Shannon Entropy in a European Seabass (Dicentrarchus labrax) System during the Initial Recovery Period after a Short-Term Exposure to Methylmercury

Methylmercury (MeHg) is an environmental contaminant of increasing relevance as a seafood safety hazard that affects the health and welfare of fish. Non-invasive, on-line methodologies to monitor and evaluate the behavior of a fish system in aquaculture may make the identification of altered systems feasible-for example, due to the presence of agents that compromise their welfare and wholesomeness-and find a place in the implementation of Hazard Analysis and Critical Control Points and Fish Welfare Assurance Systems. The Shannon entropy (SE) of a European seabass (Dicentrarchus labrax) system has been shown to differentiate MeHg-treated from non-treated fish, the former displaying a lower SE value than the latter. However, little is known about the initial evolution of the system after removal of the toxicant. To help to cover this gap, the present work aims at providing information about the evolution of the SE of a European seabass system during a recuperation period of 11 days following a two-week treatment with 4 mu g center dot MeHg/L. The results indicate that the SE of the system did not show a recovery trend during the examined period, displaying erratic responses with daily fluctuations and lacking a tendency to reach the initial SE values.We wish to thank Grupo Tinamenor (Cantabria, Spain) for providing the European sea bass, Urtzi Izagirre for his contribution to the design of the experimental treatments, and Xabier Lekube and Gregor Bwye for technical assistance. The work received financial support from the Spanish Ministry of Economy and Competitiveness Project number: CTM2012-40203-C02-01, Towards science-based standard biomarker methods, suitable to diagnose and monitor pollution biological effects in the Bay of Biscay for the purpose of implementing the European Marine Strategy Framework Directive-BMW and Project number: RTC-2014-2837-2, Minimizacion de la problematica del mercurio del atun y valorizacion del atun como alimento saludable-SELATUN

A Heated Debate: Climate Change and Conflict in Africa

The worst drought in a century in Southern Africa at the end of last year slowed the iconic Victoria Falls on the Zimbabwean–Zambian border to a rill, fuelling renewed discussion about climate change. It also epitomised the potential repercussions of the phenomenon for livelihoods and security on the African continent. However, current research only sees a weak connection between climate and violent conflict. Sub-Saharan Africa is the world region most affected by climate change. Parts of East Africa, the Sahel, and Southern Africa have been the most severely impacted on. Existing research largely sees climate change as a "threat multiplier," and perceives high poverty and low state capability as more influential drivers of conflict. General assessments of how climate affects conflict mask important differ­ences: In some parts of Africa, extreme weather events (such as droughts) and rising temperatures threaten the most vulnerable already - namely, those that are poor and rely on rain-fed agriculture. Pastoralist agricultural production and pronounced differences between ethnic groups are particularly dangerous risk factors. Yet uncertainty about climate's precise effects is still high. Under certain conditions, climate change can lead to increased conflict but also cooperation in affected communities across Africa. New research needs to investigate more thoroughly the mechanisms underlying how individuals and communities react to weather extremes and long-term climatic changes. It is of particular relevance to understand how increased societal cooperation as well as adequate state policies can help overcome climate change's adverse effects among those most vulnerable people. Following up on its last report from 2014, in 2022 the climate-conflict link will be re-evaluated for the next Intergovernmental Panel on Climate Change (IPCC) Assessment Report. Better understanding the pathways that lead to violent conflict and focusing on the most vulnerable members of society, namely those who directly rely on rain-fed agriculture, is a necessary precondition for devising adequate policies to tame climate change's adverse effects on security. Supporting the mitigation of climate change's detrimental effects for the most vulnerable in Africa should be a key focus for European and German Africa policy

Multilingual audio information management system based on semantic knowledge in complex environments

This paper proposes a multilingual audio information management system based on semantic knowledge in complex environments. The complex environment is defined by the limited resources (financial, material, human, and audio resources); the poor quality of the audio signal taken from an internet radio channel; the multilingual context (Spanish, French, and Basque that is in under-resourced situation in some areas); and the regular appearance of cross-lingual elements between the three languages. In addition to this, the system is also constrained by the requirements of the local multilingual industrial sector. We present the first evolutionary system based on a scalable architecture that is able to fulfill these specifications with automatic adaptation based on automatic semantic speech recognition, folksonomies, automatic configuration selection, machine learning, neural computing methodologies, and collaborative networks. As a result, it can be said that the initial goals have been accomplished and the usability of the final application has been tested successfully, even with non-experienced users.This work is being funded by Grants: TEC201677791-C4 from Plan Nacional de I + D + i, Ministry of Economic Affairs and Competitiveness of Spain and from the DomusVi Foundation Kms para recorder, the Basque Government (ELKARTEK KK-2018/00114, GEJ IT1189-19, the Government of Gipuzkoa (DG18/14 DG17/16), UPV/EHU (GIU19/090), COST ACTION (CA18106, CA15225)

On the Analysis of Speech and Disfluencies for Automatic Detection of Mild Cognitive Impairment

Alzheimer's disease is characterized by a progressive and irreversible cognitive deterioration. In a previous stage, the so-called Mild Cognitive Impairment or cognitive loss appears. Nevertheless, this previous stage does not seem sufficiently severe to interfere in independent abilities of daily life, so it is usually diagnosed inappropriately. Thus, its detection is a crucial challenge to be addressed by medical specialists. This paper presents a novel proposal for such early diagnosis based on automatic analysis of speech and disfluencies, and Deep Learning methodologies. The proposed tools could be useful for supporting Mild Cognitive Impairment diagnosis. The Deep Learning approach includes Convolutional Neural Networks and nonlinear multifeature modeling. Additionally, an automatic hybrid methodology is used in order to select the most relevant features by means of nonparametric Mann-Whitney U test and Support Vector Machine Attribute evaluation.This work has been supported by FEDER and MICINN, TEC2016-77,791-C4-2-R, and UPV/EHU-Basque Research Groups IT11156 and Basque Country EleKin Research Grou

Changes in Day/Night Activity in the 6-OHDA-Induced Experimental Model of Parkinson’s Disease: Exploring Prodromal Biomarkers

The search for experimental models mimicking an early stage of Parkinson's disease (PD) before motor manifestations is fundamental in order to explore early signs and get a better prognosis. Interestingly, our previous studies have indicated that 6-hydroxydopamine (6-OHDA) is a suitable model to induce an early degeneration of the nigrostriatal system without any gross motor impairment. Considering our previous findings, we aim to implement a novel system to monitor rats after intrastriatal injection of 6-OHDA to detect and analyze physiological changes underlying prodromal PD. Twenty male Sprague-Dawley rats were unilaterally injected with 6-OHDA (n = 10) or saline solution (n = 10) into the right striatum and placed in enriched environment cages where the activity was monitored. After 2 weeks, the amphetamine test was performed before the sacrifice. Immunohistochemistry was developed for the morphological evaluation and western blot analysis to assess molecular changes. Home-cage monitoring revealed behavioral changes in response to 6-OHDA administration including significant hyperactivity and hypoactivity during the light and dark phase, respectively, turning out in a change of the circadian timing. A preclinical stage of PD was functionally confirmed with the amphetamine test. Moreover, the loss of tyrosine hydroxylase expression was significantly correlated with the motor results, and 6-OHDA induced early proapoptotic events. Our findings provide evidence for a novel prodromal 6-OHDA model following a customized monitoring system that could give insights to detect non-motor deficits and molecular targets to test neuroprotective/neurorestorative agents.This study has been financially supported by the University of the Basque Country (UPV/EHU) PPG 17/51 and GIU 092/19, the Basque Government (Saiotek SA-2010/00028, ELEKIN, Engineering and Society and Bioengineering, and ELKARTEK 18/99), "Ministerio de Ciencia e Innovacion" (SAF2016 77758 R), FEDER funds, the European Union COST Action (CA15225, CA18106), DomusVi Foundation (FP18/76), and Government of Gipuzkoa (HELENA: Multisensory stimulation tools for Alzheimer Disease). CR appreciates the previous economic support received from UPV/EHU and the current postdoctoral fellowship received from Alfonso Martin Escudero Foundation

Automatic Analysis of Archimedes’ Spiral for Characterization of Genetic Essential Tremor Based on Shannon’s Entropy and Fractal Dimension

Among neural disorders related to movement, essential tremor has the highest prevalence; in fact, it is twenty times more common than Parkinson's disease. The drawing of the Archimedes' spiral is the gold standard test to distinguish between both pathologies. The aim of this paper is to select non-linear biomarkers based on the analysis of digital drawings. It belongs to a larger cross study for early diagnosis of essential tremor that also includes genetic information. The proposed automatic analysis system consists in a hybrid solution: Machine Learning paradigms and automatic selection of features based on statistical tests using medical criteria. Moreover, the selected biomarkers comprise not only commonly used linear features (static and dynamic), but also other non-linear ones: Shannon entropy and Fractal Dimension. The results are hopeful, and the developed tool can easily be adapted to users; and taking into account social and economic points of view, it could be very helpful in real complex environments.This research was partially funded by the Basque Goverment, the University of the Basque Country by the IT1115-16 project-ELEKIN, Diputacion Foral de Gipuzkoa, University of Vic-Central University of Catalonia under the research grant R0947, and the Spanish Ministry of Science and Innovation TEC2016-77791-C04-R

Euskarazko hizketa jarraituaren ezagutza automatikoa eredu estokastikoen bidez

Erabiltzaile-makina komunikazio natural bat garatzeko sistemarako erabiltzaileari ezaguna egingo zaion hizkuntza bat definitu behar da lehendabizi. hizketa-ezagutza automatikorako sistemek (Automatic Speech Recognition, ASR) normalean konfigurazio-tresnak dituzte erabiltzaileak nahi duen hizkuntza aukeratzeko. Teknologia berrietan, beste arlo batzuetan bezala, gehien erabiltzen diren hizkuntzak batzuk besterik ez direla ezin uka daiteke, batetik, hiztun kopuru handia dutelako (ingelesak, frantsesak, gaztelaniak, e.a.), eta, bestetik, gizarte eleaniztun batean komunikazioa errazten duten hizkuntzak erabiltzeko beharragatik. @@ Hizketaren tratamenduaren eremuan, non helburu nagusia erabiltzailearentzako interfaze lagunkoien garapena den, erabiltzaileak erosoen erabiliko duen hizkuntza aukeratu ahal izatea beharrezkoa da. Hauxe da sistema eleanitzen garapena sasoi betean egotearen arrazoia. Hizketaren tratamendua gero eta garatuago dago hiztun gehiengoa duten hizkuntzen kasuan (ingelesa, gaztelania, frantsesa, e.a.) eta horietarako sistema oso aurreratuak eta prestazio handikoak dituzte. Hizkuntza minorizatuen kasuan, berriz, aurrerapenak askoz erritmo mantsoagoan gauzatzen dira, dudarik gabe, interes komertzial faltagatik. Dena dela, azken urteotan ahalegin handiak egin dira. Hedapen handikoak ez diren hizkuntzen aurrerapenaren adibide bat azken belaunaldiko sistema eleanitzak dira. Sistema horietan, aldez aurretiko konfiguraziorik gabeko sistema naturalagoa sortu nahi dute, aldi berean erabilitako hizkuntzetarako sistemaren baliabideak optimizatu nahirik. Sistema mota hauen ugaritzeak eta baliabideen optimizazio handiagoaren bilaketak, turkiera bezala hainbeste ikertu ez diren hizkuntzetan oinarritutako ikerketak bultzatu dituzte. Hauek ASR sistemetara aplika daitezkeen hizkuntza ezberdinen egitura eta hotsei buruzko ezagutza berriak dakartzate. @@ Tesi honek, baliabideen garapena eta euskararako hizketa jarraituaren ezagutzarako sistemei (Continuous Speech Recognition, CSR) eskainitako hamar urtetako prozesuari amaiera jartzen dio. Zentzu honetan euskaraz egindako lehenengo lana da hau. Ikerkuntza-lan honetan beste hizkuntza batzuetan ezagutzen genituen esfortzu, lan eta emaitzak berresan behar izan ditugu eta hizketaren ezagutze automatikorako sistemen (Automatic Speech Recognition, ASR) garapenaren alderdi askotan, gaiari buruzko azken ekarpenen berri jaso dugu ere bai. @@ Euskara, tesi-lan honek oinarri izan duen hizkuntza, Europan dagoen hizkuntza bizi zaharrenetakoa da eta azken urteotan hizkuntza honetarako sistema automatizatuen garapenean aurrerapen nabarmenak ikusi ditugu. ASRren eremuan egiten ari diren ikerketetan lagundu nahi du lan honek, baita hizketaren tratamenduari dagokionez euskararako dagoen hutsunea bete ere, lortutako emaitzetako batzuk ASR eremuan generikoki aplikatu ahal izateko asmoz. Beste alde batetik, lan honen garapena eta bertatik atera daitezkeen ikerketak, martxan dauden proiektu eleanitzetarako edo euskara erabiliko duten etorkizuneko proiektuetarako ekarpen eta erreferentzia garbia izango dira. Zehaztearren, lanak euskararako CSR sistema baten garapena du oinarr

Application of Entropy and Fractal Dimension Analyses to the Pattern Recognition of Contaminated Fish Responses in Aquaculture

The objective of the work was to develop a non-invasive methodology for image acquisition, processing and nonlinear trajectory analysis of the collective fish response to a stochastic event. Object detection and motion estimation were performed by an optical flow algorithm in order to detect moving fish and simultaneously eliminate background, noise and artifacts. The Entropy and the Fractal Dimension (FD) of the trajectory followed by the centroids of the groups of fish were calculated using Shannon and permutation Entropy and the Katz, Higuchi and Katz-Castiglioni's FD algorithms respectively. The methodology was tested on three case groups of European sea bass (Dicentrarchus labrax), two of which were similar (C1 control and C2 tagged fish) and very different from the third (C3, tagged fish submerged in methylmercury contaminated water). The results indicate that Shannon entropy and Katz-Castiglioni were the most sensitive algorithms and proved to be promising tools for the non-invasive identification and quantification of differences in fish responses. In conclusion, we believe that this methodology has the potential to be embedded in online/real time architecture for contaminant monitoring programs in the aquaculture industry.Grupo Tinamenor (Cantabria, Spain) is gratefully acknowledged for generously providing the European sea bass used in this work. We also wish to thank Urtzi Izagirre for his contribution to the design of the experimental treatments and to Xabier Lekube and Gregor Bwye for assistance with the fish during the experiment. The Spanish Ministry of Economy and Competitivity is gratefully acknowledged for the financial support to the project BMW: Biomarcadores estandar de base cientifica en mejillon, para diagnosticar y monitorizar los efectos biologicos de la polucion en el G. de Bizkaia: implementacion de la DEME (Grant no CTM2012-40203-C02-01)