A new model for automatic normalization of multitemporal satellite images using Artificial Neural Network and mathematical methods

Relative Radiometric Normalization is often required in remote sensing image analyses particularly in the land cover change detection process. Normalization process minimizes the radiometric differences between two images caused by inequalities in the acquisition conditions rather than changes in surface reflectance. A wide range of RRN methods have been developed to adjust linear models. This paper proposes an automated Relative Radiometric Normalization (RRN) method to adjust a non-linear model based on an Artificial Neural Network (ANN) and unchanged pixels. The proposed method includes the following stages: (1) automatic detection of unchanged pixels based on a new idea that uses CVA (Change Vector Análysis) method, PCA (Principal Component Analysis) transformation and K-means clustering technique, (2) evaluation of different architectures of perceptron neural networks to find the best architecture for this specific task and (3) use of the aforementioned network for normalizing the subject image. The method has been implemented on two images taken by the TM sensor. Experimental results confirm the effectiveness of the presented technique in the automatic detection of unchanged pixels and minimizing imaging condition effects (i.e., atmosphere and other effective parameters).     

Algebraic Characterization of Dense-Separability Among Compact Spaces

In this note, we show that a compact Hausdorff space X is dense-separable if and only if every family of ideals of C(X) with zero intersection has a countable subfamily with zero intersection. As a consequence of this characterization we observe that every compact dense-separable space whith Soc(C(X)) = 0 has a countable dense and co-dense subset.     

2D Poly(arylene vinylene) Covalent Organic Frameworks via Aldol Condensation of Trimethyltriazine

Designing structural order in electronically active organic solids remains a great challenge in the field of materials chemistry. Now, 2D poly(arylene vinylene)s prepared as highly crystalline covalent organic frameworks (COFs) by base‐catalyzed aldol condensation of trimethyltriazine with aromatic dialdehydes are reported. The synthesized polymers are highly emissive (quantum yield of up to 50 %), as commonly observed in their 1D analogues poly(phenylene vinylene)s. The inherent well‐defined porosity (surface area ca. 1000 m² g^?1, pore diameter ca. 11 Å for the terephthaldehyde derived COF‐1) and 2D structure of these COFs also present a new set of properties and are likely responsible for the emission color, which is sensitive to the environment. COF‐1 is highly hydrophilic and reveals a dramatic macroscopic structural reorganization that has not been previously observed in framework materials.     

Nanofluid Today

Journal of Thermal Analysis and Calorimetry -     

Self‐Healing Polyester Urethane Supramolecular Elastomers Reinforced with Cellulose Nanocrystals for Biomedical Applications

Stretchable self‐healing urethane‐based biomaterials have always been crucial for biomedical applications; however, the strength is the main constraint of utilization of these healable materials. Here, a series of novel, healable, elastomeric, supramolecular polyester urethane nanocomposites of poly(1,8‐octanediol citrate) and hexamethylene diisocyanate reinforced with cellulose nanocrystals (CNCs) are introduced. Nanocomposites with various amounts of CNCs from 10 to 50 wt% are prepared using solvent casting technique followed by the evaluation of their microstructural features, mechanical properties, healability, and biocompatibility. The synthesized nanocomposites indicate significantly higher tensile modulus (approximately 36–500‐fold) in comparison to the supramolecular polymer alone. Upon exposure to heat, the materials can reheal, but nevertheless when the amount of CNC is greater than 10 wt%, the self‐healing ability of nanocomposites is deteriorated. These materials are capable of rebonding ruptured parts and fully restoring their mechanical properties. In vitro cytotoxicity test of the nanocomposites using human dermal fibroblasts confirms their good cytocompatibility. The optimized structure, self‐healing attributes, and noncytotoxicity make these nanocomposites highly promising for tissue engineering and other biomedical applications.     

Thermal performance investigation of DQW GaInNAs laser diodes

In this work, we optimize the thermal performance of a double quantum well GaInNAs ridge waveguide laser using an accurate in-house 2D electro-opto-thermal laser simulator. The simulator has shown good agreement with experiments after a detailed calibration procedure. Using calibrated material parameters, we investigate the influence of the cladding doping level on the heat generation within the laser. It is found that due to the competition between Joule heating and free carrier absorption, an optimum cladding doping level exists.     

Non-minimally coupled quintom model inspired by string theory

In this Letter we consider a quintom model of dark energy with a single scalar field T given by a Lagrangian which inspired by tachyonic Lagrangian in string theory. We consider non-minimal coupling of tachyon field to the scalar curvature, then we obtain the equation of state (EoS), and the condition required for the model parameters when ω crosses over −1.     

Transmission dynamics of novel coronavirus SARS-CoV-2 among healthcare workers,a case study in Iran

One of the main concerns during the COVID-19 pandemic was the protection of healthcare workers against the novel coronavirus. The critical role and vulnerability of healthcare workers during the COVID-19 pandemic leads us to derive a mathematical model to express the spread of coronavirus between the healthcare workers. In the first step, the SECIRH model is introduced, and then the mathematical equations are written. The proposed model includes eight state variables, i.e., Susceptible, Exposed, Carrier, Infected, Hospitalized, ICU admitted, Dead, and finally Recovered. In this model, the vaccination, protective equipment, and recruitment policy are considered as preventive actions. The formal confirmed data provided by the Iranian ministry of health is used to simulate the proposed model. The simulation results revealed that the proposed model has a high degree of consistency with the actual COVID-19 daily statistics. In addition, the roles of vaccination, protective equipment, and recruitment policy for the elimination of coronavirus among the healthcare workers are investigated. The results of this research help the policymakers to adopt the best decisions against the spread of coronavirus among healthcare workers.

     

Self-Assembly Behavior and Application of Terphenyl-Cored Trimaltosides for Membrane-Protein Studies: Impact of Detergent Hydrophobic Group Geometry on Protein Stability

Amphipathic agents are widely used in various fields including biomedical sciences. Micelle-forming detergents are particularly useful for in vitro membrane-protein characterization. As many conventional detergents are limited in their ability to stabilize membrane proteins, it is necessary to develop novel detergents to facilitate membrane-protein research. In the current study, we developed novel trimaltoside detergents with an alkyl pendant-bearing terphenyl unit as a hydrophobic group, designated terphenyl-cored maltosides (TPMs). We found that the geometry of the detergent hydrophobic group substantially impacts detergent self-assembly behavior, as well as detergent efficacy for membrane-protein stabilization. TPM-Vs, with a bent terphenyl group, were superior to the linear counterparts (TPM-Ls) at stabilizing multiple membrane proteins. The favorable protein stabilization efficacy of these bent TPMs is likely associated with a binding mode with membrane proteins distinct from conventional detergents and facial amphiphiles. When compared to n-dodecyl-β-d -maltoside (DDM), most TPMs were superior or comparable to this gold standard detergent at stabilizing membrane proteins. Notably, TPM-L3 was particularly effective at stabilizing the human β₂ adrenergic receptor (β₂AR), a G-protein coupled receptor, and its complex with G_s protein. Thus, the current study not only provides novel detergent tools that are useful for membrane-protein study, but also suggests a critical role for detergent hydrophobic group geometry in governing detergent efficacy.     

Synthesis of boronic acid‐functionalized poly(glycerol‐oligoγ‐butyrolactone): Nano‐networks for efficient electrochemical sensing of biosystems

Despite the outstanding properties of hyperbranched polyglycerols such as biocompatibility and multifunctionality, enough attention has not been paid to the synthesis of their functional copolymers. This problem has limited the structural diversity of hyperbranched polyglycerols and hampers further developments and their practical usage. In this work, butyrolactone segments were incorporated into the backbone of polyglycerols by one‐pot ring‐opening copolymerization of a mixture of glycidol and γ‐butyrolactone in the presence of tin(II) 2‐ethylhexanoate. Poly(glycerol‐oligoγ‐butyrolactone)s were then crosslinked by 2,5‐thiophenediylbisboronic acid to obtain polymeric nanonetworks with 140 nm average size. Afterwards, the gold electrode was modified by the polymeric nano‐networks, and it was used for the determination of glucose, glycated hemoglobin, and Escherichia coli in phosphate buffer solution (pH = 9.0) through cyclic voltammetry and impedance spectroscopic. Taking advantage of the straightforward synthesis, cheap precursors and multifunctionality of poly(glycerol‐oligoγ‐butyrolactone)s, they could be used for real‐time sensing of a wide range of biosystems. © 2019 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2019, 57, 1430–1439