Framework for global sensitivity analysis in a complex 1D-2D coupled hydrodynamic model: Highlighting its importance on flood management over large data-scarce regions.

Sensitivity analysis determines how perturbation or variation in the values of an independent variable affects a particular dependent variable. The present study attempts to comprehend the sensitivity of the static input parameters on the accuracy of the outputs in a hydrodynamic flood model, which subsequently improves the model accuracy. Hydrodynamic flood modeling is computationally strenuous and data-intensive. Moreover, the accuracy of the flood model outputs is extremely sensitive to the quality of hydrologic and hydraulic inputs, along with a set of static parameters that are traditionally assumed and primarily used for calibration. Therefore, we focus on developing a framework for global sensitivity analysis (GSA) of static input parameters in a 1D-2D coupled hydrodynamic flood modeling system. A set of numerical experiments is conducted by perturbing various combinations of input parameters from their standard (or observed) values to generate flow hydrographs. Nonparametric probability density functions (PDFs) of the river discharge at different locations are compared to calculate the Kullback-Leibler (KL) entropy or KL-divergence, which is used to quantify the sensitivity of the input parameters. We demonstrated the proposed framework on a highly flood-prone rural catchment of the Shilabati River in West Bengal, India, and infer that the sensitivity of the static input parameters is highly dynamic, and their importance varies spatially from the upstream to the downstream of the river. However, Manning's n values of the channel and the banks are significantly sensitive irrespective of the location in the river reach. We suggest that any flood modeling exercise should accompany a GSA, which sets a guideline for the modelers to prioritize the set of sensitive static input parameters during data monitoring, collection, and retrieval. This study is the first attempt at a GSA in a 1D-2D coupled hydrodynamic flood modeling system, whose importance cannot be over-emphasized in any flood modeling platform. The proposed novel framework is generic and can be implemented prior to flood risk analyses for any floodplain management exercise. All free and commercially-available flood models can incorporate the proposed framework for a GSA as an extension toolbox.

A phase field model combined with a genetic algorithm for polycrystalline hafnium zirconium oxide ferroelectrics.

Ferroelectric hafnium zirconium oxide (HZO) thin films show significant promise for applications in ferroelectric random-access memory devices, ferroelectric field-effect transistors, and ferroelectric tunneling junctions. However, there are shortcomings in understanding ferroelectric switching, which is crucial in the operation of these devices. Here a computational model based on the phase field method is developed to simulate the switching behavior of polycrystalline HZO thin films. Furthermore, we introduce a novel approach to optimize the effective Landau coefficients describing the free energy of HZO by combining the phase field model with a genetic algorithm. We validate the model by accurately simulating switching curves for HZO thin films with different ferroelectric phase fractions. The simulated domain dynamics during switching also shows amazing similarity to the available experimental observations. The present work also provides fundamental insights into enhancing the ferroelectricity in HZO thin films by controlling the grain morphology and crystalline texture. It can potentially be extended to improve the ferroelectric properties of other hafnia based thin films.

Net ecosystem CO2 exchange from jute crop (Corchorus olitorius L.) and its environmental drivers in tropical Indo-Gangetic plain using open-path eddy covariance technique.

Present study is a maiden attempt to assess net ecosystem exchange (NEE) of carbon dioxide (CO2) flux from jute crop (Corchorus olitorius L.) in the Indo-Gangetic plain by using open-path eddy covariance (EC) technique. Diurnal variations of NEE were strongly influenced by growth stages of jute crop. Daytime peak NEE varied from - 5 µmol m-2 s-1 (in germination stage) to - 23 µmol m-2 s-1 (in fibre development stage). The ecosystem was net CO2 source during nighttime with an average NEE value of 5-8 µmol m-2 s-1. Combining both daytime and nighttime CO2 fluxes, jute ecosystem was found to be a net CO2 sink on a daily basis except the initial 9 days from date of sowing. Seasonal and growth stage-wise NEEs were computed, and the seasonal total NEE over the jute season was found to be - 268.5 gC m-2 (i.e. 10.3 t CO2 ha-1). In different jute growth stages, diurnal variations of NEE were strongly correlated (R2 > 0.9) with photosynthetic photon flux density (PPFD). Ecosystem level photosynthetic efficiency parameters were estimated at each growth stage of jute crop using the Michaelis-Menten equation. The maximum values of photosynthetic capacity (Pmax, 63.3 ± 1.15 µmol CO2 m-2 s-1) and apparent quantum yield (α, 0.072 ± 0.0045 µmol CO2 µmol photon-1) were observed during the active vegetative stage, and the fibre development stage, respectively. Results of the present study would significantly contribute to understanding of the carbon flux from the Indian agro-ecosystems, which otherwise are very sparse.

Smartphone-Enabled Paper-Based Hemoglobin Sensor for Extreme Point-of-Care Diagnostics.

We report a simple, affordable (∼0.02 US $/test), rapid (within 5 min), and quantitative paper-based sensor integrated with smartphone application for on-spot detection of hemoglobin (Hgb) concentration using approximately 10 µL of finger-pricked blood. Quantitative analytical colorimetry is achieved via an Android-based application (Sens-Hb), integrating key operational steps of image acquisition, real-time analysis, and result dissemination. Further, feedback from the machine learning algorithm for adaptation of calibration data offers consistent dynamic improvement for precise predictions of the test results. Our study reveals a successful deployment of the extreme point-of-care test in rural settings where no infrastructural facilities for diagnostics are available. The Hgb test device is validated both in the controlled laboratory environment (n = 200) and on the field experiments (n = 142) executed in four different Indian villages. Validation results are well correlated with the pathological gold standard results (r = 0.9583) with high sensitivity and specificity for the healthy (n = 136) (>11 g/dL) (specificity: 97.2%), mildly anemic (n = 55) (<11 g/dL) (sensitivity: 87.5%, specificity: 100%), and severely anemic (n = 9) (<7 g/dL) (sensitivity: 100%, specificity: 100%) samples. Results from field trials reveal that only below 5% cases of the results are interpreted erroneously by classifying mildly anemic patients as healthy ones. On-field deployment has unveiled the test kit to be extremely user friendly that can be handled by minimally trained frontline workers for catering the needs of the underserved communities.

Fine balance of chemotactic and hydrodynamic torques: When microswimmers orbit a pillar just once.

We study the detention statistics of self-propelling droplet microswimmers attaching to microfluidic pillars. These droplets show negative autochemotaxis: they shed a persistent repulsive trail of spent fuel that biases them to detach from pillars in a specific size range after orbiting them just once. We have designed a microfluidic assay recording microswimmers in pillar arrays of varying diameter, derived detention statistics via digital image analysis, and interpreted these statistics via the Langevin dynamics of an active Brownian particle model. By comparing data from orbits with and without residual chemical field, we can independently estimate quantities such as hydrodynamic and chemorepulsive torques, chemical coupling constants and diffusion coefficients, as well as their dependence on environmental factors such as wall curvature. This type of analysis is generalizable to many kinds of microswimmers.