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Analytical and Computational Analysis of Perturbed Finite-Core Trailing Vortices Including Transient Ground Effect
No full textAn analytical and computational campaign is conducted to examine the unsteady nature and stability properties of streamwise-oriented trailing vortices. Two classes of streamwise vortex dynamics are investigated: the self-induced motion of an isolated trailing vortex that is perturbed at its point of origin; and an equal-strength, counter-rotating vortex pair approaching a ground plane. Computational fluid dynamics (CFD) simulations using the research code FDL3DI study the evolution of an isolated, single vortex whose flow profile is imposed as a time-varying inflow boundary condition in an otherwise uniform flow. Small- amplitude uni- and bi-directional motions of the vortex center position on the boundary lead to a self-induced rotation of the vortices that is not convectively amplified, in contrast to existing experimental results for the vortex wake of heaving wings in laboratory conditions.The temporal stability of equal-strength, counter-rotating vortex pairs descending to- ward a planar wall is examined analytically and computationally. A mathematical model determines the time histories of the center positions and deformation perturbations of the trailing vortices by marching forward in time the vortex filament method based on Biot- Savart induction. A non-modal stability analysis of the vortex trajectories determines the optimal perturbation of the vortex system, i.e., the wavenumber and initial condition that yield the maximum perturbation growth for any instant in time. Direct numerical integration of the vortex system highlights the sensitivity of the vortex pair to initial conditions and the time dependence of the optimal wavenumber. Complementary viscous and inviscid CFD simulations of this system using Lamb-Oseen vortices facilitate a comparison to the inviscid theoretical model for selected streamwise wavenumber perturbations and highlight the effects of viscous vortex-wall interactions on system stability and flow structures. The combined theoretical and computational analysis reveals that the local suppression of the Crow instability of the vortex pair in the presence of a wall may be described by inviscid arguments alone
Passive Microwave Remote Sensing of Snowmelt and Soil Thaw in the Kuparuk Basin, Alaska
No full textThe relationship between snow and permafrost on Arctic terrain has significant implications for water storage, flooding hazards, and infrastructure vulnerability. Studies show that earlier snowmelt and high runoff cause increased permafrost thaw and earlier freeze/thaw cycles. This can be especially problematic for communities in Arctic regions facing disproportionate warming from climate change. To analyze permafrost vulnerability due to snowmelt dynamics, we compared snowmelt and soil freeze/thaw (FT) on different landcover types in the Kuparuk River Basin in Northern Alaska from 2010-2019. We used Calibrated, Enhanced-resolution Brightness Temperatures (CETB) from two passive microwave sensors, Special Sensor Microwave Imager/Sounder (SSMIS: F18) 37 GHz vertically polarized channel and Soil Moisture Active Passive (SMAP) 1.41 GHz vertically and horizontally polarized channels. Snowmelt onset timing and duration are derived from brightness temperature (Tb) and diurnal amplitude variations (DAV) threshold exceedances which are sensitive to changing levels of liquid water content in the snowpack. Soil thaw and refreeze dynamics are captured using a freeze/thaw (FT) retrieval algorithm that uses a frost factor index derived from normalized polarization ratio of the SMAP brightness temperatures. extit{In situ} soil temperature and snow depth are used to relate microwave signals to surface and subsurface conditions. With the use of multiple microwave frequencies, snow melt and soil thaw are difficult to differentiate between one another as FT and CETB melt onset occurred around the same day. However, the SMAP signals demonstrated sensitivity to subsurface thawing and importance for understanding gradual melt and refreeze of the subsurface before snow melt accumulation and during snow off conditions. The preliminary use of calibrated-enhanced passive microwave on a heterogeneous landscape allowed us to assess Tb thresholds for melt onset and highlight differences in Tb distribution over time across various sites in the Kuparuk basin. Quantifying these relationships and and refining algorithms to monitor these landscapes supports community resilience at finer spatial scales and our understanding of a dynamic and rapidly changing Arctic environment
Gender Difference in Medicare Payments to Registered Dietitians and Nutritionists in 2021
No full textGender pay gap is commonly observed in the labor market, and healthcare industry is no exception. Despite they account for over 90% of the workforce in these fields, female healthcare professionals earn significantly less compared to men. This study examined gender differences in Medicare payments to registered dietitians and nutritionists. Analyzing data from the 2021 Medicare Physician and Other Practitioners by Provider dataset and the Doctors and Clinicians National Downloadable File, this study documented the extent of gender-based payment disparities among registered dietitians and nutritionists. The findings revealed a consistent pattern where women received lower payments, even when accounting for service density, patient panel complexity, number of unique billing codes, beneficiaries age, population density and practice years. While the gender payment gap narrowed from 2017 to 2021, underlying systemic issues warrant further research for an equitable healthcare system
(Un)Ethical AI: Fact and Fiction
No full textThis lesson template provides a non-technical introduction to ethical considerations about AI, through the lens of a Captain America film.We are bombarded with claims about the ways that AI algorithms are remaking society, often made with hyperbolic comparisons to science fiction. How should we evaluate these claims? Though they hear about the impact of "algorithms" all the time, students often do not know what they are or how they work, unless they are pursuing courses in computer science. In order to effectively evaluate the news around them, and understand which tools are valuable and which are troubling, students in nontechnical fields need to understand what an algorithm is and how one can be ethically deployed. This lesson is designed to introduce the concept of ethical AI through the movie Captain America: Winter Soldier, which has a subplot about an AI-powered assassination device, and compare this fictional tool to real-world cases including social network recommender algorithms, FICO credit scores, and automated resume classification programs. The lesson will include a conceptual description of a neural network, with an emphasis on training data and the limitations of systems that aim to predict the future based on data from the past. Knowledge of coding or mathematical principles will not be assumed. Instructors can include additional or alternative examples of AI in pop culture at their discretion. Students will be able to describe how a neural network works, including the concepts of training data, classification, and measurement error. They will also be able to discuss the ethical principles behind gathering data, training models, and deploying them. They will be able to evaluate for themselves whether a model was ethically developed and whether, and in what contexts, it should be deployed.</p
Collaborative Spoken Word Poetry with AI - Project Summary
No full textStructure for leading an in-class creative activity, based in iterative theatrical devising and driven by group collaboration with generative AI.This Lehigh AI Project provides a structure for a creative activity in order to experiment with and reflect upon the potential of AI for artistic collaboration. Over the course of a 75-minute in-class exercise, students (or other participants) engage in an iterative artistic process with text- and image-generating AI applications. Over a sequence of steps, students develop a creative work that incorporates poetic text, digital imagery, and embodied performance. The process combines individual effort and group decision-making, entangling both in artistic collaboration with AI. The exercise concludes with a presentation of the work to their peers and a reflective discussion about creation, authorship, and originality. The design of this exercise is modeled after general devising techniques in theatrical practice as well as the \u27cut-up\u27 method popularized by William S. Burroughs.
This project presents a structured walkthrough of the creative activity, documenting the instructions, reasoning, and supplemental notes for each step in order for an instructor to guide the class in AI artmaking and reflection
The Pitfalls of Ascribing Moral Agency to Corporations
No full textPolicy Points Government and civil society should be held more accountable for creating food and beverage regulatory policies rather than assigning moral agency to the food and beverage industry. Nutrition policymaking institutions should ensure civil society\u27s ability to design regulatory policy. Government policymaking institutions should be isolated from industry interference
Exploring influential factors in peer upvoting within social annotation
No full textUpvotes serve important purposes in online social annotation environments. However, limited studies have explored the influential factors affecting peer upvoting in online collaborative learning. In this study, we analysed the factors influencing students\u27 upvotes received from their peers as 91 participants utilized Perusall, an online social annotation system, for collaborative reading. The participants were asked to collaboratively annotate 29 reading materials in a semester. We collected student reading behaviours and analysed their annotations with a text‐mining tool of Linguistic Inquiry and Word Count (LIWC). Moreover, conditional inference tree was used to determine the relative importance of explanatory factors to the upvotes students received. The results showed that the high‐upvote group made significantly more annotations, posted more responses to others\u27 annotations and displayed fewer negative emotions in annotations than those who did not receive upvotes. The two groups of students had no significant differences in the upvotes given to others, as well as cognitive activities and positive emotions involved in annotations. Moreover, the number of annotations was the determining factor in predicting the upvotes that one could receive in social annotation activities. This study has significant practical implications regarding providing interventions in social annotation‐based collaborative reading. Practitioner notes What is already known about this topic Social annotations enhance students\u27 reading experience, facilitate knowledge sharing and collaboration, promote high‐quality learning interactions and ultimately lead to improved performance. In social annotation environments, receiving upvotes from peers is not only a type of feedback but also a form of motivation, social interaction and social validation. No study has explored the influential factors in peer upvoting within social annotation‐based learning. What this paper adds This study was the first to examine social annotations through the lens of the community of inquiry framework. We investigated the relationships between students\u27 cognitive and social presence in their annotations and the upvotes they received in an online social annotation environment. Our study revealed the strategies for obtaining upvotes from peers in social annotation‐based learning environments. Implications for practice and/or policy The high‐upvote group made significantly more annotations, posted more responses to others\u27 annotations and displayed fewer negative emotions in annotations compared to the low‐upvote group. The two groups of students did not show significant differences in the upvotes they gave to others or in the cognitive activities and positive emotions involved in annotations. The number of annotations was the primary factor predicting the number of upvotes received in the collaborative reading. This study could inform the design of future online social annotation systems to better support collaborative learning and peer interaction
Comparison of screening methods for computer adaptive tests to predict reading and math performance
No full textThe present study compared the diagnostic accuracy of a single computer adaptive test (CAT), Star Reading or Star Math, and a combination of the two in a gated screening framework to predict end‐of‐year proficiency in reading and math. Participants included 13,009 students in Grades 3–8 who had at least one fall screening score and end‐of‐year state test score in reading and math. First, diagnostic accuracy statistics were evaluated for a single screening measure to predict proficiency on end‐of‐year tests. Second, a gated screening framework was simulated to examine the diagnostic accuracy of a combination of screening measures (i.e., scores from the CATs and the end‐of‐year test). The diagnostic accuracy of each screening method was compared. Results suggest that diagnostic accuracy did not improve for the gated screening method when compared to the single screening method. The gated screening method tended to yield low sensitivity values ( M = 0.42, range = 0.35–0.48) and high specificity values ( M = 0.97, range = 0.95–0.99). The only condition to reach acceptable sensitivity and specificity (>0.70) was a single reading screener predicting reading outcomes. Sample specific cut‐scores from receiver operating curve (ROC) analyses led to improved diagnostic accuracy outcomes relative to all other methods. , Practitioner Points The diagnostic accuracy did not improve for the gated screening method when compared to the single screening method. Across the screening conditions, the only method to yield acceptable diagnostic accuracy was when a single reading screener predicted reading outcomes. Utilizing multiple assessment measures cannot be justified according to the results of the study
Deep learning-based predictive classification of functional subpopulations of hematopoietic stem cells and multipotent progenitors
No full textAbstract
Background
Hematopoietic stem cells (HSCs) and multipotent progenitors (MPPs) play a pivotal role in maintaining lifelong hematopoiesis. The distinction between stem cells and other progenitors, as well as the assessment of their functions, has long been a central focus in stem cell research. In recent years, deep learning has emerged as a powerful tool for cell image analysis and classification/prediction.
Methods
In this study, we explored the feasibility of employing deep learning techniques to differentiate murine HSCs and MPPs based solely on their morphology, as observed through light microscopy (DIC) images.
Results
After rigorous training and validation using extensive image datasets, we successfully developed a three-class classifier, referred to as the LSM model, capable of reliably distinguishing long-term HSCs, short-term HSCs, and MPPs. The LSM model extracts intrinsic morphological features unique to different cell types, irrespective of the methods used for cell identification and isolation, such as surface markers or intracellular GFP markers. Furthermore, employing the same deep learning framework, we created a two-class classifier that effectively discriminates between aged HSCs and young HSCs. This discovery is particularly significant as both cell types share identical surface markers yet serve distinct functions. This classifier holds the potential to offer a novel, rapid, and efficient means of assessing the functional states of HSCs, thus obviating the need for time-consuming transplantation experiments.
Conclusion
Our study represents the pioneering use of deep learning to differentiate HSCs and MPPs under steady-state conditions. This novel and robust deep learning-based platform will provide a basis for the future development of a new generation stem cell identification and separation system. It may also provide new insight into the molecular mechanisms underlying stem cell self-renewal.
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Effect of SSP370 and SSP245 on the future carbon sink for the conterminous U.S.
No full text[2024-09-08: Added readme-2024-09-08.docx, policy_comparison.xlsx, and policy_ssp245.usa48.xlsx]Files pertaining to submitted article Effect of SSP370 and SSP245 on the future carbon sink for the conterminous U.S. to Plants People Planetppp_tem_code.tar.gz: C++ code for version of TEM-Hydro used in this study, along with Make file and 10 xml files for each of the model experimentsppp_ssp245_climate.tar.gz: climate input files for SSP245 scenarios, including both transient and constant climate (tair = surface temperature, prec = precipitation, dtr = daily temperature range, vpr = vapor pressure, clds = clouds)ppp_ssp370_climate.tar.gz: climate input files for SSP370 scenarios, including both transient and constant climate (tair = surface temperature, prec = precipitation, dtr = daily temperature range, vpr = vapor pressure, clds = clouds)ppp_inputs.tar.gz: other input files, including CO2 for SSP245 and SSP370, ozone (ioo3baucru_2014lf.usa48), N deposition (ndeplf_2014.usa48), average wind speed (windlf.usa48), soil texture (cruigbptxtlf.usa48), elevation (crutbaselvlf.usa48)ppp_lulcc.tar.gz: land use and land cover change files and maximum cohort files for, transient for SSP370 (cruHurtt3.2.1lulccohrtsr_hurtt_out_2015_2099_fix.usa48, cruHurtt3.2.1mxcohrtsr_hurtt_out_2015_2099_fix.usa48), SSP245 (cruHurtt3.2.1lulccohrtsr_hurtt_out_2015_2099_ssp245.usa48, cruHurtt3.2.1mxcohrtsr_hurtt_out_2015_2099_ssp245.usa48) and constant (cruHurtt3.2.1lulccohrtsr_hurtt_out_2015.usa48, cruHurtt3.2.1mxcohrtsr_hurtt_out_2015.usa48)ecdfiles.tar.gz: parameters used in TEMdatfiles.tar.gz: calibrated parameters used in TEM for each PFTTime series summary statistic output for SSP245 (summary_statistics_SSP245.zip) and SSP370 (summary_statistics_SSP370.zip)Mapped file for 2070-2099 means for SSP245 (maps_SSP245_2070_2099.zip, maps_SSP370_2070_2099.zip).output_FUTURESSP370LULCC.USTOT_revised.xlsx: final figure data for SSP370 and comparisons with SSP245output_FUTURESSP245LULCC.USTOT_revised.xlsx: final figure data for SSP245pfts_revised.xlsx: data for figures with PFT-specific informationhurtt_lulcusa_ssp370.out.xlsx: land use and land cover data figureslulcc_futures_figures_revised_new.pptx: final figure in paperpolicy*.xlsx: data for policy figures 7 and 8</ul