A Systematic Literature Review and Future Perspectives for Handling Big Data Analytics in COVID-19 Diagnosis.

In today's digital world, information is growing along with the expansion of Internet usage worldwide. As a consequence, bulk of data is generated constantly which is known to be "Big Data". One of the most evolving technologies in twenty-first century is Big Data analytics, it is promising field for extracting knowledge from very large datasets and enhancing benefits while lowering costs.

Arginine deiminase produced by lactic acid bacteria as a potent anti-cancer drug.

Bacterial-based cancer immunotherapy has recently gained widespread attention due to its exceptional mechanism of rich pathogen-associated molecular patterns in anti-cancer immune responses. Contrary to conventional cancer therapies such as surgery, chemotherapy, radiation and phototherapy, bacteria-based cancer immunotherapy has the unique ability to suppress cancer by selectively accumulating and growing in tumours. In the view of this, several bacterial strains are being used for the treatment of cancer.

CdS nanocrystallites sensitized ZnO nanosheets for visible light induced sonophotocatalytic/photocatalytic degradation of tetracycline: From experimental results to a generalized model based on machine learning methods.

CdS/ZnO nanosheets heterostructures ((x)CdS/ZNs) with different mole ratios of Cd/Zn ((x) = 0.2, 0.4, and 0.

Nanoresonator vibrational behaviour analysis of single- and double-layer graphene with atomic vacancy and pinhole defects.

Context: Nanosensors and actuators are frequently made of graphene. Any defect in the graphene's manufacturing has an impact on its sensing performance and on its dynamic behaviour. Using a molecular dynamics technique, the influence of pinhole defects and atomic defects on the performance parameters of single-layer graphene sheets (SLGSs) and double-layer graphene sheets (DLGSs) with various boundary conditions and lengths is explored.

Association of Laccase from Bacillus cereus O2-B and Pseudomonas aeruginosa O1-P with the bio-degradation of polymers: an in vitro to in silico approach.

Plastic accumulation has become a serious environmental threat. Mitigation of plastic is important to save the ecosystem of our planet. With current research being focused on microbial degradation of plastics, microbes with the potential to degrade polyethylene were isolated in this study.

An XAI approach for COVID-19 detection using transfer learning with X-ray images.

The coronavirus disease (COVID-19) has continued to cause severe challenges during this unprecedented time, affecting every part of daily life in terms of health, economics, and social development. There is an increasing demand for chest X-ray (CXR) scans, as pneumonia is the primary and vital complication of COVID-19. CXR is widely used as a screening tool for lung-related diseases due to its simple and relatively inexpensive application.

Hypothetical confirmation for the anti-bacterial compound potassium succinate-succinic acid in comparison with certain succinate derivatives.

The development of antibacterial medications has recently been promoted due to the non- effective usage of antibiotics and the rise in severe bacterial infections. The effectiveness of antimicrobial therapy alternatives is constrained due to the prevalence of germs that are resistant to medications. Our current study's goal is to favor metallic compounds for antibiotic delivery in order to increase the effectiveness of the antibacterial regimen.

A path forward in the development of new aerosol drug delivery devices for pediatrics.

Inhaled medications are widely accepted as being the optimal route for treating pediatric respiratory diseases, a leading cause of hospitalization and death. Despite jet nebulizers being the preferred inhalation device for neonates and infants, current devices face performance issues with most of the drug never reaching the target lung location. Previous work has aimed to improve pulmonary drug deposition, yet nebulizer efficiency remains low.

Identification and prioritization of potential therapeutic molecules against LpxA from - A computational study.

A. baumannii is a ubiquitously found gram-negative, multi-drug resistant bacterial species from the ESKAPE family of pathogens known to be the causative agent for hospital-acquired infections such as pneumonia, meningitis, endocarditis, septicaemia and urinary tract infections. is implicated as a contributor to bloodstream infections in approximately 2% of all worldwide infections.

Investigation and modeling of electric vehicle enablers (EVE) for successful penetration in context to India: mitigating the effect of urban sprawl on transportation.

Urban sprawl in context to transportation is a matter of serious concern. It creates unusual environmental challenges for an emerging economy like India, known for geographical spread, population, and use of fossil fuel-based automobiles on road. Indian automotive sector is often held responsible for the emission of greenhouse gasses causing serious environmental deterioration.

Species distribution modelling of (Falc.) A. DC.: Present distribution and impacts of potential climate change.

Species distribution modelling (SDM) is an important tool to examine the possible change in the population range and/or niche-shift under current environment and predicted climate change. is an economically and ecologically important tree species inhabiting Pakistan and Afghanistan in dense patches, and species range is contracting rapidly. This study hypothesize that predicted climate change might remarkably influence the existing distribution pattern of in the study area.

Impacts of COVID-19 pandemic on environment, society, and food security.

Coronavirus disease (COVID)-19 is a viral and transferable disease caused by severe respiratory syndrome-coronavirus-2. It can spread through breathing droplets in human beings. It caused 5.

Self-Charging Piezo-Supercapacitor: One-Step Mechanical Energy Conversion and Storage.

With the contemplations of ecological and environmental issues related to energy harvesting, piezoelectric nanogenerators (PNGs) may be an accessible, sustainable, and abundant elective wellspring of energy in the future. The PNGs' power output, however, is dependent on the mechanical energy input, which will be intermittent if the mechanical energy is not continuous. This is a fatal flaw for electronics that need continuous power.

RADIC:A tool for diagnosing COVID-19 from chest CT and X-ray scans using deep learning and quad-radiomics.

Deep learning (DL) algorithms have demonstrated a high ability to perform speedy and accurate COVID-19 diagnosis utilizing computed tomography (CT) and X-Ray scans. The spatial information in these images was used to train DL models in the majority of relevant studies. However, training these models with images generated by radiomics approaches could enhance diagnostic accuracy.

Deep Learning Models for Multiple Face Mask Detection under a Complex Big Data Environment.

The Covid-19 (coronavirus) pandemic creates a worldwide health crisis. According to the WHO, the effective protection system is wearing a face mask in public places. Many studies proved that carrying a face mask is also one of the precautions to decrease the possibility of viral transmission.

Initial Performance Analysis of the At-Altitude Radiance Ratio Method for Reflectance Conversion of Hyperspectral Remote Sensing Data.

In remote sensing, the conversion of at-sensor radiance to surface reflectance for each pixel in a scene is an essential component of many analysis tasks. The empirical line method (ELM) is the most used technique among remote sensing practitioners due to its reliability and production of accurate reflectance measurements. However, the at-altitude radiance ratio (AARR), a more recently proposed methodology, is attractive as it allows reflectance conversion to be carried out in real time throughout data collection, does not require calibrated samples of pre-measured reflectance to be placed in scene, and can account for changes in illumination conditions.

Motivating Personal Climate Action through a Safety and Health Risk Management Framework.

Background: There is overwhelming evidence the impacts of climate change present a probable threat to personal health and safety. However, traditional risk management approaches have not been applied to ameliorate the crises. The purpose of this study was to assess the impact on personal motivation for action of a communication intervention that framed climate change as a safety issue that can be mitigated through a safety and health risk management framework.

Parametric Study of Gold Nanoparticles Synthesis under Micro-Continuous Flow Conditions.

The synthesis of gold nanoparticles (GNPs) using chemical reduction in batch and microreactor methods has been reported. A parametric study of the effect of several parameters on the size of gold nanoparticles was performed in batch synthesis mode using the modified Martin method. The best-obtained conditions were used to synthesize gold nanoparticles using a glass chip microreactor, and the size of the resulting GNPs from both methods was compared.

Comparison of machine learning and deep learning-based methods for locomotion mode recognition using a single inertial measurement unit.

Locomotion mode recognition provides the prosthesis control with the information on when to switch between different walking modes, whereas the gait phase detection indicates where we are in the gait cycle. But powered prostheses often implement a different control strategy for each locomotion mode to improve the functionality of the prosthesis. Existing studies employed several classical machine learning methods for locomotion mode recognition.

Effects of Sound Quality on the Accuracy of Telephone Captions Produced by Automatic Speech Recognition: A Preliminary Investigation.

Purpose: Automatic speech recognition (ASR) is commonly used to produce telephone captions to provide telecommunication access for individuals who are d/Deaf and hard of hearing (DHH). However, little is known about the effects of degraded telephone audio on the intelligibility of ASR captioning. This research note investigates the accuracy of telephone captions produced by ASR under degraded audio conditions.

Experimental investigation on the performance characteristics and emissions of a CI engine fueled with enhanced microwave-assisted Karanja seed bio-oil.

The main objective of the present research work is to utilise the produced bio-oil from microwave pyrolysis of Karanja, a non-edible seed, as fuel for diesel engines by increasing some up-gradation in the quality of the fuel. The emulsification process is carried out to improve the stability of the diesel-bio-oil blend using SPAN 80 and TWEEN 80, which lasted for 28 days without any layer separation termed as EKB20. The addition of 5% DEE and 10% DEE into EKB20 is done to enhance the combustion characteristics of the diesel engine.

CNN Features and Optimized Generative Adversarial Network for COVID-19 Detection from Chest X-Ray Images.

Coronavirus is a RNA type virus, which makes various respiratory infections in both human as well as animals. In addition, it could cause pneumonia in humans. The Coronavirus affected patients has been increasing day to day, due to the wide spread of diseases.

Magnetic Application of Gadolinium Orthoferrite Nanoparticles Synthesized by Sol-Gel Auto-Combustion Method.

In this manuscript, we present the synthesis of gadolinium orthoferrite nanoparticles using the sol-gel auto-combustion technique. The obtained gadolinium orthoferrite nanoparticles were annealed at various temperatures, such as 800 °C, 900 °C, 1000 °C, and 1100 °C. The synthesized materials were analyzed by various instrumental characterizations.

An integrated approach for an impact assessment of the tank water and groundwater quality in Coimbatore region of South India: implication from anthropogenic activities.

Groundwater in the Coimbatore region is very much essential for irrigation and human beings' day-to-day life activities. This research focuses on the impact of anthropogenic activities on the surface water quality of four tanks in Coimbatore city and its influences on disturbing the groundwater quality as well. Water quality is degrading as a result of encroachment and other anthropogenic activities.

One-Pot Synthesis of N-Rich Porous Carbon for Efficient CO Adsorption Performance.

N-enriched porous carbons have played an important part in CO adsorption application thanks to their abundant porosity, high stability and tailorable surface properties while still suffering from a non-efficient and high-cost synthesis method. Herein, a series of N-doped porous carbons were prepared by a facile one-pot KOH activating strategy from commercial urea formaldehyde resin (UF). The textural properties and nitrogen content of the N-doped carbons were carefully controlled by the activating temperature and KOH/UF mass ratios.