Coherent Patterning of Matter Waves with Subwavelength Localization

We propose the Subwavelength Localization via Adiabatic Passage (SLAP) technique to coherently achieve state-selective patterning of matter waves well beyond the diffraction limit. The SLAP technique consists in coupling two partially overlapping and spatially structured laser fields to three internal levels of the matter wave yielding state-selective localization at those positions where the adiabatic passage process does not occur. We show that by means of this technique matter wave localization down to the single nanometer scale can be achieved. We analyze in detail the potential implementation of the SLAP technique for nano-lithography with an atomic beam of metastable Ne* and for coherent patterning of a two-component 87Rb Bose-Einstein condensate.Comment: 6 pages, 5 figure

Hierarchical information fusion for decision making in craniofacial superimposition

Craniofacial superimposition is one of the most important skeleton-based identification methods. The process studies the possible correspondence between a found skull and a candidate (missing person) through the superimposition of the former over a variable number of images of the face of the latter. Within craniofacial superimposition we identified three different stages, namely: (1) image acquisition-processing and landmark location; (2) skull-face overlay; and (3) decision making. While we have already proposed and validated an automatic skull-face overlay technique in previous works, the final identification stage, decision making, is still performed manually by the expert. This consists of the determination of the degree of support for the assertion that the skull and the ante-mortem image belong to the same person. This decision is made through the analysis of several criteria assessing the skull-face anatomical correspondence based on the resulting skull-face overlay. In this contribution, we present a hierarchical framework for information fusion to support the anthropologist expert in the decision making stage. The main goal is the automation of this stage based on the use of several skull-face anatomical criteria combined at different levels by means of fuzzy aggregation functions. We have implemented two different experiments for our framework. The first aims to obtain the most suitable aggregation functions for the system and the second validates the proposed framework as an identification system. We tested the framework with a dataset of 33 positive and 411 negative identification instances. The present proposal is the first automatic craniofacial superimposition decision support system evaluated in an objective and statistically meaningful way. © 2017 Elsevier B.V

Renormalization vs Strong Form Factors for One Boson Exchange Potentials

We analyze the One Boson Exchange Potential from the point of view of Renormalization theory. We show that the nucleon-meson Lagrangean while predicting the NN force does not predict the NN scattering matrix nor the deuteron properties unambiguously due to the appearance of short distance singularities. While the problem has traditionally been circumvented by introducing vertex functions via phenomenological strong form factors, we propose to impose physical renormalization conditions on the scattering amplitude at low energies. Working in the large Nc approximation with pi,sigma,rho and omega mesons, we show that, once these conditions are applied, results for low energy phases of proton-neutron scattering as well as deuteron properties become largely insensitive to the form factors and to the vector mesons and yield a reasonable agreement with the data, for realistic values of the coupling constants.Comment: 30 pages, 17 fig

Sensitivity and representativeness of One-Health surveillance for diseases of zoonotic potential at health facilities relative to household visits in rural Guatemala

Most human and animal disease notification systems are unintegrated and passive, resulting in underreporting. Active surveillance can complement passive efforts, but because they are resource-intensive, their attributes must be evaluated. We assessed the sensitivity and representativeness of One-Health surveillance conducted at health facilities compared to health facilities plus monthly household visits in three rural communities of Guatemala. From September 2017 to November 2018, we screened humans for acute diarrheal, febrile and respiratory infectious syndromes and canines, swine, equines and bovines for syndromic events or deaths. We estimated the relative sensitivity as the incidence rate ratio of detecting an event in health facility surveillance compared to household surveillance from Poisson models. We used interaction terms between the surveillance method and sociodemographic factors or time trends to assess effect modification as a measure of relative representativeness. We used generalized additive models with smoothing splines to model incidence over time by surveillance method. We randomized 216 households to health facility surveillance and 198 to health facility surveillance plus monthly household visits. Health facility surveillance alone was less sensitive than when combined with household surveillance by 0.42 (95% CI: 0.34, 0.53), 0.56 (95% CI: 0.39, 0.79), 0.02 (95% CI: 0.00, 0.10), 0.28 (95% CI: 0.15, 0.50) and 0.22 (95% CI: 0.03, 0.92) times for human acute infections, human severe acute infections, and deaths in canines, swine and equines, respectively. Health facility surveillance alone underrepresented Spanish speakers (interaction p-value = 0.0003) and persons in higher economic assets (interaction p-values = 0.0008). The trend in incidence over time was different between the two study groups, with a larger decrease in the group with household surveillance (all interaction p-values <0.10). Surveillance at health facilities under ascertains syndromes in humans and animals which leads to underestimation of the burden of zoonotic disease. The magnitude of under ascertainment was differentially by sociodemographic factors, yielding an unrepresentative sample of health events. However, it is less time-intensive, thus might be sustained over time longer than household surveillance. The choice between methodologies should be evaluated against surveillance goals and available resources

Human mesenchymal stem cells growth and osteogenic differentiation on piezoelectric poly(vinylidene fluoride) microsphere substrates

The aim of this work was to determine the influence of the biomaterial environment on human mesenchymal stem cell (hMSC) fate when cultured in supports with varying topography. Poly(vinylidene fluoride) (PVDF) culture supports were prepared with structures ranging between 2D and 3D, based on PVDF films on which PVDF microspheres were deposited with varying surface density. Maintenance of multipotentiality when cultured in expansion medium was studied by flow cytometry monitoring the expression of characteristic hMSCs markers, and revealed that cells were losing their characteristic surface markers on these supports. Cell morphology was assessed by scanning electron microscopy (SEM). Alkaline phosphatase activity was also assessed after seven days of culture on expansion medium. On the other hand, osteoblastic differentiation was monitored while culturing in osteogenic medium after cells reached confluence. Osteocalcin immunocytochemistry and alizarin red assays were performed. We show that flow cytometry is a suitable technique for the study of the differentiation of hMSC seeded onto biomaterials, giving a quantitative reliable analysis of hMSC-associated markers. We also show that electrosprayed piezoelectric poly(vinylidene fluoride) is a suitable support for tissue engineering purposes, as hMSCs can proliferate, be viable and undergo osteogenic differentiation when chemically stimulated.The authors thank the Portuguese Foundation for Science and Technology (FCT) for financial support under project PTDC/EEI-SII/5582/2014, Strategic Funding UID/FIS/04650/2013 and grants SFRH/BPD/90870/2012 (C.R.) and SFRH/BPD/121526/2016 (D.M.C). The authors acknowledge funding by the Spanish Ministry of Economy and Competitiveness (MINECO) through the project MAT2016-76039-C4-3-R (AEI/FEDER, UE) and from the Basque Government Industry Department under the ELKARTEK program. JLGR, LC, RSS and AS acknowledge funding by the Conselleria de Educación, Investigación, Cultura y Deporte of the Generalitat Valenciana through PROMETEO/2016/063 project. CIBER-BBN is an initiative funded by the VI National R&D&i Plan 2008–2011, Iniciativa Ingenio 2010, Consolider Program, CIBER Actions and financed by the Instituto de Salud Carlos III with assistance from the European Regional Development. This work was partially financed with FEDER funds (CIBERONC (CB16/12/00284)). The authors acknowledge the assistance and advice of Electron Microscopy Service of the UPVinfo:eu-repo/semantics/publishedVersio

Ownership and control in a competitive industry

We study a differentiated product market in which an investor initially owns a controlling stake in one of two competing firms and may acquire a non-controlling or a controlling stake in a competitor, either directly using her own assets, or indirectly via the controlled firm. While industry profits are maximized within a symmetric two product monopoly, the investor attains this only in exceptional cases. Instead, she sometimes acquires a noncontrolling stake. Or she invests asymmetrically rather than pursuing a full takeover if she acquires a controlling one. Generally, she invests indirectly if she only wants to affect the product market outcome, and directly if acquiring shares is profitable per se. --differentiated products,separation of ownership and control,private benefits of control

Evolutionary discriminative confidence estimation for spoken term detection

The final publication is available at Springer via http://dx.doi.org/10.1007/s11042-011-0913-zSpoken term detection (STD) is the task of searching for occurrences of spoken terms in audio archives. It relies on robust confidence estimation to make a hit/false alarm (FA) decision. In order to optimize the decision in terms of the STD evaluation metric, the confidence has to be discriminative. Multi-layer perceptrons (MLPs) and support vector machines (SVMs) exhibit good performance in producing discriminative confidence; however they are severely limited by the continuous objective functions, and are therefore less capable of dealing with complex decision tasks. This leads to a substantial performance reduction when measuring detection of out-of-vocabulary (OOV) terms, where the high diversity in term properties usually leads to a complicated decision boundary. In this paper we present a new discriminative confidence estimation approach based on evolutionary discriminant analysis (EDA). Unlike MLPs and SVMs, EDA uses the classification error as its objective function, resulting in a model optimized towards the evaluation metric. In addition, EDA combines heterogeneous projection functions and classification strategies in decision making, leading to a highly flexible classifier that is capable of dealing with complex decision tasks. Finally, the evolutionary strategy of EDA reduces the risk of local minima. We tested the EDA-based confidence with a state-of-the-art phoneme-based STD system on an English meeting domain corpus, which employs a phoneme speech recognition system to produce lattices within which the phoneme sequences corresponding to the enquiry terms are searched. The test corpora comprise 11 hours of speech data recorded with individual head-mounted microphones from 30 meetings carried out at several institutes including ICSI; NIST; ISL; LDC; the Virginia Polytechnic Institute and State University; and the University of Edinburgh. The experimental results demonstrate that EDA considerably outperforms MLPs and SVMs on both classification and confidence measurement in STD, and the advantage is found to be more significant on OOV terms than on in-vocabulary (INV) terms. In terms of classification performance, EDA achieved an equal error rate (EER) of 11% on OOV terms, compared to 34% and 31% with MLPs and SVMs respectively; for INV terms, an EER of 15% was obtained with EDA compared to 17% obtained with MLPs and SVMs. In terms of STD performance for OOV terms, EDA presented a significant relative improvement of 1.4% and 2.5% in terms of average term-weighted value (ATWV) over MLPs and SVMs respectively.This work was partially supported by the French Ministry of Industry (Innovative Web call) under contract 09.2.93.0966, ‘Collaborative Annotation for Video Accessibility’ (ACAV) and by ‘The Adaptable Ambient Living Assistant’ (ALIAS) project funded through the joint national Ambient Assisted Living (AAL) programme