Using electroencephalogram to continuously discriminate feelings of personal thermal comfort between uncomfortably hot and comfortable environments

Thermal comfort is an important factor for the design of buildings. Although it has been well recognized that many physiological parameters are linked to the state of thermal comfort or discomfort of humans, how to use physiological signal to judge the state of thermal comfort has not been well studied. In this paper, the feasibility of continuously determining feelings of personal thermal comfort was discussed by using electroencephalogram (EEG) signals in private space. In the study, 22 subjects were exposed to thermally comfortable and uncomfortably hot environments, and their EEG signals were recorded. Spectral power features of the EEG signals were extracted, and an ensemble learning method using linear discriminant analysis or support vector machine as a sub-classifier was used to build the discriminant model. The results show that an average discriminate accuracy of 87.9% can be obtained within a detection window of 60 seconds. This study indicates that it is feasible to distinguish whether a person feels comfortable or too hot in their private space by multi-channel EEG signals without interruption and suggests possibility for further applications in neuroergonomics.     

Study on maximum power point tracking of photovoltaic array in irregular shadow

Traditional maximum power point tracking (MPPT) methods can hardly find global maximum power point (MPP) because output characteristics curve of photovoltaic (PV) array may have multi local maximum power points in irregular shadow, and thus easily fall into the local maximum power point. To address this drawback, Considering that sliding mode variable structure (SMVS) control strategy have such advantages as simple structure, fast response and strong robustness, and P&O method have the advantages of simple principle and convenient implementation, so a new algorithm combining SMVS control method and P&O method is proposed, besides, PI controller is applied to reduce system chattering caused by switching sliding surface. It is applied to MPPT control of PV array in irregular shadow to solve the problem of multi-peak optimization in partial shadow. In order to verity the rationality of the proposed algorithm, the experimental circuit is built, which achieves MPPT control by means of the proposed algorithm and P&O method. The experimental results show that compared with the traditional P&O algorithm, the proposed algorithm can fast track the global MPP, tracking speed increases by 60% and the relative error decreased by 20%. Moreover, the system becomes more stable near the MPP, the fluctuations of output power is greatly reduced, and thus make full use of solar energy.     

开关磁阻直线电机的设计及其推力优化

设计了一种开关磁阻直线电机,使用JMAG软件对其进行了仿真和优化。进行了推力公式的推导,研究了导通顺序和初始位置对电机推力的影响,并分析了三种典型情况的磁力线分布。对电机的定子和动子的齿部和轭部高度、宽度及铁耗进行仿真优化,得出了最优参数。将有取向硅钢应用于该电机,研究了推力与轧制角的关系,并与使用普通硅钢的开关磁阻直线电机进行了对比,推力有一定提升。提出在动子齿部开切向槽的方案,结果表明,开切向槽对推力的影响较小,并能显著减小推力波动。     

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.     

高强铝合金双脉冲VPPA焊缝成形机理

建立双脉冲VPPA(variable polarity plasma arc)焊接系统，进行7A52高强铝合金双脉冲VPPA焊接工艺试验，研究低频脉冲调制叠加高频脉冲对VPPA焊接过程中焊缝成形和焊缝力学性能的影响. 结果表明，低频脉冲周期性振荡液态熔池，可获得表面饱满的鱼鳞纹焊缝；高频脉冲使电弧更为集中，有效地提高了电弧能量密度，穿透力加强；双脉冲耦合振荡加强了对熔池的搅动作用细化了铝合金焊缝晶粒. 焊接接头抗拉强度达到384.13 MPa，相比VPPA焊接接头强度提高了10.21%左右；焊接接头断面收缩率和断后伸长率均有一定程度的提高. 铝合金双脉冲VPPA焊接工艺提高了焊接接头力学性能.     

Optimal scheduling of single stage batch plants with direct heat integration

This paper addresses the multi-objective optimization problem arising in the operation of heat integrated batch plants, where makespan and utility consumption are the two conflicting objectives. A new continuous-time MILP formulation with general precedence variables is proposed to simultaneously handle decisions related to timing, product sequencing, heat exchanger matches (selected from a two-stage superstructure) and their heat loads. It features a complex set of timing constraints to synchronize heating and cooling tasks, derived from Generalized Disjunctive Programming. Through the solution of an industrial case study from a vegetable oil refinery, we show that major savings in utilities can be achieved while generating the set of Pareto optimal solutions through the ɛ-constraint method.     

Group sequential crossover trial designs with strong control of the familywise error rate

Crossover designs are an extremely useful tool to investigators, and group sequential methods have proven highly proficient at improving the efficiency of parallel group trials. Yet, group sequential methods and crossover designs have rarely been paired together. One possible explanation for this could be the absence of a formal proof of how to strongly control the familywise error rate in the case when multiple comparisons will be made. Here, we provide this proof, valid for any number of initial experimental treatments and any number of stages, when results are analyzed using a linear mixed model. We then establish formulae for the expected sample size and expected number of observations of such a trial, given any choice of stopping boundaries. Finally, utilizing the four-treatment, four-period TOMADO trial as an example, we demonstrate that group sequential methods in this setting could have reduced the trials expected number of observations under the global null hypothesis by over 33%.     

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.