120 research outputs found
Introduction to bio-based materials
No full textBio-based materials can be defined as goods that are primarily made of a substance or compounds obtained from biomass, which can exist naturally or be synthesized. They can also be products of processes that employ biomass. Strictly speaking, a lot of everyday materials, such as paper, wood, and leather, can be called bio-based materials; nevertheless, the phrase is usually used to describe contemporary materials that have undergone more intensive processing. Biocomposites, solvents, polymers, and bulk chemicals are among the materials derived from biomass sources. The numerous methods used to transform biomass components into fuels and products with added value fall into one of two general categories: thermochemical or biochemical. Additionally, conventional enzyme separation, fermentation, and plant breeding—the three primary biotechnological processes—are employed. Although this claim is being extensively examined, bio-based materials are thought to offer potentially greener substitutes than their petroleum-based competitors. Emerging bio-based materials that could rival traditional materials are a constant source of innovation, and the possibilities for incorporating them into both new and established goods are only now being investigated
Handbook of Bio-Based Materials for Smart Manufacturing
No full textIn recent years, the convergence of biotechnology and manufacturing has ushered in a new era of sustainable innovation and efficiency. Incorporating bio-based materials into smart manufacturing processes has become a crucial strategy to minimize environmental impact, promote circularity, and propel technological advancements across various industries. This handbook, divided into four key sections, is a comprehensive overview and a holistic approach to the principles, applications, challenges, and opportunities associated with integrating bio-based materials into modern manufacturing practices.Handbook of Bio-Based Materials for Smart Manufacturing begins with an exploration of fundamental characteristics, properties, and processing techniques. From bio-based polymers to composites and blends, readers will gain insights into the diverse array of materials derived from renewable biomass sources and their potential applications in smart manufacturing environments. The handbook illustrates the role of bio-based materials in additive manufacturing, coatings, packaging, energy applications, automotive, aerospace, construction, biomedical, textiles, electronics, and more, showcasing the versatility and adaptability of these materials across various sectors.By examining emerging trends, future directions, and the vision for sustainable manufacturing practices, readers will gain valuable insights into the changing landscape of bio-based materials and their potential impact on the future of smart manufacturing. This handbook is a valuable resource for researchers, engineers, industry professionals, and students seeking to deepen their understanding of bio-based materials and their role in driving sustainable innovation in manufacturing.</div
Prediction of Bitcoin Price using Data Mining
No full textBitcoin is a computerized digital money and exchange network, represents an essential change in financial sectors, an interesting number of customers and excellent evaluation of channel inspection. In this research, dataset related to ten cryptocurrencies are used and created a new dataset by taking the closing price of each cryptocurrency for the research goal to ascertain how the direction and accuracy of price of the Bitcoin can be predicted by using data mining methods. Features engineering evaluated that all the ten cryptocurrencies are strongly correlated with each other. The task is achieved by implementation of supervised learning method in which random forest, support vector classifier, gradient boosting classifier, and neural network classifier are used under classification category and linear regression, recurrent neural network, gradient boosting regressor are used under regression category. In the classification category, support vector classifier achieved the highest accuracy of 62.31% and precision value 0.77. In regression category, gradient boosting regressor got the highest R-squared value 0.99
Monitoring Blood Flow in Animal Models Using a Camera-Based Technique
Get PDFBlood flow dynamics plays a critical role in maintaining tissue health, as it delivers nutrients and oxygen while removing waste products. It is especially important when there is a disruption in cerebral autoregulation due to trauma, which can induce ischemia or hyperemia and can lead to secondary brain injury. Thus, there is a need for noninvasive techniques that can allow continuous monitoring of blood flow during intervention. Optical techniques have become increasingly practical for measuring blood flow due to their non-invasive, continuous, and relatively lower-cost nature. This research focused on developing a low-cost, scalable optical technique for measuring blood flow by implementing speckle contrast optical spectroscopy using a fiber-camera-based approach. This technique is particularly well-suited for measuring blood flow in deep tissues, such as the brain, which is challenging to access using traditional optical methods. A two-channel continuous wave speckle contrast optical spectroscopy device was developed, and the device was rigorously tested using phantoms. Then, it is applied to monitor blood flow changes in the brain following traumatic brain injury (TBI) in mice. The results indicate that trauma-induced significant blood flow decreases consistent with the recent literature. Overall, this approach provides noninvasive continuous measurements of blood flow in preclinical models such as traumatic brain injury
Contextual Suggestions Based on Driving Stage and Context
Full text linkA framework for providing suggestions based on drive context is described. Described techniques can be implemented in virtual assistant or other software accessed via a device directly installed in a vehicle or available via a user mobile device paired with a vehicle infotainment system. With user permission, a drive context and a drive stage (e.g., pre-drive, active drive, end of drive) is determined based on one or more user-permitted factors, and is utilized along with other permitted contextual information to generate a ranked list of suggestions for activities such as media playback, communication actions (calls, messages, etc.), etc. and of informational content. The top ranking suggestions are provided to the user via a user interface. User selection of the suggestions can trigger user-requested actions such as starting media playback, placing a call, etc
Monitoring Cerebral Functional Response using sCMOS-based High Density Near Infrared Spectroscopic Imaging
Get PDFNeurovascular coupling is an important concept that indicates the direct link between neuronal electrical firing with the vascular hemodynamic changes. Functional Near Infrared Spectroscopy (fNIRS) can measure changes in cerebral vascular parameters of oxy-hemoglobin and deoxyhemoglobin concentrations and thus can provide neuronal activity through neurovascular coupling. Currently many commercial fNIRS devices are available, but they are limited by the number of channels (usually having only 8 detectors), which can limit the sensitivity, contrast, and resolution of imaging. High-density imaging can improve sensitivity, contrast, and resolution by providing many measurements and averaging the signals originating from the target cerebral focus area compared to background tissue. Here a multi-channel, low-cost, high-density imaging system based on scientific CMOS (Complementary Metal-Oxide-Semiconductor) detector will be presented. The CMOS camera is fiber-coupled such that on one end fibers are focused on the pixels on the CMOS camera, which allows individual pixels (or binned sub-pixels) to act as detectors, while the other end of the fibers can be positioned on a wearable optical probe. After the device details, I will show the device validation using a series of the dynamic flow phantom experiments mimicking the brain activation and finally human motor cortex experiments (finger tapping experiments). The results demonstrate that this system can obtain high-density data sets with higher contrast and resolution. This wearable, high-density optical neuroimaging technology is expected to find many applications including pediatric neuroimaging at clinics and assessing human cognitive performance
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