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Conversion of biomass into doped activated carbons (ACs) via green processes is envisioned as a promising path toward modern energy storage applications. ACs are commonly synthesized using strong bases, which are associated with environment and operation risks. Thus, it is necessary to find alternative and green activation reagents. Herein, we report a multi-functional molecular salt (sodium pyrithione) as an activation reagent for the economically viable preparation of doped ACs with a large surface area, rich dopants, and porous structures. The formation of carbons and the variation in the composition and pore architecture were demonstrated. The prepared ACs were then fabricated into cathodes for a zinc-ion capacitor. We correlated the properties of ACs with their performance by analyzing electrochemical measurements. Meanwhile, the optimal SPHC-based ZIC delivered high capacity and excellent cycling stability over 20 000 cycles under practical conditions. Moreover, we found that long-term chemical adsorption/desorption on active sites of ACs influences the cathode structure and thus leads to a loss of capacity and changes in the energy storage mechanism. Overall, this work provides an alternative protocol for the synthesis of doped ACs, which can be used as cathodes materials for practical high-performance ZICs. [ABSTRACT FROM AUTHOR]

This review summarizes programmable microfluidics, an advanced method for precise fluid control in microfluidic technology through microchannel design or liquid properties, referring to microvalves, micropumps, digital microfluidics, multiplexers, micromixers, slip-, and block-based configurations. Different microvalve types, including electrokinetic, hydraulic/pneumatic, pinch, phase-change and check valves, cater to diverse experimental needs. Programmable micropumps, such as passive and active micropumps, play a crucial role in achieving precise fluid control and automation. Due to their small size and high integration, microvalves and micropumps are widely used in medical devices and biological analysis. In addition, this review provides an in-depth exploration of the applications of digital microfluidics, multiplexed microfluidics, and mixer-based microfluidics in the manipulation of liquid movement, mixing, and splitting. These methodologies leverage the physical properties of liquids, such as capillary forces and dielectric forces, to achieve precise control over fluid dynamics. SlipChip technology, which branches into rotational SlipChip and translational SlipChip, controls fluid through sliding motion of the microchannel. On the other hand, innovative designs in microfluidic systems pursue better modularity, reconfigurability and ease of assembly. Different assembly strategies, from one-dimensional assembly blocks and two-dimensional Lego®-style blocks to three-dimensional reconfigurable modules, aim to enhance flexibility and accessibility. These technologies enhance user-friendliness and accessibility by offering integrated control systems, making them potentially usable outside of specialized technical labs. Microfluidic programmable strategies for channels and flow hold promising applications in biomedical research, chemical analysis and drug screening, providing theoretical and practical guidance for broader utilization in scientific research and practical applications. [ABSTRACT FROM AUTHOR]

Interface is the focus of composite material research. The interfacial structure of composites is affected by many factors, including particle size, additional elements, and preparation technology. This paper aims to investigate how heat affects the interfacial microstructure and mechanical properties of tungsten carbide particle-reinforced steel matrix composites. In this study, tungsten carbide particles were sealed as porous preforms, and the composites were prepared by casting infiltration method, with molten high-chromium steel filling the preforms. The heat gain of the composite gradually decreased in the infiltration direction from the substrate to the composite surface. The interfacial microstructure and properties of the composites were characterized by scanning electron microscopy, transmission electron microscopy, x-ray diffraction, microhardness test and three-point bending fatigue test. The results revealed that the α-W2C phase decomposed before the h-WC phase, and the M3W3C carbide increased with the dissolution of tungsten carbide particles. α-W2C and h-WC were completely decomposed in the high-heating joint surface area, and the interface boundary is clearly visible. With the decrease in heat, h-WC could not be completely decomposed, and a large number of gray rod-like phases of h-WC appeared in the interface. The bonding strength of the composite gradually decreased, and the average Vickers hardness of the interface decreased from 1376 to 855 HV while plasticity increased. [ABSTRACT FROM AUTHOR]

Functional traits play a vital role in mediating the responses of ecosystem services to environmental changes and in predicting the functioning of the ecosystem. However, the connection between functional traits and ecosystem services has become increasingly intricate due to climate change and human activities for degraded ecosystems. To investigate this relationship, we selected 27 sampling sites in the Yanhe River Basin of the Chinese Loess Plateau, each containing two types of vegetation ecosystems: natural vegetation and artificial vegetation ecosystems. At each sampling site, we measured ecosystem services and calculated the composition index of community traits. We established a response–effect trait framework that included environmental factors such as climate, elevation and human activities. Our results showed that leaf tissue density (LTD) was the overlapping response and effect trait when responding to climate change. LTD is positively correlated with mean annual temperature and negatively correlated with supporting services. Under the influence of human activities, leaf nitrogen content and leaf dry matter content were carriers of environmental change. Comparing the two vegetation ecosystems, the relationship between functional traits and ecosystem services showed divergent patterns, indicating that human activities increased the uncertainty of the relationship between functional traits and ecosystem services. Trait-based ecology holds promise for enhancing predictions of ecosystem services responses to environmental changes. However, the predictive ability is influenced by the complexity of environmental changes. In conclusion, our study highlights the importance of understanding the complex connection between functional traits and ecosystem services in response to climate changes and human activities. [ABSTRACT FROM AUTHOR]

Optical encryption is an increasingly significant technique in the realm of information security. In the recent decade, there has been considerable interest in using planar optics elements for information encryption. However, information leakage possibly occurs due to limited encrytion channels available for single‐layer devices. To circumvent this problem, a novel encryption method is put forward using secret sharing cascaded liquid crystal (LC) elements with spatial dislocation, which can produce near‐field patterns and far‐field holographic images under different illumination conditions. Specifically, Malus's Law and its inherent one‐to‐four mapping of rotational degeneracy, along with the Pancharatnam‐Berry (PB) phase introduced by LC molecules, to achieve multi‐channel encryption are utilized. Therefore, each cascaded LC unit can manipulate the amplitude and phase imparted to output light independently, thus only by obtaining both LC devices can decryption be realized. To further enhance the encryption security, the author purposely divide each LC device into multiple regions and find that the encrypted patterns can only be recovered when the two LC elements align precisely with a specific dislocation. These experimental measurements agree well with the design, thus demonstrating the strong encryption capability and broad application prospects of the design approach in the field of optical encryption with high cost‐effectiveness. [ABSTRACT FROM AUTHOR]

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Layered double hydroxide (LDH) is considered a highly promising electrode material for supercapacitors (SCs) due to its high theoretical specific capacitance. However, LDH powders often suffer from poor electrical conductivity, structure pulverization, slow charge transport, and insufficient active sites. Herein, a self‐supporting electrode with a Mott–Schottky heterostructure has been designed for high‐performance SCs. The electrode consists of low crystallinity NiCo‐LDH nanosheets and vertical graphene (VG) directly grown on carbon cloth. The LDH was converted from a metal–organic framework (MOF) by the sol–gel method. This self‐supporting electrode provides fast charge transfer, reducing the pulverization effect and energy barrier. The Mott–Schottky heterostructure of LDH@VG regulates electron density and enhances electron transfer, as confirmed by density functional theory calculation. The optimized LDH@VG heterostructure electrode exhibits an excellent areal capacitance of 5513.8 mF cm−2 and rate capability of 82.1%. Furthermore, the fabricated hybrid SC demonstrates excellent energy density of 404.8 μWh cm−2 at 1.6 mW cm−2 and a remarkable cycling life, with a capacitance of 92.0% after 10 000 cycles. This work not only provides a simple dip‐coating and MOF conversion method to synthesize heterojunction‐based electrodes, but also broadens the horizon for designing advanced electrode materials for SCs. [ABSTRACT FROM AUTHOR]

Background: Plant-specific TIFY proteins play crucial roles in regulating plant growth, development, and various stress responses. However, there is no information available about this family in Artemisia argyi, a well-known traditional medicinal plant with great economic value. Results: A total of 34 AaTIFY genes were identified, including 4 TIFY, 22 JAZ, 5 PPD, and 3 ZML genes. Structural, motif scanning, and phylogenetic relationships analysis of these genes revealed that members within the same group or subgroup exhibit similar exon-intron structures and conserved motif compositions. The TIFY genes were unevenly distributed across the 15 chromosomes. Tandem duplication events and segmental duplication events have been identified in the TIFY family in A. argyi. These events have played a crucial role in the gene multiplication and compression of different subfamilies within the TIFY family. Promoter analysis revealed that most AaTIFY genes contain multiple cis-elements associated with stress response, phytohormone signal transduction, and plant growth and development. Expression analysis of roots and leaves using RNA-seq data revealed that certain AaTIFY genes showed tissue-specific expression patterns, and some AaTIFY genes, such as AaTIFY19/29, were found to be involved in regulating salt and saline-alkali stresses. In addition, RT-qPCR analysis showed that TIFY genes, especially AaTIFY19/23/27/29, respond to a variety of hormonal treatments, such as MeJA, ABA, SA, and IAA. This suggested that TIFY genes in A. argyi regulate plant growth and respond to different stresses by following different hormone signaling pathways. Conclusion: Taken together, our study conducted a comprehensive identification and analysis of the TIFY gene family in A. argyi. These findings suggested that TIFY might play an important role in plant development and stress responses, which laid a valuable foundation for further understanding the function of TIFY genes in multiple stress responses and phytohormone crosstalk in A. argyi. [ABSTRACT FROM AUTHOR]

Background: The active functionalities of RNA are recognized to be heavily dependent on the structure and sequence. Therefore, a model that can accurately evaluate a design by giving RNA sequence-structure pairs would be a valuable tool for many researchers. Machine learning methods have been explored to develop such tools, showing promising results. However, two key issues remain. Firstly, the performance of machine learning models is affected by the features used to characterize RNA. Currently, there is no consensus on which features are the most effective for characterizing RNA sequence-structure pairs. Secondly, most existing machine learning methods extract features describing entire RNA molecule. We argue that it is essential to define additional features that characterize nucleotides and specific sections of RNA structure to enhance the overall efficacy of the RNA design process. Results: We develop two deep learning models for evaluating RNA sequence-secondary structure pairs. The first model, NU-ResNet, uses a convolutional neural network architecture that solves the aforementioned problems by explicitly encoding RNA sequence-structure information into a 3D matrix. Building upon NU-ResNet, our second model, NUMO-ResNet, incorporates additional information derived from the characterizations of RNA, specifically the 2D folding motifs. In this work, we introduce an automated method to extract these motifs based on fundamental secondary structure descriptions. We evaluate the performance of both models on an independent testing dataset. Our proposed models outperform the models from literatures in this independent testing dataset. To assess the robustness of our models, we conduct 10-fold cross validation. To evaluate the generalization ability of NU-ResNet and NUMO-ResNet across different RNA families, we train and test our proposed models in different RNA families. Our proposed models show superior performance compared to the models from literatures when being tested across different independent RNA families. Conclusions: In this study, we propose two deep learning models, NU-ResNet and NUMO-ResNet, to evaluate RNA sequence-secondary structure pairs. These two models expand the field of data-driven approaches for learning RNA. Furthermore, these two models provide the new method to encode RNA sequence-secondary structure pairs. [ABSTRACT FROM AUTHOR]

Self‐trapped excitons (STEs) of lead‐free perovskites have aroused tremendous interest in remote optical thermometry due to strong exciton–phonon coupling and large Stokes shifts. Herein, a bright multimodal and multiplexed optical thermometer is constructed with high sensitivity (Sr) and self‐calibrating ability based on Cs2NaInCl6:Er3+ double perovskite, allowing for fast and simplified reading via mobile devices. Intriguingly, Er3+ doping not only shows the characteristic green emissions but also introduces nanoelectronic domains through a new localized valance band maximum and breaks the symmetry of In3+ site, which facilitates the generation of more STEs. The temperature‐sensitive blue emission of STEs and temperature‐insensitive green emission of Er3+ endow multimodal optical thermometry including time‐resolved and ratiometric readout schemes with a maximum Sr of 3.8% K−1, where an upconversion primary thermometry serves as a reference to calibrate other modes. Meanwhile, the designed thermometers show robust photostability, repeatability, and structural stability for long‐time working and storage. In addition, the remarkable thermochromic phenomenon from blue to green enables a quick color‐multiplexed thermography on a smartphone, which is utilized to capture real‐time 2D thermal imaging of microelectronic devices. This work demonstrates the great potential of lead‐free double perovskite for low‐cost and portable optical thermometry. [ABSTRACT FROM AUTHOR]

Objectives: Plasma bile acid (BA) has been widely studied as pathophysiological factors in chronic liver disease. But the changes of plasma BA level in lean metabolic dysfunction-associated fatty liver disease (MAFLD) remains unclear. Here, we clarified the BA metabolic characteristics of lean MAFLD and explored its significance and mechanism as a marker. Methods: We employed ultra-performance liquid chromatography tandem mass spectrometry based on BA metabonomics to characterize circulating bile acid in lean MAFLD patients. Explore its significance as serum biomarkers by further cluster analysis, functional enrichment analysis, and serum concentration change analysis of differential BAs. Evaluation of diagnostic value of differential BAs by ROC analysis. Results: A total of 65 BAs were detected and 17 BAs were identified which showed different expression in the lean-MAFLD group compared with the normal group. Functional annotation and enrichment analysis of KEGG and HMDB showed that differential BAs were mainly related to bile acid biosynthesis, bile secretion, cholesterol metabolism, and familial hypercholangitis, involving diseases including but not limited to cirrhosis, hepatocellular carcinoma, chronic active hepatitis, colorectal cancer, acute liver failure, and portal vein obstruction. ROC analysis displayed that the 6 BA metabolites (GCDCA-3S, GUDCA-3S, CDCA-3S, NCA, TCDCA, and HDCA) exhibited well differential diagnostic ability in discriminating between lean MAFLD patients and normal individuals with an area under the curve (AUC) ⩾0.85. Conclusions: We delineated the characteristics of BA level in patients with lean MAFLD, and identified 6 potential plasma BA biomarkers of lean MAFLD. Plain Language Summary: Analysis of serum bile acid profile characteristics and identification of new biomarkers in fatty liver disease accompanied by metabolic abnormalities in people with normal weight based on the technology of high-resolution mass spectrometry Objectives: The physique of lean MAFLD patient is normal or even leaner. They often does not pay enough attention to the onset of fatty liver disease. Plasma bile acids (BAs) have been extensively studied as pathophysiological actors in chronic liver disease. But the changes of plasma BA level in fatty liver disease accompanied by metabolic abnormalities in people with normal weight remains unclear. Here, we clarified the BA metabolic characteristics of lean MAFLD and explored its significance and mechanism as a marker. Methods: we employed an advanced mass spectrometry technology to characterize circulating bile acid in lean lean MAFLD patients. To explore its significance as a marker by bioinformatics methods, such as cluster analysis, functional enrichment analysis, and relative content change analysis of differential BAs. Evaluation diagnostic accuracy and determine threshold points of BAs by Receiver Operating Characteristic analysis. Results: A total of 65 BAs were detected and 17 BAs were identified which showed different expression in the lean MAFLD group compared with the normal group. Bioinformatics analysis showed that differential BAs were mainly related to bile acid biosynthesis, bile secretion, cholesterol metabolism, and familial hypercholangitis, involving diseases including but not limited to cirrhosis, hepatocellular carcinoma, chronic active hepatitis, colorectal cancer, acute liver failure, and portal vein obstruction. ROC analysis displayed that the six BA metabolites (GCDCA-3S, GUDCA-3S, CDCA-3S, NCA, TCDCA and HDCA) exhibited well differential diagnostic ability in discriminating between lean MAFLD patients and normal individuals with an area under the curve (AUC) ≥ 0.85. Conclusions: We delineated the characteristics of BA level in patients with lean MAFLD, and identified six potential plasma BA biomarkers of lean MAFLD. This strategy provided broad clinical application prospects for disease assessment. [ABSTRACT FROM AUTHOR]

Although messenger RNA translation is tightly regulated to preserve protein synthesis and cellular homeostasis, chronic exposure to interferon‐γ (IFN‐γ) in several cancers can lead to tryptophan (Trp) shortage via the indoleamine‐2,3‐dioxygenase (IDO)‐ kynurenine pathway and therefore promotes the production of aberrant peptides by ribosomal frameshifting and tryptophan‐to‐phenylalanine (W>F) codon reassignment events (substitutants) specifically at Trp codons. However, the effect of Trp depletion on the generation of aberrant peptides by ribosomal mistranslation in gastric cancer (GC) is still obscure. Here, it is shows that the abundant infiltrating lymphocytes in EBV‐positive GC continuously secreted IFN‐γ, upregulated IDO1 expression, leading to Trp shortage and the induction of W>F substitutants. Intriguingly, the production of W>F substitutants in EBV‐positive GC is linked to antigen presentation and the activation of the mTOR/eIF4E signaling pathway. Inhibiting either the mTOR/eIF4E pathway or EIF4E expression counteracted the production and antigen presentation of W>F substitutants. Thus, the mTOR/eIF4E pathway exposed the vulnerability of gastric cancer by accelerating the production of aberrant peptides and boosting immune activation through W>F substitutant events. This work proposes that EBV‐positive GC patients with mTOR/eIF4E hyperactivation may benefit from anti‐tumor immunotherapy. [ABSTRACT FROM AUTHOR]

DABMA is a chemical molecule optimized from the parent compound ABMA and exhibits broad‐spectrum antipathogenic activity by modulating the host's endolysosomal and autophagic pathways. Both DABMA and ABMA inhibit severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) in a cellular assay, which further expands their anti‐pathogen spectrum in vitro. However, their precise mechanism of action has not yet been resolved. TMEM175 is a newly characterized endolysosomal channel which plays an essential role in the homeostasis of endosomes and lysosomes as well as organelle fusion. Here, we show that DABMA increases the endosomal TMEM175 current through organelle patch clamping with an EC50 of 17.9 μm. Depletion of TMEM175 protein significantly decreases the antitoxin activity of DABMA and affects its action on acidic‐ and Rab7‐positive endosomes as well as on endolysosomal trafficking. Thus, TMEM175 is necessary for DABMA's activity and may represent a druggable target for the development of anti‐infective drugs. Moreover, DABMA, as an activator of the TMEM175 channel, may be useful for the in‐depth characterization of the physiological and pathological roles of this endolysosomal channel. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the clinical outcomes of arthroscopic inside-out ganglionectomy of dominant dorsal wrist ganglion. Methods: Patients with dominant wrist ganglion cyst treated in our hospital from January 1, 2014 to June 31, 2023 was enrolled in this retrospective analysis. All patients underwent dye-assist arthroscopic inside-out ganglionectomy. After discharge, the patients were followed for a minimum of 6 months. The primary outcomes were to assess patient wrist function using the Patient-Rated Wrist Evaluation (PRWE) and Mayo Modified Wrist Score (MMWS). The secondary outcomes were visual analog score (VAS), wrist active range of motion (ROM), grip strength, recurrence rate and complication. Results: All ganglion were successfully resected after dye staining. Patients were followed for an average of 12.17 months. There were no significant changes between preoperative and postoperative wrist active ROM or grip strength, except for wrist flexion (which showed a slightly greater improvement after surgery, P = 0.049), there were notable improvements in VAS, MMWS, and PRWE postoperatively. Recurrence occurred in 3 patients. No major complications observed during the follow-up period. Conclusion: Dye-assist arthroscopic inside-out ganglionectomy is safe and uncomplicated, worth of clinical promotion. [ABSTRACT FROM AUTHOR]

Asymmetric spin–orbit interaction (ASOI) breaks the limitations in conjugate symmetry of traditional geometric phase metasurfaces, bringing new opportunities for various applications such as spin-decoupled holography, imaging, and complex light field manipulation. Since anisotropy is a requirement for spin–orbit interactions, existing ASOI mainly relies on meta-atom with C1 and C2 symmetries, which usually suffer from an efficiency decrease caused by the propagation phase control through the structural size. Here, we demonstrate for the first time that ASOI can be realized in meta-atoms with rotational symmetry ≥3 by combining the generalized geometric phase with the propagation phase. Utilizing an all-metallic configuration, the average diffraction efficiency of the spin-decoupled beam deflector based on C3 meta-atoms reaches ∼84 % in the wavelength range of 9.3–10.6 μm, which is much higher than that of the commonly used C2 meta-atoms with the same period and height. This is because the anisotropy of the C3 metasurface originates from the lattice coupling effect, which is relatively insensitive to the propagation phase control through the meta-atom size. A spin-decoupled beam deflector and hologram meta-device were experimentally demonstrated and performed well over a broadband wavelength range. This work opens a new route for ASOI, which is significant for realizing high-efficiency and broadband spin-decoupled meta-devices. [ABSTRACT FROM AUTHOR]

Polarization is the nature of optics. Exploiting metasurface's polarizations can enhance the multiplexing capacity but face a limited number of channels. For example, a single‐layer metasurface can offer three independent channels with six degrees of freedom (DoFs) including the amplitude and phase of Ex, Exy(yx), and Ey of the Jones matrix. In this work, it is theoretically demonstrated that the degrees of freedom of dual‐layer metasurfaces can reach eight, overcoming the polarization multiplexing constraints of single‐layer metasurfaces and that the cross‐talk can be largely reduced as compared with single‐layer metasurfaces when the channel number is larger than three. Numerical calculations manifest a decrease of 100%, 63%, and 50% for the cross‐talk of channels 4, 5, and 6, respectively. As a proof‐of‐concept demonstration of high‐capacity polarization multiplexing, an arbitrary‐polarization‐controlled 5‐channel dual‐layer metasurface exhibiting five nanoprintings and five holographic images with reduced cross‐talk under different incident and output polarizations is successfully designed. Thus, the research highlighting the high‐multiplexing‐capacity of dual‐layer metasurfaces can significantly advance multifunctional optical devices with high efficiency, simple integration, and ease of manipulation. [ABSTRACT FROM AUTHOR]

Coal is a prominent energy resource in China. Therefore, it is crucial to accurately extract the coal-covered areas. Taking Xinjiang's Zhundong mining region as the study area, Landsat 8 OLI data were employed to assess the spectral curves of four typical ground objects, including vegetation, bare land, water body and bare coal. The Normalized Difference Bare Coal Index (NDBCI) and the Normalized Difference Coal Index (NDCI) were developed to extract coal-covered area. Higher-resolution Sentinel-2B data for the same period were used for verification, with extraction accuracy evaluated by five metrics including Kappa coefficient, Overall accuracy, Checking accuracy, Checking completeness and F1-score. The results of extracting coal-covered areas showed that (1) the NDBCI showed 'internal fragmentation' and the NDCI demonstrated 'pixel overflow' during the extraction process. Therefore, we determined the optimal thresholds −0.03 for NDBCI and 0.04 for NDCI. (2) NDBCI distinguished pixels with lower grey-scale values, such as water body, road and gangue. However, some dump zones and shed patches were misclassified. (3) NDCI generated clear boundaries and more complete interiors, and the dump zone and shed could be distinguished. However, some water body parts were misclassified as coal-covered areas. (4) Combined application of NDBCI and NDCI generated a 'complementary' effect better than both individual modes. Kappa coefficient, Overall accuracy and F1-score reached 0.95, 98.76% and 0.75, respectively. This study successfully extracted coal-covered areas by developing a remote sensing index based on spectral traits and a priori knowledge of the study area. The proposed combined extraction mode achieved high accuracy for rapid and reliable identification of coal-covered areas. Highlights: Two new remote sensing indexes for coal-covered area extraction were proposed in this paper. Complementary advantages were found between NDBCI and NDCI in the extraction. Accuracy assessment was performed based on manually deciphered high-precision raster data. [ABSTRACT FROM AUTHOR]

African swine fever (ASF) is an acute infectious disease with a high mortality rate in both domestic and wild boars. Commercial vaccines or antiviral drugs for ASF were not available due to the complex diversity of the structure and genome of its pathogen African swine fever virus (ASFV). In recent years, there have been many reports on candidate strains of attenuated vaccines for ASFV. In this study, we obtained a recombinant virus named SY18ΔL60LΔCD2v by simultaneously deleting the L60L gene and CD2v gene from highly virulent strain SY18. In vitro, SY18ΔL60LΔCD2v displayed a decreased growth kinetic compared to that of parental SY18. In vivo, high doses (105 TCID50) of SY18ΔL60LΔCD2v can protect pigs (5/5) from attacks by the parental SY18 strain (102 TCID50). Low doses (102 TCID50) of SY18ΔL60LΔCD2v only protected 20% of pigs (1/5) from attacks by the parental SY18 strain (102 TCID50). The results indicated that the absence of these two genes in SY18 could induce protection against the homologous parental strain, and there were no obvious clinical symptoms or viremia. These results indicate that the SY18ΔL60LΔCD2v strain can serve as a new live attenuated vaccine candidate for the prevention and control of ASFV infection. [ABSTRACT FROM AUTHOR]

Rechargeable neutral aqueous zinc−air batteries (ZABs) are a promising type of energy storage device with longer operating life and less corrosiveness compared with conventional alkaline ZABs. However, the neutral ZABs normally possess poor oxygen evolution reactions (OERs) and oxygen reduction reactions performance, resulting in a large charge–discharge voltage gap and low round‐trip efficiency. Herein, we demonstrate a sunlight‐assisted strategy for achieving an ultralow voltage gap of 0.05 V in neutral ZABs by using the FeOOH‐decorated BiVO4 (Fe‐BiVO4) as an oxygen catalyst. Under sunlight, the electrons move from the valence band (VB) of Fe‐BiVO4 to the conduction band producing holes in VB to promote the OER process and hence reduce the overpotential. Meanwhile, the photopotential generated by the Fe‐BiVO4 compensates a part of the charging potential of neutral ZABs. Accordingly, the energy loss of the battery could be compensated via solar energy, leading to a record‐low gap of 0.05 V between the charge and discharge voltage with a high round‐trip efficiency of 94%. This work offers a simple but efficient pathway for solar‐energy utilization in storage devices, further guiding the design of high energy efficiency of neutral aqueous ZABs. [ABSTRACT FROM AUTHOR]

Copyright of Rare Metals is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ultra-short-term photovoltaic (PV) power forecasting is crucial in the scheduling and functioning of contemporary electrical systems, playing a key role in promoting renewable energy integration and sustainability. In this paper, a novel hybrid model, termed AI_VMD-HS_CNN-BiLSTM-A, is introduced to tackle the challenges associated with the volatility and unpredictability inherent in PV power output. Firstly, Akaike information criterion variational mode decomposition (AI_VMD) integrates the Akaike information criterion with variational mode decomposition (VMD) and reduces data complexity, enhancing grid optimization and energy efficiency. The adaptive selection of optimal parameters enhances VMD decomposition performance, supporting sustainable energy management. Secondly, the hierarchical scale-transform convolutional architecture (HS_CNN) supplements the traditional convolutional neural network (CNN) with two channels featuring distinct dilation rates, thereby extracting dual levels of time-scale information for a more comprehensive data representation. Finally, a bidirectional long short-term memory neural network (BiLSTM) with an attentional mechanism combines past and future data to enable more accurate forecasts, aiding in carbon reduction and smart grid advancements. Experimentation with data from the Alice Springs PV plant in Australia demonstrates that the proposed AI_VMD-HS_CNN-BiLSTM-A model exhibits superior adaptability and accuracy in multiple time-scale forecasting compared to the baseline models. This approach is important for decision-making and scheduling in grid-connected photovoltaic systems, enhancing energy resilience and promoting the sustainable development of renewable energy. [ABSTRACT FROM AUTHOR]

Near‐infrared (NIR) fluorescent probes with aggregation‐induced emission (AIE) properties are of great significance in cell imaging and cancer therapy. However, the complexity of its synthesis, poor photostabilities, and expensive raw materials still pose some obstacles to their practical application. This study reported an AIE luminescent material with red emission and its application in in vitro imaging and photodynamic therapy (PDT) study. This material has the characteristics of simple synthesis, large Stokes shift, good photostabilities, and excellent lipid droplets‐specific testing ability. Interestingly, this red‐emitting material can effectively produce reactive oxygen species (ROS) under white light irradiation, further achieving PDT‐mediated killing of cancer cells. In conclusion, this study demonstrates a simple approach to synthesize NIR AIE probes with both imaging and therapeutic effects, providing an ideal architecture for constructing long‐wavelength emission AIE materials. [ABSTRACT FROM AUTHOR]

Purpose: Osteosarcoma (OS) is a primary bone tumor with high malignancy and poor prognosis. Ferroptosis plays a crucial role in OS. This study aimed to evaluate the effects of Ankyrin 1 (ANK1) on OS and to investigate its specific mechanisms. Methods: Microarray datasets related to "osteosarcoma" were selected for this study. Relevant hub genes in OS were identified through bioinformatics analysis. Transfected U-2OS and MG-63 cells were used for in vitro experiments. The effects of ANK1 overexpression on cell viability, migration, and invasion were determined through CCK-8, wound healing, and transwell assays. An OS mouse model was established for the in vivo experiments. Hematoxylin-eosin staining and immunohistochemistry were conducted to observe the histological effects of ANK1 overexpression on mouse tumors. TUNEL staining was performed to evaluate apoptosis in mouse. Results: There were 159 common differentially expressed genes in the GSE16088 and GSE19276 datasets. The hub genes ANK1, AHSP, GYPB, GYPA, KEL, and ALAS2 were identified. Pan-cancer analysis verified that ANK1 was closely associated with cancer prognosis and immune infiltration. Furthermore, ANK1 overexpression inhibited the proliferation, migration, and invasion of OS cells and promoted ferroptosis, while ferroptosis inhibitor (fer-1) weakened these effects. Moreover, ANK1 overexpression suppressed tumor growth, promoted apoptosis, reduced the number of Ki67 positive cells, and elevated the number of caspase-3 positive cells in vivo. Conclusions: ANK1 is a prognosis biomarker of OS that can alleviate the progression of OS by promoting ferroptosis. [ABSTRACT FROM AUTHOR]

Developing light yet strong aluminum (Al)-based alloys has been attracting unremitting efforts due to the soaring demand for energy-efficient structural materials. However, this endeavor is impeded by the limited solubility of other lighter components in Al. Here, we propose to surmount this challenge by converting multiple brittle phases into a ductile solid solution in Al-based complex concentrated alloys (CCA) by applying high pressure and temperature. We successfully develop a face-centered cubic single-phase Al-based CCA, Al55Mg35Li5Zn5, with a low density of 2.40 g/cm3 and a high specific yield strength of 344×103 N·m/kg (typically ~ 200×103 N·m/kg in conventional Al-based alloys). Our analysis reveals that formation of the single-phase CCA can be attributed to the decreased difference in atomic size and electronegativity between the solute elements and Al under high pressure, as well as the synergistic high entropy effect caused by high temperature and high pressure. The increase in strength originates mainly from high solid solution and nanoscale chemical fluctuations. Our findings could offer a viable route to explore lightweight single-phase CCAs in a vast composition-temperature-pressure space with enhanced mechanical properties. By overcoming the limited solubility of other lighter components in aluminum using high pressure and high temperature, a low-density, high specific strength, and single-phase aluminum-based complex concentrated alloy is developed. [ABSTRACT FROM AUTHOR]

Accurate and reliable PV power probabilistic-forecasting results can help grid operators and market participants better understand and cope with PV energy volatility and uncertainty and improve the efficiency of energy dispatch and operation, which plays an important role in application scenarios such as power market trading, risk management, and grid scheduling. In this paper, an innovative deep learning quantile regression ultra-short-term PV power-forecasting method is proposed. This method employs a two-branch deep learning architecture to forecast the conditional quantile of PV power; one branch is a QR-based stacked conventional convolutional neural network (QR_CNN), and the other is a QR-based temporal convolutional network (QR_TCN). The stacked CNN is used to focus on learning short-term local dependencies in PV power sequences, and the TCN is used to learn long-term temporal constraints between multi-feature data. These two branches extract different features from input data with different prior knowledge. By jointly training the two branches, the model is able to learn the probability distribution of PV power and obtain discrete conditional quantile forecasts of PV power in the ultra-short term. Then, based on these conditional quantile forecasts, a kernel density estimation method is used to estimate the PV power probability density function. The proposed method innovatively employs two ways of a priori knowledge injection: constructing a differential sequence of historical power as an input feature to provide more information about the ultrashort-term dynamics of the PV power and, at the same time, dividing it, together with all the other features, into two sets of inputs that contain different a priori features according to the demand of the forecasting task; and the dual-branching model architecture is designed to deeply match the data of the two sets of input features to the corresponding branching model computational mechanisms. The two a priori knowledge injection methods provide more effective features for the model and improve the forecasting performance and understandability of the model. The performance of the proposed model in point forecasting, interval forecasting, and probabilistic forecasting is comprehensively evaluated through the case of a real PV plant. The experimental results show that the proposed model performs well on the task of ultra-short-term PV power probabilistic forecasting and outperforms other state-of-the-art deep learning models in the field combined with QR. The proposed method in this paper can provide technical support for application scenarios such as energy scheduling, market trading, and risk management on the ultra-short-term time scale of the power system. [ABSTRACT FROM AUTHOR]

Dynamic displacement is an important indicator for bridge safety estimation but is difficult to measure due to economic or technological limitations. Dynamic responses of a passing vehicle include the bridge dynamic response information. This study proposes a framework utilizing artificial neural networks to efficiently and accurately predict bridge displacements from the dynamic response of a passing vehicle. The input and the output of the networks are the vehicle acceleration responses and the bridge dynamic displacement responses, respectively. The implemented framework consists of convolutional neural network (CNN) and gated recurrent units (GRU). CNN is adept at feature extraction in the microcosm of short‐term time series, revealing intricate nuances. As a complement, GRU plays a crucial role in extracting features of macroscopic long‐term time series. The CNN‐GRU network can efficiently extract higher‐order features contained in the input data. Numerical experiments are conducted using the developed vehicle‐bridge interaction (VBI) system model to obtain requisite data for training the deep neural network. The impact of the presence or absence of roadway irregularities and the number of vehicles are discussed, indicating the accuracy of the framework. Furthermore, a laboratory experiment is conducted to further assess the performance of the CNN‐GRU network. Results indicate that the CNN‐GRU network offers an effective alternative for bridge displacement measurements. [ABSTRACT FROM AUTHOR]

Phytochemical investigation on the fruiting bodies of the medicinal fungus Ganoderma lingzhi led to the isolation of a new norsteroid, namely ganonorsterone A (1), together with one known steroid, cyathisterol (2). The structure and absolute configuration of compound 1 were assigned by extensive analysis of MS, NMR data, and quantum-chemical calculations including electronic circular dichroism (ECD) and calculated 13C NMR-DP4+ analysis. Bioassay results showed that compound 1 displayed moderate inhibition on NO production in RAW 264.7 macrophages. [ABSTRACT FROM AUTHOR]

A comprehensive analysis of regional climate changes is essential in arid and semi-arid regions to optimize water resources management. This research aims to evaluate the changes in temperature and precipitation across the Mujib Basin in Jordan, using the most recent Coupled Model Inter-comparison Project Phase 6 (CMIP6) model. Firstly, the performance of six CMIP6 general circulation models (GCMs) to reproduce historical temperature and precipitation from 1985 to 2014 was evaluated using observed climate data. The most suitable GCM was then bias-corrected using the linear scaling approach. The findings demonstrate that the EC-Earth3–Veg model could reasonably simulate the historical climate pattern of the Mujib Basin, with coefficient of determination (R2) values of 0.90, 0.83, and 0.65 for monthly Tmin, Tmax, and precipitation, respectively. Under both the SSP2-4.5 and SSP5-8.5 scenarios, Tmax is projected to increase by 1.4 to 3.9 °C and 1.6 to 6.8 °C, respectively, whereas Tmin increases from 1.4 to 3.4 °C and 1.6 to 6.4 °C. Furthermore, precipitation is projected to decrease by 4.61–23.2% at the end of the 21st century. These findings could help policymakers in formulating better adaptation strategies to reduce the impact of climate change in Jordan This is a crucial step toward becoming a climate-resilient nation. [ABSTRACT FROM AUTHOR]

During the past few years, metasurface polarization optics has experienced remarkable advances, resulting in revolutionary applications in imaging, sensing, computing, etc. The realization of complex optical operations requires the consideration of both the individual meta‐atoms as well as their intricate couplings. However, conventional design methods face challenges as design degrees of freedom and functionality complexity. Additionally, previous studies are restricted to the local design of single meta‐atoms based on explicit mapping relationships while ignoring interactions, resulting in an inability to meet the on‐demand requirements of complex light‐field operations. Here, a global design strategy based on field‐driven polygon evolution to achieve the inverse design of large‐scale coupled meta‐atoms is proposed. Through two global simulations, it can effectively reshape any given target optical field into an optimal structural distribution of devices without knowing mapping relationship. Near‐perfect spin‐decoupled beam‐splitting and high‐performance focusing, as well as the generation of arbitrary vector optical fields on the Poincaré sphere with a maximal diffraction efficiency closely approaching 100%, are experimentally demonstrated. This strategy opens up a new avenue for a rapid inverse design of large‐scale, high‐performance multifunctional meta‐devices, which can hold significant implications for both classical and quantum information processing domains. [ABSTRACT FROM AUTHOR]

The aerodynamic characteristics of the train under the stationary thunderstorm downburst wind were studied. The thunderstorm downburst wind test device was employed to simulate the thunderstorm downburst wind field. Based on the rigid model pressure measurement tests, analyses were conducted on the influence of radial distance on the pressure coefficients on the train surface, the aerodynamic load coefficients of the train section, and the total force coefficients of the middle and head cars. On this basis, combined with the computational fluid dynamics model, further exploration was conducted on the characteristics of the mean pressure on the train surface and the flow field around the train at different radial distances under the stationary thunderstorm downburst wind. The research results show that the train's total aerodynamic coefficients fluctuate with the train's position. The non-uniform distribution of the lateral force coefficient for each train section is primarily caused by variations in the wind yaw angle along the train's longitudinal axis. Variations in the wind attack angle at different radial distances cause the total lateral force coefficient to change accordingly. When the radial distance r/Dj = 0.5, there is no significant vortex-shedding phenomenon in the flow field around the train. However, when radial distance r/Dj = 1 and 1.5, the leeward surface exhibits a regular vortex-shedding phenomenon. Vortex shedding starts at the junction of the leeward surface and the top surface, extending from the middle car along the train's longitudinal axis toward the front and rear. [ABSTRACT FROM AUTHOR]

The epidemic has profoundly changed the world's landscape. In the current modeling and analysis of the epidemic's spatiotemporal dynamics, there is a lack of accurate descriptions of individual and collective trajectories, making it difficult to meet the demands for precision epidemic prevention. To address this issue, based on the analysis of existing methods for spatiotemporal analysis of the epidemic and trajectory description models, combined with health code punch-in data, a spatiotemporal threedimensional coordinate system is established with latitude and longitude as the x and y axes and time as the z axis. The health code punch-in data are used as trajectory nodes to present the spatiotemporal trajectories of carriers and close contacts. Individual, paired, and group trajectories are accurately described in sequence, thereby constructing a "mountain-shaped" trajectory description model that integrates spatiotemporal topological relationships. This model accurately locates the spatiotemporal range that needs to be controlled within the three-dimensional coordinate system, thereby achieving precise epidemic prevention. Experiments conducted on the Foursquare Dataset simulation dataset demonstrate that the "mountain" model effectively reduces the scope of investigation and the number of personnel, and it has broad application scenarios. [ABSTRACT FROM AUTHOR]

Simple Summary: Our study provides the first record of Pacific sleeper sharks in 1629 m deep waters off the southeast coast of Hainan Island in the South China Sea. At a site, we placed a dead cow as bait and a metal-framed cage with cameras and observed eight individuals and their feeding activities by using ROV diving. The record indicates an expansion of the known distribution range of the Pacific sleeper sharks to the west of the northern South China Sea. Such a finding demonstrates that the habitat ranges of large animals are far wider in deep seas than we know from observations in the upper layer, and habitat expansion of some animal populations may have already taken place under intensive anthropogenic influences such as climate changes. We conducted an experiment of planting a dead cow and a metal-framed cage with cameras on the 1629 m deep sea floor off the southeast coast of Hainan Island in the northwestern South China Sea, using ROV diving and setting up a video camera on the cage to observe animals who came to eat the bait. The deep-sea cameras captured footage of eight Pacific sleeper sharks (Somniosus pacificus) swimming and feeding around the dead cow. To our knowledge, this is the first time the occurrence of such a shark species has been reported in the South China Sea. Eight individuals were differentiated based on the characteristic differences displayed in the images, with lengths of 1.9 to 5.1 m estimated. The video camera also recorded the predators' behavior of tearing at the dead cow on the seabed. It was discovered that Pacific sleeper sharks are not strictly solitary and exhibit queue-feeding behavior. This study is significant as it documents a record of a data-scarce shark species, for which little information is available in the literature. It also documents an expansion of the species' known habitat from the north Pacific Ocean into the South China Sea. Such sharks diving into the deep sea to predate on dead animals also suggests that occurrences of large chunks of dead organic bodies falling onto the deep sea might have been more frequent than we previously thought in the South China Sea. The findings have implications for understanding the geographic connectivity of large swimming animals between the South China Sea and the Pacific Ocean and provide scientific evidence for formulating conservation and management strategies for sharks and other large animals in the oceans. [ABSTRACT FROM AUTHOR]

This paper presents a novel analytical approach for predicting the volume loss of a tunnel face during advancement with different longitudinal slope angles. The proposed approach utilizes the continuous velocity field of a circular tunnel face in undrained clay and combines the upper-bound limit analysis with the mobilized strength design method to derive the relationship between the load factor and the volume loss. An analytical expression is proposed for the relationship between the face support pressure and surface deformation, accounting for the longitudinal slope angle. Parametric studies are conducted to explore the impact of the longitudinal slope angle on the ground surface settlement during tunnel face advancement. The results reveal that the ground surface settlement increases with the tunneling longitudinal gradient in a downward direction but decreases for tunneling in an upward direction when the supporting pressure remains unchanged and the ground surface is horizontal. As the tunneling direction is parallel to the inclined ground surface, the impact on the ground surface settlement becomes more significant and cannot be ignored in engineering practice. [ABSTRACT FROM AUTHOR]

SUMMARY: Citrus is a model plant for studying adventitious embryos, a form of asexual reproduction controlled by a single dominant gene, RWP. This gene has been identified as the causal gene for nucellar embryogenesis, but its function has not yet been fully understood. In this study, we used the fast‐growing Fortunella hindsii as a system to explore chromatin accessibility during the nucellar embryony initiation, emphasizing elevated chromatin accessibility in polyembryonic (PO) genotypes compared to monoembryonic ones (MO). Notably, a higher level of accessible chromatin was observed in one allele of the promoter region of FhRWP, consistent with increased expression of the allele carrying the causal structural variant. By independently performing RNAi and gene editing experiments on PO genotypes, we found the downregulation of FhRWP expression could reduce the number of nucellar embryos, while its knockout resulted in abnormal axillary bud development. In overexpression experiments, FhRWP was identified as having the unique capability of inducing the embryogenic callus formation in MO stem segments, possibly through the regulation of the WUS‐CLV signaling network and the ABA and cytokinin pathway, marking the inaugural demonstration of FhRWP's potential to reignite somatic cells' embryogenic fate. This study reveals the pleiotropic function of RWP in citrus and constructs a regulatory network during adventitious embryo formation, providing a new tool for bioengineering applications in plant regeneration. Significance Statement: FhRWP plays a central role in regulating multiple developmental phenotypes, including axillary bud differentiation, nucellar embryo formation, and somatic embryogenesis in citrus. [ABSTRACT FROM AUTHOR]

Partial discharge in oil paper insulation is an important reason for insulation breakdown. The study of partial discharge in transformer oil is of great significance for ensuring the reliability of transformers. In this paper, a comprehensive observation platform of partial discharge with needle plate electrode and oil-paper insulation is built, and the original shape image set of partial discharge is collected and established. Through multi-channel convolution processing of the true color image, gray level equivalent distribution of 3D section, segmentation stretching of threshold interval and binary neighborhood search, a general technical method suitable for processing a series of low brightness discharge images with background interference is finally obtained. [ABSTRACT FROM AUTHOR]

Variational Quantum Algorithms (VQAs) have made great success in the Noisy Intermediate-Scale Quantum (NISQ) era due to their relative resilience to noise and high flexibility relative to quantum resources. Quantum Architecture Search (QAS) aims to enhance the performance of VQAs by refining the structure of the adopted Parameterized Quantum Circuit (PQC). QAS is garnering increased attention owing to its automation, reduced reliance on expert experience, and its ability to achieve better performance while requiring fewer quantum gates than manually designed circuits. However, existing QAS algorithms optimize the structure from scratch for each VQA without using any prior experience, rendering the process inefficient and time-consuming. Moreover, determining the number of quantum gates, a crucial hyper-parameter in these algorithms is a challenging and time-consuming task. To mitigate these challenges, we accelerate the QAS algorithm via a meta-trained generator. The proposed algorithm directly generates high-performance circuits for a new VQA by utilizing a meta-trained Variational AutoEncoder (VAE). The number of quantum gates required in the designed circuit is automatically determined based on meta-knowledge learned from a variety of training tasks. Furthermore, we have developed a meta-predictor to filter out circuits with suboptimal performance, thereby accelerating the algorithm. Simulation results on variational quantum compiling and Quantum Approximation Optimization Algorithm (QAOA) demonstrate the superior performance of our method over a state-of-the-art algorithm, namely Differentiable Quantum Architecture Search (DQAS). [ABSTRACT FROM AUTHOR]

A seismic-induced landslide is a common geological catastrophe that occurs in nature. The Wangjiayan landslide, which was triggered by the Wenchuan earthquake, is a typical case in point. The Wanjiayan landslide caused many casualties and resulted in enormous property loss. This study constructs a simple surficial failure model based on the upper bound approach of three-dimensional (3D) limit analysis to evaluate the slope stability of the Wangjiayan case, while a traditional two-dimensional (2D) analysis is also conducted as a reference for comparison with the results of the 3D analysis. A quasi-static calculation is used to study the effect of the earthquake in terms of horizontal ground acceleration, while a parametric study is conducted to evaluate the critical cohesion of slopes. Rather than employing a 3D analysis, using the 2D analysis yields an underestimation regarding the safety factor. In the Wangjiayan landslide, the difference in the factors of safety between the 3D and 2D analyses can reach 20%. The sliding surface morphology as determined by the 3D method is similar to actual morphology, and the parameters of both are also compared to analyze the reliability of the proposed 3D method. [ABSTRACT FROM AUTHOR]

Polycystic ovary syndrome (PCOS) is the leading cause of anovulatory infertility. Inadequate understanding of the ovulation drivers hinders PCOS intervention. Herein, we report that follicle stimulating hormone (FSH) controls follicular fluid (FF) glutamine levels to determine ovulation. Murine ovulation starts from FF-exposing granulosa cell (GC) apoptosis. FF glutamine, which decreases in pre-ovulation porcine FF, elevates in PCOS patients FF. High-glutamine chow to elevate FF glutamine inhibits mouse GC apoptosis and induces hormonal, metabolic, and morphologic PCOS traits. Mechanistically, follicle-development-driving FSH promotes GC glutamine synthesis to elevate FF glutamine, which maintain follicle wall integrity by inhibiting GC apoptosis through inactivating ASK1-JNK apoptotic pathway. FSH and glutamine inhibit the rapture of cultured murine follicles. Glutamine removal or ASK1-JNK pathway activation with metformin or AT-101 reversed PCOS traits in PCOS models that are induced with either glutamine or EsR1 -KO. These suggest that glutamine, FSH, and ASK1-JNK pathway are targetable to alleviate PCOS. [ABSTRACT FROM AUTHOR]

Light-driven cancer theranostics has shown inexhaustible and vigorous vitality by virtue of its high efficacy, prominent controllability and noninvasiveness. Exploration of an all-round theranostic material simultaneously affording both multimodal diagnosis imaging and synergistic phototherapy would be an appealing yet significantly challenging task. Herein, a novel nanomedicine Ir@PPEG-MeEPO was ingeniously constructed by integrating beforehand 1O2-charged amphiphilic polymer and well-tailored Ir(III) complex IrDPTP, which was featured by second near-infrared (NIR-II) aggregation-induced emission (AIE) tendency, efficient reactive oxygen species (ROS) generation, good photothermal conversion efficiency and high-performance hydrogen gas production. To the best of our knowledge, IrDPTP held the longest emission wavelength among all reported AIE Ir (III) complexes. Moreover, Ir@PPEG-MeEPO was capable of controllably releasing ROS via triggered photothermal effect upon NIR irradiation, making it well-adapted to hypoxic environment of tumor. Those distinctive characteristics of Ir@PPEG-MeEPO endowed it with unprecedented performance on sextuple theranostics comprised of NIR-II fluorescence-photoacoustic-photothermal trimodal imaging and photodynamic-photothermal-hydrogen trimodal therapy, witnessed by the precise tumor diagnosis and complete tumor elimination. The study would open up new perspectives for the exploration of superior nanomedicine for practical cancer theranostics. [ABSTRACT FROM AUTHOR]

Background: With the increasing application of guided endodontics to treat complex root canal treatment, the entire process of root canal treatment has become more precise, reducing damage to tooth structure and improving success rates. However, due to the limitations of the operating space, the use of guided endodontic templates in posterior root canal treatment is less common. This study aims to compare the accuracy and reliability of selective laser melting (SLM) and traditional stereolithography etching (SLA) guided endodontic templates for posterior root canals, providing better treatment strategies for posterior root canal treatment. Methods: The teeth were randomly assigned to either SLM or SLA group. Preoperative cone-beam computed tomography (CBCT) and a three-dimensional (3D) scanner were used to establish the 3D root canal system and the accurate occlusal models of the teeth. The virtual access to the canal access was designed using Mimics 19.0 and 3-Matic 11.0. The endodontic access was performed based on either SLM or SLA templates. The accuracy of endodontic preparation was measured in three-dimensions by calculating deviations from planned accesses. The template height and tooth substance loss rates in each group were measured. Results: SLM-guided templates have a low average deviation at the entry point and apical portion of the bur of total posterior teeth (including premolars and molars) and individual molars (P < 0.05). Moreover, there was a significant difference in angular deviations and height of template in total posterior teeth and individual molars (P < 0.05). The mean substance loss rate of the SLA group was slightly greater than that of the SLM group, but the difference was not statistically (P > 0.05). Conclusions: SLM-guided endodontics provides a more predictable and precise location of root canal orifice for the treatment of posterior teeth. [ABSTRACT FROM AUTHOR]

Independent manipulation of transmitted and reflected light fields is a key technology for the realization of multifunctional optical applications, which can be implemented based on multilayered plasmonic or supercell subwavelength structures. However, the former is not suitable for the optical bands, while the latter is insufficient in generating large phase gradients. Here, an adjoint-optimization-based inverse design methodology is proposed, which utilizes the polarization-selective local interference between individual meta-atoms and enables monolayer dielectric metasurfaces to decouple the wavefront of transmitted and reflected optical fields. Moreover, this methodology serves to mitigate the aperiodic electromagnetic crosstalk inherent between adjacent meta-atoms, consequently leading to a significant enhancement in the performance of meta-devices. We analyzed the physical mechanism of adjoint optimization and proposed the concept of phase factors, highlighting their importance in the rapid inverse design of meta-devices-an aspect often overlooked in previous research. To demonstrate the feasibility and robustness of our method, we optimize monolayer metasurfaces with different initial structures. These devices efficiently focus and deflect x-linearly and y-linearly polarized incident light in transmission and reflection spaces, respectively. Overall, this methodology holds immense potential for designing multifunctional, high-performing metasurfaces that meet multiple constraints, opening up broad prospects for applications. [ABSTRACT FROM AUTHOR]

Slope failures in nature and engineering are typically three-dimensional (3D). The rotational failure mechanism derived from the variational limit equilibrium (LE) method shows superior performance in the stability analysis of the 3D slope. In contrast to the traditional LE methods, it avoids arbitrary kinematical and statical assumptions. Stability charts obtained by the variational LE method are used to derive explicit expression equations of the safety factor, also known as the stability equations, for both 3D reinforced and unreinforced slopes. These equations are highly accurate and can provide a convenient means to assess slope stability in practical engineering. An example of a convex reinforced slope with a turning arc is illustrated in this study to investigate the effect of the 3D effects on the required reinforcement length for design. The results indicate that the 2D method underestimates the required reinforcement length when dealing with a 3D reinforced slope problem. Furthermore, a forensic analysis of the Yeager Airport reinforced slope is conducted within the framework of the variational LE method. The required strength for stability is found to be significantly less than the allowable strength of reinforcements without considering the decrease in soil shear strength. However, the required strength greatly exceeds the allowable strength when the decrease in soil shear strength is considered. The results verify that the decrease in shear strength of the weak layer is responsible for the collapse. [ABSTRACT FROM AUTHOR]

Recently, full Poincaré beams (FPBs) with spatially variant polarization states spanning the entire surface of the Poincaré sphere have attracted considerable interests. Expanding the FPBs into an array way has the promising applications from multiparticle manipulation to optical communication. However, how to efficiently generate a high‐purity FPB array with intracavity method remains elusive. Here, a metasurface‐integrated degenerate cavity laser is proposed for efficient generation of 10 × 10 FPB array, where a pair of metasurfaces are adopted to independently modulate the circular polarization state while compensating the mode discrepancies within the cavity. Such a design strategy enables a self‐reproducing intracavity optical field, concurrently ensuring the stabilization of intracavity oscillation. It is numerically demonstrated that the purity of orbital angular momentum (OAM) in the first‐order FPB array can approach to 92.89%, with a root‐mean‐square error (RMSE) of polarization ellipse parameters below 8.17%. This work provides a compact and efficient design platform for the generation of a variety of vector beam arrays and may find promising applications in free space communication and multiple particle manipulation. [ABSTRACT FROM AUTHOR]

Background: In this study we investigated the impact of ABC stroke score on the recurrence of paroxysmal atrial fibrillation (PAF) following radiofrequency catheter ablation (RFCA). Methods: A total of 132 patients with PAF who underwent RFCA from October 2018 to September 2019 were included in this study. During the first phase of this study the patients were categorized into two groups based on late recurrence of atrial fibrillation after RFCA. In the second phase, the patients were further divided into two groups based on whether their ABC stroke score was ≥ 6.5. Result: The univariate analysis indicated that the risk factors for late recurrence of PAF included early recurrence, ABC stroke score, CHA2DS2-VASc score, and NT-proBNP (P < 0.05). Cox multivariate regression analysis revealed that ABC stroke score (P = 0.006) and early recurrence (P = 0.000) were independent predictors of late recurrence, and ABC stroke score ≥ 6.5 was a risk for predicting recurrence of PAF after RFCA with a sensitivity of 66.7% and specificity of 65.7%. After the completion of the 1:1 matching, the univariate Cox analysis indicated that an elevated score of ABC stroke (≥ 6.5) was an independent predictor of late recurrence of PAF (HR = 2.687, 95% CI: 1.036–6.971, P = 0.042). However, using an ABC stroke score cut off at 6.4 predicted the recurrence of atrial tachyarrhythmia with 85% sensitivity and 58.5% specificity. Conclusion: An ABC stroke score ≥ 6.4 is a predictor for late recurrence of PAF after RFCA. [ABSTRACT FROM AUTHOR]

Environmental changes induced by urbanization may significantly alter plant survival strategies, thereby introducing uncertainties in their ability to withstand extreme heat. This study, centered on Jinhua City, distinguished urban, suburban, and rural areas to represent the various intensities of urbanization. It examined the leaf function properties of evergreen and deciduous trees common in these regions, focusing on leaf and branch characteristics. Employing an analysis of variance (ANOVA), principal component analysis (PCA), and path analysis (PA) of the plant functional traits and the climatic factors of each region, this study assessed the impact of urbanization on plant survival strategies. By tracking changes in plant functional traits from June to August, it explored the capacity of plants to acclimate to urban-warming-related heat stress across different urbanization gradients. The findings revealed that leaf thickness (LT) and stomatal size (SS) initially decreased and then increased, whereas specific leaf area (SLA) and leaf tissue density (LTD) first rose and then declined, from rural to urban regions. From June to August, branch wood density (WD), chlorophyll (Chl) content, LTD, and leaf dry matter content (LDMC) increased, whereas SLA and leaf water content (LWC) diminished, in all regions. PCA suggested that there was no significant change in the resource allocation strategy of plants (p > 0.05), with drought tolerance significantly reduced in the suburbs on the gradient of urbanization (p < 0.05). During the summer, with high temperature, plants were predominantly biased towards slow-return, conservative strategies, particularly among evergreen species. Compared to precipitation, PA revealed a significant urban warming effect. During summer, temperature was the main factor influencing resource investment strategy and drought resistance, with a notably stronger impact on the former. The high temperature in summer promoted a conservative survival strategy in plants, and the urbanization effect increased their tolerance to high temperatures. [ABSTRACT FROM AUTHOR]