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Abstract The use of nanomaterials and nanostructures have been revolutionizing the advancements of science and technology in various engineering and medical fields. As an example, Carbon Nanotubes (CNTs) have been extensively used for the improvement of mechanical, thermal, electrical, magnetic, and deteriorative properties of traditional composite materials for applications in high-performance structures. The exceptional materials properties of CNTs (i.e., mechanical, magnetic, thermal, and electrical) have introduced them as promising candidates for reinforcement of traditional composites. Most structural configurations of CNTs provide superior material properties; however, their geometrical shapes can deliver different features and characteristics. As one of the unique geometrical configurations, helical CNTs have a great potential for improvement of mechanical, thermal, and electrical properties of polymeric resin composites.

Abstract Soft actuators with pneumatic network have innovative potential applications in medical and rehabilitation areas. The performance of this kind of actuators is determined by the design of chambers and the properties of the active extensible layer and the passive inextensible layer. In this article, actuator with isosceles trapezoidal chambers is proposed. Orthogonal experiment design and finite element method are used to optimize the structure of actuators. Results indicate that adding constrain-limiting paper in the passive layer can significantly reduce the bending radius. Position of the paper in the passive layer also affects the bending radius. Actuators with trapezoidal chambers can have a smaller bending radius compared with that with rectangle chambers. The bending radius decreases as the ratio of short base to long base of trapezoid decreases. Increasing the number density of chambers can further reduce the bending radius.

Significant growth of Unmanned Aerial Vehicles (UAV) has unlocked many services and applications opportunities in the healthcare sector. Aerial transportation of medical cargo delivery can be an effective and alternative way to ground-based transport systems in times of emergency. To improve the security and the trust of such aerial transportation systems, Blockchain can be used as a potential technology to manage, operate and monitor the entire process. In this paper, we present a blockchain network solution based on Ethereum for the transportation of medical cargo such as blood, medicines, vaccines, etc. The smart contract solution developed in solidity language was tested using the Truffle program. Ganache blockchain test network was employed to host the blockchain network and test the operation of the proposed blockchain model. The suitability of the model is validated in real-time using a UAV and all the flight data are captured and uploaded into the blockchain.

Mass is one important suspicious object for breast cancer diagnosis in mammograms. Computer-aided detection (CAD) based on fully supervised deep learning achieves high performance for mass detection in mammograms. The lack of fine-grained expert labels becomes the bottleneck for the large-scale application of CAD to achieve detection in mammograms. Weakly supervised methods provide a solution to tackle the annotation problems, including in the application for mass detection. However, previous works face the problem of insufficient localization information, which affect the ability of mass detection. In this paper, we propose a multi-view enhancing mass detection network (MVMDNet) with dual view inputs that contains craniocaudal (CC) and mediolateral oblique (MLO) view of mammograms, where different view features are interacted and fused to enhance localization information.

Abstract The demand for contactless, rapid manufacturing has increased over the years, especially during the COVID-19 pandemic. Additive manufacturing (AM), a type of rapid manufacturing, is a computer-based system that precisely manufactures products. It proves to be a faster, cheaper, and more efficient production system when integrated with cloud-based manufacturing (CBM). Similarly, the need for semiconductors has grown exponentially over the last five years. Several companies could not keep up with the increasing demand for many reasons. One of the main reasons is the lack of a workforce due to the COVID-19 protocols. This article proposes a novel technique to manufacture semiconductor chips in a fast-paced manner. An algorithm is integrated with cloud, machine vision, sensors, and email access to monitor with live feedback and correct the manufacturing in case of an anomaly.

Abstract The hot corrosion studies for the die-casted magnesium (Mg) silver (Ag) alloys are carried out through the steam heating route. The Magnesium Silver (QE22A) alloy is fixed under the top lid of the pressure cooker (2 liters) and filled with water and 5% salt (NaCl) solution. The specimens are treated with different time intervals (10, 20, and 30 minutes), with the steam temperature maintained at 100°C around the specimen. The results showed an increase in the corrosion rate with the increase in the steaming time. Further, after the specimens have cooled down to room temperature, similar experiments are repeated for the second and third cycles. Here the formation of the oxide layers over the specimen has reduced the corrosion rate. The structural, surface study was carried out through scanning electron microscopy (SEM), X-ray diffraction (XRD), and energy-dispersive spectroscopy (EDS) to know the corrosion behavior on the specimen.

This SAE Standard establishes the performance specifications for the zero-tolerance breath alcohol detection system to reduce the risks of driving under the influence of alcohol. It defines the accuracy and precision requirements of the breath alcohol concentration (BrAC) measurement, as well as the acceptability criteria and key parameters to test these requirements. Additionally, this standard sets the performance requirements of the system for ethanol sensitivity, the response time, and the electrical, mechanical, and environmental conditions the system may encounter throughout the lifespan of the vehicle.

This monograph covers the fundamentals, fabrication, testing, and modeling of ambient energy harvesters based on three main streams of energy-harvesting mechanisms: piezoelectrics, ferroelectrics, and pyroelectrics. It addresses their commercial and biomedical applications, as well as the latest research results. Graduate students, scientists, engineers, researchers, and those new to the field will find this book a handy and crucial reference because it provides a comprehensive perspective on the basic concepts and recent developments in this rapidly expanding field.

Laser Detecting Systems Enhancing Survivability and Lethality on the Battlefield Designing With Plastics for Military Equipment Engine Air-Brakes Paving the Way to Quieter Aircraft Nett Warrior Enhancing Battlefield Connectivity and Communications XPONENTIAL 2018 - An AUVSI Experience Communications in Space: A Deep Subject First Air-Worthy Metal-Printed RF Filter Ready for Takeoff Validation of Automated Prediction of Blood Product Needs Algorithm Processing Continuous Non-Invasive Vital Signs Streams (ONPOINT4) Using a combination of non-invasive sensors, advanced algorithms, and instruments built for combat medics could reduce hemorrhaging and improve survival rates. Calculation of Weapon Platform Attitude and Cant Using Available Sensor Feedback Successful development of mobile weapon systems must incorporate operation on sloped terrain.

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