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This paper reports an approach to interpolate planar laser-induced fluorescence (PLIF) images of CH2O between consecutive experimental data by means of computational imaging realized with convolutional neural network (CNN). Such a deep learning based method can achieve higher temporal resolution for 2D visualization of intermediate species in combustion based on high-speed experimental images. The
Increasing global light pollution1,2 threatens the night-time darkness to which most animals are adapted. Light pollution can have detrimental effects on behavior,3–5 including by disrupting the journeys of migratory birds,5,6 sand hoppers,7–9 and moths.10 This is particularly concerning, since many night-active species rely on compass information in the sky, including the moon,11,12 the skylight
During hematopoietic development, definitive hematopoietic cells are derived from hemogenic endothelial (HE) cells through a process known as endothelial to hematopoietic transition (EHT). During EHT, transitioning cells proliferate and undergo progressive changes in gene expression culminating in the new cell identity with corresponding changes in function, phenotype and morphology. However, the
Nutritional stability – a food system’s capacity to provide sufficient nutrients despite disturbance – is an important, yet challenging to measure outcome of diversified agriculture. Using 55 years of data across 184 countries, we assemble 22,000 bipartite crop-nutrient networks to quantify nutritional stability by simulating crop and nutrient loss in a country, and assess its relationship to crop
Potassium (K) is one of the main and most hazardous trace species released to the gas-phase during thermochemical conversion of biomass. Accurate experimental data and models of K release are needed to better understand the chemistry involved. Tunable diode laser absorption spectroscopy (TDLAS) is used for simultaneous real-time in situ measurements of gas-phase atomic K, water (H2O) and gas tempe
Granitic rocks constitute a global raw material key asset for aggregate production. Their technical performance is, however, highly variable and knowledge on the aggregate functionality of granites in different geological settings is incomplete. This study investigates systematic variations in resistance to fragmentation (Los Angeles value) and wear (Micro-Deval value) for granitic rocks along a 1
Aqueous coordination of cyanide and verification of the composition of the resulting coordination compound is important to ensure confidence in its coordination. Isothiocyanato compounds 1–7 were synthesized employing different synthetic routes and the complex, [Mo2O2(μ-S)2(SCN)5(CH3CN)]3−, 4, was structurally characterized. Ligand exchange reaction of 4 with cyanide forms 8, a cyano complex. Comp
Dopaminergic treatment in combination with rehabilitative training enhances long-term recovery after stroke. However, the underlying mechanisms on structural plasticity are unknown. Here, we show an increased dopaminergic innervation of the ischemic territory during the first week after stroke induced in Wistar rats subjected to transient occlusion of the middle cerebral ar-tery (tMCAO) for 120 mi
Objective: To study the relationship between sociodemographic factors and pyelonephritis. Methods: A nationwide open cohort study consisting of 2,052,873 women (76.2% Swedish-born) aged 15-50 years was conducted (1997-2018). The outcome was the first event of acute uncomplicated pyelonephritis diagnosed in primary healthcare settings in relation to the sociodemographic factors. Cox regression mode
Raytracing is a widespread tool for room acoustic simulations, and one of its main advan-tages is the inclusion of surface scattering. Although surface scattering has been acknowledged as a central aspect of accurate raytracing simulations for many years, there is ongoing research into its effects and how to implement it better. This study evaluates three different algorithms for surface scatterin
The Grassmannian model represents harmonic maps from Riemann surfaces by families of shift-invariant subspaces of a Hilbert space. We impose a natural symmetry condition on the shift-invariant subspaces that corresponds to considering an important class of harmonic maps into symmetric and k-symmetric spaces. Using an appropriate description of such symmetric shift-invariant subspaces we obtain new
Background/Aims. Obesity is a well-established risk factor for the development of numerous chronic diseases. However, there is a small proportion of obese individuals that seem to escape these aforementioned conditions—Metabolically Healthy Obesity (MHO). Our aim was to do a metabolic and biomarker profiling of MHO individuals. Method. Associations between different biomarkers (proteomics, lipidom
The starting point of this paper is to document considerable cross-country variation in the “labor wedge”, a common measure of labor market frictions. Its variation is theoretically isomorphic to differences in a preference-for-leisure parameter. The paper proceeds to investigate what might explain the variation. It presents three separate empirical exercises supportive of the view that, to a subs
Nontypeable Haemophilus influenzae (NTHi) is a Gram-negative human pathogen that causes infections mainly in the upper and lower respiratory tract. The bacterium is associated with bronchitis and exacerbations in patients suffering from chronic obstructive pulmonary disease and frequently causes acute otitis media in preschool children. We have previously demonstrated that the binding of C4b bindi
While Bayesian Optimization (BO) is a very popular method for optimizing expensive black-box functions, it fails to leverage the experience of domain experts. This causes BO to waste function evaluations on bad design choices (e.g., machine learning hyperparameters) that the expert already knows to work poorly. To address this issue, we introduce Bayesian Optimization with a Prior for the Optimum
Having access to realistic and empirically grounded passenger valuations of public transport trip components facilitate the undertaking of necessary trade-offs during planning of transport networks. Discrete choice estimation of path choice preferences is a practical way to obtain such preferences. This paper proposes a new take on the empirical foundation of path choice estimation based on reveal
We give three elementary proofs of a nice equality of definite integrals, recently proven by Ekhad, Zeilberger, and Zudilin. The equality arises in the theory of bivariate hypergeometric functions, and has connections with irrationality proofs in number theory. We furthermore provide a generalization together with an equally elementary proof and discuss some consequences.
