Mesoscopic Rydberg Gate based on Electromagnetically Induced Transparency

We demonstrate theoretically a parallelized C-NOT gate which allows to entangle a mesoscopic ensemble of atoms with a single control atom in a single step, with high fidelity and on a microsecond timescale. Our scheme relies on the strong and long-ranged interaction between Rydberg atoms triggering Electromagnetically Induced Transparency (EIT). By this we can robustly implement a conditional transfer of all ensemble atoms among two logical states, depending on the state of the control atom. We outline a many body interferometer which allows a comparison of two many-body quantum states by performing a measurement of the control atom.Comment: published versio

Implication of Sialidases in Salmonella Infection: Genome Release of Sialidase Knockout Strains from Salmonella enterica Serovar Typhimurium LT2.

Sialidases, which are widely distributed in nature, cleave the α-ketosidic bond of terminal sialic acid residue. These emerging virulence factors degrade the host glycan. We report here the release of seven sialidase and one sialic acid transporter deletion in Salmonella enterica serovar Typhimurium strain LT2, which are important in cellular invasion during infection

Scanning tunneling microscopy investigation of 2H-MoS_2: A layered semiconducting transition‐metal dichalcogenide

Scanning tunneling microscopy (STM) has been enormously successful in solving several important problems in the geometric and electronic structure of homogeneous metallic and semiconducting surfaces. A central question which remains to be answered with respect to the study of compound surfaces, however, is the extent to which the chemical identity of constituent atoms may be established. Recently, progress in this area was made by Feenstra et al. who succeeded in selectively imaging either Ga or As atoms on the GaAs (110) surface. So far this is the only case where such selectivity has been achieved. In an effort to add to our understanding of compound surface imaging we have undertaken a vacuum STM study of 2H-MoS_2, a material which has two structurally and electronically different atomic species at its surface

Shigella Draft Genome Sequences: Resources for Food Safety and Public Health.

Shigella is a major foodborne pathogen that infects humans and nonhuman primates and is the major cause of dysentery and reactive arthritis worldwide. This is the initial public release of 16 Shigella genome sequences from four species sequenced as part of the 100K Pathogen Genome Project

Draft Genome Sequences of Campylobacter jejuni Strains That Cause Abortion in Livestock.

Campylobacter jejuni is an intestinal bacterium that can cause abortion in livestock. This publication announces the public release of 15 Campylobacter jejuni genome sequences from isolates linked to abortion in livestock. These isolates are part of the 100K Pathogen Genome Project and are from clinical cases at the University of California (UC) Davis

Quantitative maps of geomagnetic perturbation vectors during substorm onset and recovery

We have produced the first series of spherical harmonic, numerical maps of the time‐dependent surface perturbations in the Earth's magnetic field following the onset of substorms. Data from 124 ground magnetometer stations in the Northern Hemisphere at geomagnetic latitudes above 33° were used. Ground station data averaged over 5 min intervals covering 8 years (1998–2005) were used to construct pseudo auroral upper, auroral lower, and auroral electrojet (AU*, AL*, and AE*) indices. These indices were used to generate a list of substorms that extended from 1998 to 2005, through a combination of automated processing and visual checks. Events were sorted by interplanetary magnetic field (IMF) orientation (at the Advanced Composition Explorer (ACE) satellite), dipole tilt angle, and substorm magnitude. Within each category, the events were aligned on substorm onset. A spherical cap harmonic analysis was used to obtain a least error fit of the substorm disturbance patterns at 5 min intervals up to 90 min after onset. The fits obtained at onset time were subtracted from all subsequent fits, for each group of substorm events. Maps of the three vector components of the averaged magnetic perturbations were constructed to show the effects of substorm currents. These maps are produced for several specific ranges of values for the peak |AL*| index, IMF orientation, and dipole tilt angle. We demonstrate an influence of the dipole tilt angle on the response to substorms. Our results indicate that there are downward currents poleward and upward currents just equatorward of the peak in the substorms' westward electrojet.Key PointsShow quantitative maps of ground geomagnetic perturbations due to substormsThree vector components mapped as function of time during onset and recoveryCompare/contrast results for different tilt angle and sign of IMF Y‐componentPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110891/1/jgra51610.pd

Draft Genome Sequence of Multidrug-Resistant Abortive Campylobacter jejuni from Northern California.

Campylobacter jejuni is an enteric bacterium that can cause abortion in livestock. This is the release of a multidrug-resistant Campylobacter jejuni genome from an isolate that caused an abortion in a cow in northern California. This isolate is part of the 100K Pathogen Genome Project

Neural Attentive Session-based Recommendation

Given e-commerce scenarios that user profiles are invisible, session-based recommendation is proposed to generate recommendation results from short sessions. Previous work only considers the user's sequential behavior in the current session, whereas the user's main purpose in the current session is not emphasized. In this paper, we propose a novel neural networks framework, i.e., Neural Attentive Recommendation Machine (NARM), to tackle this problem. Specifically, we explore a hybrid encoder with an attention mechanism to model the user's sequential behavior and capture the user's main purpose in the current session, which are combined as a unified session representation later. We then compute the recommendation scores for each candidate item with a bi-linear matching scheme based on this unified session representation. We train NARM by jointly learning the item and session representations as well as their matchings. We carried out extensive experiments on two benchmark datasets. Our experimental results show that NARM outperforms state-of-the-art baselines on both datasets. Furthermore, we also find that NARM achieves a significant improvement on long sessions, which demonstrates its advantages in modeling the user's sequential behavior and main purpose simultaneously.Comment: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. arXiv admin note: text overlap with arXiv:1511.06939, arXiv:1606.08117 by other author