RODRIGUEZ-SERRANO, PERRONNIN: LABEL EMBEDDING FOR TEXT RECOGNITION 1 Label embedding for text recognition

The standard approach to recognizing text in images consists in first classifying local image regions into candidate characters and then combining them with high-level word models such as conditional random fields (CRF). This paper explores a new paradigm that departs from this bottom-up view. We propose to embed word labels and word images into a common Euclidean space. Given a word image to be recognized, the text recognition problem is cast as one of retrieval: find the closest word label in this space. This common space is learned using the Structured SVM (SSVM) framework by enforcing matching label-image pairs to be closer than non-matching pairs. This method presents the following advantages: it does not require costly pre- or post-processing operations, it allows for the recognition of never-seen-before words and the recognition process is efficient. Experiments are performed on two challenging datasets (one of license plates and one of scene text) and show that the proposed method is competitive with standard bottom-up approaches to text recognition. 1 Introduction and related wor

Building uncertainty models on top of black-box predictive APIs

With the commoditization of machine learning, more and more off-the-shelf models are available as part of code libraries or cloud services. Typically, data scientists and other users apply these models as ''black boxes'' within larger projects. In the case of regressing a scalar quantity, such APIs typically offer a predict() function, which outputs the estimated target variable (often referred to as y¿ or, in code, y_hat). However, many real-world problems may require some sort of deviation interval or uncertainty score rather than a single point-wise estimate. In other words, a mechanism is needed with which to answer the question ''How confident is the system about that prediction?'' Motivated by the lack of this characteristic in most predictive APIs designed for regression purposes, we propose a method that adds an uncertainty score to every black-box prediction. Since the underlying model is not accessible, and therefore standard Bayesian approaches are not applicable, we adopt an empirical approach and fit an uncertainty model using a labelled dataset (x, y) and the outputs y¿ of the black box. In order to be able to use any predictive system as a black box and adapt to its complex behaviours, we propose three variants of an uncertainty model based on deep networks. The first adds a heteroscedastic noise component to the black-box output, the second predicts the residuals of the black box, and the third performs quantile regression using deep networks. Experiments using real financial data that contain an in-production black-box system and two public datasets (energy forecasting and biology responses) illustrate and quantify how uncertainty scores can be added to black-box outputs

Dynamic Model Derivation of a 3RRR Robot Based in Screw Theory

In this article a technique to obtain a dynamic model of a 3RRR robot from its kinematic model based on screw theory is proposed, which allows to obtain the open or closed robot kinematics. First the kinematic model is obtained in a compact form and then the dynamic model is obtained from the Euler Lagrange method, with this the simplicity and compactness characteristics are transferred to the dynamic model. The dynamic model is obtained initially for the actuated joints and then for the effector coordinates through its interrelations. To prove the effectiveness of this theoretical derivation the obtained model is tested with a proportional-derivative controller (PD) because it provides a simple control strategy that can be extended later to more effective controllers

New tracheal stainless steel stent pilot study: twelve month follow-up in a rabbit model

Background Canine tracheal collapse is a complex airway pathology without promising treatment results. Currently nitinol stents are the best surgical option; however, some professionals are doubting if stent placement is the best option due to the associated complications. Objective Determine the technical feasibility, safety, and long-term follow-up after the implantation of a new tracheal stent designed for canine tracheal collapse. Methods Thirteen healthy, adult female New Zealander rabbits were involved in this pilot study.A new intra-tracheal device (Reference number 902711 patent registered as CasMin-Twine) was implanted in ten animals. Deployment was performed under general anesthesia, making a puncture incision via a 21 Gauge needle in the intra-tracheal space where the stent was introduced with a screwing process. The device was fixed to the tracheal wall with a non-absorbable suture. Computerized Tomography (CT) and an endoscopy to study structural abnormalities were performed after 30, 90 and 365 days after stent placement. Results Technical and clinical success was 100%. There was no significant change in behavior or respiratory disorders. CT studies showed no significant alterations. After the 30 days, 60% of the animals showed partial endothelization in the endoscopy study, and only one animal still presented partial endothelization after 12 months. Mucus accumulation was only present in 40% of cases and classified as low, without respiratory consequences. Only one animal presented a single granuloma at caudal stent tip. Conclusions This new tracheal stent (CasMin-Twine) is an effective and safe procedure with promising results, and also shows the possibility of removing the device after endothelization has been produced. New studies should be carried out to evaluate the effectiveness in patients with tracheomalacia. Clinical Significance/Impact This new product can give veterinarians a new option of treatment for this complicated pathology. Minimizing specific equipment for its deployment, CasMin-Twine will be more accessible for all professionals

Catalog and distribution atlas of the Scarabaeoidea (Insecta: Coleoptera) of El Salvador

Menos del 1% de la literatura sobre la biodiversidad de El Salvador es sobre invertebrados terrestres, lo que limita nuestro conocimiento de la diversidad, riqueza y distribución de este grupo en el territorio. Los Scarabaeoidea son megadiversos en múltiples ecosistemas y cumplen muchas funciones. Este trabajo tiene como objetivo catalogar los Scarabaeoidea en El Salvador. Se realizó una revisión exhaustiva de la literatura publicada y se revisaron numerosas colecciones entomológicas con material relevante. Se construyeron mapas para visualizar la distribución conocida de cada especie en el país. Existen 295 especies de escarabajos (incluyendo 19 nuevos registros en el país) representando 106 géneros en 7 familias en El Salvador. Se conocen seis especies precursoras. Veintidós especies se descartan como presentes en El Salvador, ya sea porque no son especies válidas o por identificaciones erróneas o registros dudosos. Este trabajo es la primera aproximación al conocimiento de los Scarabaeoidea en El Salvador, un territorio que usualmente se considera de nula importancia para la conservación de la biodiversidad regional debido a su reducida superficie, alta tasa de deforestación y sobrepoblación. Los resultados de este trabajo refuerzan la necesidad de realizar prospección biológica en el territorio para conocer, conservar y proteger la biodiversidad remanente. 2023 Universidad Nacional Autónoma de México. Todos los derechos reservados.Less than 1% of the literature on El Salvador s biodiversity is about terrestrial invertebrates, which limits our knowledge of this group s diversity, richness, and distribution in the territory. Scarabaeoidea are megadiverse in multiple ecosystems and perform many functions. This work aims to catalog the Scarabaeoidea in El Salvador. We conducted an exhaustive review of published literature and reviewed numerous entomological collections with relevant material. Maps were constructed to visualize the known distribution of each species in the country. There are 295 scarab beetle species (including 19 new country records) representing 106 genera in 7 families in El Salvador. Six precinctive species are known. Twenty-Two species are discarded as occurring in El Salvador, either because they are not valid species or because of misidentifications or dubious records. This work is the first approach to knowing the Scarabaeoidea in El Salvador, a territory that is usually considered of no importance for the conservation of regional biodiversity due to its small area, high rate of deforestation, and overpopulation. The results of this work reinforce the need for biological prospecting in the territory to know, conserve, and protect the remaining biodiversity. © 2023 Universidad Nacional Autonoma de Mexico. All rights reserved

Reticulocyte Maturation Parameters Are Reliable Early Predictors of Hematopoietic Engraftment after Allogeneic Stem Cell Transplantation

AbstractEarly detection of donor-derived hematopoietic restoration after allogeneic stem cell transplantation (allo-SCT) is a crucial issue in the management of heavily immunocompromised patients. The aim of this prospective study was to validate our previously defined cutoff values for reticulocyte maturation parameters as early predictors of hematopoietic engraftment. Importantly, the effect of clinical variables in reticulocyte engraftment was also sought. For this purpose, we prospectively studied 136 consecutive patients undergoing allo-SCT from related (n = 89) or unrelated (n = 47) donors. High fluorescence reticulocytes (RETH), immature reticulocyte fraction (IRF), mean fluorescence index (MFI), and mean reticulocyte volume (MRV) were automatically measured in peripheral blood samples drawn on a daily basis. We previously defined reticulocyte engraftment when MFI ≥10, RETH ≥3%, IRF ≥10%, and MRV ≥110 fL. Median neutrophil engraftment was 18 days (range, 10-35 days); for reticulocyte parameters, the values were 14 days for IRF (range, 7-45 days), 14 days for MFI (range, 7-43 days), 15 days for RETH (range, 7-43 days), and 21 days for MRV (range, 9-74 days). These differences reached statistical significance for MFI and IRF when compared with standard neutrophil recovery, even when analyzing siblings or unrelated donors separately. In univariate analysis, donor-recipient ABO disparity adversely influenced erythroid engraftment (P = .04 for IRF, P = .03 for MFI), but the infusion of >2.9 × 106/kg of CD34+ cells was associated with a shorter time to reach erythroid engraftment (P = .02 for IRF and MFI). In Cox regression analysis, ≥100/μL neutrophils and IRF ≥10% were predictive parameters for standard neutrophil engraftment. Based on these findings, we suggest that serial measurement of IRF or MFI should be routinely used to trace hematopoietic restoration after allo-SCT because these preceded standard neutrophil recovery by a median of 4 days and are therefore very useful to make clinical decisions