The present work establishes and validates HILIC strategies simple, accurate, exact and precise in pure form and inpharmaceutical dosage for separating and determining theophylline. These methods are developed on HILIC theophyllineseparation in columns ZIC2 and ZIC3. The eluent was prepared by mixing buffer (20% sodium acetate-40 mM, pH 5.5), 80%acetonitrile. The flow rate is 0.8 mL/min, with gradient elution and UV detection at 270 nm. In the ZIC2 and ZIC3 columns oftheophylline determining, the concentration range was 0.01-4μg.ml-1. The lower limit of detection and quantification fortheophylline were determined as 0.130, 0.190 μg.ml-1 and accuracy were 99.70%, 99.58% on ZIC2 and ZIC3, respectively. TheHILIC methods developed and validat

Recent research looking for acknowledgment of strategically influence of Robinson and self question at progressing the reading comprehension for students of sixth class .

To achieve research goal so the researcher mentally chose primary sixth class  at  the school (Tashti the primary) that followed education directorate of province (Jamjamal)/Suliymania for the scholastic year 2012-2013 as application field for their experiment of boys' number reached to (95) (female and male)students in reality (32) of the first experimental group and (31) student (female and male) from controlled group, the researcher rewarded between of three variable groups (timing period, intelligence ,Kurdish language degr

The behavior of AC conductivity (σ_ac), loss tangent (tan δ), and relative permittivity (ε′) for composites of PVC-P/graphite electrode waste (GEW) was investigated, and a qualitative explanation was provided as a function of PVC-P weight fractions (0, 5, 10, 15, 20, and 25) wt. percent, temperature (30-90) °C, and frequency (100Hz-2MHz). The behaviors of the composites' ac. conductivity and impedance as a frequency function and temperature have been examined. The permittivity was shown to rise with increasing temperature (Tg). The relative permittivity increased as the GEW filler concentration increased and was highest in the low-frequency range; nevertheless decreased as the frequency increased.

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The porosity of materials is important in many applications, products and processes, such as electrochemical devices (electrodes, separator, active components in batteries), porous thin film, ceramics, soils, construction materials, ..etc. This can be characterized in many different methods, and the most important methods for industrial purposes are the N2 gas adsorption and mercury porosimetry. In the present paper, both of these techniques have been used to characterize some of Iraqi natural raw materials deposits. These are Glass Sand, Standard Sand, Flint Clay and Bentonite. Data from both analyses on the different types of natural raw materials deposits are critically examined and discussed. The results of specific surface are

This paper is concerned with pre-test single and double stage shrunken estimators for the mean (?) of normal distribution when a prior estimate (?0) of the actule value (?) is available, using specifying shrinkage weight factors ?(?) as well as pre-test region (R). Expressions for the Bias [B(?)], mean squared error [MSE(?)], Efficiency [EFF(?)] and Expected sample size [E(n/?)] of proposed estimators are derived. Numerical results and conclusions are drawn about selection different constants included in these expressions. Comparisons between suggested estimators, with respect to classical estimators in the sense of Bias and Relative Efficiency, are given. Furthermore, comparisons with the earlier existing works are drawn.

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The current study deals with the performance of constructed wetland (CW) incorporating a microbial fuel cell (MFC) for wastewater treatment and electricity generation. The whole unit is referred to as CW-MFC. This technique involves two treatments; the first is an aerobic treatment which occurs in the upper layer of the system (cathode section) and the second is anaerobic biological treatment in the lower layer of the system (anode section). Two types of electrode material were tested; stainless steel and graphite. Three configurations for electrodes arrangement CW-MFC were used. In the first unit of CW-MFC, the anode was graphite plate (GPa) and cathode was also graphite plate (GPc), in the second CW-MFC unit, the anode was stainless st