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Under the theoretical support of fuzzy sets theory and confidence index, the proposed approach involves the development of a high‐order robust control method that incorporates optimization techniques to address uncertain systems. First, the utilization of fuzzy sets theory is employed to establish a fuzzy dynamical model. Second, the design of a high‐order robust controller is performed. Third, the design parameters are optimized based on confidence index, and the values are found that minimize the control cost. The simulation results show that this high‐order robust control has significant advantages in dealing with uncertainty, as well as minimizing the control cost. It can be ensured the uniform boundedness and uniform ultimate boundedness. Thus, this proposed method offers the advantage of achieving both robustness and optimality simultaneously. [ABSTRACT FROM AUTHOR]

[Display omitted] • Electron beam irradiation technology was first used to graft modify propylene separators in sodium metal batteries. • Grafted polyacrylic acid enhances electrolyte affinity and efficiently regulates Na+ ion flux. • The improved anode/separator interface enhances the cyclability and reversibility of sodium metal anodes. Sodium metal batteries (SMBs) are considered as strong alternatives to lithium-ion batteries (LIBs), due to the inherent merits of sodium metal anodes (SMAs) including low redox potential (−2.71 V vs. SHE), high theoretical capacity (1166 mAh g−1), and abundant resources. However, the uncontrollable Na dendrite growth has significantly impeded the practical deployment of SMBs. Separator modification has emerged as an effective strategy for substantially enhancing the performance of SMAs. Herein, for the first time, we present the successful grafting polyacrylic acid (PAA) onto polypropylene (PP) separators (denoted as PP-g-PAA) using highly efficient electron beam (EB) irradiation to improve the cyclability of SMAs. The polar carboxyl groups of PAA can facilitate the electrolyte wetting and provide ample mechanical strength to resist dendrite penetration. Consequently, the regulation of Na+ ion flux enables uniform Na+ deposition with dendrite-free morphology, facilitated by the favorable anode/separator interface. The PP-g-PAA separator significantly enhances the cyclability of fabricated cells. Notably, the lifespan of Na||Na symmetric cells can be extended up to 5519 h at 1 mA cm−2 and 1 mAh cm−2. The stable design of the anode/separator interface achieved through polyolefin separator modification presented in this study holds promise for the further advancement of next-generation advanced battery systems. [ABSTRACT FROM AUTHOR]

This investigation employs Latent Profile Analysis (LPA) to analyze data from 1298 Chinese university students, aiming to clarify the mechanisms through which individual psychological resources, primarily academic self-efficacy and positive coping strategies, affect student satisfaction in the context of academic stress. Four distinct profiles emerged based on levels of academic self-efficacy and positive coping strategies: Low-Spirited, General Copers, Capable but Passive, and Optimistic and Confident. These profiles demonstrate significant variances in the sources of academic stress, student engagement, and student satisfaction, with a ranking order from most to least satisfied as follows: Optimistic and Confident, Capable but Passive, General Copers, and Low-spirited. While academic stress uniformly augments engagement across all profiles, its effect on student satisfaction diverges—negatively for Low-spirited and General Copers, and positively for Capable but Passive and Optimistic and Confident. The analysis reveals varying levels of academic stress-tolerance among profiles, highlighting the critical role of academic self-efficacy and indicating a possible nonlinear relationship between student engagement and satisfaction. These findings enhance our comprehension of student satisfaction's intricate dynamics and suggest strategies to alleviate academic stress and improve psychological well-being. [ABSTRACT FROM AUTHOR]

Identifying road freight cargo types is crucial for regional economic interaction and transportation optimization. Existing methods primarily rely on manual labeling and the rule, neither of which can achieve automated semantic enhancement of large-scale road freight trajectories. Consequently, this study proposes a semi-supervised trajectory semantic enhancement method for identifying cargo types based on trajectory feature extraction and point-of-interest (POI) association. The raw trajectories are segmented and enriched with the closest POIs. The sample labeling method with POI semantic enhancement is then proposed using company registration information. Finally, the spatiotemporal and sequential features of labeled freight trips are extracted to build a self-training semi-supervised model for identifying the cargo type of road freight. Experimental studies on real trajectory data demonstrate superior accuracy and robustness compared to existing methods, with accuracy and F1 values reaching 81.4 and 0.77%, respectively. The proposed sample labeling method improves representativeness and universality, increasing accuracy by 7.8–14.4% and F1 value by 8.5–34.5% compared to the rule-based method. The semi-supervised model improves accuracy by 8.9% and F1 value by 29.1% compared to the supervised model when only 10.0% of samples were labeled. This method enables automatic and full-sample cargo type identification in real-world large-scale transportation systems. [ABSTRACT FROM AUTHOR]

Cutaneous melanoma is an aggressive type of skin cancer with a complex genetic landscape caused by the malignant transformation of melanocytes. This study aimed at providing an in silico network model based on the systematic profiling of the melanoma-associated genes considering germline mutations, somatic mutations, and genome-wide association study signals accounting for a total of 232 unique melanoma risk genes. A protein–protein interaction network was constructed using the melanoma risk genes as seeds and evaluated to describe the functional landscape in which the melanoma genes operate within the cellular milieu. Not only were the majority of the melanoma risk genes able to interact with each other at the protein level within the core of the network, but this showed significant enrichment for genes whose expression is altered in human melanoma specimens. Functional annotation showed the melanoma risk network to be significantly associated with processes related to DNA metabolism and telomeres, DNA damage and repair, cellular ageing, and response to radiation. We further explored whether the melanoma risk network could be used as an in silico tool to predict the efficacy of anti-melanoma phytochemicals, that are considered active molecules with potentially less systemic toxicity than classical cytotoxic drugs. A significant portion of the melanoma risk network showed differential expression when SK-MEL-28 human melanoma cells were exposed to the phytochemicals harmine and berberine chloride. This reinforced our hypothesis that the network modeling approach not only provides an alternative way to identify molecular pathways relevant to disease but it may also represent an alternative screening approach to prioritize potentially active compounds. [ABSTRACT FROM AUTHOR]

Weakly supervised semantic segmentation (WSSS) principally obtains pseudo-labels based on the class activation maps (CAM) to handle expensive annotation resources. However, CAM easily involves false and local activation due to the the lack of annotation information. This paper suggests weakly supervised learning as semantic information mining to extend object mask. We proposes a novel architecture to mining semantic information by modeling through long-range dependencies from in-sample and inter-sample. Considering the confusion caused by the long-range dependencies, the images are divided into blocks and carried out self-attention operation on the premise of fewer classes to obtain long-range dependencies, to reduce false predictions. Moreover, we perform global to local weighted self-supervised contrastive learning among image blocks, and the local activation of CAM is transferred to different foreground area. Experiments verified that superior semantic details and more reliable pseudo-labels are captured through these suggested modules. Experiments on PASCAL VOC 2012 demonstrated the proposed model achieves 76.6% and 77.4% mIoU in val and test sets, which is superior to the comparison baselines. [ABSTRACT FROM AUTHOR]

Background: Anxiety affects approximately 40% of Parkinson's disease (PD) patients. However, little is known about its predictors and development over time. Objective: To identify the clinical factors and biomarkers associated with development of anxiety in patients with newly diagnosed PD, and to test which risk factors predict increases in anxiety over time. Methods: Data from the Parkinson's Progression Markers Initiative (PPMI) were utilized. The primary outcome was the State–Trait Anxiety Inventory (STAI). Covariates were demographics, motor and non‐motor symptoms, cognitive functions, dopamine transporter imaging data, and cerebrospinal fluid (CSF) biomarkers. We examined the association of risk factors at baseline and over 4 years with changes in anxiety scores over time. Results: A total of 252 patients met the inclusion criteria (mean age: 61.36 years, SD 9.53). At year 4, 42 patients had developed anxiety. Baseline predictors of increase in anxiety scores were greater autonomic dysfunction, dysexecutive function, CSF t‐tau levels, excessive daytime sleepiness, and lower olfactory function scores but not motor scores. Over 4 years, change in anxiety scores correlated with deterioration in overall cognitive function, excessive daytime sleepiness, as well as depression and disability, and to a lesser degree worsening of Movement Disorder Society‐Unified Parkinson's Disease Rating Scale (MDS‐UPDRS) motor scores and caudate dopaminergic uptake changes. Conclusions: These findings suggest that development of anxiety in PD is not primarily based on a dopaminergic deficit in the basal ganglia but related to non‐dopaminergic or extrastriatal pathology. Early dysexecutive function predicts development of anxiety but increase in anxiety levels correlates most strongly with more global cognitive decline. [ABSTRACT FROM AUTHOR]

In recent years, unmanned aerial vehicles (UAVs) have gained popularity due to their flexibility, mobility, and accessibility in various fields, including search and rescue (SAR) operations. The use of UAVs in SAR can greatly enhance the task success rates in reaching inaccessible or dangerous areas, performing challenging operations, and providing real-time monitoring and modeling of the situation. This article aims to help readers understand the latest progress and trends in this field by synthesizing and organizing papers related to UAV search and rescue. An introduction to the various types and components of UAVs and their importance in SAR operations is settled first. Additionally, we present a comprehensive review of sensor integrations in UAVs for SAR operations, highlighting their roles in target perception, localization, and identification. Furthermore, we elaborate on the various applications of UAVs in SAR, including on-site monitoring and modeling, perception and localization of targets, and SAR operations such as task assignment, path planning, and collision avoidance. We compare different approaches and methodologies used in different studies, assess the strengths and weaknesses of various approaches, and provide insights on addressing the research questions relating to specific UAV operations in SAR. Overall, this article presents a comprehensive overview of the significant role of UAVs in SAR operations. It emphasizes the vital contributions of drones in enhancing mission success rates, augmenting situational awareness, and facilitating efficient and effective SAR activities. Additionally, the article discusses potential avenues for enhancing the performance of UAVs in SAR. [ABSTRACT FROM AUTHOR]

In this study, we aim to analyze the electromagnetic interference (EMI) regarding the Five-hundred-meter Aperture Spherical radio Telescope (FAST) caused by base stations in the International Mobile Telecommunications-2000 (IMT-2000) frequency band. By analyzing the frequency bands used by the transmitting and receiving devices and the surrounding environmental parameters and utilizing an approach to predicting radio wave propagation loss that is based on deterministic methods, we conclude by comparing the predicted received power at the FAST with its interference protection threshold. Our analysis demonstrates that, currently, only 55.31% of IMT-2000 base stations in the FAST radio quiet zone (RQZ) meet the protection threshold. Additionally, this article verifies the applicability and accuracy of the radio wave propagation model used in the research based on field strength measurements. Overall, this study provides valuable insights for improving the electromagnetic environment surrounding FAST and reducing the EMI caused by mobile communication base stations. It also provides corresponding analysis methods and useful suggestions for analyzing electromagnetic radiation interference in other radio telescopes. [ABSTRACT FROM AUTHOR]

The chemical formula of basic zinc chloride is Zn5(OH)8Cl2 · H2O (denoted as ZHC). It is a new type of zinc source additive, widely used in the feed industry. In this article, micron‐sized hexagonal flake ZHC with a diameter of 10–60 µm is directly prepared by ammonia precipitation method using ZnCl2 as raw material. The products are characterized and analyzed by X‐ray diffraction, scanning electron microscopy, and laser particle size analyzer. The effects of reaction temperature, ammonia flow rate, aging time, and reactant concentration on the product morphology are studied. Under the optimum reaction conditions, the ZnCl2 concentration is 2.0 mol L−1, NH3 flow rate is 300 mL min−1, the reaction time is 1 h, the reaction temperature is 80 °C, and the aging time is 5 h. Lastly, the yield reaches 49.06%. The growth habit of ZHC is theoretically analyzed by the Morphology program. The calculation results are in good agreement with the experimental results. The change of (003) crystal plane exposure caused by temperature is an important reason for the non‐ideality of macroscopic morphology. [ABSTRACT FROM AUTHOR]

Airborne hyperspectral imaging plays an increasingly important role in environmental monitoring. However, due to the limitations of the acquisition conditions, there are uneven radiation and chromatic aberrations in the mosaic data. Accurate preprocessing of the original data is the premise of qualitative and quantitative remote sensing. In this study, we proposed a comprehensive radiation distortion correction method that integrates radiation attenuation difference correction, topographic correction, and multi-strip images consistency adjustment (RA-TOC-CA). First, the radiation attenuation equation was constructed by combining the viewing geometry, terrain, and the elevation difference between the UAV and the ground to eliminate the radiation attenuation difference of pixels acquired at the different instantaneous field of view (IFOV). Second, an improved kernel-driven BRDF model was built combining terrain information and illumination-viewing (flight attitude and sensor IFOV) geometry to eliminate the radiation unevenness and BRDF distortion caused by topography. Third, adjusting the reflectance of multi-strip images according to the homonymous points' reflectance of adjacent strips should be equal, eliminating the radiation differences between multiple strips. Based on multi-strip airborne hyperspectral images collected in the Shaanxi province of China, the correction results of the RA-TOC-CA method were compared with those of the SCS+C and Minnaert+SCS methods regarding various evaluation criteria. The results showed that SCS+C and Minnaert+SCS can reduce the topographic effect but cannot eliminate the reflectance difference at the edges of adjacent images, and SCS+C overcorrects the reflectance. RA-TOC-CA weakened the topographic effects and brightness gradient, which was physically stable and generalizable. Compared with previous studies, RA-TOC-CA provided a complete radiation distortion correction method for airborne hyperspectral images and had a solid theoretical basis. This study introduces an effective method for radiation distortion correction of airborne hyperspectral images and provides technical support for large-scale applications of hyperspectral images. [ABSTRACT FROM AUTHOR]

Reported here is the synthesis of a macrocycle with equatorial coordination sites for the construction of self-assembled metallacages. The macrocycle is prepared via a post-modification on the equator of biphen[n]arene. Utilizing this macrocycle as a ligand, three prismatic cages and one octahedral cage were synthesized by regulating the geometric structures and coordination number of metal acceptors. The multi-cavity configuration of prismatic cage was revealed by single-crystal structure. We prove that a macrocycle with equatorial coordination sites can be an excellent building block for synthesizing structure-diverse metallacages. Our results provide a typical example and a general method for the design and synthesis of metallacages. [ABSTRACT FROM AUTHOR]

As one of the most important greenhouse gases, water vapor plays a vital role in various weather and climate processes. In recent years, a near-infrared ratio technique based on satellite images has become a research hotspot in the field of precipitable water vapor (PWV) monitoring. This study proposes a Level 2A PWV data retrieval method based on Sentinel-2 images (S2-L2A), which considers land-cover types and is more suitable for local areas. The radiative transfer model MODTRAN 5 is used to simulate the atmospheric radiative transfer process and obtain lookup tables (LUTs) for PWV retrieval. The spatial distribution of S2-L2A PWV is validated using Global Positioning System (GPS), Terra-MODIS PWV product (MOD05), and Level 2A product provided by ESA (ESA-L2A), while the time series results are evaluated using MOD05. Results show that the PWV retrieved by S2-L2A is both highly correlated and has low bias with the three PWV products, and is closer to the reference data than the MOD05 and ESA-L2A PWV. The relative PWV value in the morning is: bare soil > vegetation-covered area > construction land; as the elevation increases, the PWV value decreases. This study also analyzes the error distribution of the PWV data retrieved by S2-L2A, and finds that inversion error increases with AOT value, but decreases with elevation and normalized difference vegetation index (NDVI). Compared with the three water vapor products, the PWV data retrieved by the proposed method has high accuracy and can provide large-scale and high-spatial-resolution PWV data for many research fields, such as agriculture and meteorology. [ABSTRACT FROM AUTHOR]

Mutations in LRRK2 are the most common genetic cause of Parkinson's disease. Despite substantial research efforts, the physiological and pathological role of this multidomain protein remains poorly defined. In this study, we used a systematic approach to construct the general protein-protein interactome around LRRK2, which was then evaluated taking into consideration the differential expression patterns and the co-expression behaviours of the LRRK2 interactors in 15 different healthy tissue types. The LRRK2 interactors exhibited distinct expression features in the brain as compared to the peripheral tissues analysed. Moreover, a high degree of similarity was found for the LRRK2 interactors in putamen, caudate and nucleus accumbens, thus defining a potential LRRK2 functional cluster within the striatum. The general LRRK2 interactome paired with the expression profiles of its members constitutes a powerful tool to generate tissue-specific LRRK2 interactomes. We exemplified the generation of the tissue-specific LRRK2 interactomes and explored the functions highlighted by the "core LRRK2 interactors" in the striatum in comparison with the cerebellum. Finally, we illustrated how the LRRK2 general interactome reported in this manuscript paired with the expression profiles can be used to trace the relationship between LRRK2 and specific interactors of interest, here focusing on the LRRK2 interactors belonging to the Rab protein family. Author summary: Parkinson's disease is characterized by the progressive degeneration of the brain (neurodegeneration) involving the brain regions responsible for controlling fine movements. The exact mechanism responsible for Parkinson's neurodegeneration is still unclear, however different mutations in multiple genes have been associated with the disease. Mutations in the LRRK2 gene constitute a genetic risk factor for both familial and sporadic Parkinson's disease, suggesting that the LRRK2 protein may play an important role in Parkinson's. It has been suggested LRRK2 to be a "hub protein", meaning a protein involved in the orchestration of multiple functions within the cell; functions that are probably activated with regional and temporal specificity. Here, we constructed a computational model centred on LRRK2 by collecting information related to the hundreds of proteins that have been found able to interact with LRRK2 (LRRK2 interactome). This model can be used to simulate LRRK2 functions in different tissues, additionally it can be used to trace specific LRRK2 interactors and follow their behaviour across different tissues. For example, we showed a dichotomy for the LRRK2 interactome expression between the brain and the peripheral tissues; while the brain regions forming the striatum (the structure mostly affected in Parkinson's) showed a similar functional profile. [ABSTRACT FROM AUTHOR]

The transcription factor Ethylene Responsive Factor (ERF) is crucial for responding to various environmental stressors. Proteins containing the ERF-associated amphiphilic repression (EAR) motif often inhibit gene expression. However, the functions of LkERF, an EAR motif-containing protein from Larix kaempferi , especially in reactive oxygen species (ROS) homeostasis, are not well understood. In the present research, we introduce a novel transcription factor, LkERF6, which contains an EAR motif and positively regulates gene expression, thereby enhancing drought and salt tolerance in tobacco. LkERF6 is classified within the ERF-B1 subfamily due to its conserved AP2/ERF domain and EAR motif. Subcellular localization assays demonstrated LkERF6 is primarily localized in the nucleus. Further analysis revealed that LkERF6 interacts with GCC and DRE elements and is significantly induced by NaCl and PEG 6000. Moreover, LkERF6 transgenic tobacco plants exhibit lower ROS accumulation and higher levels of antioxidant enzyme activities. Additionally, correlation analysis identified a strong association between LkERF6 and three genes: LkSOD , LkCCS , and LkCAT. Y1H, EMAS, and DLR assays confirmed that LkERF6 directly interacts with the promoters of these genes through GCC-box and DRE-box to activate their expression. These findings shed new light on the function of EAR motif-containing transcription factors and highlight LkERF6's crucial role in enhancing abiotic stress resistance by activating multiple ROS clearance genes. • LkERF6, containing the EAR motif, improves plant resistance. • Overexpression of LkERF6 decreases levels of H 2 O 2 and O 2 −. • LkERF6 upregulates the expression of LkSOD , LkCCS , and LkCAT. [ABSTRACT FROM AUTHOR]

Both herpes simplex virus (HSV) and varicella-zoster virus (VZV) belong to herpesviruses family, and the cutaneous infections with HSV or VZV often present similar clinical symptoms, making it challenging in differentiation. Hence, simultaneous detection of herpes simplex virus (HSV) and varicella-zoster virus (VZV) holds great significance for protecting the public health safety. Herein, simultaneous detection of HSV and VZV was innovatively realized based on electrochemiluminescence (ECL) biosensor. Structure-optimized iridium(III) complex coordinated in ZIF-8 nanoemitters (Irbt-ZIF-8-NH 2) were synthesized as anodic emitters. Notably, Irbt-ZIF-8-NH 2 showed remarkable ECL performance with N -(2-hydroxyethyl)piperazine- N' -2-ethanesulfonic acid (HEPES) as the novel efficient co-reactant over the traditional TPrA. The proposed biosensor in this work demonstrated outstanding performance within the linear range of 10 fM to 1 nM, with the detection limit of 1.5 fM for HSV and 2.2 fM for VZV. Importantly, it also exhibited satisfactory recoveries with RSDs in the analysis of viral nucleic acids samples extracted from HSV or VZV infected cells. This work inevitably provides a promising alternative assay for simultaneously detecting HSV and VZV, which would promote to the advancement of efficient and sensitive techniques to tackle significant global health concerns caused by herpesviruses outbreak in the future. [Display omitted] • Simultaneous detection of HSV and VZV was realized based on ECL biosensor. • Structure-optimized ZIF-8-based ECL nanoemitters was prepared. • Novel efficient co-reactant HEPES for ZIF-8-based ECL probe was exploited. • The biosensor was successfully applied to detect viral nucleic acids samples. • This strategy offers a promising alternative assay for diagnosis of HSV and VZV. [ABSTRACT FROM AUTHOR]

The main challenges of remote sensing image scene classification are extracting discriminative features and making full use of the training data. The current mainstream deep learning methods usually only use the hard labels of the samples, ignoring the potential soft labels and natural labels. Self-supervised learning can take full advantage of natural labels. However, it is difficult to train a self-supervised network due to the limitations of the dataset and computing resources. We propose a self-supervised knowledge distillation network (SSKDNet) to solve the aforementioned challenges. Specifically, the feature maps of the backbone are used as supervision signals, and the branch learns to restore the low-level feature maps after background masking and shuffling. The "dark knowledge" of the branch is transferred to the backbone through knowledge distillation (KD). The backbone and branch are optimized together in the KD process without independent pre-training. Moreover, we propose a feature fusion module to fuse feature maps dynamically. In general, SSKDNet can make full use of soft labels and has excellent discriminative feature extraction capabilities. Experimental results conducted on three datasets demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Porous media are assumed as a bunch of curved capillaries of rough pore-solid surface, with capillary size distributions and surface roughness following the fractal scaling laws, for which a permeability model is derived to capture both tortuosity and roughness of the pore space in this work. First, the fractal geometry theory and the regarding methods are used to simulate tortuosity and roughness, and then, the permeability of porous media is linked to pore area fractal dimension, tortuosity fractal dimension, relative mean roughness, and other structural parameters (e.g., characteristic length and maximum and minimum pore size). Each parameter in the proposed model has specific physical meaning, which is able to reveal certain mechanisms that affect permeability comprehensively. For several porous media samples, the predicted permeability data based on the current fractal model are compared with the experimental measurement data and the permeability model predictions for other porous media with smooth capillary channels. A good agreement was found between the predicted values of the new permeability fractal model and the experimental data. [ABSTRACT FROM AUTHOR]

Temporal action localization is currently an active research topic in computer vision and machine learning due to its usage in smart surveillance. It is a challenging problem since the categories of the actions must be classified in untrimmed videos and the start and end of the actions need to be accurately found. Although many temporal action localization methods have been proposed, they require substantial amounts of computational resources for the training and inference processes. To solve these issues, in this work, a novel temporal-aware relation and attention network (abbreviated as TRA) is proposed for the temporal action localization task. TRA has an anchor-free and end-to-end architecture that fully uses temporal-aware information. Specifically, a temporal self-attention module is first designed to determine the relationship between different temporal positions, and more weight is given to features within the actions. Then, a multiple temporal aggregation module is constructed to aggregate the temporal domain information. Finally, a graph relation module is designed to obtain the aggregated graph features, which are used to refine the boundaries and classification results. Most importantly, these three modules are jointly explored in a unified framework, and temporal awareness is always fully used. Extensive experiments demonstrate that the proposed method can outperform all state-of-the-art methods on the THUMOS14 dataset with an average mAP that reaches 67.6% and obtain a comparable result on the ActivityNet1.3 dataset with an average mAP that reaches 34.4%. Compared with A2Net (TIP20), PCG-TAL (TIP21), and AFSD (CVPR21) TRA can achieve improvements of 11.7%, 4.4%, and 1.8%, respectively on the THUMOS14 dataset. [ABSTRACT FROM AUTHOR]

Bi2TiO4F2 nanosheets with abundant polarity surfaces make them a good candidate photocatalyst for CH4 activation. Decorated with AuPd alloy nanoparticles, highly efficient CH4 to CH3OH transformation of 277.32 μmol g−1 h−1 with 93.5% selectivity is achieved over a AuPd/Bi2TiO4F2 nanosheet photocatalyst, which is 7.4 times higher than that of the pristine Bi2TiO4F2 nanosheets. [ABSTRACT FROM AUTHOR]

• At 440 °C, ammonia can reduce Fe 2 O 3 to Fe 3 O 4 in the oxide layer. • Nitridation-Oxidation-Reduction (NOR) treatment can increase the Fe3O4 content in the oxide layer to 84.57%. • With the increase of Fe3O4 content in the oxide layer, the corrosion resistance of the oxide layer is also improved. The nitriding post-oxidation composite treatment is clean and pollution-free, and the high corrosion resistance of the modified layer has aroused extensive research interest. The phase composition and microstructure of Fe 3 O 4 /Fe 2 O 3 film are key factors determining corrosion resistance. We propose a Nitridation-Oxidation-Reduction (NOR) treatment technology nitriding followed by oxidation treatment and then reduction treatment. The precise phase composition and microstructure of the oxide film were characterized and analyzed, and the corrosion resistance of the oxide film was evaluated. Through reduction treatment, the Fe 3 O 4 phase content increased from 54.95 % to 84.75 %, the corrosion potential increased by 0.07 V and the corrosion current density decreased by 2.06 × 10-6A. After NOR treatment, the oxide film has extremely high corrosion resistance, which will have important theoretical and engineering application value. [ABSTRACT FROM AUTHOR]

• The original banded structure affects the mechanical properties of the workpiece. • Milling leads to material accumulation, work-hardened layers and stress concentration. • The presence of inclusions reduces the mechanical and fatigue properties of the steel. A batch of medical orthopedic screwdriver T15 products require a torque of 7.5 N·m, and the torque test after mass production is lower than 6.5 N·m, which cannot meet the process requirements. The fracture morphology and microstructure were characterized by stereo microscope (SM), optical microscope (OM) and field emission electron microscope (SEM), respectively. Their mechanical properties were evaluated by Vickers hardness tester and torque tester. The research results indicate that the failure of T15 screwdriver was predominantly by the mechanism of ductile fracture which occurred at the point of maximum torque force at the outermost shear plane. By increasing the solid solution temperature to 1050 °C and using surface shot peening treatment, microstructure and segregation milling tool marks were eliminated, surface compressive stress was increased, and the torque reached 7.8 N·m. [ABSTRACT FROM AUTHOR]

Intercity freight connections have reshaped urban networks and posed significant urban planning challenges. Previous studies mainly used annual statistical data or online orders, which are criticized for the poor timeliness and data representativeness. This study presents a method to construct freight flow networks by analyzing large-sample truck trajectories using spatiotemporal and semantic data mining. The spatiotemporal interaction patterns and influencing factors of intercity freight connections in China are then investigated. Key findings include: (1) The proposed method enables multidimensional and dynamic investigations by constructing timely and refined freight flow networks. (2) The network structure and spatial pattern of freight connections in China show monthly stability, significant spatial heterogeneity, symmetry, and a typical scale-free property. (3) Spatial interaction patterns are related to freight transportation scale. High-freight-volume regions form complete and homogeneous networks with activity space expanding, while low-freight-volume regions exhibit heterogeneity with connections focused on core cities. (4) More than 92 % of the socioeconomic factors exhibit significant nonlinear enhancement when interacting with distance. The nonlinear interaction between economic development level and distance is the most influential, explaining 23.7 %–85.7 % of the connection strength. These findings facilitate reasonable urban policy formulation and regional industrial collaboration. • The refined freight flow network supports multidimensional and dynamic analysis. • Freight flows exhibit monthly stability, symmetry, and scale-free characteristics. • The spatial organization of freight flows is heterogeneous across various regions. • Distance enhances over 92 % of socioeconomic factors nonlinearly. [ABSTRACT FROM AUTHOR]

For metal materials, the corresponding mechanical indicators obtained by tensile experiments at different strain rates are different. Herein, after the quenching and cold‐rolling process, a deformed lath martensite structure is obtained in low‐carbon steel. A scanning electron microscope (SEM), transmission electron microscope (TEM), and 3D atom probe (3DAP) analyses are used in this research. The results show that measurement uncertainty exists and when the strain rate is 0.0021 s−1 at room temperature, the elongation is at its minimum value, which gets into an extreme point. C atoms segregate into the martensite boundary when the strain rate brittleness occurs from 3DAP analysis. This phenomenon indicates that the supersaturated C atoms in the steel undergo nonequilibrium segregation at the lath boundary during the elastic phase of stretching, which results in strain rate brittleness. [ABSTRACT FROM AUTHOR]

Deuterium magnetic resonance spectroscopic imaging (DMRSI) has recently been recognized as a potentially powerful tool for noninvasive imaging of brain energy metabolism and tumor. However, the low sensitivity of DMRSI has significantly limited its utility for both research and clinical applications. This work presents a novel machine learning-based method to address this limitation. The proposed method synergistically integrates physics-based subspace modeling and data-driven deep learning for effective denoising, making high-resolution dynamic DMRSI possible. Specifically, a novel subspace model was used to represent the dynamic DMRSI signals; deep neural networks were trained to capture the low-dimensional manifolds of the spectral and temporal distributions of practical dynamic DMRSI data. The learned subspace and manifold structures were integrated via a regularization formulation to remove measurement noise. Theoretical analysis, computer simulations, and in vivo experiments have been conducted to demonstrate the denoising efficacy of the proposed method which enabled high-resolution imaging capability. The translational potential was demonstrated in tumor-bearing rats, where the Warburg effect associated with cancer metabolism and tumor heterogeneity were successfully captured. The new method may not only provide an effective tool to enhance the sensitivity of DMRSI for basic research and clinical applications but also provide a framework for denoising other spatiospectral data. [ABSTRACT FROM AUTHOR]

BACKGROUND: Pedicle screw fixation is the preferred surgical treatment for clinical treatment of lumbar degenerative disease currently. The stability of pedicle screw fixation system can be evaluated from the perspective of biomechanics and finite element method is more and more popular in analyzing stress of pedicle screw fixation of vertebral body for researchers. OBJECTIVE: To analyze the stress and displacement changes of human lumbar spine in bending movement from the biomechanical point of view when unilateral and bilateral pedicle screws are fixed, providing theoretical reference for practical clinical application. METHODS: Three-dimensional models were established based on CT data of the volunteers. The volunteers signed the informed consent. This study was approved by the Hospital Ethics Committee. Abaqus software was used to simulate the actual stress conditions. Finite element analysis of lumbar spine flexion was performed during unilateral and bilateral pedicle screw fixation. The stress and displacement of lumbar vertebra, disc and pedicle screw were observed under two fixation methods. RESULTS AND CONCLUSION: (1) Under bilateral fixation, the stress on the left screw was 22.2 MPa, and the stress on the right screw was 21.14 MPa, which was far less than the stress of the screw under unilateral fixation (79.19 MPa). The stress of intervertebral disc in unilateral fixation was 87% larger than that in bilateral fixation; the stress of vertebral body in bilateral fixation was 72% smaller than that in unilateral fixation. (2) From the perspective of displacement, the displacement of screw, lumbar disc and centrum under bilateral fixation were 53%, 55% and 62% smaller than that under unilateral fixation, respectively. (3) Therefore, from the mechanical point of view, bilateral pedicle screw fixation has less stress level, which is friendlier to the human body than unilateral fixation and thus more conducive to the recovery of patients. [ABSTRACT FROM AUTHOR]

Taking Wenchang Pavilion, the landmark building of Pengcheng historical and cultural block in Handan as an example, this study analyzed Wenchang Pavilion architecture, used 3D laser point cloud digital mapping to investigate and study the background, shape, decoration art etc. and put forward the protection strategy of historical buildings in combination with Wenchang Pavilion so as to provide reference for the research and protection renewal of Wenchang Pavilion and other historical remains of Wenchang Pavilion. [ABSTRACT FROM AUTHOR]

Memristor devices are promising nanoscale low-power components, which are expected to significantly reduce power consumption and improve speed of deep learning accelerators if the longitudinal and transverse structure is used. However, memristor devices such as resistive random access memory and phase change memory are difficult to manufacture in small batches because they are prone to various device nonideality. It is particularly important to simulate the performance of memristor deep learning systems and test the effects of nonideal characteristics before circuit level implementation. In this paper, a large-scale memristor-based neural network based on residual neural networks is built to study the influence of non-ideal characteristics of memristors. The influence of four types of non-ideal characteristics on deep learning models is analyzed. The corresponding solutions are discussed. The non-ideal characteristics are tested on the constructed memristor-based neural network. The recognition accuracy of the neural network based on two ideal memristor models reach 64.84% and 64.63% respectively. The further test results show that with the increase of non-ideal characteristics, the recognition accuracy decreases, which prove that the non-ideal characteristics of memristors have a great influence on the practical application of deep learning models, and provide guidance for the practical application of memristors. [ABSTRACT FROM AUTHOR]

To explore novel and efficient ECL luminophores, a series of cationic iridium(III) complexes with 4,7-diphenyl-1,10-phenanthroline as the ancillary ligand and various main ligands were investigated in this work. The comprehensive studies demonstrate complex 1, with 2-phenylbenzothiazole (bt) as main ligand, exhibited superior ECL properties in aqueous buffer compared to other complexes. Importantly, the structurally optimized complex 1 was successfully further encapsulated into silica nanoparticles to prepare electrochemiluminescent iridium(III)-doped silica nanoparticles (Ir@SiO 2 NPs). These Ir@SiO 2 NPs were then utilized to construct a sensitive and specific ECL aptamer sensor for detecting acetamiprid residues in tea. Notably, our developed sensor demonstrated wide linear ranges from 10 pM to 10 μM and low limit of detection of 1.3 pM. These experimental results presented in this work undoubtedly demonstrate iridium(III)-doped silica nanoparticles as a new and efficient type of ECL nano-emitter have great potentials in ECL-related analytical applications in the future. [Display omitted] • A series of iridium(III) complexes as new ECL luminophores were investigated. • Silica nanoparticles with structure-optimized iridium complexes were prepared. • A new ECL aptamer sensor to monitor acetamiprid residues in tea were constructed. • The aptamer sensor exhibited notable sensitivity, selectivity and reliability. [ABSTRACT FROM AUTHOR]

Abstract: An effective three‐component fixation of atmospheric CO2 with readily available 1,2‐dichloroethane and aromatic amine toward oxazolidinones catalyzed by in situ NHC was developed. The reaction occurred in good to excellent yields with good generality and wide functional group tolerance, including challenging steric hindered substituted‐dichloroethane (e.g. 1,2‐dichloropropane and 2,3‐dichlorobutane). The catalytic system is not sensitive to air and moisture, and high yield of oxazolidinone was achieved even with about 0.3 atm of pressure of carbon dioxide. The mechanistic study suggests that the reaction catalyze by in situ NHC via NHC‐CO2 adduct, 1‐butyl‐3‐methylimidazolium‐2‐carboxylate as intermediate and aminochloride involves in reaction pathways. The catalyst can be recycled for at least 3 times without obvious loss of catalytic activity. The protocol is also effective to prepare six‐membered 3‐aryl‐1,3‐oxazinan‐2‐one and even seven‐membered 3‐aryl‐1,3‐oxazepan‐2‐one, when 1,3‐dichloropropane and 1,4‐dichlorobutane was employed. [ABSTRACT FROM AUTHOR]

A convenient and effective method of synthesizing 3-aryl-2-oxazolidinones from cyclic carbonates and aryl amines catalyzed by bio-catalyst adenine in the presence of Et3N under solvent-free conditions is described. The protocol is suitable for the wide scope of substrates, e.g. cyclic carbonates with or without substitutes, and aryl amines with either electron-withdrawing or electron-donating group. The products were obtained in good to excellent yields under the optimal conditions, even in steric hindered cases. The effect of reaction time, temperature, loading of catalyst, and amount of starting materials in the reaction were investigated, and the reaction mechanism is discussed. [ABSTRACT FROM AUTHOR]

This paper presents the CFD modeling and experimental verifications of oscillating flow and heat transfer processes in the micro coaxial Stirling-type pulse tube cryocooler (MCSPTC) operating at 90–170 Hz. It uses neither double-inlet nor multi-bypass while the inertance tube with a gas reservoir becomes the only phase-shifter. The effects of the frequency on flow and heat transfer processes in the pulse tube are investigated, which indicates that a low enough frequency would lead to a strong mixing between warm and cold fluids, thereby significantly deteriorating the cooling performance, whereas a high enough frequency would produce the downward sloping streams flowing from the warm end to the axis and almost puncturing the gas displacer from the warm end, thereby creating larger temperature gradients in radial directions and thus undermining the cooling performance. The influence of the pulse tube length on the temperature and velocity when the frequencies are much higher than the optimal one are also discussed. A MCSPTC with an overall mass of 1.1 kg is worked out and tested. With an input electric power of 59 W and operating at 144 Hz, it achieves a no-load temperature of 61.4 K and a cooling capacity of 1.0 W at 77 K. The changing tendencies of tested results are in good agreement with the simulations. The above studies will help to thoroughly understand the underlying mechanism of the inertance MCSPTC operating at very high frequencies. [ABSTRACT FROM AUTHOR]

Purpose: Precise lateralizing the epileptogenic zone in patients with drug-resistant mesial temporal lobe epilepsy (mTLE) remains challenging, particularly when routine MRI scans are inconclusive (MRI-negative). This study aimed to investigate the synergy of fast, high-resolution, whole-brain MRSI in conjunction with simultaneous [18F]FDG PET for the lateralization of mTLE. Methods: Forty-eight drug-resistant mTLE patients (M/F 31/17, age 12–58) underwent MRSI and [18F]FDG PET on a hybrid PET/MR scanner. Lateralization of mTLE was evaluated by visual inspection and statistical classifiers of metabolic mappings against routine MRI. Additionally, this study explored how disease status influences the associations between altered N-acetyl aspartate (NAA) and FDG uptake using hierarchical moderated multiple regression. Results: The high-resolution whole-brain MRSI data offers metabolite maps at comparable resolution to [18F]FDG PET. Visual examinations of combined MRSI and [18F]FDG PET showed an mTLE lateralization accuracy rate of 91.7% in a 48-patient cohort, surpassing routine MRI (52.1%). Notably, out of 23 MRI-negative mTLE, combined MRSI and [18F]FDG PET helped detect 19 cases. Logistical regression models combining hippocampal NAA level and FDG uptake improved lateralization performance (AUC=0.856), while further incorporating extrahippocampal regions such as amygdala, thalamus, and superior temporal gyrus increased the AUC to 0.939. Concurrent MRSI/PET revealed a moderating influence of disease duration and hippocampal atrophy on the association between hippocampal NAA and glucose uptake, providing significant new insights into the disease's trajectory. Conclusion: This paper reports the first metabolic imaging study using simultaneous high-resolution MRSI and [18F]FDG PET, which help visualize MRI-unidentifiable lesions and may thus advance diagnostic tools and management strategies for drug-resistant mTLE. [ABSTRACT FROM AUTHOR]

In this paper a new two-dimensional chaotic map based on Logistic map and Chebyshev map is proposed. The performance analysis and evaluation show the proposed map has a very wide range of chaos and good ergodicity. Further, a new image encryption algorithm is designed using the chaotic map with Rubik's Cube transform and Brownian motion model. The encryption process is 'confusion - Rubik's cube transformation - diffusion'. In the confusion stage, a method combining Brownian motion theory and chaotic sequence is proposed. Then combining the advantages of chaotic system and Rubik's cube, a Rubik's Cube transformation algorithm is proposed. The scrambled pixel matrix and the chaotic matrix are spliced into a hexahedron structure, and the Rubik's Cube is dynamically scrambled through a pseudo-random sequence. Finally, the XOR operation is performed on the basis of the two-dimensional Hénon chaotic map. The experimental results show that the algorithm has the advantages of large key space, strong robustness and high security, and can resist common cryptanalysis attacks. [ABSTRACT FROM AUTHOR]

• A ruthenium complex with aggregation-induced enhanced emission has been reported. • A ruthenium-based AIEE luminophore has been employed as protein staining agent. • TPE unit has been incorporated into luminescent ruthenium complex. A new ruthenium complex with tetraphenylethylene (TPE) unit (abbreviated as RuPhen-TPE) has been designed and successfully synthesized in this work. The phenomenon of aggregation-induced enhanced emission (AIEE) for this new ruthenium complex has been reported for the first time in this work. Most importantly, this new ruthenium complex with AIEE effect has been further employed as a novel protein staining agent and also exhibited excellent protein staining properties, which may open a new avenue to develop new kinds of protein staining agents in the future. [ABSTRACT FROM AUTHOR]

Nonlocal heavy-duty diesel trucks (HDDTs) transported across regions cause serious pollution in local atmospheric environments. However, previous studies misestimate the number of nonlocal HDDTs in the region and cannot identify the origin of the HDDTs on unmonitored road segments, resulting in unclear spatiotemporal distribution patterns of the emission contributions. This study therefore inferred the origins of HDDTs using trajectory data mining and obtained an accurate decomposition of the emission contribution from nonlocal HDDTs, from the single-vehicle-based HDDT emission inventory. A case study is conducted in Beijing. The results showed that the emission contribution of HDDTs from other regions to Beijing has a significant aggregation pattern and power function relationship with distance. The majority of nonlocal HDDTs in Beijing originate from Hebei and Tianjin and have the largest interaction intensity with Beijing, contributing 43% of the traffic counts and 37.05% of the emission intensity of HDDTs in Beijing. Temporally, the emission contribution of HDDTs from different regions has daily periodicity and is affected by major festivals. Nonlocal HDDTs dominate night-time emissions, which contributed 69.94% of total emissions at 1:00 a.m. The spatial heterogeneity of the emission contribution structure is mainly attributable to the traffic volume, highway freight ton-kilometers, and tertiary industry proportion. These findings extend the scientific understanding of the emission contributions of HDDTs and provide an important scientific basis for future strategies related to the control and management of emissions from HDDTs. [Display omitted] • The origin of heavy-duty diesel trucks is inferred based on trajectory mining. • A single-vehicle-based vehicle emission inventory is established. • Emission contribution structure of heavy-duty diesel trucks shows heterogeneity. • Emission contribution of heavy-duty diesel trucks has daily periodicity. [ABSTRACT FROM AUTHOR]

Nonlocal heavy-duty diesel trucks (HDDTs) transported across regions cause serious pollution in local atmospheric environments. However, previous studies misestimate the number of nonlocal HDDTs in the region and cannot identify the origin of the HDDTs on unmonitored road segments, resulting in unclear spatiotemporal distribution patterns of the emission contributions. This study therefore inferred the origins of HDDTs using trajectory data mining and obtained an accurate decomposition of the emission contribution from nonlocal HDDTs, from the single-vehicle-based HDDT emission inventory. A case study is conducted in Beijing. The results showed that the emission contribution of HDDTs from other regions to Beijing has a significant aggregation pattern and power function relationship with distance. The majority of nonlocal HDDTs in Beijing originate from Hebei and Tianjin and have the largest interaction intensity with Beijing, contributing 43% of the traffic counts and 37.05% of the emission intensity of HDDTs in Beijing. Temporally, the emission contribution of HDDTs from different regions has daily periodicity and is affected by major festivals. Nonlocal HDDTs dominate night-time emissions, which contributed 69.94% of total emissions at 1:00 a.m. The spatial heterogeneity of the emission contribution structure is mainly attributable to the traffic volume, highway freight ton-kilometers, and tertiary industry proportion. These findings extend the scientific understanding of the emission contributions of HDDTs and provide an important scientific basis for future strategies related to the control and management of emissions from HDDTs. [Display omitted] • The origin of heavy-duty diesel trucks is inferred based on trajectory mining. • A single-vehicle-based vehicle emission inventory is established. • Emission contribution structure of heavy-duty diesel trucks shows heterogeneity. • Emission contribution of heavy-duty diesel trucks has daily periodicity. [ABSTRACT FROM AUTHOR]

Poly(3,3-bisazidomethyl oxetane) (PBAMO) and glycidyl azide polymer (GAP) were terminated by diisocyanate (TDI) and then extended by 1,4-butanediol (BDO) to synthesis the PBAMO/GAP random block ETPE. The mechanical properties and thermal decomposition behavior of the ETPE were studied by tensile test, differential scanning calorimetry test and thermogravimetric analysis (TG) test. And the thermal decomposition mechanism was studied by TG/Fourier transform infrared/mass spectrometry system. The results indicated that the mechanical properties of the ETPE worked best at w(TDI + BDO) = 30 %. In addition, the ETPE had two decomposition processes, and the gas products mainly come from the first degradation stage of azide groups. [ABSTRACT FROM AUTHOR]

This paper presents the CFD modeling and experimental verifications of a single-stage inertance tube coaxial Stirling-type pulse tube cryocooler operating at 30–35 K using mixed stainless steel mesh regenerator matrices without either double-inlet or multi-bypass. A two-dimensional axis-symmetric CFD model with the thermal non-equilibrium mode is developed to simulate the internal process, and the underlying mechanism of significantly reducing the regenerator losses with mixed matrices is discussed in detail based on the given six cases. The modeling also indicates that the combination of the given different mesh segments can be optimized to achieve the highest cooling efficiency or the largest exergy ratio, and then the verification experiments are conducted in which the satisfactory agreements between simulated and tested results are observed. The experiments achieve a no-load temperature of 27.2 K and the cooling power of 0.78 W at 35 K, or 0.29 W at 30 K, with an input electric power of 220 W and a reject temperature of 300 K. [ABSTRACT FROM AUTHOR]

A two-dimensional axis-symmetric CFD model of a miniature coaxial Stirling-type pulse tube cryocooler with an overall weight of 920 g operating at 128 Hz is established, and systematic simulations of the performance characteristics at different temperatures are conducted. Both thermal equilibrium and non-equilibrium mechanisms for the porous matrix are considered, and the regenerator losses including the gas and solid conduction, the pressure drop and the imperfect interfacial heat transfer are calculated, respectively. The results indicate that the pressure drop loss is dominant during the first 85% and 78% of regenerator length for the thermal equilibrium and non-equilibrium models, respectively, and it decreases monotonously from warm to cold end due to the steadily decreasing Darcy and Forchheimer terms, whereas other entropy generations share similar changing tendencies, going up gradually near the warm end, increasing dramatically from about 60% of length and then decreasing sharply near the cold end. The reasons for these entropy variations are discussed. [ABSTRACT FROM AUTHOR]

The steel slag was investigated for the removal of p-nitrophenol (4-NP) from simulated sewage by batch adsorption and fixed-bed column absorption experiments. The results showed that the maximum adsorption capacity was 109.66 mg/g at 298 K, pH of 7, initial concentration 100 mg/L, and dose 0.8 g/L. The adsorption process fitted the Langmuir isothermal adsorption model and followed pseudo-second-order kinetic models, the activation energy of adsorption (Ea) was 10.78 kJ/mol, which indicated that the adsorption was single-molecule layer physical adsorption. The regeneration efficiency was still maintained at 84.20% after five adsorption-desorption cycles. The column adsorption experiments showed that the adsorption capacity of the Thomas model reached 13.69 mg/g and the semi-penetrating time of the Yoon-Nelson model was 205 min at 298 K. Fe 3 O 4 was identified as the main adsorption site by adsorption energy calculation, XRD and XPS analysis. The FT-IR, Zeta potential, and ionic strength analysis indicated that the adsorption mechanism was hydrogen bonding interaction and electrostatic interaction. This work proved that steel slag could be utilized as a potential adsorbent for phenol-containing wastewater treatment. [Display omitted] • The adsorption capacity of the steel slag for p-nitrophenol was 109.66 mg/g. • The Fe 3 O 4 composition of steel slag was the main adsorption active site. • Hydrogen bond and electrostatic interaction constitute the main adsorption. • The regeneration effect of steel slag retained 84.5% after 5 adsorption-desorption cycles. [ABSTRACT FROM AUTHOR]

The steel slag was investigated for the removal of p-nitrophenol (4-NP) from simulated sewage by batch adsorption and fixed-bed column absorption experiments. The results showed that the maximum adsorption capacity was 109.66 mg/g at 298 K, pH of 7, initial concentration 100 mg/L, and dose 0.8 g/L. The adsorption process fitted the Langmuir isothermal adsorption model and followed pseudo-second-order kinetic models, the activation energy of adsorption (Ea) was 10.78 kJ/mol, which indicated that the adsorption was single-molecule layer physical adsorption. The regeneration efficiency was still maintained at 84.20% after five adsorption-desorption cycles. The column adsorption experiments showed that the adsorption capacity of the Thomas model reached 13.69 mg/g and the semi-penetrating time of the Yoon-Nelson model was 205 min at 298 K. Fe 3 O 4 was identified as the main adsorption site by adsorption energy calculation, XRD and XPS analysis. The FT-IR, Zeta potential, and ionic strength analysis indicated that the adsorption mechanism was hydrogen bonding interaction and electrostatic interaction. This work proved that steel slag could be utilized as a potential adsorbent for phenol-containing wastewater treatment. [Display omitted] • The adsorption capacity of the steel slag for p-nitrophenol was 109.66 mg/g. • The Fe 3 O 4 composition of steel slag was the main adsorption active site. • Hydrogen bond and electrostatic interaction constitute the main adsorption. • The regeneration effect of steel slag retained 84.5% after 5 adsorption-desorption cycles. [ABSTRACT FROM AUTHOR]

• ZTA/HCCI composite was prepared by casting and the annealing process was studied. • The composite annealing at 780℃, the hardness of the components got the lowest. • Fe and O formatted the diffusion layer under the high temperature holding process. In this study, the soften annealing process of the ZTA ceramic particles reinforced HCCI composite has been investigated. With the annealing temperature from 860℃ to 780℃, the hardness of the HCCI matrix decreased from 603.44 HV to 444.78 HV, and the hardness of ZTA ceramic particles decreased from 1536.29 HV to 1324.30 HV. The EDS elements map results indicate that the content of the diffusion layer is mainly Fe-O mixture. The high constant of Fe and O element diffuse to format the diffusion layer under the high temperature holding process. [ABSTRACT FROM AUTHOR]

• We systematically summarized the structure and function of IL-10 family factors in detail and activated different downstream pathways. We focus on the role of IL-10 in different kidney diseases. Understanding the role of IL-10 in regulating the pathogenesis of kidney disease. • We demonstrate for the first time the role of IL-10 in various kidney diseases including AKI, CKD, DN and LN. • A better understanding of IL-10 as an anti-inflammatory factor based on the improvement of inflammatory response, immune regulation, and tissue fibrosis could lead to the development of new therapeutic targets for various kidney diseases, thereby improving the prognosis of kidney disease patients. Kidney disease is a global health problem with high mortality and socioeconomic burden, including acute kidney injury (AKI), chronic kidney disease (CKD), diabetic nephropathy (DN),and lupus nephritis (LN). However, IL-10 is an anti-inflammatory factor. During severe infection in kidney disease, maintaining tissue homeostasis by inhibiting excessive inflammatory response, regulating immune suppression, delaying tissue fibrosis, and promoting tissue repair. Therefore, improving the pathogenesis and identifying effective therapeutic targets are significant for treating and diagnosing kidney diseases. Thus, the current review describes the structure and function of the IL-10 family and focuses on crucial role in kidney disease. We further discuss the regulatory mechanisms through which IL-10 is involved in kidney disease progression. [ABSTRACT FROM AUTHOR]

Highlights: [•] A novel two-step oxidation process was used to prepare polyaniline nanofibers. [•] The process is suitable for synthesizing in larger scale. [•] The products have homogenous morphologies and higher yields. [ABSTRACT FROM AUTHOR]

This paper investigates nonlinear bifurcation behaviors in the input-series output-parallel (ISOP) connected DC-DC converters under peak current control operating in continuous conduction mode. Circuit simulation demonstrates typical nonlinear phenomena occurring in the ISOP connected DC-DC converters. A precise discrete-time mapping model is presented to analyze the stability and bifurcation phenomena in the ISOP connected DC-DC converters. Interaction of the outside voltage loop and inner loop leads to coexisting slow-scale and fast-scale bifurcation which is investigated under two different values of the bandwidth. [ABSTRACT FROM AUTHOR]

The molecular mechanisms underlying age‐related declines in learning and long‐term memory are still not fully understood. To address this gap, our study focused on investigating the transcriptional landscape of a singularly identified motor neuron L7 in Aplysia, which is pivotal in a specific type of nonassociative learning known as sensitization of the siphon‐withdraw reflex. Employing total RNAseq analysis on a single isolated L7 motor neuron after short‐term or long‐term sensitization (LTS) training of Aplysia at 8, 10, and 12 months (representing mature, late mature, and senescent stages), we uncovered aberrant changes in transcriptional plasticity during the aging process. Our findings specifically highlight changes in the expression of messenger RNAs (mRNAs) that encode transcription factors, translation regulators, RNA methylation participants, and contributors to cytoskeletal rearrangements during learning and long noncoding RNAs (lncRNAs). Furthermore, our comparative gene expression analysis identified distinct transcriptional alterations in two other neurons, namely the motor neuron L11 and the giant cholinergic neuron R2, whose roles in LTS are not yet fully elucidated. Taken together, our analyses underscore cell type‐specific impairments in the expression of key components related to learning and memory within the transcriptome as organisms age, shedding light on the complex molecular mechanisms driving cognitive decline during aging. [ABSTRACT FROM AUTHOR]