Monitoring tropical forests under a functional perspective with satellite‐based vegetation optical depth

Monitoring ecosystem functions in forests is a priority in a climate change scenario, as climate‐induced events may initially alter the functions more than slow‐changing attributes, such as biomass. The ecosystem functional properties (EFPs) are quantities that characterize key ecosystem processes. They can be derived by point observations of gas and energy exchanges between the ecosystems and the atmosphere that are collected globally at FLUXNET flux tower sites and upscaled at ecosystem level. The properties here considered describe the ability of ecosystems to optimize the use of resources for carbon uptake. They represent functional forest information, are dependent on environmental drivers, linked to leaf traits and forest structure, and influenced by climate change effects. The ability of vegetation optical depth (VOD) to provide forest functional information is investigated using 2011–2014 satellite data collected by the Soil Moisture and Ocean Salinity mission and using the EFPs as reference dataset. Tropical forests in Africa and South America were analyzed, also according to ecological homogeneous units. VOD jointly with water deficit information explained 93% and 87% of the yearly variability in both flux upscaled maximum gross primary productivity and light use efficiency functional properties, in Africa and South America forests respectively. Maps of the retrieved properties evidenced changes in forest functional responses linked to anomalous climate‐induced events during the study period. The findings indicate that VOD can support the flux upscaling process in the tropical range, affected by high uncertainty, and the detection of forest anomalous functional responses. Preliminary temporal analysis of VOD and EFP signals showed fine‐grained variability in periodicity, in signal dephasing, and in the strength of the relationships. In selected drier forest types, these satellite data could also support the monitoring of functional dynamics.     

Evaluation of oil dispersion formulation of nematophagus fungus,Pochonia chlamydosporia against root-knot nematode,Meloidogyne incognita in cucumber

Root-knot nematode, Meloidogyne incognita is considered as one of the major non-insect pests of crops. The management of these root feeders becomes highly challenging due to a strong host-parasitic relationship. Pochonia chlamydosporia is a nematophagus fungus that colonizes eggs of nematodes. This study aimed to test the efficacy of P. chlamydosporia (NAIMCC-SF0039) against M. incognita. An oil dispersion formulation of P. chlamydosporia was prepared using emulsifiers and vegetable oil. This formulation had a shelf-life of 90 days (3.3 × 10⁸ CFU/mL) at room temperature (28 ± 1 °C). The inhibitory effect of oil formulation was tested against M. incognita by inoculating it on the egg mass. We found that colonization of the gelatinous matrix occurred on the third day of inoculation followed by complete egg parasitization on the seventh day. A greenhouse trial was laid out to evaluate the biocontrol potential of P. chlamydosporia in cucumber (Cucumis sativus). The results showed that the application of talc formulation of P. chlamydosporia at the rate of 1 kg per acre during planting, followed by delivery of 1 L of oil dispersion formulation through drip lines at 30-day intervals caused the highest reduction of nematode infestation. This treatment recorded 67.9 and 57.5% reduction in egg masses and soil nematode population respectively than that of control.     

An ex-situ and in vitro approach towards the bioremediation of carcinogenic hexavalent chromium

Abstract

Chromium, ranking the second most among toxic heavy metal pollutants in the world, causing respiratory, cardiovascular and renal problems in human beings is under study herein. We examined the biological remediation of the carcinogenic Cr (VI) polluted soils by indigenous yeast isolates. The total element analysis of the treated sample was determined by Energy Dispersion X-ray Micro Analysis (EDXMA). The sample under study was observed to have a high concentration of 458.29 mgKg^?1 Cr (VI), determined by Atomic Absorption Spectroscopy (AAS) and DPC analysis. The most tolerant isolate designated as CSR was used for in vitro and ex-situ bioremediation studies of Cr (VI). The isolate achieved significant bioremediation of 86% in vitro and 75.12% in ex-situ method. The optimal conditions for in vitro bioremediation were found to be 28?°C and a pH of 6. The ITS1, 5.8S rRNA and D1, D2 domain of LSU rRNA gene characterization of the isolate CSR illustrated that it belongs to Ustilago genera. The isolate was deposited in NCBI GenBank as Ustilago sp. CSR (KY284846). Although, Ustilago is generally a pathogenic fungus, our study opens up the scope of using Ustilago spp. for bioremediation of the carcinogenic heavy metal Chromium.     

“21世纪海上丝绸之路”沿线典型城市气溶胶光学厚度时空分布特征与成因

气溶胶作为悬浮分散在大气中的固态或液态微小颗粒物,对人体健康具有巨大影响,探索区域大气气溶胶变化特征和规律,对监测评估大气环境质量(尤其是人口聚集的城市地区)具有重要意义。本研究以东南亚、南亚和西亚“21世纪海上丝绸之路”沿线9个典型支点城市为例,基于MCD19A2 550 nm AOD产品,结合气象因素、土地利用数据和夜间灯光数据等,探讨亚洲发达城市区域带气溶胶的时空分布、变化特征、影响因素和成因驱动。结果表明: 2013—2018年间,9个城市气溶胶光学厚度(AOD)年平均值从高到低依次为卡拉奇、多哈、吉大港、曼谷、科伦坡、胡志明市、新加坡、瓜达尔和仰光。受区域气候系统和气溶胶类型的影响,各地区年、季和月AOD时序特征差异显著。大多数城市AOD高值区主要分布在城市中心区域或社会经济(如工农业)快速发展的地区。不同气象因素对各地区AOD的影响略有差异:降雨量、相对湿度和风速对东南亚4个城市(胡志明市、曼谷、新加坡和仰光)的影响较大,温度、相对湿度和风速与南亚4个城市(吉大港、科伦坡、卡拉奇和瓜达尔)和西亚多哈的AOD相关性较大。城市区域AOD受社会经济、城市化发展以及气象因素耦合协同作用的综合影响,其中,卡拉奇表现得最显著。     

Characterization of zinc oxide nanocrystals with different morphology for application in ultraviolet‐light photocatalytic performances on rhodamine B

ZnO nanostructures of different morphology (nanorods, nano‐leaf, nanotubes) were favourably grown using a chemical precipitation process. The prepared ZnO nanostructures were characterized systematically using absorption spectroscopy, emission spectroscopy, X‐ray diffraction (XRD), scanning electron microscopy (SEM) and Fourier transform infrared studies. XRD results showed the hexagonal wurtzite phase of the synthesized ZnO nanostructures. Structural properties such as average crystallite size, lattice constants, volume of the unit cell, atomic fraction, and structural bonds were also studied. The optical band gap of the synthesized ZnO nanocrystals varied from 3.52 eV to 3.69 eV with high quantum yield of the blue emission (~420 nm). Urbach energy for ZnO nanocrystals was calculated to be 0.702 eV, 0.901 eV, and 0.993 eV for nanorods, nano‐leaf, and tube like ZnO crystals, respectively. Morphology of the fabricated nanostructures was investigated using SEM. Photocatalytic degradation of rhodamine B (Rh B) in solution under UV irradiation was explored with different ZnO morphology. Photocatalytic experiments showed that ZnO nano‐leaf had a higher degradation rate of photocatalytic activity of photodegrading Rh B compared with the other tube shape and rods shape nanostructures. The Rh B dye degraded considerably by ～79.05%, 74.41%, and 69.8% within 120 min in the presence of the as‐fabricated fern nano‐leaf, nanotubes, and nanorods of the ZnO nanocrystals at room temperature.     

Deep Learning Using Havrda-Charvat Entropy for Classification of Pulmonary Optical Endomicroscopy

1) ObjectivePulmonary optical endomicroscopy (POE) is an imaging technology in real time. It allows to examine pulmonary alveoli at a microscopic level. Acquired in clinical settings, a POE image sequence can have as much as 25% of the sequence being uninformative frames (i.e. pure-noise and motion artifacts). For future data analysis, these uninformative frames must be first removed from the sequence. Therefore, the objective of our work is to develop an automatic detection method of uninformative images in endomicroscopy images.2) Material and methodsWe propose to take the detection problem as a classification one. Considering advantages of deep learning methods, a classifier based on CNN (Convolutional Neural Network) is designed with a new loss function based on Havrda-Charvat entropy which is a parametrical generalization of the Shannon entropy. We propose to use this formula to get a better hold on all sorts of data since it provides a model more stable than the Shannon entropy.3) ResultsOur method is tested on one POE dataset including 3895 distinct images and is showing better results than using Shannon entropy and behaves better with regard to the problem of overfitting. We obtain 70% of accuracy with Shannon entropy versus 77 to 79% with Havrda-Charvat.4) ConclusionWe can conclude that Havrda-Charvat entropy is better suited for restricted and or noisy datasets due to its generalized nature. It is also more suitable for classification in endomicroscopy datasets.     

Macular pigment and macular volume in eyes of patients with cystic fibrosis

Abstract

Background. Because patients with cystic fibrosis (CF) are living longer, chronic malabsorption of carotenoids associated with CF resulting in decreased macular pigment (MP) may affect macular long-term health in later-life pathology. This study compared the macular pigment optical density (MPOD) and corresponding central macular volume (MV) of adult CF subjects and age-matched normal controls subjects to determine whether chronic malabsorption associated with CF could adversely affect macular photoreceptor anatomy. Objective. Our aim was to compare MPOD with measurements of central MV in CF patients with age-matched controls. Design. In nine adult CF patients (ages: 29–46) without a history of carotenoid supplementation or known retinal or optic nerve disease MPOD and MV were measured by heterochromatic flicker photometry (HFP) and optical coherence tomography (OCT), respectively, and compared to results obtained from 14 age-matched controls. Results. MPOD was significantly reduced at 15’ and 30’ eccentricities in CF subjects compared to normal subjects (mean difference ?0.21 at 15’, ?0.25 at 30’, p < 0.005). No significant difference, in MV noted at any of the eccentricities tested between CF and normal subjects (CF: normal MV ratios ranged from 0.94 to 1.1 for all eccentricities with p > 0.1 at all eccentricities). Best corrected vision acuity and fundus examination were normal in all subjects. Conclusions. Unsupplemented CF patients have markedly lower levels of macular carotenoids (e.g., lutein and zeaxanthin), but well-maintained visual function and no significant reductions in central MV primarily composed of macular photoreceptors. Future studies are needed to determine whether the lifelong decrease in protective central retinal carotenoids predisposes CF patients to later-life retinal pathology.     

Microplate-based,label-free detection of biomolecular interactions: applications in proteomics

This review describes a new type of label-free optical biosensor that is inexpensively manufactured from continuous sheets of plastic film and incorporated into standard format microplates to enable highly sensitive, high-throughput detection of small molecules, proteins and cells. The biosensor and associated detection instrumentation are applied to review two fundamental limiting issues for assays in proteomics research and drug discovery: requirement for quantitative measurement of protein concentration and specific activity, and measurements made with complex systems in highly parallel measurements. SRU BIosystems, Inc.’s BIND? label-free detection will address these issues using data examples for hybridoma screening, epitope binning and mapping, small-molecule screening, and cell-based functional assays. The review describes several additional applications that are under development for the system, and the key issues that will drive adoption of the technology over the next 5 years.     

Satellite microwave detection of boreal forest recovery from the extreme 2004 wildfires in Alaska and Canada

The rate of vegetation recovery from boreal wildfire influences terrestrial carbon cycle processes and climate feedbacks by affecting the surface energy budget and land‐atmosphere carbon exchange. Previous forest recovery assessments using satellite optical‐infrared normalized difference vegetation index (NDVI) and tower CO₂ eddy covariance techniques indicate rapid vegetation recovery within 5–10 years, but these techniques are not directly sensitive to changes in vegetation biomass. Alternatively, the vegetation optical depth (VOD) parameter from satellite passive microwave remote sensing can detect changes in canopy biomass structure and may provide a useful metric of post‐fire vegetation response to inform regional recovery assessments. We analyzed a multi‐year (2003–2010) satellite VOD record from the NASA AMSR‐E (Advanced Microwave Scanning Radiometer for EOS) sensor to estimate forest recovery trajectories for 14 large boreal fires from 2004 in Alaska and Canada. The VOD record indicated initial post‐fire canopy biomass recovery within 3–7 years, lagging NDVI recovery by 1–5 years. The VOD lag was attributed to slower non‐photosynthetic (woody) and photosynthetic (foliar) canopy biomass recovery, relative to the faster canopy greenness response indicated from the NDVI. The duration of VOD recovery to pre‐burn conditions was also directly proportional (P < 0.01) to satellite (moderate resolution imaging spectroradiometer) estimated tree cover loss used as a metric of fire severity. Our results indicate that vegetation biomass recovery from boreal fire disturbance is generally slower than reported from previous assessments based solely on satellite optical‐infrared remote sensing, while the VOD parameter enables more comprehensive assessments of boreal forest recovery.