Why is the condensed phase of DNA preferred at higher temperature? DNA compaction in the presence of a multivalent cation

Upon the addition of multivalent cations, a giant DNA chain exhibits a large discrete transition from an elongated coil into a folded compact state. We performed single-chain observation of long DNAs in the presence of a tetravalent cation (spermine), at various temperatures and monovalent salt concentrations. We confirmed that the compact state is preferred at higher temperatures and at lower monovalent salt concentrations. This result is interpreted in terms of an increase in the net translational entropy of small ions due to ionic exchange between higher and lower valence ions.Comment: 4pages,3figure

Photon collection from a trapped ion--cavity system

We present the design and implementation of a trapped ion cavity QED system. A single ytterbium ion is confined by a micron-scale ion trap inside a 2 mm optical cavity. The ion is coherently pumped by near resonant laser light while the cavity output is monitored as a function of pump intensity and cavity detuning. We observe a Purcell enhancement of scattered light into the solid angle subtended by the optical cavity, as well as a three-peak structure arising from strongly driving the atom. This system can be integrated into existing atom{photon quantum network protocols and is a pathway towards an efficient atom{photon quantum interface

Fabrication Infrastructure to Enable Efficient Exploration and Utilization of Space

Unlike past one-at-a-time mission approaches, system-of-systems infrastructures will be needed to enable ambitious scenarios for sustainable future space exploration and utilization. Fabrication infrastructure will be needed to support habitat structure development, tools and mechanical part fabrication, as well as repair and replacement of ground support and space mission hardware such as life support items, vehicle components and crew systems. The fabrication infrastructure will need the In Situ Fabrication and Repair (ISFR) element, which is working in conjunction with the In Situ Resources Utilization (ISRU) element, to live off the land. The ISFR Element supports the entire life cycle of Exploration by: reducing downtime due to failed components; decreasing risk to crew by recovering quickly from degraded operation of equipment; improving system functionality with advanced geometry capabilities; and enhancing mission safety by reducing assembly part counts of original designs where possible. This paper addresses the fabrication infrastructures that support efficient, affordable, reliable infrastructures for both space exploration systems and logistics; these infrastructures allow sustained, affordable and highly effective operations on the Moon, Mars and beyond

Adiabatic quantum algorithm for search engine ranking

We propose an adiabatic quantum algorithm for generating a quantum pure state encoding of the PageRank vector, the most widely used tool in ranking the relative importance of internet pages. We present extensive numerical simulations which provide evidence that this algorithm can prepare the quantum PageRank state in a time which, on average, scales polylogarithmically in the number of webpages. We argue that the main topological feature of the underlying web graph allowing for such a scaling is the out-degree distribution. The top ranked $\log(n)$ entries of the quantum PageRank state can then be estimated with a polynomial quantum speedup. Moreover, the quantum PageRank state can be used in "q-sampling" protocols for testing properties of distributions, which require exponentially fewer measurements than all classical schemes designed for the same task. This can be used to decide whether to run a classical update of the PageRank.Comment: 7 pages, 5 figures; closer to published versio

Smooth-AP: Smoothing the Path Towards Large-Scale Image Retrieval

Optimising a ranking-based metric, such as Average Precision (AP), is notoriously challenging due to the fact that it is non-differentiable, and hence cannot be optimised directly using gradient-descent methods. To this end, we introduce an objective that optimises instead a smoothed approximation of AP, coined Smooth-AP. Smooth-AP is a plug-and-play objective function that allows for end-to-end training of deep networks with a simple and elegant implementation. We also present an analysis for why directly optimising the ranking based metric of AP offers benefits over other deep metric learning losses. We apply Smooth-AP to standard retrieval benchmarks: Stanford Online products and VehicleID, and also evaluate on larger-scale datasets: INaturalist for fine-grained category retrieval, and VGGFace2 and IJB-C for face retrieval. In all cases, we improve the performance over the state-of-the-art, especially for larger-scale datasets, thus demonstrating the effectiveness and scalability of Smooth-AP to real-world scenarios.Comment: Accepted at ECCV 202

24^{24}Mg(pp, α\alpha)21^{21}Na reaction study for spectroscopy of 21^{21}Na

The $^{24}$Mg($p$, $\alpha$)$^{21}$Na reaction was measured at the Holifield Radioactive Ion Beam Facility at Oak Ridge National Laboratory in order to better constrain spins and parities of energy levels in $^{21}$Na for the astrophysically important $^{17}$F($\alpha, p$)$^{20}$Ne reaction rate calculation. 31 MeV proton beams from the 25-MV tandem accelerator and enriched $^{24}$Mg solid targets were used. Recoiling $^{4}$He particles from the $^{24}$Mg($p$, $\alpha$)$^{21}$Na reaction were detected by a highly segmented silicon detector array which measured the yields of $^{4}$He particles over a range of angles simultaneously. A new level at 6661 $\pm$ 5 keV was observed in the present work. The extracted angular distributions for the first four levels of $^{21}$Na and Distorted Wave Born Approximation (DWBA) calculations were compared to verify and extract angular momentum transfer.Comment: 11 pages, 6 figures, proceedings of the 18th International Conference on Accelerators and Beam Utilization (ICABU2014

Classification of protein interaction sentences via gaussian processes

The increase in the availability of protein interaction studies in textual format coupled with the demand for easier access to the key results has lead to a need for text mining solutions. In the text processing pipeline, classification is a key step for extraction of small sections of relevant text. Consequently, for the task of locating protein-protein interaction sentences, we examine the use of a classifier which has rarely been applied to text, the Gaussian processes (GPs). GPs are a non-parametric probabilistic analogue to the more popular support vector machines (SVMs). We find that GPs outperform the SVM and na\"ive Bayes classifiers on binary sentence data, whilst showing equivalent performance on abstract and multiclass sentence corpora. In addition, the lack of the margin parameter, which requires costly tuning, along with the principled multiclass extensions enabled by the probabilistic framework make GPs an appealing alternative worth of further adoption

Worker heterogeneity, new monopsony, and training

A worker's output depends not only on his/her own ability but also on that of colleagues, who can facilitate the performance of tasks that each individual cannot accomplish on his/her own. We show that this common-sense observation generates monopsony power and is sufficient to explain why employers might expend resources on training employees even when the training is of use to other firms. We show that training will take place in better-than-average or ‘good’ firms enjoying greater monopsony power, whereas ‘bad’ firms will have low-ability workers unlikely to receive much training