In this study, the flexural performance of a new composite beam–slab system filled with concrete material was investigated, where this system was mainly prepared from lightweight cold-formed steel sections of a beam and a deck slab for carrying heavy floor loads as another concept of a conventional composite system with a lower cost impact. For this purpose, seven samples of a profile steel sheet–dry board deck slab (PSSDB/PDS) carried by a steel cold-formed C-purlins beam (CB) were prepared and named “composite CBPDS specimen”, which were tested under a static bending load. Specifically, the effects of the profile steel sheet (PSS) direction (parallel or perpendicular to the span of the specimen) using different C-purlins configurations (double sections connected face-to-face, double separate sections, and a single section) were investigated. The research discussed the specimens’ failure modes, flexural behavior, bending capacity, bending strain relationships, and energy absorption index of specimens. Generally, the CBPDS specimens with the PSS slab placed in a parallel direction achieved approximately a 13–40% higher bending capacity compared with the corresponding specimens with a perpendicular PSS direction (depending on the configuration of the beam). Fabricating the beam of the CBPDS specimen with double C-purlins (face-to-face) led to more effective concrete confinement behavior compared with the double separate C-purlins beam. The related specimen recorded a 10% higher bending capacity. Finally, the suggested composite CBPDS system exhibited a sufficient energy absorption capability of the static bending load because it demonstrated high strength and high ductility.
This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ
... Show MoreThis research is an attempt to study aspects of syntactic deviation in AbdulWahhab Al-Bayyati with reference to English. It reviews this phenomenon from an extra-linguistic viewpoint. It adopts a functional approach depending on the stipulates of systemic Functional Grammar as developed by M.A.K. Halliday and others adopting this approach. Within related perspective, fairly’s taxonomy (1975) has been chosen to analyze the types of syntactic deviation because it has been found suitable and relevant to describe this phenomenon. The research hypothesizes that syntactic deviation is pervasive in Arabic poetry, in general and in Abdul-Wahhab Al-Bayyati Poetry in specific, and can be analyzed in the light of systemic Functional Grammar
... Show MoreBackground: The present study aimed to assess the distribution, prevalence, severity of malocclusion in Baghdad governorate in relation to gender and residency Materials and Methods: A multi-stage stratified sampling technique was used in this investigation to make the sample a representative of target population. The sample consisted of 2700 (1349 males and 1351 females) intermediate school students aged 13 years representing 3% of the total target population. A questionnaire was used to determine the perception of occlusion and orthodontic treatment demand of the students and the assessment procedures for occlusal features by direct intraoral measurement using veriner and an instrument to measure the rotated and displaced teeth. Results a
... Show MoreMultiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of
... Show MoreThe electrocardiogram (ECG) is the recording of the electrical potential of the heart versus time. The analysis of ECG signals has been widely used in cardiac pathology to detect heart disease. The ECGs are non-stationary signals which are often contaminated by different types of noises from different sources. In this study, simulated noise models were proposed for the power-line interference (PLI), electromyogram (EMG) noise, base line wander (BW), white Gaussian noise (WGN) and composite noise. For suppressing noises and extracting the efficient morphology of an ECG signal, various processing techniques have been recently proposed. In this paper, wavelet transform (WT) is performed for noisy ECG signals. The graphical user interface (GUI)
... Show MorePsoriasis is a complex autoimmune disorder characterized by skin inflammation with keratinocyte proliferation, and 85% of cases present as plaque-type psoriasis. Biologics such as ustekinumab (UST) are highly successful therapies for psoriasis. To achieve maximum clinical efficacy while minimizing undesirable effects, therapeutic drug monitoring (TDM) for biologics has emerged. This study aims to measure the UST trough level (TL) and anti-drug antibodies (ADAs) and to evaluate clinical response in Iraqi patients with moderate-to-severe psoriasis in order to make appropriate recommendations for modifying therapy. This cross-sectional study enrolled 75 patients, divided into two groups: Group 1, patients who achieved the UST target TL (≥0.6
... Show MoreTraffic‐induced ground vibrations cause significant problems for residents and nearby structures. Reducing the effect of these vibrations on the neighboring environment is a key challenge, particularly in urban areas. This study presents both numerical and experimental investigations of the performance of mass scatters for screening ground vibrations. A three‐dimensional numerical model is validated and extended to conduct a comparative study on the efficiency of three geotechnical methods of isolation. These methods include trench barriers, wave‐impeding blocks (WIBs), and mass scatters. The results showed that mass scatters represent an efficient way of scattering ground vi
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for