MEMORABLE TOURISM EXPERIENCES (MTE): INTEGRATING ANTECEDENTS, CONSEQUENCES AND MODERATING FACTOR

Purpose - The concept of tourism as an experience is gaining interest among practitioners and academics alike. This study contributes to the tourism literature by integrating the antecedents and outcomes of memorable tourism experiences (MTE) and consumer-level factors as moderators into a single model. Design - The study applies primary survey using structured questionnaire. The study hypotheses are empirically tested based on survey data of 700 tourists (both domestic and foreign) in India. Methodology - The data collected is analyzed using structural equation modeling. The model also includes the moderating role of tourists’ openness to experience. Findings - Findings show a positive impact of destination attributes on MTE. MTE is observed to positively affect its immediate outcomes, perceived value and satisfaction from tourism experiences. Subsequently, satisfaction has a positive effect of loyalty and word of mouth (WOM), but perceived value affects only on word of mouth. Openness to experience moderated the impact of destination attributes on MTE. Originality - The study makes new theoretical and managerial contributions. The study is one of the first of its kind to integrate the antecedents and outcomes of MTE in a single study. Moreover, the study also considers the moderating influence of tourist personality in the same study

Epigenetic regulation of key genes involved in Cervical malignancy

microRNAs (miRNAs) are single stranded non-coding RNAs of about 22 nucleotides that have been reported to be involved in various biological processes like embryonic development, cell proliferation, differentiation, apoptosis, developmental timing etc. The role of miRNAs as tumor suppressors/oncomiRs has been reported in many cancers. In this study, we performed genome-wide expression analysis of miRNAs as well as mRNAs in cervical cancer and obtained 257 up-regulated and 81 down-regulated mRNAs as well as 27 up-regulated & 14 down-regulated miRNAs. Enrichment analysis of differentially expressed mRNAs of cervical cancer revealed CYR61 (cysteine-rich, angiogenic inducer, 61) as a key gene involved in vascularisation of the tumors. This CYR61 was found to harbor target sites (7mer-m8) for hsa-miR-221 as inferred from TargetScan predictions. From qRT-PCR study in HeLa cell lines, we found that CYR61 is over-expressed, whereas hsa-miR-221 is down-regulated in cancer system. The altered expression of CYR61 might be due to down-regulation of hsa-miR-221 as this miRNA has target sites within 3/UTR of CYR61 which can be further confirmed by luciferase reporter assay. We hypothesize that hsa-miR-221 might be playing a role in metastatic spread and lethality in cervical cancer by altering the expression of the corresponding mRNA through RNA interference mechanism. Moreover, it can be expected that the altered expression of hsa-miR-221 may be due to promoter hypermethylation of the miRNA gene or through targeting by other non-coding RNAs, such as lncRNAs which need further studies in future

Deep learning to filter SMS spam

The popularity of short message service (SMS) has been growing over the last decade. For businesses, these text messages are more effective than even emails. This is because while 98% of mobile users read their SMS by the end of the day, about 80% of the emails remain unopened. The popularity of SMS has also given rise to SMS Spam, which refers to any irrelevant text messages delivered using mobile networks. They are severely annoying to users. Most existing research that has attempted to filter SMS Spam has relied on manually identified features. Extending the current literature, this paper uses deep learning to classify Spam and Not-Spam text messages. Specifically, Convolutional Neural Network and Long Short-term memory models were employed. The proposed models were based on text data only, and self-extracted the feature set. On a benchmark dataset consisting of 747 Spam and 4,827 Not-Spam text messages, a remarkable accuracy of 99.44% was achieved

Normal form for singular Bautin bifurcation in a slow-fast system with Holling type III functional response

Over the last few decades, complex oscillations of slow-fast systems have been a key area of research. In the theory of slow-fast systems, the location of singular Hopf bifurcation and maximal canard is determined by computing the first Lyapunov coefficient. In particular, the analysis of canards is based on the genericity condition that the first Lyapunov coefficient must be non-zero. This manuscript aims to further extend the results to the case where the first Lyapunov coefficient vanishes. For that, the analytic expression of the second Lyapunov coefficient and the investigation of the normal form for codimension-2 singular Bautin bifurcation in a predator-prey system is done by explicitly identifying the locally invertible parameter-dependent transformations. A planar slow-fast predator-prey model with Holling type III functional response is considered here, where the prey population growth is affected by the weak Allee effect, and the prey reproduces much faster than the predator. Using geometric singular perturbation theory, normal form theory of slow-fast systems, and blow-up technique, we provide a detailed mathematical investigation of the system to show a variety of rich and complex nonlinear dynamics including but not limited to the existence of canards, relaxation oscillations, canard phenomena, singular Hopf bifurcation, and singular Bautin bifurcation. Additionally, numerical simulations are conducted to support the theoretical findings

Feasibility of laparoscopy in management of ectopic pregnancy: experience from a tertiary care hospital

Background: Ectopic pregnancy is an important cause of maternal morbidity and mortality. For surgical management, laparoscopy is preferred option. In developing world for ruptured ectopic pregnancy laparotomy is done at most of places. In this study we have assessed feasibility of laparoscopic management in both ruptured and unruptured ectopic pregnancy.Methods: A prospective study, conducted over period of 1 year from July 2014 to July 2015 in Department of Obstetrics & Gynecology, All India Institute of Medical Sciences, New Delhi. In 110 patients of ectopic pregnancy parameters studied were age and parity, symptoms, risk factors, diagnostic methods, site of ectopic, management and its outcome. Primary objective was to evaluate management outcome of ectopic pregnancy and to assess feasibility of laparoscopy in ectopic pregnancy. Ruptured ectopic pregnancy with massive hemoperitoneum were analyzed separately. Secondary objective was to study demographic characters and risk factors of ectopic pregnancy.Results: Surgical management was required in 93.6% patients, out of which 86.4% were managed laparoscopically. Unruptured ectopic pregnancy was managed successfully by laparoscopy in 96.6% (29/30) patients. Ectopic was ruptured in 73 (66.3%) cases, laparoscopy was attempted in 91.7% (67/73). In 10.4% (7/67) patients laparoscopy had to be converted to laparotomy and it was successful in 89.5%. Out of 16 patients with massive hemoperitoneum, 12(75%) were managed laparoscopically. There was no mortality.Conclusions: In most of cases laparoscopy is safe and successful. Laparoscopy is feasible in ruptured ectopic cases including selected cases with massive hemoperitoneum thus avoiding unnecessary laparotomy and associated morbidity. Timely diagnosis and management prevents mortality

Is this question going to be closed? : Answering question closibility on Stack Exchange

Community question answering sites (CQAs) are often flooded with questions that are never answered. To cope with the problem, experienced users of Stack Exchange are now allowed to mark newly-posted questions as closed if they are of poor quality. Once closed, a question is no longer eligible to receive answers. However, identifying and closing subpar questions takes time. Therefore, the purpose of this paper is to develop a supervised machine learning system that predicts question closibility, the possibility of a newly posted question to be eventually closed. Building on extant research on CQA question quality, the supervised machine learning system uses 17 features that were grouped into four categories, namely, asker features, community features, question content features, and textual features. The performance of the developed system was tested on questions posted on Stack Exchange from 11 randomly chosen topics. The classification performance was generally promising and outperformed the baseline. Most of the measures of precision, recall, F1-score, and AUC were above 0.90 irrespective of the topic of questions. By conceptualizing question closibility, the paper extends previous CQA research on question quality. Unlike previous studies, which were mostly limited to programming-related questions from Stack Overflow, this one empirically tests question closibility on questions from 11 randomly selected topics. The set of features used for classification offers a framework of question closibility that is not only more comprehensive but also more parsimonious compared with prior works