Freestanding Oxide Membranes for Epitaxial Ferroelectric Heterojunctions.

Since facile routes to fabricate freestanding oxide membranes were previously established, tremendous efforts have been made to further improve their crystallinity, and fascinating physical properties have been also reported in heterointegrated freestanding membranes. Here, we demonstrate our synthetic recipe to manufacture highly crystalline perovskite SrRuO3 freestanding membranes using new infinite-layer perovskite SrCuO2 sacrificial layers. To accomplish this, SrRuO3/SrCuO2 bilayer thin films are epitaxially grown on SrTiO3 (001) substrates, and the topmost SrRuO3 layer is chemically exfoliated by etching the SrCuO2 template layer. The as-exfoliated SrRuO3 membranes are mechanically transferred to various nonoxide substrates for the subsequent BaTiO3 film growth. Finally, freestanding heteroepitaxial junctions of ferroelectric BaTiO3 and metallic SrRuO3 are realized, exhibiting robust ferroelectricity. Intriguingly, the enhancement of piezoelectric responses is identified in freestanding BaTiO3/SrRuO3 heterojunctions with mixed ferroelectric domain states. Our approaches will offer more opportunities to develop heteroepitaxial freestanding oxide membranes with high crystallinity and enhanced functionality.

Multi-Layered Filtration Framework for Efficient Detection of Network Attacks Using Machine Learning.

The advancements and reliance on digital data necessitates dependence on information technology. The growing amount of digital data and their availability over the Internet have given rise to the problem of information security. With the increase in connectivity among devices and networks, maintaining the information security of an asset has now become essential for an organization. Intrusion detection systems (IDS) are widely used in networks for protection against different network attacks. Several machine-learning-based techniques have been used among researchers for the implementation of anomaly-based IDS (AIDS). In the past, the focus primarily remained on the improvement of the accuracy of the system. Efficiency with respect to time is an important aspect of an IDS, which most of the research has thus far somewhat overlooked. For this purpose, we propose a multi-layered filtration framework (MLFF) for feature reduction using a statistical approach. The proposed framework helps reduce the detection time without affecting the accuracy. We use the CIC-IDS2017 dataset for experiments. The proposed framework contains three filters and is connected in sequential order. The accuracy, precision, recall and F1 score are calculated against the selected machine learning models. In addition, the training time and the detection time are also calculated because these parameters are considered important in measuring the performance of a detection system. Generally, decision tree models, random forest methods, and artificial neural networks show better results in the detection of network attacks with minimum detection time.

Impact of tourism development upon environmental sustainability: a suggested framework for sustainable ecotourism.

The empirical research investigated the relationship between tourism development and environmental suitability to propose a framework for sustainable ecotourism. The framework suggested a balance between business and environmental interests in maintaining an ecological system with the moderating help of government support and policy interventions. The study population encompasses tourism stakeholders, including tourists, representatives from local communities, members of civil administration, hoteliers, and tour operators serving the areas. A total of 650 questionnaires were distributed to respondents, along with a brief description of key study variables to develop a better understanding. After verifying the instrument's reliability and validity, data analysis was conducted via hierarchical regression. The study findings revealed that a substantial number of people perceive socio-economic benefits, including employment and business openings, infrastructure development from tourism development, and growth. However, the state of the natural and environmental capital was found to be gradually degrading. Alongside the social environment, social vulnerability is reported due to the overutilization of land, intrusion from external cultures, and pollution in air and water due to traffic congestion, accumulation of solid waste, sewage, and carbon emissions. The study suggested a model framework for the development of sustained ecotourism, including supportive government policy interventions to ensure effective conservation of environmental and natural resources without compromising the economic viability and social well-beings of the locals. Furthermore, the variables and the constructs researched can be replicated to other destinations to seek valuable inputs for sustainable destination management elsewhere.

Revitalization of tourism and hospitality sector: preempting pandemics through lessons learned.

The devastating effects of the COVID-19 pandemic have left many repercussions for the tourism industry to preempt any future catastrophe of this nature. The research aims to propose recommendations for the post-COVID-19 business world to revitalize and reclaim their market space and win back their volumes without any fear of indefinite closures and continued lockdowns in the industry. Drawing from the literature, the study assumed revitalization through responsiveness, use of advanced technology, customers' and employees' willingness, enhanced skills, adherence to standard operating procedures and protective measures, and restructuring via a public-private partnership. For the purpose, survey method was employed to collect data from the industry. After confirmation of the reliability and validity, the regression analyses supported effective revitalization through government responsiveness, use of digital technology, psychological recouping of customers' willingness, enhancing technical skills through training, strict adherence to protective measures, and destination restructuring and reorganization through a public-private partnership. The study proclaimed that Pakistan's tourism and hospitality sector development has evolved through the COVID-19 situation, and is likely to revamp and revitalize into a sustainable business. Once achieving sustainability, the revamped industry will likely to increase revenue, generate employment, and alleviate poverty through thriving public-private partnerships, community involvement, and community well-being without compromising people's health.

The Research on Organizational Justice in Scopus Indexed Journals: A Bibliometric Analysis of Seven Decades.

The organizational justice terminology has had a long journey to become one of the significant contributors to organizational success. Recently, an intense global upsurge in the use of organizational justice terms in publications has forced us for this bibliometric analysis in order to look at the overall publications on organizational justice. The objective of the current research is to advance knowledge about organizational justice research trends using Scopus database and bibliometric analysis research. The analysis was performed to see the publication trends between the years 1941 and 2018; it used authors, journals, countries, academic discipline, research institutes/universities, and various keywords related to organizational justice as search words. After careful consideration and using multiple checkpoints for eliminating irrelevant studies, 5,650 research articles were analyzed. In the realm of organizational justice, procedural justice was the most frequently occurred among other dimensions. Moreover, variables such as organizational trust, job satisfaction, organizational commitment, citizenship behavior, ethics, and turnover are major concepts that occurred within organizational justice research. Some variables with infrequent occurrences, along with future recommendations and study limitations, are also discussed.