Why Proper Technique Works: An Insight into Scientific Principles that Make Skating Possible

As a figure skater and a premed student, I have found that my understanding of science and interest in the human body has helped me better understand certain aspects of the sport and recommendations by coaches. Recent advancements in figure skating have led to questions about the impacts of quadruple jumps on young female athletes. My project aimed at providing coaches with some science background about concepts related to figure skating and correct technique to not only help them with injury prevention, but also to help foster an interest in science in a unique population. After doing research and interviewing figure skating coaches and exercise science experts, I created a brochure, shown in the video, that highlighted key science topics related to figure skating. I planned to distribute this brochure to local ice rinks, but was unable to do so because of the COVID pandemic. I instead chose to electronically deliver the brochure using club email lists, and will distribute the brochure at a later time. I additionally created a blog post, shown in the video, that can be published on Stem-o-sphere that added some off-ice elements to my content since skaters were confined to this training during the pandemic

Fabrication of living soft matter by symbiotic growth of unicellular microorganisms

We report the fabrication of living soft matter made as a result of the symbiotic relationship of two unicellular microorganisms. The material is composed of bacterial cellulose produced in situ by acetobacter (Acetobacter aceti NCIMB 8132) in the presence of photosynthetic microalgae (Chlamydomonas reinhardtii cc-124), which integrates into a symbiotic consortium and gets embedded in the produced cellulose composite. The same concept of growing living materials can be applied to other symbiotic microorganism pairs similar to the combination of algae and fungi in lichens, which is widespread in Nature. We demonstrate the in situ growth and immobilisation of the C. reinhardtii cells in the bacterial cellulose matrix produced by the simultaneous growth of acetobacter. The effect of the growth media composition on the produced living materials was investigated. The microstructure and the morphology of the produced living biomaterials were dependent on the shape of the growth culture container and media stirring conditions, which control the access to oxygen. As the photosynthetic C. reinhardtii cells remain viable and produce oxygen as they spontaneously integrate into the matrix of the bacterial cellulose generated by the acetobacter, such living materials have the potential for various applications in bio-hydrogen generation from the immobilised microalgae. The proposed approach for building living soft matter can provide new ways of immobilising other commercially important microorganisms in a bacterial cellulose matrix as a result of symbiosis with acetobacter without the use of synthetic binding agents and in turn increase their production efficiency

The Effects of Intermittent Solar Radiation in Off-grid Solar Power System A Case Study of Two Cities; Sacramento, CA and Miami, FL 'Worst Month' method

This study illustrates the impact of the solar radiation by comparing the design of two off-grid PV systems installed in two different locations have same annual average solar irradiation (insolation) values at fixed tilt angle. The case study selected the city of Sacramento, CA and Miami, FL. The monthly average Irradiation values in Sacramento are very diverse where the minimum, average and maximum values are spaced compared with the values in Miami which have no significant variation of solar irradiation from month to month. Comparing the Design of the two different systems will reflect the impact of the sporadic solar insolation on the rating values for the components of each system, which is affecting PV system cost. The design assumes the same load based and the worst case scenario of the solar irradiation. Each system will consist of PV modules, charge controller, power inverter and batteries

Deep Learning in Chest Radiography: From Report Labeling to Image Classification

Chest X-ray (CXR) is the most common examination performed by a radiologist. Through CXR, radiologists must correctly and immediately diagnose a patient’s thorax to avoid the progression of life-threatening diseases. Not only are certified radiologists hard to find but also stress, fatigue, and lack of experience all contribute to the quality of an examination. As a result, providing a technique to aid radiologists in reading CXRs and a tool to help bridge the gap for communities without adequate access to radiological services would yield a huge advantage for patients and patient care. This thesis considers one essential task, CXR image classification, with Deep Learning (DL) technologies from the following three aspects: understanding the intersection of CXR interpretation and DL; extracting multiple image labels from radiology reports to facilitate the training of DL classifiers; and developing CXR classifiers using DL. First, we explain the core concepts and categorize the existing data and literature for researchers entering this field for ease of reference. Using CXRs and DL for medical image diagnosis is a relatively recent field of study because large, publicly available CXR datasets have not been around for very long. Second, we contribute to labeling large datasets with multi-label image annotations extracted from CXR reports. We describe the development of a DL-based report labeler named CXRlabeler, focusing on inductive sequential transfer learning. Lastly, we explain the design of three novel Convolutional Neural Network (CNN) classifiers, i.e., MultiViewModel, Xclassifier, and CovidXrayNet, for binary image classification, multi-label image classification, and multi-class image classification, respectively. This dissertation showcases significant progress in the field of automated CXR interpretation using DL; all source code used is publicly available. It provides methods and insights that can be applied to other medical image interpretation tasks

Scheduling Household Appliances using Genetic Algorithms

Smart grids with their advanced communication capabilities and sensing methodologies introduce a smart manner for energy management systems. In fact, the fast development of smart grid technologies provide an advanced control over the energy offered and consumed by the suppliers and the consumers of the electricity, respectively. The growing usage of electricity is leading to an increased demand on the following scarce resources: energy, oil and coal. This will result in increasing electricity prices. Moreover, the continuing growth of electricity is negatively affecting the environment. Therefore, coming up with a planned schedule for household appliances for controlling Demand Side Management in smart grids is beneficial on the economic and environmental level. In this paper, we present a scheduling algorithm using heuristic optimization that will serve as a solution to create a schedule for home appliances that minimizes the monetary expenses and protects the environment indirectly

Differences in Cultural Intelligence and Cognitive Flexibility among Saudi Scholarship Students and International Students in Saudi Universities: A study of Selected Variables

ملخص: هدفت الدراسة للكشف عن الفروق في الذكاء الثقافي والمرونة المعرفية تبعًا لمتغيري مدة الخبرة عبر الثقافية ومستوى الكفاءة في اللغة الثانية. ونهجت الدراسة المنهج الوصفي المقارن، وبلغ مجموع العينة (836) من الطلبة المبتعثين السعوديين إلى الولايات المتحدة الأمريكية وبريطانيا وكندا وأستراليا ونيوزلندا وإيرلندا وسنغافورة، والطلبة الدوليين في الجامعات السعودية متمثلة في: جامعة أم القرى، والجامعة الإسلامية، وجامعة الملك عبد العزيز، وجامعة الإمام محمد بن سعود، وجامعة الملك سعود، وجامعة الأميرة نورة، وجامعة الملك خالد. واستُخدم مقياسي الذكاء الثقافي، والمرونة المعرفية. وتوصلت نتائج الدراسة لوجود فروق في الذكاء الثقافي تبعًا لمدة الخبرة عبر الثقافية لدى المبتعثين لصالح المقيمين لأكثر من سبع سنوات، بينما كانت الفروق في عينة الدوليين لصالح المقيمين أقل من سنة. ولم توجد فروق في المرونة المعرفية تبعًا لمدة الخبرة عبر الثقافية لدى المبتعثين ووجدت لدى الطلبة الدوليين لصالح المقيمين أقل من سنة. ووجدت فروق في الذكاء الثقافي تبعًا لمستوى الكفاءة في اللغة الثانية لدى العينتين لصالح الكفاءة الأعلى. ولم توجد فروق في المرونة المعرفية تبعًا لمستوى الكفاءة في اللغة الثانية لدى المبتعثين، بينما وجدت لدى الطلبة الدوليين لصالح الكفاءة الأعلى. وأوصت الدراسة بالقيام بالفعاليات عبر الثقافية التي تزيد التعرض وتدعم الخبرات، كما توصي بالحرص على الإعداد اللغوي الجيد للطلبة المغتربين.Abstract: The study aimed to reveal differences in cultural intelligence and cognitive flexibility depending on the variables of duration of cross-cultural experience and degree of competence in the second language. The study adopted the descriptive, comparative approach, and the total sample amounted to (836) Saudi students on scholarships to the United States of America, Britain, Canada, Australia, New Zealand, Ireland, Singapore and international students in Saudi universities. Tools employed by the study included; Cultural Intelligence Scale, and the Cognitive Flexibility Scale. The study concluded there is Differences were found in cultural intelligence according to the length of experience in the sample of students on scholarship with preference to resident students for more than seven years, while the differences in the sample of internationals give favor to residents for less than one year. There were no differences registered in cognitive flexibility according to the duration of experience of the scholarship students. On the other hand, differences were found in cognitive flexibility according to the period of experience of international students with preference to resident students for less than one year. Differences were found in cultural intelligence according to the level of proficiency in the second language in the two samples of scholarship and international students in favor with preference to those with higher linguistic competence. No significant differences reported in cognitive flexibility according to the level of proficiency in the second language of the scholarship sample, while differences were found in cognitive flexibility according to the level of competence in the second language with preference to those of higher competence. The study recommended carrying out of cross-cultural activities that increase contact of students and support experiences. It is also recommended to ensure good language preparation for international students

A novel optimized neutrosophic k-means using genetic algorithm for skin lesion detection in dermoscopy images

This paper implemented a new skin lesion detection method based on the genetic algorithm (GA) for optimizing the neutrosophic set (NS) operation to reduce the indeterminacy on the dermoscopy images. Then, k-means clustering is applied to segment the skin lesion regions

Urban Health Related Air Quality Indicators over the Middle East and North Africa Countries Using Multiple Satellites and AERONET Data

Air pollution is reported as one of the most severe environmental problems in the Middle East and North Africa (MENA) region. Remotely sensed data from newly available TROPOMI - TROPOspheric Monitoring Instrument on board Sentinel-5 Precursor, shows an annual mean of high-resolution maps of selected air quality indicators (NO2, CO, O3, and UVAI) of the MENA countries for the first time. The correlation analysis among the aforementioned indicators show the coherency of the air pollutants in urban areas. Multi-year data from the Aerosol Robotic Network (AERONET) stations from nine MENA countries are utilized here to study the aerosol optical depth (AOD) and Ångström exponent (AE) with other available observations. Additionally, a total of 65 different machine learning models of four categories, namely: linear regression, ensemble, decision tree, and deep neural network (DNN), were built from multiple data sources (MODIS, MISR, OMI, and MERRA-2) to predict the best usable AOD product as compared to AERONET data. DNN validates well against AERONET data and proves to be the best model to generate optimized aerosol products when the ground observations are insufficient. This approach can improve the knowledge of air pollutant variability and intensity in the MENA region for decision makers to operate proper mitigation strategies

Quantifying Demonstration Quality for Robot Learning and Generalization

Learning from Demonstration (LfD) seeks to democratize robotics by enabling diverse end-users to teach robots to perform a task by providing demonstrations. However, most LfD techniques assume users provide optimal demonstrations. This is not always the case in real applications where users are likely to provide demonstrations of varying quality, that may change with expertise and other factors. Demonstration quality plays a crucial role in robot learning and generalization. Hence, it is important to quantify the quality of the provided demonstrations before using them for robot learning. In this paper, we propose quantifying the quality of the demonstrations based on how well they perform in the learned task. We hypothesize that task performance can give an indication of the generalization performance on similar tasks. The proposed approach is validated in a user study (N = 27). Users with different robotics expertise levels were recruited to teach a PR2 robot a generic task (pressing a button) under different task constraints. They taught the robot in two sessions on two different days to capture their teaching behaviour across sessions. The task performance was utilized to classify the provided demonstrations into high-quality and low-quality sets. The results show a significant Pearson correlation coefficient (R = 0.85, p < 0.0001) between the task performance and generalization performance across all participants. We also found that users clustered into two groups: Users who provided high-quality demonstrations from the first session, assigned to the fast-adapters group, and users who provided low-quality demonstrations in the first session and then improved with practice, assigned to the slow-adapters group. These results highlight the importance of quantifying demonstration quality, which can be indicative of the adaptation level of the user to the task