Identification and characterization of the fibrinogen-like domain of fibrinogen-related proteins in the mosquito, Anopheles gambiae, and the fruitfly, Drosophila melanogaster, genomes

BACKGROUND: The fibrinogen-like (FBG) domain, which consists of approximately 200 amino acid residues, has high sequence similarity to the C-terminal halves of fibrinogen β and γ chains. Fibrinogen-related proteins (FREPs), which contain FBG domains in their C-terminal region, are found universally in vertebrates and invertebrates. In invertebrates, FREPs are involved in immune responses and other aspects of physiology. To understand the complexity of this family in insects, we analyzed FREPs in the mosquito genome and made comparisons to FREPs in the fruitfly genome. RESULTS: By using the genome data of the mosquito, Anopheles gambiae, 53 FREPs were identified, whereas only 20 members were found in the Drosophila melanogaster genome. Using sequence profile analysis, we found that FBG domains have high sequence similarity and are highly conserved throughout the FBG domain region. By secondary structure analysis and comparison, the FBG domains of FREPs are predicted to function in recognition of carbohydrates and their derivatives on the surface of microorganisms in innate immunity. CONCLUSION: Detailed sequence and structural analysis discloses that the FREP family contains FBG domains that have high sequence similarity in the A. gambiae genome. Expansion of the FREP family in mosquitoes during evolutionary history is mainly accounted for by a major expansion of the FBG domain architecture. The characterization of the FBG domains in the FREP family is likely to aid in the experimental analysis of the ability of mosquitoes to recognize parasites in innate immunity and physiologies associated with blood feeding

How to represent paintings: a painting classification using artistic comments

The goal of large-scale automatic paintings analysis is to classify and retrieve images using machine learning techniques. The traditional methods use computer vision techniques on paintings to enable computers to represent the art content. In this work, we propose using a graph convolutional network and artistic comments rather than the painting color to classify type, school, timeframe and author of the paintings by implementing natural language processing (NLP) techniques. First, we build a single artistic comment graph based on co-occurrence relations and document word relations and then train an art graph convolutional network (ArtGCN) on the entire corpus. The nodes, which include the words and documents in the topological graph are initialized using a one-hot representation; then, the embeddings are learned jointly for both words and documents, supervised by the known-class training labels of the paintings. Through extensive experiments on different classification tasks using different input sources, we demonstrate that the proposed methods achieve state-of-art performance. In addition, ArtGCN can learn word and painting embeddings, and we find that they have a major role in describing the labels and retrieval paintings, respectively

A Case Study of Ground Source Heat Pump System in China

ABSTRACT A case study of a ground source coupled heat pump and air conditioning system in China is introduced in the paper. Two types of U shaped Ground Coupled Heat Exchangers (GCHE) were adopted. One is the conventional closed loop borehole heat exchanger, and the other is the heat exchanger buried in the foundation pile. The floor area to be heated in winter or cooled in the summer is 3715 m 2 , with a heating load of 148kW and a cooling load of 320kW. The system has been operated since 2003 and data for one year are summarized and analyzed. These data include the inlet and outlet temperatures of the GCHE and the surrounding soil temperature. The heating and cooling performances of the system are also evaluated

Soil salinity is the main factor influencing the soil bacterial community assembly process under long-term drip irrigation in Xinjiang, China

Identifying the potential factors associated with the impact of long-term drip irrigation (DI) on soil ecosystems is essential for responding to the environmental changes induced by extensive application of DI technology in arid regions. Herein, we examined the effects of the length of time that DI lasts in years (NDI) on soil bacterial diversity as well as the soil bacterial community assembly process and the factors influencing it. The results showed that long-term DI substantially reduced soil salinity and increased soil bacterial diversity while affecting the soil bacterial community structure distinctly. Null model results showed that the soil bacterial community assembly transitioned from stochastic processes to deterministic processes, as NDI increased. Homogeneous selection, a deterministic process, emerged as the dominant process when NDI exceeded 15 years. Both random forest and structural equation models showed that soil salinity was the primary factor affecting the bacterial community assembly process. In summary, this study suggested that soil bacteria respond differently to long-term DI and depends on the NDI, influencing the soil bacterial community assembly process under long-term DI

Magnetic-field control of topological electronic response near room temperature in correlated Kagome magnets

Strongly correlated Kagome magnets are promising candidates for achieving controllable topological devices owing to the rich interplay between inherent Dirac fermions and correlation-driven magnetism. Here we report tunable local magnetism and its intriguing control of topological electronic response near room temperature in the Kagome magnet Fe3Sn2 using small angle neutron scattering, muon spin rotation, and magnetoresistivity measurement techniques. The average bulk spin direction and magnetic domain texture can be tuned effectively by small magnetic fields. Magnetoresistivity, in response, exhibits a measurable degree of anisotropic weak localization behavior, which allows the direct control of Dirac fermions with strong electron correlations. Our work points to a novel platform for manipulating emergent phenomena in strongly-correlated topological materials relevant to future applications

Assessment of correlation energies based on the random-phase approximation

The random-phase approximation to the ground state correlation energy (RPA) in combination with exact exchange (EX) has brought Kohn-Sham (KS) density functional theory one step closer towards a universal, "general purpose first principles method". In an effort to systematically assess the influence of several correlation energy contributions beyond RPA, this work presents dissociation energies of small molecules and solids, activation energies for hydrogen transfer and non-hydrogen transfer reactions, as well as reaction energies for a number of common test sets. We benchmark EX+RPA and several flavors of energy functionals going beyond it: second-order screened exchange (SOSEX), single excitation (SE) corrections, renormalized single excitation (rSE) corrections, as well as their combinations. Both the single excitation correction as well as the SOSEX contribution to the correlation energy significantly improve upon the notorious tendency of EX+RPA to underbind. Surprisingly, activation energies obtained using EX+RPA based on a KS reference alone are remarkably accurate. RPA+SOSEX+rSE provides an equal level of accuracy for reaction as well as activation energies and overall gives the most balanced performance, which makes it applicable to a wide range of systems and chemical reactions.Comment: 14 pages, 5 figures, full articl

The Impact of Atmosphere on the Local Luminescence Properties of Metal Halide Perovskite Grains.

Metal halide perovskites are exceptional candidates for inexpensive yet high-performing optoelectronic devices. Nevertheless, polycrystalline perovskite films are still limited by nonradiative losses due to charge carrier trap states that can be affected by illumination. Here, in situ microphotoluminescence measurements are used to elucidate the impact of light-soaking individual methylammonium lead iodide grains in high-quality polycrystalline films while immersing them with different atmospheric environments. It is shown that emission from each grain depends sensitively on both the environment and the nature of the specific grain, i.e., whether it shows good (bright grain) or poor (dark grain) luminescence properties. It is found that the dark grains show substantial rises in emission, while the bright grain emission is steady when illuminated in the presence of oxygen and/or water molecules. The results are explained using density functional theory calculations, which reveal strong adsorption energies of the molecules to the perovskite surfaces. It is also found that oxygen molecules bind particularly strongly to surface iodide vacancies which, in the presence of photoexcited electrons, lead to efficient passivation of the carrier trap states that arise from these vacancies. The work reveals a unique insight into the nature of nonradiative decay and the impact of atmospheric passivation on the microscale properties of perovskite films