223 research outputs found
A New Log Lindley Distribution with Applications
This paper introduces a new generalization of the Lindley distribution introduced by [1], using the basic idea of [2] and along the lines of [3]. The new distribution is a compound of the Lindley and logarithmic distributions. We refer to the new model as the logarithmic-Lindley (Log-L) distribution. This model is capable of modeling various shapes of aging and failure criteria. The properties of the Log-L model are discussed, and the maximum likelihood estimation method is used to evaluate the parameters involved. Finally, the usefulness of the new model for modeling reliability data is illustrated using a two real data sets with simulation study
Trusted Microservices: A Security Framework for Users' Interaction with Microservices Applications
Microservices architecture emerges as a promising software design approach that provides large scale soft-ware systems with flexibility, scalability and fault tolerance. Moreover, it is considered a suitable design to be implemented using software containers provided with several cloud providers. However, microservices suffer from several security challenges that hinder its progress. The concept of microservices is to break down the system functionality to a number of small coherent services. Hence, using microservices as a design approach increases the security risks by expanding the risk surface. In contrast to microservices, monolithic applica-tions are implemented as a bulk of codes using single programming language. Such environment has several drawbacks related to flexibility and maintainability, but limits security issues. On the other hand, microservices implementation uses several programming languages and frameworks to implement small units of system func-tionality. Such environment opens the door to new critical security issues. The proposed work introduces the problem of securing microservices and provides a novel approach to protect microservices applications from masquerade attacks. The proposed framework also provides high protection to users from malicious services. The framework was implemented using 150 software containers to define users' HTTP requests and a set of 20 microservices were tested to proof its applicability and benefits
Deep learning-based classification of eye diseases using Convolutional Neural Network for OCT images
Deep learning shows promising results in extracting useful information from medical images. The proposed work applies a Convolutional Neural Network (CNN) on retinal images to extract features that allow early detection of ophthalmic diseases. Early disease diagnosis is critical to retinal treatment. Any damage that occurs to retinal tissues that cannot be recovered can result in permanent degradation or even complete loss of sight. The proposed deep-learning algorithm detects three different diseases from features extracted from Optical Coherence Tomography (OCT) images. The deep-learning algorithm uses CNN to classify OCT images into four categories. The four categories are Normal retina, Diabetic Macular Edema (DME), Choroidal Neovascular Membranes (CNM), and Age-related Macular Degeneration (AMD). The proposed work uses publicly available OCT retinal images as a dataset. The experimental results show significant enhancement in classification accuracy while detecting the features of the three listed diseases
SIMULTANEOUS EXTRACTION AND RAPID HPLC BASED QUANTIFICATION OF CROCIN AND SAFRANAL IN SAFFRON (CROCUS SATIVUS L.)
Objective: Saffron (Crocus sativus L.) is one of the most valuable crops with high medicinal values used in many diseases. The aim of the study was to establish the reliability and rapid HPLC method for analysis of crocin and safranal concentration present in stigmata of saffron in the market as well as field grown samples.Methods: Field grown and market stigmata of saffron were used for extraction of crocin and safranal. The linear dynamic ranges were established after validating the robustness of critical method parameters. The Agilent1260-Infinity Quaternary LC system was used for the preparation of calibration standards and quantification of crocin and safranal in C. sativus stigmata.Results: A good linearity was achieved in the range of 10-30 µg for each compound with the determination coefficient (R2). The calibration curves revealed linear regression (r. 0.997) for this rapid HPLC method and limit of quantifications (LOQs) were achieved in the range of 3.4 µg/ml for crocin and 10.2 µg/ml for safranal. The limit of detection (LODs) for all standards was ≤4.2 µg/ml. The range of crocin content (10.43-16.32 mg/g) and safranal (5.19-5.21 mg/g) was estimated in saffron samples.Conclusion: This method may serve the purpose of accurate quantification of crocin and safranal present in the stigmata of the plant in a quick time period.Keywords: Saffron, Crocin, Safranal, Extraction, Quantification, HPL
Induced Sputum Substance P in Children with Difficult-to-Treat Bronchial Asthma and Gastroesophageal Reflux: Effect of Esomeprazole Therapy
Objectives. To assess the induced sputum substance P (ISSP) levels in children having difficult-to-treat asthma (DA) with and without gastroesophageal reflux (GER). We aimed also to evaluate the association of GER with childhood DA, relationship of GER severity with childhood asthma control test (C-ACT), FEV1, peak expiratory flow (PEF) variability, and ISSP. Finally, we tried to evaluate esomeprazole treatment effect on C-ACT and FEV1 in children with DA. Methods. Spirometry, C-ACT, upper gastrointestinal endoscopy, and ISSP measurement were done for children with DA compared to healthy controls. Results. ISSP was high in DA with higher levels in the group having associated GER. In the latter group, ISSP and C-ACT improved significantly after esomeprazole treatment while FEV1 and PEF variability did not improve. Reflux severity was positively correlated with ISSP and negatively correlated with FEV1. Conclusions. GER was found in 49% of our patients with childhood DA. Very high ISSP levels in children with DA may be used as a marker for presence of GERD. Esomeprazole therapy improved asthma symptoms but did not improve lung function
Burning velocity measurement of lean methane-air flames in a new nanosecond DBD microplasma burner platform
This paper presents the initial characterization of a new burner design to study the effect of non-thermal plasma
discharge on combustion characteristics at atmospheric pressure. The burner allows stabilizing an inverted cone
flame in a mixture flowing through a perforated plate designed as a microplasma reactor. The design principle of
the microplasma reactor is based on the dielectric barrier discharge scheme which helps to generate a stable nonthermal
plasma discharge driven by nanosecond high-voltage pulses in the burner holes. The consumed power
and pulse energy have been calculated from simultaneously measurements of current and voltage of the electrical
pulses. Time-resolved measurements of direct emission spectra for nitrogen second positive system N2(C-B)
have been done to determine the rotational and vibrational temperatures of the plasma discharge. By fitting the
spectra with SPECAIR simulation data, it was found that the rotational and vibrational temperatures are 480 K
and 3700 K, respectively, for the discharge in methane-air mixture with an equivalence ratio of 0.5 at atmospheric
pressure. The influence of a high-voltage (5 kV) pulsed nanosecond discharge on the laminar burning
velocity of methane-air flame has been investigated over a range of equivalence ratios (0.55–0.75). The laminar
burning velocity was calculated by the conical flame area method which has been validated by other published
data. CH* chemiluminescence image analysis has been applied to accurately determine the flame area. The
results show an increase of the burning velocity of about 100% in very lean (Φ= 0.55) flames as a result of the
plasma discharge effect
Worldwide reduction in MERS cases and deaths since 2016
Since 2012, Middle East respiratory syndrome (MERS) coronavirus has infected 2,442 persons worldwide. Case-based data analysis suggests that since 2016, as many as 1,465 cases and 293–520 deaths might have been averted. Efforts to reduce the global MERS threat are working, but countries must maintain vigilance to prevent further infections
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