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Fluid flow in miniature devices is often characterized by a boundary "slip" at the wall, as opposed to the classical paradigm of a "no-slip" boundary condition. While the traditional mathematical description of fluid flow as expressed by the differential forms of mass and momentum conservation equations may still suffice in explaining the resulting flow physics, one inevitable challenge against a correct quantitative depiction of the flow velocities from such considerations remains in ascertaining the correct slip velocity at the wall in accordance with the complex and convoluted interplay of exclusive interfacial phenomena over molecular scales. Here, we report an analytic engine that applies combined physics-based and data-driven modeling to arrive at a quantitative depiction of the interfacial slip via a molecular-dynamics-trained machine learning algorithm premised on fluid structuration at the wall. The resulting mapping of the system parameters to a single signature data that bridges the molecular and continuum descriptions is envisaged to be a preferred computationally inexpensive route as opposed to expensive multi-scale or molecular simulations that may otherwise be inadequate to resolve the flow features over experimentally tractable physical scales. [ABSTRACT FROM AUTHOR]

Demand for broadband internet has far outpaced its availability. In addition, the "new normal" imposed by the COVID-19 pandemic has further disadvantaged unserved and underserved areas. To address this challenge, federal and state agencies are funding internet service providers (ISPs) to deploy broadband infrastructure in these areas. To support goals to provide broadband service to as many people as possible as quickly as possible, policymakers and ISPs may benefit from better tools to predict take rates and formulate effective strategies to increase the adoption of high-speed internet. However, there is typically insufficient data available to understand consumer attitudes. We propose using an agent-based model grounded in the Theory of Planned Behavior, a behavioral theory that explains the consumer's decision-making process. The model simulates residential broadband adoption by capturing the effect of market competition, broadband service attributes, and consumer characteristics. We demonstrate the effectiveness of this type of tool via a use case in Missouri to show how simulation results can inform predictions of broadband adoption. In the model, broadband take rates increase as the presence of existing internet users in the area increases and price decreases. With further development, this type of simulation can guide decision-making for infrastructure and digital literacy investment based on demand as well as support the design of market subsidies that aim to reduce the digital divide. [ABSTRACT FROM AUTHOR]

Regional weather and climate are generally impacted by global climatic phenomenon′s. Understanding the impact of global climate phenomenon′s on an atmospheric branch of the hydrological cycle is crucial to make advances in skillful precipitation forecast. The present study adopts a multiscale approach based on wavelets for unravelling the linkages between teleconnections and atmospheric moisture transport over homogeneous regions of Indian sub-continent. We investigated linkages between atmospheric moisture transport quantified as monthly integrated water vapor transport (IVT) during 1951–2022 over selected homogeneous regions and eight large scale climate oscillations using wavelet and global wavelet coherence. Our results indicate significant heterogeneity in linkages across different regions and across multiple timescales. In particular, the Indian Ocean Dipole (IOD) influence monthly IVT at intra-annual to inter-annual scale over all regions. The El Niño–Southern Oscillation (ENSO) have strong connection to monthly IVT at inter-annual scale whereas over west central region both IOD and ENSO strongly influence IVT at inter-decadal scale. While the Atlantic Multi-Decadal Oscillation and Pacific Decadal Oscillation have an impact on IVT in the north-east and southern regions, the Arctic Oscillation and North Atlantic oscillation have a strong inter-annual connection to IVT, majorly in the northwest and hilly regions. Overall, the methodology offers an effective approach for capturing the dynamics of atmospheric moisture transport in time–frequency space and provide a practical reference for prediction of atmospheric moisture transport linked precipitation over different regions of Indian subcontinent. [ABSTRACT FROM AUTHOR]

Background and Aim: While European Society of Pediatric Gastroenterology Hepatology and Nutrition advocates a no‐biopsy pathway for the diagnosis of celiac disease (CeD) in children if IgA anti‐tissue transglutaminase antibody (anti‐tTG ab) titer is ≥10‐fold upper limit of normal (ULN) and have a positive IgA anti‐endomysial antibody (EMA); the data for anti‐tTG Ab titer‐based diagnosis of CeD in adults is still emerging. We planned to validate if IgA anti‐tTG Ab titer ≥10‐fold predicts villous abnormalities of modified Marsh grade ≥2 in Asian adult patients with CeD. Methods: We recruited 937 adult patients with positive anti‐tTG Ab from two databases, including AIIMS Celiac Clinic and Indian National Biorepository. The diagnosis of definite CeD was made on the basis of a positive anti‐tTG Ab and the presence of villous abnormalities of modified Marsh grade ≥2. Results: Of 937 adult patients with positive anti‐tTG Ab, 889 (91.2%) showed villous abnormalities of modified Marsh grade ≥2. Only 47.6% of 889 adults with CeD had anti‐ tTG Ab titers of ≥10‐fold. The positive predictive value (PPV) and specificity of anti tTG Ab titer ≥10‐fold for predicting modified Marsh grade ≥2 were 99.8% and 98%, respectively. At anti‐tTG Ab titer ≥11‐fold, specificity and PPV were 100% for predicting villous abnormalities of modified Marsh grade ≥2. Conclusions: Approximately 50% of adults with CeD may benefit from the no biopsy pathway, reducing the health burden and risks of gastroscopy/anesthesia. [ABSTRACT FROM AUTHOR]

The unprecedented sea ice loss in the Arctic is due to its stronger surface warming than other parts across the globe, resulting in far‐flung effects on weather and climate at different spatial and temporal scales. We investigate how Arctic Sea ice and Indian summer monsoon rainfall (ISMR) are associated at seasonal scale and when preconditioned by Arctic Oscillation (AO) phases. This study also examines the potential predictability using correlation and composite analysis. The results indicate a significant decline in sea ice extent (SIE) at a rate of 0.055 Mkm2/year (p < 0.05). The strong association between SIE and precipitation in the Indian region is confirmed by correlation values ranging from −0.6 to 0.6 (p < 0.05). The spatial patterns of seasonal SIE and precipitation association remain consistent for 1979–2021. We found that the prevailing AO phases influence the association of sea ice with ISMR precipitation. The high correlation between SIE and ISMR anomalies suggests that Arctic Sea ice could be a reliable predictor for ISMR. [ABSTRACT FROM AUTHOR]

Background and Aim: Celiac disease (CeD) has now become a global disease with a worldwide prevalence of 0.67%. Despite being a common disease, CeD is often not diagnosed and there is a significant delay in its diagnosis. We reviewed the impact of the delay in the diagnosis on the severity of manifestations of CeD. Methods: We reviewed clinical records of 726 consecutive patients with CeD from the Celiac Clinic database and the National Celiac Disease Consortium database. We extracted specific data including the demographics, symptoms at presentation, time of onset of symptoms, time to diagnosis from the onset of the symptoms, and relevant clinical data including fold‐rise in anti‐tissue transglutaminase antibody (IgA anti‐tTG Ab) and severity of villous and crypt abnormalities as assessed using modified Marsh classification. Results: The median duration between the onset of symptoms and the diagnosis of CeD was 27 months (interquartile range 12–60 months). A longer delay in the diagnosis of CeD from the onset of symptoms was associated with lower height for age, lower hemoglobin, higher fold rise in IgA Anti tTG titers, and higher severity of villous and crypt abnormalities. About 18% of patients presented with predominantly non‐gastrointestinal complaints and had a longer delay in the diagnosis of CeD. Conclusions: There is a significant delay in the diagnosis of CeD since the onset of its symptoms. The severity of celiac disease increases with increasing delay in its diagnosis. There is a need to keep a low threshold for the diagnosis of CeD in appropriate clinical settings. [ABSTRACT FROM AUTHOR]

Health-care settings have an important responsibility toward environmental health and safety. The operating room is a major source of environmental pollution within a hospital. Inhalational agents and nitrous oxide are the commonly used gases during general anesthesia for surgeries, especially in the developing world. These greenhouse gases contribute adversely to the environmental health both inside the operating room and in the outside atmosphere. Impact of these anesthetic agents depends on the total consumption, characteristics of individual agents, and gas flows, with higher levels increasing the environmental adverse effects. The inimical impact of nitrous oxide is higher due to its longer atmospheric half-life and potential for destruction of the ozone layer. Anesthesiologist of today has a choice in the selection of anesthetic agents. Prudent decisions will help in mitigating environmental pollution and contributing positively to a greener planet. Therefore, a shift from inhalational to intravenous-based technique will reduce the carbon footprint of anesthetic agents and their impact on global climate. Propofol forms the mainstay of intravenous anesthesia technique and is a proven drug for anesthetic induction and maintenance. Anesthesiologists should appreciate growing concerns about the role of inhalational anesthetics on the environment and join the cause of environmental responsibility. In this narrative review, we revisit the pharmacological and pharmacokinetic considerations, clinical uses, and discuss the merits of propofol-based intravenous anesthesia over inhalational anesthesia in terms of environmental effects. Increased awareness about the environmental impact and adoption of newer, versatile, and user-friendly modalities of intravenous anesthesia administration will pave the way for greener anesthesia practice. [ABSTRACT FROM AUTHOR]

Background: Acromioclavicular joint dislocations accounts for about 12% of shoulder girdle injuries. However, there is no gold standard procedure for surgical treatment of acute high-grade AC joint injury. Recently, the endobutton technique has been elucidated for the treatment of AC-joint dislocation. Hence, we employed this technique and analyzed its outcome. Material & Method: 24 patients aged between 20-65 years with acute Type III-VI AC joint dislocation were included in the study. Radiograph of both clavicle anteroposterior (AP) stress view was obtained to diagnose. All patients were treated with tight loop endobutton technique. Postoperative rehabilitation regimen was followed for all the patients. Outcome was assessed using VAS, UCLA score, DASH score and AP radiograph of affected side at regular intervals. Result: A higher prevalence of males was observed (83.3%) with mean age of 37.5 ± 12.5 years. RTA was the most common cause of injury. For clinical outcome, the mean postoperative VAS was 0.35 ± 0.48 and mean postoperative UCLA score was 29.5. 8 patients had excellent results and 16 patients had good results according to UCLA score. DASH score decreased gradually postoperatively, with significant improvement starting from the third month post-surgery. Radiologically loss of reduction was observed in only 5 cases. Conclusion: Tight loop Endobutton technique is a simple, cost-effective, one-time surgery which restores the coraco-clavicular (CC) interval and maintains it till the native ligaments heal. It proves to be an excellent alternative modality to treat the AC joint dislocation. [ABSTRACT FROM AUTHOR]

Microscopy-based tuberculosis (TB) diagnosis i.e., Ziehl-Neelsen (ZN) stained smear screening still remains the primary diagnostic method in resource poor and high TB burden countries, however itrequires considerable experience and is bound to human errors. In remote areas, wherever expert microscopist is not available, timely diagnosis at initial level is not possible. Artificial intelligence (AI)-based microscopy may be a solution to this problem. A prospective observational multi-centric clinical trial to evaluate microscopic examination of acid-fast bacilli (AFB) in sputum by the AI based system was done in three hospitals in Northern India. Sputum samples from 400 clinically suspected cases of pulmonary tuberculosis were collected from three centres. Ziehl-Neelsen staining of smears was done. All the smears were observed by 3 microscopist and the AI based microscopy system. AI based microscopy was found to have a sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of 89.25%, 92.15%, 75.45%, 96.94%, 91.53% respectively. AI based sputum microscopy has an acceptable degree of accuracy, PPV, NPV, specificity and sensitivity and thus may be used as a screening tool for the diagnosis of pulmonary tuberculosis. [ABSTRACT FROM AUTHOR]

Background: Acute‐on‐chronic liver failure (ACLF) is associated with a high short‐term mortality rate in the absence of liver transplantation. The role of therapeutic plasma exchange (TPE) in improving the outcomes of ACLF and acute decompensation (AD) is unclear. In this retrospective analysis, we aimed to determine the impact of TPE on mortality in patients with ACLF. Methods: ACLF patients receiving TPE with standard medical treatment (SMT) were propensity score matched (PSM) with those receiving SMT alone (1:1) for sex, grades of ACLF, CLIF C ACLF scores, and the presence of hepatic encephalopathy. The primary outcomes assessed were mortality at 30 and 90 days. Survival analysis was performed using Kaplan Meier survival curves. Results: A total of 1151 patients (ACLF n = 864 [75%], AD [without organ failure] n = 287 [25%]) were included. Of the patients with ACLF (n = 864), grade 1, 2, and 3 ACLF was present in 167 (19.3%), 325 (37.6%), and 372 (43.0%) patients, respectively. Thirty‐nine patients received TPE and SMT, and 1112 patients received only SMT. On PSM analysis, there were 38 patients in each group (SMT plus TPE vs SMT alone). In the matched cohort, the 30‐days mortality was lower in the TPE arm compared to SMT (21% vs 50%, P =.008), however, the 90‐day mortality was not significantly different between the two groups (36.8% vs 52.6%, P =.166); HR, 0.82 (0.44‐1.52), P =.549. Conclusion: TPE improves short‐term survival in patients with ACLF, but has no significant impact on long‐term outcomes. Randomized control trials are needed to obtain a robust conclusion in this regard. [ABSTRACT FROM AUTHOR]

This study sought to report the degree to which postgraduate trainees in radiation oncology perceive their education has been impacted by the COVID-19 pandemic. A cross-sectional online survey was administered from June to July 2020 to trainee members of the Canadian Association of Radiation Oncology (CARO) (n = 203). Thirty-four trainees responded with a 17% response rate. Just under half of participants indicated that COVID-19 had a negative/very negative impact on training (n = 15; 46%). The majority agreed/strongly agreed that they feared family/loved ones would contract COVID-19 (n = 29, 88%), felt socially isolated from friends and family because of COVID-19 (n = 23, 70%), and had difficulty concentrating on tasks because of concerns about COVID-19 (n = 17, 52%). Changes that had a negative/very negative impact on learning included limitations to travel and networking (n = 31; 91%) and limited patient contact (n = 19; 58%). Virtual follow-ups (n = 25: 76%) and in-patient care activities (n = 12; 36%) increased. Electives were cancelled in province (n = 10; 30%), out-of-province (n = 16; 49%), and internationally (n = 15; 46%). Teaching from staff was moderately reduced to completely suppressed (n = 23, 70%) and teaching to medical students was moderately reduced to completely suppressed (n = 27, 82%). Significant changes to radiation oncology training were wrought by the pandemic, and roughly half of trainees perceive that these changes had a negative impact on training. Innovations in training delivery are needed to adapt to these new changes. [ABSTRACT FROM AUTHOR]

Blastic plasmacytoid dendritic cell neoplasm is a rare and aggressive haematopoietic neoplasm with poor prognosis. It usually presents with cutaneous lesions and symptoms secondary to bone marrow involvement. Due to rarity and lack of standard treatment protocols, these cases are difficult to diagnose and treat. We report a case of a female in early adolescence who presented with skin nodules on the leg. The diagnosis was established by immunophenotypic studies. We discuss the investigations and treatment options available to diagnose and treat this malign [ABSTRACT FROM AUTHOR]

This paper introduces the Graphics Processing Unit (GPU)-based tool Geo-Temporal eXplorer (GTX), integrating a set of highly interactive techniques for visual analytics of large geo-referenced complex networks from the climate research domain. The visual exploration of these networks faces a multitude of challenges related to the geo-reference and the size of these networks with up to several million edges and the manifold types of such networks. In this paper, solutions for the interactive visual analysis for several distinct types of large complex networks will be discussed, in particular, time-dependent, multi-scale, and multi-layered ensemble networks. Custom-tailored for climate researchers, the GTX tool supports heterogeneous tasks based on interactive, GPU-based solutions for on-the-fly large network data processing, analysis, and visualization. These solutions are illustrated for two use cases: multi-scale climatic process and climate infection risk networks. This tool helps one to reduce the complexity of the highly interrelated climate information and unveils hidden and temporal links in the climate system, not available using standard and linear tools (such as empirical orthogonal function analysis). [ABSTRACT FROM AUTHOR]

Flutter-based energy harnessing is a promising mean to power microelectronic devices located at remote locations, however, due to out of reach flow demand, marginal advancement is evident in this field. The present work evaluates energy harnessing potential of flutter under different flow fields generated with respect to different shapes of a bluff body. A proof of concept is demonstrated to employ flutter for energy harnessing activity at approachable ambient flow conditions. A test assembly of laminated sheet along with three different bluff bodies (triangular, square, D-shape) is considered. Initially, flow simulations are performed to visualize flow dynamics that qualitatively indicated that the pressure gradient due to downstream circulation and its distribution over the trailing plate are the key parameters to influence the flutter phenomenon. Subsequently, wind tunnel testing confirmed that presence of an upstream body reduces critical velocity significantly. Among all the cases, the D-shape body causes flutter at lowest flow velocity of 5.1 m/s which is 50% lower than 10.2 m/s observed in benchmark case of without upstream body. In order to harvest energy, piezoelectric material (MFC) is used and an output ranging from 0.89 to 1.16 mW across an optimum load resistance of 200 KΩ is observed corresponding to different cases. The D-shape body showed highest output at lowest flow velocity. In terms of ratio of output to input power, the D-shape, square and triangular shaped bodies showed 11.4, 6.7, and 4.6 times higher yield, respectively, when compared with the benchmark case study. [ABSTRACT FROM AUTHOR]

In this work, a novel design of Zinc Oxide (ZnO) and bi-metallic (Ag–Au) layers based surface plasmon resonance (SPR) biosensor with barium titanate (BaTiO3) and graphene is proposed. The proposed structure consists of SF10 glass prism, ZnO, Ag, Au, BaTiO3, and graphene as a top layer for biomolecules adsorption. Here, the performance of this structure is studied and analysed for sensitivity along with the accuracy of detection and quality parameter for the shift in refractive index (RI) from 1.33 (sensing medium) to 1.45 and our reported results show that addition of bimetallic (Ag–Au) layers along with BaTiO3, improve the sensitivity of the proposed structure to 14.85% for the same RI range compared to last reported MoS2-graphene-based SPR sensor. Here at λ = 632.8 nm , maximum sensitivity is reported as 116.67 degree/RIU while the accuracy of detection and the quality parameter are obtained as 4.54 and 37.87 RIU−1 respectively. These high-performance parameters of the design make this structure suitable for biosensing applications. [ABSTRACT FROM AUTHOR]

Human blood is made up primarily of water. Water is significantly involved in balancing the human body. It affects the component of blood like mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and mean platelets volume (MPV). The water concentration varies from 80 to 90% in blood. The change in water concentration changes the refractive index of plasma, and the change in the refractive index of plasma also changes the refractive index of blood. The proposed structure is designed to analyze the water concentration in human blood by analyzing the shifting in resonant peak and this shifting is processed by machine learning algorithm to estimate the concentration of water in human blood. Nanocavity ring structures in the waveguide region are designed as sensing nodes in this proposed structure. The air hole radius of these Nanocavity ring structures is 80 and 50 nm, whereas the proposed structure's dimension is 12.15 by 8.45 μm2. The sensitivity of the design structure is 570 nm/RIU, and the quality factor is 650. The structure is simulated through the Finite Difference Time Domain (FDTD) method. [ABSTRACT FROM AUTHOR]

Intraoperative airway obstruction is a nightmare for anesthesiologists, especially in head and neck surgeries. Due to the proximity of airway and surgical area, it will be difficult for anesthesiologists for the airway access. There are many causes of intraoperative airway obstruction. To the best of our literature search, there is no case report of airway obstruction due to betadine solution. Here we present a case of airway obstruction due to endotracheal tube blockade by the use of betadine solution in the surgery of cervical region in a child posted for posterior C1‑C2 fusion in prone position on skull pins. [ABSTRACT FROM AUTHOR]

Investigation of SST–streamflow connectivity unravels the large‐scale climate influences that may have a potential role in modulating local hydrological components. Most studies exploring this relationship only focus on a single timescale; however, various atmospheric and oceanic phenomena occur at different temporal scales, which must be considered. This study examines the association of sea surface temperature (SST) and streamflow in Germany, divided into three regions, viz. Alpine, Atlantic and Continental, at timescales ranging from seasonal to interannual by integrating wavelet transform and complex network techniques. Wavelet transform is used to decompose the time series into multiple frequency signals. The network theory identifies the spatial connections for the 99 percentile correlation coefficient value based on these decomposed signals. The degree centrality metric is used to evaluate the characteristics of the spatially embedded networks. Our results re‐establish known SST regions that have a potential connection with the various streamflow regions of Germany. Spatial patterns that resemble the North Atlantic SST tripole‐like pattern is predominant for Alpine streamflow regions at finer timescale. Equatorial Atlantic Mode regions observed for Atlantic streamflow at interannual timescale and Vb weather system connected regions in the Mediterranean Sea have appeared for all the streamflow regions of Germany. Besides, continental streamflow regions exhibited combined characteristics of the Alpine and Atlantic streamflow spatial patterns. In addition to the above regions, we also identify the scale‐specific patterns in the Pacific, Indian and Southern Ocean regions at different timescales. [ABSTRACT FROM AUTHOR]

In recent years, distributed denial of service (DDoS) attacks pose a serious threat to network security. How to detect and defend against DDoS attacks is currently a hot topic in both industry and academia. There have been a lot of methodologies and tools devised to detect DDoS attacks and reduce the damage they cause. Still, most of the methods cannot simultaneously achieve efficient detection with a small number of false alarms. In this case, deep learning techniques are appropriate and effective algorithm to categorize both normal and attacked information. Hence, a novel a feature selection-whale optimization algorithm-deep neural network (FS-WOA–DNN) method is proposed in this research article to mitigate DDoS attack in effective manner. Initially, pre-processing step is carried out for the input dataset where min–max normalization technique is applied to replace all the input in a specified range. Later on, that normalized information is fed into the proposed FS-WOA to select the optimal set of features for ease the classification process. Those selected features are subjected to deep neural network classifier to categorize normal and attacked data. Further to enhance the security of proposed model, the normal data are secure with the help of homomorphic encryption and are securely stored in the cloud. The proposed algorithm will be simulated using the MATLAB tool and tested experimentally that shows 95.35% accuracy in detecting DDoS attack. [ABSTRACT FROM AUTHOR]

Drought is a natural disaster affects water resources, agriculture, and social and economic development due to its long-term and frequent occurrence. It is crucial to characterize and monitor drought and its propagation to minimize the impact. However, spatiotemporal assessment of drought characteristics over India at the sub-basin scale based on terrestrial water storage is unexplored. In this study, the Terrestrial water storage anomalies (TWSA) obtained from a Gravity Recovery and Climate Experiment and precipitation data are used to characterize the propagation of drought. Combined Climatological Deviation Index (CCDI) and GRACE-Drought Severity Index (GRACE-DSI) were computed as CCDI utilizes both precipitation and TWSA data while GRACE-DSI uses only TWSA data. Our results showed that GRACE-DSI exhibits significant negative trends over most of the Indian sub-basins compared to CCDI, indicating that most of the drought events are due to depletion of TWS. While other sub-basins show changing trends for GRACE-DSI and CCDI. The number of sub-basins showing significant negative trends for GRACE-DSI is more than that for CCDI. Hence TWS is depleting for most of the subbasins in India. Our results show that Indo-Gangetic plains face many drought events during 2002–2004, 2009–2014 & 2015–2017. Maximum drought duration and drought severity obtained for the area of North Ladakh (not draining into Indus basins) by GRACE-DSI are 26 months (2002–2004) and − 44.2835, respectively. The maximum drought duration and drought severity obtained for the Shyok sub-basin by CCDI is 17 months (2013–2015) and − 13.4392, respectively. Monthly trend analysis revealed that 39 & 23 no. of sub-basins show significant negative GRACE-DSI trends for October and CCDI for November, respectively. At the same time, the seasonal trend shows that total 34 and 14 sub-basins exhibited a significant negative trend at post-monsoon Kharif season for both the GRACE-DSI & CCDI, respectively. [ABSTRACT FROM AUTHOR]

We investigate whether the distribution of maximum seasonal streamflow is significantly affected by catchment or climate state of the season/month ahead. We fit the Generalized Extreme Value (GEV) distribution to extreme seasonal streamflow for around 600 stations across Europe by conditioning the GEV location and scale parameters on 14 indices, which represent the season-ahead climate or catchment state. The comparison of these climate-informed models with the classical GEV distribution, with time-constant parameters, suggests that there is a substantial potential for seasonal forecasting of flood probabilities. The potential varies between seasons and regions. Overall, the season-ahead catchment wetness shows the highest potential, although climate indices based on large-scale atmospheric circulation, sea surface temperature or sea ice concentration also show some skill for certain regions and seasons. Spatially coherent patterns and a substantial fraction of climate-informed models are promising signs towards early alerts to increase flood preparedness already a season ahead. [ABSTRACT FROM AUTHOR]

The tectonically active North Western (NW) Himalaya landscape has evolved out of long-term active gradational interaction of major drainage systems. Landslides act as a primary erosion agent in these landscapes. We analyzed the spatial distribution of landslide occurrences along the Chenab, Beas, Sutlej, Yamuna, Ganga, and Kali rivers catchments in NW Himalaya to characterize landscape attributes. Further, spatial variability across different climatic zones viz., Western Disturbances –Indian Summer Monsoon (WD-ISM) was assessed. Seismicity and geochronological data were used to analyze the impact of bedrock landslides on landscape evolution. The denudation rate of the studied catchments was spatially correlated with exhumation age, precipitation intensity, and topographic variables. The highest probability of frequent landslides occurrence was found in the zones with ~24–32° of slope range, ~800–1200 m of relief range, in 1200–2400 m elevation range, which coincides with the precipitation erosivity range of ~1500–3000 mm/year in NW Himalayan river catchments. These zones also correlate well with the zones of cloudburst occurrences in NW Himalaya. Landslides in the Higher Himalaya, north of the MCT and across westerly dominated catchments such as Chenab, Beas, and Sutlej along the orographic barrier, are primarily triggered by higher tectonic activity. In contrast, landslides adjacent to the MCT in the front of the orographic barrier and across summer monsoon-dominated catchments such as Yamuna, Ganga, and Kali are controlled by litho-tectonics and mainly induced by higher precipitation intensity. It has been observed that catchments dominated by westerlies have a higher mean denudation rate and mean exhumation age than catchments driven by the Indian summer monsoon. [ABSTRACT FROM AUTHOR]

This article exhibits a fiber plasmonic sensor based on a silver (Ag) layer and a silicon nitride (Si3N4) layer with a wide dynamic range of refractive index sensing. The Taguchi (L9) orthogonal array method is applied to optimize the design parameters such as fiber core, sensing region length, and the thickness of Ag/Si3N4 layers. The performance of the structure is investigated for the full-width half maxima (FWHM) as the smaller the better (STB). The smaller FWHM favors accurate detection, high-quality factor, and better sensitive detection of biomolecules. With the use of analysis of variance (ANOVA), it is evident that for the normalized transmitted power, the Ag layer thickness contributes 47.36%, while the Si3N4 layer thickness contributes 0.06% only. Furthermore, the length of the sensing region has the highest dominating factor effect of 53.26% whereas the thickness of the Si3N4 layer has the least dominating factor effect of 6.90% on FWHM. This work has shown the highest sensitivity of 6287 nm/RIU whereas the quality factor and detection accuracy are 873.19 RIU−1 and 87.31 respectively. Hence, Taguchi’s optimization approach is suitable in multilevel optimization of different control factors that lead to the robust design of the fiber SPR sensor. [ABSTRACT FROM AUTHOR]

In remote area industrial systems, energy consumption monitoring is a crucial challenge. As the conventional monitoring methods lack an intelligent approach, the finest energy consumption monitoring is not possible. Hence, Internet of Things (IoT) based monitoring methods have been developed by recent industrial systems. Therefore, in this research, a novel cloud with IoT based energy monitoring technique is developed. The energy parameters of the Computer Numerical Control based milling machine has been gathered using IoT based Current Transducers , Voltage Transducers , and power sensors. The IoT device includes Zigbee or Bluetooth for managing communication between the machine and the monitoring system. Then the obtained data is stored in the cloud storage platform for large scale machine energy data in the windows platform. Later on, the obtained data from cloud storage is processed by the novel Normalized Recursive Least Kalman Filter for event detection processing. Moreover, the feature extraction has been done using the proposed Simplified Principal Component Analysis method. Furthermore, the energy utilization of the machine is monitored over various situations using the proposed novel Dynamic Self-evolving Reasoning based Fuzzy Neural algorithm. The Median Absolute Deviation is estimated for the conditional inference of the system. The software implementation of this work is done in MATLAB. The power consumption of the machine is validated under various cases. Besides, the proposed simulation outcomes are compared with various existing energy monitoring systems for verifying the significance of the developed method. [ABSTRACT FROM AUTHOR]

Background: Children undergoing surgical procedures can experience significant anxiety and distress during the perioperative period. The use of sedative premedication may help to reduce anxiety, minimize the emotional trauma, and facilitate a smooth induction of anesthesia. Midazolam is most commonly used as a premedication agent in children. Dexmedetomidine is a highly selective alpha-2 adrenoreceptor agonist that provides sedation, anxiolysis, and analgesic effects without causing respiratory depression. Aims and Objectives: The aim of the study was to compare intranasally administered dexmedetomidine and oral midazolam for premedication in pediatric patients undergoing cochlear implant surgeries. Materials and Methods: This prospective randomized controlled study included 60 ASA Grade I and II patients between 1 and 6 years of age who underwent cochlear implant surgeries under general anesthesia. Patients were divided into two groups. Group A received 1µg/kg intranasal dexmedetomidine and Group B patients received 0.5 mg/kg oral midazolam 45 min before induction. The pediatric separation anxiety was assessed using the pediatric separation anxiety scale (PSAS) while shifting the patient to operating room (OR) and mask acceptance was assessed by the attending anesthesiologist using mask acceptance scale (MAS) in OR who is blinded to the drug given. Heart rate (HR) and oxygen saturation were monitored till the end of procedure was noted on a pre-structured proforma. Results: The mean PSAS in intranasal dexmedetomidine group was 1.00±0.00, while in the oral midazolam group was 2.10±0.31 (P=0.000). The mean MAS in intranasal dexmedetomidine group was 1.00±0.00, while in the oral midazolam group was 2.13±0.35 (P=0.000). Mean HR (P>0.05), systolic blood pressure (P>0.05), and diastolic blood pressure (P>0.05) were comparable between both the groups. There was a statistically significant association seen between sedation grade and the groups (P=0.000), showing that groups are dependent on the sedation group. There was a statistically significant association seen between wake up behavior grade and the groups (P=0.000), showing that groups are dependent on the wake up behavior grade. Conclusion: Intranasal dexmedetomidine is an effective and safe alternative for premedication in view of parental separation, mask acceptance, hemodynamic stability, and sedation for the children undergoing cochlear implant surgeries under general anesthesia. [ABSTRACT FROM AUTHOR]

Ethiopia witnessed tremendous precipitation variability and extremes linked with large-scale climate anomalies. This study investigated the long-term spatiotemporal trends of precipitation extremes, significant change points, and its teleconnection to climate anomalies. We used a daily CHIRPS gridded precipitation dataset of the past four decades covering from 1981 to 2019. Eight extreme precipitation indices are defined here based on Expert Team on Climate Change Detection and Indices guidelines. We used the Mann–Kendall test, Sen's slope estimator, and Pettitt's test to investigate trends of the precipitation change in terms of the magnitude and change point of time series. Wavelet coherence and correlation coefficient are used to identify the relationship between precipitation extremes and climate indices. Our results show a significantly decreasing trend for the Kiremt season (June to Sept) and Belg season (Feb to May) over southeast Ethiopia. The majority of grid points experience a change in time series during 1990 to 2012. Most precipitation extreme indices show an increasing trend over the south and southwest region, except consecutive wet days (CWD), which shows a decreasing trend at similar locations. The multiscale analysis presents strong coherence between precipitation anomaly and Nino 3.4 and IOD over the south and southeast region. Similarly, spatial correlation shows that IOD and Nino 3.4 are positively correlated to R10mm, R25mm, PRCTOT, Rx5day, R95ptot, and R99ptot over south, southwest, and southeast parts of the country. A negative correlation is observed with CDD for similar locations along with NAO climate index for most precipitation extremes. [ABSTRACT FROM AUTHOR]

River discharge and water level data play a vital role for various hydrological applications worldwide. However, limited availability of in-situ data has drawn attention towards using remote sensing techniques to monitor river flow. Indeed, multi-mission satellite altimetry data has been used to generate stage-discharge rating curves through power-law relations and empirical methods. The validation of hydrodynamic model-based rating curves is missing. We investigate the potential of available altimetry series (Jason 2, Jason 3, Saral/AltiKa, Sentinel 3A and Sentinel 3B) over Mahanadi River to validate the estimated rating curves at virtual stations. The hydrodynamic model (HEC-RAS) was developed and 07 virtual stations were identified for Mahanadi River from Boudh to Mundali Barrage. During calibration (July-October, 2018) and validation (July-October, 2018), Root Mean Square Error (RMSE) and Nash-Sutcliffe Efficiency (NSE) between simulated and in-situ water level was found to be (0.46 m, 0.83) and (0.45 m, 0.76) respectively. The calibrated and validated model was used to generate rating curves at virtual stations. The RMSE ranging between 27 cm to 88 cm was observed between simulated and altimetry water levels, specifying the potential of all the altimeters with varying specifications to validate the rating curves. The rating curves estimated at virtual stations provide a cost-effective tool for monitoring river flows at additional locations, producing discharge time series for various hydrological applications and assessing of contribution of lateral tributaries. [ABSTRACT FROM AUTHOR]

Hydrological model calibration is a quintessential step in model development, and the time scale of calibration depends on the application. However, the implications of choice of time scale of calibration have not been explored extensively. Here, we evaluate the effect of the time scale of calibration on model sensitivity, best parameter ranges, and predictive uncertainty for three river basins using the Soil and Water Assessment Tool (SWAT) model. Multiple models were set up for three different catchments from southern India. Our results showed that the sensitivity of the parameters, best parameter ranges, and model performance are conditioned on the time scale of calibration. The models calibrated at coarser time scales marginally outperformed the models calibrated at fine time scale in terms of Nash-Sutcliffe efficiency and percentage bias. Transfer of parameters across scales (both from coarse to fine and from fine to coarse) have a general tendency to worsen the model performance in all three catchments, with few exceptions. [ABSTRACT FROM AUTHOR]

Background and Aims: Robotic surgeries often require a relatively long duration of pneumo‑peritoneum and trendelenburg position which may accentuate changes in endo‑tracheal tube (ETT) cuff pressure leading to pressure related complications. The aim of this study was to analyze changes in ETT cuff pressures during various stages of pneumo‑peritoneum and surgical positioning and its correlation with airway pressure changes. Material and Methods: A prospective observational study was planned after approval of institutional review board on 60 patients undergoing elective robotic pelvic surgery requiring head down position. Baseline cuff pressure was adjusted to 25 cm H2 O. ETT cuff pressure, peak airway pressure and end tidal CO2 (ETCO2 ) was measured at various time intervals before and after pneumo‑peritoneum and head down. Ventilatory parameters were kept fixed after baseline setting. Those requiring any change were excluded. Pearson’s coefficient was used for correlation and ANOVA for trend of parameters at different time intervals (P value <0.05 was considered significant). Results: Baseline cuff pressure after manual inflation was 46.2 ± 17.4 cm H2 O. Significant correlation was observed between change in cuff pressure and increase in peak airway pressure at the end of the surgery (r = 0.4, P < 0.05). Serial measurements of ETT cuff pressure, peak airway pressure and ETCO2 were significantly increased compared to baseline (P < 0.05). Conclusion: Significant increases in ETT cuff pressure may be seen in robotic surgeries, with a positive correlation between change in cuff pressure and increase in airway pressures. Objective adjusted measurement of cuff pressure and airway pressures is recommended for such surgeries. [ABSTRACT FROM AUTHOR]

The static deflections of the cutting tool and thin-walled components are key sources contributing to the deviation of a machined surface from the design specifications during the end milling operation. The machined surface deviation is expressed using geometric tolerances such as flatness and cylindricity parameters specified as per the Geometric Dimensioning and Tolerancing (GD&T) standard (ASME Y14.5-2009 or ISO 1101). The present work investigates the effect of component configuration, engagement area, and workpiece curvature by comparing geometric errors during the end milling of zero and constant curvature thin-walled components. An integrated computational framework incorporating the mechanistic force model, finite element (FE)-based workpiece deflection model, cantilever beam formulation-based tool deflection model, and particle swarm optimization (PSO)-based geometric tolerance estimation model has been adopted from the previous work of authors. The effect of component geometry and cutter-workpiece transition are investigated on the geometric tolerance (flatness and cylindricity) by conducting computational studies and machining experiments under identical cutting conditions. The concept of "Equivalent Radial Depth of Cut (RDOC)" is introduced to derive component configurations with the identical cutter-workpiece transition area. The influence of workpiece curvature on the geometric tolerance parameters is also investigated in the paper. The outcomes are substantiated by performing computational studies and machining experiments. It is recognized that the relatively enhanced stiffness of the curved components offers an inherent machining advantage in comparison to straight components to the process planners. [ABSTRACT FROM AUTHOR]

Climate change and urbanization are significantly magnifying flood hazard, leading to a greater vulnerability of urban concentrations. This paper investigates the impact of climate change on urban flooding using future projected rainfall data and a calibrated hydraulic model. Two urban watersheds in Delhi, India (the Qudesia Nallah catchment and the Jahangirpuri drain catchment) are considered to evaluate the climate change impact on urban flooding. Regional climate models (RCMs) are used to project future precipitation, which is then utilized by the hydraulic model to evaluate the impact on flooding. Climate data from three RCMs extracted from the Coordinated Regional Climate Downscaling Experiment (CORDEX) are used to study the impact of climate change for historical (1990–2016) and future scenario (Representative Concentration Pathway (RCP) 4.5, 2021–2100). The rainfall projections are fed as 2-, 5-, 10-, and 20-year return periods to a calibrated hydrodynamic Storm Water Management Model (SWMM). The results show that the flooded nodes vary between 2–6 and 12–43, respectively, in the Qudesia Nallah catchment and the Jahangirpuri drain catchment under present conditions but increase from 11 to 51 and 42 to 91, respectively, for future climate conditions. The results suggest that the risk of occurrence of flooding, duration, and frequency in the two study areas will increase in the future when compared to those under the present conditions. The results also indicate that the damage induced by the 20-year return period rainfall at the present time will likely be caused just by the 2-year return period in the future. This is due to the greater likelihood of rainfall extremes in the region. The potential flooding sites identified in this study will provide the urban municipalities with substantive information to perform ameliorative strategies. [ABSTRACT FROM AUTHOR]

The quantification of spatial propagation of extreme precipitation events is vital in water resources planning and disaster mitigation. However, quantifying these extreme events has always been challenging as many traditional methods are insufficient to capture the nonlinear interrelationships between extreme event time series. Therefore, it is crucial to develop suitable methods for analyzing the dynamics of extreme events over a river basin with a diverse climate and complicated topography. Over the last decade, complex network analysis emerged as a powerful tool to study the intricate spatiotemporal relationship between many variables in a compact way. In this study, we employ two nonlinear concepts of event synchronization and edit distance to investigate the extreme precipitation pattern in the Ganga river basin. We use the network degree to understand the spatial synchronization pattern of extreme rainfall and identify essential sites in the river basin with respect to potential prediction skills. The study also attempts to quantify the influence of precipitation seasonality and topography on extreme events. The findings of the study reveal that (1) the network degree is decreased in the southwest to northwest direction, (2) the timing of 50th percentile precipitation within a year influences the spatial distribution of degree, (3) the timing is inversely related to elevation, and (4) the lower elevation greatly influences connectivity of the sites. The study highlights that edit distance could be a promising alternative to analyze event-like data by incorporating event time and amplitude and constructing complex networks of climate extremes. [ABSTRACT FROM AUTHOR]

Model error (or model uncertainty) were probabilistically characterized for modified compression field theory (MCFT) Simplified and General Method approaches using experimental databases that contained reinforced concrete (RC) beams having shear failures with and without stirrups (168 and 368 specimens, respectively). It was found that when compared to the design shear model currently used in ACI‐318, the General Method produced low model error variability indicating better consistency for the determination of shear strength. Structural reliabilities were then calculated for RC beams in shear designed to MCFT General Method (AASHTO LRFD, CSA A23.3‐14, AS3600‐2018) for a live‐to‐dead load ratio between 0 and 5, and for capacity reduction factor ϕ = 0.70, 0.75, and 0.80. It was concluded that the ϕ‐factor for shear failure for Australian standards can be increased from 0.70 to 0.75 for RC beams with stirrups, providing a 7.1% increase in the design shear capacity and contributing to sustainable design and reduction in greenhouse gas emissions due to more efficient usage of materials. [ABSTRACT FROM AUTHOR]

Globally, mountain systems are unevenly exposed to risks of extreme precipitation. Within the Himalayan region, precipitation extremes are a rising concern, but their current understanding is limited. In this study, we use 113 years of precipitation data to rank and characterize precipitation extremes in the Indian Western Himalayas (IWH). Our statistical ranking method integrates precipitation spatial extent and its intensity across different durations for determining the severity of extreme events. The proposed ranking method accounts for multi‐day duration ranking method to capture persistent precipitation episodes. Results show that the method accurately detects and ranks the most extreme precipitation events that occurred in the IWH and indicate locations of these events. Our results highlight that critical long duration events in the region (e.g., 10 days) are missed at ranks at shorter duration (e.g., 2–3 days), thereby highlighting the importance to multi‐day precipitation extremes ranking. In addition, the proposed ranking method provides information about the event duration that will be associated with the highest impact on society, carrying high significance. Our findings are valuable for flood risk management and disaster risk reduction. [ABSTRACT FROM AUTHOR]

This paper aims to analyze mode shapes and corresponding strain distribution in a two-dimensional plane structure exhibiting flow-induced vibration in the wake field of four different upstream bluff bodies such as cylinder, square, triangle, and D-shape. This research is important from the point of view of flow-induced piezoelectric energy harvesting; wherein, induced strain in the structure is directly related to the amount of energy generated. Mainly, all investigations are carried out at low Reynolds number (Re = 200); however, to widen the scope of the work, other Reynolds numbers are also considered (Re = 300, 500, and 750). The results obtained indicated that the plane structure vibrates in different mode shapes under different wake fields. The square section dominantly gives rise to the fundamental mode vibration, whereas, cylinder, D-shape, and triangular bluff body induce vibration in a mix of fundamental and higher bending modes. Analysis of the corresponding flow regime shows that the position of reattachment point of the downstream shear layer plays an important role in the realization of different vibration modes. The strain distribution under different cases revealed that the wake of a cylindrical bluff body produces highest peak strain, and D-shape bluff body results in highest cumulative strain. From the aspect of energy harvesting, a quantitative comparison of strain-induced and per second charge generation have indicated that for an equivalent flow condition, the D-shape will produce higher energy per unit time than the cases of a square, cylinder, and triangular cross-sections. [ABSTRACT FROM AUTHOR]

Adequate and efficient precipitation data is a major concern due to its spatiotemporal variability and topographic and climatic factors. Satellite-based products are an alternative for a reliable precipitation estimate in basins having a complicated topography and diverse climate zones. Satellite products with global coverage and continuous data are freely available; however, understanding spatial connections is essential for reliable hydrological applications. In this study, complex network concepts like clustering coefficient, degree, degree distribution, average neighbour and architecture employed to investigate spatial connections in a basin. We also identified influential grid points in the precipitation network using weighted degree betweenness. Our results reveal that the correlation method does not significantly affect the network topology. However, the correlation threshold influences the spatial distribution of the clustering coefficient and degree values of precipitation network. The spatial distribution of clustering coefficient and degree indicated an inverse relationship independent of similarity measures and correlation thresholds. The architecture of precipitation based on satellite and observed data shows small-world behaviour for the certain correlation threshold range. Our findings unravel spatial precipitation connections and provide a way for hydrological applications in further research. [ABSTRACT FROM AUTHOR]

Wetlands in urban ecosystems provide significant environmental benefits. In the present study, the concept of urban constructed wetland development is studied from the viewpoint of urban planning with dynamic water level orifice setting controller. A two-step modelling procedure is carried out: (1) development of a hybrid model, by coupling a well-established two-dimensional hydrodynamic model (International River Interface Cooperative, iRIC) with a one-dimensional physically-based, distributed-parameter model (Storm Water Management Model, SWMM), to compute and map flood scenarios and to identify the flood-prone areas; and (2) use of SWMM to simulate the water inflow to the proposed constructed wetland, which acts as a cushion for storing excess flood water. The proposed methodology is implemented on the Jahangirpuri drain catchment located in Delhi, India. Results show that the hybrid model is effective, and the simulations are observed to be in good agreement with the recorded data, which assist in detecting the flood-prone areas. Further, an estimation of the impact of the proposed constructed wetland on catchment hydrology indicates an overall reduction of 23% in flooding adjacent to the channel with a significant reduction in backflow as well as water depth in the drain. The flapgate at the outlet of the wetland helps in maintaining the desired water depth in the wetland. The outcomes of this study will assist the hydrologists and administrators in urban stormwater management and planning to mitigate the impact of floods in urban watersheds. [ABSTRACT FROM AUTHOR]

Purpose: Definitive antiviral treatment is not available for COVID-19 infection, with the exception of remdesivir, which still evokes many doubts. Various monotherapy or combination therapies with antivirals or other agents have been tried. The present study aims to evaluate the therapeutic potential of hydroxychloroquine and lopinavir–ritonavir in combination with ribavirin in mild–severe COVID-19. Patients and Methods: A single-center, open-label, parallel-arm, stratified randomized controlled trial evaluated the therapeutic potential of combination antiviral therapies. Enrolled patients in the severe category were randomized into three groups: (A) standard treatment, (B) hydroxychloroquine+ribavirin+standard treatment, or (C) lopinavir+ritonavir+ribavirin+standard treatment; while the non-severe category comprised two groups: (A) standard treatment or (B) hydroxychloroquine+ribavirin. Combination antivirals were given for 10 days and followed for 28 days. The primary endpoints were safety, symptomatic and laboratory recovery of organ dysfunctions, and time to SARS-CoV-2 RT-PCR negative report. Results: In total, 111 patients were randomized: 24, 23, and 24 in severe categories A, B, and C, respectively, and 20 in each of the non-severe groups. Two patients receiving ribavirin experienced drug induced liver injury, and another developed QT prolongation after hydroxychloroquine. In the severe category, 47.6%, 55%, and 30.09% in A, B, and C groups, respectively, showed symptomatic recovery, compared to 93.3% and 86.7% in A and B groups, respectively, in the non-severe category at 72 hours (P 0.05). Conclusion: Though the results failed to show statistical superiority of the antiviral combination therapies to that of the standard therapy in both the severe and non-severe categories in symptomatic adult patients of COVID-19 due to very small sized trial, clinically hydroxychloroquine+ribavirin therapy is showing better recovery by 7.4% than standard therapy in the former category. However, results do indicate the benefit of standard therapy in the non-severe category by 6.6%. Furthermore, the dose of ribavirin needs to be reconsidered in the Indian population. [ABSTRACT FROM AUTHOR]

Compound extremes exhibit greater adverse impacts than their univariate counterparts. Studies have reported changes in frequency and the spatial extent of extremes in India; however, investigation of compound extremes is in the infancy state. This study investigates the historical variation of compound dry and hot extremes (CDHE) and compound wet and cold extremes (CWCE) during the Indian summer monsoon period from 1951 to 2019 using monthly data. Results are analyzed for 10 identified homogeneous regions for India. Our results unravelled that CDHE (CWCE) frequency has increased (decreased) by 1–3 events per decade for the recent period (1977–2019) relative to the base period (1951–1976). Overall, the increasing (decreasing) pattern of CDHE (CWCE) is high across North-central India, Western India, North-eastern India and South-eastern coastlines. Our findings help in identification of the parts of the country affected by frequent and widespread CDHE during the recent period, which is alarming. More detailed assessments are required to disentangle the complex physical process of compound extremes to improve risk management options. [ABSTRACT FROM AUTHOR]

Background: The alveolar--arterial oxygen (A--a) gradient measures the difference between the oxygen concentration in alveoli and the arterial system, which has considerable clinical utility. Materials and methods: It was a retrospective, observational cohort study involving the analysis of patients diagnosed with acute COVID pneumonia and required noninvasive mechanical ventilation (NIV) over a period of 3 months. The primary objective was to investigate the utility of the A--a gradient (pre-NIV) as a predictor of 28-day mortality in COVID pneumonia. The secondary objective included the utility of other arterial blood gas (ABG) parameters (pre-NIV) as a predictor of 28-day mortality. The outcome was also compared between survivors and nonsurvivors. The outcome variables were analyzed by receiver-operating characteristic (ROC) curve, Youden index, and regression analysis. Results: The optimal criterion for A--a gradient to predict 28-day mortality was calculated as ≤430.43 at a Youden index of 0.5029, with the highest area under the curve (AUC) of 0.755 (p <0.0001). On regression analysis, the odds ratio for the A--a gradient was 0.99. A significant difference was observed in ABG predictors, including PaO2, PaCO2, A--a gradient, AO2, and arterial--alveolar (a--A) (%) among nonsurvivors vs survivors (p-value <0.001). The vasopressor requirement, need for renal replacement therapy, total parenteral requirement, and blood transfusion were higher among nonsurvivors; however, a significant difference was achieved with the vasopressor need (p <0.001). Conclusion: This study demonstrated that the A--a gradient is a significant predictor of mortality in patients initiated on NIV for worsening respiratory distress in COVID pneumonia. All other ABG parameters also showed a significant AUC for predicting 28-day mortality, although with variable sensitivity and specificity. [ABSTRACT FROM AUTHOR]