Schiff bases (Sh1-Sh3) have been synthesized (p-aminophenol) was condensed with different aromatic aldehyde in ethanol inthe presence of glacial acetic acid as catalyst. These Schiff bases on treatment with monochloroacetyl choride gave 3-chloro-1-(4-hydroxyphenyl)-4-(substituted)azetidin-2-one(Az4-Az6), with αmercaptoacetic acid gave 3-(4-hydroxyphenyl)-2-( substituted)thiazolidin-4-one (Th7-Th9) and with anthranilic acid gave 3-(4-hydroxyphenyl)-2(substituted)-2,3-dihydroquinazolin-4(1H)-one (Qu10-Qu12). The purity of the derivatives was confirmed by TLC. The some compoundsidentify by (FT-IR and1H, 13C-NMR) data. Some of derivatives were evaluated activity against several microbesto determine ability to inhibit bacterial in some h

As the word can fluctuate between central and peripheral dlalten it represents the first lexical meaning and the second represents the meaning that gain by the context in which it appear so this research came to show signs that can be acquired the root ( GUM ) and its derivatives from the contexts in which it is mentioned in the Koran as well as siqnificant Lexical if this research is divided on two first is eating Lexical semantics , the second handled connotations in the Koran was based on what the commentators and concemed with the meanings of the Koran and the owners Almagamat in astatement that the semantic .

Amoxicillin 1 was treated with thiosemicarbazide and Phosphoryl chloride to obtain a new derivatives that contains 1,3,4-thiadiazole moiety 2. Schiff bases compounds were synthesized by the reaction of compound 2 with different aldehydes such as benzaldehyde and some substituted Benzaldehyde; p-hydroy, p-Chloro, p-Nitro, p-Dimethylamino, p-Methyl, p-Methoxy, p-Ethoxy to give compounds 3a-h. The obtained compounds have tested towards gram -ve and gram +ve bacteria. The compound shows good to moderate result towards the bacteria.

A fluorescence microscopy considered as a powerful imaging tool in biology and medicine. In addition to useful signal obtained from fluorescence microscopy, there are some defects in its images such as random variation in brightness, noise that caused by photon detection and some background pixels in the acquired fluorescence microscopic images appear wrongly auto-fluorescence property. All these practical limitations have a negative impact on the correct vision and analysis of the fluorescent microscope users. Our research enters the field of automation of image processing and image analysis using image processing techniques and applying this processing and analysis on one of the very important experiments in biology science. This research

This study proposes a pioneering Ethical Artificial Intelligence (EAI) framework for advancing sustainable development in Iraq by integrating eight multidimensional sustainability indicators—administrative, technological, economic, environmental, social, legal, security, and governance. Utilizing data from 60 completed development projects, the framework combines SPSS statistical analysis, the SMART-AI model, and Artificial Neural Networks (ANN) to identify key determinants of project success and failure. Results reveal a 37% project failure rate, with administrative and technological deficiencies emerging as the most influential predictors. The SMART-AI model achieved an accuracy of 91.3% using stratified k-fold cross-validation. A bilin

A true random TTL pulse generator was implemented and investigated for quantum key distribution systems. The random TTL signals are generated by low cost components available in the local markets. The TTL signals are obtained by using true random binary sequences based on registering photon arrival time difference registered in coincidence windows between two single – photon detectors. The true random TTL pulse generator performance was tested by using time to digital converters which gives accurate readings for photon arrival time. The proposed true random pulse TTL generator can be used in any quantum -key distribution system for random operation of the transmitters for these systems

 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.