Using hyperspectral data to quantify water-quality parameters in the Wabash River and its tributaries,Indiana

A hand-held spectrometer was used to collect above-water spectral measurements for measuring optically active water-quality characteristics of the Wabash River and its tributaries in Indiana. Water sampling was undertaken concurrent with spectral measurements to estimate concentrations of chlorophyll (chl) and total suspended solids (TSS). A method for removing sky and Sun glint from field spectra for turbid inland waters was developed and tested. Empirical models were then developed using the corrected field spectra and in situ chl and TSS data. A subset of the field measurements was used for model development and the rest for model validation. Spectral characteristics indicative of waters dominated by different inherent optical properties (IOPs) were identified and used as the basis of selecting bands for empirical model development. It was found that the ratio of the reflectance peak at the red edge (704 nm) with the local minimum caused by chl absorption at 677 nm was a strong predictor of chl concentrations (coefficient of determination (R²) = 0.95). The reflectance peak at 704 nm was also a good predictor for TSS estimation (R² = 0.75). In addition, we also found that reflectance within the near-infrared (NIR) wavelengths (700–890 nm) all showed a strong correlation (0.85–0.91) with TSS concentrations and generated robust models. Results suggest that hyperspectral information provided by field spectrometer can be used to distinguish and quantify water-quality parameters under complex IOP conditions.     

Effect of watershed parameters on mercury distribution in different environmental compartments in the Mobile Alabama River Basin, USA

Total mercury (THg) and mono-methylmercury (MeHg) levels in water, sediment, and largemouth bass (LMB) (Micropterus salmoides) were investigated at 52 sites draining contrasting land use/land cover and habitat types within the Mobile Alabama River Basin (MARB). Aqueous THg was positively associated with iron-rich suspended particles and highest in catchments impacted by agriculture. Sediment THg was positively associated with sediment organic mater and iron content, with the highest levels observed in smaller catchments influenced by wetlands, followed by those impacted by agriculture or mixed forest, agriculture, and wetlands. The lowest sediment THg levels were observed in main river channels, except for reaches impacted by coal mining. Sediment MeHg levels were a positive function of sediment THg and organic matter and aqueous nutrient levels. The highest levels occurred in agricultural catchments and those impacted by elevated sulfate levels associated with coal mining. Aqueous MeHg concentrations in main river channels were as high as those in smaller catchments impacted by agriculture or wetlands, suggesting these areas were sources to rivers. Elevated Hg levels in some LMB were observed across all types of land use and land cover, but factors such as shallow water depth, larger wetland catchment surface area, low aqueous potassium levels, and higher Chl a concentrations were associated with higher Hg burdens, particularly in the Coastal Plain province. It is suggested that the observed large variability in LMB Hg burdens is linked to fish displacement by anglers, differences in food web structure, and sediment biogeochemistry, with surficial sediment iron oxides buffering the flux of MeHg from sediments to deeper water pelagic food webs.     

Deep Learning Approach for Analysis and Characterization of COVID-19

Early diagnosis of a pandemic disease like COVID-19 can help deal with a dire situation and help radiologists and other experts manage human resources more effectively. In a recent pandemic, laboratories perform diagnostics manually, which requires a lot of time and expertise of the laboratorial technicians to yield accurate results. Moreover, the cost of kits is high, and well-equipped labs are needed to perform this test. Therefore, other means of diagnosis is highly desirable. Radiography is one of the existing methods that finds its use in the diagnosis of COVID-19. The radiography observes change in Computed Tomography (CT) chest images of patients, developing a deep learning-based method to extract graphical features which are used for automated diagnosis of the disease ahead of laboratory-based testing. The proposed work suggests an Artificial Intelligence (AI) based technique for rapid diagnosis of COVID-19 from given volumetric chest CT images of patients by extracting its visual features and then using these features in the deep learning module. The proposed convolutional neural network aims to classify the infectious and non-infectious SARS-COV2 subjects. The proposed network utilizes 746 chests scanned CT images of 349 images belonging to COVID-19 positive cases, while 397 belong to negative cases of COVID-19. Our experiment resulted in an accuracy of 98.4%, sensitivity of 98.5%, specificity of 98.3%, precision of 97.1%, and F1-score of 97.8%. The additional parameters of classification error, mean absolute error (MAE), root-mean-square error (RMSE), and Matthew’s correlation coefficient (MCC) are used to evaluate our proposed work. The obtained result shows the outstanding performance for the classification of infectious and non-infectious for COVID-19 cases.     

Granularity-based workflow scheduling algorithm for cloud computing

The workflow scheduling problem has drawn a lot of attention in the research community. This paper presents a workflow scheduling algorithm, called granularity score scheduling (GSS), which is based on the granularity of the tasks in a given workflow. The main objectives of GSS are to minimize the makespan and maximize the average virtual machine utilization. The algorithm consists of three phases, namely B-level calculation, score adjustment and task ranking and scheduling. We simulate the proposed algorithm using various benchmark scientific workflow applications, i.e., Cybershake, Epigenomic, Inspiral and Montage. The simulation results are compared with two well-known existing workflow scheduling algorithms, namely heterogeneous earliest finish time and performance effective task scheduling, which are also applied in cloud computing environment. Based on the simulation results, the proposed algorithm remarkably demonstrates its performance in terms of makespan and average virtual machine utilization.     

Sensitivity and Uncertainty Analysis of the L-THIA-LID 2.1 Model

Sensitivity analysis of a model can identify key variables affecting the performance of the model. Uncertainty analysis is an essential indicator of the precision of the model. In this study, the sensitivity and uncertainty of the Long-Term Hydrologic Impact Assessment-Low Impact Development 2.1 (L-THIA-LID 2.1) model in estimating runoff and water quality were analyzed in an urbanized watershed in central Indiana, USA, using Sobol′‘s global sensitivity analysis method and the bootstrap method, respectively. When estimating runoff volume and pollutant loads for the case in which no best management practices (BMPs) and no low impact development (LID) practices were implemented, CN (Curve Number) was the most sensitive variable and the most important variable when calibrating the model before implementing practices. When predicting water quantity and quality with varying levels of BMPs and LID practices implemented, Ratio_r (Practice outflow runoff volume/inflow runoff volume) was the most sensitive variable and therefore the most important variable to calibrate the model with practices implemented. The output uncertainty bounds before implementing BMPs and LID practices were relatively large, while the uncertainty ranges of model outputs with practices implemented were relatively small. The limited observed data in the same study area and results from other urban watersheds in scientific literature were either well within or close to the uncertainty ranges determined in this study, indicating the L-THIA-LID 2.1 model has good precision.

     

Numerical Study of a Transonic Aircraft Wing for the Prediction of Flutter Failure

In the present paper, computational analysis has been carried out to assess the coupled fluid–structure interaction using NASTRAN finite element approach. A straight swept wing of aluminum material is studied at transonic zone. Analysis has been carried out to find the natural frequency by fluid–structure interaction, then adopting its natural frequency to calculate the reduced frequency for analyzing the flutter effectiveness. A typical case study of plate has been carried out for better understanding the flutter which was then adopted for the swept wing. A fluid–structure interaction phenomenon provides an additional energy to the moving object in terms of frequency in transonic zone. In this speed zone, the divergence speed results a drag that leads to the object to be in a stronger twisting mode resulting in catastrophic failure of the aircraft. The study has defined the flutter boundary of the wing in terms of velocity and frequency which will be very useful in preventing the flutter failure of the aircraft wing through appropriate design improvement or through restriction operational regime.     

EPR and optical absorption studies of Cr3+ doped lithium potassium sulphate single crystals

X-band electron paramagnetic resonance (EPR) studies of Cr³⁺ doped lithium potassium sulphate single crystals have been done at room temperature. The Cr³⁺ crystal field and spin Hamiltonian parameters have been evaluated by employing resonance line positions observed in the EPR spectra for different orientations of external magnetic field. The evaluated g, D and E values are: g_x = 2.0763 ± 0.0002, g_y = 1.9878 ± 0.0002, g_z = 1.8685 ± 0.0002 and D = 549 ± 2 × 10^?4 cm^?1, E = 183 ± 2 × 10^?4 cm^?1. Using EPR data the site symmetry of Cr³⁺ ion in the crystal is discussed. Cr³⁺ ion enters the lattice substitutionally replacing K⁺ site. The optical absorption study of the single crystal is also done in 195–925 nm wavelength range at room temperature. By correlating optical and EPR data the nature of bonding in the crystal is discussed. The calculated values of Racah parameters (B and C), crystal field parameter (D_q) and nephelauxetic parameters (h and k) are obtained as: B = 697, C = 3247, D_q = 2050 cm^?1, h = 1.146 and k = 0.21.     

Preparation and ac electrical characterizations of Cd doped SnO2 nanoparticles

Nanoparticles (NPs) of the Sn_1?xCd_xO₂ (0.0 ≤ x ≤ 0.04) were synthesized through soft chemistry method. These NPs were characterized for structural, morphological and electrical properties by X-ray diffraction, High resolution transmission electron microscopy and dielectric spectroscopy techniques respectively. Structural analysis confirms that all the NPs are having single phase rutile tetragonal structure. The NPs are of spherical shape and average size of these is found to decrease with Cd doping. Dielectric permittivity and AC conductivity of all the NPs were evaluated as a function of frequency and composition at room temperature. The frequency response of ε_r, ε_i, tan δ and σ _ac show that the dispersion is due to the interfacial polarization and these parameters decrease with doping of Cd in the SnO₂ matrix. The possible correlation between observed dielectric properties and size of NPs, and hence disorder in the system are explored.     

Comparison of Computer Models for Estimating Hydrology and Water Quality in an Agricultural Watershed

Various computer models, ranging from simple to complex, have been developed to simulate hydrology and water quality from field to watershed scales. However, many users are uncertain about which model to choose when estimating water quantity and quality conditions in a watershed. This study compared hydrologic/water quality models including Spreadsheet Tool for the Estimation of Pollutant Load (STEPL)-Purdue, Soil and Water Assessment Tool (SWAT), High Impact Targeting (HIT), Long-Term Hydrologic Impact Assessment (L-THIA), Pollutant Load (PLOAD), Spatially and Temporally Distributed Model for Phosphorus Management (STEM-P), Region 5, and ensemble modeling (using STEPL-Purdue, SWAT, L-THIA, PLOAD, and STEM-P). Model capabilities, inputs, and underlying methods to estimate streamflow, surface runoff, baseflow, nutrients, and sediment were examined. Uncalibrated, calibrated, and validated outputs of these models and uncalibrated ensemble modeling in estimating water quantity and quality for a 41.5 km² agricultural watershed in Northeastern Indiana were explored, and suggestions were provided on the selection and use of models. Models need to be selected carefully based on the simulation objectives, data availability, model characteristics, time constraints, and project budgets.

     

Stable analogues of OSB-AMP: potent inhibitors of MenE, the o-succinylbenzoate-CoA synthetase from bacterial menaquinone biosynthesis

MenE, the o-succinylbenzoate (OSB)-CoA synthetase from bacterial menaquinone biosynthesis, is a promising new antibacterial target. Sulfonyladenosine analogues of the cognate reaction intermediate, OSB-AMP, have been developed as inhibitors of the MenE enzymes from Mycobacterium tuberculosis (mtMenE), Staphylococcus aureus (saMenE) and Escherichia coli (ecMenE). Both a free carboxylate and a ketone moiety on the OSB side chain are required for potent inhibitory activity. OSB-AMS (4) is a competitive inhibitor of mtMenE with respect to ATP (K(i) =5.4±0.1 nM) and a noncompetitive inhibitor with respect to OSB (K(i) =11.2±0.9 nM). These data are consistent with a Bi Uni Uni Bi Ping-Pong kinetic mechanism for these enzymes. In addition, OSB-AMS inhibits saMenE with K(i)(app) =22±8 nM and ecMenE with K(i)(OSB) =128±5 nM. Putative active-site residues, Arg222, which may interact with the OSB aromatic carboxylate, and Ser302, which may bind the OSB ketone oxygen, have been identified through computational docking of OSB-AMP with the unliganded crystal structure of saMenE. A pH-dependent interconversion of the free keto acid and lactol forms of the inhibitors is also described, along with implications for inhibitor design.