In this work, an enhanced Photonic Crystal Fiber (PCF) based on Surface Plasmon Resonance (SPR) sensor using a sided polished structure for the detection of toxic ions Arsenic in water was designed and implemented. The SPR curve can be obtained by polishing the side of the PCF after coating the Au film on the side of the polished area, the SPR curve can be obtained. The proposed sensor has a clear SPR effect, according to the findings of the experiments. The estimated signal to Noise Ratio (SNR), sensitivity (S), resolution (R), and Figures of merit (FOM) are approaching; the SNR is 0.0125, S is 11.11 μm/RIU, the resolution is 1.8x〖10〗^(-4), and the FOM is 13.88 for Single-mode Fiber- Photonic Crystal Fiber- single mode Fiber (SMF-P

Neutral and semi-synthetic hydrophilic polymers are widely used

in pharmaceutical technology to fomlUlate as controlled release drugs

delivery systems ,cellulose derivatives is biocompatibilily, biodegradability , non-toxicity, its is a good candidate as drug carrier. In this study, polymers were used as cellulose derivatives like Methylcellulose (MC) & Soditun Carboxymetl1ylcellulose (NaCMC) as hydrogels for controlled delivery for two kinds of drugs, Cefotaxine

& Amoxycill ine trihydrate i n different media (Distilled water, Normal Saline & Buffer solution  PH=2). It has been shown that for sodium Carboxymethylcellulnse the drug release rate is more than the Mcthylcellulose and that the release

Barium–doped TiO2 / n-Si photodetector was fabricated by spray pyrolysis exhibited visible enhancement responsivity profile with peak response at 600 nm flat response between 650 and 900 nm. The quantum efficiency was 30% and specific detectivity was 5x1012 W-1Hz1/2cm at peak response. The GaAlAs laser diode was used to estimate the rise time of the detector.

In this work, the spectra of plasma glow produced by Nd:YAG laser operated at 1.064 μm on Al-Mg alloys with same molar ratio samples in air were analyzed by comparing the atomic lines of aluminum and magnesium with that of strong standard lines. The effect of laser energies on spectral lines, produced by laser ablation, were investigated using optical spectroscopy, the electron density was measured utilizing the Stark broadening of magnesium-aluminum lines and the electron temperature was calculated from the standard Boltzmann plot method. The results that show the electron temperature increases in magnesium and aluminum targets but decreases in magnesium: aluminum alloy target, also show the electron density increase all the aluminum,

  In this research we study one of the pollutants(Gelbstoff ) such as Humic  and Fulvic Acids  in tap waters by using the technique of  Raman, Flora to some regions of Baghdad , the results appear that the tap waters  were pollutants which know yellow substance or Gelbstoff instant of suspending waters, which appear through the scattering of the incident light to same the wave length of Raman ,also calculate Raman shift which was 3640 cm-1 and force constant to band (O – H ) was 743 N/m, where the peak of Raman was at the wave length 441 nm after used the excitation wave length 380 nm . The results were in an agreement with lectures [8][9][10].

A rapid high performance liquid chromatography method for the determination of sphinganine (Sa) and sphingosine (So) in urine samples by employing a silica-based monolithic column is described. The samples were first extracted using ethyl acetate and derivatized using ortho-phthaldialdehyde in the presence of 2-mercaptoethanol. C20 sphinganine was used as internal standard. Under the optimized conditions, separation was achieved using a mixture of methanol:water (93:7, v/v), column temperature at 30°C, flow rate of 1 mL min−1, and an injection volume of 10 μL. Good linearity was obtained for Sa and So over the concentration range 20–500 ng mL−1(correlation coefficients ≥0.9978). The detection limits were 0.45 ng mL−1 for Sa and

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti