Installation filter in power system to control harmonic pollution could effectively reduce the system loss and avoid harmonic resonance or current amplification.A reasonable mathematical model of filters optimization was established with making the total investment of passive filters and active filters to be least as the object function and voltage harmonic distortion rate as constraints to insure that the voltage total harmonic distortion rate was controlled within the prescribed limits.The improved genetic algorithm was used to optimize the configuration of power filters.The simulation results of optimization configuration by utilizing 16 nodes demonstrate that the algorithm can converge the global optimal solution quickly,shows its correctness and validity.
The Internet of Things (IoT) provides significant benefits for industry due to connect the devices together through the internet. Attribute-Based Encryption (ABE) is a technique can enforce an access control over data to guarantee the data security. In this paper, we propose an ABE scheme for data in industrial IoT. The scheme achieves both security and high performance. When there is a shared subpolicy among the access policies of a sensor, the scheme optimizes the encryption of the messages. Through analysis and simulation, we show that our solution is security and efficient.
The fluctuation-dissipation (FD) theorem is a fundamental result for systems near thermodynamic equilibrium. It states that the nonequilibrium relaxation dynamics is related to the spontaneous fluctuation at equilibrium. Recently we have shown that the dynamics of a dissipative system described by stochastic differential equations can be mapped to that of a thermostated Hamiltonian system, with a nonequilibrium steady state of the former corresponding to the equilibrium state of the latter. In present manuscript, the corresponding FD theorem is derived in the way parallel to the procedure for deriving the near equilibrium FD theorem, based on this mapping. The analytical results in the present approach are in good agreement with numerical results. We find some previous results are special cases of the current relations. We also suggest further studies exploiting the analogy between a general dissipative system appearing in other science branches and a Hamiltonian system.
Objective: To investigate the clinical therapeutic effect of Cinobufacini combined with Docetaxel on the advanced stomach cancer.Methods: 86 patients with advanced stomach cancer were randomly divided into observation group(43 cases) and control group(43 cases).The patients in the observation group were treated continuously with Docetaxel 120 mg +0.9% sodium chloride 250 ml d1 for 3 weeks as onecycle,meanwhile continuously with Cinobufacini 20 ml + 0.9% sodium chloride 250 ml intravenous drip for 2 weeks,once a day,2 weeks treatment and 1 week rest for 1 cycle;while the patients in the control group were treated continuously with Docetaxel 120 mg+0.9% sodium chloride 250 ml d1 only for 3 weeks as one cycle.two groups were all treated with three circles.Results: There was no statistical difference in curative effect and adverse reaction between the two groups(P0.05).However there were significant differences between the two groups in the pain relief rate(79.09% vs 32.56%) and the effective rate of increasing life quality(76.74% vs 55.81%).Conclusion: Cinobufacini combined with Docetaxel can alleviate pain distinctly and improve the life quality for the patients with advanced stomach cancer.It is a safe and effective appeasement therapeutic method.
ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTEffects of Adsorption and Reaction on the Second Harmonic Generation of Langmuir-Blodgett FilmsXinsheng Zhao, Jianhua Xing, Peng Li, Xiaoming Xie, Xiaohua Xia, Hui Li, Chunhui Huang, Tiankai Li, and Lingge XuCite this: Langmuir 1995, 11, 10, 3620–3622Publication Date (Print):October 1, 1995Publication History Published online1 May 2002Published inissue 1 October 1995https://pubs.acs.org/doi/10.1021/la00010a004https://doi.org/10.1021/la00010a004research-articleACS PublicationsRequest reuse permissionsArticle Views51Altmetric-Citations2LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts
Abstract Ultra-multiplexed fluorescence imaging has revolutionized our understanding of biological systems, enabling the simultaneous visualization and quantification of multiple targets within biological specimens. A recent breakthrough in this field is PICASSO, a mutual-information-based technique capable of demixing up to 15 fluorophores without their spectra, thereby significantly simplifying the application of ultra-multiplexed fluorescence imaging. However, this study has identified a limitation of mutual information-based techniques. They do not differentiate between spatial colocalization and spectral mixing. Consequently, mutual information-based demixing may incorrectly interpret spatially co-localized targets as non-colocalized, leading to overcorrection. We found that selecting regions within a multiplex image with low spatial similarity for measuring spectroscopic mixing results in more accurate demixing. This method effectively minimizes overcorrections and promises to accelerate the broader adoption of ultra-multiplex imaging.
Abstract Recent advances in single-cell techniques catalyze an emerging field of studying how cells convert from one phenotype to another, in a step-by-step process. Two grand technical challenges, however, impede further development of the field. Fixed cell-based approaches can provide genome-wide snapshots of cell status but have fundamental limits on revealing temporal information, and fluorescence-based live cell imaging approaches provide temporal information but are technically challenging for multiplex long-term imaging. We first developed a live-cell imaging platform that tracks cellular status change through combining endogenous fluorescent labeling that minimizes perturbation to cell physiology, and/or live cell imaging of high-dimensional cell morphological and texture features. With our platform and an A549 VIM-RFP EMT reporter line, live cell trajectories reveal parallel paths of epithelial-to-mesenchymal transition missing from snapshot data due to cell-cell heterogeneity. Our results emphasize the necessity of extracting dynamical information of phenotypic transitions from multiplex live cell imaging.
Over the past 50 years, the use of mathematical models, derived from physical reasoning, to describe molecular and cellular systems has evolved from an art of the few to a cornerstone of biological inquiry. George Oster stood out as a pioneer of this paradigm shift from descriptive to quantitative biology not only through his numerous research accomplishments, but also through the many students and postdocs he mentored over his long career. Those of us fortunate enough to have worked with George agree that his sharp intellect, physical intuition and passion for scientific inquiry not only inspired us as scientists but also greatly influenced the way we conduct research. We would like to share a few important lessons we learned from George in honor of his memory and with the hope that they may inspire future generations of scientists.
Over the past 50 years, the use of mathematical models, derived from physical reasoning, to describe molecular and cellular systems has evolved from an art of the few to a cornerstone of biological inquiry. George Oster stood out as a pioneer of this paradigm shift from descriptive to quantitative biology not only through his numerous research accomplishments, but also through the many students and postdocs he mentored over his long career. Those of us fortunate enough to have worked with George agree that his sharp intellect, physical intuition and passion for scientific inquiry not only inspired us as scientists but also greatly influenced the way we conduct research. We would like to share a few important lessons we learned from George in honor of his memory and with the hope that they may inspire future generations of scientists.
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