The risk of contracting VL. حسب Cameron Davis (19803404)

"…The parameter values are as shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0311314#pone.0311314.t001" target="_blank">Table 1</a>.…"

Decision-maker informed optimal policy design. حسب Hongru Du (4640212)

"…Increasing <i>a</i> places greater emphasis on minimizing policy cost, while decreasing it prioritizes reducing infections averted. …"

SOX10 mRNA levels are not sensitive to glucose or G-6-P concentrations. حسب Ana Luisa Dian (22258504)

"…<p><b>(A)</b> RT-qPCR quantification of the <i>SOX10</i> mRNA level in A375 cells cultured for 24 h with decreasing concentrations of glucose or under glucose starvation, as indicated (SD, <i>n</i> = 3 biological replicates). …"

Forests to Faucets 2.0 حسب U.S. Forest Service (17476914)

"…Only accurate for an individual HUC12.Calculated using RIMPRaw Important Areas for Surface Drinking Water (IMP) Value. As developed in Forests to Faucets (USFS 2011), the Important Areas for Surface Drinking Water (IMP) model can be broken down into two parts: IMPn = (PRn) * (Qn)Calculated using R, Updated September 2023IMP_RIMP, Important Areas for Surface Drinking Water (0-100 Quantiles)Calculated using R, Updated September 2023NON_FORESTAcres of non-forestPADUS and NLCDPRIVATE_FORESTAcres of private forestPADUS and NLCDPROTECTED_FORESTAcres of protected forest (State, Local, NGO, Permanent Easement)PADUS, NCED, and NLCDNFS_FORESTAcres of National Forest System (NFS) forestPADUS and NLCDFEDERAL_FORESTAcres of Other Federal forest (Non-NFS Federal)PADUS and NLCDPER_FORPRIPercent Private ForestCalculated using ArcGISPER_FORNFSPercent NFS ForestCalculated using ArcGISPER_FORPROPercent Protected (Other State, Local, NGO, Permanent Easement, NFS, and Federal) ForestCalculated using ArcGISWFP_HI_ACAcres with High and Very High Wildfire Hazard Potential (WHP)Dillon, 2018PER_WFPPercent of HU 12 with High and Very High Wildfire Hazard Potential (WHP)Dillon, 2018PER_IDRISKPercent of HU 12 that is at risk for mortality - 25% of standing live basal area greater than one inch in diameter will die over a 15- year time frame (2013 to 2027) due to insects and diseases.Krist, et Al,. 2014PERDEV_1040_45% Landuse Change 2010-2040 (low)ICLUSPERDEV_1090_45% Landuse Change 2010-2090 (low)ICLUSPERDEV_1040_85% Landuse Change 2010-2040 (high)ICLUSPERDEV_1090_85% Landuse Change 2010-2090 (high)ICLUSPER_Q40_45% Water Yield Change 2010-2040 (low) WASSI , Updated September 2023PER_Q90_45% Water Yield Change 2010-2090 (low) WASSI , Updated September 2023PER_Q40_85% Water Yield Change 2010-2040 (high) WASSI , Updated September 2023PER_Q90_85% Water Yield Change 2010-2090 (high) WASSI , Updated September 2023WFP(APCW_R * IMP_R * PER_WFP )/ 10,000Wildfire Threat to Important Surface Drinking Water Watersheds Calculated using ArcGIS, Updated September 2023IDRISK(APCW_R * IMP_R * PER_IDRISK )/ 10,000Insect & Disease Threat to Important Surface Drinking Water Watersheds Calculated using ArcGIS, Updated September 2023DEV1040_45(APCW_R * IMP_R * PERDEV_1040_45)/ 10,000 Landuse Change in Important Surface Drinking Water Watersheds 2010-2040 (low emissions) Calculated using ArcGIS, Updated September 2023DEV1090_45(APCW_R * IMP_R * PERDEV_1090_45)/ 10,000 Landuse Change in Important Surface Drinking Water Watersheds 2010-2040 (high emissions) Calculated using ArcGIS, Updated September 2023DEV1040_85(APCW_R * IMP_R * PERDEV_1040_85)/ 10,000 Landuse Change in Important Surface Drinking Water Watersheds 2010-2090 (low emissions) Calculated using ArcGIS, Updated September 2023DEV1090_85(APCW_R * IMP_R * PERDEV_1090_85)/ 10,000 Landuse Change in Important Surface Drinking Water Watersheds 2010-2090 (high emissions) Calculated using ArcGIS, Updated September 2023Q1040_45-1 * (APCW_R * IMP_R * PER_Q40_45)/ 10,000 Water Yield Decrease in Important Surface Drinking Water Watersheds 2010-2040 (low emissions) Calculated using ArcGIS, Updated September 2023Q1090_45-1 * (APCW_R * IMP_R * PER_Q90_45)/ 10,000 Water Yield Decrease in Important Surface Drinking Water Watersheds 2010-2040 (high emissions) Calculated using ArcGIS, Updated September 2023Q1040_85-1 * (APCW_R * IMP_R * PER_Q40_85)/ 10,000 Water Yield Decrease in Important Surface Drinking Water Watersheds 2010-2090 (low emissions) Calculated using ArcGIS, Updated September 2023Q1090_85-1 * (APCW_R * IMP_R * PER_Q90_85)/ 10,000 Water Yield Decrease in Important Surface Drinking Water Watersheds 2010-2090 (high emissions) Calculated using ArcGIS, Updated September 2023WFP_IMP_RWildfire Threat to Important Surface Drinking Water Watersheds (0-100 Quantiles)Calculated using R, Updated September 2023IDRISK_RInsect & Disease Threat to Important Surface Drinking Water Watersheds (0-100 Quantiles)Calculated using R, Updated September 2023DEV40_45_RLanduse Change in Important Surface Drinking Water Watersheds 2010-2040 (low emissions) (0-100 Quantiles)Calculated using R, Updated September 2023DEV40_85_RLanduse Change in Important Surface Drinking Water Watersheds 2010-2040 (high emissions) (0-100 Quantiles)Calculated using R, Updated September 2023DEV90_45_RLanduse Change in Important Surface Drinking Water Watersheds 2010-2090 (low emissions) (0-100 Quantiles)Calculated using R, Updated September 2023DEV90_85_RLanduse Change in Important Surface Drinking Water Watersheds 2010-2090 (high emissions) (0-100 Quantiles)Calculated using R, Updated September 2023Q40_45_RWater Yield Decrease in Important Surface Drinking Water Watersheds 2010-2040 (low emissions) (0-100 Quantiles)Calculated using R, Updated September 2023Q40_85_RWater Yield Decrease in Important Surface Drinking Water Watersheds 2010-2040 (high emissions) (0-100 Quantiles)Calculated using R, Updated September 2023Q90_45_RWater Yield Decrease in Important Surface Drinking Water Watersheds 2010-2090 (low emissions) (0-100 Quantiles)Calculated using R, Updated September 2023Q90_85_RWater Yield Decrease in Important Surface Drinking Water Watersheds 2010-2090 (high emissions) (0-100 Quantiles)Calculated using R, Updated September 2023RegionUS Forest Service Region numberUSFSRegionnameUS Forest Service Region nameUSFSHUC_Num_DiffThis field compares the value in column HUC12(circa 2019 wbd) with the value in HUC_12 (circa 2009 wassi)-1 = No equivalent WASSI HUC. …"

Image 3_Red blood cell lipid distribution in the pathophysiology and laboratory evaluation of chorea-acanthocytosis and McLeod syndrome patients.jpeg حسب Anne-Sophie Cloos (9082913)

"…<p>The core neuroacanthocytosis syndromes, i.e., chorea-acanthocytosis/VPS13A disease (ChAc) and McLeod syndrome/XK disease (MLS), are respectively due to mutations in VPS13A and XK genes and share similar manifestations including the formation of acanthocytes. …"

Image 2_Red blood cell lipid distribution in the pathophysiology and laboratory evaluation of chorea-acanthocytosis and McLeod syndrome patients.jpeg حسب Anne-Sophie Cloos (9082913)

"…<p>The core neuroacanthocytosis syndromes, i.e., chorea-acanthocytosis/VPS13A disease (ChAc) and McLeod syndrome/XK disease (MLS), are respectively due to mutations in VPS13A and XK genes and share similar manifestations including the formation of acanthocytes. …"

Data Sheet 2_Inertial measurement unit technology for gait detection: a comprehensive evaluation of gait traits in two Italian horse breeds.docx حسب Vittoria Asti (14490794)

"…This work aims to investigate on IMU recorded data (i) the influence of environmental factors and biometric measurements, (ii) their repeatability, (iii) the correlation with judge evaluations, and (iv) their predictive value.…"

GO and KEGG pathway analyses of the DE-mRNAs. حسب Meimei Xu (744867)

"…The color transition from blue to red indicates decreasing <i>P</i> values, indicating increasingly significant differences. …"

Proof-of-concept of fiber population statistics inference from eCAP data. Optimization is able to recover ground-truth fiber distribution parameters. حسب Joseph James Tharayil (21416715)

"…<p>a: Reference diameter distribution, and diameter distributions with initial and inferred (i.e., optimized) parameters. b: Reference eCAP and eCAPs obtained with initial and inferred (i.e., optimized) parameters. c: Difference metric between reference eCAP and eCAP with inferred parameters decreases sharply after ∼100 optimization iterations. d-e: Shape parameter (d) and scale parameter (e) converge to ground-truth values (indicated by blue line).…"

Shooting an Arrow against Convulsion: Novel Triazole-Grafted Benzenesulfonamide Derivatives as Carbonic Anhydrase II and VII Inhibitors حسب Mohamed A. Zeidan (21099628)

"…Of these, <b>5b</b> and <b>5c</b> exhibited remarkable selectivity and inhibitory efficacy toward hCA VII and hCA II over hCA I. The <i>K</i>_I values of <b>5b</b> and <b>5c</b> were 6.3 and 10.1 nM, respectively, and 21.6 and 18.9 nM, respectively. …"

Shooting an Arrow against Convulsion: Novel Triazole-Grafted Benzenesulfonamide Derivatives as Carbonic Anhydrase II and VII Inhibitors حسب Mohamed A. Zeidan (21099628)

"…Of these, <b>5b</b> and <b>5c</b> exhibited remarkable selectivity and inhibitory efficacy toward hCA VII and hCA II over hCA I. The <i>K</i>_I values of <b>5b</b> and <b>5c</b> were 6.3 and 10.1 nM, respectively, and 21.6 and 18.9 nM, respectively. …"

Shooting an Arrow against Convulsion: Novel Triazole-Grafted Benzenesulfonamide Derivatives as Carbonic Anhydrase II and VII Inhibitors حسب Mohamed A. Zeidan (21099628)

"…Of these, <b>5b</b> and <b>5c</b> exhibited remarkable selectivity and inhibitory efficacy toward hCA VII and hCA II over hCA I. The <i>K</i>_I values of <b>5b</b> and <b>5c</b> were 6.3 and 10.1 nM, respectively, and 21.6 and 18.9 nM, respectively. …"

Shooting an Arrow against Convulsion: Novel Triazole-Grafted Benzenesulfonamide Derivatives as Carbonic Anhydrase II and VII Inhibitors حسب Mohamed A. Zeidan (21099628)

"…Of these, <b>5b</b> and <b>5c</b> exhibited remarkable selectivity and inhibitory efficacy toward hCA VII and hCA II over hCA I. The <i>K</i>_I values of <b>5b</b> and <b>5c</b> were 6.3 and 10.1 nM, respectively, and 21.6 and 18.9 nM, respectively. …"

Shooting an Arrow against Convulsion: Novel Triazole-Grafted Benzenesulfonamide Derivatives as Carbonic Anhydrase II and VII Inhibitors حسب Mohamed A. Zeidan (21099628)

"…Of these, <b>5b</b> and <b>5c</b> exhibited remarkable selectivity and inhibitory efficacy toward hCA VII and hCA II over hCA I. The <i>K</i>_I values of <b>5b</b> and <b>5c</b> were 6.3 and 10.1 nM, respectively, and 21.6 and 18.9 nM, respectively. …"

Data Sheet 1_Age-related trajectories of quality of life in community dwelling older adults: findings from the Survey of Health, Aging and Retirement in Europe (SHARE).docx حسب Sarah Mendorf (11632098)

"…Clinically relevant changes were defined via the minimal clinically important difference (MCID). We applied linear regression and linear mixed models (LMM) to explore predictors of QoL trajectories.…"

Table 3_Age-related trajectories of quality of life in community dwelling older adults: findings from the Survey of Health, Aging and Retirement in Europe (SHARE).docx حسب Sarah Mendorf (11632098)

"…Clinically relevant changes were defined via the minimal clinically important difference (MCID). We applied linear regression and linear mixed models (LMM) to explore predictors of QoL trajectories.…"

Table 4_Age-related trajectories of quality of life in community dwelling older adults: findings from the Survey of Health, Aging and Retirement in Europe (SHARE).docx حسب Sarah Mendorf (11632098)

"…Clinically relevant changes were defined via the minimal clinically important difference (MCID). We applied linear regression and linear mixed models (LMM) to explore predictors of QoL trajectories.…"

Data Sheet 2_Age-related trajectories of quality of life in community dwelling older adults: findings from the Survey of Health, Aging and Retirement in Europe (SHARE).docx حسب Sarah Mendorf (11632098)

"…Clinically relevant changes were defined via the minimal clinically important difference (MCID). We applied linear regression and linear mixed models (LMM) to explore predictors of QoL trajectories.…"

Table 2_Age-related trajectories of quality of life in community dwelling older adults: findings from the Survey of Health, Aging and Retirement in Europe (SHARE).docx حسب Sarah Mendorf (11632098)

"…Clinically relevant changes were defined via the minimal clinically important difference (MCID). We applied linear regression and linear mixed models (LMM) to explore predictors of QoL trajectories.…"

Data Sheet 3_Age-related trajectories of quality of life in community dwelling older adults: findings from the Survey of Health, Aging and Retirement in Europe (SHARE).docx حسب Sarah Mendorf (11632098)

"…Clinically relevant changes were defined via the minimal clinically important difference (MCID). We applied linear regression and linear mixed models (LMM) to explore predictors of QoL trajectories.…"