Construction projects are complicated in nature and require many considerations in contractor selection. One of the complicated interactions is that between performance with the project size, and contractor financial status, and size of projects contracted. At the prequalification stage, the financial ‎requirements restrict the ‎contractors to meet minimum limits in financial criteria such as net worth, working capital and ‎annual turnover, etc. In construction projects, however, there are cases when contractors meet these requirements but show low performance in practice. The model used in the study predicts the performance by training of a neural network. The data used in the study are 72 of the most recent roadw

Rutting in asphalt mixtures is a very common type of distress. It occurs due to the heavy load applied and slow movement of traffic. Rutting needs to be predicted to avoid major deformation to the pavement. A simple linear viscous method is used in this paper to predict the rutting in asphalt mixtures by using a multi-layer linear computer programme (BISAR). The material properties were derived from the Repeated Load Axial Test (RLAT) and represented by a strain-dependent axial viscosity. The axial viscosity was used in an incremental multi-layer linear viscous analysis to calculate the deformation rate during each increment, and therefore the overall development of rutting. The method has been applied for six mixtures and at different tem

by in situ polymerization of aniline monomer, conducting polyaniline (PANI) nanocomposites containing various concentrations of carboxylic acid functionalized multi-walled carbon nanotubes (f-MWCNT) were synthesized. The morphological and electrical properties of pure PANI and PANI /MWCNT nanocomposites were examined by using Fourier transform- infrared spectroscopy (FTIR), X-ray diffraction (XRD) and Atomic Force Microscopy (AFM) respectively. FTIR spectra shows that the carboxylic acid groups formed at the both ends of the sidewalls of the MWCNTs. The aniline monomers were polymerized on the surface of MWCNTs, depending on the -* electron interaction between aniline monomers and MWCNTs and hydrogen bonding into interaction between t

Coagulation is the most important process in drinking water treatment. Alum coagulant increases the aluminum residuals, which have been linked in many studies to Alzheimer's disease. Therefore, it is very important to use it with the very optimal dose. In this paper, four sets of experiments were done to determine the relationship between raw water characteristics: turbidity, pH, alkalinity, temperature, and optimum doses of alum [   .14 O] to form a mathematical equation that could replace the need for jar test experiments. The experiments were performed under different conditions and under different seasonal circumstances. The optimal dose in every set was determined, and used to build a gene expression model (GEP). The models were co

Background: Acute leukemias (ALs) are a heterogeneous group of malignancies with various clinical, morphological, immunophenotypic, and molecular characteristics. Distinguishing between lymphoid and myeloid leukemia is often performed by flow cytometry. This study aimed to evaluate the immunophenotypic characterization and expression of immuno-markers in both acute myeloid leukemia (AML-M0) and acute T-cell lymphoblastic leukemia (T-ALL).

Methods: A retrospective cross-sectional study was conducted in the Pathology Department/Teaching Laboratories/Medical City/Iraq and included all patients newly diagnosed with AL from 5 January to 10 December 2018. Immunophenotypic analysis wa

Influential, organized groups with natural antimicrobial and anti-biofilm broad-spectrum power exist within the food chain, like a hidden dormant mimic hygienic bio life nanobodies that can terminate multiple opportunistic disease entities owing multi-stress resistant forbidden recalcitrant power, such as Candida albicans. These wonderful dynamic forces created by ALLAH Almighty are the Mycophages or fungi-eating state of fungi foodborne phages, and this project was redirected to be a dare to leap from us towards the future. Multi-stress resistant C. albicans that are resistant to different antifungal agents with their genetic tolerance plasticity to thermal pasteurization decontamination module as well as to ultraviolet irradiation

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

      In this work, a weighted H lder function that approximates a Jacobi polynomial which solves the second order singular Sturm-Liouville equation is discussed. This is generally equivalent to the Jacobean translations and the moduli of smoothness. This paper aims to focus on improving methods of approximation and finding the upper and lower estimates for the degree of approximation in weighted H lder spaces by modifying the modulus of continuity and smoothness. Moreover, some properties for the moduli of smoothness with direct and inverse results are considered.

Sequence covering array (SCA) generation is an active research area in recent years. Unlike the sequence-less covering arrays (CA), the order of sequence varies in the test case generation process. This paper reviews the state-of-the-art of the SCA strategies, earlier works reported that finding a minimal size of a test suite is considered as an NP-Hard problem. In addition, most of the existing strategies for SCA generation have a high order of complexity due to the generation of all combinatorial interactions by adopting one-test-at-a-time fashion. Reducing the complexity by adopting one-parameter- at-a-time for SCA generation is a challenging process. In addition, this reduction facilitates the supporting for a higher strength of cove

Error control schemes became a necessity in network-on-chip (NoC) to improve reliability as the on-chip interconnect errors increase with the continuous shrinking of geometry. Accordingly, many researchers are trying to present multi-bit error correction coding schemes that perform a high error correction capability with the simplest design possible to minimize area and power consumption. A recent work, Multi-bit Error Correcting Coding with Reduced Link Bandwidth (MECCRLB), showed a huge reduction in area and power consumption compared to a well-known scheme, namely, Hamming product code (HPC) with Type-II HARQ. Moreover, the authors showed that the proposed scheme can correct 11 random errors which is considered a high