A generalization of moderated statistics to data adaptive semiparametric estimation in high-dimensional biology

The widespread availability of high-dimensional biological data has made the simultaneous screening of numerous biological characteristics a central statistical problem in computational biology. While the dimensionality of such datasets continues to increase, the problem of teasing out the effects of biomarkers in studies measuring baseline confounders while avoiding model misspecification remains only partially addressed. Efficient estimators constructed from data adaptive estimates of the data-generating distribution provide an avenue for avoiding model misspecification; however, in the context of high-dimensional problems requiring simultaneous estimation of numerous parameters, standard variance estimators have proven unstable, resulting in unreliable Type-I error control under standard multiple testing corrections. We present the formulation of a general approach for applying empirical Bayes shrinkage approaches to asymptotically linear estimators of parameters defined in the nonparametric model. The proposal applies existing shrinkage estimators to the estimated variance of the influence function, allowing for increased inferential stability in high-dimensional settings. A methodology for nonparametric variable importance analysis for use with high-dimensional biological datasets with modest sample sizes is introduced and the proposed technique is demonstrated to be robust in small samples even when relying on data adaptive estimators that eschew parametric forms. Use of the proposed variance moderation strategy in constructing stabilized variable importance measures of biomarkers is demonstrated by application to an observational study of occupational exposure. The result is a data adaptive approach for robustly uncovering stable associations in high-dimensional data with limited sample sizes

Introduction of a novel 18S rDNA gene arrangement along with distinct ITS region in the saline water microalga Dunaliella

Comparison of 18S rDNA gene sequences is a very promising method for identification and classification of living organisms. Molecular identification and discrimination of different Dunaliella species were carried out based on the size of 18S rDNA gene and, number and position of introns in the gene. Three types of 18S rDNA structure have already been reported: the gene with a size of ~1770 bp lacking any intron, with a size of ~2170 bp consisting one intron near 5' terminus, and with a size of ~2570 bp harbouring two introns near 5' and 3' termini. Hereby, we report a new 18S rDNA gene arrangement in terms of intron localization and nucleotide sequence in a Dunaliella isolated from Iranian salt lakes (ABRIINW-M1/2). PCR amplification with genus-specific primers resulted in production of a ~2170 bp DNA band, which is similar to that of D. salina 18S rDNA gene containing only one intron near 5' terminus. Whilst, sequence composition of the gene revealed the lack of any intron near 5' terminus in our isolate. Furthermore, another alteration was observed due to the presence of a 440 bp DNA fragment near 3' terminus. Accordingly, 18S rDNA gene of the isolate is clearly different from those of D. salina and any other Dunaliella species reported so far. Moreover, analysis of ITS region sequence showed the diversity of this region compared to the previously reported species. 18S rDNA and ITS sequences of our isolate were submitted with accesion numbers of EU678868 and EU927373 in NCBI database, respectively. The optimum growth rate of this isolate occured at the salinity level of 1 M NaCl. The maximum carotenoid content under stress condition of intense light (400 μmol photon m-2 s-1), high salinity (4 M NaCl) and deficiency of nitrate and phosphate nutritions reached to 240 ng/cell after 15 days

Chiral force of guided light on an atom

We calculate the force of a near-resonant guided light field of an ultrathin optical fiber on a two-level atom. We show that, if the atomic dipole rotates in the meridional plane, the magnitude of the force of the guided light depends on the field propagation direction. The chirality of the force arises as a consequence of the directional dependencies of the Rabi frequency of the guided driving field and the spontaneous emission from the atom. This provides a unique method for controlling atomic motion in the vicinity of an ultrathin fiber.Comment: text and figures were revised, and a new discussion was adde

Compact superconducting dual-log spiral resonator with high Q-factor and low power dependence

A new dual-log spiral geometry is proposed for microstrip resonators, offering substantial advantages in performance and size reduction at subgigahertz frequencies when realized in superconducting materials. The spiral is logarithmic in line spacing and width such that the width of the spiral line increases smoothly with the increase of the current density, reaching its maximum where the current density is maximum (in its center for 2 resonators). Preliminary results of such a logarithmic ten-turn (2 5 turns) spiral, realized with double-sided YBCO thin film, showed a -factor seven times higher than that of a single ten-turn uniform spiral made of YBCO thin film and 64 times higher than a copper counterpart. The insertion loss of the YBCO dual log-spiral has a high degree of independence of the input power in comparison with a uniform Archimedian spiral, increasing by only 2.5% for a 30-dBm increase of the input power, compared with nearly 31% for the uniform spiral. A simple approximate method, developed for prediction of the resonant frequency of the new resonators, shows a good agreement with the test results

Symmetry breaking in binary Bose-Einstein condensates in the presence of an inhomogeneous artificial gauge field

We study a two component Bose-Einstein condensate in the presence of an inhomogeneous artificial gauge field. In response to this field, the condensate forms a localised vortex lattice structure that leads to a non-trivial symmetry breaking in the phase separated regime. The underlying physical mechanism can be understood by considering the energy landscape and we present a simplified model that is capable of reproducing the main features of the phase separation transition. The intuition gained by numerically solving this simplified model is then corroborated using the analytical Thomas-Fermi model

Revisiting the propensity score's central role: Towards bridging balance and efficiency in the era of causal machine learning

About forty years ago, in a now--seminal contribution, Rosenbaum & Rubin (1983) introduced a critical characterization of the propensity score as a central quantity for drawing causal inferences in observational study settings. In the decades since, much progress has been made across several research fronts in causal inference, notably including the re-weighting and matching paradigms. Focusing on the former and specifically on its intersection with machine learning and semiparametric efficiency theory, we re-examine the role of the propensity score in modern methodological developments. As Rosenbaum & Rubin (1983)'s contribution spurred a focus on the balancing property of the propensity score, we re-examine the degree to which and how this property plays a role in the development of asymptotically efficient estimators of causal effects; moreover, we discuss a connection between the balancing property and efficient estimation in the form of score equations and propose a score test for evaluating whether an estimator achieves balance.Comment: Accepted for publication in a forthcoming special issue of Observational Studie