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Crop models are often used to project future crop yield under climate and global change and typically show a broad range of outcomes. To understand differences in modeled responses, we analyzed modeled crop yield response types using impact response surfaces along four drivers of crop yield: carbon dioxide (C), temperature (T), water (W), and nitrogen (N). Crop yield response types help to underst
The two phases of El-Niño-Southern Oscillation (ENSO) influence both regional and global terrestrial vegetation productivity on inter-annual scales. However, the major drivers for the regional vegetation productivity and their controlling strengths during different phases of ENSO remain unclear. We herein disentangled the impacts of two phases of ENSO on regional carbon cycle using multiple data s
European forests have historically served as a major carbon sink and are a crucial part of the LULUCF sector for net-zero planning in many countries. However, national greenhouse gas inventories report that forest sink capacity has declined by one-third over the past decade. This decline has been attributed to be due to multiple interacting factors: climate conditions that now constrain rather th
Recently, a new family of quasi-2D lead-free layered double perovskites in a formula Cs4M(II)M(III)2Cl12 has attracted increasing attention, particularly in the form of colloidal nanocrystals (NCs). Herein, we successfully coordinate Sn(II) at M(II) site in this layered structure while tailoring M(III) site with two types of trivalent cations, eventually forming Cs4SnIn2Cl12 (CTIC) and Cs4SnSb
INTRODUCTION: Migraine aura affects approximately one-third of migraine patients. In some individuals, aura remains highly disabling due to the lack of effective, targeted treatment options. This study evaluates the effectiveness and long-term management of lamotrigine (LTG) in a clinical Cohort specifically burdened by frequent or severe aura.METHODS: A retrospective observational study was condu
Atmospheric inverse modelling is a method for reconstructing historical fluxes of green-house gas between land and atmosphere, using observed atmospheric concentrations and an atmospheric tracer transport model. The small number of observed atmospheric concentrations in relation to the number of unknown flux components makes the inverse problem ill-conditioned, and assumptions on the fluxes are ne
Accurate maps of past land cover and human land-use are necessary when studying the impact of anthropogenic land-cover changes on climate. Ideally the maps of past land cover would be separated into naturally occurring vegetation and human induced changes, allowing us to quantify the effect of human land-use on past climate. Here we investigate the possibility of combining regional, fossil pollen
Bayesian inference under a set of priors, called robust Bayesian analysis, allows for estimation of parameters within a model and quantification of epistemic uncertainty in quantities of interest by bounded (or imprecise) probability. Iterative importance sampling can be used to estimate bounds on the quantity of interest by optimizing over the set of priors. A method for iterative importance samp
Outbreaks, by the European spruce bark beetle (Ips typographus), cause massive ecological and economic damage across Europe. Detecting these attacks early is a significant challenge because ground-truth data of which trees are attacked and when are often scarce or unavailable. This study presents a Conditional Variational Autoencoder (CVAE) designed to detect outbreaks by combining Sentinel-2 time
In this study, we use a data assimilation framework based on the Adaptive Markov Chain Monte Carlo (MCMC) algorithm to constrain process parameters in LPJ-GUESS using CH4 eddy covariance flux observations from 14 different natural boreal and temperate wetlands. The objective is to derive a single set of calibrated parameter values. These parameters are then used in the model to validate its CH4 fl
When assessing past earth surface-climate feedbacks and past human impact on climate, accurate estimates of past land cover are required. Fossil pollen records extracted from lakes and bogs provide good insight into the local land cover around each site. For use in climate modelling these sparse observations have to be interpolated; creating continuous maps of past land cover at regional and sub-c
Machine learning (ML) is increasingly being explored in medicine and healthcare to improve decision-making and predictive capabilities. However, further research is needed to effectively apply ML models to the reliable monitoring of infectious disease outbreaks using multivariate symptom surveillance data. A central component of such monitoring is anomaly detection. To address limitations in curre
The dynamic ecosystem model LPJ-GUESS combines sophisticated plant physiological and biogeochemical processes and has been successfully used in predicting vegetation dynamics at different scales. However, the water cycling is limited to vertical water movement between the atmosphere plant-soil. Thus we have developed an enhanced version of LPJ-GUESS (called LPJ-DH) by coupling water routing and la
Dynamic global vegetation models are a common tool to assess the effect of climate and land use change on vegetation. Though most applications of dynamic global vegetation models use plant functional types, some also simulate species occurrences. While the current development aims to include more processes, e.g. the nitrogen cycle, the models still typically assume an ample seed supply allowing al
Popular Abstract in Swedish Hemolytiskt uremiskt syndrom (HUS) och trombotiskt trombocytopen purpura (TTP) är allvarliga sjukdomar hos barn och vuxna. HUS kännetecknas av mikroangiopatisk hemolytisk anemi (blodbrist med nedbrytning av röda blodkroppar), trombocytopeni (låga blodplättar) och akut njursvikt. Det är den vanligaste orsaken till akut njursvikt hos barn. Typisk HUS utlöses av tarminfektThis study investigated the pathogenesis of hemolytic uremic syndrome (HUS) and thrombotic thrombocytopenic purpura (TTP). (1) The relative roles of lipopolysaccharide and Shiga-like toxin-2 were studied in a mouse model of Escherichia coli O157:H7 infection. Both factors were found to be important for the virulence of the strain and contributed in an additive manner. The mouse model mimicked cert
Diffusion-weighted magnetic resonance imaging (DW-MRI) aims to disentangle multiple biological signal sources in each imaging voxel, enabling the computation of innovative maps of tissue microstructure. DW-MRI model development has been dominated by brain applications. More recently, advanced methods with high fidelity to histology are gaining momentum in other contexts, for example, in oncologica
One of the classical multi-view geometry problems is the so called P3P problem, where the absolute pose of a calibrated camera is determined from three 2D-to-3D correspondences. Since these solvers form a critical component of many vision systems (e.g. in localization and Structure-from-Motion), there have been significant effort in developing faster and more stable algorithms. While the current s
