Interaction with the Surrounding Water Plays a Key Role in Determining the Aggregation Propensity of Proteins

Understanding the molecular determinants of the relative propensities of proteins to aggregate in a cellular environment is a central issue for treating protein‐aggregation diseases and developing peptide‐based therapeutics. Despite the expectation that protein aggregation can largely be attributed to direct protein–protein interactions, a crucial role the surrounding water in determining the aggregation propensity of proteins both in vitro and in vivo was identified. The overall protein hydrophobicity, defined solely by the hydration free energy of a protein in its monomeric state sampling its equilibrium structures, was shown to be the predominant determinant of protein aggregation propensity in aqueous solution. Striking discrimination of positively and negatively charged residues by the surrounding water was also found. This effect depends on the protein net charge and plays a crucial role in regulating the solubility of the protein. These results pave the way for the design of aggregation‐resistant proteins as biotherapeutics.     

Profiles of Essential Oils and Correlations with Phenolic Acids and Primary Metabolites in Flower Buds of Magnolia heptapeta and Magnolia denudata var. purpurascens

Magnolia flower buds are a source of herbal medicines with various active compounds. In this study, differences in the distribution and abundance of major essential oils, phenolic acids, and primary metabolites between white flower buds of Magnolia heptapeta and violet flower buds of Magnolia denudata var. purpurascens were characterised. A multivariate analysis revealed clear separation between the white and violet flower buds with respect to primary and secondary metabolites closely related to metabolic systems. White flower buds contained large amounts of monoterpene hydrocarbons (MH), phenolic acids, aromatic amino acids, and monosaccharides, related to the production of isoprenes, as MH precursors, and the activity of MH synthase. However, concentrations of β-myrcene, a major MH compound, were higher in violet flower buds than in white flower buds, possibly due to higher threonine levels and low acidic conditions induced by comparatively low levels of some organic acids. Moreover, levels of stress-related metabolites, such as oxygenated monoterpenes, proline, and glutamic acid, were higher in violet flower buds than in white flower buds. Our results support the feasibility of metabolic profiling for the identification of phytochemical differences and improve our understanding of the correlated biological pathways for primary and secondary metabolites.     

Thermal Hysteresis Accompanying Incommensurate-Commensurate Phase Transition in Mixed Crystals (K1-xCsx)2ZnCl4

The mixed crystal (K_1-xCs_x)₂ZnCl₄ with x = 0, 0.001, 0.01, 0.1, and 0.2 with optical quality has been grown by the Czochralski method. Using the Atomic Absorption Spectroscopy (AAS) and Energy Dispersive Spectroscopy (EDS), we determined the amount of Cs ion included in the mixed crystal. By using of DTA and DSC, we observed the change of T_c and T_i. The thermal hysteresis in the dielectric constants show strong dependence on the thermal process and on the amount of impurity which are explained by the influence of the thermal process and impurity, respectively on the creation, annihilation, and growth of discommensuration (DC).     

On the Interfacial Flow Over Porous Media Composed of Packed Spheres: Part 1-Identification of the Effective Slip Length

Transport in Porous Media - The effective slip length at the interface between pure fluid flow and porous media composed of packed spheres has been accurately characterized. In this study, as the...     

Domain-Specific On-Device Object Detection Method

Object detection is a significant activity in computer vision, and various approaches have been proposed to detect varied objects using deep neural networks (DNNs). However, because DNNs are computation-intensive, it is difficult to apply them to resource-constrained devices. Here, we propose an on-device object detection method using domain-specific models. In the proposed method, we define object of interest (OOI) groups that contain objects with a high frequency of appearance in specific domains. Compared with the existing DNN model, the layers of the domain-specific models are shallower and narrower, reducing the number of trainable parameters; thus, speeding up the object detection. To ensure a lightweight network design, we combine various network structures to obtain the best-performing lightweight detection model. The experimental results reveal that the size of the proposed lightweight model is 21.7 MB, which is 91.35% and 36.98% smaller than those of YOLOv3-SPP and Tiny-YOLO, respectively. The f-measure achieved on the MS COCO 2017 dataset were 18.3%, 11.9% and 20.3% higher than those of YOLOv3-SPP, Tiny-YOLO and YOLO-Nano, respectively. The results demonstrated that the lightweight model achieved higher efficiency and better performance on non-GPU devices, such as mobile devices and embedded boards, than conventional models.     

Blue electroluminescent materials based on indeno[1,2-a]arene derivatives for Organic Light-Emitting Diodes

Abstract

In this study, as a continuous effort for searching efficient blue-emitting materials, we designed and synthesized materials based on indeno[1,2-a]arene. OLED devices using these materials were fabricated in the following sequence; ITO (180?nm)/N,N'-diphenyl-N,N'-(2-napthyl)-(1,1'-phenyl)-4,4'-diamine (NPB) (50?nm)/emitting materials (30?nm)/4,7-diphenyl-1,10-phenanthroline (Bphen) (30?nm)/Liq/Al (2/100?nm). Particularly, a device using 7,7-dimethyl-7H-indeno[1,2-a]pyrene as emitter showed maximum values of luminous efficiency, power efficiency, and external quantum efficiency of 1.10?cd/A, 0.49?lm/W, 1.47% at 20?mA/cm², respectively with CIE (x,y) coordinates of (0.15, 0.08) at 6.0V.