12096 research outputs found
Sort by
Las sanciones internacionales como herramienta de política exterior: análisis en el contexto del conflicto entre Rusia y Ucrania
No full textEl presente Trabajo de Fin de Máster trata de elaborar un informe lo más preciso posible sobre las sanciones internacionales. Además, para lograr entender en mayor medida esta herramienta de política exterior, enfocaremos el estudio al plano actual, concretamente al conflicto bélico entre Ucrania y Rusia. Se aborda, por tanto, el propósito de este tipo de medidas, los organismos que pueden imponerlas y se generará un debate que pretende hacer reflexionar acerca de si este tipo de herramientas son o no eficaces para conseguir un cambio en la actuación de los Estados infractores. Todo ello apoyado sobre diversas sentencias de gran relevancia que nos ayudan al entendimiento de los puntos anteriormente citados.This Master's thesis aims to produce as accurate a report as possible on international sanctions. Furthermore, in order to gain a better understanding of this foreign policy tool, we will focus the study on the current situation, specifically the conflict between Ukraine and Russia. The purpose of this type of measures, the bodies that can impose them, and a debate will be held on whether or not this type of tool is effective in bringing about a change in the actions of the offending states. All of this will be supported by various highly relevant rulings that will help us to understand the aforementioned points.Máster Universitario en Acceso a la Abogacía y a la Procura por la Universidad Pública de NavarraAbokatutzarako eta Prokuradoretzarako Sarbideko Unibertsitate Masterra Nafarroako Unibertsitate Publikoa
Predicting the spatial distribution of reducing sugars using near-infrared hyperspectral imaging and chemometrics: a study in multiple potato genotypes
No full textThe determination of reducing sugars in potatoes is important due to their impact on product quality during industrial processing. The significant variability of these compounds between genotypes presents a challenge to the development of accurate predictive models. This study evaluated the potential of near-infrared hyperspectral imaging (NIR-HSI) for the prediction of reducing sugars in potatoes. For this, a wide range of genotypes (n=92) from two seasons (2020-2021) was selected. Partial Least Squares Regression (PLSR) and Support Vector Machine Regression (SVMR) methods were used to build the prediction models. Furthermore, interval PLS (iPLS), recursive weighted PLS (rPLS), Genetic Algorithm (GA) and Competitive Adaptive Reweighted Sampling (CARS) were used for relevant wavelength identification to develop less computationally complex models. The best full spectrum model (SNV-PLSR) achieved coefficient of determination and root mean square error values of 0.88 and 0.053% and 0.86 and 0.057%, for calibration and external validation, respectively. Variable selection algorithms successfully reduced the dimensionality of the data without compromising the performance of the models. Robust predicted models were built with only 2.65% (CARS-PLSR) and 3.57% (iPLS-SVMR) of the total wavelengths. Finally, a pixel-wise prediction was performed on the validation set and chemical images were built to visualise the spatial distribution of reducing sugars. This study demonstrated that NIR-HSI is a feasible technique for predicting reducing sugars in several potato genotypes.This work was supported by the Ministerio de Ciencia, Innovación y Universidades (MICIU/AEI /10.13039/501100011033), (Spain), project: PID2019-109790RR-C22 and the predoctoral grant (PRE2020-094533) associated to it
Sustainable and green technologies for industrial chemical engineering
No full textThis is a reprint of the Special Issue Sustainable and Green Technologies for Industrial Chemical Engineering that was published in Eng.Editor de la obra: Antonio Gil BravoToday, industrial processes are subject to continuous review to minimize the emission of pollutants, as well as purify the effluents that are produced. Likewise, a continuous review of the raw materials used is necessary to make them more sustainable. This is the objective of this Special Issue; we set out to present examples of industrial processes adapted to these current requirements
Design of an application to control a fan array wind tunnel
No full textFan array wind tunnels (FAWTs) allow the generation of complex wind flows, with variability in space and time, for many applications. These include aeronautical engineering, civil engineering, architecture, and environmental sciences, among others. These tunnels can produce wind conditions tailored to specific requirements, for example, by recreating oscillating winds, speed gradients, or wind gusts. We propose an open-source Fan Array Wind Tunnel (FAWT) wireless control architecture that is ready to be used or modified, according to the user’s needs.
The project required interdisciplinary knowledge in electronics and computer science, with a primary focus on the latter. Skills in networking, programming (Java and Python), and the integration of hardware components such as Raspberry Pi, Adafruit EMC2101, and NanoDAQ-LTS-32 were essential. Additionally, graphical user interface design played a crucial role. The resulting system went beyond the initial expectations, delivering a highly advanced FAWT and an adaptable remote control tool, continuously improved into a valuable resource for research and application.Graduado o Graduada en Ingeniería Informática por la Universidad Pública de Navarra (Programa Internacional)Informatika Ingeniaritzan Graduatua Nafarroako Unibertsitate Publikoan (Nazioarteko Programa
Visible-light-driven photocatalytic degradation of organic dyes using a TiO2 and waste-based carbon dots nanocomposite
No full textHerein we report a visible-light-active photocatalytic nanocomposite (NC50:50) prepared from carbon dots (CDs) and TiO2 nanoparticles, which was applied to the photodegradation of organic dyes in water. The CDs incorporated corn stover, a major agricultural waste, and were prepared via hydrothermal treatment. Using a visible-light irradiation source and the dye methylene blue as a representative of the organic dyes class, we observed that a 374% enhancement of the catalytic performance was achieved by adding CDs relative to bare TiO2. This was possible due to increased visible-light absorption and better photonic efficiency. Tests using reactive species scavengers indicated that three active species (superoxide anion, hydroxyl radicals, and electrons) were responsible for the photodegradation process, differing from bare TiO2 in which only the hydroxyl radical has a relevant role. Photocatalytic degradation was also observed toward Rhodamine B, Orange II and Methyl Orange. Finally, we performed a life cycle assessment (LCA) study to assess and analyse the associated environmental impacts of NC50:50 compared with other alternatives, which revealed that NC50:50 is the alternative resulting in the least environmental impacts. In summary, NC50:50 could, under visible-light irradiation, efficiently remove different organic dyes while incorporating organic waste materials and reducing the impacts associated with their use. We expect that this study provides a base for a more environmentally sustainable design of visible-light-active photocatalysts via waste upcycling.The Portuguese "Fundaçao para a Ciencia e Tecnologia" (FCT, Lisbon) is acknowledged for funding projects PTDC/QUI-QFI/2870/2020
and 2023.13127.PEX, R&D Units CIQUP (UIDB/00081/2020 and UIDP/00081/2020) and GreenUPorto (UIDB/05748/2020 and UIDP/05748/2020), and the Associated Laboratory IMS (LA/P/0056/2020). Carlos Pereira Portuguese acknowledges the Recovery and Resilience Plan and by the NextGeneration EU European funds in its component 12 - Sustainable Bioeconomy, Investment under project Bioshoes4All (TC-C12-i01). Luís Pinto da Silva acknowledges funding from FCT under the Scientific Employment Stimulus (CEECINST/00069/2021). Ricardo Sendao acknowledges FCT for his Ph.D. grant (2021.06149.BD). Manuel
Algarra thanks the Spanish Ministry of Science and Innovation (MCIN/AEI/10.13039/501100011033) through the project PID2021-122613OB-I0
Scope of nursing practice in medical-surgical hospitalization and intensive care units
No full textObjetivo: Analizar el alcance de práctica de las enfermeras de unidades de hospitalización médico-quirúrgicas y unidades de cuidados intensivos en el contexto español, y su relación con las características individuales de las enfermeras y de su ámbito de trabajo. Método: Estudio observacional, transversal, realizado en 29 unidades de hospitalización médico-quirúrgica de adultos y 5 unidades de cuidados intensivos de la red pública de Navarra. La variable principal, el alcance de práctica de las enfermeras, se midió mediante el cuestionario de D’Amour en su versión española. Se analizaron los datos con estadística descriptiva e inferencial, estableciendo el nivel de significación en 0,05. Resultados: Un total de 310 enfermeras participaron en el estudio, y los resultados revelaron niveles aceptables del alcance de práctica enfermera. La edad y el trabajar en unidades de cuidados intensivos fueron determinantes a la hora de identificar diferencias en las actividades desempeñadas por las enfermeras en el ejercicio de su profesión. La correlación encontrada muestra que a mayor edad existe mayor probabilidad de expresar puntuaciones más bajas en la dimensión «Cuidado centrado en paciente y familia». En contraste, en la dimensión «Calidad del cuidado y seguridad del paciente» fueron las enfermeras más jóvenes las que puntuaron significativamente más bajo. Conclusiones: Comprender el alcance de práctica de las enfermeras es esencial para abordar la escasez de profesionales en los sistemas de salud. No se trata únicamente de aumentar el número de enfermeras, sino de garantizar que estas estén dedicadas a desempeñar integralmente las funciones propias de su profesión.Aim: To analyze the scope of nursing practice in medical-surgical and intensive care units in the Spanish context and its relationship with individual characteristics of nurses and their work environment. Methods: A cross-sectional observational study was carried out in 29 medical-surgical hospitalisation units and 5 intensive care units for adults in the public network of Navarre. The main variable, nurses' scope of practice, was measured using the Spanish version of the D'Amour questionnaire. Descriptive and inferential statistics were used to analyse the data, with a significance level of 0.05. Results: A total of 310 nurses participated in the study, and the results showed acceptable levels of nursing scope of practice. Age and working in intensive care units were significant factors in identifying differences in nurses¿ scope of practice activities. The correlation analysis revealed a statistically significant association between age and the likelihood of expressing lower scores in the dimension «Patient- and family-centered care.» In contrast, younger nurses exhibited significantly lower scores in the «Quality of care and patient safety» dimension. Conclusions: To address the shortage of nurses in health systems, it is essential to understand the scope of nursing practice. The challenge is not only to increase the number of nurses but also to ensure that they are working in the full range of their professional roles.Financiación obtenida por la 1.a Convocatoria de proyectos de investigación para profesores de centros miembros de la Conferencia Nacional de Decanas de Enfermería (CNDE) [Código de beca PI 013CNDE]
Extraordinary sensitivity with quasi-lossy mode resonance mode transition bands in long period fiber gratings
No full textThis study presents a novel sensor design utilizing a long-period fiber grating (LPFG) deposited with a TiO2 nanocoating via atomic layer deposition. The study combines theoretical simulations and experimental validation to optimize the grating period and modulation index to operate in the mode transition with a quasi-lossy mode resonance (LMR) behavior, i.e., the LPFG attenuation bands shift similarly to LMRs. This enables the achievement of a remarkable sensitivity of 78 nm/nm, allowing for the detection of sub-angstrom variations in film thickness, which is critical for applications in semiconductor manufacturing. Our setup facilitates continuous monitoring of the transmission spectrum, enabling real-time adjustments during deposition to maximize sensitivity. As proof of concept for the applicability of the sensor as a refractive index sensor, we demonstrated exceptional sensitivity for nitrogen detection, achieving around 10,000 nm/RIU, with a figure of merit of 200. This marks one the highest sensitivities reported for optical fiber gas sensors and suggests this technology could revolutionize the field duet to its simplicity in terms of sensor design.This work was supported in part by the Agencia Estatal de Investigación (AEI) from the Spanish Ministry of Economy and Competitiveness (MCIU/AEI/10.13039/501100011033/FEDER PID2023-149895OB-I00) research fund and by the pre-doctoral research grant of the Public University of Navarra
Torsion sensor using a high-birefringence nine-hole optical fiber
No full textThis article presents a novel high-birefringence
fiber-based torsion sensor based on a microstructured optical fiber with nine holes and seven cores microstructured
holes and cores optical fiber (MHCF) embedded into a
Sagnac interferometer (SI). A segment of this fiber is inserted
into a symmetric SMF-MMF-MHCF-MMF-SMF arrangement,
which provides efficient coupling to the multiple cores of
the birefringent fiber and, consequently, multimode interference (MMI). Fast Fourier transform (FFT) spectral data
analysis is employed to enhance measurement stability and reduce dependence on optical source variations. The
sensor demonstrates a linear response to torsion angles between −50◦ and +50◦
, with a 16-mrad/◦ sensitivity. The high
sensitivity and good linearity of the sensor are enhanced through the application of machine learning (ML) techniques.This work was supported in part by CIN/AEI/10.13039/501100011033 and Fondo Europeo de Desarrollo Regional (FEDER) \u201CA way to make Europe,\u201D under Project PID2022-137269OB; and in part by MCIN/AEI/10.13039/501100011033 and European Union (EU) \u201CNext generation EU\u201D/Plan de Recuperaci\u00F3n, Transformaci\u00F3n y Resiliencia (PRTR) under Project TED2021-130378B. Open access funding provided by Universidad P\u00FAblica de Navarra
Integración de modelos de Inteligencia Artificial para análisis de imágenes para un sistema de automatización de procesos en fábrica
No full textEste Trabajo de Fin de Grado explora la viabilidad de un sistema de autoidentificación
basado en análisis de imágenes mediante modelos de inteligencia artificial generativa,
como alternativa a la tecnología RFID empleada actualmente en entornos industriales.
El proyecto se desarrolla en el contexto de la empresa BSH Electrodomésticos, y se
integra dentro de su plataforma AutoID, basada en una arquitectura de microservicios.
La solución propuesta consiste en una aplicación web móvil para dispositivos handheld
ya disponibles en planta, desde la cual se capturan imágenes que son enviadas a un
entorno de Google Cloud. Allí, distintos modelos multimodales como GPT-4o y Gemini
procesan las imágenes y extraen información relevante de las etiquetas, así como el
estado visual del palet. Los resultados se visualizan mediante un monitor desarrollado
específicamente para comparar la precisión, eficiencia y tiempos de respuesta de los
modelos evaluados.
El trabajo analiza además las limitaciones técnicas del hardware utilizado y la capacidad
de generalización de los modelos de IA empleados. Finalmente, se presenta una
comparativa con el sistema RFID tradicional, evaluando aspectos como coste, precisión
y escalabilidad. Los resultados permiten concluir que, si bien existen desafíos, los
modelos de IA generativa ofrecen un enfoque prometedor para tareas de identificación
y control logístico en entornos industriales automatizados.This Final Degree Project explores the feasibility of a self-identification system based on
image analysis using generative artificial intelligence models as an alternative to the
RFID technology currently employed in industrial environments. The project is developed
within the context of BSH Home Appliances and is integrated into its AutoID platform,
which is built on a microservices architecture.
The proposed solution consists of a mobile web application for handheld devices already
available in the factories. From these devices, images are captured and sent to a Google
Cloud environment, where various multimodal models such as GPT-4o and Gemini
process the images, extracting relevant information from the labels and assessing the
visual condition of the pallet. The results are displayed through a custom monitoring
interface developed to compare the accuracy, efficiency, and response times of the
evaluated models.
The project also analyzes the technical limitations of the hardware used and the
generalization capabilities of the AI models. Finally, a comparison with the traditional
RFID system is presented, evaluating aspects such as cost, accuracy, and scalability.
The findings lead to the conclusion that, while challenges remain, generative AI models
offer a promising approach for identification and logistics control tasks in automated
industrial settings.Graduado o Graduada en Ingeniería en Tecnologías de Telecomunicación por la Universidad Pública de NavarraTelekomunikazio Teknologien Ingeniaritzako Graduatua Nafarroako Unibertsitate Publikoa
First case of triple resistance to EPSPS, ALS, and synthetic auxin herbicides in Bassia scoparia (L.) Voss in Europe
No full textBassia scoparia (L.) Voss has evolved resistance to five herbicide modes of action (MoAs) worldwide, including multiple resistance to up to four MoAs. Seeds were collected from a putatively resistant B. scoparia population (GUI-R) that survived successive herbicide applications of synthetic auxins, acetolactate synthase (ALS), and 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) inhibitors in a no-till winter cereal field in Catalonia, Spain, in 2022, to assess resistance levels and mechanisms. Dose-response assays confirmed that GUI-R was 2-, 340-, 42.7-, and 60-fold more resistant to glyphosate, thifensulfuron, MCPA, and 2,4-D, respectively, based on plant weight, and 3.2-, 123-, 57.9-, and 32-fold more resistant based on plant survival. GUI-R showed cross-resistance to imazamox (46 % survival), but not to dicamba or fluroxypyr (100 % mortality), at the label rate. Preliminary studies using malathion pre-treatment, a cytochrome P450 inhibitor, reversed 2,4-D resistance in GUI-R at the label rate, resulting in a 97 % reduction in biomass. Molecular studies revealed that GUI-R has 4.9 additional copies of the EPSPS:ALS gene, with no known mutations and less shikimate accumulation than the susceptible population. ALS gene sequencing identified the Pro197Ser, Pro197Leu, and Trp574Leu mutations, along with a combined Pro197Ser + Trp574Leu mutation. In conclusion, EPSPS gene amplification and ALS mutations confer target-site resistance to glyphosate, thifensulfuron and imazamox in GUI-R. Resistance to 2,4-D and MCPA is probably driven by P450-mediated non-target-site resistance and further research is necessary to confirm mechanisms. This biotype represents the first case of glyphosate resistance in Europe for the species, as well as the first triple resistance.Authors acknowledge the support from the Spanish Ministry of Science, Innovation, and Universities (grant Ramon y Cajal RYC2018-023866-I), the Spanish State Research Agency, Spain (AEI), and the European Regional Development Fund, EU (ERDF) through the project PID2020-113229RB-C42