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Atmospheric secondary aerosols are often internally mixed with organic and inorganic components, particularly dicarboxylic acids, ammonium, sulfate, nitrate, and chloride. These complex compositions enable aqueous reaction between organic and inorganic species, significantly complicating aerosol phase behavior during aging and making phase predictions challenging. We investigated carboxylate–ammonium salt mixtures using attenuated total reflection Fourier-transformed infrared spectroscopy (ATR-FTIR). The mono-, di-, and tricarboxylates included sodium pyruvate (SP), sodium tartrate (ST), and sodium citrate (SC), while the ammonium salts included NH4NO3, NH4Cl, and (NH4)2SO4. Our results demonstrated that aqueous replacement reactions between carboxylates and ammonium salts were promoted by the formation and depletion of NH3 as relative humidity (RH) changed. For SP/ammonium aerosols, NaNO3 and Na2SO4 crystallized from 35.7 % to 12.7 % and from 65.7 % to 60.1 % RH, respectively, which is lower than the values for pure inorganics (62.5 ± 9 %–32 % RH for NaNO3 and 82 ± 7 %–68 ± 5 % RH for Na2SO4). Upon hydration, the crystalline Na2SO4 and NaNO3 deliquesced at 88.8 %–95.2 % and 76.5 ± 2 %–81.9 %, which is higher than the values of pure Na2SO4 (74 ± 4 %–98 % RH) and NaNO3 (65 %–77.1 ± 3 % RH). In contrast, reaction between ST or SC and (NH4)2SO4 was incomplete due to the gel structure at low RH. Unexpectedly, aqueous Na2SO4 crystallized upon humidification in ST/(NH4)2SO4 particles at 43.6 % RH and then deliquesced with increasing RH. This is attributed to increased ion mobility in viscous particles, leading to nucleation and growth of Na2SO4 crystals. Our findings highlight the intricate interplay between chemical components within organic/inorganic aerosol and the impact of replacement reactions on aerosol aging, phase state, and subsequently atmospheric processes.

Graphene Oxide (GO) is widely used, but its hydrophilic properties make it difficult to remove once it enters water and soil environments. In this paper, the adsorption effect of calcium carbide residue (CCR) as adsorbent on GO was investigated through a series of adsorption tests. Adsorption thermodynamics, kinetics, isotherm models, and various characterization techniques were employed to explore the adsorption mechanism. Additionally, the study assessed CCR’s ability to stabilize GO-contaminated soils through unconfined compressive strength tests. The results showed that (1) at T = 303 K, with a pH of 11 and an initial GO concentration of 80 mg/L, CCR demonstrated excellent adsorption performance. (2) The adsorption process followed the Langmuir isotherm and a quasi-second-order kinetic model, indicating chemical adsorption with spontaneous heat adsorption. (3) CCR not only acts as an effective adsorbent for removing GO from wastewater but also has the potential to strengthen GO-contaminated soils. In addition, due to its favorable environmental benefits, this study has a wide range of potential applications in industrial fields such as wastewater treatment, air purification, and energy storage and conversion. This study not only proposes an effective method for removing graphene oxide from aqueous environments, but also provides a new idea for waste resource utilization, which helps to achieve the dual goals of environmental protection and resource reuse.

The Poaceae family, the fifth largest family of angiosperms, has always been an important source of cereal crops, medicinal crops, and industrial crops. However, comprehensive studies on the biological activity and chemical composition of many species are lacking. In the present study, we tested the total flavonoid and total phenol contents and antioxidant, α-glycosidase, α-amylase, acetylcholinesterase (AChE), and butyrylcholinesterase (BChE)-inhibitory activities of five Poaceae plants (Echinochloa crus-galli, Miscanthus floridulus, Sporobolus fertilis, Bromus japonicus, and Eleusine indica). As a result, the 95 % ethanol (EtOH) extract of M. floridulus (EMF) was found to possess strongest abovementioned activities among the extracts of the five different species. The IC50 value of the DPPH radical scavenging activity was 23.18 ± 0.36 μg/mL, and those of the anti-AChE, anti-BChE and anti-α-glycosidase activities were 49.92 ± 1.44, 100.37 ± 2.48, and 50.01 ± 2.15 μg/mL, respectively. Forty-four compounds were identified from the EMF through liquid chromatography–hybrid ion trap-time of flight mass spectrometry (LC–IT–TOF–MS) analysis, and the majority of these compounds were flavonoids and organic acids. In general, the obtained results highlight the medicinal value of the five members of the Poaceae family. More importantly, M. floridulus has potential for the development of multitarget anti-Alzheimer’s disease (AD) and antidiabetic agents in the pharmaceutical industry.

Whey protein is an important food ingredient, but it is also considered a major food allergen. The aim of this study was to investigate the effect of ultrasound pretreatment on the structure, IgE binding capacity, functional properties and biological activity of whey protein isolate (WPI) hydrolysates (WPH), including WPI hydrolyzed by a combination of enzymes from Bromelain and ProteAXH (BA-WPI) and WPI hydrolyzed by a combination of enzymes from Papain W-40 and ProteAXH (PA-WPI). The IgE binding capacity of BA-WPI and PA-WPI was reduced to 40.28% and 30.17%, respectively, due to disruption/exposure/shielding of conformational and linear epitopes. The IgE binding capacity of sonicated WPI was increased, but ultrasound pretreatment further reduced the IgE binding capacity of the hydrolysates to 32.89% and 28.04%. This is due to the fact that ultrasound pretreatment leads to conformational changes including increased α-helix and β-sheet structure, exposure of aromatic amino acids, surface hydrophobicity, and increased sulfhydryl content, which increases the accessibility of allergenic epitopes to WPI by the enzyme. Multispectral and LC-MS/MS results further indicated that ultrasound pretreatment altered the conformational and primary structural changes of the hydrolysates. The thermograms showed that ultrasound pretreatment mainly altered the epitope spectra of β-lactoglobulin hydrolysates, while it had less effect on the epitope spectra of α-lactalbumin hydrolysates. Additionally, ultrasound pretreatment significantly improved the foaming properties, antioxidant activity, and α-glucosidase inhibition of the hydrolysates without impairing the solubility and emulsification properties of the hydrolysates. Therefore, ultrasound pretreatment is a feasible method to reduce the allergenicity of WPH and to improve their functional properties and bioactivity. Notably, ultrasonic pretreatment improved the effectiveness and efficiency of WPI hydrolysis, which is a feasible method to produce high-quality protein feedstock in a green, efficient, and economical way.

Abstract Serine–arginine (SR) proteins are splicing factors that play essential roles in both constitutive and alternative pre-mRNA splicing. Phosphorylation of their C-terminal RS domains by SR protein kinases (SRPKs) regulates their localization and diverse cellular activities. Dysregulation of phosphorylation has been implicated in many human diseases, including cancers. Here, we report the development of a covalent protein–protein interaction inhibitor, C-DBS, that targets a lysine residue within the SRPK-specific docking groove to block the interaction and phosphorylation of the prototypic SR protein SRSF1. C-DBS exhibits high specificity and conjugation efficiency both in vitro and in cellulo. This self-cell-penetrating inhibitor attenuates the phosphorylation of endogenous SR proteins and subsequently inhibits the angiogenesis, migration, and invasion of cancer cells. These findings provide a new foundation for the development of covalent SRPK inhibitors for combatting diseases such as cancer and viral infections and overcoming the resistance encountered by ATP-competitive inhibitors.

Abstract J‐aggregation and H‐aggregation are identified as two classical models of functionally oriented non‐covalent interactions, and significant attention has been drawn by researchers. However, due to the scarcity of single‐crystal examples of H‐aggregation, a comprehensive understanding of the relationship between its stacking mode and optical behaviour has been hindered. In recent studies, two polyaromatic Schiff base compounds, Cl‐Salmphen and H‐Salmphen, were successfully synthesized, and both were found to exhibit H‐aggregation. In the findings, H‐Salmphen was shown to display typical C─H···π interactions, characteristic of Aggregation‐Induced Emission (AIE) active molecules, whereas its halogenated counterpart was identified as behaving similar to Aggregation‐Caused Quenching (ACQ) active molecules. These types of results suggest that identical intermolecular interactions can produce differing optical behaviours. Light was shed, at least in part, on the formation mechanisms of H‐type aggregates and their luminescence properties from these observations. Additionally, the high optical signal‐to‐noise ratio inherent to H‐aggregates was utilized for the exploration of water content detection. As an outcome, a high‐performance fluorescent filter paper was developed, enabling easy real‐time detection using a smartphone.

Abstract The theories for substrate recognition in enzyme catalysis have evolved from lock-key to induced fit, then conformational selection, and conformational selection followed by induced fit. However, the prevalence and consensus of these theories require further examination. Here we use cryogenic electron microscopy and African swine fever virus type 2 topoisomerase (AsfvTop2) to demonstrate substrate binding theories in a joint and ordered manner: catalytic selection by the enzyme, conformational selection by the substrates, then induced fit. The apo-AsfvTop2 pre-exists in six conformers that comply with the two-gate mechanism directing DNA passage and release in the Top2 catalytic cycle. The structures of AsfvTop2-DNA-inhibitor complexes show that substantial induced-fit changes occur locally from the closed apo-conformer that however is too far-fetched for the open apo-conformer. Furthermore, the ATPase domain of AsfvTop2 in the MgAMP-PNP-bound crystal structures coexist in reduced and oxidized forms involving a disulfide bond, which can regulate the AsfvTop2 function.

Although air quality guidelines generally use the atmospheric concentration of fine particulate matter (PM2.5) as a metric for air pollution evaluation and management, the fact cannot be ignored that different particle toxicities are unequal and significantly related to their sources and chemical compositions. Therefore, judging the most harmful source and identifying the toxic component would be helpful for optimizing air quality standards and prioritizing targeted PM2.5 control strategies to protect public health more effectively. Since the combustions of fuels, including oil, coal, and biomass, are the main anthropogenic sources of environmental PM2.5, their discrepant contributions to health risks of mixed ambient aerosol pollution dominated by the respective emission intensity and unequal toxicity of chemical components need to be identified. In order to quantify the differences between these combustion primary emissions, 10 types of PM2.5 from each typical source group, i.e., vehicle exhaust, coal combustion, and plant biomass (domestic biofuel) burning, were collected for comparative study with toxicological mechanisms. In total, 30 types of individual combustion samples were intercompared with representative urban ambient air PM2.5 samples, whose chemical characteristics and biological effects were investigated by component analysis (carbon, metals, soluble ions) and in vitro toxicity assays (cell viability, oxidative stress, inflammatory response) of human lung adenocarcinoma epithelial cells (A549). Carbonaceous fractions were plenteous in automobile exhaust and biomass burning, while heavy metals were more plentiful in PM2.5 from coal combustion and automobile exhaust. The overall ranking of mass-normalized cytotoxicity for source-specific PM2.5 was automobile exhaust > coal combustion > domestic plant biomass burning > ambient urban air, possibly with differential toxicity triggers, and showed that the carbonaceous fractions (organic carbon, OC; elemental carbon, EC) and redox-active transition metals (V, Ni, Cr) assisted by water-soluble ions (Ca2+, Mg2+, F−, Cl−) might play important roles in inducing cellular reactive organic species (ROS) production, causing oxidative stress and inflammation, resulting in cell injury and apoptosis, and thus damaging human health. Coupled with the source apportionment results of typical urban ambient air PM2.5 in eastern China, reducing toxic PM2.5 from these anthropogenic combustions will be greatly beneficial to public health. In addition to the air pollution control measures that have been implemented, like strengthening the vehicle emission standards, switching energy from coal to gas and electricity, and controlling the open incineration of agricultural straws, further methods could be considered, especially by preferentially reducing the diesel exhaust, lessening the coal combustion by replacement with low-ash clean coals, and depressing the rural crop straw biomass burning emissions.

Monitoring and predicting the dynamic responses of railway bridges under moving trains, including displacement and acceleration, are vital for evaluating the safety and serviceability of the train–bridge system. Traditionally, finite element analysis methods with high computational burden are used to predict the train-induced responses according to the given train loads and, hence, cannot easily be integrated as an available structural-health-monitoring strategy. Therefore, this study develops a novel framework, combining the train–bridge coupling mechanism and deep learning algorithms to efficiently predict the train-induced bridge responses while considering train load duration. Initially, the feasibility of using neural networks to calculate the train–bridge coupling vibration is demonstrated by leveraging the nonlinear relationship between train load and bridge responses. Subsequently, the instantaneous multiple moving axial loads of the moving train are regarded as the equivalent node loads that excite adjacent predefined nodes on the bridge. Afterwards, a deep long short-term memory (LSTM) network is established as a surrogate model to predict the train-induced bridge responses. Finally, the prediction accuracy is validated using a numerical case study of a simply supported railway bridge. The factors that may affect the prediction accuracy, such as network structure, training samples, the number of structural units, and noise level, are discussed. Results show that the developed framework can efficiently predict the train-induced bridge responses. The prediction accuracy of the bridge displacement is higher than that of the acceleration. In addition, the robustness of the displacement prediction is proven to be better than that of the acceleration with the variation of carriage number, riding speed, and measurement noise.

Robotic vertebral plate cutting poses significant challenges due to the complex bone structures of the lumbar spine, which consist of varying densities in cortical and cancellous regions. This study addresses these challenges by developing a predictive model for robotic vertebral plate cutting force and bone quality recognition through the fabrication of artificial vertebrae with controlled, consistent bone density. To address the variability in bone density between cortical and cancellous regions, CT data are utilized to predict target bone density, serving as a foundation for determining the optimal 3D printing process parameters. The proposed methodology integrates a Response Surface Methodology (RSM), Back Propagation (BP) neural network, and genetic algorithm (GA) to systematically evaluate the effects of key process parameters, such as the filling density, material flow rate, and layer thickness, on the printed vertebrae’s density. A one-factor experimental approach and RSM-based central composite design are applied to build an initial bone density prediction model, followed by Sobol’s sensitivity analysis to quantify the influence of each parameter. The GA-BP neural network model is then employed to rapidly and accurately identify optimal printing parameters for different bone layer densities. The resulting optimized models are used to fabricate personalized artificial lumbar vertebrae, which are subsequently validated through robotic cutting experiments. This research not only contributes to the advancement in personalized 3D printing technology but also provides a reliable framework for developing patient-specific surgical planning models in robot-assisted orthopedic surgery.

For metropolises like Beijing, heavy congestions cause transit passengers’ unreliable travel time, including in vehicle time and waiting time. Comparing with other managerial measures, designing a lane for bus use only is an effective method to improve travel reliability, for it can eliminate the influence on bus-driving conditions. This paper proposes a reliable and practical method to determine exclusive bus lanes (EBL). A reliability-based optimization model is established, in which the tradeoff among bus and private car passengers’ travel time, reliability, and EBL construction cost are considered. Based on the actual network, a user equilibrium demand assignment model is applied to estimate the dynamic bus flow distribution. Since the model is nonlinear, a two-step method is proposed where tangent lines are introduced to constitute an envelope curve to linearize the model. This work conducts the statistical modeling and fitting analysis with actual bus trajectory data, collected on EBL in Beijing during peak hours. Passenger travel time distributions are fitted to estimate the statistical passenger travel time; Lognormal distribution and Gaussian distribution are the best fit. The optimization results indicate that the passenger travel time reliability can be improved by 5.5% by the optimized EBL location scheme. This study will provide a theoretical basis and methodological support for improving the service level of the public transportation system in large cities through the scientific planning of exclusive bus lanes.

As one of the important components of a ship, the ship’s integrated power system is an important safeguard for ships. In order to improve the service life of the ship’s power grid, the power system should be able to realize rapid reconstruction to ensure continuous power supply of important loads when the ship is attacked or fails suddenly. Therefore, it is of vital importance to study the reconfiguration technology of the ship’s integrated power system to ensure that it can quickly and stably cope with all kinds of emergencies in order to guarantee the safe and reliable navigation of the ship. This paper takes the ship’s ring power system as the research object and sets up the maximum recovery load and the minimum number of switching operations. The load is divided uniformly and the generator efficiency is balanced for the reconstruction of comprehensive function. It also sets up the system capacity, topology, and branch current limitations of the constraints to establish a mathematical model. The load branch correlation matrix method is used for branch capacity calculation and generator efficiency equalization calculation, and the load backup power supply path matrix is added on the basis of the matrix to judge the connectivity of some loads before reconfiguration. In this paper, for the network reconfiguration of the ship circular power system, which is a discrete nonlinear problem with multiple objectives, multiple time periods, and multiple constraints, we choose to use the particle swarm algorithm, which is suitable for global optimization, with a simple structure and fewer parameters; improve the particle swarm algorithm using the swarm exchange strategy by setting up two main and auxiliary swarms for global and local search; and exchange some of the particles with the golden ratio in order to keep the diversity of the populations. The simulation results of the network reconfiguration of the ship power system show that the improved algorithm can solve the power system network reconfiguration problem more effectively and provide a feasible reconfiguration scheme in a shorter time compared with the chaotic genetic algorithm under the same fault case test, and it also proves that the use of the swarm exchange particle swarm algorithm greatly improves the performance of reconfiguring the power grid of the ship.

The metal–organic framework (MOF) is a kind of porous material with lattice materials. Due to its large surface area and structural diversity, it has made great progress in the fields of batteries, capacitors, electrocatalysis, etc. Conductive MOF (c-MOF) increases the conductivity based on the original advantages of the MOF, which is more suitable for the development of batteries, capacitors, electrocatalysis, and other fields. This review summarizes the preparation of c-MOF and the research progress of conductive MOFs in the field of electrochemical energy storage and conversion.

The oxidation of sabinene by the hydroxyl radical (OH) and ozone (O3) was investigated under atmospherically relevant conditions in the atmospheric simulation chamber SAPHIR (Simulation of Atmospheric Photochemistry In a Large Reaction Chamber) at Forschungszentrum Jülich, Germany. The rate coefficients of the reactions of sabinene with OH and with O3 were determined. The temperature dependence between 284 to 340 K of the rate coefficient of the reaction of sabinene with OH, kSAB+OH, was measured for the first time using an OH reactivity instrument, resulting in an Arrhenius expression of (1.67 ± 0.16) × 10−11 × exp((575 ± 30)/T) cm3 s−1. The values agree with those determined in chamber experiments in this work and reported in the literature for ∼ 298 K within the uncertainties of measurements. The ozonolysis reaction rate coefficient of sabinene (kSAB+O3) determined in chamber experiments at a temperature of (278 ± 2) K is (3.4 ± 0.8) × 10−17 cm3 s−1, which is 58 % lower than the value reported in the literature for room temperature. The measurement of products from the oxidation of sabinene by OH resulted in an acetone yield of (21 ± 15) %, a formaldehyde yield of (46 ± 25) %, and a sabinaketone yield of (18 ± 16) %. All yields determined in the chamber experiments agree well with values from previous laboratory studies within their uncertainties. In addition, the formaldehyde yield determined in this study is consistent with that predicted by the sabinene OH-oxidation mechanism which was devised from quantum chemical calculations by Wang and Wang (2018), whereas the acetone yield is about 15 % higher than that predicted by the mechanism. In the ozonolysis experiments, the analysis of product measurements results in an acetone yield of (5 ± 2) %, a formaldehyde yield of (48 ± 15) %, a sabinaketone yield of (31 ± 15) %, and an OH radical yield of (26 ± 29) %. The OH radical yield is lower than expected from the theoretical mechanism in Wang and Wang (2017), but the value still agrees within the uncertainty. An analysis of the chemical budget of OH radicals was performed for the chamber experiments. The analysis reveals that the destruction rate of the OH radical matches the production rate of OH, suggesting that there is no significant missing OH source for example from isomerization reactions of peroxy radicals for the experimental conditions in this work.

The widespread antibiotic use is accompanied by antibiotic resistance. A large number of antibiotic pollutants enter the water, seriously endangering the ecological environment and human health. In this study, cobalt-based materials are used to activate persulfate to treat antibiotics in wastewater based on advanced oxidation. Co3O4 is obtained at different temperatures by the one-step roasting method, eliminating the complicated preparation of traditional materials which require a large amount of reagents, generating a large amount of wastewater, and complex large-scale preparation. XRD and Raman results indicate the materials’ good crystallinity and purity. XPS and SEM indicated that the appropriate calcination temperature promoted the formation of Co2+, which was conducive to the activation of PMS for the oxidation of TCH. The catalytic activity of the materials is evaluated using tetracycline (TCH). Results suggest that 90.01 % of TCH is removed after 30 min using 0.8 g/L Co3O4–350 °C, 0.4 g/L persulfate (PMS), 25 °C, and initial pH. Moreover, pH, cyclic, and ion interference experiments indicate that the Co3O4–350 °C/PMS system exhibits a wide potential application range. Free radical scavenging experiments show that ·O2− is the main active oxygen species. Co3O4–350 °C as a PMS activator is a catalytic material with large-scale practical applications.

Abstract Nonfused ring electron acceptors (NFREAs) are promising candidates for future commercialization of organic solar cells (OSCs) due to their simple synthesis. Still, the power conversion efficiencies (PCEs) of NFREA‐based OSCs have large room for improvement. In this work, by merging end group halogenation and side chain engineering, we developed four A–D–A'–D–A type NFREAs, which we refer to as EH‐4F, C4‐4F, EH‐4Cl, and C4‐4Cl. Single crystal X‐ray diffraction revealed that multiple intermolecular S···F interactions between cyclopentadithiophene and 5,6‐difluoro‐3‐(dicyanomethylene)indanone could cause an unfavorable dimer formation, leading to ineffective π–π stackings in EH‐4F and C4‐4F, whereas no such dimer was found in EH‐4Cl and C4‐4Cl after replacing with 5,6‐dichloro‐3‐(dicyanomethylene)indanone. Moreover, although the shorter n‐butyl side chain resulted in a closer molecular packing in C4‐4Cl, EH‐4Cl (2‐ethylhexyl substitution) with proper crystallinity exhibited enhanced face‐on orientation in thin film, which is favorable for vertical charge transport and further reducing charge recombination. As a result, a PCE of 13.0% is obtained for EH‐4Cl‐based OSC with a fill factor of 0.70. This work highlights the importance of molecular packing and orientation control toward future high‐performance A–D–A'–D–A type NFREAs.

Abstract Pickering multiphase systems stabilized by solid particles have recently attracted increasing attention due to their excellent stability. Among various solid stabilizers, natural and renewable cellulosic micro/nanoparticles that are derived from agricultural and forestry sources have become promising candidates for Pickering stabilization due to their unique morphological features and tunable surface properties. In this review, recent progress on forming and stabilizing Pickering multiphase systems using cellulosic colloidal particles is summarized, including the physicochemical factors affecting their assembly at the interfaces and the preparation methods suitable for producing Pickering emulsions. In addition, relevant application prospects of corresponding Pickering multiphase materials are outlined. Finally, current challenges and future perspectives of such renewable Pickering multiphase systems are presented. This review aims to encourage the utilization of cellulosic micro/nanoparticles as key components in the development of Pickering systems, leading to enhanced performance and unique functionalities.

The crystal structure has a great influence on the dielectric and piezoelectric performance of poly(vinylidene fluoride) (PVDF). In this work, we prepared PVDF films with two typical crystalline phases (α and β). In situ Kelvin probe force microscopy (KPFM) and Piezoelectric force microscopy (PFM) were employed to investigate the responses of different PVDF crystalline phases to charge mobility, polarization, and piezoelectric properties. We used a homemade Kelvin probe force microscope (KPFM) to inject charges into the two crystalline phases to investigate the differences in the response of different crystalline phases of PVDF to electrical excitation on a microscopic scale. It was found that the α-phase has a lower charge injection barrier and is more susceptible to charge injection and that the α-phase is accompanied by a faster charge dissipation rate, which makes it easier to accumulate charge at the interface between the α-phase and β-phase PVDF. Moreover, the PFM polarization manipulation showed no change in the amplitude and phase diagram of the α-phase under ±10 V bias. In contrast, the β-phase showed a clear polarization reversal phenomenon and a significant increase in piezoelectric amplitude, which is consistent with its polar intrinsic properties. This study provides valuable insights into the multiphase contributions and a reference for designing advanced PVDF dielectrics.

Cathode materials with conversion mechanisms for aqueous zinc-ion batteries (AZIBs) have shown a great potential as next-generation energy storage materials due to their high discharge capacity and high energy density. However, improving their cycling stability has been the biggest challenge plaguing researchers. In this study, CuO microspheres were prepared using a simple hydrothermal reaction, and the morphology and crystallinity of the samples were modulated by controlling the hydrothermal reaction time. The as-synthesized materials were used as cathode materials for AZIBs. The electrochemical experiments showed that the CuO-4h sample, undergoing a hydrothermal reaction for 4 h, had the longest lifecycle and the best rate of capability. A discharge capacity of 131.7 mAh g−1 was still available after 700 cycles at a current density of 500 mA g−1. At a high current density of 1.5 A g−1, the maintained capacity of the cell is 85.4 mA h g−1. The structural evolutions and valence changes in the CuO-4h cathode material were carefully explored by using ex situ XRD and ex situ XPS. CuO was reduced to Cu2O and Cu after the initial discharge, and Cu was oxidized to Cu2O instead of CuO during subsequent charging processes. We believe that these findings could introduce a novel approach to exploring high-performance cathode materials for AZIBs.

As the depth of coal seams increases and the demand for coal grows, the deformation and failure of roadways and coal pillars also intensify. To address the instability of roadways, it is crucial to study the appropriate dimensions for coal pillars. This paper focuses on the 1513 working face of the No. 5 coal seam at Anyang Coal Mine to address the issue of insufficient basis for determining coal pillar width. Through field observations and physical similarity simulations, this study examines the overlying strata failure patterns above coal pillars post-mining and the bearing structure formed by key layers. The relationship between these factors is analyzed using theoretical analysis and physical similarity simulations. A mechanical model of the coal pillar and the “hinged-hinged” overlying strata failure structure is established, analyzing the fracture characteristics of the overlying strata and the bearing structure of the coal pillar to determine the optimal coal pillar width under these conditions. The results indicate that when the coal pillar width is optimized from 25 m to 14 m, the overlying bearing layer is disrupted by the mining activities at the working face, with the lower key layer forming a “hinged” structure upon fracture. As mining progresses, the height of the overlying strata fractures gradually increases, causing the upper key layer to also fracture and form a “hinged-hinged” structure between the high and low bearing layers. According to the “three zones” development law, the height of overlying strata failure does not continue to increase indefinitely, and the coal pillar is affected by the “hinged-hinged” structure of the bearing strata. A mechanical model of the coal pillar bearing structure is established based on the fracture combination structure of the bearing strata. By calculating the load on the “hinged-hinged” structure of the overlying strata, the appropriate coal pillar width is determined to be 15 m. Theoretical calculations, physical similarity simulation experiments, and field applications show that without changing the support conditions, the deformation of the roadway is greater when the coal pillar is narrowed, compared to its original width. The maximum deformation, located 60 m ahead of the working face, increased by 41–42%, while deformation in other areas was relatively minor. This validates the reasonableness of the determined coal pillar width.

Natural language-processing tasks have been improved greatly by large language models (LLMs). However, numerous parameters make their execution computationally expensive and difficult on resource-constrained devices. For this problem, as well as maintaining accuracy, some techniques such as distillation and quantization have been proposed. Unfortunately, current methods fail to integrate model pruning with downstream tasks and overlook sentence-level semantic modeling, resulting in reduced efficiency of distillation. To alleviate these limitations, we propose a novel distilled lightweight model for BERT named MicroBERT. This method can transfer the knowledge contained in the “teacher” BERT model to a “student” BERT model. The sentence-level feature alignment loss (FAL) distillation mechanism, guided by Mixture-of-Experts (MoE), captures comprehensive contextual semantic knowledge from the “teacher” model to enhance the “student” model’s performance while reducing its parameters. To make the outputs of “teacher” and “student” models comparable, we introduce the idea of a generative adversarial network (GAN) to train a discriminator. Our experimental results based on four datasets show that all steps of our distillation mechanism are effective, and the MicroBERT (101.14%) model outperforms TinyBERT (99%) by 2.24% in terms of average distillation reductions in various tasks on the GLUE dataset.

In high-resolution remote sensing images, there are areas with weak textures such as large building roofs, which occupy a large number of pixels in the image. These areas pose a challenge for traditional semantic segmentation networks to obtain ideal results. Common strategies like downsampling, patch cropping, and cascade models often sacrifice fine details or global context, resulting in limited accuracy. To address these issues, a novel semantic segmentation framework has been designed specifically for large-format high-resolution remote sensing images by aggregating global and local features in this paper. The framework consists of two branches: one branch deals with low-resolution downsampled images to capture global features, while the other branch focuses on cropped patches to extract high-resolution local details. Also, this paper introduces a feature aggregation module based on the Transformer structure, which effectively aggregates global and local information. Additionally, to save GPU memory usage, a novel three-step training method has been developed. Extensive experiments on two public datasets demonstrate the effectiveness of the proposed approach, with an IoU of 90.83% on the AIDS dataset and 90.30% on the WBDS dataset, surpassing state-of-the-art methods such as DANet, DeepLab v3+, U-Net, ViT, TransUNet, CMTFNet, and UANet.

This study conducted a comparative analysis of the extraction efficiency and antioxidant potential of caffeoylquinic acids (CQAs) from Blumea aromatica using deep eutectic solvents (DESs) and traditional solvents. Utilizing UPLC-Q-Orbitrap HRMS, the quantification of seven CQAs revealed concentrations ranging from 0.46 to 7.60 mg/g, with 1,5-diCQA identified as the most abundant. DESs demonstrated significant advantages (P

Polyvinyl alcohol (PVA) hydrogel is favored by researchers due to its good biocompatibility, high mechanical strength, low friction coefficient, and suitable water content. The widely distributed hydroxyl side chains on the PVA molecule allow the hydrogels to be branched with various functional groups. By improving the synthesis method and changing the hydrogel structure, PVA-based hydrogels can obtain excellent cytocompatibility, flexibility, electrical conductivity, viscoelasticity, and antimicrobial properties, representing a good candidate for articular cartilage restoration, electronic skin, wound dressing, and other fields. This review introduces various preparation methods of PVA-based hydrogels and their wide applications in the biomedical field.

This study investigates a prospective and straightforward method for producing graphene material derived from biomass, examining the influence of plant cell composition and functions. The experimental outcomes highlight ultrasound's crucial role in synthesizing graphene material sourced from biomass. Ultrasound, a pivotal element in the experiment, significantly affects graphene production from biomass by working synergistically with the liquid components in the solvent system. Notably, the ethanol content reduces the solution’s surface tension, facilitating the effective dispersion of biochar and graphene oxide sheets throughout the process. Simultaneously, the water content maintains the solution’s polarity, enhancing the cavitation effect induced by ultrasound. Biomass-derived graphene is exfoliated utilizing an ultrasonic bath system (134.4 W, 40 kHz, 0.5 W/cm2) from biochar. The as-synthesized graphene oxide exhibits a structure comprising a few layers while remaining intact, featuring abundant functional groups. Interestingly, the resulting product displays nanopores with an approximate diameter of 100 nm. These nanopores are attributed to preserving specific cell structures, particularly those with specialized cell wall structures or secondary metabolite deposits from biomass resources. The study's findings shed light on the impact of cellular structure on synthesizing graphene material sourced from biomass, emphasizing the potential application of ultrasound as a promising approach in graphene production.

During cerebral ischemia/reperfusion (I/R) injury, oxidative stress and inflammation are major contributors to disability. Finding compounds that reduce oxidative stress, inflammation and strengthen the antioxidant defense system properties is one of the vital areas of research. Therefore, the present research aimed to evaluate the effects of resveratrol loaded in copolymer nanoparticles (RES.CP.NPs) on cerebral I/R injury in rats. After preparing and characterization RES.CP.NPs, these platforms were administered to cerebral I/R injured rats at a dose of 20 mg/kg after 2 h occlusion and the neurological disability scores were measured 24 h later. The content of malondialdehyde (MDA), glutathione (GSH), and catalase (CAT) activity as well as the expression levels of TNF-α, IL-10 and NF-κB-p65 in rat brain homogenates were measured. The RES.CP.NPs synthesized in the present study had a spherical structure with a zeta potential of −38 mV and a stable RES release for 72 h. Administration of RES.CP.NPs to I/R rats resulted in significant improvement in neurological disability score, decreased MDA levels, increased GSH content, increased CAT activity, decreased TNF-α expression, increased IL-10 expression, and decreased NF-κB-p65 expression (P

A novel polysaccharide (WAMPa) was purified from Atractylodis macrocephala Koidz. WAMPa was characterized with molecular weight (MW) distribution, infrared spectrum, monosaccharide composition, methylation and nuclear magnetic resonance spectra. The backbone of WAMPa was → 2)-β-D-Glcp-(1 → interspersed with a small amount of → 5)-α-D-Araf-(1→, and the branches were the terminal α-D-Glcp-(1 → and β-D-Glcp-(1→. The immunomodulatory activities of WAMPa were investigated on two levels experiments including in vitro RAW264.7 cells and in vivo zebrafish. Meanwhile, the immune-mediated antitumor activity was evaluated by the inhibitory effect of the culture medium from WAMPa-treated RAW264.7 cells on human breast cancer cell line MCF-7. Bioactivity assays showed that WAMPa increased mRNA expression levels of TNF-α, IL-6 and iNOS, enhanced the levels of NO, and promoted the phosphorylation of ERK, p38 and JNK. Taken together, these findings revealed that WAMPa exhibited immunomodulatory effects by regulating MAPK signaling pathway. The antitumor experiments showed that WAMPa did not show a significant growth inhibition ratio on MCF-7 cells, but WAMPa-treated RAW264.7 macrophages could significantly inhibit the growth of MCF-7 cells. Thus, the antitumor activity of WAMPa was mediated mainly through the activation of macrophages. These results suggested that WAMPa could be considered as potential immunomodulatory and antitumor supplements.

Cancer, also known as malignant tumour or neoplasm, is a leading cause of death worldwide. One distinct feature from normal cells is that cancerous cells often overexpress protein on the cell membrane—for instance, the overexpression of human epidermal growth factor receptor 2. The expression of a specific protein on the cancerous cell surface acts as a marker that differentiates the normal cell and facilitates the recognition of cancerous cells. An emerging anticancer treatment, Antibody–Drug Conjugates (ADCs), utilises this unique feature to kill cancerous cells. ADCs consist of an antibody linked with a cytotoxic payload, mainly targeting the antigen found on cancerous cells. This design can increase the specificity in delivering the cytotoxin to the drug target, thus increasing the drug efficacy and reducing the side effect of cancer treatment due to off-target toxicities. There are tremendous quantities of clinical trials conducted to evaluate the safety and effectiveness of this magic drug in treating different types of cancers. However, only 12 ADCs have been approved by the FDA until now. This review provides the principles of ADCs and highlights the ADCs that FDA has approved. In addition, some of the ADCs that undergo clinical trials are discussed in this review. The application of computational techniques in addressing ADCs’ challenges and neoantigen-targeted cancer vaccines is also highlighted. Although ADCs have been seen as promising magic drugs in cancer treatment, the problems such as toxicity, the stability of the linker, the specificity of an antibody with antigen, and so on, remain a challenge in developing ADCs.