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In recent years, China has frequently experienced extreme climate events. Analyzing the trends in these extreme weather changes is crucial to mitigating the adverse impacts on human lives and preventing the disruption of water resource distribution. Based on the daily maximum and daily minimum temperatures at 139 meteorological grid points in the Liaohe River Basin from 1961 to 2020, six extreme temperature indices were calculated and selected to explore the temporal and spatial characteristics of the extreme temperature events in the Liaohe River Basin by using the linear trend analysis, the Mann-Kendall (M-K) mutation test, and the Kriging interpolation method. The results show that the index characterizing extreme warm events in the Liaohe River Basin in time shows a significant upward trend on both interannual and seasonal scales, while the index characterizing extreme cold events shows a significant downward trend. The mutation points of interannual changes were mainly distributed between 1980 and 2010. In the spatial distribution, the Liaohe River Basin as a whole is warming, and the northern part is warming more than the southern part.

Due to the influence of global climate change and human activities, the time series data of river runoff become complex and non-stationary. These properties make sequence prediction difficult and with low accuracy. In order to improve the prediction accuracy, Empirical Mode Decomposition (EMD) was introduced to Long Short-Term Memory (LSTM) networks in this paper. The EMD decomposed a non-stationary time series into multiple components. We trained an LSTM network for each component, and added their predictions to obtain the final forecasting value of original sequence. At last, the EMD-LSTM model was applied to the annual runoff sequence in the upper Heihe River. By comparing with single LSTM, it shows that the EMD-LSTM has higher accuracy for the long-term prediction of river runoff.

As the primary territories of regional carbon emission and energy consumption, most industrial parks only simply stack technology and policy under the urgent goal of emission reduction and carbon reduction. As a result, certain measures may even have negative impacts. As the primary means to determine the characteristics of carbon emissions in industrial parks, studying the driving factors of carbon emissions and proposing targeted measures can effectively achieve the carbon emission reduction goals. However the mechanism analysis of driving factors of carbon emission in industrial parks is the important means to study the characteristics of carbon emission. The selection of driving factors is many and complicated, and the selection of mechanism analysis methods is different, so it is difficult to have a comparison of research results Based on the quantitative relationship model between carbon emissions and driving factors and the method of action mechanism analysis in industrial parks, this paper evaluates and compares the relevant studies, summarizes their advantages and disadvantages, and makes relevant comments and prospects. For providing reference for the practice of driving factors of carbon emission in industrial parks, and put forward the basis for the research of carbon emission prediction.

At present, China predominantly relies on a traditional energy consumption structure for meeting its energy demands. However, in response to the increasing global awareness of environmental protection, the nation has significantly accelerated its efforts to develop clean energy sources as well as promote green development in various industries. In addition, numerous traditional energy enterprises have gradually initiated efforts to transition towards clean energy solutions. This transition to clean energy is not only pivotal in curbing pollution caused by energy usage but also instrumental in achieving China’s dual carbon targets. To gain insights into the adoption of clean energy and green development by domestic enterprises, this paper takes China Petrochemical Corporation as a case study. With comprehensive research focusing on policy, market, natural resources, and social responsibility, we will not only investigate China’s homegrown policies but also juxtapose them with international counterparts. This comparative analysis aims to offer an in-depth understanding concerning the environmental challenges and potential bottlenecks faced by Chinese enterprises as they embrace clean energy and green development approaches. Furthermore, based on thorough exploration, the paper will deliver practical suggestions and recommendations for their sustainable growth and development.

Ultrasound technology in food processing holds promise in terms of energy efficiency, environmental impact, and sustainability compared to traditional processing methods. These conventional heat-based techniques, such as salting, smoking, and frying, are energy-intensive and time-consuming. Therefore, ultrasound as a promising technology has attracted the interest of scientists and stakeholders in the food processing field. This alternative solution utilizes ultrasound and can achieve similar results with reduced energy input. This not only reduces energy consumption but also contributes to reducing carbon footprint and greenhouse gas emissions. In addition, ultrasound processing technology enhances food safety and quality by inhibiting microbial growth and killing pathogens, leading to longer shelf life and reduced food waste. However, there are also present some limitations of ultrasound in food processing through dense and complex food matrices like protein. Current research and development efforts are expected to address these challenges and expand applications in food processing. Overall, ultrasonic technology could transform the sustainability of food processing in the future.

Stochastic seismic inversion is an important part of geostatistical inversion method, and is the combination of seismic inversion and sequence simulation. In the process of random seismic inversion, firstly, the histogram distribution of random variables is counted, the variation function of random variables is calculated, and the variation range of random variables in different directions is determined. Then, for each implementation, the seismic traces are synthesized at the seismic channel position according to the calculated reflection coefficient, and the error between the synthetic traces and the original seismic traces is compared, and the inversion results are output after the required accuracy is reached. Geostatistical inversion can improve the vertical and horizontal resolution of the reservoir and accurately describe the spatial distribution of the reservoir. Taking the Heidimiao oil layer in the west slope area of Daqing Placanticline as an example, this paper expounds the application of geostatistical inversion in the work area as a whole. Combined with the results of seismic attribute analysis and well logging curve preprocessing, the inversion results formed by accurate time-depth calibration and other processes of reservoir sensitivity parameter analysis provide a basis for optimizing the target well location in the work area.

Three-dimensional geological modeling is widely used in the field of geological research. A successful three-dimensional geological model is a three-dimensional anatomy and integration of the study area. Large-scale three-dimensional geological modeling is limited by software performance and technical difficulties. There are disadvantages such as unequal model splicing elements, morphological distortion and attribute incompatibility. Based on the discrete storage method of DepthInsight software, this paper explores the large-area model fusion and splicing technology to deal with various geological conditions, and carries out large-area multi-block model fusion and splicing from the aspects of element type, quantity and attribute. The large-area 3D geological modeling technology scheme of discrete storage and block splicing is realized, which provides a reference for establishing a large-area 3D geological model.

Automobile fault diagnosis is the most technical content in automobile maintenance. The speed, accuracy and convenience of diagnosis directly affect the maintenance efficiency. Automobile fault diagnosis information is an important reference for finding and solving automobile faults. High quality information is the key to improve technical personnel's judgment and solving faults. In this paper, the methods and examples of fault diagnosis information compilation are given to guide the technical data writers to compile effective fault diagnosis information for automobiles.

Small towns with agricultural characteristics are an important entry point to promote the revitalization of rural industries. Establishing leading industries according to local development conditions is crucial to the healthy and sustainable development of agricultural towns. This paper evaluates and analyzes the choice of leading industries in Yuanjue Town, Rongchang District, Chongqing by constructing a hierarchical-principal component model, and draws conclusions. The rationality of the conclusion provides a reference for the selection of leading industries in agricultural characteristic towns in Sichuan and Chongqing.

At the beginning of 2020, COVID-19 began to explode on a large scale around the world, with medical and health institutions around the world are facing great pressure. During this period, medical institutions that treat patients with COVID-19 will also generate a large amount of medical waste. If not handled properly, infectious viruses will enter the environment and cause secondary pollution and new epidemic. Wuhan was the first city to have a large-scale outbreak during the outbreak. In the early stage of the outbreak, the relevant competent departments of medical and health institutions and medical waste disposal agencies in China quickly and timely issued a series of technical guidelines and Management measures to control secondary pollution of medical waste during COVID-19. This article analysed the medical waste disposal capacity in Wuhan city, Hubei Province and China at 2020, which also introduce the medical waste treatment measures taken in China during the outbreak, hoping to provide technical reference for other countries.

Taking Yuhuang Shannan Fund Town as a typical example, this paper established a financial innovation characteristic town social benefit evaluation system through on-site investigation and quantitative analysis. It can be summarized into five major aspects: social and livelihood development, socioeconomic development, ecological environment, infrastructure construction and related system construction. Then we constructed a structural equation model (SEM) for the evaluation of social benefits of towns, and made the assumption that the impact of the five latent variables on the total variable of social benefits is positive. Through the first-order confirmatory factor analysis and the second-order confirmatory factor analysis of the structural equation, it is concluded that the five latent variables have a positively significant impact on the social benefits and have strong internal consistency. According to the degree of influence, effective suggestions are given from private equity and industrial foundation, which provide reference and practical guidance of the construction of financial innovative towns in the future.

The economic stability and sustainable development of ethnic minority autonomous regions is an important guarantee for promoting China’s economic growth and national harmony. Based on the Solow model, the economic growth factors of Enshi Tujia and Miao Autonomous Prefecture in Hubei Province (hereinafter referred to as “Enshi Prefecture of Hubei Province”) were measured and analyzed and then extended to the economic development of the entire ethnic regions in China. Through domestic and foreign comparisons, under the premise of correct understanding and analysis of the basic laws and characteristics of economic growth in ethnic areas, this paper gives appropriate economic development suggestions to promote the rapid and stable economic development of ethnic areas in China.

As the physical carrier of Energy Internet, regional integrated energy system (RIES) has become an important role for improving comprehensive energy utilization efficiency. First, a subtle thermodynamic model of buildings and water-heating network was constructed based on differential thermal inertia model. Different from the traditional single-layer wall thermal inertial model, this paper constructed multi-layer wall thermal model. Then, an optimization scheme combining electricity and heat was established. The optimization results show that, compared with the traditional single-layer wall thermal inertia model, the proposed multi-layer wall thermal inertia model has better performance. The proposed comprehensive energy optimization scheme can reduce the cost of electricity while maintaining indoor comfort, and can provide a reference for the system operation status for distribution network dispatching.

Two-dimensional (2D) Ruddlesden-Popper (RP) perovskites have emerged as a prospective candidate to address the instability issues of traditional perovskite solar cells. However, the mechanisms of charge carrier transport of 2D perovskite films obtained by the solution process still remain elusive. In this work, we proposed a novel characterization technique based on the Kelvin probe force microscopy (KPFM) to investigate the micro-scale morphology and surface potential (SP) of the BA2MA3Pb4I13 films. In additionally, a Xenon laser source was adopted to realize the in-situ scanning of the light response of the perovskite film. The obvious increase in surface potential values in the same scanning area before and after white light illumination indicated the emergence of photo-generated charge carriers. Based on the unique photophysical properties and form formation features of the hot-cast BA2MA3Pb4I13 films, we fabricated the 2D perovskite solar cells (PSCs) with an efficiency of 10.95%. As a result, the in-situ KPFM is capable to serve as an effective approach to investigating the charge carrier behaviors in the 2D perovskites for photovoltaic applications.

This paper proposes a data-driven stochastic optimal power flow model considering the uncertainties of renewable energy sources. The proposed model also focuses on the constraints of reactive voltage, aiming at improving the safety of voltage amplitude and reactive power output at each bus. Using data-driven linearization techniques, we simplified the calculation of system. In addition, Wasserstein ambiguity set was used to describe the uncertainties of renewable energy prediction error distribution, and a robust stochastic optimal power flow model considering N-1 security constraints is established. The simulation results on IEEE-39 system showed the accuracy and effectiveness of the distributionally robust optimization model and the reactive voltage constraint model provided a more stable operation schedule.

Red elemental nanoselenium was prepared by reducing sodium selenite with ascorbic acid using Arabic resin as template in this study. The factors effecting on the particle size change of nanoselenium such as reaction time, reactant concentration, template mass fraction and reaction temperature were studied. The orthogonal experiment L9(34) was designed to determine the optimal process conditions. The elemental nanoselenium was characterized by IR and particle size analyzer. The results showed that the stable red elemental selenium with nanometer scale was prepared.

In recent years, with the improvement of large-scale planting in rural areas, greenhouse cultivation technology has been developed rapidly. Intelligent monitoring and control of modern agricultural greenhouse is a hot topic at present. Based on the design requirements of modern greenhouse and the architecture of software design, this paper designs and develops the main program, data acquisition subroutine, alarm subroutine, control keystroke subroutine and display driver subroutine of the system based on the STM32F103ZET6 main control chip, and realizes the design of intelligent monitoring and control system of greenhouse, This study is of great significance for the establishment of scientific ecological environment of plants and the realization of high quality and high yield of crops.

The 20th century is marked with climate change led by global warming. So far, many models have been applied to analyze the temperature change. However, a simple but interesting model, a random walk is hardly used in his regard. In this study, we use the random walk to model the temperature in the format of random walk that is the conversion of recorded temperature and the real recorded temperature in 60 African cities including 53 capitals for the 20th century. The results show that the random walk can satisfyingly model either temperature in the format of random walk or real recorded temperature although the fitted results from other climate models are unavailable for comparison in these 60 cities. As nothing else besides random numbers is involved in this modelling, the results seem somewhat counter-intuitively.

In this study, the calcined coal gangue was mixed with Al powder at different mass fractions (5wt%〜35wt%). After being pressed at 80MPa and sintered at 1200°C for 2h, the coal gangue/Al cermet material was obtained. The phase composition, microstructure and mechanical properties of the material were studied. The results show that the main components of the prepared materials are Al, mullite, AlN, alumina and silicon. With the increase of coal gangue powder, the hardness of coal gangue/Al cermet gradually increases, while the static compression strength first increases and then decreases. When the mass fraction of gangue is 25wt%, the coal gangue/Al cermet material has the best performance. Density is 2.23g/cm3, hardness is 752HV, static compression strength is 127.3MPa.

Generation expansion planning of UHVDC plays a crucial role in optimizing resource utilization. A mixed delivery of wind, solar, and thermal power can help achieve multiple objectives such as to stabilize power supply, to raise renewable energy ratio, to reduce the wind and solar curtailment rate, while keeping the price acceptable. This paper considers 4 objectives of generation planning of UHVDC and formulates a model to simulate the operation and thus get the key indices that are used to choose from possible generation expansion planning options. We show the effect of the proposed method using a case study of the Xinjiang 3rd UHVDC channel.

The stability of the standard sample plays a key role in the testing of the smoke detectors. A scientific and effective standard sample selection scheme is proposed in this paper. The repeatability and uniformity of the tested samples are evaluated before and after the environmental acceleration testing, and the most stable standard sample is obtained. At the same time, this paper explores the new application of the standard sample, which can be used in the calibration of the measuring ionization chamber (MIC). This work can greatly reduce the selection time and provide the standard samples for the laboratory of the smoke detectors testing which is scientific and reliable. At the same time, the difficult problem of the calibration of the measuring ionization chamber (MIC) is solved here.

This article analyzes the factors affecting the nitrification and denitrification sludge granulation, including carbon source abundance, environmental pH, electron acceptors, SRT conditions, reaction temperature, etc. In this paper, the content of impurities in sewage is clarified, and the entire treatment process, COD removal, sludge denitrification and sedimentation, and sludge formation process analysis are analyzed. The purpose is to improve the application value of activated carbon and improve the treatment effect of sewage.

The current COVID-19 pandemic creates the biggest health and economic challenges to the world. However, not much knowledge is available about this coronavirus, SARS-CoV-2, because of its novelty. Indeed, it necessarily knows the fate of proteins generated by SARS-CoV-2. Anyway, before a large-scale study on proteins from SARS-CoV-2, it would be better to conduct a small-scale study on a well-known protein from influenza A viruses, because both are positive-sense RNA viruses. Thus, we applied a simple method of amino-acid pair probability to analyze 94 neuraminidases of influenza A viruses for better understanding of their fate. The results demonstrate three features of these neuraminidases: (i) the N1 neuraminidases are more susceptible to mutations, which is the current state of the neuraminidases; (ii) the N1 neuraminidases have undergone more mutations in the past, which is the history of the neuraminidases; and (iii) the N1 neuraminidases have a larger potential towards future mutations, which is the future of the neuraminidases. Moreover, our study reveals two clues on the mutation tendency, i.e. the mutations represent a degeneration process, and chickens, ducks and geese are rendered more susceptive to mutation. We hope to apply this approach to study the proteins from SARS-CoV-2 in near future.

An Energy Pile-Soil Interface Characteristic Apparatus (EPSICA) was developed to investigate the contact mechanics of the pile-soil interface. In the center of the apparatus, there is an energy pile model, around which different soil can be filled to simulate pile in different subsoil. The soil can be saturated. By applying loads on the top of the soil, the different depths were simulated. The temperature of energy piles was controlled by the cycling fluid with a water bath. The Pt100 sensors were installed in the pile and soil to measure the temperature changes. The miniature earth pressure cells were installed on the pile surface to measure the normal stress of the pile-soil interface. The FBG quasi-distributed optical fiber technology was used to measure the hoop strain to evaluate the circumferential deformation of the pile model. Taking the sand foundation as an example, the mechanical behavior of pile-soil contact behavior during the heating and cooling cycle was studied based on the temperature of pile and soil, normal stress of pile-soil interface and hoop strain of pile. The developed apparatus provides a new method for the study of thermos-mechanical behavior of energy pile.

This study is based on our iGEM (international genetically engineered machine) 2019 competition project in which an in vitro model was established to simulate the human monitoring and regulation of blood glucose level using the “liver-on-a-chip” and a genetically engineered bacterium capable of producing proinsulin efficiently. The microfluidic device is able to accommodate cellular chassis loaded with biological parts for diabetic treatment. In addition, electrochemical biosensors were designed to detect the differential glucose concentration from the both chambers of the organ chip. The model can test different chemicals and organs, when the components in the channels and cells are altered. We have thus accomplished an in vitro model of how the proinsulin generated by engineered bacteria works on liver cells. In the near future, our research paradigm will be shifted to bacterial implantation in the human intestines to replace pancreas for the automatic secretion of insulin for diabetic patients.

Electric power industry as an indispensable energy supply in daily life and production, which is the main motive force of equipment operation in the industrial times. Therefore, in order to meet the development needs and ensure the safety of power supply, it is necessary to optimize and transform the power grid. So that energy conservation and security of supply and demand can be ensured. In this paper, the short-circuit calculation and optimization design of distributed power distribution network are studied deeply, aiming at improving the performance of power grid and promoting the rapid development and transformation of power industry.

Xilin Gol is located in the north-central part of Inner Mongolia, and its western plains are extremely scarce areas of water resources.The analysis of the precipitation in Xilin Gol is of great significance to the economic development of local animal husbandry. Time series analysis and prediction have important practical application value, and scientific and accurate prediction results can provide a key guiding role for social activities. Combined with the fast Fourier transform, the empirical modal decomposition method was used to analyze the monthly precipitation data of Xilin Gol from 1961 to 2016.The results show that the time series has a period of 6 and about 22 months.And through the calculation of the contribution rate of the IMF variance, it is found that 12 months is the main cycle of the monthly precipitation of Xilin Gol,The results show that EMD can more accurately reflect the periodic characteristics of precipitation. The research results have certain practical value for the scientific and rational use of precipitation.

Copying with the increasingly severe energy crisis and air pollution, new energy vehicles will be an inexorable trend in the near future. The E-Cell electric engineering vehicles will replace conventional oil-fired ones gradually. This paper analyses the current situation and tendency of EVs in brief, explains the function of E-Cell electric engineering vehicles and its roles in maintaining grid stability, peak load shifting and 24-hour emergency rescue service for EVs. Concerning technical application, this paper primarily designs vehicle intelligent terminal systems, Battery Management System(BMS), cable charging, wireless charging and self-charging systems. Finally, this paper designs the billing modes of charging process, and accounts for billing process of vehicle intelligent terminal systems by flow chart to ensure the accuracy during charging process.

The red elemental selenoprotein was biosynthesized by active dry yeast in this study. Through a single factor experiment and L9(34)-orthogonal test fermentation condition optimization, the selenium content was 15.72 mg/g under optimal condition. The optimum culture condition was as follows: the sodium selenite concentration (0.8 mg/mL), culture time (36 h), the yeast dosage (5 g), pH (5.5), culture temperature (30°C), and the medium Baume degree (8 °Bé). The analysis of amino acid species, content and morphology of the product showed that the red elemental selenoprotein was successfully synthesized.

Computational Fluid Dynamics (CFD) technology was used to analyse dispersion effects of 3 plates of different structures during adhesives production. Three models of the dispersion plates were designed: (1) Project 1: a plate with sharp and short teeth, (2) Project 2: a plate with sharp and long teeth, (3) Project 3: a plate with blunt and long teeth. Pictures of velocity flow contours and flow trajectories in the CFD analysis were obtained to show the flow conditions inside the Reactor. Particle studies were also run to predict adhesive particles dispersion effects of these 3 kinds of plates, so that the best structure of the plate would be chosen.

This paper presents a robust adaptive nonlinear dynamic inversion control approach for the longitudinal dynamics of an air-breathing hypersonic vehicle. The proposed approach adopts a fast adaptation law using high-gain learning rate, while a low-pass filter is synthesized with the modified adaptive scheme to filter out the high-frequency content of the estimates. This modified high-gain adaptive scheme achieves a good transient process and a nice robust property with respect to parameter uncertainties, without exciting high-frequency oscillations. Based on input-output linearization, the nonlinear hypersonic dynamics are transformed into equivalent linear systems. Therefore, the pole placement technique is applied to design the baseline nonlinear dynamic inversion controller. Finally, the simulation results of the modified adaptive nonlinear dynamic inversion control law demonstrate the proposed control approach provides robust tracking of reference trajectories.

A technique for tunable filters with low insertion loss and narrow bandwidth is proposed in the form of comb-line structure. Both resonant capacitor with pin-diodes and resonant inductance in the tunable filter were analyzed and the main source of insertion loss was obtained. A series of filters with same pin-diodes, center frequency, absolute bandwidth and low return loss was simulated. The results showed that, by changing the values of the resonant capacitor and inductance, insertion loss of the filter can be greatly restricted. This technique will allow the design of tunable LC filters with low insertion loss and narrow bandwidth.

The streambed flux is variable in space; the spatial variability results in part from bedforms, but few works on streambed fluxes in channels with strongly abrupt varying bedforms are carried out. Heat as a tracer to delineate the streambed flux pattern has been widely adopted in numerous fields. In this paper, a braided channel with complicated topography was selected as study site, where the temperature was monitored. One-dimensional (1-D) analytical method based on the amplitude attenuation (Ar) and 1-D numerical method were used to interpret the temperature. As a result, streambed fluxes of a total of 50 sites in the braided channel are obtained. From the results we can know the magnitude and direction of streamed flow velocity are spatially variable, even within a 1-m distance. Then, this study summarizes five bedform-driven flux patterns: ① downward flow driven by the head difference between groundwater and stream, ② downward flow related to a meter-scale pool, ③ a transition from upward to downward flow associated with a centimeter-scale riffle, ④ horizontal flow in braided bars and ⑤ upward flow driven by vegetation roots. Overall, multiple physical mechanisms together contributed to the complex streambed flow system, which reflected great challenges for the scaling up of point-in-space seepage flux.

Residual stresses are a consequence of welding in various structures such as ships and offshore structures. Residual stresses can be relaxed or redistributed according to the load levels during operation. The elastic shakedown phenomenon can be considered as one of the reasons for this change. This paper studies the relaxation/redistribution of weld residual stress during different levels of shakedown in a butt-welded plate chosen according to ship design and welding procedures. Welding was performed on DH36, a ship structural steel. Neutron diffraction was used to measure residual stresses in these plates in the as-welded state and after different levels of shakedown. A mixed hardening model in line with the Chaboche model is determined for both weld and base material. A numerical model is developed to estimate the shakedown limit on butt-welded plate. Further, the redistribution of residual stress in a numerical weld model according to the different levels of shakedown limit is studied. Based on the shakedown limit of the butt-welded plate, a shakedown region is determined, where the structure will undergo elastic shakedown in the presence of an existing residual stress field if the maximum stress on the load section after a few initial cycles is in the shakedown region.

For hybrid indoor network scenario with LTE, WLAN and Visible Light Communication (VLC), selecting network intelligently based on user service requirement is essential for ensuring high user quality of experience. In order to tackle the challenge due to dynamic environment and complicated service requirement, we propose a reinforcement learning solution for indoor network selection. In particular, a transfer learning based network selection algorithm, i.e., reinforcement learning with knowledge transfer, is proposed by revealing and exploiting the context information about the features of traffic, networks and network load distribution. The simulations show that the proposed algorithm has an efficient online learning ability and could achieve much better performance with faster convergence speed than the traditional reinforcement learning algorithm.

Four kinds of blueberry beverage from different varieties, a total of 140 samples were acquired and analyzed by applying of spectrum technology. Using Savitzky-Golay spectral smoothing and multiplicative scatter correction (MSC) on the sample data pretreatment, four varieties of blueberry beverage were cluster analyzed by using principal component analysis method (PCA),a three-dimensional score view was achieved by the first 3 principal components of all samples (PC1, PC2 and PC3), which shows an obvious classification effect on the blueberry beverage. The first three principal components of the load diagram analysis, the characteristic bands related with the blueberry beverage varieties were 420-430nm, 490-500nm, 570-580nm and 1350-1365nm. According to the cumulative contribution rate (99.20%) of the first 6 principal components, the first 6 principal components was choosed as the input of multilayer perceptron (MLP) neural network, 100 samples in all the blueberry beverage samples were selected as a training set, and the remaining 40 samples were used as the prediction set. Training set were trained and prediction set were predicted by applying the multilayer perceptron neural network, and the correct rate of prediction were 100%.Research shows, using principal component analysis combined with multilayer perceptron neural network to identify the varieties of blueberry beverage is feasible.

The simulation technology of the nuclear power plant are gradually applying to the nuclear power industry. However, most of the research on nuclear power plant simulation system only focus on pure computerized simulation at present, and it is difficult to fully display the characteristics of the simulating objects. In order to simulate the response characteristics of control system more really, a hardware-in-loop simulation platform of main control systems in the nuclear power plant has been developed in this paper. This simulation platform consists of thermal-hydraulic model, control and protection system model, physical DCS system and real-time interactive database. A physical industrial DCS system has been coupled to this platform to simulate the main control systems in the NPP, which makes the simulation result much closer to the actual control systems. The devoloped simulation platform has been validated by some steady and transient cases in this paper. This hardware-in-loop simulation platform can be used in the simulation and optimal design of NPP control systems. Furthermore, it can be used in the failure mode and effect analysis of the instrumentation and control systems in the nuclear power plant.

Based on analyzing SIROX the tobacco expander of its pitfalls on cleaning system like poor drainage, valve leakage, cleaning time consuming, etc., this article proposes an improvement of its cleaning system as well as an optimization of its control mode. Furthermore, this article presents a new design of automatic drainage system of the cleaning pipe as well as a real- time monitoring system. This set of system not only addresses quality issues like the over temperature of cylinder wall of the tobacco dryer and the abnormal fluctuation of the tobacco moisture after dryer, but also visualizes the valve leakage thus helps to improve the prompt maintenance of these devices. Observing the two-year operation in HCF, this system proves a high application value.

With the rapid development of Internet and gradual enriched multimedia services, diversified needs of internet services are put forward. At the same time, people’s requirements on quality of service are more stringent, traditional QoE only considers the evaluation method of network quality has not fully response service quality. At present, many research study association model of QoE and QoS only for single network and service. In this paper, a correlation model of mixed service integration network based on the environment is proposed.

In order to reduce the secondary damage of melon gum fracturing fluid for the low permeability alkali sensitivity reservoir, Optimized a kind of low molecular weight polymer fracturing fluid, and solve the technical problem of crosslinking time is not easy to control, fracturing fluid gel breaking difficult in low temperature. Through the study of the optimization of main additives, The fracturing fluid use low molecular highly active three yuan low molecular polymer as a thickener, which use of special synthetic process of polymerization with multiple active node. Its molecular weight is 200000 ~ 300000, water soluble speed is fast, site preparation easy, and thickening ability is strong. When the concentration is 0.2% ~ 0.6% in the fracturing fluid ,it can satisfy the requirement of fracturing operation. With organic zirconium and aldehyde compounds as crosslinking agent, The fracturing fluid have been achieved in good results in erlian uli of north China oilfield, ordos basin yishan slope of oil well and gas well fracturing.

It is established the ram biomass straw machine as the analysis object in this paper,the molding machine cones of stress in the forming process of the analysis of the system. We used pottery instead of Wear-resistant cast iron for improving the performance of forming sleeve. The structure of the forming sleeve was analyzed with the mechanical module of a soft named Pro/engineer in this paper. The result indicated that the program was feasible. With the sensitivity analysis we identified the suitable angle for the sleeve.

As people’s living standard improves, they are increasingly concerned with health, and researches on various kinds of sports apparatus are also growing, such as the fitness simulation horse. In this paper, we first described the advantages of the fitness simulation horse to the human body; then designed a fitness simulation horse platform with a new orthogonal parallel mechanism; set up the control system of fitness simulation horse in an open structure; established a control model of fitness simulation horse, a structure model for branched-chain control and a controller model based on the kinematics; validated these models in simulation experiments; and last made a prospect on future development.

Due to the fact that the dynamic medical material distribution is vital to the quick response to urgent demand when the Ebola virus occurs, the optimal distribution approach is explored according to the Ebola virus diffusion rule and different severity of the epidemic. First, we choose the more serious epidemic state of Sierra Leone in West Africa as the research object and the SIQR (susceptible, infected, quarantined, required) epidemic model with pulse vaccination is introduced to describe the Ebola diffusion rule and obtain the demanded vaccine and drug in each pulse. Based on the SIQR model, thirteen areas in Sierra Leone are classified into three emergency levels by clustering analysis. Then a dynamic medical material distribution model is formulated, with goals of both reducing the transportation cost and shortages. The results indicate that the proposed approach can make an outstanding contribution to fight against the Ebola virus.

The early phases of the rejection of xenografts exchanged between closely-related species are dominated by a vigorous humoral immune response. We have recently used a linkermediated polymerase chain reaction to generate Ig heavy and light chain specific cDNA libraries to examine the Ig gene control of a prototypic IgM monoclonal antibody, HAR-1, that causes the hyperacute rejection of hamster xenografts. Recombinant clones from the library were screened directly from bacterial colonies by PCR and the nucleic acid sequences of the clones established. Our results demonstrate that the HAR-1 hybridoma is encoded by Ig VH and JH genes in a germline configuration. Comparison of the cDNA sequence for HAR1-VH with the germline equivalent of the gene isolated from newborn LEW liver (provisionally designated VH1.1) showed that the two VH sequences share a nucleic acid identity of 99,3%. Similarly, the HAR-1 monoclonal uses a Ig JH gene that is 98,2% identical with the JH1 nucleic acid sequence available in the GenBank. The use of Ig VH and JH genes in a germline configuration is similar to that seen with polyreactive natural antibodies to infectious agents and autoantibodies. These humoral responses are thought to be the results of the stimulation of a T cell-independent subset of B cells, the B-1a/B-1b subset, that are responsible for producing antibodies that serve as a primitive humoral (natural antibody) defense mechanism against infectious diseases. Our results suggest that the humoral component of the rejection of xenografts in the hamster-to-rat model may represent the stimulation of this type of B cell antibody response by xenogeneic target antigens that share antigenic epitopes with bacteria and other infectious agents.