Sagnac effect in a chain of mesoscopic quantum rings

The ability to interferometrically detect inertial rotations via the Sagnac effect has been a strong stimulus for the development of atom interferometry because of the potential 10^{10} enhancement of the rotational phase shift in comparison to optical Sagnac gyroscopes. Here we analyze ballistic transport of matter waves in a one dimensional chain of N coherently coupled quantum rings in the presence of a rotation of angular frequency, \Omega. We show that the transmission probability, T, exhibits zero transmission stop gaps as a function of the rotation rate interspersed with regions of rapidly oscillating finite transmission. With increasing N, the transition from zero transmission to the oscillatory regime becomes an increasingly sharp function of \Omega with a slope \partialT/\partial \Omega N^2. The steepness of this slope dramatically enhances the response to rotations in comparison to conventional single ring interferometers such as the Mach-Zehnder and leads to a phase sensitivity well below the standard quantum limit

Polymer informatics at-scale with multitask graph neural networks

Artificial intelligence-based methods are becoming increasingly effective at screening libraries of polymers down to a selection that is manageable for experimental inquiry. The vast majority of presently adopted approaches for polymer screening rely on handcrafted chemostructural features extracted from polymer repeat units -- a burdensome task as polymer libraries, which approximate the polymer chemical search space, progressively grow over time. Here, we demonstrate that directly "machine-learning" important features from a polymer repeat unit is a cheap and viable alternative to extracting expensive features by hand. Our approach -- based on graph neural networks, multitask learning, and other advanced deep learning techniques -- speeds up feature extraction by one to two orders of magnitude relative to presently adopted handcrafted methods without compromising model accuracy for a variety of polymer property prediction tasks. We anticipate that our approach, which unlocks the screening of truly massive polymer libraries at scale, will enable more sophisticated and large scale screening technologies in the field of polymer informatics

Normalising Flows for Bayesian Gravity Inversion

Gravity inversion is a commonly applied data analysis technique in the field of geophysics. While machine learning methods have previously been explored for the problem of gravity inversion, these are deterministic approaches returning a single solution deemed most appropriate by the algorithm. The method presented here takes a different approach, where gravity inversion is reformulated as a Bayesian parameter inference problem. Samples from the posterior probability distribution of source model parameters are obtained via the implementation of a generative neural network architecture known as Normalising Flows. Due to its probabilistic nature, this framework provides the user with a range of source parameters and uncertainties instead of a single solution, and is inherently robust against instrumental noise. The performance of the Normalising Flow is compared to that of an established Bayesian method called Nested Sampling. It is shown that the new method returns results with comparable accuracy 200 times faster than standard sampling methods, which makes Normalising Flows a suitable method for real-time inversion in the field. When applied to data sets with high dimensionality, standard sampling methods can become impractical due to long computation times. It is shown that inversion using Normalising Flows remains tractable even at 512 dimensions and once the network is trained, the results can be obtained in $O(10)$ seconds.Comment: 14 pages, 6 figures, submitted for publication in Computers & Geosciences Journa

Avancées dans une réécriture de l'histoire de la transition du Jurassique au Crétacé dans le Mont Liban

The stratigraphic framework of the Upper Jurassic and Lower Cretaceous strata of Lebanon that dates back to Dubertret's publications required either consolidation or full revision. The preliminary results of our investigations in the Mount Lebanon region are presented here. We provide new micropaleontological and sedimentological information on the Salima Oolitic Limestones, which is probably an unconformity-bounded unit (possibly Early Valanginian in age), and the "Grès du Liban" (Barremian in age). Our revised bio- and holostratigraphic interpretations and the new age assignations lead us to emphasize the importance of the two hiatuses in the sedimentary record below and above the Salima, i.e., at the transition from the Jurassic to the Cretaceous.Le canevas stratigraphique du Jurassique supérieur et du Crétacé inférieur du Liban date des publications anciennes de Dubertret et aurait donc besoin d'être soit toiletté et consolidé, soit révisé de fond en comble. Les résultats préliminaires de nos recherches dans la région du Mont Liban sont exposés ici. Nous fournissons des données micropaléontologiques et sédimentologiques inédites sur les Calcaires oolithiques de Salima, qui constituent vraisemblablement une unité lithostratigraphique particulière, une "UBU", car encadrée par deux discontinuités (probablement d'âge Valanginien inférieur), et sur le Grès du Liban (d'âge barrémien). Nos nouvelles interprétations bio- et holostratigraphiques, ainsi que nos nouvelles attributions chronostratigraphiques, nous permettent de souligner l'importance des deux lacunes sédimentaires encadrant les Calcaires oolithiques de Salima, c'est-à-dire des lacunes significatives situées dans l'intervalle de transition du Jurassique au Crétacé

Analysis of methods

Information is one of an organization's most important assets. For this reason the development and maintenance of an integrated information system environment is one of the most important functions within a large organization. The Integrated Information Systems Evolution Environment (IISEE) project has as one of its primary goals a computerized solution to the difficulties involved in the development of integrated information systems. To develop such an environment a thorough understanding of the enterprise's information needs and requirements is of paramount importance. This document is the current release of the research performed by the Integrated Development Support Environment (IDSE) Research Team in support of the IISEE project. Research indicates that an integral part of any information system environment would be multiple modeling methods to support the management of the organization's information. Automated tool support for these methods is necessary to facilitate their use in an integrated environment. An integrated environment makes it necessary to maintain an integrated database which contains the different kinds of models developed under the various methodologies. In addition, to speed the process of development of models, a procedure or technique is needed to allow automatic translation from one methodology's representation to another while maintaining the integrity of both. The purpose for the analysis of the modeling methods included in this document is to examine these methods with the goal being to include them in an integrated development support environment. To accomplish this and to develop a method for allowing intra-methodology and inter-methodology model element reuse, a thorough understanding of multiple modeling methodologies is necessary. Currently the IDSE Research Team is investigating the family of Integrated Computer Aided Manufacturing (ICAM) DEFinition (IDEF) languages IDEF(0), IDEF(1), and IDEF(1x), as well as ENALIM, Entity Relationship, Data Flow Diagrams, and Structure Charts, for inclusion in an integrated development support environment

UCHL1 Is a Potential Molecular Indicator and Therapeutic Target for Neuroendocrine Carcinomas

Neuroendocrine carcinomas, such as neuroendocrine prostate cancer and small-cell lung cancer, commonly have a poor prognosis and limited therapeutic options. We report that ubiquitin carboxy-terminal hydrolase L1 (UCHL1), a deubiquitinating enzyme, is elevated in tissues and plasma from patients with neuroendocrine carcinomas. Loss of UCHL1 decreases tumor growth and inhibits metastasis of these malignancies. UCHL1 maintains neuroendocrine differentiation and promotes cancer progression by regulating nucleoporin, POM121, and p53. UCHL1 binds, deubiquitinates, and stabilizes POM121 to regulate POM121-associated nuclear transport of E2F1 and c-MYC. Treatment with the UCHL1 inhibitor LDN-57444 slows tumor growth and metastasis across neuroendocrine carcinomas. The combination of UCHL1 inhibitors with cisplatin, the standard of care used for neuroendocrine carcinomas, significantly delays tumor growth in pre-clinical settings. Our study reveals mechanisms of UCHL1 function in regulating the progression of neuroendocrine carcinomas and identifies UCHL1 as a therapeutic target and potential molecular indicator for diagnosing and monitoring treatment responses in these malignancies

A Comprehensive Association Analysis of Homocysteine Metabolic Pathway Genes in Singaporean Chinese with Ischemic Stroke

10.1371/journal.pone.0024757PLoS ONE69

Cardiovascular Risk Associated with Interactions among Polymorphisms in Genes from the Renin-Angiotensin, Bradykinin, and Fibrinolytic Systems

Vascular fibrinolytic balance is maintained primarily by interplay of tissue plasminogen activator (t-PA) and plasminogen activator inhibitor type 1 (PAI-1). Previous research has shown that polymorphisms in genes from the renin-angiotensin (RA), bradykinin, and fibrinolytic systems affect plasma concentrations of both t-PA and PAI-1 through a set of gene-gene interactions. In the present study, we extend this finding by exploring the effects of polymorphisms in genes from these systems on incident cardiovascular disease, explicitly examining two-way interactions in a large population-based study

Association of a Deletion of GSTT2B with an Altered Risk of Oesophageal Squamous Cell Carcinoma in a South African Population: A Case-Control Study

Polymorphisms in the Glutathione S-transferase genes are associated with altered risks in many cancers, but their role in oesophageal cancer is unclear. Recently a 37-kb deletion polymorphism of GSTT2B that reduces expression of GSTT2 has been described. We evaluated the influence of the GSTT1 and GSTT2B deletion polymorphisms, and the GSTP1 Ile105Val polymorphism (rs1695) on susceptibility to oesophageal squamous cell carcinoma (OSCC) in the Black and Mixed Ancestry populations of South Africa.The GSTT1, GSTT2B and GSTP1 variants were genotyped in 562 OSCC cases and 907 controls, and tested for association with OSCC and for interaction with smoking and alcohol consumption. Linkage disequilibrium (LD) between the deletions at GSTT1 and GSTT2B was determined, and the haplotypes tested for association with OSCC. Neither the GSTT1 deletion nor the GSTP1 Ile105Val polymorphism was associated with OSCC risk in the Black or Mixed Ancestry populations. The GSTT2B deletion was not associated with OSCC risk in the Black population, but was associated with reduced risk of OSCC in the Mixed Ancestry population (OR=0.71; 95% CI 0.57-0.90, p=0.004). Case-only analysis showed no interaction between the GST polymorphisms and smoking or alcohol consumption. LD between the neighboring GSTT1 and GSTT2B deletions was low in both populations (r(2)(Black)=0.04; r(2)(MxA)=0.07), thus these deletions should be assessed independently for effects on disease risk.Although there was no association between the GSTT1 deletion polymorphism or the GSTP1 Ile105Val polymorphism with OSCC, our results suggest that the presence of the recently described GSTT2B deletion may have a protective effect on the risk of OSCC in the Mixed Ancestry South African population. This is the first report of the contribution of the GSTT2B deletion to cancer risk