Box-Behnken响应面法结合BP神经网络优化黑胡椒脐贴处方研究

目的采用Box-Behnken响应面法结合BP神经网络优化黑胡椒脐贴处方。方法在前期预试验的基础上,以载药量、促渗剂用量、聚乙二醇(polyethylene glycol,PEG)6000与微粉硅胶的比例为影响因素,进行单因素试验。结合体外透皮试验,利用高效液相色谱法测定胡椒碱的含量,对胡椒碱峰面积、指纹图谱的总峰面积和脐贴的成型性、剥离残留度和基质填充情况赋以权重,所得结果为综合评价指标。在单因素试验的基础上利用Box-Behnken响应面法结合BP神经网络优化脐贴处方。结果黑胡椒脐贴的最佳处方为载药量7%、氮酮4.5%、PEG6000与微粉硅胶的质量比为43∶1。结论黑胡椒脐贴的处方合理,可为后续贴剂的药效学研究提供基础。

Box-Behnken响应面法优选改良型正骨灵活血止痛膏成型工艺

目的:优选改良型正骨灵活血止痛膏成型工艺。方法:基于Box–Behnken响应面法,以蜂蜡用量、混合温度、料液比为影响因素,以传统经验鉴别法与客观物理参数法的综合评分为评价指标,在单因素试验基础上,考察各因素对综合评分的影响,优选最佳的成型工艺条件。结果:蜂蜡用量为1.9%,混合温度为81℃,料液比为2.5∶1 g/mL。验证试验结果综合评分RSD为0.86%。结论:优选得到的改良型正骨灵活血止痛膏成型工艺稳定可行。

结合高斯滤波与MASK的G-MASK人脸对抗攻击

深度神经网络的快速发展使其在计算机视觉和自然语言处理等领域取得较大成功,但是对抗攻击会导致神经网络的表现性能降低,对各类系统的安全保密性造成严重威胁。现有黑盒攻击方法在人脸识别中性能表现较差,攻击成功率较低且生成对抗样本迁移性不高。为此,提出一种结合高斯滤波与掩码的对抗攻击方法G-MASK。利用Grad-CAM输出的热力图确定对抗样本的掩码区域,使其只在掩码区域施加扰动,提高黑盒攻击成功率,采用扰动集成方法提高黑盒迁移能力,增强黑盒攻击鲁棒性,对生成的扰动进行高斯平滑处理,降低集成模型之间干扰噪声的差异,提高图像质量且增强扰动掩蔽性。实验结果表明,针对不同的人脸识别模型,G-MASK方法在保证白盒攻击成功率较高的条件下能够显著提升黑盒攻击效果,并具有更优的掩蔽性,经过模型扰动集成的对抗样本白盒攻击成功率均提高至98.5%以上,黑盒攻击成功率最高达到75.9%,与快速梯度符号法(FGSM)、迭代快速梯度符号法(I-FGSM)和动量迭代梯度符号法(MI-FGSM)相比分别平均提升12.1、10.6和8.2个百分点,充分验证了该方法的有效性。

AN ALGORITHM FOR AUTOMATICALLY GENERATING BLACK-BOX TEST CASES

Selection of test cases plays a key role in improving testing efficiency. Black-box testing is an important way of testing, and its validity lies on the selection of test cases in some sense. A reasonable and effective method about the selection and generation of test cases is urgently needed. This letter first introduces some usualmethods on black-box test case generation,then proposes a new algorithm based on interface parameters and discusses its properties, finally shows the effectiveness of the algorithm.

Reliable Space Pursuing for Reliability-based Design Optimization with Black-box Performance Functions

Reliability-based design optimization （RBDO） is intrinsically a double-loop procedure since it involves an overall optimization and an iterative reliability assessment at each search point. Due to the double-loop procedure, the computational expense of RBDO is normally very high. Current RBDO research focuses on problems with explicitly expressed performance functions and readily available gradients. This paper addresses a more challenging type of RBDO problem in which the performance functions are computation intensive. These computation intensive functions are often considered as a ＂black-box＂ and their gradients are not available or not reliable. On the basis of the reliable design space （RDS） concept proposed earlier by the authors, this paper proposes a Reliable Space Pursuing （RSP） approach, in which RDS is first identified and then gradually refined while optimization is performed. It fundamentally avoids the nested optimization and probabilistic assessment loop. Three well known RBDO problems from the literature are used for testing and demonstrating the effectiveness of the proposed RSP method.

Operating room black box:Scrutinizer of theatre practices

Objective:Adverse surgical events are a major cause of morbidity,mortality,and disability worldw ide.The cause of many such events can be attributed to interruptions in the operating room(OR),muli-tasking by surgeons,etc.The objective of this study was to observe the types and frequency of intra-operative wor kflow interruptions in our ORs.Method:This ccoss-sectional study was conducted from March Do April of 2023.An observational approach using an audio-video recording device was employed to record OR flow disr uptions.One elective OR and one emergency OR under the Department of General Surgery were selected for the study.All open and laparoscopic surger ies conducted in the selected ORs were included.An Internet Protocol camera'was installed in the selec ted ORS with a view of the entire room,including the anesthesia station.Audio-video recording was started after the first indsion and stopped after closure of the surgical site.Result:Of the 51 cases that were studied,45(88.2%)were elective,and 18(35.3%)were laparoscopic cases.They could be classified into 8 types of open procedures and 4 types of lapar oscopic procedures.The mean maximum headcount inside the OR was 15.5土3.6 and doors opened on average of 15.8土6.0 times during a procedure.Other interruptions were surgeons attending phone calls(24,47.1%),leaving the sterile area(21,41.2%),technical disturbances(32,62.7%),anesthetic interruptions(18,35.3%),and faulty instruments(29,56.9%)Elective procedures had a signifcandy higher average number of in-terruptions per operating hour than emergency procedures(175±8.6vs.7.1±2.9,p<0.01).Condusion:Preventable factors such as faulty instruments,anesthetic interruption,and attending phone calls by the surgeon are commonly observed in ORs.They need to be addressed by timely surgical audits or the adoption of continued sureillance methods that can help take measures to minimize their occurrence.

基于动量迭代快速梯度符号的SAR-ATR深度神经网络黑盒攻击算法

合成孔径雷达自动目标识别(SAR-ATR)领域缺乏有效的黑盒攻击算法,为此,该文结合动量迭代快速梯度符号(MI-FGSM)思想提出了一种基于迁移的黑盒攻击算法。首先结合SAR图像特性进行随机斑点噪声变换,缓解模型对斑点噪声的过拟合,提高算法的泛化性能;然后设计了能够快速寻找最优梯度下降方向的ABN寻优器,通过模型梯度快速收敛提升算法攻击有效性;最后引入拟双曲动量算子获得稳定的模型梯度下降方向,使梯度在快速收敛过程中避免陷入局部最优,进一步增强对抗样本的黑盒攻击成功率。通过仿真实验表明,与现有的对抗攻击算法相比,该文算法在MSTAR和FUSAR-Ship数据集上对主流的SAR-ATR深度神经网络的集成模型黑盒攻击成功率分别提高了3%~55%和6.0%~57.5%,而且生成的对抗样本具有高度的隐蔽性。

基于LSTM-RNN的船舶操纵运动黑箱建模

当无需揭示船舶操纵运动机理过程,而只需对输入输出建立映射时,黑箱建模成为一种有效途径。本文基于长短期记忆-循环神经网络(Long Short-term Memory-recurrent Neural Network,LSTM-RNN)构建船舶航向-舵角黑箱模型,LSTM网络为10-10-1结构,误差指标为RMSE,参数学习采用Adam算法。开展实船Z型操纵实验获取了航向-舵角数据。前70%用于模型训练,后30%用于模型测试。训练后的模型使得RMSE达到设计目标。对测试集数据,训练后模型拟合优度在0.98以上,表明其具有良好的有效性和泛化性。文中航向-舵角LSTM-RNN黑箱模型结构简明清晰,参数明确,易于实际操作使用,为航向-舵角关系建模提供了一种可行方法。

<i>PP</i>and <i>P<span style='text-decoration:overline;'>P</span></i>Multi-Particles Production Investigation Based on CCNN Black-Box Approach

The multiplicity distribution (P(nch)) of charged particles produced in a high energy collision is a key quantity to understand the mechanism of multiparticle production. This paper describes the novel application of an artificial neural network (ANN) black-box modeling approach based on the cascade correlation (CC) algorithm formulated to calculate and predict multiplicity distribution of proton-proton (antiproton) (PP and PP ) inelastic interactions full phase space at a wide range of center-mass of energy . In addition, the formulated cascade correlation neural network (CCNN) model is used to empirically calculate the average multiplicity distribution nch> as a function of . The CCNN model was designed based on available experimental data for = 30.4 GeV, 44.5 GeV, 52.6 GeV, 62.2 GeV, 200 GeV, 300 GeV, 540 GeV, 900 GeV, 1000 GeV, 1800 GeV, and 7 TeV. Our obtained empirical results for P(nch), as well as nch> for (PP and PP) collisions are compared with the corresponding theoretical ones which obtained from other models. This comparison shows a good agreement with the available experimental data (up to 7 TeV) and other theoretical ones. At full large hadron collider (LHC) energy ( = 14 TeV) we have predicted P(nch) and nch> which also, show a good agreement with different theoretical models.

MiR-142-3p Regulates ILC1s by Targeting HMGB1 via the NF-κB Pathway in a Mouse Model of Early Pregnancy Loss

Objective Innate lymphoid cells(ILCs)are a class of newly discovered immunocytes.Group 1 ILCs(ILC1s)are identified in the decidua of humans and mice.High mobility group box 1(HMGB1)is predicted to be one of the target genes of miR-142-3p,which is closely related to pregnancy-related diseases.Furthermore,miR-142-3p and HMGB1 are involved in regulating the NF-κB signaling pathway.This study aimed to examine the regulatory effect of miR-142-3p on ILC1s and the underlying mechanism involving HMGB1 and the NF-κB signaling pathway.Methods Mouse models of normal pregnancy and abortion were constructed,and the alterations of ILC1s,miR-142-3p,ILC1 transcription factor(T-bet),and pro-inflammatory cytokines of ILC1s(TNF-α,IFN-γand IL-2)were detected in mice from different groups.The targeting regulation of HMGB1 by miR-142-3p in ILC1s,and the expression of HMGB1 in normal pregnant mice and abortive mice were investigated.In addition,the regulatory effects of miR-142-3p and HMGB1 on ILC1s were detected in vitro by CCK-8,Annexin-V/PI,ELISA,and RT-PCR,respectively.Furthermore,changes of the NF-κB signaling pathway in ILC1s were examined in the different groups.For the in vivo studies,miR-142-3p-Agomir was injected in the uterus of abortive mice to evaluate the abortion rate and alterations of ILC1s at the maternal-fetal interface,and further detect the expression of HMGB1,pro-inflammatory cytokines,and the NF-κB signaling pathway.Results The number of ILC1s was significantly increased,the level of HMGB1 was significantly upregulated,and that of miR-142-3p was considerably downregulated in the abortive mice as compared with the normal pregnant mice(all P<0.05).In addition,miR-142-3p was found to drastically inhibit the activation of the NF-κB signaling pathway(P<0.05).The number of ILC1s and the levels of pro-inflammatory cytokines were significantly downregulated and the activation of the NF-κB signaling pathway was inhibited in the miR-142-3p Agomir group(all P<0.05).Conclusion miR-142-3p can regulate ILC1s by targeting HMGB1 via the NF-κB signaling pathway,and attenuate the inflammation at the maternal-fetal interface in abortive mice.

Electric power generation technology of natural gas pressure reduction:Insights from black box-gray box hierarchical exergy analysis and evaluation method

Based on the“three box”exergy analysis model,a black box-gray box hierarchical exergy analysis and evaluation method is put forward in this paper,which is applied to evaluate the power generation technology of differential pressure produced by natural gas expansion.By using the exergy analysis theory,the black box-gray box hierarchical exergy analysis models of three differential pressure power generation technologies are established respectively.Firstly,the“black box”analysis models of main energy consuming equipment are established,and then the“gray box”analysis model of the total system is established.Based on the calculation results of exergy analysis indexes,the weak energy consumption equipment in the whole power generation process is accurately located.Taking a gas field in southwest China as an example,the comprehensive energy consumption evaluation of the three power generation technologies is carried out,and the technology with the best energy consumption condition among the three technologies is determined.Finally,the rationalization improvement measures are put forward from improving the air tightness,replacing the deflector and reducing the flow loss.

C57black/6小鼠全脑缺血模型脑内Bax和Bcl-2的表达

本研究采用C57black/6小鼠制备全脑缺血模型,观察脑缺血后多个脑区Bax和Bcl-2基因的表达。双侧颈总动脉夹闭(bilateral common carotid artery occlusion,BCCAO)15min,造成全脑缺血,24h后取脑组织进行Bax和Bcl-2免疫组织化学染色。结果显示:Bax阳性细胞广泛分布在大脑皮层、丘脑和杏仁核,阳性产物主要位于胞质内。除丘脑外,其他各部位Bax阳性神经元的密度缺血组均显著高于假手术组(P<0.05);缺血组各区域细胞染色灰度值均显著低于假手术组(P<0.01)。Bcl-2阳性细胞在大脑皮层和丘脑均有表达,缺血组大脑皮层内Bcl-2阳性神经元的密度显著高于假手术组(P<0.05);缺血组各区域细胞染色灰度值均显著低于假手术组(P<0.01)。以上结果表明双侧颈总动脉夹闭法致C57black/6小鼠全脑缺血模型可致多脑区Bax和Bcl-2的广泛表达,提示Bax和Bcl-2可能介导了缺血所致的神经元损伤。

云南省南苜蓿和天蓝苜蓿根瘤菌BOX-PCR分析

[目的]进行南苜蓿和天蓝苜蓿根瘤菌的BOX-PCR分析,为苜蓿高效固氮根瘤菌的筛选和接种剂的研究提供理论依据。[方法]采用boxA1R单引物对90株根瘤菌供试菌株及5株标准菌株进行BOX-PCR分析,并进行聚类分析。[结果]经过扩增得到了较多的条带,90株供试菌株共有31种BOX图谱类型。聚类分析结果显示,所有菌株在40%相似性水平上聚为一群;而在69%的相似性水平上,供试菌株可细分为7个遗传群,群1的菌株全部分离自云南省江川县路居镇天蓝苜蓿的根瘤,群3内的菌株都分离自德宏州盈江县的南苜蓿根瘤,并与标准菌株Enisfer melilotiUSDA1002T聚在一群,在群4、5、6中,除SWF67340的宿主为南苜蓿外,其他菌株的宿主都为天蓝苜蓿,群7中,除SWF66320、SWF67343、SWF65116和SWF673704株菌的宿主为天蓝苜蓿外,其余菌株的宿主都为南苜蓿。[结论]供试菌株具有丰富的遗传多样性,BOX-PCR能够区分它们之间的差异;大多数菌株按宿主及采集地聚群,但也有交叉。

Box-Behnken响应面优化超声联合双酶法提取当归地上部分总黄酮及其抗氧化活性研究

试验以当归废弃物(当归地上部分)为试验材料,在单因素试验基础上,设计Box-Behnken响应面试验,优化超声联合双酶法提取当归地上部分总黄酮的最佳提取工艺,采用DPPH和ABTS自由基法和FRAP法评价当归地上部分总黄酮的抗氧化活性。结果显示,利用超声联合双酶法提取当归地上部分总黄酮的最佳条件为乙醇浓度50%、液料比50∶1、超声时间41 min、双酶(纤维素酶∶果胶酶=2∶1)用量0.68 g/L、酶解时间93 min,此条件下,当归地上部分总黄酮提取率为8.18%。当归地上部分具有较高的抗氧化活性,在浓度为150 mg/L时,对DPPH自由基清除率为90.3%,略低于VC。在浓度为3 000 mg/L时,对ABTS清除率为88.6%,ABTS的IC50为DPPH IC50近30倍,FRAP抗氧化能力为4.64 (mg VC eq/g sample)。试验表明,当归地上部分的总黄酮具有抗氧化活性。

基于Cruise/BlackBox的电动汽车制动能量回收仿真

在使用AVL-Cruise进行整车仿真过程中,需要对制动能量回收策略进行研究。基于AVL-Cruise建立仿真平台,使用Cruise/Black Box引入控制代码,设定一个制动能量回收策略并使用Cruise/Black Box实现控制策略,使用AVL-Cruise联合Cruise/Black Box接口组件对具体的工况进行仿真分析。结果表明,基于Cruise/Black Box的电动汽车制动能量回收仿真,能够完全真实地反映制动能量回收控制策略在电动汽车上的工作过程。

Y-box结合蛋白-1与肿瘤发生

Y-box结合蛋白(Y-box binding protein,YB)是一类广泛存在于多种生物中的蛋白质家族,是一类高度保守的顺式作用调控元件,也是一种广泛表达的转录因子,发挥重要的生物学功能。Y-box结合蛋白-1(Y-box binding protein-1,YB-1)是Y-box结合蛋白家族成员之一,参与基因的转录调节、翻译调控、维持mRNA的稳定性、mRNA选择性剪接、RNA的配对、DNA的修复、细胞增殖和再生等生物学功能。大量研究表明YB-1的异常表达与许多肿瘤,如:前列腺癌、乳腺癌、肺癌、宫颈癌、淋巴瘤、卵巢癌的发生发展具有相关性。对YB-1的研究为肿瘤的治疗提供了新的方向,并可能成为肿瘤诊治的一种新的标志物。

Box-Behnken设计毛细管液相色谱法拆分α-氨基酸对映体的研究

将L-脯氨酸通过3-缩水甘油丙基三甲氧基硅烷键合到球型多孔硅胶基质上,制备了手性配体交换色谱固定相。采用高压匀浆法将制备的填料填充到毛细管柱中,在自组装的毛细管液相色谱仪上对3种α-氨基酸对映体进行了拆分。利用Box-Behnken设计对影响因素(流动相中乙腈的体积分数、中心离子Cu2+的浓度、流速)进行优化,以最大保留时间和分离度为响应值,借助二次多元回归方程,建立了相应的数学模型。响应曲面图表明:DL-天冬酰胺在5%乙腈、5 mmol/L Cu2+、流速0.139μL/min,苏氨酸在10%乙腈、5mmol/L Cu2+、流速0.167μL/min,丝氨酸在5%乙腈、7 mmol/L Cu2+、流速0.167μL/min的条件下均能得到基线分离。表明通过所制备的手性固定相,采用配体交换色谱模式可获得拆分DL-氨基酸的理想效果。

DCVAE-adv:A Universal Adversarial Example Generation Method for White and Black Box Attacks

Deep neural network(DNN)has strong representation learning ability,but it is vulnerable and easy to be fooled by adversarial examples.In order to handle the vulnerability of DNN,many methods have been proposed.The general idea of existing methods is to reduce the chance of DNN models being fooled by observing some designed adversarial examples,which are generated by adding perturbations to the original images.In this paper,we propose a novel adversarial example generation method,called DCVAE-adv.Different from the existing methods,DCVAE-adv constructs adversarial examples by mixing both explicit and implicit perturbations without using original images.Furthermore,the proposed method can be applied to both white box and black box attacks.In addition,in the inference stage,the adversarial examples can be generated without loading the original images into memory,which greatly reduces the memory overhead.We compared DCVAE-adv with three most advanced adversarial attack algorithms:FGSM,AdvGAN,and AdvGAN++.The experimental results demonstrate that DCVAE-adv is superior to these state-of-the-art methods in terms of attack success rate and transfer ability for targeted attack.Our code is available at https://github.com/xzforeverlove/DCVAE-adv.

An Efficient Method to Estimate Admittance of Black-boxed Inverter-based Resources for Varying Operating Points

Traditional analytical approaches for stability assessment of inverter-based resources(IBRs),often requiring detailed knowledge of IBR internals,become impractical due to IBRs’proprietary nature.Admittance measurements,relying on electromagnetic transient simulation or laboratory settings,are not only time-intensive but also operationally inflexible,since various non-linear control loops make IBRs’admittance models operating-point dependent.Therefore,such admittance measurements must be performed repeatedly when operating point changes.To avoid time-consuming and cumbersome measurements,admittance estimation for arbitrary operating points is highly desirable.However,existing admittance estimation algorithms usually face challenges in versatility,data demands,and accuracy.Addressing this challenge,this letter presents a simple and efficient admittance estimation method for blackboxed IBRs,by utilizing a minimal set of seven operating points to solve a homogeneous linear equation system.Case studies demonstrate this proposed method ensures high accuracy across various types of IBRs.Estimation accuracy is satisfying even when non-negligible measurement errors exist.

Box-Behnken响应面设计法优化排脓散水提工艺

目的优选排脓散最佳水提工艺。方法采用Box-Behnken响应面设计法,以水提液中3个指标性成分(柚皮苷、新橙皮苷、芍药苷)的含量和出膏率的综合评价作为考察指标,考察料液比、浸泡时间、提取时间3个因素对提取工艺的影响。结果排脓散水提的最佳工艺条件为15倍水,浸泡67min,提取74min。结论 Box-Behnken实验设计法优化排脓散的水提工艺方法可行,预测性较好。