Towards Identification of Relevant Variables in the observed Aerosol Optical Depth Bias between MODIS and AERONET observations

Measurements made by satellite remote sensing, Moderate Resolution Imaging Spectroradiometer (MODIS), and globally distributed Aerosol Robotic Network (AERONET) are compared. Comparison of the two datasets measurements for aerosol optical depth values show that there are biases between the two data products. In this paper, we present a general framework towards identifying relevant set of variables responsible for the observed bias. We present a general framework to identify the possible factors influencing the bias, which might be associated with the measurement conditions such as the solar and sensor zenith angles, the solar and sensor azimuth, scattering angles, and surface reflectivity at the various measured wavelengths, etc. Specifically, we performed analysis for remote sensing Aqua-Land data set, and used machine learning technique, neural network in this case, to perform multivariate regression between the ground-truth and the training data sets. Finally, we used mutual information between the observed and the predicted values as the measure of similarity to identify the most relevant set of variables. The search is brute force method as we have to consider all possible combinations. The computations involves a huge number crunching exercise, and we implemented it by writing a job-parallel program

The Spatial Sensitivity Function of a Light Sensor

The Spatial Sensitivity Function (SSF) is used to quantify a detector's sensitivity to a spatially-distributed input signal. By weighting the incoming signal with the SSF and integrating, the overall scalar response of the detector can be estimated. This project focuses on estimating the SSF of a light intensity sensor consisting of a photodiode. This light sensor has been used previously in the Knuth Cyberphysics Laboratory on a robotic arm that performs its own experiments to locate a white circle in a dark field (Knuth et al., 2007). To use the light sensor to learn about its surroundings, the robot's inference software must be able to model and predict the light sensor's response to a hypothesized stimulus. Previous models of the light sensor treated it as a point sensor and ignored its spatial characteristics. Here we propose a parametric approach where the SSF is described by a mixture of Gaussians (MOG). By performing controlled calibration experiments with known stimulus inputs, we used nested sampling to estimate the SSF of the light sensor using an MOG model with the number of Gaussians ranging from one to five. By comparing the evidence computed for each MOG model, we found that one Gaussian is sufficient to describe the SSF to the accuracy we require. Future work will involve incorporating this more accurate SSF into the Bayesian machine learning software for the robotic system and studying how this detailed information about the properties of the light sensor will improve robot's ability to learn.Comment: Published in MaxEnt 200

Studies on the Recovery of Bleached Corals in Andaman: Fishes as Indicators of Reef Health

The corals in Andaman and Nicobar Islands suffered extensive bleaching during April 2010 to the extent of 60–70 % due to elevated sea surface temperature (SST) and a significant portion of that is hitherto dead. This study evaluates the degree of recovery of the coral reefs and reef fishes, a year after the event. Line intercept transect (LIT) surveys were conducted in three sites, namely, North Bay, Tarmugli and Chidiyatapu for assessing coral cover together with visual census of reef fishes along the same transects. It was observed that all sites were quite badly affected during the bleaching period with more than 95 % of the corals being fully or partially bleached. Out of the bleached corals, only 54 % recovered at North Bay, whereas Tarmugli and Chidiyatapu exhibited 81 and 86 % recovery, respectively. The collapse of coral reef systems affected the abundance and diversity among fish species. Due to recovery and new recruitment of corals, live coral cover has increased, and consequently,, abundance of fishes seems to have increased. Understanding the associations of fishes and corals could possibly lead to selection of certain species of fishes as indicators of reef health. The results of the study lead to the hypothesis that fishes, especially those belong to the families, Chaetodontidae, Pomacentridae, Acanthuridae and Scaridae can be potential indicators of reef health

Detection, occurrence, and fate of emerging contaminants in agricultural environments (2019)

A review of 82 papers published in 2018 is presented. The topics ranged from detailed descriptions of analytical methods, to fate and occurrence studies, to ecological effects and sampling techniques for a wide variety of emerging contaminants likely to occur in agricultural environments. New methods and studies on veterinary pharmaceuticals, microplastics, and engineered nanomaterials in agricultural environments continue to expand our knowledge base on the occurrence and potential impacts of these compounds. This review is divided into the following sections: Introduction, Analytical Methods, Fate and Occurrence, Pharmaceutical Metabolites, Anthelmintics, Microplastics, and Engineered Nanomaterials

Enhancing the Stretchability of Two-Dimensional Materials through Kirigami: A Molecular Dynamics Study on Tungsten Disulfide

In recent years, the 'kirigami' technique has gained significant attention for creating meta-structures and meta-materials with exceptional characteristics, such as unprecedented stretchability. These properties, not typically inherent in the original materials or structures, present new opportunities for applications in stretchable electronics and photovoltaics. However, despite its scientific and practical significance, the application of kirigami patterning on a monolayer of tungsten disulfide (WS2), a van der Waals material with exceptional mechanical, electronic, and optical properties, has remained unexplored. This study utilizes molecular dynamics (MD) simulations to investigate the mechanical properties of monolayer WS2 with rectangular kirigami cuts. We find that, under tensile loading, the WS2 based kirigami structure exhibits a notable increase in tensile strain and a decrease in strength, thus demonstrating the effectiveness of the kirigami cutting technique in enhancing the stretchability of monolayer WS2. Additionally, increasing the overlap ratio enhances the stretchability of the structure, allowing for tailored high strength or high strain requirements. Furthermore, our observations reveal that increasing the density of cuts and reducing the length-to-width ratio of the kirigami nanosheet further improve the fracture strain, thereby enhancing the overall stretchability of the proposed kirigami patterned structure of WS2.Comment: 19 pages, 5 figure

Occurrence of arsenite in surface and groundwater associated with a perennial stream located in Western Nebraska, USA

Dissolved arsenic typically results from chemical weathering of arsenic rich sediments and is most often found in oxidized forms in surface water. The mobility of arsenic is controlled by its valence state and also by its association with iron oxides minerals, the forms of which are both influenced by abiotic and biotic processes in aqueous environment. In this study, speciation methods were used to measure and confirm the presence of reduced arsenic species in the surface water of Frenchman creek, a gaining stream that crosses the Colorado- Nebraska border. Selective extraction analysis of aquifer and stream bed sediments shows that the bulk of the arsenic occurs with labile iron-rich oxy(hydroxide) minerals. Total dissolved arsenic in surface and groundwater ranged from ~3–18 μg L–1, and reduced arsenic species comprise about 41% of the total dissolved arsenic (16.0 μg L–1) in Frenchman creek. Leachable arsenic in the aquifer sediment samples ranged up to 1553 μg kg–1, while samples from Frenchman creek bed sediments contained 4218 μg kg–1. Dynamic surface and groundwater interaction sustains arsenite in iron-rich surface headwaters, and the implied toxicity of reduced arsenic in this hydrogeological setting, which can be important in surface water environments around the globe

Estimation and Bias Correction of Aerosol Abundance using Data-driven Machine Learning and Remote Sensing

Air quality information is increasingly becoming a public health concern, since some of the aerosol particles pose harmful effects to peoples health. One widely available metric of aerosol abundance is the aerosol optical depth (AOD). The AOD is the integrated light extinction coefficient over a vertical atmospheric column of unit cross section, which represents the extent to which the aerosols in that vertical profile prevent the transmission of light by absorption or scattering. The comparison between the AOD measured from the ground-based Aerosol Robotic Network (AERONET) system and the satellite MODIS instruments at 550 nm shows that there is a bias between the two data products. We performed a comprehensive analysis exploring possible factors which may be contributing to the inter-instrumental bias between MODIS and AERONET. The analysis used several measured variables, including the MODIS AOD, as input in order to train a neural network in regression mode to predict the AERONET AOD values. This not only allowed us to obtain an estimate, but also allowed us to infer the optimal sets of variables that played an important role in the prediction. In addition, we applied machine learning to infer the global abundance of ground level PM2.5 from the AOD data and other ancillary satellite and meteorology products. This research is part of our goal to provide air quality information, which can also be useful for global epidemiology studies

Molecular Signaling Network and Therapeutic Developments in Breast Cancer Brain Metastasis

Breast cancer (BC) is one of the most frequently diagnosed cancers in women worldwide. It has surpassed lung cancer as the leading cause of cancer-related death. Breast cancer brain metastasis (BCBM) is becoming a major clinical concern that is commonly associated with ER-ve and HER2+ve subtypes of BC patients. Metastatic lesions in the brain originate when the cancer cells detach from a primary breast tumor and establish metastatic lesions and infiltrate near and distant organs via systemic blood circulation by traversing the BBB. The colonization of BC cells in the brain involves a complex interplay in the tumor microenvironment (TME), metastatic cells, and brain cells like endothelial cells, microglia, and astrocytes. BCBM is a significant cause of morbidity and mortality and presents a challenge to developing successful cancer therapy. In this review, we discuss the molecular mechanism of BCBM and novel therapeutic strategies for patients with brain metastatic BC

Homo-dimerization and ligand binding by the leucine-rich repeat domain at RHG1/RFS2 underlying resistance to two soybean pathogens

BACKGROUND: The protein encoded by GmRLK18-1 (Glyma_18_02680 on chromosome 18) was a receptor like kinase (RLK) encoded within the soybean (Glycine max L. Merr.) Rhg1/Rfs2 locus. The locus underlies resistance to the soybean cyst nematode (SCN) Heterodera glycines (I.) and causal agent of sudden death syndrome (SDS) Fusarium virguliforme (Aoki). Previously the leucine rich repeat (LRR) domain was expressed in Escherichia coli. RESULTS: The aims here were to evaluate the LRRs ability to; homo-dimerize; bind larger proteins; and bind to small peptides. Western analysis suggested homo-dimers could form after protein extraction from roots. The purified LRR domain, from residue 131–485, was seen to form a mixture of monomers and homo-dimers in vitro. Cross-linking experiments in vitro showed the H274N region was close (<11.1 A) to the highly conserved cysteine residue C196 on the second homo-dimer subunit. Binding constants of 20–142 nM for peptides found in plant and nematode secretions were found. Effects on plant phenotypes including wilting, stem bending and resistance to infection by SCN were observed when roots were treated with 50 pM of the peptides. Far-Western analyses followed by MS showed methionine synthase and cyclophilin bound strongly to the LRR domain. A second LRR from GmRLK08-1 (Glyma_08_g11350) did not show these strong interactions. CONCLUSIONS: The LRR domain of the GmRLK18-1 protein formed both a monomer and a homo-dimer. The LRR domain bound avidly to 4 different CLE peptides, a cyclophilin and a methionine synthase. The CLE peptides GmTGIF, GmCLE34, GmCLE3 and HgCLE were previously reported to be involved in root growth inhibition but here GmTGIF and HgCLE were shown to alter stem morphology and resistance to SCN. One of several models from homology and ab-initio modeling was partially validated by cross-linking. The effect of the 3 amino acid replacements present among RLK allotypes, A87V, Q115K and H274N were predicted to alter domain stability and function. Therefore, the LRR domain of GmRLK18-1 might underlie both root development and disease resistance in soybean and provide an avenue to develop new variants and ligands that might promote reduced losses to SCN

HISTO-ARCHITECTURE OF THE SMALL INTESTINE OF GAROLE SHEEP

Ruminants like sheep are prone to infections through ingestion of contaminated feed and water since they are reared on a free-ranging system. The gut immune system plays a major role in fighting the pathogens that gain entry through the oral route. The present study was conducted to explore the histological organization of the small intestine of the adult Garole sheep as it is the major site of absorption in the intestine. The intestine samples were collected from 10 healthy sheep. Tissues collected from the duodenum, jejunum, and ileum were fixed in a 10% neutral buffered formalin solution and processed for histological studies by following standard protocols. The small intestine revealed four distinct layers namely tunica mucosa, tunica submucosa, tunica muscularis, and tunica serosa inside out. The tunica mucosa consisted of lamina epithelialis, lamina propria with intestinal glands, and lamina muscularis. The tunica mucosa presented numerous villi of different shapes and heights lined by columnar epithelial cells with Goblet’s cells, lymphocytes, Paneth’s cells, etc. interspersed among them. Brunner’s glands were present in the initial portion of the duodenum and Peyer’s patches were observed in the middle ileum