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Carbon nanotube (CNT)-based ionizing gas sensors are susceptible to fluctuations in gas detection results due to variations in temperature, necessitating temperature compensation to align with real-world application standards. This article presents an experimental determination of the single-value sensitivity of the sensor to hydrogen (H2), where the collecting current of the sensor was observed to decrease with rising hydrogen concentration and temperature. We introduce a novel temperature compensation model based on the least-squares support vector machine optimized by the whale optimization algorithm (WOA-LSSVM), which executes temperature compensation concurrently with hydrogen concentration detection. Post-implementation of temperature compensation, there has been a significant reduction in the temperature influence coefficient of the sensor by three orders of magnitude, resulting in a substantial enhancement in the sensor’s detection performance.

Snapshot compressive imaging (SCI) is a promising technique that captures a 3-D hyperspectral image (HSI) by a 2-D detector in a compressed manner. The ill-posed inverse process of reconstructing the HSI from their corresponding 2-D measurements is challenging. However, current approaches either neglect the underlying characteristics, such as high spectral correlation, or demand abundant training datasets, resulting in an inadequate balance among performance, generalizability, and interpretability. To address these challenges, in this article, we propose a novel approach called LR2DP that integrates the model-driven low-rank prior and data-driven deep priors for SCI reconstruction. This approach not only captures the spectral correlation and deep spatial features of HSI but also takes advantage of both model-based and learning-based methods without requiring any extra training datasets. Specifically, to preserve the strong spectral correlation of the HSI effectively, we propose that the HSI lies in a low-rank subspace, thereby transforming the problem of reconstructing the HSI into estimating the spectral basis and spatial representation coefficient. Inspired by the mutual promotion of unsupervised deep image prior (DIP) and trained deep denoising prior (DDP), we integrate the unsupervised network and pre-trained deep denoiser into the plug-and-play (PnP) regime to estimate the representation coefficient together, aiming to explore the internal target image prior (learned by DIP) and the external training image prior (depicted by pre-trained DDP) of the HSI. An effective half-quadratic splitting (HQS) technique is employed to optimize the proposed HSI reconstruction model. Extensive experiments on both simulated and real datasets demonstrate the superiority of the proposed method over the state-of-the-art approaches.

Objective: The high prevalence of osteoarthritis emphasizes the need for a cost-effective and accessible method for its early diagnosis. Recently, the portability and affordability of very-low-field (VLF) magnetic resonance imaging (MRI, 10–100 mT) have caused it to gain popularity. Nevertheless, there is insufficient evidence to quantify early degenerative changes in cartilage using VLF MRI. This study assessed the potential of T1ρ and T2 mapping for detecting degenerative changes in porcine cartilage specimens using a 50 mT MRI scanner. Methods: T2- and T1ρ-weighted images were acquired using a 50 mT MRI scanner with 2D spin-echo and triple-refocused T1ρ preparation sequences. MRI scans of porcine cartilage were also acquired using a 3 T MRI scanner for comparison. A mono-exponential algorithm was applied to fit a series of T2- and T1ρ-weighted images. T2 values for CuSO4·5H2O solutions measured via Carr–Purcell–Meiboom–Gill (CPMG) and spin-echo sequences were compared to verify the algorithm's reliability. The nonparametric Kruskal-Wallis statistical test was used to compare T2 and T1ρ values. Experimental repeatability was assessed using the root-mean-square of the coefficient of variation (rmsCV). Results: T2 values of the CuSO4·5H2O solutions obtained using the spin-echo sequence showed differences within 2.3% of those obtained using the CPMG sequence, indicating the algorithm's reliability. The T1ρ values for varying concentrations of agarose gel solutions were higher than the T2 values. Furthermore, 50 mT and 3 T MRI results showed that both the T1ρ and T2 values were significantly higher for porcine cartilage degraded for 6 h vs intact cartilage, with p-values of 0.006 and 0.01, respectively. Our experimental results showed good reproducibility (rmsCV < 8%). Conclusion: We demonstrated the feasibility of quantitative cartilage imaging via T2 and T1ρ mapping at 50 mT MRI for the first time.

This article presents a resilient formation control framework for networked nonholonomic mobile robots (NMRs) that enables long-time recovery abilities subject to denial-of-service (DoS) attacks by taking advantage of the Koopman operator. Due to the intermittent interruption of communication under DoS, the transmitted signals among the networked NMRs are incomplete. In the lifted space, the infinite-dimensional Koopman operator is employed to capture a linear characteristic of the missed signals from the available signals. Specifically, a data-driven cost function is developed to approximate the infinite-dimensional Koopman operator, allowing long-term recovery capabilities for the missed signals, where the useful historical data is identified by an event-triggered mechanism (ETM). Then, the least-squares method is implemented to calculate a finite-dimensional approximation of the Koopman operator. Once DoS attacks are active, the missed signals are recovered forward from the latest received signals through the approximation Koopman operator. Furthermore, according to the recovered and transmitted signals, the resilient formation controller with a variable gain takes into account the convergence rate and the steady state formation error. The Lyapunov theorem is introduced to prove that the formation error quickly converges to the minor compact set. A distributed DoS attack example is conducted to validate the efficiency and superiority in numerical simulation, and the proposed method is implemented on the real networked NMRs.

As a pioneering multi-DOF motor, the Integrated Magnetic Suspension Spherical Induction Motor (IMSSIM) presents many advantages. Nonetheless, the IMSSIM presents a complex magnetic coupling challenge. This paper addresses the magnetic coupling issue in IMSSIM through a comprehensive investigation using the 3D finite element method (FEM). The magnetic coupling coefficients which reflect the magnetic coupling degree are proposed and analyzed. Moreover, the dynamic coupling effect inside the IMSSIM is analyzed and studied. Finally, accuracy of FEM is verified by prototype experiments.

Purpose: Two-dimensional speckle tracking echocardiography is a novel ultrasound technique, which can detect early subclinical myocardial dysfunction with high sensitivity. The purpose of this study was to explore the value of speckle tracking echocardiography in the evaluation of subclinical myocardial injury in patients with Cushing’s syndrome. Methods: 35 patients with Cushing’s syndrome and 29 healthy controls matched for age, sex, BMI, and systolic blood pressure were included in the study. All subjects were assessed using both conventional Doppler echocardiography and speckle tracking echocardiography. Among patients, they were further divided into inactive group (n = 7) and active group (n = 28) based on cortisol levels. Trend analysis was used among patients in different disease activity. Correlation analysis and linear regression analysis were used to explore influence factors related to subclinical myocardial dysfunction. Results: Left ventricular ejection fraction value showed no statistical difference between patients Cushing’s syndrome and control group. However, GLS and LVSD, show significant differences in Cushing’s syndrome group. Also, among active Cushing’s syndrome group, inactive Cushing’s syndrome group and control group, GLS (−15.4 ± 3.0 vs −18.1 ± 3.1 vs-19.4 ± 2.4, P < 0001) and LVSD (48.9 ± 21.5 vs 43.5 ± 17.9 vs 28.5 ± 8.3, P < 0001) changed significantly with the disease activity status. In addition, GLS and LVSD were both linearly corrected with 24-hour urinary cortisol level. Conclusion: GLS and LVSD are sensitive parameters in detecting and monitoring subclinical myocardial systolic dysfunction in patients with Cushing’s syndrome. Myocardial injury is linearly correlated with cortisol level, which can be partially reversed after the biochemical control of cortisol.

A cell membrane-derived vesicle (MV) that has cell-mimicking features with characteristic functionalities holds vast appeal for biomimetic nanomedicine and drug delivery but suffers from a major limitation of innate fragility and poor stability. Herein, we report a lipid-anchoring strategy for stabilizing MV for enhanced drug delivery. An array of amphiphilic mono-acyl phosphatidylcholines (MPCs) with specific hydrophobic moieties are synthesized and readily engineered on MV based on their commendable aqueous solubility and efficient membrane insertability. Incorporation of MPCs containing rigid ring structures in the hydrophobic segment demonstrates the potency of stabilizing MV by the combined ordering and condensing effects. The optimized MPC-stabilized MV exhibits prolonged circulation in the bloodstream, elevated accumulation within a tumor, and enhanced therapeutic effects of chemotherapeutic and photothermal drugs. Moreover, doxorubicin-loaded MV, engineered with mono-all-transretinoyl phosphatidylcholine as an MV stabilizer and a therapeutic prodrug, potently suppresses growth and metastasis of high-stemness tumors.

Microstructural evolution and dynamic recrystallization (DRX) mechanisms of a Ti−48Al−2Cr−2Nb (at.%) alloy prepared by selective electron beam melting (SEBM) during hot deformation at 1150 °C and 0.1 s−1were investigated by hot compression tests, optical microscope (OM), scanning electron microscope (SEM), electron back-scattered diffraction (EBSD) and transmission electron microscope (TEM). The results show that the initial microstructure of the as-SEBMed alloy exhibits layers of coarse γgrains and fine γ+α2+(α2/γ) lamellar mixture grains alternately along the building direction. During the early stage of hot deformation, deformation twins tend to form within the coarse grains, facilitating subsequent deformation, and a small number of DRX grains appear in the fine-grained regions. With the increase of strain, extensive DRX grains are formed through different DRX mechanisms in both coarse and fine-grained regions, involving discontinuous dynamic recrystallization mechanism (DDRX) in the fine-grained regions and a coexistence of DDRX and continuous dynamic recrystallization (CDRX) in the coarse- grained regions.

In this article, robust iterative learning controls are proposed for a flexible wing with iteration-varying disturbances and references having unknown coefficients. The unknown basis functions of the disturbances and references are supposed to be from an exosystem with unknown initial values. Then, a higher internal model is used to describe the unknown iteration-varying property. A strongly coupled reference model, inspired by the fourth-order ODEs of the Timoshenko beam equation, is firstly proven to admit bounded solutions. In this case, feedforward controls are designed for the flexible wing system, where the iteration-varying input disturbances are divided into unknown constants and known iteration-varying states. By finding two adaption laws, robust iterative learning controls are designed to guarantee the convergence of the tracking errors along the iteration axis, as well as the boundedness of the closed-loop system. Simulation examples are further provided for the robust output regulation of the wing.

This article investigates the input-to-state stability and integral input-to-state stability for the switched nonlinear neutral systems (SNNSs) with multiple time-varying delays (MTVDs) and asynchronous switching. According to the fact that the switching signals of the controllers and the subsystems are inconsistent, novel stability criteria on the input-to-state stability and integral input-to-state stability properties for SNNSs with MTVDs and the asynchronous switching phenomenon are presented by multiple Lyapunov-Krasovskii functionals, the merging switching signal, and the mode-dependent average dwell time technique. Compared with the existing related works, our results are less conservative. Meanwhile, our proposed works not only investigate the effects of switches and neutral terms on the stability property for SNNSs but also study the case of the systems with MTVDs and asynchronous switching. Finally, two practical examples, including the practical coupled mass-spring-damper-pendulum system, are presented to show the effectiveness of our results.

This article studies the constrained optimization problem of integrator chain multiagent systems from the distributed perspective. Particularly, all the agents collaborate to find an optimal solution of a global objective function summed by multiple local ones, each of which is just convex and belongs to an individual agent. However, the potential optimal solutions are simultaneously subject to set constraints and two kinds of equality constraints, i.e., individual equality constraint and aggregate equality constraint, whereas their involved constraint parameters are privately available to individual agents. With a proper coordinate transformation, a distributed optimization protocol is synthesized by introducing proper internal dynamics. Under the Lyapunov framework, it is shown with a convex theory that the synthesized distributed protocol enables the multiagent system to achieve the concerned constrained optimization objective. An example is finally given to confirm the optimization effectiveness.

We report a Changhsingian radiolarian assemblage from the Rencunping section of the Dalong Formation, in the northern margin of the Yangtze Platform, South China. The assemblage is composed of 37 species belonging to 20 genera, including two new species (Copicyntroides rencunpingensisn. sp. and Copicyntroides subplanusn. sp.). Together with the well documented radiolarian faunas of the Dalong Formation around the Yangtze Platform, we applied Sørensen Coefficient, an incidence-based measures of relative similarity, to examine the similarity of species associations among the sections of the Dalong Formation, including those at Rencunping, Shangsi, Hushan, Pingdingshan, Xinmin and Dongpan. We find that 165 species have been reported in the entire Dalong Formation of all sections, with variable paleobiogeographic setting from section to section within the same formation. The Sørensen Coefficient showed a high similarity between the Rencunping and Pingdingshan sections and low similarity in the Xinmin or Dongpan sections. This is interpreted as due to water mass separation between the northern and southern sides of the Yangtze Platform, probably by the physical barrier of the shallow carbonate platform in the region. We reviewed taxonomic groups and depositional conditions in each section, and determined “low latitudinal common species” or “cosmopolitan” species including Entactinia itsukaichiensis, Albaillella angusta, A. excelsa, A. protolevis, A. triangularis, Ishigaum obesum, I. trifustis, Trilonche crassispinosa, Triplanospongos musashiensisand “Hegleria-shaped” radiolarian. The radiolarian fauna of Rencunping was concluded as a typical fauna in the Dalong Formation, and its higher similarity to faunas from Japanese Islands and Southeast Asia indicates close paleogeographic positions and similar paleogeographic environments in these areas during the Changhsingian.

New types of aerial robots (NTARs) have found extensive applications in the military, civilian contexts, scientific research, disaster management, and various other domains. Compared with traditional aerial robots, NTARs exhibit a broader range of morphological diversity, locomotion capabilities, and enhanced operational capacities. Therefore, this study defines aerial robots with the four characteristics of morphability, biomimicry, multi-modal locomotion, and manipulator attachment as NTARs. Subsequently, this paper discusses the latest research progress in the materials and manufacturing technology, actuation technology, and perception and control technology of NTARs. Thereafter, the research status of NTAR systems is summarized, focusing on the frontier development and application cases of flapping-wing micro-air vehicles, perching aerial robots, amphibious robots, and operational aerial robots. Finally, the main challenges presented by NTARs in terms of energy, materials, and perception are analyzed, and the future development trends of NTARs are summarized in terms of size and endurance, mechatronics, and complex scenarios, providing a reference direction for the follow-up exploration of NTARs.

This study aimed to demonstrate a new surgical shear with an integrated energy system (Harmonic ACE®+7) value by determining its effectiveness and economic outcomes compared with conventional ultrasonic shears (CUSs) in a real-world setting.

Aerial transportation systems are important ways for cargo delivery, especially in forest fire-fighting, postdisaster rescue, etc. While the harsh working environments may lead to multirotor failure, such as blade damage. Due to the inherent dynamic coupling existing between the payload and the multirotor, the blade damage will not only affect the dynamics of the multirotor and cause positioning failure but also aggravate the payload sway motion. In order to ensure the positioning accuracy and reduce payload oscillations, a fault-tolerant control scheme for the aerial transportation system is in urgent need. To this end, a finite-time disturbance observer-based nonlinear hierarchical control scheme is designed for the aerial transportation system to handle the lumped disturbance caused by blade damage. Specifically, the following two control objectives are achieved: 1) both the positioning of the multirotor and 2) the swing suppression of the payload with blade damage condition. Lyapunov techniques and LaSalle's invariance theorem are utilized to prove the convergence of the equilibrium point. Finally, simulation and experiment tests are conducted to verify the excellent performance of the proposed control scheme with different damage degrees of blades. As far as we know, this article proposes the first fault-tolerant controller for multirotor aerial transportation systems to realize simultaneous multirotor positioning and payload swing suppression even with blade damage.

An efficient photocatalytic protocol combining heterogeneous semiconductors as photocatalysts and NHPI as a redox reagent was disclosed. Under this protocol, 3-sulfonylquinolines were formed in up to 92% yield via a multicomponent radical cascade annulation. Good substituent tolerance and gram-scale reaction showed the potential in fine chemicals modification and pharmaceutical synthesis.

FeTiO3has emerged as an interesting semiconductor photocatalyst in organic synthesis. We herein describe a visible-light-induced semiheterogeneous strategy for the synthesis of 3-(2-oxoethyl)indolin-2-ones with moderate to good yields and good functional group compatibility using recyclable FeTiO3as a photocatalyst and NHPI as a redox catalyst.

Fault detection for distributed parameter systems (DPSs) generally requires the complete model information to be known so far. However, for numerous industrial applications, it is common that accurate first-principles physical models are extremely difficult to obtain. Hence, the applicability of traditional model-based methods is being restricted. To pave the way, an adaptive neural network (AdNN) is constructed to simultaneously estimate the state variable and the unknown nonlinearity for a class of partially known nonlinear DPSs. Moreover, considering that full-state measurement is unrealistic in applications, the proposed adaptive neural observer is based on a reduced-order model, which also increases the computation efficiency. Then, the residual generation and evaluation are conducted using the output estimation error of the proposed adaptive neural observer. Bearing the effects of the neglected fast dynamics in mind, a data-driven threshold generation scheme is proposed. Extensive experimental results are presented and analyzed to validate the effectiveness of the proposed method.

A strategy of incorporating transparent inorganic semiconductors is proposed for high-performance semitransparent organic photovoltaics. Visible-transparent p-type inorganic semiconductor copper(I) thiocyanate (CuSCN) and a near-infrared acceptor BTP-eC9 can form a heterojunction with exciton dissociation ability.

Byline: Guanghao. Qin, Jiayan. Chen, Liangzhe. Li, Qing. Zhang, Ling. Xu, Sile. Yu, Wei. He, Xingru. He, Emmanuel. Pazo This study reviewed the efficacy and safety of intense pulsed light [...]

This article develops a dual model predictive control (MPC) approach that employs control Lyapunov functions (CLFs) and control barrier functions (CBFs) to support the preservation of formation and prevention of collision in multiquadrotor systems. This is accomplished by utilizing the MPC-CLFs and MPC-CBFs, which are created to establish stability and safety through CLF and CBF constraints of the MPC. The formation does not have a leader due to the implementation of the distributed MPC-CLFs method. The MPC-CBFs track the nominal inputs set by the MPC-CLFs while maintaining a safe distance from obstacles and other quadrotors. Additionally, the event-triggered mechanism detects deadlocks and the nominal states in MPC-CLFs are adapted to resolve them. Both simulation and experimental results demonstrate the effectiveness of the proposed approach.

ABSTRACTTravelers always perform some preference during the decision-making process. The preference will affect the decision results and can be improved by continuously learning. In order to understand the influence of individual preference on travel behavior choice , two individual preferences, including indifference preference and compulsive preference are considered in the paper. Two updating mechanisms of compulsive preference are proposed to obtain the choosing probability of all alternatives. Reinforcement learning models are established integrating the gain stimulating and loss stimulating considering expected utility. Nguyen Dupuis network is adopted for numerical simulation to study the updating process. Simulation results denote that the equilibrium state is much more efficient when preference learning mechanism is considered comparing with the traditional stochastic user equilibrium model, and can decrease the total travel time greatly, which can be applied for urban traffic management. Personalized traffic guidance is the effective solution to traffic congestion in the future

The effects of laser shock peening (LSP) on the microstructural evolution and mechanical properties of the Ti6242 alloy, including the residual stress, surface roughness, Vickers microhardness, tensile mechanical response, and high-cycle fatigue properties, were studied. The results showed that the LSP induced residual compressive stresses on the surface and near surface of the material. The maximum surface residual compressive stress was −661 MPa, and the compressive-stress-affected depth was greater than 1000 μm. The roughness and Vickers micro-hardness increased with the number of shocks, and the maximum hardness-affected depth was about 700 μm after three LSP treatments. LSP enhanced the fraction of low-angle grain boundaries, changed the grain preferred orientations, and notably increased the pole density of αphase on the near surface from 2.41 to 3.46. The surface hardness values of the LSP samples increased with the increase of the number of shocks due to work hardening, while the LSP had a limited effect on the tensile properties. The high-cycle fatigue life of the LSP-treated sample was significantly enhanced by more than 20% compared with that of the untreated sample, which was caused by the suppression of the initiation and propagation of fatigue cracks.

Optimizing anchor deployment is critical to ensure the performance and positioning stability of indoor positioning systems in real-world applications. In this article, a new anchor deployment optimization method is proposed to enhance the positioning performance of range-based positioning systems in the non-line-of-sight (NLOS) environment without increasing the application cost. First, a new fitness function is proposed by simultaneously considering the mean geometric dilution of precision (GDOP) and the coverage of available positioning area in the indoor NLOS environment. Then, a search architecture based on a particle swarm optimization (PSO) algorithm is proposed to optimize anchor deployment. The initialization method of swarm’s position and velocity is given, and the calculation process of the search architecture is introduced in detail. The results obtained from numerical simulations and experimental investigations verified that, for range-based positioning systems in NLOS environment, the accuracy and stability can be significantly improved by optimizing the anchor deployment through our proposed method.

A visible-light-initiated C–H trifluoromethylation of quinoxalin-2(1H)-ones was established using a Z-scheme V2O5/g-C3N4heterojunction as a recyclable photocatalyst in an inert atmosphere at room temperature under additive-free and mild conditions. A variety of trifluoromethylated quinoxalin-2-(1H)-one derivatives were heterogeneously generated in moderate to high yields, exhibiting good functional group tolerance. Remarkably, the recyclable V2O5/g-C3N4catalyst could be reused five times with a slight loss of catalytic activity.

Polysaccharides derived from Agrocybe cylindraceahave been demonstrated to exhibit various bioactivities. However, studies on their structural characteristics during the growth process are limited. This study aimed to compare the physicochemical properties and structural characteristics of alkali-extracted polysaccharides from A. cylindraceafruiting bodies (JACP) across four growth stages. Results showed that the extraction yields and protein levels of JACP declined along with the growth of A. cylindracea, while the contents of neutral sugar and glucose increased significantly. However, JACP exhibited structural characteristics similar to those across the four stages. Four polysaccharide subfractions were isolated from each growth stage, including JACP-Et30, JACP-Et50, JACP-Et60, and JACP-Et70. JACP-Et30 from the four stages and JACP-Et50 from the initial three stages were identified as heteroglucans with β-1,3-d-Glcpand β-1,6-d-Glcpresidues as main chains, respectively. However, other subfractions were considered as β-1,6-d-glucans containing minor glucuronic acid. These subfractions were predominantly replaced by Glcpresidues at the O-3 and O-6 positions. Overall, while JACP exhibited variable physicochemical properties, its structural characteristics remained stable during the growth process, offering new insights into its potential applications in the food and medicinal industries.

The bending radius of the flexible OLED down border was reduced to 0.15mm from 0.25mm by an improved bending model for the extremely narrow bezel mobile. The stability of the optimized bending model was demonstrated by simulation, and the preliminary production and environmental reliability were assessed too.

The first paired electrolysis-enabled arylation of quinoxalin-2(1H)-ones was achieved using cyanoarenes as the arylation reagents. A variety of 3-arylquinoxalin-2(1H)-ones with various important functional groups were obtained in moderate to good yields under metal- and chemical oxidant-free conditions. With a pair of reductive and oxidative processes occurring among the substrates and reaction intermediates, the power consumption can be dramatically reduced.

Reducing the weight of the negative current collector is an effective strategy for lightweighting vehicle batteries. Herein, thin copper foil with high tensile strength was prepared through electrodeposition in Br−-based aqueous solution. The synergistic effect of additive Br−, polyethylene glycol (PEG), Bis-(sodium sulfopropyl)-disulfide (SPS) on the microstructure and tensile strength of the copper foils have been systematically explored. It was found that the addition of Br−modifies the microstructure of copper via grain refinement, thereby enhancing the mechanical properties of copper foil. The obtained copper foil reaches an enhanced tensile strength of 469.8 N/mm2and an elongation of 2.2%. The results of electrochemical measurements confirm that Br−enhances electrochemical polarization of PEG and attenuates the acceleration of SPS. The improved mechanical properties of copper foils are attributed to the closer proximity and stronger adsorption energy between Br−and Cu atoms, which results in a synergy of grain refinement and nanotwinned grains associated with increased dislocation density as well as dislocations entangled around nanotwin GBs.

Microblade assemblages are among the most common prehistoric archaeological materials found on the Tibetan Plateau (TP) and are thought to indicate large scale migration to and settlement of the TP. Few microblade sites, however, have been systematically excavated, especially in the remotest, highest-elevation regions of the TP. The timing of the large-scale arrival, spread, and permanent settlement of people on the TP therefore remains controversial. In this paper, we report on a recently excavated site, Locality 3 of the Nwya Devu Site (ND3), located at 4600 meters above sea level (masl), near the shore of Ngoin Lake, on the interior TP. Our analyses reveal a fairly typical microblade technological orientation and two types of microblade cores: wedge-shaped and semi-conical, which are similar to those found throughout North China. Using Optically Stimulated Luminescence (OSL) dating and AMS 14C dating, the age of ND3 ranges from 11 to 10 ka. This date range indicates ND3 is the oldest microblade site yet recorded in the remote, high-elevation regions of the TP and thus provides important information about when and how hunter-gatherers using microblades began exploiting the higher altitudes of the TP. Taken together, studies at ND3 and throughout the TP suggest that a microblade adaptation is associated with the first prolonged human occupation of the plateau and that microblades played a significant role in mediating the risks and facilitating the mobility necessary to permanently inhabit the TP.

This paper presents an experimental and theoretical investigation into the factors influencing the sealing performance of combined slip rings. Factoring in the frictional heat from micro convex bodies and convective heat exchange between the slip ring, oil film, and air, we formulate a thermoelastic flow hybrid lubrication model for the combined slip ring seal. This model calculates the distribution of oil film thickness, pressure, temperature, velocity, and viscosity in the sealing zone, drawing on the generalized average Reynolds equation and the transmembrane average energy equation, in conjunction with the heat conduction equation of the slip ring. Utilizing the Archard wear model, we also examine the wear characteristics of the combined slip ring seal, providing insights into seal wear under these conditions. The model enables an analysis of the interplay between parameters and their impact on seal performance. The method proposed accurately predicts friction and leakage in line with experimental data, thereby providing a theoretical foundation for further numerical investigation of seal characteristics.

Carbon-encapsulated metal (CEM) catalysts effectively address supported metal catalyst instability by protecting the active metal with a shell. However, mass transfer limitations lead to reduced activity for catalytic hydrogenation reaction over most CEM catalysts. Herein, we introduce a dopant strategy aimed at incorporating nickel metal within graphene-like shells (GLS) featuring oxygen-containing functional groups (OFGs). The core of this strategy involves precise control of GLS modification and the demonstrated pivotal influence of aromatic ether linkages (═C–O–C) in GLS for significant enhancement of catalytic performance. The introduction of ═C–O–C into GLS with stability was beneficial to improve the work function of the catalyst and promoted electron transmission from Ni metal core to GLS, further elevating the catalytic activity, based on the Mott–Schottky effect. In addition, the experimental characterization and density functional theory (DFT) calculations showcased that the ═C–O–C reconstructed the electronic state of GLS, imparting it highly specific for the adsorption of hydrogen and para-chloronitrobenzene (p-CNB) to obtain para-chloroaniline (p-CAN) with high selectivity. This work manifested a feasible direction for the precise modulation and design of the OFGs in CEM catalysts to achieve highly efficient catalytic hydrogenation.

Accurate prediction of enzyme optimal temperature (Topt) is crucial for identifying enzymes suitable for catalytic functions under extreme bioprocessing conditions. The optimal growth temperature (OGT) of microorganisms serves as a key indicator for estimating enzyme Topt, reflecting an evolutionary temperature balance between enzyme-catalyzed reactions and the organism’s growth environments. Existing OGT databases, collected from culture collection centers, often fall short as culture temperature does not precisely represent the OGT. Models trained on such databases yield inadequate accuracy in enzyme Topt prediction, underscoring the need for a high-quality OGT database. Herein, we developed AI-based models to extract the OGT information from the scientific literature, constructing a comprehensive OGT database with 1155 unique organisms and 2142 OGT values. The top-performing model, BioLinkBERT, demonstrated exceptional information extraction ability with an EM score of 91.00 and an F1 score of 91.91 for OGT. Notably, applying this OGT database in enzyme Topt prediction achieved an R2value of 0.698, outperforming the R2value of 0.686 obtained using culture temperature. This emphasizes the superiority of the OGT database in predicting the enzyme Topt and underscores its pivotal role in identifying enzymes with optimal catalytic temperatures.

Aggregate is one of the most extensive existing modes of matters in the world. Besides the research objectives of inanimate systems in physical science, the entities in life science can be regarded as living aggregates, which are far from being thoroughly understood despite the great advances in molecular biology. Molecular biology follows the research philosophy of reductionism, which generally reduces the whole into parts to study. Although reductionism benefits the understanding of molecular behaviors, it encounters limitations when extending to the aggregate level. Holism is another epistemology comparable to reductionism, which studies objectives at the aggregate level, emphasizing the interactions and synergetic/antagonistic effects of a group of composed single entities in determining the characteristics of a whole. As a representative of holism, aggregation-induced emission (AIE) materials have made great achievements in the past two decades in both physical and life science. In particular, the unique properties of AIE materials endow them with in situ and real-time visual methods to investigate the inconsistency between microscopic molecules and macroscopic substances, offering researchers excellent toolkits to study living aggregates. The applications of AIE materials in life science are still in their infancy and worth expanding. In this Perspective, we summarize the research progress of AIE materials in unveiling some phenomena and processes of living systems, aiming to provide a general research approach from the viewpoint of holism. At last, insights into what we can do in the near future are also raised and discussed.

Molecular metal compounds have demonstrated excellent catalytic activity and product selectivity in the H2evolution reaction (HER) and the CO2reduction reaction (CO2RR). The heterogenization of molecular catalysts is regarded as an effective approach to improve their applicability. In this work, the molecular catalytic units [Cp*Ir(Bpy)Cl]+and [Ru(Bpy)(CO)2Cl2] are constructed in situ on the bipyridine sites of the covalent organic framework for photocatalytic HER and CO2RR, respectively. Inheriting the impressive performance of molecular catalysts, the functionalized TpBpy–M exhibits excellent catalytic activity and product selectivity. Under visible light irradiation, the H2production rate of TpBpy–Ir is about 760 μmol g–1h–1, which is 6.7 times higher than that of TpBpy without built-in catalytic sites. Also, the HCOOH production rate of TpBpy–Ru is 271 μmol g–1h–1, with an impressive selectivity of 88%. Control experiments validated that this improvement is attributed to the incorporation of molecular catalytic units into the framework. Photoluminescence spectroscopy measurements and theoretical calculation consistently demonstrate that, under illumination, the photosensitizer [Ru(Bpy)3]Cl2is excited and transfers electrons to the catalytic sites in TpBpy–M, which then catalyzes the reduction of H+and CO2.

We develop and experimentally test a prescribed performance control methodology for trajectory tracking of underactuated autonomous aerial vehicles under unknown time-varying disturbances. An extended state observer is first proposed to filter position and velocity measurements, and to compensate for disturbances, including model parametric uncertainty and/or exogenous perturbations, e.g., wind. Then, by resorting to a barrier function and to constraints on the transient and steady-state response of the position error, we derive a thrust command law that follows from a desired stabilizing force. This force is inherently associated with the vehicle's attitude, which is controlled using angular velocity commands. The errors stemming from the closed-loop system are shown to be uniformly ultimately bounded. Simulation results, including comparison data, are presented to validate the proposed solution. Experimental results are also included to showcase the performance of our strategy in a real-world application using a quadrotor vehicle.

Different from birds, bats, flies, and other flying creatures that generate propulsions by flapping a pair of wings, butterflies with two pairs of wings have their peculiar flight aerodynamics. In this article, a servo-driven biomimetic robotic butterfly, named USTButterfly, is designed to study the flight mechanism of biological butterflies. First, instead of using a single actuator to drive two pairs of wings, two servos are introduced to independently drive the left and right wings, thereby realizing tailless control of the robotic butterfly. Next, a bionic airfoil is designed inspired by the wing structure of the glasswing butterfly. Wing geometry analysis indicates that USTButterfly well matches the morphological characteristics of biological butterflies. Finally, a multicamera motion capture system is used to measure the flight characteristics of the robotic butterfly, and the results demonstrate that despite a larger Reynolds number, USTButterfly shares a similar coupled wing–body interaction with biological butterflies in the climbing flight. USTButterfly opens up a new way to study the flight specializations of biological butterflies, and offers a potential alternative paradigm for existing unmanned aerial vehicles.

The design and synthesis of a novel organic photocatalyst (OPC) have attracted broad interest from both the organic chemistry and polymer community. Herein, we presented a visible-light-induced alkylarylation of alkenes strategy for core modification of 5,10-diaryl-5,10-dihydrophenazines (DADHPs) under metal- and additive-free conditions, with the aim to develop powerful photocatalyst for organocatalyzed atom transfer radical polymerization (O-ATRP). Good tolerance for a wide variety of functional groups and affording the corresponding tetrasubstituted products in moderate to good yields were achieved in the batch and flow reactor. The experimental and computational mechanistic study confirmed that DADHPs’ radical cations and π-πstacking interactions played important roles in the alkylarylation of alkenes. A series of the tetrasubstituted DADHPs were directly synthesized from the corresponding noncore-modified phenazines, which were demonstrated to be effective organic photoredox catalysts for O-ATRP. Light responsive nature, controlled polymerization manner, and well-defined poly (methyl methacrylate) were achieved viatetrasubstituted DADHPs mediated O-ATRP.

The timing and mechanisms of the human occupation of the demanding high-altitude Tibetan Plateau environment are of great interest. Here, we report on our reinvestigations and dating of the Nwya Devu site, located nearly 4600 meters above sea level on the central Tibetan Plateau. A new microblade techno-complex was identified on a lower lake shore at this site, distinct from the previously reported blade tool assemblage. These two lithic assemblages were dated to 45.6±2.6 and 10.3±0.5 ka using optically stimulated luminescence and accelerator mass spectrometry 14C methods. They represent, respectively, the earliest known Paleolithic and microlithic sites on the interior Tibetan Plateau, indicating multiple occupation episodes of hunter-gatherers during the past 45 ka. Our studies reveal that relatively stable depositional conditions and a paleoenvironment characterized by a comparatively warm climate facilitated these multiple occupations at Nwya Devu. The contemporaneous occurrence of the Upper Paleolithic blade technology on the Tibetan Plateau and most of Eurasia between 50 and 40 ka indicates rapid, large-scale dispersals of humans that profoundly affected human demography on a large scale. Combining new archaeological evidence and previously reported genetic data, we conclude that the Tibetan Plateau provided a relatively stable habitat for Upper Paleolithic hunter-gatherers, which may have contributed to the complex and multiple-origin gene pool of present-day Tibetans.

In this work, a novel raft-like structure that combines noble metal nanoparticles (NPs) with an interconnected layer of hemispherical dielectric shell was fabricated and characterized. It was discovered that this hybrid material can enhance the optoplasmonic interaction between plasmonic and dielectric components, thereby improving the sensing performance in surface-enhanced Raman spectroscopy (SERS). Varied geometric parameters of the fabricated optoplasmonic raft, including the inner diameter and thickness of the dielectric shell, were attempted and analyzed through numerical simulation and experimental SERS measurements. With particular size, thickness, and incident orientation, the silica shell focuses the incident optical flow into the deposited silver NPs, undergoing similar near-field focusing behavior in comparison with other optoplasmonic entities. This optoplasmonic raft floating on the water surface is able to harvest the target molecules effectively through bubble enrichment, which rapidly captures and concentrates analytes from the aqueous phase. With a limited sampling time, the sensing performance of the developed optoplasmonic raft is improved by applying the optimized parameters involved in bubble enrichment. The substrates and corresponding enrichment method were implemented in the detection of methamphetamine (METH), achieving a limit of detection (LOD) down to 0.035 nM. As for practical onsite detection, the developed substrate and bubbling strategy were applied in an assembled set, employing a portable Raman spectrometer and an air pump. This set is able to detect METH dissolved in regular commercial beer, which is quite competent in the investigation of drug abuse.

KRASG12D, the most frequent KRAS oncogenic mutation, is a promising target for cancer therapy. Herein, we report the design, synthesis, and biological evaluation of a series of KRASG12DPROTACs by connecting the analogues of MRTX1133 and the VHL ligand. Structural modifications of the linker moiety and KRAS inhibitor part suggested a critical role of membrane permeability in the degradation activity of the KRASG12DPROTACs. Mechanism studies with the representative compound 8odemonstrated that the potent, rapid, and selective degradation of KRASG12Dinduced by 8owas via a VHL- and proteasome-dependent manner. This compound selectively and potently suppressed the growth of multiple KRASG12Dmutant cancer cells, displayed favorable pharmacokinetic and pharmacodynamic properties in mice, and showed significant antitumor efficacy in the AsPC-1 xenograft mouse model. Further optimization of 8oappears to be promising for the development of a new chemotherapy for KRASG12D-driven cancers as the complementary therapeutic strategy to KRAS inhibition.

Prostate cancer (PCa) is primarily driven by aberrant Androgen Receptor (AR) signaling. Although there has been substantial advancement in antiandrogen therapies, resistance to these treatments remains a significant obstacle, often marked by continuous or enhanced AR signaling in resistant tumors. While the dysregulation of the ubiquitination-based protein degradation process is instrumental in the accumulation of oncogenic proteins, including AR, the molecular mechanism of ubiquitination-driven AR degradation remains largely undefined. We identified UBE2J1 as the critical E2 ubiquitin-conjugating enzyme responsible for guiding AR ubiquitination and eventual degradation. The absence of UBE2J1, found in 5–15% of PCa patients, results in disrupted AR ubiquitination and degradation. This disruption leads to an accumulation of AR proteins, promoting resistance to antiandrogen treatments. By employing a ubiquitination-based AR degrader to adeptly restore AR ubiquitination, we reestablished AR degradation and inhibited the proliferation of antiandrogen-resistant PCa tumors. These findings underscore the fundamental role of UBE2J1 in AR degradation and illuminate an uncharted mechanism through which PCa maintains heightened AR protein levels, fostering resistance to antiandrogen therapies.

Cryopreservation presents significant opportunities for biomedical applications including cell therapy, tissue engineering, and assisted reproduction. Dimethyl sulfoxide (DMSO), the most commonly used cryoprotectant (CPA), can be added to cells to prevent cryogenic damage. However, the toxicity of cryoprotectants restrains its further development in many areas with safety concerns such as clinical treatment. Therefore, the development of low-toxicity cryoprotectants is essential for medical research. This work reports deep eutectic solvents (DES) as naturally biocompatible osmoprotectants for green and efficient cryopreservation of human umbilical cord mesenchymal stem cells (HuMSC), which may be an ideal alternative to DMSO. The six types of DESs were explored for thermal properties, toxicity, and permeability in cells. Raman spectroscopy and viscosity studies showed that DES exhibited an improved hydrogen-bonding system as the temperature decreased. By optimizing the freezing process (cooling rate, incubation time, and loading procedure) of DES, the viability of mouse embryonic fibroblast cells (NIH-3T3) after thawing was significantly improved. The HuMSC were successfully preserved with no significant difference (p> 0.05) in cell viability (94.65%) after thawing compared with DMSO, which preserved the cell differentiation function and improved the cell proliferation rate. The mechanism of DES in cryopreservation was investigated, and it was found that DES could bind water molecules and effectively inhibit the growth of ice crystals during ice recrystallization, reducing mechanical damage to cells. This study highlights the excellent performance of DES as a low-toxicity CPA for stem cell preservation, which may be a significant advance for future clinical cell therapy.

Siamese-based trackers have shown excellent performance in unmanned aerial vehicle (UAV) tracking due to their balanced accuracy and speed. However, most existing methods rely heavily on local convolution operations of CNNs for feature extraction, which fails to establish global feature relationships. In addition, the challenge of information imbalance, caused by differences in background and the prevalence of single-object scenarios, remains a significant obstacle in the current domain. This can potentially result in unwanted boundary effects in UAV tracking. To address these challenges, this article introduces a novel tracker called eccentric loss and adaptive search (ELAS), which is specifically designed for UAV videos and aims to overcome these challenges. The proposed ELAS enhances feature representation capabilities by utilizing multi-input and multimapping of information. It also addresses information imbalance through a differentiated loss function. Furthermore, an adaptive search strategy is introduced to accommodate varying search scales across different scenarios. Specifically, an additional multilayer feature enhancement (MLE) network is first introduced, which absorbs the middle and high layer information in the backbone network and directs the features to focus on global connections using self-attention, avoiding the loss of useful semantic information due to falling into local optima. Then, a novel eccentric loss is designed to guide network training, enhancing the saliency of object features on the feature map by accounting for the volatility of negative samples and estimating classification performance. Finally, an adaptive multiscale search strategy is proposed to detect the saliency of objects through between-class segmentation effectiveness and, thus, adjust the proportional scale parameter. Extensive experiments on challenging UAV benchmarks demonstrate that ELAS achieves state-of-the-art (SOTA) performance with real-time speed, confirming its effectiveness and robustness.

Self-supervised learning (SSL) has gained significant traction within the remote sensing community, with pretraining a foundation model on large-scale unlabeled datasets for the interpretation of remote sensing images (RSIs) emerging as a trending direction. This approach aims to supplant the conventional practice of loading ImageNet pretrained weights, offering a more versatile and potentially more effective solution for handling RSIs. Among SSL techniques, contrastive learning excels in extracting general representations in the field of remote sensing. However, its excessive focus on inter-instance discrimination hinders the effectiveness of pretraining due to the diverse and complex geographical information present in RSIs. Moreover, the typical two-variations-as-one-pair pattern may be suboptimal, particularly given the temporal information specific to RSIs. In this article, we propose a novel method called promoting intra-instance similarity (PIS) for short, which leverages the temporal information specific to RSIs and increases the intra-instance variations to expand the positive representation space. Additionally, by PIS within this space, our foundation models develop the ability to extract more general and instance-invariant features that prove beneficial for various downstream tasks. Experiments show that our PIS method achieves state-of-the-art (SOTA) performance on ten datasets across four downstream remote sensing tasks, demonstrating the generalizability and efficacy of the proposed method. Through our preliminary investigation into intra-instance characteristics, we believe there exists substantial potential in this aspect, holding considerable promise for further exploration. The codes are available on the website: https://github.com/ShawnAn-WHU/PIS.git.