Numerous tests are recently conducted to assess vibration's role in accelerating the heat transfer rate in various heat exchangers. In this work, the enhancement of heat transfer by the effect of transfer vibration and inclination angles on the surface of a double pipe heat exchanger experimentally has been investigated. A data acquisition system is applied to record the data of temperatures, flow rates, and frequencies over the tests. A compound technique was adopted, including the application of a set of inclination angles of (0°, 10°, 20°, and 30°) under the effect of frequency of vibration ranging from sub-resonance to over-resonance frequencies. The results showed that the overall heat transfer coefficient enhan

The current study was designed to evaluate the anti-inflammatory effect of GKB in the rat model of granulomatous inflammation. Thirty rats were distributed into five groups:  The first group served as negative control group that received distilled water (DW) only without inducting inflammation, positive control group; treated with DW with the induction of inflammation and they were assigned to cotton pellet-induced granuloma, ginkgo biloba (GKB) treated group (200mg/kg/day), dexamethasone-treated group (1mg/kg), and Prednisolone treated group (5mg/kg). All the treatments were given orally for seven consecutive days.  On day eight, the rats were anesthetized and the pellets together with granulation tissue were carefully removed

         The Na-alginate bead is commonly used in biotechnology fields such as adsorption due to ion exchange between Ca and Na with elements. Scanning electron microscopy (SEM-EDX) has proven to be a comparative method in the detections of these adsorbed elements, but the un-flat forming area of beads that can introduce impossible of the detection of element adsorbed. In contrast, X-ray fluorescence (XRF) documents analysis of elements, direct examination, which may analysis the adsorbents of elements. Here, this Study evaluated the possibility by using XRF for the direct analysis for examples of Cd and Ag in a bench stand. This Study compared this to commonly use

Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T