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A dual-channel thermal emitter, which is composed of an InAs layer atop an aluminum grating backed with a continuous aluminum film, is proposed and studied. Two resonant absorption and emission peaks are achieved at different wavelengths, leading to the achievement of dual-channel strong nonreciprocal radiations at two different wavelengths for an applied magnetic field of 2 T when the angle of incidence is 17°. The physical origin is revealed through illustrating the electromagnetic field distributions at both resonances and also verified through impedance matching. In addition, the perfect nonreciprocity remains stable within a wide range of structure parameters, lowering the cost of manufacture. Moreover, the nonreciprocal radiations for different incident angles and different magnetic fields are also investigated in detail. The concept and conclusions proposed here will be interesting for the development of novel energy conversion and capture devices. [ABSTRACT FROM AUTHOR]

This study employs a hybrid numerical-experimental calibration method based on phenomena to determine the fracture parameters of the Modified Mohr–Coulomb (MMC) model. Using a self-developed VUMAT subroutine and the element deletion technique, the fracture process of a wide plate pipeline is thoroughly analyzed. This study investigates the impact of various crack shapes on the fracture response under tensile loading and the influence of surface crack size on the initiation location of a wide plate. These results demonstrate the calibrated MMC fracture model's accurate prediction of the toughness fracture behavior of X80 pipeline steel. Under equal area conditions of the dangerous section, circular cracks exhibit lower bearing capacity compared to elliptical cracks. Elliptical cracks predominantly propagate in the thickness direction, whereas circular cracks show nearly uniform growth in all directions. Furthermore, when the crack depth is less than half of the wall thickness, the damage accumulation value at the midpoint of the crack front is maximized; conversely, when the crack front is closer to the internal measurement point of the wide plate, the damage accumulation value is maximized. [ABSTRACT FROM AUTHOR]

Rotating machinery is critical functional part of industrial mechanical equipment, and health status of rotating machinery is closely related to equipment stability, reliability and safety. Vibration signals for health prediction are often collected under operating conditions with variable loads and speeds, which makes health prediction more challenging. STFT-based time-frequency representation methods are widely used for the health prediction of rotating machinery. However, these methods lack specific learning mechanisms to effectively distinguish the time-frequency representations at different time points and frequency bands and highlight important feature information. To vanquish the weakness, this paper develops a novel dynamic adaptive time-frequency attention residual network (TFARNet) for rotating machinery intelligent health prediction. Firstly, a new adaptive STFT time-frequency attention (TFA) unit is developed to recalibrate time-frequency features, thereby enhancing important information and suppressing redundant information. Secondly, the TFA unit is inserted into the residual network, by stacking multiple residual blocks and TFA units to establish TFARNet and efficiently learn more discriminative features. Thirdly, label smoothing regularization and dynamic learning rate are employed to accelerate model convergence and optimize the model training process. Finally, three cases are carried out to evaluate the developed method. Compared with the other seven health prediction methods, the developed method can achieve higher prediction accuracy. [ABSTRACT FROM AUTHOR]

Intravitreal injection of biodegradable implant drug carriers shows promise in reducing the injection frequency for neovascular retinal diseases. However, current intravitreal ocular devices have limitations in adjusting drug release rates for individual patients, thereby affecting treatment effectiveness. Accordingly, we developed mesoporous silica nanoparticles (MSNs) featuring a surface that reverse its charge in response to reactive oxygen species (ROS) for efficient delivery of humanin peptide (HN) to retinal epithelial cells (ARPE-19). The MSN core, designed with a pore size of 2.8 nm, ensures a high HN loading capacity 64.4% (w /w). We fine-tuned the external surface of the MSNs by incorporating 20% Acetyl-L-arginine (Ar) to create a partial positive charge, while 80% conjugated thioketal (TK) methoxy polyethylene glycol (mPEG) act as ROS gatekeeper. Ex vivo experiments using bovine eyes revealed the immobilization of Ar-MSNs-TK-PEG (mean zeta potential: 2 mV) in the negatively charged vitreous. However, oxidative stress reversed the surface charge to −25 mV by mPEG loss, facilitating the diffusion of the nanoparticles impeded with HN. In vitro studies showed that ARPE-19 cells effectively internalize HN-loaded Ar-MSNs-TK, subsequently releasing the peptide, which offered protection against oxidative stress-induced apoptosis, as evidenced by reduced TUNEL and caspase3 activation. The inhibition of retinal neovascularization was further validated in an in vivo oxygen-induced retinopathy (OIR) mouse model. The study discusses the development of a novel drug delivery system utilizing charge reversal mesoporous silica nanoparticles (MSNs) for the treatment of neovascular retinal diseases. [Display omitted] • Mesoporous Silica Nanoparticles' surface charge was delicately adjusted for reversal under ROS-response. • Intravitreal injection of Ar-MSNs-TK-PEG was immobilized in the mouse vitreous; however, under oxidative stress, the surface charge reversed, facilitating nanoparticle diffusion. • HN loaded Ar-MSNs-TK-PEG provides protection against oxidative stress-induced apoptosis, evidenced by reduced TUNEL and caspase3 activation. • Intravitreal injection of HN-loaded Ar-MSNs-TK-PEG inhibit retinal neovascularization in a mice model of oxygen-induced retinopathy without inducing toxicity in retinal tissues. [ABSTRACT FROM AUTHOR]

Dual‐polarization programmable metasurfaces can flexibly manipulate electromagnetic (EM) waves while providing approximately twice the information capacity. Therefore, they hold significant applications in next‐generation communication systems. However, there are three challenges associated with the existing dual‐polarization programmable metasurfaces. This article aims to propose a novel design to address them. First, the design overcomes the challenge of element‐ and polarization‐independent controls, enabling more powerful manipulations of EM waves. Second, by using more energy‐efficient tunable components and reducing their number, the design can be nearly passive (maximum power consumption of 27.7 mW), leading to a significant decrease in the cost and power consumption of the system (at least two orders of magnitude lower than the power consumption of conventional programmable metasurfaces). Third, the design can operate in a broad bandwidth, which is attractive for practical engineering applications. Both the element and array of the metasurface are meticulously designed, and their performance has been carefully studied. The experiments demonstrate that 2D wide‐angle beam scanning can be realized. Moreover, secure communication based on directional information modulation can be implemented by exploiting the metasurface and an efficient discrete optimization algorithm, showing its programmable, multiplexing, broadband, green, and secure features. [ABSTRACT FROM AUTHOR]

Beyond 5G networks provide solutions for next-generation communications, especially digital twins networks (DTNs) have gained increasing popularity for bridging physical and digital space. However, current DTNs pose some challenges, especially when applied to scenarios that require efficient and multimodal data processing. Firstly, current DTNs are limited in communication and computational efficiency, since they require to transmit large amounts of raw data collected from physical sensors, as well as to ensure model synchronization through high-frequency computation. Second, current models of DTNs are domain-specific (e.g. E-health), making it difficult to handle DT scenarios with multimodal data processing requirements. Finally, current security schemes for DTNs introduce additional overheads that impair the efficiency. Against the above challenges, we propose a large language model (LLM) empowered DTNs framework, LLM-Twin. First, based on LLM, we propose digital twin semantic networks (DTSNs), which enable more efficient communication and computation. Second, we design a mini-giant model collaboration scheme, which enables efficient deployment of LLM in DTNs and is adapted to handle multimodal data. Then, we designed a native security policy for LLM-twin without compromising efficiency. Numerical experiments and case studies demonstrate the feasibility of LLM-Twin. To our knowledge, this is the first to propose an LLM-based semantic-level DTNs. [ABSTRACT FROM AUTHOR]

Let α , β ∈ [ 0 , 1) = R / Z such that at least one of them is irrational. It is known that the random αβ -orbits of the Bernoulli mixture of rotations of α and β by choosing them with equal probability 1 2 are uniformly distributed modulo 1 with probability one. Chen et al. (2021) [2] showed that the exceptional set in the probability space has full Hausdorff dimension. In this note, we prove that certain sets related to random αβ -orbits which are not dense in R / Z have Hausdorff dimension 1. Our result can be viewed as an improvement of the dimension result obtained by Chen, Wang and Wen. [ABSTRACT FROM AUTHOR]

Digital coding and programmable metasurfaces stand out as promising candidates in future wireless communications due to their low costs and fast‐action reprogrammable capability. However, 2 significant obstacles, namely integration and power consumption, must be addressed before large‐scale engineering application of the programmable metasurface. This work proposes an easy‐integration and energy‐saving meta‐system and demonstrates its application in wireless communications. The meta‐system features a hybrid architecture and consists of a programmable feed array and a metasurface lens. The feed array comprises 3 subarrays, in which active elements are doped with passive elements and interconnected configurations are used to efficiently reduce the number of active elements by one‐third. The meta‐lens acts as a passive phase shifter to enhance the beamforming performance, further reducing the number of active elements. Moreover, the meta‐system can switch between different modes to achieve various functions. In particular, the maximum power consumption of the meta‐system is only 54 mW, which can be considered nearly passive. A wireless communication experiment is presented, where the meta‐system simultaneously serves as the direct digital modulator and the transmitting antenna. Owing to the low cost, high integration, and nearly passive and programmable features, the meta‐system has remarkable potential for future applications in wireless communications. [ABSTRACT FROM AUTHOR]

Background: Breast cancer (BC) is the most prevalent cancer among women worldwide. Although advances have been made in the identification of predictive biomarkers, current options for early diagnosis and prognostic analysis are still suboptimal. Recently, transfer-RNA-derived RNA fragments (tRFs) have emerged as a class of small noncoding RNAs that play a role in the cancer progression. The authors aimed to identify a specific class of tRFs as a molecular marker for BC diagnosis and prognosis in clinical management. Methods: The levels of 5′-tRF-His-GTG were quantified in BC tissue (n = 101) and inflammatory normal breast tissue (n = 22) using in situ hybridization. Clinicopathological parameters were obtained, including age, tumor node metastasis stage, hormone receptor status, histopathological grade, lymphovascular invasion, and recurrence. The correlation between the expression of 5′-tRF-His-GTG and these parameters in different BC subtypes was analyzed. Patient death and cancer progression were regarded as clinical endpoints in the survival analysis. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were also performed to predict the involvement in pivotal biological process. Results: The expression of 5′-tRF-His-GTG was significantly downregulated in BC tissues and was in connection with T stage in human epidermal growth factor 2-positive and basal-like BC, as well as N stage and histopathological grade in luminal BC. Patients with low expression of 5′-tRF-His-GTG had a poor overall survival rate. Statistics of GO and KEGG pathway revealed that cation channel activity, protein catabolic process, response to temperature stimulus, cell cycle, focal adhesion, and glycerophospholipid metabolism were significantly enriched. Conclusions: This study suggests that the assessment of 5′-tRF-His-GTG expression could serve as a novel biomarker for individual diagnosis and prognosis in BC. [ABSTRACT FROM AUTHOR]

A weakly nonlinear theoretical model is established for the two-dimensional incompressible Rayleigh–Taylor–Kelvin–Helmholtz instability (RT–KHI). The evolution of the perturbation interface is analytically studied by the third-order solution of the planar RT–KHI induced by a single-mode surface perturbation. The difference between the weakly nonlinear growth for Rayleigh–Taylor instability (RTI), Kelvin–Helmholtz instability (KHI), and RT–KHI in plane geometry is discussed. The trend of bubble and spike amplitudes with the Atwood number and the Richardson number is discussed in detail. The bubble and spike amplitudes of RT–KHI change from the KHI case to the RTI case as the Richardson number increases. The deflecting distance of bubble and spike vertices becomes smaller compared to the KHI case as the Richardson number increases. The dependence of the nonlinear saturation amplitude of RT–KHI on the Atwood number, the Richardson number, and the initial perturbation is obtained. The Richardson number is as vital to the nonlinear saturation amplitude as the Atwood number. It is found that the variation of the nonlinear saturation amplitude with the Atwood number at different Richardson numbers is divided into three parts, namely, "RTI-like part," "transition part," and "KHI-like part." In the transition part, the trend of the nonlinear saturation amplitude increasing with the Atwood number is completely opposite to the RTI and KHI cases. Finally, the theory is compared to the numerical simulation under identical initial conditions and displays good correspondence in the linear and weakly nonlinear stages. [ABSTRACT FROM AUTHOR]

This study used a combination method of ultrafine grinding and pregelatinization to modify rice starch (RS) to delay its retrogradation and provide a rationale for prolonging rice product shelf life. The structure and physicochemical properties of the pregelatinized ultrafine grinding rice starch (PURS) were compared with those of RS, ultrafine grinding rice starch (URS), and pregelatinized rice starch (PRS). The microstructure, molecular weight, branched starch length distribution, short‐range order, crystal structure, and physical properties of RS, URS, PRS, and PURS were analyzed, respectively. Results showed that RS, URS, PRS, and PURS granules exhibited similar spherical or polygonal shapes, and the content of amylose and short‐branched starch in PURS increased compared with RS, URS, and PRS. Furthermore, the cross‐polarization of PRS and PURS disappeared. Long‐chain amylopectin and average molecular weight of PURS decreased significantly after ultrafine grinding. Our study suggested reduced breakdown value and setback value and improved gel stability, and PURS was beneficial for delaying retrogradation compared to RS, URS, and PRS. The ultrafine grinding method improved the water swelling capacity (WSC), solubility, pasting properties, and gelation properties of PRS. The hardness of PURS was reduced by ultrafine grinding. These suggest that the combination of ultrafine grinding and pregelatinization could improve the properties of RS. Pearson's correlation analysis showed that the structure of PURS significantly influenced the physicochemical properties. The present study was helpful in better understanding the importance of ultrafine grinding in improving the anti‐retrogradation of PURS and provided new insights into extending the shelf life of rice products by ultrafine grinding and pregelatinization. [ABSTRACT FROM AUTHOR]

Large language models (LLMs) are becoming a significant source of content generation in social networks, which is a typical complex adaptive system (CAS). However, due to their hallucinatory nature, LLMs produce false information that can spread through social networks, which will impact the stability of the whole society. The uncertainty of LLMs false information spread within social networks is attributable to the diversity of individual behaviors, intricate interconnectivity, and dynamic network structures. Quantifying the uncertainty of false information spread by LLMs in social networks is beneficial for preemptively devising strategies to defend against threats. To address these challenges, we propose an LLMs hallucination-aware dynamic modeling method via agent-based probability distributions, spread popularity and community affiliation, to quantify the uncertain spreading of LLMs hallucination in social networks. We set up the node attributes and behaviors in the model based on real-world data. For evaluation, we consider the spreaders, informed people, discerning and unwilling non-spreaders as indicators, and quantified the spreading under different LLMs task situations, such as QA, dialogue, and summarization, as well as LLMs versions. Furthermore, we conduct experiments using real-world LLM hallucination data combined with social network features to ensure the validity of the proposed quantifying scheme. [ABSTRACT FROM AUTHOR]

Bubble curtains are linear multiphase plumes that are used in industry and engineering to reduce diffusive flows between two zones. The circulating shear flow generated by the bubble plume can effectively create a particle barrier in the water; thus, it is also widely used to suppress the diffusion of suspended particles during dredging operations. To clarify the interaction mechanism between the bubble curtain and suspended particles under pressure-driven flow, experimental studies and numerical simulations were conducted to investigate the particle dynamics in the flow field around the bubble curtain. In this study, we established a formal analogy between a bubble curtain and an air curtain and qualitatively identified four typical distribution zones of the particles in the flow field. Based on the quantitative measurements and theoretical considerations, the optimal operating conditions and the upper limit of effectiveness of the bubble curtain were determined. In addition, the blocking behavior and efficiency of bubble plumes on particles with different R e U and F r U g numbers and different particle properties were simulated via the computational fluid dynamics discrete element method (CFD DEM) numerical simulation method. [ABSTRACT FROM AUTHOR]

BACKGROUND RESULTS CONCLUSION Giant salamander protein peptide is a peptide with rich functional properties. Giant salamander protein peptide KGEYNK (KK‐6) is a peptide with both antioxidant and anti‐inflammatory properties. The antioxidant and anti‐inflammatory mechanisms of KK‐6 are still unclear. When we studied the functional mechanism of KK‐6, we found that the antioxidant property of KK‐6 has a synergistic and promoting effect on anti‐inflammatory properties.KK‐6 enhances cellular resistance to LPS via the MAPK/NF‐κB signaling pathway, leading to increased levels of inflammatory factors: interleukin‐1β (764.81 ng mL−1), interleukin‐6 (1.06 ng mL−1) and tumor necrosis factor‐α (4440.45 ng mL−1). KK‐6 demonstrates potent antioxidant properties by activating the Nrf2 signaling pathway, resulting in elevated levels of antioxidant enzymes (glutathione peroxidase: 0.03 μg mL−1; superoxide dismutase: 0.589 μg mL−1) and a reduction in the concentration of the oxidative product malondialdehyde (967.05 μg mL−1).Our findings highlight the great potential of KK‐6, a peptide extracted from giant salamander protein, as a remedy for intestinal inflammation. Through its dual role as an antioxidant and anti‐inflammatory agent, KK‐6 offers a promising avenue for alleviating inflammation‐related damage and oxidative stress. This study lays the foundation for further exploration of giant salamander products and highlights their importance in health and novel food development. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Lafora disease (LD) is a syndrome of progressive myoclonic epilepsy and cumulative neurocognitive deterioration caused by recessively inherited genetic lesions of EPM2A (laforin) or NHLRC1 (malin). Neuropsychiatric symptomatology in LD is thought to be directly downstream of neuronal and astrocytic polyglucosan aggregates, termed Lafora bodies (LBs), which faithfully accumulate in an age‐dependent manner in all mouse models of LD. In this study, we applied home‐cage monitoring to examine the extent of neurobehavioral deterioration in a model of malin‐deficient LD as a means to identify robust preclinical endpoints that may guide the selection of novel genetic treatments. At 6 weeks, ∼6–7 months, and ∼12 months of age, malin‐deficient mice ("KO") and wild‐type (WT) littermates underwent a standardized home‐cage behavioral assessment designed to non‐obtrusively appraise features of rest/arousal, consumptive behaviors, risk aversion, and voluntary wheel‐running. At all timepoints, and over a range of metrics that we report transparently, WT and KO mice were essentially indistinguishable. In contrast, within WT mice compared across the same timepoints, we identified age‐related nocturnal hypoactivity, diminished sucrose preference, and reduced wheel‐running. Neuropathological examinations in subsets of the same mice revealed expected age‐dependent LB accumulation, gliosis, and microglial activation in cortical and subcortical brain regions. At 12 months of age, despite the burden of neocortical LBs, we did not identify spontaneous seizures during an electroencephalographic (EEG) survey, and KO and WT mice exhibited similar spectral EEG features. However, in an in vitro assay of neocortical function, paroxysmal bursts of network activity (UP states) in KO slices were more prolonged at 3 and 6 months of age, but similar to WT at 12 months. KO mice displayed a distinct response to pentylenetetrazole, with a greater incidence of clonic seizures and a more pronounced postictal suppression of movement, feeding, and drinking behavior. Together, these results highlight the clinicopathologic dissociation in a mouse model of LD, where the accrual of LBs may latently modify cortical circuit function and seizure threshold without clinically meaningful changes in home‐cage behavior. Our findings allude to a delay between LB accumulation and neurobehavioral decline in LD: one that may provide a window for treatment, and whose precise duration may be difficult to ascertain within the typical lifespan of a laboratory mouse. [ABSTRACT FROM AUTHOR]

The conserved bazooka (baz/par3) gene acts as a key regulator of asymmetrical cell divisions across the animal kingdom. Associated Par3/Baz-Par6-aPKC protein complexes are also well known for their role in the establishment of apical/basal cell polarity in epithelial cells. Here we define a novel, positive function of Baz/Par3 in the Notch pathway. Using Drosophila wing and eye development, we demonstrate that Baz is required for Notch signaling activity and optimal transcriptional activation of Notch target genes. Baz appears to act independently of aPKC in these contexts, as knockdown of aPKC does not cause Notch loss-of-function phenotypes. Using transgenic Notch constructs, our data positions Baz activity downstream of activating Notch cleavage steps and upstream of Su(H)/CSL transcription factor complex activity on Notch target genes. We demonstrate a biochemical interaction between NICD and Baz, suggesting that Baz is required for NICD activity before NICD binds to Su(H). Taken together, our data define a novel role of the polarity protein Baz/Par3, as a positive and direct regulator of Notch signaling through its interaction with NICD. [Display omitted] • PAR3/Bazooka acts generally in Notch-signaling in Drosophila. • PAR3/Bazooka promotes Notch signaling outside the asymmetric division context. • Notch-ICD and PAR3/Bazooka can be associated in the same physical complex. • PAR3/Bazooka acts at the level of the cleaved active Notch-ICD protein fragment. [ABSTRACT FROM AUTHOR]

Controlling the flow of light is fundamental for on-chip optical signal processing. In this paper, we investigate how to realize high contrast, high unidirectional transmission rate, and reconfigurable nonreciprocal light transmission, based on a nonlinear nanocavity asymmetrically side-coupled with a specially designed slow-light waveguide. We analytically and numerically demonstrate that the unusual multiple threshold pump power points for trigging the photon transitions between bistable states, as well as the sensitivity of the dynamic interactions to the relative delay time between the signal light and pump pulse, play crucial roles in this optical diode system. Based on these findings, a high contrast (over 22 dB) and high unidirectional transmission rate (over 70%) optical diode is achieved. More importantly, the conducting direction of the optical diode can be controllably reversed, without the need of changing the signal's wavelength or power as usually done. This approach is promising in the fields of optical information processing and quantum computing. [ABSTRACT FROM AUTHOR]

Developing functional organs from stem cells remains a challenging goal in regenerative medicine. Existing methodologies, such as tissue engineering, bioprinting, and organoids, only offer partial solutions. This perspective focuses on two promising approaches emerging for engineering human organs from stem cells: stem cell-based embryo models and interspecies organogenesis. Both approaches exploit the premise of guiding stem cells to mimic natural development. We begin by summarizing what is known about early human development as a blueprint for recapitulating organogenesis in both embryo models and interspecies chimeras. The latest advances in both fields are discussed before highlighting the technological and knowledge gaps to be addressed before the goal of developing human organs could be achieved using the two approaches. We conclude by discussing challenges facing embryo modeling and interspecies organogenesis and outlining future prospects for advancing both fields toward the generation of human tissues and organs for basic research and translational applications. Developing organs fit for transplantation remains a challenging goal in regenerative medicine. In this perspective, what is known about early human development is summarized as a blueprint for recapitulating organogenesis, and stem cell-based embryo models and interspecies organogenesis are proposed as promising strategies for generating human tissues and organs. [ABSTRACT FROM AUTHOR]

Breast cancer (BC) is the most common invasive cancer in women. M2 macrophage exosomes promote cancer development and play multiple roles in the tumor microenvironment, but the mechanism of action by which M2 macrophage exosomes promote BC remains unclear. Therefore, the purpose of this study was to investigate the mechanism by which M2 macrophage-derived exosomes promote the development of breast cancer. We collected BC tissues and determined the expression of LINC00470, followed by the establishment of M2 macrophages in culture and the isolation and identification of M2 macrophage exosomes. Next, we investigated the effects of M2 macrophage exosomes on BC cell proliferation, invasion, miR-199a-3p promoter methylation, and the expression of LINC00470, myc, DNMT3A, and miR-199a-3p. Finally, LINC00470 expression was inhibited in M2 macrophage exosomes, while miR-199a-3p expression was inhibited in BC cells, and changes in BC cell proliferation, invasion, miR-199a-3p promoter methylation, and the expression of LINC00470, myc, DNMT3A, and miR-199a-3p were analyzed. We demonstrated that LINC00470 was highly expressed in BC tissues, M2-type macrophages were successfully induced in vitro, and Dil-labeled M2 macrophage exosomes could successfully enter MDA-MB-231 and MCF-7 cells. Coculture of M2 macrophage exosomes with MDA-MB-231 and MCF-7 cells significantly enhanced the proliferation and invasion of MDA-MB-231 and MCF-7 cells, upregulated the expression of LINC00470, myc, and DNMT3A and downregulated the expression of miR-199a-3p. Moreover, the inhibition of LINC00470 expression in M2 macrophage exosomes significantly downregulated the expression of LINC00470, myc, and DNMT3A in MDA-MB-231 and MCF-7 cells, upregulated the expression of miR-199a-3p, and hypomethylated the promoter of the miR-199a-3p locus. Moreover, inhibition of LINC00470 expression in M2 macrophage-derived exosomes significantly attenuated the proliferation and invasive ability of MDA-MB-231 and MCF-7 cells, while miR-199a-3p inhibitor transfection reversed this effect. Collectively, these findings indicated that M2-type macrophage-derived exosomes promote BC proliferation and migration by regulating miR-199a-3p promoter methylation through the LINC00470-mediated myc/DNMT3a axis. [ABSTRACT FROM AUTHOR]

To tackle the issue of lack of semantic consistency between ground and non-ground points, as well as the damage to the integrity of terrain boundary information during network downsampling, we developed a Semantic Consistency-Convolutional Neural Network (SC-CNN) to improve the precision of point cloud filtering under complex terrain conditions. The novel aspects include: (1) farthest point sampling (FPS) with slope constraints, which enhances terrain contour preservation through adaptive subblock partitioning and slope-based sampling; (2) intra-class feature enhancement via copula correlation and attention mechanisms, improving the network's ability to distinguish between ground and non-ground points by focusing on intra-class feature consistency and inter-class differences; and (3) filter error correction using copula correlation and confidence intervals. refining filtering accuracy by adjusting for negatively correlated point sets. Tested on the ISPRS and 3D Vaihingen datasets, SC-CNN notably outperformed existing methods, reducing the mean total error (MT.E) by 0.17% and 1.93%, respectively, thereby significantly enhancing point-cloud filtering accuracy under complex terrain conditions. [ABSTRACT FROM AUTHOR]

Background Purpose Methods Results Conclusion The International Association for the Study of Lung Cancer (IASLC) Pathology Committee introduced a histologic grading system for invasive lung adenocarcinoma (LUAD) in 2020. The IASLC grading system, hinging on the evaluation of predominant and high‐grade histologic patterns, has proven to be practical and prognostic for invasive LUAD. However, there are still limitations in evaluating the prognosis of stage IA LUAD. Radiomics may serve as a valuable complement.To establish a model that integrates IASLC grading and radiomics, aimed at predicting the prognosis of stage IA LUAD.We conducted a retrospective analysis of 628 patients diagnosed with stage IA LUAD who underwent surgical resection between January 2015 and December 2018 at our institution. The patients were randomly divided into the training set (n = 439) and testing set (n = 189) at a ratio of 7:3. Overall survival (OS) and disease‐free survival (DFS) were taken as the end points. Radiomics features were obtained by PyRadiomics. Feature selection was performed using the least absolute shrinkage and selection operator (LASSO). The prediction models for OS and DFS were developed using multivariate Cox regression analysis, and the models were visualized through nomogram plots. The model's performance was evaluated using area under the curves (AUC), concordance index (C‐index), calibration curves, and survival decision curve analysis (DCA).In total, nine radiomics features were selected for the OS prediction model, and 15 radiomics features were selected for the DFS prediction model. Patients with high radiomics scores were associated with a worse prognosis (p < 0.001). We built separate prediction models using radiomics or IASLC alone, as well as a combined prediction model. In the prediction of OS, we observed that the combined model (C‐index: 0.812 ± 0.024, 3 years AUC: 0.692, 5 years AUC: 0.792) achieved superior predictive performance than the radiomics (C‐index: 0.743 ± 0.038, 3 years AUC: 0.633, 5 years AUC: 0.768) and IASLC grading (C‐index: 0.765 ± 0.042, 3 years AUC: 0.658, 5 years AUC: 0.743) models alone. Similar results were obtained in the models for DFS.The combination of radiomics and IASLC pathological grading proves to be an effective approach for predicting the prognosis of stage IA LUAD. This has substantial clinical relevance in guiding treatment decisions for early‐stage LUAD. [ABSTRACT FROM AUTHOR]

In light of the escalating demand for computing powers, wave‐based analog computers have emerged as a compelling study area due to their remarkable capacity for ultra‐fast operation. Here, a programmable wave‐based computer, based on programmable meta‐structures is proposed, which is also called as meta‐computer. The meta‐computer can perform various types of analog computations in real‐time in the electromagnetic (EM) wave space, including matrix‐vector multiplication, discrete Fourier transform, filtering, and solving complex matrix equations. Owing to the powerful capability of the programmable meta‐structures in manipulating the EM fields and waves in real‐time, the proposed meta‐computer exhibits the advantages of flexible re‐programmability, low complexity, and direct computation in the EM space. Two prototypes of the meta‐computer in the microwave frequency are designed and fabricated, and the computing capability is validated through both numerical simulations and experiments. This work contributes a prominent approach for fully programmable wave‐based computers with noteworthy implications for expanding the applications of analog computing. [ABSTRACT FROM AUTHOR]

Inflammasomes are a central component of innate immunity and play a vital role in regulating innate immune response. Activation of inflammasomes is also indispensable for adaptive immunity, modulating the development and response of adaptive immunity. Recently, increasing studies have shown that metabolic alterations and adaptations strongly influence and regulate the differentiation and function of the immune system. In this review, we will take a holistic view of how inflammasomes bridge innate and adaptive (especially T cell) immunity and how inflammasomes crosstalk with metabolic signals during the immune responses. And, special attention will be paid to the metabolic control of inflammasome-mediated interactions between innate and adaptive immunity in disease. Understanding the metabolic regulatory functions of inflammasomes would provide new insights into future research directions in this area and may help to identify potential targets for inflammasome-associated diseases and broaden therapeutic avenues. [Display omitted] Inflammasomes are central components of innate immunity. Recently, metabolic interactions between inflammasomes and the immune system have been suggested. This review by Wu et al. provides a holistic discussion of the link between inflammasomes, innate and adaptive immunity, and how this is influenced by metabolic signals in health and disease. [ABSTRACT FROM AUTHOR]

A novel Cr-doped BaTiO3 aerogel was successfully synthesized using a co-gelation technique that involves two metallic alkoxides and a supercritical drying method. This freshly prepared aerogel has a high specific surface area of over 100 m2/g and exhibits improved responsiveness to the simulated sunlight spectrum. Methyl orange (MO) was chosen as the simulated pollutant, and the results reveal that the Cr-doped BaTiO3 aerogel, when modified with the noble metal silver (Ag), achieves a pollutant removal rate approximately 3.2 times higher than that of the commercially available P25, reaching up to 92% within 60 min. The excellent photocatalytic performance of the Ag-modified Cr-doped BaTiO3 aerogel can be primarily attributed to its extensive specific surface area and three-dimensional porous architecture. Furthermore, the incorporation of Ag nanoparticles effectively suppresses the recombination of photo-generated electrons and holes. Stability and reusability tests have confirmed the reliability of the Ag-modified Cr-doped BaTiO3 aerogel. Therefore, this material emerges as a highly promising candidate for the treatment of textile wastewater. [ABSTRACT FROM AUTHOR]

Background: Sesterterpenoids are rare species among the terpenoids family. Ophiobolins are sesterterpenes with a 5-8-5 tricyclic skeleton. The oxidized ophiobolins exhibit significant cytotoxic activity and potential medicinal value. There is an urgent need for large amounts of ophiobolins supplication for drug development. The synthetic biology approach has been successfully employed in lots of terpene compound production and inspired us to develop a cell factory for ophiobolin biosynthesis. Results: We developed a systematic metabolic engineering strategy to construct an ophiobolin biosynthesis chassis based on Saccharomyces cerevisiae. The whole-cell biotransformation methods were further combined with metabolic engineering to enhance the expression of key ophiobolin biosynthetic genes and improve the supply of precursors and cofactors. A high yield of 5.1 g/L of ophiobolin F was reached using ethanol and fatty acids as substrates. To accumulate oxidized ophiobolins, we optimized the sources and expression conditions for P450-CPR and alleviated the toxicity of bioactive compounds to cells through PDR engineering. We unexpectedly obtained a novel ophiobolin intermediate with potent cytotoxicity, 5-hydroxy-21-formyl-ophiobolin F, and the known bioactive compound ophiobolin U. Finally, we achieved the ophiobolin U titer of 128.9 mg/L. Conclusions: We established efficient cell factories based on S. cerevisiae, enabling de novo biosynthesis of the ophiobolin skeleton ophiobolin F and oxidized ophiobolins derivatives. This work has filled the gap in the heterologous biosynthesis of sesterterpenoids in S. cerevisiae and provided valuable solutions for new drug development based on sesterterpenoids. [ABSTRACT FROM AUTHOR]

Enhancing soil stability through the incorporation of straw and biochar is well documented. Nevertheless, the combined impact of straw, biochar, and nitrogen supplementation on soil aggregates and organic carbon still needs to be explored, with limited attention given to various sieving methods in the existing literature. Therefore, the current experiment used four sieving methods—routine wet sieving (RoutW), fast-wetting sieving (FastW), slow-wetting sieving (SlowW), and wetting–stirring sieving (WetS)—to investigate the effects of adding straw (0 or 4.5 t ha−1), biochar (from maize straw, 0 or 15 t ha−1), and N (0 or 100 kg ha−1) on soil aggregate stability and soil organic C in silt–loam soil of rainfed farmland in northwest China. The field experiment was started in 2014; soil samples were collected in 2021. The results revealed that straw returned, biochar, and N addition significantly increased soil mean weight diameter (MWD) and soil organic C (SOC). Compared to CN0 (zero-amendment) plots, straw returned with nitrogen addition (SN100) significantly increased the MWD of aggregates by 130.3% (RoutW), 121.66% (FastW), 73.94% (SlowW), and 91.78% (WetS) in the 0–30 cm soil layer. The addition of biochar and nitrogen (BN100) treatment showed the most significant effects on the relative slaking index (RSI), relative mechanical breakdown index (RMI), and SOC; compared with CN0 treatment, BN100 plots can reduce RSI and RMI by 42.90% and 54.66% and increase SOC by 53.27% for all soil layers. Therefore, adding organic materials with N can enhance the stability of soil aggregates and SOC of silt–loam soils in northwest China. Integrating biochar as an organic soil amendment in the agricultural practices of northwest China presents a multifaceted solution that addresses soil health, crop productivity, and environmental sustainability. The current study provides valuable insights that support adopting this innovative approach, paving the way for future sustainable agricultural practices that can benefit both the region and the global community. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for natural stitching multiple images by integrating thin-plate spline (TPS), cylindrical projection, and plumb-line constraint. Firstly, the homography estimated under plumb-line constraint is used to transform each image to keep the scene in the image upward as much as possible, so as to suppress the accumulation of image projection deformation and make the transformed images approximately available for cylindrical projection. Then, by introducing cylindrical projection into TPS as a global transformation, a multiple image alignment framework called cylindrical projection thin-plate spline (CP-TPS) is established to accurately align the transformed images. In this step, the virtual control points (VCP) are set in the non-overlapping area of images so that the CP-TPS can produce desired deformation in the final stitched image. Finally, a seam-line intersecting the significant structure in the aligned image is automatically generated by combining TPS, dynamic programming matching, and control points triangulation. In this step, the seam-line itself is used to estimate CP-TPS parameter. Experiments were conducted on four public image sets. The results show that the proposed approach can realize the natural stitching of public multiple image sets and has the best performance, compared with Autostitch, APAP, NISwGSP, ELA, and GES-GSP. [ABSTRACT FROM AUTHOR]

Support Vector Machines (SVMs) have achieved significant success in the field of power transformer fault diagnosis. However, challenges such as determining SVM hyperparameters and their suitability for binary classification still exist. This paper proposes a novel method for power transformer fault diagnosis, called ECOC-WSO-SVM, which utilizes a White Shark Optimizer (WSO) and error correcting output codes to optimize SVMs. First, t-distributed Stochastic Neighbor Embedding (t-SNE) is employed to reduce the dimensionality of Dissolved Gas Analysis (DGA) features constructed using the correlation ratio method, from 26 dimensions. In addition, to effectively solve the hyperparameters of SVMs, a multi-strategy fusion method is proposed to improve the WSO, incorporating tent chaos initialization, elite opposite learning, and selection strategies, forming TEWSO, and its superior optimization performance is validated using IEEE CEC2021 test functions. Furthermore, to address the limitations of SVMs as a binary classifier, an error correcting output code fusion SVM is introduced, thus constructing a multi-class SVM model. Finally, the diagnostic performance of the ECOC-TEWSO-SVM model is validated using real-world data. Results demonstrate that the proposed model exhibits the best diagnostic performance compared to traditional models and those in the literature, thereby proving the significance and effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

The metric theory of limsup sets is the main topic in metric Diophantine approximation. A very simple observation by Erdös shows the dimension of the Cartesian product of two sets of Liouville numbers is 1. To disclose the mystery hidden there, we consider and present a general principle for the Hausdorff dimension of the Cartesian product of limsup sets. As an application of our general principle, it is found that \begin{equation*} \dim _{\mathcal H}W(\psi)\times \cdots \times W(\psi)=d-1+\dim _{\mathcal H}W(\psi) \end{equation*} where W(\psi) is the set of \psi-well approximable points in \mathbb {R} and \psi : \mathbb {N}\to \mathbb {R}^+ is a positive non-increasing function. Even this concrete case was never observed before. Our result can also be compared with Marstrand's famous inequality on the dimension of the Cartesian product of general sets. [ABSTRACT FROM AUTHOR]

The distributed robust optimal allocation method for multi-microgrid interconnected systems usually involves a large number of variables and constraints, and the computational complexity is high in practical applications, which makes it difficult to solve the problem. Therefore, a distributed robust optimal allocation method for multi-microgrid interconnection systems based on multi-objective swarm algorithm is proposed. A distributed robust optimization configuration constraint index model for multi-microgrid interconnection system is established. Considering the influence of energy storage technology operation characteristics on its service life, a micro-grid hybrid energy storage capacity optimization configuration model with the minimum annual comprehensive energy storage cost as the objective function is established with charge and discharge power and residual power as the constraint conditions. The multi-objective swarm algorithm is used to realize the optimization model of distributed robust configuration microgrid interconnection system. By determining the power capacity configuration of the optimal energy storage system and the corresponding frequency dividing points, the power capacity configuration of the optimal energy storage system and the corresponding frequency dividing points are determined. The hybrid energy storage configuration model of multi-microgrid interconnection system is established with the minimum alternative operating cost as the objective function, so as to realize the distributed robust optimal configuration of multi-microgrid interconnection system. The simulation results show that the distributed configuration of multi-microgrid interconnection system with the proposed method has good robustness and strong optimization control ability. [ABSTRACT FROM AUTHOR]

For the actual collected point cloud data, there are widespread challenges such as semantic inconsistency, density variations, and sparse spatial distribution. A network called PointMM is developed in this study to enhance the accuracy of point cloud semantic segmentation in complex scenes. The main contribution of PointMM involves two aspects: (1) Multi-spatial feature encoding. We leverage a novel feature encoding module to learn multi-spatial features from the neighborhood point set obtained by k-nearest neighbors (KNN) in the feature space. This enhances the network's ability to learn the spatial structures of various samples more finely and completely. (2) Multi-head attention pooling. We leverage a multi-head attention pooling module to address the limitations of symmetric function-based pooling, such as maximum and average pooling, in terms of losing detailed feature information. This is achieved by aggregating multi-spatial and attribute features of point clouds, thereby enhancing the network's ability to transmit information more comprehensively and accurately. Experiments on publicly available point cloud datasets S3DIS and ISPRS 3D Vaihingen demonstrate that PointMM effectively learns features at different levels, while improving the semantic segmentation accuracy of various objects. Compared to 12 state-of-the-art methods reported in the literature, PointMM outperforms the runner-up by 2.3% in OA on the ISPRS 3D Vaihingen dataset, and achieves the third best performance in both OA and MioU on the S3DIS dataset. Both achieve a satisfactory balance between OA, F1, and MioU. [ABSTRACT FROM AUTHOR]

In this paper, the amino acid chiral ionic liquid (AACIL) was prepared with L‐phenylalanine and imidazole. It was characterized by CD, FT‐IR, 1H NMR, and 13C NMR spectrum. The chiral recognition sensor was constructed with AACIL and Cu(II), which exhibited different chiral visual responses (solubility or color difference) to the enantiomers of glutamine (Gln) and phenylalanine (Phe). The effects of solvent, pH, time, temperature, metal ions, and other amino acids on visual chiral recognition were optimized. The minimum concentrations of Gln and Phe for visual chiral recognition were 0.20 mg/ml and 0.28 mg/ml, respectively. The mechanism of chiral recognition was investigated by FT‐IR, TEM, SEM, TG, XPS, and CD. The location of the host‐guest inclusion or molecular placement has been conformationally searched based on Gaussian 09 software. [ABSTRACT FROM AUTHOR]

This paper establishes a linear relationship between the order of the Riemann–Liouville fractional calculus and the exponent of the Hölder condition, whether the Hölder condition is global, local, or at a single point. We propose and prove a control inequality between the Hölder derivative ( H f (x , α) as defined in Proposition 12) of a continuous function and the Hölder derivative of the Riemann–Liouville fractional calculus of this function. In addition, this paper provides a more accurate estimation of the Box dimension of the graph of the Riemann–Liouville fractional integral of an arbitrary continuous function. More specifically, it establishes the result that whenever there is a continuous function whose graph has the upper Box dimension s with 1 < s ≤ 2 , the graph of its Riemann–Liouville fractional integral of order ν , with 0 < ν < 1 , has the upper Box dimension not greater than s − (s − 1) ν. [ABSTRACT FROM AUTHOR]

Spin polarization is a very important condition for spintronics applications which can easily be achieved by using ferromagnetic materials. Graphene‐based magnetic materials, which have long spin lifetime and diffusion length, are very promising as spin channel materials. In this work, Ferrocene molecules are chosen as the precursor carbon source using the chemical vapor deposition method, facilitating the synthesis of multilayer graphene films decorated with magnetic nanoclusters. This resultant material manifested planar ferromagnetism with a Curie temperature exceeding room temperature (≥300 K) and a saturation magnetization as high as 4.1 × 10−7 emu mm−2. The robust ferromagnetic coupling can plausibly be attributed to the presence of magnetic nanoclusters interspersed within the synthesized graphene, enhancing the localized magnetic moment and promoting ferromagnetic long‐range ordering. Furthermore, the Fermi level pinning at the Dirac point is observed and predominantly ascribed to the pervasive defects in the graphene derived from ferrocene. The oxygen functional groups within these defects act as charge traps, effectively anchoring the Fermi level to the Dirac point, intrinsically suppressing the ambipolar behavior of graphene. This work sheds light on potential avenues for the exploration of novel, high‐performance carbonaceous spintronics materials with economic feasibility. [ABSTRACT FROM AUTHOR]

Achieving circularly polarized organic ultralong room‐temperature phosphorescence (CP‐OURTP) with a high luminescent dissymmetry factor (glum) is crucial for diverse optoelectronic applications. In particular, dynamically controlling the dissymmetry factor of CP‐OURTP can profoundly advance these applications, but it is still unprecedented. This study introduces an effective strategy to achieve photoirradiation‐driven chirality regulation in a bilayered structure film, which consists of a layer of soft helical superstructure incorporated with a light‐driven molecular motor and a layer of room‐temperature phosphorescent (RTP) polymer. The prepared bilayered film exhibits CP‐OURTP with an emission lifetime of 805 ms and a glum value up to 1.38. Remarkably, the glum value of the resulting CP‐OURTP film can be reversibly controlled between 0.6 and 1.38 over 20 cycles by light irradiation, representing the first example of dynamically controlling the glum in CP‐OURTP. [ABSTRACT FROM AUTHOR]

Achieving circularly polarized organic ultralong room‐temperature phosphorescence (CP‐OURTP) with a high luminescent dissymmetry factor (glum) is crucial for diverse optoelectronic applications. In particular, dynamically controlling the dissymmetry factor of CP‐OURTP can profoundly advance these applications, but it is still unprecedented. This study introduces an effective strategy to achieve photoirradiation‐driven chirality regulation in a bilayered structure film, which consists of a layer of soft helical superstructure incorporated with a light‐driven molecular motor and a layer of room‐temperature phosphorescent (RTP) polymer. The prepared bilayered film exhibits CP‐OURTP with an emission lifetime of 805 ms and a glum value up to 1.38. Remarkably, the glum value of the resulting CP‐OURTP film can be reversibly controlled between 0.6 and 1.38 over 20 cycles by light irradiation, representing the first example of dynamically controlling the glum in CP‐OURTP. [ABSTRACT FROM AUTHOR]

With the increasing demands for computing powers, wave‐based computation has attracted researcher's attention due to its inherent high speed. Metasurfaces have flexible and powerful capabilities to manipulate electromagnetic waves and are good candidates for building a next‐generation of wave‐based computers. In this work, a computational‐metasurface‐based equation solver that yields real‐time solutions to arbitrary complex matrix equations (CME) in the form of K · x + c = 0 is proposed. Full‐wave simulations and experimental measurements are conducted to verify the functionality of the proposed solver. This work serves to provide a promising technique to overcome some shortcomings of the existing designs and lays the first stone of the bridge toward programmable wave‐space computers. [ABSTRACT FROM AUTHOR]

A digital coding metasurface is a platform connecting the digital space and electromagnetic wave space, and has therefore gained much attention due to its intriguing value in reshaping wireless channels and realizing new communication architectures. Correspondingly, there is an urgent need for electromagnetic information theory that reveals the upper limit of communication capacity and supports the accurate design of metasurface-based communication systems. To this end, we propose a macroscopic model and a statistical model of the digital coding metasurface. The macroscopic model uniformly accommodates both digital and electromagnetic aspects of the meta-atoms and predicts all possible scattered fields of the digital coding metasurface based on a small number of simulations or measurements. Full-wave simulations and experimental results show that the macroscopic model is feasible and accurate. A statistical model is further proposed to correlate the mutual coupling between meta-atoms with covariance and to calculate the entropy of the equivalent currents of digital coding metasurface. These two models can help reconfigurable intelligent surfaces achieve more accurate beamforming and channel estimation, and thus improve signal power and coverage. Moreover, the models will encourage the creation of a precoding codebook in metasurface-based direct digital modulation systems, with the aim of approaching the upper limit of channel capacity. With these two models, the concepts of current space and current entropy, as well as the analysis of information loss from the coding space to wave space, is established for the first time, helping to bridge the gap between the digital world and the physical world, and advancing developments of electromagnetic information theory and new-architecture wireless systems. [ABSTRACT FROM AUTHOR]

This paper presents a novel method for real‐time generation of seamless spherical panoramic videos from an omnidirectional multi‐camera system (OMS). Firstly, a multi‐view video alignment model called spherical projection constrained thin‐plate spline (SP‐TPS) was established and estimated using an approximately symmetrical seam‐line, maintaining the structure inconsistency around the seam‐line. Then, a look‐up table was designed to support real‐time processing of video re‐projection, video dodging and seam‐line updates. In the table, the overlapping areas in OMS multi‐view videos, the seam‐lines between spherical panoramas and OMS multi‐view videos and the pixel coordinate mapping relationship between spherical panoramas and OMS multi‐view videos were pre‐stored as a whole. Finally, a spherical panoramic video was outputted in real‐time through look‐up table computation under an ordinary GPU processor. The experiments were conducted on multi‐view video taken by "1 + 4" and "1 + 7" OMS, respectively. Experimental results demonstrate that compared with four state‐of‐the‐art methods reported in the literature and two bits of commercial software for video stitching, the proposed method excels in eliminating visual artefacts and demonstrates superior adaptability to scenes with varying depths of field. Assuming that OMS is not movable in the scene, this method can generate seamless spherical panoramic videos with a resolution of 8 K in real time, which is of great value to the surveillance field. [ABSTRACT FROM AUTHOR]

Measurement of the combustion temperature field is an extremely important issue in industrial production. Temperature is one of the key parameters in combustion studies. With the temperature field distribution of the combustion field obtained, heat transfer, heat convection, and heat radiation can be calculated directly and efficiently. Traditional background oriented Schlieren (BOS) is an effective method for non-axisymmetric temperature field measurements, but it requires simultaneous Schlieren imaging at multiple angles for tomographic reconstruction, which will greatly limit its application. In this paper, the compressive sensing algorithm is introduced into the temperature field reconstruction, which establishes the system of equations between the deflection angle and the refractive index gradient. Then, the reconstruction of the non-axisymmetric temperature field is realized by solving the underdetermined system of equations by the method of solving the sparse solution through the compressive sensing. First, light offsets across the non-axisymmetric temperature field are measured by the under-angled BOS system and image processing method. Second, the spatial refractive index field is reconstructed by the compressive sensing BOS method proposed in this paper. Finally, the spatial temperature field is obtained. The experimental results show that by comparing the iRadon reconstruction algorithm and the compressive sensing reconstruction algorithm, the temperature field reconstructed by the compressive sensing under the condition of the under-angled sampling of projection data had a higher accuracy than that reconstructed by the tomographic reconstruction algorithm under the same condition. The average error of the temperature field was reduced from 34.6 to 29.7 K under the same measurement conditions; however, the accuracy is better maintained by using the compressive sensing algorithm under the condition of undersampling projection. [ABSTRACT FROM AUTHOR]

Myocardial infarction is defined as a sudden decrease or interruption in blood flow to the coronary arteries, causing ischemic necrosis of the corresponding cardiomyocytes. It is unclear whether systemic macrovascular alterations are associated with retinal microvascular changes. This study utilized optical coherence tomography angiography (OCTA) to compare variations in conjunctival vascular density and fundus retinal vessel density between patients with myocardial infarction (MI) and healthy controls. This study recruited 16 patients (32 eyes) with MI and 16 healthy controls (32 eyes). The superficial retinal layer (SRL), deep retinal layer (DRL) and conjunctival capillary plexus in each eye were evaluated by OCTA. Parameters measured included the density of the temporal conjunctival capillary, retinal microvascular (MIR) and macrovascular (MAR) alterations and total MIR (TMI). The microvascular density of each retinal region was evaluated by the hemisphere segmentation (SR, SL, IL, and IR), annular partition (C1, C2, C3, C4, C5 and C6), and modified early treatment of diabetic retinopathy study (R, S, L, and I) methods. In the macular area, the superficial and deep retinal microvascular densities displayed notable variations. In the superficial layers, the superficial TMI, superficial MIR, and superficial MAR, as well as densities in the SL, IL, S, L, C1, C2, C5 and C6 regions, were significantly lower in MI patients (p < 0.05 each). In the deep layers, the deep MIR and deep TMI), as well as densities in the SL, IL, L, C1, C2 and C6 regions were significantly lower in MI patients (p < 0.05 each). In contrast, the conjunctival microvascular density was significantly higher in MI patients than in healthy controls (p < 0.001). The microvascular densities measured in the deep and superficial retinal layers and in the conjunctiva differ in MI patients and healthy controls. OCTA is effective in detecting changes in the ocular microcirculation. [ABSTRACT FROM AUTHOR]

Sodium-ion batteries (SIBs) present a prospective solution for energy storage, benefitting from their cost-effectiveness and the abundant availability of sodium reserves on Earth. The effective design of electrode materials with superior cyclability and exceptional rate capability are essential for their widespread application. In this paper, a heterostructure between binary nickel sulfide (NiS 2) and vanadium trioxide (V 2 O 3) was initially synthesized by a feasible hydrothermal and subsequent high-temperature calcination technique, which consisted of coin-like V 2 O 3 tiny sheets adhering to the surface of NiS 2 microsphere. After coating a layer of sericin-derived carbon (SC) films onto surface of NiS 2 /V 2 O 3 , as-synthesized NiS 2 /V 2 O 3 @SC composite anodes for SIBs exhibited impressive electrochemical Na+ storage performances involving an initial discharge capacity of 671.2 mAh g−1 at 1 A g−1, a capacity decay of only 0.043 and 0.066 % per cycle within 1000 cycles at 1 A g−1 and 8 A g−1, and the rate capability of 32 A g−1 with a capacity output of 406.4 mAh g−1. The NiS 2 /V 2 O 3 heterostructure with a hierarchical structure will beneficially alleviate agglomeration and volumetric expansion of active materials, improve electrical conductivity, and more importantly, enhance electrochemical kinetic transport of Na+, which makes it a potential anode application for SIBs. [ABSTRACT FROM AUTHOR]

Aerial recovery and redeployment can effectively increase the operating radius and the endurance of unmanned aerial vehicles (UAVs). However, the challenge lies in the effect of the aerodynamic force on the recovery system, and the existing road-based and sea-based UAV recovery methods are no longer applicable. Inspired by the predatory behavior of net-casting spiders, this study introduces a cable-driven parallel robot (CDPR) for UAV aerial recovery, which utilizes an end-effector camera to detect the UAV's flight trajectory, and the CDPR dynamically adjusts its spatial position to intercept and recover the UAV. This paper establishes a comprehensive cable model, simultaneously considering the elasticity, mass, and aerodynamic force, and the static equilibrium equation for the CDPR is derived. The effects of the aerodynamic force and cable tension on the spatial configuration of the cable are analyzed. Numerical computations yield the CDPR's end-effector position error and cable-driven power consumption at discrete spatial points, and the results show that the position error decreases but the power consumption increases with the increase in the cable tension lower limit (CTLL). To improve the comprehensive performance of the recovery system, a multi-objective optimization method is proposed, considering the error distribution, power consumption distribution, and safety distance. The optimized CTLL and interception space position coordinates are determined through simulation, and comparative analysis with the initial condition indicates an 83% reduction in error, a 62.3% decrease in power consumption, and a 1.2 m increase in safety distance. This paper proposes a new design for a UAV aerial recovery system, and the analysis lays the groundwork for future research. [ABSTRACT FROM AUTHOR]

A Metal-Organic Framework (MOF) based on a tricarboxylic acid ligand (H3L = biphenyl-2,4′,5-tricarboxylic acid), namely [Cd3(L)2(H2O)4] (1), had been prepared and characterized by elemental analysis, IR spectroscopy, powder X-ray diffraction (PXRD), thermogravimetric analyses (TGA), and single-crystal X-ray diffraction. Fluorescence studies showed that 1 has high quenching efficiency for testing acetone and Fe3+ ions in aqueous systems. Therefore, it can be used as a new type of fluorescence probe to detect solvent molecules and metal ions in water. [ABSTRACT FROM AUTHOR]

The rapid development of wireless communication technology has led to an increasing number of internet of thing (IoT) devices, and the demand for spectrum for these devices and their related applications is also increasing. However, spectrum scarcity has become an increasingly serious problem. Therefore, we introduce a collaborative spectrum sensing (CSS) framework in this paper to identify available spectrum resources so that IoT devices can access them and, meanwhile, avoid causing harmful interference to the normal communication of the primary user (PU). However, in the process of sensing the PUs signal in IoT devices, the issue of sensing time and decision cost (the cost of determining whether the signal state of the PU is correct or incorrect) arises. To this end, we propose a distributed cognitive IoT model, which includes two IoT devices independently using sequential decision rules to detect the PU. On this basis, we define the sensing time and cost functions for IoT devices and formulate an average cost optimization problem in CSS. To solve this problem, we further regard the optimal sensing time problem as a finite horizon problem and solve the threshold of the optimal decision rule by person-by-person optimization (PBPO) methodology and dynamic programming. At last, numerical simulation results demonstrate the correctness of our proposal in terms of the global false alarm and miss detection probability, and it always achieves minimal average cost under various costs of each observation taken and thresholds. [ABSTRACT FROM AUTHOR]

The pandemics induced by emerging SARS‐CoV‐2 variants and monkeypox virus infection have triggered the urgent need for broad‐spectrum vaccines. Except for "super" antigen designs, pattern recognition receptor (PRR) agonist‐based adjuvants might blaze a new trail, through enhancing the immune response of conserved antigen epitopes shared among variants for cross‐protection. Ideal adjuvants with proper adjustments could be conveniently applied to different antigens and antigen types in response to new pandemics. However, general strategies for modulating PRR agonist‐based adjuvant properties to tailor the optimal immunity remain to be further explored. Here, an adjuvant platform STINGsome is described, composed of a STING agonist and pH‐switchable IP9 liposomes, to simulate viral infection via STING activation and necroptosis. STINGsomes function as an efficient adjuvant to elicit broad and potent immune responses against multiple SARS‐CoV‐2 VOCs (Omicron BA.1, BA.2, BA.3, BA.4/5) and a monkeypox virus. More importantly, the adjuvant properties of STINGsomes can be tuned by simply adjusting the IP9 percentage, owing to distinct kinetics from local release to lymph node stimulation. Thus, this study provides a relatively simple strategy to adapt an adjuvant platform to different pathogenic antigens, ultimately achieving optimal protective responses. [ABSTRACT FROM AUTHOR]

Object detection technology is a popular research direction which is widely used in areas such as autonomous driving and medical diagnosis. At this stage mobile devices often have limited storage resources to deploy large object detection networks and need to meet real-time requirements. This paper proposes a lightweight and efficient object detection model based on YOLOv4, first using the lightweight network GhostNet to extract image features and reduce the number of parameters and computation of the backbone structure; then combining AFmodule and Meta-ACON activation function to enhance the feature extraction capability of the backbone network, which strengthen the mode's ability to capture image spatial feature information; this paper also designs the RL-PAFPN feature fusion structure is with the Reslayer module to further improve the model's ability to extract and fuse image features. By comparing other mainstream object detection models, the YOLOv4-Ghost-AMR network in this paper has less computation and fewer parameters, and the accuracy of the model reaches 86.83%, which is suitable for deployment in mobile devices with limited storage. The model proposed in this paper can be applied to medical, traffic and fault detection fields, which changes the traditional manual detection method and saves manpower and time costs, achieving high precision real-time object detection. [ABSTRACT FROM AUTHOR]

The early Palaeozoic orogen in South China is considered as one of the typical examples of intraplate orogens in the world. However, the nature of the orogen, for example, the onset time and the timing of tectonic transition from syn-orogenic compression to post-orogenic extension, are still controversial. Here, we present new zircon U–Pb age and Hf isotope data, and whole-rock geochemical and Sr–Nd isotopic data for migmatites and potassic mafic rocks in southern Guangdong, from the Cathaysia Block, South China. Migmatites consist of metatexite and diatexite, including various amounts of palaeosome, melanosome, and leucosome. Leucosomes from metatexite and diatexite/migmatite granite samples yield consistent U–Pb ages of 451.5 ± 2.0 Ma to 458 ± 16 Ma, respectively. Zircon U–Pb dating from two potassic plutons yield consistent crystallization ages of 451–446 Ma. Our new results of field investigation, mineralogy and microstructures, geochronology, and geochemical compositions demonstrate that the protoliths of migmatites are metasedimentary rocks, while metatexites and diatexites are the products of variable degrees of partial melting of the protolith. The potassic rocks have SiO2 contents ranging from 52.5 to 60.2 wt.%, high K2O/Na2O ratios (0.7–1.3), with MgO contents of 3.0–6.2 wt.% and Mg number of 42–57. They have enriched Sr–Nd–Hf isotopic compositions with (87Sr/86Sr)i ratios of 0.7085–0.7151, ɛNd(t) values of −9.9 to −6.2, and εHf (t) values of −10.5 to −5.3, indicating that they were generated from an enriched mantle source modified by ancient oceanic subducted sediments. Regional crustal anatexis occurred at about 451 Ma, and the timescale from crustal anatexis to melt homogenization and accumulation spans over an interval of ~15 Myr. The association of migmatites and the potassic rocks may form in post-orogenic extension setting. Thus, we suggest that the tectonic transition from syn-orogenic compression to post-orogenic extension occurred by the Late Ordovician (ca. 451–446 Ma) for the early Palaeozoic orogen in South China. [ABSTRACT FROM AUTHOR]

Metastasis is a major cause of treatment failure and poor outcomes in cancer patients. The data used in the current study was downloaded from TCGA and GEO databases. Differentially expressed metastasis-related genes were identified and the biological functions were implemented. Kaplan–Meier analysis univariate, and, multivariate Cox regression analyses were performed to identify robust prognostic biomarkers, followed by construction of the risk model and nomogram. Gene set enrichment analysis was performed to identify pathways enriched in low- and high-risk groups. POLR2J3 and MYH11 were treated as prognostic biomarkers in LSCC and the risk model was constructed. Receiver operating characteristic curves revealed the good performance of the risk model. A nomogram with high accuracy was constructed, as evidenced by calibration and decision curves. Moreover, we found that the expressions of POLR2J3 and MYH11 was significantly higher in metastasis tissues compared with those in non-metastasis tissues by RT-qPCR and IHC. Our study identified novel metastasis-related prognostic biomarkers in LSCC and constructed a unique nomogram for predicting the prognosis of LSCC patients. Moreover, we explored the related mechanisms of metastasis-related genes in regulating LSCC. [ABSTRACT FROM AUTHOR]

Motivation Antibiotic resistance presents a formidable global challenge to public health and the environment. While considerable endeavors have been dedicated to identify antibiotic resistance genes (ARGs) for assessing the threat of antibiotic resistance, recent extensive investigations using metagenomic and metatranscriptomic approaches have unveiled a noteworthy concern. A significant fraction of proteins defies annotation through conventional sequence similarity-based methods, an issue that extends to ARGs, potentially leading to their under-recognition due to dissimilarities at the sequence level. Results Herein, we proposed an Artificial Intelligence-powered ARG identification framework using a pretrained large protein language model, enabling ARG identification and resistance category classification simultaneously. The proposed PLM-ARG was developed based on the most comprehensive ARG and related resistance category information (>28K ARGs and associated 29 resistance categories), yielding Matthew's correlation coefficients (MCCs) of 0.983 ± 0.001 by using a 5-fold cross-validation strategy. Furthermore, the PLM-ARG model was verified using an independent validation set and achieved an MCC of 0.838, outperforming other publicly available ARG prediction tools with an improvement range of 51.8%–107.9%. Moreover, the utility of the proposed PLM-ARG model was demonstrated by annotating resistance in the UniProt database and evaluating the impact of ARGs on the Earth's environmental microbiota. Availability and implementation PLM-ARG is available for academic purposes at https://github.com/Junwu302/PLM-ARG , and a user-friendly webserver (http://www.unimd.org/PLM-ARG) is also provided. [ABSTRACT FROM AUTHOR]