WavNet — Visual saliency detection using Discrete Wavelet Convolutional Neural Network

In the recent advancements in image and video analysis, the detection of salient regions in the image becomes the initial step. This plays a crucial role in deciding the performance of such algorithms. In this work, a Multi-Resolution Feature Extraction (MRFE) technique that makes use of Discrete Wavelet Convolutional Neural Network (DWCNN) for generating features is employed. An Enhanced Feature Extraction (EFE) module extracts additional features from the high level features of the DWCNN, which are used to frame both channel as well as spatial attention models for yielding contextual attention maps. A new hybrid loss function is also proposed, which is a combination of Balanced Cross Entropy (BCE) loss and Edge based Structural Similarity (ESSIM) loss that effectively identifies and segments the salient regions with clear boundaries. The method is tested exhaustively with five different benchmark datasets and is proved superior to the existing state-of-the-art methods with a minimum Mean Absolute error (MAE) of 0.03 and F-measure of 0.956.     

BMS Derivatives C7-Linked to β-Cyclodextrin and Hyperbranched Polyglycerol Retain Activity against R5-HIV-1NLAD8 Isolates and Can Be Deemed Potential Microbicides

Amides from indole-3-glyoxylic acid and 4-benzoyl-2-methylpiperazine, which are related to entry inhibitors developed by Bristol-Myers Squibb (BMS), have been synthesized with aliphatic chains located at the C7 position of the indole ring. These spacers contain an azido group suitable for the well-known Cu(I)-catalyzed (3+2)-cycloaddition or an activated triple bond for the nucleophilic addition of thiols under physiological conditions. Reaction with polyols (β-cyclodextrin and hyperbranched polyglycerol) decorated with complementary click partners has afforded polyol-BMS-like conjugates that are not cytotoxic (TZM.bl cells) and retain the activity against R5-HIV-1_NLAD8 isolates. Thus, potential vaginal microbicides based on entry inhibitors, which can be called of 4^th generation, are reported here for the first time.     

Optimized microwave absorption properties by tailoring the morphology of carbon coated TiC nanoparticles by N2 pressure

Increasing the dielectric loss capacity plays an important role in enhancing the electromagnetic absorption performance of materials. It remains a challenge to simultaneously introduce multiple types of dielectric losses in the material. In this work, we show that the atomic and interfacial dipole polarizations can be simultaneously enhanced by substituting N species into both carbon coating layers and bulk TiC lattices of a core-shell TiC@C material. Additionally, substitution of N species results more exposed TiC(111) facets and refines the TiC grain sizes in the bulk material, which is beneficial for enhancing the scattering of the external electromagnetic waves. The maximum reflection loss of the N substituted TiC@C material is measured as ?47.1 dB with an effective absorbing bandwidth of 4.83 GHz at 1.9 mm, which illustrates a valuable way to further tuning the electromagnetic absorption performance of this type of materials.     

Nonlinear dielectric response and positive dielectric tunability in antipolar CaTiSiO5

Dielectric tunability has been extensively investigated in ferroelectric materials, which exhibit a negative tunability of dielectric permittivity in an external electric field. In contrast, positive tunability is rare and has been reported only in a few antiferroelectric materials. We present positive (and negative) tunability in the titanite, CaTiSiO₅. The dielectric property of CaTiSiO₅ was measured up to an extraordinarily high electric field of 40 MV/m. A nonlinear polarization field loop with no hysteresis was obtained. The dielectric permittivity of ε_r ~ 25 increases up to ε_r ~ 40 at 20 MV/m and room temperature. Although titanite has an antipolar structure and is expected to be “antiferroelectric,” its dielectric response in high electric fields up to ~40 MV/m differs from that of conventional antiferroelectrics. We demonstrate that the phase-transition temperature and dielectric tunability could be modulated through the chemical substitution of Ca_1−xLa_xTiSi_1−xAl_xO₅, in which the destabilization of the long-range antipolar order is revealed by transmission electron microscopy analysis. These results indicate that the observed dielectric response to an electric field may originate from the unique features of the antipolar and domain structures in CaTiSiO₅.     

Stable power supply of an independent power source for a remote island using a Hybrid Energy Storage System composed of electric and hydrogen energy storage systems

We propose a self-sustaining power supply system consisting of a “Hybrid Energy Storage System (HESS)” and renewable energy sources to ensure a stable supply of high-quality power in remote islands. The configuration of the self-sustaining power supply system that can utilize renewable energy sources effectively on remote islands where the installation area is limited is investigated. It is found that it is important to select renewable energy sources whose output power curve is close to the load curve to improve the efficiency of the system. The operation methods that can increase the cost-effectiveness of the self-sustaining power supply system are also investigated. It is clarified that it is important for increasing the cost effectiveness of the self-sustaining power supply system to operate the HESS with a smaller capacity of its components by setting upper limits on the output power of the renewable energy sources and cutting the infrequent generated power.     

Protection and confinement effect of carbon on Co/CoxOy nano-catalyst for efficient NaBH4 hydrolysis

The hydrolysis of sodium borohydride (NaBH₄) over catalysts is a promising method to produce hydrogen. Although Co-based catalysts exhibit high activity for NaBH₄ hydrolysis, they are still far from satisfying practical applications, especially their poor durability in alkaline media. Herein, a carbon shell structure was designed and synthesized to improve the stability of the mixture of Co⁰ and Co_xO_y nanofilms (Co/Co_xO_y@C) during NaBH₄ hydrolysis via a facile polymerization-pyrolysis strategy with Co/Co_xO_y nanofilms as the precursor. As a result, the Co/Co_xO_y@C catalyst can achieve a remarkable H₂ generation rate of 4348.6 mL min^?1 g_Co^?1 with a low activation energy of 43.6 kJ mol^?1, which is superior to most previously reported catalysts. Moreover, the catalyst shows high stability with an H₂ generation-specific rate of 79% after five cycles. The excellent performance of carbon substrate can well prevent the agglomeration of Co-based nanoparticle and improve the corrosion resistance of the active Co to BO₂^? and OH^?. This work would widen the road for the preparation of nanoconfined catalysts, which has prospective application potentials for H₂ production from NaBH₄ hydrolysis.     

Entropy analysis of unsteady MHD three-dimensional flow of Williamson nanofluid over a convectively heated stretching sheet

This article addresses an investigation of the entropy analysis of Williamson nanofluid flow in the presence of gyrotactic microorganisms by considering variable viscosity and thermal conductivity over a convectively heated bidirectionally stretchable surface. Heat and mass transfer phenomena have been incorporated by taking into account the thermal radiation, heat source or sink, viscous dissipation, Brownian motion, and thermophoretic effects. The representing equations are nonlinear coupled partial differential equations and these equations are shaped into a set of ordinary differential equations via a suitable similarity transformation. The arising set of ordinary differential equations was then worked out by adopting a well-known scheme, namely the shooting method along with the Runge-Kutta-Felberge integration technique. The effects of flow and heat transfer controlling parameters on the solution variables are depicted and analyzed through the graphical presentation. The survey finds that magnifying viscosity parameter, Weissenberg number representing the non-Newtonian Williamson parameter cause to retard the velocity field in both the directions and thermal conductivity parameter causes to reduce fluid temperature. The study also recognizes that enhancing magnetic parameters and thermal conductivity parameters slow down the heat transfer rate. The entropy production of the system is estimated through the Bejan number. It is noticeable that the Bejan number is eminently dependent on the heat generation parameter, thermal radiation parameter, viscosity parameter, thermal conductivity parameter, and Biot number. The skillful accomplishment of the present heat and mass transfer system is achieved through the exteriorized choice of the pertinent parameters.     

Theoretical estimation of dielectric loss of oxide glasses using nonequilibrium molecular dynamics simulations

To theoretically explore amorphous materials with a sufficiently low dielectric loss, which are essential for next-generation communication devices, the applicability of a nonequilibrium molecular dynamics simulation employing an external alternating electric field was examined using alkaline silicate glass models. In this method, the dielectric loss is directly evaluated as the phase shift of the dipole moment from the applied electric field. This method enabled us to evaluate the dielectric loss in a wide frequency range from 1 GHz to 10 THz. It was observed that the dielectric loss reaches its maximum at a few THz. The simulation method was found to qualitatively reproduce the effects of alkaline content and alkaline type on the dielectric loss. Furthermore, it reasonably reproduced the effect of mixed alkalines on the dielectric loss, which was observed in our experiments on sodium and/or potassium silicate glasses. Alkaline mixing was thus found to reduce the dielectric loss.     

Microstructure,phase, magnetic properties,and electromagnetic wave absorption of graphene oxide – Ni0.7Zn0.3Fe2O4 – Al2O3 aerogel

In this work, an ultralight nanocomposite of graphene oxide aerogels as a matrix and nickel-zinc ferrite (Ni_0.7Zn_0.3Fe₂O₄) nanoparticles as a second phase for the absorption of electromagnetic waves in the frequency of 1–18 GHz were fabricated by the hydrothermal - freeze-drying method. α-Al₂O₃ nanoparticles were used for further impedance matching for applications in electromagnetic wave absorption. XRD, SEM, EDS, and VNA analyses were used to characterize the sample. The effects of the amount of Ni_0.7Zn_0.3Fe₂O₄ (NZF) nanoparticles (GO: NZF volume percent ratio = 5:1 and 2:1) on the absorption of electromagnetic waves were investigated.     

Retinal microaneurysms detection using adversarial pre-training with unlabeled multimodal images

The detection of retinal microaneurysms is crucial for the early detection of important diseases such as diabetic retinopathy. However, the detection of these lesions in retinography, the most widely available retinal imaging modality, remains a very challenging task. This is mainly due to the tiny size and low contrast of the microaneurysms in the images. Consequently, the automated detection of microaneurysms usually relies on extensive ad-hoc processing. In this regard, although microaneurysms can be more easily detected using fluorescein angiography, this alternative imaging modality is invasive and not adequate for regular preventive screening.In this work, we propose a novel deep learning methodology that takes advantage of unlabeled multimodal image pairs for improving the detection of microaneurysms in retinography. In particular, we propose a novel adversarial multimodal pre-training consisting in the prediction of fluorescein angiography from retinography using generative adversarial networks. This pre-training allows learning about the retina and the microaneurysms without any manually annotated data. Additionally, we also propose to approach the microaneurysms detection as a heatmap regression, which allows an efficient detection and precise localization of multiple microaneurysms. To validate and analyze the proposed methodology, we perform an exhaustive experimentation on different public datasets. Additionally, we provide relevant comparisons against different state-of-the-art approaches. The results show a satisfactory performance of the proposal, achieving an Average Precision of 64.90%, 31.36%, and 33.55% in the E-Ophtha, ROC, and DDR public datasets. Overall, the proposed approach outperforms existing deep learning alternatives while providing a more straightforward detection method that can be effectively applied to raw unprocessed retinal images.