Search

COVID-19 has fostered the growth and transformation of digital media in every aspect, importantly in the area of electronic commerce. During these days, many new practices inhabiting in human behaviour bring new norms for the marketers. Use of online shopping has increased incrementally due to the government advisory, changing consumer buying behaviour as well. An amalgamation of the old and new medium of selling goods and services are now bringing new business challenges post pandemic for the marketer, and customer retention is one of them. Henceforth, there is a dearth of studies addressing the impact of dimension of loyalty (behaviour/ attitude) on customer retention in online shopping platforms post pandemic. This study considers post pandemic as the context of research to determine the impact of behavioural and attitudinal loyalty on customer retention for the online shopping platforms. Further research also aims to determine whether the brand image plays a critical role in mediating the relationship between dimensions (Behavioural/ Attitudinal) of loyalty and customer retention for online shopping platforms or not? In the research, primary data represent the respondent from Delhi NCR. The author applied linear regression to validate the research idea. The findings indicate that attitudinal loyalty significantly enforces customer retention over behavioural loyalty. Also, brand image mediates the impact of attitudinal loyalty on retention.

Voting-based consensus clustering is a subset of consensus techniques that makes clear the cluster label mismatch issue. Finding the best relabeling for a given partition in relation to a reference partition is known as the voting problem. As a weighted bipartite matching problem, it is frequently formulated. We propose a more generic formulation of the voting problem as a regression problem with various and multiple-input variables in this work. We demonstrate how a recently developed cumulative voting system is an exception that corresponds to a linear regression technique. We employ a randomised ensemble creation method in which an excess of clusters are randomly chosen for each ensemble partition. In order to extract the consensus clustering from the combined ensemble representation and to calculate the number of clusters, we use an information-theoretic approach. Together with bipartite matching and cumulative voting, we use it. We provide empirical data demonstrating significant enhancements in clustering stability, estimation of the real number of clusters, and accuracy of clustering based on cumulative voting. The gains are made in comparison to recent consensus algorithms as well as bipartite matching-based consensus algorithms, which struggle with the selected ensemble generation technique.

PurposeThis paper will try to uncover how e-learning is giving a new shape to the education industry. Also, it will encompass the students' perspective and experience of e-learning.Design/methodology/approachThe present study employed interpretative phenomenological analysis (IPA) to intensely scrutinize the lived-in experiences of the participants. In the present study, the respondents were selected from Delhi NCR of India. Semi-structured interviews were conducted to collect the primary data to understand the student's perspectives on the impact of information and communications technology (ICT) in education industry.FindingsThe findings have been grouped under two sections referred to as “themes,” which include “drivers for e-learning adoption” and “inhibitors which restrict the adoption of e-learning.”Practical implicationsAt present, India does not have a big market for e-learning, but there is huge potential in the country. The present study may be helpful for the educational institutions in India and in similar developing countries in understanding the students' perspectives on e-learning adoption. The educational institutions may improve their systems accordingly so that they can not only retain the students of their own countries but also attract students from other countries for further education.Social implicationsE-learning can be employed to give users quick access to ideas and experiences from a wide range of people, communities, and the cultures to increase the tangibility.Originality/valueThe study will be useful to the policymakers in the higher education sector of developing nations like India, in understanding the students' mindsets. This study makes a contribution to the growing literature on e-learning, where the researchers have determined the relative importance of various motivating and inhibiting factors which influence the adoption of e-learning. Additionally, the study has used IPA as the methodology to determine the factors, which is a novel contribution.

Through the use of blockchain technology, sensitive information may be securely communicated without the need to replicate it, which can assist in decreasing medical record mistakes and saving time by eliminating the need to duplicate information. Furthermore, the information is timestamped, which further enhances the security of the data even further. The deployment of blockchain technology in a range of healthcare situations may enhance the security and efficiency of payment transactions. In this way, only those who have been allowed access to patient medical information can see or modify such information. It is proposed in this study that blockchain technology be used to provide an accessible data storage and retrieval mechanism for patients and healthcare professionals in a healthcare system that is both safe and efficient. As of 1970, a variety of traditional knowledge-based approaches such as Personal Identification Recognition Number (PIRN), passwords, and other similar methods have been made available; however, many token-based approaches such as drivers’ licenses, passports, credit cards, bank accounts, ID cards, and keys have also been made available; however, they have all failed to establish a secure and reliable transaction channel. Because they are easily misplaced, stolen, or lost, they are usually unable to protect secrecy or authenticate the identity of a legitimate claimant. Aside from that, personally identifiable information such as passwords and PINs is very prone to fraud since they are easily forgotten or guessed by an imposter. Biometric identification and authentication (commonly known as biometrics) are attracting a great deal of attention these days, particularly in the realm of information security systems, due to its inherent potential and advantages over other conventional ways for identifying and authenticating. As a result of the device’s unique biological characteristics, which include features such as fingerprints, facepalms, hand geometry (including the iris), and the device’s iris, it can be used in a variety of contexts, such as consumer banking kiosks, airport security systems, international ports of entry, universities, office buildings, and forensics, to name a few. It is also used in several other contexts, including forensics and law enforcement. Consequently, every layer of the system—sensed data, computation, and processing of data, as well as the storage and administration of data—is susceptible to a broad variety of threats and weaknesses (cloud). There does not seem to be any suitable methods for dealing with the large volumes of data created by the fog computing architecture when normal data storage and security technologies are used. Because of this, the major objective of this research is to design security countermeasures against medical data mining vulnerabilities that originate from the sensing layer and data storage in the Internet of Things’ cloud database, both of which are discussed in more depth further down. A key allows for the creation of a distributed ledger database and provides an immutable security solution, transaction transparency, and the prohibition of tampering with patient information. This mechanism is particularly useful in healthcare settings, where patient information must be kept confidential. When used in a hospital environment, this method is extremely beneficial. As a result of incorporating blockchain technology into the fog paradigm, it is possible to alleviate some of the current concerns associated with latency, centralization, and scalability.

ICT brought waves of industry transformations, which is also visible in education industry. With the changing environment and the industry demand, student’s perspective towards learning is also changing at a fast pace. Gone are the days when teachers used to merely teach through blackboards in a lecture hall. The scenario is no more visible these days. ICT in education is being used to enhance creativity, interaction and knowledge sharing apart from student learning. But, the question is whether e-learning environment is able to achieve these objectives? This paper will try to uncover how e-learning is giving a new shape to the education industry. Also, it will encompass the students’ perspective and experience of e-learning. The results reveal that government is taking many initiatives for developing and improving this platform. Despite the efforts by the Government, students are still not fully convinced with the potential benefits of e-learning. Furthermore, these platforms have confused the students regarding which one should they opt for. Based on these findings, the authors have developed managerial implications for the educators, students as well as educational institutions.

In the era of World Wide Web, where the number of choices is irresistible, there is need to prioritize, filter, efficiently and effectively deliver significant information to solve the problem of information overload, which has posed a potential crisis for many Internet users. Recommendation systems answer this problem by penetrating through voluminous dynamically produced data to offer users with personalized information and services. This paper puts light on the various features and existing power in different prediction methods of recommender systems for assistance in research and practice in the area for developing powerful recommendation systems.

In this era of World Wide Web, where gigantic amount of data is being generated by visitors and automated application software’s in the web. These generated data is not just the data but it contains the jewels of information. To discover the hidden information in data, a lot of efforts have been done by various researchers where numerous techniques on different web log data sets have been applied. However, It has been applied here the Web log expert software tool on web data log data sets to extract the fruitful information by performing the deep analysis.

Broadly neutralizing antibodies have been associated with spontaneous clearance of the hepatitis C infection as well as viral persistence by immune escape. Further study of neutralizing antibody epitopes is needed to unravel pathways of resistance to virus neutralization, and to identify conserved regions for vaccine design. All reported broadly neutralizing antibody (BNAb) epitopes in the HCV Envelope (E2) glycoprotein were identified. The critical contact residues of these epitopes were mapped onto the linear E2 sequence. All publicly available E2 sequences were then downloaded and the contact residues within the BNAb epitopes were assessed for the level of conservation, as well as the frequency of occurrence of experimentally-proven resistance mutations. Epitopes were also compared between two sequence datasets obtained from samples collected at well-defined time points from acute ( 180days) infections, to identify any significant differences in residue usage. The contact residues for all BNAbs were contained within 3 linear regions of the E2 protein sequence. An analysis of 1749 full length E2 sequences from public databases showed that only 10 out of 29 experimentally-proven resistance mutations were present at a frequency >5%. Comparison of subtype 1a viral sequences obtained from samples collected during acute or chronic infection revealed significant differences at positions 610 and 655 with changes in residue (p

Cytokines play a major role in driving immune responses in cancer and other diseases. There is a critical need to understand how they interact and regulate one another. In this study, we examine new approaches to understand meaningful networks between cytokines and their relevance to human disease. Effect size (ES) is a way of assessing the difference between two groups with respect to a continuous measure such as cytokines. Its use, relative to p-values, gives easier understanding to whether a difference is actually clinically important or not. Results of a study can be statistically significant but still be too small to be of any practical value, or statistically insignificant but still be too large to not be of any practical value; especially when multiple comparisons adjustments are applied. As opposed to p-values, ES is independent of sample size, and thus has recently attracted the attention of researchers. When modeling cytokines, we recommend the use of the A measure of stochastic superiority A = [#Y1 > Y2) + 0.5#(Y1=Y2)]/n1n2, due to Delaney and Vargha (2002), which is appropriate for the nonparametric Wilcoxon Test. The ES of interest from this measure is A/1 – A which gives the odds that an individual in one group will score higher than an individual in the other group. Our simulation indicated that odds= 1.253, 1.763, and 2.500 are equivalent to Cohen’s d = 0.2 (small), 0.5 (medium), and 0.8 (large). We applied this measure on a panel of 26 cytokines identified in 29 subjects (15 with Metastasis and 14 without Metastasis) with gastric cancer, and revealed 11 cytokines with large ES, five of which with non-significant Sidak adjusted p-values: (from largest to smallest) G-CSF, IL-6, IL-8, MCP-1, IL-10, TNF-a, GM-CSF, MIP-1a, IL-1b, MIP-1b, and VEGF.

People who were practicing Marketing exercise's and Academicians thinks that “4 Ps” marketing framework – product, price, place and promotion adds less value to their interest or business where ongoing relationship is critical. In a process of finding a way to overcome these marketers has evolved a concept of Relationship Marketing which talks about understanding customer segments, delivering ongoing quality service, and achieving high customer satisfaction. Relationship marketing was about “putting the customer in the middle of the business circle,” in the words of Dick Lee, principal of St. Paul-based Hi-Yield Marketing. Customer Relationship management is the strongest and the most efficient method of maintaining and creating customers. The challenges for marketers doesn't stops here, as market matured from national to international to global, customer retention and acquisition become more crucial and challenging for them. Multiple options broaden the path for consumer to get access over many products and services, creating a high probability of defection. Now they have new challenge to face that is “Defection”. They are trying hard to understand what they are supposed to do so as to increase customer retention and decrease customer defection. This paper tries to understand the mediating effect of sources on customer defection (Objective knowledge versus Subjective Knowledge) and its important act on consumers repurchase behavior.

Deficiency of acid alpha-glucosidase (GAA) results in widespread cellular deposition of lysosomal glycogen manifesting as myopathy and cardiomyopathy. When GAA-/- mice were treated with rhGAA (20 mg/kg/week for up to 5 months), skeletal muscle cells took up little enzyme compared to liver and heart. Glycogen reduction was less than 50%, and some fibers showed little or no glycogen clearance. A dose of 100 mg/kg/week resulted in approximately 75% glycogen clearance in skeletal muscle. The enzyme reduced cardiac glycogen to undetectable levels at either dose. Skeletal muscle fibers with residual glycogen showed immunoreactivity for LAMP-1/LAMP-2, indicating that undigested glycogen remained in proliferating lysosomes. Glycogen clearance was more pronounced in type 1 fibers, and histochemical analysis suggested an increased mannose-6-phosphate receptor immunoreactivity in these fibers. Differential transport of enzyme into lysosomes may explain the strikingly uneven pattern of glycogen removal. Autophagic vacuoles, a feature of both the mouse model and the human disease, persisted despite glycogen clearance. In some groups a modest glycogen reduction was accompanied by improved muscle strength. These studies suggest that enzyme replacement therapy, although at much higher doses than in other lysosomal diseases, has the potential to reverse cardiac pathology and to reduce the glycogen level in skeletal muscle.

Although many lysosomal disorders are corrected by a small amount of the missing enzyme, it has been generally accepted that 20-30% of normal acid alpha-glucosidase (GAA) activity, provided by gene or enzyme replacement therapy, would be required to reverse the myopathy and cardiomyopathy in Pompe disease. We have addressed the issue of reversibility of the disease in the Gaa(-/-) mouse model. We have made transgenic lines expressing human GAA in skeletal and cardiac muscle of Gaa(-/-) mice, and we turned the transgene on at different stages of disease progression by using a tetracycline-controllable system. We have demonstrated that levels of 20-30% of normal activity are indeed sufficient to clear glycogen in the heart of young Gaa(-/-) mice, but not in older mice with a considerably higher glycogen load. However, in skeletal muscle-a major organ affected in infantile and in milder, late-onset variants in humans-induction of GAA expression in young Gaa(-/-) mice to levels greatly exceeding wildtype values did not result in full phenotypic correction, and some muscle fibers showed little or no glycogen clearance. The results demonstrate that complete reversal of pathology in skeletal muscle or long-affected heart muscle will require much more enzyme than previously expected or a different approach.

Polarization in the CD4+ mediated T-helper cell immune response is a very well characterized phenomenon in immunology; towards either Th1, Th2, or Th17 pathways. However, to-date, this concept has neither been developed nor demonstrated in a robust statistical framework. In this study, we provide a novel statistical methodology to facilitate the idea of polarization within a multivariate setting, and apply it to luminal fluid cytokine data of 90 women from the Peruvian Amazon. The panel of cytokines and chemokines for this study were assayed using separate BioRad Multiplex Array kits. In our application, we show that soil transmitted helminth (STH) infection induces statistically significant Th2 polarization in the female genital tract. To provide statistical evidence of Th2 polarization in STH-infected women at the cervix, we compare the clustering of cytokines among STH-infected versus STH-uninfected women while examining the shift in the strength of correlation for Th2 cytokines with IL-4, which is seen as a central Th2 cytokine. The proposed statistical test is one that tests if, significantly, k>1 for f(L1)=f(L2) where L1 and L2 are the loadings in the principal component analysis (PCA) framework for the STH-infected and STH-infected groups respectively. The proposed method is a confirmatory one and could be supported by visual representation of the Th polarization through heat maps. It has the potential to become the reference or gold standard when studying the polarization phenomenon in immunology as it tailors the clinical characteristics and mechanisms associated with the entire panel of cytokines and chemokines in the context of a system.

Several studies have investigated the role of cytokines/chemokines in infection and chronic and autoimmune diseases using different statistical models. Generally, only two mediators are evaluated at a time, by comparing group-specific mean concentration differences. Restricted pairwise analysis from a large array of markers which inherently operate at a systems level to regulate immune response ignores important inter-correlation structures, compromising clinical and epidemiological inference. We propose the use of a rooted correlation network as a novel statistical method which allows group-specific comparisons of a panel of soluble immune markers while adjusting for the interaction complexity. We examined soluble immune markers in luminal fluid samples from 90 HPV infected female participants with and without soil transmitted helminth (STH) co-infection in Peru. We constructed a lower triangular correlation matrix using Spearman’s correlation with Sidak adjustment for both the STH-infected and -uninfected women. Rooted correlation network was constructed for the cytokines and chemokines that were insignificant in the non-helminth group but became significant in the helminth one. The generated cytokine network demonstrated statistically significant association of Th2 pathway cytokines with the canonical Th2 cytokine IL-4. Using this new statistical model, we demonstrate that the female genital tract of STH-infected women reveals polarization towards Th2 immune response (IL-25, IL-21, IL-5, IL-10, IL-8, and IL-31) in comparison to STH-uninfected women, which was not easily recognizable when using standard bivariate methods with multiple comparisons.

Objective The etiology and pathogenesis of human inflammatory myopathies remain unclear. Findings of several studies suggest that the degree of inflammation does not correlate consistently with the severity of clinical disease or of structural changes in the muscle fibers, indicating that nonimmune pathways may contribute to the pathogenesis of myositis. This study was undertaken to investigate these pathways in myositis patients and in a class I major histocompatibility complex (MHC)–transgenic mouse model of myositis. Methods We examined muscle tissue from human myositis patients and from class I MHC–transgenic mice for nonimmune pathways, using biochemical, immunohistochemical, and gene expression profiling assays. Results Up-regulation of class I MHC in skeletal muscle fibers was an early and consistent feature of human inflammatory myopathies. Class I MHC staining in muscle fibers of myositis patients showed both cell surface and a reticular pattern of internal reactivity. The pathways of endoplasmic reticulum (ER) stress response, the unfolded protein response (glucose-regulated protein 78 pathway), and the ER overload response (NF-κB pathway) were significantly activated in muscle tissue of human myositis patients and in the mouse model. Ectopic expression of wild-type mouse class I MHC (H-2Kb) but not degradable glycosylation mutants of H-2Kb induced ER stress response in C2C12 skeletal muscle cells. Conclusion These results indicate that the ER stress response may be a major nonimmune mechanism responsible for skeletal muscle damage and dysfunction in autoimmune myositis. Strategies to interfere with this pathway may have therapeutic value in patients with this disease.

Although many lysosomal disorders are corrected by a small amount of the missing enzyme, it has been generally accepted that 20-30% of normal acid alpha-glucosidase (GAA) activity, provided by gene or enzyme replacement therapy, would be required to reverse the myopathy and cardiomyopathy in Pompe disease. We have addressed the issue of reversibility of the disease in the Gaa(-/-) mouse model. We have made transgenic lines expressing human GAA in skeletal and cardiac muscle of Gaa(-/-) mice, and we turned the transgene on at different stages of disease progression by using a tetracycline-controllable system. We have demonstrated that levels of 20-30% of normal activity are indeed sufficient to clear glycogen in the heart of young Gaa(-/-) mice, but not in older mice with a considerably higher glycogen load. However, in skeletal muscle-a major organ affected in infantile and in milder, late-onset variants in humans-induction of GAA expression in young Gaa(-/-) mice to levels greatly exceeding wildtype values did not result in full phenotypic correction, and some muscle fibers showed little or no glycogen clearance. The results demonstrate that complete reversal of pathology in skeletal muscle or long-affected heart muscle will require much more enzyme than previously expected or a different approach.

Although acute hepatitis E virus (HEV) infection is known to induce IgM and IgG humoral host immune responses, little is known about occurrence of cellular responses in this infection. We looked for evidence of lymphocyte sensitization to HEV peptides in patients with acute HEV infection.peripheral blood lymphocytes were obtained from patients with acute hepatitis E and healthy controls. Proliferation of these lymphocytes in the presence of each of seven peptides with amino acid sequences corresponding to open reading frames 2 and 3 proteins of HEV (3 and 4 peptides, respectively) were studied; no peptide was added to control wells. Proliferative responses with stimulation indices exceeding 3.0 were taken as positive.More patients showed reactivity to two or more HEV peptides than did controls (11/21 vs 5/22, p0.05). Reactivity to one peptide corresponding to open reading frame 2 of HEV was more frequent in patients than in controls (7/21 vs 1/22, p0.05).Our results show that lymphocytes of patients with acute hepatitis E show sensitization to HEV peptides. This may have significance in understanding the pathogenetic mechanisms of liver injury in this infection.

Autoantibodies to histidyl-tRNA synthetase (HisRS) or to alanyl-, asparaginyl-, glycyl-, isoleucyl-, or threonyl-tRNA synthetase occur in approximately 25% of patients with polymyositis or dermatomyositis. We tested the ability of several aminoacyl-tRNA synthetases to induce leukocyte migration. HisRS induced CD4(+) and CD8(+) lymphocytes, interleukin (IL)-2-activated monocytes, and immature dendritic cells (iDCs) to migrate, but not neutrophils, mature DCs, or unstimulated monocytes. An NH(2)-terminal domain, 1-48 HisRS, was chemotactic for lymphocytes and activated monocytes, whereas a deletion mutant, HisRS-M, was inactive. HisRS selectively activated CC chemokine receptor (CCR)5-transfected HEK-293 cells, inducing migration by interacting with extracellular domain three. Furthermore, monoclonal anti-CCR5 blocked HisRS-induced chemotaxis and conversely, HisRS blocked anti-CCR5 binding. Asparaginyl-tRNA synthetase induced migration of lymphocytes, activated monocytes, iDCs, and CCR3-transfected HEK-293 cells. Seryl-tRNA synthetase induced migration of CCR3-transfected cells but not iDCs. Nonautoantigenic aspartyl-tRNA and lysyl-tRNA synthetases were not chemotactic. Thus, autoantigenic aminoacyl-tRNA synthetases, perhaps liberated from damaged muscle cells, may perpetuate the development of myositis by recruiting mononuclear cells that induce innate and adaptive immune responses. Therefore, the selection of a self-molecule as a target for an autoantibody response may be a consequence of the proinflammatory properties of the molecule itself.