Synergistic use of Landsat 8 OLI image and airborne LiDAR data for above-ground biomass estimation in tropical lowland rainforests

Developing a robust and cost-effective method for accurately estimating tropical forest's carbon pool over large area is a fundamental requirement for the implementation of Reducing Emissions from Deforestation and forest Degradation (REDD+). This study aims at examining the independent and combined use of airborne LiDAR and Landsat 8 Operational Land Imager (OLI) data to accurately estimate the above-ground biomass (AGB) of primary tropical rainforests in Sabah, Malaysia. Thirty field plots were established in three types of lowland rainforests: alluvial, sandstone hill and heath forests that represent a wide range of AGB density and stand structure. We derived the height percentile and laser penetration variables from the airborne LiDAR and calculated the vegetation indices, tasseled cap transformation values, and the texture measures from Landsat 8 OLI data. We found that there are moderate correlations between the AGB and laser penetration variables from airborne LiDAR data (r = −0.411 to −0.790). For Landsat 8 OLI data, the 6 vegetation indices and the 46 texture measures also significantly correlated with the AGB (r = 0.366–0.519). Stepwise multiple regression analysis was performed to establish the estimation models for independent and combined use of airborne LiDAR and Landsat 8 OLI data. The results showed that the model based on a combination of the two remote sensing data achieved the highest accuracy (R 2 adj = 0.81, RMSE = 17.36%) whereas the models using Landsat 8 OLI data airborne LiDAR data independently obtained the moderate accuracy (R 2 adj = 0.52, RMSE = 24.22% and R 2 adj = 0.63, RMSE = 25.25%, respectively). Our study indicated that texture measures from Landsat 8 OLI data provided useful information for AGB estimation and synergistic use of Landsat 8 OLI and airborne LiDAR data could improve the AGB estimation of primary tropical rainforest.This work was supported by the Ministry of Higher Education of Malaysia [grant number RACE0004-STW-2012]

Through vial impedance spectroscopy (TVIS): A novel approach to process understanding for freeze-drying cycle development

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Through vial impedance spectroscopy (TVIS) provides a new process analytical technology for monitoring a development scale lyophilization process, which exploits the changes in the bulk electrical properties that occur on freezing and subsequent drying of a drug solution. Unlike the majority of uses of impedance spectroscopy, for freeze-drying process development, the electrodes do not contact the product but are attached to the outside of the glass vial which is used to contain the product to provide a non-sample-invasive monitoring technology. Impedance spectra (in frequency range 10 Hz to 1 MHz) are generated throughout the drying cycle by a specially designed impedance spectrometer based on a 1 GΩ trans-impedance amplifier and then displayed in terms of complex capacitance. Typical capacitance spectra have one or two peaks in the imaginary capacitance (i.e., the dielectric loss) and the same number of steps in the real part capacitance (i.e., the dielectric permittivity). This chapter explores the underlying mechanisms that are responsible for these dielectric processes, i.e., the Maxwell-Wagner (space charge) polarization of the glass wall of the vial through the contents of the vial when in the liquid state, and the dielectric relaxation of ice when in the frozen state. In future work, it will be demonstrated how to measure product temperature and drying rates within single vials and multiple (clusters) of vials, from which other critical process parameters, such as heat transfer coefficient and dry layer resistance, may be determined

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children <18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p<0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p<0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p<0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer

Studies of Gauge Boson Pair Production and Trilinear Couplings

The gauge boson pair production processes Wg, WW, WZ, and Zg were studied using pbarp collisions corresponding to an integrated luminosity of ~14 pb-1 at a center-of-mass energy of sqrt(s) = 1.8 TeV. Analysis of Wg prod with subsequent W boson decay to lv (l=e,mu) is reported, including a fit to the pT spectrum of the photons which leads to limits on anomalous WWg couplings. A search for WW prod with subsequent decay to l-lbar-v-vbar (l=e,mu) is presented leading to an upper limit on the WW prod cross section and limits on anomalous WWg and WWZ couplings. A search for high pT W bosons in WW and WZ prod is described, where one W boson decays to an ev and the second W boson or the Z boson decays to two jets. A maximum likelihood fit to the pT spectrum of W bosons resulted in limits on anomalous WWg and WWZ couplings. A combined fit to the three data sets which provided the tightest limits on anomalous WWg and WWZ couplings is also described. Limits on anomalous ZZg and Zgg couplings are presented from an analysis of the photon ET spectrum in Zg events in the decay channels (ee, mu-mu, and v-vbar) of the Z boson.Comment: 77 Pages including 40 Figures. Submitted to PR

Land use evaluation for Kuala Selangor, Malaysia using remote sensing and GIS technologies

Land evaluation is the process of predicting the potential use of land on the basis of its attributes and is essential in identifying the best land management practice for sound land use planning. The key objective of this study is to evaluate landuse/cover in Kuala Selangor district, Selangor as the knowledge about land use and land cover has become increasingly important in Malaysia’s goal to overcome the problems of haphazard, uncontrolled development, deteriorating environmental quality, loss of prime agricultural lands, destruction of important wetlands, and loss of wildlife habitat. The study integrates remote sensing and GIS technologies for landuse/cover evaluation. In evaluating landuse for sustainable use of natural resources several maps were taken as parameters and obtained from digital classification of SPOT 2005 data by means of supervised modes with maximum likelihood algorithm using necessary ground truth data. The vegetation density using Normalized Differential Vegetation Index (NDVI) of Kuala Selangor was classified into five categories, namely, very high (775.51 km2), high (182.61km2), moderate (67.07 km2), low (77.44 km2), and non-vegetation areas (91.35 km2). Soil suitability map and subclasses were prepared to demonstrate how soil varied in behaviour or suitability for specialised purposes. Three soil types were identified including S2 (42%), S4 (45.63%) and S5 (12.37%). Overlay analyses of landuse and landcover with vegetation density, soil suitability and erosion risk were also presented. The actual distribution and area of the classes in all layers were analyse

Reproductive and whole-body toxicity of Ag-doped and -undoped ZIF-8 nanoparticles and the building blocks: An Artemia-based comparative bioassay

The present research assessed, for the first time, toxicity of ZIF-8 (1 mg/L) and the building blocks (0.1 mg/L Zn2+ and 0.4 mg/L 2-methylimidazole (2-MIm)), besides that of AgNPs@ZIF-8 (0.25, 0.5, and 1 mg/L) and AgNO3 (0.1 mg/L) to aquatic organisms. Two consecutive generations (F0 & F1) of Artemia salina were exposed to these chemicals. All of the chemical treatments considerably caused mortality in F0, especially AgNPs@ZIF-8 and AgNO3, whereas F1 displayed notable tolerance and survived comparable to the control group, except in the case of AgNO3 treatment. Similarly, growth indices (weight, mainly in ZIF-8, Zn2+, and 2-MIm; length, in Ag-doped ZIF-8 and AgNO3) were significantly retarded in F0 and especially F1 of all treatments, and 2-MIm caused the greatest length retardation in F0. AgNPs@ZIF-8 (0.5 and 1 mg/L), 2-MIm, and AgNO3 postponed the ovary emergence in about 40%-60% of the exposed F0, and ZIF-8 delayed this phenomenon in some individuals of F0 and F1 up to 6 days. This temporal disturbance was also observed in time to first brood of almost all experimental F0 and F1 groups, with being over 80% of F1 exposed to ZIF-8, 2-MIm, and Zn2+, as well as about 50% of F0 treated with 2-MIm, and Zn2+. The highest neonate number was recorded for F0 and F1 exposed to AgNO3 and Zn2+, while ZIF-8 and, importantly, 2-MIm decreased the reproductivity to the lowest levels in both generations. Generally, the reproductive frequency was significantly decreased in all F0 and F1 treatments, especially 2-MIm, ZIF-8, AgNPs@ZIF-8 (0.25 & 1 mg/L). This study highlighted the neglected importance of 2-MIm in assessing overall toxicity of ZIF-8, and even other organic ligands of MOFs, and also filled a gap in the literature by investigating the potential effect of additives such as AgNPs on the toxicity of ZIF-8 and other MOFs

Synergistic use of Landsat 8 OLI image and airborne LiDAR data for above-ground biomass estimation in tropical lowland rainforests

Developing a robust and cost-effective method for accurately estimating tropical forest's carbon pool over large area is a fundamental requirement for the implementation of Reducing Emissions from Deforestation and forest Degradation (REDD+). This study aims at examining the independent and combined use of airborne LiDAR and Landsat 8 Operational Land Imager (OLI) data to accurately estimate the above-ground biomass (AGB) of primary tropical rainforests in Sabah, Malaysia. Thirty field plots were established in three types of lowland rainforests: alluvial, sandstone hill and heath forests that represent a wide range of AGB density and stand structure. We derived the height percentile and laser penetration variables from the airborne LiDAR and calculated the vegetation indices, tasseled cap transformation values, and the texture measures from Landsat 8 OLI data. We found that there are moderate correlations between the AGB and laser penetration variables from airborne LiDAR data (r = −0.411 to −0.790). For Landsat 8 OLI data, the 6 vegetation indices and the 46 texture measures also significantly correlated with the AGB (r = 0.366–0.519). Stepwise multiple regression analysis was performed to establish the estimation models for independent and combined use of airborne LiDAR and Landsat 8 OLI data. The results showed that the model based on a combination of the two remote sensing data achieved the highest accuracy (R 2 adj = 0.81, RMSE = 17.36%) whereas the models using Landsat 8 OLI data airborne LiDAR data independently obtained the moderate accuracy (R 2 adj = 0.52, RMSE = 24.22% and R 2 adj = 0.63, RMSE = 25.25%, respectively). Our study indicated that texture measures from Landsat 8 OLI data provided useful information for AGB estimation and synergistic use of Landsat 8 OLI and airborne LiDAR data could improve the AGB estimation of primary tropical rainforest.This work was supported by the Ministry of Higher Education of Malaysia [grant number RACE0004-STW-2012]