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Depositional setting, structural style, and sandstone distribution in three geopressured geothermal areas, Texas Gulf Coast
No full textTo obtain a print version of this publication visit: https://store.beg.utexas.edu/ and search for: RI0134.
Funded by the U.S. Department of Energy, Division of Geothermal Energy, under contract nos. DE-AS05-76ET28461 and DE-AC08-79ET27111.Three areas in the Texas Gulf Coastal Plain were studied using electric logs and seismic reflection data to interpret their depositional and structural history and to compare their potential as geopressured-geothermal reservoirs. The Cuero study area, on the lower Wilcox (upper Paleocene) growth-fault trend, is characterized by closely and evenly spaced, subparallel, down-to-the-basin growth faults, relatively small expansion ratios, and minor block rotation. Distributary-channel sandstones in the geopressured lower Wilcox Group of the South Cook fault block appear to be the best geothermal aquifers in the Cuero area. The Blessing study area, on the lower Frio (Oligocene) growth-fault trend, shows wider and more variable fault spacing and much greater expansion ratios and block rotation, particularly during early Frio time. Thick geopressured sandstone aquifers are laterally more extensive in the Blessing area than in the Cuero area. The Pleasant Bayou study area, like the Blessing area, is on the Frio growth-fault trend, and its early structural development was similar; rapid movement of widely spaced faults resulted in large expansion ratios and major block rotation. However, a late-stage pattern of salt uplift and withdrawal complicated the structural style. Thick geopressured lower Frio sandstone aquifers are highly permeable and laterally extensive, as in the Blessing area. In all three areas, geopressured aquifers were created where early, rapid movement along down-to-the-basin growth faults juxtaposed shallow-water sands against older shales, probably deposited in slope environments. Major transgressions followed the deposition of reservoir sands and probably also influenced the hydraulic isolation that allowed the buildup of abnormal pressures. Of the three areas, the Pleasant Bayou area has the best potential for geothermal energy production because of larger fault block area, greater thickness and lateral continuity of individual sandstones, and higher formation temperatures and pressures.UT LibrariesBureau of Economic Geolog
Editorial: The 3rd Special Issue on Optimization Heuristics in Estimation
No full textEditorial
The 3rd Special Issue on Optimization Heuristics in Estimatio
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
The Stochastics of Threshold Accepting: Analysis of an Application to the Uniform Design Problem
No full textThreshold Accepting (TA) is a powerful optimization heuristic from the class of stochastic local search algorithms. It has been applied successfully to different optimization problems in statistics and econometrics, including the uniform design problem. Using the latter application as example, the stochastic properties of a TA implementation are analyzed. We provide a formal framework for the analysis of optimization heuristics like TA, which can be used to estimate lower bounds and to derive convergence results. It is also helpful for tuning real applications. Based on this framework, empirical results are presented for the uniform design problem. In particular, for two problem instances, the rate of convergence of the algorithm is estimated to be of the order of a power of -0.3 to -0.7 of the number of iterations. --Heuristic optimization,Threshold Accepting,Stochastic analysis of heuristics
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Checklist of the avian diversity of Alaska
No full textMore than just a state, Alaska constitutes the entire northwestern extent of North America. Alaska is a vast area (586,412 mi2/1,518,800 km2 of land), spanning nearly 60 degrees of longitude and 20 degrees of latitude, with roughly ~45,000 mi/72,000 km of coastline. The area considered here includes surrounding waters within the U. S. 200-nautical-mile exclusive economic zone (see Gibson and Withrow 2015) and thus represents an area of over 2,000,000 mi2/~5,000,000 km2. It represents the eastern half of Beringia, a pivotally important area for the exchange of New and Old World avifaunas and for high-latitude avian endemism (Winker et al. 2023). Spanning a wide swath of the northern reaches of the Pacific Ocean, Alaska hosts breeding migrants from all seven continents, including tens of millions of birds from Asia (Winker and Gibson 2010).
There are three main intrinsic drivers of Alaska’s avian diversity: Its geographic size and position on the globe, the diversity of its aquatic and terrestrial habitats, and its dynamic history of climatic and habitat fluctuations. This region’s high latitude causes extreme annual seasonality, making migration a predominant life-history strategy among the state’s birds. With migration, especially long-distance migration, comes enhanced dispersal, increasing the likelihood of vagrancy and colonization.
Diverse contemporary habitat types occur in extensive expanses of nearshore and offshore marine waters; marine, brackish, and freshwater littoral zones; freshwater wetlands, rivers, lakes, and streams; the variety of heath and tundra types that dominate the Aleutian and Bering Sea islands, much of western and northern Alaska, and alpine areas; and meadows, shrubs, taiga (boreal forest), and temperate rainforests (e.g., Gabrielson and Lincoln 1959; Kessel 1979, 1998; Audubon Alaska 2014). Because of past glacial cycles, the availability and distribution of these habitats has changed throughout the Pleistocene, but the lack of major glaciation throughout much of Beringia caused the region as a whole to be a large glacial refugium within which smaller refugia also existed for some birds (Winker et al. 2023). This long-term history generated high levels of regional endemism (for this latitude) among species and subspecies of birds (ibid). In addition, southeast Alaska extends into the Pacific Northwest refugium complex, adding further to the state’s avian diversity (Shafer et al. 2010, Winker et al. 2023).
The historic climatic dynamism of the Pleistocene continues today and into the future with global warming, which is occurring about four times faster in Arctic regions than elsewhere (Previdi et al. 2021, Rantanen et al. 2022). Alaska’s extensive Arctic environments (see U.S. Congress 1984) are thus undergoing rapid changes, affecting avian occurrences and distributions in multiple ways (e.g., Marcot et al. 2015, Smith et al. 2019, Renner et al. 2024). Importantly, many changes will not be due to habitat shifts. Among migratory birds in this region, extensive movements are made in eastern and western directions, such that the time available to reproduce, more than habitat, dictates range limits. As growing seasons lengthen, these range limits can change rapidly (see Benson and Winker 2015, Winker and Gibson 2018). Together, these drivers explain not only the current diversity of Alaska birds, but also why we expect this list to continue to grow over time.
The starting point for this list is AOU (1998) and supplements through Chesser et al. (2023) for phylogenetic sequence and the limits of families, genera, and species. We no longer follow this list, because the American Ornithological Society decided to use avian nomenclature as a tool of social activism. This leaves us free to retain long-used names and to occasionally disagree over interpretations of the scientific evidence for some taxonomic changes. These differences can be found in the NOTES sections of the affected taxa and are summarized in the Appendix.
For subspecies, the starting point is Gibson and Withrow (2015) and the two subsequent reports of the Alaska Checklist Committee (Gibson et al. 2018, 2023). The Alaska Checklist Committee (ACC) has been instrumental in collating, assessing, and publishing new records of Alaska birds. Designation of status (rare, casual, accidental; see Key to occurrence, below) at the species level follows this committee’s Checklist of Alaska Birds, 31st edition (Gibson et al. 2025). Changes from these starting points are based on published evidence and are referenced and explained (except for changes to status, which can generally be found in the ACC reports). The breeding status for all taxa is also given (see Key).
We consider subspecies to be populations or groups of populations that breed in a portion of the species’ range that have a diagnosably different phenotype from other subspecies (in presumably heritable traits). Subspecies have the potential for gene flow between them, and diagnosability generally follows the 75% Rule (Patten and Unitt 2002, Winker and Haig 2010). We recognize that some of the subspecies recognized here might not meet stringent contemporary standards of diagnosability, but until they are examined in more detail and those results are published, we maintain the historical perspective as a working hypothesis. Subspecies in brackets are those not represented by an archived specimen and/or where the identity is an inference (usually geographic). Our ability to find differences among populations, especially in genetics, has grown immensely, but some traits (e.g., neutral genetic differences, vocalizations in taxa where they are learned) are not as indicative of the long-term, adaptive changes that subspecies nomenclature attempts to capture.
For brevity, we do not give distributional statements, those being available elsewhere (e.g., AOU 1957, 1998; Vaurie 1959, 1965; Dickinson and Remsen 2013; Dickinson and Christidis 2014; del Hoyo and Collar 2014, 2016; Gibson and Withrow 2015; etc.). Full citations to the authorities for taxa listed here can be obtained, for example, from A. P. Peterson’s website (Zoonomen.net), D. Lepage’s and Birds Canada website Avibase (avibase.bsc-eoc.org), and in Lynx Edicions Handbook of the Birds of the World series.
Alaska’s avian checklist has grown at a remarkably steady average of 3.5 species per year since the mid-1900s and shows no sign of reaching an asymptote. Gabrielson and Lincoln (1959) discussed 311 species of Alaska birds, and that number grew steadily through Kessel and Gibson (1978: 381), Gibson and Kessel (1992: 436), Gibson and Kessel (1997: 448), Gibson et al. (2003: 468), Gibson et al. (2008: 485), Gibson et al. (2013: 499), Gibson et al. (2018: 521), and Gibson et al. (2023: 541). This checklist of Alaska’s birds now includes 548 species and an additional 119 subspecies. Of these 548 species, 55 are rare, 159 are casual, and 85 are accidental; 234 species regularly breed within the state (“B”; with an additional 75 regularly breeding subspecies). An additional 38 species have at one time or another bred within the state (“b”), and 8 probably have (“?”), but are not here considered a normal part of the nesting avifauna
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
L-kynurenine as a prognostic marker for early mortality in patients with acute myeloid leukemia
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