Gyrotactic microorganisms bioconvection in combined convective magnetohydrodynamic Casson nanofluid flow over a vertically surfaced saturated porous media with variable viscosity

The current article focuses on mass and thermal transfer analysis of a two-dimensional immovable combined convective nanofluid flow including motile microorganisms with temperature-dependent viscosity on top of a vertical plate through a porous medium, and a model has been developed to visualize the velocity slip impacts on a nonlinear partial symbiotic flow. The governed equations include all of the above physical conditions, and suitable nondimensional transfigurations are utilized to transfer the governed conservative equations to a nonlinear system of differential equations and obtain numerical solutions by using the Shooting method. Numerical studies have been focusing on the effects of intricate dimensionless parameters, namely, the Casson fluid parameter, Brownian motion parameter, thermophoresis parameter, Peclet number, bioconvection parameter, and Rayleigh number, which have all been studied on various profiles such as momentum, thermal, concentration, and density of microorganisms. The concentration boundary layer thickness and density of microorganisms increased as the Casson fluid parameter, Brownian and thermophoresis parameters increased, whereas the bioconvection parameter, Peclet number, and Rayleigh number increased. The thermal boundary layer thickness, concentration boundary layer thickness, and density of microorganisms all decreased. The velocity distribution decreases as the Peclet number, bioconvection, and thermophoresis parameters rise but rises as the Rayleigh number, Brownian motion parameter, and Casson fluid parameter rise. These are graphed via plots along with divergent fluid parameters.     

An automated patient monitoring using discrete‐time wireless sensor networks

In recent years, Internet of Things (IoT) devices are used for remote health monitoring. For remotely monitoring a patient, only the health information at different time points are not sufficient; predicted values of biomarkers (for some future time points) are also important. In this article, we propose a powerful statistical model for an efficient dynamic patient monitoring using wireless sensor nodes through Bayesian Learning (BL). We consider the setting where a set of correlated biomarkers are measured from a patient through wireless sensors, but the sensors only report the ordinal outcomes (say, good, fair, high, or very high) to the sink based on some prefixed thresholds. The challenge is to use the ordinal outcomes for monitoring and predicting the health status of the patient under consideration. We propose a linear mixed model where interbiomarker correlations and intrabiomarker dependence are modeled simultaneously. The estimated and the predicted values of the biomarkers are transferred over the internet so that health care providers and the family members of the patient can remotely monitor the patient. Extensive simulation studies are performed to assess practical usefulness of our proposed joint model, and the performance of the proposed joint model is compared to that of some other traditional models used in the literature.     

Inhibitory Monoclonal Antibodies and Their Recombinant Derivatives Targeting Surface-Exposed Carbonic Anhydrase XII on Cancer Cells

Monoclonal and recombinant antibodies are widely used for the diagnostics and therapy of cancer. They are generated to interact with cell surface proteins which are usually involved in the development and progression of cancer. Carbonic anhydrase XII (CA XII) contributes to the survival of tumors under hypoxic conditions thus is considered a candidate target for antibody-based therapy. In this study, we have generated a novel collection of monoclonal antibodies (MAbs) against the recombinant extracellular domain of CA XII produced in HEK-293 cells. Eighteen out of 24 MAbs were reactive with cellular CA XII on the surface of live kidney and lung cancer cells as determined by flow cytometry. One MAb 14D6 also inhibited the enzymatic activity of recombinant CA XII as measured by the stopped-flow assay. MAb 14D6 showed the migrastatic effect on human lung carcinoma A549 and renal carcinoma A498 cell lines in a ‘wound healing’ assay. It did not reduce the growth of multicellular lung and renal cancer spheroids but reduced the cell viability by the ATP Bioluminescence assay. Epitope mapping revealed the surface-exposed amino acid sequence (35-FGPDGENS-42) close to the catalytic center of CA XII recognized by the MAb 14D6. The variable regions of the heavy and light chains of MAb 14D6 were sequenced and their complementarity-determining regions were defined. The obtained variable sequences were used to generate recombinant antibodies in two formats: single-chain fragment variable (scFv) expressed in E. coli and scFv fused to human IgG1 Fc fragment (scFv-Fc) expressed in Chinese Hamster Ovary (CHO) cells. Both recombinant antibodies maintained the same specificity for CA XII as the parental MAb 14D6. The novel antibodies may represent promising tools for CA XII-related cancer research and immunotherapy.     

Process monitoring method based on correlation variable classification and vine copula

Chemical processes are becoming increasingly complicated, leading to an increase in process variables and more complex relationships among them. The vine copula has a significant advantage in portraying the dependence of high-dimensional variables. However, as the dimensions increase, the vine copula model incurs a high computational load; such pressure greatly reduces model efficiency. Relationships among variables in the industrial process are complex. Different variables may be strongly or weakly associated or even independent. This paper proposes a process monitoring method based on correlation variable classification and vine copula. The weighted correlation measure is first used to divide variables into a correlated subspace and weakly correlated subspace. Then, two vine structures, C-vine and D-vine, are applied to the correlated and weakly correlated subspaces, respectively. This method takes advantage of C-vine for correlated variables and the flexibility of D-vine for weakly correlated variables. Finally, comprehensive statistics are established based on different subspaces. Monitoring results of the numerical system and the Tennessee Eastman process demonstrate the effectiveness and validity of the proposed method.     

一种变步长D-Rake多用户检测器

在时变多径衰落信道下,接收到的CDMA信号功率变化较大,此时D-Rake盲自适应多用户检测器性能显著下降,将变步长LMS算法与基于主分量的相干合并引入到D-Rake(DecorrelatingRake)检测器中,构成一种变步长D-Rake,称之为VD-Rake(Variablestep-sizeDecorrelatingRake)检测器。该检测器能克服原D-Rake检测器对信号功率变化较敏感等缺点,有效地改善了D-Rake检测器的性能。     

面积坐标法构造含转角自由度的四结点膜元

以四边形面积坐标作为工具,构造了两个含转角自由度的广义协调四边形单元AQ4和lAQ4。它们通过强式分片检验,与同类单元相比,具有很高的计算精度,能消除梯形闭锁现象,有很强的抗网格畸变的能力。     

变差函数在地下水位估值中的应用研究

用数值方法进行地下水水资源评价时 ,需要给出每个节点上的初始地下水位值。本文着重阐述了区域化变量和变差函数及其计算步骤 ,指出变差函数在分析地下水位的空间变异的重要性     

建筑墙体表面传热系数辨识研究

对实验房间南向墙体内表面中心区域的换热过程进行实验，发现当风速在0－5．5m/s之间时，表面传热系数在8－18W（m^2.K）之间波动，而风向对墙体表面传热系数影响不大；用辅助变量法分析墙体表面传热过程，并结合实验推导出墙体表面传热系数。模型的预测结果与实测结果吻合良好。     

数字电位器的应用技术

从应用的角度出发，介绍合理设计应用电路和合理选择数字电位器的种类与型号，来克服数字电位器普遍存在的主要缺点的方法。文章具有较强的针对性和可操作性，对数字电位器的应用实践具有指导作用。     

概率空间中的一个不等式

设｛Ｚ，（Ｗ）｝是定义在概率空间上的独立的随机变量序列，Ｚ（Ｗ）具有方差为期望Ｅ（Ｚｎ）＝０．本文证明了对任意算数序列｛ｂｎ｝及任意的存在充分大的整数Ｎ＞０使当Ｎ＇＞Ｎ″＞Ｎ时．有此不等式在随机级数研究中有重要作用．