PCM-based hybrid thermal management system for photovoltaic modules: A comparative analysis.

Proper temperature regulation of photovoltaic (PV) modules increases their performance. Among various cooling techniques, phase change materials (PCMs) represent an effective thermal management route, thanks to their large latent heat at constant temperatures. Radiative cooling (RC) is also recently explored as a passive option for PV temperature regulation. In this paper, a heat sink (HS), phase change materials, and radiative cooling are integrated with photovoltaic modules to achieve low and uniform temperature distribution along the PV module and improved performance. Eight different combinations are considered for the proposed system, including HS, PCM, and RC, and their various combinations. The PCM is selected according to the environmental conditions of the selected location. A comprehensive 2-D model is developed and analyzed in COMSOL-Multiphysics software by solving the governing equations using the finite element method. The performance analysis is carried out for the climatic conditions of the Atacama Desert, having high solar radiation and ambient temperature. The effects of PCM height, ambient temperature, wind velocity, and solar radiation on the performance of the proposed system are studied. The performance of eight different configurations is also compared. The maximum reductions in PV temperature, maximum PV power, and a minimum drop in PV conversion efficiency are observed to be 22 oC, 152 W, and 14% using a combined heat sink and radiative cooling systems, among all other configurations. The findings of this study can be used to select the best PV cooling method among different configurations.

Molecular Docking and In Silico Simulation of Trichinella spiralis Membrane-Associated Progesterone Receptor Component 2 (Ts-MAPRC2) and Its Interaction with Human PGRMC1.

Background. Trichinellosis is a foodborne zoonotic disease caused by Trichinella spp., including Trichinella spiralis. This parasitic disease ranks as seven of the most infectious in the world. In this context, it is important to develop a vaccine that can combat Trichinellosis, especially for humans and pigs. This would be an important step in preventing transmission. In this study, we focus on homology modelling, binding site prediction, molecular modelling, and simulation techniques used to explore the association between Trichinella spiralis membrane-associated progesterone receptor component 2 (Ts-MAPRC2) and the human PGRMC1 protein. It was found that the progesterone receptor component 2 of T. spiralis has 44.54% sequence identity with human PGRMC1 (PDB ID: 4X8Y). Binding sites predicted for human PGRMC1 are GLU 7, PHE 8, PHE 10, PHE 18, LEU 27, ASP 36, and VAL 104. Molecular docking has six clusters based on Z scores. They range from -1.5 to 1.8. It was found that the progesterone receptor component 2 of T. spiralis has 44.54% sequence identity with human PGRMC1. During simulation, the average RMSD was 2.44 ± 0.20 Å, which indicated the overall stability of the protein. Based on docking studies and computational simulations, we hypothesized that the interaction of the proteins Trichinella spiralis membrane-associated progesterone receptor component 2 and human PGRMC1 formed stable complexes. The discovery of Ts-MAPRC2 may pave the way for the development of drugs and vaccines to treat Trichinellosis.

Multimodal Registration of White Matter Brain Data via Optimal Mass Transport.

The elastic registration of medical scans from different acquisition sequences is becoming an important topic for many research labs that would like to continue the post-processing of medical scans acquired via the new generation of high-field-strength scanners. In this note, we present a parameter-free registration algorithm that is well suited for this scenario as it requires no tuning to specific acquisition sequences. The algorithm encompasses a new numerical scheme for computing elastic registration maps based on the minimizing flow approach to optimal mass transport. The approach utilizes all of the gray-scale data in both images, and the optimal mapping from image A to image B is the inverse of the optimal mapping from B to A. Further, no landmarks need to be specified, and the minimizer of the distance functional involved is unique. We apply the algorithm to register the white matter folds of two different scans and use the results to parcellate the cortex of the target image. To the best of our knowledge, this is the first time that the optimal mass transport function has been applied to register large 3D multimodal data sets.