Heart ventricular histology and microvasculature together with aortic histology and elastic lamellar structure: A comparison of a novel dual-purpose to a broiler chicken line

The use of dual-purpose chickens is a strategy to avoid killing one-day-old male chicks of egg laying lines. Lohmann Dual (LD) is a novel dual-purpose chicken line created by the crossbreeding of layer and broiler lines. However, many of the cardiovascular diseases of broilers are likely to be associated with intensive genetic selection for growth and feed conversion efficiency. This study aimed to compare the macroscopic and microscopic structure of the heart and the aorta of the LD chicken line with that of the broiler chicken line, Ross 308 (Ross) under typical husbandry conditions for meat production. Eighty, one-day-old male chicks of each line were housed for 5 weeks (Ross) and 9 weeks (LD). Six birds of each line were sampled weekly. Heart mass, thickness of ventricular walls, cardiomyocyte size and blood capillary density as well as aortic diameter and thickness, number of elastic lamellae and elastic fiber percentage in the aortic wall were determined. The growth patterns of the heart were the same in the two lines. Although LD chickens had a lower absolute heart mass than that of Ross chickens, the relative heart mass in both lines was similar. The cardiomyocytes of LD chickens were larger than those of Ross’s of the same body weight (BW), nevertheless both lines had similar thicknesses of their ventricular walls. The blood capillary density was greater in the LD heart than in that of the Ross heart. The aorta of LD chickens had proportionally; a greater aortic lumen radius, larger numbers of elastic lamellae and more elastic fibers than in Ross chickens. Our results suggest that the heart and aorta of the LD chickens have not been disadvantaged by their intensive genetic selection; furthermore, LD chickens have a better myocardial capillary supply and better aortic mechanical properties than those of Ross chickens

IoT network algorithm for production quality control

In report the algorithm for creating the IoT network for control product parameters is proposed. It includes steps: sensors measure parameters which sending in IoT platform, its processing and store in DB, applications informed farm managers about results

Predication of nano-silica modified porous asphalt under dynamic creep by using finite element analysis

In areas with heavy rainfall, the conventional pavement may not be suitable due to low drainage capability. This will cause to a storm failure. To solve this, Porous asphalt (PA) is one of the innovative asphalts that can significantly overcome the issue of storm-water problem. The high air voids content characteristic of PA compares with conventional pavement in Malaysia is very suitable in managing the storm-water. However, PA suffers a few problems such as decrement of strength and tensile strength due to high air voids content which lead to permanent deformation. In order to enhance the performance of PA against the permanent deformation an additive material used to increase the strength of the PA called Nano-silica particles. Therefore, the purpose of this study is to evaluate the dynamic creep of Nano-silica modified PA by developing a finite element analysis (FEA) model. Moreover, this study the dynamic creep performance of porous asphalt with different proportion of Nano-silica particles 0%, 2% and 4% was predicted. A finite element model will be simulated by using ABAQUS 6.14 software for the PA sample in order to achieve the objectives of the study. From this study it was concluded that, the develop model was reliable use to predict the performance of PA in terms of dynamic creep and the utilizing of Nano-silica in PA mixture result changes in the rheological properties of the asphalt binder which lead to an enhancement of its performance against the permanent deformation

Resilient modulus prediction of nano-silica modified porous asphalt using Finite Element Analysis

Repetitive traffic load is the most important factor influencing porous asphalt (PA) performance. The performance of asphalt is mostly influenced by the loading magnitude of heavy vehicles. In order to improve the service performance of PA under heavy traffic conditions. the decrement of stiffness is one of the failures that occur on the PA which mainly caused by the repeated load from a large number of different types of vehicles which leads to reduce the characteristic of PA in terms of stiffness and durability. Moreover, to enhance the performance of PA against the stiffness reduction an additive material used to increase the strength of the PA called Nano-silica particles. Thus, the aim of the study to investigate the resilient modulus of Nano-silica modified PA and develop a finite element analysis FEA model to predicate the resilient modulus. In this study, three different Nano-silica contents 0%, 2% and 4% by weight of PA mixture were investigated. To achieve this, a finite element model was developed and simulated by using ABAQUS 6.14 software for the PA samples to predict the resilient modulus performance. A comparative study was done among the unmodified and modified PA mixtures considering the resilient modules value. The result showed that Nano-silica is recommended as an additive in PA mixture, as the result of the modified PA mixture with 2% of NS was 4357Mpa while the unmodified was 3001Mpa. Thus, the addition of NS to PA mixture Capable in increasing the strength and quality of asphalt mixture

Location prediction based on a sector snapshot for location-based services

In location-based services (LBSs), the service is provided based on the users' locations through location determination and mobility realization. Most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shaped cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. Such techniques are the new Markov-based mobility prediction (NMMP) and prediction location model (PLM) that deal with inner cell structure and different levels of prediction, respectively. The NMMP and PLM techniques suffer from complex computation, accuracy rate regression, and insufficient accuracy. In this paper, a novel cell splitting algorithm is proposed. Also, a new prediction technique is introduced. The cell splitting is universal so it can be applied to all types of cells. Meanwhile, this algorithm is implemented to the Micro cell in parallel with the new prediction technique. The prediction technique, compared with two classic prediction techniques and the experimental results, show the effectiveness and robustness of the new splitting algorithm and prediction technique

IOT components for production quality monitoring

To automate the creation of IoT systems, design tools are used in the form of IoT platforms. The structure of the stack in the IoT network is considered. The connection of sensors with means of primary processing, including protocols and data structure, is described. A generalized algorithm for creating a network using the IoT plat-form Bluemix from IBM is presented. The forms of the developed user interface are described

Utilization Potential of Glass Fiber and Crumbled Rubber as Subgrade Reinforcement for Expansive Soil

Due to its high potential for volume change, expansive soil is a problematic building material that can cause harm to road infrastructure. The purpose of this study is to examine the effect of glass fiber and rubber on the properties of expansive soil and their suitability as subgrade reinforcement in road applications. For different percentages of glass fiber and rubber in the soil, the Maximum Dry Density (MDD), Optimum Moisture Content (OMC), and CBR were measured. The results demonstrated that the incorporation of glass fiber and rubber improved the soil's properties. With increasing fiber and rubber content, the MDD and CBR increased, while the OMC decreased. In addition, the strength of the reinforced soil was significantly greater than that of the unreinforced soil. The research indicates that the addition of glass fiber and rubber can improve the efficacy of expansive soil as subgrade reinforcement in road applications.   Doi: 10.28991/HEF-2023-04-03-06 Full Text: PD

Refurbishment of public housing villas in the United Arab Emirates (UAE): energy and economic impact

© 2016, Springer Science+Business Media Dordrecht. This study aims at assessing the technical and economic benefits of refurbishing existing public housing villas in the UAE. Four representative federal public housing villas built between 1980s and 2010s were modeled and analyzed. The Integrated Environmental Solutions-Virtual Environment (IES-VE) energy modeling software was used to estimate the energy consumption and savings due to different refurbishment configurations applied to the villas. The refurbishment technical configurations were based on the UAE’s Estidama green buildings sustainability assessment system. The refurbishment configurations include upgrading three elements: the wall and roof insulation as well as replacing the glazing. The annual electricity savings results indicated that the most cost-efficient refurbishment strategy is upgrading of wall insulation (savings up to 20.8 %) followed by upgrading the roof’s insulation (savings up to 11.6 %) and lastly replacing the glazing (savings up to 3.2 %). When all three elements were refurbished simultaneously, savings up to 36.7 % were achieved (villa model 670). The savings translated to CO2 emission reduction of 22.6 t/year. The simple and discounted payback periods for the different configurations tested ranged between 8 and 28 and 10 and 50 years, respectively