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Positive autoantibodies in living liver donors

World Journal of Hepatology 2022年第9期14卷 1757-1766页

作者： joyce loh Koji Hashimoto Choon Hyuck David Kwon Masato Fujiki Jamak Modaresi Esfeh Department of Internal Medicine Cleveland Clinic FoundationClevelandOH 44195United States Digestive Diseases Institute Cleveland Clinic FoundationClevelandOH 44195United States Digestive Disease and Surgery Institute Cleveland Clinic FoundationClevelandOH 44195United States

BACKGROUND There is a nationwide shortage of organs available for liver *** donors help meet this growing *** uncommonly,donors will have positive ***,it is unclear whether donor positive autoantibodies are correlated with worse outcomes following living liver donor *** To analyze the significance of positive autoantibodies in donors on post-transplant outcomes in *** We performed a retrospective review of living liver donors who had undergone liver transplantation between January 1,2012 and August 31,*** characteristics and pre-transplant data including antinuclear antibodies(ANA)and anti-smooth muscle antibody titers were collected in *** of interest were post-transplantation complications including mortality,biliary strictures,biliary leaks,infection,and *** recipients and donors without measured pre-transplant autoantibody serologies were excluded from this *** 172 living donor liver transplantations were performed during the study period,of which 115 patients met inclusion criteria.37(32%)living donors were autoantibody-positive with a median ANA titer of 1:160(range 1:80 to 1:1280)and median anti-SMA titer of 1:40(range 1:20 to 1:160).There were no significant differences in baseline demographics between the autoantibody positive and negative ***-transplantation rates of death(P value=1),infections(P value=0.66),and overall rates of complications(P value=0.52)were similar between the autoantibody positive and negative *** incidences of anastomotic strictures and rejection were observed in the autoantibody positive group;however,these differences were not statistically significant(P value=0.07 and P value=0.30 respectively).CONCLUSION Isolated pre-transplant autoantibody positivity is not correlated to worse post-transplant outcomes in living liver donor transplants.

关键词： Antinuclear antibodies Anti-smooth muscle antibody Liver transplantation Treatment outcome Transplant donors

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Fusion of Landsat 8 OLI and PlanetScope Images for Urban Forest Management in Baton Rouge, Louisiana

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Journal of Geographic Information System 2022年第5期14卷 444-461页

作者： Yaw Adu Twumasi Abena Boatemaa Asare-Ansah Edmund Chukwudi Merem Priscilla Mawuena loh John Bosco Namwamba Zhu Hua Ning Harriet Boatemaa Yeboah Matilda Anokye Rechael Naa Dedei Armah Caroline Yeboaa Apraku Julia Atayi Diana Botchway Frimpong Ronald Okwemba Judith Oppong Lucinda A. Kangwana Janeth Mjema Leah Wangari Njeri joyce McClendon-Peralta Valentine Jeruto Department of Urban Forestry and Natural Resources Southern University and A&M College Baton Rouge USA Department of Urban and Regional Planning Jackson State University Jackson USA Department of Geography and Tourism Studies Brock University Catharines Canada

In recent years image fusion method has been used widely in different studies to improve spatial resolution of multispectral images. This study aims to fuse high resolution satellite imagery with low multispectral imagery in order to assist policymakers in the effective planning and management of urban forest ecosystem in Baton Rouge. To accomplish these objectives, Landsat 8 and PlanetScope satellite images were acquired from United States Geological Survey (USGS) Earth Explorer and Planet websites with pixel resolution of 30m and 3m respectively. The reference images (observed Landsat 8 and PlanetScope imagery) were acquired on 06/08/2020 and 11/19/2020. The image processing was performed in ArcMap and used 6-5-4 band combination for Landsat 8 to visually inspect healthy vegetation and the green spaces. The near-infrared (NIR) panchromatic band for PlanetScope was merged with Landsat 8 image using the Create Pan-Sharpened raster tool in ArcMap and applied the Intensity-Hue-Saturation (IHS) method. In addition, location of urban forestry parks in the study area was picked using the handheld GPS and recorded in an excel sheet. This sheet was converted into Excel (.csv) file and imported into ESRI ArcMap to identify the spatial distribution of the green spaces in East Baton Rouge parish. Results show fused images have better contrast and improve visualization of spatial features than non-fused images. For example, roads, trees, buildings appear sharper, easily discernible, and less pixelated compared to the Landsat 8 image in the fused image. The paper concludes by outlining policy recommendations in the form of sequential measurement of urban forest over time to help track changes and allows for better informed policy and decision making with respect to urban forest management.

关键词： Remote Sensing Image Fusion Multispectral Images Urban Forest Landsat 8 Operational Land Imager (OLI) PlanetScope Baton Rouge

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Land Resource Areas and Spatial Analysis of Potential Location of Bioenergy Crops Production in Mississippi

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Journal of Sustainable Bioenergy Systems 2021年第4期11卷 187-214页

作者： Yaw Adu Twumasi Edmund Chukwudi Merem John Bosco Namwamba Jacob Banafo Annan Tomas Ayala-Silva Abena Boatemaa Asare-Ansah Zhu Hua Ning Judith Oppong Priscilla Mawuena loh Diana Botchway Frimpong Faustina Owusu Janeth Ernest Mjema Ronald Okwemba Olipa Simon Mwakimi Brilliant Mareme Petja Caroline Olufunke Akinrinwoye joyce McClendon-Peralta Hermeshia Jonee Mosby Department of Urban Forestry and Natural Resources Southern University and A&M College Baton Rouge Louisiana USA Department of Urban and Regional Planning Jackson State University Jackson Mississippi USA USDA-ARS Tropical Agriculture Research Station 2200 P.A. Mayaguez Puerto Rico USA Institute of Resource Assessment University of Dares Salam Dares Salam Tanzania Water Research Commission (WRC) Private Bag X03 Gezina South Africa

Mississippi State is renowned for its land resource areas (LRA) and production of bioenergy crops which generate both agricultural and economic benefits. Agricultural commodities play a key role in economic growth, therefore the ability to produce more would enhance development. This paper offers an analysis of the production of bioenergy crops in Mississippi. Relative measures, time series graphs and descriptive statistics coupled with geographic information systems (GIS) mapping using ArcMap were employed to generate the outcome of this research. The outcome of the statistical analysis indicated that corn and soybeans were the most produced crops in Agricultural Districts 10 and 40. These districts produced more bioenergy crops than the other districts. GIS mapping results also showed that the potential area for bioenergy crops is in zone 131 of the Mississippi Land Resource Area (MLRA). This zone has an absolute advantage in the production of these crops which includes the diversity of biomass production such as corn, cotton, soybeans, wheat, rice, barley, grain sorghum, canola, camelina, algae, hardwoods, and softwood. The paper recommends a constant GIS mapping and land management systems for each agricultural district in Mississippi to enable researchers and farmers to determine the factors which contribute towards the increasing and decreasing trends in the production of the bioenergy crops.

关键词： Land Resource Areas GIS Bioenergy Crops Descriptive Statistics Mississippi

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An Assessment of the Potential Use of Forest Residues for the Production of Bio-Oils in the Urban-Rural Interface of Louisiana

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Open Journal of Forestry 2022年第4期12卷 479-502页

作者： Yaw A. Twumasi Zhu H. Ning John B. Namwamba Edmund C. Merem Abena B. Asare-Ansah Harriet B. Yeboah Matilda Anokye Diana B. Frimpong Priscilla M. loh Julia Atayi Judith Oppong Cynthia C. Ogbu Rechael N. D. Armah Caroline Y. Apraku Opeyemi I. Oladigbolu joyce McClendon-Peralta Department of Urban Forestry and Natural Resources Southern University and A&M College Baton Rouge USA Department of Urban and Regional Planning Jackson State University Jackson USA Department of Geography and Tourism Studies Brock University St. Catharines Canada

Louisiana is endowed with forest resources. Forest wastes generated after thinning, land clearing, and logging operations, such as wood debris, tree trimmings, barks, sawdust, wood chips, and black liquor, among others, can serve as potential fuels for energy production in Louisiana. This paper aims to evaluate the potential annual volumes of forest wastes established on detailed and existing data on the forest structure in the rural-urban interface of Louisiana. It also demonstrates the state’s prospects of utilizing forest wastes to produce bio-oils. The data specific to the study was deduced from secondary data sources to obtain the annual average total residue production in Louisiana and estimate the number of logging residues available for procurement for bioenergy production. The total biomass production per year was modeled versus years by polynomial regression curve fitting using Microsoft Excel. Results of the model show that the cumulative annual total biomass production for 2025 and 2030 in Louisiana is projected to be 80000000 Bone Dry Ton (BDT) and 16000000 (BDT) respectively. The findings of the study depict that Louisiana has a massive biomass supply from forest wastes for bioenergy production. Thus, the potential for Louisiana to become an influential player in the production of bio-based products from forest residues is evident. The author recommends that future research can use Geographic Information Systems (GIS) to create maps displaying the potential locations and utilization centers of forest wastes for bioenergy production in the state.

关键词： Bioenergy Production Bio-Oils Polynomial Regression Bio-Products Forest Residues Logging Residues Wood Wastes Louisiana

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Bioenergy Crops as a Promising Alternative to Fossil Fuels in Louisiana: A Geographic Information System (GIS) Perspective

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Journal of Sustainable Bioenergy Systems 2022年第4期12卷 57-81页

作者： Yaw A. Twumasi Zhu H. Ning John B. Namwamba Abena B. Asare-Ansah Edmund C. Merem Harriet B. Yeboah Judith Oppong Matilda Anokye Diana B. Frimpong Priscilla M. loh Julia Atayi Rechael N. D. Armah Caroline Y. Apraku Opeyemi I. Oladigbolu Cynthia C. Ogbu Leah W. Njeri joyce McClendon-Peralta Department of Urban Forestry and Natural Resources Southern University and A&M College Baton Rouge USA Department of Urban and Regional Planning Jackson State University Jackson USA Department of Geography and Tourism Studies Brock University St. Catharines Canada

Rising greenhouse gas emissions are causing climate change, and the world’s focus has shifted to the need to reduce our reliance on fossil fuels. There has been a rise in the published literature on the utilization of crops for bioenergy production in Louisiana. However, very few scholarly documents have used Geographic Information Systems (GIS) to map the distribution of potential bioenergy crops in Louisiana. This study seeks to fill the void by evaluating the potential of bioenergy crops in Louisiana for energy production using GIS. Given this objective, the agricultural census data for 1999, 2009, 2019, and 2020 obtained from the U.S. Department of Agriculture were used in the analysis. The quantities of various crops produced in the state were loaded into an attribute table and joined to a shapefile using ArcGIS software. The symbology tool’s graduated option was used to create five maps representing each of the bioenergy crops in Louisiana. The findings of the GIS analysis show that some of the parishes, such as Franklin produced the most bushels of corn (13,795,416), Iberia produced the most tons of sugarcane (1,697,980), East Carroll produced the most bushels of soybean (8,237,991), Tensas harvested the most bales of cotton (80,898) and Avoyelles produced the most bushels of sorghum (630,694). The abundance and availability of crops as raw materials for energy production will translate into lower prices in terms of energy use, making bioenergy crops a promising alternative to fossil fuels. In addition, gasoline price data from 1993-2022 was obtained from U.S. Energy Information Administration. A regression model for the average annual gasoline price over the years was constructed. The results show that the average annual gasoline price variation with respect to years is statistically significant (p 0.05). This suggests that gasoline prices will generally rise despite a price drop over the years. The paper concludes by outlining policy recommendations in the

关键词： Bioenergy Crops Biomass Fossil Fuel Gasoline Geographic Information Sys-tem (GIS) Regression Analysis Louisiana

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Estimation of Land Surface Temperature from Landsat-8 OLI Thermal Infrared Satellite Data. A Comparative Analysis of Two Cities in Ghana

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Advances in Remote Sensing 2021年第4期10卷 131-149页

作者： Yaw A. Twumasi Edmund C. Merem John B. Namwamba Olipa S. Mwakimi Tomas Ayala-Silva Diana B. Frimpong Zhu H. Ning Abena B. Asare-Ansah Jacob B. Annan Judith Oppong Priscilla M. loh Faustina Owusu Valentine Jeruto Brilliant M. Petja Ronald Okwemba joyce McClendon-Peralta Caroline O. Akinrinwoye Hermeshia J. Mosby Department of Urban Forestry and Natural Resources Southern University and A&M College Baton Rouge Louisiana USA Department of Urban and Regional Planning Jackson State University Jackson Mississippi USA Institute of Resource Assessment University of Dares Salam Dares Salam Tanzania USDA-ARS Tropical Agriculture Research Station Mayaguez Puerto Rico USA Water Research Commission (WRC) Private Bag X03 Gezina South Africa

This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to compare land surface temperature of two cities in Ghana: Accra and Kumasi. These cities have human populations above 2 million and the corresponding anthropogenic impact on their environments significantly. Images were acquired with minimum cloud cover (ere used. The shapefiles of Accra and Kumasi were used to extract from the full scenes to subset the study area. Thermal band data numbers were converted to Top of Atmospheric Spectral Radiance using radiance rescaling factors. To determine the density of green on a patch of land, normalized difference vegetation index (NDVI) was calculated by using red and near-infrared bands i.e. Band 4 and Band 5. Land surface emissivity (LSE) was also calculated to determine the efficiency of transmitting thermal energy across the surface into the atmosphere. Results of the study show variation of temperatures between different locations in two urban areas. The study found Accra to have experienced higher and lower dry season and wet season temperatures, respectively. The temperature ranges corresponding to the dry and wet seasons were found to be 21.0985

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Time Series Analysis on Selected Rainfall Stations Data in Louisiana Using ARIMA Approach

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Open Journal of Statistics 2021年第5期11卷 655-672页

作者： Yaw A. Twumasi Jacob B. Annan Edmund C. Merem John B. Namwamba Tomas Ayala-Silva Zhu H. Ning Abena B. Asare-Ansah Judith Oppong Diana B. Frimpong Priscilla M. loh Faustina Owusu Lucinda A. Kangwana Olipa S. Mwakimi Brilliant M. Petja Ronald Okwemba Caroline O. Akinrinwoye Hermeshia J. Mosby joyce McClendon-Peralta Department of Urban Forestry and Natural Resources Southern University and A&M College Baton Rouge Louisiana USA Department of Urban and Regional Planning Jackson State University Jackson Mississippi USA USDA-ARS Tropical Agriculture Research Station Mayaguez Puerto Rico USA Institute of Resource Assessment University of Dares Salam Dares Salam Tanzania Water Research Commission (WRC) Private Bag X03 Gezina South Africa

Precipitation is very important for both the environment and its inhabitants. Agricultural activities mostly depend on precipitation and its availability. Therefore, the ability to predict future precipitation values at specific stations is key for environmental and agricultural decision making. This research developed Autoregressive Integrated Moving Average (ARIMA) models for selected stations with Integrated component and Autoregressive Moving Average (ARMA) for selected stations without Integrated component at Louisiana State. The ARIMA module is represented as ARIMA(p, d, q)(P,D,Q). The selected lag order for the Autoregressive (AR) component is represented with p and P for seasonal AR component, while the integrated form (number of times data were differenced) is d and D for seasonal differencing, and the Moving Average (MA) lag order is q and Q for seasonal MA component. Data from 1950 to 2020 were employed in this research. Results of the analysis indicated that Baton Rouge (ARIMA (0,1,1) (0,0,2)12), Abbeville (ARMA (0,0,1) (0,0,2)12), Monroe Regional (ARMA (0,0,1) (0,0,0)12), New Orleans Airport (ARMA (1,0,0) (0,0,2)12), Alexandria (ARMA (1,0,1) (0,0,0)12), Logansport (ARIMA (0,1,2) (0,0,0)12), New Orleans Audubon (ARMA (1,0,0) (0,0,0)12), Lake Charles Airport (ARMA (2,0,2) (0,0,0)

关键词： Precipitation ARIMA Models Time Series Lowess Louisiana

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Analysis of Precipitation Trends and Prediction in Selected Cities in the Southeast Louisiana

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Atmospheric and Climate Sciences 2022年第4期12卷 698-727页

作者： Yaw A. Twumasi John B. Namwamba Zhu H. Ning Edmund C. Merem Priscilla M. loh Abena B. Asare-Ansah Jacob B. Annan Ronald Okwemba Harriet B. Yeboah Caroline Y. Apraku Janeth Mjema Rechael N. D. Armah Matilda Anokye Lucinda A. Kangwana Judith Oppong Julia Atayi Cynthia C. Ogbu Opeyemi I. Oladigbolu Diana B. Frimpong joyce McClendon-Peralta Department of Urban Forestry and Natural Resources Southern University and A&M College Baton Rouge LA USA Department of Urban and Regional Planning Jackson State University Jackson MS USA Department of Geography and Tourism Studies Brock University St. Catharines Canada

The impacts of climate change are being felt in Louisiana, in the form of changing weather patterns that have resulted in changes in floods, hurricanes, tornadoes frequencies of occurrence, and magnitudes, among others resulting in, flooding. The variabilities in rainfall in a drainage basin affect water availability and sustainability. This study analyzed the precipitation data of Southeastern Louisiana, United States, for the period 1990 to 2020. Data used in the study was from, Donaldsonville, Galliano, Lafourche, Gonzales, Ascension, Morgan, New Orleans, Audubon, Plaquemine, and Ponchatoula, Tangipahoa, weather stations. These stations were selected because the differences between each of their highest and lowest average annual rainfall data were greater than 20 inches. To investigate climate patterns and trends for the given weather stations in Southeastern Louisiana, precipitation data were analyzed on annual time scales using data collected from the World Bank Group Climate Change Knowledge Portal for Development Practitioners and Policy Makers and the Applied Climate Information System (ACIS) of the National Weather Service Prediction Center. The data were further aggregated using annual average blocks of 4 years, and linear and polynomial regression was performed to establish trends. The highest and lowest average annual rainfall data for Donaldsonville, Galliano, Lafourche, Gonzales, Ascension, Morgan, New Orleans, Audubon, Plaquemine, and Ponchatoula, Tangipahoa, weather stations were, 75 and 48, 71 and 44, 73.5 and 52.7, 75 and 46.4, 72 and 41.3, 94 and 55.3, Ponchatoula, and 78.6 and 44, respectively. Plaquemine recorded the highest average annual average rainfall while New Orleans, Audubon station recorded the lowest. The projection of the precipitation in 2030 has been carried out to inform scientists and stakeholders about the approximate quantity of rainfall expected and enable them to make their expected impacts on agriculture, economy, etc. The pr

关键词： Precipitation Linear and Polynomial Regression Extrapolating Models Southeastern Louisiana

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Flood Mapping in Mozambique Using Copernicus Sentinel-2 Satellite Data

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Advances in Remote Sensing 2022年第3期12卷 80-105页

作者： Yaw A. Twumasi Edmund C. Merem John B. Namwamba Abena B. Asare-Ansah Jacob B. Annan Zhu H. Ning Rechael N. D. Armah Caroline Y. Apraku Harriet B. Yeboah Julia Atayi Matilda Anokye Diana B. Frimpong Ronald Okwemba Olipa S. Mwakimi Judith Oppong Brilliant M. Petja Janeth Mjema Priscilla M. loh Lucinda A. Kangwana Valentine Jeruto Leah Wangari Njeri joyce McClendon-Peralta Department of Urban Forestry and Natural Resources Southern University and A & M College 102 Fisher Hall Baton Rouge Louisiana USA Department of Urban and Regional Planning Jackson State University 101 Capitol Center Jackson Mississippi USA Department of Geography and Tourism Studies Brock University St. Catharines Ontario Canada Institute of Resource Assessment University of Dares Salam Dares Salam Tanzania Water Research Commission (WRC) Private Bag X03 Gezina South Africa

Over the last two decades, Mozambique has experienced tremendous tropical cyclonic activities causing many flooding activities accompanied by disastrous human casualties. Studies that integrate remote sensing, elevation data and coupled with demographic analysis in Mozambique are very limited. This study seeks to fill the void by employing satellite data to map inundation caused by Tropical Cyclones in Mozambique. In pursuit of this objective, Sentinel-2 satellite data was obtained from the United States Geological Survey (USGS)’s Earth Explorer free Online Data Services imagery website covering the months of March 20, 2019, March 25, 2019, and April 16, 2019 for two cities, Maputo and Beira in Mozambique. The images were geometrically corrected to remove, haze, scan lines and speckles, and then referenced to Mozambique ground-based Geographic: Lat/Lon coordinate system and WGS 84 Datum. Data from twelve spectral bands of Sentinel-2 satellite, covering the visible and near infrared sections of the electromagnetic spectrum, were further used in the analysis. In addition, Normalized Difference Water Index (NDWI) within the study area was computed using the green and near infrared bands to highlight water bodies of Sentinel-2 detectors. To project and model the population of Mozambique and see the impact of cyclones on the country, demographic data covering 1980 to 2017 was obtained from the World Bank website. The Exponential Smoothing (ETS) method was adopted to forecast the population of Mozambique. Results from NDWI analysis showed that the NDWI is higher for flood areas and lower for non-flooded ones. The ETS algorithm results indicate that the population of Mozambique would nearly double by 2047. Human population along the coastal zone in the country is also on the rise exponentially. The paper concludes by outlining policy recommendations in the form of uniform distribution of economic activities across the country and prohibition of inland migration to the coas

关键词： Tropical Cyclones Floods Remote Sensing NDWI Exponential Smoothing (ETS) Digital Elevation Model (DEM) Sentinel-2 Satellite Mozambique

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Fusion of Landsat 8 OLI and PlanetScope Images for Urban Forest Management in Baton Rouge, Louisiana

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Journal of Geographic Information System 2022年第5期

作者： yaw adu twumasi abena boatemaa asare-ansah edmund chukwudi merem priscilla mawuena loh john bosco namwamba zhu hua ning harriet boatemaa yeboah matilda anokye rechael naa dedei armah caroline yeboaa apraku julia atayi diana botchway frimpong ronald okwemba judith oppong lucinda a. kangwana janeth mjema leah wangari njeri joyce mcclendon-peralta valentine jeruto

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