Simulation research on scattering characteristics by complex targets

A simulation approach based on a full-wave numerical method is presented to study electromagnetic characteristics by complex targets. How to validate simulation results is considered thoroughly under no analytical and measured data, where a double-check criterion is designed for our simulation approach. As an example, the scattering of F-117A is studied by using our simulation approach under all polarizations, different frequency bands, incident and scattering directions, etc., some of which, such as cross-polarization, bistatic RCS, have not been considered in the previous literature.

Support vector regression model for complex target RCS predicting

The electromagnetic scattering computation has developed rapidly for many years; some computing problems for complex and coated targets cannot be solved by using the existing theory and computing models. A computing model based on data is established for making up the insufficiency of theoretic models. Based on the ＂support vector regression method＂, which is formulated on the principle of minimizing a structural risk, a data model to predicate the unknown radar cross section of some appointed targets is given. Comparison between the actual data and the results of this predicting model based on support vector regression method proved that the support vector regression method is workable and with a comparative precision.

SCTE: RCS Prediction System for ComplexTarget and Interaction with Environment

A RCS prediction system named SCTE (Scattering from Complex Target and Environment) for calculating high-frequency electromagnetic scattering from complex target within complex environment is presented. The scattering body is described by Computer-Aided-Design (CAD) representations in which the complex body is modeled as NURBS (Non-Uniform Rational B-spline) surfaces. The complex environment (rough surface of sea or ground) is also carefully considered by using fractal function. Scattering fields are calculated by using physical optics and the equivalent currents methods. There is a good agreement between the present results and that from measurements which demonstrates the accuracy of this system.

An Approach to RCS Computation for Complex Targets

A practical approach for calculating the RCS (Radar Cross Section) of complex targets modeled with wire-grid-frame is presented. A way for generating a polyhedron model (facet-wedge model) with the wire-grid-frame data is described. For storing and reading the data of the polyhedron model in an easy way, a data structure is given.

Mammalian target of rapamycin complex 1 as an inducer of neurotrophic factors in dopaminergic neurons

The defining neuropathological feature of Parkinson＇s disease （PD） is the loss of nigrostriatal dopaminergic （DA） projections. This results in striatal dopamine levels and a biochemical reduction of movement disorders, such as a tremor at rest, rigidity of the limbs, bradykinesia, and postural instability （Kim et al., 2011; Kim et al., 2012; Burke and O＇Malley, 2013; Leem et al., 2014; Namet al., 2014）.

Scattering simulation and reconstruction of a 3D complex target above an underlying surface using SIMO radar with plane array

A SIMO(single input and multiple output) system of a step-frequency(SF) radar is used.It works in downward-looking spotlight mode and moves within a 2D synthetic plane array.A 3D(three-dimensional) matrix of bistatic scattering fields is produced in both the amplitude and phase from a 3D complex-shaped electric-large target above background surface.In numerical simulation,the bidirectional analytic ray tracing(BART) method is applied to calculate bistatic scattering in the SIMO observations from a volumetric target above background rough surface.An improved 3D RMA(range migration algorithm) is then utilized to make the imaging.Its 3D imaging is applied to reconstruct the target profile.As validation and comparison,the scattering fields of some simple targets are computed with comparisons of the BART and FEKO software.The SIMO techniques of imaging and reconstruction for a 3D target,such as a tank-like model over rough surface,are presented.

Role of mammalian target of rapamycin complex 2 in primary and secondary liver cancer

The mammalian target of rapamycin(mTOR)acts in two structurally and functionally distinct protein complexes,mTOR complex 1(mTORC1)and mTOR complex 2(mTORC2).Upon deregulation,activated mTOR signaling is associated with multiple processes involved in tumor growth and metastasis.Compared with mTORC1,much less is known about mTORC2 in cancer,mainly because of the unavailability of a selective inhibitor.However,existing data suggest that mTORC2 with its two distinct subunits Rictor and mSin1 might play a more important role than assumed so far.It is one of the key effectors of the PI3K/AKT/mTOR pathway and stimulates cell growth,cell survival,metabolism,and cytoskeletal organization.It is not only implicated in tumor progression,metastasis,and the tumor microenvironment but also in resistance to therapy.Rictor,the central subunit of mTORC2,was found to be upregulated in different kinds of cancers and is associated with advanced tumor stages and a bad prognosis.Moreover,AKT,the main downstream regulator of mTORC2/Rictor,is one of the most highly activated proteins in cancer.Primary and secondary liver cancer are major problems for current cancer therapy due to the lack of specific medical treatment,emphasizing the need for further therapeutic options.This review,therefore,summarizes the role of mTORC2/Rictor in cancer,with special focus on primary liver cancer but also on liver metastases.

3,6-dichlorobenzo[b]thiophene-2-carboxylic acid alleviates ulcerative colitis by suppressing mammalian target of rapamycin complex 1 activation and regulating intestinal microbiota

BACKGROUND 3,6-dichlorobenzo[b]thiophene-2-carboxylic acid(BT2)is a benzothiophene carboxylate derivative that can suppress the catabolism of branched-chain amino acid(BCAA)-associated mammalian target of rapamycin complex 1(mTORC1)activation.Previous studies have demonstrated the therapeutic effects of BT2 on arthritis,liver cancer,and kidney injury.However,the effects of BT2 on ulcerative colitis(UC)are unknown.AIM To investigate the anti-UC effects of BT2 and the underlying mechanism.METHODS Mouse UC models were created through the administration of 3.5%dextran sodium sulfate(DSS)for 7 d.The mice in the treated groups were administered salazosulfapyridine(300 mg/kg)or BT2(20 mg/kg)orally from day 1 to day 7.At the end of the study,all of the mice were sacrificed,and colon tissues were removed for hematoxylin and eosin staining,immunoblot analyses,and immunohistochemical assays.Cytokine levels were measured by flow cytometry.The contents of BCAAs including valine,leucine,and isoleucine,in mouse serum were detected by liquid chromatography-tandem mass spectrometry,and the abundance of intestinal flora was analyzed by 16S ribosomal DNA sequencing.RESULTS Our results revealed that BT2 significantly ameliorated the inflammatory symptoms and pathological damage induced by DSS in mice.BT2 also reduced the production of the proinflammatory cytokines interleukin 6(IL-6),IL-9,and IL-2 and increased the anti-inflammatory cytokine IL-10 level.In addition,BT2 notably improved BCAA catabolism and suppressed mTORC1 activation and cyclooxygenase-2 expression in the colon tissues of UC mice.Furthermore,highthroughput sequencing revealed that BT2 restored the gut microbial abundance and diversity in mice with colitis.Compared with the DSS group,BT2 treatment increased the ratio of Firmicutes to Bacteroidetes and decreased the abundance of Enterobacteriaceae and Escherichia-Shigella.CONCLUSION Our results indicated that BT2 significantly ameliorated DSS-induced UC and that the latent mechanism involved the suppression of BCAA-associated mTORC1 activation and modulation of the intestinal flora.

Attractive target wave patterns in complex networks consisting of excitable nodes

This review describes the investigations of oscillatory complex networks consisting of excitable nodes, focusing on the target wave patterns or say the target wave attractors. A method of dominant phase advanced driving （DPAD） is introduced to reveal the dynamic structures in the networks supporting osciUations, such as the oscillation sources and the main excitation propagation paths from the sources to the whole networks. The target center nodes and their drivers are regarded as the key nodes which can completely determine the corresponding target wave patterns. Therefore, the center （say node A） and its driver （say node B） of a target wave can be used as a label, （A, B）, of the given target pattern. The label can give a clue to conveniently retrieve, suppress, and control the target waves. Statistical investigations, both theoretically from the label analysis and numerically from direct simulations of network dynamics, show that there exist huge numbers of target wave attractors in excitable complex networks if the system size is large, and all these attractors can be labeled and easily controlled based on the information given by the labels. The possible applications of the physical ideas and the mathematical methods about multiplicity and labelability of attractors to memory problems of neural networks are briefly discussed.

大规模个性化定制的价值涌现原理——价值共创的新形态

依托生产模式的三维结构框架,从复杂性视角,针对手工生产、大规模生产、大规模定制、大规模个性化和大规模个性化定制等主要生产模式,分析其中从价值交易到价值共创再到价值涌现的价值生成演化历程,提炼出客户维、生产维和服务维3个维度下的价值生成路径。基于局部作用导致整体涌现的系统科学观念,揭示出大规模个性化定制的价值涌现原理,明确了该原理的基本内涵。人单合一是大规模个性化定制的一种具体实现,其价值创造规律遵从价值涌现原理。生态价值是人单合一价值创造的源泉,海尔的超模块平台组织结构可实现人单合一中的价值涌现。大规模个性化定制的价值生成过程具有涌现性特征,它以价值涌现的方式表现出来,是价值共创的一种新形态。

复杂背景下基于YOLOv7-tiny的图像目标检测算法

“黑飞”无人机一旦带有炸弹等物品,会对人们带来威胁。对在公园、游乐场、学校等复杂背景下“黑飞”的无人机进行目标检测是十分必要的。前沿算法YOLOv7-tiny属于轻量级网络,具有更小的网络结构和参数,更适合检测小目标,但在识别小目标无人机时出现特征提取能力弱、回归损失大、检测精度低的问题;针对此问题,提出了一种基于YOLOv7-tiny改进的无人机图像目标检测算法YOLOv7-drone。首先,建立无人机图像数据集;其次,设计一种新的注意力机制模块SMSE嵌入到特征提取网络中,增强对复杂背景下无人机目标的关注度;然后,在主干网络中融入RFB结构,扩大特征层的感受野,丰富特征信息以增强特征提取的鲁棒性;然后,改进网络中的特征融合机制,通过新增小目标检测层,增加对小尺度目标的检测精度;然后,改变损失函数提高模型的收敛速度,减少损失以增强模型的鲁棒性;最后,引入可变形卷积(Deformable convolution, DCN),更好的根据目标本身形状进行特征提取,提升了检测精度。在PASCAL VOC公共数据集上进行对比实验,结果表明改进后的算法YOLO7-drone相比于YOLOv7-tiny,平均精度(map@0.5)提升了6%;在自制无人机数据集上进行实验,结果表明YOLOv7-drone与原算法相比,平均精度(map@0.5)提高了6.1%,并且检测速度为72帧/s;与YOLOv5l、YOLOv7目标检测算法进行对比实验,结果表明改进后的算法在平均精度(map@0.5)上分别高于对比算法4%、3.1%,验证了文中算法的可行性。

复杂水文微弱多目标激光探测仿真与实验

为了探究在近岸复杂水体中激光探测对微弱目标的探测能力,研究水质、目标特征、目标距离对水下激光探测的影响具有重要理论和应用价值。论文建立了水下微弱目标激光探测模型,采用蒙特卡洛仿真验证了不同浊度微弱多目标激光探测性能,模拟了不同距离下微弱目标的激光后向散射回波信号,对多个不同反射系数的目标后向散射回波特性进行了分析。同时设计并研制了灵巧便携式水下微弱目标激光探测系统,进行了实验室及外场湖泊环境下的多目标探测、测距测试验证。在浊度为12.87 NTU的近岸湖泊水域,该系统可在10 m范围内对3~4个直径为80~400μm的不同低反射系数的混合小目标进行有效探测,平均测量误差为±0.11 m,与理论仿真结果一致。本文研究结果可为蓝绿激光水下多微弱目标探测链路计算、系统设计及参数优化提供参考,可以支撑近海浑浊水体下水下障碍物激光探测工程实践。

受体相互作用蛋白激酶1调节癌症进展和免疫反应的研究现状

受体相互作用蛋白激酶1(receptor-interacting protein kinase 1,RIPK1)是一种多结构域丝氨酸/苏氨酸蛋白激酶。它通过磷酸化特定的蛋白质,引起下游的信号转导和生物效应。近年来,随着对RIPK1的深入研究,学者发现其在自身免疫性疾病、神经退行性疾病,以及多种实体瘤和血液肿瘤中具有重要意义。一方面,RIPK1通过激活特定通路如核因子-κB(nuclear factor-κB,NF-κB)和丝裂原活化蛋白激酶(mitogen-activated protein kinase,MAPK)等促进细胞存活及炎症反应。另一方面,RIPK1通过与胱天蛋白酶-8(cysteinyl aspartate specific proteinase-8,caspase-8)作用促进凋亡,或与RIPK3和混合谱系激酶结构域样假激酶(mixed lineage kinase domain-like protein,MLKL)作用促进坏死性凋亡的发生。RIPK1作为上游信号在不同肿瘤患者中表达水平不同。其支架功能和激酶活性可以调节癌症进展,也可以启动机体适应性免疫,抑制肿瘤进展;此外,还能产生免疫抑制性肿瘤微环境而促进肿瘤的发展。其双重作用在调节癌症的发生、发展及机体免疫反应方面都有所展现,可以作为新的治疗靶点控制癌症进展。该文从RIPK1的结构入手,深入探讨其功能,特别是其在调节癌症进展和免疫反应方面的功能,为癌症靶向药物的开发提供新的思路。

复杂场景下一种改进的单目标跟踪算法研究

针对部分复杂场景下目标跟踪存在跟踪框漂移问题,基于孪生候选区域生成网络(SiamRPN),融合通道注意力模块和选择核心模块(SK Module),提出一种单目标跟踪算法CAKSiamRPN。特征提取部分引入高效通道注意模块(ECAM)和基于标准化的通道注意力模块(NCAM),在不降低通道维度的情况下,摒弃相似信息,突出显著特征,关注并提取特定信息;在候选区域生成网络(RPN)嵌入SK Module,增强全局信息嵌入,减少填充操作的影响。将改进算法与SiamRPN及其它经典单目标跟踪算法在OTB100和UAV123数据集上进行实验对比。实验结果表明:跟踪精度和成功率明显提高,能更好地适应复杂场景,具有更强的鲁棒性。

中药复方的现代基础研究进展述评

中药复方的现代基础研究是中药现代化发展的必经之路。本文从中药复杂作用模式解析研究策略与方法、中药直接靶点发现技术与应用、系统生物学驱动的中药复杂作用解析三个方面,对中药复方的现代基础研究进行综述,并对其未来发展进行展望。

公共区域监控视频运动目标跟踪系统设计

公共监控区域中的运动目标在运动方向和运动速度方面具有一定的随机性,这增加了目标跟踪难度。为了提升运动目标的跟踪性能,设计了公共区域监控视频运动目标跟踪系统。通过设计系统总体框架,确定了系统工作流程;基于建立的总体框架完成了系统各个硬件模块的设计,并着重设计了系统检测跟踪模块,使用Kalman滤波算法预测视频运动目标状态辅助该模块完成目标的精准跟踪;依据系统工作流程完成了系统的软件流程设计;结合系统的硬件、软件设计实现对公共区域的视频运动目标检测跟踪。实验结果表明,设计系统在跟踪公共区域的视频运动目标时,跟踪时间短、跟踪精度高、检测跟踪性能高。

基于网络靶点收敛算法预测治疗晚期肺腺癌的候选药物

目的:筛选晚期肺腺癌调控网络的收敛基因集,借助关联性图谱(CMap)预测治疗晚期肺腺癌的候选药物。方法:利用TCGA数据库检索肺腺癌转录组与临床数据,使用R4.0.3软件筛选肺腺癌早晚期患者的差异基因,使用Kaplan-Meier与log秩检验识别预后基因。DAVID和KEGG数据库对预后基因进行富集分析。依据背景网络构建差异预后基因调控网络,集体影响(CI)算法计算网络收敛基因集,将基因集导入CMap获得治疗晚期肺腺癌的候选药物,进一步对候选药物进行查找和分析。结果:共获得差异表达基因3409个,其中1981个与生存显著相关。富集分析结果显示,预后基因主要与细胞分裂、染色体分离、有丝分裂细胞周期、DNA复制、B细胞激活、T细胞激活等生物学过程相关;CI方法筛选得到晚期肺腺癌收敛预后基因96个,通过CMap连接图计算得到排名前20的候选化合物,其中,thapsigargin和nutlin-3通过文献验证对晚期肺腺癌有潜在的治疗作用。结论:借助生物信息学、网络靶点收敛算法和CMap数据库挖掘对晚期肺腺癌具有治疗作用的药物,为发现疾病的候选治疗靶点与药物开辟了新途径和思路。

基于NGG-YOLOv5的空对地UXO目标检测方法

为提高无人机在复杂环境下对地面未爆弹(UXO)目标的辨识精度,提出了一种改进YOLOv5的UXO目标检测方法。该方法在YOLOv5的基础上,改进原YOLOv5网络的损失函数以提高对UXO目标的识别精度,同时,通过添加注意力机制、改进马赛克数据增强、改进预测框筛选机制提高对UXO目标的识别效率,实现了空对地场景下对UXO目标的检测,并具有较好的精度和速度。实验选取多组不同复杂背景的UXO数据集进行标注并训练,得到UXO目标模型,然后从模型训练结果和目标检测结果的角度评估方法和模型的正确性。实验结果表明:NGG-YOLOv5所得模型检测准确性和检测速度对比原YOLOv5有明显的提升,准确率从78%提高至91%,平均精度均值(mAP)从50%提高至56%,在所用4种复杂背景下均可有效检测出UXO目标,且漏警率低。

基于YOLOv5s-AntiUAV的反无人机目标检测算法研究

随着无人机的应用领域不断拓展,无人机的“黑飞”给公共安全造成严重损害。为解决侵入式无人机小目标在复杂飞行环境下的错检和漏检问题,提出基于YOLOv5s-AntiUAV的反无人机目标检测算法。首先,引入结合深度超参数卷积的Slim-Neck范式,增强算法特征提取能力并保持计算效率。其次,在骨干和颈部网络引入SPD-Conv模块,提高在低分辨率图像中小目标的检测性能。最后,用Alpha-CIoU替换YOLOv5s算法中的CIoU,增强算法泛用性。YOLOv5s-AntiUAV算法与YOLOv5s、SSD和Faster R-CNN算法在数据集Anti-UAV上的对比实验结果表明,改进算法的mAP@0.5值分别增长了1.1、12.1和4.9个百分点,凸显其实用性。由在VisDrone2019数据集上进行的迁移实验显示,相较于YOLOv5s算法,改进算法mAP@0.5值提升了4.5个百分点,表明其相较于原算法具有更强的鲁棒性。

随机数据丢包情况下组网雷达功率分配算法

在组网雷达系统中,由于节点间通信信号传播存在路径衰落等问题,雷达量测数据与资源调度数据的传输接收存在随机性。引入随机丢包变量,用以表征数据接收的随机性,建立丢包状态下组网雷达多目标跟踪功率分配模型,推导了该模型多目标跟踪误差期望下界,最终建立了总功率一定条件下,以最小化目标威胁度加权期望跟踪误差下界的数学优化模型,并通过凸优化算法求解。仿真结果表明,与不考虑随机丢包变量的功率分配算法相比,所提算法在多种场景下均能有效提高目标跟踪精度。