The neutrophil/ lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) have the potential to be inflammatory markers that reflect the activity of many inflammatory diseases. The aim of this study was to evaluate the NLR and PLR as potential markers of disease activity in patients with ankylosing spondylitis.

This investigation reports application of a mesoporous nanomaterial based on dicationic ionic liquid bonded to amorphous silica, namely nano-N,N,N′,N′-tetramethyl-N-(silican-propyl)-N′-sulfo-ethane-1,2-diaminium chloride (nano-[TSPSED][Cl]2), as an extremely effectual and recoverable catalyst for the generation of bis(pyrazolyl)methanes and pyrazolopyranopyrimidines in solvent-free conditions. In both synthetic protocols, the performance of this catalyst was very useful and general and presented attractive features including short reaction times with high yields, reasonable turnover frequency and turnover number values, easy workup, high performance under mild conditions, recoverability and reusability in 5 consecutive runs without lo

Mutations in genes encoding proteins necessary for detoxifying oxidative stress products have been predicted to increase susceptibility to lung cancer (LC). Despite this, the association between waterpipe tobacco smoking (WP), genetic polymorphisms, and LC risk remains poorly understood. This is the first study to explore the relationship between WP tobacco smoking and these genetic factors. Previously, we investigated the association of GSTP1 SNPs (rs1695-A/G and rs1138272-C/T) with LC in Iraqi males who smoke WP. Here, we expanded our analysis to include GSTM1 (active/null) and GSTT1 (active/null) genotypes, both individually and in combination with GSTP1 SNPs. Multiplex PCR and RFLP-PCR assays were utilized to determine the genotypes of

In this study, biodiesel was prepared from chicken fat via a transesterification reaction using Mussel shells as a catalyst. Pretreatment of chicken fat was carried out using non‐catalytic esterification to reduce the free fatty acid content from 36.28 to 0.96 mg KOH/g oil using an ethanol/ fat mole ratio equal to 115:1. In the transesterification reaction, the studied variables were methanol: oil mole ratio in the range of (6:1 ‐ 30:1), catalyst loading in the range of (9‐15) wt%, reaction temperature (55‐75 °C), and reaction time (1‐7) h. The heterogeneous alkaline catalyst was greenly synthesized from waste mussel shells throughout a calcin

Mature oil reservoirs surrounded with strong edge and bottom water drive aquifers experience pressure depletion and water coning/cresting. This laboratory research investigated the effects of bottom water drive and gas breakthrough on immiscible CO2-Assisted Gravity Drainage (CO2-AGD), focusing on substantial bottom water drive. The CO2-AGD method vertically separates the injected CO2 to formulate a gas cap and Oil. Visual experimental evaluation of CO2-AGD process performance was performed using a Hele-Shaw model. Water-wet sand was used for the experiments. The gas used for injection was pure CO2, and the “oleic” phase was n-decane with a negative spreading coefficient. The aqueous phase was deionized water. To evaluate the feasibilit

Aromaticity, antiaromaticity and chemical bonding in the ground (S0), first singlet excited (S1) and lowest triplet (T1) electronic states of disulfur dinitride, S2N2, were investigated by analysing the isotropic magnetic shielding, σiso(r), in the space surrounding the molecule for each electronic state. The σiso(r) values were calculated by state-optimized CASSCF/cc-pVTZ wave functions with 22 electrons in 16 orbitals constructed from gauge-including atomic orbitals (GIAOs). The S1 and T1 electronic states were confirmed as 11Au and 13B3u, respectively, through linear response CC3/aug-cc-pVTZ calculations of the vertical excitation energies for eight singlet (S1–S8) and eight triplet (T1–T8) electronic states. The aromaticities of S

This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi