Analysis of Modeling the Influence of Electromagnetic Fields Radiated by Industrial Static Converters and Impacts on Operators Using Maxwell’s Equations

The study of Electromagnetic Compatibility is essential to ensure the harmonious operation of electronic equipment in a shared environment. The basic principles of Electromagnetic Compatibility focus on the ability of devices to withstand electromagnetic disturbances and not produce disturbances that could affect other systems. Imperceptible in most work situations, electromagnetic fields can, beyond certain thresholds, have effects on human health. The objective of the present article is focused on the modeling analysis of the influence of geometric parameters of industrial static converters radiated electromagnetic fields using Maxwell’s equations. To do this we used the analytical formalism for calculating the electromagnetic field emitted by a filiform conductor, to model the electromagnetic radiation of this device in the spatio-temporal domain. The interactions of electromagnetic waves with human bodies are complex and depend on several factors linked to the characteristics of the incident wave. To model these interactions, we implemented the physical laws of electromagnetic wave propagation based on Maxwell’s and bio-heat equations to obtain consistent results. These obtained models allowed us to evaluate the spatial profile of induced current and temperature of biological tissue during exposure to electromagnetic waves generated by this system. The simulation 2D results obtained from computer tools show that the temperature variation and current induced by the electromagnetic field can have a very significant influence on the life of biological tissue. The paper provides a comprehensive analysis using advanced mathematical models to evaluate the influence of electromagnetic fields. The findings have direct implications for workplace safety, potentially influencing standards and regulations concerning electromagnetic exposure in industrial settings.

中国北方沙漠化地区生态重建的环境政策研究——基于Bioe-conomic Model

论文以内蒙古沙漠化地区为例,运用Bioe-conom ic M odel,比较自由放牧与耕垦、禁牧与禁垦、控制放牧规模与禁垦的土地利用政策情景下,引进舍饲养牛技术与信贷服务和增加非农就业机会对农户土地利用决策及其家庭收入的影响,据此探讨中国北方地区沙漠化发展的人文驱动机制以及生态重建的环境政策。结果表明:实施控制放牧规模与禁垦的环境政策,同时引进舍饲养牛技术能够有效地促进生态重建并提高农户收入;引进舍饲养牛技术需要启动基金,提供信贷服务和增加非农就业机会是贫困农户引进该技术的前提。因此,迫切需要调整宏观环境政策,提高农业集约化经营水平和城乡联系力度,从而提高农户家庭收入、减轻农民对环境的依赖性和促进农村的可持续发展。

Analysis and FDTD Modeling of the Influences of Microwave Electromagnetic Waves on Human Biological Systems

The interactions of electromagnetic waves with the human body are complex and depend on several factors related to the characteristics of the incident wave, including its frequency, its intensity, the polarization of the tissue encountered, the geometry of the tissue and its electromagnetic properties. That’s to say, the dielectric permittivity, the conductivity and the type of coupling between the field and the exposed body. A biological system irradiated by an electromagnetic wave is traversed by induced currents of non-negligible density;the water molecules present in the biological tissues exposed to the electromagnetic field will begin to oscillate at the frequency of the incident wave, thus creating internal friction responsible for the heating of the irradiated tissues. This heating will be all the more important as the tissues are rich in water. This article presents the establishment from a mathematical and numerical analysis explaining the phenomena of interaction and consequences between electromagnetic waves and health. Since the total electric field in the biological system is unknown, that is why it can be determined by the Finite Difference Time Domain FDTD method to assess the electromagnetic power distribution in the biological system under study. For this purpose, the detailed on the mechanisms of interaction of microwave electromagnetic waves with the human body have been presented. Mathematical analysis using Maxwell’s equations as well as bio-heat equations is the basis of this study for a consistent result. Therefore, a thermal model of biological tissues based on an electrical analogy has been developed. By the principle of duality, an electrical model in the dielectric form of a multilayered human tissue was used in order to obtain a corresponding thermal model. This thermal model made it possible to evaluate the temperature profile of biological tissues during exposure to electromagnetic waves. The simulation results obtained from computer tools show that the temperature in the biological tissue is a linear function of the duration of exposure to microwave electromagnetic waves.

Hydrogen production via steam reforming of bio-oil model compounds over supported nickel catalysts

The steam reforming of four bio-oil model compounds（acetic acid,ethanol,acetone and phenol） was investigated over Ni-based catalysts supported on Al2O3 modified by Mg,Ce or Co in this paper.The activation process can improve the catalytic activity with the change of high-valence Ni（Ni2O3,NiO） to low-valence Ni（Ni,NiO）.Among these catalysts after activation,the Ce-Ni/Co catalyst showed the best catalytic activity for the steam reforming of all the four model compounds.After long-term experiment at 700°C and the S/C ratio of 9,the Ce-Ni/Co catalyst still maintained excellent stability for the steam reforming of the simulated bio-oil（mixed by the four compounds with the equal masses）.With CaO calcinated from calcium acetate as CO2 sorbent,the catalytic steam reforming experiment combined with continuous in situ CO2 adsorption was performed.With the comparison of the case without the adding of CO2 sorbent,the hydrogen concentration was dramatically improved from 74.8% to 92.3%,with the CO2 concentration obviously decreased from 19.90% to 1.88%.

Technological Options to Ameliorate Waste Treatment of Intensive Pig Production in China:An Analysis Based on Bio-Economic Model

Ameliorating waste treatment by technological improvements affects the economic and the ecological-environment benefits of intensive pig production. The objective of the research was to develop and test a method to determine the technical optimization to ameliorate waste treatment methods and gain insight into the relationship between technological options and the economic and ecological effects. We developed an integrated bio-economic model which incorporates the farming production and waste disposal systems to simulate the impact of technological improvements in pig manure treatment on economic and environmental benefits for the case of a pilot farm in Beijing, China. Based on different waste treatment technology options, three scenarios are applied for the simulation analysis of the model. The simulation results reveal that the economic-environmental benefits of the livestock farm could be improved by reducing the cropland manure application and increasing the composting production with the current technologies. Nevertheless, the technical efficiency, the waste treatment capacity and the economic benefits could be further improved by the introduction of new technologies. It implies that technological and economic support policies should be implemented comprehensively on waste disposal and resource utilization to promote sustainable development in intensive livestock production in China.

Extended Generalized Riccati Equation Mapping for Thermal Traveling-Wave Distribution in Biological Tissues through a Bio-Heat Transfer Model with Linear/Quadratic Temperature-Dependent Blood Perfusion

Analytical thermal traveling-wave distribution in biological tissues through a bio-heat transfer (BHT) model with linear/quadratic temperature-dependent blood perfusion is discussed in this paper. Using the extended generalized Riccati equation mapping method, we find analytical traveling wave solutions of the considered BHT equation. All the travelling wave solutions obtained have been used to explicitly investigate the effect of linear and quadratic coefficients of temperature dependence on temperature distribution in tissues. We found that the parameter of the nonlinear superposition formula for Riccati can be used to control the temperature of living tissues. Our results prove that the extended generalized Riccati equation mapping method is a powerful tool for investigating thermal traveling-wave distribution in biological tissues.

A Mathematical Model to Solve Bio-Heat Transfer Problems through a Bio-Heat Transfer Equation with Quadratic Temperature-Dependent Blood Perfusion under a Constant Spatial Heating on Skin Surface

We consider the one-dimensional bio-heat transfer equation with quadratic temperature-dependent blood perfusion, which governs the temperature distribution inside biological tissues. Using an extended mapping method with symbolic computation, we obtain the exact analytical thermal traveling wave solution, which describes the non-uniform temperature distribution inside the bodies. The found exact solution is used to investigate the temperature distribution in the tissues. It is found that the surrounding medium with higher temperature does not necessarily imply that the tissue will quickly (after a short duration of heating process) reach the desired temperature. It is also found that increased perfusion causes a decline in local temperature.

Modelling Financially Optimal Afforestation and Forest Management Scenarios Using a Bio-Economic Model

The expansion of non-industrial private forests (NIPF) in Ireland is unique in the European context in which the almost doubling of forest cover within the last thirty years has taken place largely on farmland. This is not surprising as Ireland has some of the highest growth rates for conifers in Europe and also has a large proportion of land which is marginal for agriculture but highly productive under forests. However, in recent years, afforestation in Ireland as in many European countries has fallen well short of policy targets. As the farm afforestation decision essentially involves an inter-temporal land use change, farmers need comprehensive information on forest market returns under different environmental conditions and forest management regimes. This paper describes the systematic development of a cohort forest bio-economic model which examines financially optimal afforestation and management choices. Simulating a range of productivity and harvesting scenarios for Sitka spruce, we find that different objectives result in different outcomes. We see substantial differences between the biologically optimal rotation, the reduced rotation in common usage and the financially optimal rotation which maximises net present value and find that the results are particularly sensitive to the choice of management and methodological assumptions. Specifically, we find that better site productivity and thin versus no-thin options result in shorter rotations across all optimisations, reinforcing the usefulness of this type of financial modelling approach. This information is critical for future policy design to further incentivise afforestation of agricultural land.

An Extensive Study and Review of Privacy Preservation Models for the Multi-Institutional Data

The deep learning models hold considerable potential for clinical applications, but there are many challenges to successfully training deep learning models. Large-scale data collection is required, which is frequently only possible through multi-institutional cooperation. Building large central repositories is one strategy for multi-institution studies. However, this is hampered by issues regarding data sharing, including patient privacy, data de-identification, regulation, intellectual property, and data storage. These difficulties have lessened the impracticality of central data storage. In this survey, we will look at 24 research publications that concentrate on machine learning approaches linked to privacy preservation techniques for multi-institutional data, highlighting the multiple shortcomings of the existing methodologies. Researching different approaches will be made simpler in this case based on a number of factors, such as performance measures, year of publication and journals, achievements of the strategies in numerical assessments, and other factors. A technique analysis that considers the benefits and drawbacks of the strategies is additionally provided. The article also looks at some potential areas for future research as well as the challenges associated with increasing the accuracy of privacy protection techniques. The comparative evaluation of the approaches offers a thorough justification for the research’s purpose.

Submicro-battery effect and selective bio-oxidation model of gold-bearing arsenopyrite by Thiobacillus ferrooxidans

Through the study by electronic probe it was found that many new cracks and holes appear on the surface of gold bearing arsenopyrite crystal oxidized by Thiobacillus ferrooxidans, which are along with some directions. Then the selective bio oxidation model of gold bearing arsenopyrite was set up. The selective bio oxidation resulting from the submicro battery effect of gold/ arsenopyrite mineral pairs naturally forms in the gold bearing arsenopyrite crystal. Thiobacillus ferrooxidans has priority to oxidize the place of gold rich and oxidizes selectedly along with the crystal border, crystal face and crack. The bacteria oxidation process of gold bearing arsenopyrite is divided into three stages: the first stage is the surface oxidation, the second stage is restraining oxidation and the third stage is the filament oxidation, bacteria oxidize along with cracks of arsenopyrite.

An Optical Model for the Remote-Sensing of Absorption Coefficients of Phytoplankton in Oceanic/Coastal Waters

A new model for the remote sensing of absorption coefficients of phytoplankton aph (λ) in oceanic and coastal waters is developed and tested with SeaWiFS and MODIS-Aqua data. The model is derived from a rela-tionship of the remote sensing reflectance ratio Rrs (670)/Rrs (490) and aph (490) and aph (670) (from large in-situ data sets). When compared with over 470 independent in-situ data sets, the model provides accurate retrievals of the aph (λ) across the visible spectrum, with mean relative error less than 8%, slope close to unity and R2 greater than 0.8. Further comparison of the SeaWiFS-derived aph (λ) with in-situ aph (λ) values gives similar and consistent results. The model when used for analysis of MODIS-Aqua imagery, provides more realistic values of the phytoplankton absorption coefficients capturing spatial structures of the massive algal blooms in surface waters of the Arabian Sea. These results demonstrate that the new algorithm works well for both the coastal and open ocean waters observed and suggest a potential of using remote sensing to provide knowledge on the shape of phytoplankton absorption spectra that are a requirement in many inverse models to estimate phytoplankton pigment concentrations and for input into bio-optical models that predict carbon fixation rates for the global ocean.

Early Diagnosis of Bipolar Disorder Coming Soon:Application of an Oxidative Stress Injury Biomarker(BIOS)Model

Early distinction of bipolar disorder(BD)from major depressive disorder(MDD)is difficult since no tools are available to estimate the risk of BD.In this study,we aimed to develop and validate a model of oxidative stress injury for predicting BD.Data were collected from 1252 BD and 1359 MDD patients,including 64 MDD patients identified as converting to BD from 2009 through 2018.30 variables from a randomly-selected subsample of 1827(70%)patients were used to develop the model,including age,sex,oxidative stress markers(uric acid,bilirubin,albumin,and prealbumin),sex hormones,cytokines,thyroid and liver function,and glycolipid metabolism.Univariate analyses and the Least Absolute Shrinkage and Selection Operator were applied for data dimension reduction and variable selection.Multivariable logistic regression was used to construct a model for predicting bipolar disorder by oxidative stress biomarkers(BIOS)on a nomogram.Internal validation was assessed in the remaining 784 patients(30%),and independent external validation was done with data from 3797 matched patients from five other hospitals in China.10 predictors,mainly oxidative stress markers,were shown on the nomogram.The BIOS model showed good discrimination in the training sample,with an AUC of 75.1%(95%CI:72.9%–77.3%),sensitivity of 0.66,and specificity of 0.73.The discrimination was good both in internal validation(AUC 72.1%,68.6%–75.6%)and external validation(AUC 65.7%,63.9%–67.5%).In this study,we developed a nomogram centered on oxidative stress injury,which could help in the individualized prediction of BD.For better real-world practice,a set of measurements,especially on oxidative stress markers,should be emphasized using big data in psychiatry.

Research on Function Based Method for Bio-Inspiration Knowledge Modeling and Transformation

Biological inspirations are good design mimicry resources. This paper proposes a function based approach for modeling and transformation of bio-inspiration design knowledge. A general functional modeling method for biological domain and engineering domain design knowledge is introduced. Functional similarity based bio-inspiration transformation between biological domain and engineering domain is proposed. The biological function topology transfer and analog solution recomposition are also discussed in this paper.

NTI|bio模拟猴痘全球暴发桌面推演的介绍

根据世界卫生组织报告,猴痘疫情出现在非传统流行国家,部分病例无相关流行地的旅行史,因此存在人际传播的可能。在2021年3月17日,美国非盈利组织核威胁倡议协会下的全球生物政策和计划团队(NTI|bio)与慕尼黑安全会议(MSC)共同组织召开一次桌面推演,其目的是减少具有潜在灾难性后果的生物威胁,案例为虚拟的经基因合成、编辑和改造的猴痘病毒。通过介绍本次推演,为相关疫情大流行的防控提供案例和借鉴工具,以应对未来可能出现的各类全球疫情大流行。举措应包括建立公共卫生预警系统等,从而实现早发现、早评估、早处理,同时还需要建立联合评估机制以应对来历不明的高危险生物事件,通过多学科的共同研究和努力形成综合应对措施。

生物样本库建设在临床专业学位研究生人才培养中的作用

当前,我国临床专业学位硕士研究生培养与住院医师规范化培训全面接轨的“双轨合一”模式已在全国范围内广泛开展。新模式明显提升了专业学位硕士研究生的临床能力,但“重临床、轻科研”的现象普遍存在,以致专业学位硕士研究生的科研能力及科研思维明显不足。生物样本库作为临床科研转化医学研究的关键平台,对科学研究、转化应用及人才培养具有重要的支撑作用。在生物样本库的建设过程中,可培养具有创新意识和实践能力的高素质复合型医学人才。文章重点介绍了我国临床医学研究生培养现状、生物样本库发展现状、生物样本库在医学研究生培养过程中的作用、成效以及设想,以期在新时代背景下构建专业学位研究生人才培养新模式。

基于多源数据的特长隧道驾驶疲劳模型

为研究驾驶人在特长隧道内驾驶疲劳演变过程及其影响因素,基于实车试验采集的多源数据,对特长隧道内驾驶疲劳分类判别以及驾驶疲劳影响因素关系模型展开了研究。通过差异显著性分析和相关性分析筛选出闭眼百分率P80、瞳孔直径变异系数和加速度作为疲劳敏感性指标,并分析了各指标随行驶时间累积的变化规律。为构建驾驶疲劳分类判别模型,基于卡罗林斯卡嗜睡量表(Karolinska sleeping scale,KSS)主观疲劳检测结果,将疲劳程度划分清醒状态、半疲劳状态和疲劳状态,采用构造多类分类器的方法将不同疲劳状态样本进行组合分类,利用网格搜索法进行分类模型的参数寻优,并将筛选出的疲劳敏感性指标作为分类模型的输入变量,建立了基于网格搜索法的多分类支持向量机疲劳状态判别模型(GS-M-SVMs模型)。然后根据疲劳状态分类判别模型,利用有序多分类Logistic模型建立了特长隧道疲劳程度与影响因素的关系模型,对特长隧道内驾驶疲劳影响因素进行了探究。研究结果表明:疲劳敏感性指标变化规律可有效表征特长隧道内驾驶疲劳演变过程,而GS-M-SVMs模型分类检测准确率达到90.75%,对疲劳程度的分类识别效果较好,并且累积行驶时间和隧道长度显著影响驾驶人的疲劳程度,其模型回归系数分别为2.634和0.395,表明累积行驶时间是驾驶人在特长隧道路段中疲劳程度加重的最主要因素,隧道照度和隧道线形等因素并无显著影响。

沙拉酱对胡萝卜中活性物质体外消化的影响

以胡萝卜为原料,与沙拉酱复配成质量比为6∶1(T1)、4∶1(T2)、2∶1(T3)的胡萝卜沙拉样品,以不加沙拉酱的胡萝卜为对照(CK),采用体外静态INFOGEST消化模型,评估胡萝卜沙拉中主要活性物质(β-胡萝卜素、总酚和V-C)的生物可及性和消化特性。结果显示:除CK和T3的V-C外,活性物质含量经胃消化后均急剧下降,经肠道消化后又上升;添加沙拉酱明显提高了β-胡萝卜素、总酚和V-C的稳定性和生物可及性,T3组中3种生物活性物质在模拟消化过程中较稳定,生物可及性较高;各组的平均粒径D[3,2]和粒径分布强度均先增大,在模拟胃消化阶段消化60 min时最大,随后减至最小,T3组的D[3,2]在模拟消化过程中较小(0.13~5.03μm)。可见,沙拉酱可提高胡萝卜中β-胡萝卜素、总酚和V-C的生物可及性,并具有较好的消化特性,其中以T3组效果较佳。

基于注意力Seq2Seq神经网络的生物强化系统厌氧发酵菌体质量预测研究

生物强化厌氧发酵系统能够提高发酵效率和产物质量。然而,在生物强化甲烷厌氧发酵过程中,关键的生物参数难以实时在线测量。为了解决这一问题,提出了一种基于注意力融入Seq2Seq-LSTM模型的质量预测方法。通过编码器将时间序列数据输入,并引入注意力机制以增强对重要信息的关注,从而得到更新后的中间向量;在解码器中同样引入注意力机制,利用LSTM神经网络对当前时刻的中间向量和输入信息进行综合处理。同时,为了提高模型的稳定性,使用了Adamw梯度下降优化器进行训练。最后,将该方法与LSTM、AM-LSTM模型一同应用于甲烷发酵菌体质量预测并进行对比。实验结果表明,该模型拟合能力和预测准确性均优于其他两种模型,能够更好适用于甲烷发酵菌体质量的在线预测。

基于DSP/BIOS设备驱动模型的视频驱动程序开发

以TMS320DM642芯片为例,介绍了一种基于DSP/BIOS类/微型驱动模型编写视频驱动程序的方法。在类/微型驱动模型中,通过将驱动模型分为与硬件无关和与硬件相关的两层,使驱动程序的编写更为简化。应用程序通过调用类驱动的函数来间接调用微驱动函数,进而达到控制外部设备的目的。与传统的软件开发相比较,基于两层的驱动模型提高驱动程序的开发效率,增加了代码的兼容性和可移植性。

模型及ChemBioOffice在有机化学实验中的应用

有机化学是药学专业非常重要又较难学习的一门专业基础课,认识有机化合物的结构是学好这门课程的基础,单纯平面教学无法深入地将分子的实际空间结构加以充分展示。通过在有机化学实验课中开设球棍模型搭建及Chem Bio Office软件应用这一内容,利用立体、形象的原子间的相对位置,可以促进学生迅速地理解、掌握化合物的立体结构,把握有机分子构成的基本方式,为后续的教学内容打下良好的基础。