For regional groundwater flow models (areas greater than 100,000 km ), improper choice of map projection parameters can result in model error for boundary conditions dependent on area (recharge or evapotranspiration simulated by application of a rate using cell area from model discretization) and length (rivers simulated with head-dependent flux boundary). Smaller model areas can use local map coordinates, such as State Plane (United States) or Universal Transverse Mercator (correct zone) without introducing large errors. Map projections vary in order to preserve one or more of the following properties: area, shape, distance (length), or direction. Numerous map projections are developed for different purposes as all four properties cannot be preserved simultaneously. Preservation of area and length are most critical for groundwater models. The Albers equal-area conic projection with custom standard parallels, selected by dividing the length north to south by 6 and selecting standard parallels 1/6th above or below the southern and northern extent, preserves both area and length for continental areas in mid latitudes oriented east-west. Custom map projection parameters can also minimize area and length error in non-ideal projections. Additionally, one must also use consistent vertical and horizontal datums for all geographic data. The generalized polygon for the Floridan aquifer system study area (306,247.59 km ) is used to provide quantitative examples of the effect of map projections on length and area with different projections and parameter choices. Use of improper map projection is one model construction problem easily avoided.
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http://dx.doi.org/10.1111/gwat.12450 | DOI Listing |
Sci Data
January 2025
Remote Sensing Centre for Earth System Research (RSC4Earth), Leipzig University, Leipzig, 04103, Germany.
With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show promise but require well-structured, high-quality, and curated analysis-ready datasets. Earth observation datasets comprehensively monitor ecosystem dynamics and responses to climatic extremes, yet the data complexity can challenge the effectiveness of machine learning models.
View Article and Find Full Text PDFCell
January 2025
Program in Bioinformatics, Boston University, Boston, MA 02215, USA; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada; Center for Network Systems Biology, Boston University, Boston, MA 02218, USA; Department of Chemistry, Boston University, Boston, MA 02215, USA; Department of Chemical Physiology and Biochemistry, Division of Oncological Sciences, Knight Cancer Institute, Oregon Health and Science University, Portland, OR, USA. Electronic address:
Knowledge of protein-metabolite interactions can enhance mechanistic understanding and chemical probing of biochemical processes, but the discovery of endogenous ligands remains challenging. Here, we combined rapid affinity purification with precision mass spectrometry and high-resolution molecular docking to precisely map the physical associations of 296 chemically diverse small-molecule metabolite ligands with 69 distinct essential enzymes and 45 transcription factors in the gram-negative bacterium Escherichia coli. We then conducted systematic metabolic pathway integration, pan-microbial evolutionary projections, and independent in-depth biophysical characterization experiments to define the functional significance of ligand interfaces.
View Article and Find Full Text PDFMed Phys
January 2025
Department of Radiation Oncology, Duke University, North Carolina, USA.
Background: The electronic compensation (ECOMP) technique for breast radiation therapy provides excellent dose conformity and homogeneity. However, the manual fluence painting process presents a challenge for efficient clinical operation.
Purpose: To facilitate the clinical treatment planning automation of breast radiation therapy, we utilized reinforcement learning (RL) to develop an auto-planning tool that iteratively edits the fluence maps under the guidance of clinically relevant objectives.
G3 (Bethesda)
January 2025
W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA.
The mosquito Aedes aegypti is an emerging model insect for invertebrate neurobiology. We detail the application of a dual transgenesis marker system that reports the nature of transgene integration with circular donor template for CRISPR-Cas9-mediated homology-directed repair at target mosquito chemoreceptor genes. Employing this approach, we demonstrate the establishment of cell-type-specific T2A-QF2 driver lines for the A.
View Article and Find Full Text PDFFront Neural Circuits
January 2025
Department of Advanced Medical and Surgical Sciences, Advanced MRI Research Center, University of Campania "Luigi Vanvitelli", Naples, Italy.
The substantia nigra pars compacta (SNc), one of the main dopaminergic nuclei of the brain, exerts a regulatory function on the basal ganglia circuitry via the nigro-striatal pathway but its possible dopaminergic innervation of the thalamus has been only investigated in non-human primates. The impossibility of tract-tracing studies in humans has boosted advanced MRI techniques and multi-shell high-angular resolution diffusion MRI (MS-HARDI) has promised to shed more light on the structural connectivity of subcortical structures. Here, we estimated the possible dopaminergic innervation of the human thalamus via an MS-HARDI tractography of the SNc in healthy human young adults.
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