Roadside Vertical Axis Wind Turbine (VAWT): An Effective Evolutionary Design for Australian Highway Commuters with Minimum Dynamic Stall

There are multiple approaches of design for Vertical Axis Wind Turbines (VAWT) that have been studied by engineers and leaps have been made in high performing innovations. By harnessing the energy from these wind turbines, the problem of roadside lights shortage can be solved. This can help to prevent the accidents while providing clean energy. The importance of coastal areas like Australian beaches regarding wind turbines cannot be neglected as a higher number of people like to live near coastal vicinity. Also, most of the freeways in Australia expand across the sea. In this paper, one such design has been analyzed to implement across the highways. But still with many advancements in technology, an immense gap is present in the research of implementation of VAWTs. The design discussed in the current study is a VAWT which can be installed on the side of the highway roads to provide clean and cheap energy for illuminating the roads. Computational Fluid Dynamics (CFD) was conducted on the blades of the turbine to analyze its performance under operating conditions. Furthermore, the paper elaborates the generation of drag and lift on the blades of the turbine. A wind speed of 60 km/h just produced 6.1 N force on the turbine blades as a result of drag. The cost analysis showed the cheap production of such mechanism that can provide longer service when installed.

Modelling of debris-flow susceptibility and propagation: a case study from Northwest Himalaya

The geological and geographical position of the Northwest Himalayas makes it a vulnerable area for mass movements particularly landslides and debris flows. Mass movements have had a substantial impact on the study area which is extending along Karakorum Highway(KKH) from Besham to Chilas. Intense seismicity, deep gorges, steep terrain and extreme climatic events trigger multiple mountain hazards along the KKH, among which debris flow is recognized as the most destructive geohazard. This study aims to prepare a field-based debris flow inventory map at a regional scale along a 200 km stretch from Besham to Chilas. A total of 117 debris flows were identified in the field, and subsequently, a point-based debris-flow inventory and catchment delineation were performed through Arc GIS analysis. Regional scale debris flow susceptibility and propagation maps were prepared using Weighted Overlay Method(WOM) and Flow-R technique sequentially. Predisposing factors include slope, slope aspect, elevation, Topographic Roughness Index(TRI), Topographic Wetness Index(TWI), stream buffer, distance to faults, lithology rainfall, curvature, and collapsed material layer. The dataset was randomly divided into training data(75%) and validation data(25%). Results were validated through the Receiver Operator Characteristics(ROC) curve. Results show that Area Under the Curve(AUC) using WOM model is 79.2%. Flow-R propagation of debris flow shows that the 13.15%, 22.94%, and 63.91% areas are very high, high, and low susceptible to debris flow respectively. The propagation predicated by Flow-R validates the naturally occurring debris flow propagation as observed in the field surveys. The output of this research will provide valuable input to the decision makers for the site selection, designing of the prevention system, and for the protection of current infrastructure.

银杏受精的形质变化及其种胚生长发育的候周期观察

【目的】探究银杏种实受精时的内、外部形态变化;观察种胚发育的结构及数量变化规律。【方法】在7月中旬银杏种实形态建成后,以5 d为周期连续采样,观察其受精前、中、后期的外种皮颜色变化;制作系列石蜡切片,使用光学显微镜和电子显微镜观察种胚结构的内部变化。统计分析不同时期“圆球胚、小子叶胚、大子叶胚、近成熟胚、完全成熟胚”5种类型种胚比例。【结果】五天一候的频度观察发现,银杏外种皮由绿转黄是受精的外部形质标志;外种皮由圆润变得缩皱,是胚胎开始发育的外部形态指标。8月中旬完成受精,形成合子;9月初,种胚肉眼可见,此时绝大多数为圆球胚和小子叶胚;9月下旬,小子叶胚占比最多(85%);到10月中旬,大子叶胚占比数量上升(63%);至11月上旬,近成熟胚占比为71%;到翌年1月下旬,57%已达完全成熟胚阶段。【结论】采用气象候周期采样频度,辅以光镜、电镜显微技术,首次获得了银杏在受精以及种胚始育时段种实的外部形质变化高精图;以候周期统计了种胚发育过程中相应的各种胚类型的数量比例。在研究过程中,新发现银杏种胚的子叶表面已经具气孔,中部具螺纹管胞,胚轴具维管束;首次大数据统计获得约1.5%的银杏种实有双胚发育现象,这些研究结果丰富了对银杏生殖发育的认识。

Performance Enhancement of XML Parsing Using Regression and Parallelism

The Extensible Markup Language(XML)files,widely used for storing and exchanging information on the web require efficient parsing mechanisms to improve the performance of the applications.With the existing Document Object Model(DOM)based parsing,the performance degrades due to sequential processing and large memory requirements,thereby requiring an efficient XML parser to mitigate these issues.In this paper,we propose a Parallel XML Tree Generator(PXTG)algorithm for accelerating the parsing of XML files and a Regression-based XML Parsing Framework(RXPF)that analyzes and predicts performance through profiling,regression,and code generation for efficient parsing.The PXTG algorithm is based on dividing the XML file into n parts and producing n trees in parallel.The profiling phase of the RXPF framework produces a dataset by measuring the performance of various parsing models including StAX,SAX,DOM,JDOM,and PXTG on different cores by using multiple file sizes.The regression phase produces the prediction model,based on which the final code for efficient parsing of XML files is produced through the code generation phase.The RXPF framework has shown a significant improvement in performance varying from 9.54%to 32.34%over other existing models used for parsing XML files.

基于GIS的巴基斯坦北部文化遗址时空分布特征及保护对策

巴基斯坦北部地区是历史上犍陀罗文化的中心区域,拥有大量的印度教、佛教和伊斯兰教文化遗址。借助考古文献资料、数字高程模型以及野外实地调查与验证数据,运用GIS空间分析方法,对巴基斯坦北部地区印度教、佛教和伊斯兰教文化遗址的时空分布特征、保存现状进行研究,并提出相应保护对策。结果表明:巴基斯坦北部地区先后经历了印度教文化、佛教文化、伊斯兰教文化的传入、兴衰等演变过程。核密度估计显示3种文化遗址分布范围、聚集程度有所不同,但都以伊斯兰堡周边区域聚集程度最高。基于高分辨率的DEM分析表明,90%以上的文化遗址距离河流小于800 m,反映其位置选择对于河流的依赖与需求。从分布的高程看,3种文化遗址大多数在800 m以下、坡度范围在0°~10°之间,主要沿河道和交通要道分布。统计数据表明:伊斯兰教遗址数目最多,佛教遗址次之,印度教遗址最少,反映遗址保存的数量随时间而变化。由于自然因素和人类活动,一些文化遗址如古佩拉、维吉等保存状况较差,亟待加大保护力度。针对遗址目前的保存状况与面临的风险,提出对应的保护措施。

纱罗组织对芳纶织物交织阻力的影响

为增强芳纶机织物的纬纱交织阻力,将纱罗组织和平纹组织结合,以提升纬纱对横向抽拔作用的抵御能力。通过准静态纱线抽拔试验发现:在交织阻力-位移曲线的退屈曲区内,纬纱的最大交织阻力和经纬纱屈曲交换程度密切相关;在黏滑区内,曲线呈现出一种震荡衰减趋势;纱线所受的交织阻力和被抽拔纱线根数几乎呈线性关系;同时抽拔2根、3根和4根纱线的最大交织阻力对比于单纱抽拔的最大交织阻力的增幅分别是160%、289%和389%;纱罗组织的引入,有效增强了经纱对纬纱的握持性能。单纱抽拔试验结果表明,平纹/纱罗复合结构织物的纬纱所受最大交织阻力比平纹结构增加约20%。多纱抽拔试验结果表明,交织阻力的最大增量约为65%。

A Color Image Encryption Scheme Based on Singular Values and Chaos

The security of digital images transmitted via the Internet or other public media is of the utmost importance.Image encryption is a method of keeping an image secure while it travels across a non-secure communication medium where it could be intercepted by unauthorized entities.This study provides an approach to color image encryption that could find practical use in various contexts.The proposed method,which combines four chaotic systems,employs singular value decomposition and a chaotic sequence,making it both secure and compression-friendly.The unified average change intensity,the number of pixels’change rate,information entropy analysis,correlation coefficient analysis,compression friendliness,and security against brute force,statistical analysis and differential attacks are all used to evaluate the algorithm’s performance.Following a thorough investigation of the experimental data,it is concluded that the proposed image encryption approach is secure against a wide range of attacks and provides superior compression friendliness when compared to chaos-based alternatives.

Flexible Global Aggregation and Dynamic Client Selection for Federated Learning in Internet of Vehicles

Federated Learning(FL)enables collaborative and privacy-preserving training of machine learning models within the Internet of Vehicles(IoV)realm.While FL effectively tackles privacy concerns,it also imposes significant resource requirements.In traditional FL,trained models are transmitted to a central server for global aggregation,typically in the cloud.This approach often leads to network congestion and bandwidth limitations when numerous devices communicate with the same server.The need for Flexible Global Aggregation and Dynamic Client Selection in FL for the IoV arises from the inherent characteristics of IoV environments.These include diverse and distributed data sources,varying data quality,and limited communication resources.By employing dynamic client selection,we can prioritize relevant and high-quality data sources,enhancing model accuracy.To address this issue,we propose an FL framework that selects global aggregation nodes dynamically rather than a single fixed aggregator.Flexible global aggregation ensures efficient utilization of limited network resources while accommodating the dynamic nature of IoV data sources.This approach optimizes both model performance and resource allocation,making FL in IoV more effective and adaptable.The selection of the global aggregation node is based on workload and communication speed considerations.Additionally,our framework overcomes the constraints associated with network,computational,and energy resources in the IoV environment by implementing a client selection algorithm that dynamically adjusts participants according to predefined parameters.Our approach surpasses Federated Averaging(FedAvg)and Hierarchical FL(HFL)regarding energy consumption,delay,and accuracy,yielding superior results.

Recoloring tomato fruit by CRISPR/Cas9-mediated multiplex gene editing

Fruit color is an important horticultural trait,which greatly affects consumer preferences.In tomato,fruit color is determined by the accumulation of different pigments,such as carotenoids in the pericarp and f lavonoids in the peel,along with the degradation of chlorophyll during fruit ripening.Since fruit color is a multigenic trait,it takes years to introgress all color-related genes in a single genetic background via traditional crossbreeding,and the avoidance of linkage drag during this process is difficult.Here,we proposed a rapid breeding strategy to generate tomato lines with different colored fruits from red-fruited materials by CRISPR/Cas9-mediated multiplex gene editing of three fruit color-related genes(PSY1,MYB12,and SGR1).Using this strategy,the red-fruited cultivar‘Ailsa Craig’has been engineered to a series of tomato genotypes with different fruit colors,including yellow,brown,pink,light-yellow,pink-brown,yellow-green,and light green.Compared with traditional crossbreeding,this strategy requires less time and can obtain transgene-free plants with different colored fruits in less than 1 year.Most importantly,it does not alter other important agronomic traits,like yield and fruit quality.Our strategy has great practical potential for tomato breeding and serves as a reference for improving multigene-controlled traits of horticultural crops.

两种考虑温度影响的SiC JFET仿真模型

针对目前物理建模方法参数获取困难、行为建模方法需要大量实验数据的问题,该文提出两种简单易用的考虑温度影响的Si C JFET功率器件Saber环境建模方法。模型I基于Saber软件提供的JFET模板实现,问题的难点转化为如何准确提取建模对象Si C JFET的相关模板参数;模型II根据器件厂商提供的Si C JFET的PSpice模型,在Saber环境中搭建相应的电路实现,问题的难点转化为如何分析透彻器件厂商提供的模型中各参数的物理意义,并如何调整这些参数使其能准确模拟建模对象的静态和动态特性。该文详细阐述两种仿真模型的特点及具体实现方法,并从静态特性和动态特性两个方面,从仿真和实验两个角度,验证两种仿真模型的正确性和有效性,比较两种建模方法的适用性。

Brain Tumor Detection and Classification Using PSO and Convolutional Neural Network

Tumor detection has been an active research topic in recent years due to the high mortality rate.Computer vision(CV)and image processing techniques have recently become popular for detecting tumors inMRI images.The automated detection process is simpler and takes less time than manual processing.In addition,the difference in the expanding shape of brain tumor tissues complicates and complicates tumor detection for clinicians.We proposed a newframework for tumor detection aswell as tumor classification into relevant categories in this paper.For tumor segmentation,the proposed framework employs the Particle Swarm Optimization(PSO)algorithm,and for classification,the convolutional neural network(CNN)algorithm.Popular preprocessing techniques such as noise removal,image sharpening,and skull stripping are used at the start of the segmentation process.Then,PSO-based segmentation is applied.In the classification step,two pre-trained CNN models,alexnet and inception-V3,are used and trained using transfer learning.Using a serial approach,features are extracted from both trained models and fused features for final classification.For classification,a variety of machine learning classifiers are used.Average dice values on datasets BRATS-2018 and BRATS-2017 are 98.11 percent and 98.25 percent,respectively,whereas average jaccard values are 96.30 percent and 96.57%(Segmentation Results).The results were extended on the same datasets for classification and achieved 99.0%accuracy,sensitivity of 0.99,specificity of 0.99,and precision of 0.99.Finally,the proposed method is compared to state-of-the-art existingmethods and outperforms them.

Detection of Babesia bovis in blood samples and its effect on the hematological and serum biochemical profile in large ruminants from Southern Punjab

Objective:To determine the presence of Babesia bovis(B.bovis)in large ruminants in southern Punjab and its effect on hematological and serum biochemical profile of host animals.Methods:Blood samples were collected from 144 large ruminants,including 105 cattle and 39 buffaloes,from six flistricts in southern Punjab including Multan,Layyali,Muzaffar Garh,Bhakar.Bahawalnagar and Vehari.Data on the characteristics of animals and herds were collected through questionnaires.Different blood(hemoglobin,glucose)and serum(ALT.AST,I.DH,cholesterol)parameters of calves and cattle were measured and compared between parasite positive and negative samples to demonstrate the effect of B.bovis on the blood and serological profile of infected animals.Results:27 out of 144 animals,from 5 out of 6 sampling districts,produced the541-bp fragment specific for B.bovis.Age of animals(P=0.02),presence of ticks on animals(P=0.04)and presence of ticks on dogs associated with herds(P=0.5)were among the major risk factors involved in the spread of bovine babesiosis in the study area.ALT concentrations were the only serum biochemical values that significantly varied between parasite positive and negative cattle.Conclusions:This study has reported for the first time the presence of B.bavis in large ruminant and the results can lead to the prevention of babesiosis in the region to increase the livestock output.

TCP/IP Based Intelligent Load Management System in Micro-Grids Network Using MATLAB/Simulink

Computerized power management system with fast and optimal communication network overcomes all major dicrepencies of undue or inadequate load relief that were present in old conventional systems. This paper presents the basic perception and methodology of modern and true intelligent load management scheme in micro grids topology by employing TCP/IP protocol for fast and intelligent switching. The network understudy performs load management and power distribution intelligently in a unified network. Generated power is efficiently distributed among local loads through fast communication system of server in the form of source and clients in the form of loads through TCP/IP. The efficient use of information between server and clients enables to astutely control the load management in a power system of micro grids system. The processing time of above stated system comes out to be 10ms faster than others which ensure very less delay as compared to conventional methods. The Micro Grids system operating through TCP/IP control has been implemented in MATLAB/Simulink and results have been verified.

Effect of age and gender on some blood biochemical parameters of apparently healthy small ruminants from Southern Punjab in Pakistan

Objective:To report and compare the hematological and serum biochemical profile of goal and sheep from Rahim Yar Khan district in Southern Punjab.Methods:One hundred and twenty blood samples(98 goat and 22 sheep) were collected and their blood glucose, hemoglobin and serum biochemical parameters,cholesterol,aspartate transaminase(AST), alanine aminotransferase(ALT) and lactate dehydrogenase(LDH) were determined by using spectrophotometer.Parameters were compared between goat and sheep.Results:It was observed that glucose(P=0.001),LDH(P=0.001) and ALT(P=0.001) concentrations differed significantly between sheep and goats.The studied parameters were compared between buck and goats and also between young goats(less than 12 months old) and adults(more than 12 months old).It was found that age and gender did not affect these hematological and serum biochemical parameters. Condusions:It can be concluded that sheep have overall higher values than goals for studied hematological and serum biochemical parameters.

Scenario of dengue infection & its control in Pakistan: An up-date and way forward

Dengue fever is one of the major health problems in tropical and subtropical areas throughout the world. The causative agent of dengue fever is the dengue virus which is an enveloped single stranded RNA virus belongs to the family Flaviviridae and has five distinct serotypes(DENV-1,DENV-2, DENV-3, DENV-4 and DENV-5). Dengue virus is transmitted to human via bite of Aedes aegypti and Aedes albopictus mosquitoes. The clinical symptoms of dengue fever ranging from mild to severe form as dengue hemorrhagic fever and dengue shock syndrome. Pakistan is dengue endemic since 1994 but from 2006, Pakistan faced the worst condition regarding dengue in which thousands of people affected by the disease and hundreds of people lost their lives. DENV-2, DENV-3 and DENV-1 are the prevalent serotypes in Pakistan. Common diagnostic techniques are being used in Pakistan such as enzyme-linked immunosorbent assay,polymerase chain reaction and rapid diagnostic tests, while differential diagnosis, limitations of diagnostic methods and poor health care system are the real challenges in dengue diagnosis.Favorable climatic conditions, unplanned urbanization, travelling etc., are major factors responsible for dengue epidemics in Pakistan. This presentation provides update about dengue circumstances in Pakistan and also describes the way how to improve dengue situation in Pakistan.

A Multilevel Deep Feature Selection Framework for Diabetic Retinopathy Image Classification

Diabetes or Diabetes Mellitus(DM)is the upset that happens due to high glucose level within the body.With the passage of time,this polygenic disease creates eye deficiency referred to as Diabetic Retinopathy(DR)which can cause a major loss of vision.The symptoms typically originate within the retinal space square in the form of enlarged veins,liquid dribble,exudates,haemorrhages and small scale aneurysms.In current therapeutic science,pictures are the key device for an exact finding of patients’illness.Meanwhile,an assessment of new medicinal symbolisms stays complex.Recently,Computer Vision(CV)with deep neural networks can train models with high accuracy.The thought behind this paper is to propose a computerized learning model to distinguish the key precursors of Dimensionality Reduction(DR).The proposed deep learning framework utilizes the strength of selected models(VGG and Inception V3)by fusing the extracated features.To select the most discriminant features from a pool of features,an entropy concept is employed before the classification step.The deep learning models are fit for measuring the highlights as veins,liquid dribble,exudates,haemorrhages and miniaturized scale aneurysms into various classes.The model will ascertain the loads,which give the seriousness level of the patient’s eye.The model will be useful to distinguish the correct class of seriousness of diabetic retinopathy pictures.

Acute Inferior Myocardial Infarction Presenting as Anterior ST Segment Elevation Myocardial Infarction on ECG

A 51-year-old man presented to the emergency department with acute substernal chest pain. ECG showed ST-segment elevation in the left precordial leads. Coronary angiography demonstrated an occlusion of the right coronary artery (RCA) and no significant stenosis in left anterior descending coronary artery (LAD). The occlusion of a non-dominant RCA may result in anterior ST-segment elevation ECG changes, which could disorient both general and interventional cardiologists.

Hydro and Wind Power Integration: A Case Study of Dargai Station in Pakistan

Pakistan is facing acute energy crises since last few years. Due to shortage of fuel oil and its sky touching prices, it seems very uneconomical to generate electricity from fuel oil. In order to generate cheap electricity we have to rely on renewable energy resources. To address these challenges, wind power generation is among the popular options in the world which is now being considered in Pakistan as well. However unremitting change in wind speed from calm to stormy introduces real challenges. Storing wind energy in batteries during the periods of low demand seems an expensive option, especially when dealing with large scale power generation. Due to incessantly varying nature of wind speed, it is not feasible to rely only on wind power for cheap power production. Also, it is not thriftily possible to construct separate transmission line. However if we integrate wind power with hydro power, we can utilize the maximum possible transmission capacity. Existing hydro power station operating in that area or pumped storage scheme can be used. This paper is an attempt to analyze coordination of wind generation with hydro power in those areas of Pakistan where both wind and hydro power sources exist. In this paper, different issues have been analyzed taking case study of Dargai. This paper is first attempt in Pakistan about integration of wind and hydro power to draw some general conclusions and to point out some areas in which further research can be done.

Stability Evaluation of Slopes Using Kinematic and Limit Equilibrium Analyses in Seismically Active Balakot, KPK, Pakistan

The Northern segment of Pakistan, especially Balakot city is affected up to large extent by the landslides. Tectonically, it lies in the proximity of Hazara Kashmir Syntaxis and other two active regional faults: Main Boundary and Hazara Frontal Thrusts that traversing right through the Balakot town. This study focuses on the evaluation of slopes near Balakot town in static and pseudo-static condition. A geological map is produced at 1:24,000 scale to separate various rock and soil units. During reconnaissance study, two slopes were selected which seem prone to sliding. The procured data on condition of natural slope, properties of material entailed, structural setting, and vegetation cover distribution was gathered. Discontinuity Surveys of slopes were carried out to collect discontinuity parameters. Kinematic analyses were performed on DIPS v. 7.0 to assess mode of failures based on joints data. Limit equilibrium analyses were carried out at Slide v. 7.0 to check factor of safety at different conditions. The study concluded that the slopes were affected by the plane, wedge and toppling failures, while although in seismically active zone, circular failure is not likely.