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Economic Indicators of the College Station-Bryan MSA, December 2023
No full textThe Business-Cycle Index increased to 232 in October 2023 compared to 231 in September. The local unemployment rate remained unchanged at 3.3% in October compared to September. Local nonfarm employment increased by 0.10% from September to October. October��������s inflation-adjusted taxable sales were up by 2.4% from September. Among comparable college towns, the percentage of 20-24 aged residents was highest in the College Station-Bryan MSA at 17.6%
Elevation Tracking Using Wearables and Machine Learning
No full textThe increased integration of technology in emergency management situations has enhanced communication among first responders during critical incidents. Current initiatives in the commercial health and fitness tracking spheres aim to improve indoor location tracking, but these techniques have not been applied to emergency scenarios due to a lack of precision in elevation. While most commercial wearable devices can classify lateral movement with precision, the z-axis poses a challenge for these devices and requires increased precision for high-stress situations. The objective of this research is to develop a compact wearable device, approximately the size of a phone and worn on the bicep, that uses machine learning to accurately classify elevation. This implementation uses a suite of sensors including absolute orientation, acceleration, pressure, temperature, and heart rate sensors. The integration of these sensors aims to facilitate precise classification of activities linked to elevation gain for use in emergency scenarios and general fitness scenarios. An example of the emergency scenario use case is a firefighter in a burning building. If a firefighter passes out within a burning building, this device can notify a fire captain and determine the exact location of the emergency responder with improved elevation accuracy. This device also improves the general fitness example by allowing for more precise statistics on floor climbed data and distinguishing automatic versus manual movement. Notably, existing research in this domain lacks comprehensive coverage of edge cases, particularly in distinguishing between manual and automatic activities during elevation changes. The primary insight for this prototype is floors climbed. The collaborative efforts of the Hardware and Power Supply Lead, Microcontroller and Database Lead, Machine Learning Lead, and Android Application Developer are integral to the successful realization of this solution. Overall, this research contributes to advancing the field of wearable technology by enhancing the accuracy of elevation change classification and expanding the capabilities of fitness and health monitoring devices
Solar Energy Powered Extraction for Essential Oils
No full textBy concentrating on three main goals, the proposed research project aims to meet the increasing demand for environmentally friendly and sustainable methods in the production of essential oils: obtaining essential oils from locally grown plants and food waste, utilizing extraction methods powered by renewable energy, and creating a thorough life cycle assessment framework. This multidisciplinary strategy seeks to close knowledge gaps, encourage creative and ecologically conscious activities, and optimize the project's potential benefits and influence across several industries; personal hygiene and the food industry to name a few. Essential oils, prized for their aromatic and therapeutic properties, have gained increased recognition, particularly post-COVID-19. They are produced through various methods, including traditional techniques like hydro distillation and steam distillation, each accompanied by its set of challenges. These challenges have paved the way for the emergence of modern technologies such as supercritical fluid extraction (SFE) to address them. The drawbacks of traditional methods include reliance on non-renewable energy sources, potential degradation of essential oils due to heat, and limitations in the scope of essential oil applications. The advent of SFE represents a contemporary solution aimed at mitigating these challenges and enhancing the overall efficiency and quality of essential oil extraction. This project aimed to investigate two specific essential oils: limonene extracted from orange peels and Ziziphus spina-christi L extracted from the Sidra tree, chosen for its accessibility and native presence in Qatar. The methods were carried out at the laboratory scale with the assumption of the capability to upscale to an industrial scale within the inherent limitations of the process with the addition of simulating SFE on Aspen Plus V14 in lieu of obtaining experimental data
CaveCrawler: An Interactive Analysis Suite for Cavefish Bioinformatics
Get PDFThe growing use of genomics data in diverse animal models enables researchers to identify genomic and transcriptional differences between species and experimental groups. Genetics databases have played critical roles in establishing the most widely recognized genetic model organisms, such as fruit flies and mice, but most emerging model species for evolutionary biology research lack such databases. One such emerging model organism is the Mexican tetra, Astyanax mexicanus. This fish species exists as eyed surface populations and at least 30 cave populations, providing a system to study convergent evolution. Further, since the surface and cave morphs differ in phenotypes with clinical relevance, the Mexican tetra is an emerging model system for human disease. Though researchers are increasingly using genomic, transcriptional, and functional genetic approaches to study disease and evolution using this species, there currently exists no centralized database for accessing Mexican tetra genetics data and comparing results from across studies. We generated a web-based analysis suite which integrates datasets from different studies, then demonstrated the utility of our tool by identifying genes whose transcription and markers of selection differ between populations and across experimental contexts. Results of diverse studies can be analyzed in conjunction with each other and with other genetic data, such as Gene Ontology (GO) information, to enable biological inferences from across studies and identify future avenues of research. Furthermore, the framework that we have built for A. mexicanus can be adjusted for use in other emerging model systems, enabling research which is only possible in species not traditionally used in genetic analyses