Crossover between the Dense Electron-Hole Phase and the BCS Excitonic Phase in Quantum Dots

Second order perturbation theory and a Lipkin-Nogami scheme combined with an exact Monte Carlo projection after variation are applied to compute the ground-state energy of $6\le N\le 210$ electron-hole pairs confined in a parabolic two-dimensional quantum dot. The energy shows nice scaling properties as N or the confinement strength is varied. A crossover from the high-density electron-hole phase to the BCS excitonic phase is found at a density which is roughly four times the close-packing density of excitons.Comment: Improved variational and projection calculations. 17 pages, 3 ps figures. Accepted for publication in Int. J. Mod. Phys.

Dental Treatment under General Anesthesia in Healthy and Medically Compromised/Developmentally Disabled Children: A Comparative Study

Aim: To compare the type, number of procedures and working time of dental treatment provided under dental general anesthesia (DGA) in healthy and medically compromised/developmentally disabled children (MCDD children). Design: This cross-sectional prospective study involved 80 children divided into two groups of 40 children each. Group 1 consisted of healthy and Group 2 consisted of MCDD children. Results: Healthy children needed more working time than MCDD children, the means being 161±7.9 and 84±5.7 minutes, respectively (P= 0.0001). Operative dentistry and endodontic treatments showed a significant statistical difference (P= 0.0001). The means of procedures were 17±5.0 for healthy children and 11±4.8 for MCDD children (P= 0.0001). Conclusions: Healthy children needed more extensive dental treatment than MCDD children under DGA. The information from this sample of Mexican children could be used as reference for determining trends both within a facility as well as in comparing facilities in cross-population studies

Active galactic nuclei synapses: X-ray versus optical classifications using artificial neural networks

(Abridged) Many classes of active galactic nuclei (AGN) have been defined entirely throughout optical wavelengths while the X-ray spectra have been very useful to investigate their inner regions. However, optical and X-ray results show many discrepancies that have not been fully understood yet. The aim of this paper is to study the "synapses" between the X-ray and optical classifications. For the first time, the new EFLUXER task allowed us to analyse broad band X-ray spectra of emission line nuclei (ELN) without any prior spectral fitting using artificial neural networks (ANNs). Our sample comprises 162 XMM-Newton/pn spectra of 90 local ELN in the Palomar sample. It includes starbursts (SB), transition objects (T2), LINERs (L1.8 and L2), and Seyferts (S1, S1.8, and S2). The ANNs are 90% efficient at classifying the trained classes S1, S1.8, and SB. The S1 and S1.8 classes show a wide range of S1- and S1.8-like components. We suggest that this is related to a large degree of obscuration at X-rays. The S1, S1.8, S2, L1.8, L2/T2/SB-AGN (SB with indications of AGN), and SB classes have similar average X-ray spectra within each class, but these average spectra can be distinguished from class to class. The S2 (L1.8) class is linked to the S1.8 (S1) class with larger SB-like component than the S1.8 (S1) class. The L2, T2, and SB-AGN classes conform a class in the X-rays similar to the S2 class albeit with larger fractions of SB-like component. This SB-like component is the contribution of the star-formation in the host galaxy, which is large when the AGN is weak. An AGN-like component seems to be present in the vast majority of the ELN, attending to the non-negligible fraction of S1-like or S1.8-like component. This trained ANN could be used to infer optical properties from X-ray spectra in surveys like eRosita.Comment: 15 pages, 7 figures, accepted for publication in A&A. Appendix B only in the full version of the paper here: https://dl.dropboxusercontent.com/u/3484086/AGNSynapsis_OGM_online.pd

Modeling and forecasting gender-based violence through machine learning techniques

Gender-Based Violence (GBV) is a serious problem that societies and governments must address using all applicable resources. This requires adequate planning in order to optimize both resources and budget, which demands a thorough understanding of the magnitude of the problem, as well as analysis of its past impact in order to infer future incidence. On the other hand, for years, the rise of Machine Learning techniques and Big Data has led different countries to collect information on both GBV and other general social variables that in one way or another can affect violence levels. In this work, in order to forecast GBV, firstly, a database of features related to more than a decade’s worth of GBV is compiled and prepared from official sources available due to Spain’s open access. Then, secondly, a methodology is proposed that involves testing different methods of features selection so that, with each of the subsets generated, four techniques of predictive algorithms are applied and compared. The tests conducted indicate that it is possible to predict the number of GBV complaints presented to a court at a predictive horizon of six months with an accuracy (Root Median Squared Error) of 0.1686 complaints to the courts per 10,000 inhabitants—throughout the whole Spanish territory—with a Multi-Objective Evolutionary Search Strategy for the selection of variables, and with Random Forest as the predictive algorithm. The proposed methodology has also been successfully applied to three specific Spanish territories of different populations (large, medium, and small), pointing to the presented method’s possible use elsewhere in the world

Exact solutions of an elliptic Calogero--Sutherland model

A model describing N particles on a line interacting pairwise via an elliptic function potential in the presence of an external field is partially solved in the quantum case in a totally algebraic way. As an example, the ground state and the lowest excitations are calculated explicitly for N=2.Comment: 4 pages, 3 figures, typeset with RevTeX 4b3 and AMS-LaTe

Proper motions of the HH1 jet

We describe a new method for determining proper motions of extended objects, and a pipeline developed for the application of this method. We then apply this method to an analysis of four epochs of [S~II] HST images of the HH~1 jet (covering a period of $\sim 20$~yr). We determine the proper motions of the knots along the jet, and make a reconstruction of the past ejection velocity time-variability (assuming ballistic knot motions). This reconstruction shows an "acceleration" of the ejection velocities of the jet knots, with higher velocities at more recent times. This acceleration will result in an eventual merging of the knots in $\sim 450$~yr and at a distance of $\sim 80"$ from the outflow source, close to the present-day position of HH~1.Comment: 12 pages, 8 figure