Prediction of Soil Water Content and Electrical Conductivity using Random Forest Methods with UAV Multispectral and Ground-Coupled Geophysical Data

The volumetric water content (VWC) of soil is a critical parameter in agriculture, as VWC strongly influences crop yield, provides nutrients to plants, and maintains the microbes that are needed for the biological health of the soil. Measuring VWC is difficult, as it is spatially and tempo-rally heterogeneous, and most agricultural producers use point measurements that cannot fully capture this parameter. Electrical conductivity (EC) is another soil parameter that is useful in agricul-ture, since it can be used to indicate soil salinity, soil texture, and plant nutrient availability. Soil EC is also very heterogeneous; measuring EC using conventional soil sampling techniques is very time consuming and often fails to capture the variability in EC at a site. In contrast to the point-based methods used to measure VWC and EC, multispectral data acquired with unmanned aerial vehicles (UAV) can cover large areas with high resolution. In agriculture, multispectral data are often used to calculate vegetation indices (VIs). In this research UAV-acquired VIs and raw multispectral data were used to predict soil VWC and EC. High-resolution geophysical methods were used to acquire more than 41,000 measurements of VWC and 8,000 measurements of EC in 18 traverses across a field that contained 56 experimental plots. The plots varied by crop type (corn, soybeans, and al-falfa) and drainage (no drainage, moderate drainage, high drainage). Machine learning was per-formed using the random forest method to predict VWC and EC using VIs and multispectral data. Prediction accuracy was determined for several scenarios that assumed different levels of knowledge about crop type or drainage. Results showed that multispectral data improved prediction of VWC and EC, and the best predictions occurred when both the crop type and degree of drainage were known, but drainage was a more important input than crop type. Predictions were most accurate in drier soil, which may be due to the lower overall variability of VWC and EC under these conditions. An analysis of which multispectral data were most important showed that NDRE, VARI, and blue band data improved predictions the most. The final conclusions of this study are that inexpensive UAV-based multispectral data can be used to improve estimation of heterogenous soil properties, such as VWC and EC in active agricultural fields. In this study, the best estimates of these properties were obtained when the agriculture parameters in a field were fairly homogeneous (one crop type and the same type of drainage throughout the field), although improvements were observed even when these conditions were not met. The multispectral data that were most useful for prediction were those that penetrated deeper into the soil canopy or were sensitive to bare soil

Prediction of Soil Water Content and Electrical Conductivity using Random Forest Methods with UAV Multispectral and Ground-Coupled Geophysical Data

The volumetric water content (VWC) of soil is a critical parameter in agriculture, as VWC strongly influences crop yield, provides nutrients to plants, and maintains the microbes that are needed for the biological health of the soil. Measuring VWC is difficult, as it is spatially and tempo-rally heterogeneous, and most agricultural producers use point measurements that cannot fully capture this parameter. Electrical conductivity (EC) is another soil parameter that is useful in agricul-ture, since it can be used to indicate soil salinity, soil texture, and plant nutrient availability. Soil EC is also very heterogeneous; measuring EC using conventional soil sampling techniques is very time consuming and often fails to capture the variability in EC at a site. In contrast to the point-based methods used to measure VWC and EC, multispectral data acquired with unmanned aerial vehicles (UAV) can cover large areas with high resolution. In agriculture, multispectral data are often used to calculate vegetation indices (VIs). In this research UAV-acquired VIs and raw multispectral data were used to predict soil VWC and EC. High-resolution geophysical methods were used to acquire more than 41,000 measurements of VWC and 8,000 measurements of EC in 18 traverses across a field that contained 56 experimental plots. The plots varied by crop type (corn, soybeans, and al-falfa) and drainage (no drainage, moderate drainage, high drainage). Machine learning was per-formed using the random forest method to predict VWC and EC using VIs and multispectral data. Prediction accuracy was determined for several scenarios that assumed different levels of knowledge about crop type or drainage. Results showed that multispectral data improved prediction of VWC and EC, and the best predictions occurred when both the crop type and degree of drainage were known, but drainage was a more important input than crop type. Predictions were most accurate in drier soil, which may be due to the lower overall variability of VWC and EC under these conditions. An analysis of which multispectral data were most important showed that NDRE, VARI, and blue band data improved predictions the most. The final conclusions of this study are that inexpensive UAV-based multispectral data can be used to improve estimation of heterogenous soil properties, such as VWC and EC in active agricultural fields. In this study, the best estimates of these properties were obtained when the agriculture parameters in a field were fairly homogeneous (one crop type and the same type of drainage throughout the field), although improvements were observed even when these conditions were not met. The multispectral data that were most useful for prediction were those that penetrated deeper into the soil canopy or were sensitive to bare soil

Plasma exchange for COVID-19 thrombo-inflammatory disease.

Severe COVID-19 disease is a hyperinflammatory, pro-thrombotic state. We undertook plasma exchange (PEX) to determine its effects on organ function and thrombo-inflammatory markers. Seven critically ill adults with severe COVID-19 respiratory failure (PaO2:FiO2 ratio 800 IU/L and D-dimer >1000 μg/L (or doubling from baseline) received PEX, daily, for a minimum of 5 days. No other immunomodulatory medications were initiated during this period. Seven patients matched for age and baseline biochemistry were a comparator group. Coagulation screening revealed no evidence of coagulopathy. However, von Willebrand Factor (VWF) activity, antigen and VWF antigen: ADAMTS13 ratio, Factor VIII and D-dimers were all elevated. Following 5 days of PEX, plasma levels of all the above, and ferritin levels, were significantly reduced (P < .05) while lymphocyte counts normalized (P < .05). The PaO2:FiO2 ratio increased from a median interquartile range (IQR) of 11.6 (10.8-19.7) kPa to 18.1 (16.0-25.9) kPa (P < .05). Similar improvements were not observed in controls. Acute kidney injury (AKI) occurred among five patients in the control arm but not in patients receiving PEX. PEX improved oxygenation, decreased the incidence of AKI, normalized lymphocyte counts and reduced circulating thrombo-inflammatory markers including D-Dimer and VWF Ag:ADAMTS13 ratio

Deposition of fluoride on enamel surfaces released from varnishes is limited to vicinity of fluoridation site

The aim of the in-situ study was to determine fluoride uptake in non-fluoridated, demineralized enamel after application of fluoride varnishes on enamel samples located at various distances from the non-fluoridated samples. All enamel samples used were demineralized with acidic hydroxyethylcellulose before the experiment. Intra-oral appliances were worn by ten volunteers in three series: (1, Mirafluorid, 0.15% F; 2, Duraphat, 2.3% F and 3, unfluoridated controls) of 6 days each. Each two enamel samples were prepared from 30 bovine incisors. One sample was used for the determination of baseline fluoride content (BFC); the other was treated according to the respective series and fixed in the intra-oral appliance for 6 days. Additionally, from 120 incisors, each four enamel samples were prepared (one for BFC). Three samples (a–c) were placed into each appliance at different sites: (a) directly neighboured to the fluoridated specimen (=next), (b) at 1-cm distance (=1 cm) and (c) in the opposite buccal aspect of the appliance (=opposite). At these sites, new unfluoridated samples were placed at days 1, 3 and 5, which were left in place for 1 day. The volunteers brushed their teeth and the samples with fluoridated toothpaste twice per day. Both the KOH-soluble and structurally bound fluoride were determined in all samples to determine fluoride uptake and were statistically analyzed. One day, after fluoridation with Duraphat, KOH-soluble fluoride uptake in specimen a (=next) was significantly higher compared to the corresponding samples of both the control and Mirafluorid series, which in turn were not significantly different from each other. At all other sites and time points, fluoride uptake in the enamel samples were not different from controls for both fluoride varnishes. Within the first day after application, intra-oral-fluoride release from the tested fluoride varnish Duraphat leads to KOH-soluble fluoride uptake only in enamel samples located in close vicinity to the fluoridation site

Tuning the Coordination Structure of Cu-N-C Single Atom Catalysts for Simultaneous Electrochemical Reduction of CO2 and NO3 - to Urea

Closing both the carbon and nitrogen loops is a critical venture to support the establishment of the circular, net-zero carbon economy. Although single atom catalysts (SACs) have gained interest for the electrochemical reduction reactions of both carbon dioxide (CO₂RR) and nitrate (NO₃RR), the structure–activity relationship for Cu SAC coordination for these reactions remains unclear and should be explored such that a fundamental understanding is developed. To this end, the role of the Cu coordination structure is investigated in dictating the activity and selectivity for the CO₂RR and NO3RR. In agreement with the density functional theory calculations, it is revealed that Cu-N₄ sites exhibit higher intrinsic activity toward the CO₂RR, whilst both Cu-N₄ and Cu-N₄−x-Cx sites are active toward the NO3RR. Leveraging these findings, CO₂RR and NO₃RR are coupled for the formation of urea on Cu SACs, revealing the importance of *COOH binding as a critical parameter determining the catalytic activity for urea production. To the best of the authors’ knowledge, this is the first report employing SACs for electrochemical urea synthesis from CO₂RR and NO₃RR, which achieves a Faradaic efficiency of 28% for urea production with a current density of −27 mA cm–2 at −0.9 V versus the reversible hydrogen electrode.Josh Leverett, Thanh Tran-Phu, Jodie A. Yuwono, Priyank Kumar, Changmin Kim, Qingfeng Zhai, Chen Han, Jiangtao Qu, Julie Cairney, Alexandr N. Simonov, Rosalie K. Hocking, Liming Dai, Rahman Daiyan, and Rose Ama

Structural and compositional variations of basic Cu(II) chlorides in the herbertsmithite and gillardite structure field.

© 2017 The Mineralogical Society. This document is the author’s final accepted version of the journal article. You are advised to consult the published version if you wish to cite from it

ESHAP and G-CSF is a superior blood stem cell mobilizing regimen compared to cyclophosphamide 1.5 g m−2 and G-CSF for pre-treated lymphoma patients: a matched pairs analysis of 78 patients

Cyclophosphamide 1.5 g m−2followed by granulocyte colony-stimulating factor (G-CSF) is an effective peripheral blood stem cell (PBSC) mobilizing regimen, but has limited anti-lymphoma activity. We therefore assessed the mobilizing potential of ESHAP (etoposide, ara-C, methylprednisolone and cisplatin), a potent second-line lymphoma regimen followed by G-CSF. The results were compared in 78 patients with relapsed or resistant lymphomas with the use of cyclophosphamide 1.5 g m−2followed by G-CSF in a matched pairs analysis, matching the ESHAP recipients (for predetermined prognostic factors) from a cohort of 178 lymphoma patients mobilized with cyclophosphamide and G-CSF. The total numbers of mononuclear cells collected at apheresis was similar with both regimens but ESHAP plus G-CSF resulted in a significantly higher percentage of CD34+ cells, absolute number of CD34+ cells and GM-CFC (all with P -values < 0.001). The number of patients requiring only one apheresis harvest to achieve a CD34+ cell yield of > 2.0 × 106kg−1was greatly increased in the ESHAP recipients (56/78 vs 17/78, P< 0.001). The total number of progenitor cells collected was not significantly different with the two mobilization regimens because of this higher number of apheresis in the cyclophosphamide group. The proportion of patients who failed to achieve a minimum CD34+ cell target of 1 × 106kg−1with the pooled harvests was less in the ESHAP arm (four patients vs nine patients) despite an increased number of aphereses in the cyclophosphamide recipients. ESHAP plus G-CSF is well tolerated and is an excellent mobilization regimen in patients with pre treated lymphoma. © 2000 Cancer Research Campaig

Influence of hydraulic property correlation on predicted dense nonaqueous phase liquid source zone architecture, mass recovery and contaminant flux

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94685/1/wrcr9972.pd