Christ University

About: Christ University is a education organization based out in Bengaluru, India. It is known for research contribution in the topics: Computer science & Convection. The organization has 2267 authors who have published 2715 publications receiving 14575 citations. The organization is also known as: Christ College & Christ University.

A Novel Assessment of Healthcare Waste Disposal Methods: Intuitionistic Hesitant Fuzzy MULTIMOORA Decision Making Approach

Abstract: Waste produced from medical facilities systems incorporates a blend of dangerous waste which can posture dangers to humans and ecological receptors. Lacking administration of healthcare waste can prompt hazard to medicinal service specialists, patients, public health, communities and the wider environment. Hence, proper management of healthcare waste is imperative to reduce the associated health and environment risk. In this paper, we extend the MULTIMOORA decision making method with intuitionistic hesitant fuzzy set to evaluate the healthcare waste treatment methods. Intuitionistic hesitant fuzzy set is a generalized form of a hesitant fuzzy set. Intuitionistic hesitant fuzzy set considers the uncertainty of data in a single framework and take more information into account. The MULTIMOORA method consists of three parts namely the ratio system, reference point approach and the full multiplicative form. In the optimal ranking methods, the IHF-MULTIMOORA method is uncomplicated it is able to be used practically with high dimension intuitionistic hesitant fuzzy sets. For pathological, pharmaceutical, sharp, solid and chemical wastes, the preferred waste disposal methods are deep burial, incineration, autoclave, deep burial, and chemical disinfection, respectively.

Efficient chemical fixation of CO2 from direct air under environment-friendly co-catalyst and solvent-free ambient conditions

Abstract: The capture and conversion of CO2 from direct air into value-added products under mild conditions represents a promising step towards environmental remediation and energy sustainability. Consequently, herein, we report the first example of a Mg(II)-based MOF exhibiting highly efficient fixation of CO2 from direct air into value-added cyclic carbonates under eco-friendly co-catalyst and solvent-free mild conditions. The bifunctional MOF catalyst was rationally constructed by utilizing an eco-friendly Lewis acidic metal ion, Mg(II), and a nitrogen-rich tripodal linker, TATAB. The MOF possesses a high BET surface area of 2606.13 m2 g−1 and highly polar 1D channels decorated with a high density of CO2-philic sites which promote a remarkably high CO2 uptake of 50.2 wt% at 273 K with a high heat of adsorption value of 55.13 kJ mol−1. The high CO2-affinity combined with the presence of a high density of nucleophilic and Lewis acidic sites conferred efficient catalytic properties to the Mg-MOF for chemical fixation of CO2 from direct air under environment-friendly mild conditions. The remarkable performance of the Mg-MOF for the fixation of CO2 from direct air was further supported by in-depth theoretical calculations. Moreover, the computational studies provided an insight into the mechanistic details of the catalytic process in the absence of any co-catalyst and solvent. Overall, this work represents a rare demonstration of carbon capture and utilization (CCU) from direct air under eco-friendly mild conditions.

Survey of prevalence of anxiety and depressive symptoms among 1124 healthcare workers during the coronavirus disease 2019 pandemic across India.

Abstract: Background A prospective study was conducted during the second phase of the coronavirus disease 2019 (COVID-19) pandemic in India to assess the prevalence of anxiety and depressive symptoms among healthcare workers (HCWs) and factors that influence the outcome. Methods A self-administered questionnaire was completed by 1124 HCWs during the COVID-19 pandemic (March 30, 2020, to April 2, 2020). Demographic data, questions on COVID-19 and scores of the Hospital Anxiety and Depression Scale were analysed using the chi-square test (Bonferroni correction) and binary logistic regression. Results The study consists of 1124 HCWs, including 749 doctors, 207 nurses, 135 paramedics, 23 administrators and ten supporting staff members. The prevalence of anxiety and depressive symptoms were reported as 37.2% and 31.4%, respectively. The risk factors for anxiety were female gender (30.6% vs 45.5%), age group (20–35 years) (50.4% vs 61.2%), unmarried (21.2% vs 30.6%) and job profile (nurse) (14.7% vs 26.4%). The protective factor was having service of more than 20 years (23.4% vs 14.8%). The risk factors for depression were age group (20-35 years) (51.3% vs 61.3%) and employed at a primary care hospital (16.2% vs 23.4%). The protective factors were job profile (doctor) (69.9% vs 59.6%) and having service of more than 20 years (22.3% vs 15.5%). Conclusion Approximately one-third of the HCWs reported anxiety and depressive symptoms. The risk factors for anxiety symptoms were female gender, younger age and job profile (nurse) and for depressive symptoms were younger age and working at a primary care hospital. Future research studies should identify strategies for providing a safer and supportive work environment for HCWs to face epidemics/pandemics.

The industry use cases for the Digital Twin idea

Abstract: Digital Twin Technology has taken the place in top 10 strategic technology trends in 2017 termed by Gartner Inc. Digital Twin concept brings out the virtual depiction or the digital representation of the real world equipment, device or system whereas the real world and the virtual world gets the highest synchronization. The digital representation of the complete life cycle of a product from its design phase to the maintenance phase will give the prophetic analysis of the problems to the business. This greatest advantage of foreseeing problems in the development of a device will give early warnings, foil downtime, cultivate novel prospects and inventing enhanced devices or gadgets for the later use at the lesser expense by means of digital representations. Indeed, these will devise a larger influence on conveying superior consumer feeling also in the enterprise. The emerging trends such as Artificial Intelligence, Machine Learning, Deep Learning, Internet of Things and Big Data used in Industry 4.0 play a vital role in Digital Twin and they are mostly adopted in the world of manufacturing, Industrial Internet of Things, and automobile business world. The penetration, wide coverage and the advancement of the Internet of Things in real-world have elevated the power of Digital Twins more economical and reachable for the world of various businesses. 1. Manufacturing: Digital Twin has brought out the change in the existing manner of the manufacturing segment. Digital Twins have a substantial influence on the design of products and their manufacturing and maintenance. Because of its influence the manufacturing more competent and augmented while dropping throughput times. 2. Industrial IoT: Integrating digital twin with industrial firms will facilitate the activities such as monitoring, tracking and controlling industrial systems in digital means. We can potentially experience the power of digital twin since it captures environmental data such as locality, settings of the devices, financial frameworks, etc., other than the operational data, which benefits in foreseeing the forthcoming operations and incongruities. 3. Healthcare: Since the healthcare sector demands higher accuracy in diagnosis and treatment, with the important data from IoT, digital twins can play a vital role by reducing the expense for the patient, precautionary alerts to avoid health deterioration and giving tailored health support system. This will be great support especially in developing countries like India. 4. Smart cities: Digital Twin coupled with IoT data can augment the efficient planning of the smart city and execution of its building by supplementing financial progress, effectual administration of resources, lessening of environmental impression and escalate the complete worth of a resident's life. The digital twin prototypical can aid city organizers and legislators in the smart city planning by retrieving the visions from numerous sensor networks and smart systems. The information received from the digital twins supports them in reaching well-versed choices concerning the future as well. 5. Automobile: Automobile industry can get voluminous benefits out of Digital Twins for producing the simulated framework of a coupled vehicle. It retrieves the behavioral and functional information of the vehicle and services in examining the inclusive performance efficiency of the vehicle as well as the features connected along with it. Digital Twin also supports in supplying a justly enhance support and service for the consumers. 6. Retail: Alluring client satisfaction is a fundamental factor in the merchandising world. Digital twin employment can play a key role in supplementing the retail customer experience by forming virtual twins for customers and modeling fashions for them on it. Digital Twins also supports enhanced planning of stock maintenance, safekeeping procedures, and human resource administration in an augmented means.

Insights on bar quenching from a multiwavelength analysis: The case of Messier 95

Abstract: The physical processes related to the effect of bars in the quenching of star formation in the region between the nuclear/central sub-kiloparsec region and the ends of the bar (bar region) of spiral galaxies is not fully understood. It is hypothesized that the bar can either stabilize the gas against collapse, inhibiting star formation, or efficiently consume all the available gas, leaving no fuel for further star formation. We present a multiwavelength study using the archival data of an early-type barred spiral galaxy, Messier 95, which shows signatures of suppressed star formation in the bar region. Using optical, ultraviolet (UV), infrared, CO, and HI imaging data we study the pattern of star formation progression and stellar/gas distribution, and try to provide insights into the process responsible for the observed pattern. The FUV–NUV pixel colour map reveals a cavity devoid of UV flux in the bar region that matches the length of the bar, which is ∼4.2 kpc. The central nuclear region of the galaxy shows a blue colour clump and along the major axis of the stellar bar the colour progressively becomes redder. Based on a comparison to single stellar population models, we show that the region of galaxy along the major axis of the bar, unlike the region outside the bar, is comprised of stellar populations with ages ≥350 Myr; there is a star-forming clump in the centre of younger ages of ∼150 Myr. Interestingly the bar region is also devoid of neutral and molecular hydrogen but has an abundant molecular hydrogen present at the nuclear region of the galaxy. Our results are consistent with a picture in which the stellar bar in Messier 95 is redistributing the gas by funnelling gas inflows to nuclear region, thus making the bar region devoid of fuel for star formation.