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Fast permeation and effective solute-solute separation provide the opportunities for sustainable water treatment, but they are hindered by ineffective membranes. We present here the construction of a nanofiltration membrane with fast permeation, high rejection, and precise Cl - /SO 4 2- separation by spatial and temporal control of interfacial polymerization via graphitic carbon nitride (g-C 3 N 4 ). The g-C 3 N 4 nanosheet binds preferentially with piperazine and tiles the water-hexane interface as revealed by molecular dynamics studies, thus lowering the diffusion rate of PIP by one order of magnitude and restricting its diffusion pathways towards the hexane phase. As a result, membranes with nanoscale ordered hollow structure are created. Transport mechanism across the structure is clarified using computational fluid dynamics simulation. Increased surface area, lower thickness, and a hollow ordered structure are identified as the key contributors to the water permeance of 105 L m 2 ·h −1 ·bar −1 with a Na 2 SO 4 rejection of 99.4% and a Cl - /SO 4 2- selectivity of 130, which is superior to state-of-the-art NF membranes. Our approach for tuning the membrane microstructure enables the development of ultra-permeability and excellent selectivity for ion-ion separation, water purification, desalination, and organics removal. Membranes with precise ion-ion separation are critical for sustainable water treatment. Here, authors demonstrated controlled construction of a nanofiltration membrane with fast permeation and high Cl - /SO 4 2- selectivity by simultaneous spatial and temporal control of interfacial polymerization.

Pedestrian recognition has great practical value and is a vital step toward applying path planning and intelligent obstacle avoidance in autonomous driving. In recent years, laser radar has played an essential role in pedestrian detection and recognition in unmanned driving. More accurate high spatial dimension and high-resolution data could be obtained by building a three-dimensional point cloud. However, the point cloud data collected by laser radar is often massive and contains a lot of redundancy, which is not conducive to transmission and storage. So, the processing speed grows slow when the original point cloud data is used for recognition. On the other hand, the compression processing of many laser radar point clouds could save computing power and speed up the recognition processing. The article utilizes the fusion point cloud data from laser radar to investigate the fast pedestrian recognition algorithm. The focus is to compress the collected point cloud data based on the boundary and feature value extraction and then use the point cloud pedestrian recognition algorithm based on image mapping to detect pedestrians. This article proposes a point cloud data compression method based on feature point extraction and reduced voxel grid. The Karlsruhe Institute of Technology and Toyota Technological Institute data set is used to investigate the proposed algorithm experimentally. The outcomes indicate that the peak signal-to-noise ratio of the compression algorithm is improved by 6.02%. The recognition accuracy is improved by 16.93%, 17.2%, and 16.12%, corresponding to simple, medium, and difficult scenes, respectively, when compared with the point cloud pedestrian recognition method based on image mapping, which uses the random sampling method to compress the point cloud data. The proposed method could achieve data compression better and ensure that many feature points are retained in the compressed Point Cloud Data (PCD). Thus, the compressed PCD achieves pedestrian recognition through an image-based mapping recognition algorithm.

As a peer-to-peer “P2P” distributed ledger, the blockchain has the advantages of decentralization, no trust, open autonomy, and nontampering. Therefore, many users are willing to conduct transactions in blockchain cryptocurrency systems such as Bitcoin and Ethereum. However, the throughput of traditional blockchain is extremely low, and the transaction is so delayed. The payment channel network is the most promising solution to expand the blockchain for widespread use. Achieving secure instant payment on the payment channel can significantly increase transaction throughput and reduce transaction delays. When the payment channel is closed, the balance in the channel will be returned to an account on the blockchain. In this paper, we discuss the design and the implementation of a multiparty payment channel network based on smart contracts. Where a two-party payment channel is designed based on blockchain and smart contracts, a new multiparty payment channel is established on the basis of the payment channel. A detailed definition and description are given, and the creation, update, and closing functions of the multiparty payment channel are designed. Moreover, we design a multiparty payment channel smart contract, deploy it to the local private blockchain, and conduct simulation and testing. The delay time of different transaction methods is counted, and the network topology type, transaction amount, and other factors are studied. The impact of transaction success rate and the gas consumption of different transaction methods are analyzed through multiple sets of experimental statistics.

Fringe projection profilometry (FPP) has been widely used for 3D reconstruction, surface measurement, and reverse engineering. However, if the surface of an object has a high reflectivity, overexposure can easily occur. Image saturation caused by overexposure can lead to an incorrect intensity of the captured pattern images, resulting in phase and measurement errors of FPP. To address this issue, we propose a phase retrieval method for the 3D shape measurement of high-reflectivity surfaces based on π phase-shifting fringes. Our method only requires eight images to be projected, including three single-frequency three-step phase-shifting patterns and one pattern used to provide phase unwrapping constraints, called conventional patterns, as well as the π phase-shifting patterns corresponding to the four conventional patterns, called supplemental patterns. Saturated pixels of conventional fringes are replaced by unsaturated pixels in supplemental fringes to suppress phase retrieval errors. We analyzed all 16 replacement cases of fringe patterns and provided calculation methods for unwrapped phases. The main advantages of our method are as follows: (1) By combining the advantages of the stereo phase unwrapping (SPU) algorithm, the number of projected fringes is reduced. (2) By utilizing the phase unwrapping constraint provided by the fourth fringe pattern, the accuracy of SPU is improved. For highly reflective surfaces, the experimental results demonstrate the performance of the proposed method.

Biothiols such as cysteine, homocysteine, and glutathione play significant roles in important biological activities, and their abnormal concentrations have been found to be closely associated with certain diseases, making their detection a critical task. To this end, fluorescent probes have become increasingly popular due to their numerous advantages, including easy handling, desirable spatiotemporal resolution, high sensitivity, fast response, and favorable biocompatibility. As a result, intensive research has been conducted to create fluorescent probes for the detection and imaging of biothiols. This brief review summarizes recent advances in the field of biothiol-responsive fluorescent probes, with an emphasis on rational probe design, including the reaction mechanism, discriminating detection, reversible detection, and specific detection. Furthermore, the challenges and prospects of fluorescence probes for biothiols are also outlined.

Cytokinins are one of the most important phytohormones and play essential roles in multiple life processes in planta. Root-derived cytokinins are transported to the shoots via long-distance transport. The mechanisms of long-distance transport of root-derived cytokinins remain to be demonstrated. In this study, we report that OsABCG18, a half-size ATP-binding cassette transporter from rice (Oryza sativa L.), is essential for the long-distance transport of rootderived cytokinins. OsABCG18 encodes a plasma membrane protein and is primarily expressed in the vascular tissues of the root, stem, and leaf midribs. Cytokinin profiling, as well as [14C]trans-zeatin tracer, and xylem sap assays, demonstrated that the shootward transport of root-derived cytokinins was significantly suppressed in the osabcg18 mutants. Transport assays in tobacco (Nicotiana benthamiana) indicated that OsABCG18 exhibited efflux transport activities for various substrates of cytokinins. While the mutation reduced root-derived cytokinins in the shoot and grain yield, overexpression of OsABCG18 significantly increased cytokinins in the shoot and improved grain yield. The findings for OsABCG18 as a transporter for long-distance transport of cytokinin provide new insights into the cytokinin transport mechanism and a novel strategy to increase cytokinins in the shoot and promote grain yield.

Human infection with avian influenza A H7N9 virus emerged in eastern China in February, 2013, and has been associated with exposure to poultry. We report the clinical and microbiological features of patients infected with influenza A H7N9 virus and compare genomic features of the human virus with those of the virus in market poultry in Zhejiang, China. Between March 7 and April 8, 2013, we included hospital inpatients if they had new-onset respiratory symptoms, unexplained radiographic infiltrate, and laboratory-confirmed H7N9 virus infection. We recorded histories and results of haematological, biochemical, radiological, and microbiological investigations. We took throat and sputum samples, used RT-PCR to detect M, H7, and N9 genes, and cultured samples in Madin-Darby canine kidney cells. We tested for co-infections and monitored serum concentrations of six cytokines and chemokines. We collected cloacal swabs from 86 birds from epidemiologically linked wet markets and inoculated embryonated chicken eggs with the samples. We identified and subtyped isolates by RT-PCR sequencing. RNA extraction, complementary DNA synthesis, and PCR sequencing were done for one human and one chicken isolate. We characterised and phylogenetically analysed the eight gene segments of the viruses in the patient's and the chicken's isolates, and constructed phylogenetic trees of H, N, PB2, and NS genes. We identified four patients (mean age 56 years), all of whom had contact with poultry 3–8 days before disease onset. They presented with fever and rapidly progressive pneumonia that did not respond to antibiotics. Patients were leucopenic and lymphopenic, and had impaired liver or renal function, substantially increased serum cytokine or chemokine concentrations, and disseminated intravascular coagulation with disease progression. Two patients died. Sputum specimens were more likely to test positive for the H7N9 virus than were samples from throat swabs. The viral isolate from the patient was closely similar to that from an epidemiologically linked market chicken. All viral gene segments were of avian origin. The H7 of the isolated viruses was closest to that of the H7N3 virus from domestic ducks in Zhejiang, whereas the N9 was closest to that of the wild bird H7N9 virus in South Korea. We noted Gln226Leu and Gly186Val substitutions in human virus H7 (associated with increased affinity for α-2,6-linked sialic acid receptors) and the PB2 Asp701Asn mutation (associated with mammalian adaptation). Ser31Asn mutation, which is associated with adamantane resistance, was noted in viral M2. Cross species poultry-to-person transmission of this new reassortant H7N9 virus is associated with severe pneumonia and multiorgan dysfunction in human beings. Monitoring of the viral evolution and further study of disease pathogenesis will improve disease management, epidemic control, and pandemic preparedness. Larry Chi-Kin Yung, National Key Program for Infectious Diseases of China.

Summary The flag leaf and grain belong to the source and sink, respectively, of cereals, and both have a bearing on final yield. Premature leaf senescence significantly reduces the photosynthetic rate and severely lowers crop yield. Cytokinins play important roles in leaf senescence and determine grain number. Here, we characterized the roles of the rice (Oryza sativa L.) cytokinin oxidase/dehydrogenase OsCKX11 in delaying leaf senescence, increasing grain number, and coordinately regulating source and sink. OsCKX11 was predominantly expressed in the roots, leaves, and panicles and was strongly induced by abscisic acid and leaf senescence. Recombinant OsCKX11 protein catalysed the degradation of various types of cytokinins but showed preference for trans‐zeatin and cis‐zeatin. Cytokinin levels were significantly increased in the flag leaves of osckx11 mutant compared to those of the wild type (WT). In the osckx11 mutant, the ABA‐biosynthesizing genes were down‐regulated and the ABA‐degrading genes were up‐regulated, thereby reducing the ABA levels relative to the WT. Thus, OsCKX11 functions antagonistically between cytokinins and ABA in leaf senescence. Moreover, osckx11 presented with significantly increased branch, tiller, and grain number compared with the WT. Collectively, our findings reveal that OsCKX11 simultaneously regulates photosynthesis and grain number, which may provide new insights into leaf senescence and crop molecular breeding.

Reservoir temperature estimation is crucial for geothermal studies, but traditional methods are complex and uncertain. To address this, we collected 83 sets of water chemistry and reservoir temperature data and applied four machine learning algorithms. These models considered various input factors and underwent data preprocessing steps like null value imputation, normalization, and Pearson coefficient calculation. Cross-validation addressed data volume issues, and performance metrics were used for model evaluation. The results revealed that our machine learning models outperformed traditional fluid geothermometers. All machine learning models surpassed traditional methods. The XGBoost model, based on the F-3 combination, demonstrated the best prediction accuracy with an R 2 of 0.9732, while the Bayesian ridge regression model using the F-4 combination had the lowest performance with an R 2 of 0.8302. This study highlights the potential of machine learning for accurate reservoir temperature prediction, offering geothermal professionals a reliable tool for model selection and advancing our understanding of geothermal resources.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent for coronavirus 2019 (COVID-19) pneumonia. Little is known about the kinetics, tissue distribution, cross-reactivity, and neutralization antibody response in patients with COVID-19. Two groups of patients with RT-PCR-confirmed COVID-19 were enrolled in this study: 12 severely ill patients in intensive care units who needed mechanical ventilation and 11 mildly ill patients in isolation wards. Serial clinical samples were collected for laboratory detection. Results showed that most of the severely ill patients had viral shedding in a variety of tissues for 20-40 days after onset of disease (8/12, 66.7%), while the majority of mildly ill patients had viral shedding restricted to the respiratory tract and had no detectable virus RNA 10 days after onset (9/11, 81.8%). Mildly ill patients showed significantly lower IgM response compared with that of the severe group. IgG responses were detected in most patients in both the severe and mild groups at 9 days after onset, and remained at a high level throughout the study. Antibodies cross-reactive to SARS-CoV and SARS-CoV-2 were detected in patients with COVID-19 but not in patients with MERS. High levels of neutralizing antibodies were induced after about 10 days after onset in both severely and mildly ill patients which were higher in the severe group. SARS-CoV-2 pseudotype neutralization test and focus reduction neutralization test with authentic virus showed consistent results. Sera from patients with COVID-19 inhibited SARS-CoV-2 entry. Sera from convalescent patients with SARS or Middle East respiratory syndrome (MERS) did not. Anti-SARS-CoV-2 S and N IgG levels exhibited a moderate correlation with neutralization titers in patients' plasma. This study improves our understanding of immune response in humans after SARS-CoV-2 infection.