1925 research outputs found
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Glutathione reductase regulation in mouse skeletal muscle stimulated ex-vivo: a pilot study
No full textMuscle contraction induces oxidant production that matches the magnitude, duration, and intensity of the contractile stimulus, however the effects on redox-sensitive proteins are still not well understood. In the present study, we aimed to measure the redox signaling response to skeletal muscle stimulation in an ex vivo model. We hypothesized that muscle stimulation would induce an increase in oxidation of the antioxidant protein glutathione reductase (GSR). Extensor digitorum longus (EDL) muscles were removed from mice and one muscle was stimulated ex vivo. The stimulated muscle received thirty isometric tetanic stimulations (500 ms train, 0.8 ms pulse duration, 140 Hz) delivered with 500 ms breaks in between each tetanus. This stimulation loop was delivered ten times for a total of 300 tetanic stimulations. On average, the maximum force a tetanic stimulation produced decreased by 79% percent following the protocol, confirming that the muscle was fatigued. The control EDL muscle was placed in an oxygenated Krebs bath for an equal amount of time, but did not undergo stimulation. Following the experiment, both muscles were flash frozen in liquid nitrogen, stored at -80 °C and later homogenized in reducing and non-reducing buffer. Levels of GSR were measured via western blotting. There were no significant changes in overall protein abundance. However, the amount of GSR located at 55kDa, the expected molecular weight, showed a trend increasing in response to stimulation p=0.0754. A trend was also observed toward increasing GSR with stimulation at the elevated (>100kDa) molecular weight (p=0.0711). An unexpected result of the study was the significant effect of animal as a random variable nested within sex on the data (p=<0.0001). We investigated the effects of order of the experiments, age, body weight, and sex on the inter-animal variability, however no clear trends emerged. While these results require further investigation to fully understand the patterns of oligomerization of GSR in skeletal muscle tissue, as far as we are aware these are the first data to describe oxidation/oligomerization of GSR. It is still unclear how oxidation/oligomerization affects enzyme function, turnover, or localization of GSR and further work is necessary
Predictive Communication for Unmanned Aerial Vehicle (UAV) Networks
No full textUnmanned Aerial Vehicles (UAVs), commonly known as drones, is an emerging technology with a huge potential to transform our lives into smart and connected communities by providing efficient infrastructure solutions for a wide range of military, industrial and commercial applications. UAVs empower innovative solutions that save lives and save the planet. However, there are several challenges and issues that limit the applicability of drones for many applications, not only due to UAVs' intrinsic and technological limitations, but also due to design and networking constraints. UAV networks composed of freely flying nodes create highly dynamic environments, where conventional networking protocols, which rely on stationary network contact graphs, fail to perform efficiently. Also, the efficiency of the networking protocols in terms of the incurred energy cost and the transmission delay can dramatically fall due to the networks failure in perceiving and predicting the environment. As a potential solution, Artificial Intelligence (AI) can revolutionize current networking methodologies by integrating computational intelligence into UAV networking solutions.
The aim of this project is to investigate the state of art of communication, computation and scheduling methods for UAV networking and propose novel solutions to solve the current issues and drawbacks. By using the prediction power of Machine Learning (ML) algorithms, we aim to better perceive the network topology, channel status, traffic distribution and resource availability to improve service provisioning. First, we propose three AI-enabled routing protocols for UAV networks that act based on learning from past history and anticipating future network states, yielding high performance for a variety of network scenarios and applications. Next, we suggest a predictive optimized compression policy for energy-efficient networking by avoiding excessive information exchange in dynamic scenarios. Last, we present an optimal sampling technique that reduces the interference and the overall energy consumption by a timely transmission of fresh data packets with considerable information content for Internet of Things (IoT). In summary, we believe that the offered solutions can revolutionize the current methods and pave the road to use UAVs in various IoT applications to benefit the society and the global economy
Spectrum sharing and management in Unmanned Aerial Vehicle networks
No full textSmall autonomous vehicles received a lot of attention in commercial, military, and personal applications in the recent era. The fast growth in the number of these vehicles raises many challenges in terms of safety, primary, security, communications, control and coordination in such large scale autonomous systems. One of these challenges is to secure the required radio spectrum for reliable communication and data transmission among the vehicles and the ground station. Spectrum scarcity is one of the key challenges toward developing emerging applications such as Unmanned Aerial Vehicle (UAV) networks, where the agents are mobile, have limited energy and computation capabilities while often requiring high data transmission rates. In many previous works, the UAVs are considered as flying base stations (BSs) to extend the coverage of cellular networks or as a relay to enable device-to-device (D2D) communications. In this research, we investigate the operations of UAV networks in disaster scenarios, where the communication infrastructure may be damaged and develop different coordination mechanisms between the UAV networks and the ground users. We study a scenario where the UAVs suffer from spectrum scarcity in their network and they require to lease additional spectrum from ground users in exchange to deliver their packets. Many parameters such as mobility, throughput, fairness, and reliability affect the task of spectrum assignment. This study aims at developing new approaches using reinforcement learning to solve this spectrum assignment problem.
Moreover, packet scheduling is one of the techniques that the relay UAV considers into account for choosing the ground users to service. Many factors such as the Quality-of-Service (QoS), queue length, application service time, and energy can play an important role in packet scheduling. We studied an imitation learning approach (Behavioral cloning) to mimic an expert behavior to perform an autonomous packet scheduling task. On the other hand, compared to the applications such as flying base station or flying relay, UAVs can connect to the cellular BS as flying User Equipment (UE). In applications like this, it is crucial to have an interference management scheme to minimize the interfering effect on the ground UEs as well. In this study, we address this challenge by using apprenticeship learning via inverse reinforcement learning to account for the interference concern based on expert behavior. Finally, a practical implementation of drones is performed during a prescribed pile fire at Northern Arizona Coconino forest to collect aerial imagery using 4K cameras and a thermal camera. The collected data is used to define a dataset for different challenges such as "Fire and NoFire'' classification and fire segmentation
Exploring the psychological experiences and resiliency practices of Navajo mothers who give birth to and care for a premature infant in a rural-serving neonatal intensive care unit
Get PDFAccording to recent statistics, Indigenous mothers have one of the highest percentages of preterm births in the U.S. when compared to white mothers (Sparks et al., 2005). During 2011 to 2013, the premature birth rate in Arizona for Indigenous mothers was 14.2% compared to 10.6% for white mothers (March of Dimes, 2015). Yet, little research exists about the experiences of Indigenous mothers of premature infants in the NICU environment. For Navajo mothers, the rurality of many family homes, combined with cultural differences between mothers and hospital staff, create potential barriers to mother-infant bonding and the learning that must take place for mothers to care for infants once the infants graduate from the NICU. The purpose of this study was to explore Navajo mothers’ lived experiences before and after the birth of their premature infants, and while their premature infants are cared for in a rural-serving medical center NICU in the Southwestern U.S. To explore Navajo mothers’ lived experiences, three individuals separately participated in a demographics survey and an hour-long semi-structured interview conducted virtually. The use of Interpretive Phenomenological Analysis (IPA) for all three transcripts resulted in the emergence of three super-ordinate themes with subsequent sub-themes. Results revealed that resiliency during the perinatal period was salient for all three mothers, in particular the practice of cultural resiliency through traditional methods. Furthermore, the results highlight the need for individualized and culturally responsive treatment for Navajo and Indigenous mothers who visit and care for their high-risk or preterm infants in traditional Western healthcare settings
Impact of the Trump Administration's Modification to the Public Charge Rule on Perceptions of Immigrants' Behavior
No full textThe public charge rule that prohibited entry of any person unable to take care of himself or herself without depending on public benefits has been in existence since 1882. It was last modified in 1999 before it’s modification in February 2020 by the administration of Donald Trump. The Trump administration’s modification to the rule expanded the public benefits whose use could be used to deny upgrading of immigrant visa status. Under the modified rule, a foreign national is defined as likely to become a public charge if they use public benefits such as cash assistance, Medicaid, Supplemental Nutrition Assistance Program (SNAP), and public housing benefits. This study seeks to determine if, from the perspective of social service personnel who engage with immigrants, nonimmigrants, and mixed-status families, the Trump administration’s modification to the public charge rule has affected immigrants’ behaviors. The research reported here is based on open-ended, qualitative interviews administered to a purposive sample of ten social service personnel. To the best of my knowledge, the study is the first to examine the experience of social service personnel working with immigrants, as compared to previous studies that sampled immigrants rather than those who serve them. The study revealed that, from social service personnel’s perspective, after the change in the public charge rule, immigrants avoided using public benefits out to fear of becoming a public charge and consequently denied a green card. This fear led some immigrants and mixed-status families to withdraw or not apply for public benefits even when needed. Of greater concern to respondents is the withdrawal of US-born children from public benefits. This study can serve as a guide to creating immigration policies that minimize immigrant fear of reprisal for using public services and will allow them to apply and use public benefits legally available for them and/or their children
Education in isolation: how remote learning impacts students with disabilities in the COVID-19 Era
No full textStudents with disabilities, particularly in post-secondary education, have unique and under-researched educational experiences. Expectations of appropriate behaviors or roles constructed by educational institutions or members of faculty and staff often place unjust burdens on disabled students that impact their relationships on campus, their interactions with others, and their self-concept. The COVID-19 pandemic, which has caused significant changes to education, including the new prevalence of remote learning, has unique educational implications for students with disabilities and alters the networks of relationships and expectations of behaviors that students, faculty, and staff have for each other. Research into the changing educational experiences of disabled students before and during the COVID-19 pandemic produces grounded suggestions as to how post-secondary institutions may better support enrolled students with disabilities and critically consider issues of discrimination and structural ableism in policy and pedagogy in this shifting academic landscape
A basic model for bi-directional transfer of carbon dioxide and oxygen between digester biogas and a microalgae culture
No full textWith increasing anthropogenic influence on earth, fossil fuel usage, the principal emission source of carbon dioxide (CO2), has increased significantly at the risk of depletion in the future. Meanwhile, fossil fuel usage has also been identified as a cause for the increase in the deterioration of climate around the world. Biogas is a valuable renewable energy source that can be an alternative solution for future energy demands and mitigatory strategy for climate change. Biogas is a byproduct from the anaerobic digestion of organic wastes and this results in a gas composed mainly of methane (CH4), CO2 (30–40%) and trace amounts of other gases such as hydrogen sulfide (H2S), siloxanes, and water vapor. Purification and upgrading of biogas is necessary to increase the quality and the productivity of biogas as an energy source. Various technologies are available for biogas impurity removal; physical, chemical and biological methods. Since, physiochemical methods are expensive and environmentally hazardous, biological methods that are more environmentally friendly, cost competitive, and feasible are being developed. One promising biological method is the use of microalgae for the purification of biogas. This method involves the photosynthetic ability associated with CO2 fixation by microalgae using light energy. This research project focused on developing a basic mass transfer model for a biological gas-liquid scrubbing system that uses algae in a liquid medium to purify the CO2 present in the biogas. The model’s ability to simulate the mass transfer of gasses between the algae and the biogas in this scrubbing system was evaluated using a laboratory-based algal-scrubber. The comparison and evaluation of the model to the data collected from the laboratory work provided valuable insight into the main parameters influencing the model and its need for calibration against experimental results. Based on the results of this work, the model provided a reasonable simulation of the scrubber system indicating its potential use as a tool for design and operation of an algal based purification system. Additionally, further recommendations necessary for the research to modify and extend the development and improvement of this model are made
Considering herbivory in seed sourcing decisions for restoration materials
No full textThe success of ecological restoration relies on the sourcing of native plants that not only can successfully be grown commercially and establish at restoration sites, but also can support a broader ecological community. One of the primary ways that plants provide this support is as forage for herbivores. In the Western US, forbs have been identified as an important resource for herbivores. While much is known about a variety of native forb species and the herbivores they support, less is known about how these herbivore interactions are influenced by population-level variation in plant traits. This study utilized three species of native forbs in two common garden settings to examine the effects of source population on growth, reproduction, and herbivory. Throughout the growing season of 2020, we collected data on biomass, height, reproductive output, and survival from two different populations of each species. Half of the study plots were enclosed in mesh wire to parse out the impact of vertebrate herbivory on these metrics. We also utilized data from wildlife cameras, rodent track pads, and seed trials to establish a better understanding of the community of vertebrates present in the gardens. Despite evidence of herbivore presence in the plots and significant differences in plant traits between populations, there were no significant effects of the vertebrate exclosures on plant growth or reproduction. However, there was a significant negative effect of proximity to the garden edge on survival of Dieteria canescens. The results of this study suggest that the selection of herbivory-resistant plant materials for restoration may not require population-level specificity, at least for these species, but that commercial growers should consider garden layout when aiming to maximize propagation success
International admissions and recruitment evaluation program: a study at Northern Arizona University, Flagstaff, Arizona
No full textInternationalization of higher education growth has plummeted since the 2010 tightening of migration policy. The dynamics related to the relationship between international students seeking higher education in the United States and the institutions seeking to recruit these students reveals an area of interest. The study was envisioned and designed to describe and evaluate Northern Arizona University’s recruitment program effectiveness and suggest best strategies and practices to improve international students' enrollment. Given the context that this study occurred during a global pandemic, the researcher found that intrinsic factors may be critical to understanding nuances of any strategy at this time in history. To accomplish this goal, the researcher followed a paradigm examining existing data supplemented with interpretation from administrative personnel within the Center for International Education, NAU.
Based on a descriptive research design, this study analyzed application, enrollment, and retention data of undergraduate and graduate students with F1 visas and exchange students with J-1 visas from countries such as China, India, Ghana, Kuwait, Nigeria, etc. The existing data allowed the researcher to address the research questions by compiling descriptive statistics that led to quantitative data representation. The study found that out of the fourteen cultural groups purposely selected, the largest application and enrollment population came from Asia. The Asia region containing China, India, Kuwait, Vietnam, and Iran had the most applicants and enrollment populations
Exploring synchronous and asynchronous communication during pair work: the case of Chinese language learners
No full textInformed by sociocultural theories, collaborative writing (CW), a writing activity that involved two or more writers who share and exchange knowledge and negotiate decision-making to complete a single written text (Storch, 2002, 2013), has been found to benefit the second language (L2) students’ language learning by a substantial body of empirical research. The affordances of the synchronous and asynchronous technologies have made it possible to implement CW tasks in computer-mediated communication (CMC) environments. Previous researchers have respectively examined the L2 learners’ interaction and learning in synchronous CW tasks and asynchronous CW tasks. However, there is still a research gap about whether different modes of CMC (i.e., synchronous and asynchronous) may impact the potential of online CW tasks in L2 classrooms. Extending this inquiry, this study addressed a learner population that has been under-presented in existing CW literature and used Google Docs as the main computer-mediated technology to explore CW activities in Chinese language classrooms in both synchronous and asynchronous modes. Through analyzing triangulated data sources (i.e., Chinese learners’ pair talk when completing CW tasks, comments on Google Docs, revision histories at Google Docs, written products, post-task surveys, post-task reflection papers, post-task interviews), the author found that CMC mode impacted most pairs’ patterns of communication. In particular, all pairs were able to demonstrate highly mutual interactions when communicating via Google Docs and Zoom in the synchronous mode whereas only a small portion of the pairs developed a collaborative approach toward the CW task in the asynchronous mode when communicating via Google Docs only. Nevertheless, the CMC mode did not impact the linguistic complexity, accuracy, fluency, and holistic rating of the writing performance. Also, students reported more affordances associated with the synchronous mode: it offered CFL learners more language learning opportunities and more positive learning experiences than the asynchronous one. The study also revealed multiple constraints that require attention when implementing both synchronous and asynchronous CW tasks in future CFL learning. Last, the study found that in deciding their preference for CMC mode in future CW tasks, CFL learners prioritized whether the CMC technologies benefited their learning. The findings provided implications for both CFL pedagogy and CW software development