用Velocity Verlet积分器改进HMC抽样方法

Hamilton Monte Carlo (HMC)方法是一种常用的快速抽样方法.在对哈密顿方程进行抽样时,HMC方法使用Leapfrog积分器,这可能造成方程的位置及动量的迭代值在时间上不同步,其产生的误差会降低抽样效率及抽样结果的稳定性.为此,本文提出了IHMC(Improved HMC)方法,该方法用Velocity Verlet积分器替代Leapfrog积分器,每次迭代时都计算两变量在同一时刻的值.为验证方法的效果,本文进行了两个实验,一个是将该方法应用于非对称随机波动率模型(RASV模型)的参数估计,另一个是将方法应用于方差伽马分布的抽样,结果显示:IHMC方法比HMC方法的效率更高、结果更稳定.

Acute suppurative terminal cholangitis:Clinical characteristics of a new subtype of acute cholangitis

Background:Acute suppurative terminal cholangitis(ASTC)is rarer than acute obstructive cholangitis and is not well studied.To explore this subtype of acute cholangitis,we described our clinical experience with ASTC.Methods:We performed a retrospective review of patients with ASTC admitted to our center from September 2014 to August 2020.We analyzed their clinical characteristics,including etiology,clinical manifestations,imaging features,treatment and prognosis.Results:A total of 32 ASTC patients were included in the analysis.The majority of the patients had a history of biliary operations,and clinical manifestations were occult and atypical.The positive rate of bacterial culture was 46.9%.All the patients had typical imaging features on computed tomography and magnetic resonance imaging.Treatment with effective antibiotics was provided as soon as diagnosis was established.After treatment,most patients had a good outcome.Elevated levels of total bilirubin,aspartate aminotransferase,procalcitonin and gamma-glutamyltransferase were the characteristics of critically ill patients and were associated with relatively poor prognosis.Conclusions:Our results demonstrated that ASTC should be recognized as a new subtype of acute cholangitis,and that earlier diagnosis and more personalized treatments are needed.

ST-LSTM-SA:A New Ocean Sound Velocity Field Prediction Model Based on Deep Learning

The scarcity of in-situ ocean observations poses a challenge for real-time information acquisition in the ocean.Among the crucial hydroacoustic environmental parameters,ocean sound velocity exhibits significant spatial and temporal variability and it is highly relevant to oceanic research.In this study,we propose a new data-driven approach,leveraging deep learning techniques,for the prediction of sound velocity fields(SVFs).Our novel spatiotemporal prediction model,STLSTM-SA,combines Spatiotemporal Long Short-Term Memory(ST-LSTM) with a self-attention mechanism to enable accurate and real-time prediction of SVFs.To circumvent the limited amount of observational data,we employ transfer learning by first training the model using reanalysis datasets,followed by fine-tuning it using in-situ analysis data to obtain the final prediction model.By utilizing the historical 12-month SVFs as input,our model predicts the SVFs for the subsequent three months.We compare the performance of five models:Artificial Neural Networks(ANN),Long ShortTerm Memory(LSTM),Convolutional LSTM(ConvLSTM),ST-LSTM,and our proposed ST-LSTM-SA model in a test experiment spanning 2019 to 2022.Our results demonstrate that the ST-LSTM-SA model significantly improves the prediction accuracy and stability of sound velocity in both temporal and spatial dimensions.The ST-LSTM-SA model not only accurately predicts the ocean sound velocity field(SVF),but also provides valuable insights for spatiotemporal prediction of other oceanic environmental variables.

In vivo label-free measurement of blood flow velocity symmetry based on dual line scanning third-harmonic generation microscopy excited at the 1700 nm window

Measurement of bloodflow velocity is key to understanding physiology and pathology in vivo.While most measurements are performed at the middle of the blood vessel,little research has been done on characterizing the instantaneous bloodflow velocity distribution.This is mainly due to the lack of measurement technology with high spatial and temporal resolution.Here,we tackle this problem with our recently developed dual-wavelength line-scan third-harmonic generation(THG)imaging technology.Simultaneous acquisition of dual-wavelength THG line-scanning signals enables measurement of bloodflow velocities at two radially symmetric positions in both venules and arterioles in mouse brain in vivo.Our results clearly show that the instantaneous bloodflow velocity is not symmetric under general conditions.

Flood Velocity Prediction Using Deep Learning Approach

Floods are one of the most serious natural disasters that can cause huge societal and economic losses.Extensive research has been conducted on topics like flood monitoring,prediction,and loss estimation.In these research fields,flood velocity plays a crucial role and is an important factor that influences the reliability of the outcomes.Traditional methods rely on physical models for flood simulation and prediction and could generate accurate results but often take a long time.Deep learning technology has recently shown significant potential in the same field,especially in terms of efficiency,helping to overcome the time-consuming associated with traditional methods.This study explores the potential of deep learning models in predicting flood velocity.More specifically,we use a Multi-Layer Perceptron(MLP)model,a specific type of Artificial Neural Networks(ANNs),to predict the velocity in the test area of the Lundesokna River in Norway with diverse terrain conditions.Geographic data and flood velocity simulated based on the physical hydraulic model are used in the study for the pre-training,optimization,and testing of the MLP model.Our experiment indicates that the MLP model has the potential to predict flood velocity in diverse terrain conditions of the river with acceptable accuracy against simulated velocity results but with a significant decrease in training time and testing time.Meanwhile,we discuss the limitations for the improvement in future work.

Edge modes in finite-size systems with different edge terminals

We investigate the behavior of edge modes in the presence of different edge terminations and long-range(LR)hopping.Here,we mainly focus on such model crystals with two different types of structures(type I:“…-P-Q-P-Q-…”and type II:“…=P-Q=P-Q=…”),where P and Q represent crystal lines(CLs),while the symbols“-”and“=”denote the distance between the nearest neighbor(NN)CLs.Based on the lattice model Hamiltonian with LR hopping,the existence of edge modes is determined analytically by using the transfer matrix method(TMM)when different edge terminals are taken into consideration.Our findings are consistent with the numerical results obtained by the exact diagonalization method.We also notice that edge modes can exhibit different behaviors under different edge terminals.Our result is helpful in solving novel edge modes in honeycomb crystalline graphene and transition metal dichalcogenides with different edge terminals.

Origin of tradeoff between movement velocity and attachment duration of kinesin motor on a microtubule

Kinesin-1 motor protein is a homodimer containing two identical motor domains connected by a common long coiledcoil stalk via two flexible neck linkers. The motor can step on a microtubule with a velocity of about 1 μm·s-1and an attachment duration of about 1 s under physiological conditions. The available experimental data indicate a tradeoff between velocity and attachment duration under various experimental conditions, such as variation of the solution temperature,variation of the strain between the two motor domains, and so on. However, the underlying mechanism of the tradeoff is unknown. Here, the mechanism is explained by a theoretical study of the dynamics of the motor under various experimental conditions, reproducing quantitatively the available experimental data and providing additional predictions. How the various experimental conditions lead to different decreasing rates of attachment duration versus velocity is also explained.

Probing the Galactic Halo with RR Lyrae Stars.VI.The Radial Velocity Curve Templates of RRc Stars

We present radial velocity(RV)curve templates of RR Lyrae first-overtone(RRc)stars constructed with the Mg I b triplet and Hαlines using time-domain Medium-Resolution Survey spectra of seven RRc stars from Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST)Data Release 9.Additionally,we derive the relation between the stellar RV curve amplitudes and g-band light curve amplitudes from Zwicky Transient Facility(ZTF)public survey.For those RRc stars without ZTF g-band light curves,we provide the conversions from the light curve amplitudes in ZTF r-and i-bands,Gaia G-band,and V-band from the All-Sky Automated Survey for Supernovae to those in ZTF g-band.We validate our RV curve templates using the RRc star SV Scl and find the uncertainties of systemic RV are less than 2.11 km s~(-1)and 6.08 km s~(-1)based on the Mg I b triplet and Hαlines,respectively.We calculate the systemic RVs of 30 RRc stars using the RV curve templates constructed with the Mg I b triplet and Hαlines and find the systemic RVs are comparable with each other.This RV curve template will be particularly useful for obtaining the systemic RV of RRc using the LAMOST spectroscopy.

The Impact of Privatization on Terminal Efficiency: A Case Study of Tema Port

Port and terminal efficiency are of utmost importance to the container shipping industry due to their significance in enhancing the competitive advantage of ports within a region. Consequently, there have always been notable variations of studies around it. This paper analyzes the impact of privatization on terminal efficiency using the Port of Tema as a Case Study. The main objective of this paper is to analyze the efficiency trends of the public and private terminals in the port over the years. To achieve this objective, DEA-CCR methodology was employed to calculate the annual technical efficiency trends of the private and public terminals using four input variables and three output variables. The main results of the paper indicated that the public and private terminals were efficient for multiple years. However, the efficiency scores over the years demonstrated inconsistency, exhibiting notable fluctuations. The findings of this study will aid policymakers across the region on policies relating to the efficiency and ownership structure of ports and terminals.

Mixed Integer Robust Programming Model for Multimodal Fresh Agricultural Products Terminal Distribution Network Design

The low efficiency and high cost of fresh agricultural product terminal distribution directly restrict the operation of the entire supply network.To reduce costs and optimize the distribution network,we construct a mixed integer programmingmodel that comprehensively considers tominimize fixed,transportation,fresh-keeping,time,carbon emissions,and performance incentive costs.We analyzed the performance of traditional rider distribution and robot distribution modes in detail.In addition,the uncertainty of the actual market demand poses a huge threat to the stability of the terminal distribution network.In order to resist uncertain interference,we further extend the model to a robust counterpart form.The results of the simulation show that the instability of random parameters will lead to an increase in the cost.Compared with the traditional rider distribution mode,the robot distribution mode can save 12.7%on logistics costs,and the distribution efficiency is higher.Our research can provide support for the design of planning schemes for transportation enterprise managers.

Improved STNModels and Heuristic Rules for Cooperative Scheduling in Automated Container Terminals

Improving the cooperative scheduling efficiency of equipment is the key for automated container terminals to copewith the development trend of large-scale ships. In order to improve the solution efficiency of the existing spacetimenetwork (STN) model for the cooperative scheduling problem of yard cranes (YCs) and automated guidedvehicles (AGVs) and extend its application scenarios, two improved STN models are proposed. The flow balanceconstraints in the original model are decomposed, and the trajectory constraints of YCs and AGVs are added toacquire the model STN_A. The coupling constraint in STN_A is updated, and buffer constraints are added toSTN_A so that themodel STN_B is built.As the size of the problem increases, the solution speed of CPLEX becomesthe bottleneck. So a heuristic method containing three groups of heuristic rules is designed to obtain a near-optimalsolution quickly. Experimental results showthat the computation time of STN_A is shortened by 49.47% on averageand the gap is reduced by 1.69% on average compared with the original model. The gap between the solution ofthe heuristic rules and the solution of CPLEX is less than 3.50%, and the solution time of the heuristic rules is onaverage 99.85% less than the solution time of CPLEX. Compared with STN_A, the computation time for solvingSTN_B increases by 58.93% on average.

Machine learning for predicting the outcome of terminal ballistics events

Machine learning(ML) is well suited for the prediction of high-complexity,high-dimensional problems such as those encountered in terminal ballistics.We evaluate the performance of four popular ML-based regression models,extreme gradient boosting(XGBoost),artificial neural network(ANN),support vector regression(SVR),and Gaussian process regression(GP),on two common terminal ballistics’ problems:(a)predicting the V50ballistic limit of monolithic metallic armour impacted by small and medium calibre projectiles and fragments,and(b) predicting the depth to which a projectile will penetrate a target of semi-infinite thickness.To achieve this we utilise two datasets,each consisting of approximately 1000samples,collated from public release sources.We demonstrate that all four model types provide similarly excellent agreement when interpolating within the training data and diverge when extrapolating outside this range.Although extrapolation is not advisable for ML-based regression models,for applications such as lethality/survivability analysis,such capability is required.To circumvent this,we implement expert knowledge and physics-based models via enforced monotonicity,as a Gaussian prior mean,and through a modified loss function.The physics-informed models demonstrate improved performance over both classical physics-based models and the basic ML regression models,providing an ability to accurately fit experimental data when it is available and then revert to the physics-based model when not.The resulting models demonstrate high levels of predictive accuracy over a very wide range of projectile types,target materials and thicknesses,and impact conditions significantly more diverse than that achievable from any existing analytical approach.Compared with numerical analysis tools such as finite element solvers the ML models run orders of magnitude faster.We provide some general guidelines throughout for the development,application,and reporting of ML models in terminal ballistics problems.

Automatic velocity picking based on optimal key points tracking algorithm

Picking velocities from semblances manually is laborious and necessitates experience. Although various methods for automatic velocity picking have been developed, there remains a challenge in efficiently incorporating information from nearby gathers to ensure picked velocity aligns with seismic horizons while also improving picking accuracy. The conventional method of velocity picking from a semblance volume is computationally demanding, highlighting a need for a more efficient strategy. In this study, we introduce a novel method for automatic velocity picking based on multi-object tracking. This dynamic tracking process across different semblance panels can integrate information from nearby gathers effectively while maintaining computational efficiency. First, we employ accelerated density clustering on the velocity spectrum to discern cluster centers without the requirement for prior knowledge regarding the number of clusters. These cluster centers embody the maximum likelihood velocities of the main subsurface structures. Second, our proposed method tracks key points within the semblance volume. Kalman filter is adopted to adjust the tracking process, followed by interpolation on these tracked points to construct the final velocity model. Our synthetic data example demonstrates that our proposed algorithm can effectively rectify the picking errors of the clustering algorithm. We further compare the performances of the clustering method(CM), the proposed tracking method(TM), and the variational method(VM) on a field dataset from the Gulf of Mexico. The results attest that our method offers superior accuracy than CM, achieves comparable accuracy with VM, and benefits from a reduced computational cost.

Clinical Epidemiology and Surgical Treatment of Spontaneous Perforations of the Terminal Ileum: A Multicentre Study in Cameroon

Background: Perforations of the terminal ileum are a frequent clinical situation and a therapeutic challenge. Surgical treatment is controversial. Several surgical modalities have been proposed and postoperative morbidity and mortality remain high. The aim of this study was to review our experience in the surgical management of perforations of the terminal ileum. Patients and methods: This is a descriptive cross-sectional study with retrospective data collection from January 1, 2017 to December 31, 2021, in five hospitals in Cameroon. Patients’ demographic, clinical presentation, surgical findings and 30-days postoperative outcomes data were collected. Results: We collected 34 files. The sex ratio was 1.4 and the average age was 20.28 years. The average consultation time was 9.1 days. Abdominal pain was present in all our patients. Peritoneal irritation was present in 46 cases (88.5%). The mean time to treatment after admission was 17.5 hours. The perforation was unique in 40 cases (76.9%) and located between 6 and 10 cm from the ileocecal valve in 29 cases (55.8%). Typhoid was the most suspected etiology intraoperatively in 38 cases (73.1%). A simple suture was performed in 18 patients (34.6%), resection with anastomosis in 11 patients (21.2%) and an ileostomy in 5 patients (9.6%). The average length of hospitalization was 21.74 days. Postoperative morbidity and mortality were 32.7% and 17.3% respectively. Conclusion: Perforations of the terminal ileum are common and affect young people. Surgical procedures are varied. Reducing consultation and care times and respecting treatment principles could improve postoperative morbidity and mortality, which remain high.

Velocity equation for grenades while impacting on dry sand media

This paper deals with the collision of sphere shape grenades with sand media.The central issue of the article is the establishing of an empirical velocity equation of the grenade while impacting on sand that is used to solve motion equations of the mechanical mechanism inside the impact grenade fuze.The paper focuses on impact velocities that are lower than 5 m s^(-1).An experiment was conducted to study the velocity of the grenade while impacting on dry sand.A high-speed camera video was used to capture the grenade positions.The grenade velocity in the impact process was generated from these video data.Some types of fitting curves are used to regress the velocity equation of the grenade while interacting with the sand media and the best-fitting model is chosen.The result shows the regression curve has a high correlation with the experiment data for grenade velocities below 5 m s^(-1).The received regression equation is useful for analyzing the working ability of the inertial mechanism inside the impact grenade or analyzing and choosing the appropriate parameters of each part in the inertial mechanism to meet the required characteristics of the mechanism.

Swimming velocity of spherical squirmers in a square tube at finite fluid inertia

The three-dimensional lattice Boltzmann method(LBM)is used to simulate the motion of a spherical squirmer in a square tube,and the steady motion velocity of a squirmer with different Reynolds numbers(Re,ranging from 0.1 to 2)and swimming types is investigated and analyzed to better understand the swimming characteristics of microorganisms in different environments.First,as the Reynolds number increases,the effect of the inertial forces becomes significant,disrupting the squirmer's ability to maintain its theoretical velocity.Specifically,as the Reynolds number increases,the structure of the flow field around the squirmer changes,affecting its velocity of motion.Notably,the swimming velocity of the squirmer exhibits a quadratic relationship with the type of swimming and the Reynolds number.Second,the narrow tube exerts a significant inhibitory effect on the squirmer motion.In addition,although chirality does not directly affect the swimming velocity of the squirmer,it can indirectly affect the velocity by changing its motion mode.

Structural similarity of lithospheric velocity models of Chinese mainland

Existing lithospheric velocity models exhibit similar structures typically associated with the first-order tectonic features,with dissimilarities due to different data and methods used in model generation.The quantification of model structural similarity can help in interpreting the geophysical properties of Earth's interior and establishing unified models crucial in natural hazard assessment and resource exploration.Here we employ the complex wavelet structural similarity index measure(CW-SSIM)active in computer image processing to analyze the structural similarity of four lithospheric velocity models of Chinese mainland published in the past decade.We take advantage of this method in its multiscale definition and insensitivity to slight geometrical distortion like translation and scaling,which is particularly crucial in the structural similarity analysis of velocity models accounting for uncertainty and resolution.Our results show that the CW-SSIM values vary in different model pairs,horizontal locations,and depths.While variations in the inter-model CW-SSIM are partly owing to different databases in the model generation,the difference of tomography methods may significantly impact the similar structural features of models,such as the low similarities between the full-wave based FWEA18 and other three models in northeastern China.We finally suggest potential solutions for the next generation of tomographic modeling in different areas according to corresponding structural similarities of existing models.

Natural vibration and critical velocity of translating Timoshenko beam with non-homogeneous boundaries

In most practical engineering applications,the translating belt wraps around two fixed wheels.The boundary conditions of the dynamic model are typically specified as simply supported or fixed boundaries.In this paper,non-homogeneous boundaries are introduced by the support wheels.Utilizing the translating belt as the mechanical prototype,the vibration characteristics of translating Timoshenko beam models with nonhomogeneous boundaries are investigated for the first time.The governing equations of Timoshenko beam are deduced by employing the generalized Hamilton's principle.The effects of parameters such as the radius of wheel and the length of belt on vibration characteristics including the equilibrium deformations,critical velocities,natural frequencies,and modes,are numerically calculated and analyzed.The numerical results indicate that the beam experiences deformation characterized by varying curvatures near the wheels.The radii of the wheels play a pivotal role in determining the change in trend of the relative difference between two beam models.Comparing the results unearths that the relative difference in equilibrium deformations between the two beam models is more pronounced with smaller-sized wheels.When the two wheels are of equal size,the critical velocities of both beam models reach their respective minima.In addition,the relative difference in natural frequencies between the two beam models exhibits nonlinear variation and can easily exceed 50%.Furthermore,as the axial velocities increase,the impact of non-homogeneous boundaries on modal shape of translating beam becomes more significant.Although dealing with non-homogeneous boundaries is challenging,beam models with non-homogeneous boundaries are more sensitive to parameters,and the differences between the two types of beams undergo some interesting variations under the influence of non-homogeneous boundaries.

Damage Evolution of Ballastless Track Concrete Exposed to Flexural Fatigue Loads:The Application of Ultrasonic Pulse Velocity,Impact-echo and Surface Electrical Resistance Method

In order to clarify the fatigue damage evolution of concrete exposed to flexural fatigue loads,ultrasonic pulse velocity(UPV),impact-echo technology and surface electrical resistance(SR) method were used.Damage variable based on the change of velocity of ultrasonic pulse(Du) and impact elastic wave(Di)were defined according to the classical damage theory.The influences of stress level,loading frequency and concrete strength on damage variable were measured.The experimental results show that Du and Di both present a three-stages trend for concrete exposed to fatigue loads.Since impact elastic wave is more sensitive to the microstructure damage in stage Ⅲ,the critical damage variable,i e,the damage variable before the final fracture of concrete of Di is slightly higher than that of Du.Meanwhile,the evolution of SR of concrete exposed to fatigue loads were analyzed and the relationship between SR and Du,SR and Di of concrete exposed to fatigue loads were established.It is found that the SR of concrete was decreased with the increasing fatigue cycles,indicating that surface electrical resistance method can also be applied to describe the damage of ballastless track concrete exposed to fatigue loads.

Effects of nutrient limitations on the sinking velocity of Thalassiosira weissflogii

The sinking of diatoms is critic al to the formation of oceanic biological pumps and coastal hypoxic zones.However,little is known about the effects of different nutrient restrictions on diatom sinking.In this study,we measured the sinking velocity(SV) of Thalassiosira weissflogii using a new phytoplankton video observation instrument and analyzed major biochemical components under varying nutrient conditions.Our results showed that the SV of T.weissflogii under different nutrient limitation conditions varied substantially.The highest SV of(1.77±0.02) m/d was obtained under nitrate limitation,signific antly surpassing that under phosphate limitation at(0.98±0.13) m/d.As the nutrient limitation was released,the SV steadily decreased to(0.32±0.03) m/d and(0.15±0.05) m/d,respectively.Notably;under conditions with limited nitrate and phosphate concentrations,the SV values of T.weissflogii significantly positively correlated with the lipid content(P <0.001),with R^(2) values of 0.86 and 0.69,respectively.The change of the phytoplankton SV was primarily related to the intracellular compo sition,which is controlled by nutrient conditions but did not significantly correlate with transparent extracellular polymer and biosilica contents.The results of this study help to understand the regulation of the vertical sinking process of diatoms by nutrient restriction and provide new insights into phytoplankton dynamics and their relationship with the marine nutrient structure.