BACKGROUNDS Nasoalveolar molding (NAM) application is among presurgical management (PSM) techniques used for infants with cleft lip and palate (CLP). It helps to approximate the palatal cleft and to reshape the nasoalveolar complex prior to primary lip repair. This study aimed to explore types of PSM and the dental speciality provision for infants with CLP in Baghdad. The status of NAM usage and surgeons’ perceptions toward NAM usage were assessed. MATERIALS AND METHODS This is a cross-sectional paper-based questionnaire study that collected responses of surgeons perform primary lip and nose repair regarding PSM. The questionnaire was distributed amongst public and private hospitals in Baghdad. Twenty surgeons were enrolled (only those su
... Show MoreA simple, rapid, sensitive and inexpensive approach is described in this work based on a combination of solid‐phase extraction of 8‐hydroxyquinoline (8HQ), for speciation and preconcentration of Cr(III) and Cr(VI) in river water, and the direct determination of these species using a flow injection system with chemiluminescence detection (FI–CL) and a 4‐diethylamino phenyl hydrazine (DEAPH)–hydrogen peroxide system. At different pH, the two forms of chromium [Cr(III) and Cr(VI)] have different exchange capacities for 8HQ, therefore two columns were constructed; the pH of column 1 was adjusted to pH 3 for retaining Cr(III) and column 2 was adjusted to pH 1 for retaining of Cr(VI). The sorbe
Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T
... Show MoreThis paper presents the non-linear finite element method to study the behavior of four reinforced rectangular concrete MD beams with web circular openings tested under two-point load. The numerical finite elements methods have been used in a much more practical way to achieve approximate solutions for more complex problems. The ABAQUS /CAE is chosen to explore the behavior of MD beams. This paper also studies, the effect of both size and shape of the circular apertures of MD beams. The strengthening technique that used in this paper is externally strengthening using CFRP around the opening in the MD beams. The numerical results were compared to the experimental results in terms of ultimate load failure and displace
... Show MoreThe two objectives of the current research are :-
- Uncover the views and opinions of the students of Artistic Education Department about the relation between educational novelty and its relation with visual .
- Identifying the capabilities of the students of artistic education department .
The society of the research is the fourth class students of artistic education department - College of Fine Arts ( 83 students from both sexes ) . It was chosen ( 60 ) students sample of from both sexes by the researcher in order to conduct test upon them .The researcher has adopted descr
... Show MoreIn this research study Hardness (shore D), Water absorption,
Flexural, Impact Test, and Fracture Toughness of polymer nano
composites. The polymer nano composites based on unsaturated
polyester resin reinforced with Kevlar fibers (K.F). The samples are
attended by hand lay – up method according to (Rule mixture) for
various volume fractions of unsaturated polyester resin, fiber and
carbon nanotube. The polyester resin was matrix strengthened with
3% volume fraction from Kevlar fiber and (0.5%, 1%, 1.5%, 2%)
volume fractions of carbon nanotube. The water absorption, hardness
(shore D), flexural test, impact test and toughness fracture properties
were studied. Results showed that the water absorption increas
This paper deals with the preparation and investigation studies of a number of new complexes of Cu(II) , Zn(II) , Hg(II) , Ag(I) , Pt(IV) and Pb(II).The complexes were formed by the reaction of the mentioned metal ions with the ligand which is derived from oxadiazole (OXB), 2- (2-butyl) thio-5- phenyl – 1,3,4 – oxadiazole in the mole ratio (1:1) , (1:2) and (1:3) (metal to ligand ).The result complexes having general formulae :M(OXB)Cl2] [M(OXB)X2]H2O [ M= Cu(II) , Zn(II) M= Hg(II) , Pb(II) [M(OXB)2 X2] X= Cl– M = Cu (II), Zn (II), Hg (II), Pb (II) X= Cl–, NO3-, CH3COO- [Pt(OXB)3]Cl4 [Ag(OXB)]NO32-(2-??????? ) ???? -5- ???
... Show MoreThe inverse kinematics of redundant manipulators has infinite solutions by using conventional methods, so that, this work presents applicability of intelligent tool (artificial neural network ANN) for finding one desired solution from these solutions. The inverse analysis and trajectory planning of a three link redundant planar robot have been studied in this work using a proposed dual neural networks model (DNNM), which shows a predictable time decreasing in the training session. The effect of the number of the training sets on the DNNM output and the number of NN layers have been studied. Several trajectories have been implemented using point to point trajectory planning algorithm with DNNM and the result shows good accuracy of the end
... Show MoreThis paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback
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