Exploring research on ecotechnology through artificial intelligence and bibliometric maps

Ecotechnology, quintessential for crafting sustainable socio-environmental strategies, remains tantalizingly uncharted. Our analysis, steered by the nuances of machine learning and augmented by bibliometric insights, delineates the expansive terrain of this domain, elucidates pivotal research themes and conundrums, and discerns the vanguard nations in this field. Furthermore, we deftly connect our discoveries to the United Nations' 2030 Sustainable Development Goals, thereby accentuating the profound societal ramifications of ecotechnology.

Self-Organizing Maps to Multidimensionally Characterize Physical Profiles in Older Adults

The aim of this study is to automatically analyze, characterize and classify physical performance and body composition data of a cohort of Mexican community-dwelling older adults. Self-organizing maps (SOM) were used to identify similar profiles in 562 older adults living in Mexico City that participated in this study. Data regarding demographics, geriatric syndromes, comorbidities, physical performance, and body composition were obtained. The sample was divided by sex, and the multidimensional analysis included age, gait speed over height, grip strength over body mass index, one-legged stance, lean appendicular mass percentage, and fat percentage. Using the SOM neural network, seven profile types for older men and women were identified. This analysis provided maps depicting a set of clusters qualitatively characterizing groups of older adults that share similar profiles of body composition and physical performance. The SOM neural network proved to be a useful tool for analyzing multidimensional health care data and facilitating its interpretability. It provided a visual representation of the non-linear relationship between physical performance and body composition variables, as well as the identification of seven characteristic profiles in this cohort.

The metrix of the international impact of Mathematics: to determine the leadership through scientific impact

El propósito de este estudio es determinar los perfiles de impacto científico de los países, instituciones y autores más destacados en el campo de las matemáticas a nivel internacional. Los datos se colectaron a partir de la herramienta Essential Science Indicators. Se utilizó el software LabSOM para determinar el perfil bibliométrico de los países, las instituciones y los autores más destacados sobre la base de un análisis multiparamétrico. Los resultados muestran que no coinciden los líderes de cada indicador bibliométrico en ninguno de los niveles de agregación analizados y demuestran que esos indicadores no deben aplicarse de manera uniforme en todos los campos para medir el desarrollo científico de las disciplinas, porque cada una muestra tasas de crecimiento distintas. La evaluación multiparamétrica permite la determinación simultánea de varios indicadores bibliométricos. Este método constituye una herramienta novedosa para el análisis multiparamétrico computacional y permite la aplicación de minería de datos bibliométricos a la toma de decisiones en el más alto nivel de la organización. La novedad del estudio radica no sólo en su alcance internacional y en la actualidad de sus datos, sino también en el uso de nuevos indicadores de impacto científico en la Matemática.

Engineered Mycobacterium tuberculosis antigen assembly into core-shell nanobeads for diagnosis of tuberculosis

Despite recent advances in diagnosis, tuberculosis (TB) remains one of the ten leading causes of death worldwide. Here, we engineered Mycobacterium tuberculosis (Mtb) proteins (ESAT6, CFP10, and MTB7.7) to self-assemble into core-shell nanobeads for enhanced TB diagnosis. Respective purified Mtb antigen-coated polyester beads were characterized and their functionality in TB diagnosis was tested in whole blood cytokine release assays. Sensitivity and specificity were studied in 11 pulmonary TB patients (PTB) and 26 healthy individuals composed of 14 Tuberculin Skin Test negative (TSTn) and 12 TST positive (TSTp). The production of 6 cytokines was determined (IFNγ, IP10, IL2, TNFα, CCL3, and CCL11). To differentiate PTB from healthy individuals (TSTp + TSTn), the best individual cytokines were IL2 and CCL11 (>80% sensitivity and specificity) and the best combination was IP10 + IL2 (>90% sensitivity and specificity). We describe an innovative approach using full-length antigens attached to biopolyester nanobeads enabling sensitive and specific detection of human TB.

National Cancer Institute scientific production scientometric analysis

Introduction

Scientometrics analyzes scientific publications through bibliometric and computational techniques, whereby productivity and impact indicators are generated.

Objective

To propose a multidimensional methodology in order to obtain the scientometric profile of the National Cancer Institute (INCan), Mexico, and rank it with regard to other national health institutions.

Method

Using the LabSOM software and the ViBlioSOM methodology based on artificial neural networks, the INCan scientific production indexed in the Web of Science from 2007 to 2017 was analyzed. The multidimensional scientometric profile of the Institute was obtained and compared with that of other national health institutions.

Results

In terms of productivity, INCan ranks fourth among the 10 Mexican public health institutions indexed in the Web of Science; in the normalized impact ranking, it ranks sixth. Although out of 1323 articles 683 (51.62 %) did not receive citations, 11 articles classified as excellent (0.83 %) obtained 24 % of 11,932 citations and, consequently, INCan normalized impact rate showed a mean productivity higher than the world mean.

Conclusion

Multidimensional analysis with the proposed neural network enables obtaining a more reliable and comprehensive absolute and relative institutional scientiometric profile than that derived from measuring isolated variables.

Revisión bibliométrica de las Ciencias de la Información en América Latina y el Caribe

La bibliometría se ha utilizado para la evaluación de las diferentes áreas del conocimiento, con el objetivo de definir políticas de evaluación a los investigadores, así como definir líneas de investigación. Las ciencias aplicadas generalmente han sido las más estudiadas, no obstante, se conoce que el caso de las ciencias sociales tiene un comportamiento diferente. Por ello esta investigación describe el comportamiento bibliométrico de la temática Ciencias de la Información en América Latina y el Caribe; teniendo en cuenta las dimensiones de la producción científica, el impacto, la colaboración y la evaluación bibliométrica a nivel individual. Se utilizó para el análisis bibliométrico de los artículos científicos elaborados en la base de datos Scopus; en el periodo 2008-2012 en relación con la materia de Ciencias de la Información. Para el procesamiento y visualización de los datos, se utilizaron los programas Ucinet y Bibexcel, respectivamente. Se determinó que los investigadores de América Latina tienen el hábito de publicar sus resultados de investigación en revistas regionales. Aunque la colaboración nacional es predominante, Europa es el continente que estableció una cooperación más estrecha con América Latina. Brasil se destacó en las dimensiones de la producción, el impacto y la colaboración. La mayor influencia en la comunidad científica se obtuvo con las revistas de alto factor de impacto. Se concluye que se debe fortalecer la cultura de la publicación por parte de los investigadores de la región en revistas internacionales.AbstractBibliometrics was used to evaluate the different areas of knowledge, with the aim of defining policies for evaluation researchers and define lines of research. The applied sciences have generally been the most studied, however it is known that the case of the social sciences have a different behavior. That is why this research describes the behavior of the subject bibliometric Information Sciences in Latin America and the Caribbean; taking into account the dimensions of scientific production, impact, collaboration and bibliometric assessment at the individual level. Bibliometric analysis from scientific papers processed in the Scopus database; in the period 2008 to 2012 related to the subject area of Information Sciences were used as techniques. For processing and displaying was used the Bibexcel and the Ucinet programs. It was determined that Latin American researchers have the habit of publishing their research results in regional magazines. Although national collaboration is predominantly, Europe is the continent which established closer cooperation with Latin America. Brazil stood out in the dimensions of production, impact and collaboration. The greatest influence on the scientific community was obtained with the journals of high impact factor. It is concluded that should strengthen the culture of publication by researchers from the region in international journals.

Diagnosis of breast cancer using Bayesian networks: a case study

We evaluate the effectiveness of seven Bayesian network classifiers as potential tools for the diagnosis of breast cancer using two real-world databases containing fine-needle aspiration of the breast lesion cases collected by a single observer and multiple observers, respectively. The results show a certain ingredient of subjectivity implicitly contained in these data: we get an average accuracy of 93.04% for the former and 83.31% for the latter. These findings suggest that observers see different things when looking at the samples in the microscope; a situation that significantly diminishes the performance of these classifiers in diagnosing such a disease.