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Wound healing is a complex biological process that can trigger inflammation and oxidative stress and impair myofibrillogenesis and angiogenesis. Several advanced wound-dressing nanocomposite materials have been designed to address these issues. Here, we designed a new multifunctional styrene–ethylene–butylene–styrene/silver nanowire (SEBS/AgNWs)-based nanocomposite film with antimicrobial, antioxidant, and anti-inflammatory properties to promote wound healing. The porous morphological structure of SEBS/AgNWs enhances their antimicrobial, antioxidant, and anti-inflammatory properties. SEBS/AgNWs significantly inhibited the growth of Staphylococcus aureus, methicillin-resistant Staphylococcus aureus, and Escherichia colistrains, effectively wiping out ABTS•+, DPPH•, hydrogen peroxide (H2O2), and hydroxyl (•OH) radicals, showing their effective ROS-scavenging properties. It further showed significant antioxidant properties by increasing the levels of enzyme-like catalase (CAT), superoxide dismutase (SOD), and glutathione (GSH), while decreasing malonaldehyde (MDA) levels. Additionally, SEBS/AgNWs reduced the expression of interleukin-1β (IL-1β), IL-6, and tumor necrosis factor-α (TNF-α), while increasing levels of transforming growth factor- β (TGF-β), vascular endothelial growth factor-A (VEGF), and CD31 in wound healing. This suggests that applying a multifunctional nanoplatform based on SEBS/AgNWs could enhance wound healing and improve patient outcomes in wound care management.

This paper investigates secure control for homogeneous vehicle platoons in the presence of false data injection attacks with low communication and computation costs. We consider a scenario where each vehicle within the platoon transmits a local state vector to multiple neighboring vehicles. By leveraging these shared vectors from both preceding and following vehicles, we propose a novel and effective resilient controller for vehicle platoons against node/communication link attacks. More specifically, each vehicle determines the local state deviation vectors from neighboring vehicles. It then eliminates the vectors that are farthest from the origin, with the number of removed vectors equivalent to the maximum number of attacks. This approach offers a considerable advantage by mitigating the effects of abnormality and manipulation, making it robust against arbitrary information tampering within a pre-defined upper boundary for manipulated broadcast information. Importantly, we establish specific conditions for the proposed resilient design to guarantee the internal stability of the vehicle platoon under attacks. Extensive simulations and experiments involving four TurtleBot3s are conducted to demonstrate the effectiveness of the proposed resilient controller.

We consider a distributed personalized optimization problem over a network of nodes whose cost functions depend on a decision variable consisting of two parts: global (shared) part and local (node-specific) part. This problem structure arises in several important scenarios, where the global part captures the common feature among nodes and the local part represents the personalized feature. To solve this problem, we develop a flexible algorithmic framework employing personalized distributed stochastic gradient tracking method, where each node updates variables locally and communicates the shared part with its neighbors for coordination in a stochastic way. Different from existing works, the proposed framework provides great flexibility in designing algorithms with uncoordinated stepsizes for updating local and global parts over changing topologies. Most importantly, it can eliminate the effect of heterogeneity among nodes thanks to the gradient tracking scheme. Leveraging a properly designed Lyapunov function, we prove the convergence of the proposed algorithm for both (strongly) convex and nonconvex objective functions with cross-block Lipschitz gradients. The obtained rate results show clear dependence of the convergence performance on topology, heterogeneity of stepsize, and properties of objective functions. Numerical examples are provided to demonstrate the effectiveness of the proposed algorithm accounting for node-specific heterogeneity.

In this article, we investigate the identifiability and identification problem of switching (directed) dynamical networks (SDNs) modeled by switched linear dynamical systems. Switching signals governing the active subsystem (mode) are frequently changing, which brings challenges to the exact reconstruction of network sequences, since the state trajectory is generated by a number of subsystems at different time periods. By analyzing unobservable subspaces associated with each subsystem, we first establish necessary and/or sufficient conditions for the identifiability of SDNs under different levels of knowledge on the switching signal. Building on this, a sufficient identification condition is developed leveraging coupled Lyapunov-transpose matrix equations constructed by state trajectories with properly designed time offsets, which allows us to design a data-based approach that can exactly recover the whole network sequence, even if the switching signal is unknown a priori. More important, we develop sharper conditions for both identifiability and identification when there is certain prior knowledge available on networks. Numerical experiments on switching consensus networks and sparse networks are conducted to verify the effectiveness of the theoretical findings.

The bio-corrosion behavior and bio-compatibility of TiNbZrTa and TiNbZrTaMo high entropy alloys (HEAs) are crucial for their efficient maintenance during biological implantation. In this work, TiNbZrTa and TiNbZrTaMo HEAs were successfully prepared via vacuum melting, with a β-type titanium alloy Ti35Nb7Zr5Ta, exhibiting good biocompatibility used as a comparison. Due to the high entropy effect of equal atomic ratios, both TiNbZrTa and TiNbZrTaMo HEAs exhibit body-centered cubic (BCC) structure and lattice distortion compared to the β titanium alloy Ti35Nb7Zr5Ta. Mo elements contribute to the formation of a new BCC phase, resulting in a white matrix rich in Ta and Mo, and a dark second phase rich in Ti, Zr, and Nb. Electrochemical test results at 37 °C shown that TiNbZrTa has a wider and more stable passivation area than TiNbZrTaMo. The XPS results shown that formation of the passive film is related to the main elements added. Ti, Nb, Ta and Mo formed oxides via the solid-liquid interface and migrate inward, while Zr is formed at the passivation film/metal substrate interface and migrates outward, finally forming the layered structure of the passivation film. Additionally, the cytotoxicity test of mouse fiber cells was carried out to evaluate the biocompatibility of the HEAs. The results shown that the cell proliferation rate of TiNbZrTa and TiNbZrTaMo HEAs reached 0 and 1, respectively, with TiNbZrTa exhibiting better biocompatibility, as adding Mo reduced the cell proliferation rate. These findings may provide a method for predicting the bio-corrosion behavior and bio-compatibility of HEAs used for biological implantation.

The synthesis of carbon nanospheres (CNS) has developed rapidly in recent years, and they are widely used owing to the tunability of their porous structures and surface properties and the unique hydrodynamic advantages conferred by their spherical structures. This review summarizes the methods used to synthesize CNS and their applications in various fields. The review first describes the four main methods of CNS synthesis, i.e. the template, spray-drying, hydrothermal carbonization, Stöber and chemical vapor deposition method. Next, applications in the fields of energy storage, adsorption, biological medicine, and catalysis are expounded. Finally, some insights on the development and design of CNS are presented.

The catalytic cracking of 1,2-dichloroethane (EDC) to obtain vinyl chloride (VCM) monomer is a crucial step in the production of polyvinyl chloride (PVC). The heteroatom-doped carbon catalysts have exhibited desired performance; however, the underlying mechanism is still not fully understood. Herein, a series of B–N co-doped carbon (BNC), N-doped carbon (NC), B-doped carbon (BC) and pure carbon (C) catalysts were prepared for EDC catalytic cracking, and the synergistic mechanism between B and N was carefully investigated. The BNC catalyst exhibits prominently higher activities with an EDC conversion of 53.9% at 250 °C. Through a combination of experimental and theoretical analyses, it is rationalized that the formation of the B–N atomic pair contributes to the enhanced performance and the electronic interaction between the B–N atomic pair imparts greater basicity to the N sites, which reduces the activation energy barrier for C–H bond cleavage by 0.34 eV. The present results provide a theoretical foundation for the precise design of highly efficient non-metallic carbon-based catalysts for EDC cracking.

In battery energy storage systems, the battery and DC bus voltages vary greatly. This makes it difficult for the battery storage converter to maintain high efficiencies under all circumstances. A current-fed isolated bidirectional DC–DC converter is presented in this paper. This converter contains two series transformers, two conventional current-fed half-bridges at the battery side and two half-bridges at the DC bus side. PWM plus dual phase shift modulation with equal duty cycles and voltage-matched control is applied to ensure ZVS of all the switches and low conduction losses. The average and backflow power transmission equations and soft-switching conditions for all of the operation modes in the full operation range are analyzed comprehensively in this paper. Then six recommended modes are addressed based on the above analyses. Moreover, the control scheme and hardware design guidelines are addressed. Finally, the above theoretical analyses and control strategy are verified by experimental results.

Since the scaling of advanced technology nodes is pushing to its physical limit, lithography hotspot detection (LHD) has become more significant than ever in design for manufacturability. Recently, machine learning techniques have been deployed to greatly reduce simulation time for hotspot detection, but high-quality data are required to build a model. Many design companies do not have enough high-quality data and are hesitant to share it for fear of intellectual property theft or model ineffectiveness. Furthermore, using locally trained models with limited and similar data can lead to overfitting and a lack of generalization and robustness when applied to new designs. In this article, we propose a heterogeneous federated learning framework for LHD that can address the aforementioned issues. Our framework can overcome the challenges of nonindependent and identically distributed data and heterogeneous communication, ensuring high performance and good convergence in various scenarios. The proposed framework creates a more robust centralized global submodel through heterogeneous knowledge sharing while keeping local data private. Then, it combines the global submodel with a local submodel for better adaptation to local data heterogeneity. Our experimental results show that the proposed framework outperforms other state-of-the-art methods.

Analyzing the influence of controller parameters and physical system uncertainty is the premise of system stability design. This letter presents an intuitive analysis method for single-parameter variations in linear systems. Different from the root locus analysis, in the proposed method, the effect of single-parameter full-range variations on the system stability can be clearly visualized by simply plotting one Nyquist curve of reconstructed function at an arbitrary parameter point. Finally, the validity of the proposed method is demonstrated by a case study for the single-phase grid-following inverter.

In the grid-connected inverter, both the phase-locked loop (PLL) and dc-voltage loop (DVL) can lead to the frequency coupling in the weak grid. Instabilities caused by PLL frequency coupling have been widely discussed. For DVL, past studies have analyzed the effect of DVL parameters on the degree of frequency coupling, but it is quite unclear how DVL parameters affect the inverter stability and how DVL can be designed under the weak grid. Hence, by fully considering the abovementioned frequency coupling, an accurate admittance model of photovoltaic grid-connected inverter is established in this article. By deriving the modified admittance matrix, the effects of grid impedance and DVL parameters on the frequency coupling are clearly studied. In addition, by modeling the equivalent inverter output impedance, the impact of DVL on the inverter stability under the weak grid is revealed. As proved, the increase of DVL bandwidth ${f}_{vbw}$ and grid impedance will aggravate the frequency coupling, but the current distortion does not necessarily increase. Meanwhile, the increase of ${f}_{vbw}$ helps to improve the inverter stability under the weak grid. Accordingly, a novel design for DVL in the weak grid is proposed. Experiments verify the correctness of the analysis and design.

Phosphorus and nitrogen co-doped graphenes are synthesized by using glyphosate and melamine through the intermedium of g-C3N4template, and can be used as high efficiency catalysts for the catalytic dehydrochlorination of 1,2-dichloroethane to vinyl chloride monomer production.

This article is concerned with the strict stability problem for grid-following inverters subject to synchronous nonlinearity and large transient disturbances. First, considering that the complex nonlinear structure of the conventional phase-locked-loop-based grid synchronization scheme may be difficult to match the existing intuitive nonlinear analysis methods, a simplified open-loop grid synchronizer is developed for the grid-following control. Subsequently, the sector-bounded condition of the system nonlinear factor is derived by setting the grid voltage and power control variation intervals, and the frequency-domain conditions for absolutely stable are further obtained with the help of the circle criterion. The derived conditions illustrate that the stability assessment is intuitive because it is only necessary to observe the graphical position of the disk $d(-\psi,-\phi)$ with respect to the Nyquist curve of $-\Omega _{\alpha }(s)$. Finally, the effects of a weak grid and power control variations on system stability are further analyzed, and the effectiveness of the proposed theories is fully supported by transient experimental results.

This study aimed to identify subtypes of genomic variants associated with the efficacy of immune checkpoint inhibitors (ICIs) by conducting systematic literature search in electronic databases up to May 31, 2021. The main outcomes including overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and durable clinical benefit (DCB) were correlated with tumor genomic features. A total of 1546 lung cancer patients with available genomic variation data were included from 14 studies. The Kirsten rat sarcoma viral oncogene homolog G12C(KRASG12C) mutation combined with tumor protein P53 (TP53) mutation revealed the promising efficacy of ICI therapy in these patients. Furthermore, patients with epidermal growth factor receptor (EGFR) classical activating mutations (including EGFRL858Rand EGFRΔ19) exhibited worse outcomes to ICIs in OS (adjusted hazard ratio (HR), 1.40; 95% confidence interval (CI), 1.01–1.95; P=0.0411) and PFS (adjusted HR, 1.98; 95% CI, 1.49–2.63; P<0.0001), while classical activating mutations with EGFRT790Mshowed no difference compared to classical activating mutations without EGFRT790Min OS (adjusted HR, 0.96; 95% CI, 0.48–1.94; P=0.9157) or PFS (adjusted HR, 0.72; 95% CI, 0.39–1.35; P=0.3050). Of note, for patients harboring the Usher syndrome type-2A (USH2A) missense mutation, correspondingly better outcomes were observed in OS (adjusted HR, 0.52; 95% CI, 0.32–0.82; P=0.0077), PFS (adjusted HR, 0.51; 95% CI, 0.38–0.69; P<0.0001), DCB (adjusted odds ratio (OR), 4.74; 95% CI, 2.75–8.17; P<0.0001), and ORR (adjusted OR, 3.45; 95% CI, 1.88–6.33; P<0.0001). Our findings indicated that, USH2Amissense mutations and the KRASG12Cmutation combined with TP53mutation were associated with better efficacy and survival outcomes, but EGFRclassical mutations irrespective of combination with EGFRT790Mshowed the opposite role in the ICI therapy among lung cancer patients. Our findings might guide the selection of precise targets for effective immunotherapy in the clinic.

Accurate genome editing based on various molecular tools has always been the focus of gene-editing research and the primary goal for therapeutic application. The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 system is a well-established gene-editing method that is preferred due to its simplicity and high efficiency. In this study, a group of single-stranded DNA aptamers with high affinity and high specificity for the Cas9 protein were obtained by the systematic evolution of ligands through the exponential enrichment method. Their binding affinity and possible binding domains to the Cas9 protein were analyzed. In addition, we demonstrated the effectiveness of aptamers in regulating dCas9-modulated gene transcription, in terms of both transcriptional activation and repression. Additionally, the aptamers successfully reduced the off-target effect and improved the efficiency of gene homologous recombination repair mediated by CRISPR-Cas9. The findings suggest a potential method to better control precise gene editing and enrich the diversity of modulating tools for the CRISPR-Cas9 system.

For single-phase grid-connected inverters, the second-order generalized integrator-based phase-locked loop (SOGI-PLL) is widely used for good harmonics attenuation and frequency adaptability. However, existing studies usually neglect the frequency feedback loop in the modeling and design process, and thus, the potential instability caused by the frequency feedback loop is not well explained. Besides, the improper design of SOGI-PLL can lead to the inverter instability both under ideal and weak grid conditions. Therefore, by fully considering the coupling of the frequency feedback loop, this article establishes an accurate model for SOGI-PLL. Furthermore, effects of different PLL parameters on behaviors of both the SOGI-PLL itself and the inverter are studied, based on which a graphical method for PLL parameters design is proposed. As proved, the frequency feedback loop can deteriorate the stability and performance of both SOGI-PLL itself and inverter system, especially if rapid transient is expected. The modeling method is also extended to the low-pass filter-SOGI-PLL and the improved parameters design is discussed. Experimental results verify the correctness of the proposed PLL model and the abovementioned analysis results. The proposed model is helpful to deeply reveal the instability mechanism and provides a reference for the PLL design under nonideal grid conditions.

The stability problem of grid-following inverters has been widely investigated. Nevertheless, existing literature has not yet proposed a strict stability analysis method for the overall grid-following inverter system with nonlinear nature. By focusing on single-phase systems and using frequency-domain nonlinear theory, this article proposes a universal absolute stability criterion for the single-phase grid-following inverters (SGFIs) equipped with orthogonal-normalization-based grid synchronizer. It will be shown that a SGFI will be absolutely stable under small- and large-disturbances if both the traditional impedance criterion and the synchronous nonlinear criterion are satisfied. The usefulness and applicability of the proposed new criterion are demonstrated by a case study of the conventional LCL-type SGFI system. Finally, the theoretical analysis is fully supported by a series of steady-state and transient experimental tests.

This article presents a current control methodology equipped with a state and disturbance observer (SDO) to address the uncertain disturbance problem existing in an LCL-type single-phase grid-tied inverter system. In this methodology, disturbance feedforward compensation and full-state feedback of the combined proportional–integral (PI) regulator are utilized to provide more degrees of freedom for a robust design of the controller. In order to realize this technology without additional sensors, a reduced-order SDO is designed by decoupling the real inverter plant into a nominal model with lumped uncertainty and disturbance (LUD), making the estimation results more robust adaption for system uncertainty. Furthermore, the upper bound of the LUD is concerned and innovatively used to evaluate the size of the uncertainty region of the LUD estimated by the observer, which may be important to antidisturbance control. Other system performances, such as grid current distortion suppression and robust stability, are also analyzed. Finally, the effectiveness of the proposed control strategy is fully supported by simulation and experimental results.

Self-assembled polymer vesicles have emerged as exciting and promising materials for their potential application in drug delivery, but the dynamics of stimuli-responsive polymers in these areas with pendant functionality in order to understand the structure–property relationship under different physicochemical conditions is still open to discussion. In this work, nitroxide radical-containing copolymers were synthesized and utilized to investigate local dynamics in their vesicular assemblies. Herein, electron paramagnetic resonance (EPR) spectroscopy was applied to reveal the smart supramolecular vesicular structure and polymer chain dynamics in stimuli-responsive controlled assemblies by considering molecular-level interactions. These interactions and dynamics were dependent on the microenvironment of the assemblies, which might be affected by physicochemical parameters such as radical concentration, pH, redox agent, polarity, and viscosity. These observations help to accomplish quantitative insights into the stimuli-responsive colloidal vesicular assemblies. The vesicles were used as an anticancer drug carrier, which showed high drug loading efficiency (63.65%). The reduction-responsive prompt disassembly accelerated the release. Furthermore, the biocompatibility and anticancer activity were examined by cellular experiments against normal fibroblasts (L929) and human cervical cancer (HeLa) cell lines, respectively. The results demonstrate that this effort provides an easy strategy for designing controllable stimuli-responsive polymer nanosystems which promotes their promising application in cancer treatment.

Carbon spheres with hierarchical pore structure were successfully synthesized by using strongly basic anion exchange resins exchanged with silicate, followed by pyrolysis in an inert atmosphere and etching silica. As a result of the quaternary ammonium group in the anion exchange resin structure, these carbon spheres were doped with nitrogen. The performance of these carbon spheres in the catalytic dehydrochlorination of 1,2-dichloroethane (EDC) was improved with the increase of calcination temperature, and the carbon sphere 900-900-RC showed the highest conversion rate (96.7%) and a selectivity to vinyl chloride above 99%. The structural and surface properties of N-doped carbon spheres were characterized by scanning electron microscopy, nitrogen sorption, and Raman and X-ray photoelectron spectroscopy. The result of these characterizations further verified that the quaternary nitrogen species are as effective as pyridine nitrogen species in this catalyst.

Novel bird nest-like zinc oxide (BN-ZnO) nanostructures were for the first time exploited to develop a sensitive electrochemical glucose biosensor based on direct electron transfer of glucose oxidase (GOx) immobilized on nanostructured BN-ZnO modified electrode.

Energy management strategy (EMS) is a key technology for plug‐in hybrid electric vehicles (PHEVs). The energy management of certain series–parallel PHEVs involves the control of continuous variables, such as engine torque, and discrete variables, such as clutch engagement/disengagement. Herein, a control‐oriented model is established for a series–parallel plug‐in hybrid system with clutch engagement control from the perspective of mixed‐integer programming. Subsequently, an EMS based on continuous‐discrete reinforcement learning (CDRL), which enables simultaneous output of continuous and discrete variables, is designed. During training, state‐of‐charge (SOC) randomization is introduced to ensure that the hybrid system exhibits optimal energy‐saving performance in both high and low SOC. Finally, the effectiveness of the proposed CDRL strategy is verified by comparing EMS based on charge‐depleting charge‐sustaining (CD‐CS) with rule‐based clutch engagement control and dynamic programming (DP). In the simulation results, it is shown that, under a high SOC, the CDRL strategy proposed in this article can improve energy efficiency by 8.3% compared to CD‐CS, and the energy consumption is just 6.6% higher than the global optimum based on DP, while under a low SOC, the numbers are 4.1% and 3.9%, respectively. In this article, plug‐in hybrid electric vehicles are focused on and an energy management strategy with clutch engagement control based on continuous‐discrete reinforcement learning (RL) is proposed. The hybrid system is modeled from the perspective of mixed‐integer programming, with state‐of‐charge randomization introduced during the training process. In the comparative analysis, the optimal control performance of RL is shown.

Background: The association between vitamin D/calcium and risk of ovarian cancer is still a debatable point. The aim of our study was to systematically investigate the association between vitamin D/calcium, and the risk of ovarian cancer and estimate their dose-response association quantitatively. Methods: PubMed, EMBASE, and Web of Science databases were searched to identify relevant observational studies. Two investigators screened citations and extracted data independently. Data were extracted and the association between vitamin D/calcium and ovarian cancer risk was estimated by calculating pooled relative risks (RRs). Subgroup analyses, publication bias estimation, and dose-response analyses were carried out as well. Results: In total, 21 articles involving 980,008 participants were included in our present study. No significant association was observed between total vitamin D intake and ovarian cancer risk (RR: 1.02; 95% CI, 0.89–1.16, p= 0.81). Further subgroup analysis suggested that neither dietary vitamin D intake (RR: 0.80; 95% CI, 0.62–1.03, p= 0.09) nor supplementary vitamin D intake (RR: 0.98; 95% CI, 0.85–1.13, p= 0.80) was associated with the risk of ovarian cancer. As for calcium, total calcium intake was found to be statistically inversely associated with ovarian cancer risk in case–control studies (RR: 0.73; 95% CI, 0.63–0.86, p&lt; 0.001) but not in cohort studies (RR: 1.05; 95% CI, 0.90–1.24, p= 0.52). Besides, supplementation with calcium plus vitamin D was not effective for the prevention of ovarian cancer (p= 0.98). Of note, dose-response analysis based on cohort studies suggested a potential inverse U-shape relationship between calcium intake (including total calcium and dietary calcium) and ovarian cancer risk, which indicated that low dose of calcium intake might reduce ovarian cancer risk while high dose of calcium intake might not. Conclusions: Taken together, vitamin D could not decrease the risk of ovarian cancer. The role of calcium intake was not proven for reducing ovarian cancer risk. Besides, no evidence showed combinative use of calcium and vitamin D have additional benefits for ovarian cancer prevention.

Nitrogen-doped hierarchically porous carbon spheres are synthesized by using poly(vinylidene chloride) and melamine in alginate gel beads, and can be used as high efficiency adsorbents for the low concentration CO2capture.

In this article, we investigate a distributed online constrained optimization problem with differential privacy where the network is modeled by an unbalanced digraph with a row-stochastic adjacency matrix. To address such a problem, a distributed differentially private algorithm without introducing a trusted third-party is proposed to preserve the privacy of the participating nodes. Under mild conditions, we show that the proposed algorithm attains an $O(\log T)$ expected regret bound for strongly convex local cost functions, where $T$ is the time horizon. Moreover, we remove the need for knowing the time horizon $T$ in advance by adopting doubling trick scheme, and derive an $O(\sqrt{T})$ expected regret bound for general convex local cost functions. Our results coincide with the best theoretical regrets that can be achieved in the state-of-the-art algorithms. Finally, simulation results are conducted to validate the efficiency of our proposed algorithm.

Multi-energy systems which bring together different forms of energy, such as electricity, gas and heat, to coordinate in the process of supply, transmission and consumption provide much higher flexibility over traditional energy systems in energy utilization. This paper deals with the economic dispatch problem in multi-energy systems in a distributed manner. Each agent optimizes its local objective function with regard to local coupled limits and a global constraint via local communications only. A distributed algorithm is proposed based on duality analysis and splitting methods.This algorithm adopts a non-linear mapping method to linearize the nonlinearity arisen from coupling relationship among energy carriers. We show that the proposed algorithm converges at a nonergodic rate of O(1/k). Simulations are demonstrated to show the effectiveness of the algorithm.

We deal with a class of distributed resource allocation problems where each agent attempts to minimize its own cost while respecting network-wide resource constraints as well as local capacity limits. This problem arises from many areas, such as economic dispatch, network utility maximization, and demand response. Most existing methods are centralized while few works are devoted to solving the problem in a distributed manner. The problem becomes even more challenging when there is a (nonsmooth) regularization term in the cost function. In this paper, we propose a novel distributed algorithm (termed DuSPA) to solve the above problem based on duality analysis and splitting methods. For privacy concerns, this algorithm is not required to communicate sensitive gradient information while still achieving the optimum without sacrificing the performance. We will show that the proposed algorithm converges at a nonergodic convergence rate of $O(\frac{1}{k})$ for general convex cost functions and a linear convergence rate for smooth and strongly convex cost functions, respectively. Furthermore, we apply the proposed algorithm to an economic dispatch problem to show its effectiveness.

We consider distributed optimization problems, in which a group of agents are to collaboratively seek the global optimum through peer-to-peer communication networks. The problem arises in various application areas, such as resource allocation, sensor fusion, and distributed learning. We present a general algorithmic framework based on the Bregman method and operator splitting, which allows us to easily recover most of the existing distributed algorithms. Under this framework, we propose a general efficient distributed algorithm—distributed forward–backward Bregman splitting (D-FBBS)—to simultaneously solve the above primal problem as well as its dual. The proposed algorithm allows agents to communicate asynchronously and, thus, lends itself to stochastic networks. This algorithm is shown to have close connections with some existing well-known algorithms when dealing with fixed networks. However, we will show that it is generally different from the existing ones due to its effectiveness in handling stochastic networks. With proper assumptions, we establish a nonergodic convergence rate of $O(1/k)$ in terms of fixed-point residuals over fixed networks both for D-FBBS and its inexact version (ID-FBBS) that is more computationally efficient and an ergodic convergence rate of $O(1/k)$ for D-FBBS over stochastic networks. We also apply the proposed algorithm to sensor fusion problems to show its superior performance compared to existing methods. [ABSTRACT FROM AUTHOR]

Grid-connected LCL-filtered inverters are commonly used for distributed power generators. The LCL resonance should be treated properly. Recently, many strategies have been used to damp the resonance, but the relationships between different damping strategies have not been thoroughly investigated. Thus, this study analyses the essential mechanisms of LCL-resonance damping and reviews state-of-the-art resonance damping strategies. Existing resonance damping strategies are classified into those with single-state and multi-state feedback. Single-state feedback strategies damp the LCL resonance using feedback of a voltage or current state at the resonance frequency. Multi-state feedback strategies are summarized as zero-placement and pole-placement strategies, where the zero-placement strategy configures the zeros of a novel state combined by multi-state feedback, while the pole-placement strategy aims to assign the closed-loop poles freely. Based on these mechanisms, an investigation of single-state and multi-state feedback is presented, including detailed comparisons of the existing strategies. Finally, some future research directions that can improve LCL-filtered inverter performance and minimize their implementation costs are summarized.

We consider distributed optimization problems in which a number of agents are to seek the global optimum of a sum of cost functions through only local information sharing. In this paper, we are particularly interested in scenarios, where agents are operating asynchronously over stochastic networks subject to random failures. Most existing algorithms require coordinated and decaying stepsizes to ensure zero gap between the estimated value of each agent and the exact optimum, restricting it from asynchronous implementation and resulting in slower convergence results. To deal with this issue, we develop a new asynchronous distributed gradient method (AsynDGM) based on consensus theory. The proposed algorithm not only allows for asynchronous implementation in a completely distributed manner but also, most importantly, is able to seek the exact optimum even with constant stepsizes. We will show that the assumption of boundedness of gradients, which is widely used in the literature, can be dropped by instead imposing the standard Lipschitz continuity condition on gradients. Moreover, we derive an upper bound of stepsize within which the proposed AsynDGM can achieve a linear convergence rate for strongly convex functions with Lipschitz gradients. A canonical example of sensor fusion problems is provided to illustrate the effectiveness of the proposed algorithm. [ABSTRACT FROM PUBLISHER]

A binder-free Ir-dispersed ordered mesoporous carbon (Ir-OMC) catalytic electrode has been prepared through a designed in-situ carbonization method, which involves coating resorcinol and formaldehyde mixtures with iridium precursors onto the three-dimensional nickel foam framework, followed by in-situ calcination in N2atmosphere at 800°C for 3 h. This electrode shows a large surface area, ordered mesoporous structure and homogeneous distribution of metal nanoparticles. It presents good activity and stability towards hydrogen evolution reaction, which is attributed to the efficient mass and electron transport from the intimate contact among Ir nanoparticles, ordered mesoporous carbon matrix and 3D conductive substrate. We hope that this in-situ carbonization synthetic route can also be applied to design more high-performance catalysts for water splitting, fuel cells and other clean energy devices.

We report a carbothermal ammonia reduction (CAR) strategy for one-pot preparation of highly efficient and durable hydrogen evolution reaction (HER) electrocatalyst composed of earth abundant early transition metals. In this strategy, resin is applied both as the pre-binder and carbon source, and Pluronic F127 as the structure-directing agent. Upon annealing in NH3, the Mo-containing precursor on Ni foam undergoes the CAR, and simultaneously Ni from the substrate diffuses out, resulting in the formation of a quaternary complex structure of molybdenum-nickel bimetallic carbonitride (MoNiNC). The as-prepared electrode showed outstanding HER performance with an overpotential of 150mV at 50mAcm−2and maintained steady hydrogen bubble evolution for continuous 48h. Our strategy offers a quick and simple way to fabricate earth-abundant HER electrode with highly efficient and durable electrocatalytic performance.

In this paper, we consider the problem of distributed sensor fusion in relay-assisted sensor networks with time-varying asymmetric communications over fading channels. A Distributed INnovation based Scheme (DINS) is proposed by fusing both the local measurements and the information received from neighboring nodes. We present a hybrid TDMA scheme for efficient implementation of DINS and the design of parameters of DINS to bring the effects of fading under a satisfactory level. With an appropriate design, it is shown that our algorithm is able to produce estimates with desired asymptotic properties of unbiasedness and consistency. Simulation results are provided to demonstrate the performance of DINS.

Metal nanoparticles (MNPs) possess size-dependent desirable electronic and optical properties while metal-organic frameworks (MOFs) have an edge over extremely large specific surface areas, homogeneous structure, high porosity and remarkable chemical stability. Their combination (MNPs/MOFs) is a novel nanomaterial with broad application prospect in sensing field. To improve performance in sensing applications, we have paid great attention to synergistic effects between the two compositions above. Because of the synergistic effects between MNPs and MOFs, sensors on the basis of MNPs/MOFs composites show significant sensing enhancement with respect to stability, selectivity and sensitivity. In this review, various applications for MNPs/MOFs composites in electrochemical sensing, fluorescent sensing, colorimetric sensing, surface-enhanced Raman scattering sensing and chemiluminescence/electrochemiluminescence sensing are focused and summarized. Besides, the synergistic interactions between MNPs and MOFs was investigated. Finally, based on theoretical information from the reports as well as experimental experience, this review offers the challenges and opportunities for future research on MNPs/MOFs composites.

Pseudoaneurysms of the renal arteries are caused by focal rupture or perforation of the arterial wall, resulting in local bleeding. Such pseudoaneurysms can be observed in conditions such as nodular polyarteritis, penetrating or closed renal injury, and medically induced injuries (such as renal puncture biopsy, percutaneous nephrostomy, or partial nephrectomy). Flexible ureteroscopy (FURS) is performed entirely through the urethra to prevent potentially severe kidney damage. Because of this, almost no renal parenchymal hemorrhage occurs after FURS laser lithotripsy. Only four cases had been documented in the literature as of December 2022. In this report, we describe a 53-year-old man with a history of recurrent kidney stones who underwent FURS laser lithotripsy for bilateral kidney stones. The procedure was smoothly performed, and no active bleeding occurred. However, the patient developed recurrent macroscopic hematuria after discharge from the hospital, and renal angiography revealed a pseudoaneurysm in the distal right kidney. The pseudoaneurysm was treated with selective arterial embolization. Serious complications of FURS surgery are rare, particularly the formation of pseudoaneurysms. We report the present case to bring this potential complication to the attention of urologists.

Camelliaoil extracted from the seeds of Camellia oleiferaAbel. is a popular and high-quality edible oil, but its yield is limited by seed setting, which is mainly caused by self-incompatibility (SI). One of the obvious biological features of SI plants is the inhibition of self-pollen tubes; however, the underlying mechanism of this inhibition in C. oleiferais poorly understood. In this study, we constructed a semi-in vivopollen tube growth test (SIV-PGT) system that can screen for substances that inhibit self-pollen tubes without interference from the genetic background. Combined with multi-omics analysis, the results revealed the important role of galloylated catechins in self-pollen tube inhibition, and a possible molecular regulatory network mediated by UDP-glycosyltransferase(UGT) and serine carboxypeptidase-like(SCPL) was proposed. In summary, galloylation of catechins and high levels of galloylated catechins are specifically involved in pollen tube inhibition under self-pollination rather than cross-pollination, which provides a new understanding of SI in C. oleifera. These results will contribute to sexual reproduction research on C. oleiferaand provide theoretical support for improving Camelliaoil yield in production.

Hexaaluminates have been regarded as one of the most promising candidates for methane catalytic combustion due to their superior thermal stability up to 1600 °C. However, the main challenge for their further application lies in the difficulty in enhancing the surface area. Herein, Fe-substituted hexaaluminates (LaFexAl12−xO19, x= 0–2) with high surface areas (44–51 m2g−1) have been successfully synthesized viaa new two-step method for the first time, in which N,N-dimethylformamide (DMF) was used as a difunctional solvent to derive the precipitant dimethylamine and to control the precipitation rates of the three metal cations, leading to superior homogeneity of the precipitate and thus lowering of the phase formation temperature (lower than 1100 °C), and the resin/carbon coating process was employed to separate the crystallization and grain-growth process, avoiding the aggregation of particles. Methane catalytic combustion tests revealed that both the high surface area and the introduction of Fe could result in low apparent activation energy. The LaFeAl11O19catalyst exhibited even higher activity than the conventional Pd/Al2O3catalyst and those prepared by other methods such as the reverse microemulsion method. Mössbauer spectroscopy characterization verified that the catalytic activity of Fe cations should be related to the Fe3+ions in Al(3) sites and Al(5) sites in the mirror planes.

With the introduction of Mg2+into Fe-substituted La-hexaaluminate precursors, a series of monophasic LaMgxFeAl11−xO19(x= 0, 0.3, 0.7, 1) catalysts were prepared and tested as catalysts for CH4catalytic combustion. The results show that the introduction of an appropriate amount of Mg2+(x= 0.7) could significantly enhance the catalytic activity of Fe-substituted La-hexaaluminates and promote the resistance to deactivation after calcination at 1300 °C. The beneficial effect of Mg2+is attributed to the fact that the presence of Mg2+not only increased the distribution of Fe3+in the mirror planes of La-hexaaluminates but also effectively suppressed the generation of catalytically inactive Fe2+. Besides, the LaMg0.7FeAl10.3O19catalyst exhibits excellent stability for 100 h at 700 °C under the reaction conditions.

The application of porous carbon in catalytic transformation of cellulose has received considerable interest owing to increasing energy and environmental pressures. In this mini-review, we first outline the featured properties of porous carbon in catalytic cellulose transformation in terms of porosities and surface functionalities. An interconnected hierarchical structure and enrichment of mesopores are highly desired for reactant, intermediate, and product diffusion; while hydrophilic surfaces are favored in aqueous phase transformation and certain acidic oxygen functionalities play a role of acid sites as well as enhancing the adsorption of feedstock via1,4-glycosidic bonds. We then summarize specific reactions in cellulose transformation in the order of hydrolysis and hydrolytic hydrogenation. In the hydrolysis of cellulose, porous carbon is generally used as a solid acid by taking advantage of its enriched oxygen functionalities, while in the hydrolytic hydrogenation, carbon serves as the support of bifunctional catalysts with active acidic sites. Finally, the synthesis and potential application of specific novel porous carbon materials, such as heteroatom-modified porous carbon and mesoporous carbon composites, are highlighted.

Growing evidence indicates that lncRNAs are involved in the progression of several diseases, including osteoarthritis (OA). However, the role of the lncRNA PVT1 in OA is still unclear. The present study was aimed at exploring the impact of PVT1 on OA progression, along with potential underlying mechanisms. PVT1 expression levels in articular cartilage tissue of OA patients and non-OA patients were evaluated. To assess the proliferation and apoptosis of chondrocytes subject to treatment, PVT1, miR-497, and AKT3 were either knocked down or upregulated in IL-1β-induced chondrocytes. The variables detected were changes in levels of AKT3 and extracellular matrix (ECM)-related factors (including aggrecan, collagen Type II, and MMP-9). Elevated PVT1 levels were found in cartilage tissue of OA patients and IL-1β-induced chondrocytes. It was also observed that PVT1 knockdown and miR-497 upregulation led to enhanced cell proliferation and suppressed apoptosis. In addition, a decrease in aggrecan and collagen type II levels and an increase in MMP-9 levels were observed in IL-1β-induced chondrocytes. A dual luciferase reporter assay was performed to identify the factors that interacted with miR-497, PVT1, and AKT3. It was observed through rescue experiments that enhancing AKT3 expression or knocking down miR-497 could reverse the impacts of PVT1 knockdown in IL-1β-induced chondrocytes. An upregulation of PVT1 is observed in OA patients. On the other hand, PVT1 knockdown can decrease the effects of IL-1β on the proliferation, apoptosis, and expression of ECM-related proteins of chondrocytes through the regulation of the miR-497/AKT3 axis. PVT1 levels are elevated in the cartilage tissue of OA patients and IL-1β-induced chondrocytes. PVT1 knockdown alleviates the effects of IL-1β treatment on the proliferation and apoptosis of chondrocytes and ECM degradation in chondrocytes by regulating the miR-497/AKT3 axis.

Amyloid β peptide (Aβ), a 39 to 43 amino acid fragment of the β-amyloid precursor protein (βAPP), forms insoluble fibrillar accumulation in neurofibrillary tangles and vascular plaques. Aβ has been implicated in neuronal and vascular degeneration in brain regions susceptible to plaque formation because of its cytotoxic effect on neurons and endothelial cells (ECs). The authors used a murine cerebral endothelial cell (CEC) line and primary cultures of bovine CECs to explore the cytotoxic mechanism of Aβ. Aβ 1–40 and Aβ 25–35 peptides caused cell death in a dose-dependent and time-dependent manner. Exposure to either Aβ 25–35 or Aβ 1–40 at 10 μmol/L for 48 hours caused at least 40% cell death. Cerebral endothelial cell death was characterized by nuclear condensation, mitochondrial dysfunction, and nuclear and mitochondrial DNA damage. Aβ 25–35 activated both caspase-8 and caspase-3 in murine CECs. zVAD-fmk, a broad-spectrum caspase inhibitor, prevented Aβ 25–35-induced increase in caspase-3 activity and CEC death. N-acetyl-cysteine, an antioxidant, also prevented Aβ-induced cell death. Together, these findings indicate that Aβ-mediated CEC death is an apoptotic process that is characterized by increased oxidative stress, caspase activation, mitochondrial dysfunction, and nuclear and mitochondrial DNA damage.

Objective To explore the hypermethylated long non-coding (lnc)RNAs involved in bladder carcinogenesis and prognosis.Methods Reduced representation bisulfite sequencing and RNA sequencing were performed on five paired tumor and adjacent normal tissue samples from bladder cancer patients. The differentially methylated regions around transcription start sites and differentially expressed genes, including lncRNAs, were analyzed. Correlations between DNA methylation modifications and the expression of lncRNAs were examined. Survival analysis was surveyed on the GEPIA web server.Results We identified 19,560 hypomethylated and 68,781 hypermethylated differentially methylated regions around transcription start sites in bladder cancer tissues. In total, 2321 differentially expressed genes were found in bladder tumors, among which, 367 were upregulated and 1954 were downregulated. There were 141 downregulated genes involving eight lncRNAs that were consistently hypermethylated, while 24 upregulated genes were consistently hypomethylated. Survival analysis demonstrated that hypermethylation of lncRNAs LINC00683 and MSC-AS1 were associated with poor overall survival in bladder cancer patients.Conclusion Some lncRNAs are controlled by DNA methylation in bladder cancer and they might be important factors in bladder carcinogenesis. Hypermethylated lncRNAs including LINC00683 and MSC-AS1 have the potential to be prognostic biomarkers for bladder cancer.

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