Global Estimates Research Articles

Enhanced ocean CO2 uptake due to near-surface temperature gradients

AbstractThe ocean annually absorbs about a quarter of all anthropogenic carbon dioxide (CO2) emissions. Global estimates of air–sea CO2 fluxes are typically based on bulk measurements of CO2 in air and seawater and neglect the effects of vertical temperature gradients near the ocean surface. Theoretical and laboratory observations indicate that these gradients alter air–sea CO2 fluxes, because the air–sea CO2 concentration difference is highly temperature sensitive. However, in situ field evidence supporting their effect is so far lacking. Here we present independent direct air–sea CO2 fluxes alongside indirect bulk fluxes collected along repeat transects in the Atlantic Ocean (50° N to 50° S) in 2018 and 2019. We find that accounting for vertical temperature gradients reduces the difference between direct and indirect fluxes from 0.19 mmol m−2 d−1 to 0.08 mmol m−2 d−1 (N = 148). This implies an increase in the Atlantic CO2 sink of ~0.03 PgC yr−1 (~7% of the Atlantic Ocean sink). These field results validate theoretical, modelling and observational-based efforts, all of which predicted that accounting for near-surface temperature gradients would increase estimates of global ocean CO2 uptake. Accounting for this increased ocean uptake will probably require some revision to how global carbon budgets are quantified.

Tobit Kalman fusion filtering under dynamic event-triggering protocol with token bucket specification

This paper addresses the multi-sensor fusion filtering problem for a class of linear discrete time-varying systems with censored measurement, described by the Tobit model, and scheduled by dynamic event-triggering protocols with token bucket specification. A dynamic event-triggering mechanism is first used to determine whether to transmit measurements under the token bucket specification, allowing transmission only if there are sufficient tokens and if the event-triggering condition is satisfied. Next, two indicator variables are denoted to represent the combined impact of the dynamic event-triggering protocol and the token bucket specification. A local Tobit Kalman filtering algorithm is then designed for each node by minimizing the trace of the filtering error covariance matrix under censoring and information transmission protocols' influence. Subsequently, all local estimates from each node are transmitted to the fusion center, where global estimates are generated using a federal fusion rule. The global estimates with suitable weights are sent back to every node for predictions at subsequent time instants. Finally, an illustrative simulation example is used to evaluate performance of this fused filtering scheme proposed in this paper.

Temporary osteosynthesis of the tibial bones in repair of multiple and combined injuries

Background The incidence of injury worldwide remains high, with a global estimate of 6763 cases per 00,000 population (95 % confidence interval 6412–7147). Trauma to the limbs is a common injury to an individual anatomical area during multiple or combined trauma that accounts for 40 % to 85.2 % of cases. Assessment of the effectiveness of different fixation options and development of treatment algorithms are essential for patients with tibial fractures and multiple (combined) injuries.The objective was to determine how often temporary tibia fixation is applied for patients with multiple and combined injuries.Material and methods The original literature search was conducted on key resources including Scientific Electronic Library (www.elibrary.ru), the National Library of Medicine (www.pubmed.org), CyberLeninka between 2008 and 2023 using search words and phrases: tibial injuries, osteosynthesis of lower limbs, multiple injuries, combined injuries, temporary osteosynthesis of the tibial bones.Results and discussion A differentiated approach to the repair of bone fractures resulting from multiple and combined injuries is mostly common with the choice of fixation technique depending on the severity of injury and the severity of the patient’s condition. The definitive internal bone fixation is normally used for stable patients, “damage control” strategy is secured for borderline and severe cases using primary temporary external fixation followed by staged surgical intervention. There is no generally accepted strategy for the use of early mobilization of long bone fractures as a component of anti-shock measures in a polytrauma patient.Conclusion Certain issues remain unresolved, including the use of osteosynthesis for tibial fractures in some cohorts of patients, the optimal time of transition to definitive internal fixation, the possibility of using extrafocal osteosynthesis as a definitive treatment, the optimal configuration and assemblies to be employed. The lack of high-quality randomized controlled trials in this field is an important limitation.

Importance of aerosol composition and aerosol vertical profiles in global spatial variation in the relationship between PM2.5 and aerosol optical depth

Abstract. Ambient fine particulate matter (PM2.5) is the leading global environmental determinant of mortality. However, large gaps exist in ground-based PM2.5 monitoring. Satellite remote sensing of aerosol optical depth (AOD) offers information to help fill these gaps worldwide when augmented with a modeled PM2.5–AOD relationship. This study aims to understand the spatial pattern and driving factors of this relationship by examining η (PM2.5AOD) using both observations and modeling. A global observational estimate of η for the year 2019 is inferred from 6870 ground-based PM2.5 measurement sites and satellite-retrieved AOD. The global chemical transport model GEOS-Chem, in its high-performance configuration (GCHP), is used to interpret the observed spatial pattern of annual mean η. Measurements and the GCHP simulation consistently identify a global population-weighted mean η value of 96–98 µg m−3, with regional values ranging from 59.8 µg m−3 in North America to more than 190 µg m−3 in Africa. The highest η value is found in arid regions, where aerosols are less hygroscopic due to mineral dust, followed by regions strongly influenced by surface aerosol sources. Relatively low η values are found over regions distant from strong aerosol sources. The spatial correlation of observed η values with meteorological fields, aerosol vertical profiles, and aerosol chemical composition reveals that spatial variation in η is strongly influenced by aerosol composition and aerosol vertical profiles. Sensitivity tests with globally uniform parameters quantify the effects of aerosol composition and aerosol vertical profiles on spatial variability in η, exhibiting a population-weighted mean difference in aerosol composition of 12.3 µg m−3, which reflects the determinant effects of composition on aerosol hygroscopicity and aerosol optical properties, and a population-weighted mean difference in the aerosol vertical profile of 8.4 µg m−3, which reflects spatial variation in the column–surface relationship.

A global mathematical model of climatic suitability for Plasmodium falciparum malaria

Climatic conditions are a key determinant of malaria transmission intensity, through their impacts on both the parasite and its mosquito vectors. Mathematical models relating climatic conditions to malaria transmission can be used to develop spatial maps of climatic suitability for malaria. These maps underpin efforts to quantify the distribution and burden of malaria in humans, enabling improved monitoring and control. Previous work has developed mathematical models and global maps for the suitability of temperature for malaria transmission. In this paper, existing temperature-based models are extended to include two other important bioclimatic factors: humidity and rainfall. This model is combined with fine spatial resolution climatic data to produce a more biologically-realistic global map of climatic suitability for Plasmodium falciparum malaria. The climatic suitability index developed corresponds more closely than previous temperature suitability indices with the global distribution of P. falciparum malaria. There is weak agreement between the Malaria Atlas Project estimates of P. falciparum prevalence in Africa and the estimates of suitability solely based on temperature (Spearman Correlation coefficient of ρ=0.24\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\rho = 0.24$$\\end{document}). The addition of humidity and then rainfall improves the comparison (ρ=0.62\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\rho = 0.62$$\\end{document} when humidity added; ρ=0.70\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\rho =0.70$$\\end{document} when both humidity and rainfall added). By incorporating the impacts of humidity and rainfall, this model identifies arid regions that are not climatically suitable for transmission of P. falciparum malaria. Incorporation of this improved index of climatic suitability into geospatial models can improve global estimates of malaria prevalence and transmission intensity.

Unconditionally superconvergence error analysis of an energy-stable finite element method for Schrödinger equation with cubic nonlinearity

In this paper, the unconditionally superconvergence analysis is studied for the cubic Schrödinger equation with an energy-stable finite element method. A different approach is proposed to obtain the unconditionally superclose error estimate in H1-norm firstly without using the time splitting technique required in the previous literature. The key to the analysis is to use a priori boundedness of the numerical solution in energy norm and control the nonlinear terms rigorously by two cases, i.e., τ≤h2 and τ≥h2, where τ denotes the temporal size and h is the spatial size. Subsequently, the global superconvergence error estimate in H1-norm is derived by an effective interpolation post-processing approach. Finally, some numerical experiments are carried out to confirm the theoretical findings.

Spatiotemporal upscaling of sparse air-sea pCO2 data via physics-informed transfer learning.

Global measurements of ocean pCO2 are critical to monitor and understand changes in the global carbon cycle. However, pCO2 observations remain sparse as they are mostly collected on opportunistic ship tracks. Several approaches, especially based on direct learning, have been used to upscale and extrapolate sparse point data to dense estimates using globally available input features. However, these estimates tend to exhibit spatially heterogeneous performance. As a result, we propose a physics-informed transfer learning workflow to generate dense pCO2 estimates that are grounded in real-world measurements and remainphysically consistent. The models are initially trained on dense input predictors against pCO2 estimates from Earth system model simulation, and then fine-tuned to sparse SOCAT observational data. Compared to the benchmark direct learning approach, our transfer learning framework shows major improvements of up to 56-92%. Furthermore, we demonstrate that using models that explicitly account for spatiotemporal structures in the data yield better validation performances by 50-68%. Our strategy thus presents a new monthly global pCO2 estimate that spans for 35 years between 1982-2017.

Evaluation of ComBat harmonization for reducing across-tracer differences in regional amyloid PET analyses.

Introduction Differences in amyloid positron emission tomography (PET) radiotracer pharmacokinetics and binding properties lead to discrepancies in amyloid-β uptake estimates. Harmonization of tracer-specific biases is crucial for optimal performance of downstream tasks. Here, we investigated the efficacy of ComBat, a data-driven harmonization model, for reducing tracer-specific biases in regional amyloid PET measurements from [18F]-florbetapir (FBP) and [11C]-Pittsburgh Compound-B (PiB). Methods One-hundred-thirteen head-to-head FBP-PiB scan pairs, scanned from the same subject within ninety days, were selected from the Open Access Series of Imaging Studies 3 (OASIS-3) dataset. The Centiloid scale, ComBat with no covariates, ComBat with biological covariates, and GAM-ComBat with biological covariates were used to harmonize both global and regional amyloid standardized uptake value ratios (SUVR). Variants of ComBat, including longitudinal ComBat and PEACE, were also tested. Intraclass correlation coefficient (ICC) and mean absolute error (MAE) were computed to measure the absolute agreement between tracers. Additionally, longitudinal amyloid SUVRs from an anti-amyloid drug trial were simulated using linear mixed effects modeling. Differences in rates-of-change between simulated treatment and placebo groups were tested, and change in statistical power/Type-I error after harmonization was quantified. Results In the head-to-head tracer comparison, ComBat with no covariates was the best at increasing ICC and decreasing MAE of both global summary and regional amyloid PET SUVRs between scan pairs of the same group of subjects. In the clinical trial simulation, harmonization with both Centiloid and ComBat increased statistical power of detecting true rate-of-change differences between groups and decreased false discovery rate in the absence of a treatment effect. The greatest benefit of harmonization was observed when groups exhibited differing FBP-to-PiB proportions. Conclusion ComBat outperformed the Centiloid scale in harmonizing both global and regional amyloid estimates. Additionally, ComBat improved the detection of rate-of-change differences between clinical trial groups. Our findings suggest that ComBat is a viable alternative to Centiloid for harmonizing regional amyloid PET analyses.

Critical needs to close monitoring gaps in pan-tropical wetland CH4 emissions

Abstract Global wetlands are the largest and most uncertain natural source of atmospheric methane (CH4). The FLUXNET-CH4 synthesis initiative has established a global network of flux tower infrastructure, offering valuable data products and fostering a dedicated community for the measurement and analysis of methane flux data. Existing studies using the FLUXNET-CH4 Community Product v1.0 have provided invaluable insights into the drivers of ecosystem-to-regional spatial patterns and daily-to-decadal temporal dynamics in temperate, boreal, and Arctic climate regions. However, as the wetland CH4 monitoring network grows, there is a critical knowledge gap about where new monitoring infrastructure ought to be located to improve understanding of the global wetland CH4 budget. Here we address this gap with a spatial representativeness analysis at existing and hypothetical observation sites, using 16 process-based wetland biogeochemistry models and machine learning. We find that, in addition to eddy covariance monitoring sites, existing chamber sites are important complements, especially over high latitudes and the tropics. Furthermore, expanding the current monitoring network for wetland CH4 emissions should prioritize, first, tropical and second, sub-tropical semi-arid wetland regions. Considering those new hypothetical wetland sites from tropical and semi-arid climate zones could significantly improve global estimates of wetland CH4 emissions and reduce bias by 79% (from 76 to 16 TgCH4 y−1), compared with using solely existing monitoring networks. Our study thus demonstrates an approach for long-term strategic expansion of flux observations.

A comprehensive review of soil organic carbon estimates: Integrating remote sensing and machine learning technologies

Abstract Purpose Accurately assessing soil organic carbon (SOC) content is vital for ecosystem services management and addressing global climate challenges. This study undertakes a comprehensive bibliometric analysis of global estimates for SOC using remote sensing (RS) and machine learning (ML) techniques. It showcases the historical growth and thematic evolution in SOC research, aiming to amplify the understanding of SOC estimation themes and provide scientific support for climate change adaptation and mitigation. Materials and Methods Employing extensive literature database analysis, bibliometric network analysis, and clustering techniques, the study reviews 1,761 articles on SOC estimation using RS technologies and 490 articles on SOC employing both RS and ML technologies. Results and Discussion The results indicate that satellite-based RS, particularly the Landsat series, is predominant for estimation of SOC and other associated studies, with North America, China, and Europe leading in evaluations with Africa is having low evaluations adopting RS technology. Trends in the research demonstrate an evolution from basic mapping to advanced topics such as carbon (C) sequestration, complex modeling, and big data utilization. Thematic clusters from co-occurrence analysis suggest the interplay between technology development, environmental surveys, soil properties, and climate dynamics. Conclusion The study highlights the synergy between RS and ML, with advanced ML techniques proving to be critical for accurate SOC estimation. These findings are crucial for comprehensive ecosystem SOC estimation, informed environmental management and strategic decision-making.

Sharp Trace and Korn Inequalities for Differential Operators

AbstractWe establish sharp trace and Korn-type inequalities that involve vectorial differential operators, the focus being on situations where global singular integral estimates are not available. Starting from a novel approach to sharp Besov boundary traces by Riesz potentials and oscillations that equally applies to $$p=1$$ p = 1 , a case difficult to be handled by harmonic analysis techniques, we then classify boundary trace- and Korn-type inequalities. For $$p=1$$ p = 1 and so despite the failure of the Calderón-Zygmund theory, we prove that sharp trace estimates can be systematically reduced to full k-th order gradient estimates. Moreover, for $$1<p<\infty $$ 1 < p < ∞ , where sharp trace estimates yield Korn-type inequalities on smooth domains, we show for the basically optimal class of John domains that Korn-type inequalities persist – even though the reduction to global Calderón-Zygmund estimates by extension operators might not be possible.

Salubrious effects of proanthocyanidins on behavioral phenotypes and DNA repair deficiency in the BTBR mouse model of autism

Autism is a neurodevelopmental disorder distinguished by impaired social interaction and repetitive behaviors. Global estimates indicate that autism affects approximately 1.6% of children, with the condition progressively becoming more prevalent over time. Despite noteworthy progress in autism research, the condition remains untreatable. This serves as a driving force for scientists to explore new approaches to disease management. Autism is linked to elevated levels of oxidative stress and disturbances in the DNA repair mechanism, which may potentially play a role in its comorbidities development. The current investigation aimed to evaluate the beneficial effect of the naturally occurring flavonoid proanthocyanidins on the behavioral characteristics and repair efficacy of autistic BTBR mice. Moreover, the mechanisms responsible for these effects were clarified. The present findings indicate that repeated administration of proanthocyanidins effectively reduces altered behavior in BTBR animals without altering motor function. Proanthocyanidins decreased oxidative DNA strand breaks and accelerated the rate of DNA repair in autistic animals, as evaluated by the modified comet test. In addition, proanthocyanidins reduced the elevated oxidative stress and recovered the disrupted DNA repair mechanism in the autistic animals by decreasing the expressions of Gadd45a and Parp1 levels and enhancing the expressions of Ogg1, P53, and Xrcc1 genes. This indicates that proanthocyanidins have significant potential as a new therapeutic strategy for alleviating autistic features.

Prevalence of thyroid dysfunction among pregnant women in the horn of Africa: A systematic review and Meta-analysis

BackgroundThyroid dysfunction ranks among the most prevalent endocrine disorders. This disorder during pregnancy has been linked to adverse effects on both the mother and the baby. However, there is a scarcity of data and inconsistent documentation regarding thyroid issues in pregnant women in low-income nations. ObjectiveThe aim of this systematic review and meta-analysis was to determine the general prevalence of thyroid disorders in pregnant women. MethodsTo identify relevant studies, a comprehensive search was conducted across Scopus, PubMed, Science Direct databases, and Google Scholar and repository registers from January 1, 2000 to December 31, 2023. Ten pertinent publications were chosen for the final meta-analysis. Relevant data was extracted using Microsoft Excel and analyzed using STATA software version 17, employing a random-effect model. Sensitivity analysis was conducted to evaluate each study's impact on the outcome, and Egger's test was utilized to detect publication bias. A trim-and-fill analysis was executed to adjust for bias in the effect estimate. Heterogeneity across studies was assessed using Cochran's Q statistic and I2 statistics. Subgroup analysis was carried by study design, country and publication year. ResultsIn this systematic review and meta-analysis, the prevalence of thyroid dysfunction among 2538 pregnant women was 12.0 % (95 % CI: 8.00 %–17.00 %). To account for the significant heterogeneity observed, a random effect model was utilized. Specifically, the prevalence of hypothyroidism in pregnant women was determined to be 10.00 % (95 % CI: 4.00–16.00 %) with a high level of heterogeneity (I2 = 94.27 %, p < 0.001). Notably, the sensitivity analysis conducted did not reveal any substantial impact on the overall pooled prevalence of thyroid dysfunction. ConclusionThe meta-analysis revealed a significantly higher rate of thyroid disorders among pregnant women compared to global estimates. To assess the effects of treating thyroid conditions on pregnancy outcomes and inform clinical decisions, it is recommended to implement cost-effective thyroid-stimulating hormone screening during pregnancy.

Global Estimates of Particulate Organic Carbon Concentration From the Surface Ocean to the Base of the Mesopelagic

AbstractThe gravitational settling of organic particles from the surface to the deep ocean is an important export pathway and one of the largest components of the ocean carbon pump. The strength and efficiency of the gravitational pump are often measured using metrics reliant on reference depths and empirical formulations that parameterize the relationship between depth and the flux or concentration of particulate organic carbon (POC). Here, BGC‐Argo profiles were used to identify the isolume where POC concentration, [POC], starts to decline, revealing attenuation trends below this isolume that are remarkably consistent across the global ocean. We developed a simple empirical approach that uses observations from the first optical depth to predict [POC] from the surface ocean to the base of the mesopelagic (1,000 m), allowing assessments of spatial and temporal variability in gravitational pump efficiencies. We find that rates of [POC] attenuation are high in areas of high biomass and low in areas of low biomass, supporting the view that bloom events sometimes result in a relatively weak deep biological pump that is characterized by low transfer efficiency to the base of the mesopelagic. Our isolume‐based attenuation model was applied to satellite data to yield the first remote sensing‐based estimate of integrated global POC stock of 3.02 Pg C over the top 1,000 m, with an uncertainty of 0.69 Pg C. Of this total stock, approximately 1.02 Pg was located above the reference isolume where [POC] begins to attenuate.

The ALMA-CRISTAL survey: Dust temperature and physical conditions of the interstellar medium in a typical galaxy at z=5.66

We present new $ rest =77$ mu m dust continuum observations from the Atacama Large Millimeter/submillimeter Array of HZ10 (CRISTAL-22). This dusty main sequence galaxy at $z$=5.66 was observed as part of the Resolved Ism in STar-forming Alma Large program (CRISTAL). The high angular resolution of the ALMA Band 7 and new Band 9 data ($ ''.4$) reveals the complex structure of HZ10, which comprises two main components (HZ10-C and HZ10-W), along with a bridge-like dusty emission between them (i.e., "the bridge"). Using a modified blackbody function to model the dust spectral energy distribution (SED), we constrained the physical conditions of the interstellar medium (ISM) and its variations among the different components identified in HZ10. We find that HZ10-W (the more UV-obscured component) has an SED dust temperature of $T_ SED $sim 51.2$ K; this was found to be sim 5 K higher (which is statistically insignificant; i.e., less than 1sigma ) than that of the central component and previous global estimations for HZ10. Our new ALMA data allow us to reduce the uncertainties of global SED $ measurements by a factor of sim 2.3, compared to previous studies. The HZ10 components have (FIR) luminosity ratios and FIR surface densities values that are consistent with local starburst galaxies. However, HZ10-W shows a lower CII /FIR ratio compared to the other two components (albeit still within the uncertainties), which may suggest a harder radiation field destroying polycyclic aromatic hydrocarbon associated with emission (e.g., active galactic nuclei or young stellar populations). While HZ10-C appears to follow the tight IRX-$ UV $ relation seen in local UV-selected starburst galaxies and high-$z$ star-forming galaxies, we find that both HZ10-W and the bridge depart from this relation and are well described by dust-screen models with holes in front of a hard UV radiation field. This suggests that the UV emission, which is likely coming from young stellar populations, is strongly attenuated in the "dustier" components of the HZ10 system.

Design and performance of the Climate Change Initiative Biomass global retrieval algorithm

The increase in Earth observations from space in recent years supports improved quantification of carbon storage by terrestrial vegetation and fosters studies that relate satellite measurements to biomass retrieval algorithms. However, satellite observations are only indirectly related to the carbon stored by vegetation. While ground surveys provide biomass stock measurements to act as reference for training the models, they are sparsely distributed. Here, we addressed this problem by designing an algorithm that harnesses the interplay of satellite observations, modeling frameworks and field measurements, and generated global estimates of above-ground biomass (AGB) density that meet the requirements of the scientific community in terms of accuracy, spatial and temporal resolution. The design was adapted to the amount, type and spatial distribution of satellite data available around the year 2020. The retrieval algorithm estimated AGB annually by merging estimates derived from C- and L-band Synthetic Aperture Radar (SAR) backscatter observations with a Water Cloud type of model and does not rely on AGB reference data at the same spatial scale as the SAR data. This model is integrated with functions relating to forest structural variables that were trained on spaceborne LiDAR observations and sub-national AGB statistics. The yearly estimates of AGB were successively harmonized using a cost function that minimizes spurious fluctuations arising from the moderate-to-weak sensitivity of the SAR backscatter to AGB. The spatial distribution of the AGB estimates was correctly reproduced when the retrieval model was correctly set. Over-predictions occasionally occurred in the low AGB range (<50 Mg ha−1) and under-predictions in the high AGB range (>300 Mg ha−1). These errors were a consequence of sometimes too strong generalizations made within the modeling framework to allow reliable retrieval worldwide at the expense of accuracy. The precision of the estimates was mostly between 30% and 80% relative to the estimated value. While the framework is well founded, it could be improved by incorporating additional satellite observations that capture structural properties of vegetation (e.g., from SAR interferometry, low-frequency SAR, or high-resolution observations), a dense network of regularly monitored high-quality forest biomass reference sites, and spatially more detailed characterization of all model parameters estimates to better reflect regional differences.

Global and regional estimates of hip fracture burden associated with type 1 diabetes from 1990 to 2021.

To assess the global and regional burden of hip fractures associated with type 1 diabetes (T1D) from 1990 to 2021. The population attributable fraction was calculated by combining the published risk ratio with T1D prevalence (age ≥ 20 years) from the Global Burden of Disease study to estimate the T1D-associated hip-fracture burden. Trends were assessed using the age-standardized incidence rate (ASIR) and estimated annual percentage change (EAPC). The global incidence of T1D-related hip fractures was 290 180 in 2021 with an ASIR of 3.96 (95% confidence interval: 1.92-5.87) per 100 000 population and a male-to-female ratio of 0.54. At the super-regional level, the highest incidence (204 610) and ASIR (13.09 per 100 000 population; 6.40-25.53) were observed in high-income regions, in particular in Australasia and Western Europe. Notably, Australasia exhibited the highest EAPC, 2.90% in T1D-associated ASIR, followed by East Asia (2.73%). The incidence among those aged 45-64 years grew significantly in 14 regions over the past decade. Nationally, the ASIR increased in 166 countries from 1990 to 2021. High-income regions experienced the greatest burden of T1D-associated hip fracture, while Australasia and East Asia witnessed the largest increase over the last 32 years. Prioritizing the promotion of T1D treatment and hip-fracture screening for middle-aged females living with T1D is crucial in these regions.

Stabilizing effect of the magnetic field and decay estimates for the 3D MHD equations with only one direction dissipation

This paper focuses on the stability and decay estimates of the 3D MHD equations with only one direction dissipation near a background magnetic field. The global stability and decay estimates of the 3D Navier-Stokes equations with only one direction dissipation remain an outstanding open problem. However, when coupled with the magnetic field in the MHD system involved here, the velocity field is shown to stabilize and decay in time. This result reveals that the magnetic field stabilizes and damps the electrically conducting fluids. By utilizing time-weighted methods and the method of bootstrapping argument, we establish that any perturbation near a magnetic field is globally stable in H3(R3). Furthermore, explicit decay rates in H2(R3) are obtained.

Tiered maize and wheat nutrient removal coefficients estimated from available data

AbstractEstimates of cropland nutrient budgets at national to global scale generally rely on regional or global mean coefficients for quantifying nutrients removed in crop yield and by-products. Use of such mean values masks the variability in these coefficients. Using maize and wheat as examples, we assessed variation in nutrient removal coefficients, namely harvest index (HI), nitrogen (N), phosphorus (P) and potassium (K) concentrations of crop products (Grain N, Grain P and Grain K respectively) and N, P and K concentrations of crop residues (Residue N, Residue P, and Residue K respectively). Variation in these coefficients was assessed by three categories (Tiers) of estimation. Statistical (mixed-effects) and machine learning (random forest regression) models (Tier 3) were used to predict the coefficients using generally available predictor variables at a global level. Mean prediction accuracies (R2) of the mixed-effects and random forest models were 0.32 for maize coefficients and 0.45 for wheat coefficients when based on a random sub-selection of mainly replicated field experiment data. When predictions were applied to on-farm data only, prediction accuracies were lower (mean R2 values of 0.08 and 0.36 for maize and wheat respectively). Variation in, and dearth of on-farm data for the coefficients contributed to these poor prediction accuracies. Until the limitations of on-farm data are overcome, it is recommended to use Tier 2 (regional) coefficient estimates in country and global cropland nutrient balance and nutrient use efficiency estimates. Where Tier 2 values are not available, then global average (Tier 1) coefficients can be used.

Flow-weighted sourcing of freshwater runoff from Pacific-draining continental and coastal basins in south-western Patagonia (41-56° S): characterizing regional inputs to Chilean fjords

Global estimates of the supply of dissolved and suspended materials to the ocean, in order to be relevant at either political or ecological scales, belie a finer-scale analysis necessary for understanding specific terrestrial-marine interactions. This is especially true for continental runoff to the marine critical zone of inland fjords and channels, where mechanisms, drivers, and predictions need to be elaborated in the context of changing land use and shifting climate forcing. In fjords in south-western Patagonia, runoff from small coastal and large continental basins (~310 x103 km2), sourced from a diverse geography and wide climatic gradient (&amp;lt;150 – 6,000+ mm/year), correspond with a very low density of hydrological and water quality observations. Based on the recently developed regional runoff model (FLOW), we estimated the coastal freshwater discharges and characterized flow-weighted sourcing (land use-cover type, climate, glaciers/geology, and soil province) for Pacific drainages from 41° to 56° south latitude. An estimated 692 km3/year (mean across 1979-2018), or 2% of worldwide total, is more than 85% of previous estimates for the much larger Pacific South American input. Based on limited water quality observations and inference from runoff sourcing, we predict general patterns of export for four groups of continental resources important for marine productivity, including: significant regional variation in flow seasonality, a N-S gradient in declining input of silicic acid and increased glacial input of sediment and iron, and potential shift in dissolved organic matter input sources from rainforest (potentially labile) to peatlands (refractory). Finally, we emphasize the temporal and spatial consequences of near-reference condition river runoff for marine ecosystem productivity and function in the Patagonian fjords, with specific recommendations for water quality standards and sustained monitoring for coupled river and marine ecosystems.