On the Verbal and Non-Verbal Features in Chinese-English Interpretation

This paper investigates the verbal and non - verbal features of interpretation from Chinese into English . On the one hand the language of interpretation belongs to the category of oral language, So It determines the path an interpreter should follow while interpreting . On the other hand it is suggested that the non - verbal approach plays an important role in interpretation. Therefore an interpreter can not be a qualified interpreter unless he is, in addition to language techniques, skilled in the application of paralanguage.

Relevance of EGFR gene mutation with pathological features and prognosis in patients with non-small-cell lung carcinoma

Objective:To study the relevance of EGFR gene mutation with pathological features and prognosis in patients with non-small-cell lung carcinoma.Methods:A total of 297 patients from July 2009 to May 2013 were chosen as objects.EGFR gene mutation were detected with fluorescence quantitative PCR.Relevance of EGFR gene mutation with clinical and pathological features was analyzed,and the prognosis of EGFR- mutant-patients and that of EGFR- wide type-patients was compared.Results:In 297 patients.136(45.79%) showed EGFR gene mutation.EGFR gene mutation had no significant relevance with age.gender,smoking history,family history of cancer and clinical stage(P>0.05);there was significant relevance between EGFR gene mutation and blood type,pathologic types,differentiation and diameter of cancer(P<0.05).The difference between prognosis of EGFR- mutant-patients and that of EGFR- wide type-patients was statistical significance(P<0.05).Conclusions:EGFR gene mutation has significant relevance with pathological features,the prognosis of EGFRmutant-paticnts is better than that of EGFR- wide type-patients.

Gender Equality:Now a Basic State Strategy——On the Salient Features of the National Program on the Development of Chinese Women(2011-2020)

The National Program on the Development of Chinese Women （2011-2020）, herein- after referred to as the ＂NewProgram,＂ was published in August 2011. This is an important document designed to ensure implementation of the basic state strategy of gender equal- ity and the all-round development of Chinese women. The New Program is a part of China＇s policy program for the protection of human rights. It sets 57 major targets to be attained over the decade. The targets cover seven fields, namely, health, education, economy,

A Comparison of Clinical Features of Depressed and Non-Depressed People Living with HIV/AIDS, in Nigeria, West Africa

Objectives: Depressive disorders are a significant public health issue. They are prevalent, disabling, and often chronic, with a high economic burden to the society. Depressive illness is the most common psychiatric disorder in HIV/AIDS with prevalence 2 to 4 times higher than the general population. It’s still questionable whether HIV related depression is clinically different from sero-positive patients without depression. Studies comparing the clinical features of depressed and non-depressed People Living with HIV/AIDs are limited, hence the need for this study. Methods: This was a hospital based, cross sectional, descriptive study of three hundred adult HIV/AIDS patients attending the HIV clinic of Kwara State specialist hospital, Sobi, Ilorin. The PHQ-9 was administered to the respondents to screen for depression. A pre-tested PHQ-9 questionnaire was used to collect data. Subject who scored one and more were assessed clinically for depression. The three keys of social determinants of depression (SDS) were assessed and the association with depression sought. Results: One hundred and seventy (56.7%) satisfied the criteria for a depressive disorder using the PHQ-9 score. Compared to non-depressed sero-positive patients, depressed HIV patients were more likely to be female, single, unemployed, with below average year of schooling, low social economic status, low social cohesion and more stressful life events. They are more prone to hopelessness, thought of taking life and plan to commit suicide. Conclusion: These findings, show that the clinical and associated features of depression differ between depressed and non-depressed sero-positive subjects, thus requiring different management.

Influence of Non-Natural Ageing Temperature on the Microstructural Characteristics and Mechanical Properties of Cast Aluminum 6063 Alloy

This research considered the effect of non-natural aging on the microstructural characteristics and mechanical properties of as-cast aluminum 6063 alloys. The samples were developed through a sand casting process and machined into tensile and impact test samples before carrying out solution heat treatment at 550?C (0.83 Tm) on two parts of the samples while retaining one part as the control. The two parts were further divided into sets denoted A and B and were aged at 180?C (0.27 Tm) and 160?C (0.24 Tm), respectively, for 12 hours. The results showed that sample A has the optimal yield strength and ultimate tensile strength of 192 and 206 MPa, respectively. Likewise, the sample gave the highest impact strength value of about 9.63 J/mm2. The observed results were supported by the optical micrograph, which revealed that the sample has evenly dispersed precipitates in its microstructure. This is deemed responsible for the observed increase in strength of the sample.

Feature Extraction and Recognition for Rolling Element Bearing Fault Utilizing Short-Time Fourier Transform and Non-negative Matrix Factorization

Due to the non-stationary characteristics of vibration signals acquired from rolling element bearing fault, thc time-frequency analysis is often applied to describe the local information of these unstable signals smartly. However, it is difficult to classitythe high dimensional feature matrix directly because of too large dimensions for many classifiers. This paper combines the concepts of time-frequency distribution（TFD） with non-negative matrix factorization（NMF）, and proposes a novel TFD matrix factorization method to enhance representation and identification of bearing fault. Throughout this method, the TFD of a vibration signal is firstly accomplished to describe the localized faults with short-time Fourier transform（STFT）. Then, the supervised NMF mapping is adopted to extract the fault features from TFD. Meanwhile, the fault samples can be clustered and recognized automatically by using the clustering property of NMF. The proposed method takes advantages of the NMF in the parts-based representation and the adaptive clustering. The localized fault features of interest can be extracted as well. To evaluate the performance of the proposed method, the 9 kinds of the bearing fault on a test bench is performed. The proposed method can effectively identify the fault severity and different fault types. Moreover, in comparison with the artificial neural network（ANN）, NMF yields 99.3% mean accuracy which is much superior to ANN. This research presents a simple and practical resolution for the fault diagnosis problem of rolling element bearing in high dimensional feature space.

Breast non-mass-like lesions on contrast-enhanced ultrasonography: Feature analysis, breast image reporting and data system classification assessment

BACKGROUND Breast non-mass-like lesions(NMLs)account for 9.2%of all breast lesions.The specificity of the ultrasound diagnosis of NMLs is low,and it cannot be objectively classified according to the 5th Edition of the Breast Imaging Reporting and Data System(BI-RADS).Contrast-enhanced ultrasound(CEUS)can help to differentiate and classify breast lesions but there are few studies on NMLs alone.AIM To analyze the features of benign and malignant breast NMLs in grayscale ultrasonography(US),color Doppler flow imaging(CDFI)and CEUS,and to explore the efficacy of the combined diagnosis of NMLs and the effect of CEUS on the BI-RADS classification of NMLs.METHODS A total of 51 breast NMLs verified by pathology were analyzed in our hospital from January 2017 to April 2019.All lesions were examined by US,CDFI and CEUS,and their features from those examinations were analyzed.With pathology as the gold standard,binary logic regression was used to analyze the independent risk factors for malignant breast NMLs,and a regression equation was established to calculate the efficiency of combined diagnosis.Based on the regression equation,the combined diagnostic efficiency of US combined with CEUS(US+CEUS)was determined.The initial BI-RADS-US classification of NMLs was adjusted according to the independent risk factors identified by CEUS,and the diagnostic efficiency of CEUS combined with BI-RADS(CEUS+BI-RADS)was calculated based on the results.ROC curves were drawn to compare the diagnostic values of the three methods,including US,US+CEUS,and CEUS+BI-RADS,for benign and malignant NMLs.RESULTS Microcalcification,enhancement time,enhancement intensity,lesion scope,and peripheral blood vessels were significantly different between benign and malignant NMLs.Among these features,microcalcification,higher enhancement,and lesion scope were identified as independent risk factors for malignant breast NMLs.When US,US+CEUS,and CEUS+BI-RADS were used to identify the benign and malignant breast NMLs,their sensitivity rates were 82.6%,91.3%,and 87.0%,respectively;their specificity rates were 71.4%,89.2%,and 92.9%,respectively;their positive predictive values were 70.4%,87.5%,and 90.9%,respectively;their negative predictive values were 83.3%,92.6%,and 89.7%,respectively;their accuracy rates were 76.5%,90.2%,and 90.2%,respectively;and their corresponding areas under ROC curves were 0.752,0.877 and 0.903,respectively.Z tests showed that the area under the ROC curve of US was statistically smaller than that of US+CEUS and CEUS+BI-RADS,and there was no statistical difference between US+CEUS and CEUS+BI-RADS.CONCLUSION US combined with CEUS can improve diagnostic efficiency for NMLs.The adjustment of the BI-RADS classification according to the features of contrastenhanced US of NMLs enables the diagnostic results to be simple and intuitive,facilitates the management of NMLs,and effectively reduces the incidence of unnecessary biopsy.

Non-Intrusive Load Identification Model Based on 3D Spatial Feature and Convolutional Neural Network

Load identification method is one of the major technical difficulties of non-intrusive composite monitoring. Binary V-I trajectory image can reflect the original V-I trajectory characteristics to a large extent, so it is widely used in load identification. However, using single binary V-I trajectory feature for load identification has certain limitations. In order to improve the accuracy of load identification, the power feature is added on the basis of the binary V-I trajectory feature in this paper. We change the initial binary V-I trajectory into a new 3D feature by mapping the power feature to the third dimension. In order to reduce the impact of imbalance samples on load identification, the SVM SMOTE algorithm is used to balance the samples. Based on the deep learning method, the convolutional neural network model is used to extract the newly produced 3D feature to achieve load identification in this paper. The results indicate the new 3D feature has better observability and the proposed model has higher identification performance compared with other classification models on the public data set PLAID.

Multi-Feature Fusion Based Relative Pose Adaptive Estimation for On-Orbit Servicing of Non-Cooperative Spacecraft

On-orbit servicing, such as spacecraft maintenance, on-orbit assembly, refueling, and de-orbiting, can reduce the cost of space missions, improve the performance of spacecraft, and extend its life span. The relative state between the servicing and target spacecraft is vital for on-orbit servicing missions, especially the final approaching stage. The major challenge of this stage is that the observed features of the target are incomplete or are constantly changing due to the short distance and limited Field of View (FOV) of camera. Different from cooperative spacecraft, non-cooperative target does not have artificial feature markers. Therefore, contour features, including triangle supports of solar array, docking ring, and corner points of the spacecraft body, are used as the measuring features. To overcome the drawback of FOV limitation and imaging ambiguity of the camera, a "selfie stick" structure and a self-calibration strategy were implemented, ensuring that part of the contour features could be observed precisely when the two spacecraft approached each other. The observed features were constantly changing as the relative distance shortened. It was difficult to build a unified measurement model for different types of features, including points, line segments, and circle. Therefore, dual quaternion was implemented to model the relative dynamics and measuring features. With the consideration of state uncertainty of the target, a fuzzy adaptive strong tracking filter( FASTF) combining fuzzy logic adaptive controller (FLAC) with strong tracking filter(STF) was designed to robustly estimate the relative states between the servicing spacecraft and the target. Finally, the effectiveness of the strategy was verified by mathematical simulation. The achievement of this research provides a theoretical and technical foundation for future on-orbit servicing missions.

论NFT数字作品的权属特点与规则适用

NFT是一种技术,它通过对数字客体进行标识、登记和固定,使其具有可支配性和特定性。数字作品经过NFT处理后,其“物”的特性得到了强化,从而在一定程度上超出了债权客体的范畴,更接近于物权客体的特征。虽然NFT数字作品的铸造和交易应该适用物权规则,但在占有和处分这些作品的过程中,其登记性和非同质性特点却十分鲜明。因此,传统物权规则在应用于该种新型物时需要进行内部调整,同时还需要与外部规则相适配。NFT与区块链登记公示的高度绑定有别于传统的动产物权登记和著作权自愿登记,它应该比照不动产而非动产物权登记机制进行规范,并明确该登记行为在著作权规则中的地位。NFT通过独特识别符形成的非同质性,与同质化代币相比存在巨大差异,因此在适用货币化、证券化规则时应该更加谨慎。

基于特征注意力提纯的显著性目标检测模型

近年来,显著性目标检测技术取得了巨大进展,其中如何选择并有效集成多尺度特征扮演了重要角色。针对现有特征集成方法可能导致的信息冗余问题,提出了一种基于特征注意力提纯的显著性检测模型。首先,在解码器中采用一个全局特征注意力引导模块(GAGM)对带有语义信息的深层特征进行注意力机制处理,得到全局上下文信息;然后,通过全局引导流将其送入解码器各层进行监督训练;最后,利用多尺度特征融合模块(FAM)对编码器提取出的多尺度特征与全局上下文信息进行有效集成,并在网格状特征提纯模块(MFPM)中进行进一步细化,以生成清晰、完整的显著图。在5个公开数据集上进行实验,结果表明,所提模型优于现有的其他显著性检测方法,并且处理速度快,当处理320×320尺寸的图像时,能以30帧以上的速度运行。

改进YOLOv5的无人机航拍图像目标检测算法

针对无人机航拍图像目标检测中目标尺度多样、相似目标众多、目标聚集导致的目标漏检、误检问题,提出了改进YOLOv5的无人机航拍图像目标检测算法DA-YOLO。提出由特征图注意力生成器和动态权重学习模块组成的多尺度动态特征加权融合网络,特征图注意力生成器融合处理不同尺度目标更重要的特征,权重学习模块自适应地调节对不同尺度目标特征的学习,该网络可增强在目标尺度多样下的辨识度从而降低目标漏检。设计一种并行选择性注意力机制(PSAM)添加到特征提取网络中,该模块通过动态融合空间信息和通道信息,加强特征的表达获得更优质的特征图,提高网络对相似目标的区分能力以减少误检。使用Soft-NMS代替YOLOv5中采用的非极大值抑制(NMS)以改善目标聚集场景下的漏检、误检。实验结果表明,改进算法在VisDrone数据集上检测精度达到37.79%,相比于YOLOv5s算法精度提高了5.59个百分点,改进后的算法可以更好地应用于无人机航拍图像目标检测中。

基于TCGA数据库分析结直肠癌中LOC676462表达及临床意义

目的探讨结直肠癌中lncRNA LOC676462表达及其与临床病理特征、预后的相关性。方法在癌症基因图谱(TCGA)数据库网站中下载结直肠癌RNA转录组数据及临床数据,进行LOC676462表达差异分析及生存分析。采用TIMER 2.0对LOC676462进行泛癌表达水平分析。收集首都医科大学附属北京友谊医院经手术治疗的100例结直肠癌肿瘤组织及癌旁组织标本,采用实时荧光定量PCR(qPCR)检测LOC676462表达量,分析LOC676462表达与结直肠癌者临床病理特征的关系。受试者特征工作曲线(ROC)分析LOC676462表达诊断结直肠癌的效能。Kaplan-meier法绘制总生存(OS)曲线。采用多因素Cox风险比例回归模型分析影响结直肠癌OS的因素。结果生物信息学分析结果显示,LOC676462在结直肠癌组织中高表达。100例结直肠癌组织中LOC676462表达量为3.421±2.250,高于癌旁组织的1±0.694,差异有统计学意义(P<0.05)。LOC676462表达与TNM分期、浸润深度及淋巴结转移有关(P<0.05)。ROC曲线分析表明,LOC676462表达诊断结直肠癌的曲线下面积为0.918(95%CI:0.882~0.955)。Kaplan-Meier结果显示,LOC676462高表达患者的5年总生存率为38%,低表达患者5年总生存率为65.9%,差异有统计学意义(P<0.05)。多因素Cox风险比例回归模型分析结果显示,TNM分期、浸润深度、肿瘤分化程度以及LOC676462表达是影响结直肠癌OS的独立因素(P<0.05)。结论长链非编码RNA LOC676462可作为促癌基因参与在结直肠癌的发生与发展,并且其可能是结直肠癌潜在的生物标志物,可作为预测结直肠癌患者生存预后的指标。

基于最佳特征子集的自适应非视距身份识别系统

身份识别一直是安防领域的研究重点,其在非视距场景下的研究存在较大意义。针对识别的舒适度和隐私性问题,提出基于最佳特征子集的自适应非视距身份识别系统。通过有效结合多种预处理手段获取Wi-Fi信号的低维有用数据;提出鲁棒性人员检测方法截取有效片段;设计有监督特征提取方法,使用“前向搜索”获取最佳特征子集;改进传统Adaboost算法实现群体变化下的自适应识别。实验评估表明,当系统中志愿者为2~12人时,与相关系统和传统分类算法相比,均具有较好的性能。

地震事件分类识别软件

非天然地震事件分类是地震监测业务部门的日常工作之一。本研究主要针对地震、爆炸和矿震的分类问题,在地震波数据处理、特征提取和人工智能综合分类的研究基础上,基于Qt开发框架,结合Python、 Matlab等多种编程语言,开发了一个具有良好的可移植性和可扩展性、具有自主知识产权的地震分类识别软件。该软件可以部署在不同操作系统上,由七个模块组成:地震数据导入模块、数据处理模块、特征提取模块、综合分类模块、特征分析模块、当量估算模块和结果分析模块。软件集成了多种时频特征提取技术和人工智能分类方法,形成了较为完整的地震类型判定流程。软件内置的地震事件分类模型准确率高于90%,适用范围较广,已推广应用于多个地震监测部门,并取得了较好的应用成果,提高了对非天然地震的快速分析能力。

基于形体特征层次分析的概念设计原型评价与演化方法

为对概念设计原型进行定量评价,实现具有形位公差需求的机械零件成形时间与制造质量之间的均衡,提出一种基于形体特征层次分析(Shape Feature Hierarchical Analysis,SFHA)的概念设计原型评价与演化方法。针对概念设计形体的孔和轴的形态特性,采用最大内切圆柱和最小外接圆柱构建特征模型,计算由分层策略所导致偏移的实际轴线位置,推算圆柱度误差大小。进行基于形位公差的自适应分层,在保证圆柱度等公差满足设计需求的情况下尽可能减少所需层数。通过改进粒子群算法进行非凸优化求解,遴选出最优的分层序列。计算特征层次化模型向正平面V(XOZ)和侧平面W(YOZ)的平行正投影面积及绝对梯度变化,实现基于SFHA的概念设计原型特征定量化描述与动态演化。以典型支座零件为例进行验证,采用熔融沉积成形设备进行物理试验,基于高精度结构光三维扫描仪获取原型零件的圆柱度误差,相较于均匀分层方法,所提出的SFHA方法制造时间可减少26.97%。

基于轻量化多尺度下采样网络的红外图像非均匀性校正算法

红外成像系统常由于探测单元的非均匀性导致成像结果出现条纹噪声。基于深度学习的红外图像非均匀校正算法为取得较好的校正结果,通常采用复杂度高的网络结构,导致计算量庞大。本文提出了一种轻量化网络的红外图像非均匀校正算法,并针对Unet网络的编码过程设计了一种轻量化多尺度下采样模块(Lightweight Multi-scale Downsampling Module,LMDM)。LMDM通过像素拆分和通道重构实现特征图下采样,利用多个串联的深度可分离卷积(Depth-wise Separable Convolution,DSC)实现多尺度特征提取。此外,该算法引入轻量化通道注意力机制用于调整特征权重,实现更好的上下文信息融合。实验结果表明,与对比算法相比,本文提出的算法在保证校正图像纹理清晰、细节丰富和边缘锐利的前提下,内存占用降低70%以上,红外图像处理速度提升24%以上。

非刚体运动特征提取在武术运动中的应用

受光照与环境因素的影响,非刚体运动中的图像会存在视差干扰,导致非刚体运动特征提取效果不佳,因此提出一种针对非刚体运动的特征提取方法。对非刚体运动图像进行高斯滤波处理,在高斯差分尺度空间内,采用特征描述算子提取初始特征点。根据特征点提取结果,计算非刚体运动特征提取的代价。引入引导滤波方法对非刚体运动图像进行视差效果优化处理,在最小视差约束下,根据置信度聚合与传播策略进行非刚体运动的特征精确提取。以武术运动作为实验对象,实验结果表明:所提方法的特征点提取精度较高,且视差提取误差率不超过2.0%。

NM23基因与非小细胞肺癌临床病理学特征及^(18)F-FDG PET/CT影像特征的相关性

目的 比较非小细胞肺癌中NM23基因表达情况不同在其临床病理学特征、^(18)F-FDG PET/CT影像特征、生存时间的差异。方法 选择2018年1月~2022年12月于新疆医科大学附属医院病理确诊为非小细胞癌的107例患者的术后标本,运用免疫组化方法检测NM23表达情况,分为NM23低表达组(≤++)(n=64)与NM23高表达组(>++)(n=43),比较两组的临床病理学特征、^(18)FFDG FDG PET/CT图像上影像特征、生存期方面的差异。结果 NM23低表达组与高表达组在性别、临床分期、组织类型、分化程度、吸烟、PET/CT图像上生长部位、生存时间的差异无统计学意义(P>0.05),但在原发灶分期、PET/CT图像上淋巴结转移情况的差异有统计学意义(P<0.05)。结论 NM23基因在非小细胞癌患者T分期、淋巴结转移方面支持其为抑癌基因。

基于先验特征聚类的目标检测优化方法

针对显著目标检测问题在没有任何先验信息的情况下,通过特征聚类和紧致性先验方案实现目标检测优化。优化后的方法包括四个步骤:首先采用超像素预处理将图像分割成超像素,以抑制噪声并降低计算复杂度;其次应用改进的虾群聚类算法对颜色特征进行分类;接着利用二维熵来衡量每个簇的紧密度,并构建背景模型;最后以背景区域与其他区域之间的对比度作为显著特征,并通过设计高斯滤波器增强其显著性。为了更好地评价显著目标检测的精度,本文通过多维评价指标进行优劣性实验分析,实验结果表明,文中算法具有较好的实时性与鲁棒性。