Multiple model PHD filter for tracking sharply maneuvering targets using recursive RANSAC based adaptive birth estimation

An algorithm to track multiple sharply maneuvering targets without prior knowledge about new target birth is proposed. These targets are capable of achieving sharp maneuvers within a short period of time, such as drones and agile missiles.The probability hypothesis density (PHD) filter, which propagates only the first-order statistical moment of the full target posterior, has been shown to be a computationally efficient solution to multitarget tracking problems. However, the standard PHD filter operates on the single dynamic model and requires prior information about target birth distribution, which leads to many limitations in terms of practical applications. In this paper,we introduce a nonzero mean, white noise turn rate dynamic model and generalize jump Markov systems to multitarget case to accommodate sharply maneuvering dynamics. Moreover, to adaptively estimate newborn targets’information, a measurement-driven method based on the recursive random sampling consensus (RANSAC) algorithm is proposed. Simulation results demonstrate that the proposed method achieves significant improvement in tracking multiple sharply maneuvering targets with adaptive birth estimation.

Cooperative guidance law based on super-twisting observer for target maneuvering

To solve the problem that multiple missiles should simultaneously attack unmeasurable maneuvering targets,a guidance law with temporal consistency constraint based on the super-twisting observer is proposed.Firstly,the relative motion equations between multiple missiles and targets are established,and the topological model among multiple agents is considered.Secondly,based on the temporal consistency constraint,a cooperative guidance law for simultaneous arrival with finite-time convergence is derived.Finally,the unknown target maneuver-ing is regarded as bounded interference.Based on the second-order sliding mode theory,a super-twisting sliding mode observer is devised to observe and track the bounded interfer-ence,and the stability of the observer is proved.Compared with the existing research,this approach only needs to obtain the sliding mode variable which simplifies the design process.The simulation results show that the designed cooperative guidance law for maneuvering targets achieves the expected effect.It ensures successful cooperative attacks,even when confronted with strong maneuvering targets.

An Efficient Radar Detection Method of Maneuvering Small Targets

Detection of maneuvering small targets has always been an important yet challenging task for radar signal processing.One primary reason is that target variable motions within coherent processing interval generate energy migrations across multiple resolution bins,which severely deteriorate the parameter estimation performance.A coarse-to-fine strategy for the detection of maneuvering small targets is proposed.Integration of small points segmented coherently is performed first,and then an optimal inter-segment integration is utilized to derive the coarse estimation of the chirp rate.Sparse fractional Fourier transform(FrFT)is then employed to refine the coarse estimation at a significantly reduced computational complexity.Simulation results verify the proposed scheme that achieves an efficient and reliable maneuvering target detection with-16dB input signal-to-noise ratio(SNR),while requires no exact a priori knowledge on the motion parameters.

Multilevel analysis of the central-peripheral-target organ pathway:contributing to recovery after peripheral nerve injury

Peripheral nerve injury is a common neurological condition that often leads to severe functional limitations and disabilities.Research on the pathogenesis of peripheral nerve injury has focused on pathological changes at individual injury sites,neglecting multilevel pathological analysis of the overall nervous system and target organs.This has led to restrictions on current therapeutic approaches.In this paper,we first summarize the potential mechanisms of peripheral nerve injury from a holistic perspective,covering the central nervous system,peripheral nervous system,and target organs.After peripheral nerve injury,the cortical plasticity of the brain is altered due to damage to and regeneration of peripheral nerves;changes such as neuronal apoptosis and axonal demyelination occur in the spinal cord.The nerve will undergo axonal regeneration,activation of Schwann cells,inflammatory response,and vascular system regeneration at the injury site.Corresponding damage to target organs can occur,including skeletal muscle atrophy and sensory receptor disruption.We then provide a brief review of the research advances in therapeutic approaches to peripheral nerve injury.The main current treatments are conducted passively and include physical factor rehabilitation,pharmacological treatments,cell-based therapies,and physical exercise.However,most treatments only partially address the problem and cannot complete the systematic recovery of the entire central nervous system-peripheral nervous system-target organ pathway.Therefore,we should further explore multilevel treatment options that produce effective,long-lasting results,perhaps requiring a combination of passive(traditional)and active(novel)treatment methods to stimulate rehabilitation at the central-peripheral-target organ levels to achieve better functional recovery.

Pyroptosis,ferroptosis,and autophagy in spinal cord injury:regulatory mechanisms and therapeutic targets

Regulated cell death is a form of cell death that is actively controlled by biomolecules.Several studies have shown that regulated cell death plays a key role after spinal cord injury.Pyroptosis and ferroptosis are newly discovered types of regulated cell deaths that have been shown to exacerbate inflammation and lead to cell death in damaged spinal cords.Autophagy,a complex form of cell death that is interconnected with various regulated cell death mechanisms,has garnered significant attention in the study of spinal cord injury.This injury triggers not only cell death but also cellular survival responses.Multiple signaling pathways play pivotal roles in influencing the processes of both deterioration and repair in spinal cord injury by regulating pyroptosis,ferroptosis,and autophagy.Therefore,this review aims to comprehensively examine the mechanisms underlying regulated cell deaths,the signaling pathways that modulate these mechanisms,and the potential therapeutic targets for spinal cord injury.Our analysis suggests that targeting the common regulatory signaling pathways of different regulated cell deaths could be a promising strategy to promote cell survival and enhance the repair of spinal cord injury.Moreover,a holistic approach that incorporates multiple regulated cell deaths and their regulatory pathways presents a promising multi-target therapeutic strategy for the management of spinal cord injury.

Targeting capabilities of engineered extracellular vesicles for the treatment of neurological diseases

Recent advances in research on extracellular vesicles have significantly enhanced their potential as therapeutic agents for neurological diseases.Owing to their therapeutic properties and ability to cross the blood–brain barrier,extracellular vesicles are recognized as promising drug delivery vehicles for various neurological conditions,including ischemic stroke,traumatic brain injury,neurodegenerative diseases,glioma,and psychosis.However,the clinical application of natural extracellular vesicles is hindered by their limited targeting ability and short clearance from the body.To address these limitations,multiple engineering strategies have been developed to enhance the targeting capabilities of extracellular vesicles,thereby enabling the delivery of therapeutic contents to specific tissues or cells.Therefore,this review aims to highlight the latest advancements in natural and targeting-engineered extracellular vesicles,exploring their applications in treating traumatic brain injury,ischemic stroke,Parkinson's disease,Alzheimer's disease,amyotrophic lateral sclerosis,glioma,and psychosis.Additionally,we summarized recent clinical trials involving extracellular vesicles and discussed the challenges and future prospects of using targeting-engineered extracellular vesicles for drug delivery in treating neurological diseases.This review offers new insights for developing highly targeted therapies in this field.

Subretinal fibrosis secondary to neovascular age-related macular degeneration:mechanisms and potential therapeutic targets

Subretinal fibrosis is the end-stage sequelae of neovascular age-related macular degeneration.It causes local damage to photoreceptors,retinal pigment epithelium,and choroidal vessels,which leads to permanent central vision loss of patients with neovascular age-related macular degeneration.The pathogenesis of subretinal fibrosis is complex,and the underlying mechanisms are largely unknown.Therefore,there are no effective treatment options.A thorough understanding of the pathogenesis of subretinal fibrosis and its related mechanisms is important to elucidate its complications and explore potential treatments.The current article reviews several aspects of subretinal fibrosis,including the current understanding on the relationship between neovascular age-related macular degeneration and subretinal fibrosis;multimodal imaging techniques for subretinal fibrosis;animal models for studying subretinal fibrosis;cellular and non-cellular constituents of subretinal fibrosis;pathophysiological mechanisms involved in subretinal fibrosis,such as aging,infiltration of macrophages,different sources of mesenchymal transition to myofibroblast,and activation of complement system and immune cells;and several key molecules and signaling pathways participating in the pathogenesis of subretinal fibrosis,such as vascular endothelial growth factor,connective tissue growth factor,fibroblast growth factor 2,platelet-derived growth factor and platelet-derived growth factor receptor-β,transforming growth factor-βsignaling pathway,Wnt signaling pathway,and the axis of heat shock protein 70-Toll-like receptors 2/4-interleukin-10.This review will improve the understanding of the pathogenesis of subretinal fibrosis,allow the discovery of molecular targets,and explore potential treatments for the management of subretinal fibrosis.

A novel detection method for warhead fragment targets in optical images under dynamic strong interference environments

A measurement system for the scattering characteristics of warhead fragments based on high-speed imaging systems offers advantages such as simple deployment,flexible maneuverability,and high spatiotemporal resolution,enabling the acquisition of full-process data of the fragment scattering process.However,mismatches between camera frame rates and target velocities can lead to long motion blur tails of high-speed fragment targets,resulting in low signal-to-noise ratios and rendering conventional detection algorithms ineffective in dynamic strong interference testing environments.In this study,we propose a detection framework centered on dynamic strong interference disturbance signal separation and suppression.We introduce a mixture Gaussian model constrained under a joint spatialtemporal-transform domain Dirichlet process,combined with total variation regularization to achieve disturbance signal suppression.Experimental results demonstrate that the proposed disturbance suppression method can be integrated with certain conventional motion target detection tasks,enabling adaptation to real-world data to a certain extent.Moreover,we provide a specific implementation of this process,which achieves a detection rate close to 100%with an approximate 0%false alarm rate in multiple sets of real target field test data.This research effectively advances the development of the field of damage parameter testing.

Targeted maintenance therapy for a young woman with cervical rhabdomyosarcoma:A case report and review of literature

BACKGROUND Rhabdomyosarcoma of the uterine cervix is a rare form of soft-tissue sarcoma predominantly affecting young women,with no established standard treatment protocol.CASE SUMMARY This report presents a case of a 17-year-old female patient presenting with in-termittent,non-cyclical vaginal bleeding and associated lower abdominal pain.Pelvic magnetic resonance imaging and additional examinations led to the dia-gnosis of cervical rhabdomyosarcoma.The primary treatment options for uterine cervical rhabdomyosarcoma include surgery,with or without adjuvant chemo-therapy and radiotherapy.This patient underwent surgery followed by a posto-perative chemotherapy regimen of gemcitabine combined with docetaxel and bevacizumab.After 19 months of follow-up,the patient showed no signs of re-currence and maintained good overall health.Given the rarity of cervix rhab-domyosarcoma,this case is presented to provide insights into the diagnosis and treatment of this condition.CONCLUSION This suggests that bevacizumab may demonstrate potential efficacy in the treat-ment of cervical rhabdomyosarcoma.In the future,targeted therapy is expected to play an increasingly significant role in the management of rhabdomyosarcoma.

Tankyrase 2 as a therapeutic target in non-small cell lung cancer: Implications for apoptosis and migration

This letter addresses Wang and Zhang's investigation into the role of tankyrase 2(TNKS2)as a pivotal driver of malignancy in non-small cell lung cancer(NSCLC)through mechanisms including apoptosis inhibition,enhanced cellular migration,andβ-catenin pathway activation.Their study in NSCLC cell lines demonstrates that TNKS2 overexpression stabilizesβ-catenin,subsequently triggering onco-genic gene expression and facilitating cellular migration-key attributes of meta-static potential.These insights position TNKS2 as a compelling target for therapy and a potential prognostic marker in NSCLC.Nevertheless,translating these in vitro findings to clinical practice requires validation in in vivo models.Addi-tionally,further research should investigate TNKS2 expression in patient samples and assess its implications in therapy resistance and combination treatment strategies.

Impact of setting distinct target blood glucose levels on endogenous insulin suppression and pharmacodynamics of insulin preparations

BACKGROUND Insulin therapy plays a crucial role in managing diabetes.Regulatory guidelines mandate assessing the pharmacokinetics(PK)and pharmacodynamics(PD)of new insulin formulations with euglycemic clamp techniques before entry into the market.Typically,blood glucose(BG)levels are maintained at 5%below baseline to suppress endogenous insulin secretion in healthy volunteers.However,in scenarios where BG baseline is relatively low,maintaining it at 5%below baseline can increase hypoglycemic risk.Consequently,we adjusted to maintain it at 2.5%below a baseline of<4.00 mmol/L.It remains uncertain whether this adjustment impacts endogenous insulin inhibition or the PD of study insulin.AIM To evaluate and compare the PD and C-peptide status using two different target BG setting methods.METHODS Data came from euglycemic clamp trials assessing the PK/PD of insulin aspart(IAsp)in healthy participants.Target BG was set at 2.5%below baseline for those with a basal BG of<4.00 mmol/L(group A),and at 5%below baseline for others(group B).The area under the curve(AUC)of IAsp(AUC_(IAsp,0-8 h))and GIR from 0 to 8 hours(AUCGIR,0-8 h)was used to characterize the PK and PD of IAsp,respectively.The C-peptide reduction and PK/PD of IAsp were compared between the two groups.RESULTS Out of 135 subjects,15 were assigned to group A and 120 to group B;however,group B exhibited higher basal Cpeptide(1.59±0.36 vs 1.32±0.42 ng/mL,P=0.006).Following propensity score matching to adjust for basal Cpeptide differences,71 subjects(15 in group A and 56 in group B)were analyzed.No significant differences were observed in demographics,IAsp dosage,or clamp quality.Group B showed significantly higher baseline(4.35±0.21 vs 3.91±0.09 mmol/L,P<0.001),target(4.13±0.20 vs 3.81±0.08 mmol/L,P<0.001),and clamped(4.10±0.17 vs 3.80±0.06 mmol/L,P<0.001)BG levels.Both groups exhibited comparable C-peptide suppression(32.5%±10.0%vs 35.6%±12.1%,P=0.370)and similar IAsp activity(AUCGIR,0-8 h:1433±400 vs 1440±397 mg/kg,P=0.952)under nearly equivalent IAsp exposure(AUC_(IAsp,0-8 h):566±51 vs 571±85 ng/mL×h,P=0.840).CONCLUSION Maintaining BG at 2.5%below a baseline of<4.00 mmol/L did not compromise the endogenous insulin suppression nor alter the observed pharmacodynamic effects of the study insulin.

Synergistic inhibition of colorectal cancer progression by silencing Aurora A and the targeting protein for Xklp2

BACKGROUND Unraveling the pathogenesis of colorectal cancer(CRC)can aid in developing prevention and treatment strategies.Aurora kinase A(AURKA)is a key participant in mitotic control and interacts with its co-activator,the targeting protein for Xklp2(TPX2)microtubule nucleation factor.AURKA is associated with poor clinical outcomes and high risks of CRC recurrence.AURKA/TPX2 co-overexpression in cancer may contribute to tumorigenesis.Despite its pivotal role in CRC development and progression,the action mechanism of AURKA remains unclear.Further research is needed to explore the complex interplay between AURKA and TPX2 and to develop effective targeted treatments for patients with CRC.AIM To compare effects of AURKA and TPX2 and their combined knockdown on CRC cells.METHODS We evaluated three CRC gene datasets about CRC(GSE32323,GSE25071,and GSE21510).Potential hub genes associated with CRC onset were identified using the Venn,search tool for the retrieval of interacting genes,and KOBAS platforms,with AURKA and TPX2 emerging as significant factors.Subsequently,cell models with knockdown of AURKA,TPX2,or both were constructed using SW480 and LOVO cells.Quantitative real-time polymerase chain reaction,western blotting,cell counting kit-8,cell cloning assays,flow cytometry,and Transwell assays were used.RESULTS Forty-three highly expressed genes and 39 poorly expressed genes overlapped in cancer tissues compared to controls from three datasets.In the protein-protein interaction network of highly expressed genes,AURKA was one of key genes.Its combined score with TPX2 was 0.999,and their co-expression score was 0.846.In CRC cells,knockdown of AURKA,TPX2,or both reduced cell viability and colony number,while blocking G0/G1 phase and enhancing cell apoptosis.Additionally,they were weakened cell proliferation and migration abilities.Furthermore,the expression levels of B-cell lymphoma-2-Associated X,caspase 3,and tumor protein P53,and E-cadherin increased with a decrease in B-cell lymphoma-2,N-cadherin,and vimentin proteins.These effects were amplified when both AURKA and TPX2 were concurrently downregulated.CONCLUSION Combined knockdown of AURKA and TPX2 was effective in suppressing the malignant phenotype in CRC.Coinhibition of gene expression is a potential developmental direction for CRC treatment.

An Effective Multiple Model Least Squares Method in Tracking of a Maneuvering Target

A polynomial model, time origin shifting model(TOSM, is used to describe the trajectory of a moving target .Based on TOSM, a recursive laeast squares(RLS) algorithm with varied forgetting factor is derived for tracking of a non-maneuvering target. In order to apply this algorithm to maneuvering targets tracking ,a tracking signal is performed on-line to determine what kind of TOSm will be in effect to track a target with different dynamics. An effective multiple model least squares filtering and forecasting method dadpted to real tracking of a maneuvering target is formulated. The algorithm is computationally more effcient than Kalman filter and the percentage improvement from simulations show both of them are considerably alike to some extent.

Maneuvering target tracking using threshold interacting multiple model algorithm

To avoid missing track caused by the target maneuvers in automatic target tracking system, a new maneuvering target tracking technique called threshold interacting multiple model （TIMM） is proposed. This algorithm is based on the interacting multiple model （IMM） method and applies a threshold controller to improve tracking accuracy. It is also applicable to other advanced algorithms of IMM. In this research, we also compare the position and velocity root mean square （RMS） errors of TIMM and IMM algorithms with two different examples. Simulation results show that the TIMM algorithm is superior to the traditional IMM alzorithm in estimation accuracy.

Maneuvering target tracking of UAV based on MN-DDPG and transfer learning

Tracking maneuvering target in real time autonomously and accurately in an uncertain environment is one of the challenging missions for unmanned aerial vehicles(UAVs).In this paper,aiming to address the control problem of maneuvering target tracking and obstacle avoidance,an online path planning approach for UAV is developed based on deep reinforcement learning.Through end-to-end learning powered by neural networks,the proposed approach can achieve the perception of the environment and continuous motion output control.This proposed approach includes:(1)A deep deterministic policy gradient(DDPG)-based control framework to provide learning and autonomous decision-making capability for UAVs;(2)An improved method named MN-DDPG for introducing a type of mixed noises to assist UAV with exploring stochastic strategies for online optimal planning;and(3)An algorithm of taskdecomposition and pre-training for efficient transfer learning to improve the generalization capability of UAV’s control model built based on MN-DDPG.The experimental simulation results have verified that the proposed approach can achieve good self-adaptive adjustment of UAV’s flight attitude in the tasks of maneuvering target tracking with a significant improvement in generalization capability and training efficiency of UAV tracking controller in uncertain environments.

An impact angle constraint integral sliding mode guidance law for maneuvering targets interception

An integral sliding mode guidance law(ISMGL)combined with the advantages of the integral sliding mode control(SMC)method is designed to address maneuvering target interception problems with impact angle constraints.The relative motion equation of the missile and the target considering the impact angle constraint is established in the longitudinal plane,and an integral sliding mode surface is constructed.The proposed guidance law resolves the existence of a steady-state error problem in the traditional SMC.Such a guidance law ensures that the missile hits the target with an ideal impact angle in finite time and the missile is kept highly robust throughout the interception process.By adopting the dynamic surface control method,the ISMGL is designed considering the impact angle constraints and the autopilot dynamic characteristics.According to the Lyapunov stability theorem,all states of the closed-loop system are finally proven to be uniformly bounded.Simulation results are compared with the general sliding mode guidance law and the trajectory shaping guidance law,and the findings verify the effectiveness and superiority of the ISMGL.

Modified unscented Kalman filter using modified filter gain and variance scale factor for highly maneuvering target tracking

To improve the low tracking precision caused by lagged filter gain or imprecise state noise when the target highly maneuvers, a modified unscented Kalman filter algorithm based on the improved filter gain and adaptive scale factor of state noise is presented. In every filter process, the estimated scale factor is used to update the state noise covariance Qk, and the improved filter gain is obtained in the filter process of unscented Kalman filter （UKF） via predicted variance Pk｜k-1, which is similar to the standard Kalman filter. Simulation results show that the proposed algorithm provides better accuracy and ability to adapt to the highly maneuvering target compared with the standard UKF.

Sensor scheduling for ground maneuvering target tracking in presence of detection blind zone

Continuous and stable tracking of the ground maneuvering target is a challenging problem due to the complex terrain and high clutter. A collaborative tracking method of the multisensor network is presented for the ground maneuvering target in the presence of the detection blind zone(DBZ). First, the sensor scheduling process is modeled within the partially observable Markov decision process(POMDP) framework. To evaluate the target tracking accuracy of the sensor, the Fisher information is applied to constructing the reward function. The key of the proposed scheduling method is forecasting and early decisionmaking. Thus, an approximate method based on unscented sampling is presented to estimate the target state and the multi-step scheduling reward over the prediction time horizon. Moreover, the problem is converted into a nonlinear optimization problem, and a fast search algorithm is given to solve the sensor scheduling scheme quickly. Simulation results demonstrate the proposed nonmyopic scheduling method(Non-MSM) has a better target tracking accuracy compared with traditional methods.

Multiple model efficient particle filter based track-before-detect for maneuvering weak targets

It is a tough problem to jointly detect and track a weak target, and it becomes even more challenging when the target is maneuvering. The above problem is formulated by using the Bayesian theory and a multiple model(MM) based filter is proposed. The filter presented uses the MM method to accommodate the multiple motions that a maneuvering target may travel under by adding a random variable representing the motion model to the target state. To strengthen the efficiency performance of the filter,the target existence variable is separated from the target state and the existence probability is calculated in a more efficient way. To examine the performance of the MM based approach, a typical track-before-detect(TBD) scenario with a maneuvering target is used for simulations. The simulation results indicate that the MM based filter proposed has a good performance in joint detecting and tracking of a weak and maneuvering target, and it is more efficient than the general MM method.

Extended differential geometric guidance law for intercepting maneuvering targets

Without assumptions made on motion states of missile and target, an extended differential geometric guidance law is derived. Through introducing a line of sight rotation coordinate system, the derivation is simplified and has more explicit physical significances. The extended law is theoretically applicable to any engagement scenarios. Then, on basis of the extended law, a modified one is designed without the requirement of target acceleration and an approach is proposed to determining the applied direction of commanded missile acceleration. Qualitative analysis is carried out to study the capture performance and a criterion for capture is given. Simulation results indicate the two laws are effective and make up the deficiency that pure proportional navigation suitable for endoatmospheric interceptions cannot deal with high-speed maneuvering targets. Furthermore, the correctness of the criterion is validated.