Nonlinear atom interferometer surpasses classical precision limit

Interference is fundamental to wave dynamics and quantum mechanics. The quantum wave properties of particles are exploited in metrology using atom interferometers, allowing for high-precision inertia measurements [1, 2]. Furthermore, the state-of-the-art time standard is based on an interferometric technique known as Ramsey spectroscopy. However, the precision of an interferometer is limited by classical statistics owing to the finite number of atoms used to deduce the quantity of interest [3]. Here we show experimentally that the classical precision limit can be surpassed using nonlinear atom interferometry with a Bose-Einstein condensate. Controlled interactions between the atoms lead to non-classical entangled states within the interferometer; this represents an alternative approach to the use of non-classical input states [4-8]. Extending quantum interferometry [9] to the regime of large atom number, we find that phase sensitivity is enhanced by 15 per cent relative to that in an ideal classical measurement. Our nonlinear atomic beam splitter follows the "one-axis-twisting" scheme [10] and implements interaction control using a narrow Feshbach resonance. We perform noise tomography of the quantum state within the interferometer and detect coherent spin squeezing with a squeezing factor of -8.2dB [11-15]. The results provide information on the many-particle quantum state, and imply the entanglement of 170 atoms [16]

Laser Cooling of Optically Trapped Molecules

Calcium monofluoride (CaF) molecules are loaded into an optical dipole trap (ODT) and subsequently laser cooled within the trap. Starting with magneto-optical trapping, we sub-Doppler cool CaF and then load $150(30)$ CaF molecules into an ODT. Enhanced loading by a factor of five is obtained when sub-Doppler cooling light and trapping light are on simultaneously. For trapped molecules, we directly observe efficient sub-Doppler cooling to a temperature of $60(5)$ $\mu\text{K}$. The trapped molecular density of $8(2)\times10^7$ cm$^{-3}$ is an order of magnitude greater than in the initial sub-Doppler cooled sample. The trap lifetime of 750(40) ms is dominated by background gas collisions.Comment: 5 pages, 5 figure

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

Discovery and Preclinical Validation of Salivary Transcriptomic and Proteomic Biomarkers for the Non-Invasive Detection of Breast Cancer

A sensitive assay to identify biomarkers using non-invasively collected clinical specimens is ideal for breast cancer detection. While there are other studies showing disease biomarkers in saliva for breast cancer, our study tests the hypothesis that there are breast cancer discriminatory biomarkers in saliva using de novo discovery and validation approaches. This is the first study of this kind and no other study has engaged a de novo biomarker discovery approach in saliva for breast cancer detection. In this study, a case-control discovery and independent preclinical validations were conducted to evaluate the performance and translational utilities of salivary transcriptomic and proteomic biomarkers for breast cancer detection.Salivary transcriptomes and proteomes of 10 breast cancer patients and 10 matched controls were profiled using Affymetrix HG-U133-Plus-2.0 Array and two-dimensional difference gel electrophoresis (2D-DIGE), respectively. Preclinical validations were performed to evaluate the discovered biomarkers in an independent sample cohort of 30 breast cancer patients and 63 controls using RT-qPCR (transcriptomic biomarkers) and quantitative protein immunoblot (proteomic biomarkers). Transcriptomic and proteomic profiling revealed significant variations in salivary molecular biomarkers between breast cancer patients and matched controls. Eight mRNA biomarkers and one protein biomarker, which were not affected by the confounding factors, were pre-validated, yielding an accuracy of 92% (83% sensitive, 97% specific) on the preclinical validation sample set.Our findings support that transcriptomic and proteomic signatures in saliva can serve as biomarkers for the non-invasive detection of breast cancer. The salivary biomarkers possess discriminatory power for the detection of breast cancer, with high specificity and sensitivity, which paves the way for prediction model validation study followed by pivotal clinical validation

An abrupt weakening of the subpolar gyre as trigger of Little Ice Age-type episodes

We investigate the mechanism of a decadal-scale weakening shift in the strength of the subpolar gyre (SPG) that is found in one among three last millennium simulations with a state-of-the-art Earth system model. The SPG shift triggers multicentennial anomalies in the North Atlantic climate driven by long-lasting internal feedbacks relating anomalous oceanic and atmospheric circulation, sea ice extent, and upper-ocean salinity in the Labrador Sea. Yet changes throughout or after the shift are not associated with a persistent weakening of the Atlantic Meridional Overturning Circulation or shifts in the North Atlantic Oscillation. The anomalous climate state of the North Atlantic simulated after the shift agrees well with climate reconstructions from within the area, which describe a transition between a stronger and weaker SPG during the relatively warm medieval climate and the cold Little Ice Age respectively. However, model and data differ in the timing of the onset. The simulated SPG shift is caused by a rapid increase in the freshwater export from the Arctic and associated freshening in the upper Labrador Sea. Such freshwater anomaly relates to prominent thickening of the Arctic sea ice, following the cluster of relatively small-magnitude volcanic eruptions by 1600 CE. Sensitivity experiments without volcanic forcing can nonetheless produce similar abrupt events; a necessary causal link between the volcanic cluster and the SPG shift can therefore be excluded. Instead, preconditioning by internal variability explains discrepancies in the timing between the simulated SPG shift and the reconstructed estimates for the Little Ice Age onset

X-ray emission from the Sombrero galaxy: discrete sources

We present a study of discrete X-ray sources in and around the bulge-dominated, massive Sa galaxy, Sombrero (M104), based on new and archival Chandra observations with a total exposure of ~200 ks. With a detection limit of L_X = 1E37 erg/s and a field of view covering a galactocentric radius of ~30 kpc (11.5 arcminute), 383 sources are detected. Cross-correlation with Spitler et al.'s catalogue of Sombrero globular clusters (GCs) identified from HST/ACS observations reveals 41 X-rays sources in GCs, presumably low-mass X-ray binaries (LMXBs). We quantify the differential luminosity functions (LFs) for both the detected GC and field LMXBs, whose power-low indices (~1.1 for the GC-LF and ~1.6 for field-LF) are consistent with previous studies for elliptical galaxies. With precise sky positions of the GCs without a detected X-ray source, we further quantify, through a fluctuation analysis, the GC LF at fainter luminosities down to 1E35 erg/s. The derived index rules out a faint-end slope flatter than 1.1 at a 2 sigma significance, contrary to recent findings in several elliptical galaxies and the bulge of M31. On the other hand, the 2-6 keV unresolved emission places a tight constraint on the field LF, implying a flattened index of ~1.0 below 1E37 erg/s. We also detect 101 sources in the halo of Sombrero. The presence of these sources cannot be interpreted as galactic LMXBs whose spatial distribution empirically follows the starlight. Their number is also higher than the expected number of cosmic AGNs (52+/-11 [1 sigma]) whose surface density is constrained by deep X-ray surveys. We suggest that either the cosmic X-ray background is unusually high in the direction of Sombrero, or a distinct population of X-ray sources is present in the halo of Sombrero.Comment: 11 figures, 5 tables, ApJ in pres

Somatic diversification of variable lymphocyte receptors in the agnathan sea lamprey

Although jawless vertebrates are apparently capable of adaptive immune responses, they have not been found to possess the recombinatorial antigen receptors shared by all jawed vertebrates. Our search for the phylogenetic roots of adaptive immunity in the lamprey has instead identified a new type of variable lymphocyte receptors (VLRs) composed of highly diverse leucine-rich repeats (LRR) sandwiched between amino- and carboxy-terminal LRRs. An invariant stalk region tethers the VLRs to the cell surface by means of a glycosyl-phosphatidyl-inositol anchor. To generate rearranged VLR genes of the diversity necessary for an anticipatory immune system, the single lamprey VLR locus contains a large bank of diverse LRR cassettes, available for insertion into an incomplete germline VLR gene. Individual lymphocytes express a uniquely rearranged VLR gene in monoallelic fashion. Different evolutionary strategies were thus used to generate highly diverse lymphocyte receptors through rearrangement of LRR modules in agnathans ( jawless fish) and of immunoglobulin gene segments in gnathostomes ( jawed vertebrates).Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62870/1/nature02740.pd

Impaired Embryonic Development in Mice Overexpressing the RNA-Binding Protein TIAR

TIA-1-related (TIAR) protein is a shuttling RNA-binding protein involved in several steps of RNA metabolism. While in the nucleus TIAR participates to alternative splicing events, in the cytoplasm TIAR acts as a translational repressor on specific transcripts such as those containing AU-Rich Elements (AREs). Due to its ability to assemble abortive pre-initiation complexes coalescing into cytoplasmic granules called stress granules, TIAR is also involved in the general translational arrest observed in cells exposed to environmental stress. However, the in vivo role of this protein has not been studied so far mainly due to severe embryonic lethality upon tiar invalidation.Journal ArticleResearch Support, Non-U.S. Gov'tSCOPUS: ar.jinfo:eu-repo/semantics/publishe

A prospective cohort study of biomarkers of prenatal tobacco smoke exposure: the correlation between serum and meconium and their association with infant birth weight

<p>Abstract</p> <p>Background</p> <p>The evaluation of infant meconium as a cumulative matrix of prenatal toxicant exposure requires comparison to established biomarkers of prenatal exposure.</p> <p>Methods</p> <p>We calculated the frequency of detection and concentration of tobacco smoke metabolites measured in meconium (nicotine, cotinine, and trans-3'-hydroxycotinine concentrations) and three serial serum cotinine concentrations taken during the latter two-thirds of pregnancy among 337 mother-infant dyads. We estimated the duration and intensity of prenatal tobacco smoke exposure using serial serum cotinine concentrations and calculated geometric mean meconium tobacco smoke metabolite concentrations according to prenatal exposure. We also compared the estimated associations between these prenatal biomarkers and infant birth weight using linear regression.</p> <p>Results</p> <p>We detected nicotine (80%), cotinine (69%), and trans-3'-hydroxycotinine (57%) in most meconium samples. Meconium tobacco smoke metabolite concentrations were positively associated with serum cotinine concentrations and increased with the number of serum cotinine measurements consistent with secondhand or active tobacco smoke exposure. Like serum cotinine, meconium tobacco smoke metabolites were inversely associated with birth weight.</p> <p>Conclusions</p> <p>Meconium is a useful biological matrix for measuring prenatal tobacco smoke exposure and could be used in epidemiological studies that enroll women and infants at birth. Meconium holds promise as a biological matrix for measuring the intensity and duration of environmental toxicant exposure and future studies should validate the utility of meconium using other environmental toxicants.</p

Early identification of first-year students at risk of dropping out of high-school entry medical school: the usefulness of teachers' ratings of class participation

Dropping out from undergraduate medical education is costly for students, medical schools, and society in general. Therefore, the early identification of potential dropout students is important. The contribution of personal features to dropout rates has merited exploration. However, there is a paucity of research on aspects of student experience that may lead to dropping out. In this study, underpinned by theoretical models of student commitment, involvement, and engagement, we explored the hypothesis of using inferior participation as an indicator of a higher probability of dropping out in year 1. Class participation was calculated as an aggregate score based on teachers' daily observations in class. The study used a longitudinal dataset of six cohorts of high-school entry students (N = 709, 67% females) in one medical school with an annual intake of 120 students. The findings confirmed the initial hypothesis and showed that lower scores of class participation in year 1 added predictive ability to pre-entry characteristics (Pseudo-R2 raised from 0.22 to 0.28). Even though the inclusion of course failure in year 1 resulted in higher explanatory power than participation in class (Pseudo-R2 raised from 0.28 to 0.63), ratings of class participation may be advantageous to anticipate dropout identification, as those can be collected prior to course failure. The implications for practice are that teachers' ratings of class participation can play a role in indicating medical students who may eventually drop out. We conclude that the scores of class participation can contribute to flagging systems for the early detection of student dropouts.(undefined)info:eu-repo/semantics/acceptedVersio