Runx2 regulates peripheral nerve regeneration to promote Schwann cell migration and re-myelination

Runx2 is a major regulator of osteoblast differentiation and function;however,the role of Runx2 in peripheral nerve repair is unclea r.Here,we analyzed Runx2expression following injury and found that it was specifically up-regulated in Schwann cells.Furthermore,using Schwann cell-specific Runx2 knocko ut mice,we studied peripheral nerve development and regeneration and found that multiple steps in the regeneration process following sciatic nerve injury were Runx2-dependent.Changes observed in Runx2 knoc kout mice include increased prolife ration of Schwann cells,impaired Schwann cell migration and axonal regrowth,reduced re-myelination of axo ns,and a block in macrophage clearance in the late stage of regeneration.Taken together,our findings indicate that Runx2 is a key regulator of Schwann cell plasticity,and therefore peripheral nerve repair.Thus,our study shows that Runx2 plays a major role in Schwann cell migration,re-myelination,and peripheral nerve functional recovery following injury.

Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots:A Barrier Function Sliding Mode Approach

The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.

Migration pattern of a population of Barn Swallows(Hirundo rustica)breeding in East Asian tropical region

Birds exhibit a high degree of migratory diversity,which is influenced by various ecological factors and life history strategies.Conducting studies on tropical bird migration,of which research is scarce,and comparing it with temperate birds can enhance our understanding of bird migration behaviour and its underlying mecha-nisms.In this study,we explored the migration behaviour of a breeding population of the Barn Swallow(Hirundo rustica)in Zhanjiang,southern China,a region located in the northern tropics,using light-level geolocators.From 2021 to 2023,we deployed geolocators on 92 breeding swallows and retrieved geolocators successfully from 23 individuals.These swallows all exhibited migratory behaviour,and wintering on various islands in Southeast Asia.They displayed sex differences in their wintering locations.All males concentrated in Borneo,while females primarily chose Borneo but also dispersed to the Philippines,South China Sea,and Vietnam for wintering.The studied swallow population adopted a seasonal migration pattern of“indirect in autumn,direct in spring”,bypassing the ecological barrier of the South China Sea in autumn and tending to directly cross it in spring migration.Moreover,the distance and duration of autumn migration was significantly longer than those of the spring migration.Compared to temperate Barn Swallows,the Barn Swallow population breeding in Zhanjiang adopts a pattern of“intra-tropical migration”and initiates autumn migration earlier.The formation of their migration pattern may be limited by ecological and physiological factors.

Entropy of deterministic trajectory via trajectories ensemble

We present a formulation of the single-trajectory entropy using the trajectories ensemble. The single-trajectory entropy is affected by its surrounding trajectories via the distribution function. The single-trajectory entropies are studied in two typical potentials, i.e., harmonic potential and double-well potential, and in viscous environment by interacting trajectory method. The results of the trajectory methods are in agreement well with the numerical methods(Monte Carlo simulation and difference equation). The single-trajectory entropies increasing(decreasing) could be caused by absorption(emission) heat from(to) the thermal environment. Also, some interesting trajectories, which correspond to the rare evens in the processes, are demonstrated.

The roles of macrophage migration inhibitory factor in retinal diseases

Macrophage migration inhibitory factor(MIF),a multifunctional cytokine,is secreted by various cells and participates in inflammatory reactions,including innate and adaptive immunity.There are some evidences that MIF is involved in many vitreoretinal diseases.For example,MIF can exacerbate many types of uveitis;measurements of MIF levels can be used to monitor the effectiveness of uveitis treatment.MIF also alleviates trauma-induced and glaucoma-induced optic nerve damage.Furthermore,MIF is critical for retinal/choroidal neovascularization,especially complex neovascularization.MIF exacerbates retinal degeneration;thus,anti-MIF therapy may help to mitigate retinal degeneration.MIF protects uveal melanoma from attacks by natural killer cells.The mechanism underlying the effects of MIF in these diseases has been demonstrated:it binds to cluster of differentiation 74,inhibits the c-Jun N-terminal kinase pathway,and triggers mitogen-activated protein kinases,extracellular signal-regulated kinase-1/2,and the phosphoinositide-3-kinase/Akt pathway.MIF also upregulates Toll-like receptor 4 and activates the nuclear factor kappa-B signaling pathway.This review focuses on the structure and function of MIF and its receptors,including the effects of MIF on uveal inflammation,retinal degeneration,optic neuropathy,retinal/choroidal neovascularization,and uveal melanoma.

The Impact of Hula Project (1993-2018) on Nutrient Migrations

During the 1950s the Hula wetlands and old lake were drained and the land converted utilization to agriculture and ecotourism. As a result of the drainage, the Peat Soil was exposed to atmospheric oxygen. The geochemical environment was modified from reductive to oxidative and the Nitrogen in it was converted from Ammonium to Nitrate. Intensive migration of Nitrate from the Hula Valley induced a national concern of water quality deterioration in the lake which was dissipated when Nitrogen deficiency was developed in Lake Kinneret. Forty years after drainage the ecosystem structure was renovated (Hula Project, HP) aimed at agricultural management and nutrient migration reduction. The paper examines through evaluation of the ecological data record (1993-2018) the impact of hydrological changes, attributed to the HP implementation on nutrient dynamics within surface waters in the Hula Valley. It is suggested that soil moisture elevation by irrigation in summer reduced Phosphorus and enhanced Nitrate concentrations.

Joint Optimization of Resource Allocation and Trajectory Based on User Trajectory for UAV-Assisted Backscatter Communication System

The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization variables.An iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method,and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.

Migration of a Progestin Implant into a Pulmonary Artery: Observation of a Case at the Reference Health Center of Commune III of the District of Bamako in Mali

It was a 36-year-old patient, 5th Pregnancy, 5th Delivery, 4 live children, and I deceased, had a consultation in the department for the removal of implants. Questioning revealed that she had had the implant three years ago without medical follow-up. It was in view of the difficulties in extracting the capsule that the chest X-ray and CT scan carried out concluded that the implant had migrated into a branch of the left pulmonary artery. Therapeutic abstention has been the attitude of cardiovascular surgeons.

An Efficient Long Short-Term Memory and Gated Recurrent Unit Based Smart Vessel Trajectory Prediction Using Automatic Identification System Data

Maritime transportation,a cornerstone of global trade,faces increasing safety challenges due to growing sea traffic volumes.This study proposes a novel approach to vessel trajectory prediction utilizing Automatic Identification System(AIS)data and advanced deep learning models,including Long Short-Term Memory(LSTM),Gated Recurrent Unit(GRU),Bidirectional LSTM(DBLSTM),Simple Recurrent Neural Network(SimpleRNN),and Kalman Filtering.The research implemented rigorous AIS data preprocessing,encompassing record deduplication,noise elimination,stationary simplification,and removal of insignificant trajectories.Models were trained using key navigational parameters:latitude,longitude,speed,and heading.Spatiotemporal aware processing through trajectory segmentation and topological data analysis(TDA)was employed to capture dynamic patterns.Validation using a three-month AIS dataset demonstrated significant improvements in prediction accuracy.The GRU model exhibited superior performance,achieving training losses of 0.0020(Mean Squared Error,MSE)and 0.0334(Mean Absolute Error,MAE),with validation losses of 0.0708(MSE)and 0.1720(MAE).The LSTM model showed comparable efficacy,with training losses of 0.0011(MSE)and 0.0258(MAE),and validation losses of 0.2290(MSE)and 0.2652(MAE).Both models demonstrated reductions in training and validation losses,measured by MAE,MSE,Average Displacement Error(ADE),and Final Displacement Error(FDE).This research underscores the potential of advanced deep learning models in enhancing maritime safety through more accurate trajectory predictions,contributing significantly to the development of robust,intelligent navigation systems for the maritime industry.

GIPC1 promotes tumor growth and migration in gastric cancer via activating PDGFR/PI3K/AKT signaling

The high mortality rate associated with gastric cancer(GC)has resulted in an urgent need to identify novel therapeutic targets for GC.This study aimed to investigate whether GAIP interacting protein,C terminus 1(GIPC1)represents a therapeutic target and its regulating mechanism in GC.GIPC1 expression was elevated in GC tissues,liver metastasis tissues,and lymph node metastases.GIPC1 knockdown or GIPC1 blocking peptide blocked the platelet-derived growth factor receptor(PDGFR)/PI3K/AKT signaling pathway,and inhibited the proliferation and migration of GC cells.Conversely,GIPC1 overexpression markedly activated the PDGFR/PI3K/AKT signaling pathway,and promoted GC cell proliferation and migration.Furthermore,platelet-derived growth factor subunit BB(PDGF-BB)cytokines and the AKT inhibitor attenuated the effect of differential GIPC1 expression.Moreover,GIPC1 silencing decreased tumor growth and migration in BALB/c nude mice,while GIPC1 overexpression had contrasting effects.Taken together,our findings suggest that GIPC1 functions as an oncogene in GC and plays a central role in regulating cell proliferation and migration via the PDGFR/PI3K/AKT signaling pathway.

Trajectory planning for multi-robot coordinated towing system based on stability

Given the unconstrained characteristics of the multi-robot coordinated towing system,the rope can only provide a unidirectional constraint force to the suspended object,which leads to the weak ability of the system to resist external disturbances and makes it difficult to control the trajectory of the suspended object.Based on the kinematics and statics of the multi-robot coordinated towing system with fixed base,the dynamic model of the system is established by using the Newton-Euler equations and the Udwadia-Kalaba equations.To plan the trajectories with high stability and strong control,trajectory planning is performed by combining the dynamics and stability of the towing system.Based on the dynamic stability of the motion trajectory of the suspended object,the stability of the suspended object is effectively improved through online real-time planning and offline manual adjustment.The effectiveness of the proposed method is verified by comparing the motion stability of the suspended object before and after planning.The results provide a foundation for the motion planning and coordinated control of the towing system.

Optimization of LSTM Ship Trajectory Prediction Based on Hybrid Genetic Algorithm

Accurate prediction of the movement trajectory of sea surface targets holds significant importance in achieving an advantageous position in the sea battle field.This prediction plays a crucial role in ensuring security defense and confrontation,and is essential for effective deployment of military strategy.Accurately predicting the trajectory of sea surface targets using AIS(Automatic Identification System)information is crucial for security defense and confrontation,and holds significant importance for military strategy deployment.In response to the problem of insufficient accuracy in ship trajectory prediction,this study proposes a hybrid genetic algorithm to optimize the Long Short-Term Memory(LSTM)algorithm.The HGA-LSTM algorithm is proposed for ship trajectory prediction.It can converge faster and obtain better parameter solutions,thereby improving the effectiveness of ship trajectory prediction.Compared to traditional LSTM and GA-LSTM algorithms,experimental results demonstrate that this algorithm outperforms them in both single-step and multi-step prediction.

General Optimal Trajectory Planning:Enabling Autonomous Vehicles with the Principle of Least Action

This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and efficiently.Firstly,we employ the fifth-order Bezier curve to generate and smooth the reference path along the road centerline.Cartesian coordinates are then transformed to achieve the curvature continuity of the generated curve.Considering the road constraints and vehicle dynamics,limited polynomial candidate trajectories are generated and smoothed in a curvilinear coordinate system.Furthermore,in selecting the optimal trajectory,we develop a unified and auto-tune objective function based on the principle of least action by employing AVs to simulate drivers’behavior and summarizing their manipulation characteristics of“seeking benefits and avoiding losses.”Finally,by integrating the idea of receding-horizon optimization,the proposed framework is achieved by considering dynamic multi-performance objectives and selecting trajectories that satisfy feasibility,optimality,and adaptability.Extensive simulations and experiments are performed,and the results demonstrate the framework’s feasibility and effectiveness,which avoids both dynamic and static obstacles and applies to various scenarios with multi-source interactive traffic participants.Moreover,we prove that the proposed method can guarantee real-time planning and safety requirements compared to drivers’manipulation.

Phase-stable wide-bandgap perovskites enabled by suppressed ion migration

Wide-bandgap(>1.7 eV)perovskites suffer from severe light-induced phase segregation due to high bromine content,causing irreversible damage to devices stability.However,the strategies of suppressing photoinduced phase segregation and related mechanisms have not been fully disclosed.Here,we report a new passivation agent 4-aminotetrahydrothiopyran hydrochloride(4-ATpHCl)with multifunctional groups for the interface treatment of a 1.77-eV wide-bandgap perovskite film.4-ATpH^(+)impeded halogen ion migration by anchoring on the perovskite surface,leading to the inhibition of phase segregation and thus the passivation of defects,which is ascribed to the interaction of 4-ATpH^(+)with perovskite and the formation of low-dimensional perovskites.Finally,the champion device achieved an efficiency of 19.32%with an open-circuit voltage(V_(OC))of 1.314 V and a fill factor of 83.32%.Moreover,4-ATpHCl modified device exhibited significant improved stability as compared with control one.The target device maintained 80%of its initial efficiency after 519 h of maximum power output(MPP)tracking under 1 sun illumination,however,the control device showed a rapid decrease in efficiency after 267 h.Finally,an efficiency of 27.38%of the champion 4-terminal all-perovskite tandem solar cell was achieved by mechanically stacking this wide-bandgap top subcell with a 1.25-eV low-bandgap perovskite bottom subcell.

The activation of adenosine monophosphate–activated protein kinase inhibits the migration of tongue squamous cell carcinoma cells by targeting Claudin-1 via epithelial–mesenchymal transition

Background:The role of Claudin-1 in tongue squamous cell carcinoma(TSCC)metastasis needs further clarification,particularly its impact on cell migration.Herein,our study aims to investigate the role of Claudin-1 in TSCC cell migration and its underlying mechanisms.Methods:36 TSCC tissue samples underwent immunohistochemical staining for Claudin-1.Western blotting and immunofluorescence analyses were conducted to evaluate Claudin-1 expression and distribution in TSCC cells.Claudin-1 knockdown cell lines were established using short hairpin RNA transfection.Migration effects were assessed through wound healing assays.Furthermore,the expression of EMTassociated molecules was measured via western blotting.Results:Claudin-1 expression decreased as TSCC malignancy increased.Adenosine monophosphate–activated protein kinase(AMPK)activation led to increased Claudin-1 expression and membrane translocation,inhibiting TSCC cell migration and epithelial–mesenchymal transition(EMT).Conversely,Claudin-1 knockdown reversed these inhibitory effects on migration and EMT caused by AMPK activation.Conclusions:Our results indicated that AMPK activation suppresses TSCC cell migration by targeting Claudin-1 and EMT pathways.

Migration Networks Pattern of China’s Floating Population from the Perspective of Complex Network

Since China’s reform and opening-up,the growing disparity between urban and rural areas and regions has led to massive migration.With China’s Rural Revitalization Strategy and the industrial transfer from the eastern coastal areas to the inland,the migration direction and pattern of the floating population have undergone certain changes.Using the 2017 China Migrants Dynamic Survey(CMDS),excluding Hong Kong,Macao,and Taiwan regions of China,organized by China’s National Health Commission,the relationship matrix of the floating population is constructed according to the inflow place of the interviewees and their outflow place(the location of the registered residence)in the questionnaire survey.We then apply the complex network model to analyze the migration direction and network pattern of China’s floating population from the city scale.The migration network shows an obvious hierarchical agglomeration.The first-,second-,third-and fourth-tier distribution cities are municipalities directly under the central government,provincial capital cities,major cities in the central and western regions and ordinary cities in all provinces,respectively.The migration trend is from the central and western regions to the eastern coastal areas.The migration network has‘small world’characteristics,forming nine communities.It shows that most node cities in the same community are closely linked and geographically close,indicating that the migration network of floating population is still affected by geographical proximity.Narrowing the urban-rural and regional differences will promote the rational distribution this population.It is necessary to strengthen the reform of the registered residence system,so that the floating population can enjoy urban public services comparable to other populations,and allow migrants to live and work in peace.

MAD2L2 overexpression attenuates the effects of TNF-α-induced migration and invasion capabilities in colorectal cancer cells

Background:Colorectal cancer is a major global health concern,exacerbated by tumor necrosis factor-alpha(TNF-α)and its role in inflammation,with the effects of Mitotic Arrest Deficient 2 Like 2(MAD2L2)in this context still unclear.Methods:The colorectal carcinoma cell lines HCT116 and SW620 were exposed to TNF-αfor a period of 24 h to instigate an inflammatory response.Subsequent assessments were conducted to measure the expression of inflammatory cytokines,the activity within the p38 mitogen-activated protein kinase(p38 MAPK)and Phosphoinositide 3-Kinase/AKT Serine/Threonine Kinase pathway(PI3K/AKT)signaling cascades.Transcriptome sequencing and subsequent integrative analysis with the Cancer Genome Atlas(TCGA)program database revealed a significant downregulation of the key factor MAD2L2.Enhancement of MAD2L2 expression was facilitated via lentiviral vector-mediated transfection.The influence of this overexpression on TNF-α-prompted inflammation,intracellular signaling pathways,and the migratory and invasive behaviors of the colorectal cancer cells was then scrutinized.Results:TNF-αtreatment significantly increased the expression of Interleukin-1 beta(IL-1β)and Interleukin-6(IL-6),activated the MAPK p38 and PI3K/AKT signaling pathways,and enhanced cell migration and invasion.A decrease in MAD2L2 expression was observed following TNF-αtreatment.However,overexpression of MAD2L2 reversed the effects of TNF-α,reducing IL-1βand IL-6 levels,attenuating PI3K/AKT pathway activation,and inhibiting cell migration and invasion.Conclusions:Overexpression of MAD2L2 attenuates the pro-inflammatory effects of TNF-α,suggesting that MAD2L2 plays a protective role against TNF-α-induced migration and invasion of colorectal carcinoma cells.Therefore,MAD2L2 holds potential as a therapeutic target in the treatment of colorectal cancer.

Research on Anthropomorphic Obstacle Avoidance Trajectory Planning for Adaptive Driving Scenarios Based on Inverse Reinforcement Learning Theory

The forward design of trajectory planning strategies requires preset trajectory optimization functions,resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits.In addition,owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios,it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters.Therefore,an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed.First,numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset.Subsequently,a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory.Furthermore,a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function,and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed.Finally,the proposed strategy is verified based on real driving scenarios.The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the“emergency degree”of obstacle avoidance and the state of the vehicle.Moreover,this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories,effectively improving the adaptability and acceptability of trajectories in driving scenarios.

Application of Gaussian Beam Summation Migration in Reflected In-seam Wave Imaging

The geological conditions for coal mining in China are complex,with various structural issues such as faults and collapsed columns seriously compromising the safety of coal mine production.In-seam wave exploration is an effective technique for acquiring detailed information on geological structures in coal seam working faces.However,the existing reflected in-seam wave imaging technique can no longer meet the exploration precision requirements,making it imperative to develop a new reflected in-seam wave imaging technique.This study applies the Gaussian beam summation(GBS)migration method to imaging coal seams'reflected in-seam wave data.Firstly,with regard to the characteristics of the reflected in-seam wave data,methods such as wavefield removal and enveloped superposition are employed for the corresponding wavefield separation,wave train compression and other processing of reflected in-seam waves.Thereafter,imaging is performed using the GBS migration technique.The feasibility and effectiveness of the proposed method for reflected in-seam wave imaging are validated by conducting GBS migration tests on 3D coal-seam fault models with different dip angles and throws.By applying the method to reflected in-seam wave data for an actual coal seam working face,accurate imaging of a fault structure is obtained,thereby validating its practicality.

LFM Radar Source Passive Localization Algorithm Based on Range Migration

Traditional single-satellite passive localization algorithms are influenced by frequency and angle measurement accuracies,resulting in error estimation of emitter position on the order of kilometers.Subsequently,a single-satellite localization algorithm based on passive synthetic aper-ture(PSA)was introduced,enabling high-precision positioning.However,its estimation of azimuth and range distance is considerably affected by the residual frequency offset(RFO)of uncoopera-tive system transceivers.Furthermore,it requires data containing a satellite flying over the radia-tion source for RFO search.After estimating the RFO,an accurate estimation of azimuth and range distance can be carried out,which is difficult to achieve in practical situations.An LFM radar source passive localization algorithm based on range migration is proposed to address the dif-ficulty in estimating frequency offset.The algorithm first provides a rough estimate of the pulse repetition time(PRT).It processes intercepted signals through range compression,range interpola-tion,and polynomial fitting to obtain range migration observations.Subsequently,it uses the changing information of range migration and an accurate PRT to formulate a system of nonlinear equations,obtaining the emitter position and a more accurate PRT through a two-step localization algorithm.Frequency offset only induces a fixed offset in range migration,which does not affect the changing information.This algorithm can also achieve high-precision localization in squint scenar-ios.Finally,the effectiveness of this algorithm is verified through simulations.