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The interdisciplinary circular economy literature recommends longer-lasting products, to reduce pollution from repeated production and disposal. For any type of appliance, we assume that consumers choose among variants with different durability. Firms are competitive. Standard Pigouvian analysis shows that optimal taxes depend on pollution and not on product life. Here, we find conditions where consumers choose lives that are too short—a “durability gap.” First, we show that suboptimal existing output taxes imply suboptimal durability. An increase in uniform tax on all variants encourages purchase of a more durable variant and raises welfare. Second, welfare also is raised by a subsidy for choosing a more durable variant or by a marginally binding durability mandate. Third, we find that a social discount rate less than the private rate is the strongest case for policy to favor durability. Fourth, the consumer misperceptions we study have ambiguous implications for durability policy.

Objective: Lobula giant motion detectors (LGMDs) in locusts effectively predict collisions and trigger avoidance, with potential applications in autonomous driving and UAVs. Research on LGMD characteristics splits into two views: one focusing on the presynaptic visual pathway, the other on the postsynaptic LGMD neurons. Both perspectives have support, leading to two computational models, but they lack a biophysical description of the individual LGMD neuron behavior. This paper aims to mimic and explain LGMD behavior based on fractional spiking neurons (FSNs) and construct a biomimetic visual model for the LGMD compatible with these characteristics. Methods: We implement the visual model using an event camera to simulate photoreceptors and follow the ON/OFF visual pathway, incorporating lateral inhibition to mimic the LGMD system from the bottom up. Second, most computational models of motion perception use only the dendrites within the LGMD neurons as the ideal pathway for linear summation, ignoring dendritic effects inducing neuronal properties. Thus, we introduce FSN circuits by altering dendritic morphological parameters to simulate multi-scale spike frequency adaptation (SFA) observed in LGMDs. Additionally, we add one more circuit of dendritic trees into the FSNs to be compatible with the postsynaptic feed-forward inhibition (FFI) in LGMD neurons, providing a novel explanatory and predictive model. Results: We test that the event-driven biomimetic visual model can achieve collision detection and looming selection in different complex scenes, especially fast-moving objects.

As the grid incorporates more voltage-source converters (VSCs), the stability issues arising from VSC-grid interactions escalate. While passivity theory offers a promising solution, existing passivity-based controller designs primarily rely on heuristic methods, which do not advance stability beyond achieving passivity. To fully exploit the available degrees of freedom, this article proposes employing an optimal state-feedback control that refines control parameters using an optimization algorithm. The optimization objective aims at maximizing the external stability by minimizing the product of two-norms of the phase curve and magnitude curve of the VSC's output admittance. Compared with the conventional passivity-based design, the proposed control method improves the external stability with nondissipative grid impedance and can mostly achieve dissipativity. The optimization algorithm and the process for generating starting points for the optimization are detailed. Experimental validations confirm the effectiveness of this optimal state-feedback control in enhancing VSC-grid interaction stability.

Degradation of polyolefin (PE) plastic by a traditional chemical method requires a high pressure and a high temperature but generates complex products. Here, sulfur vacancy-rich ZnIn2S4and hydroxy-rich ZnIn2S4were rationally fabricated to realize photocatalytic degradation of PE in an aqueous solution under mild conditions. The results reveal that the optimized photocatalyst could degrade PE into CO2and CO, and PE had a weight loss of 84.5% after reaction for 60 h. Systematic experiments confirm that the synergetic effect of hydroxyl groups and S vacancies contributes to improve the photocatalytic degradation properties of plastic wastes. In-depth investigation illustrates that the active radicals attack (h+and •OH) weak spots (C–H and C–C bonds) of the PE chain to form CO2, which is further selectively photoreduced to CO. Multimodule synergistic tandem catalysis can further improve the utilization value of plastic wastes; for example, product CO2/CO in the plastic degradation process can be converted in situ into HCOOH by coupling with electrocatalytic technology.

Light detection and ranging (LiDAR) is a critical sensor for autonomous driving, offering precise 3-D environmental insights. However, large vehicles, such as autonomous buses, face unique challenges with single LiDAR systems, such as limited field of view (FOV) and sparse point cloud data. This article introduces a multi-LiDAR-inertial-wheel odometry and mapping system to overcome these challenges. The proposed system employs a multisensor fusion method that integrates data from multiple LiDARs, an inertial measurement unit (IMU), and wheel encoders. We utilize B-spline curves for IMU data interpolation and the error state Kalman filter (ESKF) for state estimation, significantly enhancing vehicle localization accuracy and robustness. To validate our approach, we presented a comprehensive multisensor simultaneous localization and mapping (SLAM) dataset using real-world data from autonomous buses in urban environments. Experimental results show that our method achieves state-of-the-art localization accuracy and reliability in complex environments. Across all sequences, the root mean square (rms) of the absolute translational error (ATE) for our method is 1.92 m, approximately 80% lower than the second-best method, which had an error of 10.21 m. The generated high-precision point cloud maps demonstrate the system’s potential for autonomous driving applications, improving perception and navigation.

Diabetic wounds has a gradually increasing incidence and morbidity. Excessive inflammation due to immune imbalance leads to delayed wound healing. Here, we reveal the interconnection between activation of the NLRP3 inflammatory pathway in endotheliocyte and polarization of macrophages via the cGAS-STING pathway in the oxidative microenvironment. To enhance the immune-regulation based on repairing mitochondrial oxidative damage, a zeolitic imidazolate framework-8 coated with cerium dioxide that carries Rhoassociated protein kinase inhibition Y-27632 (CeO2–Y@ZIF-8) is developed. It is encapsulated in a photocross-linkable hydrogel (GelMA) with cationic quaternary ammonium salt groups modified to endow the antibacterial properties (CeO2–Y@ZIF-8@Gel). CeO2with superoxide dismutase and catalase activities can remove excess reactive oxygen species to limit mitochondrial damage and Y-27632 can repair damaged mitochondrial DNA, thus improving the proliferation of endotheliocyte. After endotheliocyte uptakes CeO2–Y@ZIF-8 NPs to degrade peroxides into water and oxygen in cells and mitochondria, NLRP3 inflammatory pathway is inhibited and the leakage of oxidatively damaged mitochondrial DNA (Ox-mtDNA, a damage-associated molecular pattern) through mPTP decreases. Futhermore, as the cGAS-STING pathway activated by Ox-mtDNA down-regulated, the M2 phenotype polarization and anti-inflammatory factors increase. Collectively, CeO2–Y@ZIF-8@Gel, through remodulating the crosstalk between macrophage reprogramming and angiogenesis to alleviate inflammation in the microenvironment and accelerates wound healing.

Background: Currently, there is no clear consensus on whether medical treatment or endoscopic treatment should be used for peptic ulcer bleeding patients with adherent clot. The aim of this study is to investigate the hemostatic effects of medical treatment, single endoscopic treatment, and combination endoscopic treatment for peptic ulcer bleeding (PUB) patients with adherent clot. Methods: We retrospectively analyzed PUB patients with adherent clot who underwent endoscopic examination or treatment in our center from March 2014 to January 2023 and received intravenous administration of proton pump inhibitors. Patients were divided into medical treatment (MT) group, single endoscopic treatment (ST) group, and combined endoscopic treatment (CT) group. Subsequently, inverse probability of treatment weighting (IPTW) was performed to calculate the rebleeding rate. Results: A total of 605 eligible patients were included in this study. After IPTW, the rebleeding rate in the MT group on days 3, 7, 14, and 30 were 13.3 (7.3), 14.2 (7.8), 14.5 (7.9), and 14.5 (7.9), respectively; the rebleeding rates in the ST group were 17.4 (5.1), 20.8 (6.1), 20.8 (6.1), and 20.8 (6.1), respectively; the rebleeding rates in the CT group were 0.4 (0.9), 1.7 (3.3), 2.3 (4.5), and 2.3 (4.5), respectively. Although the rebleeding rate in the medical treatment group was higher, there was no significant difference among the three groups on days 3, 7, 14, and 30 (P = 0.132, 0.442, 0.552, and 0.552). Conclusions: Medical therapy has similar hemostatic efficacy with endoscopic treatment for PUB patients with adherent clot (FIIb ulcers). However, for patients with more risk factors and access to well-equipped endoscopy centers, endoscopic treatment may be considered. The choice of treatment approach should be based on the individual conditions of the patient, as well as other factors such as medical resources available.

Surface and interfacial engineering of nanomaterials is essential for improving dispersion stability in liquids. In this study, we report that oleic acid (OA)- and stearic acid (SA)-functionalized layered double hydroxide (LDH) nanosheets as lubricant additives can achieve high dispersion and reduce friction and wear. LDH is a typical layered structure, and OA and SA are long-chain organic molecules that are not only compatible with base oils but also act as friction-reducing agents. The OA and SA molecules were branched onto ZnMgAl LDH nanosheets using dehydration condensation between the exposed OH groups on the surface of LDH and the COOH groups on the OA and SA molecules. Compared with that of the pristine ZnMgAl LDH, the dispersion of OA-ZnMgAl LDH and SA-ZnMgAl LDH was significantly improved. The surface-modified LDH exhibited superior tribological properties and great stability due to the synergistic lubrication effect between OA, SA, and LDH. Even at an ultralow concentration (0.15 wt %), the coefficient of friction and wear volume were reduced by ∼65 and ∼99%, respectively, compared to those of the base oil. Due to the green and simple synthesis method and excellent tribological properties, surface-functionalized LDH has enormous possibilities for future industrial applications.

•Id3 limits PD-1 expression and exuberant effector differentiation of Th1 cells, protecting them from PD-1–mediated suppression during GVHD.•Id3 reduces chromatin accessibility of transcription factors that drive T-cell PD-1 transcription, differentiation, and dysfunction.

Compared to signalized intersections, unsignalized intersections possess greater potential and risks in solving traffic congestion. While using the Multi-Risk Management strategy based on Cooperative Optimization and the Predicted Inter-Distance Profile (MRMCO-PIDP), a Dynamic MRMCO (D-MRMCO) coordination optimization architecture for Connected Autonomous Vehicles (CAVs) is studied in this paper. The primary objective of this work is to propose an MRMCO-PIDP approach that is suitable for dynamic environments and to address the issue of local minima solutions associated with the penalty function. To overcome the challenges associated with local minima, we incorporated the Metropolis Criterion to cross the possible local optimal solution. Additionally, a new intersection area model has been established, allowing CAVs to make different risk-level decision-making strategies based on their specific positions within the intersection.

In this letter, a new reconstructed variational Bayesian (RVB) Kalman filter is proposed for handling heavy-tailed and skewed noises. The Student's t distribution is used to model predicted state, and the skewed Gaussian-exponential mixture distribution is used to model measurement noises. In order to more accurately deal with process noises, we model the predicted covariance based on the inverse Wishart distribution. Subsequently, a new RVB framework is proposed to separate the iterations of process and measurement noise related parameters, which achieves decoupling of hidden variables. Under the new RVB framework, the RVB-ST-SGEM-KF algorithm is derived. The superiority of the proposed RVB framework and algorithm are validated through a maneuvering target tracking scenario.

Motivated by the diverse services provided by various on-demand service platforms to satisfy customers’ different needs, we investigate the pricing of an on-demand crowdsourced delivery platform (CDP) with differentiated service levels. Using a multinomial logit model, we propose a two-sided market framework for investigating the pricing decisions of a CDP with two differentiated service levels under a general variable commission scheme and a fixed-rate commission scheme. The results show that 1) the two-sided pricing mechanism (price and wage decisions) allows the supply to match the demand for different service levels, except when the CDP adopts a fixed-rate commission scheme; and 2) depending on the magnitude of the fixed commission rate, adopting a fixed-rate commission scheme has different impacts on the equilibrium outcomes. We also extend our model by including the commission scheme and multiple service levels. The results show that 1) the CDP can achieve a higher optimal profit under the courier classification scheme than under a benchmark variable commission scheme, and 2) offering senders and couriers diversified service levels benefits the CDP. This article provides CDP practitioners with a quantitative tool for pricing for service-level menus.

Machine Learning is widely studied in battery state of health (SOH) estimation due to its advantage in establishing the non-linear mapping between measurements and SOH. However, the requirement of a big dataset and the lack of robustness limit the practical application, especially in small sample learning. To tackle these challenges, an optimal ensemble framework called BaggELM (bagging extreme learning machine) is proposed for battery SOH estimation. Specifically, the required dataset is reduced by optimizing the input voltage and the hyperparameters of the BaggELM algorithm. Moreover, a statistical post-processing method is used to aggregate multiple ELMs, and the final estimate is determined by the maximum probability density value. As a result, the effects of random parameterization of ELM and the training data size on SOH estimation are suppressed, thus improving the robustness and accuracy of the conventional BaggELM. Compared to other classic machine learning methods, the proposed method reduces the required data size, maintains strong robustness and high estimation accuracy, making it a promising solution for small-sample-based SOH estimation. Finally, the effectiveness of the proposed estimation framework is verified using the accelerated aging dataset from Lithium Iron Phosphate (LFP) and Nickel Manganese Cobalt (NMC) batteries.

Herein, we prepared Pd nanoparticle (NP) catalysts using XC-72 carbon supports through a tailored deposition–precipitation method. Our primary objective was to unravel the size effects of Pd NPs on hydrogenation of tetraacetyldibenzylhexaazaisowurtzitane (TADBIW), a pivotal intermediate for synthesis of high energy density materials hexanitrohexaazaisowurtzitane (CL-20). The controlled modulation of Pd NP size ranged from a mere 1.8 nm to 7.4 nm. Remarkably, our investigations into TADBIW hydrogenation unveiled a fascinating trend: the ultrasmall-sized Pd NPs with a diameter of 1.8 nm exhibited excellent yield and reaction rates. In stark contrast, their larger-sized counterparts demonstrated diminished catalytic activities. To disclose the size-dependent nature, various characterization techniques were employed, including XRD, TEM, XPS, CO and H2pulse chemisorption. The comprehensive analysis revealed that the ultrasmall-sized Pd possessed more positively charged sites and exhibited higher dispersion. This unique configuration facilitated an accelerated adsorption of hydrogen and the electron-rich substrate TADBIW. Notably, this phenomenon led to a reduction in the activation energy through a thermodynamic effect, thereby enhancing overall catalytic performance. Our results strongly suggested that the ultrasmall-sized Pd NPs can exert a dominated influence on the physical and chemical states of the active sites, playing a key role in triggering the adsorption and activation of the substrate TADBIW. These findings not only deepen our understanding of the intricate connections between Pd NP size and catalytic activity but also open new avenues for advancing the design and optimization of catalysts in the hydrodebenzylation methodologies and synthesis of related compounds.

Chrysanthemum flowers are rich in phenolic substances. The chrysanthemum flower tea (CT) obtained by simulating the process of hot water brewing as the research object and 80% methanol aqueous extract (ME) as the controls to explore the composition of phenolic compounds and antioxidant capacities of five varieties of chrysanthemum flowers including Xueju, Taiju, Hangbaiju, Gongjuand Jinzhanju. Nine phenolic compounds including p-hydroxybenzoic acid, catechin, vanillic acid, caffeic acid, syringic acid, epicatechin, p-coumaric acid, ferulic acid and sinapic acid were initially identified and quantified by using high-performance liquid chromatography with diode-array detection (HPLC-DAD). The content of catechin in Xueju, Taiju, Hangbaiju, Gongjuand Jinzhanjuwas 45.6, 50.9, 51.8, 55.0 and 53.2 µg/g, respectively, which is the highest among the nine monomeric phenolic compounds. The Xuejuvariant had the largest total phenolic content of 123.7 mg gallic acid equivalent (GAE)/g and total flavonoid content of 92.5 catechin equivalent (CE)/g when compared to other cultivars, which was also consistent with the results from the HPLC-DAD measurements. After 15 min of simulated brewing, the DPPH radical eliminating ability of different varieties of CT was higher than that of the ME which corresponded with the FRAP results. The process of tea making improves the bioactive component and antioxidant activity of the chrysanthemum flower.

The integration of large-scale heterogeneous electric vehicles (EVs) into the distribution network increases the system management complexity significantly. Due to the flexible charging/discharging operation and shiftable energy consumption during the parking time, EVs possess a great dispatching potential for the distribution network. This article develops an analytical polytope approximation (APA) aggregation model to efficiently depict the dispatchable regions of large-scale EVs with uncertainties and proposes a bilevel cooperative optimization approach for EV aggregators to participate in the distribution network day-ahead optimal scheduling. Uncertainties of EVs are modeled by chance constraints with different confidence levels to accommodate various regulatory requirements. The proposed approach can obtain large-scale EVs dispatchable capabilities with minimum flexibility loss and realize the regulation command disaggregation without violations. Numerical case studies are conducted on IEEE 33-bus and 141-bus distribution networks based on real data sets, which show that the proposed approach outperforms other state-of-art methods in terms of low operation flexibility conservatism, high system economics, and computational efficiency.

In this article, a finite-time event-triggered disturbance observer (FTETDO) is first designed to handle external disturbance of multiple quadrotor UAVs (QUAVs). The designed FTETDO can effectively reduce update number of observer and the estimation error achieves practical finite-time stability without Zeno behavior. Then a distributed finite-time tracking control strategy is proposed to realize the practical finite-time stability of multiple QUAVs formation. In order to overcome the computational explosion problem, the finite-time filter is employed and the error compensation mechanism is developed to eliminate the influence of filter error on tracking error. Based on the Lyapunov theory, it is proved that the designed control strategy can guarantee practical finite-time stability of the closed-loop system. Finally, simulation is carried out to testify the efficiency of the developed control scheme.

The cloud vendors provide sharing resources for millions of tenants across the world to achieve economies of scale. At the same time, the cloud network keeps the performance isolation between different tenants as if they use their private dedicated resources. However, heavy hitters caused by a single tenant at cloud gateways will break such isolation, undermining the predictable performance expected by other cloud tenants. To prevent it, heavy hitter detection becomes a key concern at the performance-critical cloud gateways but faces the dilemma between fine granularity and low overhead. In this work, we present CloudSentry, a scalable two-stage heavy hitter detection system dedicated to multi-tenant cloud gateways against such a dilemma. CloudSentry uses CPU utilization as an indicator of heavy hitters and conducts a lightweight coarse-grained detection running 24/7 to detect such CPU spikes. Then it invokes a fine-grained detection to precisely dump and analyze the potential heavy-hitter packets at the CPU spikes. After that, a more comprehensive analysis is conducted to associate heavy hitters with the cloud service scenarios and invoke a corresponding backpressure procedure. CloudSentry significantly reduces memory, computation and storage overhead compared with existing approaches. In a gateway cluster under an average traffic throughput of 251 Gbps, CloudSentry consumes only a fraction of 2%–5% CPU utilization with 8 KB run-time memory, producing only 10 MB heavy hitter logs during one month. Additionally, as it has been deployed in Alibaba Cloud for over two years, we share case studies and a lot of deployment experiences in this article.

Covalent organic frameworks (COFs) are an emerging class of crystalline porous materials with promising applications. However, the lack of an efficient, systematic, and scalable synthesis protocol to produce high-quality COFs with desirable structures still hinders their further promotion and application. Here, based on the concept of dynamic covalent chemistry, we propose to achieve the rapid preparation of imine-linked COFs by employing imine exchange reactions, which allows us to adopt a facile solution stirring refluxing synthetic method due to the change of the reaction type. Such a synthesis protocol not only avoids harsh reaction conditions but also enables us to obtain crystalline COF-300 in 20 min with an ultrahigh space-time yield of >850 kg m–3day–1. The resulting product exhibited superior porosity and carbon capture performance compared to that of the previously reported synthetic methods. Moreover, this synthetic strategy can also be extended to the preparation of various imine-linked COFs.

Photosensitizers and photothermal agents have attracted increasing attention for in vitro diagnosis, but the combination remains challenging. Herein, a light-driven photocatalytic–photothermal synergetic system integrated microfluidic distance-based analytical device (PCPT-μDAD) for visual, portable, sensitive, and quantitative detection of targets was developed. Target DNA was recognized and initiated the hybridization chain reaction to form a double-stranded DNA/SYBR Green I (dsDNA/SG-I) complex. By applying the photosensitization of the dsDNA/SG-I complex and the photothermal effect of oxidized 3,3′,5,5′-tetramethylbenzidine, the target concentration can effectively translate into a visual distance signal readout. Importantly, the light-driven PCPT-μDAD greatly improves the controllability of catalytic reactions and signal amplification efficiency. The light-driven PCPT-μDAD shows a low limit of detection (fM level), good stability, and high reproducibility for nucleic acid detection.

In terms of digital control delay, dissipation of the current controller is necessary to enhance the interactive stability between grid-following converters and the grid. The key principle is to make the real part of the converter output admittance non-negative below Nyquist frequency. Besides the fundamental current control, a phase-lead compensation should be introduced for the dissipative design of harmonic resonant controllers. However, derivation of the compensation angle requires calculating the partial derivative of real part of converter output admittance, which is nontrivial, especially in the presence of grid voltage feedforward. This letter provides a simple calculation method for the compensation angle to achieve dissipativity, and its effectiveness is verified through experiments.

Digital proportional-resonant (PR) controllers have proven effective when used with an active power filter (APF) to compensate for nonlinear load harmonics. Their performances may, however, degrade significantly when implemented with a low-end microcontroller due to coefficient quantization errors. The extent of the degradation depends on the chosen operator, form of the second-order resonant module, and the structure for implementing the PR controller. These three factors are now comprehensively evaluated to find suitable schemes for implementing an example sixth-order PR controller for an APF. The target is to retain accurate tracking even when realized with a low bit count. Furthermore, to quantify the analysis, the sensitivity of poles and zeros (SPZ) and the sensitivity of gain (SG) have been defined to index quantization influences on different implementations. The computed SPZ and SG trends have then been borrowed for explaining the simulation and experimental results presented in this article, and identifying three suitable realization forms with lower coefficient sensitivities.

Four general practioners share perspectives on their career pathways, which span different models in both partnered and salaried GP work, and reflect on the challenges and benefits of each model.

Finding network biomarkers from gene co-expression networks (GCNs) has attracted a lot of research interest. A network biomarker is a topological module, i.e., a group of densely connected nodes in a GCN, in which the gene expression values correlate with sample labels. Compared with biomarkers based on single genes, network biomarkers are not only more robust in separating samples from different categories, but are also able to better interpret the molecular mechanism of the disease. The previous network biomarker detection methods either employ distance based clustering methods or search for cliques in a GCN to detect topological modules. The first strategy assumes that the topological modules should be spherical in shape, and the second strategy requires all nodes to be fully connected. However, the relations between genes are complex, as a result, genes in the same biological process may not be directly, strongly connected. Therefore, the shapes of those modules could be oval or long strips. Hence, the shapes of gene functional modules and gene disease modules may not meet the aforementioned constraints in the previous methods. Thus, previous methods may break up the genes belonging to the same biological process into different topological modules due to those constraints. To address this issue, we propose a novel network biomarker detection method by using Gaussian mixture model clustering which allows more flexibility in the shapes of the topological modules. We have evaluated the performance of our method on a set of eight TCGA cancer datasets. The results show that our method can detect network modules that possess better discriminate power, and provide biological insights.

In the current energy transactions of multi-park integrated energy system (M-PIES), aiming at the problems that the interaction between the supply side and the demand side is not fully considered, the sharing potential of multiple energy sources is not fully tapped, the benefit distribution mechanism considering the contribution of the load aggregator (LA) is lacking, and with the all-round development of the carbon trading market (CTM), the existing ladder-type carbon trading (LCT) mechanism has insufficient capacity to limit CO2discharges of M-PIES, etc., this paper puts forward a low-carbon optimal operation strategy of M-PIES considering the multi-energy sharing trading mechanism (MSTM) and asymmetric Nash bargaining (ANB). Firstly, the interaction between supply and demand (IS&D) is fully considered, and the benefit maximization model of PIES operator-LA multi-agent alliance considering MSTM and improved ladder-type carbon trading mechanism (ILCTM) is established by using Nash negotiation theory (NNT). Then, according to the different bargaining capabilities of each agent, a profit distribution model based on ANB is proposed, and it is solved by alternating direction method of multipliers (ADMM). Finally, through the comparison of different cases, it is proved that the proposed method can further reduce CO2discharges of M-PIES, improve the benefits of each agent and alliance, and realize the fair and reasonable distribution of energy sharing (ES) benefits.

Acute kidney injury (AKI) is closely associated with the overproduction of reactive oxygen species (ROS), which can cause multiple organ dysfunctions without timely treatment. However, only supportive treatments are currently available for AKI in clinics. Here, we developed nanomaterials of hyperbranched polyphosphoester (PPE) containing abundant thioether (S-PPE NP) and thioketal bonds (TK-PPE NP). Our data demonstrates that S-PPE NP exhibits an excellent capability of absorbing and scavenging multiple types of ROS, including H2O2, •OH, and •O2–, via thioether oxidation to sulfone or sulfoxide; it was also determined that S-PPE NP efficiently eliminates intracellular ROS, thus preventing cellular damage. Moreover, S-PPE NP was able to efficiently accumulate in the injured kidneys of AKI-bearing mice. As a result, the administration of S-PPE NP provided a superior therapeutic effect in AKI-bearing mice by downregulating ROS- and inflammation-related signaling pathways, thus reducing cell apoptosis. This thioether-containing polymer represents a promising broad-spectrum ROS scavenger that can be used for effective AKI treatments.

This study aimed to develop and validate a simple-to-use nomogram for predicting the delayed radiographic recovery in children with mycoplasma pneumoniae pneumonia (MPP) complicated with atelectasis. A retrospective study of 306 children with MPP complicated with atelectasis was performed at the Children’s Hospital of Chongqing Medical University from February 2017 to March 2020.The patients were divided into recovery group and delayed recovery group based on chest CT scan 1 month after discharge. A least absolute shrinkage and selection operator (LASSO) regression model was used to identify the optimal predictors, and the predictive nomogram was plotted by multivariable logistic regression. The nomogram was assessed by calibration, discrimination, and clinical utility. LASSO regression analysis identified that lactate dehydrogenase (LDH), duration of illness prior to bronchoalveolar lavage (BAL), systemic glucocorticoid use and extrapulmonary complications were the optimal predictors for delayed radiographic recovery. The nomogram was plotted by the four predictors. The area under the Receiver Operating Characteristic (ROC) curve of the nomogram was 0.840 (95% CI = 784 ∼ 0.896) in the training set and 0.833 (95% CI = 0.8737 ∼ 0.930) in the testing set. The calibration curve demonstrated that the nomogram was well-fitted, and decision curve analysis (DCA) showed that the nomogram was clinically beneficial. This study developed and validated a simple-to-use nomogram for predicting delayed radiographic recovery in children with MPP complicated with atelectasis. This might be generally applied in clinical practice.

Limestone-calcined clay-cement (LC3), as one of the most promising sustainable cements, has been under development over the past decade. However, many uncertainties remain regarding its rheological behaviors, such as the metakaolin content of calcined clay. This study aims to investigate the effect of increasing the content of fine-grained metakaolin in calcined clay on the rheology of LC3 pastes. Rheological behaviors and early-age hydration of studied mixtures were characterized using flow curve, constant shear rate, small amplitude oscillatory shear and isothermal calorimetry tests. Results show that increasing the content of fine-grained metakaolin decreased flowability but promoted structural build-up and early-age hydration. These phenomena can be attributed to the decrease of mean interparticle distance caused by the increased amount of fine-grained metakaolin, which may enhance colloidal interactions, C-S-H nucleation and direct contact between particles. Overall, modifying the fine-grained metakaolin content is a feasible approach to control the rheology of LC3 pastes.

Background: Whether combination therapy has higher hemostatic efficacy than epinephrine injection monotherapy in different Forrest classifications is not clear. This study aimed to compare hemostatic efficacy between epinephrine injection monotherapy (MT) and combination therapy (CT) based on different Forrest classifications. Methods: We retrospectively analyzed peptic ulcer bleeding (PUB) patients who underwent endoscopic epinephrine injections or epinephrine injections combined with a second therapy between March 2014 and June 2022 in our center, and the patients were divided into MT group or CT group. Subsequently, a propensity score matching analysis (PSM) was performed and rebleeding rates were calculated according to Forrest classifications via a stratified analysis. Results: Overall, 605 patients who met the inclusion criteria were included, and after PSM, 173 patients in each of the CT and MT groups were included. For PUB patients with nonbleeding visible vessels (FIIa), the rebleeding rates by Days 3, 7, 14, and 30 after PSM were 8.8%, 17.5%, 19.3%, and 19.3% in the MT group, respectively, and rates were 0%, 4.1%, 5.5%, and 5.5% in the CT group, respectively, with significant differences observed between the two groups by Days 3, 7, 14, and 30 (P = 0.015, P = 0.011, P = 0.014, and P = 0.014, respectively). However, for PUB patients with oozing bleeding (FIb), the rebleeding rates by Days 3, 7, 14, and 30 after PSM were 14.9%, 16.2%, 17.6%, and 17.6% in the MT group, respectively, and rates were 13.2%, 14.7%, 14.7%, and 16.2% in the CT group, respectively, with no significant differences observed between the two groups by Days 3, 7, 14, and 30 (P = 0.78, P = 0.804, P = 0.644 and P = 0.825). Conclusion: Combined therapy has higher hemostatic efficacy than epinephrine injection monotherapy for PUB patients with visible blood vessel (FIIa) ulcers. However, epinephrine injection monotherapy is equally as effective as combined therapy for PUB patients with oozing blood (FIb) ulcers.

Surfactants play a vital role in the removal of lignin and subsequent enzymatic saccharification of lignocellulosic biomass. In this work, a surfactant-mediated alkaline pretreatment (SMAP) with short residence time and low NaOH loading has been successfully developed for enhancing enzymatic hydrolysis of a potential energy plant, Miscanthus sinensis, and evaluating its potential as a feedstock for biofuel production. As compared to individual alkaline pretreatment (AP), the SMAP process resulted in significantly more hemicellulose removal, more efficient delignification, higher cellulose content (55% vs. 51%), and stronger morphological disruption of the pretreated stalks, making them more accessible to cellulases and/or microorganisms. As a result, SMAP produced a significantly higher sugar yield of 402.5 mg/g than the control and AP group (287.8 mg/g) (p< 0.05). Among the tested surfactants, Tween 40 was identified as a potential candidate for SMAP of biomass wastes. SMAP with mild conditions (i.e., 121 °C, 10 min, 1.0% NaOH, 1.0% Tween 40) gave the highest sugar yield of 566.0 mg/g, which were 6.5-folds greater than the raw stalk. These demonstrations for using SMAP to achieve enhanced lignin removal and sugar recovery from biomass highlight its strong application potentials of improving bioconversion of lignocellulosic biomass like Miscanthus sinensis, hence making this crop a valuable energy plant.

Environmental changes could dramatically affect biodiversity and the distribution of species. Predicting and understanding the dynamics of vegetation distribution can provide valuable insights into ecosystems’ response to climatic and environmental changes. Opisthopappus(containing two species Opisthopappus taihangensisand Opisthopappus longilobus) is an endangered and endemic genus in the Taihang Mountains of China, which is regarded as a center of distribution and diversity for many plant genera. However, little is known about climatic and environmental changes impact on the distribution of Opisthopappus. Thus, based on maximum entropy model (MaxEnt), we predicted the potential distribution under past, current and future climate conditions, explored the niche difference between the two species and determined the critical environmental factors. Our findings revealed that the distribution areas of O. taihangensisincreased from the last interglacial to the last glacial maximum (LGM) periods, while that of O. longilobusdecreased gradually. Compared to LGM, O. taihangensisand O. longilobusdecreased their distribution ranges in the mid-Holocene period, which are generally similar to the current distribution areas of two species. In the future periods, the predicted distribution areas increased for both species and presented a trend toward the center areas of the Taihang Mountains. Meanwhile, precipitation of wettest month and isothermality were the most important factors influencing the distribution of Opisthopappus. Significant niche differentiation between O. taihangensisand O. longilobusoccurred gradually with time. These results provide useful information for understanding evolution and conservation of O. taihangensisand O. longilobusin Taihang Mountains.

Under weak grid conditions, there is a strong nonlinear coupling between phase-locked loops (PLLs) and the doubly-fed induction generators (DFIGs), and the influence of its dynamic characteristics on system stability cannot be ignored. For a system to be stable, the dynamic properties must be considered. First, based on instantaneous power theory, the sub-synchronous frequency component of power oscillation in a three-phase symmetrical system with the participation of a PLL is deduced. Second, the PLL transient stability is studied under two power grid structures. Third, to connect with the power grid model, a DFIG with a PLL structure is established, and the phase disturbance of the PLL is used as the excitation signal. In the rotor current inner loop and the voltage outer loop transfer processes, the PLL phase disturbance component plays a role. A d-axis structure block diagram of the current loop with the PLL phase disturbance component is constructed, and the disturbance transfer function is deduced. The influence mechanism of the PLL control parameters on system power oscillation is investigated. Finally, the modeling simulation verifies the validity of the theoretical analysis.

Frequency-domain dissipativity of the converter admittance provides an intuitive approach to analyze wideband resonances due to the interactions with the grid. Although the reasons for high- and low-frequency resonances are different, it is found that the proportional capacitor voltage feedforward (CVF) can affect and reshape the converter admittance in a wide frequency range. To enhance wideband dissipativity under a weak/capacitive grid, a proportional–integral (PI)–derivative CVF is proposed in this article. Specifically, high-frequency dissipativity can be guaranteed through the multisampling control (MSC) with proportional–derivative CVF. The low-frequency nondissipative region caused by the phase-locked loop (PLL) and proportional CVF can be compensated through multiorder integrations. In light of grid frequency disturbances, modified integrators are further proposed for the multiorder integrations. The proposed method also applies to the conventional double-sampling control (DSC) with regard to the low-frequency dissipativity enhancement. Finally, experiments validate the proposed control method.

Network embedding – finding a low dimensional representation of the nodes with attributes in a hierarchical, directed network remains a challenging problem in the machine learning community. An emerging approach is to embed complex networks – networks of real-world systems – into hyperbolic space due to the fact that hyperbolic space can better naturally represent such a network's hierarchical structure. Existing hyperbolic embedding approaches, however, cannot handle the embedding of attributed directed networks to an arbitrary embedding dimension. To fill this gap, we introduce HEADNet, for Hyperbolic Embedding of Attributed Directed Networks, an algorithm based on extending previous works for embedding directed attributed networks to Gaussian distributions in hyperbolic space of arbitrary dimension. Through experimentation on a variety of both synthetic and real-world networks, we show that HEADNet can achieve competitive performance on common downstream machine learning tasks, including predicting directed links for previously unseen nodes. HEADNet provides an inductive hyperbolic embedding method for directed attributed networks, which opens the door to hyperbolic manifold learning on a wider range of real-world networks. The source code is freely available at https://github.com/DavidMcDonald1993/HEADNET.

Capacitor current active damping is a common method to achieve dissipation for LCL-filtered grid-connected converters using grid-side current control. However, the dissipative characteristic of converter output admittance near the critical frequency can easily be jeopardized by the filter parameter deviation. Besides, the grid voltage feedforward is often overlooked when designing dissipativity, which is, however, preferred to improve transient performance. To tackle these challenges, a multisampled current control scheme is proposed in this article. By combining the capacitor current active damping and the capacitor voltage feedforward, not only the dissipation can be achieved below the Nyquist frequency but also the dissipativity robustness against the filter parameter deviation is enhanced. Besides, the LCL-filter resonant frequency can be designed near the critical frequency, which simplifies the internal stability design. Finally, the effectiveness of the proposed method is verified through the experiments.

The discovery of ultra-low lattice thermal conductivity has always been an urgent task to break through the thermoelectric performance of environment-friendly SnTe materials. As an effective lattice modulation strategy, lattice softening without deteriorating electrical transport has attracted much attention. Herein, we systematically compare and explore the electron-phonon transport characteristics of Q-doped SnTe-GeTe alloys (Q = Bi, Sb, and Ag), especially the visible lattice softening at sound velocity. The high solid-solution of GeTe significantly reduces the sound velocity, and the apparent strong phonon softening is the major contribution to the low lattice thermal conductivity. However, additional Sb/Bi/Ag doping exhibits various modulations on its “softening”. Bi and Ag with large ionic radii easily destroy the crystal structure and restore the sound velocity close to that of pristine SnTe, while Sb with smaller ionic radius maintains the sound velocity. The Debye-Callaway model quantifies phonon softening and defect scattering, elucidating the exotic lattice thermal conductivity distortion. Additionally, the compensated band convergence and carrier concentration modulation synergistically optimize the electrical transport. The trade-off between lattice softening and electronic band modulation ultimately leads to the zTvalues of ~1.0, ~1.1, and ~0.8 in Sn0.66Ge0.3Bi0.04Te, Sn0.66Ge0.3Sb0.04Te, and Sn0.66Ge0.3Ag0.04Te, respectively. This work not only confirms the feasible manipulation of high-concentration GeTe alloying on the lattice softening of SnTe, but also emphasizes the significant modulation effect of trace aliovalent ion doping, providing a useful reference for optimization of lattice thermal conductivity.

Due to the complexity, time variability, and mutability of the noncooperative maneuvering target, the dynamic tracking model of the target does not match with the actual state, which reduces the tracking accuracy or even completely tracking loss. In this article, an expectation maximization-based adaptive modified unbiased minimum-variance estimation (EM-AMUMVE) algorithm is proposed for highly maneuvering target tracking with model mismatch. First, the virtual maneuvering noise and the first-order Markov process model are integrated to quantitatively describe the maneuvering acceleration according to the boundness of the maneuvering acceleration. Then, the maneuvering acceleration and state estimation are derived based on the unbiased minimum-variance criterion, and the expectation maximization (EM) is introduced in the updating procedure of the quadratic Bayesian filter to adaptively estimate the mean and covariance of virtual maneuvering noise and thus to improve the accuracy of maneuvering acceleration estimation. Finally, the optimality of the adaptive modified maneuvering acceleration estimation is theoretically proved, and the tracking scenarios of time-varying maneuvering target with model mismatch and reentry gliding trajectory of typical hypersonic vehicle hypersonic technology vehicle 2 (HTV-2) are built to demonstrate the validness, convergence, sensitivity, and engineering practicability of the proposed algorithm.

Robot systems with both “intrinsic safety” and “high output” are expected to be implemented in heavy-duty industries such asconstruction and manufacturing. But there are currently no effective solutions. In our previous work, a backdrivable piston using magnetorheological fluid (MRF) whose viscosity can vary with the applied magnetic field was developed. However, it was a passive device, and its active control scheme was not proposed. The design was complex enough to hinder its implementation to robot arms. In this article, we develop an easily implementable rotary actuator using MRF and propose a basic controller. The actuator was designed based on a vane motor and was driven by hydraulic oil (i.e., MRF), so it can generate high torque. It also has a built-in MRF valve in the vane which can change the output torque and backdrivability with the magnetic field controlled by coil current. Each component was designed to maximize the dynamic range of output torque and backdrivability based on a multiphysics coupling model of electromagnetics, MRF magnetization, and fluid dynamics. Moreover, three basic control modes including backdrivable, high-response, and power-efficiency modes were designed and tested. The experimental results showed that the proposed MRF actuator had both high output and intrinsic backdrivability, and control modes could show the advantages of the MRF actuator.

As dendrites are essential parts of neurons, they are crucial factors for neuronal activities to follow multiple timescale dynamics, which ultimately affect information processing and cognition. However, in the common SNN (Spiking Neural Networks), the hardware-based LIF (Leaky Integrate-and-Fire) circuit only simulates the single timescale dynamic of soma without relating dendritic morphologies, which may limit the capability of simulating neurons to process information. This study proposes the dendritic fractal model mainly for quantifying dendritic morphological effects containing branch and length. To realize this model, We design multiple analog fractional-order circuits (AFCs) which match their extended structures and parameters with the dendritic features. Then introducing AFC into FLIF (Fractional Leaky Integrate-and-Fire) neuron circuits can demonstrate the same multiple timescale dynamics of spiking patterns as biological neurons, including spiking adaptation, inter-spike variability with power-law distribution, first-spike latency, and intrinsic memory. By contrast, it further enhances the degree of mimicry of neuron models and provides a more accurate model for understanding neural computation and cognition mechanisms.

• Ultrafine-grained Nb-Cu immiscible alloys were fabricated via mechanical alloying and spark plasma sintering. • The addition of Cu could not only enhance compressive strength and fracture strain but also significantly improve corrosion resistance. • The sintered Nb-3Cu showed the strongest antibacterial activity both against E. coli and S. aureus. • In vitro and In vivo evaluations indicated that the present Nb-3Cu alloy is a promising candidate for heavy load-bearing hard tissue repair. The biocompatible metallic implants with strong osteointegration often lack the ability of anti-infection. The biocompatible niobium (Nb) containing the antibacterial copper (Cu), the obtained Nb-Cu alloy, could be a potential candidate to solve this issue. To test this hypothesis, ultrafine-grained Nb-Cu immiscible alloys were fabricated via mechanical alloying and spark plasma sintering. The aim of this study was to investigate the microstructure, mechanical properties, magnetic susceptibility, corrosion behavior, ion release, and the bactericidal activity, biocompatibility and osteogenic potential of the Nb-Cu alloys in vitro and their osteogenesis and osteointegration ability in vivo with a comparison with pure Nb. The rat cranial defect model and the bone screws insertion in rabbit femoral bone were used to evaluate the osteogenesis and osteointegration ability, respectively. The results showed that after the addition of 3 wt.% of Cu, the compressive strength was significantly improved from 1.57 GPa to 2.21 GPa and the magnetic susceptibility slightly decreased. The Nb-3 wt.% Cu (Nb-3Cu) alloy exhibited higher corrosion resistance than pure Nb in Hank's solution and strong bactericidal activity against both E. coli and S. aureus. In vitro , the Nb-3Cu alloy showed comparable biocompatibility with pure Nb. The addition of 3 wt.% Cu also significantly enhanced the expression of osteogenesis-related genes (RUNX2, ALP, COLA1 and OCN) of pre-osteoblasts. In vivo , the Nb-3Cu alloy promoted bone regeneration at the defect sites and showed enhanced osteointegration after 12 weeks of implantation. Such a good combination of high mechanical strength and corrosion resistance, strong antibacterial activity and improved osteogenesis and osseointegration ability enables the present Nb-3Cu alloy a promising candidate for heavy load-bearing hard tissue repair. [Display omitted] [ABSTRACT FROM AUTHOR]

The wind speed signal measured by the mechanical anemometer lags behind the wind speed at the wind wheel surface of the wind turbine in time. The wind speed reconstruction algorithm adopted by the ordinary lidar anemometer is insufficient. For the sake of enhancing the accuracy of wind speed forecast on the surface of wind turbines in wind farms for wind turbine pitch control strategies, an modified sparrow search algorithm (SSA) based on sinusoidal chaotic mapping is proposed to improve the BP neural network wind speed prediction model. According to the characteristics that lidar measure wind speed at multiple points, a multiple regression forecast model is build, and then the wind speed is predicted. Simulation tests were conducted using lidar wind measurement data from a wind farm in Xinjiang and analyzed and in contrast to a BP neural network wind speed prediction model. The experimental results indicated that the four error evaluation indicators of the Sine-SSA-BP algorithm are all smaller than the BP neural network. In contrast to the single BP neural network wind speed forecast model, sine chaotic mapping modified sparrow search algorithm optimized BP neural network has significantly improved prediction accuracy.

ABSTRACTFucoxanthin, one of the most abundant carotenoids from edible brown seaweeds, for years has been used as a bioactive dietary supplement and functional food ingredient. Recently, fucoxanthin was reported to penetrate the blood–brain barrier, and was superior to other carotenoids to exert anti-neurodegenerative disorder effects via acting on multiple targets, including amyloid protein aggregation, oxidative stress, neuroinflammation, neuronal loss, neurotransmission dysregulation and gut microbiota disorder. However, the concentration of fucoxanthin required for in vivoneuroprotective effects is somewhat high, and the poor bioavailability of this molecule might prevent its clinical use. As such, new strategies have been introduced to overcome these obstacles, and may help to develop fucoxanthin as a novel lead for neurodegenerative disorders. Moreover, it has been shown that some metabolites of fucoxanthin may produce potent in vivoneuroprotective effects. Altogether, these studies suggest the possibility for future development of fucoxanthin as a one-compound-multiple-target or pro-drug type pharmaceutical or nutraceutical treatment for neurodegenerative disorders.Trial registration:ClinicalTrials.gov identifier: NCT03625284.Trial registration:ClinicalTrials.gov identifier: NCT02875392.Trial registration:ClinicalTrials.gov identifier: NCT03613740.Trial registration:ClinicalTrials.gov identifier: NCT04761406.

Emergent topological textures coupled with ferroic orders have become the promising basis for exotic phenomena and application advances. While the number of materials observed with polar topological textures is growing, manipulation of these emergent polar topologies with the aid of external stimuli (e.g. electric field, strain, thermal perturbation) remains rare. Here, we report a pyrotoroidic transition accompanying the Curie transition in face-on lamellae of poly(vinylidene fluoride-ran-trifluoroethylene) (P(VDF-TrFE)), with a chirality reversal revealed in the polar topology. The existence of toroidal order in paraelectric polymers has been validated by further confirming the toroidal order in face-on lamellae of relaxor ferroelectric polymer induced by physical defects. This work demonstrates the manipulation of polar topological texture with the controls of the thermal condition. It should also expand the reach of toroidal polar topologies to a range of flexible materials and offer an insight into their formation.

Sinuscalide A (1), featuring an uncommon 8/8-fused carbon scaffold, three new norditerpenes, sinuscalides B–D (2–4), and sinuscatone A (5), with a 5/4/9 tricyclic carbon ring system, along with four known compounds were isolated from the South China Sea soft coral Sinularia scabra. The structures of the new compounds were established by extensive spectroscopic analysis, X-ray diffraction, and electronic circular dichroism (ECD). A plausible biosynthetic pathway for 1was proposed. In a bioassay, compound 1showed antiviral activity against human enterovirus EV71 (IC50= 5.0 μM) and an inhibitory effect against RANKL-induced osteoclastogenesis (92.3% inhibition at 10 μM). Compound 5exhibited mild inhibition against Streptococcus pneumoniaeand Salmonella paratyph(MIC 16 μg/mL).