A computationally efficient multi-domain active learning method for crop mapping using satellite image time-series

Crop mapping through classification of Satellite Image Time-Series (SITS) data can provide precious information for several agricultural applications, such as crop monitoring, yield forecasting, and crop inventory. However, several issues affect the classification performance of SITS data. As one of the most challenging problems, constituent images of time-series provide different levels of information about crops. These differences are the result of dynamic spectral responses of crops and also the variable atmospheric and sensor conditions. The second issue is the unavailability of adequate high-quality samples for training the classifier. In this study, we proposed a novel computationally efficient Multi-Domain Active Learning (MDAL) method which takes advantage of Multiple Kernel Learning (MKL) and Active Learning (AL) algorithms to address these two issues. The proposed method uses MKL algorithms to address the issues associated with different information level of the data, which generally cannot be modelled using the well-known classification algorithms. AL algorithms were also used for semi-automatic selection of training samples. However, most of the MKL algorithms are very computationally demanding. Consequently, using them in the MDAL method can dramatically increase the computational costs. Thus, in this paper, we presented the similarity-based MKL algorithms. Thanks to their low computational complexities, these algorithms are the most suitable MKL algorithms that can be used in the MDAL method. We evaluated the proposed method using two multispectral SITS datasets, acquired by RapidEye and SPOT sensors. The obtained results of the MDAL method for these datasets respectively showed 8.2% and 5.87% increase in the overall accuracy of classification as compared to the accuracy of the standard AL algorithm. The results also showed that in the case of adopting the SimpleMKL algorithm (a common MKL algorithm in the literature) the computational time of the MDAL method is 577 and 474 seconds for RapidEye and SPOT datasets, respectively. However, in the case of adopting the similarity-based MKL algorithms, these computational times respectively decreases to 4 and 2 seconds.     

Room‐Temperature Partial Conversion of α‐FAPbI3 Perovskite Phase via PbI2 Solvation Enables High‐Performance Solar Cells

The two‐step conversion process consisting of metal halide deposition followed by conversion to hybrid perovskite has been successfully applied toward producing high‐quality solar cells of the archetypal MAPbI₃ hybrid perovskite, but the conversion of other halide perovskites, such as the lower bandgap FAPbI₃, is more challenging and tends to be hampered by the formation of hexagonal nonperovskite polymorph of FAPbI₃, requiring Cs addition and/or extensive thermal annealing. Here, an efficient room‐temperature conversion route of PbI₂ into the α‐FAPbI₃ perovskite phase without the use of cesium is demonstrated. Using in situ grazing incidence wide‐angle X‐ray scattering (GIWAXS) and quartz crystal microbalance with dissipation (QCM‐D), the conversion behaviors of the PbI₂ precursor from its different states are compared. α‐FAPbI₃ forms spontaneously and efficiently at room temperature from P₂ (ordered solvated polymorphs with DMF) without hexagonal phase formation and leads to complete conversion after thermal annealing. The average power conversion efficiency (PCE) of the fabricated solar cells is greatly improved from 16.0(±0.32)% (conversion from annealed PbI₂) to 17.23(±0.28)% (from solvated PbI₂) with a champion device PCE > 18% due to reduction of carrier recombination rate. This work provides new design rules toward the room‐temperature phase transformation and processing of hybrid perovskite films based on FA⁺ cation without the need for Cs⁺ or mixed halide formulation.     

The effect of soil salinity on the use of the universal triangle method to estimate saline soil moisture from Landsat data: application to the SMAPEx-2 and SMAPEx-3 campaigns

In this article, a method based on UTM called salinity-based soil moisture content (S_SMC) is developed. Since the soil moisture depends on the soil salinity (SS) in semi-arid regions, the S_SMC method employs the SS as an effective and augmented variable in conventional UTM to estimate SMC in these areas. In calibration step, initially, a linear regression model between the land surface temperature (LST), the normalized difference vegetation index (NDVI), and the SS is applied using in situ measurements to assess the influence of the SS in SMC estimation. Then, a non-linearity model is conducted through insertion of more terms in the linear equation and an optimal model of S_SMC is yielded. Moreover, the SS is obtained using a linear model from two selected salinity indices derived from Landsat images and in situ measurements. In estimation step, the LST, NDVI, and the SS are obtained using Landsat data. The S_SMC method is evaluated in the Soil Moisture Active Passive Experiment (SMAPEx)-2 and SMAPEx-3 campaigns in wet and dry conditions, respectively, over two scenes of Landsat images. The results demonstrated that the S_SMC method is appropriate in non-irrigated areas. In these areas, the S_SMC method improves R² (coefficient of determination) from 22% to 65% in SMAPEx-2 and from 24% to 50% in SMAPEx-3. Moreover, the results have shown that the SMC can be estimated at satellite level with a root mean square error of 0.06 and 0.02 (m³ m^?3) in wet and dry condition, respectively. Therefore, the SS is a key parameter to adjust conventional UTM to improve the SMC estimation by the S_SMC method.     

The synergistic cooperation between MCM-41 and azithromycin: a pH responsive system for drug adsorption and release

The capability of MCM-41 silica for accepting and delivering poorly soluble azithromycin (AZT) in water is reported as robust drug delivery system. This property has been evidenced by using two MCM-41 samples with different pore sizes as hosts of AZT. The choice of this macrolide antibiotic is due not only to its low bioavailability but also to its molecular size which lies in the range of pore diameter of MCM-41s. The drug was loaded inside the pore voids of the mesoporous when MCM-41 was stirred at AZT solution, based on XRD, Nitrogen adsorption–desorption isotherms, TGA analysis data and FT-IR spectroscopy. The amount of AZT stored inside the pores of MCM-41 s was between 22 and 25 wt%. The loaded drug was released in different rates from the particles by changing the pH (1.7 and 7.4) to give a smart pH-responsive carrier system. The drug release kinetics was fitted to Korsmeyer–Peppas and Higuchi models which indicated that the rate of drug release was controlled by the diffusion of the drug. The result of the present study confirms that the controlled adsorption and liberation of AZT may improve the oral bioavailability of poor water soluble AZT. This study demonstrates the feasibility of designing reliable drug delivery systems by appropriate choice of the matrix and the organic molecule. In general, MCM-41 is a promising matrix for AZT adsorption with different application from drug delivery to wastewater filtration.     

An alternative modal combination rule for adaptive pushover analysis

The main purpose of the present study is to develop an alternative modal combination rule for use in the adaptive pushover analysis. Since the quadratic modal combination rules do not take into account the sign reversals of the modal load vectors in the higher modes, the accuracy of the advanced pushover methods are decreased. The proposed modal combination rule is a direct vectorial addition technique in which the relative contribution of each mode and its sign are taken into account. The proposed modal combination rule is employed within the displacement‐based adaptive pushover technique, and an alternative pushover procedure is developed. In order to verify the accuracy of the proposed method, two reference buildings are used, and the obtained results from the proposed method and nonlinear time history analysis are compared. It is concluded that the proposed method can estimate the benchmark responses with remarkable accuracy. Copyright © 2016 John Wiley & Sons, Ltd.     

Mussel‐Inspired Conductive Cryogel as Cardiac Tissue Patch to Repair Myocardial Infarction by Migration of Conductive Nanoparticles

The engineered cardiac patch (ECP) is a promising strategy to repair infarct myocardium and restore the cardiac function. An ideal ECP should be able to mimic the primary attributes of native myocardium, which includes a high resilience, good cardiomyocyte adhesion, and synchronous contraction. Here, a mussel‐inspired dopamine crosslinker is used to integrate polypyrrole (Ppy) nanoparticles, gelatin‐methyacrylate, and poly(ethylene glycol) diacrylate into a cryogel form. The dopamine crosslinker and Ppy nanoparticles are coordinated to obtain optimal mechanical and superelastic properties for the ECP. The dopamine facilitates the uniform distribution of the Ppy nanoparticles, which migrate and fuse from the scaffold to the surface of the cardiomyocytes, revealing a potential mechanism for restoring infarct myocardium. The incorporated Ppy nanoparticles thus significantly enhance the functionalization of the cardiomyocytes, resulting in excellent synchronous contraction by increasing the expression of α‐actinin and CX‐43. Cardiomyocytes‐loaded ECP can improve the cardiac function in myocardial‐infarction (MI) affected rat models. The results show that the fractional shortening and ejection fraction are elevated by about 50% and that the infarct size is reduced by 42.6%. Collectively, this study highlights an effective cardiac patch based on mussel‐inspired conductive particle adhesion and a superelastic cryogel promising for the restoration of infarcted myocardium.     

A new complete model of switch-mode plasma cutting power supply

A complete model of switch-mode plasma cutting power supply and its simulation are developed. The full bridge isolated pulse width modulation (PWM) buck converter in continuous conduction mode (CCM) for high watt plasma power supply is approached. Reduced ripple current and improved power factor are achieved in the plasma power supply. With a PID control strategy, circuit responses become more stable and faster with low overshoot during load and current changing. The converter achieved high efficiency under 3 to 15kW load conditions.     

Probabilistic safety assessment of self-centering steel braced frame

The main drawback of conventional braced frames is implicitly accepting structural damage under the design earthquake load, which leads to considerable economic losses. Controlled rocking self-centering system as a modern low-damage system is capable of minimizing the drawbacks of conventional braced frames. This paper quantifies main limit states and investigates the seismic performance of self-centering braced frame using a Probabilistic Safety Assessment procedure. Margin of safety, confidence level, and mean annual frequency of the self-centering archetypes for their main limit states, including PT yield, fuse fracture, and global collapse, are established and are compared with their acceptance criteria. Considering incorporating aleatory and epistemic uncertainties, the efficiency of the system is examined. Results of the investigation indicate that the design of low- and mid-rise self-centering archetypes could provide the adequate margin of safety against exceeding the undesirable limit-states.     

Fault detection of wind energy conversion systems using recurrent neural networks

Structure of wind energy conversion systems (WECSs) must be robust against faults. In order to accurately study WECSs during occurrence of faults and to explore the impact of faults on each component of the WECSs, a detailed model is required in which both mechanical and electrical parts of the WECSs are properly involved. In addition, a fault detection system (FDS) is required to diagnose the occurred faults at the appropriate time in order to ensure a safe system operation, avoid heavy economic losses, prevent damage to adjacent relevant systems and facilitate timely repair of failed components. This can be performed by subsequent actions through fast and accurate detection of faults. In this paper, by utilising a comprehensive dynamic model of the WECS, an FDS is presented using dynamic recurrent neural networks. In industrial processes, dynamic neural networks are known as a good mathematical tool for fault detection. The proposed FDS detects faults of the generator's angular velocity sensor, pitch angle sensors and pitch actuators. The presented FDS has high capability of fault detection in short time and it has much low false alarms rate. Simulation results verify validity and usefulness of the proposed fault detection scheme.     

Slotless axial flux hysteresis motor, modelling and performance calculation

Hysteresis motors are exciterless and brushless machines with outstanding characteristics such as constant torque and speed, robust structure, low and constant starting current and smooth operation. On the contrary, hysteresis machines have some usage limitations such as low power factor, efficiency and torque density. Comparatively, the low efficiency of common hysteresis motors is mostly related to the parasitic losses generated by the slots. In general, closed or semi-closed slots are employed in the hysteresis machines to reduce the slotting effects and parasitic losses. A new slotless hysteresis motor is introduced. This structure with singular performance is named dasiaslotless dual-rotor discs hysteresis motordasia (SDDHM). The capability of being fabricated as a cascade or multi-stack structure, plus the easy manufacturing process and high torque density and efficiency are some advantages of the proposed machine. A field analysis yielding to an equivalent circuit for the steady-state operating condition is presented. All elements of the equivalent circuit are formulated based on design parameters. The simulation of a prototype machine is given and its excellent performance is illustrated. Simulation results are compared with those of the experiment and this validates the proposed model.