Empresas B en Uruguay. Una gestión estratégica apoyada en la gestión del conocimiento
Tesis Materias > Ciencias Sociales Universidad Internacional Iberoamericana México > Investigación > Tesis Doctorales Cerrado Español El tejido empresarial juega un papel determinante en el desarrollo económico y social de un país. No obstante, en los últimos años su actuación ha inducido un deterioro ambiental, cuyos efectos también han repercutido en la equidad social. En este sentido, para contribuir positivamente con el entorno, las organizaciones han desarrollado progresivamente nuevos modelos de negocios, que incorporan en su gestión los intereses de los agentes afectados por sus operaciones. Dentro de estos modelos, se identifican las Empresas B cuyo propósito, trasciende los esquemas planteados por la responsabilidad social empresarial o corporativa, al asumir como parte de la planificación estratégica el logro de objetivos económicos, sociales y medioambientales, aportando de esta manera soluciones a los problemas de la sociedad a través de la creación de valor agregado derivado de la innovación y el conocimiento. Sobre la base de lo expuesto, en este estudio se propone un modelo gerencial para las empresas B de Uruguay, que incorpora la gestión del conocimiento dentro del proceso de planificación estratégica. Metodológicamente, se adoptó un enfoque cuantitativo fundamentado en una fase descriptiva-explicativa; al tiempo que la población la conformaron las Empresas B certificadas por el Sistema B-Uruguay. Como resultados de la investigación, se encontró que las organizaciones objeto de estudio son un fenómeno empresarial de reciente data en Uruguay. No obstante, se destacan sus aportes al desarrollo social a partir del triple propósito que cumplen en la prestación de servicios o la producción de bienes. Finalmente, el estudio representa un aporte para el desarrollo de los programas en gestión empresarial, en la medida que el modelo gerencial diseñado contribuye con la creación de una cultura corporativa responsable, que a largo plazo genera un valor sostenible para los distintos grupos de interés, al tiempo que aporta soluciones a los problemas socio ambientales de la sociedad, en la medida que sustenta un uso racional de los recursos disponibles. metadata Gámbaro Pereira, Esteban Osvaldo mail SIN ESPECIFICAR (2021) Empresas B en Uruguay. Una gestión estratégica apoyada en la gestión del conocimiento. Doctoral thesis, Universidad Internacional Iberoamericana México.
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El tejido empresarial juega un papel determinante en el desarrollo económico y social de un país. No obstante, en los últimos años su actuación ha inducido un deterioro ambiental, cuyos efectos también han repercutido en la equidad social. En este sentido, para contribuir positivamente con el entorno, las organizaciones han desarrollado progresivamente nuevos modelos de negocios, que incorporan en su gestión los intereses de los agentes afectados por sus operaciones. Dentro de estos modelos, se identifican las Empresas B cuyo propósito, trasciende los esquemas planteados por la responsabilidad social empresarial o corporativa, al asumir como parte de la planificación estratégica el logro de objetivos económicos, sociales y medioambientales, aportando de esta manera soluciones a los problemas de la sociedad a través de la creación de valor agregado derivado de la innovación y el conocimiento. Sobre la base de lo expuesto, en este estudio se propone un modelo gerencial para las empresas B de Uruguay, que incorpora la gestión del conocimiento dentro del proceso de planificación estratégica. Metodológicamente, se adoptó un enfoque cuantitativo fundamentado en una fase descriptiva-explicativa; al tiempo que la población la conformaron las Empresas B certificadas por el Sistema B-Uruguay. Como resultados de la investigación, se encontró que las organizaciones objeto de estudio son un fenómeno empresarial de reciente data en Uruguay. No obstante, se destacan sus aportes al desarrollo social a partir del triple propósito que cumplen en la prestación de servicios o la producción de bienes. Finalmente, el estudio representa un aporte para el desarrollo de los programas en gestión empresarial, en la medida que el modelo gerencial diseñado contribuye con la creación de una cultura corporativa responsable, que a largo plazo genera un valor sostenible para los distintos grupos de interés, al tiempo que aporta soluciones a los problemas socio ambientales de la sociedad, en la medida que sustenta un uso racional de los recursos disponibles.
| Tipo de Documento: | Tesis (Doctoral) |
|---|---|
| Palabras Clave: | Gestión del conocimiento, Planificación estratégica, Empresas b, Innovación, Sostenible, Triple impacto. |
| Clasificación temática: | Materias > Ciencias Sociales |
| Divisiones: | Universidad Internacional Iberoamericana México > Investigación > Tesis Doctorales |
| Depositado: | 31 Ene 2022 23:55 |
| Ultima Modificación: | 20 Sep 2023 23:30 |
| URI: | https://repositorio.unini.edu.mx/id/eprint/501 |
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Single-cell omics for nutrition research: an emerging opportunity for human-centric investigations
Understanding how dietary compounds affect human health is challenged by their molecular complexity and cell-type–specific effects. Conventional multi-cell type (bulk) analyses obscure cellular heterogeneity, while animal and standard in vitro models often fail to replicate human physiology. Single-cell omics technologies—such as single-cell RNA sequencing, as well as single-cell–resolved proteomic and metabolomic approaches—enable high-resolution investigation of nutrient–cell interactions and reveal mechanisms at a single-cell resolution. When combined with advanced human-derived in vitro systems like organoids and organ-on-chip platforms, they support mechanistic studies in physiologically relevant contexts. This review outlines emerging applications of single-cell omics in nutrition research, emphasizing their potential to uncover cell-specific dietary responses, identify nutrient-sensitive pathways, and capture interindividual variability. It also discusses key challenges—including technical limitations, model selection, and institutional biases—and identifies strategic directions to facilitate broader adoption in the field. Collectively, single-cell omics offer a transformative framework to advance human-centric nutrition research.
Manuela Cassotta mail manucassotta@gmail.com, Yasmany Armas Diaz mail , Danila Cianciosi mail , Bei Yang mail , Zexiu Qi mail , Ge Chen mail , Santos Gracia Villar mail santos.gracia@uneatlantico.es, Luis Alonso Dzul López mail luis.dzul@uneatlantico.es, Giuseppe Grosso mail , José L. Quiles mail , Jianbo Xiao mail , Maurizio Battino mail maurizio.battino@uneatlantico.es, Francesca Giampieri mail francesca.giampieri@uneatlantico.es,
Cassotta
<a class="ep_document_link" href="/17878/1/s13018-025-06422-7.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
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Background Anterior shoulder instability is a common condition, especially among young and active individuals, often associated with both osseous and soft tissue injuries. Recent innovations have introduced various surgical options for managing critical and subcritical instability. Therefore, the primary objective of this systematic review was to collect, synthesize, and integrate international research published across multiple scientific databases on shoulder ligamentoplasty, arthroscopic Latarjet, dynamic anterior stabilization (DAS), and arthroscopic Trillat techniques used in the treatment of shoulder instability. Method A structured search was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and the PICOS model, up to January 30, 2025, in the MEDLINE/PubMed, Web of Science (WOS), ScienceDirect, Cochrane Library, SciELO, EMBASE, SPORTDiscus, and Scopus databases. The risk of bias was evaluated, and the PEDro scale was used to assess methodological quality. Results The initial search yielded a total of 964 articles. After applying the inclusion and exclusion criteria, the final sample consisted of 25 articles. These studies demonstrated a high standard of methodological quality. The review summarized the effects of ligamentoplasty, arthroscopic Latarjet, dynamic anterior stabilization, and arthroscopic Trillat techniques in treating shoulder instability, detailing the sample population, immobilization period, frequency of instability episodes—including recurrent dislocations and subluxations—surgical methods, study designs, assessed variables, main findings, and reported outcomes. Conclusions Arthroscopic ligamentoplasty is advantageous in preserving the patient’s native anatomy, maintaining joint integrity, and allowing for alternative interventions in case of failure. The arthroscopic Trillat technique offers a minimally invasive solution for anterior instability without significant bone loss. The DAS technique utilizes the biceps tendon to provide dynamic stabilization, aiming to generate a sling effect over the subscapularis muscle. The Latarjet procedure remains the gold standard for managing anterior glenoid bone loss greater than 20%. Each surgical option for anterior shoulder instability carries specific implications, and treatment decisions should be tailored based on bone loss severity, capsuloligamentous quality, and the patient’s functional needs.
Carlos Galindo-Rubín mail , Yehinson Barajas Ramón mail , Fernando Maniega Legarda mail , Álvaro Velarde-Sotres mail alvaro.velarde@uneatlantico.es,
Galindo-Rubín
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Background/Objectives: Estimating energy and macronutrients from food images is clinically relevant yet challenging, and rigorous evaluation requires transparent accuracy metrics with uncertainty and clear acknowledgement of reference data limitations across heterogeneous sources. This study assessed ChatGPT-5, a general-purpose vision-language model, across four scenarios differing in the amount and type of contextual information provided, using a composite dataset to quantify accuracy for calories and macronutrients. Methods: A total of 195 dishes were evaluated, sourced from Allrecipes.com, the SNAPMe dataset, and Home-prepared, weighed meals. Each dish was evaluated under Case 1 (image only), Case 2 (image plus standardized non-visual descriptors), Case 3 (image plus ingredient lists with amounts), and Case 4 (replicates Case 3 but excluding the image). The primary endpoint was kcal Mean Absolute Error (MAE); secondary endpoints included Median Absolute Error (MedAE) and Root Mean Square Error (RMSE) for kcal and macronutrients (protein, carbohydrates, and lipids), all reported with 95% Confidence Intervals (CIs) via dish-level bootstrap resampling and accompanied by absolute differences (Δ) between scenarios. Inference settings were standardized to support reproducibility and variance estimation. Source stratified analyses and quartile summaries were conducted to examine heterogeneity by curation level and nutrient ranges, with additional robustness checks for error complexity relationships. Results and Discussion: Accuracy improved from Case 1 to Case 2 and further in Case 3 for energy and all macronutrients when summarized by MAE, MedAE, and RMSE with 95% CIs, with absolute reductions (Δ) indicating material gains as contextual information increased. In contrast to Case 3, estimation accuracy declined in Case 4, underscoring the contribution of visual cues. Gains were largest in the Home-prepared dietitian-weighed subset and smaller yet consistent for Allrecipes.com and SNAPMe, reflecting differences in reference curation and measurement fidelity across sources. Scenario-level trends were concordant across sources, and stratified and quartile analyses showed coherent patterns of decreasing absolute errors with the provision of structured non-visual information and detailed ingredient data. Conclusions: ChatGPT-5 can deliver practically useful calorie and macronutrient estimates from food images, particularly when augmented with standardized nonvisual descriptors and detailed ingredients, as evidenced by reductions in MAE, MedAE, and RMSE with 95% CIs across scenarios. The decline in accuracy observed when the image was omitted, despite providing detailed ingredient information, indicates that visual cues contribute meaningfully to estimation performance and that improvements are not solely attributable to arithmetic from ingredient lists. Finally, to promote generalizability, it is recommended that future studies include repeated evaluations across diverse datasets, ensure public availability of prompts and outputs, and incorporate systematic comparisons with non-artificial-intelligence baselines.
Marcela Rodríguez- Jiménez mail , Gustavo Daniel Martín-del-Campo-Becerra mail , Sandra Sumalla Cano mail sandra.sumalla@uneatlantico.es, Jorge Crespo-Álvarez mail jorge.crespo@uneatlantico.es, Iñaki Elío Pascual mail inaki.elio@uneatlantico.es,
Rodríguez- Jiménez
<a class="ep_document_link" href="/17884/1/s12939-025-02596-y.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
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Background Maternal and child undernutrition remains a major global health concern despite modest progress. Accelerating reductions in stunting and wasting will require increased investments in nutrition-sensitive interventions, which target nutrition impacts outside of the healthcare setting. This review examines the effects of four types of nutrition-sensitive interventions —cash/food transfers, nutrition-sensitive agriculture, water/sanitation/hygiene, and school nutrition— on maternal and child nutrition outcomes and dietary diversity. Methods We synthesized the evidence using an initial broad search and synthesis for nutrition-sensitive interventions, followed by targeted searches and syntheses for specific interventions and nutrition outcomes. Meta-analyses were performed to evaluate the impacts of cash transfers and agricultural interventions, while a narrative synthesis was produced for additional nutrition-sensitive interventions. Additionally, qualitative synthesis was incorporated to provide insights into the relationship between implementation context and program effectiveness. Results Our initial evidence synthesis included 260 quantitative studies, and additional targeted searches produced 72 eligible articles. Meta-analyses reveal positive impacts on dietary diversity for cash transfers without nutrition-specific components (0.14 SMD; 95% CI: 0.06–0.22), and some nutrition-sensitive agricultural interventions (0.24 SMD; 95% CI: 0.11–0.37). Cash transfers have larger effects on dietary diversity when they include behavior change communication or other nutrition-specific elements (0.41 SMD; 95% CI; 0.15–0.66), whereas agriculture programs with nutrition-specific elements do not show larger effects on dietary diversity than those without. Narrative syntheses indicate that homestead food production interventions may reduce anemia, school feeding interventions may improve anthropometric outcomes, and WASH interventions are most effective when combined with other nutrition initiatives. Conclusions We find consistent evidence that nutrition-sensitive programs contribute to dietary diversity and may have small but positive effects on nutrition outcomes, such as anthropometric outcomes and anemia. Integrating nutrition into social protection, agriculture, and education sectors is essential for addressing the underlying causes of malnutrition, such as dietary diversity.
Thomas de Hoop mail , Adria Molotsky mail , Rebecca Walcott mail , Pablo Gaitán-Rossi mail , Sonia Hernández-Cordero mail , Amos Laar mail , Torben Behmer mail , Hoa Thi Mai Nguyen mail , Averi Chakrabarti mail , Garima Siwach mail , Varsha Ranjit mail , Vania Lara-Mejía mail , Bianca Franco-Lares mail , Mireya Vilar mail ,
de Hoop
<a class="ep_document_link" href="/17885/1/s41598-025-26052-7.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>
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Mango is one of the most beloved fruits and plays an indispensable role in the agricultural economies of many tropical countries like Pakistan, India, and other Southeast Asian countries. Similar to other fruits, mango cultivation is also threatened by various diseases, including Anthracnose and Red Rust. Although farmers try to mitigate such situations on time, early and accurate detection of mango diseases remains challenging due to multiple factors, such as limited understanding of disease diversity, similarity in symptoms, and frequent misclassification. To avoid such instances, this study proposes a multimodal deep learning framework that leverages both leaf and fruit images to improve classification performance and generalization. Individual CNN-based pre-trained models, including ResNet-50, MobileNetV2, EfficientNet-B0, and ConvNeXt, were trained separately on curated datasets of mango leaf and fruit diseases. A novel Modality Attention Fusion (MAF) mechanism was introduced to dynamically weight and combine predictions from both modalities based on their discriminative strength, as some diseases are more prominent on leaves than on fruits, and vice versa. To address overfitting and improve generalization, a class-aware augmentation pipeline was integrated, which performs augmentation according to the specific characteristics of each class. The proposed attention-based fusion strategy significantly outperformed individual models and static fusion approaches, achieving a test accuracy of 99.08%, an F1 score of 99.03%, and a perfect ROC-AUC of 99.96% using EfficientNet-B0 as the base. To evaluate the model’s real-world applicability, an interactive web application was developed using the Django framework and evaluated through out-of-distribution (OOD) testing on diverse mango samples collected from public sources. These findings underline the importance of combining visual cues from multiple organs of plants and adapting model attention to contextual features for real-world agricultural diagnostics.
Muhammad Mohsin mail , Muhammad Shadab Alam Hashmi mail , Irene Delgado Noya mail irene.delgado@uneatlantico.es, Helena Garay mail helena.garay@uneatlantico.es, Nagwan Abdel Samee mail , Imran Ashraf mail ,
Mohsin