bluuebunny/crossref_metadata_2025_split huggingface dataset:
The double‐edged sword of systemic corticosteroid therapy in viral pneumonia: A case report and comparative review of influenza‐associated mucormycosis versus COVID‐19 associated mucormycosis
Authors: Ahmadikia Kazem , Hashemi Seyed Jamal , Khodavaisy Sadegh , Getso Muhammad Ibrahim , Alijani Neda , Badali Hamid , Mirhendi Hossein , Salehi Mohammadreza , Tabari Azin , Mohammadi Ardehali Mojtaba , Kord Mohammad , Roilides Emmanuel , Rezaie Sassan 
Published: February 2021

AbstractAcute respiratory distress syndrome is a common complication of severe viral pneumonia, such as influenza and COVID‐19, that requires critical care including ventilatory support, use of corticosteroids and other adjunctive therapies to arrest the attendant massive airways inflammation. Although recommended for the treatment of viral pneumonia, steroid therapy appears to be a double‐edged sword, predisposing patients to secondary bacterial and invasive fungal infections (IFIs) whereby impacting morbidity and mortality. Mucormycosis is a fungal emergency with a highly aggressive tendency for contiguous spread, associated with a poor prognosis if not promptly diagnosed and managed. Classically, uncontrolled diabetes mellitus (DM) and other immunosuppressive conditions including corticosteroid therapy are known risk factors for mucormycosis. Upon the background lung pathology, immune dysfunction and corticosteroid therapy, patients with severe viral pneumonia are likely to develop IFIs like aspergillosis and mucormycosis. Notably, the combination of steroid therapy and DM can augment immunosuppression and hyperglycaemia, increasing the risk of mucormycosis in a susceptible individual. Here, we report a case of sinonasal mucormycosis in a 44‐year‐old woman with hyperglycaemia secondary to poorly controlled diabetes following dexamethasone therapy on a background of influenza pneumonia and review 15 available literatures on reported cases of influenza and COVID‐19 associated mucormycosis.
Sinus rhythm heart rate increase after atrial fibrillation ablation is associated with lower risk of arrhythmia recurrence
Authors: Killu Ammar M. , Witt Chance M. , Sugrue Alan M. , Vaidya Vaibhav , Monahan Kristi H. , Barnes Stephanie , Lenz Charles J. , Yogeswaran Vidhushei , Sun Philip Y. , Hodge David O. , Friedman Paul A. , Packer Douglas L. , Asirvatham Samuel J. 
Published: February 2021

AbstractBackgroundPulmonary vein isolation (PVI) with autonomic modulation may be more successful than PVI alone for atrial fibrillation (AF) ablation and may be signaled by changes in sinus rhythm heart rate (HR) post ablation. We sought to determine if a change in sinus rhythm HR predicted AF recurrence post PVI.MethodsPatients who underwent AF ablation from 2000 to 2011 were included if sinus rhythm was noted on ECG within 90 days pre and 7 days post ablation. Basic ECG interval and HR changes were analyzed and outcomes determined.ResultsA total of 1152 patients were identified (74.3% male, mean age 57 ± 11 years). Mean AF duration was 5.2 ± 5.3 years. Paroxysmal AF was noted in 712 (61.8%) of the patients. Mean EF was 61% ± 6%. Sinus rhythm HR was 61 ± 11 pre‐ablation and 76 ± 13 bpm post‐ablation (27% ± 24% increase, p < .001). The ability of relative HR change post‐ablation to predict AF recurrence was borderline (hazard ratio 0.65 [0.41–1.01], p = .067). With patients separated into quartiles based on the relative HR change, the upper quartile with the largest relative increase in HR had a significantly lower rate of AF recurrence compared to the lowest quartile following multi variable modeling (p = .038). There were significant changes in PR (171 ± 28 to 167 ± 30 ms) and QTc (424 ± 25 to 434 ± 29 ms) intervals (both p < .001) but these were not predictive of outcome.ConclusionRelative changes in HR post AF ablation correlates with AF recurrence. Further prospective studies are needed to confirm this relationship.
COVID‐19 antibody screening with SARS‐CoV‐2 red cell kodecytes using routine serologic diagnostic platforms
Authors: Nagappan Radhika , Flegel Willy A. , Srivastava Kshitij , Williams Eleanor C. , Ryzhov Ivan , Tuzikov Alexander , Galanina Oxana , Shilova Nadezhda , Sukhikh Gennady , Perry Holly , Bovin Nicolai V. , Henry Stephen M. 
Published: February 2021

AbstractBackgroundThe Coronavirus disease 2019 (COVID‐19) pandemic is having a major global impact, and the resultant response in the development of new diagnostics is unprecedented. The detection of antibodies against severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has a role in managing the pandemic. We evaluated the feasibility of using SARS‐CoV‐2 peptide Kode Technology‐modified red cells (C19‐kodecytes) to develop an assay compatible with existing routine serologic platforms.Study Design and MethodsA panel of eight unique red cells modified using Kode Technology function‐spacer‐lipid constructs and bearing short SARS‐CoV‐2 peptides was developed (C19‐kodecyte assay). Kodecytes were tested against undiluted expected antibody‐negative and ‐positive plasma samples in manual tube and three column agglutination technology (CAT) platforms. Parallel analysis with the same peptides in solid phase by enzyme immunoassays was performed. Evaluation samples included >120 expected negative blood donor samples and >140 COVID‐19 convalescent plasma samples, with independent serologic analysis from two centers.ResultsSpecificity (negative reaction rate against expected negative samples) in three different CAT platforms against novel C19‐kodecytes was >91%, which correlated with published literature. Sensitivity (positive reaction rate against expected positive convalescent, PCR‐confirmed samples) ranged from 82% to 97% compared to 77% with the Abbott Architect SARS‐CoV‐2 IgG assay. Manual tube serology was less sensitive than CAT. Enzyme immunoassay results with some Kode Technology constructs also had high sensitivity.ConclusionsC19‐kodecytes are viable for use as serologic reagent red cells for the detection of SARS‐CoV‐2 antibody with routine blood antibody screening equipment.
El legado internacional de los megaeventos deportivos en Brasil: lecciones políticas y económicas para los países de la semiperiferia
Authors: Pulleiro Méndez Carlos 
Published: February 2021

Después de una década de intereses políticos y económicos compartidos en la organización de megaeventos deportivos por parte de los estados semiperiféricos y las federaciones deportivas internacionales, el caso de Brasil, con la organización de la Copa Mundial FIFA en 2014 y los Juegos Olímpicos de Río de 2016, ha cambiado la dinámica de esta relación.
Por un lado, los estados de la semiperiferia han conformado los riesgos asociados con la organización de megaeventos deportivos respecto a la desestabilización política, económica y social del país. Por otro lado, la incapacidad de los megaeventos deportivos para generar los legados positivos que fueran prometidos durante la fase de candidatura ha generado cuestionamientos respecto al rol de las organizaciones deportivas y sus campeonatos como herramientas de desarrollo.
Ordinate Systems for Quadratures Similar to Tchebycheff’s Ordinates
Authors: Karelitz George B. 
Published: February 2021

Abstract
The author presents a geometrical interpretation of Tchebycheff’s rule for calculating quadratures and shows that other systems of ordinates can be chosen which will be as valid as Tchebycheff’s. A system of ordinates is proposed, the virtue of which lies in the fact that the longitudinal location of the center of gravity of the ship’s lines can be obtained with good accuracy without increasing the errors of area calculations.
Distributed Gravity and Temperature Loading in Two-Dimensional Elasticity Replaced by Boundary Pressures and Dislocations
Authors: Biot M. A. 
Published: February 2021

Abstract
This paper deals with two-dimensional stresses due to an important class of body forces. Gravity stresses and temperature stresses are produced by body forces of the type investigated.
In the case of gravity stresses it is proved that these stresses may be calculated by forgetting about the action of gravity on the body and applying instead only external normal loads that are identical with a hydrostatic pressure.
This opens the possibility of applying photoelastic tests to the measurement of gravity stresses; a model loaded by these external pressures would show an isochromatic fringe pattern identical with the one that would appear in a model submitted to an intense gravity field. In Fig. 5 is shown the type of external loading to be applied to find the gravity stresses in a dam.
In the case of two-dimensional temperature stress in cylindrical bodies where the temperature distribution is stationary, it is shown that a distinction is to be made between solid and hollow cylinders. For a solid cylinder the only thermal stress component appearing is an axial stress acting perpendicularly to cross-sectional planes. In other words, the solid cylinder expands freely along the cross-sectional planes. For a hollow cylinder a general stress condition may arise which is identical with the stresses produced by cutting a longitudinal slit of a certain small width in the cylinder wall and sticking together the two sides of the slit (dislocation).
Film Lubrication in Sleeve Bearings
Authors: Stone M. 
Published: February 2021

Abstract
The author discusses the design of bearings as based on fluid friction in hydrodynamic films and investigates the limiting design factors in such bearings. He points out that the thickness of the oil film is dependent on the viscosity of the lubricant alone and that this thickness may be controlled, thus making it possible to base the design of a bearing on a minimum thickness of the oil film. Two appendixes conclude the report, one which presents simplified theoretical considerations for the design of film-lubricated bearings while the other explains the highly accurate electromagnetic micrometer used for determining shaft positions in the bearing.
Journal Bearing Performance
Authors: Baudry R. , Tichvinsky L. M. 
Published: February 2021

Abstract
This paper contains an application of the hydrodynamical theory of lubrication to the practical design of journal bearings. In a simplified method satisfactory for most engineering applications the authors consider the journal bearing as a plane bearing. Then correction factors make allowance for (1) the type of the journal bearing, (2) the shape of the oil film and width-length ratio of the bearing, and (3) the losses in the nonactive parts of the bearing.
In a more accurate method, the same correction factors are applied to the rather complete data published on journal bearings of infinite width. It is also shown that the clearance of the bearing can vary between rather large values and still maintain closely optimum conditions of performance of the bearing. Results of tests are shown to be in close agreement with these methods of calculation.
A Method of Harmonic Analysis
Authors: Lewis Frank M. 
Published: February 2021

Abstract
The method of harmonic analysis described in this paper is of the selected ordinate type. It is similar to the Fischer Hinnen analysis in that a different spacing of ordinates is used for each harmonic component to be determined, and no multiplications are necessary. The basis of derivation is the assumption that the curve to be analyzed can be replaced by a parabola passing through certain ordinates in each half period of the harmonic component. A spacing of these ordinates is then found such that the sum of the ordinates is proportional to the harmonic component of the parabolas replacing the original curve.
Spacings have been determined for 3, 5, and 7 ordinates per half period, corresponding to parabolas of second, fourth, and sixth orders. In the five and seven ordinate rules it is necessary to use a multiplying factor of 1/2 for the end ordinates.
In use a set of transparent charts with the ordinates for each component are constructed. Laid over the curve to be analyzed, the ordinates can be quickly summed on a strip of paper.
The accuracy of the method is relatively high and in use it is of the utmost simplicity, so that with a set of charts once prepared, correct results can be obtained by the most unskilled computer.
Predicting Track Geometry Defect Probability Based on Tie Condition Using Pattern Recognition Technique
Authors: Alsahli Ali , Zarembski Allan M. , Attoh-Okine Nii 
Published: February 2021

Abstract
Rail transportation plays a vital role in U.S. transportation. According to the National Transportation Statistics report from the Bureau of Transportation Statistics, railroads generate 29% of ton-miles of freight, whereas air, truck, water, and pipeline transportation represent the rest of the freight traffic. In the passenger spectrum, the 2016 National Transit Summary and Trends report stated that trips using rail transit modes increased from 2012 to 2016. These facts show the importance of rail transportation in the United States and highlight the critical importance of railroad traffic safety. Based on the FRA 2016 statistics, track-related defects are the second-largest cause of rail accidents. Furthermore, track irregularities resulting from defects in these parameters lead to an increase in dynamic forces that accelerate the rate of track deterioration. Consequently, the need to monitor and detect the presence and types of defects on railway tracks arises. The availability of track geometry cars and autonomous visual inspection vehicles has made acquiring track information easier. However, the need to study and understand these data remains unfulfilled. Machine learning has recently started to gain popularity in the field of railroad research due to increasing computational capacity and the need for such tools to provide information that is more useful. Techniques such as deep convolutional neural networks (DCNN), artificial neural networks, and support vector machines have been used for prediction problems in railroad research.
This paper combines engineering judgments and statistical analysis to develop analytical models to estimate the probability of developing geometry defects as a function of tie conditions. The analysis is based on data provided by Georgetown Rail’s AURORA tie inspection system and from a major US class 1 railroad track geometry cars. The data used in this analysis relates to a geometry defect dataset and a tie condition dataset. The geometry dataset covers 125,554 geometry defects taken from several years of track-geometry inspection data. The data collection period was from 2014 to 2016. Convolutional neural network models were developed to estimate the probability of defects given tie patterns, as well as the outputs of the models used to build multiple regression models. Additionally, various data analysis issues were addressed in this paper. This paper’s contribution includes predictive models of track geometry defects as a function of tie condition and position. The models provide approaches to predicting the probability of geometry defects as functions of tie conditions and positions.
Calculation of Convective and Radiative Heat Transfer Coefficient Using Thermography During a Physical Exercise
Authors: Gurupatham Sathish K. , Velumani Priyanka , Vaidhya Revathy 
Published: February 2021

Abstract
A detailed model of human thermoregulation and a numerical algorithm to predict thermal comfort is a novel field of research and has wide applications in the auto/transportation industry and in the heating, ventilating, and air-conditioning (HVAC) industry. Anatomically specific convective and radiative heat transfer coefficients for the human body will be required to understand the human thermal physiological and comfort models. It necessitates to create hygienic and thermally comfortable spaces for the best productivity of the users. The physiological nature of thermal comfort during a transient condition such as a physical exercise or travel in an automobile are not yet well understood. In this paper, thermography has been applied to measure the convective and radiative heat transfer coefficients which has not been done before. Three different recovery processes were considered after the running of a human model on a treadmill with a range of speeds starting from 2 miles/hour to 10 miles/hour for stretch of twenty minutes. The recovery process included, (a) fan-assisted cooling with an air velocity of 0.5 m/s for 30 minutes, (b) fan-assisted cooling with an air velocity of 1.5 m/s for 30 minutes, and (c) natural cooling with no assistance of fan for 30 minutes. Thermal images were taken for forehead, trunk, arms, hands, legs of the models and the convective heat transfer coefficient and radiative heat transfer coefficient were calculated. The human models included both male and female, and belonged to two different age groups of less than 15 and above 40 with a total of 24 participants. The results show that though the temperatures, measured using thermography, for various parts of the human body changed locally, the overall calculated radiative heat transfer coefficients matched with the ASHRAE handbook values, and the calculated convective heat transfer coefficient increased with the increase of air velocity, while the models cooled down after the workout. Interestingly, the skin temperature decreased, initially, as the exercise progressed. After the completion of exercise, the skin temperature exhibited a quick rise during the recovery period with a subsequent decrease in the temperature, later. This trend was the same with all different age groups and sex of the models. The results also confirm that thermal images can be relied on for calculating the convective and radiative heat transfer coefficients of the human body to determine the heat transfer rate.
Deep Learning for Intelligent Bubble Size Detection in the Spallation Neutron Source Visual Target
Authors: Rasheed Fayaz , Dominguez-Ontiveros Elvis E. , Weinmeister Justin R. , Barbier Charlotte N. 
Published: February 2021

Abstract
The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) will undergo proton power upgrade (PPU), increasing the proton beam power from 1.4 MW to 2.8 MW. From 2.8 MW, 2.0 MW will go to the current First Target Station and the rest will go to the future Second Target Station (STS). The First Target Station uses a liquid mercury target that is contained in a 316L stainless steel vessel. The proton beam is pulsed at 60 Hz, with a pulse of about 0.7μs. When the proton beam hits the target, the intense energy deposition leads to a rapid rise in temperature in the mercury. This temperature rise creates pressure waves that propagate through the mercury and cause cavitation erosion. The power upgrade will cause stronger pressure waves that will further increase damage because of cavitation. Injecting small helium bubbles in the mercury has been an efficient method of mitigating the pressure wave at 1.4 MW. However, at higher power, additional mitigation is necessary. Therefore, the 2 MW target vessel will be equipped with swirl bubblers and an additional gas injection port near the nose to inject more gas in the target. To develop a gas injection strategy and design, flow visualization in water with a transparent prototypical target (“visual target”) was performed. Bubble sizes and their spatial distribution in the flow loop are crucial to understanding the effectiveness of the bubbles in mitigating pressure waves. Bubbles were generated in the visual target under varied conditions of input pressures with helium and air. Images were captured using a high-speed camera at varied frame rates at different positions away from the swirl bubbler and different depths in the flow loop under varying lighting conditions. Initially, methods such as circular Hough transforms were applied after a series of images processing to obtain a general distribution of bubble sizes. Bubbles smaller than 500 μm are preferred to effectively mitigate the effect of pressure waves, which demands an accurate bubble detection and sizing system. Intelligent detection and identification of bubble sizes alleviate misdetection and improves accuracies. Employing neural networks, intelligent detection of bubble sizes and their distribution was developed and provides a robust alternative to traditional techniques. Human intervention was employed to label in-focus and out-of-focus bubbles in the set of training images. An object detection network using a pretrained convolutional neural network was created that extracted the features from the training images. Data augmentation was used to improve network accuracy through a random transformation of the original data.
Efficiency Centered Maintenance of Preheat Train of a Crude Oil Distillation Unit
Authors: Fajardo J. , Yabrudy D. , Barreto D. , Negrete C. , Sarria B. , Cardona C. 
Published: February 2021

Abstract
Nowadays, maintenance is based on the synergistic integration of operational reliability and timely maintenance, which guarantees the required availability and optimal cost. Operational reliability implies producing more, better performance, longer life, and availability. Timely maintenance involves the least time out of service, fewer maintenance costs, fewer operating costs, and less money. In this work, we study the preheating train of a crude distillation unit of a refinery, which processes 994 m3/h, which presents a formation of a fouling layer inside it. Among the impacts of fouling is the reduction in the effectiveness of heat transfer, the increase in fuel consumption, the increase in CO2 emissions, the increase in maintenance costs, and the decrease in the profit margin of process. An appropriate cleaning program of the surface of the heat exchanger network is necessary to preserve its key performance parameters, preferably close to design values. This paper presents the maintenance method centered on energy efficiency, to plan the intervention of the preheating train equipment maintenance, which considers the economic energy improvement and the cost of the type of maintenance. The method requires the calculation of the fouling evolution from which the global heat transfer coefficient is obtained, and the heat flux is determined as a function of time. It was observed that, as time passes, the resistance provided by fouling increases and that the overall heat transfer coefficient decreases. The energy efficiency centered maintenance has an indicator of economic justification (factor J) that relates the economic-energy improvement achieved when performing maintenance, taking into account the economic effort invested. Depending on the cost of the type of maintenance to be performed, a threshold should be chosen, from which the maintenance activity is justified. The effectiveness values of the heat exchanger (ε) and the J indicator are used to form a criticality matrix, which allows prioritizing maintenance activities in each equipment. The planning of the implementation dates of the maintenance of each heat exchanger, from the maintenance method centered on energy efficiency applied to the crude distillation unit’s, preheat train, constitutes a contribution in this specific field. The conceptual design of the maintenance method centered on energy efficiency presented in this work is feasible for other heat transfer equipment used in oil refineries and industry in general. The procedure developed uses real operation values, and with its implementation, a saving of 150000 US dollars was achieved.