On optical solutions to the Kadomtsev–Petviashviliequation with a local Conformable derivativeitle

In fact, due to the existence of this category of equations, our understanding of many phenomena around us becomes more complete. In this paper, we study an integrable partial differential equation called the Kadomtsev–Petviashvili equation with a local conformable derivative. This equation is used to describe nonlinear motion. In order to solve the equation, it is first necessary to convert the form of the equation from a partial derivative to an equation with ordinary derivatives using a suitable variable change. The resulting form will then be the basis of our work to determine the main solutions. All the solutions reported in the paper for the present equation are quite different from the previous findings in other papers. All necessary calculations are provided using symbolic computing software in Maple

HISR: Hybrid Implicit Surface Representation for Photorealistic 3D Human Reconstruction

Neural reconstruction and rendering strategies have demonstrated state-of-the-art performances due, in part, to their ability to preserve high level shape details. Existing approaches, however, either represent objects as implicit surface functions or neural volumes and still struggle to recover shapes with heterogeneous materials, in particular human skin, hair or clothes. To this aim, we present a new hybrid implicit surface representation to model human shapes. This representation is composed of two surface layers that represent opaque and translucent regions on the clothed human body. We segment different regions automatically using visual cues and learn to reconstruct two signed distance functions (SDFs). We perform surface-based rendering on opaque regions (e.g., body, face, clothes) to preserve high-fidelity surface normals and volume rendering on translucent regions (e.g., hair). Experiments demonstrate that our approach obtains state-of-the-art results on 3D human reconstructions, and also shows competitive performances on other objects.Comment: Accepted by AAAI 2024 main trac

catena-Poly[[dichloridomercury(II)]-N′-nicotinoylnicotinohydrazide]

The title complex, [HgCl2(C12H10N4O2)]n, is composed of one HgII ion, one nnh ligand (nnh = N′-nicotinoylnicotinohydrazide) and two coordinated chloride ions. The HgII ion shows a distorted tetrahedral geometry, being surrounded by two N atoms from two nnh ligands and two chloride ions. Due to the bridging role of nnh, the HgII atoms are connected into polymeric chains along the c axis, which are further interlinked via N—H...O and C—H...Cl hydrogen-bonding interactions, forming a three-dimensional network

Micromechanism Study of Molecular Compatibility of PVDF/PEI Blend Membrane

In this paper, the compatibility of polyetherimide (PEI) with different contents as a high-performance copolymer and polyvinylidene fluoride (PVDF) was studied, and 5%–20% PEI was prepared by the non-solvent-induced phase inversion method. The compatibility of PVDF and PEI was evaluated by analyzing the physical structure and properties of the blend membrane, the microstructure, the glass transition temperature Tg, the enthalpy, and the mechanism of the polymer blend enthalpy change. The results show that the blend membranes have -NH and C=O-N binding energies at X-ray photoelectron spectroscopy (XPS), which preliminarily proves that fluorine–amine bonds are formed between the polymers, and new spectra appeared by Fourier transform infrared (FTIR) and X-ray diffraction (XRD) peaks, which further proves that the two have the formation of fluorine–amine bonds, the Tg and enthalpy of the mixed membrane was increased, and a scanning electron microscope (SEM) observed that the membrane pores changed from finger-like pores to sponge-like macropores. When the content of PEI is 15%, the performance of the blended membrane is the best, the water contact angle increases to 58.5°, the porosity increases to 17.33%, the maximum force increases to 8.04 N, and the elongation at break decreases to 24.26%, the pure water flux is 1870.292 L/m2·h, and the oil rejection is 87%. In addition, the enthalpy change of polymer blending further proves that PEI and PVDF are compatible systems and have a good performance improvement for PVDF

MRFA-Net: Multi-Scale Receptive Feature Aggregation Network for Cloud and Shadow Detection

The effective segmentation of clouds and cloud shadows is crucial for surface feature extraction, climate monitoring, and atmospheric correction, but it remains a critical challenge in remote sensing image processing. Cloud features are intricate, with varied distributions and unclear boundaries, making accurate extraction difficult, with only a few networks addressing this challenge. To tackle these issues, we introduce a multi-scale receptive field aggregation network (MRFA-Net). The MRFA-Net comprises an MRFA-Encoder and MRFA-Decoder. Within the encoder, the net includes the asymmetric feature extractor module (AFEM) and multi-scale attention, which capture diverse local features and enhance contextual semantic understanding, respectively. The MRFA-Decoder includes the multi-path decoder module (MDM) for blending features and the global feature refinement module (GFRM) for optimizing information via learnable matrix decomposition. Experimental results demonstrate that our model excelled in generalization and segmentation performance when addressing various complex backgrounds and different category detections, exhibiting advantages in terms of parameter efficiency and computational complexity, with the MRFA-Net achieving a mean intersection over union (MIoU) of 94.12% on our custom Cloud and Shadow dataset, and 87.54% on the open-source HRC_WHU dataset, outperforming other models by at least 0.53% and 0.62%. The proposed model demonstrates applicability in practical scenarios where features are difficult to distinguish

HISR: Hybrid Implicit Surface Representation for Photorealistic 3D Human Reconstruction

Neural reconstruction and rendering strategies have demonstrated state-of-the-art performances due, in part, to their ability to preserve high level shape details. Existing approaches, however, either represent objects as implicit surface functions or neural volumes and still struggle to recover shapes with heterogeneous materials, in particular human skin, hair or clothes. To this aim, we present a new hybrid implicit surface representation to model human shapes. This representation is composed of two surface layers that represent opaque and translucent regions on the clothed human body. We segment different regions automatically using visual cues and learn to reconstruct two signed distance functions (SDFs). We perform surface-based rendering on opaque regions (e.g., body, face, clothes) to preserve high-fidelity surface normals and volume rendering on translucent regions (e.g., hair). Experiments demonstrate that our approach obtains state-of-the-art results on 3D human reconstructions, and also shows competitive performances on other objects

A complex amplitude control method of metasurface based on full phase modulation

Unlike the Pancharatnam-Berry phase and spin-decoupled metasurface, which only modifies the phase of the cross-polarization components, the full-phase modulation metasurface achieves independent wavefront control of the co– and cross-polarization components of circularly polarized waves. As a result, a novel concept for multifunctional manipulation of the metasurface is presented in this paper, which is a complex amplitude control method based on full-phase modulation via a metasurface. This method allows for simultaneous and independent amplitude and phase manipulation of the co– and cross-polarization components of circularly polarized waves. At 980 nm wavelength, the results of complex amplitude control for incident circularly polarized light (left circularly polarized or right circularly polarized) demonstrate the feasibility of the method