An Assessment of Sea Ice Motion Products in the Robeson Channel Using Daily Sentinel-1 Images

Sea ice motion is an essential parameter when determining sea ice deformation, regional advection, and the outflow of ice from the Arctic Ocean. The Robeson Channel, which is located between Ellesmere Island and northwest Greenland, is a narrow but crucial channel for ice outflow. Only three Eulerian sea ice motion products derived from ocean/sea ice reanalysis are available: GLORYS12V1, PSY4V3, and TOPAZ4. In this study, we used Lagrangian ice motion in the Robeson Channel derived from Sentinel-1 images to assess GLORYS12V1, PSY4V3, and TOPAZ4. The influence of the presence of ice arches, and wind and tidal forcing on the accuracies of the reanalysis products was also investigated. The results show that the PSY4V3 product performs the best as it underestimates the motion the least, whereas TOPAZ4 grossly underestimates the motion. This is particularly true in regimes of free drift after the formation of the northern arch. In areas with slow ice motion or grounded ice floes, the GLORYS12V1 and TOPAZ4 products offer a better estimation. The spatial distribution of the deviation between the products and ice floe drift is also presented and shows a better agreement in the Robeson Channel compared to the packed ice regime north of the Robeson Channel.

Non-Uniform Spline Quasi-Interpolation to Extract the Series Resistance in Resistive Switching Memristors for Compact Modeling Purposes

An advanced new methodology is presented to improve parameter extraction in resistive memories. The series resistance and some other parameters in resistive memories are obtained, making use of a two-stage algorithm, where the second one is based on quasi-interpolation on non-uniform partitions. The use of this latter advanced mathematical technique provides a numerically robust procedure, and in this manuscript, we focus on it. The series resistance, an essential parameter to characterize the circuit operation of resistive memories, is extracted from experimental curves measured in devices based on hafnium oxide as their dielectric layer. The experimental curves are highly non-linear, due to the underlying physics controlling the device operation, so that a stable numerical procedure is needed. The results also allow promising expectations in the massive extraction of new parameters that can help in the characterization of the electrical device behavior.

Multiphoton Laser Fabrication of Hybrid Photo-Activable Biomaterials

The possibility to shape stimulus-responsive optical polymers, especially hydrogels, by means of laser 3D printing and ablation is fostering a new concept of “smart” micro-devices that can be used for imaging, thermal stimulation, energy transducing and sensing. The composition of these polymeric blends is an essential parameter to tune their properties as actuators and/or sensing platforms and to determine the elasto-mechanical characteristics of the printed hydrogel. In light of the increasing demand for micro-devices for nanomedicine and personalized medicine, interest is growing in the combination of composite and hybrid photo-responsive materials and digital micro-/nano-manufacturing. Existing works have exploited multiphoton laser photo-polymerization to obtain fine 3D microstructures in hydrogels in an additive manufacturing approach or exploited laser ablation of preformed hydrogels to carve 3D cavities. Less often, the two approaches have been combined and active nanomaterials have been embedded in the microstructures. The aim of this review is to give a short overview of the most recent and prominent results in the field of multiphoton laser direct writing of biocompatible hydrogels that embed active nanomaterials not interfering with the writing process and endowing the biocompatible microstructures with physically or chemically activable features such as photothermal activity, chemical swelling and chemical sensing.

Optimization of Corrosion Wear Resistance of the NiCrBSi Laser-Clad Coatings Fabricated on Ti6Al4V

Ni-based alloy powder (NiCrBSi) was applied to prepare coatings on Ti6Al4V by laser cladding to improve the wear resistance of the latter under corrosion. The scanning speed was found to be an essential parameter that could adjust the microstructure of the coatings. Changes in the microstructures of the coatings with the scanning speed were highlighted, and the relationships between the microstructures and microhardness, fracture toughness, corrosion, and corrosion wear resistance of the coatings were established. Results indicated that the matrix changes from Ti2Ni + TiNi to primary γ(Ni) + eutectics (γ(Ni) + Ni3Ti) with increasing scanning speed. Moreover, reinforcement phases changed from TiB2 + TiC (5 mm∙s−1) to TiB2 + TiC + Cr7C3 (11 mm∙s−1) to TiB2 + TiC + Cr7C3 + CrB (17 mm∙s−1). The average microhardness of the coatings first increased and then decreased, and the corresponding fracture toughness showed the opposite trend. The optimum combination of these properties was observed in the coating prepared at 11 mm∙s−1. This coating demonstrated excellent wear resistance in 3.5 wt.% NaCl solution, as well as a high corrosion potential, a low corrosion current density, and a low current density when the electrode initially entered a comparatively stable corrosion state. Moreover, compared with coatings prepared at other scanning speeds, this coating revealed a higher critical potential for oxidation film destruction. The results of this research collectively show that regulating the microstructures of laser-clad coatings by applying different scanning speeds is a feasible strategy to optimize the wear resistance of the coatings under corrosion.

Understanding the Evolution of Government Attention in Response to COVID-19 in China: A Topic Modeling Approach

The effective control over the outbreak of COVID-19 in China showcases a prompt government response, in which, however, the allocation of attention, as an essential parameter, remains obscure. This study is designed to clarify the evolution of the Chinese government’s attention in tackling the pandemic. To this end, 674 policy documents issued by the State Council of China are collected to establish a text corpus, which is then used to extract policy topics by applying the latent dirichlet allocation (LDA) model, a topic modelling approach. It is found that the response policies take different tracks in a four-stage controlling process, and five policy topics are identified as major government attention areas in all stages. Moreover, a topic evolution path is highlighted to show internal relationships between different policy topics. These findings shed light on the Chinese government’s dynamic response to the pandemic and indicate the strength of applying adaptive governance strategies in coping with public health emergencies.

New correction method for the scattering coefficient measurements of a three-wavelength nephelometer

The aerosol scattering coefficient is an essential parameter for estimating aerosol direct radiative forcing and can be measured by nephelometers. Nephelometers are problematic due to small errors of nonideal Lambetian light source and angle truncation. Hence, the observed raw scattering coefficient data need to be corrected. In this study, based on the random forest machine learning model and taking Aurora 3000 as an example, we have proposed a new method to correct the scattering coefficient measurements of a three-wavelength nephelometer under different relative humidity conditions. The result shows that the empirical corrected values match Mie-calculation values very well at all three wavelengths and under all of the measured relative humidity conditions, with more than 85 % of the corrected values having less than 2 % error. The correction method obtains a scattering coefficient with high accuracy and there is no need for additional observation data.

Point Zero Charge Determination and Fluoride Adsorption on Natural Red Ash (Metal Oxide)

The PZC is essential parameter for the characterization of certain materials used for the treatment of organic or inorganic wastes in the environment, particularly from waste water and industrial sludge. Potentiometric titration and batch experimentation method was used to determine PZC value and type of adsorption isotherm behavior observed. Red ash is the natural metal oxides collected from the rift valley of Ethiopia which have PZC values of 3.35 for 0.5g, 1g and 1.5g adsorbent dose studied. On the adsorbent surface, monolayer and homogeneous adsorption process of fluoride observed. Therefore, based on the interest of the researcher and the adjustment of the pH of red ash solution might used for the treatment of ionic wastes.

The avian compass can be sensitive even without sustained electron spin coherence

Theoretical studies indicating the presence of long-lived coherence in the radical pair system have engendered questions about its utilitarian role in the avian compass. In this paper, we investigate the role of electron spin coherence in a multinuclear radical pair system including its impact on compass sensitivity. We find that sustenance of long-lived electron spin coherence is unlikely in a multinuclear hyperfine environment. After probing the role of the hyperfine interactions in the compass, we affirm the hyperfine anisotropy to be an essential parameter for the necessary sensitivity required for the compass action. Thereby, we identify a parameter regime where the compass would exhibit good sensitivity even without sustained electron spin coherence.

Prediction of Transmission Coefficients of Regular Wave Attenuation by Emergent Vegetation

Transmission coefficient (Kt) for wave attenuation by vegetation is essential parameter for predicting the wave height. In this paper, based on the experimental data of three kind of artificial vegetation model, genetic programming (GP), artificial neural networks (ANNs) and multivariate non-linear regression (MNLR) were used to analyze the dimensionless factors including Ursell number (Ur), relative width (RB) relative height (α) and volume fraction (φ). The proposed GP formulae were compared with MNLR and ANNs. The predictions of GP models were in good agreement with measured data, and outperformed MNLR equations. Otherwise, GP and ANNs were used to obtain the weight of each factor. The results can provide a reference for the artificial planting of the three plants.