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Abstract Objective Knee osteoarthritis is the most common osteoarthritis and imposes a significant burden on patients’ lives. Several treatment methods can promote cartilage repair to varying extents, but there are limited studies on the combined application of different treatments. The purpose of this study is to evaluate the clinical efficacy of microfracture combined with fibrinogen and platelet-rich plasma (PRP) under arthroscopic in treating knee osteoarthritis, so as to provide a basis for clinical treatment decisions. Method A total of 113 patients with knee osteoarthritis who received orthopedic treatment from January 2021 to June 2022 were selected. They were divided into two groups according to whether they received fibrinogen and PRP treatment in addition to microfracture treatment. The two groups were analyzed to compare the differences in knee joint function and quality of life at different points. Results The study compared changes in knee joint function scores and quality of life between the two groups after treatment and found that the quality of life of patients in the combined treatment group was significantly better than that of patients who received microfracture only (at 12-month follow-up, EuroQol-VAS scores were 64.32 ± 5.63 for the microfracture group (MFx) and 75.65 ± 8.57 for the fibrinogen combined with platelet-rich plasma-assisted microfracture group (FPRPA MFx); P = 0.015; at 24-month follow-up, EuroQol-VAS scores were 66.47 ± 5.18 for the MFx group and 79.40 ± 7.43 for the FPRPA MFx group, P = 0.022). There was also a strong correlation between patients’ quality of life and knee joint function score index (IKDC score correlation coefficient r=-0.375, Lysholm score correlation coefficient r = 0.497, MOCART score correlation coefficient r = 0.579, VAS score correlation coefficient r = 0.242, T2 value correlation coefficient r=-0.293, P

Abstract Excessive glucocorticoid (GC) action is linked to various metabolic disorders. Recent findings suggest that disrupting skeletal GC signaling prevents bone loss and alleviates metabolic disorders in high-fat diet (HFD)-fed obese mice, underpinning the neglected contribution of skeletal GC action to obesity and related bone loss. Here, we show that the elevated expression of 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1), the enzyme driving local GC activation, and GC signaling in osteoblasts, are associated with bone loss and obesity in HFD-fed male mice. Osteoblast-specific 11β-HSD1 knockout male mice exhibit resistance to HFD-induced bone loss and metabolic disorders. Mechanistically, elevated 11β-HSD1 restrains glucose uptake and osteogenic activity in osteoblast. Pharmacologically inhibiting osteoblastic 11β-HSD1 by using bone-targeted 11β-HSD1 inhibitor markedly promotes bone formation, ameliorates glucose handling and mitigated obesity in HFD-fed male mice. Taken together, our study demonstrates that osteoblastic 11β-HSD1 directly contributes to HFD-induced bone loss, glucose handling impairment and obesity.

Abstract Stretchable electronics commonly assemble multiple material modules with varied bulk moduli and surface chemistry on one packaging substrate. Preventing the strain-induced delamination between the module and the substrate has been a critical challenge. Here we develop a packaging substrate that delivers mechanically stable module/substrate interfaces for a broad range of stiff and stretchable modules with varied surface chemistries. The key design of the substrate was to introduce module-specific stretchability and universal adhesiveness by regionally tuning the bulk molecular mobility and surface molecular polarity of a near-hermetic elastic polymer matrix. The packaging substrate can customize the deformation of different modules while avoiding delamination upon stretching up to 600%. Based on this substrate, we fabricated a fully stretchable bioelectronic device that can serve as a respiration sensor or an electric generator with an in vivo lifetime of 10 weeks. This substrate could be a versatile platform for device assembly.

Organic proteins are attractive owing to their unique optical properties, remarkable mechanical characteristics, and biocompatibility. Manufacturing multifunctional structures on organic protein films is essential for practical applications; however, the controllable fabrication of specific structures remains challenging. Herein, we propose a strategy for creating specific structures on silk film surfaces by modulating the bulging and ablation of organic materials. Unique surface morphologies such as bulges and craters with continuously varying diameters were generated based on the controlled ultrafast laser-induced crystal-form transition and plasma ablation of the silk protein. Owing to the anisotropic optical properties of the bulge/crater structures with different periods, the fabricated organic films can be used for large-scale inkless color printing. By simultaneously engineering bulge/crater structures, we designed and demonstrated organic film-based optical functional devices that achieves holographic imaging and optical focusing. This study provides a promising strategy for the fabrication of multifunctional micro/nanostructures that can broaden the potential applications of organic materials.

Abstract Specific emitter identification is pivotal in both military and civilian sectors for discerning the unique hardware distinctions inherent to various launchers, it can be used to implement security in wireless communications. Recently, a large number of deep learning-based methods for specific emitter identification have been proposed, achieving good performance. However, these methods are trained based on a large amount of data and the data are independently and identically distributed. In actual complex environments, it is very difficult to obtain reliable labeled data. Aiming at the problems of difficulty in data collection and annotation, and the large difference in distribution between training data and test data, a method for individual radiation source identification based on ensemble domain adversarial neural network was proposed. Specifically, a domain adversarial neural network is designed and a Transformer encoder module is added to make the features obey Gaussian distribution and achieve better feature alignment. Ensemble classifiers are then used to enhance the generalization and reliability of the model. In addition, three real and complex migration environments, Alpine–Montane Channel, Plain-Hillock Channel, and Urban-Dense Channel, were constructed, and experiments were conducted on WiFi dataset. The simulation results show that the proposed method exhibits superior performance compared to the other six methods, with an accuracy improvement of about 3%.

Abstract Bismuth(Bi)‐doped optical fibers are widely used in various aspects such as fiber lasers and amplifiers. Despite extensive research efforts to explore high‐gain Bi‐doped fibers, the pursuit of Bi‐doped fibers with emission over an extremely wide wavelength range remains unfulfilled. Here, the strategy of cluster control via regulating glass structure is proposed. It is applied to construct Bi‐doped photonic glass with ultra‐broadband near‐infrared (NIR) emission and a full width at half maximum (FWHM) of 343 nm. The strategy is further combined with the modified chemical vapor deposition (MCVD) technique with solution doping. The fiber exhibits ultra‐broadband amplified spontaneous emission (ASE) covering the entire fiber communication band (1260–1625 nm). Finally, the fiber exhibits higher optical gain and bandwidth compared with the fiber without cluster control. This device can be utilized to potentially enhance the capacity of telecommunication systems.

Abstract Treatment response and prognosis estimation in advanced pulmonary adenocarcinoma are challenged by the significant heterogeneity of the disease. The current Response Evaluation Criteria in Solid Tumors (RECIST) criteria, despite providing a basis for solid tumor response evaluation, do not fully encompass this heterogeneity. To better represent these nuances, we introduce the intertumoral heterogeneity response score (THRscore), a measure built upon and expanding the RECIST criteria. This retrospective study included patients with 3–10 measurable advanced lung adenocarcinoma lesions who underwent first‐line chemotherapy or targeted therapy. The THRscore, derived from the coefficient of variation in size for each measurable tumor before and 4–6 weeks posttreatment, unveiled a correlation with patient outcomes. Specifically, a high THRscore was associated with shorter progression‐free survival, lower tumor response rate, and a higher tumor mutation burden. These associations were further validated in an external cohort, confirming THRscore's effectiveness in stratifying patients based on progression risk and treatment response, and enhancing the utility of RECIST in capturing complex tumor behaviors in lung adenocarcinoma. These findings affirm the promise of THRscore as an enhanced tool for tumor response assessment in advanced lung adenocarcinoma, extending the RECIST criteria's utility.

With the rapid development of acoustic and magnetic stealth technology, the effectiveness of mainstream acoustic detection and passive magnetic detection has been greatly reduced. The classical airborne transient electromagnetic method(ATEM), with the advantages of active detection, sensitivity to highly conductive targets, and high detection speed, has great potential in the field of underwater detection of highly conductive targets. Based on the principle of the airborne transient electromagnetic method, this paper obtained the vertical magnetic field response formula in the time domain based on the form of a circular central loop device and studied the vertical magnetic field response characteristics in the one-dimensional model with different depths of the target layer and different transmitting and receiving heights by constructing the layered model of seawater-highly conductive layer–seawater–seabed rock. Based on the three-dimensional time domain finite volume method, the forward calculation of the underwater cuboid with high conductivity was carried out, and the attenuation curve of dBz/dt at the center of the receiving coil was obtained. The one-dimensional and three-dimensional simulation results all show that the vertical magnetic field response characteristics are significantly different when there is a target with high conductivity in seawater, compared with the condition with no target. In the inversion imaging, the simulation data of different signal-to-noise ratios(SNRs) were synthesized by Gaussian white noise, and the one-dimensional calculation of underwater targets was carried out in combination with OCCAM inversion algorithm, so as to compare the detection effect of underwater targets under different SNRs. Inversion results show that when the SNR is greater than or equal to 10 dB, the highly conductive layer in the water can be effectively detected; when it reaches 40 dB, the depth and thickness information of the highly conductive layer can also be well judged. Finally, at an SNR of 40 dB, the resistivity value of the high conductive layer is reduced proportionally, and it is found that this method still has a significant response to the depth information of the target layer. According to the above forward and inversion calculation processes, the feasibility of this method in the field of underwater detection of highly conductive targets is effectively verified.

Abstract Photonic crystals are utilized in many noteworthy applications like optical communications, light flow control, and quantum optics. Photonic crystal with nanoscale structure is important for the manipulation of light propagation in visible and near-infrared range. Herein, we propose a novel multi beam lithography method to fabricate photonic crystal with nanoscale structure without cracking. Using multi-beam ultrafast laser processing and etching, parallel channels with subwavelength gap are obtained in yttrium aluminum garnet crystal. Combining optical simulation based on Debye diffraction, we experimentally show the gap width of parallel channels can be controlled at nanoscale by changing phase holograms. With the superimposed phase hologram designing, functional structures of complicated channel arrays distribution can be created in crystal. Optical gratings of different periods are fabricated, which can diffract incident light in particular ways. This approach can efficiently manufacture nanostructures with controllable gap, and offer an alternative to the fabrication of complex photonic crystal for integrated photonics applications.

Summary: The increasing emergence of Cas9 variants has attracted broad interest, as these variants were designed to expand CRISPR applications. New Cas9 variants typically feature higher editing efficiency, improved editing specificity, or alternative PAM sequences. To select Cas9 variants and gRNAs for high-fidelity and efficient genome editing, it is crucial to systematically quantify the editing performances of gRNAs and develop prediction models based on high-quality datasets. Using synthetic gRNA-target paired libraries and next-generation sequencing, we compared the activity and specificity of gRNAs of four SpCas9 variants. The nucleotide composition in the PAM-distal region had more influence on the editing efficiency of HiFi Cas9 and LZ3 Cas9. We further developed machine learning models to predict the gRNA efficiency and specificity for the four Cas9 variants. To aid users from broad research areas, the machine learning models for the predictions of gRNA editing efficiency within human genome sites are available on our website.

Abstract Life science studies involving clustered regularly interspaced short palindromic repeat (CRISPR) editing generally apply the best-performing guide RNA (gRNA) for a gene of interest. Computational models are combined with massive experimental quantification on synthetic gRNA-target libraries to accurately predict gRNA activity and mutational patterns. However, the measurements are inconsistent between studies due to differences in the designs of the gRNA-target pair constructs, and there has not yet been an integrated investigation that concurrently focuses on multiple facets of gRNA capacity. In this study, we analyzed the DNA double-strand break (DSB)-induced repair outcomes and measured SpCas9/gRNA activities at both matched and mismatched locations using 926,476 gRNAs covering 19,111 protein-coding genes and 20,268 non-coding genes. We developed machine learning models to forecast the on-target cleavage efficiency (AIdit_ON), off-target cleavage specificity (AIdit_OFF), and mutational profiles (AIdit_DSB) of SpCas9/gRNA from a uniformly collected and processed dataset by deep sampling and massively quantifying gRNA capabilities in K562 cells. Each of these models exhibited superlative performance in predicting SpCas9/gRNA activities on independent datasets when benchmarked with previous models. A previous unknown parameter was also empirically determined regarding the “sweet spot” in the size of datasets used to establish an effective model to predict gRNA capabilities at a manageable experimental scale. In addition, we observed cell type-specific mutational profiles and were able to link nucleotidylexotransferase as the key factor driving these outcomes. These massive datasets and deep learning algorithms have been implemented into the user-friendly web service http://crispr-aidit.com to evaluate and rank gRNAs for life science studies.

This investigation explores the structural and electronic properties of low-temperature-grown (InAs)4(GaAs)3/Be-doped InAlAs and InGaAs/Be-doped InAlAs multiple quantum wells (MQWs), utilizing migration-enhanced epitaxy (MEE) and conventional molecular beam epitaxy (MBE) growth mode. Through comprehensive characterization methods including transmission electron microscopy (TEM), Raman spectroscopy, atomic force microscopy (AFM), pump–probe transient reflectivity, and Hall effect measurements, the study reveals significant distinctions between the two types of MQWs. The (InAs)4(GaAs)3/Be-doped InAlAs MQWs grown via the MEE mode exhibit enhanced periodicity and interface quality over the InGaAs/Be-InAlAs MQWs grown through the conventional molecule beam epitaxy (MBE) mode, as evidenced by TEM. The AFM results indicate lower surface roughness for the (InAs)4(GaAs)3/Be-doped InAlAs MQWs by using the MEE mode. Raman spectroscopy reveals weaker disorder-activated modes in the (InAs)4(GaAs)3/Be-doped InAlAs MQWs by using the MEE mode. This originates from utilizing the (InAs)4(GaAs)3 short period superlattices rather than InGaAs, which suppresses the arbitrary distribution of Ga and In atoms during the InGaAs growth. Furthermore, pump–probe transient reflectivity measurements show shorter carrier lifetimes in the (InAs)4(GaAs)3/Be-doped InAlAs MQWs, attributed to a higher density of antisite defects. It is noteworthy that room temperature Hall measurements imply that the mobility of (InAs)4(GaAs)3/Be-doped InAlAs MQWs grown at a low temperature of 250 °C via the MEE mode is superior to that of InGaAs/Be-doped InAlAs MQWs grown in the conventional MBE growth mode, reaching 2230 cm2/V.s. The reason for the higher mobility of (InAs)4(GaAs)3/Be-doped InAlAs MQWs is that this short-period superlattice structure can effectively suppress alloy scattering caused by the arbitrary distribution of In and Ga atoms during the growth process of the InGaAs ternary alloy. These results exhibit the promise of the MEE growth approach for growing high-performance MQWs for advanced optoelectronic applications, notably for high-speed optoelectronic devices like THz photoconductive antennas.

For the purpose of assessing the transient voltage stability of renewable energy grid more effectively and to measure the epistemic uncertainty of the evaluation results, a power system transient voltage stability assessment method based on residual stochastic differential equation network (SDE-Net) is proposed in this paper. Considering the transient stability characteristics is chronological, the proposed network takes the time series of the basic physical quantity measurement data of the power system as the input. The internal features of time series data are extracted by residual convolution block based stochastic differential equation network in this paper. Meanwhile, the proposed method introduces the focal loss function to eliminate the imbalance of the samples and improve the accuracy of transient stability assessment. In particular, the drift network for learning prediction of stability and the diffusion network for learning uncertainty measurement in residual SDE-Net are trained respectively. As a result, case study on modified IEEE 30- bus system demonstrate the residual SDE-Net’s superior performances on both transient voltage stability assessment and stability evaluation result confidence estimation.

The low-temperature-grown InGaAs (LT-InGaAs) photoconductive antenna has received great attention for the development of highly compact and integrated cheap THz sources. However, the performance of the LT-InGaAs photoconductive antenna is limited by its low resistivity and mobility. The generated radiated power is much weaker compared to the low-temperature-grown GaAs-based photoconductive antennas. This is mainly caused by the low abundance of excess As in LT-InGaAs with the conventional growth mode, which inevitably gives rise to the formation of As precipitate and alloy scattering after annealing. In this paper, the migration-enhanced molecular beam epitaxy technique is developed to grow high-quality (InAs)m/(GaAs)n short-period superlattices with a sharp interface instead of InGaAs on InP substrate. The improved electron mobility and resistivity at room temperature (RT) are found to be 843 cm2/(V·s) and 1648 ohm/sq, respectively, for the (InAs)m/(GaAs)n short-period superlattice. The band-edge photo-excited carrier lifetime is determined to be ~1.2 ps at RT. The calculated photocurrent intensity, obtained by solving the Maxwell wave equation and the coupled drift–diffusion/Poisson equation using the finite element method, is in good agreement with previously reported results. This work may provide a new approach for the material growth towards high-performance THz photoconductive antennas with high radiation power.

Phase transformation and microstructure change are important ways for the mechanical property improvement of Ti2AlNb alloys, such as ductility, tensile strength, and fracture toughness. However, the brittle α2 phase is stable, and phase transformation is difficult to be introduced at a lower temperature. This seriously affects the mechanical properties of Ti2AlNb alloy. Here, we propose a new method to promote phase transformation in Ti2AlNb alloy by deformation-induced defects through laser shock peening (LSP). The results show that after LSP, high-density defects were observed in the α2 phase, such as dislocations and stacking faults (SFs). After heat treatment at 600 ℃, the phase transformation from α2 phase to O phase was observed in the Ti2AlNb alloy treated by LSP, forming twinned and chessboard-like morphologies with nanoscale grain size. High-density defects induced by LSP reduced the thermodynamic barrier of phase transformation from α2 phase to O phase. LSP promoted the lattice distortion and Nb element diffusion in Ti2AlNb alloy at high temperatures. This work provides a new method to promote phase transformation in Ti2AlNb alloy, which may be used to improve other materials' mechanical properties.

Constructing strong metal-support interactions (SMSI) is an effective means of regulating the interfacial properties of noble metal-based supported catalysts. Here, the authors propose a strategy of ultrafast laser-induced SMSI that can be constructed on a CeO2-supported Pt system by confining electric field in localized interface.

Background: Models predicting future macrovascular invasion in hepatocellular carcinoma are constructed to assist timely interventions. Methods: A total of 366 HCC cases were retrospectively collected from five Chinese hospitals between April 2007 and November 2016: the training dataset comprised 281 patients from four hospitals; the external validation dataset comprised 85 patients from another hospital. Multi-task deep learning network-based models were constructed to predict future macrovascular invasion. The discrimination, calibration, and decision curves were compared to identify the best model. We compared the time to macrovascular invasion and overall survival using the best model and related image heterogeneity scores (H-score). Then, we determined the need for a segmentation subnet or the replacement deep learning algorithm by logistic regression in screening clinical/radiological factors. Finally, an applet was constructed for future application. Findings: The best model combined clinical/radiological factors and radiomic features. It achieved best discrimination (areas under the curve: 0·877 in the training dataset and 0·836 in the validation dataset), calibration, and decision curve. Its performance was not affected by the treatments and disease stages. The subgroups had statistical significance for time to macrovascular invasion (training: hazard ratio [HR] = 0·073, 95% confidence interval [CI]: 0·032–0·167, p < 0·001 and validation: HR = 0·090, 95%CI: 0·022–0·366, p < 0·001) and overall survival (training: HR = 0·344, 95%CI: 0·246–0·547, p < 0·001 and validation: HR = 0·489, 95%CI: 0·279 – 0·859, p = 0·003). Similar results were achieved when the patients were subdivided by the H-score. The subnet for segmentation and end-to-end deep learning algorithms improved the performance of the model. Interpretation: Our multi-task deep learning network-based model successfully predicted future macrovascular invasion. In high-risk populations, besides the current first-line treatments, more therapies may be explored for macrovascular invasion.

Digital twin (DT) framework is introduced in the context of application for power grid online analysis. In the development process of a new power grid real-time online analysis system, an online analysis digital twin (OADT) has been implemented to realize the new online analysis architecture. The OADT approach is presented and its prominent features are discussed. The presentation, discussion, and performance testing are based on a large-scale grid network model (40K+ buses), exported directly from the EMS system of an actual power grid. A plan to apply the OADT approach to digitize power grid dispatching rules is also outlined.

In recent years, a large number of high voltage direct current (HVDC) transmission projects have been connected to AC systems. This has started to have an impact on AC/DC hybrid power grids, particularly receiving terminal power grids. An HVDC system is a large-scale power electronic integrated nonlinear system, and it includes a primary system and a control and protection system. Hence, the precision and degree of detail of HVDC systems directly affect the actual effect of simulation. In recent years, in the case of the normal operation and failure of AC power grids, the abnormal fluctuation and even locking of HVDC systems caused by the inappropriate strategies of the control and protection system component have strongly affected power grids. This has significantly affected the safety and stability of receiving power grids and normal operation. In this study, the actual engineering HVDC control logic provided by a manufacturer is analyzed and simulated based on the user defined component library of the ADPSS electromagnetic transient calculation program, and an HVDC control model based on an actual system is established. The accuracy of the DC control custom model based on ADPSS is verified through the simulation of an actual power grid. Keywords: ADPSS, HVDC control and protection system, Detailed electromagnetic transient simulation, AC–DC large power grid system

The recent discovery of memristive devices based on two-dimensional materials have attracted much interest for emerging applications on flexible memory, neuromorphic computing, and so forth. Reducing the thickness to a single-layer level would prompt the scaling limit to sub-nanometer. However, monolayer materials based vertical memristive devices generally suffer inferior performance with high operating voltage, large leakage currents, and poor reliability. In this study, an interfacial polymer layer is inserted between the monolayer hexagonal boron nitride (h-BN) and top electrodes, which not only helps to constrain the conducting filament size but also block the formation of excess filaments from the bottom Cu foil. Therefore, the device shows stable bipolar resistive switching behavior with low operating voltage (< 500 mV), large on/off ratio (up to 105), long retention time (> 105 s), and excellent flexibility. It is demonstrated that tunneling conduction is shown in off-state and on-state current conducts via metallic conducting filaments, which are formed by the substitute of metal ions for lattice vacancies in h-BN. This work presents a scalable interface engineering strategy to control the interactions between metal ions and defects in monolayer h-BN films and sheds light on their promising application for large-scale integrated ultrathin flexible memory.

Abstract Highly nanotwinned (NT) metals have advantages such as high strength, good ductility, favorable corrosion resistance, and thermal stability. It has been demonstrated that the introduction of high density NT microstructures can enhance the tribological properties of metals. However, the influence of the microstructure and the composition of NT alloys on the tribological behavior are not clear. In this work, the sliding wear behavior of fully NT materials, specifically Cu-Al and Cu-Ni alloys, are studied by a nanoscratch technique using a nanoindenter. The effects of microstructure and chemical composition on the wear properties are also studied. The results show that the chemical composition has an obvious influence on the wear resistance and microstructural deformation. For NT Cu-Al alloys, the hardness and sliding wear resistance improve with increased Al content from Cu-2wt.%Al to Cu-6wt.%Al. NT Cu-10wt.%Ni alloy shows even better wear resistance than Cu-6wt.%Al. The microstructural analysis shows that NT Cu alloys with higher wear resistance correspond to a smaller deformation-affected zone. The improvement of sliding wear properties of Cu-Al alloys with higher Al content may be ascribed to their decreased stacking fault energy. NT Cu-Ni alloy shows better wear resistance than Cu-Al alloy, this may be related to the formation of intermetallic compounds in Cu-Al system. This study broadens the knowledge about tribological properties of NT materials and provides a potential method to optimize their sliding wear resistance by altering the chemical composition of NT Cu alloys.

The current DSA system used in the dispatching control centers in China is a near real-time analysis system with response speed in the order of minutes. Based on a review of the state-of-the-art in online analysis and discussion of distributed data processing and computation architecture patterns, a new online analysis architecture is proposed. The primary goal of the new architecture is to increase the online analysis response speed to the order of seconds. A reference implementation of the proposed online analysis architecture to validate the feasibility of implementing the architecture and some performance testing results are presented.

Laser shock peening (LSP) with nanosecond or femtosecond laser pulses is applied to improve the mechanical properties of metallic materials. Thus, it is necessary to compare the effects of different processing methods on microstructure changes and property improvement. In this study, nanosecond LSP (NLSP), femtosecond LSP (FLSP), and LSP with combined nanosecond and femtosecond laser pulses (F-NLSP) are conducted on Ti6Al4V alloys to compare the surface morphologies, in-depth microstructures, and nanohardness changes. In FLSP, the peened surface is smooth, and the affected depth is limited near the peened surface. NLSPed and F-NLSPed samples present rough surfaces due to the severe ablation process. Small equiaxed grains with no preferred grain orientation are denser in F-NLSPed samples than that in NLSPed samples. Compared with NLSPed samples, the affected depth and amplitude of in-depth nanohardness are larger in F-NLSPed samples. This is attributed to the increased laser absorption of incident laser on the treated surface by femtosecond laser pulses. The results in this study show the effects of different LSP methods and provide chances in engineering potentials for material property improvements.

Dynamic security assessment (DSA) is widely used in dispatching operation systems, and the small signal stability is one of the DSA's most time-consuming calculation methods. In this article, a fast method is proposed aiming to predict the small signal stability metrics of designated oscillation mode, for example frequency or damping ratio. The method is much faster than the simulation and suitable for the online application. First, the t-distributed stochastic neighbour embedding (t-SNE) algorithm is performed which can create a mapping from the power system components to 2D coordinate depending on the electrical distance of each other; then, it will be transformed into a grid structure by meshing operation, on which the convolutional neural network (CNN) model can be run properly. Finally, with a large amount of simulation samples, the CNN model can be well trained using static quantities as its input and small signal stability metrics as its prediction target. While a new operation mode needs to be evaluated, the result will be obtained by CNN directly. The validity of proposed method is verified using online data of State Grid Corp of China. It is proved that the method meets the requirements for speed and accuracy of online analysis system.

Metal nanoparticles (NPs) have attracted growing attention in recent years for electronic packaging applications. Ag NPs have emerged as a promising low-temperature bonding material owing to their unique characteristics. In this study, we mainly review our research progress on the interconnection of using polyol-based Ag NPs for electronic packaging. The synthesis, sintering-bonding process, bonding mechanism, and high-temperature joint properties of Ag NP pastes are investigated. The paste containing a high concentration of Ag NPs was prepared based on the polyol method and concentration. A nanoscale layer of organic components coated on the NPs prevents the coalescence of Ag NPs. The effects of organic components on the bondability of the Ag NP paste were studied. Compared to the aqueous-based Ag NP paste, the polyol-based Ag NP with the reduction of organic component can improve the bondability, and the coffee ring effect was successfully depressed due to the increased Marangoni flow. The sintering behaviors of Ag NPs during the bonding process were investigated using the classical sphere-to-sphere approach. The mechanical property of joints using this Ag paste was better than that using Pb95Sn5 solders after storage at high temperatures. The sintering–bonding technology using polyol-based Ag NPs was helpful to the low-temperature interconnection for electronic packaging applications.

The steep thermal gradient and complicated thermal cycle occur in the fabrication of Ti6Al4V alloy during laser solid forming (LSF). That leads to obvious anisotropic mechanical properties and requires essential heat treatments to improve its performance. In this work, different heat treatment strategies under vacuum condition were used to study the evolution of microstructures and mechanical properties of Ti6Al4V alloy produced by LSF. The results show that transformation from α phase into lamellar α + β dual-phases structure is introduced at low temperature (550 °C), and the α phase is broken and refined at higher temperature (800 °C). Tensile tests present the increase of elongations in the horizontal and vertical directions by 12.4% and 13.2% for specimens treated by two-step heat treatment (750 °C × 4 h + 500 °C × 1 h). Fatigue crack growth (FCG) lives of LSFed Ti6Al4V alloy after different heat treatments were improved due to the elimination of residual tensile stress and the transformation of α phase into α + β dual-phase structure. Specimens treated at 800 °C for 4 h exhibit a higher fatigue life among those heat-treated alloys. The low sensitivities of the FCG behavior in the Paris-zone to different heat treatments under vacuum condition are explored in the FCG testing of Ti6Al4V alloy.

Ag nanorods (Ag NRs) with a mean aspect ratio of 3.9 were prepared through a wet-chemical method, and the absorption spectra for various aspect ratios were obtained. The morphology transformation of Ag NRs irradiated with a femtosecond pulse laser was investigated through transmission electron microscopy (TEM). The near-field ablation was dependent on the laser polarization and wavelength. Laser-induced high electric field intensity was observed at the ends, middle, and junctions of the Ag NRs under various ablation conditions. Through simulation, the evolution mechanism was analyzed in detail. The effect of laser polarization angle on plasmonic junction welding was also investigated. By controlling the electronic field distribution, several nanostructures were obtained: bone-shaped NRs, T-shaped NRs, dimers, trimers, curved NRs, and nanodots. This study suggests a potentially useful approach for the reshaping, cutting, and welding of nanostructures.

The microstructural stability of rapidly solidified eutectic Sn⁻Pb alloy solder powders was investigated through aging at room temperature (25 °C) and temperatures of 40 °C⁻120 °C. The coarsening behavior of the Pb-rich phase both at room and elevated temperatures was observed. The evident coarsening of the Pb-rich phase was detected upon storage after 40 days. At elevated temperatures, a similar sequence of Pb-rich phase coarsening was observed; however, it occurred substantially more quickly. Pb-rich coarsening rate kinetics at different temperatures were estimated using the Arrhenius equation. The apparent activation energy was 45.53 ± 4.23 KJ/mol, which indicates that grain boundary diffusion is a crucial mass transport mechanism controlling Pb-rich phase coarsening under annealing.

Abstract Spurred by the simultaneous need for data privacy protection and data sharing, federated learning (FL) has been proposed. However, it still poses a risk of privacy leakage in it. This paper, an improved Differential Privacy (DP) algorithm to protect the federated learning model. Additionally, the Fast Fourier Transform (FFT) is used in the computation of the privacy budget $$\epsilon_{total}$$ , to minimize the impact of limited arithmetic resources and numerous users on the effectiveness of training model. Moreover, instead of direct analyses of the privacy budget $$\epsilon$$ through various methods, Privacy Loss Distribution (PLD) and privacy curves are adopted, while the number of artificial assignments hyperparameters is reduced, and the grid parameters delineated for FFT use are improved. The improved algorithm tightens parameter bounds and minimizes human factors’ influence with minimal efficiency impact. It decreases the errors caused by truncation and discreteness of PLDs while expanding the discreteness interval to reduce the calculation workload. Furthermore, an improved activation function using a temper sigmoid with only one parameter $$\tau\:$$ , smooths the accuracy curve and mitigates drastically fluctuating scenarios during model training. Finally, simulation results on real datasets show that our improved DP algorithm, which accounts for long trailing, facilitates a better balance between privacy and utility in federated learning models.

Abstract Background The aim of this study was to analyze the influence of the positioning of the components of total hip arthroplasty (THA) evaluated by the acetabular anteversion (AA) and femoral anteversion (FA) angle on postoperative gait in patients with symptomatic hip osteoarthritis secondary to hip dysplasia undergoing THA. Methods Between May 2023 and May 2024, patients with symptomatic hip osteoarthritis secondary to hip dysplasia (Crowe Type I and IV) who underwent THA were enrolled in the study. The AA angle and FA angle were measured by computer tomography (CT). Gait data were determined by using the Dynamic Right Gait & Posture analysis system. The relationship between FA, AA and gait data was analyzed by Pearson correlation test, subgroup Pearson correlation test, multiple linear regression. Results A total of 40 patients (45hips) were included in the study. Compared with preoperative, the patient’s postoperative foot progression angle, foot contact angle, plantarflexion velocity, swing foot speed, gait velocity, cadence, stride length were significantly improved. Preoperative FA is significantly different from postoperative FA (P