Motion Trend Research Articles

Monitoring slow uplift and subsidence in shallow seafloor environments using bottom pressure measurements

Summary Ultra-slow seafloor deformations are frequent in several marine environments like volcanic calderas, offshore oil and gas extraction fields subject to subsidence, and river delta regions; they can exhibit unpredictable behaviors, particularly in caldera systems situated along coastlines. However, offshore monitoring of seafloor uplift and subsidence is still very challenging. Here we present a new method to recover vertical seafloor deformation at Campi Flegrei caldera (CFc), Southern Italy, using Bottom Pressure Recorder (BPR) sensors, tide gauges and a barometer. Using data from two BPRs installed on the seabed within the MEDUSA marine infrastructure of the INGV ‘Osservatorio Vesuviano’, we transform pressure measurements into equivalent water level changes to derive the vertical seafloor displacements. We obtain high accuracy, vertical deformation records from the BPRs measurements by taking into account the high-resolution mean seawater density variation over time, estimated by applying an innovative procedure to the BPRs data and using additional barometric and sea level data. We obtained for the two BPRs an uplift of 22.8 cm over about two years, and 7 cm over about 18 months, respectively. We compare the results with data acquired by GPSs installed on the top of MEDUSA buoys, deployed at the same sites as the BPRs, which recorded the vertical seafloor deformation values of 22 cm and 6.9 cm, respectively, over the same periods. These independent datasets show a strong correlation, with correlation coefficient values of 0.98 and 0.87, and very good agreement in both the trend and amplitude of vertical motion, proving the reliability of BPRs in accurately measuring vertical seafloor deformation. The methodology we developed allows a cost-effective implementation of high accuracy seafloor vertical deformation monitoring networks.

Rapid estimation of source parameters for the 2022 Mw 6.6 Menyuan earthquake with combined high-rate GNSS and strong motion data in Northeastern Tibet

To investigate the reliability of high-rate GNSS in the rapid estimation of source parameters for the 2022 Menyuan Mw 6.6 earthquake, we collected high-rate GNSS and strong motion data within a 200 km radius of the epicenter. We performed high-precision calculations to obtain three-dimensional dynamic displacement waveforms for all stations and analyzed the reliability of source parameter estimation and coseismic deformation acquisition. The three-dimensional dynamic displacement waveforms show that the amplitude of displacement fluctuations at each station decreases with increasing distance from the epicenter. The station closest to the epicenter, C007, recorded a maximum east–west amplitude of 15 cm, a north–south amplitude of 10.8 cm, and a vertical amplitude of only 2.2 cm. The inverted epicenter location using displacement waveforms is (101.263°E, 37.802°N), with an origin time of 17:45:25.9 (UTC) and a magnitude of Mw 6.65. These results are generally consistent with those obtained from seismological methods using the seismic data. By combining high-rate GNSS and strong-motion data for magnitude estimation, an initial value of Mw 6.0 can be obtained 15 s after the earthquake, with stable convergence to Mw 6.6 within 40 s. The quality of magnitude estimation convergence is positively correlated with the number of stations. Based on the displacement waveforms 100 s before and after the earthquake, the coseismic deformation of this event can be quickly obtained. The results show opposite motion trends on the south and north sides of the seismogenic fault, with no significant vertical movement. Our results indicate that using near-field high-rate GNSS and strong motion data can rapidly and effectively estimate the source parameters and coseismic deformation of the strong earthquake, which can provide valuable reference for post-earthquake emergency response and rapid disaster assessment.

A safety posture field framework for mobile manipulators based on human–robot interaction trend and platform-arm coupling motion

Mobile manipulators are increasingly deployed in industrial settings, such as material handling and workpiece loading, where they must safely interact with humans while efficiently completing tasks. Existing motion planning methods for mobile manipulators often struggle to ensure both safety and efficiency in dynamic human-robot interaction environments. This paper proposes a Safety Posture Field framework that addresses these limitations by firstly predicting human motion trends using the improved Long Short-Term Memory neural network and applying these predictions to potential field calculations for both the mobile platform and the robotic arm. During different stages of human-robot interaction, the mobile manipulator places varying emphasis on safety and efficiency while in motion. Additionally, when the robotic arm executes operations, a platform-arm coupling motion strategy is introduced when the potential field detects risks of singularity or local optima, preventing the robotic arm from becoming unstable or failing to reach the target pose in time. This strategy enhances the system's flexibility and operational stability. Comparative experiments in simulation and real-world settings confirm the ability of the framework to maintain high safety standards while improving task efficiency, making it suitable for industrial Human-Robot Interaction applications.

SAM-Net: Spatio-Temporal Sequence Typhoon Cloud Image Prediction Net with Self-Attention Memory

Cloud image prediction is a spatio-temporal sequence prediction task, similar to video prediction. Spatio-temporal sequence prediction involves learning from historical data and using the learned features to generate future images. In this process, the changes in time and space are crucial for spatio-temporal sequence prediction models. However, most models now rely on stacking convolutional layers to obtain local spatial features. In response to the complex changes in cloud position and shape in cloud images, the prediction module of the model needs to be able to extract both global and local spatial features from the cloud images. In addition, for irregular cloud motion, more attention should be paid to the spatio-temporal sequence features between input cloud image frames in the temporal sequence prediction module, considering the extraction of temporal features with long temporal dependencies, so that the spatio-temporal sequence prediction network can learn cloud motion trends more accurately. To address these issues, we have introduced an innovative model called SAM-Net. The self-attention module of this model aims to extract an inner image frame’s spatial features of global and local dependencies. In addition, a memory mechanism has been added to the self-attention module to extract interframe features with long temporal and spatial dependencies. Our method shows better performance than the PredRNN-v2 model on publicly available datasets such as MovingMNIST and KTH. We achieved the best performance in both the 4-time-step and 10-time-step typhoon cloud image predictions. On a cloud dataset consisting of 10 time steps, we observed a decrease in MSE of 180.58, a decrease in LPIPS of 0.064, an increase in SSIM of 0.351, and a significant improvement in PSNR of 5.56 compared to PredRNN-v2.

Mitral annular dynamics after transcatheter edge-to-edge repair for functional mitral regurgitation: comparison with surgical annuloplasty

Abstract Background Transcatheter edge-to-edge repair (TEER) is a recently emerged therapeutic option for functional mitral regurgitation (FMR). Although the mitral annular shape and function may play an important role in the pathophysiology of FMR, few reports have evaluated the impact of TEER. We sought to investigate the impact of TEER on the mitral annulus and its motion in FMR compared with that of mitral annuloplasty (MAP). Methods Using three-dimensional transesophageal echocardiography, we evaluated the mitral annular morphology and dynamic motion in patients who underwent TEER or MAP before and after the procedures. Mitral annulus analysis was performed by a semi-automatic program to create a dynamic model of the three-dimensional structure, where the end-systolic annular structure was semi-automatically annotated and manually corrected, followed by automatic tracking of the annulus throughout the cardiac cycle . The mitral annular parameters such as mitral annular diameters, area, circumference, and height at all frames were automatically calculated from the model. In order to align the cardiac phase in each patient (i.e. to set the start and the end of diastole and systole at the same time for all patient), data were spline-interpolated to 100 systolic and 200 diastolic frames and then statistically analyzed. The dynamic changes of the parameters during the cardiac cycle were calculated as (maximum – minimum value) / maximum value after the interpolation. Results Patients who underwent TEER (n=20, 69±15 years, 40% female) and those who underwent MAP (n=16, 64±11 years, 6% female) had similar echocardiographic characteristics before the procedures. The maximum anteroposterior diameter and annulus area decreased after both TEER and MAP, while the intercommissural diameter decreased only after MAP but not after TEER. After TEER, the dynamic change in anteroposterior diameter throughout the cardiac cycle tended to decrease (p=0.055), while intercommissural change rather increased (p=0.049), resulting in preserved change in annulus area (p=0.74). After MAP, changes in both diameters and area decreased significantly (all p<0.05). MAP was associated with postoperative mitral annulus area immobility after adjustment (p=0.030). Conclusions The dynamic motion of the mitral annulus in patients with FMR was better preserved after TEER than after MAP. There was a decreasing trend in anteroposterior motion, which was compensated for by intercommissural motion after TEER. Future studies are needed to determine the association of these results with cardiac function and prognosis.

A novel collaborative collision avoidance decision method for multi-ship encounters in complex waterways

With the continuous growth of maritime traffic volume, multi-ship collision avoidance has gradually become one of the most crucial issues in ensuring the safety of ship navigation. This study proposes a multi-ship collaborative collision avoidance decision model (MCCA) to address the issue of multi-ship encounters in complex waterways. The model takes into account the ship spatio-temporal collision risk, relative motion trends, as well as the safety and economic considerations of ship navigation. A comprehensive collision avoidance method is designed based on the velocity obstacle method, enabling simultaneous adjustments both course and speed, with the aim of minimizing economic losses incurred by ships due to avoidance operations while ensuring ship navigation safety. Meanwhile, the NSGA-II algorithm, which has faster convergence and better effect, is used to calculate the optimal collaborative collision avoidance decision of multiple ships. Besides, both simulation and example validation are used to test the validity of the model. The results indicate that the proposed model can effectively achieve multi-ship collaborative collision avoidance in the region. Simultaneously, it holds significant reference value for guaranteeing the safety of ship navigation, enhancing supervision efficiency, and promoting the development of intelligent ship navigation systems.

Capacity of a set of CMIP6 models to simulate Arctic sea ice drift

Abstract Evaluating CMIP6 model performance helps to improve the prediction of future changes in Arctic sea ice. We analyze the seasonal cycles, distribution, and evolution of sea ice in different regions from 1979 to 2014. We compare the output from selected CMIP6 models with reference data for sea ice motion. We also discuss the correlations between sea ice motion(SIM) and sea ice thickness (SIT) in reference data, and how CMIP6 models explain them. We select EC-Earth3, ACCESS-CM2, BCC-CSM2-MR, MPI-ESM1-2-HR, and NorESM2-LM for CMIP6 study. We compare outputs with reference data: Sea ice extent (SIE) from NSIDC; SIT from PIOMAS; and SIM from the IABP buoy data. Analytical techniques include Theil-Sen and Ordinary least squares (OLS) regression. Most selected CMIP6 models have seasonal cycles of SIM lagging behind IABP observations by 1-2 month and overestimate central Arctic SIM magnitude, with MPI-ESM1-2-HR having the highest discrepancy and NorESM2-LM lowest. The models show better simulation of SIM in the ice melting season than in the growing season. Models perform worse at capturing regional differences in SIM evolution and are overly conservative when simulating the increasing trend in ice motion, especially in coastal Arctic seas during summer. There is significant negative correlation between SIT and SIM in October.

LLMDiff: Diffusion Model Using Frozen LLM Transformers for Precipitation Nowcasting.

Precipitation nowcasting, which involves the short-term, high-resolution prediction of rainfall, plays a crucial role in various real-world applications. In recent years, researchers have increasingly utilized deep learning-based methods in precipitation nowcasting. The exponential growth of spatiotemporal observation data has heightened interest in recent advancements such as denoising diffusion models, which offer appealing prospects due to their inherent probabilistic nature that aligns well with the complexities of weather forecasting. Successful application of diffusion models in rainfall prediction tasks requires relevant conditions and effective utilization to direct the forecasting process of the diffusion model. In this paper, we propose a probabilistic spatiotemporal model for precipitation nowcasting, named LLMDiff. The architecture of LLMDiff includes two networks: a conditional encoder-decoder network and a denoising network. The conditional network provides conditional information to guide the denoising network for high-quality predictions related to real-world earth systems. Additionally, we utilize a frozen transformer block from pre-trained large language models (LLMs) in the denoising network as a universal visual encoder layer, which enables the accurate estimation of motion trend by considering long-term temporal context information and capturing temporal dependencies within the frame sequence. Our experimental results demonstrate that LLMDiff outperforms state-of-the-art models on the SEVIR dataset.

Study on the influence of labyrinth seal structure on the performance of shrouded stator cascades with inter-stage cavities

Numerical simulations of a shrouded stator cascade with an inter-stage cavity were conducted using validated numerical methods to investigate the impact of different labyrinth seal structures and positions on the aerodynamic performance of the stator cascade. The study discussed the development trends of secondary flow motion and corner separation within the cascade under different labyrinth seal structures, evaluated the stator performance using total pressure loss coefficient and entropy-based loss coefficient, and revealed the interaction between cavity leakage flow and mainstream flow. The results indicate that individually changing the labyrinth seal structure or position has a negligible impact on stator performance, but simultaneously altering both the structure and position of the labyrinth seal can effectively reduce stator losses. The structure case 1-position case 2 labyrinth seal structure can reduce total pressure loss by 6.25%, while structure case 4-position case 4 reduces entropy increase loss coefficient by 7.67%. Additionally, it was found that changing the labyrinth seal structure and position can increase the circumferential velocity and momentum of cavity leakage flow at the cavity outlet, enhance the resistance of cavity leakage flow to circumferential secondary flow within the stator passage, and reduce stator losses. Altering the structure and position of the labyrinth seal effectively reduces the cavity leakage vortex at the leading edge of the cascade during the mixing process of cavity leakage flow with the mainstream, causing the passage vortex to move rearward axially.

Influence of impact velocity on the semi-sealed cylindrical shell during water entry

To study the motion characteristics and cavity evolution of the cylindrical shell with different initial velocity, the numerical simulation based on the Star-CCM+ and ABAQUS collaborative simulation method is carried out in this paper. The results show that when the shell penetrates into the water at a lower speed, only a small amount of external fluid can enter into the shell, and the internal fluid shows a reciprocating motion trend. Moreover, the speed of the shell and the force at the bottom wall show a fluctuating trend. As the speed increases, the volume of fluid entering into the interior of the shell gradually increases. After the speed reaches 30 m/s, the fluid can impact the upper wall of the shell, which also causes sudden changes in velocity and displacement. When the initial velocity of the shell reaches 80 m/s, significant deformation occurs at the upper wall of the shell, and the deformation is not fully restored after the fluid leaves the upper wall. As the speed increases, the degree of deformation gradually increases, and the volume of the cavity gradually increases.

Research on innovative fluid-driven pipe-strut tensegrity structure

As a self-equilibrated system under prestresses, the internal forces and geometric configurations of tensegrity structures are highly related. Consequently, by employing active control units internally, the lengths of structural components can be adjusted, enabling control over the structural shape and facilitating its motion and actuation. Fluid actuation, as a common type of driving mechanism, is typically achieved by using external fluid actuators or directly replacing structural components with them. In order to better realize the combination of flexible, efficient and adaptable fluid-driven strategy with lightweight, flexible and adjustable tensegrity structure, this paper proposes an innovative pipe-strut tensegrity structure based on the topology of traditional tensegrity structure. In the proposed structure, conventional cables are replaced by flexible pipes to establish a continuous fluid path. This construction concept promotes the flow of fluid within the structure, enabling the proposed structure to deform or move under the influence of the fluid flow. With structural and hydraulic analyses serving as the theoretical foundation, a simplified calculation theory based on the fluid-structure interaction is thoroughly investigated to analyze this innovative structure. Two specific examples are presented to demonstrate the feasibility of the novel configuration, validate the accuracy of the proposed calculation theory, and verify the possibility of deformation and motion trend of the proposed fluid-driven pipe-strut structure.

Contributions of core, mantle and climatological processes to Earth’s polar motion

Earth’s spin axis slowly moves relative to the crust over time. A 120-year-long record of this polar motion from astronomical and more modern geodetic measurements displays interannual and multidecadal fluctuations of 20 to 40 milliarcseconds superimposed on a secular trend of about 3 milliarcseconds per year. Earth’s polar motion is thought to be driven by various surface and interior processes, but how these processes operate and interact to produce the observed signal remains enigmatic. Here we show that predictions made by an ensemble of physics-informed neural networks trained on measurements to capture geophysical processes can explain the main features of the observed polar motion. We find that glacial isostatic adjustment and mantle convection primarily account for the secular trend. Mass redistribution on the Earth’s surface—for example, ice melting and global changes in water storage—yields a relatively weak trend but explains about 90% of the interannual and multidecadal variations. We also find that core processes contribute to both the secular trend and fluctuations in polar motion, either due to variations in torque at the core–mantle boundary or dynamical feedback of the core in response to surface mass changes. Our findings provide constraints on core–mantle interactions for which observations are rare and global ice mass balance over the past century and suggest feedback operating between climate-related surface processes and core dynamics.

Effect of magnetic needle magnetic particle grinding process on the performance of metal aluminum plates

Magnetic needle grinding processing technology is one of the magnetic grinding processing techniques. It possesses the characteristics of micro-cutting removal, small increase in processing temperature, flexible processing, high-quality, and high-precision processing. It is mainly utilized to remove burrs at the edge of the workpiece and the edge of the hole, as well as to finish the surface of the workpiece. It is frequently employed in civil, aerospace, navigation, and other fields. Due to the randomness and complexity of magnetic needle movement in magnetic abrasive finishing, it is difficult to quantify the processing parameters and predict processing effects. Therefore, this paper establishes a simulation model of magnetic needle in magnetic abrasive finishing by the coupling numerical simulation method of fluid dynamics discrete element method (CFD-DEM) to analyze the working state parameters of the magnetic needle. Through the simulation of actual working conditions, the machining process and parameters of magnetic abrasive finishing are quantified and analyzed, and the motion trend of magnetic needles during the machining process is studied. Then, the residual stress of single magnetic needle impact is analyzed with ABAQUS, and the performance enhancement of the workpiece is predicted. Finally, observations of surface morphology and validation of residual stress prediction were conducted through experiments on an aluminum plate. The results show that the residual stress of the aluminum plate is positively correlated with the number of strikes of the magnetic needle. The residual stress changes from tensile stress (+0.1 MPa) to compressive stress (-16.5 MPa). The comparison between simulation results and experimental results is good, indicating that the simulation model can comprehensively consider multiple factors such as magnetic field, particle motion, and fluid flow, and establish a magnetic needle magnetic grinding process model that is suitable for actual working conditions.

Membrane/electrolyte interplay on ammonia motion inside a flow-cell for electrochemical nitrogen and nitrate reduction

Electrochemical ammonia production from molecular nitrogen and nitrate reduction reactions at ambient conditions has gained a lot of attention in recent years, making this topic more and more appealing. The race towards good and quick results in terms of Faradaic efficiency and productivity is not always focused on the possible source of ammonia contamination. In particular, Nafion membrane is the most commonly used in this field as cell separator, discarding the possible known disadvantages coming from ammonium ions absorption and release. The wettable microporous Celgard membrane has been proposed as a substitute for Nafion membranes, despite the separation mechanism, in this case, is only dimension-driven, so it does not assure ammonium ions retention. This paper reveals that the mechanism of ammonium ions absorption and release by Nafion 117 is strongly related to the cations present in the electrolyte and to a lesser extent by its pH value. On the other hand, Celgard membrane does not show any relevant ammonium ions absorption. Moreover, the different trend of ammonium ions motion from catholyte to anolyte solution inside a flow-cell reactor shows that none of the membranes is able to avoid ammonium ions crossover and that there is a correlation between the applied potential and the motion trend. Electrochemical nitrogen and nitrate reduction tests confirm how Nafion membrane can have a big impact on the final result of ammonium ions production, especially when dealing with low production quantities, leading to mistakes in the real quantity of ammonium ions coming from the reduction reaction.

Exploring the InSAR Deformation Series Using Unsupervised Learning in a Built Environment

As a city undergoes large-scale construction and expansion, there is an urgent need to monitor the stability of the ground and infrastructure. The time-series InSAR technique is an effective tool for measuring surface displacements. However, interpreting these displacements in a built environment, where observed displacements consist of mixed signals, poses a challenge. This study uses principal component analysis (PCA) and the k-means clustering method for exploring deformation series within an unsupervised learning context. The PCA method extracts the dominant components in deformation series, whereas the clustering method identifies similar deformation series. This method was tested on Kunming City (KMC) using C-band Sentinel-1, X-band TerraSAR-X, and L-band ALOS-2 PALSAR-2 data acquired between 2017 to 2022. The experiment demonstrated that the suggested unsupervised learning approach can group PS points with similar kinematic characteristics. Five types of deformation kinematic characteristics were discovered in the three SAR datasets: upward, slight upward, stability, slight downward, and downward. According to the results, less than 20% of points exhibit significant motion trends, whereas 50% show small velocity values but still demonstrate movement trends. The remaining 30% are relatively stable. Similar clustering results were obtained from the three datasets using unsupervised methods, highlighting the effectiveness of identifying spatial–temporal patterns over the study area. Moreover, It was found that clustering based on kinematic characteristics enhances the interpretation of InSAR deformation, particularly for points with small deformation velocities. Finally, the significance of PCA decomposition in interpreting InSAR deformation was discussed, as it can better represent series with noise, enabling their accurate identification.

Experiments investigation on atomization characteristics of a liquid jet in a supersonic combustor

The atomization characteristics of a liquid jet in a supersonic combustor were studied experimentally for the first time. A phase doppler anemometry (PDA) system was utilized for the measurement of droplets properties along the cross-sectional area of spray plumes inside the cavity. The results were obtained under the inflow conditions of Ma = 2.0 supersonic crossflow with a stagnation pressure of 0.55 MPa and a stagnation temperature of 300 K. The size and velocity distribution of droplet inside the cavity are obtained based on the PDA measurements. It was found that the Sauter Mean Diameter (SMD) distribution of droplets inside the cavity ranged from 30 to 55 μm. The average streamwise velocity ranged from −20 to 150 m/s and the average vertical velocity ranged from −20 to 30 m/s. Large droplets distribute in the central area of the cavity. Small droplets spread around the central area of the bottom and sidewall areas of the cavity. The area near the sidewall may be an ideal ignition location due to the lower SMD and velocity of droplets. The time-averaged motion trend of droplets in the cavity is proposed experimentally based on the streamwise and spanwise velocity distribution profiles of droplets. The presence of a recirculation zone within the cavity is confirmed. The recirculation area inside the cavity is mainly distributed in the front half of the cavity. The droplets in the cavity show a good tracking performance. With the effect of the airflow, the droplets in the top area of the cavity move toward the bottom and rear wall of the cavity. In addition, the droplets in the middle and bottom area of the cavity move toward the front wall of the cavity especially for droplets near the sidewall. These universal curves can potentially be used for the modeling of a liquid jet in a supersonic combustor.

A spatiotemporal motion prediction network based on multi-level feature disentanglement

The prediction task is significantly challenged by the intricate scene information and motion variations present in spatiotemporal data. Existing prediction methods struggle to accurately forecast long-term outcomes, particularly for transient motions characterized by notable trends, such as hand lifts, jumps, or vehicle turns. To address these challenges, we introduce a Spatiotemporal Motion Prediction Network based on Multi-level Feature Disentanglement (FDPNet). The model delineates spatiotemporal prediction into two distinct stages: feature disentanglement and motion prediction. We first devise a Multi-level Feature Disentanglement (MFD) model to disentangle the multilayer features of motion within the temporal sequence, encompassing period, trend, and residual components. This disentanglement is based on disentangling spatiotemporal coupling, enabling the network to comprehensively grasp the genuine laws governing motion in the spatiotemporal evolution process. Second, to enhance the prediction accuracy of the network over extended periods, we introduce the Motion Differential Self-Attention LSTM unit (MDSA-LSTM). This unit employs differential operations to extract inter-frame motion trends, elevating the network's proficiency in capturing spatiotemporal correlations over long distances through an enhanced self-attention mechanism. FDPNet attains state-of-the-art performance on the Moving MNIST, UCF101, KITTI, and Caltech pedestrian datasets. These outcomes substantiate the substantial potential of this research within the realm of spatiotemporal prediction.

Deciphering the crustal anisotropy and mantle flow beneath the Indo-Burma ranges from the harmonic decomposition of the receiver functions

The hyper-oblique indentation of the Indian plate beneath the Burmese sliver gives rise to the Indo-Burma Ranges (IBR) in the eastern part of the Indian subcontinent. This geological formation encompasses one of the enigmatic hotspots and includes the densely populated regions of India and Myanmar. Harmonic Decomposition (HD) of the receiver functions, derived from the Multi-Taper Correlation (MTC) technique, is used to model seismic anisotropy and morphological crustal deformation caused by subduction underneath IBR. We used teleseismic earthquake data from eleven broadband seismic stations installed within the IBR and its foredeep region. The findings indicate that the attitude of the fast symmetry axis or dipping direction of the interface is influenced by the trend of regional geological features and absolute plate motion, with the IBR exhibiting NNE-SSW and N-S directions and the Himalayan region showing NE-SW and E-W directions. Our results reveal that the coupling of the Indian plate with the Burmese and Eurasian plates induces lithospheric fabrics that align perpendicular to the coupling direction, resulting in anisotropy in the brittle upper crust. Directional analysis of the HD model for the interfaces at the middle or lower crust reveals the strike of the fast symmetry axis in the NNE-SSW direction, which suggests the alignment of minerals and partial melt in the direction of the major shear stress. The interface across the Moho reflects four-lobed periodicity, that is, 90o ambiguity in the strike direction of the fast symmetry axis, varying from the E-W to the N-S directions. The ambiguity indicates the possibility of the 2D-induced entrained mantle flow along the subducting Indian plate and the 3D toroidal flow parallel to the trend of the IBR.

Fragment-based drug design of novel inhibitors targeting lipoprotein (a) kringle domain KIV-10-mediated cardiovascular disease.

Cardiovascular diseases (CVDs) are the leading cause of death globally, attributed to a complex etiology involving metabolic, genetic, and protein-related factors. Lipoprotein(a) (Lp(a)), identified as a genetic risk factor, exhibits elevated levels linked to an increased risk of cardiovascular diseases. The lipoprotein(a) kringle domains have recently been identified as a potential target for the treatment of CVDs, in this study we utilized a fragment-based drug design approach to design a novel, potent, and safe inhibitor for lipoprotein(a) kringle domain. With the use of fragment library (61,600 fragments) screening, combined with analyses such as MM/GBSA, molecular dynamics simulation (MD), and principal component analysis, we successfully identified molecules effective against the kringle domains of Lipoprotein(a). The hybridization process (Breed) of the best fragments generated a novel 249 hybrid molecules, among them 77 exhibiting superior binding affinity (≤ -7kcal/mol) compared to control AZ-02 (-6.9kcal/mol), Importantly, the top ten molecules displayed high similarity to the control AZ-02. Among the top ten molecules, BR1 exhibited the best docking energy (-11.85kcal/mol ), and higher stability within the protein LBS site, demonstrating the capability to counteract the pathophysiological effects of lipoprotein(a) [Lp(a)]. Additionally, principal component analysis (PCA) highlighted a similar trend of motion during the binding of BR1 and the control compound (AZ-02), limiting protein mobility and reducing conformational space. Moreover, ADMET analysis indicated favorable drug-like properties, with BR1 showing minimal violations of Lipinski's rules. Overall, the identified compounds hold promise as potential therapeutics, addressing a critical need in cardiovascular medicine. Further preclinical and clinical evaluations are needed to validate their efficacy and safety, potentially ushering in a new era of targeted therapies for CVDs.

Evaluation of stress and displacement of maxillary canine during the single canine retraction in the maxillary first premolar extraction cases- A finite element study.

This finite element study aimed to simulate maxillary canine movement during anterior teeth retraction. Three methods of maxillary canine movement including miniscrew sliding with high hooks (MSH), miniscrew sliding with low hooks (MSL), and the traditional sliding method (TS) without using miniscrews were simulated using three-dimensional finite element analysis. The initial displacement of the maxillary canine, the maximum principal stress of the periodontal ligament and the Von Mises stress were calculated. The distolingual tipping movements of the canine were shown in three movement modes. MSH showed a small tendency to lingual tipping movement and a extrusion movement while MSL had the largest lingual inclination. TS demonstrated a tendency toward distolingual torsion displacement. Compressive stress values were mainly concentrated in the range - 0.003 to -0.006MPa. For tensile stress, the distribution of MSH and MSL was concentrated in the range 0.005 to 0.009MPa, TS was mainly distributed about 0.003MPa. Von Mises equivalent stress distribution showed no significant difference. The loss of tooth torque was inevitable, irrespective of which method was used to close the extraction space. However, miniscrew application and higher hooks reduced the loss of torque and avoided lingual rotation. This study shows that miniscrew implants with different hooks can better control the movement of the maxillary canines. The non-invasive nature of the finite element analysis and its good simulation of dental stress and instantaneous motion trend have a clinical advantage in the analysis of tooth movement.