Dash Sylvereye:A Python Library for Dashboard-Driven Visualization of Large Street Networks

State-of-the-art open graph visualization tools like Gephi, KeyLines, and Cytoscape are not suitable for studying street networks with thousands of roads since they do not support simultaneously polylines for edges, navigable maps, GPU-accelerated rendering, interactivity, and the means for visualizing multivariate data. To fill this gap, we present Dash Sylvereye: a new Python library to produce interactive visualizations of primal street networks on top of tiled web maps. Thanks to its integration with the Dash framework, Dash Sylvereye can be used to develop web dashboards around temporal and multivariate street data. This is achieved by coordinating the various elements of a Dash Sylvereye visualization with other plotting and UI components provided by Dash. Additionally, Dash Sylvereye provides convenient functions to easily import OpenStreetMap street topologies obtained with the OSMnx library. Moreover, Dash Sylvereye uses WebGL for GPU-accelerated rendering when redrawing the road network. We conduct experiments to assess the performance of Dash Sylvereye on a commodity computer when exploiting software acceleration in terms of frames per second, CPU time, and frame duration. We show that Dash Sylvereye can offer fast panning speeds, close to 60 FPS, and CPU times below 20 ms, for street networks with thousands of edges, and above 24 FPS, and CPU times below 40 ms, for networks with dozens of thousands of edges. Additionally, we conduct a performance comparison against two state-of-the-art street visualization tools. We found Dash Sylvereye to be competitive when compared to the state-of-the-art visualization libraries Kepler.gl and city-roads. Finally, we describe a web dashboard application that exploits Dash Sylvereye for the analysis of a SUMO vehicle traffic simulation

Dash Sylvereye:A WebGL-powered Library for Dashboard-driven Visualization of Large Street Networks

State-of-the-art open network visualization tools like Gephi, KeyLines, and Cytoscape are not suitable for studying street networks with thousands of roads since they do not support simultaneously polylines for edges, navigable maps, GPU-accelerated rendering, interactivity, and the means for visualizing multivariate data. To fill this gap, the present paper presents Dash Sylvereye: a new Python library to produce interactive visualizations of primal street networks on top of tiled web maps. Thanks to its integration with the Dash framework, Dash Sylvereye can be used to develop web dashboards around temporal and multivariate street data by coordinating the various elements of a Dash Sylvereye visualization with other plotting and UI components provided by the Dash framework. Additionally, Dash Sylvereye provides convenient functions to easily import OpenStreetMap street topologies obtained with the OSMnx library. Moreover, Dash Sylvereye uses WebGL for GPU-accelerated rendering when redrawing the road network. We conduct experiments to assess the performance of Dash Sylvereye on a commodity computer when exploiting software acceleration in terms of frames per second, CPU time, and frame duration. We show that Dash Sylvereye can offer fast panning speeds, close to 60 FPS, and CPU times below 20 ms, for street networks with thousands of edges, and above 24 FPS, and CPU times below 40 ms, for networks with dozens of thousands of edges. Additionally, we conduct a performance comparison against two state-of-the-art street visualization tools. We found Dash Sylvereye to be competitive when compared to the state-of-the-art visualization libraries Kepler.gl and city-roads. Finally, we describe a web dashboard application that exploits Dash Sylvereye for the analysis of a SUMO vehicle traffic simulation

Decoding Online Hate in the United States: A BERT-CNN Analysis of 36 Million Tweets from 2020 to 2022

Since its inception, social media has enabled people worldwide to connect with like-minded individuals and freely express their thoughts and opinions. However, its widespread nature has not only had an immeasurable impact on society but also presented significant challenges. One such challenge is online hate speech. Consequently, the identification of hate speech has recently gained considerable attention, ranging from reactive methods, such as classifying individual posts, to proactive strategies that utilize contextual information to decipher the complex lexicon of online discussions. Despite these efforts, current research lacks a comprehensive analysis of hate speech on Twitter during the crucial 2020-2022 period, marked by significant events such as the COVID-19 pandemic. In this paper, we present a BERT-based model for classifying hate speech. To this end, we collected 36 million tweets posted in the United States on Twitter during this period. We developed, trained, and tested a BERT-based Convolutional Neural Network (BERT-CNN), using it to classify the collected tweets. The classification of this dataset revealed a high incidence of targets motivated by ethnicity, with gender and nationality as other prominent categories. This work provides insightful data on the sentiments of individuals across the United States during the events of 2020-2022

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Ciencias de la Biología y Agronomía

Este volumen I contiene 17 capítulos arbitrados que se ocupan de estos asuntos en Tópicos Selectos de Ciencias de la Biología y Agronomía, elegidos de entre las contribuciones, reunimos algunos investigadores y estudiantes. Se presenta un Estudio Comparativo de los Recursos Hidrológico-Forestales de la Microcuenca de la Laguna de Epatlan, Pue. (1993 a 2014); la Situación Actual de la Mancha de Asfalto en Maíz (Zea mays L.) en los Municipios de Jiquipilas y Ocozocoautla, Chiapas, México; las poblaciones sobresalientes de maíz de la raza Zapalote Chico, en la Región Istmeña de Oaxaca; Se indica el índice de área foliar de cultivo de Chile Poblano mediante dos métodos en condiciones protegidas; Esquivel, Urzúa y Ramírez exploran el efecto de la biofertilización con Azospirillum en el crecimiento y producción de Jitomate; esbozan su artículo sobre la determinación del nivel de Heterosis en híbridos de Maíz para la Comarca Lagunera; una investigación sobre la estabilización de semilla de Solanum lycopersicum durante el almacenamiento y estimulación de la germinación; acotan sobre el CTAB como una nueva opción para la detección de Huanglongbing en cítricos, plantean su evaluación sobre el aluminio y cómo afecta la vida de florero de Heliconia psittacorum; indican sobre el impacto del H-564C, como un híbrido de maíz con alta calidad de proteina para el trópico húmedo de México; presetan su investigación sobre la producción de Piña Cayena Lisa y MD2 (Ananas comosus L.) en condiciones de Loma Bonita, en Oaxaca; acotan sobre el efecto de coberteras como control biológico por conservación contra áfidos en Nogal Pecanero; esbozan sobre la caracterización de cuatro genotipos de Frijol Negro en Martínez de la Torre, Veracruz, México; presentan una caracterización hidroecológica de la microcuenca de Arroyo Prieto, Yuriría, Gto., y alternativas para su restauración ambiental; presentan su investigación sobre el efecto del hongo Beauveria bassiana sobre solubilización de fosfatos y la disponibilidad de fósforo en el suelo; plantean su investigación sobre la Germinación y regeneración in vitro de Epidendrum falcatum LINDL; esbozan su artículo sobre genotipos de frijol negro y su tolerancia a sequía terminal en Veracruz, México

CIBERER : Spanish national network for research on rare diseases: A highly productive collaborative initiative

Altres ajuts: Instituto de Salud Carlos III (ISCIII); Ministerio de Ciencia e Innovación.CIBER (Center for Biomedical Network Research; Centro de Investigación Biomédica En Red) is a public national consortium created in 2006 under the umbrella of the Spanish National Institute of Health Carlos III (ISCIII). This innovative research structure comprises 11 different specific areas dedicated to the main public health priorities in the National Health System. CIBERER, the thematic area of CIBER focused on rare diseases (RDs) currently consists of 75 research groups belonging to universities, research centers, and hospitals of the entire country. CIBERER's mission is to be a center prioritizing and favoring collaboration and cooperation between biomedical and clinical research groups, with special emphasis on the aspects of genetic, molecular, biochemical, and cellular research of RDs. This research is the basis for providing new tools for the diagnosis and therapy of low-prevalence diseases, in line with the International Rare Diseases Research Consortium (IRDiRC) objectives, thus favoring translational research between the scientific environment of the laboratory and the clinical setting of health centers. In this article, we intend to review CIBERER's 15-year journey and summarize the main results obtained in terms of internationalization, scientific production, contributions toward the discovery of new therapies and novel genes associated to diseases, cooperation with patients' associations and many other topics related to RD research

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Capital natural, capital humano y participación de los factores: una revisión de los métodos de medición del crecimiento económico

Este trabajo aporta tres elementos básicos para el análisis del crecimiento económico en Colombia: En primer lugar, para el cálculo de la participación de los factores en el producto, se separa el ingreso de capital físico del ingreso de capital natural y el ingreso del trabajo básico del ingreso de capital humano. Con esta metodología se comprueba que la participación de los factores reproducibles tiene una tendencia creciente como lo sugieren los modelos de innovaciones sesgadas. En segundo lugar, dada la no estacionariedad de la participación de los factores para poder hacer cálculos acerca de la productividad multifactorial se hace necesario encontrar la medida correcta de los factores. Se utiliza un método empírico para la identificación de estas medidas y se aplica a los datos colombianos. Por ´ultimo, utilizando los nuevos cálculos de participación de los factores, se desarrolla un ejercicio de contabilidad de crecimiento que permite identificar con mayor precisión el comportamiento de la productividad total de los factores.We provide three basic elements for the analysis of the economic growth in Colombia: In order to get the factor shares, we separate produced physical capital income from natural capital income and raw labor income from the human capital income. We find that the share of reproducible factors has an increasing trend (as suggested by biased innovations models). Second, given the non-stationarity of the factor shares, in order to compute the multifactorial productivity we need to find correct measures of the factors. We use an empirical method to identify such measures and we apply it to Colombian data. Finally, using the new calculations, we perform an exercise of growth accounting. This procedure allows us to identify with more precision the behavior of total factor productivity

Frailty prevalence and associated factors in the Mexican health and aging study: a comparison of the frailty index and the phenotype

Frailty is a relatively new phenomenon described mainly in the older population. There are a number of different tools that aim at categorizing an older adult as frail. Two of the main tools for this purpose are the Fried's frailty phenotype (FFP) and the frailty index (FI). The aim of this report is to determine the prevalence of frailty and associated factors using both FFP and the FI.Secondary analysis of 1108 individuals aged 60 or older is participating in the third (2012) wave from the Mexican Health and Aging Study (MHAS). The FFP and the FI were constructed and a set of variables from different domains were used to explore associations. Domains included were: socio-demographic, health-related, and psychological factors. Regarding prevalence, concordance was tested with a kappa statistic. To test significant associations when classifying with each of the tools, multiple logistic regression models were fitted.Mean (SD) age was 69.8 (7.6) years, and 54.6% (n=606) were women. The prevalence of frailty with FFP was 24.9% (n=276) while with FI 27.5% (n=305). Kappa statistics for concordance between tools was 0.34 (

An affordable 3D-printed positioner fixture improves the resolution of conventional milling for easy prototyping of acrylic microfluidic devices.

International audienceWe present a simple and low-cost positioner fixture to improve the fabrication resolution of acrylic microchannels using conventional milling machines. The positioner fixture is a mechatronic platform that consists of three piezoelectric actuators assembled in a housing made of 3D printer parts. The upper part of the housing is raised by the simultaneous actuation of the piezoelectric elements and by the deformation of 3D-printed hinge-shaped supports. The vertical positioning (Z-axis) can be controlled with a resolution of 500 nm and an accuracy of ± 1.5 µm; in contrast, conventional milling machines can achieve resolutions of 10 to 35 µm. Through simulations, we found that 3D-printed hinges can deform to reach heights up to 27 µm without suffering any mechanical or structural damage. To demonstrate the capabilities of our fixture we fabricated microfluidic devices with three weir filters that selectively capture microbeads of 3, 6 and 10 µm. We used a similar weir filter design to implement a bead-based immunoassay. Our positioner fixture increases the resolution of conventional milling machines, thus enabling the fast and easy fabrication of thermoplastic fluidic devices that require finer microstructures in their design