Comparative study of bin and bulk microphysical schemes in simulating a heavy snowfall event that occurred in Beijing during the 2022 Winter Olympic Games

A heavy snowfall event that struck Beijing during February 12-13, 2022, affected some of the training sessions and events of the Winter Olympic Games. This heavy snowfall event was simulated using the Advanced Research Weather Research and Forecasting Model with both the two-moment bulk scheme (BULK) and the spectral bin microphysics scheme (BIN), and the differences in surface precipitation, radar reflectivity, and cloud microphysics processes were compared and analyzed. It was found that surface precipitation was dominated by solid precipitation particles. The 24-h accumulated precipitation of the BULK simulation was larger than that of the BIN simulation, but both were smaller than that observed. The BIN simulation was closer to the observations in terms of the trends of variation in precipitation rate and radar reflectivity during the period of heavy precipitation. The maximum and minimum vertical velocities of the BIN simulation were notably higher than those of the BULK simulation, and the water vapor content of the BIN scheme at the heights of the −10 to −20°C levels and above the −38°C level was substantially higher than that of the BULK scheme. The contents of cloud water and snow simulated by the BIN scheme were much higher than those simulated by the BULK scheme. The nucleation of ice crystals in the middle and high layers of the BULK scheme was obvious, whereas such a process was not evident in the BIN scheme. The net production rate of ice crystals and snow simulated by the BULK scheme was stronger near the surface than that simulated by the BIN scheme, and a second peak in the conversion rate existed at heights very close to the surface below 1 km, which might account for the greater intensity of precipitation in the BULK scheme. The latent heat simulated by the BULK scheme was larger (smaller) than that simulated by the BIN scheme below (above) the height of 2 km

Hyper-Relational Knowledge Graph Neural Network for Next POI

With the advancement of mobile technology, Point of Interest (POI) recommendation systems in Location-based Social Networks (LBSN) have brought numerous benefits to both users and companies. Many existing works employ Knowledge Graph (KG) to alleviate the data sparsity issue in LBSN. These approaches primarily focus on modeling the pair-wise relations in LBSN to enrich the semantics and thereby relieve the data sparsity issue. However, existing approaches seldom consider the hyper-relations in LBSN, such as the mobility relation (a 3-ary relation: user-POI-time). This makes the model hard to exploit the semantics accurately. In addition, prior works overlook the rich structural information inherent in KG, which consists of higher-order relations and can further alleviate the impact of data sparsity.To this end, we propose a Hyper-Relational Knowledge Graph Neural Network (HKGNN) model. In HKGNN, a Hyper-Relational Knowledge Graph (HKG) that models the LBSN data is constructed to maintain and exploit the rich semantics of hyper-relations. Then we proposed a Hypergraph Neural Network to utilize the structural information of HKG in a cohesive way. In addition, a self-attention network is used to leverage sequential information and make personalized recommendations. Furthermore, side information, essential in reducing data sparsity by providing background knowledge of POIs, is not fully utilized in current methods. In light of this, we extended the current dataset with available side information to further lessen the impact of data sparsity. Results of experiments on four real-world LBSN datasets demonstrate the effectiveness of our approach compared to existing state-of-the-art methods

A prospective self-controlled study on shortening the time before taking delayed radiographs with iodized oil hysterosalpingography

Objectives: To verify the feasibility of walking to shorten the time before obtaining delayed radiographs after iodized oil hysterosalpingography (HSG). Material and methods: One hundred women with infertility were selected for HSG from June 2018 to December 2018 at the Women’s Hospital of Nanjing Medical University; the subjects were randomly divided into walking and control groups. The walking group was required to walk more than 12,000 steps within 6 hours after HSG, while the control group was prohibited from performing high-intensity exercise. The degree of pelvic adhesion was diagnosed with delayed radiographs acquired at 6 and 24 hours, and the diagnostic consistency of the radiographs at the two time points was evaluated. Results: No significant difference was observed in the baseline data between groups (p > 0.05). The delayed radiograph results in the walking group showed good agreement (p = 0.255 > 0.05, Kappa value 0.781 > 0.75), while those in the control group showed general agreement (p = 0.002 < 0.05, Kappa value 0.493 > 0.40 < 0.75). Conclusions: The time for acquiring delayed radiographs can be shortened by instructing patients to walk after HSG. This method improves the diagnostic efficiency of Iodized oil, saves time and costs, and may contribute to the popularization of HSG for female infertility screening, while offering good clinical application prospects

CRISPR dynamics during the interaction between bacteria and phage in the first year of life

Gut microbiomes in infancy have a profound impact on health in adulthood. CRISPRs play an essential role in the interaction between bacteria and phages. However, the dynamics of CRISPRs in gut microbiomes during early life are poorly understood. In this study, using shotgun metagenomic sequencing data from 82 Swedish infants' gut microbiomes, 1882 candidate CRISPRs were identified, and their dynamics were analysed. We found large-scale turnover of CRISPRs and their spacers during the first year of life. As well as changes in relative abundance of the bacteria containing CRISPR, acquisition, loss and mutation of spacers were observed within the same CRISPR array sampled over time. Accordingly, the inferred interaction network of bacteria and phage was distinct at different times. This research underpins CRISPR dynamics and their potential role in the interaction between bacteria and phage in early life.</p

CRISPR dynamics during the interaction between bacteria and phage in the first year of life

Gut microbiomes in infancy have a profound impact on health in adulthood. CRISPRs play an essential role in the interaction between bacteria and phages. However, the dynamics of CRISPRs in gut microbiomes during early life are poorly understood. In this study, using shotgun metagenomic sequencing data from 82 Swedish infants’ gut microbiomes, 1882 candidate CRISPRs were identified, and their dynamics were analysed. We found large-scale turnover of CRISPRs and their spacers during the first year of life. As well as changes in relative abundance of the bacteria containing CRISPR, acquisition, loss and mutation of spacers were observed within the same CRISPR array sampled over time. Accordingly, the inferred interaction network of bacteria and phage was distinct at different times. This research underpins CRISPR dynamics and their potential role in the interaction between bacteria and phage in early life

Comparative genomics and phylogenomics of the genus Glycyrrhiza (Fabaceae) based on chloroplast genomes

Glycyrrhiza (Fabaceae) species are rich in metabolites and widely used in medicine. Research on the chloroplast genome of Glycyrrhiza is important for understanding its phylogenetics, biogeography, genetic diversity, species identification, and medicinal properties. In this study, comparative genomics and phylogenomics of Glycyrrhiza were analyzed based on the chloroplast genome. The chloroplast genomes of six Glycyrrhiza species were obtained using various assembly and annotation tools. The final assembled chloroplast genome sizes for the six Glycyrrhiza species ranged from 126,380 bp to 129,115 bp, with a total of 109–110 genes annotated. Comparative genomics results showed that the chloroplast genomes of Glycyrrhiza showed typically lacking inverted repeat regions, and the genome length, structure, GC content, codon usage, and gene distribution were highly similar. Bioinformatics analysis revealed the presence of 69–96 simple sequence repeats and 61–138 long repeats in the chloroplast genomes. Combining the results of mVISTA and nucleotide diversity, four highly variable regions were screened for species identification and relationship studies. Selection pressure analysis indicated overall purifying selection in the chloroplast genomes of Glycyrrhiza, with a few positively selected genes potentially linked to environmental adaptation. Phylogenetic analyses involving all tribes of Fabaceae with published chloroplast genomes elucidated the evolutionary relationships, and divergence time estimation estimated the chronological order of species differentiations within the Fabaceae family. The results of phylogenetic analysis indicated that species from the six subfamilies formed distinct clusters, consistent with the classification scheme of the six subfamilies. In addition, the inverted repeat-lacking clade in the subfamily Papilionoideae clustered together, and it was the last to differentiate. Co-linear analysis confirmed the conserved nature of Glycyrrhiza chloroplast genomes, and instances of gene rearrangements and inversions were observed in the subfamily Papilionoideae

Electrochemically Fabricated Surface-Mesostructured CuNi Bimetallic Catalysts for Hydrogen Production in Alkaline Media

Ni-based bimetallic films with 20 at.% and 45 at.% Cu and mesostructured surfaces were prepared by electrodeposition from an aqueous solution containing micelles of P123 triblock copolymer serving as a structure-directing agent. The pH value of the electrolytic solution had a key effect on both the resulting Cu/Ni ratio and the surface topology. The catalytic activity of the CuNi films toward hydrogen evolution reaction was investigated by cyclic voltammetry (CV) in 1 M KOH electrolyte at room temperature. The CuNi film showed the highest activity (even higher than that of a non-mesostructured pure Ni film), which was attributed to the Ni content at the utmost surface, as demonstrated by CV studies, as well as the presence of a highly corrugated surface

Long Noncoding RNA Malat1 Protects Against Osteoporosis and Bone Metastasis

MALAT1, one of the few highly conserved nuclear long noncoding RNAs (lncRNAs), is abundantly expressed in normal tissues. Previously, targeted inactivation and genetic rescue experiments identified MALAT1 as a suppressor of breast cancer lung metastasis. On the other hand, Malat1-knockout mice are viable and develop normally. On a quest to discover the fundamental roles of MALAT1 in physiological and pathological processes, we find that this lncRNA is downregulated during osteoclastogenesis in humans and mice. Remarkably, Malat1 deficiency in mice promotes osteoporosis and bone metastasis of melanoma and mammary tumor cells, which can be rescued by genetic add-back of Malat1. Mechanistically, Malat1 binds to Tead3 protein, a macrophage-osteoclast-specific Tead family member, blocking Tead3 from binding and activating Nfatc1, a master regulator of osteoclastogenesis, which results in the inhibition of Nfatc1-mediated gene transcription and osteoclast differentiation. Notably, single-cell transcriptome analysis of clinical bone samples reveals that reduced MALAT1 expression in pre-osteoclasts and osteoclasts is associated with osteoporosis and metastatic bone lesions. Altogether, these findings identify Malat1 as a lncRNA that protects against osteoporosis and bone metastasis