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In this paper, the generalized (3+1)-dimensional nonlinear wave equation in fluid with gas bubbles is studied in soliton theory and produced by taking the Hirota bilinear operators. The first- to third rogue wave solutions through numerous rogue wave strategy by Maple typical estimations are recovered. The made conditions for the analyticity and positively of the gotten arrangements can be effectively accomplished by utilizing the specific determinations of the included values. The most merits of this plot are to recoup the Hirota bilinear models and their generalized equivalences. Also, the rational tan(Π(ξ)) technique on the generalized nonlinear wave equation is examined. The perturbed solution of the generalized nonlinear wave equation through the way of Modulational stability is studied. Finally, the graphical reenactments of the precise arrangements are portrayed. By selecting suitable values for the parameters involved in the solutions, 3D graphs, 2D contour graphs and line graphs are presented to provide graphical demonstration of the results. The reported results will be helpful to design new and better optical devices. The findings of this work may also help in problems arising in ocean engineering.

We demonstrate an all-optical method that online produces “microstructured” targets by manipulating a Laguerre-Gaussian (LG) prepulse. Besides the enhancement of the proton number, the cutoff energy is nearly doubled. Such transient “microstructured” targets are characterized using both offline and online approaches. Based on probe experiments and hydrodynamic simulations, we develop a simple model to describe the electron density distribution upon the arrival of the main pulse. Two-dimensional particle-in-cell simulations reveal that the annular plasma acts as an oscillating cavity for hot electrons and results in a cascaded acceleration effect. The combination of low-intensity LG prepulses and ultraintense Gaussian pulses opens another avenue for fine-tuning laser-plasma interactions spatiotemporally in interdisciplinary applications.

Abstract Defects within chip solder joints are usually inspected visually for defects using X-ray imaging to obtain images. The phenomenon of voids inside solder joints is one of the most likely types of defects in the soldering process, and accurate detection of voids becomes difficult due to their irregular shapes, varying sizes, and defocused edges. To address this problem, an X-ray void image segmentation algorithm based on improved PCB-DeepLabV3 is proposed. Firstly, to meet the demand for lightweight and easy deployment in industrial scenarios, mobilenetv2 is used as the feature extraction backbone network of the PCB-DeepLabV3 model; then, Attentional multi-scale two-space pyramid pooling network (AMTPNet) is designed to optimize the shallow feature edges and to improve the ability to capture detailed information; finally, image cropping and cleaning methods are designed to enhance the training dataset, and the improved PCB-DeepLabV3 is applied to the training dataset. The improved PCB-DeepLabV3 model is used to segment the void regions within the solder joints and compared with the classical semantic segmentation models such as Unet, SegNet, PSPNet, and DeeplabV3. The proposed new method enables the solder joint void inspection to get rid of the traditional way of visual inspection, realize intelligent upgrading, and effectively improve the problem of difficult segmentation of the target virtual edges, to obtain the inspection results with higher accuracy.

In poor lighting and rainy and foggy bad weather environments, road traffic signs are blurred and have low recognition, etc. A super-resolution reconstruction algorithm for complex lighting and bad weather traffic sign images was proposed. First, a novel attention residual module was designed to incorporate an aggregated feature attention mechanism on the jump connection side of the base residual module so that the deep network can obtain richer detail information; second, a cross-layer jump connection feature fusion mechanism was adopted to enhance the flow of information across layers as well as to prevent the problem of gradient disappearance of the deep network to enhance the reconstruction of the edge detail information; and lastly, a positive-inverse dual-channel sub-pixel convolutional up-sampling method was designed to reconstruct super-resolution images to obtain better pixel and spatial information expression. The evaluation model was trained on the Chinese traffic sign dataset in a natural scene, and when the scaling factor is 4, the average values of PSNR and SSIM are improved by 0.031 when compared with the latest release of the deep learning-based super-resolution reconstruction algorithm for single-frame images, MICU (Multi-level Information Compensation and U-net), the average values of PSNR and SSIM are improved by 0.031 dB and 0.083, and the actual test average reaches 20.946 dB and 0.656. The experimental results show that the reconstructed image quality of this paper's algorithm is better than the mainstream algorithms of comparison in terms of objective indexes and subjective feelings. The super-resolution reconstructed image has a higher peak signal-to-noise ratio and perceptual similarity. It can provide certain technical support for the research of safe driving assistive devices in natural scenes under multi-temporal varying illumination conditions and bad weather.

Summary: Aiming at the current SPI (solder paste inspection) system for printing solder paste similar defects detection accuracy is not high, the system intelligence degree is low and so on, design a for the solder paste similar defects and combined with phase modulation profile measurement technique and improve the YOLOX intelligent detection system. The core of the system is the improved YOLOX depth model based on s-mosica and kt-iou algorithms proposed in this paper. The experimental results show that the proposed s-mosica and kt-iou algorithms can effectively improve the detection accuracy of printed solder paste, and when combined with the YOLOX model, the best 90.33% detection accuracy is obtained, which is better than the detection performance of the existing algorithms in the same scenario, and it provides an effective and feasible reference program for the design of the SPI high-precision intelligent detection system.

To meet the demands of laser-ion acceleration at a high repetition rate, we have developed a comprehensive diagnostic system for real-time and in situ monitoring of liquid sheet targets (LSTs). The spatially resolved rapid characterizations of an LST’s thickness, flatness, tilt angle and position are fulfilled by different subsystems with high accuracy. With the help of the diagnostic system, we reveal the dependence of thickness distribution on collision parameters and report the 238-nm liquid sheet generated by the collision of two liquid jets. Control methods for the flatness and tilt angle of LSTs have also been provided, which are essential for applications of laser-driven ion acceleration and others.

Occlusion or posture change of the face in natural scenes has typical asymmetry; however, an asymmetric face plays a key part in the lack of information available for facial expression recognition. To solve the problem of low accuracy of asymmetric facial expression recognition, this paper proposes a fusion of channel global features and a spatial local information expression recognition network called the “Channel–Spatial Integration Network” (CSINet). First, to extract the underlying detail information and deepen the network, the attention residual module with a redundant information filtering function is designed, and the backbone feature-extraction network is constituted by module stacking. Second, considering the loss of information in the local key area of face occlusion, the channel–spatial fusion structure is constructed, and the channel features and spatial features are combined to enhance the accuracy of occluded facial recognition. Finally, before the full connection layer, more local spatial information is embedded into the global channel information to capture the relationship between different channel–spatial targets, which improves the accuracy of feature expression. Experimental results on the natural scene facial expression data sets RAF-DB and FERPlus show that the recognition accuracies of the modeling approach proposed in this paper are 89.67% and 90.83%, which are 13.24% and 11.52% higher than that of the baseline network ResNet50, respectively. Compared with the latest facial expression recognition methods such as CVT, PACVT, etc., the method in this paper obtains better evaluation results of masked facial expression recognition, which provides certain theoretical and technical references for daily facial emotion analysis and human–computer interaction applications.

Bearing failures are the most frequent causes of breakdowns in rotating machinery. Different levels of severity in these failures exhibit distinct fault characteristics in the vibration signal. This paper presents a bearing fault diagnosis method that considers different severity levels, involving the selection of statistics detection index symptom parameter and the application of canonical discriminant analysis (CDA). Initially, kurtosis is employed to detect abnormalities in the bearing. Subsequently, statistical analysis theory is utilized to extract efficient symptom parameters from the time domain and frequency domain vibration signals. As a statistical analysis method, CDA can discriminate between different signals by maximizing the between-group difference and minimizing the inter-group difference. By analyzing the distribution of CDA canonical scores, bearing faults can be intuitively diagnosed. The proposed method is validated using vibration signals obtained from an experimental bench with three different bearing conditions (normal, inner race fault, outer race fault) exhibiting varying severity levels. The results demonstrate the effectiveness and feasibility of diagnosing faults under different severity levels.

Abstract Background The combination of oncolytic viruses (OVs) with immune checkpoint blockades is a research hotspot and has shown good efficacy. Here, we present the first attempt to combine oncolytic herpes simplex virus 2 (OH2) with an anti-SIRPα antibody as an antitumour treatment. Our results provide unique insight into the combination of innate immunity with OV. Methods We verified the polarization and activation of OH2 in RAW264.7 cells in vitro. Subsequently, we evaluated the antitumour ability of OH2 and anti-SIRPα combined therapy in a tumour-bearing mouse model. RNA-seq and Single-cell RNA-seq were used to characterize the changes in the tumour microenvironment. Results The OH2 lysates effectively stimulated RAW264.7 cells to polarize towards the M1 but not the M2 phenotype and activated the function of the M1 phenotype in vitro. In the macrophage clearance experiment, OH2 therapy induced polarization of M1 macrophages and participated in the antitumour immune response in a tumour-bearing mouse model. Treatment with a combination of OH2 and anti-SIRPα effectively inhibited tumour growth and significantly prolonged the survival time of the mice, and this result was more obvious in the mouse model with a larger tumour volume at the beginning of the treatment. These results suggest that combination therapy can more profoundly reshape the TME and activate stronger innate and adaptive immune responses. Conclusions Our data support the feasibility of oncolytic virus therapy in combination with anti-SIRPα antibodies and suggest a new strategy for oncolytic virus therapy.

Investigating the enhancement of the interaction between laser and plasma is crucial for fundamental and applied physics research studies based on laser-induced acceleration and nuclear reactions. The improvement of energy conversion efficiency resulting in increasing reaction yields has been extensively studied by the interaction of femtosecond (fs) or picosecond (ps) lasers with nanowire targets. However, the effects of nanosecond (ns) lasers interacting with nanowire targets on energy absorption and production yield remain unknown. To address this issue, we conducted a deuterium–deuterium fusion experiment based on the collision of two plasmas induced by the interaction of the kilo-Joule-level nanosecond laser with nanowire targets. The experimental results of neutron detection indicate that the yields of nanowire targets remain at the same level as those of planar targets. We have used the counter-streaming collisionless plasma model to perform a numerical analysis of the output of nuclear reaction products at the center-of-mass energy (Ec.m.) values between 10 and 30 keV, and the calculation results are in good agreement with the experimental results. In addition, a magneto-hydrodynamic numerical simulation was also performed. It shows that the critical density of the target’s surface, which forms on the picosecond time scale, blocks the absorption of laser energy with nanosecond pulse length. Consequently, both our experimental and simulation results indicate that the enhancement factor is limited when a target with a spatial period less than µm is used in conjunction with a ns laser. Therefore, additional research is highly desirable to develop a target structure that can improve the efficiency of energy conversion between the laser and the target.

The role of chemokines in predicting the prognosis of colon cancer has not been mentioned. Chemokines have been shown to be associated with immune cell chemotaxis and activation, so the expression of chemokine genes in tumor tissue may be related to prognosis. We used a least absolute shrinkage and selection operator (LASSO) model based on chemokine gene families to construct a model that can predict the prognosis of colon cancer patients. We divided patients into high-risk groups and low-risk groups to study the prognosis. Then, we evaluated the relationship between the different risk groups in infiltration of immune cells. It was found that there was less immune cell infiltration in the high-risk group. We conducted a functional enrichment analysis based on model stratification, and explored the biological signal pathways enriched in the high and low-risk groups, which provided ideas for studying the mechanism behind its impact on prognosis. In addition, the chemokine-related gene signature could predict the response of patients to immunotherapy and chemotherapy.

Since the last IAEA-FEC in 2021, significant progress on the development of long pulse steady state scenario and its related key physics and technologies have been achieved, including the reproducible 403 s long-pulse steady-state H-mode plasma with pure radio frequency (RF) power heating. A thousand-second time scale (∼1056 s) fully non-inductive plasma with high injected energy up to 1.73 GJ has also been achieved. The EAST operational regime of high β _P has been significantly extended ( H _98y2 > 1.3, β _P ∼ 4.0, β _N ∼ 2.4 and n _e / n _GW ∼ 1.0) using RF and neutral beam injection (NBI). The full edge localized mode suppression using the n = 4 resonant magnetic perturbations has been achieved in ITER-like standard type-I ELMy H-mode plasmas with q _95 ≈ 3.1 on EAST, extrapolating favorably to the ITER baseline scenario. The sustained large ELM control and stable partial detachment have been achieved with Ne seeding. The underlying physics of plasma-beta effect for error field penetration, where toroidal effect dominates, is disclosed by comparing the results in cylindrical theory and MARS-Q simulation in EAST. Breakdown and plasma initiation at low toroidal electric fields (

Very thin free-flowing liquid sheets are promising targets for high-repetition-rate laser-ion acceleration. In this work, we report the generation of micrometer-thin free-flowing liquid sheets from the collision of two liquid jets, and study the vibration and jitter in their surface normal direction. The dependence of their motion amplitudes on the generation parameters is studied in detail. The origins of the vibration and jitter are discussed. Our results indicate that when the generation parameters are optimized, the motion amplitudes in the stable region can be stabilized below 3.7 μm to meet the stringent requirement of sheet position stability for a tight-focusing setup in laser-ion acceleration experiments.

Abstract Signet ring cell carcinoma (SRCC) has specific oncogenesis and phenotypic and treatment resistance heterogeneity. Systemic therapies are often ineffective, and predictive biomarkers to guide treatment are urgently needed. Tumor organoids have recently emerged as an ideal model for drug testing and screening. Here, we report gastric organoids established from tumor tissues comprising four SRCCs and eight non-SRCCs. Tumor organoids demonstrated different growth characteristics and morphologies. Changes in the original tumor genome were maintained during long-term culture from whole-exome sequencing (WES) analysis. Immunohistochemistry and H&E staining showed that the tissue characteristics of the primary tumor could be recapitulated. In addition, organoid lines successfully formed tumors in immunodeficient mice and maintained tumorigenic character. Different responses to 5-fluorouracil, oxaliplatin, docetaxel and irinotecan treatment were observed in SRCC and non-SRCC organoids. These results demonstrate that gastric organoid drug models, including SRCC, were highly similar to the original tumors in phenotypic and genotypic profiling and could be as living biomarkers for drug response testing.

Abstract Activated Cdc42-associated kinase 1 (ACK1), a kind of tyrosine kinase, is considered to be an oncogene in many cancers, and it is likely to become a potential target for cancer treatment. We found that the expression of the ACK1 gene in colon cancer was higher than that in normal tissues adjacent to cancer, and high expression of the ACK1 gene was associated with poor prognosis of patients. We assessed the prognosis of colon cancer based on ACK1-related genes and constructed a model that can predict the prognosis of colon cancer patients in colon cancer data from The Cancer Genome Atlas (TCGA) database. We then explored the relationship between ACK1 and the immune microenvironment of colon cancer. The overexpression of ACK1 might hinder the function of antigen-presenting cells. The colon cancer prognosis prediction model we constructed has certain significance for clinicians to judge the prognosis of patients with colon cancer. The expression of the ACK1 gene might affect the infiltration level of a variety of immune cells and immunomodulators in the immune microenvironment.

Post-acceleration of protons in helical coil targets driven by intense, ultrashort laser pulses can enhance ion energy by utilizing the transient current from the targets’ self-discharge. The acceleration length of protons can exceed a few millimeters, and the acceleration gradient is of the order of GeV/m. How to ensure the synchronization between the accelerating electric field and the protons is a crucial problem for efficient post-acceleration. In this paper, we study how the electric field mismatch induced by current dispersion affects the synchronous acceleration of protons. We propose a scheme using a two-stage helical coil to control the current dispersion. With optimized parameters, the energy gain of protons is increased by four times. Proton energy is expected to reach 45 MeV using a hundreds-of-terawatts laser, or more than 100 MeV using a petawatt laser, by controlling the current dispersion.

In this work, the high-energy-density plasmas (HEDP) evolved from joule-class-femtosecond-laser-irradiated nanowire-array (NWA) targets were numerically and experimentally studied. The results of particle-in-cell simulations indicate that ions accelerated in the sheath field around the surfaces of the nanowires are eventually confined in a plasma, contributing most to the high energy densities. The protons emitted from the front surfaces of the NWA targets provide rich information about the interactions that occur. We give the electron and ion energy densities for broad target parameter ranges. The ion energy densities from NWA targets were found to be an order of magnitude higher than those from planar targets, and the volume of the HEDP was several-fold greater. At optimal target parameters, 8% of the laser energy can be converted to confined protons, and this results in ion energy densities at the GJ/cm3 level. In the experiments, the measured energy of the emitted protons reached 4 MeV, and the changes in energy with the NWA’s parameters were found to fit the simulation results well. Experimental measurements of neutrons from 2H(d,n)3He fusion with a yield of (24 ± 18) × 106/J from deuterated polyethylene NWA targets also confirmed these results.

Electromagnetic vibration is an important excitation source for squirrel-cage induction motors. However, the electromagnetic vibration under various loadings has not been sufficiently analyzed. It is proposed in this paper that the electromagnetic vibration of motors under different loads can be obtained by analyzing the amplitude of the electromagnetic force wave. The Maxwell tensor method is employed to derive the spatial and temporal distributions of the radial force. This paper also calculates the radial force using the finite element method and decodes the calculated results using two dimensional fast Fourier transform (2D-FFT) to determine the amplitude of the electromagnetic force at the spatial order under different loads. In addition, through the modal analysis of the stator core, it can be concluded that in the case of nonresonance, the vibration response increases when the electromagnetic force of the first-order and second-order rotor slot harmonic increases. Finally, the conclusion is verified by separating the electromagnetic vibration of the motor using a vibration test rig.

Cancer stem cell (CSC) is thought to be the major cause of radio-resistance and relapse post radiotherapy (RT). Recently ultra-high dose rate “FLASH-RT” evokes great interest for its decreasing normal tissue damages while maintaining tumor responses compared with conventional dose rate RT. However, the killing effect and mechanism of FLASH irradiation (FLASH-IR) on CSC and normal cancer cell are still unclear. Presently the radiation induced death profile of CSC and normal cancer cell were studied. Cells were irradiated with FLASH-IR (∼109 Gy/s) at the dose of 6–9 Gy via laser-accelerated nanosecond particles. Then the ratio of apoptosis, pyroptosis and necrosis were determined. The results showed that FLASH-IR can induce apoptosis, pyroptosis and necrosis in both CSC and normal cancer cell with different ratios. And CSC was more resistant to radiation than normal cancer cell under FLASH-IR. Further experiments tracing lysosome and autophagy showed that CSCs had higher levels of lysosome and autophagy. Taken together, our results suggested that the radio-resistance of CSC may associate with the increase of lysosome-mediated autophagy, and the decrease of apoptosis, necrosis and pyroptosis. To our limited knowledge, this is the first report shedding light on the killing effects and death pathways of CSC and normal cancer cell under FLASH-IR. By clarifying the death pathways of CSC and normal cancer cell under FLASH-IR, it may help us improve the understanding of the radio-resistance of CSC and thus help to optimize the future clinical FLASH treatment plan.

Ultra-high dose rate FLASH irradiation (FLASH-IR) has got extensive attention since it may provide better protection on normal tissues while maintain tumor killing effect compared with conventional dose rate irradiation. The FLASH-IR induced protection effect on normal tissues is exhibited as radio-resistance of the irradiated normal cells, and is suggested to be related to oxygen depletion. However, the detailed cell death profile and pathways are still unclear. Presently normal mouse embryonic fibroblast cells were FLASH irradiated (∼109 Gy/s) at the dose of ∼10–40 Gy in hypoxic and normoxic condition, with ultra-fast laser-generated particles. The early apoptosis, late apoptosis and necrosis of cells were detected and analyzed at 6, 12, and 24 h post FLASH-IR. The results showed that FLASH-IR induced significant early apoptosis, late apoptosis and necrosis in normal fibroblast cells, and the apoptosis level increased with time, in either hypoxic or normoxic conditions. In addition, the proportion of early apoptosis, late apoptosis and necrosis were significantly lower in hypoxia than that of normoxia, indicating that radio-resistance of normal fibroblast cells under FLASH-IR can be enhanced by hypoxia. To further investigate the apoptosis related profile and potential pathways, mitochondria dysfunction cells resulting from loss of cytochrome c (cyt c–/–) were also irradiated. The results showed that compared with irradiated normal cells (cyt c+/+), the late apoptosis and necrosis but not early apoptosis proportions of irradiated cyt c–/– cells were significant decreased in both hypoxia and normoxia, indicating mitochondrial dysfunction increased radio-resistance of FLASH irradiated cells. Taken together, to our limited knowledge, this is the first report shedding light on the death profile and pathway of normal and cyt c–/– cells under FLASH-IR in hypoxic and normoxic circumstances, which might help us improve the understanding of the FLASH-IR induced protection effect in normal cells, and thus might potentially help to optimize the future clinical FLASH treatment.

Circulating tumor cells (CTCs) are considered to be related to the prognosis of cancer patients. CTC is a powerful indicator for recurrence or metastasis. The relationship, however, between the expression of programmed cell death receptor ligand 1 (PD-L1) on CTCs in peripheral blood and the prognosis, is still controversial. Here, we conducted a meta-analysis to evaluate its prognostic value. A total of 20 articles were screened from PubMed, Embase, Cochrane, China National Knowledge Internet (CNKI) and WanFang Database, and the Hazard Ratio (HR) along with 95% confidence intervals (CIs) of each article were combined to study the relationship between PD-L1 expression on CTCs and prognosis. The expression of PD-L1 on CTCs in the peripheral blood of cancer patients is associated with poor prognosis. The pooled HRs for overall survival (OS) in cancer patients were 1.85 (95% CI, 1.29–2.66, P = .001). The pooled HRs for progression-free survival (PFS) in cancer patients were 1.50 (95% CI, 1.12–2.01; P = .007). This is the first meta-analysis to clarify the expression of PD-L1 on CTCs at baseline affects the prognosis of cancer patients. Patients with CTCs expressing PD-L1 had a shorter survival time than patients with CTCs not expressing PD-L1.

Massive biomass waste with lignocellulose components can be used to produce biochar for environmental remediation. However, the impact of lignocellulose pyrolysis on biochar structure in relation to the sorption mechanism of ionizable antibiotics is still poorly understood. In this paper, diverse techniques including thermogravimetric analysis and 13C nuclear magnetic resonance were applied to investigate the properties of biochars as affected by the pyrolysis of cellulose and lignin in feedstock. Cellulose-derived biochars possessed more abundant groups than lignin-derived biochars, suggesting the greater preservation of group for cellulose during the carbonization. Higher sorption of sulfamethoxazole (SMX) was also observed by cellulose-derived biochars owing to hydrogen bond interaction. Sorption affinity gradually declined with the conversion aliphatic to aromatic carbon, whereas the enhanced specific surface area (SSA) subsequently promoted SMX sorption as evidenced by increased SSA-N2 and SSA-CO2 from 350 to 450 °C. The decreased Kd/SSA-N2 values with increasing pH values implied a distinct reduction in sorption per unit area, which could be attributed to enhanced electrostatic repulsion. This work elucidated the role of carbon phases from thermal conversion of lignocellulose on the sorption performance for sulfonamide antibiotics, which will be helpful to the structural design of carbonaceous adsorbents for the removal of ionizable antibiotics.

The acceleration of super-heavy ions (SHIs, mass number of about 200) from plasmas driven by ultrashort (tens of femtoseconds) laser pulses is a challenging topic awaiting a breakthrough. Detecting and controlling the ionization process and adopting the optimal acceleration scheme are crucial for the generation of highly energetic SHIs. Here, we report the experimental results on the generation of deeply ionized super-heavy ions (Au) with unprecedented energy of 1.2 GeV utilizing ultrathin targets and ultrashort laser pulses at an intensity of 10^{22} W/cm^{2}. A novel self-calibrated diagnostic method was developed to acquire the absolute energy spectra and charge-state distributions of Au ions abundant at the charge state of 51+ and extending to 61+. The measured charge-state distributions supported by 2D particle-in-cell simulations serve as an additional tool to inspect the ionization dynamics associated with SHI acceleration, revealing that the laser intensity is the crucial parameter over the pulse duration for Au acceleration. Achieving a long acceleration time without sacrificing the strength of the acceleration field by utilizing composite targets can substantially increase the maximum energy of Au ions.

To understand and analyze crater damage of rocks under hypervelocity impact, the hypervelocity impact cratering of 15 shots of hemispherical-nosed cylindrical projectiles into granite targets was studied within the impact velocity range of 1.91−3.99 km/s. The mass of each projectile was 40 g, and the length−diameter ratio was 2. Three types of metal material were adopted for the projectiles, including titanium alloy with a density of 4.44 g/cm3, steel alloy with a density of 7.81 g/cm3, and tungsten alloy with a density of 17.78 g/cm3. The projectile−target density ratio (ρp/ρt) ranged from 1.71 to 6.86. The depth−diameter ratios (H/D) of the craters yielded from the experiments were between 0.14 and 0.24. The effects of ρp/ρt and the impact velocity on the morphologies of the crater were evaluated. According to the experimental results, H/D of craters is negatively correlated with the impact velocity, whereas the correlation between H/D and ρp/ρt is weak positive. The crater parameters were expressed as power law relations of impact parameters by using scaling law analysis. The multiple regression analysis was utilized to obtain the coefficients and the exponents of the relation equations. The predicted values of the regression equations were close to the experimental results.

Printed Circuit Board (PCB) surface tiny defect detection is a difficult task in the integrated circuit industry, especially since the detection of tiny defects on PCB boards with large-size complex circuits has become one of the bottlenecks. To improve the performance of PCB surface tiny defects detection, a PCB tiny defects detection model based on an improved attention residual network (YOLOX-AttResNet) is proposed. First, the unsupervised clustering performance of the K-means algorithm is exploited to optimize the channel weights for subsequent operations by feeding the feature mapping into the SENet (Squeeze and Excitation Network) attention network; then the improved K-means-SENet network is fused with the directly mapped edges of the traditional ResNet network to form an augmented residual network (AttResNet); and finally, the AttResNet module is substituted for the traditional ResNet structure in the backbone feature extraction network of mainstream excellent detection models, thus improving the ability to extract small features from the backbone of the target detection network. The results of ablation experiments on a PCB surface defect dataset show that AttResNet is a reliable and efficient module. In Torify the performance of AttResNet for detecting small defects in large-size complex circuit images, a series of comparison experiments are further performed. The results show that the AttResNet module combines well with the five best existing target detection frameworks (YOLOv3, YOLOX, Faster R-CNN, TDD-Net, Cascade R-CNN), and all the combined new models have improved detection accuracy compared to the original model, which suggests that the AttResNet module proposed in this paper can help the detection model to extract target features. Among them, the YOLOX-AttResNet model proposed in this paper performs the best, with the highest accuracy of 98.45% and the detection speed of 36 FPS (Frames Per Second),which meets the accuracy and real-time requirements for the detection of tiny defects on PCB surfaces. This study can provide some new ideas for other real-time online detection tasks of tiny targets with high-resolution images. [ABSTRACT FROM AUTHOR]