Magneto-spectroscopy of excited states in charge-tunable GaAs/AlGaAs [111] quantum dots

We present a combined experimental and theoretical study of highly charged and excited electron-hole complexes in strain-free (111) GaAs/AlGaAs quantum dots grown by droplet epitaxy. We address the complexes with one of the charge carriers residing in the excited state, namely, the ``hot'' trions X$^{-*}$ and X$^{+*}$, and the doubly negatively charged exciton X$^{2-}$. Our magneto-photoluminescence experiments performed on single quantum dots in the Faraday geometry uncover characteristic emission patterns for each excited electron-hole complex, which are very different from the photoluminescence spectra observed in (001)-grown quantum dots. We present a detailed theory of the fine structure and magneto-photoluminescence spectra of X$^{-*}$, X$^{+*}$ and X$^{2-}$ complexes, governed by the interplay between the electron-hole Coulomb exchange interaction and the heavy-hole mixing, characteristic for these quantum dots with a trigonal symmetry. Comparison between experiment and theory of the magneto-photoluminescence allows for precise charge state identification, as well as extraction of electron-hole exchange interaction constants and $g$-factors for the charge carriers occupying excited states.Comment: 12 pages, 5 figure

Quantifying trading behavior in financial markets using Google Trends

Crises in financial markets affect humans worldwide. Detailed market data on trading decisions reflect some of the complex human behavior that has led to these crises. We suggest that massive new data sources resulting from human interaction with the Internet may offer a new perspective on the behavior of market participants in periods of large market movements. By analyzing changes in Google query volumes for search terms related to finance, we find patterns that may be interpreted as “early warning signs” of stock market moves. Our results illustrate the potential that combining extensive behavioral data sets offers for a better understanding of collective human behavior

Spin-SS generalization of fractional exclusion statistics

We study fractional exclusion statistics for quantum systems with SU(2) symmetry (arbitrary spin $S$), by generalizing the thermodynamic equations with squeezed strings proposed by Ha and Haldane. The bare hole distributions as well as the statistical interaction defined by an infinite-dimensional matrix specify the universality class. It is shown that the system is described by the level-$2S$ WZW model and has a close relationship to non-abelian fractional quantum Hall states. As a low-energy effective theory, the sector of {\it massless} Z$_{2S}$ parafermions is extracted, whose statistical interaction is given by a finite-dimensional matrix.Comment: 11pages, REVTE

Wigner crystal model of counterion induced bundle formation of rod-like polyelectrolytes

A simple electrostatic theory of condensation of rod-like polyelectrolytes under influence of polyvalent ions is proposed. It is based on the idea that Manning condensation of ions results in formation of the Wigner crystal on a background of a bundle of rods. It is shown that, depending on a single dimensionless parameter, this can be the densely packed three-dimensional Wigner crystal or the two-dimensional crystal on the rod surfaces. For DNA the location of charge on the spiral results in a model of the one-dimensional Wigner crystal. It is also argued that the Wigner crystal idea can be applied to self-assembly of other polyelectrolytes, for example, colloids and DNA-lipid complexes.Comment: 4 pages; typos corrected, references adde

A study on text-score disagreement in online reviews

In this paper, we focus on online reviews and employ artificial intelligence tools, taken from the cognitive computing field, to help understanding the relationships between the textual part of the review and the assigned numerical score. We move from the intuitions that 1) a set of textual reviews expressing different sentiments may feature the same score (and vice-versa); and 2) detecting and analyzing the mismatches between the review content and the actual score may benefit both service providers and consumers, by highlighting specific factors of satisfaction (and dissatisfaction) in texts. To prove the intuitions, we adopt sentiment analysis techniques and we concentrate on hotel reviews, to find polarity mismatches therein. In particular, we first train a text classifier with a set of annotated hotel reviews, taken from the Booking website. Then, we analyze a large dataset, with around 160k hotel reviews collected from Tripadvisor, with the aim of detecting a polarity mismatch, indicating if the textual content of the review is in line, or not, with the associated score. Using well established artificial intelligence techniques and analyzing in depth the reviews featuring a mismatch between the text polarity and the score, we find that -on a scale of five stars- those reviews ranked with middle scores include a mixture of positive and negative aspects. The approach proposed here, beside acting as a polarity detector, provides an effective selection of reviews -on an initial very large dataset- that may allow both consumers and providers to focus directly on the review subset featuring a text/score disagreement, which conveniently convey to the user a summary of positive and negative features of the review target.Comment: This is the accepted version of the paper. The final version will be published in the Journal of Cognitive Computation, available at Springer via http://dx.doi.org/10.1007/s12559-017-9496-

PPAR? Downregulation by TGF in Fibroblast and Impaired Expression and Function in Systemic Sclerosis: A Novel Mechanism for Progressive Fibrogenesis

The nuclear orphan receptor peroxisome proliferator-activated receptor-gamma (PPAR-γ) is expressed in multiple cell types in addition to adipocytes. Upon its activation by natural ligands such as fatty acids and eicosanoids, or by synthetic agonists such as rosiglitazone, PPAR-γ regulates adipogenesis, glucose uptake and inflammatory responses. Recent studies establish a novel role for PPAR-γ signaling as an endogenous mechanism for regulating transforming growth factor-ß (TGF-ß)- dependent fibrogenesis. Here, we sought to characterize PPAR-γ function in the prototypic fibrosing disorder systemic sclerosis (SSc), and delineate the factors governing PPAR-γ expression. We report that PPAR-γ levels were markedly diminished in skin and lung biopsies from patients with SSc, and in fibroblasts explanted from the lesional skin. In normal fibroblasts, treatment with TGF-ß resulted in a time- and dose-dependent down-regulation of PPAR-γ expression. Inhibition occurred at the transcriptional level and was mediated via canonical Smad signal transduction. Genome-wide expression profiling of SSc skin biopsies revealed a marked attenuation of PPAR-γ levels and transcriptional activity in a subset of patients with diffuse cutaneous SSc, which was correlated with the presence of a ''TGF-ß responsive gene signature'' in these biopsies. Together, these results demonstrate that the expression and function of PPAR-γ are impaired in SSc, and reveal the existence of a reciprocal inhibitory cross-talk between TGF-ß activation and PPAR-γ signaling in the context of fibrogenesis. In light of the potent anti-fibrotic effects attributed to PPAR-γ, these observations lead us to propose that excessive TGF-ß activity in SSc accounts for impaired PPAR-γ function, which in turn contributes to unchecked fibroblast activation and progressive fibrosis. © 2010 Wei et al

Gene expression drives the evolution of dominance.

Dominance is a fundamental concept in molecular genetics and has implications for understanding patterns of genetic variation, evolution, and complex traits. However, despite its importance, the degree of dominance in natural populations is poorly quantified. Here, we leverage multiple mating systems in natural populations of Arabidopsis to co-estimate the distribution of fitness effects and dominance coefficients of new amino acid changing mutations. We find that more deleterious mutations are more likely to be recessive than less deleterious mutations. Further, this pattern holds across gene categories, but varies with the connectivity and expression patterns of genes. Our work argues that dominance arises as a consequence of the functional importance of genes and their optimal expression levels

A bayesian meta-analysis of multiple treatment comparisons of systemic regimens for advanced pancreatic cancer

© 2014 Chan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Background: For advanced pancreatic cancer, many regimens have been compared with gemcitabine (G) as the standard arm in randomized controlled trials. Few regimens have been directly compared with each other in randomized controlled trials and the relative efficacy and safety among them remains unclear

Genome wide analysis of gene expression changes in skin from patients with type 2 diabetes

Non-healing chronic ulcers are a serious complication of diabetes and are a major healthcare problem. While a host of treatments have been explored to heal or prevent these ulcers from forming, these treatments have not been found to be consistently effective in clinical trials. An understanding of the changes in gene expression in the skin of diabetic patients may provide insight into the processes and mechanisms that precede the formation of non-healing ulcers. In this study, we investigated genome wide changes in gene expression in skin between patients with type 2 diabetes and non-diabetic patients using next generation sequencing. We compared the gene expression in skin samples taken from 27 patients (13 with type 2 diabetes and 14 non-diabetic). This information may be useful in identifying the causal factors and potential therapeutic targets for the prevention and treatment of diabetic related diseases