Similarity in Fog and Rainfall Intermittency

Intermittent fog occurrences supply significant amounts of moisture to plants in the form of fog drip onto the soil surface thereby prompting interest in their statistical behavior at multiple timescales. A comparison of rainfall and fog measurements collected at an inland tropical cloud forest in Kenya and a coastal rangeland in Northern California is presented to explore whether fog occurrences have similar intermittency characteristics as rainfall. The results confirm that both rainfall and fog show approximate power law relations for distributions of dry period and event size consistent with predictions from self-organized criticality. Moreover, the spectral exponents of the on-off time series of the fog and rainfall exhibited an approximate f(-0.8) over a broad range of frequencies f, which is remarkably close to scaling exponents across sites experiencing different rainfall generation mechanisms. These results suggest that fog intermittency shares some properties of critical behavior documented in numerous rainfall studies. Plain Language Summary Beyond rainfall, intermittent fog occurrence provides water subsidy that is needed for sustaining transpiration and photosynthesis in forests. To study the connections between fog formation and rainfall, a comparison of rainfall and fog occurrence statistics is carried out at two sites: a Kenyan inland cloud forest and a coastal forest in Northern California. For durations exceeding 1 day, rainfall and fog event sizes and dry periods appear similar. Due to these similarities, intermittency in fog occurrences may abide by general laws describing critical phenomenon.Peer reviewe

Variability in Ejection Fraction Measured By Echocardiography, Gated Single-Photon Emission Computed Tomography, and Cardiac Magnetic Resonance in Patients With Coronary Artery Disease and Left Ventricular Dysfunction

Importance: Clinical decisions are frequently based on measurement of left ventricular ejection fraction (LVEF). Limited information exists regarding inconsistencies in LVEF measurements when determined by various imaging modalities and the potential impact of such variability. Objective: To determine the intermodality variability of LVEF measured by echocardiography, gated single-photon emission computed tomography (SPECT), and cardiovascular magnetic resonance (CMR) in patients with left ventricular dysfunction. Design, Setting, and Participants: International multicenter diagnostic study with LVEF imaging performed at 127 clinical sites in 26 countries from July 24, 2002, to May 5, 2007, and measured by core laboratories. Secondary study of clinical diagnostic measurements of LVEF in the Surgical Treatment for Ischemic Heart Failure (STICH), a randomized trial to identify the optimal treatment strategy for patients with LVEF of 35% or less and coronary artery disease. Data analysis was conducted from March 19, 2016, to May 29, 2018. Main Outcomes and Measures: At baseline, most patients had an echocardiogram and subsets of patients underwent SPECT and/or CMR. Left ventricular ejection fraction was measured by a core laboratory for each modality independent of the results of other modalities, and measurements were compared among imaging methods using correlation, Bland-Altman plots, and coverage probability methods. Association of LVEF by each method and death was assessed. Results: A total of 2032 patients (mean [SD] age, 60.9 [9.6] years; 1759 [86.6%] male) with baseline LVEF data were included. Correlation of LVEF between modalities was r = 0.601 (for biplane echocardiography and SPECT [n = 385]), r = 0.493 (for biplane echocardiography and CMR [n = 204]), and r = 0.660 (for CMR and SPECT [n = 134]). Bland-Altman plots showed only moderate agreement in LVEF measurements from all 3 core laboratories with no substantial overestimation or underestimation of LVEF by any modality. The percentage of observations that fell within a range of 5% ranged from 43% to 54% between different imaging modalities. Conclusions and Relevance: In this international multicenter study of patients with coronary artery disease and reduced LVEF, there was substantial variation between modalities in LVEF determination by core laboratories. This variability should be considered in clinical management and trial design. Trial Registration: Clinicaltrials.gov Identifier: NCT00023595

Minute Sea-Level Analysis (MISELA): a high- frequency sea-level analysis global dataset

Sea-level observations provide information on a variety of processes occurring over different temporal and spatial scales that may contribute to coastal flooding and hazards. However, global research on sea-level extremes is restricted to hourly datasets, which prevent the quantification and analyses of processes occurring at timescales between a few minutes and a few hours. These shorter-period processes, like seiches, meteotsunamis, infragravity and coastal waves, may even dominate in low tidal basins. Therefore, a new global 1 min sea-level dataset – MISELA (Minute Sea-Level Analysis) – has been developed, encompassing quality-checked records of nonseismic sea-level oscillations at tsunami timescales (T<2 h) obtained from 331 tide-gauge sites (https://doi.org/10.14284/456, Zemunik et al., 2021b). This paper describes data quality control procedures applied to the MISELA dataset, world and regional coverage of tide- gauge sites, and lengths of time series. The dataset is appropriate for global, regional or local research of atmospherically induced high-frequency sea-level oscillations, which should be included in the overall sea-level extremes assessments

Root-zone soil moisture variability across African savannas : From pulsed rainfall to land‐cover switches

The main source of soil moisture variability in savanna ecosystems is pulsed rainfall. Rainfall pulsing impacts water-stress durations, soil moisture switching between wet-to-dry and dry-to-wet states, and soil moisture spectra as well as derived measures from it such as soil moisture memory. Rainfall pulsing is also responsible for rapid changes in grassland leaf area and concomitant changes in evapotranspirational (ET) losses, which then impact soil moisture variability. With the use of a hierarchy of models and soil moisture measurements, temporal variability in root-zone soil moisture and water-stress periods are analysed at four African sites ranging from grass to miombo savannas. The normalized difference vegetation index (NDVI) and potential ET (PET)-adjusted ET model predict memory timescale and dry persistence in agreement with measurements. The model comparisons demonstrate that dry persistence and mean annual dry periods must account for seasonal and interannual changes in maximum ET represented by NDVI and to a lesser extent PET. Interestingly, the precipitation intensity and soil moisture memory were linearly related across three savannas with ET/infiltration similar to 1.0. This relation and the variability of length and timing of dry periods are also discussed.Peer reviewe

Recommendations for the Evaluation of Left Ventricular Diastolic Function by Echocardiography

A

Small whole heart volume predicts cardiovascular events in patients with stable chest pain: insights from the PROMISE trial

Objectives The size of the heart may predict major cardiovascular events (MACE) in patients with stable chest pain. We aimed to evaluate the prognostic value of 3D whole heart volume (WHV) derived from non-contrast cardiac computed tomography (CT). Methods Among participants randomized to the CT arm of the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE), we used deep learning to extract WHV, defined as the volume of the pericardial sac. We compared the WHV across categories of cardiovascular risk factors and coronary artery disease (CAD) characteristics and determined the association of WHV with MACE (all-cause death, myocardial infarction, unstable angina; median follow-up: 26 months). Results In the 3798 included patients (60.5 +/- 8.2 years; 51.5% women), the WHV was 351.9 +/- 57.6 cm(3)/m(2). We found smaller WHV in no- or non-obstructive CAD, women, people with diabetes, sedentary lifestyle, and metabolic syndrome. Larger WHV was found in obstructive CAD, men, and increased atherosclerosis cardiovascular disease (ASCVD) risk score (p < 0.05). In a time-to-event analysis, small WHV was associated with over 4.4-fold risk of MACE (HR (per one standard deviation) = 0.221; 95% CI: 0.068-0.721; p = 0.012) independent of ASCVD risk score and CT-derived CAD characteristics. In patients with non-obstructive CAD, but not in those with no- or obstructive CAD, WHV increased the discriminatory capacity of ASCVD and CT-derived CAD characteristics significantly. Conclusions Small WHV may represent a novel imaging marker of MACE in stable chest pain. In particular, WHV may improve risk stratification in patients with non-obstructive CAD, a cohort with an unmet need for better risk stratification

Effects of matrix composition and configuration on forest bird movements in a fragmented Afromontane biodiversity hot spot

Peer reviewe

Automated echocardiographic detection of heart failure with preserved ejection fraction using artificial intelligence

Background: Detection of heart failure with preserved ejection fraction (HFpEF) involves integration of multiple imaging and clinical features which are often discordant or indeterminate. Objectives: We applied artificial intelligence (AI) to analyze a single apical four-chamber (A4C) transthoracic echocardiogram videoclip to detect HFpEF. Methods: A three-dimensional convolutional neural network was developed and trained on A4C videoclips to classify patients with HFpEF (diagnosis of HF, EF≥50%, and echocardiographic evidence of increased filling pressure; cases) versus without HFpEF (EF≥50%, no diagnosis of HF, normal filling pressure; controls). Model outputs were classified as HFpEF, no HFpEF, or non-diagnostic (high uncertainty). Performance was assessed in an independent multi-site dataset and compared to previously validated clinical scores. Results: Training and validation included 2971 cases and 3785 controls (validation holdout, 16.8% patients), and demonstrated excellent discrimination (AUROC:0.97 [95%CI:0.96-0.97] and 0.95 [0.93-0.96] in training and validation, respectively). In independent testing (646 cases, 638 controls), 94 (7.3%) were non-diagnostic; sensitivity (87.8%; 84.5-90.9%) and specificity (81.9%; 78.2-85.6%) were maintained in clinically relevant subgroups, with high repeatability and reproducibility. Of 701 and 776 indeterminate outputs from the HFA-PEFF and H2FPEF scores, the AI HFpEF model correctly reclassified 73.5 and 73.6%, respectively. During follow-up (median [IQR]:2.3 [0.5-5.6] years), 444 (34.6%) patients died; mortality was higher in patients classified as HFpEF by AI (hazard ratio [95%CI]:1.9 [1.5-2.4]). Conclusion: An AI HFpEF model based on a single, routinely acquired echocardiographic video demonstrated excellent discrimination of patients with versus without HFpEF, more often than clinical scores, and identified patients with higher mortality