The primary objective of this research be to develop a novel thought of fibrewise micro—topological spaces over B. We present the notions from fibrewise micro closed, fibrewise micro open, fibrewise locally micro sliceable, and fibrewise locally micro-section able micro topological spaces over B. Moreover, we define these concepts and back them up with proof and some micro topological characteristics connected to these ideas, including studies and fibrewise locally micro sliceable and fibrewise locally micro-section able micro topological spaces, making it ideal for applications where high-performance processing is needed. This paper will explore the features and benefits of fibrewise locally micro-sliceable and fibrewise locally

Solar cells has been assembly with electrolytes including I−/I−3 redox duality employ polyacrylonitrile (PAN), ethylene carbonate (EC), propylene carbonate (PC), with double iodide salts of tetrabutylammonium iodide (TBAI) and Lithium iodide (LiI) and iodine (I2) were thoughtful for enhancing the efficiency of the solar cells. The rendering of the solar cells has been examining by alteration the weight ratio of the salts in the electrolyte. The solar cell with electrolyte comprises (60% wt. TBAI/40% wt. LiI (+I2)) display elevated efficiency of 5.189% under 1000 W/m2 light intensity. While the solar cell with electrolyte comprises (60% wt. LiI/40% wt. TBAI (+I2)) display a lower efficiency of 3.189%. The conductivity raises with the

Background: Poly (methyl methacrylate) has been widely utilized for fabrication of dentures for many years as it has good advantages but not achieved all demands of the mechanical properties such as low transverse strength, low impact strength, low surface hardness, high water solubility and high water sorption. Material and method: To provide bonding between ZrO2 nanoparticles and PMMA matrix, the ZrO2 Nano-fillers were surface-treated with a saline coupling agent. Plasma surface treatment of polyethylene (PE) fiber was done to change surface fiber by using DC- glow discharge system. For characterization of interring any functional groups, the (FTIR) spectrum were done .then the mechanical properties studied to choose the appropriate perc

Background: Health professionals have a crucial role in promotion, support and management of breastfeeding. To be effective in this effort, the clinician should focus on the issue from the preconception stage through pregnancy and delivery, and continue in subsequent infant care. Aim of the study: to assess the effectiveness of the UNICEF/WHO 40-hour of breast feeding training through the assess breastfeeding knowledge and attitudes of the health profession staff before and after training course.

The herein research was carried out in order to identified the presence of bacteria in cervix and uterine lumen in Iraqi cattle during the different estrus phase with focusing on Protus and E coli. Estrus phases were determined by the structures which found on ovary (follicular growth for pro-estrus, mature growing follicle for estrus, hemorrhagic corpus luteam for meta-estrus and active corpus luteam for di-eatrus). Forty cervical swabs (ten for each estrus phase) and forty uterine swabs (ten for each estrus phase) were taken from macroscopically healthy reproductive animals after slaughtering and cultivated on nutrient agar and blood agar, the bacterial isolation were identified with biochemical teats. The present study found that

Cement-based adhesive (CBA) is used as a bonding agent in Carbon Fibre Reinforced Polymer (CFRP) applications as an alternative to epoxy-based adhesive due to the drawbacks of the epoxy system under severe service conditions which negatively affect the bond between the CFRP and strengthened elements. This paper reports the results of, an investigation carried out to develop two types of CBA using magnetized water (MW) for mixing and curing. Two magnetic devices (MD-I and MD-II), with different magnetic field strengths (9000 and 6000 Gauss) respectively, were employed for water magnetization. Different water flows with different water circulation times in the magnetizer were used for each device. Compressive and splitting tensile strength te

Photonic Crystal Fiber Fabry–Perot Interferometers (FPI) based on Surface Plasmon Resonance (SPR) was investigated in this paper in order to detect changes in photonic crystal fiber sensitivity with increasing temperature. FPI is composed of a PCF (ESM-12) solid core spliced with a single-mode fiber (SMF) on one side and a 40nm thick gold Nano film on the other. In order to obtain the SPR curve, the end of PCF can be spliced with the side of SMF before covering the gold film on the PCF. SPR results are included in the suggested sensor, based on the conclusions of the investigations. Resolution (R) is 0.0871, Signal-to-Noise Ratio (SNR) is 0.1867, a figure of merit (FOM) is 0.0069, and sensitivity (S) is 1.1481 . This sensor proposed is s

Metal nanoparticles can serve as an efficient nano-heat source with confinement photothermal effects. Thermo-plasmonic technology allows researchers to control the temperature at a nanoscale due to the possibility of precise light propagation. The response of opto-thermal generation of single gold-silica core-shell nanoparticle immersed in water and Poly-vinylpyrrolidone surrounding media is theoretically investigated. Two lasers (CW and fs pulses) at the plasmonic resonance (532 nm) are utilized. For this purpose, finite element method is used via COMSOL multiphysics to find a numerical computation of absorption cross section for the proposed core –shell NP in different media. Thermo-plasmonic response for both lasers is studied. The

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a