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Background: Prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) are two novel markers that have emerged as potential candidates as an early indication of the severity of the disease in coronavirus disease 2019 (COVID-19) patients. Objective: The objective of the study is to assess the utility of the prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) as markers of severity among patients with COVID-19 infection. Methods: This is a retrospective study conducted in a tertiary care centre in South India. A total of 80 patients diagnosed with COVID-19 were included in the study. The patients were divided into mild, moderate, and severe groups based on the clinical parameters as per Indian Council of Medical Research guidelines. Lab values taken at admission were obtained from patient records, using which the PNI and SII were calculated using standard formulae. These markers were correlated with the severity of the COVID-19 illness. Results: PNI and SII were significantly elevated in the patients with severe COVID-19 illness as compared with mild COVID-19 illness. The mean PNI among subjects with mild COVID-19 and severe COVID-19 being 46.62 ± 6.51 and 34.09 ± 5.81, respectively. The mean SII among subjects with mild COVID-19 was 9,52,287.2 ± 1,42,113, and among subjects with severe COVID-19 was 15,39,461 ± 8,04,285. The cut-off value for PNI and SII for predicting severity of COVID-19 illness was 35.93 and 5,82,400, respectively. The sensitivity for PNI was 87.5, and the SII was 95. Conclusion: The present study showed a significant correlation between the SII and PNI as markers used to determine the severity of COVID-19. Based on these findings, it can be effectively used independently of other markers to predict critical illness among COVID-19 patients.

After withdrawing the movement control order (MCO), new variant (Omicron) of COVID-19 returns as an outbreak again. Therefore, consumers are very much informed by various media to be more cautious in visiting shopping malls and spend less time in there. The purpose of this study was to identify the predictors influencing the desire to stay shorter at the shopping mall. This study was conducted in Malaysia, with the application of three psychological theories and one behavioural theory. This is quantitative research based on an online cross-sectional survey design. Data were collected from 296 respondents, by applying the online snowball sampling method through numerous media platforms i.e., Viber, WhatsApp, Messenger, and other apps in three severely affected cities in Malaysia i.e., Selangor state, Putrajaya, and Kuala Lumpur. SmartPLS was used to analyse the data. Using structural equation modelling, this study result shows risk, protection motivation, and fear have a significant effect on the desire to stay a shorter time at the shopping mall. Social norm moderates the association between fear and the desire to spend a shorter time at the shopping mall. These findings, highlight the need for a more empirical study to design more robust strategies, and a safer and risk-free shopping mall environment., Author(s): Syed Shah Alam [sup.1] , Mohammad Masukujjaman [sup.1] , Mohammed Emad Al-Shaikh [sup.2] , Mohd Helmi Ali [sup.1] , Zafir Khan Mohamed Makhbul [sup.1] , Abdullah Sanusi Othman [sup.3] [...]

Objective: To evaluate the clinical features and laboratory profile of elderly patients with Coronavirus Disease-19 (COVID-19) at a tertiary care centre in South India. Material and Methods: A hospital-based retrospective study was conducted in 1,744 elderly patients by collecting the clinical and laboratory data from COVID-19 confirmed patients from May 2020 to June 2021 in a tertiary care hospital in Bangalore, India. The clinical features, comorbidities, serum biochemical parameters and inflammatory markers were recorded and collated with disease outcomes. The clinical presentation, inflammatory markers were studied and compared between survivors and non-survivors. P-value less than 0.05 set as statistical significance. Results: The mean age of the patients was 69.7±7.4 years and the male: female ratio was 1.65:1. The most common comorbidity reported in elderly patients with COVID-19 was type 2 diabetes mellitus (46.8%), followed by hypertension (35.7%), chronic kidney disease (10.7%), and ischemic heart disease (6.47%). 41.9% of the patients did not have any co-morbidities. Out of the 1,744 elderly patients, 164 (9.4%) died and mortality was highest in the COVID-19 patients with severe disease (103 patients, 62.8%). Inflammatory markers of neutrophil/lymphocyte ratio (N/L ratio), lactate dehydrogenase (LDH), ferritin, C-reactive protein (CRP), D-Dimers and interleukin-6 were significantly elevated among the patients who did not survive. Conclusion: Mortality was highest in elderly COVID-19 patients with severe disease and most of the patients who died had one or more comorbidities. Neutrophilia, lymphopenia, eosinopenia along with elevated N/L ratio, LDH, ferritin, D-dimer, IL-6 and CRP were significantly associated with adverse disease outcomes.

Key Clinical Message Neuromyelitis optica spectrum disorders can less commonly present with area postrema syndrome progressing to myelitis. Management involves intravenous glucocorticoids, plasma exchange, and preventive immunotherapy. Abstract Neuromyelitis optica spectrum disorders can less commonly present with area postrema syndrome progressing to myelitis. The majority of patients have positive AQP4‐Ab. Diagnosis is based on clinical and imaging findings. These patients can be treated with intravenous glucocorticoids, plasma exchange, and preventive immunotherapy.

Abstract Background Persistent left superior vena cava is a well-recognized thoracic venous abnormality, most of which do not present with any symptoms. Its opening into the left atrium is uncommonly encountered and, if present, is noted to be associated with various other complex intracardiac malformations, which further complicates its management. Herein, we highlight a case of an adult with persistent left superior vena cava with a spectrum of other cardiac anomalies rarely encountered with it, which was effectively managed by tailored surgical intervention. Case presentation A 26-year-old female on meticulous evaluation was found to have left isomerism with an interrupted inferior vena cava and hemiazygos continuing as a persistent left superior vena cava. It was also associated with common atrium, partial atrioventricular canal defect, and complete heart block. This complex array of anomalies was managed surgically. Common atrium was closed with atrial neo-septation using autologous pericardial patch tailored in a way, such that the persistent left superior vena cava drained into right atrium with left atrial appendage being on right side of neo-septum. Cleft in the left atrioventricular valve was also repaired. Despite preoperative complete heart block, the patient had an uneventful postoperative recovery and was in atrial fibrillation with controlled ventricular rate, thus precluding the need for permanent pacemaker implantation. Conclusions A rare spectrum of adult congenital cyanotic heart disease was successfully managed with thorough preoperative evaluation and judicious intraoperative management. Surgical management should be tailored based on specific anatomy for reduction of morbidity and optimum results.

To the authors’ knowledge, currently, there is no review covering the different technologies applied to opening manual doors. Therefore, this review presents a summary of the various technologies available on the market as well as those under research and development for opening manual doors. Four subtopics—doorknob accessories, wheelchair-mounted door-opening accessories, door-opening robots, and door-opening drones—were used to group the various technologies for manually opening doors. It is evident that opening doors is a difficult process, and there are different ways to solve this problem in terms of the technology used and the cost of the end product. The search for an affordable assistive technology for opening manual doors is ongoing. This work is an attempt to provide wheelchair users and their healthcare providers with a one-stop source for door-opening technologies. At least one of these door-opening solutions could prove beneficial to the elderly and some wheelchair users for increased independence. The ideal option would depend on an individual’s needs and capabilities, and occupational therapists could assess and recommend the right solutions.

Introduction: The world has witnessed a surge of COVID-19 cases since the first case was reported in 2018 December, and despite the large number of cases seen across the world, there are still many gaps in the understanding of the course of the disease in different people. Several scoring systems and early warning signs have been developed to prognosticate the disease process. Clustering the patients into specific clinical phenotypes is one such strategy. In this study, we have clustered the COVID-19 patients using different variables into phenotypes and studied the outcome based on this classification. Aim and Objectives: To derive clinical phenotypes based on demographic, clinical, and laboratory data of COVID-19 patients and look at the efficiency of the phenotypes as a model for predicting course of disease. Materials and Methods: A retrospective cohort study on COVID-19 patients admitted to a tertiary care hospital in South India between July 2020 and October 2020 was conducted. Nine hundred and eighty-seven subjects fulfilling the inclusion criteria were enrolled. Results: Three clinical phenotypes were derived using 43 independent variables which included epidemiological, symptomatology, comorbidities, and laboratory values. Of the 987 patients studied, patients could be clustered into three phenotypes named A, B, and C. There were 379 patients in phenotype A, 313 in phenotype B, and 295 were in phenotype C. Males predominated in phenotypes C and B, which was 218 patients (73.9%) and 204 (65.2%), respectively. Mild disease was predominant in phenotype A (89.2%) patients, followed by10.3% of moderate disease and 0.5% of severe COVID disease. In phenotype B, 93.3% of patients had mild disease and the rest 21 (61.7%) had moderate disease. In phenotype C, 177 (60%) patients had severe COVID disease. Mortality was seen in phenotype C (23.1%). Conclusions: It can be inferred that among the phenotypes, the hyperinflammatory group was phenotype C. The independent predictive association of each variable such as age, male gender, and comorbidity is an important factor in determining the outcome but, because of the varied distribution of the multiple variables in each patient, it is not possible to consider each of these values independently and deduce the outcome, hence phenotypes which cluster the patients based on all these variables are associated with predictable outcomes The phenotypes thus can be implicated as a tool to aid in clinical management of COVID-19.

Background: Over the years, increasing obesity, hypertension and diabetes mellitus have led to higher incidence and prevalence of Non-alcoholic Fatty Liver Disease (NAFLD) in India, which was initially thought to be a disease of developed countries. NAFLD is the most common cause of chronic liver disease in the western countries and now it is in rapid rise in India. Liver biopsy is a gold standard in NAFLD diagnosis. As liver biopsy is an invasive procedure various non-invasive markers are being explored to assist in diagnosis of NAFLD. One such promising marker which is being studied is Mean Platelet Volume (MPV). Nevertheless, studies utilizing MPV for the diagnosis of NAFLD are rare. Aim and Objectives: To measure levels of MPV in NAFLD patients and compare with healthy controls. Material and Methods: A total of 86 subjects, 43 NAFLD and 43 healthy controls, were included. Baseline variables, laboratory parameters and MPV recorded were compared between both the groups. Results: Demographic variables [Body Mass Index (BMI), waist circumference], laboratory variables (total leukocyte count, platelet crit, MPV), liver function tests (alanine transferase, alkaline phosphatase, gamma glutaryl transferase) and lipid parameters (high-density lipoprotein, low-density lipoprotein, very low-density lipoprotein) were significantly higher in the NAFLD group. MPV correlated positively with aspartate aminotransferase (r: 0.2834, p=0.0082), alanine transferase level (r: 0.2834; p=0.0082) and the presence of NAFLD (0.6019; p10.6 fL yielded 72.09% sensitivity, 76.74% specificity, 75.61% positive predictive value and 73.33% negative Predictive Value. Conclusion: The study results show an increase in MPV in patients with NAFLD.

In this paper, new SVPWM switching sequences for six-phase asymmetrical induction motor drives are derived with the aim to reduce inverter's switching losses. Total three switching sequences are introduced in this paper. These sequences are derived such that the phases get continuously clamped when a current of the phases is around its peak magnitude and hence reduced switching losses are recorded. The comparative performances of these modulation techniques are studied with two existing switching sequences. Simulation, analytical and experimental results are presented. Based on these results, it is found that new switching sequences reduce switching losses effectively in dual three phase inverters.

The enhanced primary treatment of municipal primary influent under wet weather conditions was studied through a comprehensive approach from bench to full scale. The study delivered a practical solution for managing seasonal fluctuations in the influent wastewater by determining the most effective operation conditions for coagulation-flocculation. Three metal-based coagulants were tested through a series of jar tests. Alum outperformed other coagulants since 1 mg of Al added as alum with low mixing was able to remove 22 NTU, 19 mg COD, and 0.8 mg ortho-P. Three-factor analysis of variance (ANOVA) indicated that total suspended solids (TSS) removal depended mostly on rapid mixing while chemical oxygen demand (COD) and ortho-P removals depended on slow mixing and coagulant dose. In bench and full-scale operations, the addition of polymer did not lead to any pronounced improvements. Finally, turbidity and percent ultraviolet transmittance showed good correlation with TSS and ortho-P, which evokes their use as surrogates for micropollutants removal and online process control. Key words: combined sewer overflow, coagulant, alum, polymer, macropollutants. L'amelioration du traitement primaire des eaux usees municipales arrivant aux stations d'epuration pendant les saisons de pluie ou fonte des neiges a ete etudiee au moyen d'une approche globale allant de l'echelle du banc d'essai a pleine echelle. L'etude a fourni une solution pratique pour gerer les fluctuations saisonnieres des eaux usees en determinant les conditions d'operation les plus efficaces pour le processus de coagulation-floculation. Trois coagulants a base de metaux ont ete mis a l'essai au moyen d'une serie d'essais de floculation. L'alun a acheve un rendement qui a surpasse celui des autres coagulants puisque 1 mg d'Al ajoute sous forme d'alun et melange a faible vitesse, a permis d'eliminer 22 uTN, 19 mg de DCO et 0,8 mg ortho-P. L'ANOVA a trois facteurs a indique que l'elimination du total des solides en suspension (TSS) dependait principalement du melange a vitesse rapide, tandis que l'elimination de la demande chimique en oxygene (DCO) et de l'ortho-P dependait du melange a faible vitesse et de la dose du coagulante. En plus, l'ajout de polymere n'a pas entrame aucune amelioration remarquable ni a l'echelle du banc d'essai ni a pleine echelles. Enfin, la turbidite et la transmission de l'ultraviolet ont montre une bonne correlation avec le TSS et l'ortho-P, ce qui suggere la possibilite de leur utilisation comme parametres de substitutions pour reveler l'elimination des micropolluants et assister au controle du processus en ligne. [Traduit par la Redaction] Mots-cles: debordements d'egouts unitaires, coagulant, alun, polymere, macropolluant., Introduction Wastewater collection networks represent a fundamental component of a city's infrastructure and its wastewater treatment process. In areas where those networks are designed to accommodate storm water runoffs in [...]

Purpose: The manual, user-operated Arise Standing Wheelchair (SWC) is the end result of multiple design iterations based on findings and feedback from user trials. The Arise SWC provides standing functionality, outdoor mobility, affordability, and customisability. This paper describes a long-term community integration study of the Arise SWC. Methods: All participants (N = 8; 7 Male, 1 Female) were persons with spinal cord injuries. During the study period (six months), the participants integrated the Arise SWC into their daily routines. To assess the impact of the Arise SWC on various outcome measures, participants' responses were captured using a Likert-scale questionnaire at the beginning of the study, after 30 days, and after 180 days of Arise SWC usage. Results: The long-term usage of the Arise SWC positively impacted the users' standing performance (ability to stand regularly, stand at different locations, and stand in community settings), productive ability (accessibility to environmental controls and ability to perform overhead reaches), and pathophysiology (spasticity and ability to get proper sleep). Furthermore, all the users were able to independently move using the Arise SWC over even and uneven terrain (some needed minimal assistance over uneven terrain). Conclusions: Overall, we believe that Arise SWC will benefit eligible users and improve their ability and performance in daily activities. IMPLICATIONS FOR REHABILITATION: Arise Standing Wheelchair (SWC) positively impacted users' standing performance, mobility over uneven terrain, ability to transfer between surfaces, and overhead reaches. Arise SWC positively impacted users' overall physical well-being. The study shows that Arise SWC improved the users' overall daily living activities. Arise SWC, an affordable solution, is anticipated to have a global impact, especially on low-income nations. [ABSTRACT FROM AUTHOR]

Steering a wheelchair while navigating through manual doors or against obstacles is challenging for some users. Previously, a low-cost, low-tech accessory made using off-the-shelf components, conventional manufacturing, and 3D-printed fasteners demonstrated the proof-of-concept for uncrossable positive obstacle pushing or gliding. Current work presents the fabrication and testing of an entirely 3D-printed prototype of the accessory. The accessory was 3D-printed using ABS (10% fill density) in sections. A finite element stress analysis simulation was performed for the entire accessory. Prototype tests were done with the accessory installed on an unoccupied powered wheelchair against a door and an obstacle with ∼25 N and ∼50 N resistance forces, respectively. The maximum stresses in none of the crucial components exceeded the break strength of ABS. Test results demonstrate the ability and mechanical robustness of the fully 3D-printed accessory to push open manual doors, allowing easy navigation through doors, and to push or glide against obstacles. The current prototype improves over the previous prototype in terms of manufacturability, weight, design, and safety. To the best of our knowledge, this is the first demonstration of an entirely 3D-printed wheelchair accessory that pushes or glides against uncrossable positive obstacles. Future studies would involve end-user satisfaction assessment and functionality evaluation in different scenarios under clinical supervision. The pushing or gliding ability of the accessory could be beneficial to wheelchair users with neuromuscular disorders or paraplegia. Low-tech 3D-printed accessory allows wheelchair users to push or glide against doors and other obstacles. Protective nature of the accessory could prove highly beneficial to some wheelchair users (those with diabetic feet). Pushing or gliding ability of the accessory could be beneficial to wheelchair users with neuromuscular disorders or paraplegia. Accessory could reduce wheelchair accidents and falls due to uncrossable positive obstacles. 3D printing allows easy prototyping of wheelchair-related assistive technology solutions. [ABSTRACT FROM AUTHOR]

ABSTRACT: Background: Prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) are two novel markers that have emerged as potential candidates as an early indication of the severity of the disease in coronavirus disease 2019 (COVID-19) patients. Objective: The objective of the study is to assess the utility of the prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) as markers of severity among patients with COVID-19 infection. Methods: This is a retrospective study conducted in a tertiary care centre in South India. A total of 80 patients diagnosed with COVID-19 were included in the study. The patients were divided into mild, moderate, and severe groups based on the clinical parameters as per Indian Council of Medical Research guidelines. Lab values taken at admission were obtained from patient records, using which the PNI and SII were calculated using standard formulae. These markers were correlated with the severity of the COVID-19 illness. Results: PNI and SII were significantly elevated in the patients with severe COVID-19 illness as compared with mild COVID-19 illness. The mean PNI among subjects with mild COVID-19 and severe COVID-19 being 46.62 ± 6.51 and 34.09 ± 5.81, respectively. The mean SII among subjects with mild COVID-19 was 9,52,287.2 ± 1,42,113, and among subjects with severe COVID-19 was 15,39,461 ± 8,04,285. The cut-off value for PNI and SII for predicting severity of COVID-19 illness was 35.93 and 5,82,400, respectively. The sensitivity for PNI was 87.5, and the SII was 95. Conclusion: The present study showed a significant correlation between the SII and PNI as markers used to determine the severity of COVID-19. Based on these findings, it can be effectively used independently of other markers to predict critical illness among COVID-19 patients. [ABSTRACT FROM AUTHOR]

The recognition of emotions is one of the most challenging issues in human–computer interaction (HCI). EEG signals are widely adopted as a method for recognizing emotions because of their ease of acquisition, mobility, and convenience. Deep neural networks (DNN) have provided excellent results in emotion recognition studies. Most studies, however, use other methods to extract handcrafted features, such as Pearson correlation coefficient (PCC), Principal Component Analysis, Higuchi Fractal Dimension (HFD), etc., even though DNN is capable of generating meaningful features. Furthermore, most earlier studies largely ignored spatial information between the different channels, focusing mainly on time domain and frequency domain representations. This study utilizes a pre-trained 3D-CNN MobileNet model with transfer learning on the spatio-temporal representation of EEG signals to extract features for emotion recognition. In addition to fully connected layers, hybrid models were explored using other decision layers such as multilayer perceptron (MLP), k-nearest neighbor (KNN), extreme learning machine (ELM), XGBoost (XGB), random forest (RF), and support vector machine (SVM). Additionally, this study investigates the effects of post-processing or filtering output labels. Extensive experiments were conducted on the SJTU Emotion EEG Dataset (SEED) (three classes) and SEED-IV (four classes) datasets, and the results obtained were comparable to the state-of-the-art. Based on the conventional 3D-CNN with ELM classifier, SEED and SEED-IV datasets showed a maximum accuracy of 89.18% and 81.60%, respectively. Post-filtering improved the emotional classification performance in the hybrid 3D-CNN with ELM model for SEED and SEED-IV datasets to 90.85% and 83.71%, respectively. Accordingly, spatial-temporal features extracted from the EEG, along with ensemble classifiers, were found to be the most effective in recognizing emotions compared to state-of-the-art methods.