Search

Sodium-ion batteries (SIBs) are regarded as cost-effective alternatives or competitors to lithium-ion batteries for large-scale electric energy storage applications. However, their development has been hindered by the high cost of hard carbon (HC) anodes and poor electrochemical performance. To enhance the sodium storage capacity and rate performance of HC, this study accelerated the electrochemical performance of coconut-shell-derived HC anodes for SIBs through N/O codoping using ball milling and pyrolysis. Experimental results demonstrate that the simultaneous introduction of N and O generates a synergistic effect, increasing the surface oxygen-containing functional groups, defects, and interlayer spacing of coconut-shell-derived HC through the codoping of light elements. The excellent strategy has increased the slope capacity and platform capacity of HC, and the synergistic modification of N/O has increased its reversible specific capacity from 272 to 343 mA h g–1(30 mA g–1), with a retention rate of approximately 92.1% after 100 cycles. In addition, it also exhibits an excellent rate performance, reaching 178 mA h g–1at 1500 mA g–1. In summary, this study presents an effective strategy for modifying biomass-derived HC.

In this study, we addressed the poor cycling and rate performance of LiNiO2, a material with ultrahigh nickel content considered a strong contender for high-energy-density lithium-ion battery cathodes. We introduced nano-Al2O3during the lithiation process to achieve dual modified material through bulk phase element doping and in situ LiAlO2coating. Comparison revealed notable improvements in the modified materials. In particular, LiNi0.99Al0.01O2maintained a capacity retention rate of 73.1% after 300 cycles in a long-cycle test at 0.5C current density, outperforming the undoped material. In rate performance tests, the doped samples consistently exhibited higher discharge-specific capacities than that of the undoped counterpart. Notably, at a high current density of 5C, LiNi0.99Al0.01O2exhibited a discharge-specific capacity of 101.75 mAh g–1. The results indicate that an appropriate amount of Al doping can effectively stabilize the layered structure of the cathode material and delay the irreversible phase transition from H2 to H3. Further, Al doping facilitates the formation of a LiAlO2coating on the surface of the particles. This coating acts as a fast-ion conductor, enhancing the transport of lithium ions and reducing the erosion of the active material by the electrolyte.

Currently, little is known about the characteristics of oxide films on Ti alloys exposed to the secondary circuit water environment of small modular reactors (SMRs). In this study, multiple microstructural characterization techniques were employed to meticulously characterize the oxide film characteristics of the TA16 alloy after 6000 h and 8000 h of exposure to a simulated SMR secondary circuit water environment. The results indicate that the oxide films on the 6000 h specimen are composed of a microcrystalline anatase TiO2interior layer and a coarse-grained anatase TiO2exterior layer, while the oxide film on the 8000 h specimen typically consists of a microcrystalline anatase TiO2inner layer, an NiFe2O4middle layer, and a coarse-grained anatase TiO2outer layer. As the corrosion time is extended to 8000 h, the presence of NiFe2O4oxide particles can be attributed to oxide deposition by the 316L stainless steel autoclave used in the corrosion experiments, which results in the migration of Ni and Fe ions onto the surface of the Ti alloy.

The oxidation products formed on ferritic/martensitic (F/M) steel exposed to oxygen-saturated lead-bismuth eutectic (LBE) at 550 °C for 1000 h were investigated using various characterizations. The results indicate that the corrosion products consist of three distinct layers from the inside to the outside: the inner oxidation zone (IOZ), a middle oxide layer, and the growth front facing LBE. In the IOZ, although O has penetrated the entire oxidation layer, the martensite laths and ferrite grains remain visible. However, significant segregation of Cr and O along the laths and grain boundaries has occurred, resulting in the formation of strip-shaped Cr2O3particles. In the matrix adjacent to the IOZ, Cr atoms have segregated at the grain boundaries and martensite laths, forming Cr-rich regions, while O atoms have not yet infiltrated. During the growth of Fe3O4grains, the priority formed strip-shaped Cr2O3particles are pushed toward the corrosion front until they detach from the F/M steel and disperse into the LBE, resulting in nearly pure Fe3O4grains in the middle layer. The gradient three-layer structure of the oxidation product is closely associated with the segregation of Cr and the gradient distribution of oxygen partial pressure (PO2).

Eutectic high-entropy alloys (EHEAs) represent attractive candidate materials for overcoming the strength-ductility trade-off, which can be enhanced through the directional alignment of the lamellar structure along the loading direction. Here, we put forward a new route to optimize the strength-ductility synergy without orientation dependence. Through a combination of severe plastic deformation and annealing, we convert the initially lamellar structure into a dual-phase structure comprised of ultrafine equiaxed grains. The significant grain refinement improves the yield strength from 703 MPa to 1199 MPa without sacrificing any ductility. During deformation, the localized softening resistance of the achieved dual-phase microstructure avoids necking, and the intrinsic microcrack-arresting mechanism effectively improves the fracture resistance. Grain boundaries and phase boundaries provide nucleation sites for dislocations and restrict dislocation transfer while the strain incompatibility is accommodated by geometrically necessary dislocations. This work demonstrates that dual-phase alloys comprised of ultrafine equiaxed grains provide a pathway for strengthening without loss of ductility.

Ultrasensitive analysis of organic molecules is crucial for various fundamental research and applications. State-of-the-art techniques for this purpose can achieve detection limits of several hundred ppq (parts-per-quadrillion), while a higher sensitivity is pursued constantly. To achieve this goal, we develop femtosecond laser assisted chemical ionization for mass spectrometry. This technique combines the advantages of femtosecond laser ionization and chemical ionization, either of which enables subppt (parts-per-trillion) mass spectrometry analysis of organic molecules. The results demonstrate that the developed ionization technique, when employed in mass spectrometry, can surpass femtosecond laser ionization by more than 3 orders of magnitude in sensitivity, while still maintaining good versatility and the ability to work under ambient conditions. This work paves the way for subppq analysis of organic molecules in gas phase and even in ambient environments, which can open up new research fields for trace substance analysis in atmospheric environment, clinical diagnosis, biomedical studies, etc.

As a soft material with biocompatibility and stimulation response, ionic conductive hydrogel‐based wearable strain sensors show great potential across a wide spectrum of engineering disciplines, but their mechanical toughness is limited in practical applications. In this study, freeze‐thawing techniques were utilized to fabricate double‐network hydrogels of poly(vinyl alcohol)/polyacrylamide (PVA/PAM) with both covalent and physical cross‐linking networks. These double‐network hydrogels demonstrate excellent mechanical performance, with an elongation at break of 2253% and tensile strength of 268.2 kPa. Simultaneously, they also display a high sensitivity (Gage factor, GF = 2.32 at 0%–200% strain), achieve a rapid response time of 368 ms without the addition of extra conductive fillers or ions, stable signal transmission even after multiple cycles, and fast response to human motion detection.

Rheumatoid arthritis (RA) is a complex inflammatory disease of the joints, which is often accompanied by degeneration of articular cartilage and bone erosion, seriously affecting the quality of life and psychological state of patients. RA is difficult to be cured completely, and currently the main purpose of relief is through the use of anti-inflammatory and antirheumatic drugs, hormones, and biological agents. Tofacitib is a new type of small molecule inhibitor, which has a good effect in the treatment of RA. The current direct drug delivery method has serious side effects caused by the systemic distribution of the drug, so there is a need to develop an intelligent drug delivery system to realize precise treatment. In this work, tofacitib, gallic acid, targeted molecule folic acid, and Fe(III) were selected to assemble a novel type of artificial controllable nanodrug GF-TF. The self-photoacoustic/magnetic resonance imaging (self-PA/MRI) monitored the enrichment of GF-TF in the lesion in real-time, and artificially regulated the addition of deferoxamine (DFO) at the optimal enrichment. DFO strongly chelates Fe(III) in GF-TF and causes its structure to disintegrate gradually, and the self-PA/MRI signal of GF-TF became weaker while tofacitib began to be released, thus realizing the precise and artificially controlled release of the drug under the guidance of imaging. This nanodrug not only achieves efficient aggregation of drugs in inflamed joints, but also achieves real-time monitoring and precise control of drug release through self-PA/MRI, providing a new strategy for the precise treatment of RA.

AbstractAs a pivotal node in modulating various cell behaviors, Rho-associated kinase-1 (ROCK1) has attracted significant attention as a promising therapeutic target in a variety of diseases. Benzamide has been widely reported as a ROCK1 inhibitors in recent years. To better understand its pharmacological properties and to explore its potential inhibitors, a series of ROCK1 inhibitors derived from N-methyl-4-(4-pyrazolidinyl) benzamides (MPBs) were investigated by using three-dimensional quantitative structure-activity relationship (3D-QSAR) models, pharmacophore models, molecular docking, and molecular dynamics (MD) simulation. The comparative Molecular Field Analysis (CoMFA) model (q2= 0.616, R2= 0.972, ONC = 4, and r2pred= 0.983) and the best Comparative Molecular Similarity Indices Analysis (CoMSIA) model (q2= 0.740, R2= 0.982, ONC = 6, and r2pred= 0.824) exhibited reliable predictability with satisfactory validation parameters. In the subsequent virtual screening, VS03 and VS05 were identified to have superior predicted activities and higher docking scores, meanwhile they demonstrated to be reasonably stable in the binding pocket through MD simulations. These results provide a significant theoretical direction for the rational design and development of novel ROCK1 inhibitors.Communicated by Ramaswamy H. Sarma

Rapidly obtaining the coverage characteristics of leaching solution in In-situ Leaching Area of Sandstone Uranium Mines is a necessary condition for optimizing well locations reasonably. In the presented study, the improved algorithm of the Fast Marching Method (FMM) was studied for rapidly solving coverage characteristics to replace the groundwater numerical simulator. First, the effectiveness of the FMM was verified by simulating diffusion characteristics of the leaching solution in In-situ Leaching Area. Second, based on the radial flow pressure equation and the interaction mechanism of the front diffusion of production and injection well flow field, an improved FMM which is suitable for In-situ Leaching Mining, was developed to achieve the co-simulation of production and injection well. Finally, the improved algorithm was applied to engineering practice to guide the design and production. The results show that the improved algorithm can efficiently solve the coverage characteristics of leaching solution, which is consistent with those obtained from traditional numerical simulators. In engineering practice, the improved FMM can be used to rapidly analyze the leaching process, delineate Leaching Blind Spots, and evaluate the rationality of well pattern layout. Furthermore, it can help to achieve iterative optimization and rapid decision-making of production and injection well locations under large-scale mining area models.

Hot-carrier transistors are a class of devices that leverage the excess kinetic energy of carriers. Unlike regular transistors, which rely on steady-state carrier transport, hot-carrier transistors modulate carriers to high-energy states, resulting in enhanced device speed and functionality. These characteristics are essential for applications that demand rapid switching and high-frequency operations, such as advanced telecommunications and cutting-edge computing technologies1–5. However, the traditional mechanisms of hot-carrier generation are either carrier injection6–11or acceleration12,13, which limit device performance in terms of power consumption and negative differential resistance14–17. Mixed-dimensional devices, which combine bulk and low-dimensional materials, can offer different mechanisms for hot-carrier generation by leveraging the diverse potential barriers formed by energy-band combinations18–21. Here we report a hot-emitter transistor based on double mixed-dimensional graphene/germanium Schottky junctions that uses stimulated emission of heated carriers to achieve a subthreshold swing lower than 1 millivolt per decade beyond the Boltzmann limit and a negative differential resistance with a peak-to-valley current ratio greater than 100 at room temperature. Multi-valued logic with a high inverter gain and reconfigurable logic states are further demonstrated. This work reports a multifunctional hot-emitter transistor with significant potential for low-power and negative-differential-resistance applications, marking a promising advancement for the post-Moore era.

High-frequency power converters are gaining increasing attention and popularity due to the high power density and high efficiency demand in electric vehicles (EVs). In this condition, high-frequency current sensing accuracy is essential. However, existing current sensing methods cannot meet the needs in terms of low power loss, small size, being contactless, or large bandwidth. This article proposes a new current sensing technique with bandwidth enhancement. First, a skin effect model for commonly used rectangular conductors is investigated. Then, variations of out-of-plane and in-plane magnetic fields caused by skin effects are analyzed theoretically. It reveals that measuring out-of-plane magnetic fields shows a larger bandwidth than measuring in-plane magnetic fields. Subsequently, a circle trace for current sensing is proposed. The corresponding simulation results illustrate necessary considerations in a circle trace-based printed circuit board (PCB) design. Then, the current responses of a proposed circle trace and a conventional straight trace are compared in experiments. In experiments, the step current response has an average improvement of 48%, and the measurement bandwidth is extended from 10 to 200 kHz using the circle trace method. These experimental results confirm that the circle trace shows better performances. Thus, the proposed method is validated for application in high-frequency current sensing.

In recent years, analog circuits have received extensive attention and are widely used in many emerging applications. The high demand for analog circuits necessitates shorter circuit design cycles. To achieve the desired performance and specifications, various geometrical symmetry constraints must be carefully considered during the analog layout process. However, the manual labeling of these constraints by experienced analog engineers is a laborious and time-consuming process. To handle the costly runtime issue, we propose a graph-based learning framework to automatically extract symmetric constraints in analog circuit layout. The proposed framework leverages the connection characteristics of circuits and the devices’ information to learn the general rules of symmetric constraints, which effectively facilitates the extraction of device-level constraints on circuit netlists. The experimental results demonstrate that compared to state-of-the-art symmetric constraint detection approaches, our framework achieves higher accuracy and F1-score.

Overtaking is a common driving behaviour used by human drivers while driving. Therefore, the decision on overtaking is very important in the automatic driving decision. To be able to improve the passing efficiency of intelligent vehicles, it is crucial to be able to interact with oncoming vehicles with different driving styles. An overtaking decision needs to be adapted to the situation where the vehicle being overtaken is potentially stationary or moving. Therefore, this paper proposes an overtaking decision method based on potential conflict area based on the requirements. Firstly, the planning method for each stage is given, and the generation method of the potential conflict area is proposed. Second, the interaction process between the host vehicle and the opposite oncoming vehicle is modelled by a dynamic game based on the potential conflict area. A driving style assessment method for oncoming vehicles based on potential conflict area is proposed. Thirdly, the priority of passing the potential conflict area of multiple oncoming vehicles is divided to correct the speed planning in the waiting and the speed payoff function in the game. Finally, the overtaking decision is simulated and validated by Virtual Test Drive.

Detection of circulating tumor DNA (ctDNA) in liquid biopsy is of great importance for tumor diagnosis but difficult due to its low amount in bodily fluids. Herein, a novel ctDNA detection platform is established by quantifying DNA amplification by-product pyrophosphate (PPi) using a newly designed bivariable lanthanide metal–organic framework (Ln-MOF), namely, Ce/Eu-DPA MOF (CE-24, DPA = pyridine-2,6-dicarboxylic acid). CE-24 MOF exhibits ultrafast dual-response (fluorescence enhancement and enzyme-activity inhibition) to PPi stimuli by virtue of host–guest interaction. The platform is applied to detecting colon carcinoma-related ctDNA (KARS G12D mutation) combined with the isothermal nucleic acid exponential amplification reaction (EXPAR). ctDNA triggers the generation of a large amount of PPi, and the ctDNA quantification is achieved through the ratio fluorescence/colorimetric dual-mode assay of PPi. The combination of the EXPAR and the dual-mode PPi sensing allows the ctDNA assay method to be low-cost, convenient, bioreaction-compatible (freedom from the interference of bioreaction systems), sensitive (limit of detection down to 101fM), and suitable for on-site detection. To the best of our knowledge, this work is the first application of Ln-MOF for ctDNA detection, and it provides a novel universal strategy for the rapid detection of nucleic acid biomarkers in point-of-care scenarios.

Although in vitroneuronal network models hold great potential for advancing neuroscience research, with the capacity to provide fundamental insights into mechanisms underlying neuronal functions, the dynamics of cell communication within such networks remain poorly understood. Here, we develop a customizable, polymer modified three-dimensional gold microelectrode array with sufficient stability for high signal-to-noise, long-term, neuronal recording of cultured networks. By using directed spatial and temporal patterns of electrical stimulation of cells to explore synaptic-based communication, we monitored cell network dynamics over 3 weeks, quantifying communication capability using correlation heatmaps and mutual information networks. Analysis of synaptic delay and signal speed between cells enabled us to establish a communication connectivity model. We anticipate that our discoveries of the dynamic changes in communication across the neuronal network will provide a valuable tool for future studies in understanding health and disease as well as in developing effective platforms for evaluating therapies.

Broody behavior is regulated by hypothalamic prolactin secretion, which seriously affects egg production in poulty production. Numerous studies have provided evidence that animal behavior is governed by dynamic bidirectional communication between specific gut bacteria and their host viathe brain–gut–microbiome axis. However, little research focused on how the gut microbiota influence broody behavior in poultry. In this study, Zhedong white geese in laying and brooding phases were selected. Ten differentially abundant bacteria in cecum were detected between brooding and laying geese through metagenomic analyses and 16S rRNA sequencing (P<0.05), and Bacteroides fragiliswas specifically identified as a key driver species in the brooding geese. Moverover, the serum metabolites were quantified, and the 313 differentially abundant metabolites were found between the two groups of different physiological geese. They were primarily enriched in the tryptophan metabolism pathways. Pearson correlation analyses revealed there was a significant positive correlation between B. fragilisabundance and the context of 11 tryptophan metabolism-related metabolites (such as serotonin, etc.) in broody geese, which hinted that those tryptophan metabolites might be produced or driven by B. fragilis. Finally, the serum hormone levels were also measured. We found there was a positive correlation between B. fragilisabundance and content of serotonin. Besides, prolactin secreted by the pituitary gland was greater in brooding geese than that in laying geese, which was also highly correlated with B. fragilisabundance. This result implied that B. fragiliscould promote the secretion of prolactin by the pituitary gland. Together, the current study findings provided the information on gut microbiota influencing broody behavior, B. fragilisproduced or driven more serum serotonin, and stimulated the pituitary gland to secret more prolactin, which potentially offered a new enlightenment for the intervention of broody behavior in poultry.

Sporadic or late-onset Alzheimer’s disease (LOAD) accounts for more than 95% of Alzheimer’s disease (AD) cases without any family history. Although genome-wide association studies have identified associated risk genes and loci for LOAD, numerous studies suggest that many adverse environmental factors, such as social isolation, are associated with an increased risk of dementia. However, the underlying mechanisms of social isolation in AD progression remain elusive. In the current study, we found that 7 days of social isolation could trigger pattern separation impairments and presynaptic abnormalities of the mossy fibre-CA3 circuit in AD mice. We also revealed that social isolation disrupted histone acetylation and resulted in the downregulation of 2 dentate gyrus (DG)-enriched miRNAs, which simultaneously target reticulon 3 (RTN3), an endoplasmic reticulum protein that aggregates in presynaptic regions to disturb the formation of functional mossy fibre boutons (MFBs) by recruiting multiple mitochondrial and vesicle-related proteins. Interestingly, the aggregation of RTN3 also recruits the PP2A B subunits to suppress PP2A activity and induce tau hyperphosphorylation, which, in turn, further elevates RTN3 and forms a vicious cycle. Finally, using an artificial intelligence-assisted molecular docking approach, we determined that senktide, a selective agonist of neurokinin3 receptors (NK3R), could reduce the binding of RTN3 with its partners. Moreover, application of senktide in vivoeffectively restored DG circuit disorders in socially isolated AD mice. Taken together, our findings not only demonstrate the epigenetic regulatory mechanism underlying mossy fibre synaptic disorders orchestrated by social isolation and tau pathology but also reveal a novel potential therapeutic strategy for AD.

AbstractBenign prostatic hyperplasia (BPH) is a common disease that affects the quality of life of middle-aged and older men. We investigated the therapeutical effects of Chengshi Beixie Fenqing Decoction (CBFD), a classic traditional Chinese medicine prescription, on BPH through in vivomodel and network pharmacology. Bioactives in CBFD were detected through UPLC-Q-Tof-MS/MS and GC-MS, and filtered by the modified Lipinski’s rule. Target proteins associated with the filtered compounds and BPH are selected from public databases. Venn diagram identified the overlapping target proteins between the bioactives-interacted target proteins and the BPH-targeted proteins. The bioactive-protein interactive networking of BPH was analyzed through the KEGG pathway on STRING to identify potential ligand-target and visualized the rich factors on the R packet. After that, the molecular docking test (MDT) was performed between bioactives and target proteins. It showed that the mechanism of CBFD against BPH was related to 104 signaling pathways of 42 compounds. AKT1, 6-demethyl-4′-methyl-N-methylcoclaurine and relaxin signaling pathways were selected as a hub target, key bioactivitie and hub signaling pathway, respectively. In addition, three major compounds, 6-demethyl-4′-methyl-N-methylcoclaurine, isoliensinine and liensinine, had the highest affinity on MDT for the three crucial target proteins, AKT1, JUN and MAPK1. These proteins were associated with the relaxin signaling pathway, which regulated the level of nitric oxide and is implicated in both BPH development and CBFD. We concluded that the three key bioactivities found in Plumula nelumbinis of CBFD may contribute to improving BPH condition by activating the relaxin signaling pathways.Communicated by Ramaswamy H. Sarma

Graph data-driven machine fault diagnosis methods make success using sufficient data recently. However, in the actual industry, there are rare failure data in historical data, leading to insufficient graph representation ability and reducing diagnosis performance. In this article, a generalized graph contrastive learning (GCL) framework for few-shot machine fault diagnosis is proposed. First, spectrum features of vibration data-based samples are used to calculate Euclidean distance matrix for constructing K-nearest neighborhood graph (KNNG), where K adjacent neighbors of each sample are connected. Avoiding excess calculation cost for graph construction, positive and negative KNNGs are constructed by changing parameter K. To make full use of few-shot samples, an unsupervised GCL subtask is set for pretraining graph deep learning model. Further, the unsupervised pretrained model is semisupervised trained using original KNNGs for outputting unlabeled nodes’ labels. The proposed method achieves 99.83%, 99.56% in bearing and gearbox dataset, respectively, and the proposed GCL framework works for different graph neural networks.

The extensive use of fossil fuels has resulted in large amounts of carbon dioxide being emitted into the air and has led to a number of environmental problems. Given the abundance of both carbon dioxide and sunlight in the earth’s atmosphere, converting solar energy into chemical energy by photothermally catalyzing carbon dioxide hydrogenation to produce methanol is a potential strategy. By using the coprecipitation approach, a Ni-doped In2O3catalyst was created, and its compositional valence, morphology, specific surface area, band gap, and other properties were assessed by XRD, XPS, TEM, BET, H2-TPR, CO2-TPD, and UV–vis characterization. Methanol production from carbon dioxide hydrogenation is stable and effective under lower pressure (1 MPa) photothermal settings, with an efficiency of 63.4 gMeOHh–1kgcat–1, which is approximately 120% higher than that of pure In2O3under the same circumstances.

Water instability and sensing homogeneity are the Achilles’ heel of CsPbX3NPs in biological fluids application. This work reports the preparation of Mn2+:CsPbCl3@SiO2yolk–shell nanoparticles (YSNPs) in aqueous solutions created through the integration of ligand, surface, and crystal engineering strategies. The SN2 reaction between 4-chlorobutyric acid (CBA) and oleylamine (OAm) yields a zwitterionic ligand that facilitates the dispersion of YSNPs in water, while the robust SiO2shell enhances their overall stability. Besides, Mn2+doping in YSNPs not only introduces a second emission center but also enables potential postsynthetic designability, leading to the switching from YSNPs to MnO2@YSNPs with excellent oxidase (OXD)-like activity. Theoretical calculations reveal that electron transfer from CsPbCl3to in situMnO2and the adsorption–desorption process of 3,3′,5,5′-tetramethylbenzidine (TMB) synergistically amplify the OXD-like activity. In the presence of ascorbic acid (AA), Mn4+in MnO2@YSNPs (fluorescent nanozyme) is reduced to Mn2+and dissociated, thereby inhibiting the OXD-like activity and triggering fluorescence “turn-on/off”, i.e., dual-mode recognition. Finally, a biomarker reporting platform based on MnO2@YSNPs fluorescent nanozyme is constructed with AA as the reporter molecule, and the accurate detection of human serum alkaline phosphatase (ALP) is realized, demonstrating the vast potential of perovskites in biosensing.

Graphical Abstract:

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.

Free-running InGaAs/InP single-photon detectors (SPDs) based on negative-feedback avalanche diodes (NFADs) are the key components for applications requiring asynchronous single-photon detection in the near-infrared region. From the perspective of practical applications, the features of SPDs in terms of high photon detection efficiency (PDE), low noise, large sensitive area, and compactness are highly desired for system integration and performance enhancement.Here, we present the implementation of a compact four-channel multimode fiber coupling free-running InGaAs/InP SPD, with the best overall performance to date. On the one hand, we design and fabricate structure-optimized InGaAs/InP NFAD devices with 25 $\mu$m diameter active area and integrated thin film resistors to enhance the maximum achievable PDE. On the other hand, we apply a compact thermoacoustic cryocooler to regulate the operating temperature of NFADs within a large range, and design a dedicated readout circuit with minimized parasitic parameters and tunable settings of hold-off time to suppress the afterpulsing effect. The SPD is then characterized to achieve remarkable overall performance simultaneously at 1550 nm, i.e., 40% PDE, 2.3 kcps dark count rate, 8% afterpulse probability and 49 ps timing jitter (full width at half maximum) under the conditions of 5.9 V excess bias voltage, 10 $\mu$s hold-off time and 213 K operation temperature. Such performance and the results of the long-term stability tests indicate that the SPD could be a favorable solution for practical applications.

Prepubertal male patients with cancer have decreased fertility after treatment, but there are currently no suitable means for fertility rescue. Testicular transplantation seems to be a promising treatment. The short-term insufficiency of blood supply after transplantation is the key problem that needs to be solved. In this research, nitric oxide (NO), a gas and small molecule transmitter with the effect of promoting angiogenesis, acted at the site of testicular transplantation. Herein, poloxamer-407 (P407) and lipid microbubble materials served as transport carriers for NO and helped NO to function at the transplant site. P407 hydrogel loaded with NO microbubbles (PNO) slowly released NO in vitro. The three-dimensional space of the hydrogel provided a stable environment for NO microbubbles, which is conducive to the continuous release of NO. In this study, 25% PNO (w/v) was selected, and the gelling temperature was 19.47 °C. The gelling efficiency was relatively high at body temperature. Rheological experiments showed that PNO, at this concentration, had stable mechanical properties. The results from in vivoexperiments demonstrated that testicular grafts in the PNO group exhibited a notably accelerated blood flow recovery compared to the other groups. Additionally, the PNO group displayed a significant improvement in reproductive function recovery. In conclusion, PNO exhibited slow release of NO, and a small amount of NO promoted angiogenesis in testicular grafts and restored reproductive function.

Parkinson’s disease (PD) is a common neurodegenerative disorder with no cure. Astragalus membranaceusis used in Chinese culture as a food supplement to boost immunity. The present study aimed to explore the neuroprotective effects of total flavonoids extracted from A. membranaceus(TFA) and their protective mechanisms. TFA offered neuroprotection against 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) in the mouse model of Parkinsonism, by improving behavior performance in the gait analysis and pole test, and inhibiting the decline of tyrosine hydroxylase (TH) positive neurons and TH protein expression in substantia nigra of mice. TFA also prevented 1-methyl-4-phenylpyridinium (MPP+) induced neurotoxicity in SH-SY5Y cells, by increasing GSH and GSH/GSSG ratio, and reducing reactive oxygen species. In addition, the neuroprotective effects of TFA were associated with its ability to restore MPTP/MPP+induced downregulation of SLC7A11 and glutathione peroxidase 4 (GPX-4). In conclusion, we demonstrated that TFA exerted significant neuroprotection against MPTP/MPP+induced neurodegeneration by inhibiting ferroptosis through the regulation of SLC7A11/GPX-4 axis, suggesting the use of TFA as a possible food supplement in the prevention of PD.

Transformer has shown great potential in extracting global features, and it can achieve better classification performance with a large number of training samples compared with other deep learning (DL) models. However, most of the existing Transformer-based models for hyperspectral image (HSI) classification simply use the multihead self-attention and channel multilayer perceptron (MLP) modules that contain many parameters to learn, resulting in poor performance in a few-shot learning scenario. To overcome the above issue, a lightweight self-pooling Transformer (SPFormer) is proposed for few-shot HSI classification. First, a one-layer autoencoder based on self-supervised learning is built to reduce the dimensionality of HSI. Second, two parameter-free modules, channel shuffle for multihead self-pooling with sparse mapping (CSSM-MHSP) and central token mixer (CTM), are proposed for mapping spectral features to higher dimensions and promoting information interaction between pixels, respectively. Third, a lightweight channel embedding is designed to extract deep spectral features. Finally, a fully connected layer is used for classification. The classification performance of the proposed method is evaluated on four benchmark datasets, showing its superiority in classification accuracy, generalization performance, and model complexity compared to existing state-of-the-art methods with limited training samples.

With the widespread use of deep neural networks (DNNs) in intelligent systems, DNN accelerators with high performance and energy efficiency are greatly demanded. As one of the feasible processing-in-memory (PIM) architectures, 3-D stacked-DRAM-based PIM (DRAM-PIM) architecture enables large-capacity memory and low-cost memory access, which is a promising solution for DNN accelerators with better performance and energy efficiency. However, the low-access-cost characteristics of stacked DRAM and the distributed manner of memory access and data storing require us to rebalance the hardware design and DNN mapping. In this article, we propose NicePIM to efficiently explore the design space of hardware architecture and DNN mapping of DRAM-PIM-based DNN inference accelerators, which consists of three key components: 1) PIM-Tuner; 2) PIM-Mapper; and 3) data-scheduler. PIM-Tuner optimizes the hardware configurations leveraging a DNN model for classifying area-compliant PIM-node designs and a deep kernel learning model for identifying better-hardware parameters. PIM-Mapper explores a variety of DNN mapping configurations, including parallelism between branches of DNN, DNN layer partitioning, DRAM capacity allocation, and data layout pattern in DRAM, to generate high-hardware-utilization DNN mapping schemes for various hardware configurations. The data-scheduler employs an integer-linear-programming-based data scheduling algorithm to alleviate the inter-PIM-node communication overhead of data-sharing brought by DNN layer partitioning. Experimental results demonstrate that NicePIM can optimize hardware configurations for DRAM-PIM systems effectively and can generate high-quality DNN mapping schemes with latency and energy cost reduced by 37% and 28% on average, respectively, compared to the baseline method.

Purpose: Facing the high-power requirements of large-scale or super-scale scale vibratory machines, the multi-machine parallel technology by adding the number of exciters is a feasible solution. In the paper, the self-synchronous characteristics and Sommerfeld effect of a vibration system driven by four non-ideal induction motors rotating in arbitrary directions on a rigid body are investigated to expand the application of the multi-machine parallel technology in large vibratory machines. Methods: The dynamic coupling model of the whole vibration system is established by using the Lagrange method. A modified direct separation of motion method is innovatively applied to transfer the complex synchronous motion problem of four time-varying coupling dynamic systems to that of four time-invariant systems. The synchronization and stability conditions of the modified system are given by using the perturbation method. Results: The Sommerfeld effect and self-synchronization near the natural frequency of the vibration system interact with each other. The synchronous states of four motors will change before and after the natural frequency of the vibration system. The rotating directions of four motors influence the synchronous states of four motors largely. Conclusion: To implement the purpose of enlarge the excitation force by increasing the number of exciters, four motors should work before the system’ natural frequency. For vibration attenuation, four motors should work after the system natural frequency and the power of the motors should be very large to avoid the capture of motor speed. Self-synchronization of four motors is helpful for vibration attenuation.

To avoid coarse crystallization of glassy inclusions in Si–Mn deoxidized steel during hot rolling, the effect of MgO on the structure and crystallization behavior of CaO–SiO2–Al2O3inclusions was investigated. The results showed that the crystallization temperature of the oxide melts decreased with increasing MgO content from 0 to 15.7 wt.%, which suggested that the addition of MgO would increase the temperature range of the crystalline transition. The increase in MgO content could decrease the crystallization activation energy of inclusions. With the increase in MgO content, the relative fractions of QSi0and QSi1structure units increased, and those of structure units QSi2, QSi3, and QSi4decreased, increasing the depolymerization degree of the silicate structure. The crystallization ratio of glassy inclusions in the steel crucible increased from 19.7% to 98.3% with increasing MgO content from 0 to 15.7 wt.%. The addition of MgO improved the crystallization ability of inclusions, because MgO provides free oxygen O2−to destroy the bridging oxygens and form non-bridging oxygens O−, which depolymerizes silicate network structure and simplifies the [SiO4]-tetrahedral structure. In addition, MgO would promote the precipitation of the Mg-containing phases with a high melting point. When the MgO content was increased above 12.1 wt.%, MgO·Al2O3and 2MgO·SiO2crystalline phases would precipitate from the inclusions.