Reform of Teaching Practice of Modern Instrumental Analysis in Biotechnology Programs

Through the online and offline practical reform of the Modern Instrumental Analysis course of biotechnology majors from teaching content,teaching method,teaching demonstration to teaching effect,the traditional single offline lecture is transformed into diversified and interactive modern teaching.The practical reform enriches and optimizes the course content,perfects and improves the course assessment system,and improves the teaching quality.It achieves the student-centered and application-oriented teaching goal,and also provides reference for further cultivating high-quality applied talents.

Digital Application Objectives and Benefit Analysis of BIM Technology in Large-Scale Comprehensive Development Projects

This paper discusses the digital application and benefit analysis of building information model(BIM)technology in the large-scale comprehensive development project of the Guangxi headquarters base.The project covers a total area of 92,100 square meters,with a total construction area of 379,700 square meters,including a variety of architectural forms.Through three-dimensional modeling and simulation analysis,BIM technology significantly enhances the design quality and efficiency,shortens the design cycle by about 20%,and promotes the collaboration and integration of project management,improving the management efficiency by about 25%.During the construction phase,the collision detection and four-dimensional visual management functions of BIM technology have improved construction efficiency by about 15%and saved the cost by about 10%.In addition,BIM technology has promoted green building and sustainable development,achieved the dual improvement of technical and economic indicators and social and economic benefits,set an example for enterprises in digital transformation,and opened up new market businesses.

Large-scale two-dimensional nonlinear FE analysis on PGA amplification effect with depth and focusing effect of Fuzhou Basin

Based on the explicit finite element(FE) method and platform of ABAQUS,considering both the inhomogeneity of soils and concave-convex fluctuation of topography,a large-scale refined two-dimensional(2D) FE nonlinear analytical model for Fuzhou Basin was established.The peak ground motion acceleration(PGA) and focusing effect with depth were analyzed.Meanwhile,the results by wave propagation of one-dimensional(1D) layered medium equivalent linearization method were added for contrast.The results show that:1) PGA at different depths are obviously amplified compared to the input ground motion,amplification effect of both funnel-shaped depression and upheaval areas(based on the shape of bedrock surface) present especially remarkable.The 2D results indicate that the PGA displays a non-monotonic decreasing with depth and a greater focusing effect of some particular layers,while the 1D results turn out that the PGA decreases with depth,except that PGA at few particular depth increases abruptly; 2) To the funnel-shaped depression areas,PGA amplification effect above 8 m depth shows relatively larger,to the upheaval areas,PGA amplification effect from 15 m to 25 m depth seems more significant.However,the regularities of the PGA amplification effect could hardly be found in the rest areas; 3) It appears a higher regression rate of PGA amplification coefficient with depth when under a smaller input motion; 4) The frequency spectral characteristic of input motion has noticeable effects on PGA amplification tendency.

Instrumental neutron activation analysis of beachrock samples of South East Coast of Tamilnadu,India

Element profiles of some beach rock samples collected from South East Coast of Tamilnadu, India have been determined using single comparator method of INAA. The geo-chemical behavior of the elements in the region is discussed. The irradiations were done at thermal neutron flux of ~ 1011 cm-2·s-1 at 20kW power using Kalpakkam Mini Reactor (KAMINI), IGCAR, Kalpakkam, Tamilnadu, India. Around 19 elements have been determined from 15 samples by high-resolution gamma spectrometry. The accuracy and precision were evaluated by assaying the irradiated Standard Reference Material (SRM 1646a Estuarine sediment) and were found to be in good agreement with certified values.

Preliminary Application of Combinatorial Measurement and Regression Analysis Method to High Precision Instrumental Analysis

With determination micro-Fe by 1, 10-phenanthroline spectrophotometry for example, they are systematically introduced the combinatorial measurement and regression analysis method application about metheodic principle, operation step and data processing in the instrumental analysis, including: calibration curve best linear equation is set up, measurand best linear equation is set up, and calculation of best value of a concentration. The results showed that mean of thrice determination , s = 0 μg/mL, RSD = 0. Results of preliminary application are simply introduced in the basic instrumental analysis for atomic absorption spectrophotometry, ion-selective electrodes, coulometry and polarographic analysis and are contrasted to results of normal measurements.

A Multilevel Hierarchical Parallel Algorithm for Large-Scale Finite Element Modal Analysis

The strict and high-standard requirements for the safety and stability ofmajor engineering systems make it a tough challenge for large-scale finite element modal analysis.At the same time,realizing the systematic analysis of the entire large structure of these engineering systems is extremely meaningful in practice.This article proposes a multilevel hierarchical parallel algorithm for large-scale finite element modal analysis to reduce the parallel computational efficiency loss when using heterogeneous multicore distributed storage computers in solving large-scale finite element modal analysis.Based on two-level partitioning and four-transformation strategies,the proposed algorithm not only improves the memory access rate through the sparsely distributed storage of a large amount of data but also reduces the solution time by reducing the scale of the generalized characteristic equation(GCEs).Moreover,a multilevel hierarchical parallelization approach is introduced during the computational procedure to enable the separation of the communication of inter-nodes,intra-nodes,heterogeneous core groups(HCGs),and inside HCGs through mapping computing tasks to various hardware layers.This method can efficiently achieve load balancing at different layers and significantly improve the communication rate through hierarchical communication.Therefore,it can enhance the efficiency of parallel computing of large-scale finite element modal analysis by fully exploiting the architecture characteristics of heterogeneous multicore clusters.Finally,typical numerical experiments were used to validate the correctness and efficiency of the proposedmethod.Then a parallel modal analysis example of the cross-river tunnel with over ten million degrees of freedom(DOFs)was performed,and ten-thousand core processors were applied to verify the feasibility of the algorithm.

Trend Analysis of Large-Scale Twitter Data Based on Witnesses during a Hazardous Event: A Case Study on California Wildfire Evacuation

Social media data created a paradigm shift in assessing situational awareness during a natural disaster or emergencies such as wildfire, hurricane, tropical storm etc. Twitter as an emerging data source is an effective and innovative digital platform to observe trend from social media users’ perspective who are direct or indirect witnesses of the calamitous event. This paper aims to collect and analyze twitter data related to the recent wildfire in California to perform a trend analysis by classifying firsthand and credible information from Twitter users. This work investigates tweets on the recent wildfire in California and classifies them based on witnesses into two types: 1) direct witnesses and 2) indirect witnesses. The collected and analyzed information can be useful for law enforcement agencies and humanitarian organizations for communication and verification of the situational awareness during wildfire hazards. Trend analysis is an aggregated approach that includes sentimental analysis and topic modeling performed through domain-expert manual annotation and machine learning. Trend analysis ultimately builds a fine-grained analysis to assess evacuation routes and provide valuable information to the firsthand emergency responders.

Stability Analysis of Continuous-Time Fuzzy Large-Scale System

A continuous-time fuzzy large-scale system F consists of some interconnected Takagi-Sugeno fuzzy subsystems. Two sufficient conditions for the asymptotic stability of this system (namely, theorem 1 and theorem 2) are derived via a multiple Lyapunov function approach. In theorem 1, the information of membership functions of fuzzy rules should be known in order to analyze the stability of F. But in general this information is not easy to be acquired for their time-varying property. So theorem 2 is provided to judge the asymptotic stability of F, based on which there is no need to know the information of membership functions in stability analysis. Finally, a numerical example is given to show the utility of the method proposed in this paper.

Explorations in Experimental Teaching of Traditional Chinese Medicine Instrumental Analysis Based on the Training of Innovative Talents

Training students’innovative thinking is an essential task of talent training in colleges and universities,and how to train students’innovativeness in experimental teaching is the focus of modern education.Experimental lesson of instrumental analysis is an important section for integrating students’theories and practices,in view of the characteristics of traditional Chinese medicine major and instrumental analysis lesson,this lesson orientates opening up students’innovative thinking,explores the way of improving students’innovative ability in an all-around way through reforming the experimental teaching of instrumental analysis according to the teaching objectives.

Elemental Analysis of Air Suspended Particles in Rasht City Using Instrumental Neutron Activation Analysis

Instrumental neutron activation analysis （INAA） has turned out to be particularly useful in the analysis of suspended particles. This work describes the INAA characterization of air particulate matter collected in Rasht city, Iran. The particulate matter was collected in two sampling sites for elemental analysis in the period of winter-summer 2009. Samples have been transferred to the environmental laboratory of radiation applications research school. Neutron exposures were performed in Tehran Research Reactor, and measurements were carried out using HPGe detectors coupled to gamma ray spectrometer. In these filter samples, the elements, AI, As, Ba, Br, Ca, CI, Co, Cr, Cu, Fe, Hg, K, La, Mg, Mn, Na, Sb, Sc, Ti, V and Zn were determined using different irradiation and counting protocols. Results show that mean concentration of most air-pollutants in Rasht are lower than those measured in other cities in Iran （Tehran, Shiraz, Isfahan）. Collected data were also compared with reported results for other cities in the world.

Assessment of some chemical element contents in Traganum nudatum Del shrub using instrumental neutron activation analysis

Instrumental neutron activation analysis(INAA)has been used to determine some chemical element contents(K,Ca,Na,Fe,Zn,Co,Eu,Sb,and Sc)in Traganum nudatum Del(Chenopodiaceae family)consumed in North African rangelands by sheep livestock.Samples were collected from the area of Djelfa in an arid steppe of Algeria.Results show that pasture halophyte had sufficient levels of K,Ca,Zn,and Co to meet the requirements of ruminants.However,it seems that this halophyte shrub had substantial amounts of Na,higher than the critical level established by the National Research Council(NRC).Eu,Sb,and Sc were within the safety baseline of all the assayed elements recommended by the NRC.The high Na content(～10 g/kg)in this halophytic species requires elevated intake of water by livestock.

DEVELOPMENT OF VIRTUAL INSTRUMENT IN CHARACTERISTIC ANALYSIS OF ROTATING MACHINERY BASED ON INSTANTANEOUS FREQUENCY ESTIMATION

Based on the recently quick-developing time-frequency analysis (TFA)technique and virtual instrument (VI) technique, a virtual instrument in characteristic analysis ofrotating machinery is researched and developed successfully. By utilizing instantaneous frequencyestimation (IFE) theoretics of TFA technique, and based on IFE of peak searching on thetime-frequency spectrum, order analysis (OA) functions is put forward and implemented, such as orderspectrum, order spectrum matrix, order tracking, order tracking filtering, and order componentextraction, etc. Unlike the home and abroad existing popular characteristic analyzers, which needkey phasing devices such as shaft encoder, phase-locked loop (PLL), phase-locked multiple frequency,tachometer, etc, to implement constant angle sampling directly or indirectly, whereas thisinstrument only uses the vibration signal of rotating machinery to carry out OA. This instrumentmakes up the shortage of these traditional instruments in analyzing the non-stationary signal ofrun-up and run-down process of rotating machinery. Therefore, it is a great breakthrough for theexisting order analyzers.

THEORY AND APPLICATION OF WAVELET ANALYSIS INSTRUMENT LIBRARY

Some new theory and algorithms on wavelet analysis are proposed, including continuous wavelet transform （CWT）, discrete wavelet transform （DWT）, wavelet package transform （WPT）, wavelet denosing and mother wavelet selection, etc. Using the component-based hierarchy mode, the platform for virtual instrument （VI） is constructed, and the functions such as data sampling, data analysis and data present, etc are provided. Subsequently, the wavelet analysis library is designed and developed. The library consists of expert system, experienced database, development platform and abundant wavelet analysis functional module, which together implement general and special wavelet analysis in the field of mechanical engineering, energy source, transportation and biomedicine, etc. Finally, the wavelet analysis virtual instrument library is applied to detect fault called engine knock. Experimental result indicates that the wavelet analysis virtual instrument library can efficiently solve the engineering problem such as detecting engine knock.

RESEARCH OF WAVELET TRANSFORM INSTRUMENT SYSTEM FOR SIGNAL ANALYSIS

After brief describing the Principle of wavelet transform (WT) of signals, a new signals analysis system based on wavelet transform is introduced. The design and development of the instryment of wavelet transform are described. A number of practical uses of this system demonstrate that wavelet transform system is specially functional in identifying and processing impulse, singular and non-smooth signals, so that it should be evaluated the most advanced signal analyzing system.

Structural optimization of precision instruments through modal analysis

In order to improve the dynamic stability of precision instruments during the design process, a compositive design method based on modal analysis of structure is proposed. With uniform boundary conditions and material characters, the results of Finite Element Analysis (FEA) vary with models. It should be checked whether the model is correctly simplified. Modal experiments can be used for such purpose. The method combines the high efficiency and agility of FEA with the reliability and accuracy of experiments, and avoids the drawbacks of FEA or experiments, such as uncertainty of FEA and high cost of experiments. Taking rotor frame structure as an example, this method is applied as follows: First the modal characters of structure are analyzed with FEA, and then the natural frequencies of the structure are tested by experiments to check the reliability of FEA method, and finally the design scheme is optimized by modifying structure parameters with confirmed FEA.

Dynamic Hypergraph Modeling and Robustness Analysis for SIoT

The Social Internet of Things(SIoT)integrates the Internet of Things(IoT)and social networks,taking into account the social attributes of objects and diversifying the relationship between humans and objects,which overcomes the limitations of the IoT’s focus on associations between objects.Artificial Intelligence(AI)technology is rapidly evolving.It is critical to build trustworthy and transparent systems,especially with system security issues coming to the surface.This paper emphasizes the social attributes of objects and uses hypergraphs to model the diverse entities and relationships in SIoT,aiming to build an SIoT hypergraph generation model to explore the complex interactions between entities in the context of intelligent SIoT.Current hypergraph generation models impose too many constraints and fail to capture more details of real hypernetworks.In contrast,this paper proposes a hypergraph generation model that evolves dynamically over time,where only the number of nodes is fixed.It combines node wandering with a forest fire model and uses two different methods to control the size of the hyperedges.As new nodes are added,the model can promptly reflect changes in entities and relationships within SIoT.Experimental results exhibit that our model can effectively replicate the topological structure of real-world hypernetworks.We also evaluate the vulnerability of the hypergraph under different attack strategies,which provides theoretical support for building a more robust intelligent SIoT hypergraph model and lays the foundation for building safer and more reliable systems in the future.

Large-Scale Carbon Dioxide Storage in Salt Caverns:Evaluation of Operation,Safety,and Potential in China

Underground salt cavern CO_(2) storage(SCCS)offers the dual benefits of enabling extensive CO_(2) storage and facilitating the utilization of CO_(2) resources while contributing the regulation of the carbon market.Its economic and operational advantages over traditional carbon capture,utilization,and storage(CCUS)projects make SCCS a more cost-effective and flexible option.Despite the widespread use of salt caverns for storing various substances,differences exist between SCCS and traditional salt cavern energy storage in terms of gas-tightness,carbon injection,brine extraction control,long-term carbon storage stability,and site selection criteria.These distinctions stem from the unique phase change characteristics of CO_(2) and the application scenarios of SCCS.Therefore,targeted and forward-looking scientific research on SCCS is imperative.This paper introduces the implementation principles and application scenarios of SCCS,emphasizing its connections with carbon emissions,carbon utilization,and renewable energy peak shaving.It delves into the operational characteristics and economic advantages of SCCS compared with other CCUS methods,and addresses associated scientific challenges.In this paper,we establish a pressure equation for carbon injection and brine extraction,that considers the phase change characteristics of CO_(2),and we analyze the pressure during carbon injection.By comparing the viscosities of CO_(2) and other gases,SCCS’s excellent sealing performance is demonstrated.Building on this,we develop a long-term stability evaluation model and associated indices,which analyze the impact of the injection speed and minimum operating pressure on stability.Field countermeasures to ensure stability are proposed.Site selection criteria for SCCS are established,preliminary salt mine sites suitable for SCCS are identified in China,and an initial estimate of achievable carbon storage scale in China is made at over 51.8-77.7 million tons,utilizing only 20%-30%volume of abandoned salt caverns.This paper addresses key scientific and engineering challenges facing SCCS and determines crucial technical parameters,such as the operating pressure,burial depth,and storage scale,and it offers essential guidance for implementing SCCS projects in China.

Large-scale spatial data visualization method based on augmented reality

Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.

Analysis of optical axis deviation caused by structural stiffness in equatorial telescopes

The impact of structural stiffness on optical axis deviation poses a significant challenge in the design of equatorial telescope structures.A comprehensive analysis during the design process can reduce the reliance of a telescope on advanced control technologies,thereby improving its economic feasibility.Although full-system finite element analyses are reliable,they are encumbered by significant time requirements and limitations in covering all possible telescope orientations.Therefore,we propose an efficient and comprehensive analytical method to evaluate the optical axis deviation of equatorial telescopes across a full range of angles.To address the challenge of ensuring that the analysis covers all possible positions of an equatorial telescope,based on a model from SiTian project,we analyze the optical axis deviations caused by the fork arm at 25 different angles and then use fitting methods to obtain results for all angles.Based on the analysis results of the optical axis deviation caused by the stiffness of the optical tube in the horizontal position,we derive the results for the tube at any position using geometric relationships.Finally,we calculate the coupling factors and combine these impacts.Furthermore,we identify six discrete feature points to reflect possible telescope orientations and conduct comprehensive finite element analyses.The results are in alignment with those acquired through a comprehensive computational approach.

Analysis and Design of Surgical Instrument Localization Algorithm

With the help of surgical navigation system,doctors can operate on patients more intuitively and accurately.The positioning accuracy and real-time performance of surgical instruments are very important to the whole system.In this paper,we analyze and design the detection algorithm of surgical instrument location mark,and estimate the posture of surgical instrument.In addition,we optimized the pose by remapping.Finally,the algorithm of location mark detection proposed in this paper and the posture analysis data of surgical instruments are verified and analyzed through experiments.The final result shows a high accuracy.