Ride-hailing services can make travel easier for disadvantaged communities in low-density transit deserts

Ride-hailing services are often seen as benefiting the middle classes and other well-off Americans. But can they also serve people living in low-density areas, especially those who do not own vehicles? In new research, Shengxiao (Alex) Li, Wei Zhai, Junfeng Jiao, and Chao (Kenneth) Wang examined how ride-hailing services have reshaped transportation across neighborhoods in Austin, Texas. They find that while ride-hailing services mainly serve those who live downtown, where transit services are available, they also have the potential to help people living in low-income and low-density neighborhoods, and those without vehicles

Excellent HER and OER Catalyzing Performance of Se-vacancies in Defects-engineering PtSe2: From Simulation to Experiment

Facing with grave climate change and enormous energy demand, catalyzer gets more and more important due to its significant effect on reducing fossil fuels consumption. Hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) by water splitting are feasible ways to produce clean sustainable energy. Here we systematically explored atomic structures and related STM images of Se defects in PtSe2. The equilibrium fractions of vacancies under variable conditions were detailly predicted. Besides, we found the vacancies are highly kinetic stable, without recovering or aggregation. The Se vacancies in PtSe2 can dramatically enhance the HER performance, comparing with, even better than Pt(111). Beyond, we firstly revealed that PtSe2 monolayer with Se vacancies is also a good OER catalyst. The excellent bipolar catalysis of Se vacancies were further confirmed by experimental measurements. We produced defective PtSe2 by direct selenization of Pt foil at 773 K using a CVD process. Then we observed the HER and OER performance of defective PtSe2 is much highly efficient than Pt foils by a series of measurements. Our work with compelling theoretical and experimental studies indicates PtSe2 with Se defects is an ideal bipolar candidate for HER and OER

Gut microbiota influences feeding behavior via changes in olfactory receptor gene expression in Colorado potato beetles

The Colorado potato beetle (CPB) is an internationally recognized plant quarantine pest that causes serious losses to potato agricultural production. The gut microbiota plays an important role in its growth and development, and the olfactory system plays an important role in insect feeding behavior. The gut microbiota is known to be capable of inducing changes in the olfactory systems of insects. However, the way these associated gut microbes influence the feeding-related behaviors of CPBs remains unclear. To explore the relationship between them, fresh potato leaves immersed in a mixture of five antibiotics (tetracycline, penicillin, ofloxacin, ciprofloxacin, and ampicillin) at specific concentrations for 1 h were fed to adult CPBs to reduce the abundance of gut microbes. We found that the feeding behavior of CPBs was significantly affected by the gut microbiota and that Pseudomonas was significantly higher in abundance in the control group than in the antibiotic group. We then used transcriptome sequencing to explore the differences in olfactory receptor genes in the heads of non-treatment and antibiotic-fed CPBs. Through Illumina Hiseq™ sequencing and screening of differential genes, we found that the olfactory receptor gene LdecOR9 was significantly upregulated and LdecOR17 was significantly downregulated after antibiotic feeding. A real-time polymerase chain reaction was used to verify the changes in olfactory receptor gene expression in the non-treatment groups and antibiotic-treated groups. The feeding behavior was partially rescued after CPBs were re-fed with intestinal bacteria. These results indicate that a certain amount of gut microbiota can result in the loss of the olfactory discrimination ability of CPBs to host plants. In summary, this study investigated the relationship between gut microbiota and olfactory genes, providing a reference for research on microbial control

IL-33 Aggravates DSS-Induced Acute Colitis in Mouse Colon Lamina Propria by Enhancing Th2 Cell Responses

Interleukin- (IL-) 33, a member of the IL-1 cytokine family, is an important modulator of the immune system associated with several immune-mediated diseases. IL-33 was expressed in high level on epithelial cells of intestinal tract. It suggested that IL-33 plays a potential role in inflammatory bowel diseases (IBD). We investigated the role of interleukin- (IL-) 33 in dextran sulphate sodium- (DSS-) induced acute colitis in mice using recombinant mouse IL-33 protein (rIL-33). We found that DSS-induced acute colitis was aggravated by rIL-33 treatment. rIL-33-treated DSS mice showed markedly reduced levels of interferon- (IFN-)γ and IL-17A in their colon lamina propria lymphocytes (LPL), but the levels of Th2 cytokines, such as IL-5 and IL-13, in these cells were significantly increased, compared to DSS mice treated with PBS. Our results suggested that IL-33 stimulated CD4+T cells and caused the cell to adopt a Th2-type response but at the same time suppressed Th17 and Th1 cell responses. Therefore, IL-33 may be involved in pathogenesis of DSS-induced acute colitis by promoting Th2 cell response in intestinal mucosa of mice. Modulation of IL-33/ST2 signaling by monoclonal antibody (mAb) could be a novel biological therapy in DSS-induced acute colitis

Electrostatic-Assembly-Driven Formation of Supramolecular Rhombus Microparticles and Their Application for Fluorescent Nucleic Acid Detection

In this paper, we report on the large-scale formation of supramolecular rhombus microparticles (SRMs) driven by electrostatic assembly, carried out by direct mixing of an aqueous HAuCl4 solution and an ethanol solution of 4,4′-bipyridine at room temperature. We further demonstrate their use as an effective fluorescent sensing platform for nucleic acid detection with a high selectivity down to single-base mismatch. The general concept used in this approach is based on adsorption of the fluorescently labeled single-stranded DNA (ssDNA) probe by SRM, which is accompanied by substantial fluorescence quenching. In the following assay, specific hybridization with its target to form double-stranded DNA (dsDNA) results in desorption of ssDNA from SRM surface and subsequent fluorescence recovery

Timing of uplift and evolution of the Lüliang Mountains, North China Craton

This study analyses evidence for reformed basin development and basin-mountain coupling associated with development of the Ordos Basin and the Lüliang Mountains, China. Gaining an improved understanding of the timing and nature of uplift and evolution of the Lüliang Mountains is important for the reconstruction of the eastern sedimentary boundary of the Ordos Basin (a major petroliferous basin) as well as for providing insight into the evolution and breakup of the North China Craton (NCC). Based on systematic sampling for fission track analysis, it is suggested that the main phase of uplift of the Lüliang Mountains occurred since later part of the Early Cretaceous. Three evolutionary stages of uplift and development are identified: slow initial uplift (120–65 Ma), accelerated uplift (65–23 Ma), and intensive uplift (23 Ma to present), with the majority of the uplift activity having occurred during the Cenozoic. The history of uplift is non-equilibrium and exhibits complexity in temporal and spatial aspects. The middle and northern parts of the Lüliang Mountains were uplifted earlier than the southern part. The most intensive episode of uplift activity commenced in the Miocene and was associated with a genetic coupling relationship with the eastern neighboring Cenozoic Shanxi Grabens. The uplifting and evolutionary processes of the Lüliang Mountains area since later part of the Early Cretaceous share a unified regional geodynamic setting, which was accompanied by uplift of the Mesozoic Ordos Basin and development of the neighboring Cenozoic Shanxi Grabens. Collectively, this regional orogenic activity is related principally to the far-field effects of both the compression sourced from the southwestern Tibet Plateau and westward subduction of the Pacific Plate in Cenozoic

Fabrication of iron oxide core/gold shell submicrometer spheres with nanoscale surface roughness for efficient surface-enhanced Raman scattering

A method to synthesize Fe3O4 core/Au shell submicrometer structures with very rough surfaces on the nanoscale is reported. The Fe3O4 particles were first modified with uniform polymers through the layer-by-layer technique and then adsorbed a lot of gold nanoseeds for further Au shell formation. The shell was composed of a large number of irregular nanoscale Au particles arranged randomly, and there were well-defined boundaries between these Au nanoparticles. The Fe3O 4 core/Au shell particles showed strong plasmon resonance absorption in the near-infrared range, and can be separated quickly from solution by an external magnet. This kind of very rough Fe3O4 core/Au shell multicomponent was used in the adsorption of 4-aminothiophenol and as a substrate for detection by surface-enhanced Raman spectroscopy

Self-Supervised Learning for Point-Cloud Classification by a Multigrid Autoencoder

It has become routine to directly process point clouds using a combination of shared multilayer perceptrons and aggregate functions. However, this practice has difficulty capturing the local information of point clouds, leading to information loss. Nevertheless, several recent works have proposed models that establish point-to-point relationships based on this procedure. However, to address the information loss, in this study we use self-supervised methods to enhance the network’s understanding of point clouds. Our proposed multigrid autoencoder (MA) constrains the encoder part of the classification network so that it gains an understanding of the point cloud as it reconstructs it. With the help of self-supervised learning, we find the original network improves performance. We validate our model on PointNet++, and the experimental results show that our method improves overall classification accuracy by 2.0% and 4.7% with ModelNet40 and ScanObjectNN datasets, respectively