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While signed distance fields (SDFs) in theory offer infinite level of detail, they are typically rendered using the sphere tracing algorithm at finite resolutions, which causes the common rasterized image synthesis problem of aliasing. Most existing optimized antialiasing solutions rely on polygon mesh representations; SDF-based geometry can only be directly antialiased with the computationally expensive supersampling or with post-processing filters that may produce undesirable blurriness and ghosting. In this work, we present cone-traced supersampling (CTSS), an efficient and robust spatial antialiasing solution that naturally complements the sphere tracing algorithm, does not require casting additional rays per pixel or offline pre-filtering, and can be easily implemented in existing real-time SDF renderers. CTSS performs supersampling along the traced ray near surfaces with partial visibility – object contours – identified by evaluating cone intersections within a pixel's view frustum. We further introduce subpixel edge reconstruction (SER), a technique that extends CTSS to locate and resolve complex pixels with geometric edges in relatively flat regions, which are otherwise undetected by cone intersections. Our combined solution relies on a specialized sampling strategy to minimize the number of shading computations and correlates sample visibility to aggregate the samples. With comparable antialiasing quality at significantly lower computational cost, CTSS is a reliable practical alternative to conventional supersampling.

In this study, the particle velocity and spatial distribution of a plastic abrasive jet were modeled for the removal of surface coatings from a new generation of ship hulls by plastic abrasive jet machining. The particle velocity in the jet has been accurately tested through high-speed photography. It was found that the particle velocity of plastic abrasives with the same particle size was larger than conventional abrasives. Downstream from the nozzle exit axis, the divergence profile of the abrasive jet is approximately linear at distances up to 6.2dN; at distances higher than 6.2dN, the divergence profile line of the abrasive jet is approximately “flared”. The particle velocity of the plastic abrasive increased with increasing jet pressure, and no significant decrease of particle velocity was found in the limited measurement range. The instantaneous velocity distribution of the particles has been discussed in terms of axial and radial directions along the jet. For the radial velocity distribution of the abrasive jet, a relatively steady state is observed in the cross-section of the jet near the nozzle outlet. The results of the model calculations are in accordance with the experimental test data in terms of both tendency and margin of change.

Reinforcement learning (RL) has emerged as a key technique for designing dialogue policies. However, action space inflation in dialogue tasks has led to a heavy decision burden and incoherence problems for dialogue policies. In this paper, we propose a novel decomposed deep Q-network (D2Q) that exploits the natural structure of dialogue actions to perform decomposition on Q-function, realizing efficient and coherent dialogue policy learning. Instead of directly evaluating the Q-function, it consists of two separate estimators, one for the abstract action-value functions and the other for the specific action-value functions, both sharing a common feature layer. The abstract action-value function determines the speech act of the system action, while the specific action-value function focuses on the concrete action. This structure establishes a logical relationship between the user and the system on speech actions, avoiding the problem of incoherence. Moreover, the abstract action-value function shields unreasonable specific actions in the inflated action space, reducing the decision complexity. Our results show that the problem of incoherence is prevalent in existing approaches, which significantly impacts the efficiency and quality of dialogue policy learning. Our D2Q architecture alleviates this problem and performs significantly better than competitive baselines in both evaluated and human experiments. Further experiments validate the generality of our method. It can be easily extended to other RL-based dialogue policy approaches.

Multimodal image fusion is one of the important research directions in the field of multimodal fusion. This technique can realize image and data enhancement by using complementary multimodal images and be widely used in medicine, industry, security and fire protection, automatic driving and consumer electronics. In this work, we propose a transformer-based universal fusion (TUFusion) algorithm, and it has a multidomain fusion capability. The advantage of TUFusion algorithm is the design of hybrid transformer and convolutional neural network (CNN) encoder structure and a new composite attention fusion strategy, which has the ability of global and local information integration. Compared with the classical state-of-the-art multimodal image fusion methods, the experimental result on multidomain data sets showed that the TUFusion algorithm has certain universality in image fusion. Meanwhile, the TUFusion algorithm we proposed achieves good values on peak signal to noise ratio (PSNR), root mean square error (RMSE) and structural similarity index measure (SSIM). The code of the TUFusion algorithm in this article is available at https://github.com/windrunners/TUFusion.

Heat-stable antifungal factor (HSAF) isolated from Lysobacter enzymogenesis considered a potential biocontrol agent. However, the target of HSAF in phytopathogenic fungi remains unclear. In this study, we investigated the target of HSAF in Valsa pyrithat causes fatal pear Valsa canker. Thirty-one HSAF-binding proteins were captured and identified by surface plasmon resonance (SPR) and high-performance liquid chromatography–mass spectrometry (LC–MS/MS), and 11 deletion mutants were obtained. Among these mutants, only ΔVpVEB1showed decreased sensitivity to HSAF. Additionally, ΔVpVEB1exhibited significantly reduced virulence in V. pyri. Molecular docking and SPR results revealed that HSAF bound to threonine 569 and glycine 570 of VpVeb1, which are crucial for AAA ATPase activity. Another study showed that HSAF could decrease the ATPase activity of VpVeb1, leading to the reduced virulence of V. pyri. Taken together, this study first identified the potential target of HSAF in fungi. These findings will help us better understand the model of action of HSAF to fungi.

Photodynamic therapy (PDT) still faces great challenges with suitable photosensitizers, oxygen supply, and reactive oxygen species (ROS) accumulation, especially in the tumor microenvironment, feathering hypoxia, and high glucose metabolism. Herein, a carbon dots (CDs)-based bifunctional nanosystem (MnZ@Au), acting as photosensitizer and nanozyme with cascading glucose oxidase (GOx)- and catalase (CAT)-like reactivity, was developed for improving hypoxia and regulating glucose metabolism to enhance PDT. The MnZ@Au was constructed using Mn-doped CDs (Mn-CDs) as a core and zeolitic imidazolate framework-8 (ZIF-8) as a shell to form a hybrid (MnZ), followed by anchoring ultrasmall Au nanoparticles (AuNPs) onto the surface of MnZ through the ion exchange and in situreduction methods. MnZ@Au catalyzed glucose consumption and oxygen generation by cascading GOx- and CAT-like nanozyme reactions, which was further enhanced by its own photothermal properties. In vitroand in vivostudies also confirmed that MnZ@Au greatly improved CDs penetration, promoted ROS accumulation, and enhanced PDT efficacy, leading to efficient tumor growth inhibition in the breast tumor model. Besides, MnZ@Au enabled photoacoustic (PA) imaging to provide a mapping of Mn-CDs distribution and oxygen saturation, showing the real-time catalytic process of MnZ@Au in vivo. 18F-Fluorodeoxyglucose positron emission tomography (18F-FDG PET) imaging also validated the decreased glucose uptake in tumors treated by MnZ@Au. Therefore, the integrated design provided a promising strategy to utilize and regulate the tumor microenvironment, promote penetration, enhance PDT, and finally prevent tumor deterioration.

This brief is concerned with the robust stabilization issue of cyber-physical systems (CPSs) under periodic Denial-of-Service (DoS) attacks with quantized feedback sliding-mode control (SMC) based on event-triggered mechanism (ETM). The ETM is introduced for reducing the load of network communication, and states generated by the ETM are quantized to construct the available information of the design of sliding-mode controller. Sufficient conditions for robust stabilization of the system under periodic DoS attacks are proposed to ensure the reachability of sliding manifold. In addition, a lower bound of the quantized measurement saturation parameter is derived to guarantee the quantizer capture system states in only one step under periodic DoS attacks. After that, this brief proves that the execution time interval of the ETM has a positive lower bound and thus no Zeno behaviors occur. The effectiveness of this proposed method is finally verified by an example of a satellite control system.

Erosion equations were developed to predict the material removal of polyurethane coatings on carbon fiber reinforced plastic (CFRP) surfaces and validated through experimental data. The effects of abrasive properties, process parameters, and organic coating properties (such as fracture toughness and hardness) were considered in the equations. As the erosion angle increased, elastoplastic deformation in the oblique direction and repeated "deformation" in the normal direction were the main reasons for material removal. The ductile erosion behavior was confirmed by experimental data because the maximum erosion rate occurred at an incident angle of 30°. The coefficient and index in the equations were determined by experimental data, and the equations were verified. The developed equations could accurately predict the quantity loss of organic coatings under different particle sizes and particle velocities, and the erosion equations were in good agreement with the experimental data.

CFST is a new building material developed on the basis of steel bars and concrete, which is frequently employed in bridge construction in China. The arch rib is the main stress part CFST arch bridge has a long span, and the safety of the arch rib directly determines the working performance of the whole bridge. Therefore, to better understand the stress of the arch bridge and ensure its safety of the bridge, the research employs the finite element program Midas to establish a long span concrete filled steel tube full bridge model and analyzes axial force, stress, and displacement of arch rib in each construction stage of the arch bridge. The results show that in different construction stages, the axial force on each section increases gradually. The upper and lower edges of the steel pipe are shown as a gradually increasing negative stress. The displacement change between each section is between (2–4) mm. To sum up, the finite element full bridge analysis based on Midas can accurately obtain the stress state of long-span bridges with CFST arcs. By using this technology, data from large-span CFST arch bridges may be efficiently employed in bridge optimum building, improving the load-bearing capabilities of the arch bridge.

A novel Adaptive Iteration Learning Control (AILC) method is proposed to solve the trajectory tracking problem for a class of nonlinear uncertain systems with external disturbances. Furthermore, the output of system is required to be bounded by a time-varying function. To this end, a Barrier Lyapunov Function (BLF) term is integrated into the AILC scheme such that the impact of the uncertainties and disturbances are significantly reduced without violating the output constraints. A Barrier Composite Energy Function (BCEF) is utilized to analyze the convergence of state error and the boundedness of output. The validity of the proposed AILC scheme is verified by a numerical example. In addition, a high-fidelity simulation platform that can generate a real-life turbulent flow is utilized to demonstrate the robustness of the algorithm.

The friction coefficient and wear rate of pretreated graphite with liquid nitrogen were obtained by using a ball-on-disk tester, and the wear of GCr15–graphite seal pairs with the low-temperature time-dependent pretreatment was discussed by comparing the wear morphology. The results show that liquid nitrogen pretreatment can affect the hardness and interlayer spacing of graphite. The range of the friction coefficients of pretreated graphite changes from 0.17 to 0.22. With the increase of liquid nitrogen pretreatment time, the wear mechanism of graphite would change from dominated three-body wear to adhesion wear. The experimental results of the mechanical seal with liquid nitrogen pretreatment show that the wear rate of stator is less than 0.00165 mm3·N−1·m−1, and the graphite shows a good low-temperature compatibility.

Fidelity plays an important role in quantum information processing, which provides a basic scale for comparing two quantum states. At present, one of the most commonly used fidelities is Uhlmann-Jozsa (U-J) fidelity. However, U-J fidelity needs to calculate the square root of the matrix, which is not trivial in the case of large or infinite density matrices. Moreover, U-J fidelity is a measure of overlap, which has limitations in some cases and cannot reflect the similarity between quantum states well. Therefore, a novel quantum fidelity measure called quantum Tanimoto coefficient (QTC) fidelity is proposed in this paper. Unlike other existing fidelities, QTC fidelity not only considers the overlap between quantum states, but also takes into account the separation between quantum states for the first time, which leads to a better performance of measure. Specifically, we discuss the properties of the proposed QTC fidelity. QTC fidelity is compared with some existing fidelities through specific examples, which reflects the effectiveness and advantages of QTC fidelity. In addition, based on the QTC fidelity, three discrimination coefficients d1QTC, d2QTC, and d3QTC are defined to measure the difference between quantum states. It is proved that the discrimination coefficient d3QTC is a true metric. Finally, we apply the proposed QTC fidelity-based discrimination coefficients to measure the entanglement of quantum states to show their practicability.

Sensing biomarkers in exhaled breath offers a potentially portable, cost-effective, and noninvasive strategy for disease diagnosis screening and monitoring, while high sensitivity, wide sensing range, and target specificity are critical challenges. We demonstrate a deep learning-assisted plasmonic sensing platform that can detect and quantify gas-phase biomarkers in breath-related backgrounds of varying complexity. The sensing interface consisted of Au/SiO2nanopillars covered with a 15 nm metal–organic framework. A small camera was utilized to capture the plasmonic sensing responses as images, which were subjected to deep learning signal processing. The approach has been demonstrated at a classification accuracy of 95 to 98% for the diabetic ketosis marker acetone within a concentration range of 0.5–80 μmol/mol. The reported work provides a thorough exploration of single-sensor capabilities and sets the basis for more advanced utilization of artificial intelligence in sensing applications.

Due to the prevalent application of machine learning (ML) techniques and the intrinsic black-box nature of ML models, the need for good explanations that are sufficient and necessary towards locally interpreting a model’s prediction has been well recognized and emphasized. Existing explanation approaches, however, favor either the sufficiency or necessity. To fill this gap, in this paper, we propose an approach for generating local explanations that are both sufficient and necessary. Our approach, DDImage, automatically produces local explanations for ML-based image classifiers in a post-hoc way. The core idea behind DDImage is to discover an appropriate explanation by debugging the given input image via a series of image reductions, with respect to the sufficiency and necessity properties. Evaluation of DDImage using publicly available datasets and popular classification models reveals its effectiveness and efficiency. Compared with three state-of-the-art approaches, DDImage demonstrates a superior performance in producing small-sized explanations preserving both sufficiency and necessity, and it also shows promising stability and efficiency. We also identify the impact of segmentation granularity, reveal the performance variance for different target models, and further show that our approach is applicable across different problem domains.

Short-term passenger flow prediction under planned events is important to reduce passenger delay and ensure operational safety in metro systems. However, most studies make predictions under normal conditions. The study proposes a naïve Bayes transition model for short-term passenger flow prediction under planned events. The target prediction scenario identification is modeled as a binary classification problem using naïve Bayes. The sub-models are developed using gradient boosting decision tree (GBDT) and deep learning (DL) models for normal and planned event scenarios with predictor variables tailored to different passenger demand patterns. The sub-predictor from GBDT or DL is selected based on the inferred prediction scenario. The case study uses automatic fare collection (AFC) data of Shanghai and Hong Kong metro systems. The results show that the proposed model outperforms other representative individual and fusion models. The results also highlight the effectiveness of the predictive transition mechanism between the normal and planned events and also the event information representation.

Radioactive U(VI) in nuclear wastewater is a global environmental pollutant that poses a great threat to human health. Therefore, it is of great significance to develop a U(VI) sensor with desirable sensitivity and selectivity. Inspired by electron-donating group modification for enhancement of binding affinity toward U(VI), we report an amine group functionalization of UiO-66-NH2, using a low-cost, environmentally friendly, and low-temperature NH3plasma technique as a fluorescence switching nanoprobe for highly sensitive and selective detection of U(VI). The resulting amine-functionalized UiO-66-NH2(LTP@UiO-66-NH2) shows dramatically enhanced fluorescence emission and selective sensitivity for U(VI) on the basis of the quenching effect. The quenching efficiency increases from 58 to 80% with the same U(VI) concentration (17.63 μM) after NH3plasma functionalization. As a result, the LTP@UiO-66-NH2has the best Ksv(1.81 × 105M–1, 298 K) and among the lowest LODs (0.08 μM, 19.04 ppb) compared with those reported in the literature. Intraday and interday precision and application in real environment experiments indicate stable and accurate U(VI) detection performance. Fluorescence lifetime and temperature-dependent detection experiments reveal that the quenching mechanism belongs to the static quenching interaction. The highly selective fluorescence detection is attributed to the selective binding of U(VI) by the rich functionalized amine groups of LTP@UiO-66-NH2. This work provides an efficient fluorescence probe for highly sensitive U(VI) detection in water, and a new strategy of tailored plasma functionalization for developing a practical MOF sensor platform for enhanced fluorescence emission, sensitivity, and selectivity for detecting trace amounts of radioactive species in the environment.

Unplanned events present significant challenges for operations and management in metro systems. Short-term ridership prediction can help agencies to better design contingency strategies under unplanned events. Though many short-term prediction methods have been proposed in the literature, most studies focused on typical situations or planned events. The study develops methods for the short-term metro ridership prediction under unplanned events. It explores event impact representation mechanisms and deals with the imbalanced data training problem in building the prediction model under unplanned events. Typical machine learning and deep learning methods are developed for exploration. A large-scale automatic fare collection (AFC) dataset and event record data for a heavily used metro system are used for empirical studies. The analysis found that the same type of unplanned event shares a similar and consistent demand change pattern (with respect to the demand under typical situations) at the station level. The synthetic minority oversampling technique (SMOTE) can enrich the ridership observations under unplanned events and generate a balanced dataset for model training. Given the occurrence of unplanned events, the results show that a combination of demand change ratio and the SMOTE oversampling technique enables the prediction models to learn the impact of unplanned events and improve the prediction accuracy under unplanned events. However, the oversampling methods (i.e., SMOTE and replication) slightly deteriorate the prediction accuracy for ridership under normal conditions. The findings provide insights into mechanisms for disruption impact representation and oversampling imbalanced data in model training, and guide the development of models for short-term prediction under unplanned events.

The rapid development of space technology has made it increasingly important to use space robots for on-orbit services. Space crawling robots can perform extravehicular condition monitoring, spacecraft fault location and diagnosis, repair and maintenance by carrying different payloads and traversing the spacecraft surface, which has received wide attention from researchers. A prototype of space crawling robot has been designed in this work, which is a quadrupedal insect-like configuration with integrated bionic adhesion material on the bottom of the four feet, and can walk on the satellite surface in a gravity-free space environment. The design and implementation of the crawling robot control system is carried out based on Robot Operating System, including hardware system construction and software architecture design. The tripod gait was also designed to enable the robot to crawl more stably in space. At last, the basic capabilities of the designed space crawling robot are tested in the ground environment, and the results demonstrate the robot’s body control capability, omnidirectional walking capability, and obstacle crossing and avoidance capability.

Self-resistance genes are deployed by many microbial producers of bioactive natural products to avoid self-toxicity. Myxin, a di-N-oxide phenazine produced by Lysobacter antibioticusOH13, is toxic to many microorganisms and tumor cells. Here, we uncovered a self-defense strategy featuring the antibiotic biosynthesis monooxygenase (ABM) family protein LaPhzX for myxin degradation. The gene LaPhzXis located in the myxin biosynthetic gene cluster (LaPhz), and its deletion resulted in bacterial mutants that are more sensitive to myxin. In addition, the LaPhzXmutants showed increased myxin accumulation and reduction of its derivative, compound 4, compared to the wild-type strain. Meanwhile, in vitro biochemical assays demonstrated that LaPhzX significantly degraded myxin in the presence of nicotinamide adenine dinucleotide phosphate (NADPH), nicotinamide adenine dinucleotide (NADH), flavin mononucleotide (FMN), and flavin adenine dinucleotide (FAD). In addition, heterologous expression of LaPhzXin Xanthomonas oryzaepv. oryzaeand Escherichia coliincreased their resistance to myxin. Overall, our work illustrates a monooxygenase-mediated self-resistance mechanism for phenazine antibiotic biosynthesis.

The alkaline hydrogen evolution reaction (HER) of MoS2is hampered by its sluggish water dissociation kinetics as well as limited edge sites. Herein, Ni3S2/MoS2is fabricated as a model catalyst to highlight interfacial structural and electronic modulations of MoS2for realizing its high performance in the alkaline HER. Experiments and density functional theory results demonstrate that the coupled Ni3S2species can not only promote the adsorption and dissociation of H2O to boost the alkaline HER kinetics but also tailor the inert plane of MoS2to create abundant unsaturated edge-like active sites, while the interfacial electron interaction can regulate the band gaps and Gibbs free energy of hydrogen adsorption of MoS2to improve the electron conductivity as well as HER activity. Moreover, field emission scanning electron microscopy, transmission electron microscopy, Raman, ex situsynchrotron radiation X-ray absorption, and X-ray photoelectron spectroscopy results reveal the excellent structural stability of Ni3S2/MoS2during the HER. As expected, the target Ni3S2/MoS2achieves an ultralow overpotential of 68 mV at 10 mA cm–2, a fast alkaline HER kinetics, and remarkable durability. The proposed concept of interfacial structural and electronic reorganization could be extended to develop other functional materials.

Acute myeloid leukemia (AML) is an aggressive hematopoietic malignancy for which there is an unmet need for novel treatment strategies. Here, we characterize the growth arrest and DNA damage-inducible gene gamma (GADD45g) as a novel tumor suppressor in AML. We show that GADD45g is preferentially silenced in AML, especially in AML with FMS-like tyrosine kinase 3–internal tandem duplication (FLT3-ITD) mutations and mixed-lineage leukemia (MLL)-rearrangements, and reduced expression of GADD45g is correlated with poor prognosis in patients with AML. Upregulation of GADD45g impairs homologous recombination DNA repair, leading to DNA damage accumulation, and dramatically induces apoptosis, differentiation, and growth arrest and increases sensitivity of AML cells to chemotherapeutic drugs, without affecting normal cells. In addition, GADD45g is epigenetically silenced by histone deacetylation in AML, and its expression is further downregulated by oncogenes FLT3-ITD and MLL-AF9 in patients carrying these genetic abnormalities. Combination of the histone deacetylase 1/2 inhibitor romidepsin with the FLT3 tyrosine kinase inhibitor AC220 or the bromodomain inhibitor JQ1 exerts synergistic antileukemic effects on FLT3-ITD+ and MLL-AF9+ AML, respectively, by dually activating GADD45g. These findings uncover hitherto unreported evidence for the selective antileukemic role of GADD45g and provide novel strategies for the treatment of FLT3-ITD+ and MLL-AF9+ AML.

It is a research hotspot of electric propulsion system that a high energy density permanent magnet machine is used as its main power. In general, the power system of electric propulsion consists of batteries, inverters and high energy density permanent magnet machines and loads. Based on harmonic effect of PWM sine alternating current generated by inverter, iron loss model of high energy density permanent magnet machine is established under inverter power harmonic, and iron loss calculation flow chart of high energy density permanent magnet machine for electric propulsion system is shown. The influences of different stator outer diameter and rotor inner diameter on iron loss are analyzed by using the finite element method. Through the above analysis, a 30 kW high energy density permanent magnet machine was designed. Then the noload test and iron loss separation test were carried out, verifying that the machine has very low core loss.

Aseries of novel anthranilic diamides analogues(9a–9t) containing trifluoroethoxyl pyrazole moiety was designed and synthesized and their insecticidal bioactivities against Mythimna separata(Walker, M. separata) and Plutellaxylostella(P. xylostella) were evaluated. The structures of the title compounds were confirmed by 1H NMR, 13C NMR and HRMS. Preliminary insecticidal activities showed that some of the title compounds possessed good to excellent bioactivities towards M. separataand P. xylostella. Compounds 9c and 9t exhibited 100% mortality rate against M. separateat 0.2 mg/L. For the P. xylostella, the synthesized compounds(9c–9e, 9i and 9o) showed 70%, 80%, 75 %, 65% and 60% insecticidal activities at 1×10−6mg/L, respectively, higher than that of chlorantraniliprole(0). Based on excellent insecticidal activities, the mode of the action was tested by the calcium-imaging technique, the results of which demonstrated that the novel compounds shared the same target with chlorantraniliprole. The binding pose of the most active compound 9t in RyRs of P. xylostellawas predicted by molecular docking, which showed that compound 9t interacted with the residues Glu140(A) and His147(A) viahydrogen bond.

Mitochondria of hematopoietic stem cells (HSCs) play crucial roles in regulating cell fate and preserving HSC functionality and survival. However, the mechanism underlying HSC regulation remains poorly understood. Here, we identify transcription factor TWIST1 as a novel regulator of HSC maintenance through modulation of mitochondrial function. We demonstrate that Twist1 deletion results in significantly decreased lymphoid-biased HSC frequency, markedly reduced HSC dormancy and self-renewal capacity, and skewed myeloid differentiation in steady-state hematopoiesis. Twist1-deficient HSCs are more compromised in tolerance of irradiation- and 5-fluorouracil–induced stresses and exhibit typical phenotypes of senescence. Mechanistically, Twist1 deletion induces transactivation of voltage-gated calcium channel (VGCC) Cacna1b, which exhausts lymphoid-biased HSCs, impairs genotoxic hematopoietic recovery, and enhances mitochondrial calcium levels, metabolic activity, and reactive oxygen species production. Suppression of VGCC by a calcium channel blocker largely rescues the phenotypic and functional defects in Twist1-deleted HSCs under both steady-state and stress conditions. Collectively, our data, for the first time, characterize TWIST1 as a critical regulator of HSC function acting through the CACNA1B/Ca2+/mitochondria axis and highlight the importance of Ca2+ in HSC maintenance. These observations provide new insights into the mechanisms for the control of HSC fate.

In decision-making systems, conflict management is an important concept that represents the degree of dissimilarity between bodies of evidence, ultimately enhancing decision-making performance. Jousselme's distance, as the most commonly employed one so far, is used to measure the distance between basic belief assignments (BBAs) in Dempster-Shafer (D-S) evidence theory. However, the Jousselme's distance has limitations, which can also be demonstrated in other methods theoretically. To address this issue, a BBA refinement method and a novel multi-granularity distance are proposed in this paper. Moreover, the methods are verified to be effective in the problems that Jousselme's distance cannot satisfy. Additionally, a hypothetical physical model is employed to verify the practicability of the proposed methods with multiple granularity. Furthermore, based on the proposed multiple granularity distance, a novel decision-making algorithm is designed. The results validate that the proposed decision-making method is beneficially applicable to classification scenarios and different real-world data. [ABSTRACT FROM AUTHOR]

Fluorinated organic compounds represent a growing and important family of commercial chemicals. Introduction of fluorine into active ingredients has become an effective way to develop modern crop protection products. Given the particular properties of fluorine and high efficiency and selectivity of diamide insecticides, we designed and synthesized 27 anthranilic diamides analogues containing fluoro-sustituted phenylpyrazole. A preliminary bioassay indicated that most target compounds exhibited good biological activity against Mythimna separataand Plutella xylostella. Compound IIIfcontaining a 2,4,6-trifluoro-substituted benzene ring showed 43% insecticidal activity against M. separataat 0.1 mg L–1, while the control chlorantraniliprole was 36%. The activity of IIIeagainst P. xylostellaat 10–5mg L–1was 94%, compared with that of the control being 70%. Thus, introduction of fluorine into diamide insecticides was useful for increasing activity. Insect electrophysiology studies showed that the calcium concentration in the nerve cells of third M. separatalarvae was elevated by IIIf, which further confirmed that ryanodine receptor (RyR) was its potential target.

To cope with the global food shortage and insect pest, there is an urgent need to discover new pesticides with novel modes of actions. Ryanodine receptor (RyR) insecticides showed great promise in integrated pest management. Herein, we report the synthesis of novel anthranilic diamide derivatives incorporating pyrrole moieties targeting at insect RyRs. The structures were confirmed by 1H NMR, 13C NMR, 19F NMR, and high-resolution mass spectrometry. The preliminary bioassay results indicated that most of the title compounds showed good to excellent insecticidal activities against the oriental armyworm (Mythimna separata) and diamondback moth (Plutella xylostella). For the oriental armyworm, Ijdisplayed the same level of larvicidal activity as the positive control chlorantraniliprole, with an LC50value of 0.21 mg/L. For the diamondback moth, In, Io, Ip,and Iqexhibited higher insecticidal activities than chlorantraniliprole. In particular, Inhad 50% larvicidal activity at 0.00001 mg/L. The calcium imaging technique was applied to study the effect of Ij, In,and Ipon the intracellular calcium ion concentration ([Ca2+]i) in central neurons isolated from the oriental armyworm. The results indicated that the tested compounds, such as chlorantraniliprole, could activate the insect RyRs. Furthermore, comparative molecular field analysis and density functional theory calculations were carried out to study the structure–activity relationship.

An experimental test system for cryogenic high-speed hydrodynamic non-contact mechanical seals is developed. Based on this system, the performances of seals under different working conditions are studied in detail in this paper. With the experimental results, the main performances of the seals (such as inlet and outlet temperatures, separated speed, face temperature, friction force, friction coefficient, leakage rate) are obtained, and the relationships of the performances with the inlet fluid pressure, the closing force and the rotational speed are discussed. The results show that the difference between the outlet and inlet temperatures decreases with increasing inlet fluid pressure. As the speed increases, the friction force varies little and remains at a constant value. The friction coefficient of the seal is approximately 0.12 and basically does not change with the speed. The leakage rate is also maintained at approximately 190 g/s. With the increase in the closing force, the friction at the seal’s face does not change greatly, which indicates that the friction at the face is always in a stable state with the seal’s closing force.

Short-term metro passenger flow prediction is vital for the operation and management of metro systems. Most studies focus on the higher prediction accuracy with statistical and machine learning methods, but little attention has been paid to the prioritization and selection of feature variables, especially for different metro station types. This study aims to analyze the effect of feature variables on the prediction results, and then select appropriate predictor variables accordingly. A novel three-stage framework is proposed to prioritize feature variables for short-term metro passenger flow prediction, including station clustering, feature extraction, and variable prioritization. A hierarchical clustering algorithm (AHC) is developed for station clustering, the results of which are verified by the K-means and Davies-Bouldin (DB) statistical index. We then extract the temporal, spatial, and external features. Finally, the association between the variables and the prediction results is explored using tree-based models. The proposed framework is demonstrated and validated with data collected from Shanghai Metro Automatic Fare Collection (AFC) system. The results highlight that the importance of feature variables for developing models varies between stations, whereas only a few variables are found to explain most of the variation in the testing dataset; different feature variables lead to distinct differences in prediction accuracy, and simply adding more predictor variables does not necessarily lead to higher prediction accuracy. In addition, the station type and prediction type (i.e., tap-in and tap-out) have little influence on the selection of feature variables.

We examined the dynamics of dissolved inorganic carbon (DIC) and pH in the Pearl River Estuary (PRE) and the adjacent northern South China Sea (NSCS) shelf in summer, aiming for a better understanding of the interaction between eutrophication, hypoxia, and ocean acidification. Using a semi‐analytical diagnostic approach based on validated multiple end‐member water mass mixing models, we showed a −191 ± 54 μmol kg−1deficit in DIC concentrations in an extensive surface plume bulge, corresponding to a significant pH increase of ∼ 0.57 ± 0.19 units relative to conservative mixing. In contrast, DIC additions in the bottom hypoxic zone reached ∼ 139 ± 21 μmol kg−1, accompanied by a decrease in pH of −0.30 ± 0.04 units. In combination with stable carbon isotopic compositions, we found biological production and CO2outgassing to be responsible for DIC deficits in surface waters, while degradation of organic matter (OM) accounted for DIC additions in bottom waters. The PRE‐NSCS plume system as a whole served as a net source of atmospheric CO2from the perspective of Lagrangian observations, because strong CO2outgassing in the inner estuary overwhelmed the CO2uptake in the plume despite strong phytoplankton blooms. Using a two‐layer box model, we further estimated that at least ∼ 45 ± 13% of eutrophication‐driven OM production in the surface plume accounted for 67 ± 18% of the DIC addition and oxygen consumption in bottom waters. Eutrophication also buffered ocean acidification in surface waters while hypoxia enhanced it in bottom waters, but their effects on acid‐base buffering capacity were secondary to the amplification of coastal ocean acidification caused by freshwater inputs.

In our previous work, a series of polyethylenimine (PEI)-derived cation exchangers were synthesized using PEI-grafted resin FF-PEI-L740 (ionic capacity, 740 mmol·L−1) as the basic resin to study lysozyme adsorption and chromatographic behavior. It was found that the resin with an ionic capacity of 630 mmol·L−1(FF-PEI-CR630) possessed high adsorption performance towards lysozyme at 0–100 mmol·L−1NaCl. Therefore, in this work, FF-PEI-CR630 was selected to study the influences of pH and ionic strength (IS) on protein adsorption and chromatographic behavior towards lysozyme. The increase of lysozyme adsorption capacity in the pH range of 6 to 10 was observed. However, the uptake rate decreased in the pH range of 6 to 8 and then remained essentially unchanged from pH 8 to pH 10. Increasing IS led to decreased protein adsorption capacity and increased uptake rate in different pH ranges. Besides, FF-PEI-CR630 maintained dynamic binding capacity as high as over 150 mg·ml−1at pH 8–10 without NaCl. The research has thus provided insight into the selection of proper pH and IS conditions for protein purification by using FF-PEI-CR630.

Among Lysobacterspecies, Lysobacter antibioticushas been demonstrated to be an interesting source of antimicrobial metabolites for the biocontrol of plant diseases. Although the antibacterial activity was attributed to N-oxide phenazines, the active compounds involved in the antifungal function remained unknown. In this work, an antifungal compound was isolated and identified as p-aminobenzoic acid (pABA). Antifungal activity screening revealed that pABA shows activity against a number of plant pathogens. The genes involved in the synthetic route of this compound in OH13 were identified. Further, the production of pABA was optimized by modification of the carbon source using engineered L. antibioticusOH13 strains.

Amorphous ethylene–cyclic olefin copolymers (COCs) which can be used in cell phone lenses and prefilled syringes have attracted increasing attention due to their excellent and tunable thermal properties. In order to better explain the influence of COC microstructure (cyclic olefin types and content) on the glass transition mechanism, we used molecular dynamics (MD) simulations to track the evolution of free volume, diffusion coefficients, atomic mobility, trans conformation probabilities, and characteristic parameters of α-relaxation kinetics during the quenching process. MD results show that for the classic COC E-co-NB (ethylene–norbornene copolymer), an increase in cyclic olefin content from 25 to 50 mol % reduces atomic mobility, limiting the molecular chain movement at higher temperatures and improving Tg. Compared to NB, the more rigid rings in tricyclopentadiene (TCPD) and exo-1,4,4a,9,9a,10-hexahydro-9,10(1′,2′)-bridged phenylidene-1,4-bridged methylideneanthracene (HBM) have the following effects: (1) reducing the thermal expansion coefficient and overall chain mobility; (2) enhancing the diffusion energy barrier; (3) promoting the formation of local ordered structures; (4) accelerating α-relaxation dynamics at high temperatures and improving the dynamic fragility m. These lead to an upward shift in the temperature region where chain movement is limited and thus improve Tgand high-temperature dimensional stability. In this simulation, the correlation equation between Tg, m, and the microstructural parameters of COCs is established, which is of great significance for the development of COCs with high performance.

To suspend uncertainty, we can simply just choose to believe. A leap of faith - or the suspensionof uncertainty - is the essence of trust, yet it remains a relatively unexplored phenomenon within the entrepreneurship literature. Trust reflects a willingness to bear risks, and as such, it is an underappreciated risk-bearing mechanism. Choosing to trust not only translates into the way entrepreneurs negotiate, but as we will see, also into the negotiated outcome. In the current study, we show that trust relates positively to negotiations, but we find that positional negotiations relate negatively to accomplishments, whereas collaborative negotiations relate positively. We study entrepreneurs who act as ifthose whom they are negotiating with are trustworthy, and we explore the effects of such leaps of faith on not only collaborative, but also positional negotiations, and their interaction effects. Using abductive reasoning, we unpack three related design principles.

Multidrug resistance (MDR) is the major cause for chemotherapy failure, which constitutes a formidable challenge in the field of cancer therapy. The synergistic chemo-photothermal treatment has been reported to be a potential strategy to overcome MDR. In this work, rationally designed enzyme-degradable, hyperbranched polyphosphoester nanomedicines were developed for reversing MDR via the codelivery of doxorubicin and IR-780 (hPPEDOX&IR) as combined chemo-photothermal therapy. The amphiphilic hyperbranched polyphosphoesters with phosphate bond as the branching point were synthesized via a simple but robust one-step polycondensation reaction. The self-assembled hPPEDOX&IRexhibited good serum stability, sustained release, preferable tumor accumulation, and enhanced drug influx of doxorubicin in resistant MCF-7/ADR cells. Moreover, the degradation of hPPEDOX&IRwas accelerated in the presence of alkaline phosphatase, which was overexpressed in various cancers, resulting in the fast release of encapsulated doxorubicin. The enzyme-degradable polymer generated synergistic chemo-photothermal cytotoxicity against MCF-7/ADR cells and, thus, the efficient ablation of DOX-resistant tumor without regrowth. This delivery system may open a new avenue for codelivery of chemo- and photothermal therapeutics for MDR tumor therapy.

Lysobacter enzymogenesis less-studied, but emerging as a powerful biocontrol bacterium producing multiple antimicrobial weapons including lytic enzymes, toxins, secondary metabolites and protein secretion systems. The loss of surface-attached flagellum, production of heat-stable antifungal factor (HSAF, also named as Ningrongmycin) as a novel antifungal antibiotic, and the use of the type IV secretion system (T4SS) rather than the common type VI secretion system (T6SS) to kill competitors make this species unique. These distinct features set L. enzymogenesapart from well-studied plant beneficial biocontrol agents, such as Bacillusand Pseudomonas. This review describes what takes L. enzymogenesto be a unique biocontrol warrior by focusing to illustrate how the lack of flagellum governs morphological and functional co-adaptability, what adapted signaling transduction pathways are adopted to coordinate the biosynthesis of HSAF, and how to ecologically adapt plant rhizosphere by cell-to-cell interacting microbiome members viathe bacterial-killing T4SS.

The deep and inner beds of solid tumors lack lymphocytic infiltration and are subjected to various immune escape mechanisms. Reversing immunosuppression deep within the tumor is vital in clinical cancer therapy, however it remains a huge challenge. In this work, we have demonstrated the use of a second window near-infrared (NIR(II)) photothermal treatment to trigger more homogeneous and deeper immunogenic cancer cell death in solid tumors, thereby eliciting both innate and adaptive immune responses for tumor control and metastasis prevention. Specifically, photothermal transducers with similar components, structures, and photothermal conversion efficiencies, but different absorptions in red light, NIR(I), and NIR(II) biowindows, were constructed by controlling the self-assembly of gold nanoparticles on fluidic liposomes. In vitro, photothermal treatments induced immunogenic cell death (ICD) that were accompanied by the release of damage-associated molecular patterns (DAMPs) regardless of the wavelength of incident lasers. In vivo, NIR(II) light resulted in a more homogeneous release and distribution of DAMPs in the deeper parts of the tumors. With the induction of ICD, NIR(II) photothermal therapy simultaneously triggered both innate and adaptive immune responses and enabled efficient tumor control with 5/8 of the mice remaining tumor-free in the cancer vaccination assay. Additionally, the NIR(II) photothermal treatment in combination with checkpoint blockade therapy exerted long-term tumor control over both primary and distant tumors. Finally, using systemically administered two-dimensional polypyrrole nanosheets as a NIR(II) transducer, we achieved striking therapeutic effects against whole-body tumor metastasis viaa synergistic photothermal-immunological response.

Intratumoral glucose depletion-induced cancer starvation represents an important strategy for anticancer therapy, but it is often limited by systemic toxicity, nonspecificity, and adaptive development of parallel energy supplies. Herein, we introduce a concept of cascaded catalytic nanomedicine by combining targeted tumor starvation and deoxygenation-activated chemotherapy for an efficient cancer treatment with reduced systemic toxicity. Briefly, nanoclustered cascaded enzymes were synthesized by covalently cross-linking glucose oxidase (GOx) and catalase (CAT) viaa pH-responsive polymer. The release of the enzymes can be first triggered by the mildly acidic tumor microenvironment and then be self-accelerated by the subsequent generation of gluconic acid. Once released, GOx can rapidly deplete glucose and molecular oxygen in tumor cells while the toxic side product, i.e., H2O2, can be readily decomposed by CAT for site-specific and low-toxicity tumor starvation. Furthermore, the enzymatic cascades also created a local hypoxia with the oxygen consumption and reductase-activated prodrugs for an additional chemotherapy. The current report represents a promising combinatorial approach using cascaded catalytic nanomedicine to reach concurrent selectivity and efficiency of cancer therapeutics.

Both diffusion-limited and perfusion-limited hypoxia are associated with tumor progression, metastasis, and the resistance to therapeutic modalities. A strategy that can efficiently overcome both types of hypoxia to enhance the efficacy of cancer treatment has not been reported yet. Here, it is shown that by using biomimetic ultrathin graphdiyne oxide (GDYO) nanosheets, both types of hypoxia can be simultaneously addressed toward an ideal photodynamic therapy (PDT). The GDYO nanosheets, which are oxidized and exfoliated from graphdiyne (GDY), are able to efficiently catalyze water oxidation to release O2and generate singlet oxygen (1O2) using near-infrared irradiation. Meanwhile, GDYO nanosheets also exhibit excellent light-to-heat conversion performance with a photothermal conversion efficiency of 60.8%. Thus, after the GDYO nanosheets are coated with iRGD peptide-modified red blood membrane (i-RBM) to achieve tumor targeting, the biomimetic GDYO@i-RBM nanosheets can simultaneously enhance tumor reoxygenation and blood perfusion for PDT. This study provides new insights into utilizing novel water-splitting materials to relieve both diffusion- and perfusion-limited hypoxia for the development of a novel therapeutic platform.

We reported the preparation of well-defined poly(thionophosphoester)s as oxidation-responsive materials that undergo peroxide-triggered degradation. The polymers were synthesized via the controlled ring-opening polymerization of cyclic thionophosphoesters initiated with hydroxyl terminal small molecule and macromolecular initiators and catalyzed with 1,5,7-triazabicyclo[4.4.0]dec-5-ene in tetrahydrofuran at room temperature. The resulting poly(thionophosphoester)s were characterized in detail by NMR spectroscopy and size exclusion chromatography. Polymerization of cyclic oxophosphoester (P═O) monomers exhibited broad molecular weight distribution and severe side reactions, while narrow molecular weight distribution (ĐM∼ 1.1) was achieved without significant transesterifications using thionophosphoester (P═S) monomers. The reaction kinetics of thionophosphoester monomers were in agreement with living polymerization characteristics. Furthermore, by replacing P═O bond by P═S, the polymers changed from hydrophilic to hydrophobic. These well-controlled sulfur-containing polymers are more resistant to hydrolytic degradation but undergo peroxide-triggered degradation. Poly(thionophosphoester)s are thus promising in the field of biomedical materials.

Colletotrichum fructicola, a fungal pathogen that causes bitter rot disease in pears, has recently emerged in Eastern Asia and caused enormous economic losses and crop penalties. For this reason, new strategies for the management of bitter rot disease are greatly needed and can have a great impact on the field. In this regard, our research group recently reported that p-aminobenzoic acid (pABA), which was found in the secretions of rhizobacterium Lysobacter antibioticusOH13, showed a broad spectrum of antifungal activities. Following this project, the antifungal mode of action of pABA has been elucidated in this work indicating that pABA affects the fungal cell cycle of C. fructicolaby inhibiting septation during cell division. pABA stability and diffusion screening revealed that pABA degrades after 15 days and is able to cross the pear skin into the external parts of the mesocarp. In vivo studies demonstrated that pABA shows high curative ability against the infection of C. fructicolain pears. To show the efficacy of OH13 for the biocontrol of bitter rot disease, cultures of OH13 containing 379.4 mg/L pABA were sprayed on inoculated pears, significantly reducing the symptoms of the pathogen.

Electrochemiluminescence (ECL) has emerged as one of the most important methods for in vitro diagnosis and detection, but it is still limited in sensitivity for ultrasensitive biodetections. Fast and ultrasensitive detection of biomolecules is critical, especially for the clinical detection of cardiac troponin I (cTnI) for cardiac infarction diagnosis. In this study, an effective tactic was developed to enhance ECL efficiency of the luminol system, by combined use of Co2+-based metal organic frameworks (MOF), zeolitic imidazolate frameworks (ZIF-67), and luminol-capped Ag nanoparticles (luminol-AgNPs). The integration leads to a pronounced ∼115-fold enhancement in luminol ECL. On the basis of this fascinating sensing platform, a robust label-free ECL immunosensor was constructed for ultrasensitive detection of cTnI, the main marker of myocardial infarction, with good stability and a detection limit as low as 0.58 fg mL–1(S/N = 3).

Coastal areas, where sea breeze are prevalent, generally have good wind power resources and are favorable sites for wind farms. Corkscrew sea breezes, having greater wind power than backdoor sea breezes, dominate the local circulations in summer over the coastal area of Jiangsu province, China. Daily Weather Research and Forecasting simulations were conducted for the summer of 2012. Evaluations of 12 corkscrew sea breezes near the coast suggested that simulations captured the overall characteristics of wind changes with sea breezes, except an overestimate of wind speeds by up to 1 m/s at 10 m above ground level and a cold bias at night. Another prominent bias is the underestimated low‐level vertical wind shear at night. A representative corkscrew sea breeze in July 2012 was used to document the typical spatial structure and diurnal evolution of corkscrew sea breezes. Initiated at 1000 Local Standard Time (LST), the sea breeze reached its maximum strength at 1700 LST with an inland penetration depth of 70 km, an offshore extent up to 150 km, and a vertical extent of ~500 m. The fully developed circulation was accompanied by a coastal jet with maximum winds up to 11 m/s ~200 m above ground level. A series of sensitivity simulations indicated that simulated land‐surface temperatures and boundary‐layer mixing are the two key factors for low‐level wind simulation. Nocturnal stable boundary layer still remains a challenge for boundary layer schemes tested here. Corkscrew sea breezes dominate local circulations in summer over the coastal area of Jiangsu, ChinaWRF simulations have a cold bias and low level wind overestimate at night for 12 corkscrew sea breezesLand‐surface temperatures and boundary‐layer mixing are the two key factors for low level wind simulation

Cancer radiation therapy (RT) is limited by endogenous DNA repair of tumor cells and microenvironmental hypoxia in tumor tissues. Herein, we demonstrated an effective cancer chemo-radiotherapy strategy based on choline phosphate liposomal nanomedicines, which inhibit the intrinsic radioresistance of RT and concomitantly harness the RT-induced hypoxia to produce additional toxicity to overcome post-RT radioresistance. To achieve this strategy, a radiotherapy sensitizer, vorinostat, and a hypoxia-activated banoxantrone dihydrochloride (AQ4N) were simultaneously delivered to a tumor using liposomes composed of an inverted polarity lipid 2-((2,3-bis(oleoyloxy)propyl)dimethylammonio)ethyl ethyl phosphate (DOCPe). The DOCPe liposomes exhibited a longer blood circulation time and enhanced tumor accumulation, compared to their zwitterionic phosphocholine counterpart. The RT was sensitized by vorinostat to kill non-tolerant normoxic tumor cells efficiently. The irradiation aggravated hypoxia-activated AQ4N to further potentiate RT treatment. This chemo-radiotherapy combination showed excellent tumor treatment efficacy and is promising for future clinical translation.

In order to enhance the stability of single-phase microgrid, virtual synchronous generator (VSG) control method is investigated in this paper. Its electromagnetic model and electromechanical model are established to illustrate the performance of VSG. Considering the 2nd fluctuation of fundamental-frequency in the output power, an instantaneous power calculation strategy is proposed based on the intrinsic frequency of single-phase VSG. Besides, a virtual power calculation method is presented to achieve islanded/grid-connected seamless transition. Stability analysis and comparison simulation results demonstrate the correctness of the presented power calculation method. At last, the effectiveness of the proposed approach is verified by comparison experiments of islanded/grid-connected operations in a 500 VA single-phase inverter.

Coastal lagoons with small catchment basins are highly sensitive to natural processes and anthropogenic activities. To figure out the environmental changes of a coastal lagoon and its contribution to carbon burial, two sediment cores were collected in Xincun Lagoon, southeastern Hainan Island and 210Pb activities, grain size parameters, total organic carbon (TOC), total nitrogen (TN), total inorganic carbon (TIC) and stable carbon isotopes (δ13C) were measured. The results show that in 1770–1815, the decreasing water exchange capacity with outer open water, probably caused by the shifting and narrowing of the tidal inlet, not only diminished the currents and fined the sediments in the lagoon, but also reduced the organic matter of marine sources. From 1815 to 1950, the sedimentary environment of Xincun Lagoon was frequently influenced by storm events. These extreme events resulted in the high fluctuation of sediment grain size and sorting, as well as the great variation in contributions of terrestrial (higher plants, soils) and marine sources (phytoplankton, algae, seagrass). The extremely high content of TIC, compared to TOC before 1950 could be attributed to the large-scale coverage of coral reefs. However, with the boost of seawater aquaculture activities after 1970, the health growth of coral species was severely threatened, and corresponding production and inorganic carbon burial flux reduced. The apparent enhanced inorganic carbon burial rate after 1990 might result from the concomitant carbonate debris produced by seawater aquaculture. This result is important for local government long-term coastal management and environmental planning.

Markov logic networks (MLNs) have emerged as a powerful representation that incorporates first-order logic and probabilistic graphical models. They have shown very good results in many problem domains. However, current implementations of MLNs do not scale well due to the large search space and the intractable clause groundings, which is preventing their widespread adoption. In this paper, we propose a general framework named Ground Network Sampling (GNS) for scaling up MLN learning and inference. GNS offers a new instantiation perspective by encoding ground substitutions as simple paths in the Herbrand universe, which uses the interactions existing among the objects to constrain the search space. To further make this search tractable for large scale problems, GNS integrates random walks and subgraph pattern mining, gradually building up a representative subset of simple paths. When inference is concerned, a template network is introduced to quickly locate promising paths that can ground given logical statements. The resulting sampled paths are then transformed into ground clauses, which can be used for clause creation and probabilistic inference. The experiments on several real-world datasets demonstrate that our approach offers better scalability while maintaining comparable or better predictive performance compared to state-of-the-art MLN techniques. [ABSTRACT FROM AUTHOR]