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The classification of infrasound events has considerable importance in improving the capability to identify the types of natural disasters. The traditional infrasound classification mainly relies on machine learning algorithms after artificial feature extraction. However, guaranteeing the effectiveness of the extracted features is difficult. The current trend focuses on using a convolution neural network to automatically extract features for classification. This method can be used to extract signal spatial features automatically through a convolution kernel; however, infrasound signals contain not only spatial information but also temporal information when used as a time series. These extracted temporal features are also crucial. If only a convolution neural network is used, then the time dependence of the infrasound sequence will be missed. Using long short-term memory networks can compensate for the missing time-series features but induces spatial feature information loss of the infrasound signal. A multiscale squeeze excitation-convolution neural network-bidirectional long short-term memory network infrasound event classification fusion model is proposed in this study to address these problems. This model automatically extracted temporal and spatial features, adaptively selected features, and also realized the fusion of the two types of features. Experimental results showed that the classification accuracy of the model was more than 98%, thus verifying the effectiveness and superiority of the proposed model. [ABSTRACT FROM AUTHOR]

In this paper, we show the existence of uniform rational lc polytopes for foliations with functional boundaries in dimension ⩽3$\leqslant 3$. As an application, we prove the global ACC for foliated threefolds with arbitrary DCC coefficients. We also provide applications on the accumulation points of lc thresholds of foliations in dimension ⩽3$\leqslant 3$. [ABSTRACT FROM AUTHOR]

In addition to directly determining the inverted velocity, it is crucial to assess the uncertainty (or confidence) of the relevant velocity imaging results. This is especially true when dealing with time-lapse seismic data, which play a crucial role in detecting changes in fluid movement in petroleum reservoirs. In this study, we developed an iterative Kalman filter-based method to monitor time-lapse changes in the subsurface using traveltime tomography. Our approach considers the uncertainty of the results. We successfully verified the validity of our proposed method through synthetic crosshole and time-lapse tests. Our iterative Kalman filter-based method provides reasonable reconstruction results suitable for accessing uncertainties, and the algorithm can be used to monitor changes in the subsurface medium. [ABSTRACT FROM AUTHOR]

We study the relationship between Iitaka fibrations and the conjecture on the existence of complements, assuming the good minimal model conjecture. In one direction, we show that the conjecture on the existence of complements implies the effective log Iitaka fibration conjecture. As a consequence, the effective log Iitaka fibration conjecture holds in dimension |$3$|⁠. In the other direction, for any Calabi-Yau type variety |$X$| such that |$-K_{X}$| is nef, we show that |$X$| has an |$n$| -complement for some universal constant |$n$| depending only on the dimension of |$X$| and two natural invariants of a general fiber of an Iitaka fibration of |$-K_{X}$|⁠. We also formulate the decomposable Iitaka fibration conjecture, a variation of the effective log Iitaka fibration conjecture which is closely related to the structure of ample models of pairs with non-rational coefficients, and study its relationship with the forestated conjectures. [ABSTRACT FROM AUTHOR]

The microstructures throughout a 696 × 1360 mm cross-section of an ISO 1.2738 prehardened steel block for a plastic mold were characterized via optical and electron microscopy and electron backscatter diffraction. The hardness, strength, and polishing performance of the steel block were also tested. The results showed that the microstructure of the steel bloom from the edge to the core consisted of tempered sorbite, tempered bainite, and pearlite microstructures. Abnormal upper bainite and coarse carbides were also found. The bloom sections with hardness values of 37.4 to 39.3 HRC comprised tempered sorbite and bainite. The hardness of the core was approximately 36.5 HRC due to the presence of pearlite. The tensile and yield strengths were the same in the edge and middle areas mainly owing to tempered sorbite. The polishing performance was affected by the microstructure. Tempered sorbite produced the best polishing performance due to its fine and uniform microstructure, whereas that of tempered bainite and pearlite, which contained large carbide particles and mixed phases, was worse. [ABSTRACT FROM AUTHOR]

The classification and distinction between nuclear explosions and natural earthquake events are essential to the Comprehensive Nuclear Test Ban Treaty. Nuclear explosion data are lacking; thus, classification problems must be studied in small sample scenarios. The classification problem of the eXtreme Gradient Boosting (XGBoost) model in one small sample scenario is examined using the sparrow search algorithm (SSA) algorithm to optimize the key hyperparameters of the model automatically. The shortcomings of SSA are addressed by using a Gaussian chaotic mapping method, introducing a population proportion dynamic adjustment strategy, and proposing a step-size adjustment factor for modification. The problem of the uneven initial population distribution is addressed by constructing the (modified SSA) MSSA–XGBoost classification model, thereby reducing population diversity and affecting the convergence speed of the algorithm. The fixed proportion problem of the sparrow population, which easily falls into the local optimal solution, is solved using the aforementioned approach. The fixed update step position of the discoverer is also resolved, thus limiting the global search capability and optimization efficiency of the algorithm and realizing the independent optimization of three important hyperparameters. Furthermore, artificial feature extraction can be avoided using this approach, and the number of iterations, maximum tree depth, and learning rate can be automatically optimized, achieving excellent results in small sample seismic event classification. Experimental results reveal that the classification accuracy of the MSSA–XGBoost model is 96.37%, demonstrating its superiority to the original model (93.47%) as well as to the support vector machine and convolutional neural network. Meanwhile, a nearly 30% improvement is observed in computational efficiency. [ABSTRACT FROM AUTHOR]

Acute lung injury (ALI) is a severe respiratory disease with a high mortality rate. The integrity of the pulmonary endothelial barrier influences the development and prognosis of ALI. Therefore, it has become an important target for ALI treatment. Extracellular vesicles (EVs) are promising nanotherapeutic agents against ALI. Herein, endothelium‐derived engineered extracellular vesicles (eEVs) that deliver microRNA‐125b‐5p (miRNA‐125b) to lung tissues exerting a protective effect on endothelial barrier integrity are reported. eEVs that are modified with lung microvascular endothelial cell‐targeting peptides (LET) exhibit a prolonged retention time in lung tissues and targeted lung microvascular endothelial cells in vivo and in vitro. To improve the efficacy of the EVs, miRNA‐125b is loaded into EVs. Finally, LET‐EVs‐miRNA‐125b is constructed. The results show that compared to the EVs, miRNA‐125b, and EVs‐miRNA‐125b, LET‐EVs‐miRNA‐125b exhibit the most significant treatment efficacy in ALI. Moreover, LET‐EVs‐miRNA‐125b is found to have an important protective effect on endothelial barrier integrity by inhibiting cell apoptosis, promoting angiogenesis, and protecting intercellular junctions. Sequencing analysis reveals that LET‐EVs‐miRNA‐125b downregulates early growth response‐1 (EGR1) levels, which may be a potential mechanism of action. Taken together, these findings suggest that LET‐EVs‐miRNA‐125b can treat ALI by protecting the endothelial barrier integrity. [ABSTRACT FROM AUTHOR]

In this paper, we prove the rational coefficient case of the global ACC for foliated threefolds. Specifically, we consider any lc foliated log Calabi-Yau triple (X,\mathcal {F},B) of dimension 3 whose coefficients belong to a set \Gamma of rational numbers satisfying the descending chain condition, and prove that the coefficients of B belong to a finite set depending only on \Gamma. To prove our main result, we introduce the concept of generalized foliated quadruples, which is a mixture of foliated triples and Birkar-Zhang's generalized pairs. With this concept, we establish a canonical bundle formula for foliations in any dimension. As for applications, we extend Shokurov's global index conjecture in the classical MMP to foliated triples and prove this conjecture for threefolds with nonzero boundaries and for surfaces. Additionally, we introduce the theory of rational polytopes for functional divisors on foliations and prove some miscellaneous results. [ABSTRACT FROM AUTHOR]

Sulfur mustard (SM) is a blister‐producing chemical warfare agent which could lead to a cascade of systemic damage, especially severe acute lung injury. Oxidative stress is considered to be vital processes for the SM toxicity mechanism. We previously proved the therapeutic effect of exosomes derived from bone marrow mesenchymal stromal cells in promoting the repair of alveolar epithelial barrier and inhibiting apoptosis. However, the key functional components in exosomes and the underlying mechanisms have not been fully elaborated. This research shed light on the function of the key components of human umbilical cord mesenchymal stem cell‐derived exosomes (HMSCs‐Ex). We noted that HMSCs‐Ex‐derived miR‐199a‐5p played a vital role in reducing pneumonocyte oxidative stress and apoptosis by reducing reactive oxygen species, lipid peroxidation products and increasing the activities of antioxidant enzymes in BEAS‐2B cells and mouse models after exposure to SM for 24 h. Furthermore, we demonstrated that the overexpression of miR‐199a‐5p in HMSCs‐Ex treatment induced a further decrease of Caveolin1 and the activation of the mRNA and protein level of NRF2, HO1 and NQO1, compared with HMSCs‐Ex administration. In summary, miR‐199a‐5p was one of the key molecules in HMSCs‐Ex that attenuated SM‐associated oxidative stress via regulating CAV1/NRF2 signalling pathway. [ABSTRACT FROM AUTHOR]

Let $(X\ni x,B)$ be an lc surface germ. If $X\ni x$ is klt, we show that there exists a divisor computing the minimal log discrepancy of $(X\ni x,B)$ that is a Kollár component of $X\ni x$. If $B\not=0$ or $X\ni x$ is not Du Val, we show that any divisor computing the minimal log discrepancy of $(X\ni x,B)$ is a potential lc place of $X\ni x$. This extends a result of Blum and Kawakita who independently showed that any divisor computing the minimal log discrepancy on a smooth surface is a potential lc place. [ABSTRACT FROM AUTHOR]

Purpose: Accurate three-dimensional (3D) models play crucial roles in computer assisted planning and interventions. MR or CT images are frequently used to derive 3D models but have the disadvantages that they are expensive or involving ionizing radiation (e.g., CT acquisition). An alternative method based on calibrated 2D biplanar X-ray images is highly desired. Methods: A point cloud network, referred as LatentPCN, is developed for reconstruction of 3D surface models from calibrated biplanar X-ray images. LatentPCN consists of three components: an encoder, a predictor, and a decoder. During training, a latent space is learned to represent shape features. After training, LatentPCN maps sparse silhouettes generated from 2D images to a latent representation, which is taken as the input to the decoder to derive a 3D bone surface model. Additionally, LatentPCN allows for estimation of a patient-specific reconstruction uncertainty. Results: We designed and conducted comprehensive experiments on datasets of 25 simulated cases and 10 cadaveric cases to evaluate the performance of LatentLCN. On these two datasets, the mean reconstruction errors achieved by LatentLCN were 0.83 mm and 0.92 mm, respectively. A correlation between large reconstruction errors and high uncertainty in the reconstruction results was observed. Conclusion: LatentPCN can reconstruct patient-specific 3D surface models from calibrated 2D biplanar X-ray images with high accuracy and uncertainty estimation. The sub-millimeter reconstruction accuracy on cadaveric cases demonstrates its potential for surgical navigation applications. [ABSTRACT FROM AUTHOR]

We show that |mKX|$|mK_X|$ defines a birational map and has no fixed part for some bounded positive integer m for any 12$\frac{1}{2}$‐lc surface X such that KX$K_X$ is big and nef. For every positive integer n≥3$n\ge 3$, we construct a sequence of projective surfaces Xn,i$X_{n,i}$, such that KXn,i$K_{X_{n,i}}$ is ample, mld(Xn,i)>1n${\rm {mld}}(X_{n,i})>\frac{1}{n}$ for every i, limi→+∞mld(Xn,i)=1n$\lim _{i\rightarrow +\infty }{\rm {mld}}(X_{n,i})=\frac{1}{n}$, and for any positive integer m, there exists i such that |mKXn,i|$|mK_{X_{n,i}}|$ has nonzero fixed part. These results answer the surface case of a question of Xu. [ABSTRACT FROM AUTHOR]

For -lc Fano-type varieties with fixed dimension, we show that | − m (K X + B) | defines a birational map for some positive integer m depending only on and the dimension for any pair (X , B) when vol (− (K X + B)) and the coefficients of B are bounded away from 0. When vol (− (K X + B)) approaches to zero, we construct an example to show that the effective birationality fails even if X is fixed, (X , B) is ′ -lc for some positive real number ′ , and the coefficients of B belong to a descending chain condition (DCC) set. We also show the effective birationality holds for sub-pairs (X , B) under certain conditions. [ABSTRACT FROM AUTHOR]

As an advanced near-net-shape processing method in which directly preformed, semi-finished products are created from liquid metals, spray forming has become popular in the development and application of new materials and is supporting industrialization. However, as investigated in this work, the problems of segregation and low hardness exist in the actual industrialization process, particularly for large-diameter M3 high-speed steel. It was here found that the annual ring segregation morphologies were mostly distributed from the edge to 1/2R, with a large number of stripes primarily enriched in C, Mo, and Cr elements, and the degree of segregation was mild. The ring segregation was located at the 1/2R position, where the main elemental enrichments were C, W, Mo, Cr, and V, and the segregation degree was severe. The formation of segregation during deposition is described based on an equilibrium solidification model. A slow cooling rate and heat dissipation from the surface to the inside were judged to be the main factors causing segregation and changes in the carbide morphology. In terms of hardness, with the increase in the quenching temperature to 1230 °C, the tempering hardness increased significantly. The analysis shows that a faster cooling rate in the atomization stage caused the solidified droplets to exhibit rapid solidification characteristics, and there was a higher proportion of MC carbide in the deposited billet. MC carbides cannot be fully dissolved using the conventional heat treatment process, which decreases the C, Cr, Mo, and V contents in the solution and, thus, reduces the secondary hardening capability. The findings show that, when the spray forming process is used to prepare large-diameter materials, it should not be considered a rapid solidification technology simply because of its atomization stage. Moreover, more attention should be paid to the influence of microstructure transformation during atomization and deposition. [ABSTRACT FROM AUTHOR]

In robot-assisted ultrasound-guided needle biopsy, it is essential to conduct calibration of the ultrasound probe and to perform hand-eye calibration of the robot in order to establish a link between intra-operatively acquired ultrasound images and robot-assisted needle insertion. Based on a high-precision optical tracking system, novel methods for ultrasound probe and robot hand-eye calibration are proposed. Specifically, we first fix optically trackable markers to the ultrasound probe and to the robot, respectively. We then design a five-wire phantom to calibrate the ultrasound probe. Finally, an effective method taking advantage of steady movement of the robot but without an additional calibration frame or the need to solve the AX = XB equation is proposed for hand-eye calibration. After calibrations, our system allows for in situ definition of target lesions and aiming trajectories from intra-operatively acquired ultrasound images in order to align the robot for precise needle biopsy. Comprehensive experiments were conducted to evaluate accuracy of different components of our system as well as the overall system accuracy. Experiment results demonstrated the efficacy of the proposed methods. [ABSTRACT FROM AUTHOR]

Pedicle screw insertion with robot assistance dramatically improves surgical accuracy and safety when compared with manual implantation. In developing such a system, hand–eye calibration is an essential component that aims to determine the transformation between a position tracking and robot-arm systems. In this paper, we propose an effective hand–eye calibration method, namely registration-based hand–eye calibration (RHC), which estimates the calibration transformation via point set registration without the need to solve the AX = XB equation. Our hand–eye calibration method consists of tool-tip pivot calibrations in two-coordinate systems, in addition to paired-point matching, where the point pairs are generated via the steady movement of the robot arm in space. After calibration, our system allows for robot-assisted, image-guided pedicle screw insertion. Comprehensive experiments are conducted to verify the efficacy of the proposed hand–eye calibration method. A mean distance deviation of 0.70 mm and a mean angular deviation of 0.68° are achieved by our system when the proposed hand–eye calibration method is used. Further experiments on drilling trajectories are conducted on plastic vertebrae as well as pig vertebrae. A mean distance deviation of 1.01 mm and a mean angular deviation of 1.11° are observed when the drilled trajectories are compared with the planned trajectories on the pig vertebrae. [ABSTRACT FROM AUTHOR]

Geomagnetic vector field is always measured by a strapdown triaxial magnetometer on a vehicle. The magnetometer measurements are polluted by the magnetometer inherent errors, misalignment error, and vehicle-generated magnetic inferences. With the aid of absolute attitude information from the gyro, the calibration accuracy has been proved to be greatly improved, especially for vector measurements. However, the performance of calibration methods is greatly affected by the gyro bias, which causes error accumulated over time in the absolute attitude information. In this work, we propose an improved calibration method robust to gyro bias based on relative attitude information from the gyro. Simulation results indicated that the proposed method can estimate the calibration parameters more accurately and stably than the traditional method when the gyro bias exists. The influence on the calibration accuracy of the different parts of the gyro bias is also analyzed by simulation. Experiment using a low-cost gyro proved that the proposed method can effectively improve the estimation accuracy of the calibration parameters, as the influence on the traditional method of the gyro bias is 2–3 orders of magnitude higher than that on the proposed method. [ABSTRACT FROM AUTHOR]

Approaches to reliably predict the developmental potential of embryos and select suitable embryos for blastocyst culture are needed. The development of time-lapse monitoring (TLM) and artificial intelligence (AI) may help solve this problem. Here, we report deep learning models that can accurately predict blastocyst formation and usable blastocysts using TLM videos of the embryo's first three days. The DenseNet201 network, focal loss, long short-term memory (LSTM) network and gradient boosting classifier were mainly employed, and video preparation algorithms, spatial stream and temporal stream models were developed into ensemble prediction models called STEM and STEM+. STEM exhibited 78.2% accuracy and 0.82 AUC in predicting blastocyst formation, and STEM+ achieved 71.9% accuracy and 0.79 AUC in predicting usable blastocysts. We believe the models are beneficial for blastocyst formation prediction and embryo selection in clinical practice, and our modeling methods will provide valuable information for analyzing medical videos with continuous appearance variation. Liao et al. propose a deep learning model to predict blastocyst formation using TLM videos following the first three days of embryogenesis. The authors develop an ensemble prediction model, STEM and STEM+, which were found to exhibit 78.2% and 71.9% accuracy at predicting blastocyst formation and useable blastocysts respectively. [ABSTRACT FROM AUTHOR]

In view of the fact that the flexible wheels are most prone to fatigue damage during the operation of hollow super flat series harmonic reducers, and their fatigue life seriously restricts the service life of the harmonic gear reducers, the stress characteristics and fatigue life of those flexible wheels were studied based on the finite element simulation software HyperMash. The influences of load, gear length, gear thickness and flexible wheel height on the stress and fatigue life were analyzed. The results show that the load is the most important factor affecting the fatigue life of flexible wheels. This conclusion can provide guidance for the follow-up mechanical structure optimization. [ABSTRACT FROM AUTHOR]

Magnetic dipole localization methods have a wide application range. Resolving equations of magnetic gradient tensor is a classical method to obtain the direction of the relative position vector, but the real solution hides in four possible solutions. The Scalar Triangulation and Ranging (STAR) method is also effective but is less accurate than the real solution of tensor equations. To solve the two problems, we proposed a novel direction determination approach by combining the advantages of the two methods. Based on the cube tensor measurement array from the STAR method, a novel way to calculate the distance between the dipole and the sensor array is proposed. Then, a novel real-time magnetic dipole localization method is obtained. Results of simulation experiments indicate that our method raises the successful localization area by 43% compared with the traditional method, and the baseline length of the sensor array dominates the performance of our method. [ABSTRACT FROM AUTHOR]

Prior art emission spectra of light sources utilized in chromatic confocal sensors share two disadvantages: the uneven spectral power distribution (SPD) and the fixed distribution characteristic. Consequently, the detected peak signal intensity is regulated by the SPD properties of the light source and the spectrum transmittance characteristics of the dispersive lens. To achieve this, 18 types of monochromatic light-emitting diodes (LEDs) with different peak wavelengths were selected to create a wide-spectrum light source with a tunable SPD. The SPD characteristics of the light source can be modified by adjusting the luminous intensity of each LED. The tungsten halogen lamp, the "white" LED, and the designed light source were selected as the light sources for the chromatic confocal measurement system, respectively. Comparing the peak signals obtained under various light sources. The experimental results show that, in the range of 400 to 700 nm, the peak signal intensity extreme value ratio measured with the designed light source is 1.81:1, and the normalized light intensity standard deviation is 0.118. The corresponding light intensity extreme value ratio of halogen tungsten lamp and white LED is 23.3:1, 300:1, and the normalized light intensity standard deviation is 0.302, 0.228. With the help of the designed light source, a group of wave crest signals with uniform light intensity distribution can be obtained. This can reduce the influence of the SPD characteristics of the light source itself and the transmissivity characteristics of the dispersive objective lens on the measured signal, and ensure the accuracy of spectral detection. [ABSTRACT FROM AUTHOR]