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Efficiently adsorbing Pd(II) from acidic radioactive waste liquid is crucial for ensuring the safety of the radioactive waste vitrification process and significantly alleviating the scarcity of precious metals. However, the stability and selectivity of most current adsorbents are limited, hindering their practical application under acidic conditions. To address these limitations, a covalent organic framework (DHTP-TPB COF) was prepared with a high nitrogen content, leveraging the high affinity of its soft ligand Nwith palladium to achieve high selectivity. This work demonstrated that DHTP-TPB COF exhibits rapid adsorption kinetics, with equilibrium achieved within 10 min. The framework also boasts a high adsorption capacity of 142.8 mg/g and impressive reusability in 1.0 M nitric acid. Moreover, the DHTP-TPB COF displays excellent selectivity for Pd(II), even in the presence of 13 interfering ions. By combining FT-IR, XPS spectroscopy, and DFT theoretical calculations, the dense Nsites in the framework have a strong affinity for Pd(II), resulting in exceptional adsorption performance that was confirmed. The findings of this study highlight the potential of COFs with robust linkers and customized functional groups to effectively and selectively capture Pd(II) under harsh environmental conditions of high-level liquid waste.

Deploying federated learning (FL) applications in unmanned aerial vehicle (UAV)-assisted wireless networks can enable ground terminals (GTs) to perform complex machine learning tasks with their own data. However, the FL is inefficient in practice due to the massive model parameters and device heterogeneity. In this paper, we propose a joint client selection and model compression scheme for FL (csmcFL) to improve training efficiency. Specifically, the average throughput of users is first improved by optimizing the UAV deployment location based on user communication fairness. Then, a low-rank decomposition of the fully connected layer in the CNN is performed to compress the model parameters, and partial devices are screened to implement model compression through the client selection strategy to alleviate the excessive aggregation time due to device heterogeneity. We perform extensive simulation experiments in different data distribution scenarios, and the experimental results show that the proposed scheme significantly reduces the data volume of the transmitted model while achieving higher model accuracy compared to the baseline scheme.

ABSTRACTOpenStreetMap (OSM) as one of the most successful projects of Volunteered Geographical Information (VGI) has attracted millions of contributors to work together and produces massive open geographical data. However, the co-work does not always run smoothly since mapping can involve conflicted understandings of the reality. In this paper, we investigate behaviors of mapping related to territorial disputes to reveal the characteristics of contributions and examine the contradictions between ground truth as the vision of OSM and the theory of critical cartography. We perform our experiments from the perspectives of entities, changesets, and contributors using the full history data of OSM. The experiments show that territorial-dispute-related contributions have substantially different characteristics from various aspects but they cannot be treated as outliers either, considering that most contributors do not focus on disputed boundaries. Interpreting OSM data as a converging state to ground truth or equally opinions can both be inaccurate. We also find that mapping disputes may not be absolutely negative in a VGI project.

Cadmium (Cd) accumulation in rice grain is of health concern. Identifying genes involved in grain Cd accumulation and performing molecular breeding may reduce it. In this study, knockout of OsNRAMP2, a member of the NRAMPfamily, reduced grain Cd concentrations by more than 38%, and overexpressing OsNRAMP2increased grain Cd concentrations by more than 50%. Physiological experiments showed that OsNRAMP2facilitated Cd translocation from root to shoot by positively regulating Cd efflux from the vacuoles. At filling stage, OsNRAMP2was highly expressed in all tissues except for husk, suggesting its role in Cd remobilization. Changes in OsNRAMP2expression affected the concentrations of Fe, Mn, Zn, and Cu in grain and also affected rice growth. Phylogenetic analysis showed that the distribution of OsNRAMP2haplotypes between japonicaand indicawas different. Among the four haplotypes of OsNRAMP2, Hap 1, with a 6-bp nucleotide insertion in exon 1, had grain Cd concentration at least 45.3% lower than any of the other three haplotypes. Almost all (99.3%) japonicaaccessions but rare indicaaccessions (4.44%) from the 3K sequenced rice genomes carry Hap 1 of OsNRAMP2. Our study sheds light on the molecular mechanism of grain Cd accumulation and provides a promising target for low-Cd rice breeding.

Accurate identification of the resectable epileptic lesion is a precondition of operative intervention to drug-resistant epilepsy (DRE) patients. However, even when multiple diagnostic modalities are combined, epileptic foci cannot be accurately identified in ∼30% of DRE patients. Inflammation-associated low-density lipoprotein receptor-related protein-1 (LRP1) has been validated to be a surrogate target for imaging epileptic foci. Here, we reported an LRP1-targeted dual-mode probe that is capable of providing comprehensive epilepsy information preoperatively with SPECT imaging while intraoperatively delineating epileptic margins in a sensitive high-contrast manner with surface-enhanced resonance Raman scattering (SERRS) imaging. Notably, a novel and universal strategy for constructing self-assembled monolayer (SAM)-based Raman reporters was proposed for boosting the sensitivity, stability, reproducibility, and quantifiability of the SERRS signal. The probe showed high efficacy to penetrate the blood–brain barrier. SPECT imaging showed the probe could delineate the epileptic foci clearly with a high target-to-background ratio (4.11 ± 0.71, 2 h). Further, with the assistance of the probe, attenuated seizure frequency in the epileptic mouse models was achieved by using SPECT together with Raman images before and during operation, respectively. Overall, this work highlights a new strategy to develop a SPECT/SERRS dual-mode probe for comprehensive epilepsy surgery that can overcome the brain shift by the co-registration of preoperative SPECT and SERRS intraoperative images.

Stimulated by the structural feature of the [NiFe]-hydrogenase active sites, five new heteroleptic 1,2-bis(p-substitutedphenyl)ethylene-1,2-dithiolate nickel complexes containing the N-(p-methoxyphenyl)-bis(diphenylphosphine)amine ligand, [p-CH3OC6H4N(PPh2)2]Ni[S2C2(C6H4R-p)2)] (R = CH3O (1), CH3(2), H (3), Br (4), and F (5)), were synthesized and characterized. The crystal structure analysis of 2and 4·CH2Cl2indicates that the two complexes have an almost perfect S2P2square planar coordination environment defined by the 1,2-diarylethylene-1,2-dithiolate and bis(diphenylphosphine)amine ligands. The electrochemical behavior and electrocatalytic hydrogen-evolving activity were investigated using trifluoroacetic acid (TFA) as the proton source in combination with cyclic voltammetry (CV) and controlled potential electrolysis (CPE). The turnover frequencies (TOF) and overpotentials (η) for hydrogen evolution of 1–5(0.25 mM) in DMF are estimated to be 423–894 s−1and 0.91–1.02 V with 67.32 mM TFA, respectively. Faradaic efficiencies (FE) of 66.15–98.20% and turnover numbers (TON) of 13.16–35.92 are achieved under the CPE experiments over 18 hour periods at −2.00 V vs.Fc+/Fc, respectively. Density functional theory (DFT) calculations display that the electron-withdrawing substituent on the 1,2-diarylethylene-1,2-dithiolate ligand can reduce the energy levels of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) of the complex, leading to lower negative redox and catalytic potentials. On the basis of the experiments and the theoretical calculations, an ECEC electrocatalytic mechanism for hydrogen production is proposed. Intriguingly, excellent electrochemical stability of 1–5in hydrogen generation is observed, which can act as potential candidates for electrocatalysts with high tolerance. These research findings confirm that the synthesized heteroleptic complexes can serve as homogeneous molecular electrocatalysts for hydrogen production with high tolerance.

Studies on the association between growth-differentiation factor-15 (GDF-15) level and adverse outcomes have yielded conflicting results in patients with stable coronary artery disease (CAD). This meta-analysis aimed to evaluate the association of baseline GDF-15 level with adverse outcomes in stable CAD patients.

Human lung adenosquamous cell carcinoma (LUAS), containing both adenomatous and squamous pathologies, exhibits strong cancer plasticity. We find that ALK rearrangement is detectable in 5.1–7.5% of human LUAS, and transgenic expression of EML4-ALK drives lung adenocarcinoma (LUAD) formation initially and squamous transition at late stage. We identify club cells as the main cell-of-origin for squamous transition. Through recapitulating lineage transition in organoid system, we identify JAK-STAT signaling, activated by EML4-ALK phase separation, significantly promotes squamous transition. Integrative study with scRNA-seq and immunostaining identify a plastic cell subpopulation in ALK-rearranged human LUAD showing squamous biomarker expression. Moreover, those relapsed ALK-rearranged LUAD show notable upregulation of squamous biomarkers. Consistently, mouse squamous tumors or LUAD with squamous signature display certain resistance to ALK inhibitor, which can be overcome by combined JAK1/2 inhibitor treatment. This study uncovers strong plasticity of ALK-rearranged tumors in orchestrating phenotypic transition and drug resistance and proposes a potentially effective therapeutic strategy.

With the development of DNA nanotechnology, DNA has been widely used to construct a variety of nanomachines. Among them, a DNA walker is a unique nanomachine that can move continuously along a specific orbit to fulfill diverse functions. In this paper, a dual signal amplification electrochemical biosensor based on a DNA walker and DNA nanoflowers is constructed for high sensitivity detection of Staphylococcus aureus(S. aureus). Two groups of double-stranded DNA are modified on the surface of a gold electrode. The binding of S. aureuswith its aptamer induces the disintegration of the long double strands and releases the DNA walker. With the help of exonuclease III (Exo III), the DNA walker moves along the electrode surface and continuously hydrolyzes the anchored short double strands. The introduction of a specially customized circular DNA and phi29 DNA polymerase initiates the rolling circle amplification (RCA) reaction. DNA nanoflowers are formed at high local concentration of DNA in the solution, which provide binding sites for electroactive methylene blue (MB) and thus produce intense signal. Under the best conditions, the current response is linearly related to the logarithm of the concentration of S. aureusranging from 60 to 6 × 107CFU/mL, and the detection limit is 9 CFU/mL. In addition, the proposed biosensor has achieved satisfactory results in the detection of actual water samples and diluted honey samples, which confirm the practicability of the biosensor and its application potential in environmental monitoring and food safety.

Parallel arrays with coprime subarrays have shown its potential advantages for two dimensional direction of arrival (DOA) estimation. In this paper, by introducing two flexible coprime factors to enlarge the inter-element spacing of parallel uniform subarrays, we propose a generalized parallel coprime array (GPCA) geometry. The proposed geometry enjoys flexible array layouts by the coprime factors and enables to extend the array aperture to achieve great improvement of estimation performance. Meanwhile, we verify that GPCA always can obtain M2 degrees of freedom (DOFs) in co-array domain via 2M sensors after optimization, which outperforms sparse parallel array geometries, such as parallel coprime array (PCA) and parallel augmented coprime array (PACA), and is the same as parallel nested array (PNA) with extended aperture. The superiority of GPCA geometry has been proved by numerical simulations with sparse representation methods.

With rising living standards, there is an increasing demand for high-quality rice. Rice quality is mainly defined by milling quality, appearance quality, cooking and eating quality, and nutrition quality. Among them, chalkiness is a key trait for appearance quality, which adversely affects cooking and eating quality, head rice yield, and commercial value. Therefore, chalkiness is undesirable, and reducing chalkiness is a major goal in rice quality improvement. However, chalkiness is a complex trait jointly influenced by genetic and environmental factors, making its genetic study and precision improvement a huge challenge. With the rapid development of molecular techniques, much knowledge has been gained about the genes and molecular networks involved in chalkiness formation. The present review describes the major environmental factors affecting chalkiness and summarizes the quantitative trait loci (QTL) associated with chalkiness. More than 150 genes related to chalkiness formation have been reported. The functions of the genes regulating chalkiness, primarily those involved in starch synthesis, storage protein synthesis, transcription regulation, organelle development, grain shape regulation, and high-temperature response, are described. Finally, we identify the challenges associated with genetic improvement of chalkiness and suggest potential strategies. Thus, the review offers insight into the molecular dynamics of chalkiness and provides a strong basis for the future breeding of high-quality rice varieties.

Background: A pangenome aims to capture the complete genetic diversity within a species and reduce bias in genetic analysis inherent in using a single reference genome. However, the current linear format of most plant pangenomes limits the presentation of position information for novel sequences. Graph pangenomes have been developed to overcome this limitation. However, bioinformatics analysis tools for graph format genomes are lacking. Results: To overcome this problem, we develop a novel strategy for pangenome construction and a downstream pangenome analysis pipeline (PSVCP) that captures genetic variants’ position information while maintaining a linearized layout. Using PSVCP, we construct a high-quality rice pangenome using 12 representative rice genomes and analyze an international rice panel with 413 diverse accessions using the pangenome as the reference. We show that PSVCP successfully identifies causal structural variations for rice grain weight and plant height. Our results provide insights into rice population structure and genomic diversity. We characterize a new locus (qPH8-1) associated with plant height on chromosome 8 undetected by the SNP-based genome-wide association study (GWAS). Conclusions: Our results demonstrate that the pangenome constructed by our pipeline combined with a presence and absence variation-based GWAS can provide additional power for genomic and genetic analysis. The pangenome constructed in this study and the associated genome sequence and genetic variants data provide valuable genomic resources for rice genomics research and improvement in future.

Glioma is the most frequent form of malignant brain tumors. Surgical debulking is a major strategy for glioma treatment. However, there is a great challenge for the neurosurgeons to intraoperatively identify the true margins of glioma because of its infiltrative nature. Tumor residues or microscopic satellite foci left in the resection bed are the main reasons leading to early recurrence as well as poor prognosis. In this study, a surface-enhanced resonance Raman scattering (SERRS) probe was developed to intraoperatively guide glioma resection. In this probe, molecular reporters with absorptive maxima at the near-infrared wavelength range were covalently functionalized on the surface of gold nanostars. This SERRS probe demonstrated an ultrahigh sensitivity with a detection limit of 5.0 pM in aqueous solution. By the development of glioma xenografts in a mouse dorsal skin window chamber, extravasation of this probe from leaky tumor vasculature as functions of time and distance to tumor boundary was investigated. Importantly, the invasive margin of the tumor xenograft was demarcated by this probe with a high signal-to-background ratio. Preoperative magnetic resonance imaging (MRI) first defined the position of orthotopic glioma xenografts in the brain of rat models, and the craniotomy plan was designed. The brain tumor was then excised intraoperatively step-by-step with the assistance of a handheld Raman scanner till the Raman signals of the probe completely disappeared in the resection bed. Notably, longitudinal MRI showed that SERRS-guided surgery significantly reduced the tumor recurrence rate and improved the overall survival of rat models compared with the white light-guided surgery. Overall, this work demonstrates the prognostic benefit of SERRS-guided glioma surgery in animal models. Because delineation of tumor-invasive margins is a common challenge faced by the surgeons, this SERRS probe with a picomolar detection limit holds the promise in improving the surgical outcome of different types of infiltrated tumors.

Quantum repeaters1–4 are essential elements for demonstrating global-scale quantum communication. Over the past few decades, tremendous efforts have been dedicated to implementing a practical quantum repeater5–10 . However, nested purification1 , the backbone of a quantum repeater, remains a challenge because the capacity for successive entanglement manipulation is still absent. Here, we propose and demonstrate an architecture of nested purification using spontaneous parametric downconversion sources11 . A heralded entangled photon pair with higher fidelity is successfully purified from two copies of low-fidelity pairs that experience entanglement swapping and noisy channels. By delicately designing the optical circuits, double-pair emission noise is eliminated automatically and the purified state can be used for scalable entanglement connections to extend the communication distance. Combined with a quantum memory, our approach can be applied immediately in the implemention of a practical quantum repeater. A nested purification protocol is developed by combining entanglement purification and swapping. It works for the spontaneous parametric downconversion sources as well as other physical systems that suffer from double-pair emission noise.

Metal materials often suffer acid and alkaline corrosion during long-term service due to the low interfacial compatibility of anti-corrosion materials, which seriously limits their service life and safety. Here, a new strategy for preparing efficient corrosion inhibitors with high interfacial compatibility and environment-friendly was proposed through the synthesized two semi flexible nonplanar double Schiff bases containing two aromatic rings, 4,4’-(1,2-propanediyl)bis(azaneylylidene)bis(methaneylylidene)bis(2,6-dimethoxyphenol) (PAMP) and N,N’-(1,3-propandiyl)bis(1-(2-pyridyl)methanimine) (PPM). The corrosion inhibition efficiencies for mild steel by PAMP and PPM were evaluated in 1.0 mol L-1HCl solution with weight loss measurement. The weight loss results showed that the maximum corrosion inhibition efficiencies of PAMP and PPM are 87.56% and 91.36% at 30 °C, respectively. The corrosion inhibition enhancements were also explored through electrochemical investigation, scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and water contact angle measurement. The results suggested two double Schiff bases are mixed type corrosion inhibitors, and obey Langmuir adsorption isotherm with spontaneous physi- and chemisorption for PAMP whilst spontaneous chemisorption for PPM on mild steel surface to form a compact protective film due to their high interfacial compatibility. The nature of adsorption process of two double Schiff bases on mild steel surface was also inferred by using the adsorption data and the activation parameters. Furthermore, density functional theory (DFT) calculations showed that the energy gaps (ΔE) of the neutral PAMP and PPM molecules are 4.3887 eV and 5.1297 eV, respectively, while the ΔEvalues of their protonated forms are closer. DFT calculations and molecular dynamic (MD) simulations further disclosed that the difference of the corrosion inhibition effects between PAMP and PPM mostly come from the significant difference of steric hindrance and adsorption morphology together with intrinsic molecular parameters. This strategy is universal for the efficient protection of metal materials in long-term service.

Coherently manipulating a number of entangled qubits is the key task of quantum information processing. In this paper, we report on the experimental realization of a ten-photon Greenberger–Horne–Zeilinger state using thin BiB_3O_6 crystals. The observed fidelity is 0.606±0.029, demonstrating a genuine entanglement with a standard deviation of 3.6σ. This result is further verified using p-value calculation, obtaining an upper bound of 3.7×10^−3 under an assumed hypothesis test. Our experiment paves a new way to efficiently engineer BiB_3O_6 crystal-based multi-photon entanglement systems, which provides a promising platform for investigating advanced optical quantum information processing tasks such as boson sampling, quantum error correction, and quantum-enhanced measurement.

Exfoliated graphene oxide (EG)/MoO2composites are synthesized by a simple solid-state graphenothermal reduction method. Graphene oxide (GO) is used as a reducing agent to reduce MoO3and as a source for EG. The formation of different submicron sized morphologies such as spheres, rods, flowers, etc., of monoclinic MoO2on EG surfaces is confirmed by complementary characterization techniques. As-synthesized EG/MoO2composite with a higher weight percentage of EG performed excellently as an anode material in lithium-ion batteries. The galvanostatic cycling studies aided with postcycling cyclic voltammetry and galvanostatic intermittent titrations followed by ex situ structural studies clearly indicate that Li intercalation into MoO2is transformed into conversion upon aging at low current densities while intercalation mechanism is preferably taking place at higher current rates. The intercalation mechanism is found to be promising for steady-state capacity throughout the cycling because of excess graphene and higher current density even in the operating voltage window of 0.005–3.0 V in which MoO2undergoes conversion below 0.8 V.

A multi-symbol phase modulation format, the 8 phase shift keying (8PSK) with 50% return-to-zero (RZ) clock, is proposed and demonstrated in this scheme for 30-Gb/s optical access downlink transmission applications using phase equalization technique in MSPE. RZ-8PSK optical signals are generated by cascading three phase modulators and a dual-arm Mach-Zehnder modulator. Superimposed 50% RZ clock is extracted and recovered for achieving access restoration. The result show the reception performance of 50% RZ-8PSK signals with phase equalization after transmission over SMF-28 is good.

A parallel real-time visualization software tool HiVecMap is proposed here for large-scale geographic vector data mapping. HiVecMap calculates the mapping value of each display cell instead of the value of each vector feature. The mapping value of each display cell is determined by the number of geographic vector features in the corresponding spatial range. Thereby, the computational complexity is depends on the number of the cells rather than the number of features of the whole geographic dataset. When the number of the cells is much smaller than the number of geographic features, the visualization efficiency can be greatly improved. HiVecMap is implemented with the MPI+OpenMP parallel strategy, and has been extensively tested. Results show that large-scale geographic vector data can be online mapped in real-time, which has a performance improvement of more than ten times compared with the existing best methods.

Linear transceiver designs are investigated for distributed two-way relaying networks, which aim at minimising the Weighted Mean Square Error (WMSE) of data detections. The forwarding matrices at relays and equalization matrices at destinations are jointly optimised. To overcome the challenging limitations introduced by individual power constraints, a Semi-Definite Relaxation (SDR) called element-wise relaxation is proposed, which can transform the original optimization problem into a standard convex optimization problem. In this research, two-way relaying is understood from a pure signal processing perspective which can potentially simplify the theoretical analysis. Finally, simulation results are used for assessing the performance advantage of the proposed algorithm.

At present, the profile in the impeller axial plane of the engine water pump is designed by using the method of the projection on the axial plane, which needs repeat calculation and plentiful and complicated works. The profile in the impeller axial plane is designed by the design method of the hyperbola profile according to the principle of the angle flow which follows liquid flow law. This way provides a simple and available method for the engineers that embark on the impeller design. It can avoid the complication of conventional way and save large amount of manpower and funds. The model is built by CAD and analyzed by CFD. The result shows that the reversed flows and the secondary flows are evidently reduced. At the same time, the experiment verified that the head and efficiency of the pump are improved distinctly.

Using a linear variable filter in front of photo-detector array such as CCD or CMOS detector array, we could minimize the impact of stray light and improve the resolution of micro spectrometers. Unfortunately, this method could not exhibit the spectral resolution of a parallel filter in the same way, because the transmitted beam from a linear variable filter has broadening. The broadening becomes limited in the linear variable filter for high-resolution spectral systems. In this study, through theoretical analysis of the focused beam and the experiments, we developed a method to improve the resolution of micro spectrometer. This method was useful for practical engineering applications.

The black hole mass, along with the ratio of the accretion rate to the Eddington accretion rate, is a fundamental parameter of active galactic nuclei. Using our new method to estimate the black hole mass, we developed our sample and estimated black hole masses, indicated by $M_\mathrm{H}$for 12 blazars. We compared 12 cases, for each of which the relevant black hole mass was also estimated by the $L_\mathrm{5100} \hbox{--} R_\mathrm{BLR}$relation or the $M_\mathrm{BH} \hbox{--} \sigma$correlation method, which is indicated by $M_\mathrm{\sigma}$. We also found that (1) $M_\mathrm{H}$values are systematically lower than $M_\mathrm{\sigma}$, but the differences between $M_\mathrm{\sigma}$and $M_\mathrm{H}$are very small for most sources; (2) there is a significant correlation between $M_\mathrm{\sigma}$and $M_\mathrm{H}$, the correlation coefficient being $r = 0.66$with a chance probability of $p \sim 1.9 \times 10^{-2}$. Based on these properties mentioned above, we have shown that the small systematical difference between $M_\mathrm{\sigma}$and $M_\mathrm{H}$is probably due to some systematic errors in our method.

Topological relationships between two spatial features represent important knowledge in Geographical Information Systems (GIS). In the last few years, many models that represent topological relationships have been proposed. But these models cannot represent the topological relationships between heterogeneous geometrycollection features, which are composed of different dimensional geometries. In this paper, the formal definition of regular heterogeneous geometrycollection and regularization rules are given. Based on the spatial model, two methods for representing topological relationships between these complex features are proposed. The first method is Dimensionally Extended Nine-Intersection Model Based on Components (DE-9IMBC) that extends Dimensionally Extended Nine-Intersection Model (DE-9IM) and takes into account the topological relationships between components of these complex features. The advantage of DE-9IMBC is that a large number of different topological relationships can be checked. The second method extends the definitions of topological relationships in Open Geodata Interoperability Specification (Open GIS), and redefines the seven named topological relationships: {Disjoint, Touches, Within, Crosses, Overlaps, Contains and Equal}, to represent the topological relationships between heterogeneous geometrycollection features. It is proven that the seven extended topological relationships are complete and mutually exclusive, and they are suitable for being embedded in spatial query languages.

Considering the Klein–Nishina effects for high-energy $\gamma$-ray emissions, we derived a corrected form of the basic Elliot–Shapiro formula. Two new lower limits to the time scales of the variability expected from an accreting Schwarzschild black hole and Kerr black hole were derived, respectively. For a sample of 25 GeV $\gamma$-ray-loud blazars known to have the shortest time scales of flux variability, $t_\mathrm{min}$, we studied the corrected Elliot–Shapiro relations between $t_\mathrm{min}$and the GeV $\gamma$-ray luminosities in both the high and low states, respectively. We observe that: (1) No sources have been observed to have GeV $\gamma$-ray luminosities in the low state above the corrected Eddington limit being produced by a Kerr black hole and a Schwarzschild black hole. (2) Only one source has been observed to have a luminosity in the high state above the corrected Eddington limit being produced by a Kerr black hole and a Schwarzschild black hole, which is a new argument for not invoking relativistic beaming models for the present EGRET observational data alone. Our conclusion is that if one considers the Klein–Nishina effect, the evidence for beamed emission from the present gamma-ray data alone is weak. Obviously, our conclusion is consistent with that of Dermer and Gehrels (1995, ApJ, 447, 103), but it is a new independent evidence.

ABSTRACTThe vast majority (>90%) of glioblastoma (GBM) patients belong to the isocitrate dehydrogenase 1 wild type (IDH1WT) group which exhibits a poor prognosis with a median survival of less than 15 months. This study demonstrated numerous immunosuppressive genes as well as β-catenin gene, pivotal for Wnt/β-catenin signaling, were upregulated in 206 IDH1WTglioma patients using the Chinese Glioma Genome Atlas (CGGA) database. The increase in microglia with an immunosuppressive phenotype and the overexpression of β-catenin protein were further verified in IDH1WTGBM patients and IDH1WTGL261 glioma allografts. Subsequently, we found that IDH1WTGL261 cell-derived conditioned medium activated Wnt/β-catenin signaling in primary microglia and triggered their transition to an immunosuppressive phenotype. Blocking Wnt/β-catenin signaling not only attenuated microglial polarization to the immunosuppressive subtype but also reactivated immune responses in IDH1WTGBM allografts by simultaneously enhancing cytotoxic CD8+T cell infiltration and downregulating regulatory T cells. Positron emission tomography imaging demonstrated enhanced proinflammatory activities in IDH1WTGBM allografts after the blockade of Wnt signaling. Finally, gavage administration of a Wnt signaling inhibitor significantly restrained tumor proliferation and improved the survival of model mice bearing IDH1WTGBM allografts. Depletion of CD8+T cells remarkably abrogated the therapeutic efficacy induced by the Wnt signaling inhibitor. Overall, the present work indicates that the crosstalk between IDH1WTglioma cells and immunosuppressive microglia is important in maintaining the immunosuppressive glioma microenvironment. Blocking Wnt/β-catenin signaling is a promising complement for IDH1WTGBM treatment by improving the hostile immunosuppressive microenvironment.

Evaluating the node importance correctly is a crucial issue for complex networks research. If a network has multiple or ambiguous morphological features, the evaluation result of an individual index may be unilateral. Meanwhile, the results may be inconsistent if different indexes are adopted simultaneously. To solve the problem, an integrated approach is proposed based on relative entropy. In this approach, a system of multiple indexes is constructed firstly. Then each evaluation result of an individual index is handled into a discrete distribution. Finally an optimal integrated evaluation solution is obtained by linear programming. This approach has a well-formed theoretic basis and an easily-calculated procedure, which can be used in a variety of complex networks. Experimental results show that the proposed approach is more effective than other different methods proposed in some literatures. [ABSTRACT FROM AUTHOR]

Nowadays, bike-sharing is available in many cities, solving the problem of the last mile, and it is an environmental-friendly way to commute. However, there is a tidal phenomenon in the bike-sharing system, and the rents/returns of bikes at different stations are unbalanced. Thus, bikes at different stations need to be rebalanced regularly and station-level demand prediction plays an essential role in bike-sharing rebalancing. In this paper, a novel deep graph convolutional network (GCN) model with temporal attention (TAGCN) is proposed for bike check-out/in number prediction of each station. TAGCN can not only model the spatial and temporal dependency between varying stations, but also reflect the influence of different time granularity, which are hour-level, day-level and week-level time periodicity. With the help of well-designed temporal attention mechanism, our model can capture the dynamical temporal correlations and comprehensive spatial patterns in bike check-out/in flow effectively. The proposed model consistently outperforms state-of-the-art methods on four real-world bike-sharing datasets that are four seasons data of Divvy Bike System in Chicago. [ABSTRACT FROM AUTHOR]

Multi-step station-level crowd flow prediction (Ms-SLCFP) is to predict the count of people that would depart from or arrive at subway/bus/bike stations in multiple future consecutive time periods. By providing a long term view, it benefits the decision making in related applications, such as public safety, traffic management, etc. However, performing Ms-SLCFP is challenging as complicated spatiotemporal correlations are formed among stations due to the flowing crowd. Besides, the crowd flow at a single station fluctuates a lot though the regularity is obvious at the regional level. To tackle such issues, we propose a deep neural networks-based model with spatiotemporal hierarchical attention mechanisms, called ST-HAttn for short, for Ms-SLCFP. The notable contributions are that ST-HAttn performs attention mechanisms (AM) in two ways: 1) implementing AM at both station level and regional level; 2) implementing AM to explicitly model the pairwise correlations of station-region instead of station-station. The intuition is to alleviate the negative impact on Ms-SLCFP due to the fluctuation of the crowd flow at the station level. Verified on three real-world datasets, ST-HAttn outperforms the state-of-the-art methods in terms of Ms-SLCFP. [ABSTRACT FROM AUTHOR]

• Multi-step ahead prediction using deep neural networks based model. • No RNNs for sequence-to-sequence modelling. • Attention mechanism layers in both space and time domain. • A fast computed pre-predicted result enhancing subsequent steps prediction. In taxi dispatch systems, predicting citywide passenger pickup/dropoff demand is indispensable for developing effective taxi distribution and scheduling strategies to resolve the demand-service mismatch. Compared with predicting next-step only, predicting multiple steps is preferable since it can provide a long term view, thus preventing short-sighted strategies. However, multi-step citywide passenger demand prediction (MsCPDP) is challenging due to the complicated spatiotemporal correlations in the distribution of passenger demand and the lack of ground truth from pre-steps for the prediction of subsequent steps. In this paper, a deep-learning-based prediction model with spatiotemporal attention mechanism is proposed for MsCPDP. The model, called ST-Attn, follows the general encoder-decoder framework for modelling sequential data but adopts a multiple-output strategy without recurrent neural network units. The spatiotemporal attention mechanism learns to determine the focus on those parts of the city at certain periods that are more relevant to the passenger demand in the predicted region and time period. In addition, a pre-predicted result calculated by spatiotemporal kernel density estimation is fed to ST-Attn, which provides a reference for further accurate prediction. Experiments on three real-world datasets are carried out to verify ST-Attn's performance, and the results show that ST-Attn outperforms the baselines in terms of MsCPDP. [ABSTRACT FROM AUTHOR]