step in selection of protocols. Packet delivery ratio, jitter, and throughput are common measures used for the comparison of protocols. 2019, Springer-Verlag London Ltd., part of Springer Nature. -
Succession planning in India: The path less traversed /
The Management Accountant, Vol.54, Issue 2, pp.30-33, ISSN No: 2581-5504. -
Chemical castration: Justice for victims or justice for the rapist /
American Journal of Criminal Law, Vol.3, pp.1-5, ISSN No: 2581-5504. -
Evaluating the Pertinence of Pose Estimation model for Sign Language Translation
Sign Language is the natural language used by a community that is hearing impaired. It is necessary to convert this language to a commonly understandable form as it is used by a comparatively small part of society. The automatic Sign Language interpreters can convert the signs into text or audio by interpreting the hand movements and the corresponding facial expression. These two modalities work in tandem to give complete meaning to each word. In verbal communication, emotions can be conveyed by changing the tone and pitch of the voice, but in sign language, emotions are expressed using nonmanual movements that include body posture and facial muscle movements. Each such subtle moment should be considered as a feature and extracted using different models. This paper proposes three different models that can be used for varying levels of sign language. The first test was carried out using the Convex Hull-based Sign Language Recognition (SLR) finger spelling sign language, next using a Convolution Neural Network-based Sign Language Recognition (CNN-SLR) for fingerspelling sign language, and finally pose-based SLR for word-level sign language. The experiments show that the pose-based SLR model that captures features using landmark or key points has better SLR accuracy than Convex Hull and CNN-based SLR models. 2023 World Scientific Publishing Europe Ltd. -
Effortless and beneficial processing of natural languages using transformers
Natural Language Processing plays a vital role in our day-to-day life. Deep learning models for NLP help make human life easier as computers can think, talk, and interact like humans. Applications of the NLP models can be seen in many domains, especially in machine translation and psychology. This paper briefly reviews the different transformer models and the advantages of using an Encoder-Decoder language translator model. The article focuses on the need for sequence-to-sequence language-translation models like BERT, RoBERTa, and XLNet, along with their components. 2022 Taru Publications. -
Insider attack detection using deep belief neural network in cloud computing
Cloud computing is a high network infrastructure where users, owners, third users, authorized users, and customers can access and store their information quickly. The use of cloud computing has realized the rapid increase of information in every field and the need for a centralized location for processing efficiently. This cloud is nowadays highly affected by internal threats of the user. Sensitive applications such as banking, hospital, and business are more likely affected by real user threats. An intruder is presented as a user and set as a member of the network. After becoming an insider in the network, they will try to attack or steal sensitive data during information sharing or conversation. The major issue in today's technological development is identifying the insider threat in the cloud network. When data are lost, compromising cloud users is difficult. Privacy and security are not ensured, and then, the usage of the cloud is not trusted. Several solutions are available for the external security of the cloud network. However, insider or internal threats need to be addressed. In this research work, we focus on a solution for identifying an insider attack using the artificial intelligence technique. An insider attack is possible by using nodes of weak users systems. They will log in using a weak user id, connect to a network, and pretend to be a trusted node. Then, they can easily attack and hack information as an insider, and identifying them is very difficult. These types of attacks need intelligent solutions. A machine learning approach is widely used for security issues. To date, the existing lags can classify the attackers accurately. This information hijacking process is very absurd, which motivates young researchers to provide a solution for internal threats. In our proposed work, we track the attackers using a user interaction behavior pattern and deep learning technique. The usage of mouse movements and clicks and keystrokes of the real user is stored in a database. The deep belief neural network is designed using a restricted Boltzmann machine (RBM) so that the layer of RBM communicates with the previous and subsequent layers. The result is evaluated using a Cooja simulator based on the cloud environment. The accuracy and F-measure are highly improved compared with when using the existing long short-term memory and support vector machine. 2022 CRL Publishing. All rights reserved. -
Evidence of microRNAs origination from chloroplast genome and their role in regulating Photosystem II protein N (psbN) mRNA
The microRNAs are endogenous, regulating gene expression either at the DNA or RNA level. Despite the availability of extensive studies on microRNA generation in plants, reports on their abundance, biogenesis, and consequent gene regulation in plant organelles remain naVve. Building on previous studies involving pre-miRNA sequencing in Abelmoschus esculentus, we demonstrated that three putative microRNAs were raised from the chloroplast genome. In the current study, we have characterized the genesis of these three microRNAs through a combination of bioinformatics and experimental approaches. The gene sequence for a miRNA, designated as AecpmiRNA1 (A. esculentus chloroplast miRNA), is potentially located in both the genomic DNA, i.e., nuclear and chloroplast genome. In contrast, the gene sequences for the other two miRNAs (AecpmiRNA2 and AecpmiRNA3) are exclusively present in the chloroplast genome. Target prediction revealed many potential mRNAs as targets for AecpmiRNAs. Further analysis using 5N RACE-PCR determined the AecpmiRNA3 binding and cleavage site at the photosystem II protein N (psbN). These results indicate that AecpmiRNAs are generated from the chloroplast genome, possessing the potential to regulate mRNAs arising from chloroplast gene(s). On the other side, the possibility of nuclear genome-derived mRNA regulation by AecpmiRNAs cannot be ruled out. 2024, Termedia Publishing House Ltd.. All rights reserved. -
Exploring graph-based global similarity estimates for quality recommendations
Data sparsity or the insufficiency of past user preferences in predicting future user needs continues to be a major challenge for RS engines. We propose a solution to the sparsity problem by exploring similarity measures that capture the global patterns of commonality between users or items by leveraging on indirect ways of connecting users (items) through a user (item) graph. Entities (users or items) sharing common features are connected to each other by edges weighted by their proximity or distance. Graph-based techniques, for estimating transitive similarity between entities not directly connected, are exploited to bring the entities closer thus facilitating collaboration. Furthermore, we also propose a combined user-item graph approach for exploiting the similarity between users preferring similar items (and vice versa). In this work, we have suggested alternatives to the already existing global similarity assessment and we aim to investigate the appropriateness of the proposed techniques under differing data features. 2014 Inderscience Enterprises Ltd. -
Folksonomy-based fuzzy user profiling for improved recommendations
Genre is a major factor influencing user decisions to peruse an item in domains such as movies, books etc. Recommender systems, generally have, at their disposal, information regarding genres/categories that a movie/book belongs to. However, the degree of membership of the objects in these categories is typically unavailable. Such information, if available, would provide a better description of items and consequently lead to quality recommendations. In this paper, we propose an approach to infer the degree of genre presence in a movie by examining the various tags conferred on them by various users. Tags are user-defined metadata for items and embed abundant information about various facets of user likes, their opinion on the quality and the type of object tagged. Leveraging on tags to guide the genre degree determination exploits crowd sourcing to enrich item content description. Fuzzy logic naturally models human logic allowing for the nuanced representation of features of objects and thus is utilized to derive such gradual representation as well as for modeling user profiles. To the best of our knowledge ours is one of the first approaches to utilize such folksonomy information to infer genre degrees subsequently used for recommendations. The proposed method has the twin advantages of utilizing enriched content information for recommendation as well as squeezing the information from the user-item-tag and user-item ratings spaces and condensing them into fuzzy user profiles. The fuzzy user and object representations are leveraged both for the design of content-based as well as collaborative recommender systems. Experimental evaluations establish the effectiveness of the proposed approaches as compared to other baselines. 2013 Elsevier Ltd. All rights reserved.