Analysis of the Impacts of COVID-19 using Deep Convolutional Neural Network

COVID-19 is the transmittable disease that emerged as a recent epidemic and threatened the lives of various people. The emerged pandemic initiated a change in the people's routine and impacted a serious financial crisis. This initiated a necessity for developing a deeper insight of the COVID-19 disease and multiple researches are performed based on the COVID-19 epidemic, which possess the challenges of basic analysis of information about the disease, lack of data, lack of knowledge about the parameters that cause disease and to overcome this a deep COVID-19 analysis epidemic via the deep CNN classifier is accomplished in the research. The impact of the disease is examined based on the gender, age group, symptoms and outbreak of the disease. This analysis provides comprehensive information about the disease and helps in making the preventive measures, which will greatly reduce the impacts of the disease. The accomplishment of deep CNN instinctively analyzes the essential features needed for the classification that helps in reducing the effort and time of the individuals. The performance is analyzed with the metrics specificity, accuracy and sensitivity, which obtained values of 0.48 %, 0.27 %, 2.82 % corresponding to and 2.88 %, 1.5 %, 0.36% considering training percentage, which is more efficient. © 2023 IEEE.

Neglected keratitis caused by Exserohilum rostratum from the arid region of north-west India leading to vision loss-a case report

Objectives: To report a case of complete loss of vision due to delay in diagnosis of fungal keratitis caused by Exserohilum rostratum in an immunocompetent patient from the arid area of north-west India. Method(s): A65-year-old femalefarmer was admittedto ophthalmology witha history ofpain, redness, watering, andforeign body sensation in the left eye for 2 months. She had a history of trauma by splinters 2 months back. On ocular examination, a large corneal ulcer of about 7 x8 mm size at 2-8'o' clock position in the left eye was present with diffuse corneal edema. She had no history of diabetes mellitus, hypertension, tuberculosis, COVID-19, and steroid eye drops instillation.There was no relevant previous history of any ocular surgery also. She was negative for hepatitis-B and human immune deficiency virus on serology. All her hematological parameters were within normal limits. Patient was treated with moxifloxacin, carboxy methyl cellulose eye drops, and Neosporin eye ointment for around 2 months at primary health care facilities and later referred to our hospital for further management. Corneal scraping of the patient was sent to our laboratory for potassium hydroxide mount and culture identification. Result(s): Fungus was identified as E. rostratum on the basis of gross, macroscopic, and microscopic morphology. Gram's staining was bacteriologically negative while true fungal hyphae were seen. In KOH mount pigmented, septate, and branched true hyphae were seen. Bacterial culture was reported sterile. Lactophenol cottonblue mount of culturerevealed dematiaceoushyphae alongwith 4-9septate elongated, ellipsoid macro-conidia of 14-90 mum with prominent dark conspicuous hilum and geniculate conidiophore arranged sympodially. On the basis of these characteristics, it was diagnosed as E. rostratum. After the diagnosis patient was switched over to topical natamycin 5% two hourly and oral itraconazole 200 mg BD from moxifloxacin and neosporin.To which the patient responded symptomatically.Ulcer healed in a month leaving behind a lateral scar. However, vision is permanently compromised and the patient is advised for therapeutic penetrating keratoplasty (TPK). Conclusion(s): Exserohilum rostratum is generally regarded as a pathogen in hot and humid climates.However, the isolation of this organism in our area highlights the pathogenic potential of this emerging fungus in arid climates also.Ophthalmologists need to be made aware of the significance of prompt mycological identification to prevent vision loss.

Intra vascular lithotripsy facilitated Transfemoral TAVR

Transcatheter aortic valve replacement (TAVR) is now the standard of therapy for elderly population with severe aortic stenosis. Several studies have established that the outcomes of TAVR are superior when compared with Surgical aortic valve replacement (SAVR), especially when the access route is transfemoral arterial approach. In the elderly population with advanced age and numerous comorbidities, iliofemoral arterial disease (IAD) is not uncommon and it precludes the use of this route for TAVR. Peripheral Intravascular lithotripsy (IVL) has been previously established as an excellent safe and efficient modality to treat symptomatic occlusive calcific iliofemoral artery disease. The same principle of IVL has been recently used successfully to modify the vascular compliance of heavily calcified iliofemoral arteries thereby enabling large bore sheath advancement and safe passage of TAVR delivery catheter systems. We report the first case of Intravascular lithotripsy facilitated Transfemoral TAVR (TF-TAVR) in India. This case was done in December 2020 by the “femoral route” in order to keep the TAVR procedure simple straightforward and discharge the patient back home quickly in Covid times. The use of Intravascular Lithotripsy (IVL)was based on evidence of good outcomes in trials of peripheral vascular disease of lower limbs as well as from the good outcomes of few registries on IVL facilitated TAVR.1,2,3,4,5,6,8 The second case was done in August 2021 by us for another patient successfully.

Trajectory Planning and Optimization of Robotic ARM

Automation of processes through the use of industrial robots is a critical component of the transition to Industry 4.0. This paper aims to present the design of a biomedical robotic manipulator and attempt to simulate its trajectory in a virtual environment. The task of collecting samples for COVID-19 serves as a case study for the manipulator. Using the CAD tool, a suitable design was developed to meet the task requirements. After determining the end effector waypoints, path planning was carried out. Following that, a cubic polynomial trajectory was implemented in the MATLAB environment to obtain the time-scheduled third-order trajectories of the robot joints. Finally, the trajectory optimization algorithm based on the concept of via-points was developed to reduce the energy consumed by the robot while performing the task. The results from the optimization algorithm showed the energy savings of approximately 28% by following the optimized trajectory. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Quantitative Efficacy of Common Virucidal Disinfectants Against Viral Surrogates on Porous and Nonporous Surfaces

The objectives of this effort were threefold: (a) compare Ebola virus (EBOV) with a potential surrogate, the enveloped vaccinia virus (VACV), for susceptibility to disinfectants;(b) generate efficacy data for five U.S. Environmental Protection Agency-registered virucidal chemicals and one experimental disinfectant, 5 percent vinegar, against VACV;and (c) compare the efficacy of three chemicals against Phi 6 (a bacteriophage surrogate for EBOV) and VACV. The Organisation for Economic Co-operation and Development (OECD) method was adopted for efficacy evaluations. Of the three test viruses, VACV was found be the most persistent virus. Of six disinfectants, Peridox disinfectant (Contec;Spartanburg, SC) was most effective against all three viruses. Bioxy-S sanitizer (Atomes, Inc.;Quebec, Canada) was effective against all three viruses. The other four disinfectants were not very effective against VACV. Peridox disinfectant, 0.2 percent peracetic acid (PAA), and 0.5 percent bleach were effective against Phi 6 in the absence of blood. In the presence of blood (dried and wet), both Peridox disinfectant and PAA were equally effective against Phi 6. VACV is recommended as a potential surrogate for EBOV. More importantly, this study highlights that the DoD must generate its own database on efficacy of disinfectants for military surfaces to select effective chemicals in the event of a pandemic resulting from an infectious virus.

RT PCR positivity of COVID -19 patients & its temporal relation to time

Background:COVID-19 being an airborne High Consequence Infectious Disease (HCID) warrants early detection to con- tain spread especially in a pandemic that has gripped the world by storm. RT-PCR (Real time polymerase chain reaction) is considered the gold standard confirmatory test for COVID-19. The assay is based on detection of viral RNA and genes located in different regions of SARS-COV 2 genome with a potent detection limit of >=10 genomic copies per reaction. Average duration of RT-PCR result becoming negative from positive gives an idea as to how long a patient needs quaran- tine and also a perception of clinical recovery. Methods:This study includes 1766 positive patients tested at JLN Medical College Ajmer, Rajasthan, out of the total pa- tient who underwent RT-PCR testing from 26-08-2020 to 17-11-2020. The samples were collected through oro or naso- pharyngeal swabs. Automated RNA extraction was done using Thermofisher and Perkin Elmer machines and RT -PCR was done on Bio-Rad Machines. Results:Out of 1766 samples, 61 samples in the age group of 0-14 years (children and young adolescents) showed an average duration of 10.5 days and range of 3-18 days to be reported negative, 1537 in the age group of 15-65 years (working age population) had an average duration of 11.3 days and range 1 -32 days, 168 for >=66 years (elderly popula- tion) had an average duration of 10.7 days and range of 1-23 days. When gender is compared, 505 were females with average illness duration of 10.7 days and range 1-32 days and 1261 were males with average duration of 11.2 days and range 1-31 days. Conclusions:Once tested positive there is a very subtle difference in duration of being reported negative between the various age groups and gender with children and young adolescents getting an earlier negative result than others and females earlier than the male population.

Transfer Learning Based COVID-19 Patient Classification

The COVID-19 pandemic has had drastic global effects and has severely influenced our daily lives. One way to lessen the impact is by integrating Artificial Intelligence technology in medical imaging. It is vital to accurately and quickly assess positive COVID-19 patients, which can be done using their Chest X-Rays (CXR). In this study, a CXR dataset containing three classes namely: normal, viral pneumonia, and COVID-19 is used. After preprocessing the dataset, Transfer Learning methods are applied to the dataset. Re-training ResNet 50 gave the overall highest accuracy of 99.2%. Meanwhile, the Support Vector Machine (SVM) classifier performed the best with InceptionResNetV2 model giving an accuracy of 98.424%. This paper aims to provide a robust and accurate method to classify positive COVID-19 patients. © 2021, Springer Nature Singapore Pte Ltd.