Search

Rangeland ecosystems in the western United States are vulnerable to climate change, fire, and anthropogenic disturbances, yet classification of rangeland areas remains difficult due to frequently sparse vegetation canopies that increase the influence of soils and senesced vegetation, the overall abundance of senesced vegetation, heterogeneity of life forms, and limited ground-based data. The Rangeland Condition Monitoring Assessment and Projection (RCMAP) project provides fractional vegetation cover maps across western North America using Landsat imagery and artificial intelligence from 1985 to 2023 at yearly time-steps. The objectives of this case study are to apply hyperspectral data from several new data streams, including Sentinel Synthetic Aperture Radar (SAR) and Earth Surface Mineral Dust Source Investigation (EMIT), to the RCMAP model. We run a series of five tests (Landsat-base model, base + SAR, base + EMIT, base + SAR + EMIT, and base + Landsat NEXT [LNEXT] synthesized from EMIT) over a difficult-to-classify region centered in southwest Montana, USA. Our testing results indicate a clear accuracy benefit of adding SAR and EMIT data to the RCMAP model, with a 7.5% and 29% relative increase in independent accuracy (R2), respectively. The ability of SAR data to observe vegetation height allows for more accurate classification of vegetation types, whereas EMIT’s continuous characterization of the spectral response boosts discriminatory power relative to multispectral data. Our spectral profile analysis reveals the enhanced classification power with EMIT is related to both the improved spectral resolution and representation of the entire domain as compared to legacy Landsat. One key finding is that legacy Landsat bands largely miss portions of the electromagnetic spectrum where separation among important rangeland targets exists, namely in the 900–1250 nm and 1500–1780 nm range. Synthesized LNEXT data include these gaps, but the reduced spectral resolution compared to EMIT results in an intermediate 18% increase in accuracy relative to the base run. Here, we show the promise of enhanced classification accuracy using EMIT data, and to a smaller extent, SAR.

The accuracy of surface reflectance estimation for satellite sensors using radiance-based calibrations can depend significantly on the choice of solar spectral irradiance (or solar spectrum) model used for atmospheric correction. Selecting an accurate solar spectrum model is also important for radiance-based sensor calibration and estimation of atmospheric parameters from irradiance observations. Previous research showed that Landsat 8 could be used to evaluate the quality of solar spectrum models. This paper applies the analysis using five previously evaluated and three more recent solar spectrum models using both Landsat 8 (OLI) and Landsat 9 (OLI2). The study was further extended down to 10 nm resolution and a wavelength range from Ultraviolet A (UVA) to shortwave infrared (SWIR) (370–2480 nm) using inversion of field irradiance measurements. The results using OLI and OLI2 as well as the inversion of irradiance measurements were that the more recent Chance and Kurucz (SA2010), Meftah (SOLAR-ISS) and Coddington (TSIS-1) models performed better than all of the previous models. The results were illustrated by simulating dark and bright surface reflectance signatures obtained by atmospheric correction with the different solar spectrum models. The results showed that if the SA2010 model is assumed to be the “true” solar irradiance, using the TSIS-1 or the SOLAR-ISS model will not significantly change the estimated ground reflectance. The other models differ (some to a large extent) in varying wavelength areas.

A synthesis of the first-in-class pan-serotype dengue virus inhibitor NITD-688 is presented. The Gewald reaction of N -(tert -butoxycarbonyl)-6,6-dimethylpiperidin-3-one with malononitrile and sulfur in the presence of l -proline as a catalyst gave tert -butyl 2-amino-3-cyano-6,6-dimethyl-6,7-dihydrothieno[3,2- c ]pyridine-5(4 H)-carboxylate. This was coupled with [4-(aminosulfonyl)phenyl]acetic acid by using propane-phosphonic acid anhydride. A subsequent reductive alkylation with cyclohexanecarboxaldehyde gave NITD-688. Preliminary results of our attempts to control the regioselectivity of the Gewald synthesis of the 2-amino-3-cyanothiophene core are also presented. [ABSTRACT FROM AUTHOR]

Cardiovascular disease (CVD) is the leading cause of death worldwide, accounting for over one-third of all deaths in Singapore. An analysis of age-standardized mortality rates (ASMR) for CVD in Singapore revealed a deceleration in the initial rapid decline in ASMR. A decrease in smoking prevalence may have contributed to the initial rapid decline in ASMR. Furthermore, other major risk factors, such as diabetes mellitus, hypertension, elevated low-density lipoprotein levels, and obesity, are steadily rising. Singapore's CVD economic burden is estimated to be 8.1 billion USD (11.5 billion SGD). The burden of CVD can only be reduced using individual and population-based approaches. Prevention programs must also be developed based on an understanding of risk trends. Therefore, this article attempts to capture the burden of CVD, trends in risk factor control, preventive care, disparities, and current unmet needs, particularly in atherosclerotic cardiovascular disease management in Singapore., Competing Interests: OS is an employee of Novartis (Singapore) Pte Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (© 2024 Sia, Simon, Loh and Poh.)

Background: Elevated lipoprotein(a) [Lp(a)] is a common hyperlipidaemic condition with strong genetic predisposition and is independently associated with ischaemic heart disease (IHD). A Mendelian randomisation study has suggested that elevated Lp(a) is likely to confer similar causal risks as heterozygous familial hypercholesterolemia for premature IHD. We aimed to characterise the clinical profiles of admitted patients with IHD with at least one Lp(a) measurement. We also investigated whether elevated Lp(a) concentration was associated with premature onset of IHD., Methods: This is a descriptive, non-interventional, retrospective study with data from a single tertiary hospital IHD Lp(a) cohort in Singapore, which consecutively recruited 521 patients with IHD admitted to the hospital., Results: A total of 82.2% were men, 46.6% had newly diagnosed IHD and 10% had premature IHD. The median Lp(a) levels was 35.2 nmol/L. 70.8% of patients had normal Lp(a) concentrations (<70 nmol/L), 13.4% of people with Lp(a) ⩾ 70 to <120 nmol/L and 15.7% of patients with Lp(a) ⩾ 120 nmol/L. Lp(a) distribution was positively skewed to the right for all ethnicities. Patients of Indian ethnicity and of female gender had higher levels of Lp(a) compared with other ethnicities and gender, respectively. Multivariable regression analysis identified Lp(a) ⩾ 155 mmol/L to be associated with development of premature IHD (OR = 2.90, 95% CI: 1.26-6.67, p  = 0.012)., Conclusion: There exist differences in Lp(a) distribution across ethnicities and gender. The subgroup analysis suggests that Lp(a) ⩾ 155 mmol/L was associated with premature onset of IHD.