High-power polarization-maintaining LP11-mode fiber laser based on long-period fiber grating for precise welding.

An LP11-mode output all-fiber laser was presented, utilizing long-period fiber gratings (LPFGs) and polarization-maintaining optical fiber (PMF). The LPFG was designed and fabricated, achieving a 90.56% efficiency in LP01 to LP11 mode conversion. Furthermore, the transmission stability of LP11-mode in the PMF was also explored, with the spatial mode overlap ratio exceeding 0.95. Ultimately, the high-power polarization-maintaining (PM) fiber laser, capable of the LP11 mode output, was constructed, with the output power of 600 W and the beam quality M2 of 2.84. During the process of welding a thick Al-plate, the LP11 fiber laser exhibits a notable 1.88 times greater depth of fusion compared to the commercial single-mode fiber laser, when operating at the laser welding head speed of 100 mm/s. For applications demanding non-circular symmetric high-order modes, this research holds substantial potential for widespread adoption within the field of industrial processing.

The impacts of latent profiles and transitions of stresses on adolescent mental health: A person-centred analysis.

Research has demonstrated robust links between adolescent stress and serious psychological problems. The current study aimed to identify latent stress profiles of 1510 adolescents (59.7% females; Mage  = 16.77 years, SD = 0.86) based on five stresses (parental stresses, family environment stresses, academic stresses, teacher stresses, and peer stresses) at three time points (T1/2/3). Moreover, this study would investigate the transition patterns of these profiles over time and examine the associations between the profiles and adverse psychological symptoms (e.g., anxiety, depression, nonsuicidal self-injury [NSSI], and suicidal ideation). Three latent stress profiles were identified, including High-stress profile, Medium-stress profile, and Low-stress profile. The three profiles were significantly different on the levels of T1/2/3 anxiety, depression, NSSI, and suicidal ideation. The profile memberships remained relatively stable across three time points. Notably, the present study found gender differences, with boys were more likely to be in the High-stress profile and to transition from the Medium- to the High-stress profile, compared to girls. Furthermore, left-behind adolescents were more likely to be in the High-stress profile than non-left-behind adolescents. The findings highlight the importance of adopting 'this-approach-fits-this-profile' interventions for adolescents. Parents and teachers are advised to adopt different strategies for girls and boys.

Visualization analysis of research hotspots on structural topology optimization based on CiteSpace.

Structural topology optimization has gained widespread attention due to more possibilities of innovative structural design. The current research focus/hotspots, application areas, main research scholars, institutions and the countries involved in structural topology optimization are visually presented through clustering and visual analysis based on CiteSpace. The four metric dimensions of the literatures in this paper are as follows: annual quantity of papers and core countries, core authors and co-authors' institutions, hotspots and burst terms, and the highly co-cited papers. The results show the research hotspots in this field are concentrated on keywords such as "level set method", "sensitivity analysis", "homogenization", "genetic algorithm", etc. Regarding the research frontier, "moving morphable component (MMC)", "additive manufacturing (AM)" and "deep learning" are hot topics. In addition, Y. Sui, Z. Kang and O. Sigmund, etc. have high publications. M. Bendsøe and O. Sigmund have high citations. Dalian University of Technology, Technical University of Denmark, etc. are prominent institutions. Moreover, China accounts for more than 34% in the terms of original WOS literatures following by the USA and Australia. This paper could identify structural topology optimization development patterns for the scholars concerned with this field, especially novices, to quickly focus and track the research priorities.

Prediction of In-Flight Particle Properties and Mechanical Performances of HVOF-Sprayed NiCr-Cr3C2 Coatings Based on a Hierarchical Neural Network.

High-velocity oxygen fuel (HVOF) spraying is a promising technique for depositing protective coatings. The performances of HVOF-sprayed coatings are affected by in-flight particle properties, such as temperature and velocity, that are controlled by the spraying parameters. However, obtaining the desired coatings through experimental methods alone is challenging, owing to the complex physical and chemical processes involved in the HVOF approach. Compared with traditional experimental methods, a novel method for optimizing and predicting coating performance is presented herein; this method involves combining machine learning techniques with thermal spray technology. Herein, we firstly introduce physics-informed neural networks (PINNs) and convolutional neural networks (CNNs) to address the overfitting problem in small-sample algorithms and then apply the algorithms to HVOF processes and HVOF-sprayed coatings. We proposed the PINN and CNN hierarchical neural network to establish prediction models for the in-flight particle properties and performances of NiCr-Cr3C2 coatings (e.g., porosity, microhardness, and wear rate). Additionally, a random forest model is used to evaluate the relative importance of the effect of the spraying parameters on the properties of in-flight particles and coating performance. We find that the particle temperature and velocity as well as the coating performances (porosity, wear resistance, and microhardness) can be predicted with up to 99% accuracy and that the spraying distance and velocity of in-flight particles exert the most substantial effects on the in-flight particle properties and coating performance, respectively. This study can serve as a theoretical reference for the development of intelligent HVOF systems in the future.

A multi-scale pooling convolutional neural network for accurate steel surface defects classification.

Surface defect detection is an important technique to realize product quality inspection. In this study, we develop an innovative multi-scale pooling convolutional neural network to accomplish high-accuracy steel surface defect classification. The model was built based on SqueezeNet, and experiments were carried out on the NEU noise-free and noisy testing set. Class activation map visualization proves that the multi-scale pooling model can accurately capture the defect location at multiple scales, and the defect feature information at different scales can complement and reinforce each other to obtain more robust results. Through T-SNE visualization analysis, it is found that the classification results of this model have large inter-class distance and small intra-class distance, indicating that this model has high reliability and strong generalization ability. In addition, the model is small in size (3MB) and runs at up to 130FPS on an NVIDIA 1080Ti GPU, making it suitable for applications with high real-time requirements.

Directional sweat transport of monolayered cotton-fabrics fabricated through femtosecond-laser induced hydrophilization for personal moisture and thermal management.

Personal moisture and thermal management fabrics that can facilitate sweat removal and regulating skin temperature are highly desired for improving human comfort and performance. Here, we demonstrate a hydrophobic/superhydrophilic Janus cotton-fabric through femtosecond-laser-induced hydrophilization. The engineering Janus cotton-fabric can unidirectionally transport human sweat spontaneously. More importantly, the Janus fabrics can maintain human body temperature 2-3 °C lower than the conventional cotton fabrics, implying the cooling effect in thermal environment. In addition, the Janus fabric has lower wet skin adhesion in comparison with a conventional hydrophilic cotton fabric. The water vapor transmission rate (WVTR) of a Janus fabric is comparable to the traditional hydrophilic cotton fabrics. Overall, the successful creation of the Janus fabrics provides new insights for the development of moisture-wicking/thermal-management fabrics for satisfying the growing demand of personal comfort.

Application of machine learning and its improvement technology in modeling of total energy consumption of air conditioning water system.

Accurate energy consumption model is the basis of energy saving optimal control of air conditioning system. The existing energy consumption model of air conditioning water system mainly focuses on a certain equipment or a part of the cycle. However, the coupling between water system equipment will affect the setting of optimal energy consumption of equipment. It is necessary to establish the energy consumption model of water system as a whole. However, air conditioning water system is a highly nonlinear complex system, and its precise physical model is difficult to establish. The main goal of this paper is to develop an accurate machine learning modeling and optimization technique to predict the total energy consumption of air conditioning water system by using the actual operation data collected. The main contributions of this work are as follows: (1) Three commonly used machine learning techniques, artificial neural network (ANN), support vector machine (SVM) and classification regression tree (CART), are used to build prediction models of air conditioning water system energy consumption. The results show that all the three models have fast training speed, but the ANN model has better performance in cross-validation. (2) The improved differential evolution algorithm was used to optimize the parameters (initial weights and thresholds) of the ANN, which solved the problem that the ANN is easy to fall into the local optimal solution. The simulation results show that the root mean square error (RMSE) of the improved model decreases by 20.5%, the mean absolute error (MAE) decreases by 30.2%, and the coefficient of determination (R2) increases from 0.9227 to 0.9512. (3) Sensitivity analysis of the established optimization model shows that chilled water flow, chilled water outlet temperature and air conditioning load are the main factors affecting the total energy consumption.

An improved method combined SMC and MLESO for impedance control of legged robots' electro-hydraulic servo system.

The electro-hydraulic servo system (EHSS) drives the hydraulic quadruped robot, which has the advantages such as high load capacity, fast response velocity, and powerful motion ability. EHSS of single leg consists of three sets of hydraulic drive unit (HDU), which is the joint driver. As a result, HDU control is the fundamental control of the hydraulic quadruped robot, and it controls the robot's motion performance directly. In order to improve the control accuracy and adaptability to different working conditions of impedance control for HDU, a composite control method combining sliding mode control (SMC) and model-based linear extended state observer (MLESO), which is called SMC-MLESO, is designed in this paper. Firstly, the chattering problem of SMC is improved by designing a novel composite reaching law and adding total disturbance to sliding mode control law. Secondly, the parameters of sliding mode surface are calculated by the optimal control. The parameters of MLESO are calculated by the bandwidth of the controller. And the known model of the system is added to observer to reduce the influence of sensor noise. Finally, comparative experiments show that SMC-MLESO has a good control effect. The maximum error of using SMC-MLESO is 0.101 mm and the biggest change of the maximum error is 36.5% under different working conditions, which is better than PI+Gcp and PI+Gcp+Gfp(The two controllers were designed by the author's previous research, which was published by Journal of the Franklin Institute).

Nonsmooth Continuous-Time Distributed Algorithms for Seeking Generalized Nash Equilibria of Noncooperative Games via Digraphs.

In this article, the problem of distributed generalized Nash equilibrium (GNE) seeking in noncooperative games is investigated via multiagent networks, where each player aims to minimize his or her own cost function with a nonsmooth term. Each player's cost function and feasible action set in the noncooperative game are both determined by actions of others who may not be neighbors, as well as his/her own action. Particularly, feasible action sets are constrained by private convex inequalities and shared linear equations. Each player can only have access to his or her own cost function, private constraint, and a local block of shared constraints, and can only communicate with his or her neighbours via a digraph. To address this problem, a novel continuous-time distributed primal-dual algorithm involving Clarke's generalized gradient is proposed based on consensus algorithms and the primal-dual algorithm. Under mild assumptions on cost functions and graph, we prove that players' actions asymptotically converge to a GNE. Finally, a simulation is presented to demonstrate the effectiveness of our theoretical results.

Erythrocyte membrane bioengineered nanoprobes via indocyanine green-directed assembly for single NIR laser-induced efficient photodynamic/photothermal theranostics.

Traditional combinational photodynamic therapy (PDT) and photothermal therapy (PTT) were limited in clinical therapy of cancer due to exceptionally low drug payload and activation by light with separate wavelengths. We have accidentally discovered that zinc phthalocyanine (ZNPC, a typical hydrophobic photosensitizer) and indocyanine green (ICG, a clinically approved fluorescence probe) could be co-assembled into carrier-free nanodrugs (almost 100 wt%) for single NIR laser-induced efficient PDT/PTT. Interestingly, ICG could act as "transformers" for modulating the geometric shape of ZNPC/ICG co-assembling structures from needle-like/spindle-like structure via cubic structure finally to spherical structure. Unfortunately, the nanodrugs suffered from rapid immune clearance. The ZNPC-ICG nanoprobes were further embedded into the erythrocyte membrane (RBC)-camouflaged framework. The designed ZNPC-ICG@RBC could be efficiently accumulated within the tumor sites (continue for ~60 h) and rapidly internalized into cancer cells upon laser irradiation rather than macrophage RAW264.7 cells. Compared with the free ZnPC or ICG, the biomimetic ZNPC-ICG@RBC nanoprobes exhibited amplified therapeutic effects by simultaneously producing ROS and hyperthermia, thereby synergistically improving antitumor efficiency and eliminating the tumors without any regrowth under the guidance of fluorescence imaging. The co-delivery of ZnPC and ICG via a biomimetic carrier-free system might be a promising strategy for bimodal phototherapy of cancer.

Distributed Algorithms Involving Fixed Step Size for Mixed Equilibrium Problems With Multiple Set Constraints.

In this brief, the problem of distributively solving a mixed equilibrium problem (EP) with multiple sets is investigated. A network of agents is employed to cooperatively find a point in the intersection of multiple convex sets ensuring that the sum of multiple bifunctions with a free variable is nonnegative. Each agent can only access information associated with its own bifunction and a local convex set. To solve this problem, a distributed algorithm involving a fixed step size is proposed by combining the mirror descent algorithm, the primal-dual algorithm, and the consensus algorithm. Under mild conditions on bifunctions and the graph, we prove that all agents' states asymptotically converge to a solution of the mixed EP. A numerical simulation example is provided for demonstrating the effectiveness of theoretical results.

Self-Distinguishing and Stimulus-Responsive Carrier-Free Theranostic Nanoagents for Imaging-Guided Chemo-Photothermal Therapy in Small-Cell Lung Cancer.

Lack of tumor targeting and low drug payload severely impedes various nanoagents further employed in small-cell lung cancer (SCLC). Therefore, how to develop a new targeting ligand and enhance drug payload has been an urgent need for SCLC therapy. Herein, we first sift and verify that capreomycin (Cm) has a high affinity toward CD56 receptors overexpressed on SCLC cells. Motivated by the concept of self-targeted drug delivery, Cm is selected as the specific targeting ligand toward CD56 receptors and chemodrug doxorubicin (Dox) is adopted to be covalently linked via the redox-responsive disulfide linkage. The synthesized self-distinguishing prodrug (Dox-ss-Cm) and FDA-approved photosensitizer indocyanine green (ICG) as structural motifs can be self-assembled into theranostic nanoagents (ICG@Dox-ss-Cm NPs) within an aqueous solution. Such carrier-free nanoagents with high drug payload can exert targeted on-demand drug release under multiple stimuli of intracellular lysosomal acidity, glutathione (GSH), and an external near-infrared (NIR) laser. Besides, our nanoagents can be specifically self-targeted to SCLC sites in vivo and self-distinguishing via SCLC cells in vitro; thus, they decrease the undesirable effects on normal tissues and organs. Further in vitro and in vivo studies uniformly confirm that such nanoagents show highly synergistic effects for SCLC chemo-photothermal therapy (PTT) under the precise guidance of NIR fluorescence (NIRF)/photoacoustic (PA) imaging. Taken together, our work can provide a novel and promising strategy for the targeted treatment of SCLC.

Design of light/ROS cascade-responsive tumor-recognizing nanotheranostics for spatiotemporally controlled drug release in locoregional photo-chemotherapy.

Carrier-free nanotheranostics with high drug loading and no carrier-related toxicity are highly promising cancer therapy agents. However, the limited tumor accumulation and poorly controlled drug release of these nanotheranostics continue to be major challenges that restrict clinical applications. In this study, we develop a tumor-recognizing carrier-free nanotheranostic with light/reactive oxygen species (ROS) cascade-responsiveness for spatiotemporally selective photo-chemotherapy. The nanotheranostic is constructed by co-assembly of the indocyanine green (ICG) photosensitizer and the mannose-thioketal-doxorubicin conjugate (MAN-TK-DOX) (abbreviated as IMTD), efficiently preventing premature DOX leakage during blood circulation while reducing nonspecific damage to normal tissues/cells. Once accumulated in tumor tissues, IMTD rapidly diffuses into cancer cells via lectin receptors-mediated endocytosis. Photoacoustic/fluorescence-imaging-guided laser irradiation induces local hyperthermia and ROS generation in tumor cells, thereby promoting apoptosis. Together, the ICG-generated ROS and the endogenous ROS in cancer cells synergistically enhance DOX release, resulting in more efficient chemotherapeutic effects. The in vitro and in vivo results consistently demonstrate that IMTD achieves superior tumor accumulation, highly controllable drug release, and synergetic photo-chemotherapy. Therefore, the co-assembly of an ROS-sensitive targeting ligand-chemodrug conjugate and a photosensitizer could be used to develop spatiotemporally light-activatable nanotheranostics for precision cancer therapy. STATEMENT OF SIGNIFICANCE: Synergistic phototherapy and chemotherapy have been considered as a promising cancer treatment modality to maximize the therapeutic efficacy. Unfortunately, most nanodrugs consisting of chemotherapeutic drug and photosensitizer suffer from suboptimal tumor accumulation and poorly controlled drug release, which results in reduced therapeutic outcome. In this study, Mannose (MAN) was conjugated to the anticancer drug doxorubicin (DOX) by a ROS-sensitive thioketal linker (TK), the obtained amphiphilic MAN-TK-DOX could serve as an ideal self-carrier material to deliver photosensitizer, thus to achieve high-efficient tumor-targeting, spatiotemporal controlled drug release, and superior antitumor effect. We believe that the ROS-sensitive amphiphilic targeting ligand-chemodrug conjugate could be developed as a universal approach for designing tumor-targeted nanodrugs with precisely controlled drug release.

Tumor-Specific Endogenous FeII-Activated, MRI-Guided Self-Targeting Gadolinium-Coordinated Theranostic Nanoplatforms for Amplification of ROS and Enhanced Chemodynamic Chemotherapy.

Low drug payload and lack of tumor-targeting for chemodynamic therapy (CDT) result in an insufficient reactive oxygen species (ROS) generation, which seriously hinders its further clinical application. Therefore, how to improve the drug payload and tumor targeting for amplification of ROS and combine it with chemotherapy has been a huge challenge in CDT. Herein, methotrexate (MTX), gadolinium (Gd), and artesunate (ASA) were used as theranostic building blocks to be coordinately assembled into tumor-specific endogenous FeII-activated and magnetic resonance imaging (MRI)-guided self-targeting carrier-free nanoplatforms (NPs) for amplification of ROS and enhanced chemodynamic chemotherapy. The obtained ASA-MTX-GdIII NPs exhibited extremely high drug payload (∼96 wt %), excellent physiological stability, long circulating ability (half-time: ∼12 h), and outstanding tumor accumulation. Moreover, ASA-MTX-GdIII NPs could be specifically uptaken by tumor cells via folate (FA) receptors and subsequently be disassembled via lysosomal acidity-induced coordination breakage, resulting in drug burst release. Most strikingly, the produced ASA could be catalyzed by tumor-specific overexpressed endogenous FeII ions to generate sufficient ROS for enhancing the main chemodynamic efficacy, which could exert a synergistic effect with the assistant chemotherapy of MTX. Interestingly, ASA-MTX-GdIII NPs caused a lower ROS generation and toxicity on normal cell lines that seldom expressed endogenous FeII ions. Under MRI guidance with assistance of self-targeting, significantly superior synergistic tumor therapy was performed on FA receptor-overexpressed tumor-bearing mice with a higher ROS generation and an almost complete elimination of tumor. This work highlights ASA-MTX-GdIII NPs as an efficient chemodynamic-chemotherapeutic agent for MRI imaging and tumor theranostics.

Redox-Responsive and Dual-Targeting Hyaluronic Acid-Methotrexate Prodrug Self-Assembling Nanoparticles for Enhancing Intracellular Drug Self-Delivery.

The clinical translation of methotrexate (MTX) is limited because of low aqueous solubility, poor bioavailability, low uptake efficiency, and toxicity concerns. Herein, dual-acting MTX (not only targeting folate receptors but also killing cells via inhibition of intracellular folate metabolism) and hyaluronic acid (HA, targeting CD44 receptors) were selected to be covalently linked by the redox-responsive disulfide bond. The synthesized prodrug (HA-SS-MTX) as a molecular structural motif could self-assemble into simple yet multifunctional nanoparticles (HA-SS-MTX NPs) in aqueous solution. The HA-SS-MTX NPs displayed an average diameter of ∼110 nm with a uniformly spherical shape and maintained stability in different physiological media. Moreover, the HA-SS-MTX NPs could exhibit a sharp redox-dependent response for rapid structure disassembly and sequential MTX release compared to the redox-irresponsive group (HA-ADH-MTX NPs). Furthermore, the results of confocal microscopy and flow cytometry verified that the nanosystems were selectively uptaken by cancer cells via folate and CD44 receptor-mediated internalization through the dual-active targeting mechanism. In addition, HA-SS-MTX NPs could accumulate within tumor sites for a longer period. Notably, in vitro and in vivo antitumor results demonstrated that HA-SS-MTX NPs significantly promoted the death of cancer cells and enhanced the inhibition of tumor growth while reducing the toxicity as compared to MTX and HA-ADH-MTX NPs. Therefore, the smart HA-SS-MTX NPs as the simple and efficient platform have great potential in tumor-targeting drug delivery and therapy.

Light/pH-Triggered Biomimetic Red Blood Cell Membranes Camouflaged Small Molecular Drug Assemblies for Imaging-Guided Combinational Chemo-Photothermal Therapy.

Nanoparticles camouflaged by red blood cell (RBC) membranes have attracted considerable attention owing to reservation of structure of membrane and surface proteins, endowing prominent cell-specific function including biocompatibility, prolonged circulation lifetime, and reduced reticular endothelial system (RES) uptake ability. Considering the drawbacks of carrier-free nanomedicine including the serious drug burst release, poor stability, and lack of immune escape function, herein we developed and fabricated a novel RBC membranes biomimetic combinational therapeutic system by enveloping the small molecular drug coassemblies of 10-hydroxycamptothecin (10-HCPT) and indocyanine green (ICG) in the RBC membranes for prolonged circulation, controlled drug release, and synergistic chemo-photothermal therapy (PTT). The self-reorganized RBCs@ICG-HCPT nanoparticles (NPs) exhibited a diameter of ∼150 nm with core-shell structure, high drug payload (∼92 wt %), and reduced RES uptake function. Taking advantage of the stealth functionality of RBC membranes, RBCs@ICG-HCPT NPs remarkably enhanced the accumulation at the tumor sites by passive targeting followed by cellular endocytosis. Upon the stimuli of near-infrared laser followed by acidic stimulation, RBCs@ICG-HCPT NPs showed exceptional instability by heat-mediated membrane disruption and pH change, thereby triggering the rapid disassembly and accelerated drug release. Consequently, compared with individual treatment, RBCs@ICG-HCPT NPs under dual-stimuli accomplished highly efficient apoptosis in cancer cells and remarkable ablation of tumors by chemo-PTT. This biomimetic nanoplatform based on carrier-free, small molecular drug coassemblies integrating imaging capacity as a promising theranostic system provides potential for cancer diagnosis and combinational therapy.

Small Molecular Theranostic Assemblies Functionalized by Doxorubicin-Hyaluronic Acid-Methotrexate Prodrug for Multiple Tumor Targeting and Imaging-Guided Combined Chemo-Photothermal Therapy.

Because of high drug payload and minimized burden of foreign materials in the course of metabolism and excretion, carrier-free nanomedicine based on self-assembly of small-molecule therapeutic agents has attracted considerable attention in cancer therapy. However, obstacles still remained, such as lack of targeting efficiency, poor physiological stability, and serious drug burst release. Herein, we developed a self-dual-targeting prodrug conjugate by coupling methotrexate (MTX) and doxorubicin (DOX) to a hyaluronic acid (HA) backbone which enveloped the small molecular drug coassemblies of DOX and indocyanine green for specific targeting and imaging-guided chemo-photothermal therapy (PTT). The constructed nanosystems exhibited a diameter of ∼200 nm, superior physiological stability, and improved photothermal effect. Taking advantage of functionality of MTX-HA-DOX conjugate, the nanosystems remarkably enhanced the accumulation in the tumor regions by enhanced penetration and retention effect and CD44/folate receptor-mediated endocytosis. Upon the stimuli of acid, the nanosystems showed the rapid disassembly followed by the accelerated drug release. Consequently, the nanosystems demonstrated highly efficient apoptosis in cancer cells and remarkable tumor ablation by synergy between chemotherapy and PTT upon the irradiation of near-infrared laser. The multifunctional nanosystems based on small molecular theranostic assemblies could provide a promising potential in developing dual-targeting drug delivery and imaging-guided combinational therapy.

Tumor Microenvironment-Activated and Viral-Mimicking Nanodrugs Driven by Molecular Precise Recognition for dNTP Inhibition-Induced Synergistic Cancer Therapy.

The medical application of nanotechnology is promising for cancer chemotherapy. However, most of the small-molecule drug assemblies still have such disadvantages as serious drug leakage and nonideal synergistic mechanisms, resulting in undesired therapeutic effect. Both nucleoside analogue-based clofarabine (CA) and methotrexate (MTX) were used as the first-line anticancer medication. However, a single-agent chemotherapy still faced many challenges including low bioavailability and toxic side effects to normal tissues due to nonspecific biodistribution of drugs. Herein, we designed and fabricated novel viral-mimicking and carry-free nanodrugs (CA-MTX NPs) via molecular recognition-driven precise self-assembly between CA and MTX. After introduction of mild acid-responsive PEG-lipid on the surface of CA-MTX NPs, the synthetic nanodrugs with a diameter of ∼150 nm exhibited tumor microenvironment-activated characteristics and self-targeting property. The results suggested that our nanodrugs could achieve superior tumor accumulation and synergistically promote the tumor suppression by collaboratively inhibiting dNTP pools. We foresaw that the well-designed smart nanodrugs delivery system would open a new avenue in synergistic cancer therapeutics.

An improved force-based impedance control method for the HDU of legged robots.

Hydraulic drive mode enables legged robots to have excellent characteristics, such as greater power-to-weight ratios, higher load capacities, and faster response speeds than other robots. Nowadays, highly integrated valve-controlled cylinder, called hydraulic drive unit (HDU), is employed to drive the joints of these robots. However, various robot control issues exist. For example, during the walking process of legged robots, different obstacles are encountered, making it difficult to control such robots because the load characteristics of the ends of their feet change with the environment. Furthermore, although the adoption of HDU has resulted in high-performance robot control, the hydraulic systems of these robots still have problems, such as strong nonlinearity, and time-varying parameters. Consequently, robot control is very difficult and complex. This paper proposes an improved second-order dynamic compliance control system, impedance control, for HDU. The control system is designed to rectify the issues affecting the impedance control accuracy of the dynamic compliance serial-parallel composition between the HDU force control inner loop and the impedance control outer loop. Specifically, it consists of a compliance-enhanced controller and a feedforward compensation controller for the force control inner loop. Furthermore, the dynamic compliance composition of the inner and outer HDU control loops is rearranged. The results of experiments conducted indicate that the proposed method significantly improves the control accuracy compared to that of traditional force-based impedance control.