As Could We Assure Safety in Large-Scale Manufacturing of Nanoparticles for the Biomedical Use

Nanoparticles provide great advantages but also great risks. Risks associating with nanoparticles are the problem of all technologies, but they increase in many times in nanotechnologies. Adequate methods of outgoing production inspection are necessary to solve the problem of risks, and the inspection must be based on the safety standard. Existing safety standard results from a principle of “maximum permissible concentrations or MPC”. This principle is not applicable to nanoparticles, but a safety standard reflecting risks inherent in nanoparticles doesn’t exist. Essence of the risks is illustrated by the example from pharmacology, since its safety assurance is conceptually based on MPC and it has already come against this problem. Possible formula of safety standard for nanoparticles is reflected in many publications, but conventional inspection methods cannot provide its realization, and this gap is an obstacle to assumption of similar formulas. Therefore the development of nanoparticle industry as a whole (also development of the pharmacology in particular) is impossible without the creation of an adequate inspection method. There are suggested new inspection methods founded on the new physical principle and satisfying to the adequate safety standard for nanoparticles. These methods demonstrate that creation of the adequate safety standard and the outgoing production inspection in a large-scale manufacturing of nanoparticles are the solvable problems. However there is a great distance between the physical principle and its hardware realization, and a transition from the principle to the hardware demands great intellectual and material costs. Therefore it is desirable to call attention of the public at large to the necessity of urgent expansions of investigations associated with outgoing inspections in nanoparticles technologies. It is necessary also to attract attention, first, of representatives of state structures controlling approvals of the adequate safety standard to this problem, since it is impossible to compel producers providing the safety without the similar standard, and, second, of leaders of pharmacological industry, since their industry already entered into the nanotechnology era, and they have taken an interest in a forthcoming development of inspection methods.

Scale, Complexity, and Cybersecurity Risk Management

Elementary information theory is used to model cybersecurity complexity, where the model assumes that security risk management is a binomial stochastic process. Complexity is shown to increase exponentially with the number of vulnerabilities in combination with security risk management entropy. However, vulnerabilities can be either local or non-local, where the former is confined to networked elements and the latter results from interactions between elements. Furthermore, interactions involve multiple methods of communication, where each method can contain vulnerabilities specific to that method. Importantly, the number of possible interactions scales quadratically with the number of elements in standard network topologies. Minimizing these interactions can significantly reduce the number of vulnerabilities and the accompanying complexity. Two network configurations that yield sub-quadratic and linear scaling relations are presented.

Upsilon Constants and Their Usefulness in Planck Scale Quantum Cosmology

This paper introduces the two Upsilon constants to the reader. Their usefulness is described with respect to acting as coupling constants between the CMB temperature and the Hubble constant. In addition, this paper summarizes the current state of quantum cosmology with respect to the Flat Space Cosmology (FSC) model. Although the FSC quantum cosmology formulae were published in 2018, they are only rearrangements and substitutions of the other assumptions into the original FSC Hubble temperature formula. In a real sense, this temperature formula was the first quantum cosmology formula developed since Hawking’s black hole temperature formula. A recent development in the last month proves that the FSC Hubble temperature formula can be derived from the Stephan-Boltzmann law. Thus, this Hubble temperature formula effectively unites some quantum developments with the general relativity model inherent in FSC. More progress towards unification in the near-future is expected.

Likert Scale计分系统在磁共振成像预测胎盘植入深度中的应用价值

目的:评价LikertScale计分系统在磁共振成像(MRI)预测胎盘植入深度中的应用价值。方法:选取150例经产前MRI检查的前置胎盘孕妇,其中非胎盘植入63例,粘连性胎盘植入46例,植入性胎盘植入27例,穿透性胎盘植入14例,所有患者均经临床手术及病理证实。采用LikertScale计分系统对胎盘植入7个MRI征象进行评分,再累加得出总评分,由两名具有高级职称放射科医师盲法阅片。采用组内相关系数、方差分析以及最小显著性差异法进行统计学分析,并绘制受试者工作曲线,计算不同类型评分的界值。结果:两名阅片医师在非胎盘植入、粘连性胎盘植入、植入性胎盘植入及穿透性胎盘植入评分方面一致性均表现较好,组内相关系数(ICC)≥0.60,可以取两名阅片医师评分均值进行分析。穿透性胎盘植入总评分为(31.46±2.29)分,高于植入性胎盘植入总评分(27.27±1.66)分,植入性胎盘植入的总评分高于粘连性胎盘植入的总评分(22.03±2.45)分,粘连性胎盘植入的总评分高于非胎盘植入总评分(15.98±3.06)分,差异均有统计学意义(Z=205.253,P<0.05)。受试者工作曲线显示,非胎盘植入与粘连性胎盘植入之间、粘连性胎盘植入与植入性胎盘植入之间以及植入性胎盘植入与穿透性胎盘植入之间评分界值分别为20分、25分和30分。结论:Likert Scale计分系统可以预测胎盘植入深度,为MRI诊断胎盘植入深度建立了一种量化模式,从而帮助临床医师制定合理的治疗方案。

3-D Modelling of the Confederation Bridge Using Data of Full Scale Tests

Long-span bridges are special structures that require advanced analysis techniques to examine their performance. This paper presents a procedure developed to model the Confederation Bridge using 3-D beam elements. The model was validated using the data collected before the opening of the bridge to the public. The bridge was instrumented to conduct fullscale static and dynamic tests. The static tests were to measure the deflection of the bridge pier while the dynamic tests to measure the free vibrations of the pier due to a sudden release of the static load. Confederation Bridge is one of the longest reinforced concrete bridges in the world. It connects the province of Prince Edward Island and the province of New Brunswick in Canada. Due to its strategic location and vital role as a transportation link between these two provinces, it was designed using higher safety factors than those for typical highway bridges. After validating the present numerical model, a procedure was developed to evaluate the performance of similar bridges subjected to traffic and seismic loads. It is of interest to note that the foundation stiffness and the modulus of elasticity of the concrete have significant effects on the structural responses of the Confederation Bridge.

Constructing Large Scale Cohort for Clinical Study on Heart Failure with Electronic Health Record in Regional Healthcare Platform:Challenges and Strategies in Data Reuse

Regional healthcare platforms collect clinical data from hospitals in specific areas for the purpose of healthcare management.It is a common requirement to reuse the data for clinical research.However,we have to face challenges like the inconsistence of terminology in electronic health records (EHR) and the complexities in data quality and data formats in regional healthcare platform.In this paper,we propose methodology and process on constructing large scale cohorts which forms the basis of causality and comparative effectiveness relationship in epidemiology.We firstly constructed a Chinese terminology knowledge graph to deal with the diversity of vocabularies on regional platform.Secondly,we built special disease case repositories (i.e.,heart failure repository) that utilize the graph to search the related patients and to normalize the data.Based on the requirements of the clinical research which aimed to explore the effectiveness of taking statin on 180-days readmission in patients with heart failure,we built a large-scale retrospective cohort with 29647 cases of heart failure patients from the heart failure repository.After the propensity score matching,the study group (n=6346) and the control group (n=6346) with parallel clinical characteristics were acquired.Logistic regression analysis showed that taking statins had a negative correlation with 180-days readmission in heart failure patients.This paper presents the workflow and application example of big data mining based on regional EHR data.

基于组增长的小世界Scale-free网络模型

小世界和Scale-free是很多大规模复杂网络的重要特征,建立体现这些特征的网络模型是研究网络结构和行为的重要基础。针对现有模型不能全面地反映实际网络所具有的特征属性,提出了基于组增长的小世界 Scale-free网络模型。该模型在小世界和 Scale-free模型的基础上,结合了节点的本地强连接性、新增连接的度相关性和网络动态的增长方式,把小世界和 Scale-free联系了起来。仿真结果表明,该模型生成的网络图同时具有小世界和 Scale-free特征。

Likert Scale计分系统在MRI诊断侵犯性前置胎盘中的效能研究

目的评价Likert Scale(李克特量表)计分系统在MRI诊断侵犯性前置胎盘中的效能。方法回顾分析104例经产前MRI检查及术中诊断为前置胎盘孕妇的MRI图像,其中有胎盘侵犯59例,均经过临床手术及病理证实。Likert Scale计分系统是根据李克特五分量表对侵犯性前置胎盘7个MRI征象(胎盘信号不均、胎盘内条状低信号带、胎盘内异常血管、子宫肌层增多增粗血管、胎盘内外缘局部隆起、胎盘处子宫肌层模糊不清、胎盘向宫颈内口突出)进行评分,然后计算7个MRI征象评分的总分。A、B两名阅片医师对104例前置胎盘MRI图像按照Likert Scale计分系统进行评分,两名阅片医师读片一致性采用组内相关系数(intraclass correlation coefficients,ICC)衡量;诊断效能通过受试者工作特征(receiver operator characteristic,ROC)曲线分析。结果两名阅片医师在总分及各分项MRI征象评分一致性均表现较好(ICC≥0.60),可以取两名阅片医师总分及每个MRI征象评分的均值绘制诊断侵犯性前置胎盘的ROC曲线;总分、各分项MRI征象ROC曲线下面积以及各分项MRI征象ROC曲线下面积与总分进行比较,结果如下:总分(0.983)、胎盘信号不均(0.888,P=0.003)、胎盘内条状低信号带(0.918,P=0.005)、胎盘内异常血管(0.850,P=0.000)、子宫肌层增多增粗血管(0.850,P=0.000)、胎盘内外缘局部隆起(0.852,P=0.000)、胎盘处子宫肌层模糊不清(0.880,P=0.002)、胎盘向宫颈内口突出(0.747,P=0.000)。总分的ROC曲线下面积大于各分项MRI征象,差别有统计学意义(P<0.05),表明总分的诊断效能高于单个MRI征象评分。结论 Likert Scale计分系统在MRI诊断侵犯性前置胎盘中具有非常高的诊断效能。

Research on multi-time scale doubly-fed wind turbine test system based on FPGA+CPU heterogeneous calculation

As the proportion of renewable energy increases, the interaction between renewable energy devices and the grid continues to enhance. Therefore, the renewable energy dynamic test in a power system has become more and more important. Traditional dynamic simulation systems and digital-analog hybrid simulation systems are difficult to compromise on the economy, flexibility and accuracy. A multi-time scale test system of doubly fed induction generator based on FPGA+ CPU heterogeneous calculation is proposed in this paper. The proposed test system is based on the ADPSS simulation platform. The power circuit part of the test system is setup up using the EMT(electromagnetic transient simulation) simulation, and the control part uses the actual physical devices. In order to realize the close-loop testing for the physical devices, the power circuit must be simulated in real-time. This paper proposes a multi-time scale simulation algorithm, in which the decoupling component divides the power circuit into a large time scale system and a small time scale system in order to reduce computing effort. This paper also proposes the FPGA+CPU heterogeneous computing architecture for implementing this multitime scale simulation. In FPGA, there is a complete small time-scale EMT engine, which support the flexibly circuit modeling with any topology. Finally, the test system is connected to an DFIG controller based on Labview to verify the feasibility of the test system.

The Application of the Generalized Differential Formulation of the First Law of Thermodynamics for Evidence of the Tidal Mechanism of Maintenance of the Energy and Viscous-Thermal Dissipative Turbulent Structure of the Mesoscale Oceanic Eddies

The practical significance of the established generalized differential formula-tion of the first law of thermodynamics (formulated for the rotational coor-dinate system) is evaluated (for the first time and for the mesoscale oceanic eddies) by deriving the general (viscous-compressible-thermal) and partial (incompressible, viscous-thermal) local conditions of the tidal maintenance of the quasi-stationary energy and dissipative turbulent structure of the mesoscale eddy located inside of the individual fluid region of the ther-mally heterogeneous viscous (compressible and incompressible, respective-ly) heat-conducting stratified fluid over the two-dimensional bottom topog-raphy characterized by the horizontal coordinate x along a horizon-tal axis X. Based on the derived partial (incompressible) local condition (of the tidal maintenance of the quasi-stationary energy and viscous-thermal dis-sipative turbulent structure of the mesoscale eddy) and using the calculated vertical distributions of the mean viscous dissipation rate per unit mass and the mean thermal dissipation rate per unit mass in four regions near the observed mesoscale (periodically topographically trapped by nearly two-dimensional bottom topography h(x) eddy located near the northern region of the Yamato Rise in the Japan Sea, the combined analysis of the energy structure of the eddy and the viscous-thermal dissipative structure of turbulence is presented. The convincing evidence is presented of the tidal mechanism of maintenance of the eddy energy and viscous-thermal dissipa-tive structure of turbulence (produced by the breaking internal gravity waves generated by the eddy) in three regions near the Yamato Rise subjected to the observed mesoscale eddy near the northern region of the Yamato Rise of the Japan Sea.

A Quaternion Scaled Unscented Kalman Estimator for Inertial Navigation States Determination Using INS/GPS/Magnetometer Fusion

This Inertial Navigation System (INS), Global Positioning System (GPS) and fluxgate magnetometer technologies have been widely used in a variety of positioning and navigation applications. In this paper, a low cost solid state INS/GPS/Magnetometer integrated navigation system has been developed that incorporates measurements from an Inertial Navigation System (INS), Global Positioning System (GPS) and fluxgate magnetometer (Mag.) to provide a reliable complete navigation solution at a high output rate. The body attitude estimates, especially the heading angle, are fundamental challenges in a navigation system. Therefore targeting accurate attitude estimation is considered a significant contribution to the overall navigation error. A better estimation of the body attitude estimates leads to more accurate position and velocity estimation. For that end, the aim of this research is to exploit the magnetometer and accelerometer data in the attitude estimation technique. In this paper, a Scaled Unscented Kalman Filter (SUKF) based on the quaternion concept is designed for the INS/GPS/Mag integrated navigation system under large attitude error conditions. Simulation and experimental results indicate a satisfactory performance of the newly developed model.

One-Step-Installation of Offshore Wind Turbine on Large-Scale Bucket-Top-Bearing Bucket Foundation

In 2010,the first offshore wind turbine with integrated installation was established in Qidong sea area of Jiangsu Province,China,which led to the implementation phase of one-step-installation technique based on the design and construction of large-scale bucket-top-bearing (LSBTB) bucket foundation.The critical technique of LSBTB bucket foundation included self-floating towing,penetration with adjustment of horizontal levelness,removability and one-step-installation.The process of one-step-installation included the prefabrication of LSBTB bucket foundation in onshore construction base,installation and debugging of wind power,overall water transportation of foundation and wind power system,and installation of foundation and offshore wind turbine on the appointed sea area.The cost of one-step-installation technique was about 5 000 Yuan/kW,which was 30%-50% lower than that of the existing technique.The prefabrication of LSBTB bucket foundation took about two months.During the one-step-installation process,the installation and debugging of wind power and overall water transportation need about one to two days in sea area within 35 m depth.After the proposed technique is industrialized,the cost will be further reduced,and the installation capacity is expected to be up to 500 wind turbines per year.

基于多尺度Scale-Unet的单样本图像翻译

随着生成对抗网络(GAN)的发展,基于单样本的无监督图像到图像翻译(UI2I)取得了重大进展。然而,以前方法无法捕获图像中的复杂纹理并保留原始内容信息。为解决这个问题,提出了一种基于尺度可变U-Net结构(Scale—Unet)的新型单样本图像翻译结构SUGAN。所提出的SUGAN使用Scale—Unet作为生成器,利用多尺度结构和渐进方法不断改进网络结构,以从粗到细地学习图像特征。同时,提出了尺度像素损失scale-pixel来更好地约束保留原始内容信息,防止信息丢失。实验表明,与SinGAN、TuiGAN、TSIT、StyTR2等公共数据集Summer■Winter、Horse■Zebra上的方法相比,该方法生成图像的SIFID值平均降低了30%。所提方法可更好地保留图像内容信息,同时生成详细逼真的高质量图像。

Uncertainties of landslide susceptibility prediction:influences of different study area scales and mapping unit scales

This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.

浙江金华不同城市绿地大型土壤动物群落结构与多样性

2004年10-11月对金华市市区8种城市绿地生境中的大型土壤动物群落进行了调查,共获得大型土壤动物1231只,隶属3门8纲20目。其中优势类群为近孔寡毛目、膜翅目、双尾目和蜘蛛目,常见类群为正蚓目、等足目、柄眼目、鞘翅目、鳞翅目、双翅目和同翅目,其余类群为稀有类群。不同城市绿地生境中的土壤动物的类群组成以及个体数不同。在土壤动物研究中,群落复杂性指数(C)比Shannon-Wiener指数(H′)更能体现群落的复杂性与多样性,且能修正不同类群个体数对多样性的影响。大型土壤动物显示了明显的表聚现象,垂直分布有明显差异,类群数和个体数随深度增加而减少。群落聚类以及排序的结果显示,8种城市绿地生境中的大型土壤动物群落可以分为6大类:草坪类、草地类、新植草坪类、无草本层的人工林类、有草本层的人工林类和灌木林类。

Scale-space effect and scale hybridization in image intelligent recognition of geological discontinuities on rock slopes

Geological discontinuity(GD)plays a pivotal role in determining the catastrophic mechanical failure of jointed rock masses.Accurate and efficient acquisition of GD networks is essential for characterizing and understanding the progressive damage mechanisms of slopes based on monitoring image data.Inspired by recent advances in computer vision,deep learning(DL)models have been widely utilized for image-based fracture identification.The multi-scale characteristics,image resolution and annotation quality of images will cause a scale-space effect(SSE)that makes features indistinguishable from noise,directly affecting the accuracy.However,this effect has not received adequate attention.Herein,we try to address this gap by collecting slope images at various proportional scales and constructing multi-scale datasets using image processing techniques.Next,we quantify the intensity of feature signals using metrics such as peak signal-to-noise ratio(PSNR)and structural similarity(SSIM).Combining these metrics with the scale-space theory,we investigate the influence of the SSE on the differentiation of multi-scale features and the accuracy of recognition.It is found that augmenting the image's detail capacity does not always yield benefits for vision-based recognition models.In light of these observations,we propose a scale hybridization approach based on the diffusion mechanism of scale-space representation.The results show that scale hybridization strengthens the tolerance of multi-scale feature recognition under complex environmental noise interference and significantly enhances the recognition accuracy of GD.It also facilitates the objective understanding,description and analysis of the rock behavior and stability of slopes from the perspective of image data.

Measurement invariance and latent mean differences of the Chinese version physical activity self-efficacy scale across gender and education levels

Background: Self-efficacy has been identified as an important determinant of youth's behavior change including physical activity(PA) participation. However, the dimensionality check of a PA self-efficacy scale has rarely been conducted in China. The current study aims to examine(1) the unidimensionality of a shortened Chinese version of PA self-efficacy scale(S-PASESC);(2) the measurement invariance of S-PASESC across gender and levels of education;(3) the latent factor mean difference between gender and levels of education;(4) the direct effects of self-efficacy on PA by different gender and education levels; and(5) the comparisons of the direct effects of self-efficacy on PA across gender and education levels.Methods: The participants were 5 th through 11 th grade public school students recruited from 7 cities located in different geographic regions of China. The final data include a total of 3003 participants(49.7% boys) who have completed the scales.Results: Confirmatory factor analysis(CFA) test supported the unidimensionality of S-PASESC. The S-PASESC is invariant across gender and 3 levels of education at both configural, full metric, and full scalar levels. Findings from latent mean comparisons showed that boys reported higher PA self-efficacy than girls. Students' perceived PA self-efficacy tend to decrease from elementary to high school. Finally, self-efficacy positively related to PA by groups of different gender and education levels and the relationship between self-efficacy and PA is stronger among middle school boys than girls.Conclusion: Findings suggest S-PASESC is a valid scale for measuring Chinese students' PA self-efficacy.

Validity,Reliability,and Measurement Invariance of the Thai Smartphone Application-Based Addiction Scale and Bergen Social Media Addiction Scale

Background:In recent years,there has been increased research interest in both smartphone addiction and social media addiction as well as the development of psychometric instruments to assess these constructs.However,there is a lack of psychometric evaluation for instruments assessing smartphone addiction and social media addiction in Thailand.The present study evaluated the psychometric properties and gender measurement invariance of the Thai version of the Smartphone Application-Based Addiction Scale(SABAS)and Bergen Social Media Addiction Scale(BSMAS).Method:A total of 801 Thai university students participated in an online survey from January 2022 to July 2022 which included demographic information,SABAS,BSMAS,and the Internet Gaming Disorder Scale-Short Form(IGDS9-SF).Results:Confirmatory Factor Analyses(CFAs)found that both the SABAS and BSMAS had a one-factor structure.Findings demonstrated adequate psychometric properties of both instruments and also supported measurement invariance across genders.Moreover,scores on the SABAS and BSMAS were correlated with scores on the IGDS9-SF.Conclusion:The results indicated that the SABAS and BSMAS are useful psychometric instruments for assessing the risk of smartphone addiction and social media addiction among Thai young adults.

Multi-Level, Multi-Scale Modeling and Predictive Mapping for Jaguars in the Brazilian Pantanal

Multi-level multi-scale resource selection models using machine learning were compared and contrasted for generating predictive maps of jaguar habitat (Panthera onca) in the Brazilian Pantanal. Multiple spatial scales and temporal movement levels were run within several analytical modeling frameworks for comparison. Included in the analysis were multi-scale raster grains (30 m, 90 m, 180 m, 360 m, 720 m, 1440 m) and GPS collaring temporal movement levels (point, path, and step). Various analytical methods were used for comparison of models that could accommodate data structural levels (group, individual, case-control). Models compared included conditional logistic regression, generalized additive modeling (GAM), and classification regression trees, such as random forests (RF) and gradient boosted regression tree (GBM). The goals of the study were to discuss the potential and limitations for machine learning methods using GPS collaring data to produce predictive habitat suitability mapping using the various scales and levels available. Results indicated that choosing the appropriate temporal level and raster scale improved model outputs. Overall, larger level analytical modeling frameworks and those that used multi-scale raster grains showed the best model evaluation with the inherent condition that they predict a broader scale and subset of data. The identification of the appropriate spatial scale, temporal scale and statistical model need careful consideration in predictive mapping efforts.

Water as a Standard Substance of a Logarithmic Poison Scale

The lethal dose LD50 represents the most important experimental value for acute toxicity. The simple logarithmic calculation of -log10 LD50 = value leads to the possible poison power pLD. As with the pH or pK value, respectively, for acid or the scale of earthquake intensities the logarithm helps making large differences of orders of magnitude easier to understand since they are more comparable. The higher the pLD value, the higher is the power of poison. An increase of the pLD value by 1 stands for a tenfold increase in toxicity. The lethal acute dose for water, one of the most important and at the same time non-toxic substances of all, is about one tenth of the body weight. This leads to a possible pLD value for water of 1, an ideal starting value for a logarithmic poison scale.