Realization of a three-dimensional photonic topological insulator

Confining photons in a finite volume is in high demand in modern photonic devices. This motivated decades ago the invention of photonic crystals, featured with a photonic bandgap forbidding light propagation in all directions. Recently, inspired by the discoveries of topological insulators (TIs), the confinement of photons with topological protection has been demonstrated in two-dimensional (2D) photonic structures known as photonic TIs, with promising applications in topological lasers and robust optical delay lines. However, a fully three-dimensional (3D) topological photonic bandgap has never before been achieved. Here, we experimentally demonstrate a 3D photonic TI with an extremely wide (> 25% bandwidth) 3D topological bandgap. The sample consists of split-ring resonators (SRRs) with strong magneto-electric coupling and behaves as a 'weak TI', or a stack of 2D quantum spin Hall insulators. Using direct field measurements, we map out both the gapped bulk bandstructure and the Dirac-like dispersion of the photonic surface states, and demonstrate robust photonic propagation along a non-planar surface. Our work extends the family of 3D TIs from fermions to bosons and paves the way for applications in topological photonic cavities, circuits, and lasers in 3D geometries

Valley-Hall photonic topological insulators with dual-band kink states

Extensive researches have revealed that valley, a binary degree of freedom (DOF), can be an excellent candidate of information carrier. Recently, valley DOF has been introduced into photonic systems, and several valley-Hall photonic topological insulators (PTIs) have been experimentally demonstrated. However, in the previous valley-Hall PTIs, topological kink states only work at a single frequency band, which limits potential applications in multiband waveguides, filters, communications, and so on. To overcome this challenge, here we experimentally demonstrate a valley-Hall PTI, where the topological kink states exist at two separated frequency bands, in a microwave substrate-integrated circuitry. Both the simulated and experimental results demonstrate the dual-band valley-Hall topological kink states are robust against the sharp bends of the internal domain wall with negligible inter-valley scattering. Our work may pave the way for multi-channel substrate-integrated photonic devices with high efficiency and high capacity for information communications and processing

A simplified climate change model and extreme weather model based on a machine learning method

The emergence of climate change (CC) is affecting and changing the development of the natural environment, biological species, and human society. In order to better understand the influence of climate change and provide convincing evidence, the need to quantify the impact of climate change is urgent. In this paper, a climate change model is constructed by using a radial basis function (RBF) neural network. To verify the relevance between climate change and extreme weather (EW), the EW model was built using a support vector machine. In the case study of Canada, its level of climate change was calculated as being 0.2241 ("normal"), and it was found that the factors of CO2 emission, average temperature, and sea surface temperature are significant to Canada's climate change. In 2025, the climate level of Canada will become "a little bad" based on the prediction results. Then, the Pearson correlation value is calculated as being 0.571, which confirmed the moderate positive correlation between climate change and extreme weather. This paper provides a strong reference for comprehensively understanding the influences brought about by climate change

Morphological and phylogenetic analyzes reveal two new species of Melanconiella from Fujian Province, China

IntroductionSpecies of Melanconiella include a diverse array of plant pathogens as well as endophytic fungi. Members of this genus have been frequently collected from the family Betulaceae (birches) in Europe and North America. Little, however, if known concerning the distribution of Melanconiella and/or their potential as pathogens of other plant hosts.MethodsFungi were noted and isolated from diseased leaves of Loropetalum chinense (Chinese fringe flower) and Camellia sinensis (tea) in Fujian Province, China. Genomic DNA was extracted from fungal isolates and the nucleotide sequences of four loci were determined and sued to construct phylogenetic trees. Morphological characteristics of fungal structures were determined via microscopic analyses.ResultsFour strains and two new species of Melanconiella were isolated from infected leaves of L. chinense and C. sinensis in Fujian Province, China. Based on morphology and a multi-gene phylogeny of the internal transcribed spacer regions with the intervening 5.8S nrRNA gene (ITS), the 28S large subunit of nuclear ribosomal RNA (LSU), the second largest subunit of RNA polymerase II (RPB2), and the translation elongation factor 1-α gene (TEF1-α), Melanconiellaloropetali sp. nov. and Melanconiellacamelliae sp. nov. were identified and described herein. Detailed descriptions, illustrations, and a key to the known species of Melanconiella are provided.DiscussionThese data identify new species of Melanconiella, expanding the potential range and distribution of these dark septate fungi. The developed keys provide a reference source for further characterization of these fungi

Lenvatinib improves anti-PD-1 therapeutic efficacy by promoting vascular normalization via the NRP-1-PDGFRβ complex in hepatocellular carcinoma

IntroductionThe limited response to immune checkpoint blockades (ICBs) in patients with hepatocellular carcinoma (HCC) highlights the urgent need for broadening the scope of current immunotherapy approaches. Lenvatinib has been shown a potential synergistic effect with ICBs. This study investigated the optimal method for combining these two therapeutic agents and the underlying mechanisms.MethodsThe effect of lenvatinib at three different doses on promoting tissue perfusion and vascular normalization was evaluated in both immunodeficient and immunocompetent mouse models. The underlying mechanisms were investigated by analyzing the vascular morphology of endothelial cells and pericytes. The enhanced immune infiltration of optimal-dose lenvatinib and its synergistic effect of lenvatinib and anti-PD-1 antibody was further evaluated by flow cytometry and immunofluorescence imaging.ResultsThere was an optimal dose that superiorly normalized tumor vasculature and increased immune cell infiltration in both immunodeficient and immunocompetent mouse models. An adequate concentration of lenvatinib strengthened the integrity of human umbilical vein endothelial cells by inducing the formation of the NRP-1-PDGFRβ complex and activating the Crkl-C3G-Rap1 signaling pathway in endothelial cells. Additionally, it promoted the interaction between endothelial cells and pericytes by inducing tyrosine-phosphorylation in pericytes. Furthermore, the combination of an optimal dose of lenvatinib and an anti-PD-1 antibody robustly suppressed tumor growth.ConclusionsOur study proposes a mechanism that explains how the optimal dose of lenvatinib induces vascular normalization and confirms its enhanced synergistic effect with ICBs

Assessing the structure and diversity of fungal community in plant soil under different climatic and vegetation conditions

IntroductionUnderstanding microbial communities in diverse ecosystems is crucial for unraveling the intricate relationships among microorganisms, their environment, and ecosystem processes. In this study, we investigated differences in the fungal community structure and diversity in soils from two contrasting climatic and vegetation conditions: the Xinjiang western China plateau and the Fujian southeastern coastal province.MethodsA total of 36 soil samples collected from two climatic regions were subjected to high-throughput ITS gene sequencing for fungal community analysis. In conjunction soil physicochemical properties were assessed and compared. Analyses included an examination of the relationship of fungal community structure to environmental factors and functional profiling of the community structure was using the FUNGuild pipeline.ResultsOur data revealed rich fungal diversity, with a total of 11 fungal phyla, 31 classes, 86 orders, 200 families, 388 genera, and 515 species identified in the soil samples. Distinct variations in the physicochemical properties of the soil and fungal community structure were seen in relation to climate and surface vegetation. Notably, despite a colder climate, the rhizosphere soil of Xinjiang exhibited higher fungal (α-)diversity compared to the rhizosphere soil of Fujian. β-diversity analyses indicated that soil heterogeneity and differences in fungal community structure were primarily influenced by spatial distance limitations and vegetation type. Furthermore, we identified dominant fungal phyla with significant roles in energy cycling and organic matter degradation, including members of the Sordariomycetes, Leotiomycetes, Archaeosporomycetes, and Agaricomycetes. Functional analyses of soil fungal communities highlighted distinct microbial ecological functions in Xinjiang and Fujian soils. Xinjiang soil was characterized by a focus on wood and plant saprotrophy, and endophytes, whereas in Fujian soil the fungal community was mainly associated with ectomycorrhizal interactions, fungal parasitism, and wood saprotrophy.DiscussionOur findings suggest fungal communities in different climatic conditions adapt along distinct patterns with, plants to cope with environmental stress and contribute significantly to energy metabolism and material cycling within soil-plant systems. This study provides valuable insights into the ecological diversity of fungal communities driven by geological and environmental factors

Consumers' demand for local food products: An investigation into the power of label information

The local food movement continues to grow as consumers around the world become increasingly conscientious about where their foods come from. While it has been observed that consumers are willing to pay higher prices for local food products, the reasons driving the premium are not fully understood. The purpose of this research project is to investigate how different locally-related marketing messages and different product-origin information influence consumers’ valuation of locally-produced food products. To do this, we employ an incentive compatible experiment designed to measure participants’ willingness-to-pay (WTP) for five locally produced foods under different information treatments. Results indicate that both product-origin information and local-related marketing information have significant effect on consumers’ willingness-to-pay, with participants willing to pay significantly more for food that they are told originates from their region. These results can inform how local brands develop their value proposition, target valuable customer segments, create effective marketing communications with appealing labels that call-for-action, and come up with profitable pricing strategies