Numerous blood biomarkers are altered in COVID-19 patients; however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus. The study was aimed to identify patient groups with a high and low risk of developing COVID-19 using a cluster analysis of several biomarkers. 137 women with confirmed SARS CoV-2 RNA testing were collected and analyzed for biochemical profiles. Two-dimensional automated hierarchy clustering of all biomarkers was applied, and patients were sorted into classes. Biochemistry marker variations (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) have split COVID-19 patients into two groups(severe cases and non-severe cases groups). Ferritin, lactate dehydrogenase LDH, D-dimer and CRP were markedly increased in COVID-19 patients in the first group (severe cases). Our findings imply that early measured levels of (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) are linked to a decreased probability of COVID-19 severity. Elevated levels of this biomarker may predict COVID severity development.
In this paper, integrated quantum neural network (QNN), which is a class of feedforward
neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that
... Show MoreSpeech recognition is a very important field that can be used in many applications such as controlling to protect area, banking, transaction over telephone network database access service, voice email, investigations, House controlling and management ... etc. Speech recognition systems can be used in two modes: to identify a particular person or to verify a person’s claimed identity. The family speaker recognition is a modern field in the speaker recognition. Many family speakers have similarity in the characteristics and hard to identify between them. Today, the scope of speech recognition is limited to speech collected from cooperative users in real world office environments and without adverse microphone or channel impairments.
The proposed design of neural network in this article is based on new accurate approach for training by unconstrained optimization, especially update quasi-Newton methods are perhaps the most popular general-purpose algorithms. A limited memory BFGS algorithm is presented for solving large-scale symmetric nonlinear equations, where a line search technique without derivative information is used. On each iteration, the updated approximations of Hessian matrix satisfy the quasi-Newton form, which traditionally served as the basis for quasi-Newton methods. On the basis of the quadratic model used in this article, we add a new update of quasi-Newton form. One innovative features of this form's is its ability to estimate the energy functio
... Show MoreAbstract. In this work, some new concepts were introduced and the relationship between them was studied. These concepts are filter directed-toward, nano-closure-directed-toward and nano-closure-converge to point, and some theories and results about these concepts were presented. A definition almost-nano-converges for set, almost-nano-cluster-point, and definition of quasi-nano-Hausdorff-closed and was also called nano-Hausdorff-closed relative, were also presented several theories related to these definitions were presented and the relationship between them was studied . We also provided other generalizations, including nano closure continuous mappings and it was also called as nano-weaklycontinuous- mappings, as well as providing a definit
... Show MoreThis study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat
... Show MoreSand production in unconsolidated reservoirs has become a cause of concern for production engineers. Issues with sand production include increased wellbore instability and surface subsidence, plugging of production liners, and potential damage to surface facilities. A field case in southeast Iraq was conducted to predict the critical drawdown pressures (CDDP) at which the well can produce without sanding. A stress and sanding onset models were developed for Zubair reservoir. The results show that sanding risk occurs when rock strength is less than 7,250 psi, and the ratio of shear modulus to the bulk compressibility is less than 0.8 1012 psi2. As the rock strength is increased, the sand free drawdown and depletion becomes larger. The CDDP
... Show Moreأن صفة التغير المتسارع في نمط الحياة ولّد مبدأ اللايقين عند إتخاذ القرارات المالية لأي ظاهرة عموماً أو نشاط إقتصادي على وجه الخصوص. وهذا يتطلب الأستعانة بالأدوات الأحصائية كمنهج علمي يساعد في وصفها وتحليلها كمياً ومن ثم التنبؤ بها مستقبلاً كمحاولة لسبر غور اللايقين الذي يكتنف المستقبل كمجهول يتوجس منه الجميع. وقد أصبح متخذ القرار الأستثماري أو صاحب رأس المال وغيرهما من المضاربين والمتعاملين في الاسواق الما
... Show MoreThe aim of this paper is to derive a posteriori error estimates for semilinear parabolic interface problems. More specifically, optimal order a posteriori error analysis in the - norm for semidiscrete semilinear parabolic interface problems is derived by using elliptic reconstruction technique introduced by Makridakis and Nochetto in (2003). A key idea for this technique is the use of error estimators derived for elliptic interface problems to obtain parabolic estimators that are of optimal order in space and time.
تلعب الاعتمادات المستندية دوراً كبيراً وخطيراً في التجارة الدولية باعتبارها إحدى أوسع أدوات الدفع انتشاراً في العالم سواءاً كان ذلك بالنسبة للمستورد أم للمصدر وتغطيتها للمخاطر المحتملة لكلا الطرفين، فهي تؤمن للمصدر استلام قيمة البضاعة بالكامل عند تنفيذها لشروط العقد، ويسمح للمستورد بعدم الدفع إلا بعد إتمام شحن البضاعة وتقديم المستندات المطلوبة واستلامها.
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... Show MoreThe deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the
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