Spatial distribution of soil salinization under the influence of human activities in arid areas,China

The Hotan Prefecture of Xinjiang Uygur Autonomous Region,China belongs to arid desert climate,with significant soil salinization issues.The study selected six rivers in Hotan Prefecture(Pishan,Qaraqash,Yurungqash,Celle,Kriya,and Niya rivers)to explore the spatial distribution of soil salinization in this area and its underlying mechanisms.Sampling was conducted along each river's watershed,from the Gobi in the upper reaches,through the anthropogenic impact area in the middle reaches,to the desert area in the lower reaches.Soil physical-chemical indicators,including total soluble salts,pH,K+,Na+,Ca2+,Mg2+,SO42-,Cl-,CO32-,HCO3-,organic matter,available nitrogen,available phosphorus,and available potassium,were tested,along with the total dissolved solids of surface water and groundwater.The results revealed that the soil water and nutrient contents in anthropogenic impact area were higher than those in Gobi and desert areas,while the pH and total soluble salts were lower than those in Gobi and desert areas.The ions in the soil of the study area were primarily Cl-,SO42-,K+,and Na+,and the ion concentration of soil salt were positively correlated with surface water and groundwater.Overall,the study area exhibited low soil water content,low clay content,infertile soil,and high soil salinization,dominated by weak to moderate chloride-sulfate types.Compared with Gobi and desert areas,the soil in anthropogenic impact area had higher soil water content,lower pH,lower soluble salts,and higher nutrients,indicating that human farming activities help mitigate salinization.These findings have practical implications for guiding the scientific prevention and control of soil salinization in the arid areas and for promoting sustainable agricultural development.

Evaluating the Impacts of Human Activities on Diversity, Abundance, and Distribution of Large Mammals in Nimule National Park, South Sudan

Globally, human activities have a significant impact on the diversity, abundance, and distribution of large mammals in Protected Areas (PAs). These disturbances increase human pressure on biodiversity and species habitats, highlighting the need for conservation. This study aimed to assess the abundance and distribution of large mammals in different habitat types within Nimule National Park (NNP) and understand the impacts of human activities on them. Data on the abundance and distribution of large mammals and their respective habitat types were collected through line transect surveys. Human activity signs were observed and recorded along the transect lines. To estimate the impacts of human activities on the diversity, abundance, and distribution of large mammal species, as well as to identify any significant differences between them and their habitat types, the study utilized the Kruskal Wallis test, Polynomial multiple regressions, and diversity indices. The findings from the Shannon-Weiner and Simpson indices indicated that large mammal species were more diverse inside the park (H’ = 1.136;D = 0.570) compared to the buffer zone (H’ = 0.413;D = 0.171), with 85% (443 out of 510 samples) recorded within Nimule National Park. The species abundance showed a semi-balanced status (0.58). The diversity results among different habitat types revealed that large mammals were more diverse and highly distributed in both open woodlands (244) and dense woodlands (192), while riverine vegetation had the lowest diversity (8). Statistical tests demonstrated a highly significant difference at a 99% confidence interval (p-value = 0.01) between habitat types and identified species of large mammals. Additionally, the results highlighted the high abundance of Uganda kob (274), baboons (141), and warthog (57) across most habitat types, accounting for at least 75% of their distribution. The most prevalent human activities observed were cattle footprints (27%) and cattle dung (14%). Human footprints and tree cutting combined accounted for 9%, indicating the practice of livestock grazing, poaching, encroachment, and fuelwood collection by local communities. However, these activities did not appear to significantly impact the diversity, abundance, and distribution of large mammals in Nimule National Park. Therefore, it is crucial to foster shared responsibilities and engage relevant stakeholders in the management and conservation of large wildlife species. Regular community awareness programs should be implemented to cultivate a sense of ownership. Moreover, it is recommended that a comprehensive survey be conducted on the population status of all mammal species in Nimule National Park, including its surrounding Buffer Zone. Monitoring the impact of human activities on their behavior and habitats using satellite images should also be carried out at least every five to ten years.

A Combination of Residual Distribution and the Active Flux Formulations or a New Class of Schemes That Can Combine Several Writings of the Same Hyperbolic Problem:Application to the 1D Euler Equations

We show how to combine in a natural way(i.e.,without any test nor switch)the conservative and non-conservative formulations of an hyperbolic system that has a conservative form.This is inspired from two different classes of schemes:the residual distribution one(Abgrall in Commun Appl Math Comput 2(3):341–368,2020),and the active flux formulations(Eyman and Roe in 49th AIAA Aerospace Science Meeting,2011;Eyman in active flux.PhD thesis,University of Michigan,2013;Helzel et al.in J Sci Comput 80(3):35–61,2019;Barsukow in J Sci Comput 86(1):paper No.3,34,2021;Roe in J Sci Comput 73:1094–1114,2017).The solution is globally continuous,and as in the active flux method,described by a combination of point values and average values.Unlike the“classical”active flux methods,the meaning of the point-wise and cell average degrees of freedom is different,and hence follow different forms of PDEs;it is a conservative version of the cell average,and a possibly non-conservative one for the points.This new class of scheme is proved to satisfy a Lax-Wendroff-like theorem.We also develop a method to perform nonlinear stability.We illustrate the behaviour on several benchmarks,some quite challenging.

Optimal Location and Sizing of Distributed Generator via Improved Multi-Objective Particle Swarm Optimization in Active Distribution Network Considering Multi-Resource

In the framework of vigorous promotion of low-carbon power system growth as well as economic globalization,multi-resource penetration in active distribution networks has been advancing fiercely.In particular,distributed generation(DG)based on renewable energy is critical for active distribution network operation enhancement.To comprehensively analyze the accessing impact of DG in distribution networks from various parts,this paper establishes an optimal DG location and sizing planning model based on active power losses,voltage profile,pollution emissions,and the economics of DG costs as well as meteorological conditions.Subsequently,multiobjective particle swarm optimization(MOPSO)is applied to obtain the optimal Pareto front.Besides,for the sake of avoiding the influence of the subjective setting of the weight coefficient,the decisionmethod based on amodified ideal point is applied to execute a Pareto front decision.Finally,simulation tests based on IEEE33 and IEEE69 nodes are designed.The experimental results show thatMOPSO can achieve wider and more uniformPareto front distribution.In the IEEE33 node test system,power loss,and voltage deviation decreased by 52.23%,and 38.89%,respectively,while taking the economy into account.In the IEEE69 test system,the three indexes decreased by 19.67%,and 58.96%,respectively.

Blockchain-Based Power Transaction Method for Active Distribution Network

A blockchain-based power transaction method is proposed for Active Distribution Network(ADN),considering the poor security and high cost of a centralized power trading system.Firstly,the decentralized blockchain structure of the ADN power transaction is built and the transaction information is kept in blocks.Secondly,considering the transaction needs between users and power suppliers in ADN,an energy request mechanism is proposed,and the optimization objective function is designed by integrating cost aware requests and storage aware requests.Finally,the particle swarm optimization algorithm is used for multi-objective optimal search to find the power trading scheme with the minimum power purchase cost of users and the maximum power sold by power suppliers.The experimental demonstration of the proposed method based on the experimental platform shows that when the number of participants is no more than 10,the transaction delay time is 0.2 s,and the transaction cost fluctuates at 200,000 yuan,which is better than other comparison methods.

The numerical simulation and inversion fitting of radon concentration distribution in homogeneous overburden above active fault zones

Based on the convection and diffusion mechanisms of radon migration, in this paper we deduce the two-dimensional differential equation for radon transportation in the overburden above active fault zones with an unlimited extension along the strike. Making use of the finite difference method, the radon concentration distribution in the overburden above active faults is calculated and modeled. The active fault zone parameters, such as the depth and the width of the fault zone, and the value of radon concentration, can be inverted from the measured radon concentration curve. These realize quantitative interpretation for radon concentration anomalies. The inversion results are in good agreement with the actual fault zone parameters.

Combined CNN-LSTM Deep Learning Algorithms for Recognizing Human Physical Activities in Large and Distributed Manners:A Recommendation System

Recognizing human activity(HAR)from data in a smartphone sensor plays an important role in the field of health to prevent chronic diseases.Daily and weekly physical activities are recorded on the smartphone and tell the user whether he is moving well or not.Typically,smartphones and their associated sensing devices operate in distributed and unstable environments.Therefore,collecting their data and extracting useful information is a significant challenge.In this context,the aimof this paper is twofold:The first is to analyze human behavior based on the recognition of physical activities.Using the results of physical activity detection and classification,the second part aims to develop a health recommendation system to notify smartphone users about their healthy physical behavior related to their physical activities.This system is based on the calculation of calories burned by each user during physical activities.In this way,conclusions can be drawn about a person’s physical behavior by estimating the number of calories burned after evaluating data collected daily or even weekly following a series of physical workouts.To identify and classify human behavior our methodology is based on artificial intelligence models specifically deep learning techniques like Long Short-Term Memory(LSTM),stacked LSTM,and bidirectional LSTM.Since human activity data contains both spatial and temporal information,we proposed,in this paper,to use of an architecture allowing the extraction of the two types of information simultaneously.While Convolutional Neural Networks(CNN)has an architecture designed for spatial information,our idea is to combine CNN with LSTM to increase classification accuracy by taking into consideration the extraction of both spatial and temporal data.The results obtained achieved an accuracy of 96%.On the other side,the data learned by these algorithms is prone to error and uncertainty.To overcome this constraint and improve performance(96%),we proposed to use the fusion mechanisms.The last combines deep learning classifiers tomodel non-accurate and ambiguous data to obtain synthetic information to aid in decision-making.The Voting and Dempster-Shafer(DS)approaches are employed.The results showed that fused classifiers based on DS theory outperformed individual classifiers(96%)with the highest accuracy level of 98%.Also,the findings disclosed that participants engaging in physical activities are healthy,showcasing a disparity in the distribution of physical activities between men and women.

Identification and distribution of 13003 landslides in the northwest margin of Qinghai-Tibet Plateau based on human-computer interaction remote sensing interpretation

The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remains insufficiently explored concerning landslide occurrence and dispersion.With the planning and construction of the Xinjiang-Tibet Railway,a comprehensive investigation into disastrous landslides in this area is essential for effective disaster preparedness and mitigation strategies.By using the human-computer interaction interpretation approach,the authors established a landslide database encompassing 13003 landslides,collectively spanning an area of 3351.24 km^(2)(36°N-40°N,73°E-78°E).The database incorporates diverse topographical and environmental parameters,including regional elevation,slope angle,slope aspect,distance to faults,distance to roads,distance to rivers,annual precipitation,and stratum.The statistical characteristics of number and area of landslides,landslide number density(LND),and landslide area percentage(LAP)are analyzed.The authors found that a predominant concentration of landslide origins within high slope angle regions,with the highest incidence observed in intervals characterised by average slopes of 20°to 30°,maximum slope angle above 80°,along with orientations towards the north(N),northeast(NE),and southwest(SW).Additionally,elevations above 4.5 km,distance to rivers below 1 km,rainfall between 20-30 mm and 30-40 mm emerge as particularly susceptible to landslide development.The study area’s geological composition primarily comprises Mesozoic and Upper Paleozoic outcrops.Both fault and human engineering activities have different degrees of influence on landslide development.Furthermore,the significance of the landslide database,the relationship between landslide distribution and environmental factors,and the geometric and morphological characteristics of landslides are discussed.The landslide H/L ratios in the study area are mainly concentrated between 0.4 and 0.64.It means the landslides mobility in the region is relatively low,and the authors speculate that landslides in this region more possibly triggered by earthquakes or located in meizoseismal area.

Application of DSAPSO Algorithm in Distribution Network Reconfiguration with Distributed Generation

With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more complex.This complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent algorithms.Consequently,traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local optima.To tackle this issue,a more advanced particle swarm optimization algorithm is proposed.To address the varying emphases at different stages of the optimization process,a dynamic strategy is implemented to regulate the social and self-learning factors.The Metropolis criterion is introduced into the simulated annealing algorithm to occasionally accept suboptimal solutions,thereby mitigating premature convergence in the population optimization process.The inertia weight is adjusted using the logistic mapping technique to maintain a balance between the algorithm’s global and local search abilities.The incorporation of the Pareto principle involves the consideration of network losses and voltage deviations as objective functions.A fuzzy membership function is employed for selecting the results.Simulation analysis is carried out on the restructuring of the distribution network,using the IEEE-33 node system and the IEEE-69 node system as examples,in conjunction with the integration of distributed energy resources.The findings demonstrate that,in comparison to other intelligent optimization algorithms,the proposed enhanced algorithm demonstrates a shorter convergence time and effectively reduces active power losses within the network.Furthermore,it enhances the amplitude of node voltages,thereby improving the stability of distribution network operations and power supply quality.Additionally,the algorithm exhibits a high level of generality and applicability.

Distributed Active Partial Label Learning

Active learning(AL)trains a high-precision predictor model from small numbers of labeled data by iteratively annotating the most valuable data sample from an unlabeled data pool with a class label throughout the learning process.However,most current AL methods start with the premise that the labels queried at AL rounds must be free of ambiguity,which may be unrealistic in some real-world applications where only a set of candidate labels can be obtained for selected data.Besides,most of the existing AL algorithms only consider the case of centralized processing,which necessitates gathering together all the unlabeled data in one fusion center for selection.Considering that data are collected/stored at different nodes over a network in many real-world scenarios,distributed processing is chosen here.In this paper,the issue of distributed classification of partially labeled(PL)data obtained by a fully decentralized AL method is focused on,and a distributed active partial label learning(dAPLL)algorithm is proposed.Our proposed algorithm is composed of a fully decentralized sample selection strategy and a distributed partial label learning(PLL)algorithm.During the sample selection process,both the uncertainty and representativeness of the data are measured based on the global cluster centers obtained by a distributed clustering method,and the valuable samples are chosen in turn.Meanwhile,using the disambiguation-free strategy,a series of binary classification problems can be constructed,and the corresponding cost-sensitive classifiers can be cooperatively trained in a distributed manner.The experiment results conducted on several datasets demonstrate that the performance of the dAPLL algorithm is comparable to that of the corresponding centralized method and is superior to the existing active PLL(APLL)method in different parameter configurations.Besides,our proposed algorithm outperforms several current PLL methods using the random selection strategy,especially when only small amounts of data are selected to be assigned with the candidate labels.

Distribution patterns of rock mass displacement in deeply buried areas induced by active fault creep slip at engineering scale

Active fault creep slip induces deformation of rock mass buried deeply in fault zones that significantly affect the operational safety of long linear projects passing through it.Displacement distribution patterns of rock masses in active fault zones which have been investigated previously are the key design basis for such projects.Therefore,a discrete element numerical model with different fault types,slip time,dip angles,and complex geological features was established,and then the creep slip for normal,reverse,and strike-slip faults were simulated to analyze the displacement distribution in the fault rock mass.A disk rotation test system and the corresponding laboratory test method were developed for simulating rock mass displacement induced by creep slippage of faults.A series of rotation tests for softand hard-layered specimens under combined compression and torsional stress were conducted to verify the numerical results and analyze the factors influencing the displacement distribution.An S-shaped displacement distribution independent of fault dip angle was identified corresponding to reverse,normal,and strike-slip faults.The results indicated that the higher the degree of horizontal extrusion,the softer the rock mass at the fault core,and the higher the degree of displacement concentration in the fault core;about 70%of the creep slip displacement occurs within this zone under 100 years of creep slippage.

DISTRIBUTION OF ACTIVE EARTH PRESSURE OF RETAINING WALL WITH WALL MOVEMENT OF ROTATION ABOUT TOP

Based on the Coulomb's theory that the earth pressure against the back of a retaining wall is due to the thrust exerted by the sliding wedge of soil from the back of the wall to a plane which passes through the bottom edge of the wall and has an inclination equal to the angle of θ, the theoretical answers to the unit earth pressure, the resultant earth pressure and the point of application of the resultant earth pressure on a retaining wall were obtained for the wall movement mode of rotation about top. The comparisons were made among the formula presented here, the formula for the wall movement mode of translation, the Coulomb's formula and some experimental observations. It is demonstrated that the magnitudes of the resultant earth pressures for the wall movement mode of rotation about top is equal to that determined by the formula for the wall movement mode of translation and the Coulomb's theory. But the distribution of the earth pressure and the points of application of the resultant earth pressures have significant difference.

EFFECTS OF EXTERNAL DONOR ON ACTIVE CENTER DISTRIBUTION OF SUPPORTED ZIEGLER-NATTA CATALYST

The composition distribution (CD) and microisotacticity distribution (ID) of propene/1-hexene copolymer synthesized by MgCl2/DIBP/TiCl4 (DIBP: diisobutyl phthalate) were determined by fractionating the copolymers according to crystallinity and characterizing the fractions by (CNMR)-C-13. The effects of two alkoxysilane donors, triethoxyphenylsilane (PTES) and dimethoxydi-tert-butylsilane (TBMS), on CD and ID of the copolymers were compared. Three main parts in the CD diagram of each copolymer were distinguished, which were correlated to active center distribution (ACD) based on three groups of different active centers. By studying the changes in l-hexene content, microisotacticity and reactivity ratio product of three typical fractions, the effects of external donor on ACD were better elucidated. It was found that TBMS shows much stronger effects on ACD than PTES. In the former system, most fractions were produced on active centers with relatively lower r(1)r(2), higher reactivity to I-hexene, and higher stereospecificity as compared to the system without external donor. It is concluded that the observed very extensive changes in ACD are mainly resulted by the formation of new types of active centers, possibly by coordination of external donor to certain positions on the catalyst.

Study on the distribution of active centers in novel low Ti-loading MgCl2-supported Ziegler-Natta catalyst

Novel MgCl2-supported Ziegler-Natta (Z-N) catalysts prepared using a new one-pot ball milling method can effectively control the amounts of Ti-loading in the catalysts. Complex GPC data on polypropylene synthesized by these novel catalysts were analyzed using the method of fitting the molecular weight distribution (MWD) curves with a multiple Flory-Schulz function. It was found that multiple active centers exist in these novel catalysts. Detailed study of the effects of the Ti-loadings in the catalysts on the distribution of the active centers showed that the Ti-loadings in the novel MgCl2-supported Z-N catalysts might affect the proportion of each type of active centers; and might be the main factor responsible for the effect of the Ti-loadings on the microstructure, the molecular weight and molecular weight distribution width of the resultant polymer, the catalytic activity and polymerization kinetics.

Distribution of phosphorylated Elk-1 in rat brain after Y-maze active avoidance training in a temporal manner

BACKGROUND： Elk-1 mRNA distributes extensively in the neurons of mice, rat and human brains, and the Elk-1 expression may be correlated with the synaptic plasticity, learning and memory. OBJECTIVE： To observe the distribution of phosphorylated Elk-1 （pEIk-1） in whole brain of rats received Y-maze active avoidance training and the changes of pEIk-1 expression at different time points after training. DESIGN ： A randomized controlled study SETTING ： Research Room of Neurobiology, the Second Affiliated Hospital of Southern Medical University MATERIALS ： Fifty-five male clean-degree SD rats of 3-4 months old, weighing 200-250 g, were provided by the Experimental Animal Center of Southem Medical University. The rabbit anti-monoclonal pEIk-1 antibody was purchased from Cell Signal Transduction Company, and ABC kit from Vector Company. METHODS ： The experiments were carried out in the Research Room of Neurobiology, Second Affiliated Hospital of Southern Medical University from September 2004 to February 2005. ① Grouping： The rats were randomly divided into training group （n = 25）, sham-training group （n = 25） and normal control group （n = 5）, and the training and sham-training groups were observed at 0, 1, 3, 6 and 24 hours after training, which represented the five phases in the process of leaming and memory. ② Y-maze training： The rats were preconditioned in the electrical Y-maze apparatus, 20 minutes a day for 3 days continuously, and training began from the 4^th day. In the training group, the rats were trained with the combination of light and electddty. Each rat repeated for 60 times in each training, and the correct times were recorded, those correct for less than 25 times were taken as unqualified, and excluded from the training group, and supplemented by other rats in time. In the sham-training group, there was no fixed correlation between the application of light and electricity. The rats in the normal contrel group were given not any training. ③Detection of pEIk-1 expression： The rats were anesthetized after Y-maze training, brain tissue was removed to prepare coronal freezing sections, and the pEIk-1 expression was detected with routine ABC method. MATN OUTCOME MEASURES： ① Distribution of pEIk-1 immuno-positive neurons in whole brain of rats in the normal control group. ②Comparison of the expression of pEIk-1 immuno-positive neurons in whole brain at different time points after training between the training group and sham-training group. RESULTS ： All the 55 rats were involved in result analysis. ③ Distribution of pEIk-1 immuno-positive neurons in the whole brain of rats in the normal control group： Strong expressions of pEIk-1 immuno-positive neurons were observed in prefrontal lobe, granular layer of olfactory bulbs, Purkinje cell layer and granular layer of cerebellum, whole stdate cortex, temporal cortex, pre-pyriform cortex, hypothalamic supraoptic nucleus, hypothalamic paraventricular nucleus and periventricular nucleus, thalamic paraventricular nucleus, pronucleus and postnucleus of amygdala cortex, central nucleus of amygdala, medial amygdaloid nucleus, entorhinal cortex, hippocampal dentate gyros, CA1-4 regions, caudate-putamen, material division, brain stem spinal nucleus of trigeminal nerve, and superior olivary nucleus, and those in hippocampal dentate gyrus and CA1 region were the strongest.② Distribution of pEIk-1 immuno-positive neurons in the whole brain of rats at different time points after training in the training group and sham-training group： In the training group, the expressions were obviously enhanced in caudate-putamen of striatum, material division, most cortexes, hippocampal dentate gyrus, hippocampal CA regions, nucleus amygdalae, thalamic paraventricular nucleus, Purkinje cell layer of cerebellum, entorhinal cortex, hypothalamic supraoptic nucleus, hypothalamic paraventricular nucleus, and periventricular nucleus at 0 hour after training, and the enhancement lasted for 6 hours at least, and those at 24 hours were decreased to normal. In the sham-training group, obvious enhanced expressions of pEIk-1 immuno-positive neurons could be observed in most cortexes, nucleus amygdalae, entorhinal cortex, hypothalamic supraoptic nucleus, hypothalamic paraventdoular nucleus and periventricular nucleus, brain stem spinal nucleus of trigeminal nerve, Purkinje cell layer and granular layer of cerebellum at O, 1, 3 and 6 hours, and decreased to normal after 24 hours. The expressions in material division, caudate-putamen of striatum, hippocampus were not obviously enhanced as compared with those in the normal control group, but significantly different from those in the training group （0, 1, 3, 6 hours after training, material division： F= 0.576, 0.023, 0.116, 8.873, P〈 0.01; caudate-putamen： F= 0.157, 0.427, 0.030, 0.001, P〈 0.01; hippocampus： F= 6.716, 2.405, 14.137, 1.416, P 〈 0.05-0.01 ）. CONCLUSION： The expression of activated pEIk-1 can be detected in the learning related brain areas under normal status, and the perk-1 expression in the brain areas dynamically changed in a time-dependent manner after Y-maze training, and it is indicated that pEIk-1 is involved in the learning and memory process in Y-maze related brain areas.

DEPENDENCE OF THE DISTRIBUTION OF ACTIVE CENTERS ON MONOMER IN SUPPORTED ZIEGLER-NATTA CATALYSTS

Distribution of active centers(ACD)of ethylene or 1-hexene homopolymerization and ethylene-1-hexene copolymerization with a MgCl_2/TiCl_4 type Z-N catalyst were studied by deconvolution of the polymer molecular weight distribution into multiple Flory components.Each Flory component is thought to be formed by a certain type of active center. ACD of ethylene-1-hexene copolymer with very low 1-hexene incorporation was compared with that of ethylene homopolymer to see the effect of introducingα-olefin on ethyle...

Method for Determination of Optimal Installed Capacity of Renewable Sources of Energy by the Criterion of Minimum Losses of Active Power in Distribution System

New method for determination of optimal placement and value of installed capacity of renewable source of energy (RES) by the criterion of minimum losses of active power, that allows taking into consideration the dependence of RES on natural conditions of region, schedule of energy supply, parameters and configuration of distribution network is suggested in the paper. Results of computations of test scheme confirm the efficiency of the proposed method and its simplicity as compared with the methods considered in literature sources.

Power Distribution Strategy Considering Active Power Loss for DFIGs Wind Farm

With the development of concentrated wind power areas, new energy’s dispatching problems are more prominent with its fast expansion. However, we can maximize the utilization of wind power under power curtailment conditions by optimal wind power dispatching. The paper studies on the basic theories of wind power turbines, and analyses the power’s control and output characteristics of wind turbine, which analyses the double-fed inductor generator’s excellent decoupling control of power and its excellent reactive power output capability. By studying the characteristics of wind power output, this paper provides a strategy for optimal dispatch in wind power generation. The calculation results show that the total active and reactive power output of the wind farm match the request of dispatch center. And the total active loss and total reactive loss is the least in the meantime.

Particle swarm optimization algorithm for simultaneous optimal placement and sizing of shunt active power conditioner(APC)and shunt capacitor in harmonic distorted distribution system

Due to development of distribution systems and increase in electricity demand,the use of capacitor banks increases.From the other point of view,nonlinear loads generate and inject considerable harmonic currents into power system.Under this condition if capacitor banks are not properly selected and placed in the power system,they could amplify and propagate these harmonics and deteriorate power quality to unacceptable levels.With attention of disadvantages of passive filters,such as occurring resonance,nowadays the usage of this type of harmonic compensator is restricted.On the other side,one of parallel multi-function compensating devices which are recently used in distribution system to mitigate voltage sag and harmonic distortion,performs power factor correction,and improves the overall power quality as active power conditioner(APC).Therefore,the utilization of APC in harmonic distorted system can affect and change the optimal location and size of shunt capacitor bank under harmonic distortion condition.This paper presents an optimization algorithm for improvement of power quality using simultaneous optimal placement and sizing of APC and shunt capacitor banks in radial distribution networks in the presence of voltage and current harmonics.The algorithm is based on particle swarm optimization(PSO).The objective function includes the cost of power losses,energy losses and those of the capacitor banks and APCs.

Radioactive Element Distribution Characteristics of Red Mud based Field Road Cement before and after Hydration

Red mud was firstly used as a raw material in sintering field road cement. Then, the radioactive element distribution characteristics of red mud based field road cement（RFC） before and after hydration were comparatively investigated. The experimental results indicated that the specific activity of ^（226）Ra and ^（232）Th increased after sintering process from raw material to clinker, as a result of concentrating effect on ^（226）Ra and ^（232）Th during sintering process, but the specific activity of ^（40）K decreased after sintering process as a result of volatilization effect. Radionuclide ^（226）Ra mainly distributed in RFC silicate phases（C_xS）, ^（232）Th distributed more in RFC interstitial phases than RFC silicate phases（C_xS）, ^（40）K mainly distributed in RFC interstitial phases. With increasing hydration ages of RFC pastes, the specific activity of ^（226）Ra kept increasing, ^（232）Th remained consistency all the same and ^（40）K declined. The radioactivity of RFC was in the recommended safe limit of Chinese National Standards GB6566-2010 during its preparation and application process.