Background: Normal thyroid function is essential for neonatal growth and brain development. In a newborn infant with severe disease, endocrine regulation of hormones can be affected by abnormal metabolism. The assessment of thyroid parameters results in the recognition of a dysfunction and its association with disease severity. Objective: This study aimed to assess thyroid function profiles in critically ill neonates in the neonatal intensive care unit (NICU) compared with healthy controls. Additionally, we aimed to detect the presence of TD and its possible association with critical illness. Methods: A case-control study was performed in 100 neonates, comprising 50 sick neonates and 50 healthy controls. We measured thyroid functio

The steel jetty selected for strengthening is in Baghdad city, over Tigris River, consists of 55 short spans, each of approximately 4 meters and one naviga-tional opening of 12 m. The bridge is 224 meters length and 8 meters in width. The strengthening system was designed to remove overstresses that occurred when the bridge was subjected to abnormal loads of 380 tons. A strengthening system which installed in spring 2008 was used where the main concept is to depend on added side supporting elements which impose reversal forces on the bridge to counteract most of the loads expected from the abnormal heavy loads. The bridge was load tested before and after the strengthening system was activated. The load test results indicate that the strengt

<p>Energy and memory limitations are considerable constraints of sensor nodes in wireless sensor networks (WSNs). The limited energy supplied to network nodes causes WSNs to face crucial functional limitations. Therefore, the problem of limited energy resource on sensor nodes can only be addressed by using them efficiently. In this research work, an energy-balancing routing scheme for in-network data aggregation is presented. This scheme is referred to as Energy-aware and load-Balancing Routing scheme for Data Aggregation (hereinafter referred to as EBR-DA). The EBRDA aims to provide an energy efficient multiple-hop routing to the destination on the basis of the quality of the links between the source and destination. In

This study employs wavelet transforms to address the issue of boundary effects. Additionally, it utilizes probit transform techniques, which are based on probit functions, to estimate the copula density function. This estimation is dependent on the empirical distribution function of the variables. The density is estimated within a transformed domain. Recent research indicates that the early implementations of this strategy may have been more efficient. Nevertheless, in this work, we implemented two novel methodologies utilizing probit transform and wavelet transform. We then proceeded to evaluate and contrast these methodologies using three specific criteria: root mean square error (RMSE), Akaike information criterion (AIC), and log

An annular two-phase, steady and unsteady, flow model in which a conductingfluid flow under the action of magnetic field is concavely. Two models arepresented, in the model one; the magnetic field is perpendicular to the long side ofthe channel, while in the model two is perpendicular to the short side. Also, westudy, to some extent the single-phase liquid flow.It is found that the motion and heat transfer equations are controlled by differentdimensionless parameters namely, Reynolds, Hartmann, Prandtl, and Poiseuilleparameters. The Laplace transform technique is used to solve each of the motion andheat transfer equations. The effects of each of dimensionless parameters upon thevelocity and heat transfer is analyzed.A comprehensive study fo

The fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c