103 research outputs found
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A numerical study on slip flow heat transfer in micro-poiseuille flow
This paper was presented at the 3rd Micro and Nano Flows Conference (MNF2011), which was held at the Makedonia Palace Hotel, Thessaloniki in Greece. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, Aristotle University of Thessaloniki, University of Thessaly, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute.In the present study, two-dimensional incompressible momentu and energy equations are solved with slip velocity and temperature jump boundary conditions in a parallel plate micro channel. The computations are performed for micro channels with CHF (Constant heat flux) boudary conditions to obtain heat transfer characteristics of gaseous flow in slip regime. The effects of creep flow and viscous dissipation are neglected in this study. The numerical methodology is based on Semi-Implicit method for pressure-linked equations (SIMPLE) method. The governing equations are developed by using perturbation expansions of velocity, pressure and temperature fields. It was found that Nusselt number and was substantially reduced for slip flow regimes compared with the continuum flows. The obtained solutions are compared with available numerical and analytical results and found that present study has good agreement with that works
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Modeling of micro flows using perturbation method
This paper was presented at the 3rd Micro and Nano Flows Conference (MNF2011), which was held at the Makedonia Palace Hotel, Thessaloniki in Greece. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, Aristotle University of Thessaloniki, University of Thessaly, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute.A new method for modeling micro flows is presented in this research. The basis of this method is the development of governing continuum equations on fluid dynamics using perturbation expansion of the velocity, pressure, density and temperature fields in dependence of Knudsen number. In the present work, we use three-term perturbation expansions and reach three order of equations O(1), O(Kn), O(Kn2). Required
boundary conditions (BC) for solving each order of these equations are obtained by substitution of the perturbation expansions into the general boundary conditions for the velocity slip and temperature jump. This set of equations is discretized in two-dimensional state on a staggered grid using the finite volume method. A three-part computer program has been produced for solving the set of discretized equations. Each part of this code, solve one order of the equations with the SIMPLE algorithm. Incompressible slip micro Poiseuille and micro Couette flows are solved either analytically or numerically using the perturbation method (PM). Good agreement is found between analytical and numerical results in the low Knudsen numbers, whereas numerical results deviate from analytical results by increasing the Knudsen number. The
results of perturbation method are also compared with the results obtained from different slip models
The effect of Bifidobacterium bifidum supernatant and cell mass on the proliferation potential of rat bone marrow-derived stromal cells
Background: Mesenchymal stem cells (MSCs) are widely used to treat various diseases, however, their proliferative potential reduces after a number of passages. It has been shown that some probiotics such as Bifidobacterium bifidum (B. bifidum) affect the proliferation of various cell lineages. The present study aimed to investigate the effect of B. bifidum on the proliferation of rat bone marrow stromal cells (rBMSCs) and to develop a method for compensating their proliferation reduction after some passages. Methods: The present experimental study was conducted at Tehran University of Medical Sciences, Tehran, Iran, in 2017. The stromal cells were isolated from rBMSCs and their mesenchymal properties were confirmed by osteogenic and adipogenic differentiation media and staining. B. bifidum was cultured and the B. bifidum supernatant (BS) and bacterial cell mass (BCM) were extracted. The rBMSCs were treated with different concentrations of BS and BCM. The MTT assay was performed to measure the number of viable cells in the culture. Cell proliferation was analyzed using the paired-sample t test. Results: Cell proliferation increased as the concentration of bacteria was increased logarithmically (0, 0.1, 0.3, 0.9, 3, 9, 30 μL/mL). In comparison with BS, cells treated with BCM showed increased cell proliferation at lower concentrations. This effect was caused by removing the �de Man, Rogosa, and Sharpe� (MRS) broth medium from the BCM culture. The optimal concentration of bacteria with the most significant effect on rBMSCs proliferation was determined. Conclusion: A significant increase in the proliferation of stromal cells was observed; confirming the stimulatory potential of probiotics (B. bifidum) on various cells. The use of products containing probiotic bacteria can increase the proliferation potential of BMSCs. © 2020, Shiraz University of Medical Sciences. All rights reserved
Multi-view Face Detection Using Deep Convolutional Neural Networks
In this paper we consider the problem of multi-view face detection. While
there has been significant research on this problem, current state-of-the-art
approaches for this task require annotation of facial landmarks, e.g. TSM [25],
or annotation of face poses [28, 22]. They also require training dozens of
models to fully capture faces in all orientations, e.g. 22 models in HeadHunter
method [22]. In this paper we propose Deep Dense Face Detector (DDFD), a method
that does not require pose/landmark annotation and is able to detect faces in a
wide range of orientations using a single model based on deep convolutional
neural networks. The proposed method has minimal complexity; unlike other
recent deep learning object detection methods [9], it does not require
additional components such as segmentation, bounding-box regression, or SVM
classifiers. Furthermore, we analyzed scores of the proposed face detector for
faces in different orientations and found that 1) the proposed method is able
to detect faces from different angles and can handle occlusion to some extent,
2) there seems to be a correlation between dis- tribution of positive examples
in the training set and scores of the proposed face detector. The latter
suggests that the proposed methods performance can be further improved by using
better sampling strategies and more sophisticated data augmentation techniques.
Evaluations on popular face detection benchmark datasets show that our
single-model face detector algorithm has similar or better performance compared
to the previous methods, which are more complex and require annotations of
either different poses or facial landmarks.Comment: in International Conference on Multimedia Retrieval 2015 (ICMR
A randomized controlled clinical trial evaluating quality of life when using a simple acupressure protocol in women with primary dysmenorrhea
Objective: To evaluate a simple acupressure protocol in LIV3 and LI4 acupoints in women with primary dysmenorrhea.
Methods: This paper reports a randomized, single blinded clinical trial. 90 young women with dysmenorrhea were recruited to three groups to receive 20 minutes acupressure every day in either LIV3 or LI4, or placebo points. Acupressure was timed five days before menstruation for three successive menstrual cycles. On menstruation, each participant completed the Wong Baker faces pain scale, and the quality of life short form -12 (QOL SF-12).
Results: Intensity and duration of pain between the three groups in the second and third cycles during the intervention (p<0.05) differed significantly. Significant differences were seen in all domains of QOL except for mental health (p=0.4), general health (p=0.7) and mental subscale component (p=0.12) in the second cycle, and mental health (p=0.9), and mental subscale component (p=0.14) in the third cycle.
Conclusion: Performing the simple acupressure protocol is an effective method to decrease the intensity and duration of dysmenorrhea, and improve the QOL.
Key words: Dysmenorrhea, acupressure, quality of life
Registration ID in IRCT: IRCT2016052428038N
АДАПТИВНОЕ УПРАВЛЕНИЕ ПРИЛОЖЕНИЯМИ МОБИЛЬНЫХ ТЕЛЕФОНОВ ДЛЯ УВЕЛИЧЕНИЯ ПРОДОЛЖИТЕЛЬНОСТИ ИХ АВТОНОМНОЙ РАБОТЫ
Modern mobile phones are multifunctional devices that provide users various services and alternative communication channels for the transmission of information by installing applications on them. Utilization of such applications causes to increasing of the energy consumption of mobile phones and, as a result, to the reduction of their battery life. An approach to increasing of the mobile phones functioning duration due to the adaptive control of the applications used on them is suggested in the article.Современные мобильные телефоны являются многофункциональными устройствами, обеспечивающими посредством установки на них приложений предоставление пользователям различных услуг и альтернативных каналов связи для передачи информации. Применение таких приложений обуславливает рост энергопотребления мобильных телефонов и, как следствие, сокращение времени их автономной работы. В статье предложен подход к увеличению продолжительности функционирования мобильных телефонов за счет адаптивного управления используемыми на них приложениями
Voltammetric aptasensors for protein disease biomarkers detection: a review
"Available online 24 May 2016"An electrochemical aptasensor is a compact analytical device where the bioreceptor (aptamer) is coupled to a transducer surface to convert a biological interaction into a measurable signal (current) that can be easily processed, recorded and displayed. Since the discovery of the Systematic Evolution of Ligands by Enrichment (SELEX) methodology, the
selection of aptamers and their application as bioreceptors has become a promising tool in the design of electrochemical aptasensors. Aptamers present several advantages that highlight their usefulness as bioreceptors such as chemical stability, cost effectiveness and ease of modification towards detection and immobilization at different transducer surfaces. In this review, a special emphasis is given to the potential use of electrochemical aptasensors for the detection of protein disease biomarkers using voltammetry techniques. Methods for the immobilization of aptamers onto electrode surfaces are discussed, as well as different
electrochemical strategies that can be used for the design of aptasensors.The authors acknowledge the financial support from the Strategic
funding of UID/BIO/04469/2013 unit, from Project POCI-01-0145-
FEDER-006984 – Associate Laboratory LSRE-LCM funded by FEDER
funds through COMPETE2020 - Programa Operacional Competitividade
e Internacionalização (POCI) – and by national funds through FCT -
Fundação para a Ciência e a Tecnologia and project ref. RECI/BBB-EBI/
0179/2012 (project number FCOMP-01-0124-FEDER-027462) and S.
Meirinhos's doctoral grant (ref SFRH/BD/65021/2009) funded by
Fundação para a Ciência e a Tecnologia
Effect of Crumb Rubber on Mechanical Properties of Crushed Recycled Pavement Materials
Due to the increase of construction wastes and end-of-life tyres, recycling of the waste concrete and scrape tyre have become an important issue around the world. Therefore, the aim of this research is to study the effect of crumb rubber on strength properties of recycled concrete aggregate (RCA) as base/subbase pavement layers. In this study, crumb rubber with particle size of 10-15 mm was added to 20 mm RCA at 0.5, 1 and 2% by weight percentages of the RCA, and the strength properties of the samples were examined by unconfined compression strength as well as resilient modulus tests. It was concluded that addition of crumb rubber resulted in decreasing the UCS and resilient modulus, and increasing the toughness in terms of failure strain and deformability index
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Boosting algorithms for detector cascade learning
The problem of learning classifier cascades is considered. A new cascade boosting algorithm, fast cascade boosting (FCBoost), is proposed. FCBoost is shown to have a number of interesting properties, namely that it 1) minimizes a Lagrangian risk that jointly accounts for classification accuracy and speed, 2) generalizes adaboost, 3) can be made cost-sensitive to support the design of high detection rate cascades, and 4) is compatible with many predictor structures suitable for sequential decision making. It is shown that a rich family of such structures can be derived recursively from cascade predictors of two stages, denoted cascade generators. Generators are then proposed for two new cascade families, last-stage and multiplicative cascades, that generalize the two most popular cascade architectures in the literature. The concept of neutral predictors is finally introduced, enabling FCBoost to automatically determine the cascade conffguration, i.e., number of stages and number of weak learners per stage, for the learned cascades. Experiments on face and pedestrian detection show that the resulting cascades outperform current state-of-the-art methods in both detection accuracy and speed. © 2014 Mohammad Saberian and Nuno Vasconcelos
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