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Highlights High-entropy oxides O3-Na0.95Li0.06Ni0.25Cu0.05Fe0.15Mn0.49O2 cathode constructed by compatible radius and different Fermi level ions was designed for solid-state Na-ion batteries. Na0.95Li0.06Ni0.25Cu0.05Fe0.15Mn0.49O2 cathode exhibits high-rate performance, air stability and electrochemically thermal stability. A series of characterizations were performed to explore energy storage mechanism of Na0.95Li0.06Ni0.25Cu0.05Fe0.15Mn0.49O2.

The significant regulatory role of palmitoylation modification in cancer-related targets has been demonstrated previously. However, the biological functions of Nrf2 in stomach cancer and whether the presence of Nrf2 palmitoylation affects gastric cancer (GC) progression and its treatment have not been reported. Several public datasets were used to look into the possible link between the amount of palmitoylated Nrf2 and the progression and its outcome of GC in patients. The palmitoylated Nrf2 levels in tumoral and peritumoral tissues from GC patients were also evaluated. Both loss-of-function and gain-of-function via transgenic experiments were performed to study the effects of palmitoylated Nrf2 on carcinogenesis and the pharmacological function of 2-bromopalmitate (2-BP) on the suppression of GC progression in vitro and in vitro. We discovered that Nrf2 was palmitoylated in the cytoplasmic domain, and this lipid posttranslational modification causes Nrf2 stabilization by inhibiting ubiquitination, delaying Nrf2 destruction via the proteasome and boosting nuclear translocation. Importantly, we also identify palmitoyltransferase zinc finger DHHC-type palmitoyltransferase 2 (DHHC2) as the primary acetyltransferase required for the palmitoylated Nrf2 and indicate that the suppression of Nrf2 palmitoylation via 2-bromopalmitate (2-BP), or the knockdown of DHHC2, promotes anti-cancer immunity in vitro and in mice model-bearing xenografts. Of note, based on the antineoplastic mechanism of 2-BP, a novel anti-tumor drug delivery system ground 2-BP and oxaliplatin (OXA) dual-loading gold nanorods (GNRs) with tumor cell membrane coating biomimetic nanoparticles (CM@GNRs-BO) was established. In situ photothermal therapy is done using near-infrared (NIR) laser irradiation to help release high-temperature-triggered drugs from the CM@GNRs-BO reservoir when needed. This is done to achieve photothermal/chemical synergistic therapy. Our findings show the influence and linkage of palmitoylated Nrf2 with tumoral and peritumoral tissues in GC patients, the underlying mechanism of palmitoylated Nrf2 in GC progression, and novel possible techniques for addressing Nrf2-associated immune evasion in cancer growth. Furthermore, the bionic nanomedicine developed by us has the characteristics of dual drugs delivery, homologous tumor targeting, and photothermal and chemical synergistic therapy, and is expected to become a potential platform for cancer treatment.

Highly active bifunctional oxygen electrocatalysts accelerate the development of high-performance Zn-air battery, but suffer from the mismatched activities of oxygen evolution reaction (OER) and oxygen reduced reaction (ORR). Herein, highly integrated bifunctional oxygen electrocatalysts, cobalt-tin alloys coated by nitrogen doped carbon (CoSn@NC) are prepared by MOFs-derived method. In this hybrid catalyst, the binary CoSn nanoalloys mainly contribute to highly active OER process while the Co (or Sn)−N−C serves as ORR active sites. Rational interaction between CoSn and NC donates more rapid reaction kinetics than Pt/C (ORR) and IrO2 (OER). Such CoSn@NC holds a promise as air-cathode electrocatalyst in Zn-air battery, superior to Pt/C + IrO2 catalyst. First-principles calculations predict that CoSn alloys can upgrade charge redistribution on NC and promote the transfer to reactants, thus optimizing the adsorption strength of oxygen-containing intermediates to boost the overall reactivity. The tuning of oxygenate adsorption by interactions between alloy and heteroatom-doped carbon can guide the design of bifunctional oxygen electrocatalysts.

Abstract Gastric signet ring cell carcinoma (GSRC) is a special subtype of gastric cancer (GC) associated with poor prognosis, but an in-depth and systematic study of GSRC is lacking. Here, we perform single-cell RNA sequencing to assess GC samples. We identify signet ring cell carcinoma (SRCC) cells. Microseminoprotein-beta (MSMB) can be used as a marker gene to guide the identification of moderately/poorly differentiated adenocarcinoma and signet ring cell carcinoma (SRCC). The upregulated differentially expressed genes in SRCC cells are mainly enriched in abnormally activated cancer-related signalling pathways and immune response signalling pathways. SRCC cells are also significantly enriched in mitogen-activated protein kinase and oestrogen signalling pathways, which can interact and promote each other in a positive feedback loop. SRCC cells are shown to have lower cell adhesion and higher immune evasion capabilities as well as an immunosuppressive microenvironment, which may be closely associated with the relatively poor prognosis of GSRC. In summary, GSRC exhibits unique cytological characteristics and a unique immune microenvironment, which may be advantageous for accurate diagnosis and treatment.

Water quality prediction is important for maintaining water stability and control in marine environments. However, water quality parameters are affected by complex environmental factors.Marine time series data exhibit distribution shift and nonstationarity problems, owing to environmental heterogeneity.It is still difficult to obtain the spatial and time dependence of time series data with existing models and the model prediction accuracy cannot be guaranteed. Therefore, this paper proposes a graph-based convolutional neural network model, allowing networks and sequences to interact smoothly. The Time-graph convolutional fusion network(T-GCFN) consists of a graph convolutional fusion network(GCFN) and Time-pyramidal fusion attention(T-PFA). To obtain the spatial dependence of the original sequence, the original sequence is first decomposed into three subsequences by STL, and then the GCFN obtains the original sequence and trinomial subsequence through a multilayer T-GCN.Internal topology information is also obtained. Second, to eliminate the distribution differences between the training and test sets, the T-PFA is weakened using RevIN.To address the distribution shift problem of the sequence and the nonstationarity problem of the destationarized attention attenuation sequence, a higher weight is assigned to the sequence. Finally, depending on the long and short time series of the obtained sequence, the subsequence is downsampled by cross-learning, and the local features are extracted. Experiments on dissolved oxygen, salinity and temperature at six marine ranches on the Shandong peninsula were carried out using the T-GCFN, and the results were compared with those of other deep learning models. The experimental results show that the T-GCFN has better prediction performance and can achieve high-precision predictions of ocean chemistry parameters in the next three days.

Abstract Gastric cancer (GC) remains the third leading cause of cancer-related deaths. Chemoresistance is the major determinant of GC treatment failure. To explore the molecular mechanisms of GC chemoresistance, mass spectrometry was performed to detect the genes altered in expression between chemoresistant and chemosensitive GC. PRKA kinase anchor protein 8L (AKAP-8L) was identified as one of the top upregulated genes in chemoresistant GC tissues. Moreover, the higher AKAP-8L expression was associated with the lower survival rate in GC patients. Overexpression of AKAP-8L enhanced the GC cell stemness and chemoresistance of oxaliplatin in vivo and in vitro. AKAP-8L deficiency obtained the opposite results. Mechanistically, AKAP-8L interacted with Stearoyl-CoA desaturase 1 (SCD1) mRNA and IGF2BP1 protein, and regulated SCD1 mRNA stability via IGF2BP1-dependent manner. SCD1 played a critical role in mediating the function of AKAP-8L in GC cell stemness and chemoresistance. Clinically, AKAP-8L and SCD1 protein levels was positively associated with human GC chemoresistance. Taken together, our results demonstrated that AKAP-8L facilitates GC chemoresistance via regulating SCD1-mediated stemness of GC cells. AKAP8L may represent a novel therapeutic target to overcome GC chemoresistance.

In order to study the influence of water-lubricated bearings on the vibration of the marine magnetic pump, the vibration characteristics of the marine magnetic pump under different flow rates and bearing structural parameters (bearing clearance, eccentricity, and length–diameter ratio) were numerically analyzed. The internal flow fields of marine magnetic pumps and water-lubricated bearing were numerically calculated, and experimental verification of their external characteristics results was conducted. The results show that the vibration velocity level of the pump increases with the increase in the bearing clearance and the bearing eccentricity, and the vibration velocity level of the pump gradually decreases with the increase in the bearing length–diameter ratio. The clearance has the greatest influence on the vibration of the pump, the length–diameter ratio the second, and the eccentricity the smallest. The peak value of vibration velocity at the pump outlet at the vibration measurement point is the highest, the peak value of vibration velocity at the pump inlet is second, and the peak value of vibration velocity at the pump foot is the smallest. However, the peak value of vibration velocity at the pump inlet is most sensitive to changes in operating conditions and bearing structural parameters, with a maximum increase of 6.2 dB. Therefore, the change in the peak value of vibration velocity at the pump inlet can be used as the main indicator for monitoring the operating status of bearings.

Hyperspectral imaging often suffers from various types of noise, including sensor non-uniformity and atmospheric disturbances. Removing multiple types of complex noise in hyperspectral images (HSIs) while preserving high fidelity in spectral dimensions is a challenging task in hyperspectral data processing. Existing methods typically focus on specific types of noise, resulting in limited applicability and an inadequate ability to handle complex noise scenarios. This paper proposes a denoising method based on a network that considers both the spatial structure and spectral differences of noise in an image data cube. The proposed network takes into account the DN value of the current band, as well as the horizontal, vertical, and spectral gradients as inputs. A multi-resolution convolutional module is employed to accurately extract spatial and spectral noise features, which are then aggregated through residual connections at different levels. Finally, the residual mixed noise is approximated. Both simulated and real case studies confirm the effectiveness of the proposed denoising method. In the simulation experiment, the average PSNR value of the denoised results reached 31.47 at a signal-to-noise ratio of 8 dB, and the experimental results on the real data set Indian Pines show that the classification accuracy of the denoised hyperspectral image (HSI) is improved by 16.31% compared to the original noisy version.

Because of the complicated imaging conditions in space and the finite imaging systems on satellites, the resolution of remote sensing images is limited. The process of increasing an image’s resolution, image super-resolution, aims to obtain a clearer image. High-resolution (HR) images are affected by various input conditions, such as motion, imaging blur, down-sampling matrix, and various types of noise. Changes in these conditions seriously affect low-resolution (LR) images, so if the imaging process is a pathological problem, super-resolution reconstruction is a pathological anti-problem. To optimize the imaging quality of satellites without changing the optical system, we chose to reconstruct images acquired by satellites using deep learning. We changed the original super-resolution generative adversarial nets network, upgraded the generator’s network part to ResNet-50, and inserted an additional fully connected (FC) layer in the network of the discriminator part. We also modified the loss function by changing the weight of regularization loss from 2 × 10−8 to 2 × 10−9, aiming to preserve more detail. In addition, we carefully and specifically chose remote sensing images taken under low-light circumstances from GF-5 satellites to form a new dataset for training and validation. The test results proved that our method can obtain good results. The reconstruction peak signal-to-noise ratio (PSNR) at the scaling factors of 2, 3, and 4 reached 32.6847, 31.8191, and 30.5095 dB, respectively, and the corresponding structural similarity (SSIM) reached 0.8962, 0.8434, and 0.8124. The super-resolution speed was also satisfactory, making real-time reconstruction more probable.

The competition between base-induced elimination (E2) and bimolecular nucleophilic substitution (SN2) is of significant importance in organic chemistry and is influenced by many factors. The electronic structure calculations for the gas-phase reactions of F− + RY (R = CH3, C2H5, iC3H7, tC4H9, and Y = Cl, I) are executed at the MP2 level with aug-cc-pVDZ or ECP/d basis set to investigate the α-methyl substitution effect. The variation in barrier height, reaction enthalpy, and competition of SN2/E2 as a function of methyl-substitution and leaving group ability has been emphasized. And the nature of these rules has been explored. As the degree of methyl substitution on α-carbon increases, the E2 channel becomes more competitive and dominant with R varying from C2H5, iC3H7, to tC4H9. Energy decomposition analysis offers new insights into the competition between E2 and SN2 processes, which suggests that the drop in interaction energy with an increasing degree of substitution cannot compensate for the rapid growth of preparation energy, leading to a rapid increase in the SN2 energy barrier. By altering the leaving group from Cl to I, the barriers of both SN2 and E2 monotonically decrease, and, with the increased number of substituents, they reduce more dramatically, which is attributed to the looser transition state structures with the stronger leaving group ability. Interestingly, ∆E0‡ exhibits a positive linear correlation with reaction enthalpy (∆H) and halogen electronegativity. With the added number of substituents, the differences in ∆E0‡ and ∆H between Y = Cl and I likewise exhibit good linearity.

Abstract Due to the continuous rise in biofilm‐related infections, biofilms seriously threaten human health. The formation of biofilms makes conventional antibiotics ineffective and dampens immune clearance. Therefore, it is important to understand the mechanisms of biofilm formation and develop novel strategies to treat biofilms more effectively. This review article begins with an introduction to biofilm formation in various clinical scenarios and their corresponding therapy. Established biofilm models used in research are then summarized. The potential targets which may assist in the development of new strategies for combating biofilms are further discussed. The novel technologies developed recently for the prevention and treatment of biofilms including antimicrobial surface coatings, physical removal of biofilms, development of new antimicrobial molecules, and delivery of antimicrobial agents are subsequently presented. Finally, directions for future studies are pointed out.

Abstract High‐capacity alloying‐type anodes suffer poor rate capability due to their great volume expansion, while high‐rate intercalation‐type anodes are troubled with low theoretical capacity. Herein, a novel mechanism of alloying in the intercalative frameworks is proposed to confer both high‐capacity and high‐rate performances on anodes. Taking the indium‐vanadium oxide (IVO) as a typical system, alloying‐typed In is dispersed in the stable intercalative V2O3 to form a solid solution. The alloying‐typed In element provides high lithium storage capacity, while the robust, Li‐conductive V−O frameworks effectively alleviate the volume expansion and aggregation of In. Benefiting from the above merits, the anode exhibits a high specific capacity of 1364 mA h g−1 at 1 A g−1 and an extraordinary cyclic performance of 814 mA h g−1 at 10 A g−1 after 600 cycles (124.9 mA h g−1 after 10 000 cycles at 50 A g−1). The superior electrochemical rate capability of (In,V)2O3 solid solution anode rivals that of the reported alloying anode materials. This strategy can be extended for fabricating other alloying/intercalation hybrid anodes, such as (Sn,V)O2 and (Sn,Ti)O2, which demonstrates the universality of confining alloying motifs in intercalative frameworks for rapid and high‐capacity lithium storage.

Hyperspectral anomaly detection (HAD) is an important application of hyperspectral images (HSI) that can distinguish anomalies from background in an unsupervised manner. As a common unsupervised network in deep learning, autoencoders (AE) have been widely used in HAD and can highlight anomalies by reconstructing the background. This study proposed a novel spatial–spectral joint HAD method based on a two-branch 3D convolutional autoencoder and spatial filtering. We used the two-branch 3D convolutional autoencoder to fully extract the spatial–spectral joint features and spectral interband features of HSI. In addition, we used a morphological filter and a total variance curvature filter for spatial detection. Currently, most of the datasets used to validate the performance of HAD methods are airborne HSI, and there are few available satellite-borne HSI. For this reason, we constructed a dataset of satellite-borne HSI based on the GF-5 satellite for experimental validation of our anomaly detection method. The experimental results for the airborne and satellite-borne HSI demonstrated the superior performance of the proposed method compared with six state-of-the-art methods. The area under the curve (AUC) values of our proposed method on different HSI reached above 0.9, which is higher than those of the other methods.

In order to better predict ultimate bearing capacity of perfobond leiste shear connection (PBL), the six specimens were designed for push-out test, and the prediction models were built based on an Improved Adaptive Genetic Algorithm (IAGA) and Back Propagation neural network (BPNN) algorithm. With the finite element model established, it was found that the effects of different parameters on the ultimate bearing capacity of PBL vary greatly if using a single parameter method. The calculation results showed that transverse reinforcement diameter, hole diameter of steel plate, the thickness of steel plate and the strength grade of concrete were the four key factors affecting the ultimate bearing capacity of PBL. In order to overcome the disadvantages of BPNN, such as slow convergence speed and easy to fall into local optimization, an improved adaptive genetic algorithm is used to optimize the initial weights and thresholds of BPNN. The comparison shows that the algorithm is superior to the standard genetic algorithm and other heuristic algorithms, in terms of convergence speed, global search ability and robustness. The IAGA-BPNN prediction model was established. Using the experimental data obtained from both the fatigue test and the references as samples to train the prediction model, the results show that the IAGA-BPNN algorithm proposed in this article can accurately predict the ultimate bearing capacity of PBL, with an average error of 1.69%. The comprehensive sensitivity analysis (CSA) method adopts to explore the relative contribution of each key factors and the interaction between the key factors, and the analysis results show that the ultimate bearing capacity of PBL increases significantly with the increase of the thickness of steel plate and hole diameter of steel plate. The accuracy and stability were better than formulas for calculating the ultimate bearing capacity and the BP neural network prediction algorithm.

Nonmetallic co-doping and surface hole construction are simple and efficient strategies for improving the photocatalytic activity and regulating the electronic structure of g-C3N4. Here, the g-C3N4 catalysts with B-F or B-S co-doping combined with nitrogen vacancies (Nv) are designed. Compared to the pristine g-C3N4, the direction of the excited electron orbit for the B-F-co-doped system is more matching (N2pz→C2pz), facilitating the separation of electrons and holes. Simultaneously, the introduced nitrogen vacancy can further reduce the bandgap by generating impurity states, thus improving the utilization rate of visible light. The doped S atoms can also narrow the bandgap of the B-S-Nv-co-doped g-C3N4, which originates from the p-orbital hybridization between C, N, and S atoms, and the impurity states are generated by the introduction of N vacancies. The doping of B-F-Nv and B-S-Nv exhibits a better CO2 reduction activity with a reduced barrier for the rate-determining step of around 0.2 eV compared to g-C3N4. By changing F to S, the origin of the rate-determining step varies from *CO2→*COOH to *HCHO→*OCH3, which eventually leads to different products of CH3OH and CH4, respectively.

The influence of the substrate material and adhesion of the interface on the scratch resistance of poly(methylmethacrylate) (PMMA) in a multilayer system was explored using scratch tests and finite-element analysis. Experimental results showed that the influence of the substrate material on the scratch resistance of PMMA was not significant if the top layer was a PMMA bulk material. If the top layer was a PMMA film, a hard substrate (such as steel) reduced its scratch resistance and puncture occurred after material removal. Compared with a two-layer PMMA/PMMA system (without glue), the critical loads for scratch damage to a PMMA/glue/PMMA system were reduced under linearly increasing normal load scratch tests. Puncture was not found after material removal in the PMMA/glue/PMMA system. This study provides significance for design of scratch-resistant multilayer polymer systems.

Due to their high absorption coefficient and long carrier lifetime, halide perovskites are promising candidates for photocatalysts. For this study, the antisolvent crystallization protocol and the colloidal crystal templating approach were combined to fabricate the highly crystalline cesium lead bromide perovskite with inverse opal morphology (IO-CsPbBr3). Scanning electron microscopy and transmission electron microscope images demonstrate the three-dimensional well-ordered porous structures of the IO-CsPbBr3 and their single-crystalline features. The presented approach not only provides hierarchical porous structures but also enhances overall crystallinity. When used as catalysts to promote the polymerization of 2,2′,5′,2″-ter-3,4-ethylenedioxythiophene, the highly crystalline IO-CsPbBr3 exhibits a superior photocatalytic performance compared to its polycrystalline counterpart. Furthermore, the morphology and the crystalline structure of the highly crystalline IO-CsPbBr3 are well preserved under photocatalytic conditions. This novel approach enables the preparation of a halide perovskite inverse opal with high crystallinity.

Diabetes mellitus (DM) is a chronic disease affecting nearly 400 million people worldwide. In order to manage the disease, patients need to monitor the blood glucose level by puncturing the finger several times a day, which is uncomfortable and inconvenient. We present here a potential non-invasive monitoring method based on the velocity of ultrasonic waves generated in glucose solution by the photoacoustic principal, which can recognize the glucose concentration down to 20mg/dL. In order to apply this method to warm bodies, we carefully designed the experiment and performed measurements from 30 °C to 50 °C to generate a set of calibration curves, which may be used by engineers to build devices. Most importantly, we have theoretically explained the relationship between the compressibility and the glucose concentration. Our results show that the compressibility of solution decreases with the glucose concentration, which clarified the controversy between theory and experiment results in the literature. The derived formula is generally validity, which can be used to nondestructively measure solution concentration for other types of solutions using photoacoustic principle.

Directional dithering of a laser beam potentially limits the detection accuracy of a laser triangulation displacement probe. A theoretical analysis indicates that the measurement accuracy will linearly decrease as the laser dithering angle increases. To suppress laser dithering, a scheme for reduction of the influence of laser beam directional dithering in a laser triangulation displacement probe, which consists of a collimated red laser, a laser beam pointing control setup, a receiver lens, and a charge-coupled device, is proposed in this paper. The laser beam pointing control setup is inserted into the source laser beam and the measured object and can separate the source laser beam into two symmetrical laser beams. Hence, at the angle at which the source laser beam dithers, the positional averages of the two laser spots are equal and opposite. Moreover, a virtual linear function method is used to maintain a stable average of the positions of the two spots on the imaging side. Experimental results indicate that with laser beam pointing control, the estimated standard deviation of the fitting error decreases from 0.3531 mm to 0.0100 mm , the repeatability accuracy can be lowered from ±7 mm to ±5 μ m , and the nonlinear error can be reduced from ±6 % FS (full scale) to ±0.16 % FS.