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The main purpose of manufacturing companies is to achieve the fulfillment of strategies and to increase productivity and competitiveness while adapting to market changes. For this, it is necessary to measure employee and global performance. This article is aimed to analyze the application of fuzzy indicators for measuring employee performance in manufacturing companies, by using a systematic literature review of the works published in scientific databases, from 2008 to 2021. The results show that the use of fuzzy indicators helps to reduce the subjectivity and uncertainty of the evaluator. The application of different fuzzy methods for performance measurement allows to perform an effective evaluation and to make more appropriate decisions with greater impact on global performance. [ABSTRACT FROM AUTHOR]

El artículo analiza Comuna 23, una obra coreográfica del Movimiento en Colectivo (mec), destacando su importancia en la representación y transformación social a través del arte. La pieza utiliza la danza como medio para explorar y expresar las vivencias y desafíos de una localidad imaginaria que simboliza la realidad social y cultural de Cali. Se enfoca en cómo la danza, entrelazada con temas de identidad y resistencia, se convierte en un lenguaje poderoso para la expresión y el cambio social. La obra es un reflejo de la vida urbana en Cali, revelando las tensiones y esperanzas de sus habitantes. La danza, como acto de rebeldía y deriva, permite a los bailarines y al público conectar con experiencias personales y colectivas, desafiando las estructuras sociales existentes. El análisis destaca la relevancia de Comuna 23 en el contexto cultural caleño y su contribución a la discusión sobre la función del arte en la sociedad.

Los inductores de valor son recursos y características que posee una organización para generar valor para sí misma y sus socios, en el marco de una alianza estratégica que les permita alcanzar los objetivos estratégicos. El propósito de este trabajo fue validar un instrumento mediante la consulta a expertos, para conocer cuáles inductores de valor son clave para la gestión de alianzas entre universidades. Se realizó la consulta a 31 jueces que fueron medidos en su idoneidad como expertos mediante el coeficiente de competencia experta; posteriormente, se analizó validez de contenido mediante la V de Aiken y se determinó la confiabilidad del instrumento mediante el cálculo del Alfa de Cronbach y el análisis del Omega de MacDonald. Se obtuvieron quince inductores para la generación de valor que son coincidentes tanto en lo reportado en la literatura como en el proceso de validación con los expertos, así mismo los resultados del Alfa de Cronbach (0,940) y el Omega de MacDonald (0,944), confirman la confiabilidad del instrumento. Teniendo en cuenta lo anterior, se concluye que el instrumento es válido y adecuado para recabar información asociada a los inductores de valor en las organizaciones.

La infancia es una invención de la modernidad, en tanto sensibilidad de la sociedad y la familia frente a los niños, que lleva a otorgarles una importancia no asignada en la antigüedad ni en el medioevo. Benjamin, Agamben, Marcuse y Kohan, autores de la teoría y pedagogía crítica, la comprenden como una experiencia de cambio y de formación no reductible solo a los niños. Por ello, en singular, infancia se entiende como experiencia formativa, y en lugar de estar asociada a concepciones reduccionistas de comprensión biológica, reconoce implicaciones antropológicas, pedagógicas e históricas, tales como: comienzo, despertar, historicidad y lenguaje, y afirma la posibilidad de formación por vía educativa. En plural, infancias, expresan las múltiples materializaciones contextuales, conceptuales y biográficas de la infancia. Por lo anterior, el propósito de este trabajo es comprender que, desde las obras de Benjamin, Agamben, Marcuse y Kohan, la infancia y las infancias implican pedagógicamente reconocer la posibilidad de perfectibilidad – formación humana desde la educación. Para ello, la metodología establecida fue una aproximación crítico – reconstructiva que permitió develar la concepción de infancia en los autores, y de paso establecer una crítica pedagógica a la sociedad que sirve de contenedor existencial a los autores y obras citadas. De modo que el singular permite reconstruir el sentido colectivo, dado por estos pedagogos, y el plural sirve para identificar las diferencias según sus temas y problemas.

Using point of care ultrasound (POCUS) to evaluate patients with syncope in the emergency department facilitates the timely diagnosis of life-threatening . Case: A 56-year-old woman presented to the emergency department of a hospital in Bogotá, Colombia, for a episode. Vital signs, physical examination, electrocardiogram, and routine laboratory tests were normal. Cardiac POCUS was performed, which identified an mass located in the left atrium, measuring 35x28mm, which in left atrial systole appeared to occupy the entire chamber. She underwent surgical resection of the mass and revealed atrial . Conclusions: POCUS was useful in the rapid diagnosis of atrial in a woman presenting with syncope.

Kemajuan teknologi informasi berkembang kearah finansial dalam melakukan prediski. Banyak model algoritma prediksi data keuangan telah dikembangkan. Prediksi kebangkrutan merupakan sesuatu yang sangat penting bagi organisasi atau perusahaan dalam mengambil keputusan yang diperlukan oleh pemodal dan investor. Prediksi kebangkrutan termasuk dalam permasalahan ketidakseimbangan kelas dalam model kalsifikasi karena jumlah data yang termasuk dalam kelas bangkrut jauh lebih sedikit dibandingkan dengan data yang termasuk dalam kelas tidak bangkrut. Tujuan dari penelitian ini adalah untuk menghasilkan model klasifikasi yang baik untuk prediksi risiko kebangkrutan pada perusahaan. preprocessing data dilakukan untuk melakukan optimasi algoritma klasifikasi dengan metode oversampling SMOTE agar menghasilkan model kalsifikasi yang optimal. Algoritma klasifikasi yang digunakan adalah Random Forest Classification untuk mendapatkan hasil prediksi kebangkrutan yang optimal. Berdasarkan hasil pengujian yang telah dilakukan didapatkan bahwa performa klasifikasi meningkat sebesar 7,40% setelah dilakukan preprocessing data dengan menggunakan teknik oversampling SMOTE pada algoritma Random Forest Classifier.

This study aimed to investigate the macronutrient and carotenoid content of red and yellow Coffea arabica var. Caturra pulp, a by-product of coffee processing in Colombia. The study employed ultra-sound-assisted extraction (UAE) to extract carotenoids, and a 23 factorial design was used to evaluate the effects of pulp color, biomass-solvent ratio, and solvent mixture composition on carotenoid content and extraction yield. The condition that provided the highest carotenoid extraction was further encapsulated by spray drying and added to a dairy product. The results showed that coffee pulp has significant dietary fiber content and high levels of carotenoids, with yellow pulp having a higher content than red pulp. Lutein isomers and lutein esters were the most abundant carotenoids found in both red and yellow coffee pulp. The highest carotenoid extraction was achieved using a 1:40 (g/mL) biomass:solvent ratio and a 20:80% v/v Ethanol:Ethyl Acetate solvent mixture for the yellow pulp. The carotenoid extract also demonstrated high encapsulation efficiency (46.57 ± 4.03%) and was found to be stable when added to a fermented milk product. This study presents an alternative solution for utilizing coffee by-products in Colombia, which could positively impact the families of over half a million Colombian coffee producers.

Introducción: La lúdica aborda el uso del juego con una finalidad educativa, pero sin embargo, existen otros enfoques que trascienden esa perspectiva, encontrando así toda una oportunidad de análisis y reflexión, como la propuesta en el presente artículo, en torno a la discriminación. Objetivo: Analizar los aportes de la lúdica a la disminución de causales de discriminación en la educación escolar, a partir de la caracterización e identificación del uso de estrategias pedagógicas lúdicas y la determinación de los elementos que la lúdica puede aportar para la reducción de dicha discriminación. Metodología: Se fundamentó en el marco de la investigación cualitativa de tipo narrativa, utilizando las entrevistas semiestructuradas como técnica de recolección de datos. Resultados y discusión: Se establece que la lúdica constituye una estrategia pedagógica pertinente para la disminución de causas de discriminación al interior de las aulas, siendo no solo, una forma de ejercer pedagogía que trasciende la visión reduccionista en la concepción del juego por el juego, para asociarse a un factor motivacional que la convierte en parte fundamental de los aprendizajes, la expresión de sentimientos y el desarrollo físico, emocional e intelectual. Conclusiones: La lúdica como parte de la práctica docente, usada de manera estratégica puede motivar experiencias de aprendizaje significativo y a su vez impactar procesos relacionados a la convivencia escolar y la discriminación social.

The current requirements of many manufacturing companies, such as the fashion, textile, and clothing industries, involve the production of multiple products with different processing routes and products with short life cycles, which prevents obtaining deterministic setup and processing times. Likewise, several industries present restrictions when changing from one reference to another in the production system, incurring variable and sequence-dependent setup times. Therefore, this article aims to solve the flexible job shop scheduling problem (FJSSP) considering due windows, sequence-dependent setup times, and uncertainty in processing and setup times. A genetic algorithm is proposed to solve the FJSSP by integrating fuzzy logic to minimize the weighted penalties for tardiness/earliness. The proposed algorithm is implemented in a real-world case study of a fabric finishing production system, and it is compared with four heuristics adapted to the FJSSP such as earliest due date, critical reason, shortest processing time, and Monte Carlo simulation. Results show that the performance of the proposed algorithm provides efficient and satisfactory solutions concerning the objective function and computing time since it overperforms (more than 30%) the heuristics used as benchmarks.

Using a novel unsupervised method to integrate multi-omic data, we previously identified a breast cancer group with a poor prognosis. In the current study, we characterize the biological features of this subgroup, defined as the high-risk group, using various data sources. Assessment of three published hypoxia signatures showed that the high-risk group exhibited higher hypoxia scores (p < 0.0001 in all three signatures), compared to the low-risk group. Our analysis of the immune cell composition using CIBERSORT and leukocyte fraction showed significant differences between the high and low-risk groups across the entire cohort, as well as within PAM50 subtypes. Within the basal subtype, the low-risk group had a statistically significantly higher spatial fraction of tumor-infiltrating lymphocytes (TILs) compared to the high-risk group (p = 0.0362). Our findings indicate that this subgroup with poor prognosis is driven by a distinct biological signature with high activation of hypoxia-related genes as well as a low number of TILs., Competing Interests: Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

What environmental regularities support infant communicative learning from social interactions? We propose that infants allocate their attention toward and learn from external events that are contingent on their own behaviors. We tested the robustness of the influence of contingency on communicative learning by using a non-biological stimulus, a remote-controlled car, as the social partner. The car approached infants and produced a speech sound either contingently to infants' vocalizations or on a yoked schedule. Two additional groups had an unfamiliar human experimenter as their social partner in contingent and yoked control conditions. We assessed whether infants formed expectations about their partner's responsiveness to their vocalizations. Expectations made based on contingent responsiveness would support the role of contingency in promoting plasticity in early communicative learning. Infants across all conditions increased their vocalization rates when their partner paused in responding, suggesting that they expected their vocalizations to influence their partners' behavior. Infants vocalized significantly more to the social partner than their caregiver if they received contingent rather than yoked responses from the social partner, regardless of if the partner was a human or non-biological agent. Contingent responses to prelinguistic vocalizations facilitated the formation of expectations for interactivity of social partners., (© 2024 International Congress of Infant Studies.)

Brain waste clearance from the interstitial fluid environment is challenging to measure, which has contributed to controversy regarding the significance of glymphatic transport impairment for neurodegenerative processes. Dynamic contrast enhanced MRI (DCE-MRI) with cerebrospinal fluid administration of Gd-tagged tracers is often used to assess glymphatic system function. We previously quantified glymphatic transport from DCE-MRI data utilizing regularized optimal mass transport (rOMT) analysis, however, information specific to glymphatic clearance was not directly derived. To fill this knowledge gap, we here implemented unbalanced rOMT analysis which allows for assessment of both influx and clearance. Dynamic influx/clearance brain maps were derived from rTg-DI rats with cerebral amyloid angiopathy (CAA) and TgSD-AD rats with Alzheimer's disease (AD). The rTg-DI rats with severe CAA disease exhibited abnormal influx/clearance kinetics, while TgSD-AD rats with a moderate Aβ plaque load exhibited normal transport suggesting that different Aβ lesions and their overall burden differentially impact glymphatic system function., Competing Interests: The authors declare no competing financial interests., (© 2024 The Author(s).)

Although recent advanced sequencing technologies have improved the resolution of genomic and proteomic data to better characterize molecular phenotypes, efficient computational tools to analyze and interpret the large-scale omic data are still needed. To address this, we have developed a network-based bioinformatic tool called Ollivier-Ricci curvature-omics (ORCO). ORCO incorporates gene interaction information with omic data into a biological network, and computes Ollivier-Ricci curvature (ORC) values for individual interactions. ORC, an edge-based measure, indicates network robustness and captures global gene signaling changes in functional cooperation using a consistent information passing measure, thereby helping identify therapeutic targets and regulatory modules in biological systems. This tool can be applicable to any data that can be represented as a network. ORCO is an open-source Python package and publicly available on GitHub at https://github.com/aksimhal/ORC-Omics.

Melanoma response to immune-modulating therapy remains incompletely characterized at the molecular level. In this study, we assess melanoma immunotherapy response using a multi-scale network approach to identify gene modules with coordinated gene expression in response to treatment. Using gene expression data of melanoma before and after treatment with nivolumab, we modeled gene expression changes in a correlation network and measured a key network geometric property, dynamic Ollivier-Ricci curvature, to distinguish critical edges within the network and reveal multi-scale treatment-response gene communities. Analysis identified six distinct gene modules corresponding to sets of genes interacting in response to immunotherapy. One module alone, overlapping with the nuclear factor kappa-B pathway (NFkB), was associated with improved patient survival and a positive clinical response to immunotherapy. This analysis demonstrates the usefulness of dynamic Ollivier-Ricci curvature as a general method for identifying information-sharing gene modules in cancer., (© 2024. The Author(s).)

Network properties account for the complex relationship between genes, making it easier to identify complex patterns in their interactions. In this work, we leveraged these network properties for dual purposes. First, we clustered pediatric sarcoma tumors using network information flow as a similarity metric, computed by the Wasserstein distance. We demonstrate that this approach yields the best concordance with histological subtypes, validated against three state-of-the-art methods. Second, to identify molecular targets that would be missed by more conventional methods of analysis, we applied a novel unsupervised method to cluster gene interactomes represented as networks in pediatric sarcoma. RNA-Seq data were mapped to protein-level interactomes to construct weighted networks that were then subjected to a non-Euclidean, multi-scale geometric approach centered on a discrete notion of curvature. This provides a measure of the functional association among genes in the context of their connectivity. In confirmation of the validity of this method, hierarchical clustering revealed the characteristic EWSR1-FLI1 fusion in Ewing sarcoma. Furthermore, assessing the effects of in silico edge perturbations and simulated gene knockouts as quantified by changes in curvature, we found non-trivial gene associations not previously identified., (© 2024. The Author(s).)

Abstract: The use of distance simulation has rapidly expanded in recent years with the physical distance requirements of the COVID-19 pandemic. With this development, there has been a concurrent increase in research activities and publications on distance simulation. The authors conducted a systematic review of the peer-reviewed distance health care simulation literature. Data extraction and a risk-of-bias assessment were performed on selected articles. Review of the databases and gray literature reference lists identified 10,588 titles for review. Of those, 570 full-text articles were assessed, with 54 articles included in the final analysis. Most of these were published during the COVID-19 pandemic (2020-2022). None of the included studies examined an outcome higher than a Kirkpatrick level of 2. Most studies only examined low-level outcomes such as satisfaction with the simulation session. There was, however, a distinction in studies that were conducted in a learning environment where all participants were in different locations ("distance only") as compared with where some of the participants shared the same location ("mixed distance"). This review exclusively considered studies that focused solely on distance. More comparative studies exploring higher level outcomes are required to move the field forward., Competing Interests: The authors declare no conflict of interest., (Copyright © 2023 Society for Simulation in Healthcare.)

The plasma cell cancer multiple myeloma (MM) varies significantly in genomic characteristics, response to therapy, and long-term prognosis. To investigate global interactions in MM, we combined a known protein interaction network with a large clinically annotated MM dataset. We hypothesized that an unbiased network analysis method based on large-scale similarities in gene expression, copy number aberration, and protein interactions may provide novel biological insights. Applying a novel measure of network robustness, Ollivier-Ricci Curvature, we examined patterns in the RNA-Seq gene expression and CNA data and how they relate to clinical outcomes. Hierarchical clustering using ORC differentiated high-risk subtypes with low progression free survival. Differential gene expression analysis defined 118 genes with significantly aberrant expression. These genes, while not previously associated with MM, were associated with DNA repair, apoptosis, and the immune system. Univariate analysis identified 8/118 to be prognostic genes; all associated with the immune system. A network topology analysis identified both hub and bridge genes which connect known genes of biological significance of MM. Taken together, gene interaction network analysis in MM uses a novel method of global assessment to demonstrate complex immune dysregulation associated with shorter survival., (© 2023. The Author(s).)

Melanoma response to immune-modulating therapy remains incompletely characterized at the molecular level. In this study, we assess melanoma immunotherapy response using a multi-scale network approach to identify gene modules with coordinated gene expression in response to treatment. Using gene expression data of melanoma before and after treatment with nivolumab, we modeled gene expression changes in a correlation network and measured a key network geometric property, dynamic Ollivier-Ricci curvature, to distinguish critical edges within the network and reveal multi-scale treatment-response gene communities. Analysis identified six distinct gene modules corresponding to sets of genes interacting in response to immunotherapy. One module alone, overlapping with the nuclear factor kappa-B pathway (NFKB), was associated with improved patient survival and a positive clinical response to immunotherapy. This analysis demonstrates the usefulness of dynamic Ollivier-Ricci curvature as a general method for identifying information-sharing gene modules in cancer.

Statin-induced necrotizing myopathy (SINM) is an uncommon but severe complication associated with statin medication. SINM can develop at any point after a person starts taking steroids. It is now being acknowledged as a component of the broader category of "statin-induced myopathy." Like other immune-mediated necrotizing muscle diseases, statin-induced myositis is identified by weakness in proximal muscles, increased serum creatine kinase (CK) levels, and, in some cases, dysphagia and respiratory distress. In addition, there is evidence of muscle cell damage when examined under a microscope, occurring with minimal or no infiltration of inflammatory cells. Diagnosing SINM promptly is frequently challenging due to its unpredictable development over time, with symptoms sometimes emerging many years after the initial exposure to statins. One distinctive characteristic of SINM is the continued presence of muscle inflammation and elevated CK levels even after discontinuing statin treatment. Currently, no clinical trials are available to guide how to manage statin-induced immune-mediated necrotizing myopathy (IMNM). Here, we present a case of a 42-year-old woman diagnosed with SINM and was found to have persistently elevated CPK despite discontinuation of statins. Our case also suggests that intravenous (IV) immunoglobins and steroids are an effective and well-tolerated alternative to immunosuppressants., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Altaf et al.)

Background: Distance simulation is defined as simulation experiences in which participants and/or facilitators are separated from each other by geographic distance and/or time. The use of distance simulation as an education technique expanded rapidly with the recent COVID-19 pandemic, with a concomitant increase in scholarly work., Methods: A scoping review was performed to review and characterize the distance simulation literature. With the assistance of an informationist, the literature was systematically searched. Each abstract was reviewed by two researchers and disagreements were addressed by consensus. Risk of bias of the included studies was evaluated using the Risk of Bias 2 (RoB 2) and Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I) tools., Results: Six thousand nine hundred sixty-nine abstracts were screened, ultimately leading to 124 papers in the final dataset for extraction. A variety of simulation modalities, contexts, and distance simulation technologies were identified, with activities covering a range of content areas. Only 72 papers presented outcomes and sufficient detail to be analyzed for risk of bias. Most studies had moderate to high risk of bias, most commonly related to confounding factors, intervention classification, or measurement of outcomes., Conclusions: Most of the papers reviewed during the more than 20-year time period captured in this study presented early work or low-level outcomes. More standardization around reporting is needed to facilitate a clear and shared understanding of future distance simulation research. As the broader simulation community gains more experience with distance simulation, more studies are needed to inform when and how it should be used., (© 2023. The Author(s).)

The advance of sequencing technologies has enabled a thorough molecular characterization of the genome in human cancers. To improve patient prognosis predictions and subsequent treatment strategies, it is imperative to develop advanced computational methods to analyze large-scale, high-dimensional genomic data. However, traditional machine learning methods face a challenge in handling the high-dimensional, low-sample size problem that is shown in most genomic data sets. To address this, our group has developed geometric network analysis techniques on multi-omics data in connection with prior biological knowledge derived from protein-protein interactions (PPIs) or pathways. Geometric features obtained from the genomic network, such as Ollivier-Ricci curvature and the invariant measure of the associated Markov chain, have been shown to be predictive of survival outcomes in various cancers. In this study, we propose a novel supervised deep learning method called geometric graph neural network (GGNN) that incorporates such geometric features into deep learning for enhanced predictive power and interpretability. More specifically, we utilize a state-of-the-art graph neural network with sparse connections between the hidden layers based on known biology of the PPI network and pathway information. Geometric features along with multi-omics data are then incorporated into the corresponding layers. The proposed approach utilizes a local-global principle in such a manner that highly predictive features are selected at the front layers and fed directly to the last layer for multivariable Cox proportional-hazards regression modeling. The method was applied to multi-omics data from the CoMMpass study of multiple myeloma and ten major cancers in The Cancer Genome Atlas (TCGA). In most experiments, our method showed superior predictive performance compared to other alternative methods., Competing Interests: Declaration of Competing Interest Larry Norton discloses the following relationships and financial interests:, (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: The COVID-19 pandemic forced rapid implementation and refinement of distance simulation methodologies in which participants and/or facilitators are not physically colocated. A review of the distance simulation literature showed that heterogeneity in many areas (including nomenclature, methodology, and outcomes) limited the ability to identify best practice. In April 2020, the Healthcare Distance Simulation Collaboration was formed with the goal of addressing these issues. The aim of this study was to identify future research priorities in the field of distance simulation using data derived from this summit., Methods: This study analyzed textual data gathered during the consensus process conducted at the inaugural Healthcare Distance Simulation Summit to explore participant perceptions of the most pressing research questions regarding distance simulation. Participants discussed education and patient safety standards, simulation facilitators and barriers, and research priorities. Data were qualitatively analyzed using an explicitly constructivist thematic analysis approach, resulting in the creation of a theoretical framework., Results: Our sample included 302 participants who represented 29 countries. We identified 42 codes clustered within 4 themes concerning key areas in which further research into distance simulation is needed: (1) safety and acceptability, (2) educational/foundational considerations, (3) impact, and (4) areas of ongoing exploration. Within each theme, pertinent research questions were identified and categorized., Conclusions: Distance simulation presents several challenges and opportunities. Research around best practices, including educational foundation and psychological safety, are especially important as is the need to determine outcomes and long-term effects of this emerging field., Competing Interests: The authors declare no conflict of interest., (Copyright © 2022 Society for Simulation in Healthcare.)

The regularized optimal mass transport (rOMT) problem adds a diffusion term to the continuity equation in the original dynamic formulation of the optimal mass transport (OMT) problem proposed by Benamou and Brenier. We show that the rOMT model serves as a powerful tool in computational fluid dynamics for visualizing fluid flows in the glymphatic system. In the present work, we describe how to modify the previous numerical method for efficient implementation, resulting in a significant reduction in computational runtime. Numerical results applied to synthetic and real-data are provided., Competing Interests: Declarations Conflict of interest The authors declare that they have no conflict of interest.