Stability Enhancement of Small-Scale Power Grid with Renewable Power Sources by Variable Speed Diesel Power Plant

This paper proposes a power control method to improve a stability of a small-scale power grid with renewable energy sources. In an isolated small- scale power grid such as an island, diesel power plant is main power source which has an environmental burden and expensive running cost due to high priced fossil fuel. Thus, expanding installation of the renewable energy sources such as a wind power is strongly desirable. Such fluctuating energy sources, however, harm power quality of the small-scale power grid, and in addition, conventional power plant in the small-scale power grid cannot, in general, stabilize the grid system with such fluctuating power sources. In this study, Variable Speed Doubly-Fed Induction Generator (VS-DFIG) is proposed to be in-stalled at a diesel power plant instead of a conventional Fixed Speed Synchronous Generator (FS-SG), because quick control of a power balance in the small-scale power grid can be achieved by using the inertial energy of VS-DFIG. In addition, utilization of a Battery Energy Storage System (BESS) is also considered to assist cooperatively the VS-DFIG control. As a result of the simulation analysis by using the proposed method, it is verified that frequency fluctuations due to renewable energy source can be effectively reduced by quick power control of the VS-DFIG compared to the conventional FS-SG, and further control ability can be obtained by utilizing BESS. Moreover, the transient stability of a small-scale power grid during a grid fault can also be enhanced.

Complex Research of Using Microwave in Processing Grains and Plants Materials for Agriculture

It is observed contamination and subsequent growth of various types of mycotoxins in the production and processing of grain and non-grain crops. The contamination of grain and non-grain cereals crops harvest was analyzed. The aim of this research is using of microwave energy to disinfect grains of harvest and giving new properties to the grains and plants materials. The author has presented researches of the grains disinfection, during seedbed preparation and post processing. Rational parameters of heating rates of different biological objects were identified, revealed their dependence and impact on infection pathogens, through using of microwave energy technology. The author found a reduction of the number of pathogenic microbes and organisms at the various stages of processing agricultural products during using of microwave energy, and found new qualitative indicators of the products properties.

Comparison of Risk Assessment for a Nuclear Power Plant Construction Project Based on Analytic Hierarchy Process and Fuzzy Analytic Hierarchy Process

Recently, plant construction throughout the world, including nuclear power plant construction, has grown significantly. The scale of Korea’s nuclear power plant construction in particular, has increased gradually since it won a contract for a nuclear power plant construction project in the United Arab Emirates in 2009. However, time and monetary resources have been lost in some nuclear power plant construction sites due to lack of risk management ability. The need to prevent losses at nuclear power plant construction sites has become more urgent because it demands professional skills and large-scale resources. Therefore, in this study, the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (FAHP) were applied in order to make comparisons between decision-making methods, to assess the potential risks at nuclear power plant construction sites. To suggest the appropriate choice between two decision-making methods, a survey was carried out. From the results, the importance and the priority of 24 risk factors, classified by process, cost, safety, and quality, were analyzed. The FAHP was identified as a suitable method for risk assessment of nuclear power plant construction, compared with risk assessment using the AHP. These risk factors will be able to serve as baseline data for risk management in nuclear power plant construction projects.

Effect of high-or low-speed fluctuations on the small-scale bursting events in an active control experiment

Active control of a fully developed turbulence boundary layer(TBL) over a flat plate has been investigated with a statistical view. The piezoelectric(PZT) oscillator is employed to produce periodic input into the inner region of the TBL.A wall probe is fixed upstream of the oscillator to identify the high-or low-speed fluctuations as the detecting signals.Then, the impact of the detecting signals on the small-scale bursting process is investigated based on the data acquired by the traversing probe downstream of the oscillator. The results indicate that the small-scale bursting intensity is restrained more apparently at high-speed detecting fluctuations but less impacted at low-speed detecting fluctuations. Furthermore, the perturbed-scale fluctuations arrange the small-scale bursting process in the near-wall region. The detecting signals have an obvious impact on this arrangement, especially the high-intensity regions of the small-scale bursting events: the vibration enhances the intensity at high-speed detecting signals but weakens it at low-speed detecting signals in these regions, which gives a direct evidence on how detecting signals interfering the small-scale bursting process.

A Comparative Study of Flavonoid Water-Ethanol Extraction Process in Planted Trollius Chinensis

With rutin standard sample as the comparison, flavonoid extraction rate as an indicator, UV-2450 ultraviolet visible light spectrophotometer to measure flavonoid content in planted Trollius chinensis through orthogonal experiment, this experiment optimizes process condition of flavonoid in Trollius chinensis through water extraction and ethanol extraction. The result shows that flavonoid extraction rate of Trollius chinensis through ethanol extraction method is obviously higher than water extraction, and the optimal extraction process condition is： ethanol concentration is 75%, extraction time is 90min, extraction times are 3, and fluid material ratio is 20：1.

Using a Modified Soil-Plant-Atmosphere Scheme(MSPAS)to Simulate the Interaction between Land Surface Processes and Atmospheric Boundary Layer in Semi-Arid Regions

This paper uses a Modified Soil-Plant-Atmosphere Scheme (MSPAS) to study the interaction between land surface and atmospheric boundary layer processes. The scheme is composed of two main parts: atmospheric boundary layer processes and land surface processes. Compared with SiB and BATS, which are famous for their detailed parameterizations of physical variables, this simplified model is more convenient and saves much more computation time. Though simple, the feasibility of the model is well proved in this paper. The numerical simulation results from MSPAS show good agreement with reality. The scheme is used to obtain reasonable simulations for diurnal variations of heat balance, potential temperature of boundary layer, and wind field, and spatial distributions of temperature, specific humidity, vertical velocity, turbulence kinetic energy, and turbulence exchange coefficient over desert and oasis. In addition, MSPAS is used to simulate the interaction between desert and oasis at night, and again it obtains reasonable results. This indicates that MSPAS can be used to study the interaction between land surface processes and the atmospheric boundary layer over various underlying surfaces and can be extended for regional climate and numerical weather prediction study.

PlantScape Process系统在电站中的开发与应用

通过对PlantScape Process系统在电站的开发与应用的情况,与传统PLC和μXL系统相比,具有着更优越的开发和控制环境,功能更强大。

A Review for Model Plant Mismatch Measures in Process Monitoring

Model is usually necessary for the design of a control loop. Due to simplification and unknown dynamics, model plant mismatch is inevitable in the control loop. In process monitoring, detection of mismatch and evaluation of its influences are demanded. In this paper several mismatch measures are presented based on different model descriptions. They are categorized into different groups from different perspectives and their potential in detection and diagnosis is evaluated. Two case studies on mixing process and distillation process demonstrate the efficacy of the framework of mismatch monitoring.

Co-management of small-scale fishery in the Tonle Sap Lake,Cambodia

In Cambodia,fishery co-management is an important process to transfer authority and ownership to the communities along the Tonle Sap Lake to manage fishery.This paper aims to determine why the co-management of small-scale fishery has not been implemented satisfactorily in the Tonle Sap Lake of Cambodia.The research was primarily based on a household survey among 404 house-holds for quantitative data,equally divided between the Cham(202 households)and Khmer(202 households).Participatory process was also applied to collect qualitative data from key stake-holders.We found that limited interaction among the involved stakeholders,i.e.,unequal distribution of authority and resources co-management,has impeded implementation.The engagement of fisherfolk was influenced by dependence on fishery,law enforcement,and events organized by the communities.While the Khmer had better opportunities to participate in planning at the provincial and district levels,the Cham were only engaged in local development activities initiated by their people.However,the latter evinced a higher rate of satisfaction due to their access tofishery resources and to a large quantity of fishing gear.In the future,efforts should be made to:(1)improve resource and authority sharing among all key stakeholders;(2)urgently resolve issues pertinent to capacity building,insufficient budgets for commune councils(CoCs)and community fishery(CFi);and(3)urge law enforcement regarding illegal fishing.

Techniques and Technological Aspects of Palm Oil (Elaeis guineensis) Processing in Cameroon

Crude palm Oil (CPO) processing is very popular in African Countries. In Cameroon, various actors are involved ranging from agro-industrial complexes to traditional processing by smallholders who use very inefficient equipment and thus have low oil extraction rates. Small-scale processing by smallholders dates back to the early 1980s and has witnessed a lot of changes as a result of new actors in the sector, changing technologies and to an extent, government policies. This paper attempts a review of the origins and evolution of small-scale palm oil processing using intermediate technology, highlighting its importance to both the farmer and the national economy. An attempt is made to look into the future of this activity, with proposals for its consolidation.

The meat of the matter: plant-based meat analogue versus traditional meat product nutritional quality

Plant-based meat analogues(PBMA)are formulated to mimic the sensory characteristics of traditional meat products(TMP)using vegetarian ingredients and are increasingly popular with the trend towards plantbased diets,even among meat-eating consumers.This narrative review compared the nutritional quality of PBMA and TMP to broaden the discussion on the suitability of simulated meat products to substitute TMP,while exploring other attributes for their comparison.The complexity of PBMA and TMP means they are not entirely interchangeable.Importantly,PBMA health effects extend beyond their basic nutrient content and quality.Postprandial metabolism and satiety,for example,can be affected by product formulation,ingredient interactions,and thermomechanical processing involved in producing organoleptically acceptable PBMA.There are specific opportunities for low-sodium PBMA products to contribute to a healthy shift toward plantbased diets.In conclusion,PBMA cannot be assumed to be healthier than TMP.They should be designed with comprehensive consideration of composition and processing to ensure they support consumers who are adopting plant-based diets in realizing the theoretical health benefits.

AI-Driven Pattern Recognition in Medicinal Plants: A Comprehensive Review and Comparative Analysis

The pharmaceutical industry increasingly values medicinal plants due to their perceived safety and costeffectiveness compared to modern drugs.Throughout the extensive history of medicinal plant usage,various plant parts,including flowers,leaves,and roots,have been acknowledged for their healing properties and employed in plant identification.Leaf images,however,stand out as the preferred and easily accessible source of information.Manual plant identification by plant taxonomists is intricate,time-consuming,and prone to errors,relying heavily on human perception.Artificial intelligence(AI)techniques offer a solution by automating plant recognition processes.This study thoroughly examines cutting-edge AI approaches for leaf image-based plant identification,drawing insights from literature across renowned repositories.This paper critically summarizes relevant literature based on AI algorithms,extracted features,and results achieved.Additionally,it analyzes extensively used datasets in automated plant classification research.It also offers deep insights into implemented techniques and methods employed for medicinal plant recognition.Moreover,this rigorous review study discusses opportunities and challenges in employing these AI-based approaches.Furthermore,in-depth statistical findings and lessons learned from this survey are highlighted with novel research areas with the aim of offering insights to the readers and motivating new research directions.This review is expected to serve as a foundational resource for future researchers in the field of AI-based identification of medicinal plants.

Considerations on FGD in Coal-Fired Power Plants

Aiming at issues on flue gas des-ulfurization facing coal-fired power plants inChina, such as process selection, whetheradopting flue gas desulfurization (FGD) or not,qualification of flue gas desulfurization en-gineering company, the localization of technicalequipment, charge for SO2 emission andnormalized management, this article makes acomprehensive analysis and puts forwardconstructive suggestions. These will providesome references for those being engaged in fluegas desulfurization in coal-fired power plants.[

基于EM-Plant的中小型汽车焊装生产线仿真模拟研究

根据汽车整体加工工位的布置特点,以及工人加工时间的安排,建立汽车加工的数学模型,重组加工工位。在以EM-Plant为平台的基础上,采用离散事件控制的仿真方法,对汽车车身组装加工进行仿真,分析加工过程的瓶颈问题,找出提高汽车焊装生产线生产率的方法。

完整性视角下城市工业遗产价值评价研究

从工业遗产完整性的角度出发,关注其历史、文化和科学技术价值等方面的评价与保护现状,强调了在保护工业遗产的过程中需注重整体工艺流程设备、建构筑物以及由工业发展延伸出的配套设施和非物质文化的保留,使用层次分析法、模糊综合评价法构建评价体系对北京焦化厂工业遗存进行分级评价,通过定性与定量方法对完整性的各方面进行分析,并给出针对性建议,旨在为之后的工业遗产的价值评价与保护提供参考。

Pull the fuzes:Processing protein precursors to generate apoplastic danger signals for triggering plant immunity

The apoplast is one of the first cellular compartments outside the plasma membrane encountered by phytopathogenic microbes in the early stages of plant tissue invasion.Plants have developed sophisticated surveillance mechanisms to sense danger events at the cell surface and promptly activate immunity.However,a fine tuning of the activation of immune pathways is necessary to mount a robust and effective defense response.Several endogenous proteins and enzymes are synthesized as inactive precursors,and their post-translational processing has emerged as a critical mechanism for triggering alarms in the apoplast.In this review,we focus on the precursors of phytocytokines,cell wall remodeling enzymes,and proteases.The physiological events that convert inactive precursors into immunomodulatory active peptides or enzymes are described.This review also explores the functional synergies among phytocytokines,cell wall damage-associated molecular patterns,and remodeling,highlighting their roles in boosting extracellular immunity and reinforcing defenses against pests.

Artificial Neural Network to Predict Leaf Population Chlorophyll Content from Cotton Plant Images

Leaf population chlorophyll content in a population of crops, if obtained in a timely manner, served as a key indicator for growth management and diseases diagnosis. In this paper, a three-layer multilayer perceptron （MLP） artificial neural network （ANN） based prediction system was presented for predicting the leaf population chlorophyll content from the cotton plant images. As the training of this prediction system relied heavily on how well those leaf green pixels were separated from background noises in cotton plant images, a global thresholding algorithm and an omnidirectional scan noise filtering coupled with the hue histogram statistic method were designed for leaf green pixel extraction. With the obtained leaf green pixels, the system training was carried out by applying a back propagation algorithm. The proposed system was tested to predict the chlorophyll content from the cotton plant images. The results using the proposed system were in sound agreement with those obtained by the destructive method. The average prediction relative error for the chlorophyll density （μg cm^-2） in the 17 testing images was 8.41%.

ROS and oxidative burst:Roots in plant development

Reactive oxygen species(ROS)are widely generated in various redox reactions in plants.In earlier studies.ROS were considered toxic byproducts of aerobic metabolism.In recent years,it has become clear that ROS act as plant signaling molecules that participate in various processes such as growth and development.Several studies have elucidated the roles of ROS from seed germination to senescence.However,there is much to discover about the diverse roles of ROS as signaling molecules and their mechanisms of sensing and response.ROS may provide possible benefits to plant physiological processes by supporting cellular proliferation in cells that maintain basal levels prior to oxidative effects.Although ROS are largely perceived as either negative by-products of aerobic metabolism or makers for plant stress,elucidating the range of functions that ROS play in growth and development still require attention.

High-throughput volumetric reconstruction for 3D wheat plant architecture studies

For many tller crops,the plant archit ecture(PA),including the plant fresh weight,plant height,number of tllrs,tller angle and stem diameter,sigificantly afects the grain yield.In this study,we propose a method based on volumetric reconstruction for high-throughput three-dimensional(3D)wheat PA studies.The proposed methodology involves plant volumetric reconst ruction from multiple images,plant model processing and phenotypic parameter estimation and analysis.This study was performed on 80 Triticum aestium plants,and the results were analyzed.Comparing the automated measurements with manual measurements,the mean absolute per-centage error(MAPE)in the plant height and the plant fresh weight was 2.71%(1.08cm with an average plant height of 40.07cm)and 10.06%(1.41g with an average plant fresh weight of 14.06 g),respectively.The root mean square error(RMSE)was 137 cm and 1.79g for the plant height and plant fresh weight,respectively.The correlation cofficients were 0.95 and 0.96 for the plant height and plant fresh weight,respectively.Additionally,the proposed methodology,in-cluding plant reconstruction,model processing and trait ext raction,required only approximately 20s on average per plant using parallel computing on a graphics processing unit(GPU),dem-onstrating that the methodology would be valuable for a high-throughput phenotyping platform.