357 research outputs found
Analysis of ischaemic crisis using the informational causal entropy-complexity plane
In the present work, an ischaemic process, mainly focused on the reperfusion stage, is studied using the informational causal entropy-complexity plane. Ischaemic wall behavior under this condition was analyzed through wall thickness and ventricular pressure variations, acquired during an obstructive flow maneuver performed on left coronary arteries of surgically instrumented animals. Basically, the induction of ischaemia depends on the temporary occlusion of left circumflex coronary artery (which supplies blood to the posterior left ventricular wall) that lasts for a few seconds. Normal perfusion of the wall was then reestablished while the anterior ventricular wall remained adequately perfused during the entire maneuver. The obtained results showed that system dynamics could be effectively described by entropy-complexity loops, in both abnormally and well perfused walls. These results could contribute to making an objective indicator of the recovery heart tissues after an ischaemic process, in a way to quantify the restoration of myocardial behavior after the supply of oxygen to the ventricular wall was suppressed for a brief period.Fil: Legnani, Walter. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; Argentina. Universidad Nacional de Lanús; ArgentinaFil: Traversaro Varela, Francisco. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Redelico, Francisco Oscar. Hospital Italiano; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes; ArgentinaFil: Cymberknop, Leandro Javier. Instituto Tecnologico de Buenos Aires. Departamento de Bioingenieria; Argentina. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; ArgentinaFil: Armentano, Ricardo Luis. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; Argentina. Instituto Tecnologico de Buenos Aires. Departamento de Bioingenieria; ArgentinaFil: Rosso, Osvaldo Aníbal. Universidad de los Andes; Chile. Universidade Federal de Alagoas; Brasil. Hospital Italiano; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin
EFFECT OF CUTTING HEIGHTS AND MINERAL NPK AND/OR BIOFERTILIZATION TREATMENTS ON MORINGA OLEIFERA, L. PLANTS
This study was conducted in Hort. Dept., Fac. Agric., Minia Univ. in the two successive seasons of 2015 and 2016 on Moringa to study the effect of cutting heights (10, 20, 30 and 40 cm) and fertilization on yield productivity and chemical constituents of the plants.
Data indicated that cut plant at 10 cm was superior than other treatments on increasing branch numbers, fresh and dry weights/plant/cut and total yield/plant/season, as well as, total carbohydrates, protein and vit. C %. All used six fertilization treatments significantly increased all vegetative growth parameters and chemical constituents as compared with control. The best treatments were NPK (100 %) and bio. + 75 % NPK.
It could be recommended to cut Moringa oleifera at 10 cm above soil surface and fertilizing plants with bio. + 75 % NPK dose to obtain a good production biomass and high quality
Social Marketing , Education and the Female Workforce : A Comparison of United Arab Emirates and Kingdom of Saudi Arabia
The religious, socioeconomic, and political status are fundamental principles that form the values of women\u27s lifestyles in the Muslim World and especially in the GCC. It varies largely from nation to nation depending on how globalization has managed to affect the society in line with the lifestyles of modern living. The World Economic Forum report (WEF, 2014) shows that the UAE focuses on transforming the country into a diversified self-sustaining market-driven economy. The economic prosperity and presence in the world affairs is mainly due to the leadership\u27s decision to form a free market economy. The open economy, attractive business platform and ease of life have encouraged expatriates to work and live in the UAE forcing its social values to open up. This has had a direct effect on the lifestyles of Emirati society, and women in particular. On the other hand, the exclusion of Saudi women from public life is no doubt a heated debate in the international scene. The government of Saudi Arabia has been strictly persistent in applying its cultural values in most macro-economic aspects such as education, technology (1), and policy. The research findings prove, based on the statistical approach, that government intervention has played a vital role in increasing the contribution of women in the workforce in both countries, the UAE and KSA, by supporting the required legal and official reforms. The substantial investment in education, of both governments, has proved to be one of the most important drives to increase the women workforce. Despite the different levels of contribution in the social media platforms, the survey conducted under the context of this research revealed that social media played a positive role in motivating women to work in both countries
Deep learning model for fully automated breast cancer detection system from thermograms
Breast cancer is one of the most common diseases among women worldwide. It is considered one of the leading causes of death among women. Therefore, early detection is necessary to save lives. Thermography imaging is an effective diagnostic technique which is used for breast cancer detection with the help of infrared technology. In this paper, we propose a fully automatic breast cancer detection system. First, U-Net network is used to automatically extract and isolate the breast area from the rest of the body which behaves as noise during the breast cancer detection model. Second, we propose a two-class deep learning model, which is trained from scratch for the classification of normal and abnormal breast tissues from thermal images. Also, it is used to extract more characteristics from the dataset that is helpful in training the network and improve the efficiency of the classification process. The proposed system is evaluated using real data (A benchmark, database (DMR-IR)) and achieved accuracy = 99.33%, sensitivity = 100% and specificity = 98.67%. The proposed system is expected to be a helpful tool for physicians in clinical use
11-(4-Methoxyphenyl)-3,3-dimethyl-2,3,4,5,10,11-hexahydro-1H-dibenzo[b,e][1,4]diazepin-1-one monohydrate
In the title compound, C22H24N2O2·H2O, the co-crystallized water molecule interacts with the N and O atoms of the molecule through Ow—H⋯N, Ow—H⋯O(methyl) and N—H⋯Ow hydrogen-bonding interactions. These hydrogen bonds, along with the intermolecular N—H⋯O=C hydrogen-bonding interactions, connect the molecules into a three-dimensional network. The dihedral angle between the two aromatic rings is 65.46 (10)°
Distributed Localization in Censored Wireless Sensor Networks with Binary Data
In this paper we investigate distributed localization of an intruder in wireless sensor networks (WSNs), in which the
sensor nodes (SNs) censor their transmission to the fusion center (FC). The SNs locally detect the intruder and send their decision only if it is positive. The FC, on the other hand, uses those binary data to localize the intruder. We present the censored maximum likelihood (cML) localization algorithm, Furthermore, we derive two computationally simple localization algorithms, the quadratic approximate ML (QAML) and the linear approximate ML (LAML). The performance of the ML-based algorithms significantly outperforms the heuristics-based algorithms, such as the centroid method (CM) and the center of maximum enclosing rectangle (CMER), as the simulation results show
Modelling and control of a multi-stage interleaved DC-DC converter with coupled inductors for super-capacitor energy storage system
Interleaved converters with coupled inductors are widely used to share load current in high power applications. It offers high equivalent switching frequency and reduced output current ripples using small size magnetic components. Due to smaller common-mode inductance, control system can be designed to achieve fast dynamic response. This paper proposes 8 channel interleaved DC/DC converter for interfacing super-capacitor energy storage system to a 400V DC voltage bus. Multi-stage interleaving magnetic circuit with two-phase coupling inductor as a building block is proposed. A methodology is developed to construct the model of the multi-stage magnetic circuit from the basic two-phase coupled inductor model. The derived model is successfully used to evaluate the system power losses and to design the magnetic circuit parameters and its current controller to fulfil the DC/DC converter steady state and dynamic performance specifications. A 20kW/four stage/8 channel DC/DC converter laboratory prototype has been built to connect a super-capacitor stack to 400V DC voltage bus. Experimental investigation validates the modeling, the system losses calculations and the design specifications of the system
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