Action of a New Material on Storage of Single Base Propellant

For safety purpose during the storage of single base propellant it is important to study all factors which will act on its components through this period. This study is more demanded on changing the source of raw material. Thermal decomposition and applying of Berthelot's law helped in determination of storage period of a single base propellant after its preparation from Sudan cotton linters as a new raw material.     

An Improved Deep Structure for Accurately Brain Tumor Recognition

Brain neoplasms are recognized with a biopsy, which is not commonly done before decisive brain surgery. By using Convolutional Neural Networks (CNNs) and textural features, the process of diagnosing brain tumors by radiologists would be a noninvasive procedure. This paper proposes a features fusion model that can distinguish between no tumor and brain tumor types via a novel deep learning structure. The proposed model extracts Gray Level Co-occurrence Matrix (GLCM) textural features from MRI brain tumor images. Moreover, a deep neural network (DNN) model has been proposed to select the most salient features from the GLCM. Moreover, it manipulates the extraction of the additional high levels of salient features from a proposed CNN model. Finally, a fusion process has been utilized between these two types of features to form the input layer of additional proposed DNN model which is responsible for the recognition process. Two common datasets have been applied and tested, Br35H and FigShare datasets. The first dataset contains binary labels, while the second one splits the brain tumor into four classes; glioma, meningioma, pituitary, and no cancer. Moreover, several performance metrics have been evaluated from both datasets, including, accuracy, sensitivity, specificity, F-score, and training time. Experimental results show that the proposed methodology has achieved superior performance compared with the current state of art studies. The proposed system has achieved about 98.22% accuracy value in the case of the Br35H dataset however, an accuracy of 98.01% has been achieved in the case of the FigShare dataset.     

Alkylaminomethylation and Chloromethylation of 2,3-Diphenyl Hydroxybenzofurans

The application of the Mannich reaction to 2,3-diphenyl-5-hydroxybenzofuran 1 a and 2,3-diphenyl-6-hydroxybenzofuran 2 a , which gives rise to the corresponding aminomethyl derivatives 1 b – i and 2 b – i is described. Chemical, analytical and spectroscopic results are in a accord with the assigned structures. Attempted chloromethylation of compounds 1 a and 2 a afforded only the methylene-bis-compounds 3 and 4 , respectively.     

Wireless charging for cardiac pacemakers based on class-D power amplifier and a series–parallel spider-web coil

Biomedical implants (BMIs) and biomedical sensors (BMSs) help to improve quality of life, detect diseases, provide monitoring of vital signs, and take over the role of malfunctioning organs. These implants and sensors require continuous battery power to work effectively, but the batteries used are restricted by their limited capacity and lifetime. This research reported here involved the design and implementation of a wireless charging system based on a series–parallel spider-web coil (WPT-SP-SWC), specifically for cardiac pacemakers. The experimental design investigated several important parameters, including air gap, applied source voltage, coil size, and operating frequency. Performance metrics were evaluated in terms of output DC voltage, delivered output power, and power transfer efficiency. The target voltage was 5 V, which is adequate to charge a BMI such as a pacemaker, and three source voltages (5, 15, and 25 V) were tested. The design was examined at six operating frequencies, ranging from 1.78 MHz to 6.78 MHz. The most favorable results were achieved at 1.78 MHz. Power transfer efficiencies at a 10 mm air gap were 95.75% and 92.08% for applied voltages of 5 V and 15 V, respectively. The effectiveness of the proposed system was also validated by comparing the findings with previous articles.     

A data-driven controller for position tracking of a long-stroke piezoelectric actuator

Microsystem Technologies - Hysteresis and other nonlinearities exhibited by piezoelectric materials significantly limit the tracking capability of piezoelectric actuators (PAs). To eliminate these...     

Programming Delayed Dissolution Into Sacrificial Bioinks For Dynamic Temporal Control of Architecture within 3D-Bioprinted Constructs

Sacrificial printing allows introduction of architectural cues within engineered tissue constructs. This strategy adopts the use of a 3D-printed sacrificial ink that is embedded within a bulk hydrogel which is subsequently dissolved to leave open-channels. However, current conventional sacrificial inks do not recapitulate the dynamic nature of tissue development, such as the temporal presentation of architectural cues matching cellular requirements during different stages of maturation. To address this limitation, a new class of sacrificial inks is developed that exhibits tailorable and programmable delayed dissolution profiles (1–17 days), by exploiting the unique ability of the ruthenium complex and sodium persulfate initiating system to crosslink native tyrosine groups present in non-chemically modified gelatin. These novel sacrificial inks are also shown to be compatible with a range of biofabrication technologies, including extrusion-based printing, digital-light processing, and volumetric bioprinting. Further embedding these sacrificial templates within cell-laden bulk hydrogels displays precise control over the spatial and temporal introduction of architectural features into cell-laden hydrogel constructs. This approach demonstrates the unique capacity of delaying dissolution of sacrificial inks to modulate cell behavior, improving the deposition of mineralized matrix and capillary-like network formation in osteogenic and vasculogenic culture, respectively.     

Vertical Pod Autoscaling in Kubernetes for Elastic Container CollaborativeFramework

Kubernetes is an open-source container management tool which automates container deployment, container load balancing and container(de)scaling, including Horizontal Pod Autoscaler (HPA), Vertical Pod Autoscaler (VPA). HPA enables flawless operation, interactively scaling the number of resource units, or pods, without downtime. Default Resource Metrics, such as CPU and memory use of host machines and pods, are monitored by Kubernetes. Cloud Computing has emerged as a platform for individuals beside the corporate sector. It provides cost-effective infrastructure, platform and software services in a shared environment. On the other hand, the emergence of industry 4.0 brought new challenges for the adaptability and infusion of cloud computing. As the global work environment is adapting constituents of industry 4.0 in terms of robotics, artificial intelligence and IoT devices, it is becoming eminent that one emerging challenge is collaborative schematics. Provision of such autonomous mechanism that can develop, manage and operationalize digital resources like CoBots to perform tasks in a distributed and collaborative cloud environment for optimized utilization of resources, ensuring schedule completion. Collaborative schematics are also linked with Bigdata management produced by large scale industry 4.0 setups. Different use cases and simulation results showed a significant improvement in Pod CPU utilization, latency, and throughput over Kubernetes environment.