In situ effects of selected preservatives on total carbon, nitrogen and metals collected in sediment traps

The concentration and chemical composition of preservative or poison to use in sediment trap studies continue to present an important unresolved question. Past laboratory/field experiments designed to answer this question are difficult to interpret, because so-called analogs have been used instead of actual trap materials, which are compositionally complex. This paper presents our results on the in situ effects of formalin, azide and mercuric ion on material collected in MULTITRAPS set at 100 and 300 m for a period of six days in a coastal environment, and at 150 m for a period of 20.6 days in an oligotrophic environment. Effective preservative/poison concentrations used were predetermined from laboratory tests. Parameters tested for relative effects included particulate retention of C, N and selected trace metals, and the effects of the various preservatives/poisons introduced via diffusion chambers or free in solution on in situ microbial growth. In addition, the potential contaminating role of large, nonsinking zooplankton (i.e., “swimmers”) was investigated. Substantial differences between treatments were observed. Effects were not uniform, and appeared to be parameter-specific. For example, during the short-term deployment (six days), no significant differences in C flux were observed at 100 m, regardless of preservative used. Traps treated with azide yielded significantly lower N values. At 300 m (short-term deployment), and 150 m (long-term deployment), the azide treatments produced the lowest mean C and N values. Conversely, the formalin traps gave the highest C and N values relative to all treatments at these depths. In terms of metals, \u3e70% of both Cd and Mn were lost to the trap solutions, regardless of oceanic area or time deployed, while most of the Fe tended to remain in the particulate phase. Zinc, largely in association with the particulate phase over the six-day deployment, was lost to the density solution during the 20.6-day deployment, while Pb results were intermediate between these extremes. Results of the diffusion chamber experiment indicate that the formalin and mercuric ion treatments were equally effective regardless of the mode of introduction (i.e., diffusion chamber or free in solution). Azide did not appear as effective when introduced via diffusion

Multilingual assessment of early child development: Analyses from repeated observations of children in Kenya.

In many low- and middle-income countries, young children learn a mother tongue or indigenous language at home before entering the formal education system where they will need to understand and speak a countrys official language(s). Thus, assessments of children before school age, conducted in a nations official language, may not fully reflect a childs development, underscoring the importance of test translation and adaptation. To examine differences in vocabulary development by language of assessment, we adapted and validated instruments to measure developmental outcomes, including expressive and receptive vocabulary. We assessed 505 2-to-6-year-old children in rural communities in Western Kenya with comparable vocabulary tests in three languages: Luo (the local language or mother tongue), Swahili, and English (official languages) at two time points, 5-6 weeks apart, between September 2015 and October 2016. Younger children responded to the expressive vocabulary measure exclusively in Luo (44%-59% of 2-to-4-year-olds) much more frequently than did older children (20%-21% of 5-to-6-year-olds). Baseline receptive vocabulary scores in Luo (β = 0.26, SE = 0.05, p < 0.001) and Swahili (β = 0.10, SE = 0.05, p = 0.032) were strongly associated with receptive vocabulary in English at follow-up, even after controlling for English vocabulary at baseline. Parental Luo literacy at baseline (β = 0.11, SE = 0.05, p = 0.045) was associated with child English vocabulary at follow-up, while parental English literacy at baseline was not. Our findings suggest that multilingual testing is essential to understanding the developmental environment and cognitive growth of multilingual children

A 2k2k-Vertex Kernel for Maximum Internal Spanning Tree

We consider the parameterized version of the maximum internal spanning tree problem, which, given an $n$-vertex graph and a parameter $k$, asks for a spanning tree with at least $k$ internal vertices. Fomin et al. [J. Comput. System Sci., 79:1-6] crafted a very ingenious reduction rule, and showed that a simple application of this rule is sufficient to yield a $3k$-vertex kernel. Here we propose a novel way to use the same reduction rule, resulting in an improved $2k$-vertex kernel. Our algorithm applies first a greedy procedure consisting of a sequence of local exchange operations, which ends with a local-optimal spanning tree, and then uses this special tree to find a reducible structure. As a corollary of our kernel, we obtain a deterministic algorithm for the problem running in time $4^k \cdot n^{O(1)}$

Bioassays to Monitor Taspase1 Function for the Identification of Pharmacogenetic Inhibitors

Background: Threonine Aspartase 1 (Taspase1) mediates cleavage of the mixed lineage leukemia (MLL) protein and leukemia provoking MLL-fusions. In contrast to other proteases, the understanding of Taspase1's (patho)biological relevance and function is limited, since neither small molecule inhibitors nor cell based functional assays for Taspase1 are currently available. Methodology/Findings: Efficient cell-based assays to probe Taspase1 function in vivo are presented here. These are composed of glutathione S-transferase, autofluorescent protein variants, Taspase1 cleavage sites and rational combinations of nuclear import and export signals. The biosensors localize predominantly to the cytoplasm, whereas expression of biologically active Taspase1 but not of inactive Taspase1 mutants or of the protease Caspase3 triggers their proteolytic cleavage and nuclear accumulation. Compared to in vitro assays using recombinant components the in vivo assay was highly efficient. Employing an optimized nuclear translocation algorithm, the triple-color assay could be adapted to a high-throughput microscopy platform (Z'factor = 0.63). Automated high-content data analysis was used to screen a focused compound library, selected by an in silico pharmacophor screening approach, as well as a collection of fungal extracts. Screening identified two compounds, N-[2-[(4-amino-6-oxo-3H-pyrimidin-2-yl)sulfanyl]ethyl]benzenesulfonamideand 2-benzyltriazole-4,5-dicarboxylic acid, which partially inhibited Taspase1 cleavage in living cells. Additionally, the assay was exploited to probe endogenous Taspase1 in solid tumor cell models and to identify an improved consensus sequence for efficient Taspase1 cleavage. This allowed the in silico identification of novel putative Taspase1 targets. Those include the FERM Domain-Containing Protein 4B, the Tyrosine-Protein Phosphatase Zeta, and DNA Polymerase Zeta. Cleavage site recognition and proteolytic processing of these substrates were verified in the context of the biosensor. Conclusions: The assay not only allows to genetically probe Taspase1 structure function in vivo, but is also applicable for high-content screening to identify Taspase1 inhibitors. Such tools will provide novel insights into Taspase1's function and its potential therapeutic relevance

Faster fixed-parameter tractable algorithms for matching and packing problems. In:

Abstract We obtain faster algorithms for problems such as r-dimensional matching and r-set packing when the size k of the solution is considered a parameter. We first establish a general framework for finding and exploiting small problem kernels (of size polynomial in k). This technique lets us combine Alon, Yuster and Zwick's colorcoding technique with dynamic programming to obtain faster fixed-parameter algo- rithms for these problems. Our algorithms run in time O(n + 2 O(k) ), an improvement over previous algorithms for some of these problems running in time O(n + k O(k) ). The flexibility of our approach allows tuning of algorithms to obtain smaller constants in the exponent

Neutron time-of-flight measurements of charged-particle energy loss in inertial confinement fusion plasmas

Neutron spectra from secondary ^{3}H(d,n)α reactions produced by an implosion of a deuterium-gas capsule at the National Ignition Facility have been measured with order-of-magnitude improvements in statistics and resolution over past experiments. These new data and their sensitivity to the energy loss of fast tritons emitted from thermal ^{2}H(d,p)^{3}H reactions enable the first statistically significant investigation of charged-particle stopping via the emitted neutron spectrum. Radiation-hydrodynamic simulations, constrained to match a number of observables from the implosion, were used to predict the neutron spectra while employing two different energy loss models. This analysis represents the first test of stopping models under inertial confinement fusion conditions, covering plasma temperatures of k_{B}T≈1-4  keV and particle densities of n≈(12-2)×10^{24}  cm^{-3}. Under these conditions, we find significant deviations of our data from a theory employing classical collisions whereas the theory including quantum diffraction agrees with our data

Engineered magnetization and exchange stiffness in direct-write Co-Fe nanoelements

Media with engineered magnetization are essential building blocks in superconductivity, magnetism and magnon spintronics. However, the established thin-film and lithographic techniques insufficiently suit the realization of planar components with on-demand-tailored magnetization in the lateral dimension. Here, we demonstrate the engineering of the magnetic properties of CoFe-based nanodisks fabricated by the mask-less technique of focused electron beam induced deposition (FEBID). The material composition in the nanodisks is tuned \emph{in-situ} via the e-beam waiting time in the FEBID process and their post-growth irradiation with Ga ions. The magnetization $M_s$ and exchange stiffness $A$ of the disks are deduced from perpendicular ferromagnetic resonance measurements. The achieved $M_s$ variation in the broad range from $720$ emu/cm$^3$ to $1430$ emu/cm$^3$ continuously bridges the gap between the $M_s$ values of such widely used magnonic materials as permalloy and CoFeB. The presented approach paves a way towards nanoscale 2D and 3D systems with controllable and space-varied magnetic properties.Comment: 5 pages, 4 figure

Experimental Quantum Hamiltonian Learning

Efficiently characterising quantum systems, verifying operations of quantum devices and validating underpinning physical models, are central challenges for the development of quantum technologies and for our continued understanding of foundational physics. Machine-learning enhanced by quantum simulators has been proposed as a route to improve the computational cost of performing these studies. Here we interface two different quantum systems through a classical channel - a silicon-photonics quantum simulator and an electron spin in a diamond nitrogen-vacancy centre - and use the former to learn the latter's Hamiltonian via Bayesian inference. We learn the salient Hamiltonian parameter with an uncertainty of approximately $10^{-5}$. Furthermore, an observed saturation in the learning algorithm suggests deficiencies in the underlying Hamiltonian model, which we exploit to further improve the model itself. We go on to implement an interactive version of the protocol and experimentally show its ability to characterise the operation of the quantum photonic device. This work demonstrates powerful new quantum-enhanced techniques for investigating foundational physical models and characterising quantum technologies