Determination of total potentially available nucleosides in bovine milk

Bovine colostrum and milk samples were collected from two herds over the course of the first month post-partum, pooled for each herd by stage of lactation and total potentially available nucleosides were determined. Sample analysis consisted of parallel enzymatic treatments, phenylboronate clean-up, and liquid chromatography to quantify contributions of nucleosides, monomeric nucleotides, nucleotide adducts, and polymeric nucleotides to the available nucleosides pool. Bovine colostrum contained high levels of nucleosides and monomeric nucleotides, which rapidly decreased as lactation progressed into transitional milk. Mature milk was relatively consistent in nucleoside and monomeric nucleotide concentrations from approximately the tenth day post-partum. Differences in concentrations between summer-milk and winter-milk herds were largely attributable to variability in uridine and monomeric nucleotide concentrations

Cross-Sender Bit-Mixing Coding

Scheduling to avoid packet collisions is a long-standing challenge in networking, and has become even trickier in wireless networks with multiple senders and multiple receivers. In fact, researchers have proved that even {\em perfect} scheduling can only achieve $\mathbf{R} = O(\frac{1}{\ln N})$. Here $N$ is the number of nodes in the network, and $\mathbf{R}$ is the {\em medium utilization rate}. Ideally, one would hope to achieve $\mathbf{R} = \Theta(1)$, while avoiding all the complexities in scheduling. To this end, this paper proposes {\em cross-sender bit-mixing coding} ({\em BMC}), which does not rely on scheduling. Instead, users transmit simultaneously on suitably-chosen slots, and the amount of overlap in different user's slots is controlled via coding. We prove that in all possible network topologies, using BMC enables us to achieve $\mathbf{R}=\Theta(1)$. We also prove that the space and time complexities of BMC encoding/decoding are all low-order polynomials.Comment: Published in the International Conference on Information Processing in Sensor Networks (IPSN), 201

Spectrophotometric Procedure for Fast Reactor Advanced Coolant Manufacture Control

The paper describes a spectrophotometric procedure for fast reactor advanced coolant manufacture control. The molar absorption coefficient of dimethyllead dibromide with dithizone was defined as equal to 68864 ± 795 lmole{-1}cm{-1}, limit of detection as equal to 0.583 10{-6} g/ml. The spectrophotometric procedure application range was found to be equal to 37.88-196.3 g. of dimethyllead dibromide in the sample. The procedure was used within the framework of the development of the method of synthesis of the advanced coolant for fast reactors

Deterministic Sampling and Range Counting in Geometric Data Streams

We present memory-efficient deterministic algorithms for constructing epsilon-nets and epsilon-approximations of streams of geometric data. Unlike probabilistic approaches, these deterministic samples provide guaranteed bounds on their approximation factors. We show how our deterministic samples can be used to answer approximate online iceberg geometric queries on data streams. We use these techniques to approximate several robust statistics of geometric data streams, including Tukey depth, simplicial depth, regression depth, the Thiel-Sen estimator, and the least median of squares. Our algorithms use only a polylogarithmic amount of memory, provided the desired approximation factors are inverse-polylogarithmic. We also include a lower bound for non-iceberg geometric queries.Comment: 12 pages, 1 figur

Magnesium isotopes selection at recrystallization of MgCl2·6H2O

The change of Mg isotope composition at grain-refined zone of MgCl2·6H2O has been studied. It is shown that light isotope 24Mg enrichment occurs on that crystal end to which grain-refined zone is moving. Isotopes 25Mg, 26Mg are concentrated in the initial crystallization zone. Segregation coefficient increases at influence of constant magnetic field or direct electric current on molten zone. The obtained data are compared with the data on magnesium isotope segregation by the other physicochemical method

Spectrophotometric Procedure for Fast Reactor Advanced Coolant Manufacture Control

The paper describes a spectrophotometric procedure for fast reactor advanced coolant manufacture control. The molar absorption coefficient of dimethyllead dibromide with dithizone was defined as equal to 68864 ± 795 lmole{-1}cm{-1}, limit of detection as equal to 0.583 10{-6} g/ml. The spectrophotometric procedure application range was found to be equal to 37.88-196.3 g. of dimethyllead dibromide in the sample. The procedure was used within the framework of the development of the method of synthesis of the advanced coolant for fast reactors

Superselectors: Efficient Constructions and Applications

We introduce a new combinatorial structure: the superselector. We show that superselectors subsume several important combinatorial structures used in the past few years to solve problems in group testing, compressed sensing, multi-channel conflict resolution and data security. We prove close upper and lower bounds on the size of superselectors and we provide efficient algorithms for their constructions. Albeit our bounds are very general, when they are instantiated on the combinatorial structures that are particular cases of superselectors (e.g., (p,k,n)-selectors, (d,\ell)-list-disjunct matrices, MUT_k(r)-families, FUT(k, a)-families, etc.) they match the best known bounds in terms of size of the structures (the relevant parameter in the applications). For appropriate values of parameters, our results also provide the first efficient deterministic algorithms for the construction of such structures

Sparsity without the Complexity: Loss Localisation using Tree Measurements

We study network loss tomography based on observing average loss rates over a set of paths forming a tree -- a severely underdetermined linear problem for the unknown link loss probabilities. We examine in detail the role of sparsity as a regularising principle, pointing out that the problem is technically distinct from others in the compressed sensing literature. While sparsity has been applied in the context of tomography, key questions regarding uniqueness and recovery remain unanswered. Our work exploits the tree structure of path measurements to derive sufficient conditions for sparse solutions to be unique and the condition that $\ell_1$ minimization recovers the true underlying solution. We present a fast single-pass linear algorithm for $\ell_1$ minimization and prove that a minimum $\ell_1$ solution is both unique and sparsest for tree topologies. By considering the placement of lossy links within trees, we show that sparse solutions remain unique more often than is commonly supposed. We prove similar results for a noisy version of the problem

High-Dimensional Similarity Search with Quantum-Assisted Variational Autoencoder

Recent progress in quantum algorithms and hardware indicates the potential importance of quantum computing in the near future. However, finding suitable application areas remains an active area of research. Quantum machine learning is touted as a potential approach to demonstrate quantum advantage within both the gate-model and the adiabatic schemes. For instance, the Quantum-assisted Variational Autoencoder has been proposed as a quantum enhancement to the discrete VAE. We extend on previous work and study the real-world applicability of a QVAE by presenting a proof-of-concept for similarity search in large-scale high-dimensional datasets. While exact and fast similarity search algorithms are available for low dimensional datasets, scaling to high-dimensional data is non-trivial. We show how to construct a space-efficient search index based on the latent space representation of a QVAE. Our experiments show a correlation between the Hamming distance in the embedded space and the Euclidean distance in the original space on the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset. Further, we find real-world speedups compared to linear search and demonstrate memory-efficient scaling to half a billion data points