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We accomplish a compact 150-MHz figure-9 Er:fiber laser through the use of a hybrid device of wavelength division multiplexer and phase shifter. By combining the time-independent rate equation and nonlinear Schrödinger equation, evolution of the intracavity field towards stable mode locking state is presented. We further quantify the output characteristics of the 150-MHz figure-9 laser. Explicitly, 5.8-mW average power, center wavelength of 1561.2 nm and 3-dB spectral bandwidth of 29.2 nm are obtained. More importantly, an integrated root-mean-square relative intensity noise of 0.0016% [1 Hz, 1 MHz] and 75.8 fs timing jitter [100 Hz, 1 MHz] are measured at the fundamental repetition rate. Moreover, by referencing to a stable radio frequency, the fundamental repetition rate is locked with an in-loop relative instability of $2.78\times 10^{-12}$ at 1-s gate time.

Orally targeting nanostrategies of multiple nutraceuticals have attracted increasing attention in ulcerative colitis (UC) therapy for superior patient compliance, cost-effectiveness, and biocompatibility. However, the actual targeting delivery and bioefficacy of nutraceuticals are extremely restricted by their poor solubility, interior gastrointestinal retention, and base permeability. Herein, we developed controllable colon-targeting nanoparticles (NPs) composed of a quaternary ammonium chitosan (HTCC) shell and succinic acid-modified γ-cyclodextrin (SACD) core for precise UC treatment. Egg white-derived peptides (EWDP, typical food-derived peptides) could not only function as potential cross-linkers to induce the differential coassembly with the above biopolymers but also aid the hydrophobic curcumin (Cur) solubility as well as nutrition enhancers for oral synergism of colitis therapy. More specifically, NPs with higher EWDP coassembly efficiency exhibited better pH-sensitive colloidal tunability (e.g., smaller size, higher rigidity, and roughness) and robust nutraceuticals (EWDP/Cur) coloading capacity (24.0–33.2% ≫ 10%, pH 2.0–7.0). Compared with pure nutraceuticals, NPs exhibited excellent cellular absorption (almost 10 times) and oral bioavailability (4.19–5.05 times) enhancement via faster mucus permeation and macropinocytosis transport, indirectly regulating the systemic inflammatory response. The sustainable sequential release and targeted accumulation profiles of NPs directly facilitated the interactions with the colonic microenvironment, verified by the intestinal barrier recovery and gut microbiota restoration. Moreover, the critical role of amino acid metabolism reconfirmed the importance of EWDP coassembly efficiency in maintaining intestinal homeostasis. Overall, this study would provide a facile, quantitative, and versatile perspective into the programmable design of food-derived peptide (e.g., EWDP) coassembled nanoplatforms for oral targeted therapy of UC.

Object detection in infrared images poses a considerable challenge due to its small-scale targets, low contrast and poor signal-to-clutter ratio, often resulting in a high false alarm rate. To improve the detection accuracy on infrared small targets, we introduce Light-SGMTLM, a lightweight and saliency-guided multi-task learning model. This model integrates saliency detection into the YOLOv5x framework through a parallel multi-task learning structure and employs a joint loss function during training. Such integration significantly alleviates the impact of complex backgrounds and improves the precision of small target localization. Moreover, we have developed a streamlined module, termed SIWD, to create a more agile backbone, which establishes an optimal balance between precision and efficiency, making the model more suitable for situations with limited computational resources. Comprehensive comparative experiments were conducted on six infrared small target datasets, namely, Small-ExtIRShip, Small-SSDD, IHAST, NUAA-SIRST, IRSTD-1k, and IRDST, and we assessed the model’s performance against ten leading target detection models, such as YOLOv7, YOLOv8, DINO, and Relation-DETR. The findings reveal that our method’s unique joint learning architecture, combining saliency and object detection tasks, significantly improves accuracy for infrared small target detection. Notably, it achieved impressive mean average precision (mAP) values of 92.60% and 75.71% on the NUAA-SIRST and IRSTD-1k datasets, respectively.

It is a widely recognized challenge to achieve independently steerable multiple beams using analog circuits. The generalized joined coupler (GJC) matrices have been proved capable of realizing multiple beams with flexible beam directions and low sidelobe levels (SLs). A major advantage of GJC matrix is that the phase shifters in each row are the same, thus facilitating easy and independent control of beams. In this article, for the first time, a reconfigurable GJC matrix as a multibeam feed network (MFN) is reported using planar circuits and verified experimentally. Beam steering is realized by a series of novel low-loss tunable reflection-type phase shifters (RTPSs), which are modeled and thoroughly analyzed. Based on the hybrid couplers and tunable phase shifters, a $2\times 8$ reconfigurable GJC matrix is modeled and simulated using planar microstrip lines, and prototype is fabricated and tested. Low loss, excellent matching and continuous tuning phases with the minimum phase error are obtained from simulation as well as measurements. Finally, the designed matrix is employed to feed a linear array for steering multiple beams. The realized beam patterns have successfully demonstrated that the designed reconfigurable GJC matrix is capable of independently controlling multiple beams simultaneously.

In order to improve the accuracy and recall of product packaging colour bionic feature extraction, this paper proposes a product packaging colour bionic feature extraction method based on flower pollination algorithm. Firstly, smooth the product packaging image, extract super-pixel blocks from the image, and complete intelligent image segmentation. Then, using the flower pollination algorithm to simulate self-pollination, the conversion probability is introduced to conduct a global search for colour biomimetic features and determine the colour biomimetic features. Finally, using the sigmoid function, the determined colour biomimetic features are discretised and extracted. If the feature value is 0, the feature is not extracted, and if the value is 1, the feature is extracted to complete the colour biomimetic feature extraction. The results show that the extraction accuracy of the method in this paper can reach 99.25%, the extraction recall rate can reach 96.2% and the product packaging colour biomimetic feature effect is good.

This article proposes a data-driven online diagnosis method for detecting common electrical faults and current sensor faults (CSFs) in dual three-phase permanent-magnet synchronous motor (DTP-PMSM) drives. The proposed diagnosis method fulfills feature extraction by obtaining the average values of phase currents in the positive and negative half-cycles of fault features to reduce dimensionality. By designing a one-vote veto classification rule, the proposed diagnosis method can accurately distinguish 24 fault modes and effectively prevent misdiagnosis. The classification model consists of only 24 decision functions, making it easy to implement on the mainstream industrial microcontrollers. The experiments are carried out to verify the validity of the proposed method.

BackgroundTo delineate the clinical and mutational signatures of patients with CRB1-associated retinopathies.MethodsThis multicentre retrospective cohort study involved 40 patients with CRB1mutations and 40 age-matched and gender-matched inherited retinal diseases (IRDs). The detailed phenotyping and genotyping characteristics and genotype‐phenotype correlations of the patients were analysed.ResultsThe mean age of CRB1cohort was 27.33±14.63 years. Results showed that yellowish geographic macular degeneration (66.67%), small white or yellow dots (65.6%), hyperopia (62.5%), abnormally laminated retina (61.61%), epiretinal membrane (60.6%) and nummular pigment deposits (50%) were the most common signatures in patients with CRB1mutations. These clinical signatures were notably more prevalent among CRB1patients than among individuals in other IRD groups (p<0.001). Early-onset severe retinal dystrophy/Leber congenital amaurosis (EOSRD/LCA) patients are more likely to present these signatures than retinitis pigmentosa (RP) and macular dystrophy (MD) patients. Furthermore, a significant reduction in central foveal thickness coupled with pronounced thickening of the peripheral retina was observed more distinctly in patients with EOSRD/LCA (p<0.001). The choroidal thickness was not significantly altered compared to the normal controls, but was markedly reduced in the other IRD groups (p<0.001). 55 pathogenic variants were identified, 20 of which were novel. Null mutations were associated with EOSRD/LCA patients, and missense mutations were more prevalent in MD and RP patients.ConclusionsKey clinical and mutational signatures were demonstrated in this study, providing a comprehensive update on CRB1-associated retinopathies that will aid in diagnosis and lay the foundation for future therapeutic studies.

The terminal-cloud collaborative framework boosts precision and efficiency by integrating cloud computing power with low-latency terminal responsiveness, offering a suitable solution for the growing demands of multiplatform remote sensing (RS) image interpretation. However, the significant differences in data distribution across various RS platforms present a great challenge in balancing the cloud’s centralized processing capabilities with the local interpretation abilities of different terminals. To address this challenge, we propose a terminal-cloud cross-domain collaborative (TeCCo) framework that inherits the efficiency advantages of multiple platforms while ensuring high-accuracy interpretation of diverse data distributions from different terminals. First, the dual classifier co-learning (DCCL) module is designed to enhance cloud robustness. By combining a multilayer perceptron for instance-level classification and a graph convolutional network (GCN) for feature-level aggregation, it achieves mutual supervision and improves feature alignment across different data distributions. Second, the hypernetwork personalization (HNP) module is introduced to generate personalized classifier parameters for each terminal with little fine-tuning cost, allowing terminals to maintain their uniqueness while benefiting from the generalization advantages of collaborative training. Finally, a data-assisted progressive inference mechanism is proposed to enhance accuracy by jointly clustering the features transmitted from terminals and the features of supervised data in the cloud. Extensive experiments demonstrate that TeCCo effectively addresses data distribution challenges, enhancing both the generalization of the cloud model and the personalization of terminal models, achieving state-of-the-art (SOTA) performance in cross-domain and multiplatform RS image classification.

CuW composites are widely used in high voltage transmission, electronic information, aerospace and other cutting-edge fields. At present, the preparation methods of CuW composites based on powder metallurgy have the defects of uneven microstructure and low density. Reducing the size of tungsten particles in the CuW composites can significantly improve the microstructure uniformity and density. In this paper, an innovative idea for regulating the microstructure of CuW composites by aluminothermic coupling with magnesiothermic reduction was proposed. The thermodynamics and dynamics of the reaction system for preparation of CuW composites by this method were studied, and the microstructure of CuW composites were systematically analysed and evaluation. The researches show that the inclusion in CuW prepared by aluminothermic reduction was Al2O3, and the inclusion in CuW prepared by aluminothermic coupling with magnesiothermic reduction was MgO·Al2O3. The addition of magnesium to the reducing agent had an obvious refining effect on the tungsten particles. The mechanism was that magnesium was converted into magnesium vapor during the rapid heating process of the system, and the gas-solid, gas-liquid-solid reaction occurred with tungsten oxide to generate smaller tungsten particles. With an increase of magnesium content, the average size of tungsten particles in the microstructure of CuW gradually decreased from 2.38 μm to 0.82 μm, and the microstructure uniformity increased from 56.26% to 76.96%.

Purpose: The aim of this study was to observe the influence of differential nutritional status on bone age (BA) change according to body mass index (BMI) and analyze the risk of advanced bone age in children with overweight and obesity. Methods: In total 23,305 children from Beijing were included in this cross-sectional study. Childhood overweight and obesity were defined according to the China and World Health Organization growth criteria. The data were analyzed by the R coding platform version 4.3.0. Results: Under the Chinese criteria, 29%, 15%, and 4% of boys with overweight; 33%, 33%, and 3% of boys with obesity; 39%, 25%, and 2% of girls with overweight; and 37%, 42% and 1% of girls with obesity had advanced, significantly advanced and delayed BA, respectively. After adjustment, overweight (odds ratio, 95% confidence interval, P under the Chinese criteria: 2.52, 2.30–2.75, &lt;0.001 and 4.54, 4.06–5.09, &lt;0.001) and obesity (4.31, 3.85–4.82, &lt;0.001 and 14.01, 12.39–15.85, &lt;0.001) were risk factors for both advanced BA and significantly advanced BA. Conclusions:: Different nutritional statuses lead to differences in children’s BA development. Children with overweight and obesity have higher rates of advanced BA under two growth criteria, and girls have more advances in BA than boys do. Overweight and obesity are risk factors for advanced BA.

Humans possess the remarkable ability to perceive the intricate world by integrating multiple senses. However, the challenge of enabling humanoid robots to achieve multimodal sensing and fine recognition of metallic materials persists. In this study, we propose a flexible tactile sensor that mimics the sensory patterns of human skin, which is assembled by a flexible electromagnetic coil that is engraved on the surface of a polyimide substrate and porous MXene/CNT aerogel. This sensor is capable of detecting pressure, temperature, and inductive signals with minimal interference via three disparate response mechanisms of the piezoresistive sensing, the thermoelectric principle, and the electromagnetic induction effect, allowing the device with the abilities of sensing grasp forces and selectively identifying ferromagnetic and nonferromagnetic metals, which has a high accuracy rate of 99.2% in distinguishing mixed metals with varying ratios based on the fusion algorithm of multimodal sensory data. Further, the sensor was integrated on a humanoid robotic hand to demonstrate its recognition capacity of objects used in a kitchen setting and a simulated scenario of mineral exploration, achieving a remarkable ultrafine accuracy of 100% in distinguishing 16 common metal products. These findings will pave the way for humanoid robots to attain heightened levels of perception and recognition.

To enhance the capability of electromagnetic acoustic transducer (EMAT) in identifying defect types, this study employs the Nelder–Mead algorithm to optimize a dual-wave probe design for a rectangular sandwich structure. By exploiting the differential reflection intensities of shear and longitudinal waves on various defect types, the Grey relational analysis is utilized to analyze the echo amplitudes, facilitating the determination of defect types. Based on finite-element simulation, the design and optimization of the probe were accomplished. Simulation results demonstrate that the optimized probe’s energy conversion efficiency has increased by 137.5% compared to traditional designs. Comparative real measurements between the optimized and traditional probes confirm the high transduction efficiency of the designed structure. Twenty sets of defects, categorized into three types, were employed to evaluate the recognition capability, achieving a 100% identification rate. This offers an effective strategy to improve the recognition accuracy of defect types in electromagnetic ultrasonic detection.

In this article, an online current optimization-based fault-tolerant (FT) control is proposed to improve the FT capability of standard permanent magnet synchronous machine (PMSM) drive with open-phase fault (OPF) and open-switch fault (OSF). In the proposed FT control, the torque ripple, overcurrent endurance, and copper loss are considered to optimize the FT current reference for OPF and OSF. The optimized current reference can be obtained online by calculating the average copper loss in the OPF and OSF FT operation. By using the optimized current reference, the current tracking error can be eliminated, and a good balance between torque ripple and copper loss can be fulfilled. In this way, the torque output capability can be improved after the average copper loss is restricted. The effectiveness of the proposed FT control has been verified by experiments.

Soft tissue seal around the transmucosal region of dental implants is crucial for shielding oral bacterial invasion and guaranteeing the long-term functioning of implants. Compared with the robust periodontal tissue barrier around a natural tooth, the peri-implant mucosa presents a lower bonding efficiency to the transmucosal region of dental implants, due to physiological structural differences. As such, the weaker soft tissue seal around the transmucosal region can be easily broken by oral pathogens, which may stimulate serious inflammatory responses and lead to the development of peri-implant mucositis. Without timely treatment, the curable peri-implant mucositis would evolve into irreversible peri-implantitis, finally causing the failure of implantation. Herein, this review has summarized current surface modification strategies for the transmucosal region of dental implants with improved soft tissue bonding capacities (e.g., improving surface wettability, fabricating micro/nano topographies, altering the surface chemical composition and constructing bioactive coatings). Furthermore, the surfaces with advanced soft tissue bonding abilities can be incorporated with antibacterial properties to prevent infections, and/or with immunomodulatory designs to facilitate the establishment of soft tissue seal. Finally, we proposed future research orientations for developing multifunctional surfaces, thus establishing a firm soft tissue seal at the transmucosal region and achieving the long-term predictability of dental implants.

A novel process was proposed for synergistic extraction and separation of valuable elements from high-alumina fly ash. A thermodynamic analysis revealed that to achieve effective carbochlorination, it is crucial to conduct carbochlorination of the fly ash within the temperature range from 700 to 1000 °C. The experimental results demonstrated that under the optimal conditions, the carbochlorination efficiency for Al, Si, Ca, Ti, and Mg exceeded 81.18%, 67.62%, 58.87%, 82.15%, and 59.53%, respectively. The XRD patterns indicated that Al and Si in the mullite phase (Al6Si2O13) were chlorinated during the carbochlorination process, resulting in the formation of mullite mesophases (Al4.75Si1.25O9.63and Al1.83Si1.08O4.85). After the carbochlorination process, Al was accumulated as AlCl3in the condenser, while SiCl4and TiCl4were enriched in the exhaust gas, and CaCl2, MgCl2, and unreacted oxides remained in the residue for further recycling.

Supplemental Digital Content is Available in the Text.In this study, intensive viral load monitoring and metagenomic sequencing were performed to acute retinal necrosis cases during antiviral treatment. The plateau phase of viral load curve correlated well with the remission of active necrotizing lesions. Loss-of-function variations in viral ribonucleotide reductase gene led to impaired virulence of the virus.

As the inevitable mode of the future intelligent transportation system, VANET still exists vehicle access authentication computational overhead, handover authentication inefficiency in the context of continuous development, simply using the traditional VANET architecture has been unable to adapt to the new complexity. Therefore, a hybrid blockchain-based privacy-preserving authentication scheme is proposed. Instead of using a single chain, the scheme combines the consortium and private chains, retaining the decentralization and high security of the consortium chain while leveraging the advantages of faster transactions, lower costs, and higher privacy in the private chain. Importantly, short signature technology and homomorphic encryption technology are proposed to further improve the efficiency of entity communication and protect the delivery of private data, respectively, while pre-authentication mechanism is used to further accelerate the cross-domain authentication of vehicles. The security analysis demonstrates the good privacy protection and attack resistance of this scheme. In addition, performance simulations and evaluations show that the proposed scheme requires the least computational and communication overhead compared to other schemes. It also performs better in terms of authentication delay and packet loss rate. Finally, the availability of the proposed scheme is explained through throughput and transaction cost analysis.

The evolution and mutation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are urgent concerns as they pose the risk of vaccine failure and increased viral transmission. However, affordable and scalable tools allowing rapid identification of SARS-CoV-2 variants are not readily available, which impedes diagnosis and epidemiological surveillance. Here we present a colorimetric nucleic acid assay named MARVE (multiplexed, preamplification-free, single-nucleotide-resolved viral evolution) that is convenient to perform and yields single-nucleotide resolution. The assay integrates nucleic acid strand displacement reactions with enzymatic amplification to colorimetrically sense viral RNA using a metal ion-incorporated DNA probe (TEprobe). We provide detailed guidelines to design TEprobes for discriminating single-nucleotide variations in viral RNAs, and to fabricate a test paper for the detection of SARS-CoV-2 variants of concern. Compared with other nucleic acid assays, our assay is preamplification-free, single-nucleotide-resolvable and results are visible via a color change. Besides, it is smartphone readable, multiplexed, quick and cheap ($0.30 per test). The protocol takes ~2 h to complete, from the design and preparation of the DNA probes and test papers (~1 h) to the detection of SARS-CoV-2 or its variants (30–45 min). The design of the TEprobes requires basic knowledge of molecular biology and familiarity with NUPACK or the Python programming language. The fabrication of the origami papers requires access to a wax printer using the CAD and PDF files provided or requires users to be familiar with AutoCAD to design new origami papers. The protocol is also applicable for designing assays to detect other pathogens and their variants.

This study delves the impact of winding phase shift on the electromagnetic characteristics of operation with fault tolerance in a dual winding permanent magnet motor (DWPMSM) experiencing faults due to inter-turn short circuits. Firstly, the analytical expressions of fault inductance and short-circuit circulating current (SCCC) for a 12-slot/10-pole DWPMSM are derived based on the theory of winding function. Secondly, finite element analysis simulation models are constructed for the purpose of comparing and analyzing the amplitude of SCCC. This analysis extends to the examination of torque characteristics in the DWPMSM across various phase shift angles and speeds. The investigation reveals that the winding with a 30° phase shift exhibits the least self-inductance, while the self-inductance of the 0° phase-shift winding and the 60° phase-shift winding is larger. The amplitude of the SCCC for a 30° winding configuration is the largest. Besides, when n = 500 rpm, the torque characteristics of the 30° winding configuration are the best. Nonetheless, when n = 2500 rpm, the torque performance degrades as the count of short-circuit turns rises. Finally, the prototype is tested to verify the short circuit fault characteristics of the DWPMSM.

Rice false smut, caused by Ustilaginoidea virens, is a devastating disease that greatly reduces rice yield and quality. However, controlling rice false smut disease is challenging due to the unique infection mode of U. virens. Therefore, there is a need for early diagnosis and monitoring techniques to prevent the spread of this disease. Lateral flow strip-based recombinase polymerase amplification (LF-RPA) overcomes the limitations of current U. virensdetection technologies, which are time-consuming, require delicate equipment, and have a high false-positive rate. In this study, we used a comparative genomics approach to identify Uv_3611, a specific gene of U. virens, as the target for the LF-RPA assay. The designed primers and probe efffectively detected the genomic DNA (gDNA) of U. virensand demonstrated no cross-reactivity with related pathogens. Under optimal conditions, the LF-RPA assay demonstrated a sensitivity of 10 pg of U. virensgDNA. Additionally, by incorporating a simplified PEG-NaOH method for plant DNA extraction, the LF-RPA assay enabled the detection of U. virensin rice spikelets within 30 min, without the need for specialized equipment. Furthermore, the LF-RPA assay successfully detected U. virensin naturally infected rice and seed samples in the field. Therefore, the LF-RPA assay is sensitive, efficient, and convenient, and could be developed as a kit for monitoring rice false smut disease in the field.

While metal halide light-emitting diodes (PeLEDs) with unique optoelectronic properties are promising emitters for next-generation displays, their performance degrades rapidly due to severe ion migration during continuous operation, especially at high voltages. Here, we realize highly stable PeLEDs by designing inorganic dielectric/perovskite semiconductor emitter/organic dielectric sandwiched nanostructures to mitigate ion migration via regulating the electric field distribution. The bilateral cesium carbonate (Cs2CO3) and tetraoctylammonium bromide (TOAB) thin interlayers can not only largely reduce the voltage imposed on the perovskite layer by serving as series resistors and, thus, mitigate the ion migration but also regulate the charge carrier transfer to improve the radiative recombination efficiency. In addition, the underneath inorganic Cs2CO3film also provides more heterogeneous nucleation sites for growing high-crystallinity perovskite crystals, while the atop TOAB with bifunctional groups (organic amino and Br–ions) refines the morphology and enhances the optical properties of the perovskite film. As a result, efficient and stable green PeLEDs based on such an optoelectric-tunable nanostructure exhibit extremely slow efficiency decay as the applied voltage increases, and the external quantum efficiencies were maintained over 10% at a high bias up to 20 V.

Prediction is a vital component of motion planning for autonomous vehicles (AVs). By reasoning about the possible behavior of other target agents, the ego vehicle (EV) can navigate safely, efficiently, and politely. However, most of the existing work overlooks the interdependencies of the prediction and planning module, only connecting them in a sequential pipeline or underexploring the prediction results in the planning module. In this work, we propose a framework that integrates the prediction and planning module with three highlights. First, we propose an ego-conditioned model for causal prediction, with the introduced edge-featured graph transformer model, the impact the ego future maneuver poses to the target vehicles is demonstrated. Second, we develop a motion planner based on ‘dynamic voxels’ in the spatio-temporal domain, enabling the time-to-collision criterion evaluation and the optimal trajectory generation in continuous space. Third, the prediction and planning modules are coupled in a closed-loop and efficient form. Specifically, taking each maneuver as a cluster, representative trajectory primitives are generated for conditional prediction, and conversely, prediction results are used to score the primitives as guidance, which alleviates the duplicated callback of the prediction module. The simulations are conducted in overtaking, merging, unprotected left turns, and also scenarios with imperfect social behaviors. The comparison studies demonstrate the better safety assurance and efficiency of the proposed model, and the ablation experiments further reveal the effectiveness of the new ideas.

5052 Al and carbon fiber-reinforced polyamide 6 composite (CF-PA6) were jointed via ultrasonic welding with the assistance of temperature compensation device. The effects of the ultrasonic welding time and temperature compensation on the microstructure and mechanical properties of the joints were investigated. Through analysis of the wettability and fluidity of the molten carbon fiber-reinforced thermoplastic composites (CFRTP), the bonding mechanism and failure path of Al/CFRTP were clarified. The results show that under the conditions of temperature compensation of 220 °C and welding time of 1500 ms, the joint strength of the two components reaches 2480.4 N, which is 813.6% higher than that of Al/CFRTP components obtained at room temperature. Overall, temperature compensation prolonged the wetting time of molten CFRTP on the aluminum alloy surface. When the fluidity and wettability were coordinated with each other, a high-quality joint was formed. In addition, the ultrasonic welding process of Al/CFRTP mainly relies on “physical adsorption,” “diffusion effect,” and “mechanical locking effect” to achieve sufficient bonding, and the effect of hydrogen bonding is weak.

The development and investigation of innovative nanomaterials stand poised to advance technological progress and meet the contemporary demand for efficient, environmentally friendly, and intelligent products. Hollow nanostructures (HNS), characterized by their hollow architecture, exhibit diverse properties such as expansive specific surface area, low density, high drug-carrying capacity, and customizable structures. These elaborated structures, encompass nanospheres, nanoboxes, rings, cubes, and nanowires, have wide-ranging applications in biomedicine, materials chemistry, food industry, and environmental science. Herein, HNS and their cutting-edge synthesis methods, including solvothermal methods, liquid-interface assembly methods, and the self-templating methods are discussed in-depth. Meanwhile, the potential applications of HNS in food and biomedicine such as food packing, biosensor, and drug delivery over the past three years are summarized, together with a prospective view of future research directions and challenges. This review will offer new insights into designing next generation of hollow nanomaterials for food and biomedicine applications.

Phenylethanoid glycosides (PhGs) are naturally occurring glycosides derived from plants with various biological activities. Glycosyltransferases catalyze the production of PhGs from phenylethanols via a transglycosylation reaction. The low activity and stability of glycosyltransferase limit its industrial application. An ancestral glycosyltransferase, UGTAn85, with heat resistance, alkali resistance, and high stability was resurrected using ancestral sequence reconstruction technology. This enzyme can efficiently convert phenylethanols to PhGs. The optimal reaction temperature and pH for UGTAn85 were found to be 70 °C and pH 10.0, respectively. This study employed a combination of structure-guided rational design and co-evolution analysis to enhance its catalytic activity. Potential mutation sites were identified through computer-aided design, including homology modeling, molecular docking, Rosetta dock design, molecular dynamics simulation, and co-evolution analysis. By targeted mutagenesis, the UGTAn85 mutant Q23E/N65D exhibited a 2.2-fold increase in enzyme activity (11.85 U/mg) and elevated affinity (Km= 0.11 mM) for 2-phenylethanol compared to UGTAn85. Following a fed-batch reaction, 36.16 g/L 2-phenylethyl-β-d-glucopyranoside and 51.49 g/L salidroside could be produced within 24 h, respectively. The findings in this study provide a new perspective on enhancing the stability and activity of glycosyltransferases, as well as a potential biocatalyst for the industrial production of PhGs.

An interphase migration and enrichment model of lead and zinc during molten copper slag depletion was established. The occurrence of various components in copper slag was predicted using sulfur−oxygen potential calculations and confirmed through high-temperature experiments. The recovery rate of copper can reach 90.13% under the optimal conditions of 1200 °C, an iron to silicon mass ratio of 1.0, 3 wt.% ferrous sulfide, and a duration of 45 min. Lead (54.07 wt.%) and zinc (17.42 wt.%) are found in the flue dust as lead sulfate, lead sulfide, and zinc oxide, while copper matte contains lead (14.44 wt.%) and zinc sulfide (1.29 wt.%). The remaining lead and zinc are encapsulated as oxides within the fayalite phase.

Graphical Abstract:

434 stainless steel coatings have been applied T6061 alloy using High-Velocity Oxygen Fuel (HVOF) as a deposition technique for surface performance improvement. The relationship between the coating's deposition characteristics of thickness, homogeneity, porosity, and hardness and the spraying parameters of mainly the number of sprayed-layers and spraying distance was revealed. The coating's fracture behaviors was further studied using three-point bending and digital image correlation (DIC) technology, which allows the observation of the crack progression and record the stress distribution on the coatings. Results showed that the crack progression always occur at the oxides between the different sprayed layers or surrounding semi-melted feedstock particles, the crack progression mode is mainly depending on the number and location of oxides in the coating. Then, the crack progression mainly continued through the interface between sprayed layers while the oxide content approach or exceed a critical value of 12 %. Finally, a model for the coating fracture mechanism was established to explain the interface bonding performance between the coating and the substrate.

In contrast to the traditional avatar creation pipeline which is a costly process, contemporary generative approaches directly learn the data distribution from photographs. While plenty of works extend unconditional generative models and achieve some levels of controllability, it is still challenging to ensure multi-view consistency, especially in large poses. In this work, we propose a network that generates 3D-aware portraits while being controllable according to semantic parameters regarding pose, identity, expression and illumination. Our network uses neural scene representation to model 3D-aware portraits, whose generation is guided by a parametric face model that supports explicit control. While the latent disentanglement can be further enhanced by contrasting images with partially different attributes, there still exists noticeable inconsistency in non-face areas when animating expressions. We solve this by proposing a volume blending strategy in which we form a composite output by blending dynamic and static areas, with two parts segmented from the jointly learned semantic field. Our method outperforms prior arts in extensive experiments, producing realistic portraits with vivid expression in natural lighting when viewed from free viewpoints. It also demonstrates generalization ability to real images as well as out-of-domain data, showing great promise in real applications.

Ceramic–polymer composite solid electrolytes (CSEs) have attracted great attention by combining the advantages of polymer electrolytes and inorganic ceramic electrolytes. Herein, Li10GeP2S12(LGPS) particles are incorporated into poly(ethylene oxide) (PEO)-based reversibly interlocked polymer networks (RILNs) derived from the topological rearrangement of two PEO networks cross-linked by reversible imine bonds and disulfide linkages. A series of highly ionic conductive, self-healing CSEs are obtained accordingly. The interlocking architecture successfully inhibits PEO crystallization, increasing the amorphous phase for Li ion transportation, and stabilizes the conductive pathways of LGPS particles by its unique confinement effect. Meanwhile, the LGPS particles cooperate with the RILN matrix, forming a filler–polymer interfacial phase for additional Li ion transportation and strengthening and toughening the resultant CSEs via the strong intermolecular Li+–O2–interactions. Furthermore, the dynamic characteristics of the included reversible bonds ensure a multiple intrinsic self-healing capability. Consequently, the CSEs containing 15 wt % LGPS deliver a high ionic conductivity (1.06 × 10–3S cm–1) and high Li ion transference number (∼0.6) at 25 °C, a wide electrochemical stability window (>4.9 V), good mechanical properties (0.63 MPa, 377%), and a stable CSE/Li anode interface. The integrated Li/CSE/LiFePO4battery exhibits a specific discharge capacity of 110.8 mAh g–1at 1 C (25 °C) and a capacity retention of 76.9% after 200 cycles. Thanks to the healability, the damaged CSEs can regain the structural integrity, ion conductive capability, and cycling performance of the assembled cells. The present work provides an effective strategy to fabricate CSEs for lithium metal batteries that are workable at ambient temperature.

Air pollution exposure has been linked to a variety of adverse health outcomes among minors; yet little is known about the associated health inequity across regions and schools. Here, we assessed the unequal health burden linked to particulate matter exposure among minors of 10,358 schools in China through 12,439,232 individual health records. Our findings highlight the persistent health risks with superlinear concentration–response patterns and following inverted U-shaped risk trends, that each 10 μg/m3increase in PM2.5exposure resulted in 4.1% (3.9–4.2%) additional school absenteeism risk. Compared to urban well-built schools, minors in rural poor-built schools experienced significantly higher exposure and slower rate of risk reduction and had over 80.0% less medical resources while bearing 145.2% of the health burden. Disparities in pollution exposure, built environment, and resource allocation are intertwined to shape the health inequity pattern, especially between rural and urban schools. These findings underscore the urgency for persistent efforts aimed at disadvantaged schools to reduce pollution exposure and equitably distribute social resources, ultimately securing an impartial health-centered education for minors.