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Effects of instream wood reintroduction on transport and storage processes in a lowland sandy stream
No full textThe reintroduction of instream wood is a common technique to restore degraded streams, for example to reinstate transport and storage processes - primary controls of the movement of water, solutes, and particulates through the stream corridor - with the aim of initiating a shift towards a more natural or sustainable state. In the United Kingdom, this kind of restoration occurs predominantly in lowland sandy streams, yet to date no study has explicitly investigated its effects on transport and storage processes in such contexts. Here, we used a before-after-control-impact (BACI) experiment to test the effects of reintroducing instream wood on transport and storage processes in a lowland sandy stream under a range of stream discharges (Q), with an average of 0.0079 m3/s. In the restored reach, as compared to the control reach, the average hydraulic retention time increased by 27.6%, the average transient storage increased by 28.4%, and the residence time therein increased by 13%. Although these differences were not statistically significant, we attribute this to the inevitable large variability of field tests compared to controlled laboratory environments. We interpret the observed changes as an indication of a potential increase to transient storage overall but limited subsurface transient storage, especially during higher Q conditions. Overall, our results suggest limited effects of instream wood reintroduction on transport and storage processes in a lowland sandy stream, but also highlight challenges in evidencing such effects. Given the sensitivity of transport and storage processes to environmental setting, it may be challenging to predict the effects of restoration based on a small set of conditions or generalizations
Spatiotemporally resolved GPCR interactome uncovers unique mediators of receptor agonism
No full textCellular signaling by membrane G protein-coupled receptors (GPCRs) is governed by a complex and diverse array of mechanisms. The dynamics of a GPCR interactome, as it evolves over time and space in response to an agonist, provide a unique perspective on pleiotropic signaling decoding and functional selectivity at the cellular level. In this study, we utilized proximity-based APEX2 proteomics to investigate the interaction network of the luteinizing hormone receptor (LHR) on a minute-to-minute timescale. We developed an analytical approach that integrates quantitative multiplexed proteomics with temporal reference profiles, creating a platform to identify the proteomic environment of APEX2-tagged LHR at the nanometer scale. LHR activity is finely regulated spatially, leading to the identification of putative interactors, including the Ras-related GTPase RAP2B, which modulate both receptor signaling and post-endocytic trafficking. This work provides a valuable resource for spatiotemporal nanodomain mapping of LHR interactors across subcellular compartments
In-silico platform for the multifunctional design of 3D printed conductive components
No full textThe effective electric resistivity of conductive thermoplastics manufactured by filament extrusion methods is determined by both the material constituents and the printing parameters. The former determines the multifunctional nature of the composite, whereas the latter dictates the mesostructural characteristics such as filament adhesion and void distribution. This work provides a multi-scale computational framework to evaluate the thermo-electro-mechanical behaviour of printed conductive polymers. A full-field homogenisation model first provides the influence of material and mesostructural features (i.e., filament orientations, voids and adhesion between filaments). Then, a macroscopic continuum model elucidates the effects of thermo-electro-mechanical mixed boundary conditions. The in-silico multi-scale methodology is validated with extensive original multi-physical experiments and a functional application consisting of an electro-heatable printing cartridge. Overall, this work establishes the foundations to virtually break the gap between mesoscopic and macroscopic multifunctional responses in conductive components manufactured by additive manufacturing techniques
Incorporating the acclimation of photosynthesis and leaf respiration in the Noah-MP land surface model: model development and evaluation
No full textRealistic simulation of leaf photosynthetic and respiratory processes is needed for accurate prediction of the global carbon cycle. These two processes systematically acclimate to long-term environmental changes by adjusting photosynthetic and respiratory traits (e.g., the maximum photosynthetic capacity at 25°C (Vcmax,25) and the leaf respiration rate at 25°C (R25)) following increasingly well-understood principles. While some land surface models (LSMs) now account for thermal acclimation, they do so by assigning empirical parameterizations for individual plant functional types (PFTs). Here, we have implemented an Eco-Evolutionary Optimality (EEO)-based scheme to represent the universal acclimation of photosynthesis and leaf respiration to multiple environmental effects, and that therefore requires no PFT-specific parameterizations, in a standard version of the widely used LSM, Noah MP. We evaluated model performance with plant trait data from a 5-year experiment and extensive global field measurements, and carbon flux measurements from FLUXNET2015. We show that observed R25 and Vcmax,25 vary substantially both temporally and spatially within the same PFT (C.V. >20%). Our EEO-based scheme captures 62% of the temporal and 70% of the spatial variations in Vcmax,25 (73% and 54% of the variations in R25). The standard scheme underestimates gross primary production by 10% versus 2% for the EEO-based scheme and generates a larger spread in r (correlation coefficient) across flux sites (0.79 ± 0.16 vs. 0.84 ± 0.1, mean ± S.D.). The standard scheme greatly overestimates canopy respiration (bias: ∼200% vs. 8% for the EEO scheme), resulting in less CO2 uptake by terrestrial ecosystems. Our approach thus simulates climate-carbon coupling more realistically, with fewer parameters
Feasibly constructive proof of Schwartz-Zippel Lemma and the complexity of finding hitting sets
No full textThe Schwartz-Zippel Lemma states that if a low-degree multivariate polynomial with coefficients in a field is not zero everywhere in the field, then it has few roots on
every finite subcube of the field. This fundamental fact about multivariate polynomials has found many applications in algorithms, complexity theory, coding theory, and combinatorics. We give a new proof of the lemma that offers some advantages over the
standard proof.
First, the new proof is more constructive than previously known proofs. For every given side-length of the cube, the proof constructs a polynomial-time computable and
polynomial-time invertible surjection onto the set of roots in the cube. The domain of the surjection is tight, thus showing that the set of roots on the cube can be compressed. Second, the new proof can be formalised in Buss’ bounded arithmetic theory S1/2 for polynomial-time reasoning. One consequence of this is that the theory S1
2+dWPHP(PV) for approximate counting can prove that the problem of verifying polynomial identities (PIT) can be solved by polynomial-size circuits. The same theory can also prove the existence of small hitting sets for any explicitly described class of polynomials of
polynomial degree.
To complete the picture we show that the existence of such hitting sets is equivalent to the surjective weak pigeonhole principle dWPHP(PV), over the theory S1/2. This is a contribution to a line of research studying the reverse mathematics of computational complexity (cf. Chen-Li-Oliveira, FOCS’24). One consequence of this is that the problem of constructing small hitting sets for such classes is complete for the class APEPP of explicit construction problems whose totality follows from the probabilistic method (Kleinberg-Korten-Mitropolsky-Papadimitriou, ITCS’21; cf. Korten, FOCS’21). This class is also known and studied as the class of Range Avoidance Problems (Ren-
Santhanam-Wang, FOCS’22)
The response of carbon uptake to soil moisture stress: adaptation to climatic aridity
No full textThe coupling between carbon uptake and water loss through stomata implies that gross primary production (GPP) can be limited by soil water availability through reduced leaf area and/or stomatal conductance. Ecosystem and land-surface models commonly assume that GPP is highest under well-watered conditions and apply a stress function to reduce GPP as soil moisture declines. Optimality considerations, however, suggest that the stress function should depend on climatic aridity: ecosystems adapted to more arid climates should use water more conservatively when soil moisture is high, but maintain unchanged GPP down to a lower critical soil-moisture threshold. We use eddy-covariance flux data to test this hypothesis. We investigate how the light-use efficiency (LUE) of GPP depends on soil moisture across ecosystems representing a wide range of climatic aridity. ‘Well-watered’ GPP is estimated using the sub-daily P model, a first-principles LUE model driven by atmospheric data and remotely sensed vegetation cover. Breakpoint regression is used to relate daily β(θ) (the ratio of flux data–derived GPP to modelled well-watered GPP) to soil moisture estimated via a generic water balance model. The resulting piecewise function describing β(θ) varies with aridity, as hypothesised. Unstressed LUE, even when soil moisture is high, declines with increasing aridity index (AI). So does the critical soil-moisture threshold. Moreover, for any AI value, there exists a soil moisture level at which β(θ) is maximised. This level declines as AI increases. This behaviour is captured by universal non-linear functions relating both unstressed LUE and the critical soil-moisture threshold to AI. Applying these aridity-based functions to predict the site-level response of LUE to soil moisture substantially improves GPP simulation under both water-stressed and unstressed conditions, suggesting a route towards a robust, universal model representation of the effects of low soil moisture on leaf-level photosynthesis
Lack of harmonisation of greenhouse gases reporting standards and the methane emissions gap
No full textMonitoring companies’ contributions to climate dynamics and their exposure to transition risks requires accurate measurements of their non-carbon dioxide greenhouse gas emissions (non-CO2 GHG). However, carbon accounting standards are not harmonised and allow for some discretion when converting emissions of different GHGs into CO2 equivalent units, the currency in which carbon footprints are expressed. Focusing on methane, we build counterfactual harmonised standards using the latest IPCC Global Warming Potential (GWP) values over 100 years and estimate a cumulative gap in reported methane emissions of 170MtCO2e ( ~6Tg) over a sample of 2864 companies. Changing the counterfactual from GWP100to GWP20, as recently codified in certain jurisdictions and initiatives, increases the cumulative gap to 3300MtCO2e ( ~40Tg). The gap only covers direct emissions and hence understates the extent of potential under-reporting across value chains. Overall, our study underscores the importance of global harmonisation of CO2-equivalence standards to coherently track corporate GHG emissions and their exposure to transition risks
Three-dimensional, multimodal synchrotron data for machine learning applications
No full textMachine learning techniques are being increasingly applied in medical and physical sciences across a variety of imaging modalities; however, an important issue when developing these tools is the availability of good quality training data. Here we present a unique, multimodal synchrotron dataset of a bespoke zinc-doped Zeolite 13X sample that can be used to develop advanced deep learning and data fusion pipelines. Multi-resolution micro X-ray computed tomography was performed on a zinc-doped Zeolite 13X fragment to characterise its pores and features before spatially resolved X-ray diffraction computed tomography was carried out to characterise the topographical distribution of sodium and zinc phases. Zinc absorption was controlled to create a simple, spatially isolated, two-phase material. Both raw and processed data are available as a series of Zenodo entries. Altogether we present a spatially resolved, three-dimensional, multimodal, multi-resolution dataset that can be used to develop machine learning techniques. Such techniques include the development of super-resolution, multimodal data fusion, and 3D reconstruction algorithms
Trends in atherosclerotic heart disease-related mortality among U.S. adults aged 35 and older: a 22-year analysis
No full textBackground:
Atherosclerotic heart disease (ASHD) remains a leading cause of mortality worldwide, especially among older adults. Understanding the long-term mortality trends in ASHD can guide public health strategies and address demographic disparities.
Methods:
Mortality data for individuals aged 35 years and older were extracted from the CDC WONDER database. Age-adjusted mortality rates (AAMR) per 100,000 persons were calculated and stratified by year, gender, race, urbanization, and place of death. The trends were assessed using the annual percent change (APC) and average annual percent change (AAPC) with 95 % confidence intervals (CI) calculated through Joinpoint regression analysis.
Results:
From 1999 to 2020, 7,638,608 ASHD-related deaths were recorded. The overall AAMR declined from 291.08 in 1999 to 170.07 in 2020, with an AAPC of −2.70 % (95 % CI: 2.96 to −2.54). However, an abrupt rise was observed from 2018 to 2020 (APC: 4.55; 95 % CI: 0.77 to 6.75). Males reported higher AAMR than females (Males: 271.9 vs. Females: 151.9). Non-Hispanic (NH) White individuals had the highest AAMR (209.38), followed by NH Black (202.47), NH American Indian (176.12), Hispanic (158.1), and NH Asian (113.7) populations. Nonmetropolitan areas reported the highest AAMR (214.77), while medium metropolitan areas reported the lowest (195.41). The majority of deaths occurred in medical facilities (42.81 %), followed by decedent's homes (25.67 %), and nursing homes (24.79 %).
Conclusion:
Despite a long-term decline in ASHD-related mortality, the recent increase from 2018 to 2020 requires further study. Gender and racial disparities persist, highlighting the need for targeted public health efforts to reduce these inequities
Adrenal steroid hormone responses to exercise under thermal stress: potential role for non classic congenital adrenal hyperplasia in heat illness susceptibility
No full textWe queried whether adrenal insufficiency attributable to non-classic congenital adrenal hyperplasia (21 hydroxylase deficiency, 21OHD) might contribute to heat illness susceptibility. Patients referred to a specialist heat illness clinic (n = 2 with prior hyponatremia; n = 16 lacking documentary evidence) and controls (n = 16) underwent laboratory Heat Tolerance Assessment (HTA: 60–90 min walking, 60% relative intensity, 34°C heat), synthetic adrenocorticotrophic hormone stimulation (heat illness only) and CYP21A2 genotyping (hyponatremic heat illness only). Copeptin, cortisol, 17-hydroxyprogesterone, and 21 deoxycortisol were assayed from blood at baseline and post-HTA, with precursor product [17-hydroxyprogesterone +21 deoxycortisol] expressed relative to cortisol. Saliva and urine were assayed for free cortisol (one hyponatremic case, controls). Versus controls, normonatremic heat illness exhibited greater (p < 0.05) serum cortisol across HTA, while hyponatremic heat illness showed blunted responses in aldosterone and free cortisol (salivary cortisol 1.6 and 1.6 vs. 6.0 [4.2, 19.4] and 4.2 [3.8, 19.2] nmol.L-1; urine cortisol 19 vs. 117 +/− 71 nmol.L-1). Hyponatremic heat illness demonstrated elevated precursor product consistent with 21OHD and multiple CYP21A2 mutations. One normonatremic case of heat illness also showed elevated precursor product. These data support the potential for 21OHD to precipitate heat illness under sustained physical stress and advance a case for targeted genetic screening