Performance and Early Results from the Earth Surface Mineral Dust Source Investigation (EMIT) Imaging Spectroscopy Mission

The Earth Surface Mineral Dust Source Investigation (EMIT) acquires new observations of the Earth from a state-of-the-art, optically fast F/1.8 visible to short wavelength infrared imaging spectrometer with high signal-to-noise ratio and excellent spectroscopic uniformity. EMIT was launched to the International Space Station from Cape Canaveral, Florida, on July 14, 2022 local time. The EMIT instrument is the latest in a series of more than 30 imaging spectrometers and testbeds developed at the Jet Propulsion Laboratory, beginning with the Airborne Imaging Spectrometer that first flew in 1982. EMIT's science objectives use the spectral signatures of minerals observed across the Earth's arid and semi-arid lands containing dust sources to update the soil composition of advanced Earth System Models (ESMs) to better understand and reduce uncertainties in mineral dust aerosol radiative forcing at the local, regional, and global scale, now and in the future. EMIT has begun to collect and deliver high-quality mineral composition determinations for the arid land regions of our planet. Over 1 billion high-quality mineral determinations are expected over the course of the one-year nominal science mission. Currently, detailed knowledge of the composition of the Earth's mineral dust source regions is uncertain and traced to less than 5,000 surface sample mineralogical analyses. The development of the EMIT imaging spectrometer instrumentation was completed successfully, despite the severe impacts of the COVID-19 pandemic. The EMIT Science Data System is complete and running with the full set of algorithms required. These tested algorithms are open source and will be made available to the broader community. These include calibration to measured radiance, atmospheric correction to surface reflectance, mineral composition determination, aggregation to ESM resolution, and ESM runs to address the science objectives. In this paper, the instrument characteristics, ground calibration, in-orbit performance, and early science results are reported. © 2023 IEEE.

Zoonosis and infectious diseases

In making our way through the COVID-19 pandemic, it has become even more imperative to understand the mechanism of an infection and its evolution as an infectious agent. Given that, most diseases that have affected us to date originated from nonhuman vertebrates. Therefore, it is worth questioning this perspective in light of the pandemic. This chapter summarizes what is known so far regarding factors that influence zoonosis and identifies international bodies and recognizes their efforts in pursuing a healthier future. Finally, we critically analyze a widely cited study on the origin of SARS-CoV-2 to encourage future resolution of the debate. © 2023 Elsevier Inc. All rights reserved.

A successful thrombectomy in a case of progressive cerebral sinus thrombosis

Introduction: Cerebral venous sinus thrombosIs (CVST) is a rare condition compared to other categories encountered in stroke medicine.It occurs more frequently in patients with conditions that predispose them to other venous thrombosis, such as thrombophilias, acute malignancies, nephrotic syndrome, and COVID-19. CVST was identified as one of the rare causative of stroke. The exact mechanism of the stroke is not fully understood. However, a commonly agreed pathophysiology is that a dysfunction in arachnoid granulation can lead to sinus occlusion. Subsequently, this leads to a reduction in cerebral fluid drainage, which can increase intracranial pressure, causing capillary hypertension, cerebral oedema, decrease in cerebral perfusion pressure and venous haemorrhage. The European Stroke Organisation (ESO) supports using both MRI/MR Venogram and CT venogram as modalities for diagnosis of CVST, with no particular preference of one over the other. The standard practice in the management of cerebral venous sinus thrombosis includes treating the clot and its precipitating factors and treating the sequela of the clot as in the case we are reporting. Yet, there is no clinical guideline for the more aggressive measures to break down the clot in either AHA or European Stroke Organization, but they are used in clinical practice, with promising results in certain cases. Our case is an example of a successful mechanical thrombectomy with a lifesaving outcome. Method(s): We are reporting an unusual case of a 27- year- old lady who presented to the hyperacute stroke unit with dense right- sided weakness and expressive dysphasia. After an initial CT (Computerised Tomography) scan confirming extensive cerebral venous sinus thrombosis, she went for urgent mechanical thrombectomy. The clinical assessment after the procedure showed significant recovery in power of the right limbs and speech. She was discharged 7 days later with near full recovery. Venous thrombectomy is a rarely performed procedure. However, in this case, it was potentially lifesaving and resulted in an excellent clinical outcome. Result(s): An MRI/MRV follow up in a month demonstrated that the lesion on left centrum semiovale had regressed compared to the first scan. Also, there was some evidence of recanalization of her transverse sinuses. She was assessed by the therapist two months from the event. The patient reported some word finding difficulties and clumsiness in the right hand and leg. However, no further major event since her thrombectomy, and now aiming to get back to work. Conclusion(s): Mechanical thrombectomy in cerebral venous sinus thrombosis can be an effective, life-saving, and safe procedure with an extremely rewarding outcome. It should be considered in patients with acute neurological deterioration despite anticoagulant therapy.

Tokens Shuffling Approach for Privacy, Security, and Reliability in IoHT under a Pandemic

Privacy and security are unavoidable challenges in the future of smart health services and systems. Several approaches for preserving privacy have been provided in the Internet of Health Things (IoHT) applications. However, with the emergence of COVID-19, the healthcare centers needed to track, collect, and share more critical data such as the location of those infected and monitor social distancing. Unfortunately, the traditional privacy-preserving approaches failed to deal effectively with emergency circumstances. In the proposed research, we introduce a Tokens Shuffling Approach (TSA) to preserve collected data's privacy, security, and reliability during the pandemic without the need to trust a third party or service providers. TSA depends on a smartphone application and the proposed protocol to collect and share data reliably and safely. TSA depends on a proposed algorithm for swapping the identities temporarily between cooperated users and then hiding the identities by employing fog nodes. The fog node manages the cooperation process between users in a specific area to improve the system's performance. Finally, TSA uses blockchain to save data reliability, ensure data integrity, and facilitate access. The results prove that TSA performed better than traditional approaches regarding data privacy and the performance level. Further, we noticed that it adapted better during emergency circumstances. Moreover, TSA did not affect the accuracy of the collected data or its related statistics. On the contrary, TSA will not affect the quality of primary healthcare services. © 2022 by the authors.

Hemolysis and COVID-19 infection: A fatal combination - An interesting series of three cases

COVID-19 has wreaked havoc ever since its inception and with the protean manifestations of the disease, it is imperative that progressively data are added to the literature. COVID-19 infection is a multisystem disorder with a wide range of clinical symptomatology. Recent information garnered has laid emphasis on pathological changes at microvascular level causing thrombotic/hemostatic defects, leading to the assorted clinical presentation. We present a consortium of three confirmed COVID-19 cases whose hospital course got convoluted with grave hematological complications in the form of hemolytic uremic syndrome and autoimmune hemolytic anemia. Regrettably, all three patients succumbed to their illness.

Pentobarbital for Sedation of Adults Receiving Extracorporeal Membrane Oxygenation for Covid-19

INTRODUCTION: Sedation for ventilated patients with COVID-19 is challenging given the severity and duration of the disease. Complicating this is the introduction of extracorporeal membrane oxygenation (ECMO) for patients with refractory respiratory failure. An ECMO circuit can meaningfully alter drug pharmacokinetics by sequestering drug, increasing the volume of distribution, and altering clearance. Many common sedatives are known to be significantly impacted, thus altering standard dosing. In circumstances warranting deep sedation, such as ARDS, clinicians need a wide array of sedatives and analgesics available when managing patients receiving ECMO support. To our knowledge, no studies have assessed the use of pentobarbital as a sedative in adult patients receiving ECMO support for severe ARDS. We aimed to characterize the use of pentobarbital infusions as part of a multi-modal sedation regimen in adult patients with COVID-19 who were receiving ECMO. METHOD(S): Adults with COVID-19 who were receiving both pentobarbital and VV-ECMO support between March 2020 and December 2021 were included. The primary outcome was change in the dose of concomitant sedatives at 24- and 48-hours post-initiation of pentobarbital. Secondary outcomes included depth of sedation, ventilator synchrony, mean arterial pressure (MAP), and vasopressor doses in norepinephrine equivalents. Additionally, we assessed for adverse drug reactions (ADRs) which included hypotension and transaminitis. RESULT(S): Five patients were included. All patients were initiated on a pentobarbital infusion for the indication of ventilator dyssynchrony. Patients received pentobarbital at an initial rate of 1 mg/kg/hr and infusion rates ranged between 0.5 - 2 mg/kg/hr. Following pentobarbital initiation, all patients became synchronous with the ventilator and doses of continuous sedative infusions decreased. Additionally, the total number and daily dose of rescue sedative medications decreased following pentobarbital initiation. ADRs were common and included hypotension (60%) and transaminitis (20%). CONCLUSION(S): A pentobarbital infusion can be used as part of a multimodal sedation regimen for patients requiring high doses of sedatives to achieve ventilator synchrony.

Virtual Career Fairs: Best Practices and Student Satisfaction

Purpose of the Study: Given the social restrictions surrounding COVID-19, the virtual career fair (VCF) has replaced most traditional in-person career fairs and it may even continue as a viable post-pandemic alternative. This research primarily explores best practices for a VCF and furthermore investigates factors that impact satisfaction of student VCF participants. Method/Design and Sample: Survey data collected from students participating in a virtual career fair investigate the role of students’ preparation time, student perception of employer preparedness and the number of private, one-on-one text and video chat invites students receive in impacting student satisfaction. Results: Findings from a regression analysis reveal that student’s own preparation time and their perception of employer preparedness influenced student satisfaction with the VCF. Additionally, qualitative feedback from both students and employers support the use of best practices. Value to Marketing Educators: Involved faculty and university administrators can adopt the recommended best practices as a framework for planning, conducting, and evaluating successful VCFs. Both universities and employers will benefit as a result. © 2022, Marketing Management Association. All rights reserved.

In-silico analysis of multiepitope based vaccine targeting respiratory viruses SARS, MERS and SARS-CoV-2

BACKGROUND: Recurrent outbreaks of respiratory viruses like SARS-CoV (severe acute respiratory syndrome-coronavirus, 2002), MERS (Middle East respiratory syndrome, 2012) including the ongoing SARS-CoV-2 (2019) pandemic warrants for a single-broad-spectrum vaccine against these respiratory viruses. METHOD(S): In the present study, phylogenetic analysis followed by in-silico identification of vaccine candidates for SARS, MERS and SARS-CoV-2 was performed by exploiting T-cell and B-cell mapping to ascertain the best possible epitopes for effector humoral- and cell-mediated immune response. Further, population-coverage analysis of the identified epitopes followed by the designing of chimera of epitope-based vaccine was done using linkers and adjuvants. Docking study was done to appraise the interaction of the proposed vaccine with ACE2 (angiotensin converting enzyme-2) receptor (SARS and SARS-CoV-2) and HLA-B7 (human leukocyte antigen) receptor (MERS). The stability of the vaccine chimera was confirmed by molecular dynamics performed for 20 ns;this was followed by codon optimization and in-silico cloning. RESULT(S): Phylogenetic analysis revealed similarity among SARS-CoV-2, SARS-CoV and bat SARS-like coronavirus. Both, SARS-CoV and SARS-CoV-2 were from different class than MERS, whereas SARS-CoV-2 showed more relatedness with Bat SARS-like coronaviruses. The most suitable epitopes found were LSFELLNAPATVCGP (SARS), LVTLAILTALRLCAY (SARS-CoV-2) and YTSAFNWLL (MERS) with nearly 98% population coverage. Molecular docking followed by simulation studies revealed high number of hydrogen bonds, stable RMSD values and acceptable RMSF flexibility scores, indicating stable interactions of the vaccine with ACE2 and MHC receptors (Major histocompat-ibility complex). Expression of the designed multiepitope vaccine in E. coli (Escherichia coli) expression system was confirmed by in-silico cloning/codon optimization. CONCLUSION(S): Further, in-vitro and in-vivo experimental validation studies are required to endorse our current findings. Copyright © 2022 EDIZIONI MINERVA MEDICA.

Estimation of mask effectiveness perception for small domains using multiple data sources

Understanding the impacts of pandemics on public health and related societal issues at granular levels is of great interest. COVID-19 is affecting everyone in the globe and mask wearing is one of the few precautions against it. To quantify people’s perception of mask effectiveness and to prevent the spread of COVID-19 for small areas, we use Understanding America Study’s (UAS) survey data on COVID-19 as our primary data source. Our data analysis shows that direct survey-weighted estimates for small areas could be highly unreliable. In this paper, we develop a synthetic estimation method to estimate proportions of perceived mask effectiveness for small areas using a logistic model that combines information from multiple data sources. We select our working model using an extensive data analysis facilitated by a new variable selection criterion for survey data and benchmarking ratios. We suggest a jackknife method to estimate the variance of our estimator. From our data analysis, it is evident that our proposed synthetic method outperforms the direct survey-weighted estimator with respect to commonly used evaluation measures. © Aditi Sen, Partha Lahiri.

Ultrasound guided unilateral erector spinae blockade in open cholecystectomy in COVID-19 era

Background: The erector spinae plane (ESP) blockade acts as a potent unilateral analgesic technique. The block is performed by injecting local anaesthetic drug in the plane between the erector spinae muscle and the vertebral transverse process, with its effect due to diffusion of the local anaesthetic into the paravertebral space through spaces between the adjacent vertebrae. It is a relatively safe and easy technique as compared to the thoracic epidural because our target in ESP blockade is the transverse process, which is identified easily and is distant from neural or major vascular structures and the pleura. Aim of the study: To assess the analgesic effect of ultrasound guided unilateral erector spinae blockade in open cholecystectomy Material and methods:We present a case series of ESP blockade under ultrasound guidance in nine patients scheduled for open cholecystectomy because surgeons chose to avoid laparoscopic surgery due to the increased risk of COVID-19 infection due to intraperitoneal aerosol generation. Results: All patients with postoperative ESP blockade maintained an NRS pain score of 03/10 for 24 h, except for those requiring emergency analgesia. The pain relief was excellent in all our patients and there were no complaints of nausea, vomiting. Conclusion: ESP blockade is proving to be a successful technique for intraoperative and postoperative analgesia.

HOW HAS COVID-19 AFFECTED REFERRALS TO A TERTIARY HYPER ACUTE STROKE UNIT?

Background and aims: To observe how the Covid-19 pandemic affected trends in referrals to our tertiary hyperacute stroke unit (HASU). Methods: Referrals from emergency departments in hospitals within our sector were made electronically using the online 'Refer-A-Patient' system. We reviewed 150 referrals made post-Covid, from 16th March 2020 (when Covid restrictions were first introduced in the UK) until June 2020. These were compared with 150 referrals made pre-Covid, between March and June in 2019. Results: The patients in the pre-Covid referral cohort were significantly older on average than the post-Covid referral cohort (p=0.0476);there were more referrals under the age of 50, and fewer over the age of 80, post-Covid. We accepted significantly fewer patients for transfer post-Covid compared with pre-Covid (21% vs. 43% respectively, p=0.0001). The percentage of cases with a confirmed stroke diagnosis post-transfer was marginally higher post-Covid than pre-Covid (69% vs. 59% respectively, p=0.2443). Importantly, of the patients not accepted for transfer post-Covid, none had a subsequent stroke diagnosis. Conclusions: The Covid-19 pandemic seems to have led to a more selective approach in accepting referrals for transfer. This in turn appears to have reduced our stroke mimic rate. This poses an argument that there are benefits in being more selective. Video triage is an emerging tool, which can be used in emergency departments to aid the accuracy of selection for transfer and warrants further evaluation.

Allocation Optimization of Medical Samples For Distributed Testing

The world is witnessing the COVID-19 pandemic, which originated in the city of Wuhan, China, and has quickly spread to the whole world, with many cases having been reported in India as well. The healthcare system is going through unprecedented load on its resources while the available infrastructure is inadequate.COVID-19 samples are being tested at a massive scale and even small optimizations at this scale can save time, huge amounts of money, and resources. Particularly, the manual approach or even baseline greedy approach being used to allocate COVID-19 samples to medical labs across a state can lead to underutilization of resources. Hence, this work proposes a system to optimize the problem of allocation of medical samples to medical testing laboratories with high efficiency and minimal economic penalty. We use the Mixed Integer Programming (MIP) Model using high-performance MIP based solvers for custom applications by providing a tight integration with the branch-and-cut algorithms of the supported solvers to improve the results compared to baseline greedy approach. The system provides a transportation schedule optimized with respect to capacity of different labs and COVID-19 cases across the state of Karnataka. We tested the model on various datasets and observed significant improvement over the baseline greedy model.

A Smart Framework to Analyze Hotel Services after COVID-19

In the last decade, many websites have allowed customers to provide reviews about their experiences in dealing with different hotels like describing their opinions about different sides like cleanliness, food, employees, and other services. However, after COVID-19, new concerns have emerged linked to the health precautionary and preventive processes. At the same time, the amount of generated data (Textual Data) has become very huge (Big Data), and it needs to auto classifier for processing it where it is impossible to review manually. So, this research proposed a smart method to detect useful information from text by extracting the interesting services from comments automatically. The method depended on machine learning (ML) and compared between five different classification models (Spacy, Naïve Bayes (NB), Stochastic Gradient Descent (SGD), Passive Aggressive, and AdaBoost) to determine which one provides the best results and accuracy. According to the experiment on a real dataset containing more than 1000 records, the NB was the best accurate with 98%, while the Spacy was less and that related to the small size of training data. © 2022 Bharati Vidyapeeth, New Delhi.

Effect of tocilizumab treatment for COVID-19-induced acute respiratory distress syndrome (ARDS) on renal function of patients

Purpose: To study the effect of tocilizumab (TCZ) on the renal function of patients with severe coronavirus disease 2019 (COVID-19) induced acute respiratory distress syndrome (ARDS).

Predicting NCOVID-19 Probability Factor with Severity Index

Hospitals worldwide are struggling to cope up with patient’s admission issues related with the increasing number of COVID-19 patients’ cases mainly driven by Delta variant, as severely ill nCOVID patients are found waiting for hospital beds, which are occupied by non-critical COVID patients. To make the situation worse, people who are partially or fully vaccinated against COVID-19 are also getting re-infected. Due to the absence of prior knowledge of an index of severity for COVID-19 patients, hospitals, with limited number of ventilators and medical equipment, fail to admit patients on any priority basis. With multiple tests kit available in market till now, there is none with an instantaneous index for severity prediction for COVID. This research develops a free and user-friendly algorithm titled “SAHAYATA 1427” (renamed herein Sahayata) which predicts a factor for a patient having the probability of disease nCOVID-19 termed as “probability factor” of COVID-19 for each patient. Concurrently, the algorithm also provides an index for severity by which the patient is affected by nCOVID, termed as “severity index.” The input data is both demographic and patient provided. The severity index is determined using artificial intelligence. Using a logistic regression model with data set of existing COVID patients, Sahayata predicts the probability factor for an nCOVID-19 patient with an accuracy, precision and recall of 88.17%, 100% and 87.3%, respectively. Results indicate that it can be used effectively both at hospitals by trained medical personnel and at home by the general population. Sahayata helps the COVID-19 patients living in rural communities with smaller patients care facilities with limited equipment by providing a way for efficient treatment care. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Optimization and Adaptation of a Resource Planning Tool for Hospitals Under Special Consideration of the COVID-19 Pandemic

Hospitals and health-care institutions need to plan the resources required for handling the increased load, i.e., beds and ventilators during the COVID-19 pandemic. BaBSim.Hospital, an open-source tool for capacity planning based on discrete event simulation, was developed over the last year to support doctors, administrations, health authorities, and crisis teams in Germany. To obtain reliable results, 29 simulation parameters such as durations and probabilities must be specified. While reasonable default values were obtained in detailed discussions with medical professionals, the parameters have to be regularly and automatically optimized based on current data. We investigate how a set of parameters that is tailored to the German health system can be transferred to other regions. Therefore, we use data from the UK. Our study demonstrates the flexibility of the discrete event simulation approach. However, transferring the optimal German parameter settings to the UK situation does not work-parameter ranges must be modified. The adaptation has been shown to reduce simulation error by nearly 70%. The simulation-via-optimization approach is not restricted to health-care institutions, it is applicable to many other real-world problems, e.g., the development of new elevator systems to cover the last mile or simulation of student flow in academic study periods. © 2021 European Union

IoT based Sanitization Tunnel

The Covid-19 Pandemic has caused huge losses worldwide and is still affecting people all around the world. Even after rigorous, incessant and dedicated efforts from people all around the world, it keeps mutating and spreading at an alarming rate. In times such as these, it is extremely important to take proper precautionary measures to stay safe and help to contain the spread of the virus. In this paper, we propose an innovative design of one such commonly used public disinfection method, an Automatic Walkthrough Sanitization Tunnel. It is a walkthrough sanitization tunnel which uses sensors to detect the target and automatically disinfects it followed by irradiation using UV-C rays for extra protection. There is a proposition to add an IoT based Temperature sensor and data relay module used to detect the temperature of any person entering the tunnel and in case of any anomaly, contact nearby covid wards to facilitate rapid treatment. © 2021 IEEE.

Multi-centre development of a secure, cloud based, patient to clinician, neurology video transfer, classification and management syste

Purpose: A government funded;interactive cloud storage platform (www.vcreate.tv/neuro) allowing patients and carers to upload video and linked metadata for neurological diagnosis was established during the Covid-19 pandemic. We describe the utility for epilepsy and paroxysmal disorders in 16 centres with the first centre active from 01/05/2020. Method: Users are invited to register and utilise a password and passcode for access. Videos are uploaded with a structured history. The clinician classifies seizure type, syndrome, aetiology or other diagnosis using drop-down menus. Users and clinicians complete online evaluations. Postcode allows linkage to user index of deprivation score. Consents for teaching by the local clinical team and research within a national neurology video research database with research ethics approval are optional. All data, except the video file, transfer to the electronic patient record. Result: To 24/03/2021, 4582 video uploads (4024 paediatric, 558 adult), 1889 patients (1594 paediatric, 295 adult). 400-600 new videos per month. 323 physician and nurse users. Deprivation scores indicate equitable use across socio-economic groups. Paediatric classification: non-epileptic 55%, epileptic (36.5%), unknown (8.5%). Adult: non-epileptic 73.5% (34% dissociative, 41% movement disorders), epileptic 11%, unknown 15.5%. Paediatric seizure types include: focal impaired awareness (19%), generalised tonic clonic (18%), focal clonic (17%), epileptic spasms (13%). Non-epileptic events: tics (13%), normal behaviour (12%), sleep myoclonus (10%) gratification (8%), dissociative (5%). >95% carers ranked the system positively. Clinicians report video prevented face-to-face review in 57%, investigations in 44% and reduced time to diagnosis in 97%. Median time to review video and classify was 5 minutes. Conclusions: Remote care is facilitated, investigations prevented or prioritised, with rapid diagnosis and efficiencies in the patient pathway. A rapidly growing teaching resource and research database for semiology and machine learning diagnostics for paroxysmal disorders has been established. We plan to establish the system in low-income countries without cost.