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Clinical characteristics and risk factors of liver injury in COVID-19: a retrospective cohort study from Wuhan, China

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HEPATOLOGY INTERNATIONAL 2020年第5期14卷 723-732页

作者： Wang, Ming Yan, Weiming Qi, Weipeng Wu, Di Zhu, Lin Li, Weina Wang, Xiaojing Ma, Ke Ni, Ming Xu, Dong Wang, Hongwu Chen, Guang Yu, Haijing Ding, Hongfang Xing, Mingyou Han, Meifang Luo, Xiaoping Chen, Tao Guo, Wei Xi, Dong Ning, Qin Huazhong Univ Sci & Technol Tongji Hosp Tongji Med Coll Dept & Inst Infect Dis Wuhan 430030 Peoples R China Huazhong Univ Sci & Technol Tongji Hosp Tongji Med Coll Dept Paediat Wuhan Peoples R China

Background Coronavirus disease 2019 (COVID-19) has rapidly become a major international public health concern. This study was designed to evaluate the clinical characteristics and risk factors of COVID-19-associated liver injury. Methods A fraction of 657 COVID-19 patients were retrospectively analyzed. Clinical and laboratory data were derived from electronic medical records and compared between patients with or without liver injury. multivariate logistic regression method was used to analyze the risk factors for liver injury. Results Among 657 patients, 303 (46.1%) patients had liver injury with higher rate in severe/critically ill patients [148/257 (57.6%)] than those in moderate cases [155/400 (38.8%)]. The incidence of liver injury was much higher in male [192/303 (63.4%)] than female [111/303 (36.6%)], and in severe/critical patients [148/303 (48.8%)] with percutaneous oxygen saturation <= 93% [89/279 (31.9%)] or peak body temperature >= 38.5 degrees C [185/301 (61.5%)] on admission. Liver injury-related inflammations included increased white blood cells, neutrophils and decreased lymphocytes. More patients with liver injury than without had increased serum IL-2R, TNF alpha, ferritin, hsCRP, PCT, ESR, gamma-GT, and LDH. multivariate regression analysis revealed that increasing odds of liver injury were related to male, higher serum hsCRP (>= 10 mg/L), and neutrophil-to-lymphocyte ratio (NLR) (>= 5). Moreover, more deceased patients (14/82 (17%)) had significantly elevated serum TBIL than discharged patients [25/532 (4.7%)]. Conclusion Liver injury is a common complication in COVID-19 patients. The potential risk factors of liver injury include male, hsCRP and NLR score. A close monitor of liver function should be warned in COVID-19 patients, especially in severe/critical individuals.

关键词： COVID-19 Liver damage Clinical course Alanine aminotransferase Total bilirubin Cytokine storm Hypersensitive C-reactive protein Neutrophil-to-lymphocyte ratio multivariate regression analysis Retrospective cohort study

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Failure Propensity of GFRP Strengthen RC Beam

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JOURNAL OF FAILURE analysis AND PREVENTION 2020年第4期20卷 1308-1322页

作者： Shukla, Anjani Kumar Goswami, Prateek Maiti, Pabitra Ranjan Indian Inst Technol BHU Varanasi Varanasi Uttar Pradesh India Motilal Nehru Natl Inst Technol Prayagraj Allahabad Uttar Pradesh India

Fiber-reinforced polymer has eventually become a popular choice for retrofitting and strengthening of structural entities. Hence, a need arises to know the quantitative as well as qualitative effect of these techniques on the original integrity of the concerned structural entity. In the present study, the effect of change in width to depth ratio, percentage of steel and loading intensity in a simply supported reinforced concrete (RC) beam on the maximum deflection, stress, strain energy, natural frequencies and deflections of various modes of free vibration is obtained with the help of ANSYS Workbench 19.0 software till the failure of RC beam and a comparison is sought between the original beam and a failed beam retrofitted with one, two and three layers of GFRP sheets (Epoxy S-Glass UD). A standard beam of fixed dimensions and a two point loading was first simulated in the software while comparing the results with the manual calculations of maximum deflections to ascertain the most appropriate settings of the simulation in the three dimensional analysis environment of the software. Various beams were then analyzed altering the width to depth ratio, the percentage of tension steel and the loading intensity over the beam and the results of the static as well as modal (frequency) analysis were noted including the deflections, stresses, strains, strain energies, natural frequencies of first 5 modes of free vibrations and their respective displacements. The same beams were then retrofitted with layers of GFRP sheets with their principal axis inclined at an angle of 45 degrees with the span of the beam. The same analysis was done on the beams and the results were noted. These results are compared, and a multivariate regression analysis is performed over the results to obtain equations to testify the observations and the trends. This whole process gives a conclusion that the effect of retrofitting is insignificant for single layer GFRP while the most effective results wer

关键词： Failure analysis GFRP Reinforced concrete beams Retrofitting multivariate regression analysis Finite element analysis

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Investigation of fracture properties of rocks under drilling fluid saturation

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ENVIRONMENTAL EARTH SCIENCES 2021年第15期80卷 496-496页

作者： Karakul, Hasan Izmir Katip Celebi Univ Dept Petr & Nat Gas Engn TR-35620 Izmir Turkey

The invasion created by drilling fluids around borehole walls creates considerable variations on mechanical and physical properties of both rock materials and discontinuities. However, up to date there is no comprehensive study has been performed on the variation of fracture toughness values of rocks under drilling fluid saturation with different compositions. By considering this deficiency, the variation of fracture toughness values of five different rocks interacting with drilling fluids with different compositions was investigated in this study. The experiments showed that the negative effect of drilling fluids on fracture toughness values of rocks has a broad range and the addition of polymers to the drilling fluid prevents a dramatic decrease in the fracture toughness values of rocks. Statistical evaluations showed that the fracture toughness values of rocks can be predicted from tensile strength with moderate error by simple regression analyses. However, the multivariate regression analyses produced statistically significant prediction equations with stronger coefficients of determination. On the other hand, the prediction capability of Adaptive Neuro Fuzzy Inference System (ANFIS) model was higher than the prediction performance of simple and multivariate regression analyses.

关键词： Drilling fluid Fracture toughness Rock mass Discontunity Drilling fluid Hydraulic fracturing multivariate regression analysis

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Drivers of household consumption expenditure and carbon footprints in Finland

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JOURNAL OF CLEANER PRODUCTION 2021年 289卷 125607-125607页

作者： Salo, Marja Savolainen, Hannu Karhinen, Santtu Nissinen, Ari Finnish Environm Inst SYKE Latokartanonkaari 11 FI-00790 Helsinki Finland Univ Helsinki Fac Biol & Environm Sci Viikinkaari 1POB 65 FI-00014 Helsinki Finland

Household consumption patterns contribute to climate change. Therefore, an understanding of the drivers of household consumption (food, housing, travel, services, and tangibles) and the related carbon footprint is crucial for policy design. This article studies household expenditure and carbon footprint in an affluent European country, Finland, using Household Budget Survey data from 2016 and an environmentally extended input-output model for Finland. The multivariate regression analysis includes demographic, socio-economic and spatial explanatory variables. Compared with previous literature in this field of research, the main contribution regarding variable selection is the inclusion of region and urban form interactions. The results show that the selection of spatial variables in the model affects the results and policy-relevant conclusions on the role of region, urban form, and their interactions as spatial drivers of expenditure and carbon footprints. Regarding the socio-economic characteristics, the study includes occupational status and shows that it has some effect on expenditure patterns even when the impact of education is controlled for. Another novelty of the article is to explore the decoupling of expenditure and carbon footprint from consumption-based perspective. Expenditure and carbon footprint are first analysed separately to address their drivers individually. Then, decoupling is examined by comparing the results of the drivers of expenditure and the carbon footprint. The analysis shows little evidence of the occurrence of absolute decoupling. The article discusses how analysis based on inputoutput data can show shifts in consumption patterns in terms of commodity groups but not on a product level. In all, the findings on the selection of spatial variables and decoupling, and related policy implications, contribute to the discussion on how to analyse household consumption and carbon footprints. (c) 2021 The Authors. Published by Elsevier Ltd. This i

关键词： Household consumption Consumption expenditure Input-output analysis Carbon footprint Household budget survey multivariate regression analysis

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The significance of operating parameters on electromagnetic-solvent bitumen recovery process

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FUEL 2021年 304卷 121373-121373页

作者： Sadeghi, Asghar Hassanzadeh, Hassan Boustani, Arash Univ Calgary Dept Chem & Petr Engn Schulich Sch Engn 2500 Univ Dr NW Calgary AB T2N 1N4 Canada CNOOC Int Suite 2300500 Ctr St SE Calgary AB T2G 1A6 Canada Cayenne Solut Inc Calgary AB Canada

Current thermal bitumen recovery processes are highly vulnerable to the low oil price environments. Solventsaided processes could be a promising option over Steam Assisted Gravity Drainage (SAGD), with the potential for lowered initial capital investment and reduced operating costs. Enhanced Solvent Extraction Incorporating Electromagnetic Heating (ESEIEH (R)) technology is a novel process where electromagnetic waves and hydrocarbon solvents are employed for bitumen recovery. This study examines the significance of operating parameters on the electromagnetic-solvent process when the injected solvent is either pure propane or pure butane. The effect of several parameters, including operating pressure and applied power on various response surface models, were examined using Design of Experiment and multivariate regression analysis. Results show that the operating pressure is the main governing factor for the selection of the solvent type, while other parameters such as applied power are less significant. Generally, it is recommended to operate the process at native reservoir pressure to minimize the risk of loss of expensive solvents into the thief zones. Lack of reservoir containment (leakiness) is another important factor in the process design, especially when prescribing an operating pressure regime considerably different than that of the surrounding impairments. Due to a wide variation of the in-situ bitumen viscosity in different oil sands reservoirs, each bitumen type requires a different solvent mole fraction to mobilize the bitumen. For the type of bitumen used in this study, the optimum pressure range for butane was found to be around 800-1000 kPa, and for propane injection, around 2400-2600 kPa.

关键词： Electromagnetic-solvent coupled process Oil sands recovery Thermal-solvent techniques Experimental design multivariate regression analysis

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multivariate (O)PLS regression methods in forensic dating

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TRAC-TRENDS IN ANALYTICAL CHEMISTRY 2021年 141卷 116278-116278页

作者： Ortiz-Herrero, L. Maguregui, M. I. Bartolome, L. Univ Basque Country UPV EHU Fac Sci & Technol Analyt Chem Dept Barrio Sarriena S-N Leioa 48940 Spain Univ Basque Country UPV EHU Fac Fine Arts Painting Dept Barrio Sarriena S-N Leioa 48940 Bizkaia Spain Univ Basque Country UPV EHU Martina Casiano Technol Platform Adv Res Facil SGIker Barrio Sarriena S-N Leioa 48940 Bizkaia Spain

In recent years, the use of chemometric tools together with analytical techniques has been increasing in forensics due to their useful role in extracting additional reliable and objective information, which can be of great help in finding and understanding the connections between the forensic evidence and the suspects involved in complex crimes. Although there are various reviews available that deal with discussing the most widely used chemometric methods and their applications in forensics, most of them focus on multivariate classification and discrimination methods, overlooking multivariate regression methods. The present review aims to prove the powerful applicability of multivariate regression methods in one of the most challenging fields of forensics -forensic dating. Based on the authors' own experience and recent research studies, the review has been structured in three sections, covering the benefits and drawbacks of using multivariate regression methods in forensic dating and how to overcome these drawbacks, including also a methodological proposal on how to make optimal use of these methods. This review intends to provide a solid ground for emphasising and encouraging the application of chemometric-based methodologies in the coming years, in order to provide solutions to those challenges posed by forensic dating which cannot be solve by conventional methodologies. (c) 2021 Elsevier B.V. All rights reserved.

关键词： Forensics Dating Chemometrics multivariate regression analysis PLSR

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An Approach to Predict Unknown Diameter of Hollow-Bar Micropiles (HBMs) in Sandy Soils Considering Installation Parameters

An Approach to Predict Unknown Diameter of Hollow-Bar Microp...

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1st Session on Foundations, Soil Improvement, And Erosion at Geo-Congress on Vision, Insight, Outlook

作者： Ahsanuzzaman, Mohammad Gabr, Mohammed A. Borden, Roy H. North Carolina State Univ Dept Civil Engn Raleigh NC 27695 USA

ISBN: (数字)9780784482780

ISBN: (纸本)9780784482780

A common method for predicting ultimate shaft resistance of pile foundation in sandy soils is based on the use of effective stress and utilizing a beta-coefficient (beta) that incorporates the soil-pile interface effects. The beta is a function of coefficient of lateral earth pressure (defined as the ratio of the effective radial stress acting on the pile wall to the effective overburden stress, sigma'v) and the interface friction angle between pile wall and the soil. In the case of the self-drilling HBMs, the diameter of the formed pile is not known. The diameter of the HBMs varies significantly as the central hollow-bar penetrates soil at various rates and grout pump flow rates. The soil types and existing density also play an important role in forming the diameter. TITAN Injection Pile or HBM manufacturer company "Ischebeck" introduced a new term describing a widening value "a". This value quantifies the difference between diameters of the formed HBM and the used drill-bit. The "a" value ranges from 0.8-inch (20 mm) minimum for any type of soil to 2.0 inches (50 mm) for sandy soils and 3 inches (75 mm) for gravelly soils. However, the effect of installation parameters on the formation of diameter of HBM is not addressed in previous studies. Therefore, utilizing field-measured data, work presented herein examined the effect of both the installation parameters and soil conditions on the formed HBM diameter. multivariate regression analysis was used to develop models to predict the formed diameter of HBMs used to assess the axial pullout capacity of HBMs. Eight HBMs, four instrumented and four non-instrumented, were used in the study. The field testing program included installation of micropiles to a depth of 25 ft. (7.62 m) while varying the drill-bit insertion rate (I-R) and the grout flow rate (Q(R)). In addition, the installation methods included HBMs that were continuously drilled and grouted with neat grout water-cement ratio (w/c) of 0.4, and others that were

关键词： hollow-bar micropiles flow rate insertion rate pullout capacity effective stress (beta) method multivariate regression analysis

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Dimensional analysis and propulsion performance simulation of Underwater Vehicle Magneto-hydrodynamic Thruster

Dimensional analysis and propulsion performance simulation o...

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Global OCEANS Singapore - U.S. Gulf Coast Conference

作者： Du, Xiaoxu Liu, Xin Northwestern Polytech Univ Sch Marine Sci & Technol Xian Shaanxi Peoples R China

ISBN: (纸本)9781728154466

Magneto-hydrodynamic (MHD) thruster is a new type of underwater vehicle propulsion. To better analyze the working principle and propulsion performance of the MHD thruster, it is necessary to carry out dimensional analysis and propulsion performance simulation. Dimensional analysis is used to establish the dimensional relationship between the thrust F and the main influencing factors. Firstly, based on computational fluid dynamics, the flow field numerical simulation of the MHD thruster is carried out. Secondly, the statistical analysis method of multiple regression is used to analyze the data. Finally, the dimensionless mathematical model of the MHD thruster is obtained. This mathematical model provides a method and reference for the research of the MHD thruster.

关键词： magneto-hydrodynamic thruster dimensional analysis multivariate regression analysis

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multivariate regression Model for Total Body Water Estimation by Non-Invasive Way 23

Multivariate Regression Model for Total Body Water Estimatio...

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23rd International Conference on Computer and Information Technology (ICCIT)

作者： Khatun, Farzana Fahim, Tahasin Ahmed Sarkar, Ajay Krishno Anower, Md Shamim Rajshahi Univ Engn & Technol Dept Elect & Elect Engn Rajshahi Bangladesh

ISBN: (纸本)9781665422444

This paper shows total body water (TBW) measurement models for human body based on multivariate regression analysis by non-invasive way. A total number of 1500 people's data (750 male and 750 female) have been used to develop two models. For developing different model for male and female, two models have been *** validate the proposed models some major statistical analysis have been considered. Statistical analysis reports exhibit excellent accuracy i.e. correlation coefficient is close to unity (0.998, 0.997), presence of error within the 95% of Limit of Agreement, less bias (0.03), 0.24) and less RMSE (0.82, 0.69) and hence the proposed models will be able to measure total body water more accurately than existing models.

关键词： Bioelectrical impedance analysis multivariate regression analysis non-invasive way total body water

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Remaining Service Life Prediction of Aging Concrete Bridges Based on Multiple Relevant Explanatory Variables

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PRACTICE PERIODICAL ON STRUCTURAL DESIGN AND CONSTRUCTION 2021年第4期26卷 04021036-04021036页

作者： Srikanth, Ishwarya Arockiasamy, Madasamy Florida Atlantic Univ Dept Civil Environm & Geomat Engn 777 Glades Rd Boca Raton FL 33431 USA Florida Atlantic Univ Dept Civil Environm & Geomat Engn Ctr Infrastruct & Constructed Facil 777 Glades Rd Boca Raton FL 33431 USA

Concrete highway bridge remaining service life has been at the forefront of bridge owners' concerns for several years in terms of growing bridge maintenance needs. Distresses in concrete bridge components occur due to physical, chemical, and mechanical factors that manifest as observable symptoms of deterioration. Deterioration models realistically link the observable defects to the several explanatory variables affecting the deterioration that aid in the planning of appropriate corrective actions. Only a limited number of explanatory variables have been considered in the published literature in the development of bridge component deterioration models. This study investigates the effect of multiple relevant explanatory variables affecting the bridge component condition including aging, loads and environmental conditions, and design characteristics using a multivariate regression analysis approach. Deterioration models for both superstructure and substructure of reinforced and prestressed concrete bridges are developed and validated in the present study. The proposed models will aid the bridge engineers to predict the concrete bridge component conditions based on bridge characteristics for planning preventive maintenance. (C) 2021 American Society of Civil Engineers.

关键词： Concrete bridges Deterioration models Remaining service life prediction Preventive maintenance multivariate regression analysis Statistics

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