The ionizing background at the end of overlap

One of the most sought-after signatures of reionization is a rapid increase in the ionizing background (usually measured through the Lyman-alpha optical depth toward distant quasars). Conventional wisdom associates this with the "overlap" phase when ionized bubbles merge, allowing each source to affect a much larger volume. We argue that this picture fails to describe the transition to the post-overlap Universe, where Lyman-limit systems absorb ionizing photons over moderate lengthscales (20-100 Mpc). Using an analytic model, we compute the probability distribution of the amplitude of the ionizing background throughout reionization, including both discrete ionized bubbles and Lyman-limit systems (parameterized by an attenuation length). We show that overlap does not by itself cause a rapid increase in the ionizing background or a rapid decrease in the mean Lyman-alpha transmission toward distant quasars. More detailed semi-numeric models support these conclusions. We argue that rapid changes should instead be interpreted as evolution in the attenuation length itself, which may or may not be directly related to overlap.Comment: submitted to MNRAS, 7 pages, 5 figure

Supermassive Black Holes: Connecting the Growth to the Cosmic Star Formation Rate

In this Letter, we present a model connecting the cosmic star formation rate (CSFR) to the growth of supermassive black holes. Considering that the evolution of the massive black hole is dominated by accretion (Soltan's argument) and that the accretion process can be described by a probabilistic function directly regulated by the CSFR, we obtain the evolution of the black hole mass density. Then using the quasar luminosity function, we determine both the functional form of the radiative efficiency and the evolution of the quasar duty-cycle as functions of the redshift. We analyze four different CSFRs showing that the quasar duty-cycle, $\delta(z)$, peaks at $z\sim 8.5-11$ and so within the window associated with the reionization of the Universe. In particular, $\delta_{\rm max}\sim 0.09-0.22$ depending on the CSFR. The mean radiative efficiency, $\bar\eta(z)$, peaks at $z\sim 0.1-1.3$ with $\bar\eta_{\rm max}\sim 0.10-0.46$ depending on the specific CSFR used. Our results also show that is not necessary a supercritical Eddington accretComment: accepted for publication in MNRAS Letters (5 pages, 6 figures), Some typos fixed; MNRAS Letters 17 Aug 201

Student Self-Assessment and Faculty Assessment of Performance in an Interprofessional Error disclosure Simulation Training Program

Objectives. To conduct a prospective evaluation for effectiveness of an error disclosure assessment tool and video recordings to enhance student learning and metacognitive skills while assessing the IPEC competencies. Design. The instruments for assessing performance (planning, communication, process, and team dynamcis) in interprofessional error disclosure were developed. Student self-assessment of performance before and after viewing the recordings of their encounters were obtained. Faculty used a similar instrument to conduct real-time assessments. An instrument to assess achievement of the Interprofessional Education Collaborative (IPEC) core competencies was developed. Qualitative data was reviewed to determine student and faculty perceptions of the simulation. Assessment. The interprofessional simulation training involved a total of 233 students (50 dental, 109 nursing and 74 pharmacy). Use of video recordings made a significant difference in student self-assessment for communication and process categories of error disclosure. No differences in student self-assessments were noted among the different professions. There were differences among the family member affects for planning and communication for both pre-video and post-video data. There were significant differences between student self-assessment and faculty assessment for all paired comparisons, except communication in student post-video self-assessment. Students’ perceptions of achievement of the IPEC core competencies were positive. Conclusion. The use of assessment instruments and video recordings may have enhanced students’ metacognitive skills for assessing performance in interprofessional error disclosure. The simulation training was effective in enhancing perceptions on achievement of IPEC core competencies. This enhanced assessment process appeared to enhance learning about the skills needed for interprofessional error disclosure

Urban Visual Intelligence: Studying Cities with AI and Street-level Imagery

The visual dimension of cities has been a fundamental subject in urban studies, since the pioneering work of scholars such as Sitte, Lynch, Arnheim, and Jacobs. Several decades later, big data and artificial intelligence (AI) are revolutionizing how people move, sense, and interact with cities. This paper reviews the literature on the appearance and function of cities to illustrate how visual information has been used to understand them. A conceptual framework, Urban Visual Intelligence, is introduced to systematically elaborate on how new image data sources and AI techniques are reshaping the way researchers perceive and measure cities, enabling the study of the physical environment and its interactions with socioeconomic environments at various scales. The paper argues that these new approaches enable researchers to revisit the classic urban theories and themes, and potentially help cities create environments that are more in line with human behaviors and aspirations in the digital age

The abundance of lensing protoclusters

Weak gravitational lensing provides a potentially powerful method for the detection of clusters. In addition to cluster candidates, a large number of objects with possibly no optical or X-ray component have been detected in shear-selected samples. We develop an analytic model to investigate the claim of Weinberg & Kamionkowski (2002) that unvirialised protoclusters account for a significant number of these so-called "dark" lenses. In our model, a protocluster consists of a small virialised region surrounded by in-falling matter. We find that, in order for a protocluster to simultaneously escape X-ray detection and create a detectable weak lensing signal, it must have a small virial mass (~10^{13} \Msun) and large total mass (~ 10^{15} \Msun), with a relatively flat density profile outside of the virial radius. Such objects would be characterized by rising tangential shear profiles well beyond the virial radius. We use a semi-analytic approach based on the excursion set formalism to estimate the abundance of lensing protoclusters with a low probability of X-ray detection. We find that they are extremely rare, accounting for less than 0.4 per cent of the total lenses in a survey with background galaxy density n = 30 arcmin^{-2} and an intrinsic ellipticity dispersion of 0.3. We conclude that lensing protoclusters with undetectable X-Ray luminosities are too rare to account for a significant number of dark lenses.Comment: 18 pages, 10 figures, version accepted by MNRAS (minor changes in response to referee

Tetrahedral colloidal clusters from random parking of bidisperse spheres

Using experiments and simulations, we investigate the clusters that form when colloidal spheres stick irreversibly to -- or "park" on -- smaller spheres. We use either oppositely charged particles or particles labeled with complementary DNA sequences, and we vary the ratio $\alpha$ of large to small sphere radii. Once bound, the large spheres cannot rearrange, and thus the clusters do not form dense or symmetric packings. Nevertheless, this stochastic aggregation process yields a remarkably narrow distribution of clusters with nearly 90% tetrahedra at $\alpha=2.45$. The high yield of tetrahedra, which reaches 100% in simulations at $\alpha=2.41$, arises not simply because of packing constraints, but also because of the existence of a long-time lower bound that we call the "minimum parking" number. We derive this lower bound from solutions to the classic mathematical problem of spherical covering, and we show that there is a critical size ratio $\alpha_c=(1+\sqrt{2})\approx 2.41$, close to the observed point of maximum yield, where the lower bound equals the upper bound set by packing constraints. The emergence of a critical value in a random aggregation process offers a robust method to assemble uniform clusters for a variety of applications, including metamaterials.Comment: 24 pages, 6 figure

The abundance and clustering of dark haloes in the standard Lambda CDM cosmogony

Much evidence suggests that we live in a flat Cold Dark Matter universe with a cosmological constant. Accurate analytic formulae are now available for many properties of the dark halo population in such a Universe. Assuming current ``concordance'' values for the cosmological parameters, we plot halo abundance against redshift as a function of halo mass, of halo temperature, of the fraction of cosmic matter in haloes, of halo clustering strength, and of the clustering strength of the z=0 descendants of high redshift haloes. These plots are useful for understanding how nonlinear structure grows in the model. They demonstrate a number of properties which may seem surprising, for example: 10^9 solar mass haloes are as abundant at z=20 as L_* galaxies are today; 10^6K haloes are equally abundant at z=8 and at z=0; 10% of all matter is currently in haloes hotter than 1 keV, while more than half is in haloes too cool to trap photo-ionized gas; 1% of all matter at z=15 is in haloes hot enough to ionise hydrogen; haloes of given mass or temperature are more clustered at higher redshift; haloes with the abundance of present-day L_* galaxies are equally clustered at all z10 are more clustered at z=0 than are L_* galaxies.Comment: 10 pages, 2 ps figures, version to be published in MNRA

Data mining for prediction of length of stay of cardiovascular accident inpatients

The healthcare sector generates large amounts of data on a daily basis. This data holds valuable knowledge that, beyond supporting a wide range of medical and healthcare functions such as clinical decision support, can be used for improving profits and cutting down on wasted overhead. The evaluation and analysis of stored clinical data may lead to the discovery of trends and patterns that can significantly enhance overall understanding of disease progression and clinical management. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a data mining project approach to predict the hospitalization period of cardiovascular accident patients. This provides an effective tool for the hospital cost containment and management efficiency. The data used for this project contains information about patients hospitalized in Cardiovascular Accident’s unit in 2016 for having suffered a stroke. The Weka software was used as the machine learning toolkit.Fundação para a Ciência e a Tecnologia (UID/CEC/00319/2013

Methylseleninic acid promotes antitumour effects via nuclear FOXO3a translocation through Akt inhibition

Selenium supplement has been shown in clinical trials to reduce the risk of different cancers including lung carcinoma. Previous studies reported that the antiproliferative and pro-apoptotic activities of methylseleninic acid (MSA) in cancer cells could be mediated by inhibition of the PI3K pathway. A better understanding of the downstream cellular targets of MSA will provide information on its mechanism of action and will help to optimize its use in combination therapies with PI3K inhibitors. For this study, the effects of MSA on viability, cell cycle, metabolism, apoptosis, protein and mRNA expression, and reactive oxygen species production were analysed in A549 cells. FOXO3a subcellular localization was examined in A549 cells and in stably transfected human osteosarcoma U2foxRELOC cells. Our results demonstrate that MSA induces FOXO3a nuclear translocation in A549 cells and in U2OS cells that stably express GFP-FOXO3a. Interestingly, sodium selenite, another selenium compound, did not induce any significant effects on FOXO3a translocation despite inducing apoptosis. Single strand break of DNA, disruption of tumour cell metabolic adaptations, decrease in ROS production, and cell cycle arrest in G1 accompanied by induction of apoptosis are late events occurring after 24h of MSA treatment in A549 cells. Our findings suggest that FOXO3a is a relevant mediator of the antiproliferative effects of MSA. This new evidence on the mechanistic action of MSA can open new avenues in exploiting its antitumour properties and in the optimal design of novel combination therapies. We present MSA as a promising chemotherapeutic agent with synergistic antiproliferative effects with cisplatin. (C) 2015 Elsevier Ltd. All rights reserved.Ministerio de Ciencia e Innovacion, Spain [SAF2011-25726]; Agencia de Gestio d'Ajuts Universitaris i de Recerca (AGAUR)-Generalitat de Catalunya [2014SGR1017]; Ministerio de Economia y Competitividad, Spain [SAF2014-56059-R]; Fundacao para a Ciencia e a Tecnologia (FCT) Research Center [UID/BIM/04773/2013CBMR 1334]; National Institute of Health, USA [1R01CA118434-01A2, 1P01CA163223-01A1]; National Science Foundation, USA [EPS-0447479]; FCT [SFRH/BPD/84634/2012]; prize ICREA Academia for excellence in research; ICREA Foundation-Generalitat de Cataluny

The congested multicommodity network design problem

This paper studies a version of the fixed-charge multicommodity network design problem where in addition to the traditional costs of flow and design, congestion at nodes is explicitly considered. The problem is initially modeled as a nonlinear integer programming formulation and two solution approaches are proposed: (i) a reformulation of the problem as a mixed integer second order cone program to optimally solve the problem for small to medium scale problem instances, and (ii) an evolutionary algorithm using elements of iterated local search and scatter search to provide upper bounds. Extensive computational results on new benchmark problem instances and on real case data are presented