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Show Me a Function: More Than Meets the Eye
Full text linkMathematics is a fascinating subject used to understand functions' properties and behavior. From simple precalculus to challenging graduate-level courses, there is an intricate web of functions to explore. Unfortunately, functions that arise from real life problems are elusive, hard to characterize and can often only be approximated. In this talk, we will discuss practical methods used to uncover valuable functions in a variety of application
Research on Space Occupancy, Activity Rhythm and Sexual Segregation of White-Lipped Deer (Cervus albirostris) in Forest Habitats of Jiacha Gorge on Yarlung Zangbo River Basin Based on Infrared Camera Technology
Full text linkThe white-lipped deer (Cervus albirostris) is a rare and endangered species found in the Qinghai-Tibet Plateau in China. To understand the space occupancy, activity rhythm, and sexual segregation of the white-lipped deer, 24,096 effective photos and 827 effective videos were captured using infrared cameras from February 2020 to January 2022. The ecology and behavior of the white-lipped deer in Jiacha Gorge were studied in more detail using site occupancy models, relative abundance index, and other technologies and methods. The results show that The occupancy predicted by the model exceeds or approaches 0.5. The occupancy increases with greater altitude and with larger EVI values, while the detection rate increases with altitude only during spring and decreases with EVI values only in summer. The daily activity peaks for white-lipped deer were observed from 7:00 to 11:00 and 17:00 to 22:00, with annual activity peaks occurring from April to June and from September to November. From July to the following January, white-lipped deer mostly move in mixed-sex groups, while during the remainder of the year, they predominantly associate with individuals of the same sex. Climate, vegetation coverage, food resources, and human disturbance collectively influenced the behavior and habitat utilization of white-lipped deer. The foundational research conducted on white-lipped deer over the past two years is expected to enhance the basic understanding of white-lipped deer in the Qinghai-Tibet Plateau and contribute to future protection and management decisions.PublishedYe
George Eliot, Middlemarch, and Coventry
No full textArticle from the George Eliot Review. Digitized and hosted by the George Eliot Review Online, editor Beverley Park Rilett.Publishe
Review of Clare Carlisle's The Marriage Question: George Eliot's Double Life. A Philosophical Search for George Eliot's Figure in the Carpet
No full textArticle from the George Eliot Review. Digitized and hosted by the George Eliot Review Online, editor Beverley Park Rilett.Publishe
Review of Jillian M. Hess's How Romantics and Victorians Organized Information. Commonplace Books, Scrapbooks, and Albums
No full textArticle from the George Eliot Review. Digitized and hosted by the George Eliot Review Online, editor Beverley Park Rilett.Publishe
Linking prescribed fire, nutrient deposition and cyanobacteria dominance through pyroeutrophication in a subtropical lake ecosystem from the mid Holocene to present
No full textPrescribed fire (Rx-fire) is a common management tool for many forested ecosystems and promotes tree and forest soil health. Although burned materials from Rx-fire areas can enter adjacent aquatic environments, very few studies have focused on the water quality impacts of increased nutrients on aquatic primary producer communities. Here, we applied paleolimnological techniques on a 170-cm sediment core collected from Ditch Pond, AL, USA, a subtropical lake system located in the Conecuh National Forest where Rx-fire has been the primary management tool for ~90 years. Macroscopic charcoal, nutrients (C, N, P) and photosynthetic pigments were measured throughout the core which spans from the middle Holocene until modern day. Our research questions were: 1) What were the sedimentary nutrient and stoichiometric changes associated with the Rx-Fire period beginning in 1937 CE? and 2) Did these nutrient changes alter historic algae/cyanobacteria groups? Following the onset of Rx-fire, nutrients (C, N, P) increased in deposition in the lake with P showing the greatest proportional increase at over 300%, suggesting that P inputs from Rx-fire are a primary artifact of burning. Photosynthetic pigments showed that increases in nutrients from Rx-fire caused extensive increases in total primary producer abundance and cyanobacteria dominance, called pyroeutrophication. These data suggest a greater need to understand the implications of fire-associated nutrients on aquatic primary producers wherever fire (but especially Rx-fire) is occurring, as well as an increase in collaboration between forest and aquatic ecosystem managers.ye
Data for: Comparison of two dielectric sensors in coarse-grained soils of increasing salinity
No full textMoisture content can impact the resilient modulus of pavement base course and subgrade layers. Given its influence on the post-inundation resilient moduli of the coastal pavement and base course and subgrade layers, it is important for transportation management personnel to understand the post-inundation moisture state for short-term and long-term planning. Dielectric soil moisture sensors can be used to obtain real-time soil moisture data; however, in coastal areas these sensors will be exposed to salinity. In this study, the performance of two commercially available dielectric soil moisture sensors, one using Time Domain Reflectometry (TDR) technology and one using capacitance technology, in a laboratory environment with three different soil materials was examined. Both sensors measure volumetric water content (θ), bulk electrical conductivity (σb) and temperature. Volumetric water content values from the sensors were compared to gravimetrically obtained values. The results show that the capacitance sensor was more reliable and more accurately measured volumetric water content in all three soil materials
Reusable for who? Discussing "data science ready" repository design
No full textResearch data repositories are intended to make data FAIR - findable, accessible, interoperable, and reusable - but implementing these principles in practical terms entails deciding how to evaluate FAIRness. Recent interpretations of interoperability and reusability, in particular, have based their metrics of progress in implementation around facilitating machine processes. In other words, improving the “I” and the “R” of data in a repository translates into structuring data to be crawled and ingested by automated agents and incorporated as seamlessly as possible into aggregate datasets. This is referred to as “data science ready” research data, and some repositories are working towards this vision in consultation with computer scientists. This talk explores the implications of prioritizing the machine digestibility of research data in repository curation processes. What does this perspective imply about the relative value of datasets intended for reuse by researchers working manually to interpret, restructure, and analyze the data? About the fields of study that primarily produce data of that nature? There are tradeoffs in metadata structure and content when the intended “audience” of data is human vs. machine, and there are also risks associated with stripping research data of its context, as can easily happen when employing big data methodologies. Finally, potential impacts to the research ecosystem are considered. For instance, when data is automatically scraped at scale, what happens if the researchers that made it available miss out on attribution and citation of their work?Who will have oversight over later use, and perhaps misuse, of that data? How would the original creators know if this happened, and what could they do about it?These considerations are important because design choices that can shape the future of research practice should not go forward unexamined and unchallenged
Welcome to the Machine: Ir/Responsible Use of Machine Learning in Research Recommendation Tools
No full textMachine learning is changing how researchers interact with scholarly literature. While it has the potential to reveal exciting new connections between areas of study, popular commercial tools that provide recommendations to users based on personalized profiles developed with machine learning can negatively impact the breadth of sources they will discover. Over time, they may even limit the questions researchers are willing to explore. Find out what machine learning is and how it is being deployed to make the literature more manageable, then learn strategies to warn users about its pitfalls and advocate for the responsible use of this technology.N
