Birds’Diversity in Kalfou Forest Reserve and Its Peripheral Zone, Far North, Cameroon

The Far North Region of Cameroon is home to a great diversity of bird species, which unfortunately remains very little explored. This work was initiated to establish an inventory of birds and the factors affecting their diversity and distribution for sustainable management in the Kalfou Forest Reserve (KFR) and its periphery. Two methods were used for sampling, linear strip transects from which direct counts and indirect observations were made and the mist netting to complement the first. In total, 2525 birds were observed, including 149 species, belonging to 20 orders and 55 families. Accipitridae had the greatest number of species (11). The species richness was greater in the KFR (117 species) compared to the periphery (95 species). The specific richness was higher in wooded savannah compared to other habitats. Shannon index was significantly higher in the KFR (3.99) compared to that obtained in the periphery (3.80). The value of the Simpson index was higher on the outskirts of the KFR than on the periphery. The indices of species diversity were greater in the wooded savannah compared to other vegetation types. The seasons had no influence on bird diversity. Among the human activities encountered, the pressure indices were more important for grazing (7.3 contacts/km). Human activities have resulted in a significant decrease in specific richness. Six endangered species were encountered, four belonging to the Accipitridae family. The greater bird diversity in the reserve compared to the periphery shows that protected areas are a long-term solution for biodiversity conservation.

粒子图像测速技术:从实验室到工业应用的进展(特邀)

粒子图像测速(PIV)已成为测量流体流动速度场的重要实验技术。该方法产生瞬时流型的定量表示,通常用于帮助构建复杂流动的现象学模型和数值模拟验证。PIV分析可广泛用于实验流体力学等多个研究领域。两步处理法,即自相关和互相关,已被用于检查时空流演化,可以实现作为空间分辨率函数的涡度测量和精度估计。PIV的发展与测量流场的复杂性和难度逐渐增加紧密相关。用于测量的PIV技术发展迅速,并呈现出新的趋势,主要体现在立体PIV、断层PIV、大型PIV、微型PIV、3D PIV、行人PIV以及使用高时间/空间分辨率设备。PIV在医学研究、能源燃料、燃烧、流场测量、实时过程监测、结构变形、灌溉、声学、地质学、海洋学、水资源、林业、人群监测和采矿矿物加工等各种研究领域有着广泛的应用。本文对实验室PIV发展进行全面概述,通过在工业过程和日常生活中采用PIV进行实时监控,讨论了PIV如何以精确的时间分辨率和特殊分辨率取代现有的分析成像技术。此外,还综合比较了数值模拟和目前可用的PIV分析技术。

荧光介孔二氧化硅负载丙硫菌唑纳米颗粒的制备及性能研究

近年来,丙硫菌唑作为一种新颖的广谱杀菌剂备受关注,但由于其代谢产物对操作人员存在健康风险,导致其在中国的使用和登记受到限制。将丙硫菌唑制备为具有缓慢释放、可提高农药稳定性等特点的缓释制剂可有效改善其带来的健康风险问题。本研究采用纳米荧光介孔二氧化硅制备了丙硫菌唑缓释纳米颗粒,通过扫描电镜(SEM)、透射电镜(TEM)、傅里叶变换红外光谱(FTIR)、X-射线光电子能谱(XPS)、Brunauer-Emmett-Teller(BET)比表面积分析、热重分析(TGA)、荧光光谱以及高效液相色谱仪等手段对其结构与特性进行表征。采用透析袋法探讨了丙硫菌唑在释放介质中的释放行为;利用菌丝生长速率法测定了该载药颗粒对小麦赤霉病原菌的杀菌活性;通过激光共聚焦研究了荧光二氧化硅在小麦赤霉病菌菌丝体以及小麦中的传输情况。结果表明:所制备的载药纳米颗粒外观形貌较为规整,平均粒径为139 nm,其最大载药量可达27.14%;该纳米载药颗粒具有缓释性能,释放曲线符合Ritger-Peppas方程;载药颗粒与丙硫菌唑原药相比具有相同的毒力效果。此外,激光共聚焦结果表明,该荧光二氧化硅纳米颗粒可以在菌丝体以及小麦植株根部吸收和传导。

MSEs Credit Risk Assessment Model Based on Federated Learning and Feature Selection

Federated learning has been used extensively in business inno-vation scenarios in various industries.This research adopts the federated learning approach for the first time to address the issue of bank-enterprise information asymmetry in the credit assessment scenario.First,this research designs a credit risk assessment model based on federated learning and feature selection for micro and small enterprises(MSEs)using multi-dimensional enterprise data and multi-perspective enterprise information.The proposed model includes four main processes:namely encrypted entity alignment,hybrid feature selection,secure multi-party computation,and global model updating.Secondly,a two-step feature selection algorithm based on wrapper and filter is designed to construct the optimal feature set in multi-source heterogeneous data,which can provide excellent accuracy and interpretability.In addition,a local update screening strategy is proposed to select trustworthy model parameters for aggregation each time to ensure the quality of the global model.The results of the study show that the model error rate is reduced by 6.22%and the recall rate is improved by 11.03%compared to the algorithms commonly used in credit risk research,significantly improving the ability to identify defaulters.Finally,the business operations of commercial banks are used to confirm the potential of the proposed model for real-world implementation.

Assessing Secure OpenID-Based EAAA Protocol to Prevent MITM and Phishing Attacks in Web Apps

To secure web applications from Man-In-The-Middle(MITM)and phishing attacks is a challenging task nowadays.For this purpose,authen-tication protocol plays a vital role in web communication which securely transfers data from one party to another.This authentication works via OpenID,Kerberos,password authentication protocols,etc.However,there are still some limitations present in the reported security protocols.In this paper,the presented anticipated strategy secures both Web-based attacks by leveraging encoded emails and a novel password form pattern method.The proposed OpenID-based encrypted Email’s Authentication,Authorization,and Accounting(EAAA)protocol ensure security by relying on the email authenticity and a Special Secret Encrypted Alphanumeric String(SSEAS).This string is deployed on both the relying party and the email server,which is unique and trustworthy.The first authentication,OpenID Uniform Resource Locator(URL)identity,is performed on the identity provider side.A second authentication is carried out by the hidden Email’s server side and receives a third authentication link.This Email’s third SSEAS authentication link manages on the relying party(RP).Compared to existing cryptographic single sign-on protocols,the EAAA protocol ensures that an OpenID URL’s identity is secured from MITM and phishing attacks.This study manages two attacks such as MITM and phishing attacks and gives 339 ms response time which is higher than the already reported methods,such as Single Sign-On(SSO)and OpenID.The experimental sites were examined by 72 information technology(IT)specialists,who found that 88.89%of respondents successfully validated the user authorization provided to them via Email.The proposed EAAA protocol minimizes the higher-level risk of MITM and phishing attacks in an OpenID-based atmosphere.

Text Augmentation-Based Model for Emotion Recognition Using Transformers

Emotion Recognition in Conversations(ERC)is fundamental in creating emotionally intelligentmachines.Graph-BasedNetwork(GBN)models have gained popularity in detecting conversational contexts for ERC tasks.However,their limited ability to collect and acquire contextual information hinders their effectiveness.We propose a Text Augmentation-based computational model for recognizing emotions using transformers(TA-MERT)to address this.The proposed model uses the Multimodal Emotion Lines Dataset(MELD),which ensures a balanced representation for recognizing human emotions.Themodel used text augmentation techniques to producemore training data,improving the proposed model’s accuracy.Transformer encoders train the deep neural network(DNN)model,especially Bidirectional Encoder(BE)representations that capture both forward and backward contextual information.This integration improves the accuracy and robustness of the proposed model.Furthermore,we present a method for balancing the training dataset by creating enhanced samples from the original dataset.By balancing the dataset across all emotion categories,we can lessen the adverse effects of data imbalance on the accuracy of the proposed model.Experimental results on the MELD dataset show that TA-MERT outperforms earlier methods,achieving a weighted F1 score of 62.60%and an accuracy of 64.36%.Overall,the proposed TA-MERT model solves the GBN models’weaknesses in obtaining contextual data for ERC.TA-MERT model recognizes human emotions more accurately by employing text augmentation and transformer-based encoding.The balanced dataset and the additional training samples also enhance its resilience.These findings highlight the significance of transformer-based approaches for special emotion recognition in conversations.

Optimizing techno-functionality of germinated whole wheat flour steamed bread via glucose oxidase(Gox)and pentosanase(Pn)enzyme innovation

Germination,a powerful biofortification technique,holds immense potential in bolstering the micronutrient profile of essential staple grains,thereby paving the way for optimal nutritional enhancement.The primary goal of this study was to improve the technological functionality of germinated wheat flour by incorporating pentosanase(Pn)and glucose oxidase(Gox)enzymes,with particular emphasis on the evolutionary changes in its components.The inclusion of Gox did not produce any substantial impact on the volumetric characteristics of the steamed bread.The incorporation of Pn and Gox has been seen to enhance the overall excellence of steamed bread by optimizing loaf volume and textural characteristics while also improving the thermal stability of the dough.The existence of two endothermic peaks could be attributed to bound water or alterations in the granules within the starch crystallization region.Adding Pn and Gox reduced and increased the formation and stability time of the dough,respectively.A certain ratio was employed to assess alternations in the crystallinity of starch granules over a limited range.After steaming,a significant decrease in IR1047/1022 was observed,indicating that the elevated temperature partially disrupted the internal starch crystal structure,leading to a gelatinization reaction with water.The ratio of tensile resistance(R)and elongation(E)of dough increased significantly compared to the control.The results obtained from this study indicate that the simultaneous inclusion of enzymes(Pn+Gox)holds significant promise for expanding the technological functionality of germinated wheat flour dough and improving the quality attributes of steamed bread.

Hash Table Assisted Efficient File Level De-Duplication Scheme in SD-IoV Assisted Sensing Devices

The Internet of Things(IoT)and cloud technologies have encouraged massive data storage at central repositories.Software-defined networks(SDN)support the processing of data and restrict the transmission of duplicate values.It is necessary to use a data de-duplication mechanism to reduce communication costs and storage overhead.Existing State of the art schemes suffer from computational overhead due to deterministic or random tree-based tags generation which further increases as the file size grows.This paper presents an efficient file-level de-duplication scheme(EFDS)where the cost of creating tags is reduced by employing a hash table with key-value pair for each block of the file.Further,an algorithm for hash table-based duplicate block identification and storage(HDBIS)is presented based on fingerprints that maintain a linked list of similar duplicate blocks on the same index.Hash tables normally have a consistent time complexity for lookup,generating,and deleting stored data regardless of the input size.The experiential results show that the proposed EFDS scheme performs better compared to its counterparts.

Simulation and Experimental Analysis of Vortex Tube Using Steel Material

Experimental and computational fluid dynamics (CFD) are investigated through the vortex tube system. The benefit of vortex tube is a counter flow type tube, which has further designed and fabricated for investigation. The whole set up is consisting of a simple device that can separate a single stream of compressed air into two streams;one is at high temperature and the other is lower temperature following an inlet gas stream. The advantages of this tube are their compactness, safety, and low equipment cost mainly used in cooling and heating applications. This study addressed three-dimensional flows;the domain is using computational fluid dynamics (CFD) method and experimental approach to optimize the direction of RHVT. Through the CFD analysis, the best cold end diameter (dc), number of nozzles, and the best parameters for obtaining the highest hot gas temperature and lowest cold gas temperature were obtained and verified by experimental procedures.

Therapeutic Effectiveness of Hijama in Sciatica Pain

Hijama is an alternative mode of treatment also known as cupping therapy. It involves removal of subcutaneous stagnant blood through suction cups after making superficial incisions at particular area of the body. This study was undertaken to evaluate the efficacy of hijama in sciatica pain at Aligarh Shifa hospital. 92 patients with the history of sciatica were selected randomly between 18 - 75 years of age and hijama cups were applied generally at C7, T2 and L5/S1 vertebrae, while two cups were also applied bilaterally on L4/L5 vertebrae, four cups were additionally applied on hip joint, back of thigh, knee and calf muscle, all cups were applied thrice at an interval of 15 days between each session. The decrease in sciatic pain was assessed after three sessions of Hijama by numeric pain rating scale there was overall significant reduction in pain with 67 percent patients showing relief in pain up to varying degree. Present study suggests that hijama has been found to be effective in relieving pain and improving quality of life in majority of the patient’s, hence may be used as effective alternative tool to alleviate pain.

Role of flavonoids in plant interactions with the environment and against human pathogens-A review

Flavonoids are widely-distributed polyphenolic secondary metabolites with diverse biological activities in plants and benefit human health as protective dietary agents.They participate in plants' responses to harsh environmental conditions and effectively regulate the cell differentiation and growth.In plants,the majority of their functions are attributed to their strong antioxidative properties.Similarly,dietary flavonoids protect the human body against free radicals which are associated with the development of cancer and atherosclerosis.Plants rich in polyphenols have been used to cure various diseases because of their antibacterial,antiviral,antifungal and anticancer properties.This review summarizes the up-to-date research trends and development on flavonoids and its derivatives,working mechanisms and potential functions and applications particularly in relation to plant protection and human health.Towards the end,notable concluding remarks with a close-up look at the future research directions have also been presented briefly.

MADCR:Mobility Aware Dynamic Clustering-Based Routing Protocol in Internet of Vehicles

Internet of Vehicles(IoV)is an evolution of the Internet of Things(IoT)to improve the capabilities of vehicular ad-hoc networks(VANETs)in intelligence transport systems.The network topology in IoV paradigm is highly dynamic.Clustering is one of the promising solutions to maintain the route stability in the dynamic network.However,existing algorithms consume a considerable amount of time in the cluster head(CH)selection process.Thus,this study proposes a mobility aware dynamic clustering-based routing(MADCR)protocol in IoV to maximize the lifespan of networks and reduce the end-to-end delay of vehicles.The MADCR protocol consists of cluster formation and CH selection processes.A cluster is formed on the basis of Euclidean distance.The CH is then chosen using the mayfly optimization algorithm(MOA).The CH subsequently receives vehicle data and forwards such data to the Road Side Unit(RSU).The performance of the MADCR protocol is compared with that ofAnt Colony Optimization(ACO),Comprehensive Learning Particle Swarm Optimization(CLPSO),and Clustering Algorithm for Internet of Vehicles based on Dragonfly Optimizer(CAVDO).The proposed MADCR protocol decreases the end-toend delay by 5–80 ms and increases the packet delivery ratio by 5%–15%.

从野生与突变株云芝IBL-04提纯锰过氧化物酶及其表征（英文）

由野生及突变株云芝IBL-04制得细胞外锰过氧化物酶(MnPs),并经过硫酸铵沉淀、透析、离子交换和凝胶渗透层析法等步骤提纯.纯化的酶在十二烷基硫酸钠-聚丙烯酰胺凝胶电泳(SDS-PAGE)上于43 kDa区域呈现单一谱带,它适宜的pH值和温度分别为5.0和40°C.突变株MnPs表现出比野生株MnPs更宽的活性pH值范围和更高的热稳定性.从所选突变株所得纯化的MnPs表现出与野生株MnP几乎相同的电泳性质、稳态动力学、金属离子和EDCs降解效率.该生物酶与Mn^(2+)一起催化的反应速率最快,但最高的亲和性对应于ABTS、甲氧基羟苯基乙二醇、4-氨基苯酚和活性染料.Mn^(2+)和Cu^(2+)可显著提高MnPs的活性,但Zn^(2+),Fe^(2+),EDTA和半胱氨酸则会不同程度地抑制其活性,Hg^(2+)是最强的活性抑制剂.所有来源的MnPs均可有效催化EDCs、壬基苯酚和二氯苯氧氯酚降解,处理3 h可除去80%以上,在MnPs-介质体系中可进一步提高到90%.综上,云芝MnPs生物酶具有较高的pH适用性和热稳定性、独特的Michaelis-Menten动力学参数和高的EDCs去除效率等特点。

Clinical indicators for progression of nonalcoholic steatohepatitis to cirrhosis

Non-alcoholic fatty liver disease(NAFLD),is a disease spectrum characterized by fat accumulation in hepatocytes presenting as hepatic steatosis to advance disease with active hepatic inflammation,known as nonalcoholic steatohepatitis.Chronic steatohepatitis will lead to progressive hepatic fibrosis causing cirrhosis and increased risk for developing hepatocellular carcinoma(HCC).Fatty liver disease prevalence has increased at alarming rates alongside obesity,diabetes and metabolic syndrome to become the second most common cause of cirrhosis after alcohol related liver disease worldwide.Given this rise in prevalence,it is becoming increasingly more important to find non-invasive methods to diagnose disease early and stage hepatic fibrosis.Providing clinicians with the tools to diagnose and treat the full spectrum of NAFLD will help prevent known complications such as cirrhosis and HCC and improve quality of life for the patients suffering from this disease.This article discusses the utility of current noninvasive liver function testing in the clinical progression of fatty liver disease along with the imaging modalities that are available.Additionally,we summarize available treatment options including targeted medical therapy through four different pathways,surgical or endoscopic intervention.

An Efficient Internet Traffic Classification System Using Deep Learning for IoT

Internet of Things(IoT)defines a network of devices connected to the internet and sharing a massive amount of data between each other and a central location.These IoT devices are connected to a network therefore prone to attacks.Various management tasks and network operations such as security,intrusion detection,Quality-of-Service provisioning,performance monitoring,resource provisioning,and traffic engineering require traffic classification.Due to the ineffectiveness of traditional classification schemes,such as port-based and payload-based methods,researchers proposed machine learning-based traffic classification systems based on shallow neural networks.Furthermore,machine learning-based models incline to misclassify internet traffic due to improper feature selection.In this research,an efficient multilayer deep learning based classification system is presented to overcome these challenges that can classify internet traffic.To examine the performance of the proposed technique,Moore-dataset is used for training the classifier.The proposed scheme takes the pre-processed data and extracts the flow features using a deep neural network(DNN).In particular,the maximum entropy classifier is used to classify the internet traffic.The experimental results show that the proposed hybrid deep learning algorithm is effective and achieved high accuracy for internet traffic classification,i.e.,99.23%.Furthermore,the proposed algorithm achieved the highest accuracy compared to the support vector machine(SVM)based classification technique and k-nearest neighbours(KNNs)based classification technique.

生物催化进展:从计算到代谢工程（英文）

经过数次技术研究和超常创新战略的大发展,生物催化逐渐达到工业化水平,从而受到人们特别的关注.基于酶值,通过生物途径生产高附加值化合物和精细工业化学品成为人们最感兴趣的领域之一.更广泛的众多生物化学路线可由酶催化来实现,其中还有一些酶尚未被人们发现.另一方面,由于非同源底物和某些化学过程所必需的苛刻条件,导致酶催化过程的效率低、稳定性差,因而限制了生物催化的应用.因此,开发具有多催化特征、更高效率和稳定性的绿色催化剂,成为生物催化的重中之重.计算科学、代谢工程、合成生物,以及机器学习路线的运用为新催化剂的工程化提供了新方法.本文重点介绍了合成生物学和代谢工程在催化中的作用,讨论了用于催化的机器学习算法和如何选择一种预测蛋白质-配体相互作用的算法;为了预测键合和催化功能,综述了分子对接的重要性;最后给出了结束语、未来挑战和前景展望.

Evaluation and comparison of CMIP6 models and MERRA-2 reanalysis AOD against Satellite observations from 2000 to 2014 over China

Rapid industrialization and urbanization along with a growing population are contributing significantly to air pollution in China.Evaluation of long-term aerosol optical depth(AOD)data from models and reanalysis,can greatly promote understanding of spatiotemporal variations in air pollution in China.To do this,AOD(550 nm)values from 2000 to 2014 were obtained from the Coupled Model Intercomparison Project(CIMP6),the second version of Modern-Era Retrospective analysis for Research,and Applications(MERRA-2),and the Moderate Resolution Imaging Spectroradiometer(MODIS;flying on the Terra satellite)combined Dark Target and Deep Blue(DTB)aerosol product.We used the TerraMODIS DTB AOD(hereafter MODIS DTB AOD)as a standard to evaluate CMIP6 Ensemble AOD(hereafter CMIP6 AOD)and MERRA-2 reanalysis AOD(hereafter MERRA-2 AOD).Results show better correlations and smaller errors between MERRA-2 and MODIS DTB AOD,than between CMIP6 and MODIS DTB AOD,in most regions of China,at both annual and seasonal scales.However,significant under-and over-estimations in the MERRA-2 and CMIP6 AOD were also observed relative to MODIS DTB AOD.The long-term(2000-2014)MODIS DTB AOD distributions show the highest AOD over the North China Plain(0.71)followed by Central China(0.69),Yangtse River Delta(0.67),Sichuan Basin(0.64),and Pearl River Delta(0.54)regions.The lowest AOD values were recorded over the Tibetan Plateau(0.13±0.01)followed by Qinghai(0.19±0.03)and the Gobi Desert(0.21±0.03).Large amounts of sand and dust particles emitted from natural sources(the Taklamakan and Gobi Deserts)may result in higher AOD in spring compared to summer,autumn,and winter.Trends were also calculated for 2000-2005,for2006-2010(when China introduced strict air pollution control policies during the 11 th Five Year Plan or FYP),and for 2011-2014(during the 12 th FYP).An increasing trend in MODIS DTB AOD was observed throughout the country during 2000-2014.The uncontrolled industrialization,urbanization,and rapid economic development that mostly occurred from 2000 to 2005 probably contributed to the overall increase in AOD.Finally,China’s air pollution control policies helped to reduce AOD in most regions of the country;this was more evident during the 12 th FYP period(2011-2014)than during the 11 th FYP period(2006-2010).Therefore this study strongly advises the authority to retain or extend these policies in the future for improving air quality.

Towards Aspect Based Components Integration Framework for Cyber-Physical System

Cyber-Physical Systems(CPS)comprise interactive computation,networking,and physical processes.The integrative environment of CPS enables the smart systems to be aware of the surrounding physical world.Smart systems,such as smart health care systems,smart homes,smart transportation,and smart cities,are made up of complex and dynamic CPS.The components integration development approach should be based on the divide and conquer theory.This way multiple interactive components can reduce the development complexity inCPS.As reusability enhances efficiency and consistency in CPS,encapsulation of component functionalities and a well-designed user interface is vital for the better end-user’s Quality of Experience(QoE).Thus,incorrect interaction of interfaces in the cyber-physical system causes system failures.Usually,interface failures occur due to false,and ambiguous requirements analysis and specification.Therefore,to resolve this issue semantic analysis is required for different stakeholders’viewpoint analysis during requirement specification and components analysis.This work proposes a framework to improve the CPS component integration process,starting from requirement specification to prioritization of components for configurable.For semantic analysis and assessing the reusability of specifications,the framework uses text mining and case-based reasoning techniques.The framework has been tested experimentally,and the results show a significant reduction in ambiguity,redundancy,and irrelevancy,as well as increasing accuracy of interface interactions,component selection,and higher user satisfaction.

Engineered Hybrid Materials with Smart Surfaces for Effective Mitigation of Petroleum-Originated Pollutants

The generation and controlled or uncontrolled release of hydrocarbon-contaminated industrial wastewater effluents to water matrices are a major environmental concern.The contaminated water comes to surface in the form of stable emulsions,which sometimes require different techniques to mitigate or separate effectively.Both the crude emulsions and hydrocarbon-contaminated wastewater effluents contain suspended solids,oil/grease,organic matter,toxic elements,salts,and recalcitrant chemicals.Suitable treatment of crude oil emulsions has been one of the most important challenges due to the complex nature and the substantial amount of generated waste.Moreover,the recovery of oil from waste will help meet the increasing demand for oil and its derivatives.In this context,functional nanostructured materials with smart surfaces and switchable wettability properties have gained increasing attention because of their excellent performance in the separation of oil–water emulsions.Recent improvements in the design,composition,morphology,and fine-tuning of polymeric nanostructured materials have resulted in enhanced demulsification functionalities.Herein,we reviewed the environmental impacts of crude oil emulsions and hydrocarbon-contaminated wastewater effluents.Their effective treatments by smart polymeric nanostructured materials with wettability properties have been stated with suitable examples.The fundamental mechanisms underpinning the efficient separation of oil–water emulsions are discussed with suitable examples along with the future perspectives of smart materials.

Fractional Analysis of Viscous Fluid Flow with Heat and Mass Transfer Over a Flexible Rotating Disk

An unsteady viscous fluid flow with Dufour and Soret effect,which results in heat and mass transfer due to upward and downward motion of flexible rotating disk,has been studied.The upward or downward motion of non rotating disk results in two dimensional flow,while the vertical action and rotation of the disk results in three dimensional flow.By using an appropriate transformation the governing equations are transformed into the system of ordinary differential equations.The system of ordinary differential equations is further converted into first order differential equation by selecting suitable variables.Then,we generalize the model by using the Caputo derivative.The numerical result for the fractional model is presented and validated with Runge Kutta order 4 method for classical case.The compared results are presented in Table and Figures.It is concluded that the fractional model is more realistic than that of classical one,because it simulates the fluid behavior at each fractional value rather than the integral values.