The Current Situation and Improvement of Informatization Construction in Universities in the Era of Digital Education—Taking the Nanchong Campus of Southwest Petroleum University as an Example

Digitization of education is an important component of Digital China Strategy. China is deeply implementing the digitalization of education strategy, promoting educational reform and innovation, and accelerating the construction of a learning society and a learning country where everyone can learn, learn everywhere, and learn at all times [1]. As the cradle and gathering place of talent cultivation, universities should be at the forefront of educational informatization construction. As a comprehensive energy university in the northeastern region of Sichuan, the Nanchong Campus of Southwest Petroleum University plays an irreplaceable role in the local economic development. This article summarizes the current situation of educational informatization construction on this campus and proposes suggestions for its improvement path, providing constructive reference opinions for the development of similar universities.

Adversarial attacks and defenses for digital communication signals identification

As modern communication technology advances apace,the digital communication signals identification plays an important role in cognitive radio networks,the communication monitoring and management systems.AI has become a promising solution to this problem due to its powerful modeling capability,which has become a consensus in academia and industry.However,because of the data-dependence and inexplicability of AI models and the openness of electromagnetic space,the physical layer digital communication signals identification model is threatened by adversarial attacks.Adversarial examples pose a common threat to AI models,where well-designed and slight perturbations added to input data can cause wrong results.Therefore,the security of AI models for the digital communication signals identification is the premise of its efficient and credible applications.In this paper,we first launch adversarial attacks on the end-to-end AI model for automatic modulation classifi-cation,and then we explain and present three defense mechanisms based on the adversarial principle.Next we present more detailed adversarial indicators to evaluate attack and defense behavior.Finally,a demonstration verification system is developed to show that the adversarial attack is a real threat to the digital communication signals identification model,which should be paid more attention in future research.

Multi-layer network embedding on scc-based network with motif

Interconnection of all things challenges the traditional communication methods,and Semantic Communication and Computing(SCC)will become new solutions.It is a challenging task to accurately detect,extract,and represent semantic information in the research of SCC-based networks.In previous research,researchers usually use convolution to extract the feature information of a graph and perform the corresponding task of node classification.However,the content of semantic information is quite complex.Although graph convolutional neural networks provide an effective solution for node classification tasks,due to their limitations in representing multiple relational patterns and not recognizing and analyzing higher-order local structures,the extracted feature information is subject to varying degrees of loss.Therefore,this paper extends from a single-layer topology network to a multi-layer heterogeneous topology network.The Bidirectional Encoder Representations from Transformers(BERT)training word vector is introduced to extract the semantic features in the network,and the existing graph neural network is improved by combining the higher-order local feature module of the network model representation network.A multi-layer network embedding algorithm on SCC-based networks with motifs is proposed to complete the task of end-to-end node classification.We verify the effectiveness of the algorithm on a real multi-layer heterogeneous network.

金属矿崩落法扰动范围预测新方法及应用

为量化金属矿崩落法扰动范围,提出一种基于岩石力学参数扰动范围的预测新方法。通过将岩石力学指标与随机介质理论相结合,建立扰动范围预计修正公式。基于扰动等效中心和扰动衰减球面,推导金属矿山开采扰动的二维安全判据。将该方法应用于6个矿山和尖山矿,并利用FLAC^(3D)模型对尖山矿进行数值模拟。经对比,预测值与实测值的后验差比值为0.0357,多因素交叉分析得到该方法对结果产生的相对误差仅为0.078。研究表明,该方法的预测精度高,且不会对安全性产生显著影响。

Parameter Estimation of Linear Frequency Modulated Signals Based on Holder Coefficient

The current parameter estimation algorithms of chirp rate have high complexity and long calculation time,meantime they are difficult to achieve high estimation rate. Therefore,in order to overcome these problems,in this paper,a new parameter estimation algorithm based on Holder coefficient is presented. Firstly,this algorithm calculates the correlation curve of the Holder coefficient value under different chirp rate. Secondly,this algorithm calculates the correlation curve under different SNR. Finally,the fitting curve expression can be got by the correlation curve,and then the estimation value of chirp rate can also be got. The theory analysis and simulation results show that this algorithm is simple and easy to realize,and has much better application value for real-time estimation.

Lattice plasmon mode excitation via near-field coupling

The optical response of metal nanoparticles can be modified through near-field or far-field interaction,yet the lattice plasmon modes(LPMs)considered can only be excited from the latter.Here instead,we present a theoretical evaluation for LPM excitation via the near-field coupling process.The sample is an arrayed structure with specific units composed of upper metal disks,a lower metal hole and a sandwiched dielectric post.The excitation process and underlying mechanism of the LPM and the influence of the structure parameters on the optical properties have been investigated in detail by using a finite-difference time-domain(FDTD)numerical method.Our investigation presented here should advance the understanding of near-field interaction of plasmon modes for LPM excitation,and LPMs could find some potential applications,such as in near-field optical microscopes,biosensors,optical filters and plasmonic lasers.

靶向Trop2的抗体偶联药物治疗三阴性乳腺癌的研究进展

乳腺癌是目前全球发病率最高的恶性肿瘤之一,其中三阴性乳腺癌(triple-negative breast cancer,TNBC)占浸润性乳腺癌的10%~20%。TNBC是一种高度异质性和侵袭性的恶性肿瘤,与其他乳腺癌亚型相比,TNBC治疗手段相对匮乏,预后较差,临床上亟待寻找可用于精准治疗及提高预后的新靶点。人滋养层细胞表面抗原2(trophoblast cell surface antigen 2,Trop2)在三阴性乳腺癌及多种恶性肿瘤中高表达,其通过细胞表面受体信号在肿瘤细胞的增殖、黏附、侵袭、转移中发挥重要作用,以其为靶点的抗体偶联药物(antibody-drug conjugate,ADC)在临床上中具有广阔的应用前景。本文对靶向Trop2的ADC治疗TNBC的临床研究进展予以综述,为靶向Trop2的ADC在TNBC治疗中的临床应用和提高患者生存预后方面提供参考。

某三甲医院9年间血培养分离细菌的分布及耐药谱分析

目的分析某三甲医院血培养的细菌分布以及体外药敏结果,提供临床合理使用抗菌药物的依据。方法回顾性调查云南省第二人民医院2010年1月—2018年12月,住院及门诊送检血培养标本分离培养及药物敏感试验的结果,采用WHONET5.6软件对血培养分离到细菌的分布及药敏结果进行统计分析。结果共检出细菌2163株,其中革兰阴性杆菌1379株(63.8%),革兰阳性菌710株(32.8%),真菌74株(3.4%)。在革兰阴性菌中,以大肠埃希菌为主48.1%,其次是肺炎克雷伯菌16.0%以及甲型副伤寒沙门菌11.4%;而革兰阳性菌以凝固酶阴性葡萄球菌61.0%为主,其次是金黄色葡萄球菌16.1%及屎肠球菌5.6%;真菌以白假丝酵母35.1%、近平滑假丝酵母菌20.3%及热带假丝酵母菌17.6%为主,在真菌中检出组织胞浆菌1例;检出率前3位的科室是ICU16.2%、肿瘤科15.0%及创伤中心14.4%。药敏结果显示,耐碳青酶烯酶的肺炎克雷伯菌(CRKP)检出率13.6%,耐碳青酶烯酶的大肠埃希菌(CREC)检出率0.3%,产超广谱β-内酰胺酶(ESBLs)的大肠埃希菌和肺炎克雷伯菌的检出率分别为64.9%和36.7%;耐碳青霉烯类的鲍曼不动杆菌(CRAB)73.6%,耐碳青霉烯类的铜绿假单胞菌(CRPA)47.8%,耐甲氧西林金黄色葡萄球菌(MRSA)检出率38.6%;而检出前几位的大肠埃希菌、肺炎克雷伯菌、鲍曼不动杆菌及金黄色葡萄球菌对常用的抗菌药物存在较高的耐药率,特别是产碳青霉烯酶(KPC)、产超广谱β-内酰胺酶(ESBLs)株及耐甲氧西林葡萄球菌(MRS)的耐药率较高,产酶株与非产酶株细菌的耐药率存在较大差异(P<0.01),甲型副伤寒沙门菌除对常用的抗菌药物具有较高的敏感性。结论血培养标本中主要细菌是革兰阴性杆菌,不同细菌对抗菌药物的耐药性存在较大差异,对不明原因发热或疑似血流感染的患者抗菌药物使用之前进行血培养和体外药敏试验,对临床诊治血流感染及合理选用抗菌药物具有重要意义。

双层管式微型光纤光栅传感器封装技术

为满足厦门鹭岛柔直换流站示范工程中换流阀绝缘栅双极型晶体管(IGBT)结温监测系统对光纤光栅传感器的需求,设计了双层管式微型光纤布喇格光栅(FBG)传感器。采用点胶式和灌胶与点胶结合式2种封装方法,实现了直径为1.2mm圆柱形极小尺寸封装,通过搭建实验平台对其进行温度特性标定和重复性测试。实验结果表明:封装后的光纤光栅温度特性良好,二次拟合优度均达到0.999以上,并且均具有很好的重复性;其尺寸和性能完全满足工程现场参数要求,适用于对传感器结构参数和兼容性要求较高的场合。

不同发酵方式对萝卜泡菜理化特性和风味的影响

以接种发酵泡菜、卤水泡菜和自然发酵泡菜为研究对象,探究3种发酵方式下制备的萝卜泡菜的理化特性和风味差异。发酵96 h后,3种泡菜的pH均在4.0以下;接种发酵和自然发酵泡菜总酸的质量浓度达到5 g/L,卤水泡菜总酸的质量浓度由4 g/L增加到8 g/L;接种发酵泡菜的乳酸菌总数最高(>1×10^8 CFU/mL);接种发酵泡菜在气味、滋味与总分3方面的评分均最高。通过气质联用(gas chromatography-mass spectrometry,GC-MS)分析发现,接种发酵泡菜中果糖、塔格糖和蔗糖含量高于卤水泡菜和自然发酵泡菜,卤水泡菜中丙二醇、甘油、甘露醇、乳酸和草酸等的含量均比其他2种泡菜多,氨基酸种类也更丰富;采用固相微萃取-气质联用(solid phase microextraction-GC-MS,SPME-GC-MS)分析确定了二甲基二硫醚、二甲基三硫醚、柠檬烯、β-金合欢烯、2-壬酮、2-十一烷酮、芳樟醇和桉油精8种关键的香气活性物质,这些香气活性物质在接种发酵泡菜中更丰富。

超氧化物歧化酶对高血压合并高同型半胱氨酸血症患者早期肾损害的影响

目的探讨超氧化物歧化酶(SOD)与高血压合并高同型半胱氨酸血症(HHcy)患者早期肾损害的关系。方法选取原发性高血压患者987例,根据同型半胱氨酸(Hcy)水平将其分为普通高血压组(659例,Hcy<15μmol/L)和高血压合并HHcy组(328例,Hcy≥15μmol/L);再根据尿微量白蛋白/肌酐比值(UACR)将987例患者分为高血压不伴肾损害组(750例,UACR<30 mg/g)和高血压合并早期肾损害组(237例,30 mg/g≤UACR<300 mg/g)。根据UACR将高血压合并HHcy组328例患者分为肾损害组(106例)和无肾损害组(222例)。收集所有患者的临床资料并按以上分组进行比较。采用Spearman或Pearson相关分析探讨高血压患者UACR与Hcy、SOD的相关性。采用二元logistic回归分析探讨高血压早期肾损害的影响因素。结果高血压合并HHcy组年龄、高血压病程、吸烟及饮酒患者比例、Hcy、尿酸(UA)、血肌酐(SCr)、血尿素氮(BUN)、UACR、胱抑素C(CysC)、尿α1微球白蛋白水平均高于普通高血压组,而SOD、总胆固醇(TC)、高密度脂蛋白胆固醇(HDL-C)、估算的肾小球滤过率(eGFR)均低于普通高血压组(P<0.05)。高血压合并早期肾损害组年龄、糖尿病病史患者比例、高血压病程、心率、Hcy、空腹血糖(FPG)、糖化血红蛋白、SCr、BUN、CysC、UACR、尿α1微球白蛋白水平均高于高血压不伴肾损害组,而饮酒患者比例、舒张压、SOD、HDL-C、eGFR均低于高血压不伴肾损害组(P<0.05)。在高血压合并HHcy患者中,肾损害组SOD水平明显低于无肾损害组(P<0.001)。Spearman相关分析结果显示,UACR与SOD呈负相关,与Hcy呈正相关(P<0.001)。Pearson相关分析显示,Hcy与SOD呈负相关(P<0.001)。二元logistic回归分析结果显示,年龄、Hcy、收缩压、糖尿病病史、FPG为高血压早期肾损害的独立危险因素,而Hcy×SOD、HDL-C为独立保护因素(P<0.05)。结论SOD可能降低Hcy给高血压合并HHcy患者带来的肾损害,为后续研究SOD保护作用提供依据。

Semi-Supervised Learning with Generative Adversarial Networks on Digital Signal Modulation Classification

Deep Learning(DL)is such a powerful tool that we have seen tremendous success in areas such as Computer Vision,Speech Recognition,and Natural Language Processing.Since Automated Modulation Classification(AMC)is an important part in Cognitive Radio Networks,we try to explore its potential in solving signal modulation recognition problem.It cannot be overlooked that DL model is a complex model,thus making them prone to over-fitting.DL model requires many training data to combat with over-fitting,but adding high quality labels to training data manually is not always cheap and accessible,especially in real-time system,which may counter unprecedented data in dataset.Semi-supervised Learning is a way to exploit unlabeled data effectively to reduce over-fitting in DL.In this paper,we extend Generative Adversarial Networks(GANs)to the semi-supervised learning will show it is a method can be used to create a more dataefficient classifier.

Potential model for differential diagnosis between Crohn's disease and primary intestinal lymphoma

AIM To evaluate the usefulness of different parameters to differentiate Crohn's disease(CD) from primary intestinal lymphoma(PIL).METHODS The medical records of 85 patients with CD and 56 patients with PIL were reviewed retrospectively. Demographic, clinical, laboratory, endoscopic, and computed tomographic enterography(CTE) parameters were collected. The univariate value of each parameter was analyzed. A differentiation model was established by pooling all the valuable parameters. Diagnostic efficacy was analyzed, and a receiver operating characteristic(ROC) curve was plotted.RESULTS The demographic and clinical parameters that showed significant values for differentiating CD from PIL included age of onset, symptom duration, presence of diarrhea, abdominal mass, and perianal lesions(P < 0.05). Elevated lactate dehydrogenase and serum β2-microglobulin levels suggested a PIL diagnosis(P < 0.05). The endoscopic parameters that showed significant values for differentiating CD from PIL included multiple-site lesions, longitudinal ulcer, irregular ulcer,and intraluminal proliferative mass(P < 0.05). The CTE parameters that were useful in the identification of the two conditions included involvement of ≤ 3 segments, circular thickening of the bowel wall, wall thickness > 8 mm, aneurysmal dilation, stricture with proximal dilation, "comb sign", mass showing the "sandwich sign", and intussusceptions(P < 0.05). The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the differentiation model were 91.8%, 96.4%, 93.6%, 97.5%, and 88.5%, respectively. The cutoff value was 0.5. The area under the ROC curve was 0.989.CONCLUSION The differentiation model that integrated the various parameters together may yield a high diagnostic efficacy in the differential diagnosis between CD and PIL.

Poly(ADP-ribosyl)ation of Apoptosis Antagonizing Transcription Factor Involved in Hydroquinone-Induced DNA Damage Response

The molecular mechanism of DNA damage induced by hydroquinone （HQ） remains unclear. Poly（ADP-ribose） polymerase-1 （PARP-1） usually works as a DNA damage sensor, and hence, it is possible that PARP-1 is involved in the DNA damage response induced by HQ. In TK6 cells treated with HQ, PARP activity as well as the expression of apoptosis antagonizing transcription factor （AATF）, PARP-1, and phosphorylated H2AX （v-H2AX） were maximum at 0.5 h, 6 h, 3 h, and 3 h, respectively. To explore the detailed mechanisms underlying the prompt DNA repair reaction, the above indicators were investigated in PARP-l-silenced cells. PARP activity and expression of AATF and PARP-1 decreased to 36%, 32%, and 33%, respectively, in the cells; however, y-H2AX expression increased to 265%. Co-immunoprecipitation （co-IP） assays were employed to determine whether PARP-1 and AATF formed protein complexes. The interaction between these proteins together with the results from IP assays and confocal microscopy indicated that poly（ADP-ribosyl）ation {PARylation） regulated AATF expression, in conclusion, PARP-1 was involved in the DNA damage repair induced by HQ via increasing the accumulation of AATF through PARylation.

New Individual Identification Method of Radiation Source Signal Based on Entropy Feature and SVM

In this paper,according to the defect of methods which have low identification rate in low SNR,a new individual identification method of radiation source based on information entropy feature and SVM is presented. Firstly,based on the theory of multi-resolution wavelet analysis,the wavelet power spectrum of noncooperative signal can be gotten. Secondly,according to the information entropy theory,the wavelet power spectrum entropy is defined in this paper. Therefore,the database of signal's wavelet power spectrum entropy can be built in different SNR and signal parameters. Finally,the sorting and identification model based on SVM is built for the individual identification of radiation source signal. The simulation result indicates that this method has a high individual's identification rate in low SNR,when the SNR is greater than 4 dB,the identification rate can reach 100%. Under unstable SNR conditions,when the range of SNR is between 0 dB and 24 dB,the average identification rate is more than 92. 67%. Therefore,this method has a great application value in the complex electromagnetic environment.

Weighted Sparse Image Classification Based on Low Rank Representation

The conventional sparse representation-based image classification usually codes the samples independently,which will ignore the correlation information existed in the data.Hence,if we can explore the correlation information hidden in the data,the classification result will be improved significantly.To this end,in this paper,a novel weighted supervised spare coding method is proposed to address the image classification problem.The proposed method firstly explores the structural information sufficiently hidden in the data based on the low rank representation.And then,it introduced the extracted structural information to a novel weighted sparse representation model to code the samples in a supervised way.Experimental results show that the proposed method is superiority to many conventional image classification methods.

A Kind of Edge Detection Algorithm with Edge-Preserving Characteristics

Traditional Sobel algorithm is deeply influenced by Gaussian noise,therefore,before boundary extraction,mean filter should be done. But the filtering process is always over-smooth images'details of certain directions,so that images'edges will not be extracted correctly. Aiming at this problem,this paper puts forward a detection algorithm based on edge-preserving characteristics,by matching edge mould of different directions to definite edge preserving directions. Instead of the mean filter process,this algorithm improves the performance of traditional algorithms,and provides the simulation results. The experiment results prove that this algorithm preserves more images'edge information when canceling noise.

基于DVS的振动源与传感通道垂直距离的计算方法

振动源与传感通道的垂直距离是光缆、电缆等线路运维人员关注的重要指标之一,对如何进行线路安全处置具有重要指导意义,提出一种基于分布式振动系统(DVS)的振动源与传感通道垂直距离的计算方法。通过实时采集光缆信号数据,分析了振动波的衰减特点,选择了合适的振动波振幅谱计算模型,并给出了振幅谱与振动源间隔距离的分布方程,以及垂直距离的近似计算方法。实验证明:该算法计算出的垂直距离误差较小,符合工程设计要求,具有较高的实际应用价值。

Air Temperature Estimation with MODIS Data over the Northern Tibetan Plateau

Time series of MODIS land surface temperature(Ts) and normalized difference vegetation index(NDVI) products,combined with digital elevation model(DEM) and meteorological data from 2001 to 2012,were used to map the spatial distribution of monthly mean air temperature over the Northern Tibetan Plateau(NTP). A time series analysis and a regression analysis of monthly mean land surface temperature(Ts) and air temperature(Ta) were conducted using ordinary linear regression(OLR) and geographical weighted regression(GWR). The analyses showed that GWR,which considers MODIS Ts,NDVI and elevation as independent variables,yielded much better results [RAdj2> 0.79; root-mean-square error(RMSE) =0.51℃–1.12℃] associated with estimating Tacompared to those from OLR(RAdj2= 0.40-0.78; RMSE = 1.60℃–4.38℃).In addition,some characteristics of the spatial distribution of monthly Taand the difference between the surface and air temperature(Td) are as follows. According to the analysis of the 0℃ and 10℃ isothermals,Tavalues over the NTP at elevations of 4000–5000 m were greater than 10℃ in the summer(from May to October),and Tavalues at an elevation of3200 m dropped below 0℃ in the winter(from November to April). Taexhibited an increasing trend from northwest to southeast. Except in the southeastern area of the NTP,T d values in other areas were all larger than 0℃ in the winter.

Research of Velocity Compensation Method Based on Range Profile Feature

In this paper,based on the feature of high resolution one-dimensional range profile,two effective motion compensation methods are presented. Firstly,the processing method of stepped-frequency and the response of target moving to range profile are analyzed. Secondly,the function of range profile entropy and range profile contrast are presented for velocity compensation,and then the theory analysis,math model,and solution method are analyzed in detail. Finally,several simulation experiments are designed to prove the accuracy and effectiveness of these two methods. From the final theory analysis and simulation experiments,the conclusion can be drawn that these two methods are effective,which can get much higher velocity estimation accuracy,well real-time and easy to be used in project application. After motion compens-ation,the high resolution one-dimensional range profile will be much better than that used to be,and is used for the detection, recognition and ranging of moving targets.