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Programmed cell death ligand-1 (PD-L1) is a T cell inhibitory immune checkpoint molecule that interacts with programmed cell death-1 (PD-1) to promote immune escape of tumor cells. Compared with antibody therapies, small molecule drugs show better prospects due to their advantages such as higher bioavailability, better tissue penetration, and reduced risk of immunogenicity. Here, we found that the small molecule demethylzeylasteral (Dem) can significantly downregulate the expression of PD-L1 in colorectal cancer cells and enhance the killing effect of T cells on tumor cells. Mechanistically, Dem binds to the deubiquitinating enzyme USP22 and promotes its degradation, resulting in increased ubiquitination and degradation of PD-L1 through the proteasome pathway. In addition, Dem increased the activity of cytotoxic T cells and reduced the number of myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs) in tumor-infiltrating lymphocytes (TILs), thereby activating the tumor immune microenvironment and inhibiting the growth of subcutaneous MC38 tumors in C57BL/6 mice. Moreover, we also found that the combination of Dem and CTLA4 antibodies can further improve the efficacy of antitumor therapy. Our study reveals the mechanism by which Dem promotes PD-L1 degradation and suggests that the combination of Dem and CTLA4 antibodies may improve the efficacy of immunotherapy.

The problem of surface deformation caused by coal mining is acute and usually lasts for a long time. During coal mining, the movement of the overlying strata has a broad range of influences, which may cause surface deformation, surface cracking, and damage to structures (buildings). However, continuous deformation monitoring data are often scarce in practice, making it challenging to predict the surface deformation caused by coal mining. In this context, this paper takes Sichuan’s Guanshan coalfield as the research object and proposes a comprehensive method integrating interferometric synthetic aperture radar (InSAR) technology, the FLAC3D finite difference software, and the probability integral method to predict the surface deformation caused by mining a thin seam of coal. The results show that the trend of surface deformation estimated by the numerical simulation agrees well with the results of InSAR data and the probability integral model when using InSAR historical deformation data to invert the parameters of rock mechanics in the numerical simulation, which is beneficial to improving the reliability of the simulation results. The calculations of the probability integral method are close to the predictions of the FLAC3D numerical simulation, and a settlement deformation of 0.68 ​m is expected to occur in the Guanshan coalfield area. The comprehensive prediction method proposed in this paper effectively enhances the accuracy of surface deformation prediction under the action of mining and can provide a reference for predicting the surface subsidence of similar coal mines.

Abstract Targeting the programmed cell death 1/programmed cell death ligand 1 (PD‐1/PD‐L1) pathway has been identified as a successful approach for tumor immunotherapy. Here, we identified that the small molecule 5,7,4′‐trimethoxyflavone (TF) from Kaempferia parviflora Wall reduces PD‐L1 expression in colorectal cancer cells and enhances the killing of tumor cells by T cells. Mechanistically, TF targets and stabilizes the ubiquitin ligase HMG‐CoA reductase degradation protein 1 (HRD1), thereby increasing the ubiquitination of PD‐L1 and promoting its degradation through the proteasome pathway. In mouse MC38 xenograft tumors, TF can activate tumor‐infiltrating T‐cell immunity and reduce the immunosuppressive infiltration of myeloid‐derived suppressor cells and regulatory T cells, thus exerting antitumor effects. Moreover, TF synergistically exerts antitumor immunity with CTLA‐4 antibody. This study provides new insights into the antitumor mechanism of TF and suggests that it may be a promising small molecule immune checkpoint modulator for cancer therapy.

Abstract To monitor in situ the temperature, pH, and micro-strain change information of sandstone artifacts in the process of oxalic acid corrosion, the temperature, pH, and micro-strain fiber Bragg grating (FBG) sensors are developed. A theoretical model of the sensors is established. The surface morphology, material composition, pore structure, temperature, pH, and micro-strain of sandstone corroded by oxalic acid solutions of different concentrations are investigated. The experimental results show that the higher the concentration of oxalic acid, the stronger the corrosiveness of the sandstone. Ferrous oxalate and calcium oxalate produced by corrosion continuously precipitate from the inside of the rock, and the dual reaction of crystallization and dissolution occurs, reducing the proportion of fine pores in the rock pore suction and gravity. The oxalic acid solution is transported to the middle of the sandstone (3 cm) and undergoes the strongest chemical reaction with ore particles and debris, resulting in the maximum wavelength drift of the temperature, pH, and micro-strain sensors. The results of this study provide important support for analyzing the acid dissolution mechanism of stone cultural relics and the preventive protection of cultural relics.

Abstract Numerous applications require indoor localisation, and one of the current research areas is how to leverage low‐cost ubiquitous signals for indoor localisation. This research designs a multi‐input convolutional neural network (Multi‐CNN) localisation approach to combine natural geomagnetic signals and universal 5G communication signals. To create the location fingerprint data, the geomagnetic three‐component data and channel state information (CSI) must first undergo independent preprocessing. Subsequently, the rebuilt CSI amplitude and geomagnetic intensity are employed for separate offline training to efficiently extract the corresponding data features. Lastly, Multi‐CNN is used to estimate the user's location online. The localisation outcomes for the conference room and hall demonstrate that the Multi‐CNN algorithm can achieve average localisation accuracies of 1.41 and 2.66 m, respectively. These are higher than the single‐input CNN algorithms by 21% and 15%, and higher than backpropagation network (BPNN) algorithm by 24% and 17%, and higher than the weighted K‐nearest neighbour algorithm by 34% and 28%. The Multi‐CNN‐based localisation approach successfully fuses the diverse data, potentially satisfying most indoor localisation applications.

Soil, water, and nutrients depletion may affect sustainable agriculture in some resource-poor areas. Implementing cover crops as a conservation management strategy mitigates the loss of water, soil, nitrogen (N), and phosphorus (P) by introducing vegetation during non-crop seasons or in the spaces between rows instead of leaving the land bare. This study aimed to compare water, soil, various carbon (C) forms, N, and P losses through leaching and surface runoff in orchard fields that were managed with either no-cover crop (NC) or cover crops, including natural grass (NG), Legume grass (LG), Gramineae grass (GG), and a mixture of Legume and Gramineae grass (MG). The findings indicate that cover crop fields exhibited a significant reduction in the runoff by 33–60 %, leaching amount by 33–51 %, soil loss by 30–53 %, and total C, N, and P by 30–48 %, 30–49 %, and 30–38 %, respectively compared to NC fields. Additionally, implementing artificial grass, particularly MG, demonstrated more significant efficacy in mitigating water and soil losses and associated N and P losses. Specifically, MG fields exhibited a 40 % and 18 % reduction in runoff and leaching as well as a reduction in total C, N, and P loss by 7 %, 12 %, and 7 %, respectively, compared to NG fields. The LG field experienced a 50 % more significant N loss than the MG field, whereas the GG runoff exhibited an increase of more than 70 %. Implementing MG coverage has significantly reduced soil erosion and consequent nutrient loss, establishing it as a viable and uncomplicated approach to conserving soil and water in orchards.

Two-dimensional (2D) auxetic properties and ferromagnetism are two major focuses of research for next-generation nanomechanical and spintronic devices. However, 2D materials with the two properties at the same time are rarely reported. Based on first-principles calculations, we propose the 2D bimetallic phosphide ScMP2 (M = Mn and Cr), including three stable tetragonal monolayers. The monolayer ScMnP2 exhibit the square structural phase while there is a structural phase transition between the square ScCrP2 and the rectangular ScCrP2, which originates from the mechanism of ferroelasticity and ferroelectricity. Both monolayers ScCrP2 exhibit in-plane auxetic properties, and the value of the negative Poisson’s ratio can reach –0.322. All the three monolayers show a ferromagnetic ground state with high Curie temperature, and are a Dirac half-metal without spin–orbit coupling (SOC). When considering SOC, a nontrivial bandgap can be found in the monolayer ScMnP2, which further becomes a half-Chern insulator. Importantly, the structural phase transitions from the square lattice to the rectangular lattice in the monolayers ScCrP2 will enable a significant improvement in the values of negative Poisson’s ratio and magnetic anisotropic energy simultaneously. Taking the multiferroic (ferroelastic, ferroelectric, and ferromagnetic), auxetic, and topological properties into consideration, the 2D system of ScMP2 provide promising applications for future multifunctional nanodevices.

Abstract The PPP–RTK method, which combines the concepts of Precise of Point Positioning (PPP) and Real-Time Kinematic (RTK), is proposed to provide a centimeter-accuracy positioning service for an unlimited number of users. Recently, the PPP–RTK technique is becoming a promising tool for emerging applications such as autonomous vehicles and unmanned logistics as it has several advantages including high precision, full flexibility, and good privacy. This paper gives a detailed review of PPP–RTK focusing on its implementation methods, recent achievements as well as challenges and opportunities. Firstly, the fundamental approach to implement PPP–RTK is described and an overview of the research on key techniques, such as Uncalibrated Phase Delay (UPD) estimation, precise atmospheric correction retrieval and modeling, and fast PPP ambiguity resolution, is given. Then, the recent efforts and progress are addressed, such as improving the performance of PPP–RTK by combining multi-GNSS and multi-frequency observations, single-frequency PPP–RTK for low-cost devices, and PPP–RTK for vehicle navigation. Also, the system construction and applications based on the PPP–RTK method are summarized. Moreover, the main issues that impact PPP–RTK performance are highlighted, including signal occlusion in complex urban areas and atmosphere modeling in extreme weather events. The new opportunities brought by the rapid development of low-cost markets, multiple sensors, and new-generation Low Earth Orbit (LEO) navigation constellation are also discussed. Finally, the paper concludes with some comments and the prospects for future research.

Underwater sound speed is one of the most significant factors that affects high-accuracy underwater acoustic positioning and navigation. Due to its complex temporal variation, the forecasting of the underwater sound speed field (SSF) becomes a challenging task. Taking advantage of machine learning methods, we propose a new method for SSF forecasting based on the least square support vector machine (LSSVM) and a multi-parameter model, aiming to enhance the forecasting accuracy of underwater SSF with hourly resolution. We first use a matching extension method to standardize profile data and train the LSSVM with the parameters of observation time, temperature, salinity, and depth. We then employ radial basis function kernels to construct the forecasting model of SSF. We validate the feasibility and effectiveness of the LSSVM model by comparing it with the polynomial fitting (PF) and back propagation neural network (BPNN) methods, using hourly data obtained from the measured data and open data. The results show that the means of the root mean square for the LSSVM based on the observation time parameter and the LSSVM based on the multi-parameter model achieve 0.51 m/s and 0.45 m/s, respectively, presenting a significant improvement compared with the PF (0.82 m/s) and BPNN (0.76 m/s) methods.

Integrating the relaying drone and non-orthogonal multiple access (NOMA) technique into post-disaster emergency communications (PDEComs) is a promising way to accomplish efficient network recovery. Motivated by the above, by optimizing the drone three-dimensional (3D) deployment optimization and spectrum allocation, this paper investigates a quality of service (QoS)-driven sum rate maximization problem for drone-and-NOMA-enhanced PDEComs that aims to improve the data rate of cell edge users (CEUs). Due to the non-deterministic polynomial (NP)-hard characteristics, we first decouple the formulated problem. Next, we obtain the optimal 3D deployment with the aid of a long short-term memory (LSTM)-based recurrent neural network (RNN). Then, we transform the spectrum allocation problem into an optimal matching issue, based on which the Hungarian algorithm is employed to solve it. Finally, the simulation results show that the presented scheme has a significant performance improvement in the sum rate compared with the state-of-the-art works and benchmark scheme. For instance, by adopting the NOMA technique, the sum rate can be increased by 9.72% and the needs of CEUs can be satisfied by enabling the relaying drone. Additionally, the convergence, complexity, and performance gap caused by iterative optimization are discussed and analyzed.

Tetracyclines are refractory pollutants that cause persistent harm to the environment and human health. Therefore, it is urgently necessary to develop methods to promote the efficient degradation and conversion of tetracyclines in wastewater. This report proposes a photobiocatalytic synergistic system involving the coupling of GeO2/Zn-doped phosphotungstic acid hydrate/TiO2 (GeO2/Zn-HPW/TiO2)-loaded photocatalytic optical hollow fibers (POHFs) and an algal–bacterial biofilm. The GeO2/Zn-HPW/TiO2 photocatalyst exhibits a broad absorption edge extending to 1000 nm, as well as high-efficiency photoelectric conversion and electron transfer, which allow the GeO2/Zn-HPW/TiO2-coated POHFs to provide high light intensity to promote biofilm growth. The resulting high photocatalytic activity rapidly and stably reduces the toxicity and increases the biodegradability of tetracycline-containing wastewater. The biofilm enriched with Salinarimonas, Coelastrella sp., and Rhizobium, maintains its activity for the rapid photocatalytic degradation and biotransformation of intermediates to generate the O2 required for photocatalysis. Overall, the synergistic photocatalytic biofilm system developed herein provides an effective and efficient approach for the rapid degradation and conversion of water containing high concentrations of tetracycline.

Aqueous zinc (Zn)‐ion batteries (ZIBs) have been considered as the most promising candidate for large‐scale energy storage system. However, the severe and uncontrollable dendrite growth of Zn anodes hinders the practical application. Herein, an ultraconformal horizontal Zn deposition is achieved, which is profiting from the epitaxial interface (InGaZn6O9) formed via spontaneously alloying between liquid Ga–In alloy (EGaIn) and Zn. The exposed (0016) plane of InGaZn6O9 matches well with (002) plane of Zn, inducing horizontal and dense Zn deposition. The resultant anode endows with prolonged cycling stability, and the full battery paired with MnO2 exhibits a stable lifespan over 4400 cycles at 5 A g−1. Meanwhile, the self‐formed ultraconformal interface realizes 360° no dead angle protection of anode, which is promising in flexible electronics. And there is no obvious capacity recession of the pouch cell even after bending 180°, demonstrating impressive flexibility. More importantly, the interface can be simply fabricated over a large area, displaying the large‐scale viability. The tailored approach delivers a constructive guideline for dendrite‐free Zn anode, showing great potential in the industrial production.

With the widespread application of GNSS, the delicate handling of biases among different systems and different frequencies is of critical importance, wherein the inter-frequency clock biases (IFCBs) and observable-specific signal biases (OSBs) should be carefully corrected. Usually, a serial approach is used to calculate these products. To accelerate the computation speed and reduce the time delay, a multicore parallel estimation strategy for IFCBs, code, and phase OSBs by utilizing task parallel library (TPL) is proposed, the parallel computations, including precise point positioning (PPP), IFCBs, and OSBs estimation, being carried out on the basis of data parallelisms and task-based asynchronous programming. Three weeks of observables from the multi-GNSS experiment campaign (MGEX) network is utilized. The result shows that the IFCB errors of GPS Block IIF and GLONASS M+ satellites are nonnegligible, in which the GLONASS M+ satellite R21 shows the largest IFCB of more than 0.60 m, while those of other systems and frequencies are marginal, and the code OSBs present excellent stability with a standard deviation (STD) of 0.10 ns for GPS and approximately 0.20 ns for other satellite systems. Besides, the phase OSBs of all systems show the stability of better than 0.10 ns, wherein the Galileo satellites show the best performance of 0.01 ns. Compared with the single-core serial computing method, the acceleration rates for IFCBs and OSBs estimation are 3.10, 5.53, 9.66, and 17.04 times higher using four, eight, sixteen, and thirty-two physical cores, respectively, through multi-core parallelized execution.

To provide continuous and reliable real−time precise positioning services in challenging environments and poor internet conditions, the real−time precise corrections of the BeiDou global navigation satellite system (BDS−3) PPP−B2b signal are utilized to correct the satellite orbit errors and clock offsets. In addition to this, using the complementary characteristics of the inertial navigation system (INS) and the global navigation satellite system (GNSS), a PPP−B2b/INS tight integration model is established. With observation data collected in an urban environment, the results show that PPP−B2b/INS tight integration can ensure a decimeter−level positioning accuracy; the positioning accuracies of the E, N, and U components are 0.292, 0.115, and 0.155 m, respectively, which can provide a continuous and secure position during short interruptions in the GNSS. However, there is still a gap of about 1 dm compared with the three−dimensional (3D) positioning accuracy obtained from Deutsche GeoForschungsZentrum (GFZ) real−time products, and a gap of about 2 dm compared with the GFZ post−precise products. Using a tactical inertial measurement unit (IMU), the velocimetry accuracies of the tightly integrated PPP−B2b/INS in the E, N, and U components are all about 0.3 cm/s, and the attitude accuracy of yaw is about 0.1 deg, while the pitch and roll show a superior performance of less than 0.01 deg. The accuracies of the velocity and attitude mainly depend on the performance of the IMU in the tight integration mode, and there is no significant difference between using real−time products and post products. The performance of the microelectromechanical system (MEMS) IMU and tactical IMU is also compared, and the positioning, velocimetry, and attitude determinations with the MEMS IMU are significantly worsened.

For positioning tasks of mobile robots in indoor environments, the emerging positioning technique based on visual inertial odometry (VIO) is heavily influenced by light and suffers from cumulative errors, which cannot meet the requirements of long-term navigation and positioning. In contrast, positioning techniques that rely on indoor signal sources such as 5G and geomagnetism can provide drift-free global positioning results, but their overall positioning accuracy is low. In order to obtain higher precision and more reliable positioning, this paper proposes a fused 5G/geomagnetism/VIO indoor localization method. Firstly, the error back propagation neural network (BPNN) model is used to fuse 5G and geomagnetic signals to obtain more reliable global positioning results; secondly, the conversion relationship from VIO local positioning results to the global coordinate system is established through the least squares principle; and finally, a fused 5G/geomagnetism/VIO localization system based on the error state extended Kalman filter (ES-EKF) is constructed. The experimental results show that the 5G/geomagnetism fusion localization method overcomes the problem of low accuracy of single sensor localization and can provide more accurate global localization results. Additionally, after fusing the local and global positioning results, the average positioning error of the mobile robot in the two scenarios is 0.61 m and 0.72 m. Compared with the VINS-mono algorithm, our approach improves the average positioning accuracy in indoor environments by 69.0% and 67.2%, respectively.

With the modernization of GLONASS, four M+ and two K satellites are able to broadcast code-division multiple-access signals at a G3 frequency. The evaluation of the G3 frequency is necessary, among which the satellite-induced code pseudorange variation is one of the most important indicators. Using the code-minus-carrier (CMC) combination, it was found that the magnitude of the code pseudorange variations at the G3 frequency is about 1 m, which is primarily caused by the fact that G3 is transmitted from a different antenna, the same as G1 and G2. However, different from BDS-2 medium Earth orbit and inclined geo-synchronous orbit satellites, the code pseudorange variations at the GLONASS G3 frequency have a very weak relationship with the elevation angle, while a strong correlation exists with the time series, by using wavelet transformation and correlation analysis. Validation is carried out using a single-site model and a continuous multi-site model over 24 h, and the correction performance of these two models is comparable. The systematic deviation of the CMC and Melbourne–Wübbena combinations are significantly corrected, so only random errors remain. With a more concentrated distribution of the pseudorange residuals of single point positioning, the standard deviation of the pseudorange residuals is reduced.

Global navigation satellite system (GNSS) signals are easily blocked by urban canyons, tree-lined roads, and overpasses in urban environments, making it impossible to ensure continuous and reliable positioning using only GNSS, even with the widely used precise point positioning and real-time kinematic (PPP-RTK). Since the inertial navigation system (INS) and GNSS are complementary, a tightly coupled PPP-RTK/INS model is developed to improve the positioning performance in these GNSS-challenged scenarios, in which the atmospheric corrections are used to achieve a rapid ambiguity resolution and the mechanization results from INS are utilized to assist GNSS preprocessing, re-fixing, and reconvergence. The experiment was conducted using three sets of vehicle-mounted data, and the performance of low-cost receiver and microelectromechanical system (MEMS) inertial measurement unit (IMU) was compared. The result shows that the positioning accuracy of PPP-RTK/INS can reach 2 cm in the horizontal component and 5 cm in the vertical component in the open environment. In the complex urban environment, continuous and reliable positioning can be ensured during GNSS short interruption, ambiguity can be instantaneously re-fixed with the assistance of INS, and decimeter-level positioning accuracy can be achieved. As a result, the horizontal positioning errors of more than 95% of the total epochs were within 20 cm. In addition, average positioning accuracy better than 15 cm and 30 cm in the horizontal and vertical components, respectively, can be obtained using the low-cost receiver and MEMS IMU. Compared with tactical IMU, the improvements in positioning accuracy and the ambiguity fixing rate using the geodetic receiver were more significant.

The wide use of cooperative missions using multiple unmanned platforms has made relative distance information an essential factor for cooperative positioning and formation control. Reducing the range error effectively in real time has become the main technical challenge. We present a new method to deal with ranging errors based on the distance increment (DI). The DI calculated by dead reckoning is used to smooth the DI obtained by the cooperative positioning, and the smoothed DI is then used to detect and estimate the non-line-of-sight (NLOS) error as well as to smooth the observed values containing random noise in the filtering process. Simulation and experimental results show that the relative accuracy of NLOS estimation is 8.17%, with the maximum random error reduced by 40.27%. The algorithm weakens the influence of NLOS and random errors on the measurement distance, thus improving the relative distance precision and enhancing the stability and reliability of cooperative positioning.

Dumbbell-like structures are recently found to be energetically favored in group IV two-dimensional (2D) materials, exhibiting rich physics and many interesting properties. In this paper, using first-principles calculations, we have investigated the oxidized form of the hexagonal honeycomb (ODB-h) and zigzag dumbbell silicene (ODB-z). We confirm that both oxidization processes are energetically favorable, and their phonon spectra further demonstrate the dynamic stability. Contrary to the pristine dumbbell silicene structures (PDB-h and PDB-z silicene), these oxidized products ODB-h and ODB-z silicene are both semimetals with Dirac cones at the Fermi level. The Dirac cones of ODB-h and ODB-z silicene are at the K point and between Y and Γ points respectively, possessing high Fermi velocities of 3.1 × 10 ^5 m s ^−1 (ODB-h) and 2.9–3.4 × 10 ^5 m s ^−1 (ODB-z). The origin of the Dirac cones is further explained by tight-binding models. The semimetallic properties of ODB-h and ODB-z are sensitive to compression due to the self-absorption effect, but quite robust against the tensile strain. These outstanding properties make oxidized dumbbell silicene a promising material for quantum computing and high-speed electronic devices.

The electronic band structure and valley splitting of the WSe _2 /NiCl _2 heterostructure have been investigated by density functional theory and Berry curvature calculations. We demonstrate that the valley polarization of monolayer WSe _2 is induced due to the magnetic proximity effect caused by the single layer of ferromagnetic NiCl _2 . The magnitude of valley splitting depends on the stacking configurations of WSe _2 /NiCl _2 , and the maximum value of valley splitting reaches −11.87 meV. Large valley splitting can be achieved by adjusting the layer spacing and constructing a NiCl _2 /WSe _2 /NiCl _2 heterojunction with Ni spins arranged in parallel between two NiCl _2 sheets. The valley-contrasting Berry curvature between the K and K ′ valleys suggests that the WSe _2 /NiCl _2 -based heterostructure could potentially be used as a valleytronic device to realize the valley-polarized anomalous Hall effect as both spin and valley filter.