Dragonflies as an Important Aquatic Predator Insect and Their Po­tential for Control of Vectors of Different Diseases

Mosquitoes belong to order of Diptera.The main important vectors are genus Aedes,Culex and Anopheles.They transmit different agents such bacteria,viruses,and parasites.According to the latest information around 7 hundred million people around the world are suffering from mosquito-borne illness resulting over one million deaths.The main important disease transmitted by Anopheles is malaria.Other genus of mosquitoes including Aedes and Culex species transmit different arboviral disease to human.According to guideline of World Health Organization,the mina control of disease is vectors control.The main important vector control is using different insecticides.Using chemical insecticides for controlling mosquitoes is limited because they develop resistance against these insecticides.So,efforts have been made to control the mosquito vectors by eco-friendly techniques.In this research all,the relevant information regarding the topic of research is research through the internet and used in this paper.An intensive search of scientific literature was done in“PubMed”,“Web of Knowledge”,“Scopus”,“Google Scholar”,“SID”,etc Results shows that one of important environmental friendly vector control is biological control,using different predators and other microorganisms for vector and pest control.Dragonflies do eat mosquitos and serve as mosquito predators.They feed on mosquitos and reduce their number in outdoor areas.The dragonflies are scary biters,but they are dangerous to mosquitos.Worldwide results showed that dragonflies are able to control Aedes,Culex and Anopheles mosquito species.The artificial rearing of these predators and releasing for biological control is an appropriate measure for vector control worldwide.

Dragonflies in the City:Diversity of Odonates in Urban Davao,Philippines

Dragonflies are well-known group of insects because of their biological and ecological importance in a community,that is,they indicate the environmental health of an ecosystem.However,in an urban ecosystem,there are many threats that can affect the assemblages of dragonfly species such as the intensification of urbanization which contributes biodiversity loss of most dragonfly species.This study aimed to identify dragonfly species and determine the species richness,relative abundance,species diversity,evenness and effective number of dragonflies in selected areas in Davao City.Opportunistic sampling using sweep net and photo documentation were used during the study.The sampling lasted for three months from June 2017 to August 2017.A total of 962 individuals of dragonflies were observed and recorded comprising of six species of dragonflies from six different genera of one family.Orthethrum sabina was the most abundant among the six species recorded in all sampling sites.The species richness was six.Low species diversity was obtained in all sampling which shows that the sites were not evenly distributed and indicating that the study sites were not diverse in terms of the number of species and highly disturbed.

Deep Convolutional Neural Networks for Accurate Classification of Gastrointestinal Tract Syndromes

Accurate detection and classification of artifacts within the gastrointestinal(GI)tract frames remain a significant challenge in medical image processing.Medical science combined with artificial intelligence is advancing to automate the diagnosis and treatment of numerous diseases.Key to this is the development of robust algorithms for image classification and detection,crucial in designing sophisticated systems for diagnosis and treatment.This study makes a small contribution to endoscopic image classification.The proposed approach involves multiple operations,including extracting deep features from endoscopy images using pre-trained neural networks such as Darknet-53 and Xception.Additionally,feature optimization utilizes the binary dragonfly algorithm(BDA),with the fusion of the obtained feature vectors.The fused feature set is input into the ensemble subspace k nearest neighbors(ESKNN)classifier.The Kvasir-V2 benchmark dataset,and the COMSATS University Islamabad(CUI)Wah private dataset,featuring three classes of endoscopic stomach images were used.Performance assessments considered various feature selection techniques,including genetic algorithm(GA),particle swarm optimization(PSO),salp swarm algorithm(SSA),sine cosine algorithm(SCA),and grey wolf optimizer(GWO).The proposed model excels,achieving an overall classification accuracy of 98.25% on the Kvasir-V2 benchmark and 99.90% on the CUI Wah private dataset.This approach holds promise for developing an automated computer-aided system for classifying GI tract syndromes through endoscopy images.

The Importance of Flapping Kinematic Parameters in the Facilitation of the Different Flight Modes of Dragonflies

To better understand dragonflies’remarkable flapping wing aerodynamic performance,we measured the kinematic parameters of the wings in two different flight modes(Normal Flight Mode(NFM)and Escape Flight Mode(EFM)).When the specimens switched from normal to escape mode the flapping frequency was invariant,but the stroke plane of the wings was more horizontally inclined.The flapping of both wings was adjusted to be more ventral with a change of the pitching angle that resulted in a larger angle of attack during downstroke and smaller during upstroke to affect the flow directions and the added mass effect.Noticeably,the phasing between the fore and hind pair of wings varies between two flight modes,which affects the wing-wing interaction as well as body oscillations.It is found that the momentum stream in the wake of EFM is qualitatively different from that in NFM.The change of the stroke plane angle and the varied pitching angle of the wings diverts the momentum downwards,while the smaller flapping amplitude and less phase difference between the wings compresses the momentum stream.It seems that in order to achieve greater flight maneuverability a flight vehicle needs to actively control positional angle as well as the pitching angle of the flapping wings.

Predicting the Thickness of an Excavation Damaged Zone around the Roadway Using the DA-RF Hybrid Model

After the excavation of the roadway,the original stress balance is destroyed,resulting in the redistribution of stress and the formation of an excavation damaged zone(EDZ)around the roadway.The thickness of EDZ is the key basis for roadway stability discrimination and support structure design,and it is of great engineering significance to accurately predict the thickness of EDZ.Considering the advantages of machine learning(ML)in dealing with high-dimensional,nonlinear problems,a hybrid prediction model based on the random forest(RF)algorithm is developed in this paper.The model used the dragonfly algorithm(DA)to optimize two hyperparameters in RF,namely mtry and ntree,and used mean absolute error(MAE),rootmean square error(RMSE),determination coefficient(R^(2)),and variance accounted for(VAF)to evaluatemodel prediction performance.A database containing 217 sets of data was collected,with embedding depth(ED),drift span(DS),surrounding rock mass strength(RMS),joint index(JI)as input variables,and the excavation damaged zone thickness(EDZT)as output variable.In addition,four classic models,back propagation neural network(BPNN),extreme learning machine(ELM),radial basis function network(RBF),and RF were compared with the DA-RF model.The results showed that the DARF mold had the best prediction performance(training set:MAE=0.1036,RMSE=0.1514,R^(2)=0.9577,VAF=94.2645;test set:MAE=0.1115,RMSE=0.1417,R^(2)=0.9423,VAF=94.0836).The results of the sensitivity analysis showed that the relative importance of each input variable was DS,ED,RMS,and JI from low to high.

基于元启发式算法的船舶动力装置随机建模与性能优化

For the successful operation of any industry or plant continuous availability of power supply is essential.Many of the large-scale plants established their power generation units.Marine power plant having two generators is also fall in this category.In this study,an effort is made to derive and optimize the availability of a marine power plant having two generators,one switch board and distribution switchboards.For this purpose,a mathematical model is proposed using Markov birth death process by considering exponentially distributed failure and repair rates of all the subsystems.The availability expression of marine power plant is derived.Metaheuristic algorithms namely dragonfly algorithm(DA),bat algorithm(BA)and whale optimization(WOA)are employed to optimize the availability of marine power plant.It is revealed that whale optimization algorithm outperforms over dragonfly algorithm(DA),and bat algorithm(BA)in optimum availability prediction and parameter estimation.The numerical values of the availability and estimated parameters are appended as numerical results.The derived results can be utilized in development of maintenance strategies of marine power plants and to carry out design modifications.

Modified Dragonfly Optimization with Machine Learning Based Arabic Text Recognition

Text classification or categorization is the procedure of automatically tagging a textual document with most related labels or classes.When the number of labels is limited to one,the task becomes single-label text categorization.The Arabic texts include unstructured information also like English texts,and that is understandable for machine learning(ML)techniques,the text is changed and demonstrated by numerical value.In recent times,the dominant method for natural language processing(NLP)tasks is recurrent neural network(RNN),in general,long short termmemory(LSTM)and convolutional neural network(CNN).Deep learning(DL)models are currently presented for deriving a massive amount of text deep features to an optimum performance from distinct domains such as text detection,medical image analysis,and so on.This paper introduces aModified Dragonfly Optimization with Extreme Learning Machine for Text Representation and Recognition(MDFO-EMTRR)model onArabicCorpus.The presentedMDFO-EMTRR technique mainly concentrates on the recognition and classification of the Arabic text.To achieve this,theMDFO-EMTRRtechnique encompasses data pre-processing to transform the input data into compatible format.Next,the ELM model is utilized for the representation and recognition of the Arabic text.At last,the MDFO algorithm was exploited for optimal tuning of the parameters related to the ELM method and thereby accomplish enhanced classifier results.The experimental result analysis of the MDFO-EMTRR system was performed on benchmark datasets and attained maximum accuracy of 99.74%.

Submarine Hunter: Efficient and Secure Multi-Type Unmanned Vehicles

Utilizing artificial intelligence(AI)to protect smart coastal cities has become a novel vision for scientific and industrial institutions.One of these AI technologies is using efficient and secure multi-environment Unmanned Vehicles(UVs)for anti-submarine attacks.This study’s contribution is the early detection of a submarine assault employing hybrid environment UVs that are controlled using swarm optimization and secure the information in between UVs using a decentralized cybersecurity strategy.The Dragonfly Algorithm is used for the orientation and clustering of the UVs in the optimization approach,and the Re-fragmentation strategy is used in the Network layer of the TCP/IP protocol as a cybersecurity solution.The research’s noteworthy findings demonstrate UVs’logistical capability to promptly detect the target and address the problem while securely keeping the drone’s geographical information.The results suggest that detecting the submarine early increases the likelihood of averting a collision.The dragonfly strategy of sensing the position of the submersible and aggregating around it demonstrates the reliability of swarm intelligence in increasing access efficiency.Securing communication between Unmanned Aerial Vehicles(UAVs)improves the level of secrecy necessary for the task.The swarm navigation is based on a peer-to-peer system,which allows each UAV to access information from its peers.This,in turn,helps the UAVs to determine the best route to take and to avoid collisions with other UAVs.The dragonfly strategy also increases the speed of the mission by minimizing the time spent finding the target.

Power and Gaze in Xu Bing’s Dragonfly’s Eye

On August 18,2019,Xu exhibited“The Dragonfly’s Eye”in Today Art Museum.As a respectable writer,Xu drew attention to his elaboration to his illustration of the dragonfly through his own work through incorporating his own artistic interpretation as the new creative mode and idea in art media,further highlighting features of“The Dragonfly’s Eye”.The aesthetic feeling of human nature is emphasized in the creation of Dragonfly’s Eye.Unlike typical contemporary art video works,Dragonfly Eye delivers a whole course of illustration with exceptional production method-through the utilization of existing downloadable videos on the Internet.The project utilizes the romantic story between a young couple to comment on views of life and soul in the contemporary society.Seemingly novelty,the project ultimately centralizes at the idea of the critiquing human nature in the modern ages.

基于全直径CT扫描技术的礁灰岩孔隙结构研究

为研究南海岛礁礁灰岩微观孔隙结构特征并进行定量分析,运用X射线CT扫描设备对礁灰岩试样进行扫描;对扫描数据重建处理,得到高分辨率三维数字岩芯。运用三维可视化软件Dragonfly对数字岩芯进行可视化处理,通过阈值建立孔隙和基质的二元结构模型,计算得到礁灰岩试样的整体孔隙率及逐层面空隙率。采用最大球算法计算得到礁灰岩连通孔隙的球棒模型。结果表明:礁灰岩的整体孔隙率为7.47%~8.24%,更接近致密砂岩;逐层面孔隙率离散性均较大,呈现出非常明显的非匀质特性。研究成果可为珊瑚礁灰岩渗透特性和力学特性的深入研究提供基础。

Paleyfly:一种可扩展的高速互连网络拓扑结构

高速互连网络是高性能计算系统的重要组成部分.随着网络规模需求的扩大,如何搭建更大规模的网络是高速互连网络拓扑结构设计的关键.因此,提出一种新型层次化的拓扑结构Paleyfly(PF),其结合了Paley图强正则的特性和Random Regular(RR)图支持任意规模大小的特点.相比其他新型高速互连网络拓扑结构,Paleyfly能够有效解决在路由芯片端口数受限的背景下,Dragonfly(DF)可扩展性受限、Fat tree(Ft)物理成本高、RR结构物理布局难、路由表规模大等问题.同时,根据强正则属性在路由策略上负载均衡的优势,提出了4种路由策略来解决网络的拥塞问题.最后,通过模拟器实验比较分析PF结构与其他拓扑结构及PF结构不同路由策略的性能,验证了PF结构在不同规模以及不同通信模式配置下网络延迟优于RR结构.

Two New Records of Odonata in White Nile State, Sudan

White Nile state characterizes by rich healthy habitats especially wetlands which it supports the diversity of wildlife, Odonata species are actually poorly known in the White Nile region. A systematic survey was carried out in aquatic systems located at six localities： Kosti, A1-Kawwa, ELJebelein, Kenana cities, Om Elganateer and El Shawat islands. A total of 357 belonged to 16 species distributed in 4 families were recorded and observed. Family Libellulidae was dominant, with 9 species, followed by Coenagrionidae, Brachythemis leucosticte showed the highest abundance in compare with other species. ELJebelein area showed highest number of Odonata, while Kenana showed highest diversity, 11 species recorded from Kenana sugar scheme and Kenana Zoo Park, phyllornacrornia Africana and Olpogastra lugubris recorded only in Kenana. Agriocnemis exilis and lctinogornphus ferox were recorded for first time in Sudan

AERODYNAMIC FORCE AND FLOW STRUCTURES OF TWO AIRFOILS IN FLAPPING MOTIONS

Aerodynamic force and flow structures of two airfoils in a tandem configuration in flapping motions axe studied, by solving the Navier-Stokes equations in moving overset grids. Three typical phase differences between the fore- and aft-airfoil flapping cycles are considered. It is shown that: (1) in the case of no interaction (single airfoil), the time average of the vertical force coefficient over the downstroke is 2.74, which is about 3 times as large as the maximum steady-state lift coefficient of a dragonfly wing; the time average of the horizontal force coefficient is 1.97, which is also large. The reasons for the large force coefficients are the acceleration at the beginning of a stroke, the delayed stall and the 'pitching-up' motion near the end of the stroke. (2) In the cases of two-airfoils, the time-variations of the force and moment coefficients on each airfoil are broadly similar to that of the single airfoil in that the vertical force is mainly produced in downstroke and the horizontal force in upstroke, but very large differences exist due to the interaction. (3) For in-phase stroking, the major differences caused by the interaction are that the vertical force on FA in downstroke is increased and the horizontal force on FA in upstroke decreased. As a result, the magnitude of the resultant force is almost unchanged but it inclines less forward. (4) For counter stroking, the major differences are that the vertical force on AA in downstroke and the horizontal force on FA in upstroke are decreased. As a result, the magnitude of the resultant force is decreased by about 20 percent but its direction is almost unchanged. (5) For 90 degrees -phase-difference stroking, the major differences axe that the vertical force on AA in downstroke and the horizontal force on FA in upstroke axe decreased greatly and the horizontal force on AA in upstroke increased. As a result, the magnitude of the resultant force is decreased by about 28% and it inclines more forward. (6) Among the three cases of phase angles, inphase flapping produces the largest vertical force (also the largest resultant force); the 90 degrees -phase-difference flapping results in the largest horizontal force, but the smallest resultant force.

Aerodynamic interaction between forewing and hindwing of a hovering dragonfly

The phase change between the forewing and hindwing is a distinct feature that sets dragonfly apart from other insects.In this paper,we investigated the aerodynamic effects of varying forewing-hindwing phase di ff erence with a60 inclined stroke plane during hovering flight.Force measurements on a pair of mechanical wing models showed that in-phase flight enhanced the forewing lift by 17%and the hindwing lift was reduced at most phase differences.The total lift of both wings was also reduced at most phase di ff erences and only increased at a phase range around in-phase.The results may explain the commonly observed behavior of the dragonfly where 0 is employed in acceleration.We further investigated the wing-wing interaction mechanism using the digital particle image velocimetry（PIV）system,and found that the forewing generated a downwash flow which is responsible for the lift reduction on the hindwing.On the other hand,an upwash flow resulted from the leading edge vortex of the hindwing helps to enhance lift on the forewing.The results suggest that the dragonflies alter the phase di ff erences to control timing of the occurrence of flow interactions to achieve certain aerodynamic effects.

Experimental investigations of the functional morphology of dragonfly wings

Nowadays, the importance of identifying the flight mechanisms of the dragonfly, as an inspiration for designing flapping wing vehicles, is well known. An experimental approach to understanding the complexities of insect wings as organs of flight could provide significant outcomes for design purposes. In this paper, a comprehensive investigation is carried out on the morphological and microstructural features of dragonfly wings. Scanning electron microscopy （SEM） and tensile testing are used to experimentally verify the functional roles of different parts of the wings. A number of SEM images of the elements of the wings, such as the nodus, leading edge, trailing edge, and vein sections, which play dominant roles in strengthening the whole structure, are presented. The results from the tensile tests indicate that the nodus might be the critical region of the wing that is subjected to high tensile stresses. Considering the patterns of the longitudinal corrugations of the wings obtained in this paper, it can be supposed that they increase the load-bearing capacity, giving the wings an ability to tolerate dynamic loading conditions. In addition, it is suggested that the longitudinal veins, along with the leading and trailing edges, are structural mechanisms that further improve fatigue resistance by providing higher fracture toughness, preventing crack propagation, and allowing the wings to sustain a significant amount of damage without loss of strength.

A general method for large-scale fabrication of Cu nanoislands/dragonfly wing SERS flexible substrates

Noble metal nanorough surfaces that support strong surface-enhanced Raman scattering （SERS） is widely applied in the practical detection of organic molecules. A low-cost, large-area, and environment-friendly SERS-active substrate was acquired by sputtering inexpensive copper （Cu） on natural dragonfly wing （DW） with an easily controlled way of magnetron sputtering. By controlling the sputtering time of the fabrication of Cu on the DW, the performance of the SERS substrates was greatly improved. The SERS-active substrates, obtained at the optimal sputtering time （50 min）, showed a low detection limit （10-6M ） to 4-aminothiophenol （4-ATP）, a high average enhancement factor （EF, 1.98 x10^4）, excellent signal uniformity, and good reproducibility. In addition, the results of the 3D finite-difference time-domain （3D- FDTD） simulation illustrated that the SERS-active substrates provided high-density ＂hot spots＂, leading to a large SERS enhancement.

Descriptions of Cephalaeschna zhuae sp. nov.(Odonata: Aeshnidae) from Yunnan, China

Cephalaeschna zhuae Yang sp.nov.(holotype♂,from Yunnan Province in China)is described and illustrated,and compared with known Chinese species of Cephalaeschna.This new species has a distinct bicolor dorsal carina and special colors on the legs,which can distinguish it from other species of the genus Cephalaeschna.

Improved Dragonfly Optimizer for Intrusion Detection Using Deep Clustering CNN-PSO Classifier

With the rapid growth of internet based services and the data generated on these services are attracted by the attackers to intrude the networking services and information.Based on the characteristics of these intruders,many researchers attempted to aim to detect the intrusion with the help of automating process.Since,the large volume of data is generated and transferred through network,the security and performance are remained an issue.IDS(Intrusion Detection System)was developed to detect and prevent the intruders and secure the network systems.The performance and loss are still an issue because of the features space grows while detecting the intruders.In this paper,deep clustering based CNN have been used to detect the intruders with the help of Meta heuristic algorithms for feature selection and preprocessing.The proposed system includes three phases such as preprocessing,feature selection and classification.In the first phase,KDD dataset is preprocessed by using Binning normalization and Eigen-PCA based discretization method.In second phase,feature selection is performed by using Information Gain based Dragonfly Optimizer(IGDFO).Finally,Deep clustering based Convolutional Neural Network(CCNN)classifier optimized with Particle Swarm Optimization(PSO)identifies intrusion attacks efficiently.The clustering loss and network loss can be reduced with the optimization algorithm.We evaluate the proposed IDS model with the NSL-KDD dataset in terms of evaluation metrics.The experimental results show that proposed system achieves better performance compared with the existing system in terms of accuracy,precision,recall,f-measure and false detection rate.

Phenoloxidase and Melanization Innate Immune Activities in Green Darner Dragonfly Nymphs (Anax junius)

Insects in the Order Odonata are highly subject to infection by gregarine parasites. However, despite the important ecological roles that insects play in every ecosystem in which they exist, little research has been devoted to the description of insect immunity. Insects rely heavily on the rapid actions of innate immune mechanisms to prevent infection. We characterized the melanization response in the hemolymph of green darner dragonfly (Anax junius) nymphs. Incubation of chymotrypsin-activated hemolymph with L-DOPA resulted in volume- and time-dependent production of dopaquinone via the phenoloxidase (PO) enzyme, with biphasic accumulation of product. The PO activity was temperature-dependent, with a stepwise increase from 20℃ - 35℃ and maximum activity measured at 35℃ - 40℃. The formation of product was also inhibited in a concentration-dependent manner by diethylcarbonate, a specific inhibitor of PO activity, which indicated that the observed activity was due to the presence of PO enzyme. The rate of formation and quantity of melanin was dependent on exposure to different titers of bacteria. This is the first characterization of both PO activity and melanization response in green darner dragonflies.

An Enhanced Dragonfly Key Exchange Protocol against Offline Dictionary Attack

Dragonfly is Password Authenticated Key Exchange protocol that uses a shared session key to authenticate parties based on pre-shared secret password. It was claimed that this protocol was secure against off-line dictionary attack, but a new research has proved its vulnerability to off-line dictionary attack and proving step was applied by using “Patched Protocol” which was based on public key validation. Unfortunately, this step caused a raise in the computation cost, which made this protocol less appealing than its competitors. We proposed an alternate enhancement to keep this protocol secure without any extra computation cost that was known as “Enhanced Dragonfly”. This solution based on two-pre-shared secret passwords instead of one and the rounds between parties had compressed into two rounds instead of four. We prove that the enhanced-Dragonfly protocol is secure against off-line dictionary attacks by analyzing its security properties using the Scyther tool. A simulation was developed to measure the execution time of the enhanced protocol, which was found to be much less than the execution time of patched Dragonfly. The off-line dictionary attack time is consumed for few days if the dictionary size is 10,000. According to this, the use of the enhanced Dragonfly is more efficient than the patched Dragonfly.