Aqua­(2,9-dimethyl-1,10-phenanthroline-κ2 N,N′)bis­(2-hydroxy­benzoato-κO)manganese(II) 2,9-dimethyl-1,10-phenanthroline hemisolvate

In the asymmetric unit of the title complex, [Mn(C7H5O3)2(C14H12N2)(H2O)]·0.5C14H12N2, the MnII ion is coordinated by a bidentate 2,9-dimethyl-1,10-phenanthroline (dmphen) mol­ecule, one water mol­ecule and two monodentate 2-hydroxy­benzoate anions in a distorted trigonal-bipyramidal geometry. The OH group of the 2-hydroxy­benzoate anion is disordered over two positions with site-occupancy factors of 0.5. The asymmetric unit is completed with by an uncoordinated half-mol­ecule of dmphen, disordered about a crystallographic twofold axis. In the crystal structure, mol­ecules are linked into a two-dimensional framework by O—H⋯N, O—H⋯O and C—H⋯O hydrogen bonds. The packing of the structure is further stabilized by π–π stacking inter­actions involving dmphen mol­ecules, with centroid–centroid separations of 3.8027 (3) and 3.6319 (3) Å

Investigation of transpiration cooling with local thermal non-equilibrium model: Effects of different thermal boundary conditions at the porous-fluid interface

In this study, the main stream coupled with a porous medium with local thermal non-equilibrium assumption is analyzed. The flow inside the porous material is modelled using the Darcy–Brinkman–Forchheimer equation and the incompressible Navier-Stokes equations are solved for the main stream. Several couple conditions between the main flow temperature and the temperatures of the solid matrix and coolant flow at the fluid/porous interface is calculated. The results show that the Model C assumes the main flow temperature equals the solid phase temperature and the main flow heat flux is all imposed on the solid phase gives the most reasonable answer

Detecting modules in multiplex networks – an application for integrating expression profiles across multiple species

Multiplex network, a set of networks linked through interconnected layers, is a useful mathematical framework for data integration. Here, we present a general method to detect modules in multiplex networks and apply it in a specific biological context: to simultaneously cluster the genome-wide expression profiles of C. elegans and D. melanogaster generated by the ENOCDE and modENCODE consortia. The method revealed modules that are fundamentally cross-species and can either be conserved or species-specific. In general, the method could be applied in various contexts like the integration of different social networks

Solar Tracking Error Analysis of Fresnel Reflector

Depending on the rotational structure of Fresnel reflector, the rotation angle of the mirror was deduced under the eccentric condition. By analyzing the influence of the sun tracking rotation angle error caused by main factors, the change rule and extent of the influence were revealed. It is concluded that the tracking errors caused by the difference between the rotation axis and true north meridian, at noon, were maximum under certain conditions and reduced at morning and afternoon gradually. The tracking error caused by other deviations such as rotating eccentric, latitude, and solar altitude was positive at morning, negative at afternoon, and zero at a certain moment of noon

PanoGRF: Generalizable Spherical Radiance Fields for Wide-baseline Panoramas

Achieving an immersive experience enabling users to explore virtual environments with six degrees of freedom (6DoF) is essential for various applications such as virtual reality (VR). Wide-baseline panoramas are commonly used in these applications to reduce network bandwidth and storage requirements. However, synthesizing novel views from these panoramas remains a key challenge. Although existing neural radiance field methods can produce photorealistic views under narrow-baseline and dense image captures, they tend to overfit the training views when dealing with \emph{wide-baseline} panoramas due to the difficulty in learning accurate geometry from sparse $360^{\circ}$ views. To address this problem, we propose PanoGRF, Generalizable Spherical Radiance Fields for Wide-baseline Panoramas, which construct spherical radiance fields incorporating $360^{\circ}$ scene priors. Unlike generalizable radiance fields trained on perspective images, PanoGRF avoids the information loss from panorama-to-perspective conversion and directly aggregates geometry and appearance features of 3D sample points from each panoramic view based on spherical projection. Moreover, as some regions of the panorama are only visible from one view while invisible from others under wide baseline settings, PanoGRF incorporates $360^{\circ}$ monocular depth priors into spherical depth estimation to improve the geometry features. Experimental results on multiple panoramic datasets demonstrate that PanoGRF significantly outperforms state-of-the-art generalizable view synthesis methods for wide-baseline panoramas (e.g., OmniSyn) and perspective images (e.g., IBRNet, NeuRay)