Cookaguirre9236

Overall, this study establishes the groundwork for translatingMEWfrom planar and non-resorbable material substrates to anatomically relevant geometries and regenerative materials that the regenerative medicine field aims to create.Many explosive volcanic eruptions produce underexpanded starting gas-particle jets. The dynamics of the accompanying pyroclast ejection can be affected by several parameters, including magma texture, gas overpressure, erupted volume and geometry. With respect to the latter, volcanic craters and vents are often highly asymmetrical. Here, we experimentally evaluate the effect of vent asymmetry on gas expansion behaviour and gas jet dynamics directly above the vent. The vent geometries chosen for this study are based on field observations. The novel element of the vent geometry investigated herein is an inclined exit plane (5, 15, 30° slant angle) in combination with cylindrical and diverging inner geometries. In a vertical setup, these modifications yield both laterally variable spreading angles as well as a diversion of the jets, where inner geometry (cylindrical/diverging) controls the direction of the inclination. Both the spreading angle and the inclination of the jet are highly sensitive to reservoir (conduit) pressure and slant angle. Increasing starting reservoir pressure and slant angle yield (1) a maximum spreading angle (up to 62°) and (2) a maximum jet inclination for cylindrical vents (up to 13°). Our experiments thus constrain geometric contributions to the mechanisms controlling eruption jet dynamics with implications for the generation of asymmetrical distributions of proximal hazards around volcanic vents.A nonlinear flag is a finite sequence of nested closed submanifolds. We study the geometry of Fréchet manifolds of nonlinear flags, in this way generalizing the nonlinear Grassmannians. As an application, we describe a class of coadjoint orbits of the group of Hamiltonian diffeomorphisms that consist of nested symplectic submanifolds, i.e., symplectic nonlinear flags.Human preverbal development refers to the period of steadily increasing vocal capacities until the emergence of a child's first meaningful words. Over the last decades, research has intensively focused on preverbal behavior in typical development. Preverbal vocal patterns have been phonetically classified and acoustically characterized. More recently, specific preverbal phenomena were discussed to play a role as early indicators of atypical development. Recent advancements in audio signal processing and machine learning have allowed for novel approaches in preverbal behavior analysis including automatic vocalization-based differentiation of typically and atypically developing individuals. In this paper, we give a methodological overview of current strategies for collecting and acoustically representing preverbal data for intelligent audio analysis paradigms. Efficiency in the context of data collection and data representation is discussed. Following current research trends, we set a special focus on challenges that arise when dealing with preverbal data of individuals with late detected developmental disorders, such as autism spectrum disorder or Rett syndrome.We derandomize Valiant's (J ACM 62, Article 13, 2015) subquadratic-time algorithm for finding outlier correlations in binary data. This demonstrates that it is possible to perform a deterministic subquadratic-time similarity join of high dimensionality. Our derandomized algorithm gives deterministic subquadratic scaling essentially for the same parameter range as Valiant's randomized algorithm, but the precise constants we save over quadratic scaling are more modest. Our main technical tool for derandomization is an explicit family of correlation amplifiers built via a family of zigzag-product expanders by Reingold et al. (Ann Math 155(1)157-187, 2002). We say that a function f - 1 , 1 d → - 1 , 1 D is a correlation amplifier with threshold 0 ≤ τ ≤ 1 , error γ ≥ 1 , and strength p an even positive integer if for all pairs of vectors x , y ∈ - 1 , 1 d it holds that (i) | ⟨ x , y ⟩ | less then τ d implies | ⟨ f ( x ) , f ( y ) ⟩ | ≤ ( τ γ ) p D ; and (ii) | ⟨ x , y ⟩ | ≥ τ d implies ⟨ x , y ⟩ γ d p D ≤ ⟨ f ( x ) , f ( y ) ⟩ ≤ γ ⟨ x , y ⟩ d p D .The era of big data has witnessed an increasing availability of multiple data sources for statistical analyses. We consider estimation of causal effects combining big main data with unmeasured confounders and smaller validation data with supplementary information on these confounders. Under the unconfoundedness assumption with completely observed confounders, the smaller validation data allow for constructing consistent estimators for causal effects, but the big main data can only give error-prone estimators in general. However, by leveraging the information in the big main data in a principled way, we can improve the estimation efficiencies yet preserve the consistencies of the initial estimators based solely on the validation data. check details Our framework applies to asymptotically normal estimators, including the commonly used regression imputation, weighting, and matching estimators, and does not require a correct specification of the model relating the unmeasured confounders to the observed variables. We also propose appropriate bootstrap procedures, which makes our method straightforward to implement using software routines for existing estimators. Supplementary materials for this article are available online.Clean water is a precious resource, and policies/programmes are implemented worldwide to protect and/or improve water quality. Faecal pollution can be a key contributor to water quality decline causing eutrophication through nutrient enrichment and pathogenic contamination. The robust sourcing of faecal pollutants is important to be able to target the appropriate sector and to engage managers. Biomarker technology has the potential for source confirmation, by using, for example the biomarker suite of steroids. Steroids have been used in the differentiation of human and animal faeces; however, there is no unequivocal extraction technique. Some of the methods used include (i) Soxhlet extraction, (ii) Bligh and Dyer (BD) extraction, and (iii) accelerated solvent extraction (ASE). The less costly and time intensive technique of ASE is particularly attractive, but a current research gap concerns further comparisons regarding ASE lipid extraction from soils/slurries compared with the more traditional Soxhlet and BD extractions.