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Herein, a novel visible-light-induced 6-exo-trigdifluoromethylation cyclization and subsequent carbo-thioesterification reaction is described. This protocol allows efficient access to valuable gem-difluoro quinolin-2(1H)-ones in moderate to excellent yields under mild conditions. Broad amino sources compatibility, including cyclic morpholine, thiazolidine, thiomorpholine, pyrrolidine, 1,4-oxazepane, 2,6-dimethylmorpholine, tert-butyl piperazine-1-carboxylate and noncyclic diethylamine, N-ethylpropan-1-amine, N-benzylethanamine, N-benzyl-trimethylsilanamine, dibenzylamine, and N-(4-methoxybenzyl)ethanamine, demonstrated the practicability of this strategy. A radical–radical crossover route was proposed on the basis of radical inhibition experiments, visible light irradiation on–off test, apparent quantum efficiency (AQE) calculation, and fluorescence quenching studies.

Sleep staging is a crucial task in sleep monitoring and diagnosis, but clinical sleep staging is both time-consuming and subjective. In this study, we proposed a novel deep learning algorithm named feature fusion temporal convolutional network (FFTCN) for automatic sleep staging using single-channel EEG data. This algorithm employed a one-dimensional convolutional neural network (1D-CNN) to extract temporal features from raw EEG, and a two-dimensional CNN (2D-CNN) to extract time-frequency features from spectrograms generated through continuous wavelet transform (CWT) at the epoch level. These features were subsequently fused and further fed into a temporal convolutional network (TCN) to classify sleep stages at the sequence level. Moreover, a two-step training strategy was used to enhance the model's performance on an imbalanced dataset. Our proposed method exhibits superior performance in the 5-class classification task for healthy subjects, as evaluated on the SHHS-1, Sleep-EDF-153, and ISRUC-S1 datasets. This work provided a straightforward and promising method for improving the accuracy of automatic sleep staging using only single-channel EEG, and the proposed method exhibited great potential for future applications in professional sleep monitoring, which could effectively alleviate the workload of sleep technicians.

Zinc complexation forms hydrophobic protective layers inhibiting dendrite growth and hydrogen evolution, ensuring stable zinc metal anodes in aqueous batteries.

Pattern recognition receptors are an essential part of the immune system, which detect pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs) and help shape both innate and adaptive immune responses. When dsDNA is present, cyclic GMP-AMP Synthase (cGAS) produces a second messenger called cyclic GMP-AMP (cGAMP), which then triggers an adaptor protein called STING, and eventually activates the expression of type I interferon (IFN) and pro-inflammatory cytokines in immune cells. The cGAS-STING signaling pathway has been receiving a lot of attention lately as a key immune-surveillance mediator. In this review, we summarize the present circumstances of the cGAS-STING signaling pathway in viral infections and inflammatory diseases, as well as autoimmune diseases. Modulation of the cGAS-STING signaling pathway provides potential strategies for treating viral infections, inflammatory diseases, and autoimmune diseases.

This study aimed to analyze the correlation between urinary crystals and urinary calculi.

The urbanization and industrialization of East and Southeast Asia in decades past has significantly altered living environment and lifestyles, which may have complicated effects on the burden of asthma. We aim to examine the patterns and trends of asthma incidence rates in six major East and Southeast Asian countries as well as five major Western countries, and predict the numbers of new cases attributed to various factors.

Proper monitoring of anesthesia stages can guarantee the safe performance of clinical surgeries. In this study, different anesthesia stages were classified using near-infrared spectroscopy (NIRS) signals with machine learning. The cerebral hemodynamic variables of right proximal oxyhemoglobin (HbO2) in maintenance (MNT), emergence (EM) and the consciousness (CON) stage were collected and then the differences between the three stages were compared by phase-amplitude coupling (PAC). Then combined with time-domain including linear (mean, standard deviation, max, min and range), nonlinear (sample entropy) and power in frequency-domain signal features, feature selection was performed and finally classification was performed by support vector machine (SVM) classifier. The results show that the PAC of the NIRS signal was gradually enhanced with the deepening of anesthesia level. A good three-classification accuracy of 69.27% was obtained, which exceeded the result of classification of any single category feature. These results indicate the feasibility of NIRS signals in performing three or even more anesthesia stage classifications, providing insight into the development of new anesthesia monitoring modalities.

Currently approved targeted treatment for ROS1-rearranged non-small-cell lung cancer (NSCLC) has either inadequate intracranial activity or CNS-related toxicities. We evaluated the efficacy and safety of foritinib, a novel ALK and ROS1 inhibitor, in patients with advanced ROS1-rearranged NSCLC.

V2O5, which has multicolor and energy storage properties, is a promising electrochromic material for multifunctional electrochromic devices, but its practical application is limited by its poor lifespan and long switching time. In this work, high-performance V2O5/TiO2films were fabricated by spraying a V2O5solution on in situ-grown TiO2nanorods. Due to the porous structure formed between the TiO2nanorods and the remarkable electron transfer performance of TiO2, the switching time of the V2O5/TiO2films decreased. Moreover, the strong adhesion between the TiO2nanorods and F-doped tin oxide (FTO) glass and the increased surface roughness of the substrates significantly improved the cycling stability of the V2O5/TiO2films. With a large transmittance modulation (47.8% at 668 nm), fast response speed (τc= 5.1 s, τb= 4.2 s), and long lifespan, V2O5/TiO2films were used as electrodes for the electrochromic energy storage device (EESD), which switched in six colors through color overlay: dark orange, sandy yellow, green-yellow, yellow-green, dark green, and dark brown. Inspired by pixel displays, EESDs were designed by segmenting V2O5films to stagger the display of the electrochromic and ion storage layers, which presented 11 types of information based on different combinations of colors. This work provides inspiration for developing multifunctional electrochromic devices, especially for camouflage and information displays.

Background: The prognostic nutritional index (PNI) integrates both nutritional and immune indicators and provides promising prognostic value for various malignancies. However, there is still no specific consensus relating to the precise relationship between the pretreatment PNI and the survival outcome of patients with prostate cancer (PCa). Here, we performed a meta-analysis to determine the prognostic significance of PNI for patients with PCa. Methods: We used the PubMed, EMBASE, Web of Science, Cochrane Library (CENTRAL), and CNKI databases to identify and retrieve eligible articles that were published in any language up to the 1st March 2023. Our analysis considered hazard ratios (HRs) and 95% confidence intervals (CIs) published in the included studies. Data synthesis and analysis were conducted using Stata 15.1 software. Results: A total of ten studies featuring 1631 cases were included in our quantitative analysis. Analysis showed that a low PNI at baseline was significantly associated with poor overall survival (OS) (HR: 2.16; 95% CI: 1.40–3.34; p= 0.01), progression-free survival (PFS) (HR: 2.17; 95% CI 1.63–2.89; p< 0.001). Owing to high levels of heterogeneity, we performed subgroup analysis based on disease staging, sample size, and cutoff value; we found that disease staging may have been the source of the heterogeneity. A low pretreatment PNI was associated with poor survival outcomes for both metastatic castration-resistant prostate cancer (mCRPC) patients and nonmetastatic castration-resistant prostate cancer (nmCRPC) patients. Conclusions: A low pretreatment PNI was significantly correlated with a worse OS and PFS in patients with PCa. A low pretreatment PNI may act as a reliable and effective predictor for the prognosis of patients with PCa. Further well-designed studies should be performed to fully evaluate the prognostic performance of this novel indicator for PCa.

Flat-plate solar collectors are the leading product in the production of low-temperature hot water market, and are also one of the most widely used technologies for utilizing solar energy to generate low-temperature heat. In this study, a specific type of flat-plate collector optimized using field synergy theory was introduced, with the main change being the use of S-bend structure instead of traditional direct current channel. The study applied numerical simulation to analyze and evaluate the performance of the collector. The results showed that introducing an S-bend with a curvature radius of 90 mm can improve the efficiency of a single block collector by 0.1 %, reduce the temperature of the absorption plate by 0.33℃, and drive the angle between the velocity vector and temperature gradient (βangle) close to zero. Compared with the relatively uniform vortex structure observed in the cavity of the straight tube collector, the S-bend structure generates more complex and irregular vortex patterns. It is worth noting that the introduction of S-bend produces a unique butterfly shaped temperature distribution on the glass surface. The changes that occur in the cavity area are driven by the temperature difference between the upper and lower plate surfaces, and these new phenomena induced by S-bending deserve further in-depth discussion. These findings emphasize the importance of continuous research to develop optimized designs, improve efficiency, and promote wider applications, and provide certain ideas and references for subsequent work.

Accurate estimation of Land Surface Reflectance (LSR) is the key to Aerosol Optical Depth (AOD) retrievals. However, the current band-specific LSRs retrieval using Look-Up Tables (LUTs) are typically pseudo-LSRs obtained by atmospheric corrections to the AOD predetermined in the LUTs that do not match the surface constraints established by the true LSRs, leading to an error in modeling reflectance at the top of atmosphere (TOA) using pseudo-LSRs calculation by linear interpolation. This study proposed a new LUT search method to improve the AOD retrievals from the Particle Observing Scanning Polarimetry (POSP) sensor onboard the China GaoFen-5 (02) satellite. Atmospherically corrected LSR using ERA5 reanalysis data and POSP AOD products for the year 2022 were adopted to create a new full-spectrum LSR self-consistent surface constraint. Results showed that the retrieved POSP AOD in January 2023 using the new method agrees with the ground-truth AOD values from AErosol RObotic NETwork (AERONET) site observations with the correlation coefficient (R) at 0.703 and the root mean square error (RMSE) at 0.068. 76.77% of the values fell into the expected error (EE) envelope of range ± (0.05 + 0.15 AODAERONET), and 67.35% met the accuracy requirements of the Global Climate Observing System (GCOS).

The effective reduction of sulfur pollutant emissions during the treatment of waste resins has always posed a challenge. This study put forward a solution to using the metallic oxide enhanced Na2CO3-K2CO3system for the treatment of waste resins (CERs). Na2CO3-K2CO3was used as a medium for heat transfer and desulfurization, while CaO or ZnO functioned as catalysts in the sulfur conversion process. The thermodynamic analysis substantiated the reliability of enhanced sulfur fixation by CaO and ZnO. H2S, SO2and COS primarily generated during the destruction stage of -SO3H (280–500°C) and residues (∼700°C), which were largely absorbed through a vapor-liquid-solid reaction to generate CaCO3, ZnS and K2SO4. CaO improved the conversion of sulfur to sulfate and effectively mitigated the excessive emissions of CO2. SO2generated by the oxidation of ZnS at about 800 °C could be further absorbed by molten Na2CO3-K2CO3to form K2SO4. The proposed method exhibited in-situ desulfurization capability and effectively inhibited the sulfur migration to gaseous products. At 800°C, the sulfur retention rate, the formation rate of SO42-and the oxidation efficiency of CERs reached 91.39 %, 80.61 % and 99.99 %, respectively. The existence of CaO and ZnO facilitated the inorganic transformation of organic sulfur, and the efficient conversion of organic sulfur into inorganic compounds was achieved. This approach provides a new opportunity to improve the treatment efficiency of radioactive solid waste containing organic sulfur.

Objective: Muscleatrophy reduces the quality of life and increases morbidity and mortality from other diseases. The development of non-invasive muscle atrophy evaluation method is of great practical value. The lack of gold standard for pathological grading usually allows only the duration of weightlessness as a criterion for the degree of atrophy. However, the adaptive reductive remodeling of muscle physiology and structure shows a trend of nonlinear changes in time. Consequently, using weightlessness time as a benchmark for the degree of atrophy is inaccurate. Methods: This paper proposes a new ultrasound imaging-based method for quantifying muscle atrophy that utilizes weakly supervised information between multiple data partitions with controlled variance components, overcoming the limitations of using the weightlessness time as a criterion. We introduce a group-supervised contrastive disentanglement network (GCDNet) to disentangle the individual variances, muscle growth and atrophy components of ultrasound images, and quantify the degree of atrophy using the disentangled atrophy component. Results: The feasibility of GCDNet is validated by the separability, independence, and representativeness of the disentangled components. To simplify the application of GCDNet, a muscle atrophy scoring network requiring no reference images is developed by distilling the GCDNet's knowledge of muscle atrophy quantization. The strength of the proposed methodology allows us, for the first time to our knowledge, to study the muscle growth attribute during hind-limb unloading and the spatial distribution of muscle atrophy.

Recently, there has been significant interest in topological nodal-line semimetals due to their linear energy dispersion with one-dimensional nodal lines or loops. These materials exhibit fascinating physical properties, such as drumhead surface states and 3D anisotropic nodal-line structures. Similar to Weyl semimetals, type-II nodal-line semimetals have two crossing bands that are both electron-like or hole-like along a certain direction. However, the direct observation of type-II nodal-line Fermions has been challenging due to the lack of suitable material platforms and the low density of states. Here we present experimental evidence for the coexistence of both type-I and type-II nodal-line Fermions in ZrSiSe, which was obtained through magneto-optical and angle-resolved photoemission spectroscopy (ARPES) measurements. Our density functional theory calculations predict that the type-II nodal-line structure can be developed in the Z-R line of the first Brillouin zone based on the lattice constants of the grown single crystal. Indeed, ARPES measurements reveal the type-II nodal-line band structure. The extracted type-II Landau level transitions from magneto-optical measurements exhibit good agreement with the calculated type-II energy dispersion model based on the band structure. Our experimental results demonstrate that ZrSiSe possesses two types of nodal-line Fermions, distinguishing it from other ZrSiX (X = S, Te) materials and positioning it as an ideal platform for investigating type-II nodal-line semimetals.

1,4-Dienes are important scaffolds widely used in natural products and medicinal compounds. Herein, we report a highly efficient method for the straightforward synthesis of 1,4-dienes viaregio- and stereoselective reductive coupling of alkynes and allenes, catalyzed by visible-light photoredox cobalt. In contrast to the conventional E-alkene products, both (Z,E)-and (E,E)-1,4-dienes were synthesized with good regio- and stereoselectivities under mild conditions. In this photoredox reaction, Hünig’s base and water were utilized as hydrogen sources instead of the commonly used Hantzsch esters. The mechanistic and density functional theory studies indicate that the reaction undergoes protolysis of a cobaltacyclopentene intermediate and photocatalytic E→Zisomerization of (E,E)-1,4-dienes to (Z,E)-1,4-dienes viaan energy transfer process.

We present an efficient analytical energy gradient algorithm for the cluster-in-molecule resolution-of-identity second-order Møller–Plesset perturbation (CIM-RI-MP2) method based on the Lagrange multiplier method. Our algorithm independently constructs the Lagrangian formalism within each cluster, avoiding the solution of the coupled-perturbed Hartree–Fock (CPHF) equation for the whole system. Due to this feature, the computational cost of the CIM-RI-MP2 gradients is much lower than that of other local MP2 algorithms. Benchmark calculations of several molecules containing up to 312 atoms demonstrate the general applicability of our CIM-RI-MP2 gradient algorithm. The optimized structure of a 244-atom molecule using the CIM-RI-MP2 method with the cc-pVDZ basis set is in good agreement with the corresponding crystal structure. A single-point gradient calculation conducted for a molecular cage containing 972 atoms and 9612 basis functions takes 48 h on 25 nodes, utilizing a total of 600 CPU cores. The present CIM-RI-MP2 gradient program is applicable for obtaining the optimized geometries of large systems with hundreds of atoms.

Acetylene production from mixed a-olefins emerges as a potentially green and energy-efficient approach with significant scientific value in the selective cleavage of C–C bonds. On the Pd(100) surface, it is experimentally revealed that C2to C4a-olefins undergo selective thermal cleavage to form surface acetylene and hydrogen. The high selectivity toward acetylene is attributed to the 4-fold hollow sites which are adept at severing the terminal double bonds in a-olefins to produce acetylene. A challenge arises, however, because acetylene tends to stay at the Pd(100) surface. By using the surface alloying methodology with alien Au, the surface Pd d-band center has been successfully shifted away from the Fermi level to release surface-generated acetylene from a-olefins as a gaseous product. Our study actually provides a technological strategy to economically produce acetylene and hydrogen from a-olefins.

Purpose: Many studies have found that when the piezoelectric devices are with the sizes of micrometer/nanoscale level, another significant electromechanical coupling characteristic, namely the flexoelectric effect, also plays important role in the performance of devices. In order to investigate the effect of flexoelectricity on the thickness-shear vibration, a mathematical model of a finite piezoelectric plate with slowly varying thickness and elliptical crosssection is presented with the consideration of flexoelectric effect in this paper. Methods: The proposed model uses the first order McLaughlin series to approximate the elliptical geometric function and the its first derivative is ignored since we assume that the plate thickness varies slowly along the length. The displacement function we adopted is assumed to be antisymmetric through the thickness due to the thicknessshear vibration mode. In addition, regarding to the thin and long flexoelectric plate, only the shear strain gradient through the thickness is considered in the mathematical model. The nonlinear governing equations, which incorporate geometric nonlinearity, are converted into differential equations as function of time by the Galerkin method. The method of multiple scales is employed to obtain the solution of nonlinear governing equation with the first order approximation. The obtained frequencies of thickness-shear mode are expressed in terms of vibration amplitude, eccentricity and flexoelectric coefficients. Results and Conclusion: The results show that the nonlinear thickness-shear vibration is size dependent and flexoelectric effect has significant influence on the nonlinear thickness-shear vibration frequencies of micro thin plates. The eccentricity and geometric nonlinearity also have great influence on the nondimensional fundamental frequencies. Thus, for accurate design of nano/micro scale high precision and high frequency flexoelectric/piezoelectric devices with elliptical cross-section, flexoelectricity must be taken into consideration.

Human African trypanosomiasis (HAT) still faces few therapeutic options and emerging drug resistance, stressing an urgency for novel antitrypanosomal drug discovery. Here, we describe lead optimization efforts aiming at improving antitrypanosomal efficacy and better physicochemical properties based on our previously reported optimized hit NPD-2975 (pIC507.2). Systematic modification of the 5-phenylpyrazolopyrimidinone NPD-2975 led to the discovery of a R4-substituted analogue 31c(NPD-3519), showing higher in vitropotency (pIC507.8) against Trypanosoma bruceiand significantly better metabolic stability. Further, in vivopharmacokinetic evaluation of 31cand experiments in an acute T. bruceimouse model confirmed improved oral bioavailability and antitrypanosomal efficacy at 50 mg/kg with no apparent toxicity. With good physicochemical properties, low toxicity, improved pharmacokinetic features, and in vivoefficacy, 31cmay serve as a promising candidate for future drug development for HAT.

Background:Chronic kidney disease (CKD) is a serious public health issue worldwide, but the disease burden of CKD caused by different etiologies and changing trends has not been fully examined. Methods:We collected data from Global Burden of Disease Study 2019 (GBD 2019), including incident cases, age-standardized incidence rate (ASIR), disability-adjusted life years (DALYs), and age-standardized DALY rate between 1990 and 2019 by region, etiology, age, and sex, and calculated the estimated annual percentage change (EAPC) of the rate to evaluate the epidemiological trends. Results:Globally, incident cases of CKD increased from 7.80 million in 1990 to 18.99 million in 2019, and DALYs increased from 21.50 million to 41.54 million. ASIR increased with an EAPC of 0.69 (95% uncertainty interval [UI] 0.49–0.89) and reached 233.65 per 100,000 in 2019, while the age-standardized DALY rate increased with an EAPC of 0.30 (95% UI 0.17–0.43) and reached 514.86 per 100,000. North Africa and the Middle East, central Latin America, and North America had the highest ASIR in 2019. Central Latin America had the highest age-standardized DALY rate, meanwhile. Almost all countries experienced an increase in ASIR, and over 50% of countries had an increasing trend in age-standardized DALY rate from 1990 to 2019. CKD due to diabetes mellitus type 2 and hypertension accounted for the largest disease burden with 85% incident cases and 66% DALYs in 2019 of known causes, with the highest growth in age-standardized DALY rate and a similar geographic pattern to that of total CKD. Besides, the highest incidence rate of total and four specific CKDs were identified in people aged 70 plus years, who also had the highest DALY rate with a stable trend after 2010. Females had a higher ASIR, while males had a higher age-standardized DALY rate, the gap of which was most distinctive in CKD due to hypertension. Conclusion:The disease burden of CKD remains substantial and continues to grow globally. From 1990 to 2019, global incident cases of CKD have more than doubled and DALYs have almost doubled, and surpassed 40 million years. CKD due to diabetes mellitus type 2 and hypertension contributed nearly 2/3 of DALYs in 2019 of known causes, and had witnessed the highest growth in age-standardized DALY rate. Etiology-specific prevention strategies should be placed as a high priority on the goal of precise control of CKD.

The convergence of policy gradient algorithms hinges on the optimization landscape of the underlying optimal control problem. Theoretical insights into these algorithms can often be acquired from analyzing those of linear quadratic control. However, most of the existing literature only considers the optimization landscape for static full-state or output feedback policies (controllers). In this article, we investigate the more challenging case of dynamic output-feedback policies for linear quadratic regulation (abbreviated as dLQR), which is prevalent in practice but has a rather complicated optimization landscape. We first show how the dLQR cost varies with the coordinate transformation of the dynamic controller, and then, derive the optimal transformation for a given observable stabilizing controller. One of our core results is the uniqueness of the stationary point of dLQR when it is observable, which provides an optimality certificate for solving dynamic controllers using policy gradient methods. Moreover, we establish conditions under which dLQR and linear quadratic Gaussian control are equivalent, thus providing a unified viewpoint of optimal control of both deterministic and stochastic linear systems. These results further shed light on designing policy gradient algorithms for more general decision-making problems with partially observed information.

• The Cu NPs modified Ti 3 C 2 Cl 2 MXene (CMX) was prepared by one-step lewis acid molten salt etching method, which has the merits of safe, efficient and convenient. • The zincophilic and hydrophobic Ti 3 C 2 Cl 2 MXene (CMX) coating can provide a large number of zincophilic nucleation sites, and its high conductivity can homogenize the interfacial charge distribution and effectively inhibit the growth of zinc dendrites. At the same time, the contact between the zinc anode and the water in the electrolyte is blocked, so that the hydrogen evolution reaction (HER) and corrosion can be inhibited. • The Ti 3 C 2 Cl 2 MXene (CMX) coating can guide Zn2+ to deposit preferentially along (002) surface. Dendrites growth, chemical corrosion, and hydrogen evolution reaction (HER) on zinc anodes are the main barriers for the development of aqueous zinc-ion batteries (AZIBs). Constructing interfacial protective layer is an effective way to alleviate the side reactions on the anodes. Herein, Cu/Ti 3 C 2 Cl 2 MXene (CMX) with high zincophilic and hydrophobic property is prepared by the lewis molten salts etching method, and the CMX interface protection layer is constructed by a simple spin coating. The CMX coating layer can provide abundant nucleation sites and uniformize the charge distribution through the zincophilic Ti 3 C 2 Cl 2 MXene matrix, leading to homogenous Zn deposition. In addition, the hydrophobic coating contained anti-corrosive Cu nanoparticles can prevent the Zn anode from the electrolyte, beneficial for suppressing the chemical corrosion and HER. Therefore, the stable and reversible Zn plating/stripping is achieved for the Zn anode coated by the CMX, which exhibits the lifespan of over 1400 h at 0.5 mA cm−2, and even can steadily run for 700 h with 65 mV at 10 mA cm−2. Furthermore, CMX@Zn shows a high coulombic efficiency of over 100% for 3800 cycles, which indicates that the CMX@Zn electrode has excellent stability and reversibility of Zn stripping/plating. The full batteries assembled with ZnCoMnO/C (ZCM) cathodes also exhibits higher capacity (450.6 mAh g−1 at 0.1 A g−1) and cycle stability (capacity retention of 70% after 1500 cycles). This work enhanced the lifespan of AZIBs and broaden the research of multifunctional coating layer to other secondary batteries based on metal anodes. [Display omitted] [ABSTRACT FROM AUTHOR]

Graphical Abstract:

Purpose: This study aimed to identify the most appropriate squat posture for women by analyzing different squatting methods and weights. Methods: Twelve healthy women were recruited as subjects (age: 20.1 ± 1.2 years, height: 163.4 ± 3.7 cm, weight: 57.9 ± 4.9 kg). The 10-camera Vicon MX13 + motion capture system was used to collect squat and shallow squat motion images at 250 Hz sample rate and a Kistler force plate was used to collect ground reaction force at a 1000 Hz sample rate. The two-way ANOVA (α= .05) was applied to assess for significance. Results: The knee joint torque increased as the weight increased (p< .001). The weight affects maximum knee flexion and joint torque during extension, but no difference was found between the squat and shallow squat methods. Greater knee maximum adduction/abduction and internal/external rotation torque were found in squat lifting. Conclusion: The squat and shallow squat had a similar knee loading under the same weight. Shallow squatting yielded better knee stability, which makes it more suitable for the general female population. Squat training was found to be more suitable for well-trained athletes.

Data-driven predictive control of connected and automated vehicles (CAVs) has received increasing attention as it can achieve safe and optimal control without relying on explicit dynamical models. However, employing the data-driven strategy involves the collection and sharing of privacy-sensitive vehicle information, which is vulnerable to privacy leakage and might further lead to malicious activities. In this paper, we develop a privacy-preserving data-enabled predictive control scheme for CAVs in a mixed traffic environment, where human-driven vehicles (HDVs) and CAVs coexist. We tackle external eavesdroppers and honest-but-curious central unit eavesdroppers who wiretap the communication channel of the mixed traffic system and intend to infer the CAVs’ state and input information. An affine masking-based privacy protection method is designed to conceal the true state and input signals, and an extended form of the data-enabled predictive leading cruise control under different data matrix structures is derived to achieve privacy-preserving optimal control for CAVs. Numerical simulations demonstrate that the proposed scheme can protect the privacy of CAVs against attackers without affecting control performance or incurring heavy computations.

Low excitation voltage (LEV) electromagnetic ultrasonic detection is needed for the safety of high-temperature boilers, reactors, pipelines, and other equipment. However, the low signal intensity and high noise due to the LEV and the high-temperature environment result in a low signal-to-noise ratio (SNR) in the defect detection process. This study proposes a novel noise reduction method, called VMD-singular value decomposition (SVD)-CEEMD (VSCE), which utilizes variational mode decomposition (VMD), SVD, and complementary ensemble empirical mode decomposition (CEEMD) to extract defect information and suppress pulsating noise, instrument noise, and high-temperature structural noise. The shear wave generated by an electromagnetic acoustic transducer was used to detect two different materials at 25 V LEV, with a temperature range of 25 °C–700 °C. The VSCE method was found to improve the SNR of received signals by two to three times compared to conventional denoising methods, such as wavelet threshold denoising (WTD), VMD, and empirical mode decomposition (EMD). The positioning error of the defect location is less than 2.06%, which has proven the great application prospects and value of the VSCE methods in the LEV detection of high-temperature equipment.

The intricate and dynamic nature of eye movements serves as a window into the realms of cognition, emotion, and physiological responses. Event detection, in turn, is instrumental in the precise recognition and categorization of these diverse eye movements. Deep learning methods have recently been applied to event detection, yielding promising results. However, the intrinsic multi-scale attributes of events have often been overlooked in existing approaches. To address this, we introduce “GazeUNet”, a novel network based on U-Net and Bi-GRU, which classifies gaze samples into three categories: fixation, saccade, and post-saccadic oscillations. Firstly, multi-scale spatial features are captured using a U-Net model, and then a hierarchical bidirectional gated recurrent unit (Bi-GRU) is employed to extract temporal correlations, followed by classification through fully connected layers. Our results, derived from the analysis of three publicly available datasets, consistently showcase the superiority of the proposed model compared with other state-of-the-art methods across all categories.

Designing hybrid materials with numerous catalytic active sites, high specific surface area, and interfacial interactions is an effective strategy to improve electrocatalytic performance. In this work, iron-based metal organic frameworks (Fe-MOFs)@(Co, Ni)Fe-layered double hydroxide (LDH) is successfully constructed using the similar “MOF growing on LDH” strategy for oxygen evolution reaction and hydrogen evolution reaction in the alkaline electrolyte. The synthesized hybrid materials in this particular way show excellent electrochemical overall water-splitting performance with the cell voltage of 1.62 V at 10 mA·cm−2in the alkaline environment due to the optimized adsorption/desorption properties of metal ions on oxygen-containing species and interfacial effects of hybrid materials. Fe-MOFs@(Co, Ni)Fe-LDH also exhibits excellent hydrogen and oxygen production efficiency of 370 and 175 μL·min−1, respectively. This work draws on an effective approach to the fabrication of MOF@LDH structures and provides new insights into overall water-splitting in alkaline conditions.

Shear wave elastography (SWE) enables the measurement of elastic properties of soft materials in a non-invasive manner and finds broad applications in various disciplines. The state-of-the-art SWE methods rely on the measurement of local shear wave speeds to infer material parameters and suffer from wave diffraction when applied to soft materials with strong heterogeneity. In the present study, we overcome this challenge by proposing a physics-informed neural network (PINN)-based SWE (SWENet) method. The spatial variation of elastic properties of inhomogeneous materials has been introduced in the governing equations, which are encoded in SWENet as loss functions. Snapshots of wave motions have been used to train neural networks, and during this course, the elastic properties within a region of interest illuminated by shear waves are inferred simultaneously. We performed finite element simulations, tissue-mimicking phantom experiments, and ex vivo experiments to validate the method. Our results show that the shear moduli of soft composites consisting of matrix and inclusions of several millimeters in cross-section dimensions with either regular or irregular geometries can be identified with excellent accuracy. The advantages of the SWENet over conventional SWE methods consist of using more features of the wave motions and enabling seamless integration of multi-source data in the inverse analysis. Given the advantages of SWENet, it may find broad applications where full wave fields get involved to infer heterogeneous mechanical properties, such as identifying small solid tumors with ultrasound SWE, and differentiating gray and white matters of the brain with magnetic resonance elastography.