Microbial fuel cell is a device that uses the microorganism metabolism for the production of electricity under specific operating conditions. Double chamber microbial fuel cell was tested for the use of two cheap electrode materials copper and aluminum for the production of electricity under different operating conditions. The investigated conditions were concentration of microorganism (yeast) (0.5- 2 g/l), solutions temperature (33-45 ^oC) and concentration of glucose as a substrate (1.5- 6 g/l). The results demonstrated that copper electrode exhibit good performance while the performance of aluminum is poor. The electricity is generated with and without the addition of substrate. Addition of glucose substrate

The structural, optical and photoelectrical properties of fabricated diffusion heterojunction (HJ) solar cell, from n-type c-Si wafer of [400] direction with Boron, has been studied. AgAl alloys was used because of its properties that affect as a good connection materials. TiO2 has been used as a reflecting layer to increase the absorption radiation. The HJ has direct allowed energy gap equal to 3.1 eV. The c-Si/B HJ solar cell yielded has an active area conversion efficiency of 16.4% with an open circuit voltage of (Voc) 0.592V, short circuit current (Isc) of 2.042mA, fill factor (F.F) of 0.682 and % =10.54.

Abstract. Silver, Indium Selenium thin film with a thickness (5001±30) nm, deposited by thermal evaporation methods at RT and annealing3temperature (Ta=400, 500 and 600) K on a substrate of glass to study structural and optical properties of thin films and on p-Si wafer to fabricate the AgInSe2/p-Si heterojunction solar cell. XRD analysis shows that the AgInSe2 (AIS) deposited film at RT and annealing3temperature (Ta=400, 500 and 600) K have polycrystalline structure. The average grain size has been estimated from AFM images. The energy gap was estimated from the optical transmittance using a spectrometer type (UV.-Visible 1800 spectra photometer). From I-V characterization , the photovoltaic parameters such as, open-circuit voltage, short

due to the presence of chemoresistance and the risk of tumor recurrence and metastasis. There is a pressing necessity to develop efficient treatments to improve response for treatment and increase prolong survival of breast cancer patients. Photodynamic therapy (PDT) has attracted interest for its features as a noninvasive and relatively selective cancer treatment. This method relies on light-activated photosensitizers that, upon absorbing light, generate reactive oxygen species (ROS) with powerful cell-killing outcomes. Nuclear factor kappa B (NF-κB), a transcription factor, plays a key role in cancer development by regulating cell proliferation, differentiation, and survival. Inhibiting NF-κB can sensitize tumor cells to chemotherapeuti

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

Background: Diabetes mellitus a major factor that has adverse effects on the vascular system and the heart. It causes an increase in cardiac muscle thickness, resulting in decreased compliance and increased peripheral arterial stiffness. This study aims to assess the left ventricular mass (LVM) and left ventricular hemodynamic changes in diabetic patients measured by Doppler echocardiography. Patients and Methods: The study included 50 diabetic patients ranging in age between 25 and 80 years, (mean age: 54.1 ± 15.10, 19 males, 31 females) and 50 healthy subjects, aged 25 to 80 years (mean age: 48.52 ± 14.45, 11 males, 39 females). Doppler echocardiography was used to assess left ventricular function. The measurements included