Johnson, Myke

Myke Johnson (she/her pronoun) is a 64 year old Unitarian minister currently living in Portland Maine with her partner of 24 years. She is from Michigan and later moved to Texas and Wyoming with her family. She is the oldest out of 9 children. She grew up Catholic and found herself being an activist during her college years. She became a feminist and was part of the Women\u27s Peace Encampment, March on Washington, Marriage rights campaigns and many more. She got her doctorate degree in the Feminist Liberation Theology Program and became a minister in Massachussets. She then continued to do advocacy work and came to Maine and became a Unitarian Universalist Minister. Citation Please cite as: Querying the Past: LGBTQ Maine Oral History Project Collection, Lesbian, Gay, Bisexual, Transgender, and Queer+ Collection, Jean Byers Sampson Center for Diversity in Maine, University of Southern Maine Libraries. For more information about the Querying the Past: Maine LGBTQ Oral History Project, please contact Dr. Wendy Chapkis.https://digitalcommons.usm.maine.edu/querying_ohproject/1020/thumbnail.jp

Pattern and outcome of acute kidney injury among Sudanese adults admitted to a tertiary level hospital: a retrospective cohort study

Introduction: Little is known about the pattern and outcome of Acute Kidney injury (AKI) in Sudan. This study aimed to determine the etiology and outcome of AKI among Sudanese adults. Methods: A retrospective cohort study was conducted in a tertiary level hospital, Soba University Hospital, Sudan. The medical records of all adults admitted to hospital from the 1st of January to 31st of December 2014 were reviewed. The diagnosis and severity of AKI was defined as per the Kidney Disease Improving Global Outcomes (KDIGO) recommendations. Results: The medical records of 6769 patients were reviewed. AKI was diagnosed in 384 patients (5.7%); being community acquired in 82.6% of cases. Sepsis, volume depletion, obstructive uropathy, heart failure, acute glomerulonephritis and severe malaria were the commonest causes of AKI diagnosed in 44%, 38.5%, 8.9%, 5.7%, 4.7% and 3.1% of patients, respectively. Following treatment complete renal recovery was seen in 35.7% of patients; whereas 31.2% of patients died. Predictors of increased risk of death were old age [OR 1.03, 95% CI (1.01-1.057); P=0.003], presence of chronic liver disease [OR 2.877, 95% CI (1.5-5.5); P=0.001], sepsis [OR 2.51, 95% CI (1.912-4.493);P=0.002] and the severity of AKI [OR 3.873, 95% CI(1.498-10.013);P=0.005]. Conclusion: AKI was diagnosed in 5.7% of adults admitted to hospital. Most patients were having community acquired AKI. Old age, the presence of chronic liver disease, sepsis, and the severity of AKI as per KDIQO staging were significant predictors of mortality

STUDY THE EFFECT OF MYCOPLASMA CONTAMINATION OF EGGS USED IN VIRUS TITRATION AND EFFICACY OF SOME LIVE ATTENUATED POULTRY VIRAL VACCINES

Objective: The study of Mycoplasma gallisepticum (MG) infection is needed, not only to understand the disease process but also to understand theinterference with the evaluation of some live viral poultry vaccines. This study aims to investigate the titration and potency of some live attenuatedpoultry viral vaccines; Newcastle disease, infectious bronchitis, infectious bursal disease, and Reo in both specific pathogen-free (SPF) embryonatedchicken eggs (ECEs) and chickens.Methods: Titration of live attenuated viral poultry vaccines in ECEs was carried out by dividing the inoculated eggs into four groups; the pre-,simultaneously-, post-, and non-MG contaminated. MG effect on the potency test was carried out using seventeen groups of SPF chickens (25 chicken/group) placed into separate isolators. Each live attenuated viral poultry vaccine was inoculated into 4 groups.Results: The highest titer of these vaccines that appeared in MG pre- contaminated ECEs were 1011, 107.5, 107.9, and 10, respectively. The lowest vaccinetiters that appeared in non-MG contaminated ECEs were 108, 106, 106.8, and 1067.5, respectively. Although the potency of these previous vaccines indicated thatthe highest antibodies titer that appeared in MG pre-infected vaccinated chickens were 7.5 log, 36 enzyme-linked immunosorbent assay unit (EU), and42 EU, respectively; the lowest antibodies titer that appeared in non-MG infected vaccinated chickens were 6.5 log22, 12 EU, 17 EU, and 10 EU, respectively.Conclusion: The present study findings underline the importance of using Mycoplasma -free eggs or chicken for the production of virus vaccines.Keywords: Mycoplasma gallisepticum, Newcastle disease virus, Infectious bronchitis virus, Infectious bursal disease virus, Reo virus, Chicken, Specificpathogen-free eggs. Keywords: Mycoplasmagallisepticum,Newcastlediseasevirus,Infectiousbronchitisvirus,Infectiousbursaldiseasevirus,Reovirus,Chicken,Specific pathogen-free eggs.Â

Enhancing land cover classification in remote sensing imagery using an optimal deep learning model

The land cover classification process, accomplished through Remote Sensing Imagery (RSI), exploits advanced Machine Learning (ML) approaches to classify different types of land cover within the geographical area, captured by the RS method. The model distinguishes various types of land cover under different classes, such as agricultural fields, water bodies, urban areas, forests, etc. based on the patterns present in these images. The application of Deep Learning (DL)-based land cover classification technique in RSI revolutionizes the accuracy and efficiency of land cover mapping. By leveraging the abilities of Deep Neural Networks (DNNs) namely, Convolutional Neural Networks (CNN) or Recurrent Neural Networks (RNN), the technology can autonomously learn spatial and spectral features inherent to the RSI. The current study presents an Improved Sand Cat Swarm Optimization with Deep Learning-based Land Cover Classification (ISCSODL-LCC) approach on the RSIs. The main objective of the proposed method is to efficiently classify the dissimilar land cover types within the geographical area, pictured by remote sensing models. The ISCSODL-LCC technique utilizes advanced machine learning methods by employing the Squeeze-Excitation ResNet (SE-ResNet) model for feature extraction and the Stacked Gated Recurrent Unit (SGRU) mechanism for land cover classification. Since ‘manual hyperparameter tuning’ is an erroneous and laborious task, the AIMS Mathematics Volume 9, Issue 1, 140–159. hyperparameter selection is accomplished with the help of the Reptile Search Algorithm (RSA). The simulation analysis was conducted upon the ISCSODL-LCC model using two benchmark datasets and the results established the superior performance of the proposed model. The simulation values infer better outcomes of the ISCSODL-LCC method over other techniques with the maximum accuracy values such as 97.92% and 99.14% under India Pines and Pavia University datasets, respectively

Microbiological Assessment of Moringa Oleifera Extracts and Its Incorporation in Novel Dental Remedies against Some Oral Pathogens

AIM: To assess the antibacterial and antifungal potentials of different parts of Moringa oleifera plant using different extraction methods in attempts to formulate natural dental remedies from this plant.MATERIAL AND METHODS: Three solvents extracts (Ethanol, acetone, and ethyl acetate) of different parts of Egyptian Moringa tree were prepared and tested against oral pathogens: Staphylococcus aureus, Streptococcus mutans, and Candida albicans using disc diffusion method; As well as to incorporate the plant extract to formulate experimental toothpaste and mouthwash.  The two dental remedies  were assessed against the same microbial strains. Statistical analysis was performed using One-Way ANOVA test to compare the inhibition zone diameter and t-test.RESULTS: Ethanol  extracts  as well as leaves extracts demonstrated the highest significant mean inhibition zone values (P ≤ 0.05) against Staphylococcus aureus and Streptococcus mutans growth. However, all extracts revealed no inhibition zone against Candida albicans. For dental remedies, experimental toothpaste exhibited higher mean inhibition than the mouthwash against Staphylococcus aureus, Streptococcus mutans and only the toothpaste revealed antifungal effect against Candida albicans.CONCLUSION: The different extracts of different parts of Moringa showed an antibacterial effect against Staphylococcus aureus and Streptococcus mutans growth. The novel toothpaste of ethanolic leaves extract has antimicrobial and antifungal potential effects all selected strains

A novel neuroscience-inspired architecture: for computer vision applications

The theory behind deep learning, the human visual system was investigated and general principles of how it functions are extracted. Our finding is that there are neuroscience theories that are not utilized in deep learning. Therefore, in this work, a novel model utilizing some of those theories is developed. The new model addresses the parallel nature of the human brain compared to the hierarchal (serial) brain model that is followed by current deep learning systems. The validation of the proposed model was conducted using “Shape” feature dimension. The results show up to 2% accuracy rate compared to our implementation of DeepFace, a high performing face recognition algorithm that was developed by Facebook, is achieved under the same hardware/ software conditions; and we were able to speed up the training up to 21% per a training patch compared to DeepFace

Effect of gas-to-liquid biosludge on soil properties and alfalfa yields in an arid soil

Soils in Qatar are relatively poor in fertility. Hence, imported top soils and soil enhancing materials are used to improve agricultural yields. Therefore, this work investigated the potential of using gas-to-liquid (GTL) biosludge as a soil conditioner. It sought to increase crop yields in an arid soil with positive environmental footprint in terms of fertilizer application savings, waste utilization and minimization of landfilling. A fodder crop, alfalfa (Medicago sativa), was grown under semi-controlled pot conditions for 12 months. The plant-growth media involved soil, soil + fertilizer, soil + 3% compost, and soil plus five (0.75–12%) biosludge contents. Pertinent properties of the soils, the resulting leachates, and plant growth parameters were analyzed at set periods. Biosludge content generally increased the total porosity and volumetric abundance of different pore types, which in turn affected plant performance, especially the plant height. Alfalfa yield in terms of plant height, aboveground fresh biomass weight and the number of tillers decreased with increasing biosludge content. Mixtures with 0.75–3% biosludge content showed comparable or better plant yield in contrast to the soil, fertilizer and compost controls. The concentration of chemical species in the leachate and plant biomass of biosludge treatments were either lower or similar to the fertilizer and compost controls. Regression modeling identified leachate phosphorus concentrations, soil iron concentration and clay content as the most influential variables for the aforementioned plant performance parameters. The results suggest that GTL biosludge could potentially enhance arid soil properties and improve alfalfa yields

Dataset on the influence of gas-to-liquid biosludge on arid soil properties and growth performance of alfalfa

The dataset presented here is related to our research article entitled “Effect of gas-to-liquid biosludge on soil properties and alfalfa yields in an arid soil” [1]. It relates to selected performance parameters of alfalfa grown in an arid soil amended with five different (0.75–12%) gas-to-liquid biosludge contents, and selected properties of the soil determined using several material characterization techniques. A detailed description of the raw data relating to figures on alfalfa performance parameters such as fresh biomass weight, plant height, the number of tillers, and biomass elemental content in the companion article is provided alongside additional data on the number of days to flowering. The underlying data for leachate from the soil and underlying spectra and diffractograms for the proton nuclear magnetic resonance (1H-NMR) and X-ray diffraction (XRD) data, respectively, shown in the companion article are presented. These show changes in the pore structure characteristics and the mineralogical composition of the soil, soil-fertilizer, soil-biosludge, and soil-compost mixtures tested over time. Additional data showing the effect of the amendments on the bulk and particle densities of the soil is presented. The dataset demonstrates the influence of the industrial biosludge on arid soil properties and alfalfa yields (Kogbara et al., [1])

Recycling industrial biosludge for buffel grass production in Qatar: impact on soil, leachate and plant characteristics

The agricultural industry in Qatar is highly dependent on using soil enhancing materials due to challenging soil and climatic conditions. Hence, this work investigated the potential of industrial biosludge from the wastewater treatment plant (WWTP) of a Gas-to-Liquids (GTL) plant to enhance an arid soil compared to fertilizer and compost. A fodder crop, buffel grass (Cenchrus ciliaris), was grown in semi-controlled pots containing a typical Qatari agricultural soil and admixtures over a 12-month period. The treatments included soil plus five biosludge percentage contents: 0.75, 1.5, 3, 6 and 12%. These were compared with soil only, soil plus 20-20-20 NPK fertilizer and soil plus 3% compost controls. Analyses of soil physical and chemical properties, the resulting leachate, and plant growth characteristics were conducted at set periods. The results indicate that up to 3% biosludge content led to better plant growth compared to the controls, with the optimum at 1.5% biosludge content for all growth characteristics studied. Biosludge addition to soil increased the volume of different pore types, especially micropores, which enhanced water retention and influenced plant growth. Regression modelling identified leachate Si and Fe concentrations, and biomass K content as the most influential variables for fresh biomass weight, plant height and the number of tillers, respectively. Biosludge addition to the soil around the optimum level did not cause detrimental changes to the resulting leachate and plant biomass. The findings of this work could lead to minimization of biosludge landfilling and allow for savings in fertilizers and irrigation water in arid regions

Dataset comparing the growth of fodder crops and soil structure dynamics in an industrial biosludge amended arid soil

The dataset in this work compares the response of two fodder crops, alfalfa (Medicago sativa) and buffel grass (Cenchrus ciliaris), to industrial biosludge amendment of an arid soil in the State of Qatar. It also evaluates the response of soil structure parameters in the biosludge-amended soils containing the different fodder crops. The dataset relates to our previously published works detailed subsequently. The underlying data comparing the water storage capacity and pore structure evolution of the planted soils treated with 0.75, 1.5, and 3% biosludge contents, which showed good outcomes in the companion articles, alongside soil only and soil-fertilizer controls, are presented. These are shown in terms of the percentage of irrigation water leached, and variations in the logarithmic mean T2 (i.e., T2LM - a proxy for mean pore size) and cumulative porosity, respectively. Data on plant growth parameters such as the number of days to flowering, plant height, and aboveground fresh biomass weight in individual replicates of the different treatments as a percentage of the soil-fertilizer control are also shown. The dataset shows the different responses of both plants and the planted soils to amendments with industrial biosludge from the wastewater treatment plant of a gas-to-liquid (GTL) plant