Online pharmaceutical process analysis of Chinese medicine using a miniature mass spectrometer: Extraction of active ingredients as an example

The automation of traditional Chinese medicine(TCM)pharmaceuticals has driven the development of process analysis from offline to online.Most of common online process analytical technologies are based on spectroscopy,making the identification and quantification of specific ingredients still a challenge.Herein,we developed a quality control(QC)system for monitoring TCM pharmaceuticals based on paper spray ionization miniature mass spectrometry(mini-MS).It enabled real-time online qualitative and quantitative detection of target ingredients in herbal extracts using mini-MS without chromatographic separation for the first time.Dynamic changes of alkaloids in Aconiti Lateralis Radix Praeparata(Fuzi)during decoction were used as examples,and the scientific principle of Fuzi compatibility was also investigated.Finally,the system was verified to work stably at the hourly level for pilot-scale extraction.This mini-MS based online analytical system is expected to be further developed for QC applications in a wider range of pharmaceutical processes.

Digital Twin Framework and Its Application to Power Grid Online Analysis

Digital twin(DT)framework is introduced in the context of application for power grid online analysis.In the development process of a new power grid real-time online analysis system,an online analysis digital twin(OADT)has been implemented to realize the new online analysis architecture.The OADT approach is presented and its prominent features are discussed.The presentation,discussion,and performance testing are based on a large-scale grid network model(40K+buses),exported directly from the EMS system of an actual power grid.A plan to apply the OADT approach to digitize power grid dispatching rules is also outlined.

Real-time Online Analysis of Power Grid

The unprecedented operational complexity and se-curity risks in operating the Chinese UHV AC/DC power grid calls for a new generation of real-time(sec-order)online analysis systems to provide decision support.Our recent Digital Twin based online analysis research and development work to address the needs is presented.In addition,a high-level solution architec-ture for the future real-time online analysis systems is proposed for realizing:a)The delay of the virtual model to mirror the physical power grid is in sub-sec range;b)The downstream online analysis applications could have sec-order responsiveness.

Laser-induced Breakdown Spectroscopy as a Powerful Tool for Online Quality Control in The Refractory Industry

Raw materials have a signcant influence on the qu.ality of the final refractory products, as the crude ore often comes for processing with significant variations in chemical and mineralogical composition. Therefore, it is necessary to guarantee the stable quality of raw materials with pre-assigned qualitative factors. It is possible to solve these problems by separating raw materials by grades, including the rejection of the portions of material unsuitable for specific application, and by reasonable control of the processing parameters based on real-time infirmation about chemical composition of raw materials. This can be effectively achieved by MAYA laser ele- mental analyzers based on LIBS. Being applied in ex traction, beneficiation and processing of the mineral raw materials, LIBS analyzers can be used for automatic sor ting ＂ the ore extracted or crushed and automatic dosage of components to stabilize the composition of raw material mixtures.

A Process to Support Analysts in Exploring and Selecting Content from Online Forums

The public content increasingly available on the Internet, especially in online forums, enables researchers to study society in new ways. However, qualitative analysis of online forums is very time consuming and most content is not related to researchers’ interest. Consequently, analysts face the following problem: how to efficiently explore and select the content to be analyzed? This article introduces a new process to support analysts in solving this problem. This process is based on unsupervised machine learning techniques like hierarchical clustering and term co-occurrence network. A tool that helps to apply the proposed process was created to provide consolidated and structured results. This includes measurements and a content exploration interface.

A New Solution Architecture for Online Power System Analysis

The current DSA system used in the dispatching control centers in China is a near real-time analysis system with response speed in the order of minutes.Based on a review of the state-of-the-art in online analysis and discussion of distributed data processing and computation architecture patterns,a new online analysis architecture is proposed.The primary goal of the new architecture is to increase the online analysis response speed to the order of seconds.A reference implementation of the proposed online analysis architecture to validate the feasibility of implementing the architecture and some performance testing results are presented.

A Scalable Infrastructure for Online Performance Analysis on CFD Application

The fast-growing demand of computational fluid dynamics（CFD） application for computing resources stimulates the development of high performance computing（HPC） and meanwhile raises new requirements for the technology of parallel application performance monitor and analysis.In response to large-scale and long-time running for the application of CFD,online and scalable performance analysis technology is required to optimize the parallel programs as well as to improve their operational efficiency.As a result,this research implements a scalable infrastructure for online performance analysis on CFD application with homogeneous or heterogeneous system.The infrastructure is part of the parallel application performance monitor and analysis system（PAPMAS） and is composed of two modules which are scalable data transmission module and data storage module.The paper analyzes and elaborates this infrastructure in detail with respect to its design and implementation.Furthermore,some experiments are carried out to verify the rationality and high efficiency of this infrastructure that could be adopted to meet the practical needs.

A review of intelligent ore sorting technology and equipment development

Under the background of increasingly scarce ore worldwide and increasingly fierce market competition,developing the mining industry could be strongly restricted.Intelligent ore sorting equipment not only improves ore use and enhances the economic benefits of enterprises but also increases the ore grade and lessens the grinding cost and tailings production.However,long-term research on intelligent ore sorting equipment found that the factors affecting sorting efficiency mainly include ore information identification technology,equipment sorting actuator,and information processing algorithm.The high precision,strong anti-interference capability,and high speed of these factors guarantee the separation efficiency of intelligent ore sorting equipment.Color ore sorter,X-ray ore transmission sorter,dual-energy X-ray transmission ore sorter,X-ray fluorescence ore sorter,and near-infrared ore sorter have been successfully developed in accordance with the different characteristics of minerals while ensuring the accuracy of equipment sorting and improving the equipment sorting efficiency.With the continuous improvement of mine automation level,the application of online element rapid analysis technology with high speed,high precision,and strong anti-interference capability in intelligent ore sorting equipment will become an inevitable trend of equipment development in the future.Laser-induced breakdown spectroscopy,transientγneutron activation analysis,online Fourier transform infrared spectroscopy,and nuclear magnetic resonance techniques will promote the development of ore sorting equipment.In addition,the improvement and joint application of additional high-speed and high-precision operation algorithms(such as peak area,principal component analysis,artificial neural network,partial least squares,and Monte Carlo library least squares methods)are an essential part of the development of intelligent ore sorting equipment in the future.

Two-dimensional correlation analysis of continuous online in situ ATR-FTIR on the adsorption of butyl xanthate at the surface of α-PbO

The adsorption behavior of butyl xanthate on the surface of lead oxide was investigated using continuous online in situ attenuated total reflectance Fourier transform infrared（ATR-FTIR） spectroscopy technique and two dimensional（2D） correlation analysis.The adsorbed layer studied was prepared by coating α-PbO particles onto the surfaces of the ZnSe crystal.The appearance of spectral peaks at 1203 cm^-1,1033 cm^-1 and their red shift indicated the formation and aggregation of xanthate at the surface of α-PbO.According to 1R intensity changes after rinsing with deionized water and a NaOH solution,the adsorption was proved to be a chemisorption type.The competition between xanthate and OH^- for the surfaces leads to desorption of xanthate at higher pH.The technique of 2D correlation ATR-FTIR spectroscopy was used to evaluate the changing order of spectral intensities in the adsorption process,and the results indicated that xanthate micelles were formed at the surfaces.The adsorption kinetics of butyl xanthate was found to be a pseudo-second-order reaction model and the adsorption capacity of butyl xanthate at α-PbO was as high as 281 mg g^-1 after 150 min.

Online Energy Measure and Analysis System for Large-Scale Public Buildings

Large-scale public buildings have high energy density, which on average consume 5 to 15 times more electricity than residential buildings. In Beijing, those public buildings account for about ten percent of the total building area, but their energy consumption （except heating） amounts to more than thirty percent of the total. Few electric meters are installed in those public buildings, however, making it more difficult to monitor how the energy is used.

Design and Implementation of Prototype System for Online Handwritten Uyghur Character Recognition

Based on the analysis of the unique shapes and writing styles of Uyghur characters,we design a framework for prototype character recognition system and carry out a systematic theoretical and experimental research on its modules.In the preprocessing procedure,we use the linear and nonlinear normalization based on dot density method.Both structural and statistical features are extracted due to the fact that there are some very similar characters in Uyghur literature.In clustering analysis,we adopt the dynamic clustering algorithm based on the minimum spanning tree（MST）,and use the k-nearest neighbor matching classification as classifier.The testing results of prototype system show that the recognition rates for characters of the four different types（independent,suffix,intermediate,and initial type） are 74.67%,70.42%,63.33%,and 72.02%,respectively;the recognition rates for the case of five candidates for those characters are 94.34%,94.19%,93.15%,and 95.86%,respectively.The ideas and methods used in this paper have some commonality and usefulness for the recognition of other characters that belong to Altaic languages family.

Towards electric digital twin grid: Technology and framework review

The major hindrances in the energy system are ecological consciousness, lack of clean and sustainableenergy management, insufficient energy distribution–transmission–optimization, expensive power transfercosts, and increased customer knowledge of energy charges. Thus why, universal access to the grid with highcybersecurity, and reliability is needed to solve all these challenges. The digital twin concept turns a newdimension of technology into the world. Electric Digital Twin grid can perform online analysis of the grid inreal-time and integrates all the past and present data and express the current grid status to the producers andconsumers and also predicts the future grid status. Thus, the power grid transmission loss and location of theoverheated line and power connection missing can be detected in addition decision-making and self-healingcan possible. The future prediction saves the power grid from small to long accidents such as power outagesand even blackout problems. The whole consumers and nation feel relief from these types of accidents andsaves from large economic and business loss. The blockchain-enabled digital twin grid provides high securityfor the grid from cyberattacks. The paper conveys the framework of the electric digital twin grid and theconcept of the DT grid processing and the way of serving the producer, prosumers, consumers even the wholenation in infrastructure, education, research, economic, business, and political development.

StreamTune： dynamic resource scheduling approach for workload skew in video data center

Video surveillance applications need video data center to provide elastic virtual machine （VM） provisioning. However, the workloads of the VMs are hardly to be predicted for online video surveillance service. The unknown arrival workloads easily lead to workload skew among VMs. In this paper, we study how to balance the workload skew on online video surveillance system. First, we design the system framework for online surveillance service which con- sists of video capturing and analysis tasks. Second, we propose StreamTune, an online resource scheduling approach for workload balancing, to deal with irregular video analysis workload with the minimum number of VMs. We aim at timely balancing the workload skew on video analyzers without depending on any workload prediction method. Furthermore, we evaluate the performance of the proposed approach using a traffic surveillance application. The experimental results show that our approach is well adaptive to the variation of workload and achieves workload balance with less VMs.

A geospatial web portal for sharing and analyzing greenhouse gas data derived from satellite remote sensing images

Greenhouse gas data collected by different institutions throughout the world have significant scientific values for global climate change studies. Due to the diversity of data formats and different specifications of data access interfaces, most of those data should be first downloaded onto a local machine before they can be used. To overcome this limitation, we present a geospatial web portal for sharing and analyzing greenhouse gas data derived from remote sensing images. As a proof-of-concept, a prototype has also been designed and implemented. The work：flow of the web portal contains four processes： data access, data analysis, results visualiza- tion, and results output. A large volume of greenhouse gas data have been collected, described, and indexed in the portal, and a variety of data analysis services, such as calculating the temporal variation of regionally averaged column CO2 values and analyzing the latitudinal variations of globally averaged column CO2 values, are integrated into this portal. With the integrated geospatial data and services, researchers can collect and analyze greenhouse gas data online, and can preview and download the analysis results directly from the web portal. The geospatial web portal has been implemented as a web application, and we also used a study case to illustrate this framework.