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Unsupervised anomaly detection (AD) methods based on deep learning have attracted great attention in unlabeled data mining. The performance of these AD methods usually depends on the representation ability of normal patterns and the quality of training data. However, most deep unsupervised AD methods do not capture the distribution characteristics and the diversity of normal patterns effectively. In the meantime, they ignore the interference of abnormal samples on the model in training data with anomaly contamination. To tackle these issues, this article proposes a method named landmark block-embedded aggregation autoencoder (LBAA) for AD. LBAA constructs a filter and an aggregation autoencoder by introducing a novel normal feature learning approach to improve data quality and adjust its distribution differences from anomalies. In the normal feature learning, we define a landmark block to represent distribution of a normal class and an adaptive selection mechanism of landmark blocks’ number to obtain diverse normal features. On the basis, the filter is constructed to filter distinct anomalies and improve the quality of the contaminated training data. Then, a weighted objective function is proposed to train the aggregation autoencoder. The function can reduce the interference of anomalies and realize the aggregation of normal samples to increase the feature differences between normal and abnormal samples. Next, the trained aggregation autoencoder calculates the anomaly score of each sample by summing the reconstruction error and its median sparseness to the landmark blocks. Finally, we report on a comprehensive experiment on multiple datasets. The obtained results validate the effectiveness and robustness of LBAA.

In 3D skeleton-based action recognition, the limited availability of supervised data has driven interest in self-supervised learning methods. The reconstruction paradigm using masked auto-encoder (MAE) is an effective and mainstream self-supervised learning approach. However, recent studies indicate that MAE models tend to focus on features within a certain frequency range, which may result in the loss of important information. To address this issue, we propose a frequency decoupled MAE. Specifically, by incorporating a scale-specific frequency feature reconstruction module, we delve into leveraging frequency information as a direct and explicit target for reconstruction, which augments the MAE's capability to discern and accurately reproduce diverse frequency attributes within the data. Moreover, in order to address the issue of unstable gradient updates caused by more complex optimization objectives with frequency reconstruction, we introduce a dual-path network combined with an exponential moving average (EMA) parameter updating strategy to guide the model in stabilizing the training process. We have conducted extensive experiments which have demonstrated the effectiveness of the proposed method.

The task of instance segmentation in remote sensing images, aiming at performing per-pixel labeling of objects at the instance level, is of great importance for various civil applications. Despite previous successes, most existing instance segmentation methods designed for natural images encounter sharp performance degradations when they are directly applied to top-view remote sensing images. Through careful analysis, we observe that the challenges mainly come from the lack of discriminative object features due to severe scale variations, low contrasts, and clustered distributions. In order to address these problems, a novel context aggregation network (CATNet) is proposed to improve the feature extraction process. The proposed model exploits three lightweight plug-and-play modules, namely, dense feature pyramid network (DenseFPN), spatial context pyramid (SCP), and hierarchical region of interest extractor (HRoIE), to aggregate global visual context at feature, spatial, and instance domains, respectively. DenseFPN is a multi-scale feature propagation module that establishes more flexible information flows by adopting interlevel residual connections, cross-level dense connections, and feature reweighting strategy. Leveraging the attention mechanism, SCP further augments the features by aggregating global spatial context into local regions. For each instance, HRoIE adaptively generates RoI features for different downstream tasks. Extensive evaluations of the proposed scheme on iSAID, DIOR, NWPU VHR-10, and HRSID datasets demonstrate that the proposed approach outperforms state-of-the-arts under similar computational costs. Source code and pretrained models are available at https://github.com/yeliudev/CATNet.

Monolithic all-perovskite tandem solar cells present a promising approach for exceeding the efficiency limit of single-junction solar cells. However, the substantial open-circuit voltage loss in the wide-bandgap perovskite subcell hinders further improvements in power-conversion efficiency. Here we develop wide-bandgap perovskite films with improved (100) crystal orientation that suppress non-radiative recombination. We show that using two-dimensional perovskite as an intermediate phase on the film surface promotes heterogeneous nucleation along the (100) three-dimensional perovskite facets during crystallization. Preferred (100) orientations can be realized by augmenting the quantity of two-dimensional phases through surface composition engineering, without the need for excessive two-dimensional ligands that otherwise impede carrier transport. We demonstrate an open-circuit voltage of 1.373 V for 1.78 eV wide-bandgap perovskite solar cells, along with a high fill factor of 84.7%. This yields an open-circuit voltage of 2.21 V and a certified power-conversion efficiency of 29.1% for all-perovskite tandem solar cells, measured under the maximum power-point conditions.

Dynamic fragility (m) is reported to be inversely proportional to the stretching parameter (β) in many cases. Herein, their relation is further investigated in polyacrylate/salt complexes with ionic interactions. The introduction of metallic ions leads to a decreased enthalpy hysteresis and increased storage modulus at the glassy state, revealing that the ionic interactions act as physical cross-linkers. Further results found a reduced β value and a larger difference in relaxation time between segmental and secondary relaxation. Surprisingly, an anomalous decrease of fragility accompanied by the increase of the glass transition temperature is observed in all complexes. Moreover, the mvalue further decreases for the α′-relaxation corresponding to the restricted motions in the vicinity of ionic clusters in complex with flexible chains. We suppose that the polarities of metallic ions make extra contributions to the enthalpy change of segmental motions, thereby playing a decisive role in the activation free energy of segmental cooperative rearrangement. Most importantly, the glass transition width can be broadened significantly given that mand β decrease simultaneously, thus providing a new strategy to fabricate high-performance damping materials.

The carbonylative polymerization of olefin yields aliphatic polyketones, which are used as engineering plastics in the market due to their excellent mechanical strength, chemical resistance, and surface and barrier properties. However, the usage of precious palladium catalysts has restricted their extensive application as commodity materials. Herein, we present a series of phosphine-sulfonate Ni catalysts with a wide spectrum of electronic and steric substituents on the phosphorus moiety for the carbonylative polymerization of ethylene. Such efficient nickel-catalyzed copolymerization shows the on-demand transformation of ethylene/CO gas to polyketones with quantitative yield and product specificity. A remarkable productivity of up to 20 kg PK (g Ni)−1was obtained during ethylene/propylene/CO terpolymerization, and the polymerization productivity is independent of the type and feeding amount of α-olefin. The resulting terpolymers show comparable crystallinity, thermal stability, and tensile properties with commercial POKETONE products from Hyosung. The nickel catalyst also features the advantages of using cheap raw material sources and simple synthetic procedures that can be scaled up easily, which enables it to be a promising candidate for industrial application.

Soil utilization of phosphate ore flotation tailings (PTs) was achieved using F-fixing agents combined with organic manure treatment to address issues related to inefficient stabilization of P-F, heavy metal solidification/stabilization, poor physicochemical properties, and ecological disruption. The formulation for PTs soil utilization included 1.75 % polyaluminum sulfate (PAS), 1.75 % FeSO4, and 0.25 % CaO, with PTs content at ≥86.75 %. This approach enhanced water retention and improved nutrient and biochemical conditions. Various nutrient indexes met general planting soil requirements: organic matter 24.93 g/kg, available K 252.26 mg/kg, available Ca 2048.67 mg/kg, available Mg 246.13 mg/kg, and ammonia-nitrogen 42.47 mg/kg. The water-soluble P content of PTs-based soil decreased to 6.96 mg/kg, while available P increased to 677.99 mg/kg. Mn leaching toxicity was less than 0.016 mg/L, with a stabilization efficiency of 96.86 %. Water-soluble F in PTs-based soil was reduced to 11.133 mg/kg. This study maximized phosphorus resource utilization and prevented the migration of water-soluble P, F, and Mn to the surrounding environment. Potting experiments showed PTs-based soil was more effective than red soil and PTs-based raw materials in cabbage plantation, achieving a maximum seedling emergence rate of 98.33 %. Microbial diversity increased, and community structure improved in 40-day soil formation experiments, with PTs-based soils developing microbial communities involved in carbon and nitrogen cycling, enhancing resistance to external environmental disturbances, and promoting ecological utilization. These findings offer practical insights into the ecological utilization of large quantities of PTs and present a cost-effective approach for producing planting soils or ecological mulches from similar solid wastes.

Fatty acids play a putative role as second messengers of phytohormones and regulate the rice grain weight. However, the inner mechanism is still unclear and needs to be further studied. In this study, we identified that oleic acid (C18:1) negatively correlates while linoleic acid (C18:2) positively correlates with rice grain weight. Field trials showed that 1000-grain weight was significantly reduced when treated with the fatty acid synthesis inhibitor, Firsocostat S enantiomer (FSE), at the heading and flowering stages. RNA-seq analysis revealed that FSE affects grain weight by modulating processes, such as glycolysis, sucrose metabolism, and hormone signaling. Notably, FSE inhibited the expression of OsLIN6, which is responsible for transporting C18:1 to the phosphatidylcholine pool for C18:2 synthesis. Compared with the wild type (WT), the OsLIN6knockout mutant exhibited a lower grain weight, an increased C18:1 content, and a decreased C18:2 content. Importantly, OsARF12 was shown to bind to the OsLIN6promoter and activate its expression. In summary, this study highlights the crucial role of the fatty acid synthesis gene, OsLIN6, which was regulated by OsARF12, in rice grain weight determination, thus establishing the molecular link between fatty acid synthesis and auxin signaling.

Idiopathic pulmonary fibrosis (IPF) is a progressive, life-threatening disease with no early detection, few treatments, and dismal outcomes. Although collagen overdeposition is a hallmark of lung fibrosis, current research mostly focuses on the cellular aspect, leaving collagen, particularly its dynamic remodeling (i.e., degradation and turnover), largely unexplored. Here, using a collagen hybridizing peptide (CHP) that specifically binds unfolded collagen chains, we reveal vast collagen denaturation in human IPF lungs and delineate the spatiotemporal progression of collagen denaturation three-dimensionally within fibrotic lungs in mice. Transcriptomic analyses support that lung collagen denaturation is strongly associated with up-regulated collagen catabolism in mice and patients. We thus show that CHP probing differentiates remodeling responses to antifibrotics and highlights the resolution of established fibrosis by agents up-regulating collagen catabolism. We further develop a radioactive CHP that detects fibrosis in vivoin mice as early as 7 days postlung-injury (Ashcroft score: 2–3) by positron emission tomography (PET) imaging and ex vivoin clinical lung specimens. These findings establish collagen denaturation as a promising marker of fibrotic remodeling for the investigation, diagnosis, and therapeutic development of pulmonary fibrosis.

AbstractCholesterol is one of the essential component of lipid in membrane. We present a polarizable atomic multipole force field (FF) for the molecular dynamic simulation of cholesterol. The FF building process follows the computational framework as the atomic multipole optimized energetics for biomolecular applications (AMOEBA) model. In this framework, the electronics parameters, including atomic monopole moments, dipole moments, and quadrupole moments calculated from ab initio calculations in the gas phase, are applied to represent the charge distribution. Furthermore, the many-body polarization is modeled by following the same pattern of distributed atomic polarizabilities. Then, the bilayers composed of two typical phospholipid molecules, 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC), and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), in a range of different cholesterol concentrations are built and implemented by molecular dynamics (MD) simulations based on the proposed polarizable FF. The simulation results are statistically analyzed to validate the feasibility of the proposed FF. The structural properties of the bilayers are calculated to compare with the related experimental values. The MD values show the same trend of experimental values changes.Communicated by Ramaswamy H. Sarma

In this paper, an innovative approach for enhancing fluid transport modeling in porous media is presented, which finds application in various fields, including subsurface reservoir modeling. Fluid flow models are typically solved numerically by addressing a system of partial differential equations (PDEs) using methods such as finite difference and finite volume. However, these processes can be computationally demanding, particularly when aiming for high precision on a fine scale. Researchers have increasingly turned to machine learning to explore solutions for PDEs in order to improve simulation efficiency. The proposed method combines an adaptive multi-scale strategy with generative adversarial networks (GAN) to increase simulation efficiency on a fine scale. The devised model, called simulation enhancement GAN (SE-GAN), takes coarse-scale simulation results as input and generates fine-scale results in conjunction with the provided petrophysical properties. With this new approach, a deep learning model is trained to map coarse-scale results to fine-scale outcomes, rather than directly solving the fluid flow model. Case studies reveal that SE-GAN can achieve a significant improvement in accuracy while reducing computational time compared to the original fine-scale simulation solver. A comprehensive evaluation of numerical experiments is conducted to elucidate the benefits and limitations of this method. The potential of SE-GAN in accelerating the numerical solver for reservoir simulations is also demonstrated.

Single-molecule magnets (SMMs) are a kind of nanosized magnetic materials that are capable of storing massive bytes of information. Strongly coupling the spin centers in a proper manner is a usual approach to promote the working temperature (or blocking temperature) for SMMs. Electron delocalized radicals have been widely employed to accomplish this job. Here, we show a new manner by using weak but multiple B–Hδ−⋯ Dy3+inverse hydrogen bonding (IHB) interactions to control the magnetic couplings in a series of dimeric dysprosiacaborane SMMs. This approach leads to a record high TB100sof 10 K among non-radical bridged dimeric SMMs, which is mainly ascribed to strong ferromagnetic coupling (4.38 cm−1) and the proper alignment of the magnetic principle axes of the adjacent dysprosium(III) ions. In verifying by theoretical calculations, these results demonstrate that IHB interactions can be used to construct strong axial ferromagnetic coupling and enhancing magnetic blocking temperature for SMMs.

A new design method is proposed for a triaxial magnetic field gradient compensation system based on ferromagnetic boundary for atomic sensors. The target field method and the whale optimization algorithm are combined to design magnetic field coils thus transforming the complex analytical solution process into an intelligent optimization problem, while the boundary mirror method is introduced to decouple the coil from the magnetic shield. Magnetic field gradient coils are designed according to the coil design method and combined with the divergence and rotation theorems to form the triaxial gradients compensation system to suppress the magnetic field inhomogeneity in nine directions. The simulation and experimental results are compared with the results before and after compensation by using the box line diagram representing the statistics of the magnetic field deviation, in which the median value is reduced by 65.87% and 85.16%, the minimum by 99.66% and 77.76%, the 25 th quantile by 97.89% and 79.94%, and the 75th quantile by 91.52% and 85.17%, respectively.

Primary amines are privileged molecules in drug development. Yet, there is a noticeable scarcity of methods for directly introducing a primary amine group into the ubiquitous C(sp3)–H bonds within organic compounds. Here, we report an iron-based catalytic system that enables direct primary amination of C(sp3)–H bonds under aqueous conditions and air. Various types of C(sp3)–H bonds, including benzylic, allylic, and aliphatic ones, can be readily functionalized with high selectivity and efficiency. The broad utility of this method has been further verified by late-stage amination of 11 complex bioactive molecules. Mechanistic studies unveil a protonated iron-nitrene complex as the key intermediate for the C–H bond activation. This work extends the toolbox for direct C(sp3)–H functionalizations, opening up new opportunities for late-stage modifications of organic molecules.

Pd-based catalysts are extensively employed to catalyze CO oxidative coupling to generate DMO, while the expensive price and high usage of Pd hinder its massive application in industrial production. Designing Pd-based catalysts with high efficiency and low Pd usage as well as expounding the catalytic mechanisms are significant for the reaction. In this study, we theoretically predict that Pd stripe doping Co(1 1 1) surface exhibits excellent performance than pure Pd(1 1 1), Pd monolayer supporting on Co(1 1 1) and Pd single atom doping Co(1 1 1) surface, and clearly expound the catalytic mechanisms through the density functional theory (DFT) calculation and micro-reaction kinetic model analysis. It is obtained that the favorable reaction pathway is COOCH3–COOCH3coupling pathway over these four catalysts, while the rate-controlling step is COOCH3+CO+OCH3→2COOCH3on Pd stripe doping Co(1 1 1) surface, which is different from the case (2COOCH3→DMO) on pure Pd(1 1 1), Pd monolayer supporting on Co(1 1 1) and Pd single atom doping Co(1 1 1) surface. This study can contribute a certain reference value for developing Pd-based catalysts with high efficiency and low Pd usage for CO oxidative coupling to DMO.

This article investigates the utilization of a consequent-pole (CP) rotor design in the interior permanent magnet (IPM) motor to enhance the permanent magnet (PM) utilization ratio material and reduce leakage flux. Compared to the spoke-type IPM motor, the proposed rotor design utilizes a strong flux-focusing effect to improve performance. The evolutionary mechanism of the proposed flux-focusing rotor from flat-type and spoke-type IPM rotors is illustrated, resulting in a higher PM utilization ratio. The multiobjective genetic algorithm is employed to optimize the design of the proposed CP motor, aiming to maximize the PM material utilization while minimizing torque ripple. The optimization process begins with sensitivity analysis, exploring geometric variables of the rotor and determining their respective ranges and step sizes. Furthermore, a set of Pareto front are generated to identify optimal outcome. Finite element analysis is utilized to compare the electromagnetic performance of the two motors. The obtained results indicate that the proposed structure achieves 2.1% increase in output torque and reduction of approximately 40.2% in PM volume compared to the spoke-type motor. Finally, a 3000 r/min 10 kW prototype was manufactured and tested for confirming the effectiveness of the proposed configuration.

Patients with open abdominal (OA) wounds have a mortality risk of up to 30%, and the resulting disabilities would have profound effects on patients. Here, we present a novel double-sided adhesive tape developed for the management of OA wounds. The tape features an asymmetrical structure and employs an acellular dermal matrix (ADM) with asymmetric wettability as a scaffold. It is constructed by integrating a tissue-adhesive hydrogel composed of polydopamine (pDA), quaternary ammonium chitosan (QCS), and acrylic acid cross-linking onto the bottom side of the ADM. Following surface modification with pDA, the ADM would exhibit characteristics resistant to bacterial adhesion. Furthermore, the presence of a developed hydrogel ensures that the tape not only possesses tissue adhesiveness and noninvasive peelability but also effectively mitigates damage caused by oxidative stress. Besides, the ADM inherits the strength of the skin, imparting high burst pressure tolerance to the tape. Based on these remarkable attributes, we demonstrate that this double-sided (D-S) tape facilitates the repair of OA wounds, mitigates damage to exposed intestinal tubes, and reduces the risk of intestinal fistulae and complications. Additionally, the D-S tape is equally applicable to treating other abdominal injuries, such as gastric perforations. It effectively seals the perforation, promotes injury repair, and prevents the formation of postoperative adhesions. These notable features indicate that the presented double-sided tape holds significant potential value in the biomedical field.

This cross‐sectional study aimed to determine the epidemiology of olfactory and gustatory dysfunctions related to COVID‐19 in China. This study was conducted by 45 tertiary Grade‐A hospitals in China. Online and offline questionnaire data were obtained from patients infected with COVID‐19 between December 28, 2022, and February 21, 2023. The collected information included basic demographics, medical history, smoking and drinking history, vaccination history, changes in olfactory and gustatory functions before and after infection, and other postinfection symptoms, as well as the duration and improvement status of olfactory and gustatory disorders. Complete questionnaires were obtained from 35,566 subjects. The overall incidence of olfactory and taste dysfunction was 67.75%. Being female or being a cigarette smoker increased the likelihood of developing olfactory and taste dysfunction. Having received four doses of the vaccine or having good oral health or being a alcohol drinker decreased the risk of such dysfunction. Before infection, the average olfactory and taste VAS scores were 8.41 and 8.51, respectively; after infection, they decreased to 3.69 and 4.29 and recovered to 5.83 and 6.55 by the time of the survey. The median duration of dysosmia and dysgeusia was 15 and 12 days, respectively, with 0.5% of patients having symptoms lasting for more than 28 days. The overall self‐reported improvement rate was 59.16%. Recovery was higher in males, never smokers, those who received two or three vaccine doses, and those that had never experienced dental health issues, or chronic accompanying symptoms. The incidence of dysosmia and dysgeusia following infection with the SARS‐CoV‐2 virus is high in China. Incidence and prognosis are influenced by several factors, including sex, SARS‐CoV‐2 vaccination, history of head‐facial trauma, nasal and oral health status, smoking and drinking history, and the persistence of accompanying symptoms.

To use an automated system exploiting the advantages of both a neural network and radiomics for analysis of non‐calcified predominant plaque (NCPP). This study retrospectively included 234 patients. Using the workflow of the previous study, the coronary artery was first segmented, images containing plaques were then extracted, and a classifier was built to identify non‐calcified predominant plaques. Radiomics feature analysis and a visualization tool were used to better distinguish NCPP from other plaques. Twenty‐six representative radiomics features were selected. DenseNet achieved an area under the curve of 0.889, which was significantly larger (p= 0.001) than that obtained using a gradient‐boosted decision tree (0.859). The feature variances andenergyfeatures in calcified predominant plaque were both different from those in NCPP. Our automated system provided high‐accuracy analysis of vulnerable plaques using a deep learning approach and predicted useful features of NCPP using a radiomics‐based approach. High accuracy analysis of vulnerable plaques using a deep learning approach can be provided and useful features of high‐risk plaques using a radiomics‐based approach can be predicted.

Introduction:Acute kidney injury (AKI) is a common clinical disease, especially in the intensive care unit. Identification of reliable biomarker is of great clinical significance and benefit the therapy and prevention of AKI. The clinical significance and function of miR-874-3p in AKI development were evaluated in this study aiming to explore a novel biomarker for AKI. Methods:There were 83 AKI patients and 56 healthy individuals included, and the serum samples were collected. The AKI animal models were established via ischemic/reperfusion (I/R) and LPS on C57BL/6 mice. The expression of miR-874-3p was evaluated using PCR, while the potential downstream targets were also validated in AKI mice. The regulatory mechanism of miR-874-3p was investigated in AKI cell model established with HK-2 cell by I/R. Results:miR-874-3p was downregulated in both AKI patients and established AKI mice models. The downregulation of miR-874-3p could discriminate against AKI patients and predict poor prognosis of patients. miR-874-3p was negatively correlated with the levels of serum creatine, blood urea nitrogen, CRP, NEU, and PCT and positively correlated with the eGFR of AKI patients. In I/R- and LPS-induced AKI mice, overexpressing miR-874-3p could alleviate renal dysfunction, oxidative stress, and inflammation induced by AKI. Additionally, miR-874-3p could negatively regulate the expression of MSRB3, which was speculated as the potential mechanism underlying the function of miR-874-3p in AKI. Overexpression of miR-874-3p could alleviate the I/R-induced HK-2 cell apoptosis and decreased proliferation, which was reversed by the upregulation of MSRB3. Conclusion:miR-874-3p served as a diagnostic and prognostic biomarker of AKI and mediate the severity and development of AKI via targeting MSRB3.

ABSTRACT The bond-slip degradation relationship of a carbon fiber reinforced polymer (CFRP)-steel bonded interface is crucial for predicting the long-term behavior of CFRP-strengthened steel structure under a freeze-thaw (F-T) environment. [...]

The approval of venetoclax, a B-cell lymphoma-2 (Bcl-2) selective inhibitor, for the treatment of chronic lymphocytic leukemia demonstrated that the antiapoptotic protein Bcl-2 is a druggable target for B-cell malignancies. However, venetoclax’s limited potency cannot produce a strong, durable clinical benefit in other Bcl-2-mediated malignancies (e.g., diffuse large B-cell lymphomas) and multiple recurrent Bcl-2 mutations (e.g., G101V) have been reported to mediate resistance to venetoclax after long-term treatment. Herein, we described novel Bcl-2 inhibitors with increased potency for both wild-type (WT) and mutant Bcl-2. Comprehensive structure optimization led to the clinical candidate BGB-11417 (compound 12e, sonrotoclax), which exhibits strong in vitroand in vivoinhibitory activity against both WT Bcl-2 and the G101V mutant, as well as excellent selectivity over Bcl-xLwithout obvious cytochrome P450 inhibition. Currently, BGB-11417 is undergoing phase II/III clinical assessments as monotherapy and combination treatment.

The copolymerization of olefins with carbon monoxide (CO) affords aliphatic polyketones, which exhibit excellent mechanical strength, crystallinity, photodegradability, hydrophilicity, and surface and barrier properties. The chain-transfer copolymerization of ethylene with CO has offered an available method to regulate the molecular weight of polyketones that are amenable to conventional injection molding and extrusion. In this study, we investigated the copolymerization pathway using the [P,O]-Pd catalyst in a protonic environment. The key chain-propagating species are identified by state-of-the-art electrospray ionization mass spectrometry. These findings indicate that the copolymerization can be performed in different protonic solvents in a chain-transfer fashion; thus, the molecular weight of polyketone products can be regulated over the range of 8.13–238 kg/mol. In particular, such a chain-transfer method renders the formation of novel telechelic structures having a ketone backbone and diester chain ends selectively. The differences between [P,O]-Pd and diphosphine–Pd catalysts have been disclosed, and this study provides insights into the discovery and design of novel catalysts for this interesting copolymerization reaction.

Aminocarbonylation of alkynes with organic amines as an attractive straightforward protocol for the synthesis of high-value-added α,β-unsaturated amides is highly in demand, which is highly dependent on the performance of Pd catalysts modified by the elaborately designed ligands with various stereoelectronic properties. Herein, the bis-P,N,P-hybrid ligands (L2–L4) were successfully synthesized by using low-cost and easily handleable bis(2-chloroethyl)amine hydrochloride as the starting material. The complexation of L2with Pd(CF3COO)2could afford a stable binuclear complex L2with an ideal centrosymmetric configuration, which proved that L2served as the bis-P,P-bidental chelating ligand. It was found that L2-modified Pd(CF3COO)2(or Pd-L2) could catalyze aminocarbonylation of phenylacetylene with aniline free of any additive and organic solvent, affording the branched product N,2-diphenylacrylamide (3a) with 100% regio-selectivity in the isolated yield of 90%. However, the generality of the developed L2-Pd(CF3COO)2catalytic system is very limited.

Polycyclic aromatic hydrocarbons (PAHs) were a class of persistent organic matter, and contained PAHs wastewater was discharged into wastewater treatment plants (WWTPs) finally, which could greatly affect their operational efficiency. The toxic effects of PAHs on the two-sludge system were assessed from functional genes, resistance genes, and microbial community. Three types of PAHs including Naphthalene (NAP), Anthracene (ANT), and Phenanthrene (PHE) were individually introduced into three separate two-sludge systems. Results showed that three types of PAHs did not adversely affect on nitrification performance, but exhibited a significant toxic effect on denitrification and phosphorus (PO43--P) removal. The effluent NH4+-N was almost 0 mg/L in all three systems, the highest total nitrogen (TN) removal rate was achieved at 90.88% in the PHE system, whereas the lowest rate was 72.46% in the ANT system. Concurrently, the PO43--P removal rate decreased from 93.10% to 51.22% in the ANT system. Functional genes, such as NORB and NIRS, and resistance genes such as PAH-RHD GNF/R and NAH-F/NH-R,were enriched in the PHE and NAP system, contributing to improved pollutant removal. However, the NIRKand PAH-RHD GPF/Rwere more abundant in the ANT system, resulting in varied pollutant removal capabilities. The composition of the microbial community was also influenced by PAH exposure with some specific functional bacteria being identified across the different systems. Among the PAHs tested, ANT was found to exert the highest toxicity towards the two-sludge system, surpassing the toxic effects of NAP and PHE. This study highlights the importance of considering PAH toxicity in the context of WWTPs operations and the potential need for tailored strategies to mitigate their impact on biological processes.

Stimuli-responsive luminescent materials have attracted significant attention in the development of smart photoactive materials for both fundamental research and technological applications. In this work, a new copper iodide cluster (1) with aggregation-induced emission (AIE) characteristic, was obtained combining Cu4I4core with rhodamine B derivative ligand. 1has reversible and distinct multi-stimuli-responsive luminescence for external temperature, volatile organic compound, and mechanical force. Significantly, 1exhibited unusual large blue shift (84 nm) after being ground, which originated from the change of inter-molecular interactions. Moreover, 1exhibits high oxygen quenching efficiency for 82.2% at 1 bar. Mechanistic studies showed that the multi-stimuli-responsive luminescence properties of 1can be attributed to the regulation of cluster-centered luminescence process, metal-to-ligand charge transfer process, halide-to-metal charge transfer luminescence process and aggregation-induced barrier to oxygen process. This work not only reports an AIE copper iodide cluster, but also provides a new strategy to develop multi-stimuli-responsive luminescence materials.

Carbon dioxide, a significant greenhouse gas component, has been impacting the global climate. Photocatalytic CO2reduction is a cost-effective and eco-friendly approach. Photocatalytic CO2can combine with epoxides to produce cyclic carbonates, garnering considerable attention due to its full atom utilization and alignment with green chemistry principles. This review assesses the current state of research on photocatalytic CO2cycloaddition with epoxides, examining factors influencing efficiency through pathways and enhancement methods like light absorption, separation and transfer of photogenerated charges, active site reaction, coupling reaction, and reaction device.

Understanding the corrosion behavior of Mg alloys in the Cl−environments is crucial to preventing catastrophic accidents in their facilities due to their poor corrosion. The microstructures and corrosion behaviors of the Mg-4Gd-2Nd alloy under different heat-treatment conditions were investigated. The content of Mg41Nd5in the alloy decreased significantly with increasing heat-treatment temperature. It was found that the formation of solid solution atomic oxides separates the lamellar Mg(OH)2during the corrosion process of Mg alloys. With the increase of solid solution atomic oxides, lamellar Mg(OH)2is no longer clustered and laid flat on the alloy surface. The loose Mg(OH)2corrosion product film is eroded by Cl−and converted to the rod-like Mg2Cl(OH)3·4H2O, which lead to the detachment of the loose lamellar Mg(OH)2in pieces. Furthermore, the corrosion products of the as-extruded alloy fall off in large blocks, whereas the corrosion products of the heat-treated alloys fall off in small pieces. Therefore, 540 °C-treated specimen exhibits best corrosion resistance.

Oxides play a crucial role in shaping various properties in ferritic alloys under Helium environment. This study investigates the thermodynamic and mechanical properties of Y4Zr3O12and Y2Ti2O7oxides in ferritic alloys with and without Helium utilizing a systematic first-principles approach. Firstly, the atomic arrangement of Y and Zr atoms at cation 18fsites in δ-(Y–Zr–O) oxide is identified, while it is found that Y4Zr3O12exhibits a more robust formation tendency than Y2Ti2O7. Furthermore, it is noted that both Y4Zr3O12and Y2Ti2O7oxides demonstrate a prior ability to trap Helium compared to the bcc-Fe matrix, which leads to a substantial enhancement on the stiffness of both oxides. The elastic moduli of both Y4Zr3O12and Y2Ti2O7oxide exhibit a gradual increase with the growing Helium concentration. As a result, the enhanced shear modulus of oxides and sustained shear modulus of the bcc-Fe matrix collectively contribute to the overall strength of ferritic alloys under Helium environments. The findings in this work propose valuable insights for guiding critical strategies in the design of high-performance oxide-dispersion-strengthened ferritic alloys, particularly for applications in Helium environments.

Adding an anti-corrosion coating to the surface of magnesium (Mg) alloy is an effective means to improve its corrosion resistance, but it is particularly important to enhance the bonding force between the anti-corrosion coating and the Mg matrix. Epoxy resin coating is considered the most cost-effective approach from an industrial standpoint, while the hindering the wider utilization of Mg alloys with epoxy coating in the realm of engineering materials are due to their insufficient adhesion between Mg matrix and the epoxy coating. Here, we demonstrated a simple method for forming an epoxy resin/mineralized film composite coating. The mineralized products coatings were applied to the surface of Mg-3Nd alloy, via a direct reaction between Mg and 15 wt% Na2CO3solution. Due to the inherent lamellar structure of alkaline magnesium carbonate mineralization film, the mechanical interlocking between the epoxy resin and the Mg substrate are remarkably strengthened. Therefore, this simple surface treatment method is promising to improve the adhesion between the epoxy resin and the matrix. Moreover, the effects of mineralized products coating on the corrosion resistance of Mg with epoxy coating were researched. It was observed that the corrosion resistance of Mg alloy with composite coatings are significantly enhanced. Such an investigation aims to provide a new method for developing a cost-effective and robust epoxy resin/mineralized film composite coating protection structure of Mg alloys in practical applications.

Fiber optic temperature sensors for small-scale heat sources have an urgent need in many industrial fields, for example, the temperature field of the laser heat source, mini LED, microchip, and so on. To the best our knowledge, we first propose and demonstrate an ultrashort fiber optic temperature sensor based on a Fabry–Perot (FP) interferometer which combines a low reflection fiber Bragg grating (FBG) with Fresnel reflection (i.e., ~4%) on the fiber end face. This unique FBG exhibits a broad Gaussian spectrum with a full-width at half-maximum (FWHM) bandwidth of 12.4 nm. This FBG-FP cavity structure was fabricated by a femtosecond laser line-by-line (LbL) scanning technology, and it has stronger mechanical strength due to no damage to the fiber material compared to other fiber optic FP interferometers. The free spectrum range (FSR) of the FBG-FP cavity is about 1.56 nm, corresponding to the cavity length can be calculated to be about $530 \mu \text{m}$ . The selected dip wavelength of the FBG-FP cavity sensor changes linearly with the temperature increase, corresponding to the temperature sensitivity of 10.8 pm/°C. Moreover, the FBG-FP cavity sensor exhibits a high spatial resolution of $580 \mu \text{m}$ and it can be used to measure the temperature of the small-scale laser spot due to its compact structure. The experimental results show the temperatures at different positions of 1064 nm laser exposure area are 138.4 °C, 111.5 °C, and 74.4 °C, respectively.

Significant advancements in electronic devices and integrated circuits have been facilitated by semiconducting single-walled carbon nanotubes (SWCNTs) sorted by conjugated polymers (CPs). However, the variety of CPs with single-chirality selectivity is limited, and the sorting results are strongly dependent on the chiral distribution of the starting materials. To address this, we develop an iterative strategy to achieve single-chirality SWCNT separation from aqueous to organic systems, based on a multistep tandem extraction technique that allows a gentle and nondestructive separation of surfactants from SWCNTs, ensuring an efficient system transfer. In parallel, we refined the iterative sorting process between CPs. Employing two starting materials with narrow diameter distributions, using three CPs, we successfully sorted out five single-chirality SWCNTs of the (9,5), (8,6), (10,5), (8,7), and (11,3) species in organic systems. This strategy bridges the gap between aqueous and organic separation systems, achieving efficient complementarity between them.

Noise pollution is an often-overlooked environmental threat that poses a concealed but severe risk to public health and urban ecological environment. Despite being invisible, noise has become the second-largest environmental factor contributing to public health issues. Furthermore, noise pollution hinders the sustainable development of cities. To manage noise pollution in urban areas, intelligent noise mapping is expected to be an essential tool that can transform invisible noise problems into visible ones and provide an efficient governance basis. However, this technological approach is still in its infancy, and there is a significant gap in implementing large-scale dynamic urban noise mapping. In this article, we provide a critical review of recent advances in intelligent noise mapping, analyzing their technical principles, fundamental research topics, advantages, and limitations. We also present our insights on the development trends of intelligent noise mapping for smart cities. Finally, we identify four critical open issues and discuss our insights to address these gaps for future research. This study's findings can contribute to the development of more effective solutions to address noise pollution and promote sustainable smart cities.

Although remote sensing image registration has been developing at a high speed for decades, polarimetric synthetic aperture radar (PolSAR) image registration is still a challenging task because of the presence of polarimetric scattering differences, geometric distortions, and speckle noise. Due to the lack of PolSAR image training data, the generalization performance of deep learning-based registration methods is poor and cannot fundamentally solve the problem of PolSAR image registration. In this article, we propose a novel PolSAR image registration framework that integrates feature selection, feature descriptor extraction, and template matching. First, we use structural similarity (SSIM) to select polarimetric features that are similar in structural information, thus using structural information to overcome polarimetric scattering differences. On this basis, a feature descriptor named oriented gradient of polarimetric feature (OGPF) is proposed to overcome the polarimetric scattering information difference by extracting geometric structure information using oriented gradient channels (OGCs) and 3-D Gaussian convolution. Finally, we propose to use polarimetric whitening filter (PWF) and nonmaximum suppression (NMS) to extract keypoints with significant structural information to reduce the interference of speckle noise on keypoint selection, and further propose a template downsampling strategy to reduce the complexity of template matching. The proposed method is evaluated using six pairs of PolSAR images with different scenes, and the results show that its registration performance outperforms the state-of-the-art methods.

Deep hashing algorithms can transform high-dimensional features into low-dimensional hash codes, which can reduce storage space and improve computational efficiency in traditional information retrieval (IR) and large model related retrieval augmented generation (RAG) scenarios. In recent years, pre-trained convolutional or transformer networks are commonly chosen as the backbone in deep hashing frameworks. This involves incorporating local loss constraints among training samples, and then fine-tuning the model to generate hash codes. Due to the relatively limited local information of constraints among training samples, we propose to design the novel anchor constraint and structural constraint as internal global loss constraints with the vision transformer network, and augment external information by integrating the large vision-language model, thereby enhancing the performance of hash code generation. Additionally, to enhance the scalability of the novel deep hashing framework, we propose to incorporate the adapter module to extend its application from the image domain to the audio domain. By conducting comparative experiments and ablation analysis on various image and audio datasets, it can be confirmed that the proposed method achieves state-of-the-art retrieval results.

2,4,6-Tribromophenol (TBP) is widely distributed in environmental media, posing potential risks to human health and ecological system. The efficient treatment of TBP-contaminated water is a significant challenge. In this study, a combined process of oxidation and coagulation using Fe(iii)/CaSO3was employed to treat actual water samples spiked with TBP. The slow release of S(iv) from CaSO3into the solution benefited the treatment efficiency, and the Fe(iii)/CaSO3system not only effectively removed TBP but also significantly enhanced the removal of background organic compounds viaoxidation and coagulation. The optimal water quality was achieved with Fe(iii) and CaSO3dosages of 100 μM and 400 μM, respectively, with an initial pH of 3.5. As for the Fe(iii)/CaSO3system, larger-sized crystals were observed after treating the secondary clarifier effluent compared to that in the sole Fe(iii) coagulation process. Further coagulation after Fe(iii)/CaSO3oxidation offers a new approach to apply S(iv)-based advanced oxidation technologies in the field of water treatment, demonstrating its potential in the effective treatment of TBP in water.

As a representative of the third generation advanced high-strength steels (AHSSs), medium Mn steels (MMS) have broad development prospects in the field of automobile manufacturing. MMS with typical austenite reversion treatment have a soft duplex microstructure, i.e. ferrite + austenite, presenting a high ductility but a low yield strength. Here we show that a flash heating and cooling after austenite reversion treatment can replace the ferrite with strong martensite, which greatly enhances the yield strength of a 0.25C-4Mn steel by about 461–886 MPa. By adjusting the reversion temperature before the flash treatment, the C and Mn concentrations of reverted austenite can be altered, which determine the fraction of reverted austenite surviving the flash treatment. In addition, the mechanical stability of final retained austenite is also linked to the reversion temperature, resulting different work hardening behaviors due to transformation induced plasticity (TRIP) effect. By tweaking the reversion temperature before the flash treatment, an optimized combination of strength and ductility can be achieved. The micromechanical differences caused by the replacement of the matrix are also investigated via in-situ digital image correlation method.

To combat the crisis of today’s synthetic polymers arising from unsustainable production and disposal, it is essential for the synthetic polymer community to reshape the current polymer industry with sustainable polymers. As an emerging class of sustainable polymers, the development of chemically depolymerizable polymers (CDPs), which can undergo closed-loop depolymerization/repolymerization cycles to reproduce virgin polymers without the loss of properties from recovered monomers, offers an ideal solution to preserve finite natural resources, provides a feasible solution to the end-of-life issue of polymer waste, and thereby establishes a circular materials economy. However, two grand key challenges have been encountered in the establishment of practically useful CDPs: how to balance polymerization and depolymerization ability and how to unify conflicted depolymerizability and physical properties. Accordingly, this critical review article presents our vision for summarizing feasible strategies to overcome the above two significant challenges and the design principles for constructing an ideal CDP by highlighting selected major progress made in this rapidly expanding field.

Entrepreneurial endeavouring has been disrupted and recovered, albeit differently across societies. Resilience has been found to be promoted by institutions, especially the economy. The question is, during disruption and recovery, are institutions providing resilience for sustaining ease of starting a business? We analyse national-level effects on changing ease of starting in 202 national-level disruptions and recoveries during the recession, disruption around 2009 and recovery around 2010 and during the pandemic, disruption around 2020 and recovery around 2021. Furthermore, we analyse individual-level effects on 101,616 entrepreneurs' assessments in the four years. Change in ease of starting was more benign during the pandemic than during the recession, and more benign during recovery than during disruption. Among institutions, economic growth and the informal institution of entrepreneurialism were both bases for resilience promoting change in ease of starting. The findings contribute to contextualising enterprising as shaped by societal conditions sustaining resilience during disruption and recovery.

Objective: To develop a nomogram based on contrast-enhanced CT (CECT) image features and clinical factors for preoperatively predicting the expression level of Ki67 in patients with hepatocellular carcinoma (HCC). Methods: One hundred eighty-three patients diagnosed with HCC were included in this study. All patients underwent CECT scans before surgeries or biopsies. The Ki67 expression was assessed by immunohistochemistry. The nomogram was constructed based on a combination of CECT image features and clinical factors which showed an independent association with Ki67 expression. The area under the receiver operating characteristic curve (AUC), calibration curve and decision curve analysis (DCA) were used to verify the performance of the nomogram. Results: In multivariate logistic regression, bumpy margin, blurred margin, intra-tumoral vessels and α-fetoprotein (AFP) were identified as independent predictors of Ki67 expression (p< 0.05). Three CECT image features and one clinical factor were selected to construct the nomogram, which showed great discrimination ability in the training and validation cohort with AUCs of 0.932 and 0.870 respectively. The calibration curve and DCA indicated that the nomogram had positive clinical application. Conclusion: The nomogram, developed based on CECT image features and clinical factors in this study, provide a non-invasive method for accurately predicting the expression level of Ki67, and has the potential to support clinicians in making pretreatment decisions.

Inflammatory bowel disease (IBD) is a chronic disorder that affects millions of individuals worldwide. However, current drug therapies for IBD are plagued by significant side effects, low efficacy, and poor patient compliance. Consequently, there is an urgent need for novel therapeutic approaches to alleviate IBD. Hydrogels, three-dimensional networks of hydrophilic polymers with the ability to swell and retain water, have emerged as promising materials for drug delivery in the treatment of IBD due to their biocompatibility, tunability, and responsiveness to various stimuli. In this review, we summarize recent advancements in hydrogel-based drug delivery systems for the treatment of IBD. We first identify three pathophysiological alterations that need to be addressed in the current treatment of IBD: damage to the intestinal mucosal barrier, dysbiosis of intestinal flora, and activation of inflammatory signaling pathways leading to disequilibrium within the intestines. Subsequently, we discuss in depth the processes required to prepare hydrogel drug delivery systems, from the selection of hydrogel materials, types of drugs to be loaded, methods of drug loading and drug release mechanisms to key points in the preparation of hydrogel drug delivery systems. Additionally, we highlight the progress and impact of the hydrogel-based drug delivery system in IBD treatment through regulation of physical barrier immune responses, promotion of mucosal repair, and improvement of gut microbiota. In conclusion, we analyze the challenges of hydrogel-based drug delivery systems in clinical applications for IBD treatment, and propose potential solutions from our perspective.

The dynamic security assessment of power systems needs to scan contingencies in a preselected set through time-domain simulations. With more and more wind power generation integrated into power systems, the complexity of simulation will increase greatly if wind farms are modeled in detail. Thus, it is critical to develop dynamic equivalent methods for wind farms. The dynamic response characteristics of permanent magnet synchronous generator-wind turbine generators (PMSG-WTGs) are not only influenced by their control strategies, but also by the operating wind speeds and the fault severities. Thus, this article proposes a dynamic equivalent method for a PMSG-WTG based wind farm considering the wind speeds and the fault severities. Firstly, we propose a clustering method based on the operating wind speed and the terminal voltage of each PMSG-WTG at the end of the fault. Then, a single-machine equivalent method is introduced for each cluster of PMSG-WTGs. For the cluster of PMSG-WTGs with active power ramp recovery process, an equivalent model with segmented ramp rate limitation for active current is designed. In order to obtain the clustering indicators, a simulation-based iterative method is put forward. Eventually, the efficiency and accuracy of the proposed method are verified by the simulation results.

With the continuous development of large-scale complex hybrid AC-DC grids, the fast adjustability of HVDC systems is required by the grid to provide frequency regulation services. This article develops a fully data-driven linear quadratic regulator (LQR) for the HVDC to provide temporal frequency support. The main technical challenge is the complexity and the nonlinearity of multi-infeed hybrid AC-DC (MIDC) systems dynamics that make the LQR intractable. Based on Koopman operator (KO) theory, a Koopman eigenpairs construction method is developed to fit a global linear dynamic model of MIDC systems. Once globally linear representation of uncontrolled system dynamics is obtained offline, the control term is constituted by the gradient of the identified eigenfunctions and the control matrix $\boldsymbol{B}$. In case that $\boldsymbol{B}$ is unknown, we propose a method to identify it based on the verified Koopman eigenfunctions. The active power reference is optimized online for LCC-HVDC in a moving horizon fashion to provide frequency support, with only locally measurable frequency and transmission power. The robustness of the proposed control method against approximation errors of the linear representation in eigenfunction coordinates is analyzed. Simulation results show the effectiveness, robustness and adaptability of the proposed emergency control strategy.

In multi-infeed hybrid AC-DC (MIDC) systems, the emergency frequency control (EFC) with LCC-HVDC systems participating is of vital importance for system frequency security. Nevertheless, when regional power systems are operated by different decision-makers, the LCC-HVDC systems and their connected AC systems might be unwilling to participate in the EFC due to the costs and losses. In this paper, to incentivize the LCC-HVDC systems and their connected adjacent AC systems to participate in the droop-based EFC, a novel control-parameter-based incentive mechanism is proposed, which can flexibly deal with various possible power imbalances. Then, a non-cooperative-based incentive game model is formulated to quantitatively analyze the incentive mechanism in the MIDC system. An algorithm for seeking the Nash equilibrium is designed, and the uniqueness of Nash equilibrium is proven. Moreover, the individual rationality, incentive compatibility and social optimality of the proposed mechanism are analyzed and proven. The effectiveness of the proposed incentive mechanism is verified through a case study.

A discrete-time sensorless current control method is proposed for the interior permanent magnet synchronous motor (IPMSM) in this article. Due to the inconsistent $dq$ -axis inductance of IPMSMs, the design of the discrete-time current control method and sensorless control method is complicated. The control methods are therefore widely designed in the continuous-time domain, while the performance of these continuous-time methods is poor. In the proposed scheme, the current regulator is designed in the discrete-frequency domain based on an entirely discretized state-space model, which improves the dynamic and steady-state performance of the current control system. In terms of the electrical angle estimation method, the continuous-time model-based method leads to a significant estimation error. To improve the accuracy of the estimated back-EMF, a state-space model with a modified back-EMF (MBEMF) model is derived in the discrete-time domain. Then the observer of MBEMF and a phase-locked loop (PLL) with phase compensation are proposed based on the discrete-time state-space model. The proposal improves the accuracy of the estimated electrical angle. The proposal is designed directly in the discrete-time domain, which avoids significant performance deterioration in digital implementations. Finally, the proposed method is implemented on an IPMSM drive test rig to verify its improvement.

For several decades, the promise of implementing of lithium (Li) metal anodes has been regarded as the ‘‘holy grail’’ for Li-based batteries. Herein, we have proposed a facile design of a carbon fiber cloth (CFC) framework coated with SnO2nanoparticles through a hydrothermal process, which served as a reliable host for prestoring molten Li to produce a CFC@SnO2@Li composite anode. XRD, TEM, HRTEM, XPS and different electrochemical characterizations were carried out. Owing to the synergetic effects of the 3D conductive CFC and the coated lithiophilic SnO2nanoparticles, the designed CFC@SnO2@Li electrodes can buffer the volume changes and reduce the local current density, thus suppress the Li dendrites during cycling. Consequently, the CFC@SnO2electrodes showed a high and stable CE of 98.6% for 1000 cycles at a current density of 1 mA cm−2(1 mAh cm−2). What is more, at a high current density of 5 mA cm−2and a high areal capacity of 5 mAh cm−2, the symmetric cell displayed relatively low overpotential and long cycling lifetime of 1600 h. The results confirm its great potential as lithium metal anodes in practical battery applications.

The identification of biomarkers correlated with colorectal cancer (CRC) prognosis holds substantial importance from both clinical and scientific perspectives. Zinc finger protein 26 (ZNF26) has not been previously investigated or documented in solid tumors; thus, further research is necessary to ascertain its prognostic value in CRC. Gene expression profiles and clinicopathological data were acquired from The Cancer Genome Atlas (TCGA) database. Subsequently, expression correlation was assessed utilizing the TCGA CRC cohort. The prognostic value of ZNF26 was evaluated through Kaplan–Meier (KM) and ROC curve analyses. Following this, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to perform enrichment analysis between high- and low-ZNF26 expression groups. The association between immune cells, immune checkpoint genes, and ZNF26 expression levels was examined. Lastly, the research findings were further validated using CRC tissue samples. The results revealed that, in comparison to healthy controls, CRC significantly reduced ZNF26 expression. Elevated ZNF26 expression was associated with poorer overall survival in CRC patients. Additionally, high ZNF26 expression exhibited an inverse relationship with the immunological score and immune checkpoint gene expression in CRC patients. The findings from the TCGA data analysis were corroborated by the PCR results obtained from CRC tissue samples. ZNF26 is markedly upregulated in colorectal cancer tissues, potentially serving as a biomarker for CRC.

Efficient monitoring of production performance is crucial for ensuring safe operations and enhancing the economic benefits of the Iron and Steel Corporation. Although basic modeling algorithms and visualization diagrams are available in many scientific platforms and industrial applications, there is still a lack of customized research in production performance monitoring. Therefore, this article proposes an interactive visual analytics approach for monitoring the heavy-plate production process (iHPPPVis). Specifically, a multicategory aggregated monitoring framework is proposed to facilitate production performance monitoring under varying working conditions. In addition, A set of visualizations and interactions are designed to enhance analysts’ analysis, identification, and perception of the abnormal production performance in heavy-plate production data. Ultimately, the efficacy and practicality of iHPPPVis are demonstrated through multiple evaluations.