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In the field of nonlinear optical (NLO) materials research, the design and synthesis of novel materials are crucial for advancing modern scientific and technological development. This study employs an innovative coordination strategy, building upon the existing structure of [Ln2(CH3COO)6(H2O)4]·4H2O (Ln = Tb, Sm), to successfully synthesize a series of acetate rare-earth metal compounds [Ln2(CH3COO)6(H2O)]n[Ln = Tb(1), Er(2), Y(3)] by regulating the number of water molecules. This approach achieved a structural transition from centrosymmetric (CS) to noncentrosymmetric (NCS), endowing these compounds with significant nonlinear optical responses. We discovered that reducing the coordinated water molecules and introducing acetate as a bidentate ligand is an effective method for modulating crystal structure and realizing NLO performance. This finding not only deepens the understanding of the structure of acetate salts but also provides important theoretical and experimental support for the development of materials with potential NLO propeties.

The occurrence of adhesive failure under impact poses significant risks, including property damage, structural collapse, and even loss of life. Herein, we have developed a series of impact-resistant adhesives by incorporating dynamic B–O linkages into linear polymeric chains. These adhesives not only possess broad-area adhesion and superior adhesive strength compared to 3 M commercial products but also exhibit a shear-stiffening effect. The shear-stiffening effect provided by the B–O linkages endows the adhesives with remarkable impact resistance, achieving a force attenuation efficiency of 84.3–86.3%. Additionally, when they are bonded to target materials, the resulting sandwich structures retain their excellent impact resistance. Therefore, this class of impact-resistant adhesives with a shear-stiffening effect shows significant potential for applications in protecting precision instruments and buildings.

Full-duplex communication receives a particular interest for a better use of the spectrum. Software-defined radio (SDR) is a key enabler for intelligent full-duplex operation as it provides a few reconfigurable transmitter (Tx) and receiver (Rx) channels. As demonstrated in this article, electromagnetic coupling between the Tx and Rx channels in commercial SDR devices cannot be overlooked as it can affect the quality of the received signal. To overcome this issue, this article presents a cancellation algorithm in digital domain. This method exploits the typical architecture of SDR devices and uses the known Tx signal for cancellation without any extra hardware. Details of the algorithm are discussed, including the generation of cancellation signals, amplitude control, orthogonal identification, and phase alignment. GNU-radio platform is used to implement the cancellation algorithm in a commercial SDR device (USRP B210). Experimental results reveal that the averaged cancellation level achieves 42 dB for single-tone signal, 35 dB for single sideband signal, and 20 dB for quadrature phase shift keying signal (with a date rate of 2 Mb/s) in the frequency range of 100–6000 MHz. This work provides a cost-efficient solution for solving the coupling issues between the Tx and Rx channels in SDR, which is critical for full-duplex communication systems.

Classical domain adaptation methods acquire transferability by regularizing the overall distributional discrepancies between features in the source domain (labeled) and features in the target domain (unlabeled). They often do not differentiate whether the domain differences come from the marginals or the dependence structures. In many business and financial applications, the labeling function usually has different sensitivities to the changes in the marginals versus changes in the dependence structures. Measuring the overall distributional differences will not be discriminative enough in acquiring transferability. Without the needed structural resolution, the learned transfer is less optimal. This article proposes a new domain adaptation approach in which one can measure the differences in the internal dependence structure separately from those in the marginals. By optimizing the relative weights among them, the new regularization strategy greatly relaxes the rigidness of the existing approaches. It allows a learning machine to pay special attention to places where the differences matter the most. Experiments on three real-world datasets show that the improvements are quite notable and robust compared to various benchmark domain adaptation models.

Self-calibrating gaze estimation eliminates burdensome personal calibration by utilizing gaze behaviors to calibrate gaze estimation models automatically. However, they rely on viewing multiple specific scenes or sacrifice accuracy. Due to the pervasiveness of reading, we propose a pervasive and accurate self-calibrating approach that requires reading only a few lines of text naturally. This approach reformulates the calibration model as nonlinearly matching spatio-temporal reading patterns and the corresponding eye-feature patterns. The eye features are filtered into fixations by filtering nonreading data and saccades to ensure visual intake. Fixations are segmented into multiple lines by recovering the temporal reading pattern, thus simplifying the nonlinear matching into the line-to-line matching between segmented fixations and text lines, which is achieved by recovering the spatial reading pattern. Experimental results show that the proposed approach has comparable accuracy to state-of-the-art head-mounted gaze estimation methods, which require explicit calibration or multiple salient scenes.

Thermal softening is an inevitable process in the physical network. Polyurethane (PU), a typical commercial material, is constructed by physical networks, which undergoes the serious thermal decay on mechanical properties at high temperature. Herein, a physically cross-linked PU with a unique thermal stiffening behavior has been developed by incorporating B-N coordination with reversible B-O bonds. The B-N coordination can significantly improve the mechanical properties of the PU. The reversible B-O bonds (temperature dependent reversible transformation between B-OH and B-O-B) are conducive to constructing more multi-coordination macromolecular crosslinking points and more stable B-N coordination bonds at high temperature, endowing the PU with the special thermal stiffening behavior for the first time. Such thermal stiffening behavior compensates for the bond breakage and the network destruction caused by heat, significantly expands the rubbery plateau and delays the entire chain motion of the thermoplastic PU. As a result, the terminal flow occurs at a higher temperature up to 200°C. The modulus retention ratio of the materials is up to 87% even at 145°C, which is much higher than that of the existing PU elastomer with the physical network and even some covalent cross-link PU. Simultaneously, the physical network ensures the recyclability of the PU, and the thermal stiffening behavior is still obtained in recycled PU. This work provides a simple strategy to impart thermal stiffening behavior to the physically crosslinked PU, thereby significantly extending the operating temperature range of thermoplastic PU, which can potentially expand the scopes of PU in applications under harsh conditions.

Despite the potential of oral immunotherapy against food allergy, adverse reactions and loss of desensitization hinder its clinical uptake. Dysbiosis of the gut microbiota is implicated in the increasing prevalence of food allergy, which will need to be regulated to enable for an effective oral immunotherapy against food allergy. Here we report an inulin gel formulated with an allergen that normalizes the dysregulated ileal microbiota and metabolites in allergic mice, establishes allergen-specific oral tolerance and achieves robust oral immunotherapy efficacy with sustained unresponsiveness in food allergy models. These positive outcomes are associated with enhanced allergen uptake by antigen-sampling dendritic cells in the small intestine, suppressed pathogenic type 2 immune responses, increased interferon-γ+and interleukin-10+regulatory T cell populations, and restored ileal abundances of Eggerthellaceaeand Enterorhabdusin allergic mice. Overall, our findings underscore the therapeutic potential of the engineered allergen gel as a suitable microbiome-modulating platform for food allergy and other allergic diseases.

Reservoir subsidence induced by natural gas hydrate (NGH) dissociation is a critical safety issue during gas production from NGH reservoirs. Concerning the limited field monitoring of reservoir subsidence, this study employs a customized apparatus to investigate the subsidence behaviors of methane-hydrate-bearing sediments, considering the effects of three reservoir factors, including hydrate saturation, skeleton type, and effective overburden stress. The experimental results show that the NGH reservoir subsidence process during depressurization is controlled by pore pressure reduction and hydrate dissociation; the former mainly affects the effective stress, and the latter mainly affects the mechanical properties of gas hydrate-bearing sediments (GHBSs). The dominance of the two factors on hydrate reservoir subsidence is a dynamic and competitive process during depressurization, and the impact of hydrate dissociation becomes significant in the high hydrate saturation case. Different from coarse-grained sediments, delayed subsidence and intermittent compaction are observed in fine-grained hydrate-bearing sediments, and they are controlled by the initial hydrate saturation and permeability of the skeleton. The evolution of GHBS subsidence is similar under various effective overburden stress and it increases with effective stress. Combined with numerical simulations based on the discrete element method, it is illustrated that the lateral displacement fixed boundary, radial inhomogeneous distribution of hydrate, and excessive sample height-to-diameter ratio may led to conservative sample subsidence in laboratory experiments compared to a field NGH reservoir.

The limited optical penetration depth and hypoxic tumor microenvironment (TME) are key factors that hinder the practical applications of conventional photodynamic therapy (PDT). To fundamentally address these issues, self-luminescent photosensitizers (PSs) can achieve efficient PDT. Herein, a self-chemiluminescence (CL)-triggered Ir complex PS, namely, IrL2, with low-O2-dependence type I photochemical processes is reported for efficient PDT. The rational design achieves efficient chemiluminescence resonance energy transfer (CRET) from covalently bonded luminol units to the Ir complex in IrL2under the catalysis of H2O2and hemoglobin (Hb) to generate O2•–and 1O2. Liposome IrL2Hnanoparticles (NPs) are constructed by loading IrL2and Hb. The intracellular H2O2and loaded Hb catalyze the luminol part of IrL2H, and the Ir2part is then excited to produce types I and II reactive oxygen species (ROS) through CRET, inducing cell death, even under hypoxic conditions, and promoting cell apoptosis. IrL2His used for tumor imaging and inhibits tumor growth in 4T1-bearing mouse models through intratumoral injection without external light sources. This work provides new designs for transition metal complex PSs that conquer the limitations of external light sources and the hypoxic TME in PDT.

Visual–inertial odometry (VIO) is an important component for robots working in industrial environments to obtain accurate and robust pose estimation. In this article, we introduce a novel VIO algorithm designed specifically for 360° cameras, exploiting their wide field of view. We build our algorithm based on an EKF-based filtering framework and propose a novel measurement model for 360° camera leveraging the reprojection error on the tangent plane of the spherical surface. By this, our 360-VIO effectively mitigates errors caused by the image distortion and fully exploit the omnidirectional observation, resulting in superior accuracy and robustness toward illumination changes and fast camera movements. To the best of our knowledge, no public 360-based visual–inertial dataset is currently available. To address this gap, we have constructed a novel 360° camera dataset under different challenging environments to evaluate the performance of our proposed algorithm. The results of our experiments demonstrate the impressive robustness and accuracy of our method compared with other state-of-the-art VIO methods across diverse and challenging environments. To facilitate future research on 360-VIO, we will release the method, self-collected dataset and the calibration tool at: https://github.com/Gatsby23/360-VIO.

High purity and ultrafine DAAF (u-DAAF) is an emerging insensitive charge in initiators. Although there are many ways to obtain u-DAAF, developing a preparation method with stable operation, accurate control, good quality consistency, equipment miniaturization, and minimum manpower is an inevitable requirement to adapt to the current social technology development trend. Here reported is the microfluidic preparation of u-DAAF with tunable particle size by a passive swirling microreactor. Under the guidance of recrystallization growth kinetics and mixing behavior of fluids in the swirling microreactor, the key parameters (liquid flow rate, explosive concentration and crystallization temperature) were screened and optimized through screening experiments. Under the condition that no surfactant is added and only experimental parameters are controlled, the particle size of recrystallized DAAF can be adjusted from 98 nm to 785 nm, and the corresponding specific surface area is 8.45 m2·g−1to 1.33 m2·g−1. In addition, the preparation method has good batch stability, high yield (90.8%–92.6%) and high purity (99.0%–99.4%), indicating a high practical application potential. Electric explosion derived flyer initiation tests demonstrate that the u-DAAF shows an initiation sensitivity much lower than that of the raw DAAF, and comparable to that of the refined DAAF by conventional spraying crystallization method. This study provides an efficient method to fabricate u-DAAF with narrow particle size distribution and high reproducibility as well as a theoretical reference for fabrication of other ultrafine explosives.

Bacterial wound infections are a growing challenge in healthcare, posing severe risks like systemic infection, organ failure, and sepsis, with projections predicting over 10 million deaths annually by 2050. Antibacterial hydrogels, with adaptable extracellular matrix-like features, are emerging as promising solutions for treating infectious wounds. However, the antibacterial properties of most of these hydrogels are largely attributed to extrinsic agents, and their mechanisms of action remain poorly understood. Herein we introduce for the first time, modified imidazolidinyl urea (IU) as the polymeric backbone for developing tissue-like antibacterial hydrogels. As-designed hydrogels behave tissue-like mechanical features, outstanding antifreeze behavior, and rapid self-healing capabilities. Molecular dynamics (MD) simulation and density functional theory (DFT) calculation were employed to well-understand the extent of H-bonding and metal-ligand coordination to finetune hydrogels’ properties. In vitrostudies suggest good biocompatibility of hydrogels against mouse fibroblasts & human skin, lung, and red blood cells, with potential wound healing capacity. Additionally, the hydrogels exhibit good 3D printability and remarkable antibacterial activity, attributed to concentration dependent ROS generation, oxidative stress induction, and subsequent disruption of bacterial membrane. On top of that, in vitrobiofilm studies confirmed that developed hydrogels are effective in preventing biofilm formation. Therefore, these tissue-mimetic hydrogels present a promising and effective platform for accelerating wound healing while simultaneously controlling bacterial infections, offering hope for the future of wound care.

Implicit neural networks have demonstrated immense potential in compressing volume data for visualization. However, despite their advantages, the high costs of training and inference have thus far limited their application to offline data processing and non-interactive rendering. In this article, we present a novel solution that leverages modern GPU tensor cores, a well-implemented CUDA machine learning framework, an optimized global-illumination-capable volume rendering algorithm, and a suitable acceleration data structure to enable real-time direct ray tracing of volumetric neural representations. Our approach produces high-fidelity neural representations with a peak signal-to-noise ratio (PSNR) exceeding 30 dB, while reducing their size by up to three orders of magnitude. Remarkably, we show that the entire training step can fit within a rendering loop, bypassing the need for pre-training. Additionally, we introduce an efficient out-of-core training strategy to support extreme-scale volume data, making it possible for our volumetric neural representation training to scale up to terascale on a workstation with an NVIDIA RTX 3090 GPU. Our method significantly outperforms state-of-the-art techniques in terms of training time, reconstruction quality, and rendering performance, making it an ideal choice for applications where fast and accurate visualization of large-scale volume data is paramount.

Directly modulated lasers (DMLs) have been implemented in short-reach optical networks as an intensity modulation and direct detection (IM-DD) scheme due to their high output power, small footprint, and low-cost fabrication. However, the attainable data rate of C-band DML-based IM-DD systems faces limitations imposed by the DML bandwidth, power fading due to chromatic dispersion, and nonlinear impairments resulting from the interplay between frequency chirp and chromatic dispersion. In this paper, we propose a joint sparse Volterra nonlinear equalization (SVNE) and gradient-descent noise whitening (GD-NW) digital signal processing technique to effectively mitigate the overall impairments. Through experimental verification, we achieve, to the best of our knowledge, the highest net data rates of 142.3/143/134.6/102.8/73.7/61.4 Gb/s over 0/5/10/20/40/60 km standard single-mode fiber for C-band DML-based IM-DD links, with the help of the proposed technique. Compared with previous works, our approach leads to an increase in transmission capacity by at least 10%. Furthermore, we conduct a comprehensive investigation into the achieved net data rate considering various factors, including modulation format, peak-to-peak voltage of the electrical output, utilization of the electrical amplifier, transmission reaches and different application scenarios, DML's chirp and extinction ratio, and the roll-off factor of the pulse shaping filter. Detailed guidelines are provided for performance-oriented efficient operations and measurements of DML-based IM-DD links.

Graphical Abstract:

Uncertainty exists about whether lowering systolic blood pressure to less than 120 mm Hg is superior to that of less than 140 mm Hg, particularly in patients with diabetes and patients with previous stroke.

Stimuli-responsive adhesives with on-demand adhesion capabilities are highly advantageous for facilitating wound healing. However, the triggering conditions of stimuli-responsive adhesives are cumbersome, even though some of them are detrimental to the adhesive and adjacent natural tissues. Herein, a novel stimuli-responsive adhesive called shear-stiffening adhesive (SSA) has been created by constructing a poly(diborosiloxane)-based silicone network for the first time, and SSA exhibits a rate-responsive adhesion behavior. Furthermore, we introduced bactericidal factors (PVP-I) into SSA and applied it as a wound dressing to promote the healing of infected wounds. Impressively, the wound dressing not only has excellent biocompatibility and long-term antibacterial properties but also performs well in accelerating wound healing. Therefore, this study provides a new strategy for the synthesis of intelligent adhesives with force rate response, which simplifies the triggering conditions by the force rate. Thus, SSA has great potential to be applied in wound management as an intelligent bioadhesive with on-demand adhesion performance.

Accurate characterization of the threshold pressure gradient (TPG) in shale oil reservoirs is essential for oil production. However, oil–water two-phase flow through shale oil reservoirs with narrow pores involves thermal–hydrological–mechanical coupling, and the relationship between TPG and pore structures under multiple mechanisms has not been adequately modeled mathematically. In this paper, an analytical TPG model of shale oil reservoirs is derived first by considering the combined effects of effective stress, temperature, capillary pressure, pore structures, and boundary layer. After the established model is adequately verified by the obtainable experimental data, it is embedded into a multistage fractured horizontal well productivity model to investigate the influence of relevant parameters on shale oil production. The simulation results suggest that the TPG for the oil phase increases with the increase in effective stress, leading to the decrease in shale oil production. The cumulative oil production with dynamic TPG is much greater than that considering fixed TPG. Moreover, the wettability of the oil–water two phase (e.g., oil–water interfacial tension and equilibrium contact angle) has crucial influences on well performance; thus, changing the wettability of the oil–water two phase by chemical injection is an effective method to enhance oil recovery. The research results can provide technical support for the efficient development of shale oil reservoirs from the perspective of pore-scale two-phase nonlinear flow characteristics and macroscopic productivity evaluation.

Detection of early neoplastic lesions is crucial for improving the survival rates of patients with gastric cancer. Optical enhancement mode 2 is a new image‐enhanced endoscopic technique that offers bright images and can improve the visibility of neoplastic lesions. This study aimed to compare the detection of neoplastic lesions with optical enhancement mode 2 and white‐light imaging (WLI) in a high‐risk population. In this prospective multicenter randomized controlled trial, patients were randomly assigned to optical enhancement mode 2 or WLI groups. Detection of suspicious neoplastic lesions during the examinations was recorded, and pathological diagnoses served as the gold standard. A total of 1211 and 1219 individuals were included in the optical enhancement mode 2 and WLI groups, respectively. The detection rate of neoplastic lesions was significantly higher in the optical enhancement mode 2 group (5.1% vs. 1.9%; risk ratio, 2.656 [95% confidence interval, 1.630–4.330]; p< 0.001). The detection rate of neoplastic lesions with an atrophic gastritis background was significantly higher in the optical enhancement mode 2 group (8.6% vs. 2.6%, p< 0.001). The optical enhancement mode 2 group also had a higher detection rate among endoscopists with different experiences. Optical enhancement mode 2 was more effective than WLI for detecting neoplastic lesions in the stomach, and can serve as a new method for screening early gastric cancer in clinical practice. United States National Library of Medicine (https://www.clinicaltrials.gov), ID: NCT040720521.

Tartary buckwheat is highly valued for its abundant rutin (quercetin 3-O-rutinoside). As a flavonoid glycoside, rutin is synthesized with the crucial involvement of UDP-dependent glycosyltransferases (UGTs). However, the functions and transcriptional regulation of the UGT-encoded genes remain poorly understood. This study identified a key gene, FtUFGT163, potentially encoding flavonol 3-O-glucoside (1 → 6) rhamnosyltransferase in Tartary buckwheat through omics analysis and molecular docking methods. The recombinant FtUFGT163 expressed in Escherichia colidemonstrated the capacity to glycosylate isoquercetin into rutin. Overexpression of FtUFGT163significantly enhanced the rutin content in Tartary buckwheat. Further investigation identified a novel bZIP transcription factor, FtGBF1, that enhances FtUFGT163expression by binding to the G-box element within its promoter, thereby augmenting rutin biosynthesis. Additional molecular biology experiments indicated that the specific positive regulator of rutin, FtMYB5/6, could directly activate the FtGBF1promoter. Collectively, this study elucidates a novel regulatory module, termed “FtMYB5/6–FtGBF1–FtUFGT163”, which effectively coordinates the biosynthesis of rutin in Tartary buckwheat, offering insights into the genetic enhancement of nutraceutical components in crops.

With the acceleration of the pace of society, the problem of scarcity of time resources is becoming more prominent, which may lead to short‐sighted behavior. This study aimed to examine the impact of time scarcity on intertemporal choice and its underlying mechanisms through three experiments. Study 1 aimed to investigate the causal relationship between time scarcity and intertemporal choice and the mediating role of anxiety between time scarcity and intertemporal choice. The results showed that participants with a stronger perception of time scarcity were more likely to choose smaller and sooner gains, and that the mediating role of anxiety was significant. In Study 2, the control of time was introduced to explore whether the sense of control could alleviate the negative emotion caused by time scarcity. The results showed that individuals with high levels of control had significantly less anxiety under higher time‐scarcity conditions than those with low levels of control. In Study 3, we manipulated time scarcity and found that the sense of control moderated the mediating effect of anxiety in time scarcity and intertemporal choice. Overall, these findings suggest that the sense of control over time is associated with less anxiety from time scarcity, which in turn fosters preferences for delayed gains.

Rare genetic variants in toll-like receptor 7 (TLR7) are known to cause lupus in humans and mice. UNC93B1 is a transmembrane protein that regulates TLR7 localization into endosomes. In the present study, we identify two new variants in UNC93B1 (T314A, located proximally to the TLR7 transmembrane domain, and V117L) in a cohort of east Asian patients with childhood-onset systemic lupus erythematosus. The V117L variant was associated with increased expression of type I interferons and NF-κB-dependent cytokines in patient plasma and immortalized B cells. THP-1 cells expressing the variant UNC93B1 alleles exhibited exaggerated responses to stimulation of TLR7/-8, but not TLR3 or TLR9, which could be inhibited by targeting the downstream signaling molecules, IRAK1/-4. Heterozygous mice expressing the orthologous Unc93b1V117Lvariant developed a spontaneous lupus-like disease that was more severe in homozygotes and again hyperresponsive to TLR7 stimulation. Together, this work formally identifies genetic variants in UNC93B1 that can predispose to childhood-onset systemic lupus erythematosus.

The current study aimed to improve the acid resistance and thermostability of Bacillus velezensisa-amylase through site-directed mutagenesis, with a specific focus on its applicability to the feed industry. Four mutation sites, P546E, H572D, A614E, and K622E, were designed in the C domain of a-amylase, and three mutants, Mut1 (E), Mut2 (ED), and Mut3 (EDEE), were produced. The results showed that the specific activity of Mut3 was 50 U/mg higher than the original a-amylase (Ori) after incubation at 40 °C for 4 h. Compared to Ori, the acid resistance of Mut3 showed a twofold increase in specific activity at pH 2.0. Moreover, the results of preliminary feed hydrolysis were compared between Ori and Mut3 by designing three factors, three levels of orthogonal experiment for enzymatic hydrolysis time, feed quantity, and amount of amylase. It was observed that the enzymatic hydrolysis time and feed quantity showed an extremely significant difference (p< 0.01) in Mut3 compared to Ori. However, the amount of enzyme showed significant (p< 0.05) improvement in the enzymatic hydrolysis in Mut3 as compared to Ori. The study identified Mut3 as a promising candidate for the application of a-amylase in the feed industry.

Powder bed fusion (PBF), along with subsequent heat treatment, plays a crucial role in enhancing the impact toughness of FeCoNiCrMo0.2high-entropy alloys (HEAs) and expanding their potential applications in field for high-speed deformation. In this study, the dynamic-mechanical properties and microstructure of the as-built PBF–FeCoNiCrMo0.2HEAs and quenched PBF–FeCoNiCrMo0.2HEAs heated at 600–750 °C for 8 h were investigated. As the heating temperature increases, the columnar grains and cellular structures undergo coarsening and the dislocation density gradually decreases. Moreover, higher heating temperatures facilitate the precipitation of Mo-rich second phases. This occurrence can be primarily attributed to the segregation of Mo at the boundaries of the as-built specimens. Consequently, in the quenched specimens, the μ phases are predominantly distributed along the boundaries of the cellular structures. In the quenched Q700 specimen (heated at 700 °C for 8h), the size and volume fraction of the μ phases are measured to be 63.4 nm and 3.59%, respectively. Additionally, under the same condition, the Q700 specimens also exhibited a relatively slight increase in the size of the cellular structures. The impact energy absorption, dynamic yield strength, and dynamic compressive strength of the Q700 quenched specimens were found to be 210.1 MJ/m3, 1066 MPa, and 1649 MPa at a strain rate of 1840 s−1. These values represent a dramatic improvement of 38.1%, 52.7%, and 14.7% higher in comparison to those of the as-built specimens. Under impact deformation, the presence of the μ phases plays a significant role in impeding the movement of dislocations by acting as a pinning agent for the boundaries of the cellular structures, thereby enhancing the strength. Simultaneously, the cellular structures were significantly elongated to form the deformation bands and to coordinate the impact deformation, leading to good impact energy absorption. In combination, the synergistic strengthening and toughening effect of the μ phases and the elongated cellular structures contribute to a remarkable improvement in the impact toughness of the PBF-HEAs.

The cGAS-STING pathway plays a crucial role in innate immune activation against cancer and infections, and STING agonists based on cyclic dinucleotides (CDN) have garnered attention for their potential use in cancer immunotherapy and vaccines. However, the limited drug-like properties of CDN necessitate an efficient delivery system to the immune system. To address these challenges, we developed an immunostimulatory delivery system for STING agonists. Here, we have examined aqueous coordination interactions between CDN and metal ions and report that CDN mixed with Zn2+and Mn2+formed distinctive crystal structures. Further pharmaceutical engineering led to the development of a functional coordination nanoparticle, termed the Zinc–Mn–CDN Particle (ZMCP), produced by a simple aqueous one-pot synthesis. Local or systemic administration of ZMCP exerted robust antitumor efficacy in mice. Importantly, recombinant protein antigens from SARS-CoV-2 can be simply loaded during the aqueous one-pot synthesis. The resulting ZMCP antigens elicited strong cellular and humoral immune responses that neutralized SARS-CoV-2, highlighting ZMCP as a self-adjuvant vaccine platform against COVID-19 and other infectious pathogens. Overall, this work establishes a paradigm for developing translational coordination nanomedicine based on drug–metal ion coordination and broadens the applicability of coordination medicine for the delivery of proteins and other biologics.

Maintenance is an important technical measure to maintain and restore the performance status of equipment and ensure the safety of the production process in industrial production, and is an indispensable part of prediction and health management. However, most of the existing remaining useful life (RUL) prediction methods assume that there is no maintenance or only perfect maintenance during the whole life cycle; thus, the predicted RUL value of the system is obviously lower than its actual operating value. The complex environment of the system further increases the difficulty of maintenance, and its maintenance nodes and maintenance degree are limited by the construction period and working conditions, which increases the difficulty of RUL prediction. An RUL prediction method for a multi-omponent system based on the Wiener process considering maintenance is proposed. The performance degradation model of components is established by a dynamic Bayesian network as the initial model, which solves the uncertainty of insufficient data problems. Based on the experience of experts, the degree of degradation is divided according to Poisson process simulation random failure, and different maintenance strategies are used to estimate a variety of condition maintenance factors. An example of a subsea tree system is given to verify the effectiveness of the proposed method.

Methylmalonic acid (MMA), a by-product of propionate metabolism, is known to increase with age. This study investigates the potential of serum MMA concentrations as a biomarker for age-related clinical frailty in older patients with breast cancer. One hundred nineteen patients ≥ 70 years old with early-stage breast cancer were included (median age 76 years). G8 screening, full geriatric assessment, clinical parameters (i.e., estimated glomerular filtration rate (eGFR) and body mass index (BMI)), and serum sample collection were collected at breast cancer diagnosis before any therapy was administered. MMA concentrations were measured via liquid chromatography with tandem mass spectrometry. MMA concentrations significantly increased with age and eGFR (all P< 0.001) in this older population. The group with an abnormal G8 (≤ 14, 51% of patients) had significantly higher MMA levels than the group with normal G8 (> 14, 49%): 260 nmol/L vs. 188 nmol/L, respectively (P= 0.0004), even after correcting for age and eGFR (P= 0.001). Furthermore, in the detailed assessment, MMA concentrations correlated most with mobility (Eastern Cooperative Oncology Group (ECOG) Performance Status and Activities of Daily Living (ADL) tools, all P≤ 0.02), comorbidity (Charlson Comorbidity Index (CCI) tool, P= 0.005), and polypharmacy (P< 0.001), whereas no significant associations were noted for instrumental ADL (IADL), Mini-Mental State Examination (MMSE), Geriatric Depression Scale-15 (GDS15), Mini Nutritional Assessment-Short Form (MNA-SF), and pain (all P> 0.1). In addition, our results showed that higher MMA levels correlate with poor overall survival in breast cancer patients (P= 0.003). Elevated serum MMA concentrations at initial diagnosis are significantly associated, not only with age but also independently with clinical frailty, suggesting a possible influence of MMA on clinical frailty in older patients with early-stage breast cancer.

In long-lived room-temperature phosphorescence (RTP) materials, intermolecular interactions have been increasingly acknowledged to play crucial roles, since more and more works have proved their important role in stabilizing the triplet excitons. Herein, we mainly focus on the intermolecular hydrogen bonds and will present a computational study on their regulation of the RTP lifetime of isomer molecules in crystal form and polymorphs. The hydrogen bond is found to have a corresponding relation with phosphorescence lifetime, i.e., an isomerism crystal with a longer RTP lifetime has a larger intermolecular hydrogen-bond contribution. Further investigation on the radiative and nonradiative transition processes illustrates that hydrogen bonds have a considerable impact on the phosphorescent radiative decay rate kp, while nonradiative processes play a weak role in regulating the RTP lifetime in these crystals. Thus, the crystals with a higher intermolecular hydrogen-bond contribution could obtain a longer lifetime mainly by reducing kp. This research may supply a facile way to achieve a long phosphorescence lifetime through enhancing intermolecular hydrogen-bond contribution.

Opisina arenosella (Lepidoptera: Oecophoridae) is a major leaf-feeding pest of palm crops that has invaded several tropical and subtropical countries or regions. Habrobracon hebetor (Hymenoptera: Braconidae) is a parasitoid of O. arenosella larvae whose efficiency in controlling its hosts is inhibited by high temperatures. The body color of this wasp exhibits a plastic response to temperature (melanin fades with increasing temperature). Based on the thermal melanism hypothesis, we proposed that H. hebetor adults with lighter body color would have better biological performance at high temperatures. This paper established the link between the parasitoid’s body color phenotype and biological performance. Our results show that exposure to 32°C for more than 3 d during the pupal stage induced almost complete loss of abdominal melanin in H. hebetor adults. At the population level, when adults were held under heat stress (34°C), the percentage of abdominal melanin in the parasitoids was negatively correlated with parasitoid longevity and the number of paralyzed hosts, But, in contrast, melanization was positively correlated with parasitoid fecundity. The yellow-biotype of H. hebetor has higher host control potential in tropical regions. Related aspects of our results also improve understanding the biological significance of plastic body color in insects and provide information on host control by H. hebetor in tropical environments.

Anthocyanins are important flavonoid compounds that are abundant in Tartary buckwheat, providing a variety of bright colors and enhancing abiotic stress resistance. Our study found that FtMYB22specifically affected anthocyanin anabolism. In this study, overexpression of the FtMYB22 transcription factor in tobacco significantly reduced the accumulation of flavonol in the petals of transgenic tobacco plants. Moreover, it significantly downregulated the expression of the genes involved in anthocyanin biosynthesis in tobacco. Overexpression of the FtMYB22 transcription factor in Tartary buckwheat hairy roots significantly inhibited anthocyanin and total flavonoids biosynthesis, and downregulated the expression of the anthocyanin biosynthesis genes. Comparing wild‐type and transgenic hairy roots, FtMYB22overexpression significantly inhibited anthocyanin accumulation and downregulated most flavonoid synthesis pathway gene expression. Yeast two‐hybrid assays demonstrated that FtMYB22 could interact with the FtbHLH family member FtTT8 and the FtWD40 family member FtTTG1 to form a ternary MBW complex to inhibit anthocyanin synthesis. Therefore, FtMYB22can be exploited as a target site for further gene editing and molecular breeding to improve the resilience and quality of Tartary buckwheat. FtMYB22 was overexpressed in hairy roots of both tobacco and Tartary buckwheat.RNA‐seq analysis was performed to confirm the functionality of FtMYB22.FtMYB22 negatively regulated the expression of genes related to anthocyanin synthesis and anthocyanin content.FtMYB22 inhibits anthocyanin synthesis by creating a ternary complex MBW.

Tartary buckwheat (Fagopyrum tataricum) is a well-known pseudocereal for its health and economic value. However, abundant antinutritional factors (ANFs) reduces its health benefits. As reported, germination can improve the nutritional profile of grains. In this study, we systematically evaluate the safety of Tartary buckwheat seeds (TB) and Tartary buckwheat sprouts (TBS) used as high active ingredients. After evaluating nutrition levels, bioactive compounds and ANFs in TBS during germinating, 5th-day TBS were selected as the raw material. C57BL/6J mice were gavaged daily with distilled water, TB, or TBS for 6 weeks. The physiological indices related to ANFs were determined. Results showed that the TB intake tends to generate negative effects on the gut microbiota, and organs. Additionally, upon TB intake, the Fe3+content in serum, trypsin activity in pancreas and jejunum decreased, while the cytokine, IgE, and histamine levels in serum, water content in faeces, cytokine levels in liver and jejunum increased. Conversely, TBS did not induce any obvious negative effects on the above relevant indices and showed better lipid-lowering effect. Altogether, TBS are safer and more effective as a raw material to produce the functional food for long-term consumption with the intention of preventing and treating hyperlipidaemia.

ABSTRACTHepatocellular carcinoma (HCC) stands as the third leading cause of cancer-related fatalities globally. In this study, we observed a significant increase in the expression level of the YEATS2gene in HCC patients, and it is negatively correlated with the patients’ survival rate. While we have previously identified the association between YEATS2 and the survival of pancreatic cancer cells, the regulatory mechanisms and significance in HCC are still to be fully elucidated. Our study shows that knockdown (KD) of YEATS2 expression leads to DNA damage, which in turn results in an upregulation of γ-H2A.X expression and activation of the canonical senescence-related pathway p53/p21Cip1. Moreover, our transcriptomic analysis reveals that YEATS2 KD cells can enhance the expression of p21Cip1 via the c-Myc/miR-93-5p pathway, consequently fostering the senescence of HCC cells. The initiation of cellular senescence through dual-channel activation suggests that YEATS2 plays a pivotal regulatory role in the process of cell proliferation. Ultimately, our in vivoresearch utilizing a nude mouse tumor model revealed a notable decrease in both tumor volume and weight after the suppression of YEATS2 expression. This phenomenon is likely attributable to the attenuation of proliferative cell activity, coupled with a concurrent augmentation in the population of natural killer (NK) cells. In summary, our research results have supplemented the understanding of the regulatory mechanisms of HCC cell proliferation and indicated that targeting YEATS2 may potentially inhibit liver tumor growth.

Ferroptosis, a form of regulated cell death that is driven by iron-dependent phospholipid peroxidation, has been implicated in multiple diseases, including cancer1–3, degenerative disorders4and organ ischaemia–reperfusion injury (IRI)5,6. Here, using genome-wide CRISPR–Cas9 screening, we identified that the enzymes involved in distal cholesterol biosynthesis have pivotal yet opposing roles in regulating ferroptosis through dictating the level of 7-dehydrocholesterol (7-DHC)—an intermediate metabolite of distal cholesterol biosynthesis that is synthesized by sterol C5-desaturase (SC5D) and metabolized by 7-DHC reductase (DHCR7) for cholesterol synthesis. We found that the pathway components, including MSMO1, CYP51A1, EBPand SC5D, function as potential suppressors of ferroptosis, whereas DHCR7functions as a pro-ferroptotic gene. Mechanistically, 7-DHC dictates ferroptosis surveillance by using the conjugated diene to exert its anti-phospholipid autoxidation function and shields plasma and mitochondria membranes from phospholipid autoxidation. Importantly, blocking the biosynthesis of endogenous 7-DHC by pharmacological targeting of EBP induces ferroptosis and inhibits tumour growth, whereas increasing the 7-DHC level by inhibiting DHCR7 effectively promotes cancer metastasis and attenuates the progression of kidney IRI, supporting a critical function of this axis in vivo. In conclusion, our data reveal a role of 7-DHC as a natural anti-ferroptotic metabolite and suggest that pharmacological manipulation of 7-DHC levels is a promising therapeutic strategy for cancer and IRI.

In the search for nonlinear optical (NLO) materials with excellent overall performance, we have devoted ourselves to organic–inorganic hybrids consisting of anionic groups containing stereochemically active lone-pair (SCALP) electron cations and organic planar π-conjugated group cations. Accordingly, in this paper, two novel organic–inorganic hybrid metal halides, C4H7N2Ge0.4Sn0.6Br3(I) and C6H11N2Ge0.4Sn0.6Br3(II), have been synthesized. The powder second-harmonic technique shows that both C4H7N2Ge0.4Sn0.6Br3and C6H11N2Ge0.4Sn0.6Br3have moderately strong second-order nonlinear optical effects, which are about 2.03 (I) and 1.16 (II) times that of KH2PO4(KDP), respectively. They also have different optical band gaps of 2.75 (I) and 2.88 eV (II) due to the different sizes of the organic cations, and their photoluminescent and thermal properties were also investigated. This work provides new structural insights for the design and modulation of organic–inorganic hybrid halide materials with multiple excellent optical properties.

Modern aircraft is exposed to a variety of risks from electromagnetic environment (EME), and electromagnetic shielding is a useful method for protecting electronic equipment from the severe EME. In the meanwhile, aircraft employs more integrated modular avionics, whose enclosures are much smaller than conventional ones. Therefore, it is critical to invent new equipment for measuring the shielding effectiveness (SE) of small enclosures. This article proposes an integrated switching antenna composed of a square wave generator, switching circuit, impedance matching circuit, compact monopole, and battery. The SE of a tiny enclosure at several frequencies can be tested with an integrated switching antenna in a single test. Furthermore, the proposed construction does not require an external signal generator, which eliminates the need for any enclosure cuts for attaching a coaxial cable or soldering an antenna. To test the feasibility of the proposed antenna, a prototype is built to measure the SE of a tiny enclosure. The measurement shows a good agreement between the measured and simulated results. Furthermore, using the inverse fast Fourier transform, the time-domain SE may be determined from the frequency-domain measurements in the frequency range of 1 to 100 MHz. The calculated time-domain SE results could be useful for determining the amount of protection against lightning and high-altitude electromagnetic pulse.

The complexity of the series-fed microstrip antenna array (SFMAA) synthesis problem increases rapidly with increasing element number. When dealing with complex practical SFMAA synthesis problems, conventional ideal antenna-based and electromagnetic (EM) full-wave simulation-based methods are trapped in performance degradation and time-consuming iteratively “cut-and-try” processes. Machine-learning-assisted (MLA) methods face the “curse of dimensionality,” leading to significantly increased training and prediction times and reduced prediction performance. Here, base element (BE) modeling is used to develop a knowledge-guided and MLA synthesis method for SFMAAs. First, the similarity of BEs with different locations and dimensions is explored using knowledge-guided classification. Then, a cosine-domain learning method with low computational costs is introduced. Next, array synthesis, microwave network cascades, and MLA optimization approaches are used to design SFMAAs. This hybrid knowledge-guided and data-driven method greatly facilitates the synthesis process, achieving low training and prediction times and high accuracy. Furthermore, synthesis applications with three types of SFMAAs and various practical design goals are utilized to verify the effectiveness of the proposed method. Finally, the designed antenna prototypes are fabricated, and the measured results show excellent agreement with the simulation results.

Conformal antenna arrays become more popular on aircraft owing to significant improvement of aerodynamic and stealth performance. Since the interaction between the platform and the antenna array matters in the simulation results and their meshing produces a large matrix, the analysis of conformal array is computationally expensive. In this article, an efficient method is proposed for the analysis of arbitrary conformal array on cylindrical surface. A periodic Green’s function combined with the method of moments (MoMs) enables efficient analysis with one unit cell. In addition, the Rao–Wilton–Glisson (RWG) basis function is adopted to describe the surface current of arbitrarily shaped array element. Cylindrical periodic Green’s function (CPGF) is calculated by Wynn’s $\varepsilon $ -algorithm to improve the convergence, and a modified sampling procedure is developed for the RWG basis and weighted functions in the MoM. Key metrics of conformal array, such as the reflection coefficient, mutual coupling, and radiation pattern, are efficiently evaluated by the proposed method. The influences of conformal curvature and element interval are studied, indicating that the interval is a more important factor affecting the near-field characteristics. This method and conclusions can assist the design of various cylindrical conformal arrays.

Based on the complementary advantages of integrated positioning methods, the multisource integrated positioning technology has become one of the mainstream technologies in the field of indoor navigation and positioning. However, little literature is available on the estimating for positioning accuracy of different sources in the integration. The negative benefits of integrated positioning method are caused by inaccurately estimated accuracy, which frequently occur in two sources integrated positioning without any correction. To study how to estimate the positioning accuracy of different sources in the integration, we propose a location accuracy indicator enhanced method based on magnetic field matching (MFM) and pedestrian dead reckoning (PDR) integration using Kalman filter (KF): the prior covariance based on PDR and the posterior covariance based on MFM are adopted to calculate noise matrixes of the KF and established the location accuracy indicator enhanced filtering system. From the results, the proposed method, which was less affected by changing the matching range of the magnetic field and broadening the interval of the fingerprint database, obtained 2.746 and 1.881 m for 90% error and root-mean-square error (RMSE), respectively, and the error was 24%–27% lower than the best empirical model, including weighted nearest ${k}$ -neighborhood (WKNN)/PDR (3.776 and 2.523 m) and integrated weight nearest neighborhood (IWNN)/PDR (3.712 and 2.485 m). It was verified by the experiments that the proposed method could accurately calculate noise matrixes of the KF and provide accurate weights, having stronger positioning performance and robustness than the others.

The irregular adjacency matrix and the mismatched computation patterns of Aggregation and Combination phases make Graph Neural Networks (GNNs) challenging to compute efficiently. This paper proposes a software and hardware co-design system to reduce computational latency and memory access based on workload reorganization and feature reduction. In software, the adjacency matrix is preprocessed, and the workload in both feature and node dimensions is concentrated to optimize memory access and hardware utilization. The interlayer nodes are analyzed using Principal Component Analysis (PCA) to explore the minimum feature vector length based on information redundancy, and a unique weight initialization is utilized for retraining to trim the feature vector to the minimum length. In hardware, an efficient GCN accelerator is designed to fully support the reorganized workload by reconfigurable output node computation. The hardware accelerator is implemented using 28-nm CMOS technology. It achieves 3.3 TOPS peak throughput and 2.6 TOPS/W energy efficiency. Compared with HyGCN, this result shows that the proposed method can improve the overall performance by $5\times $ with a negligible accuracy loss of less than 0.5%.

In this article, a novel design concept for bandwidth enhancement and mutual-coupling (MC) reduction of a single quad-port cross-slot antenna with simultaneously co-polarized and dual-polarized radiation patterns is proposed and designed. Initially, the first-, second-, and third-order modes (CM1–CM3) of a dual-port single-slot antenna with co-polarized pattern are theoretically studied by using a characteristic mode analysis (CMA). The results demonstrate that when one port is excited, the electric-field null of the antenna could be shifted to another unexcited port by combining these three modes, thus reducing the MC between two ports under a co- polarized pattern. Then, the short-ended bridges are loaded across the slot, resulting to move resonant frequencies of its CM1–CM3 closely to each other. After that, the microstrip lines are selected to excite the slot antenna for wide impedance matching. In addition, the linear slot is bent in order to reduce the electrical length. With these arrangements, our proposed quad-port cross-slot antenna has gained the desired co- polarized and dual-polarized radiation patterns with low MC. Finally, our designed antenna prototype is fabricated and measured. The results indicate that the isolation bandwidth ( $\vert S_{11}\vert &lt; -10$ dB and MC $ &lt; -17$ dB) of our designed antenna is successfully extended to about 16.18% ranging from 4.83 to 5.68 GHz, becoming obviously widened compared to the traditional counterpart. Most importantly, both co- polarized and dual-polarized radiation patterns are independently realized under four ports while holding single layer, small thickness, single element, and stable radiation pattern simultaneously.

Image captioning is a core challenge in computer vision, attracting significant attention. Traditional methods prioritize caption quality, often overlooking style control. Our research enhances method controllability, enabling descriptions of varying detail. By integrating a length level embedding into current models, they can produce detailed or concise captions, increasing diversity. We introduce a length-level reranking transformer to correlate image and text complexity, optimizing caption length for informativeness without redundancy. Additionally, with caption length increase, computational complexity grows due to the autoregressive (AR) design of existing methods. To address this, our non-autoregressive (NAR) model maintains constant complexity regardless of caption length. We've developed a training approach that includes refinement sequence training and sequence-level knowledge distillation to close the performance gap between NAR and AR models. In testing, our models set new standards for caption quality on the MS COCO dataset and offer enhanced controllability and diversity. Our NAR model excels over AR models in these aspects and shows greater efficiency with longer captions. With advanced training techniques, our NAR's caption quality rivals that of leading AR models.

Given a high-level instruction, the task of Embodied Referring Expression (REVERIE) requires an embodied agent to localise a remote referred object via navigating in the unseen environment. Previous vision-language navigation methods utilise the provided fine-grained instruction as step-by-step navigation guidance to conduct strict instruction-following, while REVERIE aims to achieve efficient goal-oriented exploration according to the high-level command. In this work, we propose a Cross-modal Knowledge Reasoning (abbreviated as CKR+) framework, which incorporates the prior knowledge as decision guidance to learn the navigation scheme comprehensively. Specifically, we design a Room-Object Aware (ROA) mechanism to explicitly decouple the room- and object-related clues from instruction and visual observations. Moreover, we propose a Knowledge-enabled Entity Relation Reasoning (KERR+) module to leverage the structured knowledge from the knowledge graph explicitly and unstructured knowledge from pre-trained model implicitly, to learn the internal-external correlations among room- and object-entities for the agent to make proper decisions. We devise an Entity Prompter (EP) that embeds in the KERR+ module, which utilises the navigation history and visual entities as prompts to transfer knowledge from the pre-trained CLIP model. In addition, we develop a Reinforced End Decider (RED) to learn the stopping scheme specifically, which is achieved by a customised reinforcement learning strategy and knowledge enhanced matching. Two techniques are also introduced to improve navigation efficiency further. Extensive experiments conducted on the REVERIE benchmark demonstrate the effectiveness and superiority of our proposed methods, which boosts the key metrics, i.e., SPL and REVERIE-success rate, to 14.46% and 13.81% respectively.

The flame-retardant paper has gradually evolved into a necessary material in various industries as a result of the rising importance of fire safety, energy efficiency, and environmental preservation. Traditional cellulose paper requires the addition of a large amount of flame retardants to achieve flame retardancy, which poses a serious threat to mechanical quality and the environment. Therefore, there is an urgent need to develop inorganic fiber flame-retardant paper with good flexibility, high thermal stability, and inherent flame retardancy. Herein, inspired by the “brick-and-mortar” layered structure of nature nacre, we developed a layered composite paper with a unique alternating arrangement of organic–inorganic fibers by synergistically integrating environmentally sustainable basalt fiber (BF) and high-performance aramid nanofibers (ANFs) through a vacuum-assisted filtration process. The as-prepared ANFs/BF composite paper exhibited low thermal conductivity (0.024 W m–1K–1), high tensile strength (54.22 MPa), and excellent flexibility. Thanks to its excellent thermal stability, the mechanical strength remains at a high level (92%) after heat treatment at 300 °C for 60 min. Furthermore, the peak heat release rate and smoke generation of ANFs/BF composite paper decreased by 44.6 and 95.3%, respectively. Therefore, the composite paper is promising for applications as a protective layer in flexible electronic devices, cables, and fire-retardant and high-temperature fields.

Sodium-glucose co-transporter 2 (SGLT2) inhibitor (SGLT2i) is a novel class of anti-diabetic drug, which has displayed a promising benefit for non-alcoholic fatty liver disease (NAFLD). In this study, we investigated the protective effects of SGLT2i against NAFLD and the underlying mechanisms. The db/dbmice and western diet-induced NAFLD mice were treated with dapagliflozin (1 mg·kg−1·d−1, i.g.) or canagliflozin (10 mg·kg−1·d−1, i.g.) for 8 weeks. We showed that the SGLT2i significantly improved NAFLD-associated metabolic indexes, and attenuated hepatic steatosis and fibrosis. Notably, SGLT2i reduced the levels of pro-inflammatory cytokines and chemokines, downregulated M1 macrophage marker expression and upregulated M2 macrophage marker expression in liver tissues. In cultured mouse bone marrow-derived macrophages and human peripheral blood mononuclear cell-derived macrophages, the SGLT2i (10, 20 and 40 μmol/L) significantly promoted macrophage polarization from M1 to M2 phenotype. RNA sequencing, Seahorse analysis and liquid chromatography-tandem mass spectrometry analysis revealed that the SGLT2i suppressed glycolysis and triggered metabolic reprogramming in macrophages. By using genetic manipulation and pharmacological inhibition, we identified that the SGLT2i targeted PFKFB3, a key enzyme of glycolysis, to modulate the macrophage polarization of M1 to M2 phenotype. Using a co-culture of macrophages with hepatocytes, we demonstrated that the SGLT2i inhibited lipogenesis in hepatocytes viacrosstalk with macrophages. In conclusion, this study highlights a potential therapeutic application for repurposing SGLT2i and identifying a potential target PFKFB3 for NAFLD treatment.

Inverter-fed machines are widely used in many important industrial applications. However, the machine stator groundwall and/or turn insulation are prone to failure suffering the inverter's high dv/dt. It is necessary to identify them as early as possible but challenging due to their coupled and weak symptoms. In this article, a hybrid physics-based and data-driven approach is proposed to monitor insulation degradations. First, the physical mechanism analysis is carried out to obtain high-quality data sensitive to stator insulation conditions, i.e., the high-frequency common-mode switching oscillations. Then, the continuous wavelet transform is used to extract the time-frequency features of switching oscillations. Finally, an improved convolutional neural network is designed for the groundwall and/or turn insulation faults diagnosis. The experimental results on a 3 kW permanent magnet synchronous motor drive system demonstrate the effectiveness of the proposed method for multiple faults diagnosis with excellent sensitivity, accuracy, and robustness.

The core equipment of lithium-ion battery energy storage stations is containers composed of thousands of batteries in series and parallel. Accurately estimating the state of charge (SOC) of batteries is of great significance for improving battery utilization and ensuring system operation safety. This article establishes a 2-RC battery model. First, the Extended Kalman Filter (EKF) algorithm is used to obtain preliminary SOC estimates. Then, the updated error values of the Kalman matrix, the state variables obtained from the EKF algorithm, and the battery data during system operation are used as the training and test dataset for the Long Short-Term Memory (LSTM) neural network algorithm. Finally, the algorithm was compared and analyzed with commonly used EKF estimation methods and LSTM algorithms. It was found that the root-mean-square error of the SOC of the EKF–LSTM algorithm under different operating conditions was less than 0.8%, and the average absolute error was less than 0.5%. The estimation accuracy is higher than either the EKF algorithm or LSTM algorithm alone.

Supramolecular polymers are usually thermomechanically unstable, as their mechanical strength decreases drastically upon heating, which is a fatal shortcoming for their application. Herein, inspired by heat shock proteins (HSPs) which enable living organisms to tolerate lethal high temperatures, we design an HSP-like response to impart a supramolecular elastomer with high thermomechanical stability. The HSP-like response relies on the reversible hydrolysis of boronic acid and the tunable association strength of boron dative bonds. As the temperature increases, the boronic acid dehydrates and transforms into boroxane. The boroxane, acting as a heat shock chemical, prevents the disintegration of the supramolecular network through formation of multiple and stronger dative bonds with imidazole-containing polymers, thereby enabling the material to retain its mechanical strength at high temperatures. Such chemical transformation and network change induced by the HSP-like response are fully reversible during the heating and cooling processes. Moreover, due to the dynamic nature of the supramolecular network, the elastomer possesses recycling and self-healing abilities.

Volume data is commonly found in many scientific disciplines, like medicine, physics, and biology. Experts rely on robust scientific visualization techniques to extract valuable insights from the data. Recent years have shown path tracing to be the preferred approach for volumetric rendering, given its high levels of realism. However, real-time volumetric path tracing often suffers from stochastic noise and long convergence times, limiting interactive exploration. In this paper, we present a novel method to enable real-time global illumination for volume data visualization. We develop Photon Field Networks—a phase-function-aware, multi-light neural representation of indirect volumetric global illumination. The fields are trained on multi-phase photon caches that we compute a priori. Training can be done within seconds, after which the fields can be used in various rendering tasks. To showcase their potential, we develop a custom neural path tracer, with which our photon fields achieve interactive framerates even on large datasets. We conduct in-depth evaluations of the method's performance, including visual quality, stochastic noise, inference and rendering speeds, and accuracy regarding illumination and phase function awareness. Results are compared to ray marching, path tracing and photon mapping. Our findings show that Photon Field Networks can faithfully represent indirect global illumination within the boundaries of the trained phase spectrum while exhibiting less stochastic noise and rendering at a significantly faster rate than traditional methods.

Alleviating user interaction in handset antennas is challenging. In this communication, a systematic approach is proposed to improve the radiation efficiency of antennas in a lossy environment, exemplified by hand-loaded mobile terminal antennas. The strategy is based on $N$ -port characteristic mode (CM) analysis for composite lossy structures. To construct the network, numerous ports are strategically incorporated into the lossy antenna. Modal efficiencies are then derived for any possible subnetworks, identifying an efficient network with a smaller number of ports. By optimizing the exciting coefficients of the CMs of the subnetwork, the reactive loads at each port can be determined, leading to optimized currents and higher antenna efficiency. The approach proves effective for ultrathin handset antennas operating at multiple bands (GSM 900, DCS 1800, and PCS 1900). Without altering the structure, the proposed antennas can provide an efficiency improvement of more than 3 dB compared with the reference antenna. Antenna prototypes were fabricated, with the measured results agreeing well with the simulated ones.