A Limnological Study of Ricks Pond and the Gulpha Creek Drainage in Garland County, Arkansas

A limnological investigation of Ricks Pond and the Gulpha Creek drainage of Garland County, Arkansas was conducted between 1 June 1978, and 21 August 1978. Water samples taken from ten stations on three different dates indicated that the stream and pond systems were typical in water quality characteristics of other small, high gradient streams and impoundments in the Ouachita Mountains of Arkansas. In Ricks Pond, thermal stratification occurred along with the development of an oxygen deficient zone below a depth of one meter. Other water quality parameters indicated that Ricks Pond is a moderately productive ecosystem, with the productivity limited by the nitrogen species. The fecal coliform bacterial counts were very low, indicating no direct input of excessive amounts of fecal matter into the system during the present study. However, a Hot Springs city sewer line runs through the pond, and two manholes emerge from the pond\u27s surface. The possibility exists that this sewer line could discharge raw sewage into Ricks Pond during periods of high water. A biological investigation was also conducted in the study area, and lists of the phytoplankton, periphyton, higher aquatic vegetation, zooplankton, benthic macroinvertebrates, and fishes are presented. Twenty-seven species of fishes were collected from the Gulpha Creek drainage, and no rare or endangered forms were found. Ricks Pond is best-suited for the establishment of a put- and-take fishery for channel catfish, Ictalurus punctatus. The following recommendations were made for the establishment of such a fishery: (1) Renovation of the pond by draining and deepening it; (2) Removal of the sewer line from the pond; (3) Stocking of catchable size channel catfish at the rate of approximately 300-400 pounds per acre; (4) Periodic monitoring of the water quality

Spatially targeted nature-based solutions can mitigate climate change and nature loss but require a systems approach

Funding Information: This study was funded by the Royal Society for the Protection of Birds (RSPB) and Natural England (project code ECM 58632). The Breeding Bird Survey is a Partnership between the BTO, RSPB, and Joint Nature Conservation Committee (on behalf of Natural Resources Wales, Natural England, Council for Nature Conservation and Countryside, and NatureScot) and relies on volunteer surveyors. Simon Gillings provided tetrad-level predictions of relative abundance for wading birds. We are grateful to members of the RSPB steering group, who contributed to the development of our scenarios, and Profs. Tim Benton and Andrew Balmford who commented on an earlier version of this manuscript. Conceptualization, T.F. R.B.B. T.B.-L. G.M.B. W.J.P. and R.H.F.; methodology, T.F. T.B.-L. J.P.C. D.M. P.S. and R.H.F.; software, T.F.; formal analysis, T.F.; resources, D.M.; data curation, T.F.; writing – original draft, T.F.; writing – review & editing, R.B.B. T.B.-L. G.M.B. J.P.C. D.M. P.S. W.J.P. and R.H.F.; visualization, T.F.; supervision, W.J.P. The authors declare no competing interests. Publisher Copyright: © 2023 The AuthorsPeer reviewedPublisher PD

Comparison of structural MRI brain measures between 1.5 and 3T: Data from the Lothian Birth Cohort 1936

Multi‐scanner MRI studies are reliant on understanding the apparent differences in imaging measures between different scanners. We provide a comprehensive analysis of T(1)‐weighted and diffusion MRI (dMRI) structural brain measures between a 1.5 T GE Signa Horizon HDx and a 3 T Siemens Magnetom Prisma using 91 community‐dwelling older participants (aged 82 years). Although we found considerable differences in absolute measurements (global tissue volumes were measured as ~6–11% higher and fractional anisotropy [FA] was 33% higher at 3 T than at 1.5 T), between‐scanner consistency was good to excellent for global volumetric and dMRI measures (intraclass correlation coefficient [ICC] range: .612–.993) and fair to good for 68 cortical regions (FreeSurfer) and cortical surface measures (mean ICC: .504–.763). Between‐scanner consistency was fair for dMRI measures of 12 major white matter tracts (mean ICC: .475–.564), and the general factors of these tracts provided excellent consistency (ICC ≥ .769). Whole‐brain structural networks provided good to excellent consistency for global metrics (ICC ≥ .612). Although consistency was poor for individual network connections (mean ICCs: .275−.280), this was driven by a large difference in network sparsity (.599 vs. .334), and consistency was improved when comparing only the connections present in every participant (mean ICCs: .533–.647). Regression‐based k‐fold cross‐validation showed that, particularly for global volumes, between‐scanner differences could be largely eliminated (R (2) range .615–.991). We conclude that low granularity measures of brain structure can be reliably matched between the scanners tested, but caution is warranted when combining high granularity information from different scanners

Factors affecting faculty use of learning technologies: Implications for models of technology adoption

This study examines factors associated with the use of learning technologies by higher education faculty. In an online survey in a UK university, 114 faculty respondents completed a measure of Internet self-efficacy, and reported on their use of learning technologies along with barriers to their adoption. Principal components analysis suggested two main barriers to adoption: structural constraints within the University and perceived usefulness of the tools. Regression analyses indicated both these variables, along with Internet self-efficacy, were associated with use of online learning technology. These findings are more consistent with models of technology engagement that recognize facilitating or inhibiting conditions (unified theory of acceptance and use of technology; decomposed theory of planned behavior) than the classic technology acceptance model (TAM). Practical implications for higher education institutions are that while faculty training and digital literacy initiatives may have roles to play, structural factors (e.g., provision of resources and technical support) must also be addressed for optimal uptake of learning technologies

General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning

We thank the participants of the three cohorts (UKB, Generation Scotland (STRADL) and LBC1936) for their participation and the research teams for their work in collecting, processing and giving access to these data for analysis. We are also thankful to the brain donors to the Allen Human Brain Atlas, BrainSpan Atlas and Human Brain Transcriptome Project, and to the people who collected and processed the data and made it openly available For the purpose of open access, the author has applied a CC-BY public copyright licence to any Author Accepted Manuscript version arising from this submission.Peer reviewe

General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components: gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 29 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|β| range = 0.18 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning

General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components: gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 29 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|β| range = 0.18 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning

Endogenous Constitutions: Politics and Politicians Matter, Economic Outcomes Don’t

We study changes in the form of government as an example of endogenously determined constitutions. For a sample of 202 countries over the period 1950-2006, we find that most changes are relatively small and roughly equally likely to be either in the direction of more parliamentarian or more presidential systems. Based on a fixed effects ordered logit panel data model estimated over the period 1951-2000 for 146 countries, we find that such changes in the constitution can be explained by characteristics of the political system, internal and external political conflicts, and political leaders, whereas economic and socio-demographic variables do not matter

Physiological Stress Mediates the Honesty of Social Signals

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