Innovating in the textile industry: An uncoordinated dance between firms and their territory?

Considering the process of innovati on development, this paper aimed to examine the eff ect of diff erent dimensions of proximity and the level of coordinati on that exists in a texti le cluster. This study employed a qualitati ve method, based on indepth interviews that were conducted with two leading fi rms in a texti le cluster in Valencia, Spain, which is subject to intense competi ti on from producers in Asia. Firms were selected according to the criteria of innovati on development and opportunity. This is a pilot study that precedes a more ambiti ous one. The results suggested that fi rms' innovati ons are developed in an isolated, disconti nuous, marginal, and uncoordinated way, and clustering has a marginal eff ect. Furthermore, despite high geographical and cogniti ve proximity, low social proximity is maintained by the low level of trust between the fi rms. These fi ndings may be of signifi cant practi cal value for practi ti oners and insti tuti ons. Firms can gain a bett er understanding of the importance of being located in a cluster, as this is a key factor for their survival under intense competi ti on. However, geographical proximity is not suffi cient, and fi rms need to cooperate with each other and share their ideas and experiences. In additi on, insti tuti ons should interact more with companies, speak their language, meet their needs, and devise strong cluster initi ati ves. This study provides a more comprehensive understanding of how insti tuti ons and fi rms interact within a cluster in the process of innovati on development and elaborate upon diff erent dimensions of proximity among fi rm

An Embedded Simplified Fuzzy ARTMAP Implemented on a Microcontroller for Food Classification

In the present study, a portable system based on a microcontroller has been developed to classify different kinds of honeys. In order to do this classification, a Simplified Fuzzy ARTMAP network (SFA) implemented in a microcontroller has been used. Due to memory limits when working with microcontrollers, it is necessary to optimize the use of both program and data memory. Thus, a Graphical User Interface (GUI) for MATLAB® has been developed in order to optimize the necessary parameters to programme the SFA in a microcontroller. The measures have been carried out by potentiometric techniques using a multielectrode made of seven different metals. Next, the neural network has been trained on a PC by means of the GUI in Matlab using the data obtained in the experimental phase. The microcontroller has been programmed with the obtained parameters and then, new samples have been analysed using the portable system in order to test the model. Results are very promising, as an 87.5% recognition rate has been achieved in the training phase, which suggests that this kind of procedures can be successfully used not only for honey classification, but also for many other kinds of foodThe financial support from the Spanish Government (MAT2012-38429-C04-04, FEDER funds) is gratefully acknowledged.Garcia-Breijo, E.; Garrigues Baixauli, J.; Gil Sánchez, L.; Laguarda-Miro, N. (2013). An Embedded Simplified Fuzzy ARTMAP Implemented on a Microcontroller for Food Classification. Sensors. (13):10418-10429. https://doi.org/10.3390/s130810418S10418104291

Peer-led BASICS intervention to reduce alcohol consumption and alcohol-related consequences among university students: a randomized controlled trial

IntroductionAlcohol consumption is the main substance abused during university and is associated with physical, legal, emotional, social, and cognitive consequences. The peer-led BASICS intervention has been shown to be effective in decreasing the quantity and frequency of drinking, the estimated peak blood alcohol concentration (BAC), and the number of binge drinking episodes among this population.ObjectiveThis study evaluated the effectiveness of the peer-led BASICS intervention to reduce risky alcohol consumption among university students in the Spanish context.Materials and methodsA two-arm randomized controlled trial in a university in northern Spain including 308 first- and second-year university students recruited between October 2022 to March 2023. The intervention was a 30-min in-person peer-led motivational interview. Participants were assessed at baseline and 1-month postintervention. The primary outcome was the quantity and frequency of alcohol consumption during a typical week. The intervention effect was verified using a mixed factorial ANOVA model.ResultsCompared with students in the control group, students who received the intervention reduced the number of drinks per week by 5.7 (95% CI 5.54, 5.86); the number of drinks consumed in a typical weekend by 5.2 (95% CI 5.07, 5.33); the number of drinks consumed on the occasion of greatest consumption by 4.9 (95% CI 4.78, 5.02); the number of binge drinking episodes by 1.4 (95% CI 1.37, 1.43); the peak BAC on a typical week and on the occasion of greatest consumption decreased by 0.06 (95% CI 0.058, 0.062) and 0.09 (95% CI 0.088, 0.092); the number of alcohol-related consequences by 5.8 (95% CI 5.67, 5.93); and the motivation to change their alcohol use increased by −0.8 (95% CI −0.85, −0.75).ConclusionThe peer-led BASICS intervention is effective in changing alcohol consumption and its related consequences among Spanish university students in the short term. The action of nursing students as counselors positively impacted drinking patterns among their peers.Clinical trial registrationhttps://clinicaltrials.gov/study/NCT05639374?intr=Effectiveness%20of%20a%20Peer-led%20Program%20to%20Prevent%20Alcohol%20Consumption&rank=1&page=1&limit=10, identifier: NCT05639374

Artificial neural networks (Fuzzy ARTMAP) analysis of the dataobtained with an electronic tongue applied to a ham-curing processwith different salt formulations

tThis paper describes the determination of optimum values of the parameters of a Simplified FuzzyARTMAP neural network for monitoring dry-cured ham processing with different salt formulations tobe implemented in a microcontroller device. The employed network must be set to the limited micro-controller memory but, at the same time, should achieve optimal performance to classify the samplesobtained from this application.Hams salted with different salt formulations (100% NaCl; 50% NaCl + 50% KCl and 55% NaCl + 25%KCl + 15% CaCl2+ 5% MgCl2) were checked at four processing times, from post-salting to the end of theirprocessing (2, 4, 8 and 12 months).Measurements were taken with a potentiometric electronic tongue system formed by metal electrodesof different materials that worked as nonspecific sensors. This study aimed to discriminate ham samplesaccording to two parameters: processing time and salt formulation.The results were analyzed with an artificial neural network of the Simplified Fuzzy ARTMAP (SFAM)type. During the training and validation process of the neural network, optimum values of the controlparameters of the neural network were determined for easy implementation in a microcontroller, and tosimultaneously achieve maximum sample discrimination. The test process was run in a PIC18F450 micro-controller, where the SFAM algorithm was implemented with the optimal parameters. A data analysiswith the optimized neural network was achieved, and samples were perfectly discriminated according toprocessing time (100%). It is more difficult to discriminate all samples according to salt formulation type,but it is easy to achieve salt type discrimination within each processing block time. Thus, we concludethat the processing time effect dominates salt formulation effects.This work was financially supported by the Spanish Government and European FEDER funds (MAT2012-38429-C04-04).Gil Sánchez, L.; Garrigues Baixauli, J.; Garcia-Breijo, E.; Grau Meló, R.; Aliño Alfaro, M.; Baigts Allende, DK.; Barat Baviera, JM. (2015). Artificial neural networks (Fuzzy ARTMAP) analysis of the dataobtained with an electronic tongue applied to a ham-curing processwith different salt formulations. Applied Soft Computing. (30):421-429. https://doi.org/10.1016/j.asoc.2014.12.0374214293

Glyphosate detection by voltammetric techniques. A comparison between statistical methods and an artificial neural network

Glyphosate quantification methods are complex and expensive, and its control in natural water bodies is getting more important year after year. In order to find a new system that facilitates the detection of glyphosate, we present a comparison between two models to predict glyphosate concentration in aqueous dissolutions. One of them is done by an artificial neural network (ANN) embedded in a microcontroller and the other one is done by statistic methods (Partial Least Squares) in a computer. From an analytical point of view, voltammetric techniques have been selected to obtain electrochemical responses to different glyphosate concentrations. In order to get them, a voltammetry/amperometry device designed by our research group and called FraPlus has been used. In this work we have selected two sensitive electrodes (cobalt and copper), 10 different glyphosate concentrations and a train pulse made by nine different voltammetric pulses to build the models. The ANN developed model is able to properly relate data obtained by FraPlus and glyphosate concentrations and the obtained value for regression coefficient (R) is 0.9998 and the P-value is 0.0. Taking into account these results, we propose this ANN model based in voltammetric techniques working with glyphosate concentrations in a buffer as an approach to glyphosate detection in natural water bodies.Authors acknowledge financial support from the Universitat Politecnica de Valencia and its Centre de Cooperacio al Desenvolupament (Programa ADSIDEO-COOPERACIO 2010) for the research fellowship and support given by UNIJUI University & Staff during the stage of Prof. Laguarda in Ijui (RS-Brazil). We also thank MICINN (MAT2009-14564-C04-02) and GVA (PPC/2011/019) for their respective research fellowships.Laguarda-Miro, N.; Werner Ferreira, F.; Garcia-Breijo, E.; Ibáñez Civera, FJ.; Gil Sánchez, L.; Garrigues Baixauli, J. (2012). Glyphosate detection by voltammetric techniques. A comparison between statistical methods and an artificial neural network. Sensors and Actuators B: Chemical. 171-172:528-536. https://doi.org/10.1016/j.snb.2012.05.025S528536171-17

InnoCOVID-19: Primer congreso multidisciplinar Innocampus

[EN] The main objective of the educational innovation project Innocampus Explora is to show the existing interrelationship between the different scientific and technical degrees of Burjassot-Paterna campus of the University of Valencia. In this paper we present the InnoCOVID-19 Congress, activity organized during the 2020-21 academic year by the work team, made up of students and professors from all the Campus faculties.The objective of this conference, developed in virtual format, was to present the multidisciplinary projects that were formed on campus in response to the health crisis caused by the coronavirus SARS-CoV-2. This activity contributes to a quality transversal training for all participating students.[ES] El proyecto de innovación educativa Innocampus Explora tiene como objetivo principal mostrar la interrelación existente entre los diferentes grados científicos y técnicos del campus de Burjassot-Paterna de la Universitat de València. En este artículo presentamos el congreso InnoCOVID-19, la actividad organizada durante el curso académico 2020-21 por el equipo de trabajo, integrado por estudiantes y profesores de todas las facultades y escuelas. El objetivo de este congreso, desarrollado en formato virtual, ha sido presentar los proyectos multidisciplinares que se han formado en el campus en respuesta a la crisis sanitaria provocada por el coronavirus SARS-CoV-2. Esta actividad contribuye a una formación transversal de calidad para todos los estudiantes participantes.Proyecto UV-SFPIE PIC-1363315 financiado por el Servei de Formació Permanent i Innovació Educativa de la Universitat de València.Amorós Hernández, L.; Blas Medina, A.; Cervera Sanz, M.; Cosme Llópez, E.; García Gil, R.; García Lázaro, S.; García Robles, I.... (2021). InnoCOVID-19: Primer congreso multidisciplinar Innocampus. En IN-RED 2021: VII Congreso de Innovación Edicativa y Docencia en Red. Editorial Universitat Politècnica de València. 1171-1182. https://doi.org/10.4995/INRED2021.2021.13449OCS1171118

Innocampus Explora: una aproximación multidisciplinar a la problemática ambiental

[ES] Presentamos las actividades del proyecto de innovación Innocampus Explora desarrollado en el campus de Burjassot-Paterna de la Universitat de València y cuyo objetivo principal es mostrar la interrelación existente entre los diferentes grados científicos y técnicos del campus. En la presente anualidad, el equipo de trabajo integrado por estudiantes y profesores de todos las facultades y escuelas del campus de Burjassot-Paterna, ha desarrollado actividades en torno a la problemática medioambiental. Una visión transversal e interdisciplinar de los problemas de los usos del plástico y de la energía nuclear que enlaza con varios de los Objetivos de Desarrollo Sostenible (ODS) dictados por Naciones Unidas. Con el desarrollo de este proyecto contribuimos a una formación transversal de calidad para todos los estudiantes participantes.[EN] We present the activities of the Innocampus Explora innovation project developed on the Burjassot-Paterna campus of the Universitat de València and whose main objective is to show the interrelation between the different scientific and technical degrees on campus. In this year, the work team made up of students and professors from all the faculties and schools of the Burjassot-Paterna campus, have carried out activities around environmental issues. A cross-sectional and interdisciplinary vision of the problems of the uses of plastic and nuclear energy that link with several of the Sustainable Development Goals (SDGs) dictated by the United Nations. With the development of this project we contribute to quality transversal training for all participating students.Moros Gregorio, J.; Quílez Asensio, A.; Jimenez Romero, D.; Blas Medina, A.; Giménez Escamilla, I.; Amorós Hernández, L.; Giner, L.... (2021). Innocampus Explora: una aproximación multidisciplinar a la problemática ambiental. En IN-RED 2020: VI Congreso de Innovación Educativa y Docencia en Red. Editorial Universitat Politècnica de València. 1003-1014. https://doi.org/10.4995/INRED2020.2020.11996OCS1003101

Innocampus Explora: Nuevas formas de comunicar ciencia

[EN] Innocampus Explora aims to show the students of the Burjassot-Paterna campus of the Universitat de València how the different scientific degrees are interrelated. To do this we propose activities in which students and teachers work together to cover the interdisciplinary nature of science, both in everyday and professional issues. Throughout this course the activities developed relate to new ways to communicate science. With the development of this project we contribute to a transversal quality education for all the participating students.[ES] Innocampus Explora tiene por objetivo mostrar a los estudiantes del campus de Burjassot-Paterna de la Universitat de València cómo los diferentes grados científicos están interrelacionados. Para ello proponemos actividades en las que estudiantes y profesores trabajen conjuntamente para abarcar la interdisciplinariedad de la ciencia, tanto en temas cotidianos como profesionales. A lo largo de este curso las actividades desarrolladas se relacionan con las nuevas formas de comunicar ciencia. Con el desarrollo de este proyecto contribuimos a una formación transversal de calidad para todos los estudiantes participantes.Moros Gregorio, J.; Rodrigo Martínez, P.; Torres Piedras, C.; Montoya Martínez, L.; Peña Peña, J.; Pla Díaz, M.; Galarza Jiménez, P.... (2019). Innocampus Explora: Nuevas formas de comunicar ciencia. En IN-RED 2019. V Congreso de Innovación Educativa y Docencia en Red. Editorial Universitat Politècnica de València. 814-823. https://doi.org/10.4995/INRED2019.2019.10449OCS81482

A new MRI rating scale for progressive supranuclear palsy and multiple system atrophy: validity and reliability

AIM To evaluate a standardised MRI acquisition protocol and a new image rating scale for disease severity in patients with progressive supranuclear palsy (PSP) and multiple systems atrophy (MSA) in a large multicentre study. METHODS The MRI protocol consisted of two-dimensional sagittal and axial T1, axial PD, and axial and coronal T2 weighted acquisitions. The 32 item ordinal scale evaluated abnormalities within the basal ganglia and posterior fossa, blind to diagnosis. Among 760 patients in the study population (PSP = 362, MSA = 398), 627 had per protocol images (PSP = 297, MSA = 330). Intra-rater (n = 60) and inter-rater (n = 555) reliability were assessed through Cohen's statistic, and scale structure through principal component analysis (PCA) (n = 441). Internal consistency and reliability were checked. Discriminant and predictive validity of extracted factors and total scores were tested for disease severity as per clinical diagnosis. RESULTS Intra-rater and inter-rater reliability were acceptable for 25 (78%) of the items scored (≥ 0.41). PCA revealed four meaningful clusters of covarying parameters (factor (F) F1: brainstem and cerebellum; F2: midbrain; F3: putamen; F4: other basal ganglia) with good to excellent internal consistency (Cronbach α 0.75-0.93) and moderate to excellent reliability (intraclass coefficient: F1: 0.92; F2: 0.79; F3: 0.71; F4: 0.49). The total score significantly discriminated for disease severity or diagnosis; factorial scores differentially discriminated for disease severity according to diagnosis (PSP: F1-F2; MSA: F2-F3). The total score was significantly related to survival in PSP (p<0.0007) or MSA (p<0.0005), indicating good predictive validity. CONCLUSIONS The scale is suitable for use in the context of multicentre studies and can reliably and consistently measure MRI abnormalities in PSP and MSA. Clinical Trial Registration Number The study protocol was filed in the open clinical trial registry (http://www.clinicaltrials.gov) with ID No NCT00211224