Drastic measures such as lockdown taken by countries worldwide to contain spread of COVID-19 have influenced air pollution dynamics substantially, at a planetary scale. Several media reported the lockdown induced air pollution reduction based on quickly assembled satellite observations. However, a global-scale analysis of such reduction in air pollution backed by quality data collected from ground stations across the world and the effects of lockdown to it are missing. Here, we investigate changes in concentrations of six air pollutants: PM2.5, PM10, O3, SO2, CO, and NO2 in 40 cities between February, March 2019 and 2020. The mean monthly concentrations of PM2.5 and PM10 in February and March of 2020 were found consistently lower than in 2019 in most of the cities. After lockdown, declines of anthropogenic pollutants such as NO2, CO, PM2.5 and PM10 concentrations were seen in 19, 9, 8 and 7 cities respectively. Improvement in air quality following lockdown was observed in the world's most polluted cities including Bangalore, Beijing, Bangkok, Delhi, and Nanjing, as well as the world's major trade centers including New York, London, Paris, Seoul, Sydney, and Tokyo. More visible reduction of air pollution remains to be seen if the lockdown is prolonged. Nevertheless, such reductions are expected to be temporary because the levels are likely to go up again once the situation gets back to normal.

Background:In dentistry, esthetics has a special place. Although gingival melanin pigmentation does not present a medical problem, clinicians are often faced with a challenge of achieving gingival esthetics.Materials and Methods:A method of de-epithelialization of the pigmented gingiva using Kirkland’s gingivectomy knife is described. Twenty patients who were conscious about their gingival melanin pigmentation were selected. The gingiva of the whole of the arch was abraded until the entire visible pigmentation was removed. Clinical observations for intensity of pigmentation were recorded at baseline and then after surgery at monthly intervals over a period of 9 months according to Dummett-Gupta Oral Pigmentation Index scoring criteria proposed by Dummett C. O. in 1964.Results:The mean gingival melanin pigmentation score came down to 0.407 after 9 months as compared to preoperative score, which was 2.24. No repigmentation occurred in fair-complexioned persons. In persons with wheatish complexion, repigmentation was seen in 85.71% of the cases, but scores came down to 0.38 postoperatively as compared to 2.27 preoperatively. In dark-complexioned persons, repigmentation occurred in all cases, but the mean scores were 0.93 as compared to 2.40 preoperatively. The difference between preoperative and postoperative mean scores for each segment was put to statistical analysis by applying paired t test and was found to be significant.Conclusion:As this method has shown statistically significant results, it can be used in patients who are conscious of pigmented gingiva and want an esthetically satisfactory color.

Within the limits of this study, it could be implied that for relieving hypersensitivity, iontophoresis for all three current groups was almost equally effective, and it was found that repeated applications (up to three) gave good relief. Iontophoresis was found to be effective and safe.

CRISPR-Cas9 is a revolutionary technology because it is precise, fast and easy to implement, cheap and components are readily accessible. This versatility means that the technology can deliver a timely end product and can be used by many stakeholders. In plant cells, the technology can be applied to knockout genes by using CRISPR–Cas nucleases that can alter coding gene regions or regulatory elements, alter precisely a genome by base editing to delete or regulate gene expression, edit precisely a genome by homology-directed repair mechanism (cellular DNA), or regulate transcriptional machinery by using dead Cas proteins to recruit regulators to the promoter region of a gene. All these applications can be for: 1) Research use (Non commercial), 2) Uses related product components for the technology itself (reagents, equipment, toolkits, vectors etc), and 3) Uses related to the development and sale of derived end products based on this technology. In this contribution, we present a prototype report that can engage the community in open, inclusive and collaborative innovation mapping. Using the open data at the Lens.org platform and other relevant sources, we tracked, analyzed, organized, and assembled contextual and bridged patent and scholarly knowledge about CRISPR-Cas9 and with the assistance of a new Lens institutional capability, The Lens Report Builder, currently in beta release, mapped the public and commercial innovation pathways of the technology. When scaled, this capability will also enable coordinated editing and curation by credentialed experts to inform policy makers, businesses and private or public investment.

Purpose The purpose of this paper is to see how critical and vital artificial intelligence (AI) and big data are in today’s world. Besides this, this paper also seeks to explore qualitative and theoretical perspectives to underscore the importance of AI and big data applications in multi-sectoral scenarios of businesses across the world. Moreover, this paper also aims at working out the scope of ontological communicative perspectives based on AI alongside emphasizing their relevance in business organizations that need to survive and sustain with a view to achieve their strategic goals. Design/methodology/approach This paper attempts to explore the qualitative perspectives to build a direction for strategic management via addressing the following research questions concerned with assessing the scope of ontological communicative perspectives in AI relevant to business organizations; exploring benefits of big data combined with AI in modern businesses; and underscoring the importance of AI and big data applications in multi-sectoral scenarios of businesses in today’s world. Employing bibliometric analysis along with NVivo software to do sentiment analysis, this paper attempts to develop an understanding of what happens when AI and big data are combined in businesses. Findings AI and big data have tremendous bearing on modern businesses. Because big data comprises enormous information of diverse sorts, AI-assisted machines, tools and devices help modern businesses process it quickly, efficiently and meaningfully. Therefore, business leaders and entrepreneurs need to focus heavily on ontological and communicative perspectives to deal with diverse range of challenges and problems particularly in the context of recent crises caused by COVID-19 pandemic. Research limitations/implications There is hardly any arena of human activity wherein AI and big data are not relevant. The implication of this paper is that of combining both well so that we may find answers to the difficult and challenging multi-sectoral scenarios concerning not just businesses but life at large. Moreover, automated tools based on AI such as natural language processing and speech to text also facilitate meaningful communication at various levels not just in business organizations but other fields of human activities as well. Social implications This paper has layered social implications, as it conceptually works out as to how strategically we may combine AI and big data to benefit modern business scenarios dealing with service providers, manufacturers, entrepreneurs, business leaders, customers and consumers. All the stakeholders are socio-culturally and contextually rooted/situated, and that is how this study becomes socially relevant. Originality/value This paper is an original piece of research and has been envisioned in view of the challenging business scenarios across the world today. This paper underscores the importance of strategically combining AI and big data, as they have enormous bearing on modern businesses. The insights arrived at in this paper have implications for business leaders and entrepreneurs across the globe who could focus more on ontological and communicative perspectives of AI combined with Big Data to deal with diverse range of challenges and problems that modern businesses have been facing particularly in recent times.