Hierarchical stochastic graphlet embedding for graph-based pattern recognition

This is the final version. Available on open access from Springer via the DOI in this recordDespite being very successful within the pattern recognition and machine learning community, graph-based methods are often unusable with many machine learning tools. This is because of the incompatibility of most of the mathematical operations in graph domain. Graph embedding has been proposed as a way to tackle these difficulties, which maps graphs to a vector space and makes the standard machine learning techniques applicable for them. However, it is well known that graph embedding techniques usually suffer from the loss of structural information. In this paper, given a graph, we consider its hierarchical structure for mapping it into a vector space. The hierarchical structure is constructed by topologically clustering the graph nodes, and considering each cluster as a node in the upper hierarchical level. Once this hierarchical structure of graph is constructed, we consider its various configurations of its parts, and use stochastic graphlet embedding (SGE) for mapping them into vector space. Broadly speaking, SGE produces a distribution of uniformly sampled low to high order graphlets as a way to embed graphs into the vector space. In what follows, the coarse-to-fine structure of a graph hierarchy and the statistics fetched through the distribution of low to high order stochastic graphlets complements each other and include important structural information with varied contexts. Altogether, these two techniques substantially cope with the usual information loss involved in graph embedding techniques, and it is not a surprise that we obtain more robust vector space embedding of graphs. This fact has been corroborated through a detailed experimental evaluation on various benchmark graph datasets, where we outperform the state-of-the-art methods.European Union Horizon 2020Ministerio de Educación, Cultura y Deporte, SpainGeneralitat de Cataluny

Accuracy of the fetal cerebroplacental ratio for the detection of intrapartum compromise in nonsmall fetuses.

OBJECTIVE: To study the accuracy of the cerebroplacental ratio (CPR) for the detection of intrapartum fetal compromise (IFC) in fetuses growing over the 10th centile. METHODS: This was a prospective study of 569 nonsmall fetuses attending the day hospital unit of a tertiary hospital that underwent an ultrasound examination at 36-40 weeks, and were delivered within 4 weeks of examination. IFC was defined as a composite of: abnormal intrapartum fetal heart rate or intrapartum fetal scalp pH < 7.20 requiring cesarean section, neonatal umbilical cord pH < 7.20, 5' Apgar score < 7 and postpartum admission to neonatal or pediatric intensive care units. The accuracy of CPR for the prediction of IFC was calculated alone and in combination with other perinatal parameters using univariate and multivariate logistic regression models, which alternatively included the onset of labor to evaluate the influence of induction of labor (IOL) on IFC and a brief composite adverse outcome of two parameters to prove the strength of the approach. RESULTS: The incidence of IFC was 17.9%. CPR sensitivity was 30.4% for a false positive rate (FFR) of 10 and 14.7% for a FPP of 5% (AUC = 0.62, p < 0.001). The multivariate analysis showed that only fetal gender and parity increased the predictive accuracy of CPR alone, although the improvement was poor (AUC = 0.67, p < 0.001). No differences were observed using any of the alternative models. Finally, IOL had no influence of IFC. CONCLUSION: Despite their apparent normality, a proportion of fetuses growing over the 10th centile suffer IFC. Some of them are suitable for detection by means of CPR

Table Detection in Invoice Documents by Graph Neural Networks

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.Tabular structures in documents offer a complementary dimension to the raw textual data, representing logical or quantitative relationships among pieces of information. In digital mail room applications, where a large amount of administrative documents must be processed with reasonable accuracy, the detection and interpretation of tables is crucial. Table recognition has gained interest in document image analysis, in particular in unconstrained formats (absence of rule lines, unknown information of rows and columns). In this work, we propose a graph-based approach for detecting tables in document images. Instead of using the raw content (recognized text), we make use of the location, context and content type, thus it is purely a structure perception approach, not dependent on the language and the quality of the text reading. Our framework makes use of Graph Neural Networks (GNNs) in order to describe the local repetitive structural information of tables in invoice documents. Our proposed model has been experimentally validated in two invoice datasets and achieved encouraging results. Additionally, due to the scarcity of benchmark datasets for this task, we have contributed to the community a novel dataset derived from the RVL-CDIP invoice data. It will be publicly released to facilitate future research.European Unio

Decentralizing Science: Towards an Interoperable Open Peer Review Ecosystem using Blockchain

Science publication and its Peer Review system strongly rely on a few major industry players controlling most journals (e.g. Elsevier), databases (e.g. Scopus) and metrics (e.g. JCR Impact Factor), while keeping most articles behind paywalls. Critics to such system include concerns about fairness, quality, performance, cost, unpaid labor, transparency, and accuracy of the evaluation process. The Open Access movement has tried to provide free access to the published research articles, but most of the aforementioned issues remain. In such context, decentralized technologies such as blockchain offer an opportunity to experiment with new models for science production and dissemination relying on a decentralized infrastructure, aiming to tackle multiple of the current system shortcomings. This paper makes a proposal for an interoperable decentralized system for an open peer review ecosystem, relying on emerging distributed technologies such as blockchain and IPFS. Such system, named ``Decentralized Science'' (DecSci), aims to enable a decentralized reviewer reputation system, which relies on an Open Access by-design infrastructure, together with transparent governance processes. Two prototypes have been implemented: a proof-of-concept prototype to validate DecSci's technological feasibility, and a Minimum Viable Product (MVP) prototype co-designed with journal editors. In addition, three evaluations have been carried out: an exploratory survey to assess interest on the issues tackled, a set of interviews to confirm the main problems for editors, and another set of interviews to validate the MVP prototype. Additionally, the paper discusses the multiple interoperability challenges such proposal faces, including an architecture to tackle them. This work finishes with a review of some of the open challenges that this ambitious proposal may face

Chapter 2. The Baix Llobregat (BALL) Demographic Database, between Historical Demography and Computer Vision (nineteenth–twentieth centuries)

The main aims with this book are to compare source materials, databases and research results, as well as creating new opportunities for collaboration in the field of social and population history in the East and the West. All the contributions are based on nominative source material, mainly censuses and vital records, which have been preserved, scanned, transcribed into databases in order to be used for cross-sectional and longitudinal research. The chapters in the first part of this book mostly focus on the construction of nominative databases in Germany, Spain and Romania. The chapters in the second and third part are case studies on the relationship between marriage and fertility; mortality and fertility; marriage behavior and religion; urban mortality; migration, etc. made on the Russian, Austrian, Estonian, Hungarian and Norwegian databases

Towards Stroke Patients' Upper-limb Automatic Motor Assessment Using Smartwatches

Assessing the physical condition in rehabilitation scenarios is a challenging problem, since it involves Human Activity Recognition (HAR) and kinematic analysis methods. In addition, the difficulties increase in unconstrained rehabilitation scenarios, which are much closer to the real use cases. In particular, our aim is to design an upper-limb assessment pipeline for stroke patients using smartwatches. We focus on the HAR task, as it is the first part of the assessing pipeline. Our main target is to automatically detect and recognize four key movements inspired by the Fugl-Meyer assessment scale, which are performed in both constrained and unconstrained scenarios. In addition to the application protocol and dataset, we propose two detection and classification baseline methods. We believe that the proposed framework, dataset and baseline results will serve to foster this research field

Progression of Doppler changes in early-onset small for gestational age fetuses. How frequent are the different progression sequences?

OBJECTIVE: To evaluate the progression of Doppler abnormalities in early-onset fetal smallness (SGA). METHODS: A total of 948 Doppler examinations of the umbilical artery (UA), middle cerebral artery (MCA) and ductus venosus (DV), belonging to 405 early-onset SGA fetuses, were studied, evaluating the sequences of Doppler progression, the interval examination-labor at which Doppler became abnormal and the cumulative sum of Doppler anomalies in relation with labor proximity. RESULTS: The most frequent sequences were that in which only the UA pulsatility index (PI) became abnormal (42.1%) and that in which an abnormal UA PI appeared first, followed by an abnormal MCA PI (24.2%). In general, 71.3% of the fetuses followed the classical progression sequence UA→MCA→DV, mostly in the early stages of growth restriction (84.1%). In addition, the UA PI was the first parameter to be affected (9 weeks before delivery), followed by the MCA PI and the DV PIV (1 and 0 weeks). Finally, the UA PI began to sum anomalies 5 weeks before delivery, while the MCA and DV did it at 3 and 1 weeks before the pregnancy ended. CONCLUSIONS: In early-onset SGA fetuses, Doppler progression tends to follow a predictable order, with sequential changes in the umbilical, cerebral and DV impedances

A Decentralized Publication System for Open Science using Blockchain and IPFS

Science publication and peer review raises concerns about fairness, quality, per-formance, cost or accuracy. The Open Access movements has been unable to fulfill all itspromises, and middlemen publishers can still impose policies and concentrate profits. Thispaper, using emerging distributed technologies such as Blockchain and IPFS, proposes adecentralized publication system for open science. It provides transparent governance, adistributed reviewer reputation system, and open access by-design. The paper concludesreviewing the open challenges of such approach

Insultar con gestos en la Roma antigua y hoy

This paper deals with the use of some emblemes (i. e., gestures which, in a certain culture, have an inequivocal verbal equivalent) in classical Rome and their survival in the present time. We specifically study emblems which express ridicule and insult. Six gestures are analized; four of them were already used in Rome as mocking or insulting gestures (imitating the stork, the ears of an ass, sticking out the tongue and extending the middle finger); furthemore, two gestures have been included that were used in the Roman Antiquity but did not have the mocking meaning that they convey nowadays (the horn-sign and the fig-sign).Este artículo trata sobre el uso de algunos emblemas (esto es, gestos que, en una cultura determinada, tienen un equivalente verbal inequívoco) en la Roma clásica y su pervivencia en la época actual. Son estudiados, en concreto, los emblemas que expresan burla e insulto. Se analizan seis gestos; cuatro de ellos eran ya utilizados en Roma como gestos de mofa o insulto (imitar a la cigüeña, hacer orejas de asno, sacar la lengua y mostrar el dedo corazón); se incluyen además dos gestos que eran usados en la Antigüedad romana, pero no tenían el significado de mofa que poseen en la actualidad (hacer cuernos y el gesto de la higa)