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Hip fracture is associated with substantial morbidity and mortality, especially among the elderly. Current evidence on the association between cigarette smoking and mortality in hip-fracture patients is controversial. We performed a systematic review and meta-analysis of studies on this association.The databases Medline/PubMed, Embase, Web of Science, and Cochrane Library were searched for studies that estimated the effect of smoking on the risk of mortality in hip-fracture patients. Pooled analyses were conducted of the associations, expressed in relative risk (RR) and 95% confidence intervals (CIs). Heterogeneity was assessed using the IA total of six articles involving 3739 hip-fracture patients were included in the meta-analysis. Our results indicate that ever-active smoking was significantly associated with an increased risk of death in hip-fracture patients (pooled RR=1.26; 95% CI: 1.08-1.46). In further subgroup analysis, the risk of death was significantly higher in ever-active smokers than in never smokers in White participants (pooled RR=1.23; 95% CI: 1.05-1.44) and elderly aged ≥60 years (pooled RR=1.19; 95% CI: 1.01-1.40), with no significant association in Asian participants (pooled RR=1.42; 95% CI: 0.95-2.11). Current smokers had more risk of death than never smokers (pooled RR=1.26; 95% CI: 1.08-1.46). The association was significant in follow-up periods of ≤1 year (pooled hazard ratio, HR=1.34; 95% CI: 1.05-1.71), 3 years (pooled HR=1.22; 95% CI: 1.05-1.43), and 5 years (pooled HR=1.26; 95% CI: 1.08-1.46).Cigarette smoking is associated with an increased risk of mortality in hip-fracture patients, especially in elderly patients aged ≥60 years, current smokers, and White participants. With the extension of follow-up period, the effect on mortality of smoking is profound and lasting.

The present study was to investigated differential expressed genes (GEGs) in ischemic cardiomyopathy (ICM), and to construct regulation networks, and to study the correlation between myocardial infarction risk.Data sets were downloaded from the Gene Expression Omnibus (GEO) to screen out messenger RNA (mRNA) and long non-coding RNA (lncRNA) differentially expressed between ICM samples and normal samples. Gene Ontology (GO) function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. Differentially expressed mRNA and lncRNA were analyzed, and bioinformatics methods were used to predict and analyze microRNA (miRNA), and a competing endogenous RNA (Hub gene) regulatory network was constructed. Using the Limma software package in R language, DEGs of ICM were screened with non-heart failure donors as the control group under the conditions that the differential expression ratio was not less than 2 times, and the corrected P value was0.05. The ClusterProfiler software package was used for GO enrichment analysis and KEGG enrichment analysis. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) 11.0 online database was used to screen key genes for protein-protein interaction (PPI) network analysis.The GO function analysis and KEGG pathway analysis showed that the DEGs were significantly enriched in metabolic pathways, oxidative phosphorylation, extracellular matrix receptor interactions, and other pathways, and were closely related to fibrosis, collagen catabolic process, and inflammatory response function, and a Hub gene regulatory network related to ICM lncRNA was constructed. Bioinformatics methods were used to effectively analyze the DEGs of ICM, and the Hub gene regulatory network of ICM was successfully constructed.This study identified a certain risk correlation between ICM susceptibility genes and myocardial infarction.

Although some research papers have suggested that smoking may increase mortality in patients with sepsis, no evidence has been produced in this regard. This systematic research evaluated the risk of death in patients with sepsis who were smokers to facilitate better clinical decision making.This is a systematic review registered in PROPERO (CRD42022296654). Searches were conducted to identify suitable studies from the databases of PubMed, Embase, Web of Science and the Cochrane Controlled Register of Trials from January 1980 to June 2021. Two independent reviewers screened the articles using keywords and extracted the data. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of evidence. The primary endpoints included the mortality of patients with sepsis.Five studies involving 2694 participants were included in our study. Among the five included articles, three studies had an NOS score of 6, while the other two had an NOS score of 7. The results showed that a significantly higher risk of death was observed in smokers with sepsis compared with non-smokers with sepsis (hazard ratio, HR=1.62; 95% CI: 1.11-2.37, p=0.01). Among the patients followed for more than 2 months, the mortality rate of smokers was significantly higher (2.33 times) than that of non-smokers (HR=2.33; 95% CI: 1.83-2.96, p0.01). The difference in mortality did not reach statistical significance when the follow-up period was shorter than 2 months (HR=1.22; 95% CI: 0.96-1.56, p=0.10).Smoking increased mortality in patients with sepsis when the follow-up period was longer than 2 months.

Vγ9Vδ2 T cells play an important role in the development and progression of psoriasis vulgaris (PV), but how they promote skin inflammation and the molecular mechanisms underlying Vγ9Vδ2 T cell dysfunction are poorly understood. Here, we show that circulating Vγ9Vδ2 T cells are decreased and exhibit enhanced proliferation and increased production of IFN-γ and TNF-α in PV patients. Monocytes from PV patients express higher levels of the phosphoantigen sensor butyrophilin 3A1 (BTN3A1) than monocytes from healthy controls. Blockade of BTN3A1 suppresses Vγ9Vδ2 T cell activation and abolishes the difference in Vγ9Vδ2 T cell activation between PV patients and healthy controls. The CD14

BackgroundHER2-targeted therapy provides survival benefits to HER2-mutant non-small cell lung cancer (NSCLC). A better understanding of the clinical and genomic characterization of treatment-naïve HER2-positive NSCLC, as well as the efficacy of and resistance to HER2-targeted therapy in HER2-altered NSCLC, could promote further improvement of HER2 targeted therapy.MethodsHER2-altered NSCLC patients was retrospectively included and their genomic profiles were performed by next-generation sequencing. The clinical outcomes included overall response rate, disease control rate and progression-free survival.ResultsAmong 176 treatment-naïve patients with HER2 alterations, 64.8% harbored HER2 mutations with/without HER2 amplification, and 35.2% carried HER2 amplification only. Molecular characterization was correlated with tumor stage that late-stage NSCLC with HER2 oncogenic mutations showed a higher prevalence of TP53 mutations and a higher tumor mutation burden. However, this correlation was not found in patients with HER2 amplification only. Twenty-one patients with HER2 alterations treated with pyrotinib or afatinib were retrospectively enrolled. Pyrotinib yielded a longer median progression-free survival than afatinib (5.9 [95% CI, 3.8-13.0] vs. 4.0 months [95% CI, 1.9-6.3], P = 0.06) in these patients. Analysis of the genomic profiles before and after anti-HER2 targeted therapies identified de novo HER2 copy number gain and G518W mutation, as well as mutations involving DNA damage repair signaling, SWI–SNF complex, and epigenetic regulations as potential resistance mechanisms.ConclusionHER2-mutant NSCLC had different molecular features from HER2-amplified NSCLC, and its genomic profile was dependent of tumor stage. Pyrotinib had superior therapeutic effects than afatinib in HER2-altered NSCLC, although larger cohorts are warranted to validate it. HER2-dependent and -independent resistance mechanisms to afatinib and pyrotinib were unveiled.

Low-light image enhancement aims to improve an image's visibility while keeping its visual naturalness. Different from existing methods tending to accomplish the relighting task directly by ignoring the fidelity and naturalness recovery, we investigate the intrinsic degradation and relight the low-light image while refining the details and color in two steps. Inspired by the color image formulation (diffuse illumination color plus environment illumination color), we first estimate the degradation from low-light inputs to simulate the distortion of environment illumination color, and then refine the content to recover the loss of diffuse illumination color. To this end, we propose a novel Degradation-to-Refinement Generation Network (DRGN). Its distinctive features can be summarized as 1) A novel two-step generation network for degradation learning and content refinement. It is not only superior to one-step methods, but also capable of synthesizing sufficient paired samples to benefit the model training; 2) A multi-resolution fusion network to represent the target information (degradation or contents) in a multi-scale cooperative manner, which is more effective to address the complex unmixing problems. Extensive experiments on both the enhancement task and joint detection task have verified the effectiveness and efficiency of our proposed method, surpassing the SOTA by \textit{0.70dB on average and 3.18\% in mAP}, respectively. The code is available at \url{https://github.com/kuijiang0802/DRGN}., Comment: AAAI 2022

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Purpose:Intratumoral hepatitis B virus (HBV) integrations and mutations are related to hepatocellular carcinoma (HCC) progression. Circulating cell-free DNA (cfDNA) has shown itself as a powerful noninvasive biomarker for cancer. However, the HBV integration and mutation landscape on cfDNA remains unclear.Experimental Design:A cSMART (Circulating Single-Molecule Amplification and Resequencing Technology)-based method (SIM) was developed to simultaneously investigate HBV integration and mutation landscapes on cfDNA with HBV-specific primers covering the whole HBV genome. Patients with HCC (n = 481) and liver cirrhosis (LC; n = 517) were recruited in the study.Results:A total of 6,861 integration breakpoints including TERT and KMT2B were discovered in HCC cfDNA, more than in LC. The concentration of circulating tumor DNA (ctDNA) was positively correlated with the detection rate of these integration hotspots and total HBV integration events in cfDNA. To track the origin of HBV integrations in cfDNA, whole-genome sequencing (WGS) was performed on their paired tumor tissues. The paired comparison of WGS data from tumor tissues and SIM data from cfDNA confirmed most recurrent integration events in cfDNA originated from tumor tissue. The mutational landscape across the whole HBV genome was first generated for both HBV genotype C and B. A region from nt1100 to nt1500 containing multiple HCC risk mutation sites (OR > 1) was identified as a potential HCC-related mutational hot zone.Conclusions:Our study provides an in-depth delineation of HBV integration/mutation landscapes at cfDNA level and did a comparative analysis with their paired tissues. These findings shed light on the possibilities of noninvasive detection of virus insertion/mutation.

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Background Hepatocellular carcinoma (HCC) generally arises from a background of liver cirrhosis (LC). Patients with cirrhosis and suspected HCC are recommended to undergo serum biomarker tests and imaging diagnostic evaluation. However, the performance of routine diagnostic methods in detecting early HCC remains unpromising. Methods Here, we conducted a large-scale, multicenter study of 1675 participants including 490 healthy controls, 577 LC patients, and 608 HCC patients from nine clinical centers across nine provinces of China, profiled gene mutation signatures of cell-free DNA (cfDNA) using Circulating Single-Molecule Amplification and Resequencing Technology (cSMART) through detecting 931 mutation sites across 21 genes. Results An integrated diagnostic model called “Combined method” was developed by combining three mutation sites and three serum biomarkers. Combined method outperformed AFP in the diagnosis of HCC, especially early HCC, with sensitivities of 81.25% for all stages and 66.67% for early HCC, respectively. Importantly, the integrated model exhibited high accuracy in differentiating AFP-negative, AFP-L3-negative, and PIVKA-II-negative HCCs from LCs.

Additional file 1: Methods. Supplementary figures and legends. Table S1: Basic information of enrolled patients. Table S2: Brief summary of all participants. Table S13: Performance of single mutation site in the diagnosis of HCC.

In this paper, we study the problem of jointly estimating the optical flow and scene flow from synchronized 2D and 3D data. Previous methods either employ a complex pipeline that splits the joint task into independent stages, or fuse 2D and 3D information in an ``early-fusion'' or ``late-fusion'' manner. Such one-size-fits-all approaches suffer from a dilemma of failing to fully utilize the characteristic of each modality or to maximize the inter-modality complementarity. To address the problem, we propose a novel end-to-end framework, which consists of 2D and 3D branches with multiple bidirectional fusion connections between them in specific layers. Different from previous work, we apply a point-based 3D branch to extract the LiDAR features, as it preserves the geometric structure of point clouds. To fuse dense image features and sparse point features, we propose a learnable operator named bidirectional camera-LiDAR fusion module (Bi-CLFM). We instantiate two types of the bidirectional fusion pipeline, one based on the pyramidal coarse-to-fine architecture (dubbed CamLiPWC), and the other one based on the recurrent all-pairs field transforms (dubbed CamLiRAFT). On FlyingThings3D, both CamLiPWC and CamLiRAFT surpass all existing methods and achieve up to a 47.9\% reduction in 3D end-point-error from the best published result. Our best-performing model, CamLiRAFT, achieves an error of 4.26\% on the KITTI Scene Flow benchmark, ranking 1st among all submissions with much fewer parameters. Besides, our methods have strong generalization performance and the ability to handle non-rigid motion. Code is available at https://github.com/MCG-NJU/CamLiFlow., Comment: arXiv admin note: text overlap with arXiv:2111.10502

With high molecular rigidity and planarity, the orange-red emitter SAF-2NP realized ΦPL and Θ‖ of 99% and 85%, respectively. The optimal device demonstrated a maximum external quantum efficiency of 32.5% with an emission peak of 576 nm.

Compared with single-molecule TADF emitters, exciplexes can simplify the complicated molecule design and synthesis and have the superiority of conveniently realizing spectra with a bathochromic shift via mixing donor and acceptor components.

It is well-known that the wavelength of sunlight is continuously distributed from nanometer to micronmeter. Spheric particles with the size matched with sunlight wavelength are most suitable for the light scattering and enhance the light trapping ability according to the Mie scattering theory. In this paper, a multi-sized TiO2 microsphere (MTS) was synthesized via a facile solvothermal method. The obtained MTS samples were then investigated by field emission-scanning electron microscopy (FE-SEM), X-ray powder diffraction (XRD), size distribution measurement, and N2 adsorption–desorption measurement. FE-SEM images and size distribution curves indicate that the diameters of MTS samples range from 300 nm to 3 μm which is matched with sunlight wavelength. The possible formation mechanism of multi-sized TiO2 microsphere was also proposed. Furthermore, the optoelectronic properties of such MTS samples were explored by manufacturing them as photoanodes in dye-sensitized solar cells (DSSCs). The UV–Vis spectrum shows that the MTS has a high capacity for light scattering, which is essential for DSSCs to perform well. Interestingly, even under the condition with 30.4% decrease of dye loading, the DSSC with MTS samples as the top scattering layer showed an energy conversion efficiency of 7.22%, showing 22.4% increase in conversion efficiency when compared with the DSSC without using the top scattering layer. The novel as-prepared MTS samples as photoanodes can effectively boost light scattering and enhance the performance of the device, thus opens a door for the further utilization of sunlight in Dye-sensitized solar cells.

The sluggish oxygen reaction kinetics concomitant with the high overpotentials and parasitic reactions from cathodes and solvents is the major challenge in aprotic lithium-oxygen (Li-O2 ) batteries. Herein, PtIr multipods with a low Lewis acidity of the Pt atoms are reported as an advanced cathode for improving overpotentials and stabilities. DFT calculations disclose that electrons have a strong disposition to transfer from Ir to Pt, since Pt has a higher electronegativity than Ir, resulting in a lower Lewis acidity of the Pt atoms than that on the pure Pt surface. The low Lewis acidity of Pt atoms on the PtIr surface entails a high electron density and a down-shifting of the d-band center, thereby weakening the binding energy towards intermediates (LiO2 ), which is the key in achieving low oxygen-reduction-reaction (ORR) and oxygen-evolution-reaction (OER) overpotentials. The Li-O2 cell based on PtIr electrodes exhibits a very low overall discharge/charge overpotential (0.44 V) and an excellent cycle life (180 cycles), outperforming the bulk of reported noble-metal-based cathodes.

Vγ9Vδ2 T cells play an important role in the development and progression of psoriasis vulgaris (PV), but how they promote skin inflammation and the molecular mechanisms underlying Vγ9Vδ2 T cell dysfunction are poorly understood. Here, we show that circulating Vγ9Vδ2 T cells are decreased and exhibit enhanced proliferation and increased production of IFN-γ and TNF-α in PV patients. Monocytes from PV patients express higher levels of the phosphoantigen sensor butyrophilin 3A1 (BTN3A1) than monocytes from healthy controls. Blockade of BTN3A1 suppresses Vγ9Vδ2 T cell activation and abolishes the difference in Vγ9Vδ2 T cell activation between PV patients and healthy controls. The CD14+cells in PV skin lesions highly express BTN3A1 and juxtapose to Vδ2 T cells. In addition, IFN-γ induces the up-regulation of BTN3A1 on monocytes. Collectively, our results demonstrate a crucial role of BTN3A1 on monocytes in regulating Vγ9Vδ2 T cell activation and highlight BTN3A1 as a potential therapeutic target for psoriasis.

Aim The study aimed to report a case of anatomical variation in the mouse iliac artery. Methods Totally 35 aortas of male ApoE−/− mice were dissected, including the aortic tree and their distal branches. Results Among the 35 arteries, 1 of them showed prominent anatomic variants unexpectedly. The terminal abdominal aorta descended as a trunk and finally extended into the left external iliac artery after divided out several main branches, instead of divided into the left and right iliac arteries communis as reported in previous studies. Conclusion The present study identified a rare case of iliac artery anatomical variation in ApoE- / -mice. Mice as vertebrate mammals highly close to human anatomy, the finding might help in the pre-intervention for catheter surgery in human patients and interpreting angiography of the pelvic region by radiologists.

The Internet of Things plays an indispensable role in the development of connected vehicles, which will pave the way for road safety applications. In recent years, the concept of a cooperative collision warning system (CCWS) has been introduced and developed to enhance road safety, and it has been seen as a typical Internet-of-Vehicles application. In most CCWSs, it is vital to have a detection mechanism based on trajectory predictions where the uncertainties associated with vehicular state and motion are complex. However, most available approaches in this regard did not consider these uncertainties. Hence, this article proposes a new collision risk assessment (CRA) method where sigma trajectories that include multiple possible trajectories considering multiple aspects of vehicular motion are designed to cope with vehicular uncertainties. Our method is implemented in a novel server-based architecture, which is different from the commonly used vehicle-based controlled CCWSs. The CRA is provided as a service by a cloud server. The proposed method and architecture are validated and evaluated through extensive real-world experiments. Experimental results show that our method outperforms a referenced method in terms of CRA and achieves better robustness in tolerating communication delays and dropouts. Latencies in CRA service were analyzed, and it was found that powerful computing resources provided by cloud servers can significantly decrease computational cost, which will indirectly compensate for communication costs in the future. Based on our high-performance CRA method, the proposed architecture can be regarded as a novel option for CCWS design.

Selective laser melting (SLM) has been applied to manufacture various alloy components with excellent properties, but its further application is restricted by the intrinsic defects. In this work, the internal defect distributions in samples of three alloys (316L stainless steel, AlSi10Mg and Inconel 718) were investigated respectively, considering the effects of geometrical characteristics of the samples. The defects in the 316L stainless steel sample tend to be formed densely in the central part with large wall thickness, indicating a strong sensitivity to heat accumulation. Contrarily, the Inconel 718 sample shows a higher relative density with homogeneous defect distribution, indicating better formability for the SLM process. For the AlSi10Mg sample, the defect density keeps increasing as the deposition goes on. Typically, the defect density located at sample edges shows an abnormally high level comparing with the inner part, especially in the top sections of AlSi10Mg and Inconel 718 samples. The results are helpful for the geometrical design, the adjustment of building orientation and the further optimization of process parameters in the SLM process.

Background: Cuproptosis is a new type of cell death that induces protein toxic stress and eventually leads to cell death. Hence, regulating cuproptosis in tumor cells is a new therapeutic approach. However, studies on cuproptosis-related long noncoding RNA (lncRNA) in head and neck squamous cell carcinoma (HNSC) have not been found. This study aimed to explore the cuproptosis-related lncRNAs prognostic marker and their relationship to immune microenvironment in HNSC by using bioinformatics methods.Methods: RNA sequencing, genomic mutations, and clinical data of TCGA_HNSC were downloaded from The Cancer Genome Atlas. HNSC patients were randomly assigned to either a training group or a validation cohort. The least absolute shrinkage and selection operator Cox regression and multivariate Cox regression models were used to determine the prognostic model in the training cohort, and its independent prognostic effect was further confirmed in the validation and entire cohorts.Results: Based on previous literature, we collected 19 genes associated with cuproptosis. Afterward, 783 cuproptosis-related lncRNAs were obtained through coexpression. Cox model revealed and constructed eight cuproptosis-related lncRNAs prognostic marker (AL132800.1, AC090587.1, AC079160.1, AC011462.4, AL157888.1, GRHL3-AS1, SNHG16, and AC021148.2). Patients were divided into high- and low-risk groups based on the median risk score. The Kaplan–Meier survival curve revealed that the overall survival between the high- and low-risk groups was statistically significant. The receiver operating characteristic curve and principal component analysis demonstrated the accurate prognostic ability of the model. Univariate and multivariate Cox regression analysis showed that risk score was an independent prognostic factor. In addition, we used multivariate Cox regression to establish a nomogram of the predictive power of prognostic markers. The tumor mutation burden showed significant differences between the high- and low-risk groups. HNSC patients in the high-risk group responded better to immunotherapy than those in the low-risk group. We also found that risk scores were significantly associated with drug sensitivity in HNSC.Conclusion: In summary, our study identified eight cuprotosis-related lncRNAs signature of HNSC as the prognostic predictor, which may be promising biomarkers for predicting the benefit of HNSC immunotherapy as well as drug sensitivity.

Objectives This study aims to explore a novel intraoperative trajectory-determined strategy of grouped patient-specific drill templates (PDTs) for transoral C2 pedicle screw insertion (C2 TOPI) for atlantoaxial dislocation (AAD) with incomplete reduction and to evaluate its efficiency and accuracy. Methods Ten cadaveric C2 specimens were scanned by computed tomography (CT) and randomly divided into two groups (the PDT and freehand groups). A novel intraoperative trajectory-determined strategy of grouped PDTs was created for AAD with incomplete reduction. C2 TOPI was performed by use of the PDT technique and the fluoroscopy-guided freehand technique. After surgery, the screw deviations from the centroid of the cross-section at the midpoint of the pedicle and screw position grades were assessed in both groups. Results Compared to the freehand group, the PDT group had a significantly shorter surgery time than the freehand group (47.7 vs 61.9 min, P 0.05). Conclusion The novel intraoperative trajectory-determined strategy of grouped PDTs can be used as an accurate and feasible method for C2 TOPI for AAD with incomplete reduction.

Vehicle state estimation and path prediction, which usually involve Kalman filter and motion model, are critical tasks for intelligent driving. In vehicle state estimation, the comparative performance assessment, regarding accuracy and efficiency, of the unscented Kalman filter (UKF) and the extended Kalman filter (EKF) is rarely discussed. This paper is devoted to empirically evaluating the performance of UKF and EKF incorporating different motion models and investigating the models’ properties and the affecting factors in path prediction. Extensive real world experiments have been carried out and the results show that EKF and UKF have roughly identical accuracy in state estimation; however, EKF is faster than UKF generally; the fastest filter is about 2⋅6 times faster than the slowest. The path prediction experiments reveal that the velocity estimate and the used motion model affect path prediction; the more realistically the model reflects the vehicle's driving status, the more reliable its predictions.

Sintering or agglomeration is formed in the process of the gasification of coal when fluxing K2CO3, which leading to the entire bed defluidization. In order to study the catalytic coal gasification reactivity and agglomeration properties in pressurized fluidized bed, Wangjiata raw coal, demineralized coal with HCl-HF treatment, and raw coal with different amounts of clay mineral addition were selected. The catalytic coal gasification reactivity, the agglomeration and sintering properties were studied. As well as water-soluble catalyst recovery from the gasification residue was also determined. The results show that for potassium-catalyzed steam gasification, not only coal ash content but also composition affected the gasification reactivity, agglomeration, and catalyst recovery. The carbon conversion increased varying degrees with increasing K2CO3 loadings, K2CO3 impregnated coal showed a high degree of agglomeration, and agglomeration increased with increasing K2CO3 amount. Demineralized coal couldn't improve the agglomeration property. The addition of Clay mineral, was found to be very efficient in anti-sintering. However, compared with demineralized coal, the carbon conversion and water washing catalyst recoveries decreased obviously for those samples with the addition of clay minerals. The test verifies that part of potassium catalyst irreversibly reacted with coal ash to form relatively water-insoluble potassium compounds such as kaliophilite and sanidine.

The main challenge for lithium-oxygen (Li-O2) batteries is their sluggish oxygen evolution reaction (OER) kinetics and high charge overpotentials caused by the poorly conductive discharge products of lithium peroxide (Li2O2). In this contribution, the cesium lead bromide perovskite (CsPbBr3) nanocrystals were first employed as a high-performance cathode for Li-O2 batteries. The battery with a CsPbBr3 cathode can exhibit the lowest charge overpotential of 0.5 V and the best cycling performance of 400 cycles among all the reported perovskite-based Li-O2 cells, which represents a new benchmark. Most importantly, the density functional theory (DFT) calculations further prove that the rate limitation step during OER processes is the decomposition of LiO2 to form O2 and Li+, and the weak adsorption strength between CsPbBr3 surfaces and LiO2 results in a low charge overpotential for the CsPbBr3-based Li-O2 battery. This work first demonstrates the good potential of CsPbBr3 for application in metal-air batteries.

High-entropy alloys (HEAs) are attracting intensive attention due to their broad compositional tunability and interesting catalytic properties. However, precisely shaping the HEAs into suprathin low-dimensional nanostructures for achieving diverse applications remains an enormous challenge owing to their intrinsic thermodynamic instability. Herein we propose a new and general low-temperature method for incorporating up to eight metallic elements into one single-phase subnanometer ribbon to achieve the thinnest HEA metal materials in the world. We experimentally demonstrate that synthetic processes for suprathin HEA subnanometer ribbons (SNRs) include (1) different metal atom nucleation via galvanic exchange reaction between different metal precursors and Ag nanowire template, (2) co-reduction of different metal precursors on nanowire template, and (3) the removal of the inner Ag core. Density functional theory (DFT) calculations reveal that the crystallization and stabilization of HEA SNRs strongly depend on the "highly dynamic" Ag from the template, and the crystallization levels of HEA subnanometer ribbons are closely correlated with the concentration of Pt and Pd. We demonstrate that the present synthetic method enables the flexible control of components and concentrations in HEAs SNRs for achieving a library of HEA SNRs and also superior electrocatalytic properties. The well-designed HEA SNRs show great improvement in catalyzing the oxygen reduction reaction of fuel cells and also high discharge capacity, low charge overpotential, and excellent durability for Li-O

In this paper, we study the problem of jointly estimating the optical flow and scene flow from synchronized 2D and 3D data. Previous methods either employ a complex pipeline that splits the joint task into independent stages, or fuse 2D and 3D information in an "early-fusion" or "late-fusion" manner. Such one-size-fits-all approaches suffer from a dilemma of failing to fully utilize the characteristic of each modality or to maximize the inter-modality complementarity. To address the problem, we propose a novel end-to-end framework, called CamLiFlow. It consists of 2D and 3D branches with multiple bidirectional connections between them in specific layers. Different from previous work, we apply a point-based 3D branch to better extract the geometric features and design a symmetric learnable operator to fuse dense image features and sparse point features. Experiments show that CamLiFlow achieves better performance with fewer parameters. Our method ranks 1st on the KITTI Scene Flow benchmark, outperforming the previous art with 1/7 parameters. Code is available at https://github.com/MCG-NJU/CamLiFlow., Comment: Accepted to CVPR 2022 (Oral)

Fluorescent organic hybrid nanosheets were generated by crystallization of polymers capped with luminogenic molecules exhibiting aggregation-induced emission characteristics (AIE). During crystallization of polymers, AIE molecules were expelled out of lamellar crystals of polymers, and finally resided on the surface. The fluorescent nanosheets with dangling AIE molecules showed sensitive and specific response to explosives. Such polymer crystallization-induced fluorescent nanomaterials offers a unique avenue to fabricate functional nanomaterials with AIE molecule-enriched domains for potential applications in nanodevices, biological engineering, and so on.

Polymer/inorganic functional nanostructures are essential for the fabrication of high-performance nanodevices in the future. The synthesis of hybrid nanostructures is hindered by complicated synthetic protocols or harsh conditions. Herein, we report a facile and scalable method for the synthesis of organometallic polymer nanoribbons through crystallization of polymers capped with a ferrate complex. Nanoribbons consisted of a single crystalline polymer lamella coated with a redox-active ferrate complex on both sides. The nanoribbons had a width of approximately 70 nm and a thickness of 10 nm. With the merit of highly ordered crystalline structures of polymers and functional coating layers, as well as a highly anisotropic nature, the nanoribbons are useful in nanodevices and biosensors.