A Real-Time Small Target Vehicle Detection Algorithm with an Improved YOLOv5m Network Model

To address the challenges of high complexity,poor real-time performance,and low detection rates for small target vehicles in existing vehicle object detection algorithms,this paper proposes a real-time lightweight architecture based on You Only Look Once(YOLO)v5m.Firstly,a lightweight upsampling operator called Content-Aware Reassembly of Features(CARAFE)is introduced in the feature fusion layer of the network to maximize the extraction of deep-level features for small target vehicles,reducing the missed detection rate and false detection rate.Secondly,a new prediction layer for tiny targets is added,and the feature fusion network is redesigned to enhance the detection capability for small targets.Finally,this paper applies L1 regularization to train the improved network,followed by pruning and fine-tuning operations to remove redundant channels,reducing computational and parameter complexity and enhancing the detection efficiency of the network.Training is conducted on the VisDrone2019-DET dataset.The experimental results show that the proposed algorithmreduces parameters and computation by 63.8% and 65.8%,respectively.The average detection accuracy improves by 5.15%,and the detection speed reaches 47 images per second,satisfying real-time requirements.Compared with existing approaches,including YOLOv5m and classical vehicle detection algorithms,our method achieves higher accuracy and faster speed for real-time detection of small target vehicles in edge computing.

Identification of a dihydroorotate dehydrogenase inhibitor thatinhibits cancer cell growth by proteomic profiling

Dihydroorotate dehydrogenase(DHODH)is a central enzyme of the de novo pyrimidine biosynthesis pathway and is a promising drug target for the treatment of cancer and autoimmune diseases.This study presents the identification of a potent DHODH inhibitor by proteomic profiling.Cell-based screening revealed that NPD723,which is reduced to H-006 in cells,strongly induces myeloid differentiation and inhibits cell growth in HL-60 cells.H-006 also suppressed the growth of various cancer cells.Proteomic profiling of NPD723-treated cells in ChemProteoBase showed that NPD723 was clustered with DHODH inhibitors.H-006 potently inhibited human DHODH activity in vitro,whereas NPD723 was approximately 400 times less active than H-006.H-006-induced cell death was rescued by the addition of the DHODH product orotic acid.Moreover,metabolome analysis revealed that H-006 treatment promotes marked accumulation of the DHODH substrate dihydroorotic acid.These results suggest that NPD723 is reduced in cells to its active metabolite H-006,which then targets DHODH and suppresses cancer cell growth.Thus,H-006-related drugs represent a potentially powerful treatment for cancer and other diseases.

Methodology of drug screening and target identification for new necroptosis inhibitors

Apoptosis has been considered as the only form of regulated cell death for a long time. However, a novel form of programmed cell death called necroptosis was recently reported. The process of necroptosis is regulated and plays a critical role in the occurrence and development of multiple human diseases. Thus,the study on the molecular mechanism of necroptosis and its effective inhibitors has been an attractive field for researchers. Herein, we introduce the molecular mechanism of necroptosis and focus on the literature about necroptosis drug screening in recent years. In addition, the identification of the critical drug targets of the necroptosis is also discussed.

Computational Identification of Conserved microRNAs and Their Targets in Tea (Camellia sinensis)

MicroRNAs (miRNAs) are a class of ~22 nucleotides long non coding RNA molecules which play an important role in gene regulation at the post transcriptional level. The conserved nature of miRNAs provides the basis of new miRNA identification through homology search. In an attempt to identify new conserved miRNAs in tea, previously known plant miRNAs were used for searching their homolog in a tea Expressed Sequence Tags and full length nucleotide sequence database. The sequences showing homolog no more than four mismatches were predicted for their fold back structures and passed through a series of filtration criteria, finally led us to identify 13 conserved miRNAs in tea belonging to 9 miRNA families. A total of 37 potential target genes in Arabidopsis were identified subsequently for 7 miRNA families based on their sequence complementarity which encode transcription factors (8%), enzymes (30%) and transporters (14%) as well as other proteins involved in physiological and metabolic processes (48%). Overall, our findings will accelerate the way for further researches of miRNAs and their functions in tea.

Target Ship Identification Algorithm Based on Comprehensive Correlation Discriminant and Information Entropy

Ship type identification is an important part of electronic reconnaissance. However, in the existing methods, such as statistical-based methods and fuzzy-mathematics-based methods, the information acquired by the passive sensor is not fully utilized, and there is a certain ambiguity in the assignment relationship of the emitters-ship. They can’t conclude the accurate and reliable assignment relationship of the emitters-ship. Therefore, this paper proposes a comprehensive correlation discriminant method to obtain a more reliable and comprehensive emitters-ship assignment, and then uses information entropy method to identify the type of the target ship on the basis of this association and assign the credibility. The simulation results show that this algorithm can effectively solve the problem of target ship type identification using the information of multi-passive sensors.

OPTIMAL APPROXIMATION ALGORITHM OF FEATURE COEFFICIENTS AND IDENTIFICATION OF TARGET

On the basis of target transfer function with the early time and late time response together, a method for solving the feature coefficients of target is investigated by utilizing approximation theory and method. Then, the feature coefficients are classified by the minimum distance criterion to identify targets automatically.

RADAR TARGET IDENTIFICATION BY ADAPTIVE DISCRIMINATION WAVEFORM SYNTHESIS AND NEAREST NEIGHBOR NEURAL NETWORK

In this paper,a new radar target identification scheme is presented based on adaptivediscrimination waveform synthesis and a nearest neighbor neural network.It can directly use theimpulse response of the target to synthesize discrimination waveform,so the poles extractionprocedure is not required.Particularly,it can successfully operate on the case that the poles ofthe target are weakly dependent on the aspect angle.

METHODS OF RADAR DATA COMPRESSION AND TARGET IDENTIFICATION BASED ON BIORTHOGONAL FDWT

In this paper, by using the biorthogonal quadrature filters, the biorthogonal mul-tiresolution analysis of finite dimension space equipped with inner product and the fast discrete wavelet transform (FDWT) are constructed. The dual transform method is proposed and the radar data storage is reduced by it. The method of choosing the wavelet coefficients, and the methods of correlation and nearest neighbor classification in wavelet domain based on the compressed data, are presented. The experimental results of the classification, using the high resolution range returns from six kinds of aircrafts, show that the methods of transform, compression and recognition are efficient.

GTD MODEL-BASED TIME-SHIFT INVARIANT TARGET IDENTIFICATION USING MATCHING PURSUITS AND LIKELIHOOD RATIO TESTS

In order to improve the identification capability of ultra wide-band radar,this paper in-troduces a step-variant multiresolution approach for the time-shift parameter estimation. Subsequently,combining with the approach,a Geometrical Theory of Diffraction(GTD) model-based time-shift Invariant method to target identification using Matching Pursuits and Likelihood Ratio Test(IMPLRT) is developed. Simulation results using measured scattering signatures of two targets in an ultra wide-band chamber are presented contrasting the performance of the IMPLRT to the Wang's MPLRT technique.

Traditional Chinese medicine target identification based on ＂Target Fishing＂ strategy

OBJECTIVE Our group mainly focuses on the target identification and pharmacological mechanism study of TCM.We deeply identified the direct targets of the active ingredients in TCM using molecule probe-'Target Fishing' technology in chemical biology,and explored the related signaling pathways to explain the traditional efficiency of TCM.METHODS We synthesized biotin-tagged mole.cule probe by connecting biotin tag to TCM active molecule using PGE as a linker.Then,the biotintagged molecule probe was bound to the surface of solid beads by strong biotin-avidin interaction.Thus,the molecule probe-bound beads were mixed with cell lysates to capture the potential targets and identified by MS.RESULTS Our study found that SA which was an anti-inflammatory compound.could selectively bind to IMPDH2 in microglial cells,and SA showed weaker anti-inflammatory effect on IMPDH2-knock down microglial cells,suggesting IMPDH2 as a key anti-inflammatory target for SA.Ad.ditionally,handelin was a key anti-inflammatory compound.We identified the target protein of handelin as Hsp70 from microglial cells using target pull-down technology.Moreover,handelin showed weaker anti-inflammatory effect on Hsp70-knock down microglial cells,revealing that Hsp70 was the direct antiinflammatory target of handelin.CONCLUSION Our study provided methodology references for TCM target identification in the future,and also showed a new insight for exploring the pharmacological mechanism of TCM active ingredients.More importantly,we can perform scientific annotation for TCM efficiency by clarifying the biological functions of each target protein,showing important significance on modernization and internationalization of TCM.

An Adjoint-Free CNOP–4DVar Hybrid Method for Identifying Sensitive Areas in Targeted Observations: Method Formulation and Preliminary Evaluation

This paper proposes a hybrid method, called CNOP–4 DVar, for the identification of sensitive areas in targeted observations, which takes the advantages of both the conditional nonlinear optimal perturbation(CNOP) and four-dimensional variational assimilation(4 DVar) methods. The proposed CNOP–4 DVar method is capable of capturing the most sensitive initial perturbation(IP), which causes the greatest perturbation growth at the time of verification;it can also identify sensitive areas by evaluating their assimilation effects for eliminating the most sensitive IP. To alleviate the dependence of the CNOP–4 DVar method on the adjoint model, which is inherited from the adjoint-based approach, we utilized two adjointfree methods, NLS-CNOP and NLS-4 DVar, to solve the CNOP and 4 DVar sub-problems, respectively. A comprehensive performance evaluation for the proposed CNOP–4 DVar method and its comparison with the CNOP and CNOP–ensemble transform Kalman filter(ETKF) methods based on 10 000 observing system simulation experiments on the shallow-water equation model are also provided. The experimental results show that the proposed CNOP–4 DVar method performs better than the CNOP–ETKF method and substantially better than the CNOP method.

基于M-DBT框架的岩质边坡落石跟踪算法研究

边坡落石是一种常见的自然灾害,构建高效准确的落石监测方法对边坡安全监控十分重要。传统基于视频图像的落石监测方法缺乏对落石运动的关注。针对该问题,选取YOLOv5s和DeepSort模型,基于DBT框架,从框架、算法两个层面对模型进行改进,提出了基于M-DBT框架的落石跟踪算法。框架层面,基于Background Matting算法搭建了运动检测器,并融入原有的DBT框架中,依据运动检测结果动态调用落石跟踪算法,提出了M-DBT目标跟踪算法框架,提高了设备算力的使用效率。算法层面,基于CBAM注意力机制、ASPP空间金字塔池化、SIoU损失函数和Swin Transformer网络集成优化了YOLOv5s和DeepSort算法,提高了算法对落石特征的提取能力、预测框的准确率及检测目标ID分配精度。使用自建目标检测和图像分类数据集进行模型训练与试验,试验结果表明:基于M-DBT框架的落石跟踪算法与基于DBT框架的算法相比,能有效减少算力资源消耗(最高可减少21.5%);改进后的YOLOv5s模型检测精度提高了8.4%,岩块检测准确率最高达87%;改进后DeepSort模型的跟踪精度提升了8.9%,跟踪准确率最高达84%。所提落石跟踪算法能够实现边坡落石的检测与跟踪,具有较强的实用价值。

M通道与神经精神疾病和心血管疾病研究进展

M通道是电压门控钾通道Kv7家族的重要组成部分,主要分布在神经系统和血管系统中。M通道介导M电流(Im),稳定细胞膜电位和抑制异常放电,在调节神经元兴奋性和血管张力方面发挥重要作用。研究显示,M通道功能异常与神经精神疾病和心血管疾病存在密切关系,是药物治疗的关键靶点。本文对M通道在不同组织中结构异质性和功能进行概述,并综述其在癫痫、阿尔茨海默病、抑郁症、高血压、冠状动脉疾病、肺动脉高压等神经精神疾病和心血管疾病发生发展中的作用,为疾病治疗提供新视角和靶点。

多血型系统抗体鉴定和交叉配血策略一例抗-f合并抗-M

目的鉴定一例患者血浆中抗体的特异性并制定交叉配血的策略。方法采用盐水介质试管法和抗人球蛋白卡(LISS/Coombs卡)做抗体筛选和抗体鉴定,根据谱细胞、酶处理谱细胞及4℃谱细胞反应格局,确定患者血浆中意外抗体的特异性。结果患者Rh血型为CCDee,MN血型为NN。多种抗体鉴定结果显示,其血浆中存在同种抗体:Rh血型系统抗-f(f:ce复合抗原)合并MNS血型系统抗-M。结论抗-f仅与具有f抗原(R0、r)的红细胞反应,且能被蛋白水解酶增强;IgG类抗-M在4℃环境的反应性更强。经过输血免疫后,患者产生抗-f和抗-M抗体,交叉配血策略为优先选择无M抗原红细胞进行交叉配血,对配血相合的红细胞成分血进行RhCE抗原检测,选择无f抗原红细胞发血。

Utilizing engineered extracellular vesicles as delivery vectors in the management of ischemic stroke:a special outlook on mitochondrial delivery

Ischemic stroke is a secondary cause of mortality worldwide,imposing considerable medical and economic burdens on society.Extracellular vesicles,serving as natural nanocarriers for drug delivery,exhibit excellent biocompatibility in vivo and have significant advantages in the management of ischemic stroke.However,the uncertain distribution and rapid clearance of extracellular vesicles impede their delivery efficiency.By utilizing membrane decoration or by encapsulating therapeutic cargo within extracellular vesicles,their delivery efficacy may be greatly improved.Furthermore,previous studies have indicated that microvesicles,a subset of large-sized extracellular vesicles,can transport mitochondria to neighboring cells,thereby aiding in the restoration of mitochondrial function post-ischemic stroke.Small extracellular vesicles have also demonstrated the capability to transfer mitochondrial components,such as proteins or deoxyribonucleic acid,or their sub-components,for extracellular vesicle-based ischemic stroke therapy.In this review,we undertake a comparative analysis of the isolation techniques employed for extracellular vesicles and present an overview of the current dominant extracellular vesicle modification methodologies.Given the complex facets of treating ischemic stroke,we also delineate various extracellular vesicle modification approaches which are suited to different facets of the treatment process.Moreover,given the burgeoning interest in mitochondrial delivery,we delved into the feasibility and existing research findings on the transportation of mitochondrial fractions or intact mitochondria through small extracellular vesicles and microvesicles to offer a fresh perspective on ischemic stroke therapy.

An innovative inertial parameters identification method for non-cooperative space targets based on electrostatic interaction

Inertial characteristics of non-cooperative targets are crucial for space capture and sub-sequent on-orbit servicing.Previous methods for identifying inertial parameters involve proximity operations,which are associated with the risk of collision with non-cooperative targets.This paper introduces a long-range,contactless method for identifying the inertial parameters of a non-cooperative target during the pre-capture phase.Specifically,electrostatic interaction is used as an external excitation to alter the target's motion.A force estimation algorithm that uses measure-ments from visual and potential sensors is proposed to estimate the electrostatic interaction and eliminate the need for force sensors.Furthermore,a recursive estimation-identification framework is presented to concurrently estimate the coupled motion state,weak electrostatic interaction,and inertial parameters of the target.The simulation results show that the proposed method extends the identification distance to 170 times that of the previous method while maintaining high identifica-tion precision forall parameters.

Isolation, Molecular Identification and under Lab Evaluation of the Entomopathogenic Fungi <i>M. anisopliae</i>and <i>B. bassiana</i>against the Red Palm Weevil <i>R. ferrugineus</i>in Gaza Strip

Plant diseases generate challenging problems in commercial, agriculture and pose real economic threats to both conventional and organic farming systems. The red palm weevil (Rhynchophorus ferrugineus) (RPW) is one of the most destructive pests of palms in the world. Nowadays, control methods revolve around treatments based on chemicals, biotechnological systems using semi-chemicals or the development of the sterile insect technique (hardly sustainable at this time) and biological control. Biological control as the use of natural microorganisms, extracted products from microorganisms or genetically improved to resist or eliminate of pathogens. Our aim was to evaluate the entomopathogenicity of indigenous Beauveria bassiana and Metarhizium anisopliae obtained in Gaza strip against larvae and adults of R. ferrugineus in order to identify indigenous strains potentially suitable for Red Palm Weevil biological control. B. bassiana & M. anisopliae were isolated from larvae and adult dead of RPW from different position of Gaza strip. Morphological analysis of the isolated fungi and molecular identification was determined using PCR technique. Also, the efficiency of the isolated fungi were evaluated under lab conditions and optimized as a biological agent. On the anther hand, the ability of treated RPW male to infect females is examined and calculated using Abbott's formula. Our results showed that the B. bassiana and M. anisopliae exhibited a good biological control agent against larvae and adults of RPW. The pathogenicity of the two most virulent isolates and the toxicity assay on larvae showed a highest mortality percentage nearly to 100% by 6 days after spraying the larvae with 3.4 × 108 spores/ml of B. bassiana. The mortality percentage reaches to 90% after spraying the larvae with 3.6 × 108 spores/ml of M. anisopliae. The mortality for the adults treated with pesticide arrives to 50% and the control group 10% at the same time. The results revealed that the infection of the adult males by Entomopathogenic fungi (EPF) can be disseminated into the healthy population, after RPW treatment with B. bassiana and M. anisopliae. Our research concludes that B. bassiana and M. anisopliae locally isolated can be used as biological very effective.

Electronic Throttle Control System: Modeling, Identification and Model-Based Control Designs

Electronic throttle control (ETC) system has worked its way to becoming a standard subsystem in most of the current automobiles as it has contributed much to the improvement of fuel economy, emissions, drivability and safety. Precision control of the subsystem, which consists of a dc motor driving a throttle plate, a pre-loaded return spring and a set of gear train to regulate airflow into the engine, seems rather straightforward and yet complex. The difficulties lie in the unknown system parameters, hard nonlinearity of the pre-loaded spring that pulls the throttle plate to its default position, and friction, among others. In this paper, we extend our previous results obtained for the modeling, unknown system parameters identification and control of a commercially available Bosch’s DV-E5 ETC system. Details of modeling and parameters identification based on laboratory experiments, data analysis, and knowledge of the system are provided. The parameters identification results were verified and validated by a real-time PID control implemented with an xPC Target. A nonlinear control design was then proposed utilizing the input-output feedback linearization approach and technique. In view of a recent massive auto recalls due to the controversial uncontrollable engine accelerations, the results of this paper may inspire further research interest on the drive-by-wire technology.

Safety Evaluation of Myricetin and Crude Extract from Myrica rubra Leaves on Non-target Organisms

[ Objective] The study aimed to supply important basis for developing environment-friendly pesticides with myricetin and crude extract of Myrica rubra leaves as effective components. [ Method] According to ＂Test guidelines for environmental safety evaluation on chemical pesticides＂, the toxicity of myricetin and crude extract of M. rubra leaves on non-target organisms was determined and the safety evaluation was carried out. [Result] MyriceUn and crude extract of M. rubra leaves had low toxicity on non-target organisms, such as earthworm, silkworm and soil microbes. Myricetin showed low toxicity and the crude extract of M. rubra leaves showed middle toxicity on tadpole. The high-concentration crude extract of M. rubra leaves had some antifeedant effect on silkworm. [ Conclusion] Myricetin and crude extract of M. rubra leaves had low toxicity on non-tar- get organisms in environment and they were relatively safe.

基于LC/MS的伊犁马3600 m速度赛赛前、赛后血浆代谢组学差异变化

【目的】研究伊犁马3600 m速度赛赛前赛后血浆中代谢物的差异变化。【方法】根据马场提供的遗传系谱,挑选5匹(3♂+2♀)无亲缘关系、体重(384.40±34.18)kg、年龄为2岁的速度赛用伊犁马,每日进行等强度训练。第25 d晨饲后4 h进行3600 m速度赛,试验马以(11.75±0.87)m/s的平均速度完成比赛。赛前安稳状态下和赛后即刻测定心率和呼吸频率,采集血液、制备血浆样品,采集血浆的质谱,采用非靶向性代谢组学方法测定代谢物。【结果】与赛前心率(39.80±0.40)bpm、呼吸频率(14.00±1.80)bpm相比,3600 m速度赛赛后即刻试验马心率(80.80±7.70)bpm、呼吸频率(78.80±3.90)bpm显著升高(P<0.05)。与赛前相比,试验马赛后即刻部分血浆代谢物产生显著变化,差异代谢物主要涉及柠檬酸循环、丙氨酸、天冬氨酸和谷氨酸代谢、五糖和葡萄糖醛酸间转化、半胱氨酸与蛋氨酸代谢、氧化磷酸化、脂肪酸降解、鞘脂代谢等生化代谢途径(P<0.05)。【结论】伊犁马3600 m速度赛前、赛后血浆样本的LC/MS代谢谱存在差异,差异代谢物涉及柠檬酸循环、糖酵解系统以及脂肪代谢、氨基酸代谢等过程,3600 m速度赛伊犁马机体呈现出无氧、有氧以及混氧代谢的特点。