Towards Smarter Management of Overtourism in Historic Centres Through Visitor-Flow Monitoring

Historic centres are highly regarded destinations for watching and even participating in diverse and unique forms of cultural expression. Cultural tourism, according to the World Tourism Organization (UNWTO), is an important and consolidated tourism sector and its strong growth is expected to continue over the coming years. Tourism, the much dreamt of redeemer for historic centres, also represents one of the main threats to heritage conservation: visitors can dynamize an economy, yet the rapid growth of tourism often has negative effects on both built heritage and the lives of local inhabitants. Knowledge of occupancy levels and flows of visiting tourists is key to the efficient management of tourism; the new technologies—the Internet of Things (IoT), big data, and geographic information systems (GIS)—when combined in interconnected networks represent a qualitative leap forward, compared to traditional methods of estimating locations and flows. A methodology is described in this paper for the management of tourism flows that is designed to promote sustainable tourism in historic centres through intelligent support mechanisms. As part of the Smart Heritage City (SHCITY) project, a collection system for visitors is developed. Following data collection via monitoring equipment, the analysis of a set of quantitative indicators yields information that can then be used to analyse visitor flows; enabling city managers to make management decisions when the tourism-carrying capacity is exceeded and gives way to overtourism.Funded by the Interreg Sudoe Programme of the European Regional Development Funds (ERDF

Differential protein expression analysis of activated E2F2-/-T lymphocytes by means of label-free quantification method

Comunicaciones a congreso

Systemic Innovation Areas for Heritage-Led Rural Regeneration: A Multilevel Repository of Best Practices

This paper presents the result of the analysis of the data gathered from 20 Role Models (RM) case studies regarding their successful heritage-led rural regeneration models. For the study and comparison of the narratives of these Role Models two tools were used: the Community Capitals Framework, which studied the transference of capitals in each process and the identification of six Systemic Innovation Areas that allow this capital transference. A multilevel repository of best practices has been developed allowing the identification of common features, mechanisms for mobilisation of capitals and required resources that will facilitate the replication in other rural areas. The results of this work support the acknowledgement of the contribution of culture, together with cultural and natural heritage, to economic growth, social inclusion and environmental sustainability in rural areas reinforcing the role of culture as the fourth pillar of sustainable development

Mental Health Monitoring from Speech and Language

Concern for mental health has increased in the last years due to its impact in people life quality and its consequential effect on healthcare systems. Automatic systems that can help in the diagnosis, symptom monitoring, alarm generation etc. are an emerging technology that has provided several challenges to the scientific community. The goal of this work is to design a system capable of distinguishing between healthy and depressed and/or anxious subjects, in a realistic environment, using their speech. The system is based on efficient representations of acoustic signals and text representations extracted within the self-supervised paradigm. Considering the good results achieved by using acoustic signals, another set of experiments was carried out in order to detect the specific illness. An analysis of the emotional information and its impact in the presented task is also tackled as an additional contribution.This work was partially funded by the European Commission, grant number 823907 and the Spanish Ministry of Science under grant TIN2017-85854-C4-3-R

Speech emotion recognition in Spanish TV Debates

Emotion recognition from speech is an active field of study that can help build more natural human-machine interaction systems. Even though the advancement of deep learning technology has brought improvements in this task, it is still a very challenging field. For instance, when considering real life scenarios, things such as tendency toward neutrality or the ambiguous definition of emotion can make labeling a difficult task causing the data-set to be severally imbalanced and not very representative. In this work we considered a real life scenario to carry out a series of emotion classification experiments. Specifically, we worked with a labeled corpus consisting of a set of audios from Spanish TV debates and their respective transcriptions. First, an analysis of the emotional information within the corpus was conducted. Then different data representations were analyzed as to choose the best one for our task; Spectrograms and UniSpeech-SAT were used for audio representation and DistilBERT for text representation. As a final step, Multimodal Machine Learning was used with the aim of improving the obtained classification results by combining acoustic and textual information.The research presented in this paper was conducted as part of the AMIC PdC project, which received funding from the Spanish Ministry of Science under grants TIN2017-85854-C4- 3-R, PID2021-126061OB-C42 and PDC2021-120846-C43 and it was also partially funded by the European Union’s Horizon 2020 research and innovation program under grant agreement No. 823907 (MENHIR)

The Elaboration of human anatomy terminology for the Basque language : the contribution of translators, linguists and experts

En aquest article comparem la traducció d'un atles d'anatomia amb la revisió que es va encarregar a experts i lingüistes. L'objectiu és avaluar la mena de contribució que poden fer traductors, lingüistes i experts en l'elaboració de la terminologia de l'anatomia humana en basc. Analitzem les oracions que mostren discordances entre la traducció i la revisió respecte de les unitats lèxiques i les regles de formació usades. Hem observat que les correccions fetes pels experts i lingüistes tendeixen a substituir préstecs i calcs de regles de formació per unitats i estructures genuïnes. Arribem a la conclusió que les polítiques de planificació lingüística que pretenen proporcionar recursos terminològics propis en detriment de solucions dependents d'altres llengües no han estat assumides pels traductors per l'opacitat semàntica de la terminologia de l'anatomia i per la morfologia transparent del basc en comparació amb la del castellà.In this paper we compare the translation of an atlas of anatomy with the review that was carried out by experts in human anatomy and linguists. The goal is to evaluate the type of contribution that translators, linguists and experts can make in the elaboration of the terminology of human anatomy in Basque. We analyzed the sequences that showed discordances between translation and review with respect to the lexical units and the term formation patterns used. We found that the corrections made by experts and linguists show a clear tendency to replace lexical loanwords and calqued term formation rules by genuine elements and structures. We conclude that the aims of language planning policies of gradually providing the language with terminological resources that are less dependent on other languages have not been met by translators due to the semantic opacity of anatomical terminology and the transparent morphology of Basque compared with Spanish

Exploring genetic factors involved in huntington disease age of onset. E2F2 as a new potential modifier gene

Age of onset (AO) of Huntington disease (HD) is mainly determined by the length of the CAG repeat expansion (CAGexp) in exon 1 of the HTT gene. Additional genetic variation has been suggested to contribute to AO, although the mechanism by which it could affect AO is presently unknown. The aim of this study is to explore the contribution of candidate genetic factors to HD AO in order to gain insight into the pathogenic mechanisms underlying this disorder. For that purpose, two AO definitions were used: the earliest age with unequivocal signs of HD (earliest AO or eAO), and the first motor symptoms age (motor AO or mAO). Multiple linear regression analyses were performed between genetic variation within 20 candidate genes and eAO or mAO, using DNA and clinical information of 253 HD patients from REGISTRY project. Gene expression analyses were carried out by RT-qPCR with an independent sample of 35 HD patients from Basque Country Hospitals. We found suggestive association signals between HD eAO and/or mAO and genetic variation within the E2F2, ATF7IP, GRIN2A, GRIN2B, LINC01559, HIP1 and GRIK2 genes. Among them, the most significant was the association between eAO and rs2742976, mapping to the promoter region of E2F2 transcription factor. Furthermore, rs2742976 T allele patient carriers exhibited significantly lower lymphocyte E2F2 gene expression, suggesting a possible implication of E2F2-dependent transcriptional activity in HD pathogenesis. Thus, E2F2 emerges as a new potential HD AO modifier factor

Towards Smarter Management of Overtourism in Historic Centres Through Visitor-Flow Monitoring

Historic centres are highly regarded destinations for watching and even participating in diverse and unique forms of cultural expression. Cultural tourism, according to the World Tourism Organization (UNWTO), is an important and consolidated tourism sector and its strong growth is expected to continue over the coming years. Tourism, the much dreamt of redeemer for historic centres, also represents one of the main threats to heritage conservation: visitors can dynamize an economy, yet the rapid growth of tourism often has negative effects on both built heritage and the lives of local inhabitants. Knowledge of occupancy levels and flows of visiting tourists is key to the efficient management of tourism; the new technologies—the Internet of Things (IoT), big data, and geographic information systems (GIS)—when combined in interconnected networks represent a qualitative leap forward, compared to traditional methods of estimating locations and flows. A methodology is described in this paper for the management of tourism flows that is designed to promote sustainable tourism in historic centres through intelligent support mechanisms. As part of the Smart Heritage City (SHCITY) project, a collection system for visitors is developed. Following data collection via monitoring equipment, the analysis of a set of quantitative indicators yields information that can then be used to analyse visitor flows; enabling city managers to make management decisions when the tourism-carrying capacity is exceeded and gives way to overtourism

Systemic Innovation Areas for Heritage-Led Rural Regeneration: A Multilevel Repository of Best Practices

This paper presents the result of the analysis of the data gathered from 20 Role Models (RM) case studies regarding their successful heritage-led rural regeneration models. For the study and comparison of the narratives of these Role Models two tools were used: the Community Capitals Framework, which studied the transference of capitals in each process and the identification of six Systemic Innovation Areas that allow this capital transference. A multilevel repository of best practices has been developed allowing the identification of common features, mechanisms for mobilisation of capitals and required resources that will facilitate the replication in other rural areas. The results of this work support the acknowledgement of the contribution of culture, together with cultural and natural heritage, to economic growth, social inclusion and environmental sustainability in rural areas reinforcing the role of culture as the fourth pillar of sustainable development