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BACKGROUND: The partograph has been endorsed by World Health Organization (WHO) since 1994 which presents an algorithm for assessing maternal and foetal conditions and labor progression. Monitoring labour with a partograph can reduce adverse pregnancy outcomes such as prolonged labor, emergency C-sections, birth asphyxia and stillbirths. However, partograph use is still very low, particularly in low and middle income countries (LMICs). In Bangladesh the reported partograph user rate varies from 1.4% to 33.0%. Recently, an electronic version of the partograph, with the provision of online data entry and user aid for emergency clinical support, has been tested successfully in different settings. With this proven evidence, we conducted and operations research to test the feasibility and effectiveness of implementing an e-partograph, for the first time, in 2 public hospitals in Bangladesh.METHODS: We followed a prospective crossover design. Two secondary level referral hospitals, Jessore and Kushtia District Hospital (DH) were the study sites. All pregnant women who delivered in the study hospitals were the study participants. All nurse-midwives working in the labor ward of study hospitals were trained on appropriate use of both types of partograph along with standard labour management guidelines. Collected quantitative data was analyzed using SPSS 23 statistical software. Discrete variables were expressed as percentages and presented as frequency distribution and cross tabulations. Chi square tests were employed to test the association between exposure and outcome variables. Potential confounding factors were adjusted using multivariate binary logistic regression methods. Ethical approval was obtained from the institutional review board of the International Centre for Diarrheal Disease Research, Bangladesh (icddr,b).FINDINGS: In total 2918 deliveries were conducted at Jessore DH and 2312 at Kushtia DH during one-year study period. Of them, 1012 (506 in each facility) deliveries were monitored using partograph (paper or electronic). The trends of facility based C-section rates was downwards in both the hospitals; 43% to 37% in Jessore and from 36% to 25% in Kushtia Hospital. There was a significant reduction of prolonged labour with e-partograph use. In Kushtia DH, the prolonged labour rate was 42% during phase 1 with the paper version which came down to 29% during phase-2 with the e-partograph use. The similar result was observed in Jessore DH where the prolonged labour rate reduced to 7% with paper partograph from the reported 30% prolonged labour with e-partograph. The e-partograph user rate was higher than the paper partograph during both phases (phase 1: 3.31, CI: 2.04-5.38, p < .001 and in phase 2: 15.20 CI: 6.36-36.33, p < .001) after adjusting for maternal age, parity, gestational age, religion, mother's education, husband's education, and fetal sex.CONCLUSION: The partograph user rate has significantly improved with the e- partograph and was associated with an overall reduction in cesarean births. Use of the e-partograph was also associated with reduced rates of prolonged labour. This study has added to the growing body of evidence on the positive impact of e-partograph use. We recommend implementing e-partograph intervention at scale in both public and private hospitals in Bangladesh.TRIAL REGISTRATION: ClinicalTrials.gov NCT03509103.

Introduction This study investigates the profiles of 25 faculty members of the area of Social and Legal Sciences, from seven Spanish universities, who were selected by students with disabilities. Specifically, the aim of this paper is to understand why, despite their lack of pedagogical and disability training, they are considered to be inclusive faculty members. Objective For this purpose, we analysed the professional characteristics of these academics, their conceptions about disability, what actions they carry out to provide an inclusive response and how they consider that the current situation of university students with disabilities could be improved. Methods Semi-structured individual interviews were used to collect the data. Subsequently, a progressive analysis of the data was performed, using an inductive system of categories and codes. Results and conclusions The results show that these faculty are responsible, involved and committed to their teaching performance. Moreover, they regard reasonable adjustments as a fundamental requirement to handle the different needs of students with disabilities. This paper-which can also be useful for faculty and researchers in other areas of knowledge-comes to the conclusion that training is relevant for becoming an inclusive faculty member. Nevertheless, good will and eagerness to do one's job properly are even more important aspects., This work was supported by the Ministry of Economy and Competitiveness of Spain and ERDF funds [grant numbers EDU2016-76587-R]. https://portal.mineco.gob.es/es-es/Paginas/default.aspx NO.

Multi-robot task allocation is one of the main problems to address in order to design a multi-robot system, very especially when robots form coalitions that must carry out tasks before a deadline. A lot of factors affect the performance of these systems and among them, this paper is focused on the physical interference effect, produced when two or more robots want to access the same point simultaneously. To our best knowledge, this paper presents the first formal description of multi-robot task allocation that includes a model of interference. Thanks to this description, the complexity of the allocation problem is analyzed. Moreover, the main contribution of this paper is to provide the conditions under which the optimal solution of the aforementioned allocation problem can be obtained solving an integer linear problem. The optimal results are compared to previous allocation algorithms already proposed by the first two authors of this paper and with a new method proposed in this paper. The results obtained show how the new task allocation algorithms reach up more than an 80% of the median of the optimal solution, outperforming previous auction algorithms with a huge reduction of the execution time., This work has been partially supported by project DPI2014-57746-C03-2-R and FEDER funds.

In this paper we propose a method to create data-driven mappings from components of cognitive models to brain regions. Cognitive models are notoriously hard to evaluate, especially based on behavioral measures alone. Neuroimaging data can provide additional constraints, but this requires a mapping from model components to brain regions. Although such mappings can be based on the experience of the modeler or on a reading of the literature, a formal method is preferred to prevent researcher-based biases. In this paper we used model-based fMRI analysis to create a data-driven model-brain mapping for five modules of the ACT-R cognitive architecture. We then validated this mapping by applying it to two new datasets with associated models. The new mapping was at least as powerful as an existing mapping that was based on the literature, and indicated where the models were supported by the data and where they have to be improved. We conclude that data-driven model-brain mappings can provide strong constraints on cognitive models, and that model-based fMRI is a suitable way to create such mappings.

Suids (Sus sp.) played a crucial role in the transition to farming in northern Europe and, like in many regions, in the Netherlands pig husbandry became an important subsistence activity at Neolithic sites. Yet little is known about wild boar palaeoecology and hunting in the Late Mesolithic Netherlands with which to contextualize this transition. This paper presents the first multi-proxy analysis of archaeological suid remains in the Netherlands. It explores human-suid interactions at the Swifterbant culture sites of Hardinxveld-Giessendam Polderweg and De Bruin (5450–4250 BC) through biometric analysis, estimation of age-at-death, and stable carbon and nitrogen isotope analysis. The results reveal targeted hunting of adult wild boar in the Late Mesolithic (5450–4850 BC), with a possible shift over time towards more juveniles. The wild boar in this period are demonstrated to be of comparably large size to contemporary northern European populations and exhibiting a wide range of dietary regimes. In the final occupational period (4450–4250 BC), small suids are present, possibly domestic pigs, but there is no evidence of pig management. This study demonstrates that the nature of human-suid interactions varied over time, which may have been connected to changing environmental conditions, human mobility, and wild boar behaviour. This study also contributes the first biometric and dietary baseline for mid-Holocene wild boar in the Netherlands.

The attentional blink (AB) phenomenon reveals a bottleneck of human information processing: the second of two targets is often missed when they are presented in rapid succession among distractors. In our previous work, we showed that the size of the AB can be changed by applying transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (lDLPFC) (London & Slagter, Journal of Cognitive Neuroscience, 33, 756–68, 2021). Although AB size at the group level remained unchanged, the effects of anodal and cathodal tDCS were negatively correlated: if a given individual’s AB size decreased from baseline during anodal tDCS, their AB size would increase during cathodal tDCS, and vice versa. Here, we attempted to replicate this finding. We found no group effects of tDCS, as in the original study, but we no longer found a significant negative correlation. We present a series of statistical measures of replication success, all of which confirm that both studies are not in agreement. First, the correlation here is significantly smaller than a conservative estimate of the original correlation. Second, the difference between the correlations is greater than expected due to sampling error, and our data are more consistent with a zero-effect than with the original estimate. Finally, the overall effect when combining both studies is small and not significant. Our findings thus indicate that the effects of lDPLFC-tDCS on the AB are less substantial than observed in our initial study. Although this should be quite a common scenario, null findings can be difficult to interpret and are still under-represented in the brain stimulation and cognitive neuroscience literatures. An important auxiliary goal of this paper is therefore to provide a tutorial for other researchers, to maximize the evidential value from null findings.

The increasingly globalized workforce and the growing need for boosting employee energy have engendered both practical and research interest in stimulating employee energy in intercultural interactions. Yet neither the culture research nor the energy literature has explored the link between cultural distance and employee relational energy—the heightened level of psychological resources in social relations. This paper presents empirical evidence of cultural distance stimulating relational energy. Further, building upon the threat-rigidity theory, I propose that cultural distance stimulates relational energy more when employees perceive high levels of psychological safety. Two studies were conducted to test these two hypotheses. One laboratory experiment on 202 international students at a Dutch university provided causal evidence of the positive relationship between cultural distance and relational energy. Next, a two-wave field study on 373 international employees was conducted to replicate this main effect of cultural distance and further investigate the moderating role of psychological safety. Results supported that employees with higher levels of psychological safety are more prone to experience enhanced relational energy as a result of cultural distance. These findings contribute to the scarce research on possible positive influence of cross-cultural communication at work, and also advance the growing research on the antecedents of employee relational energy. The implications for practitioners to energize employees are also discussed.

Background Influenza illness burden is substantial, particularly among young children, older adults, and those with underlying conditions. Initiatives are underway to develop better global estimates for influenza-associated hospitalizations and deaths. Knowledge gaps remain regarding the role of influenza viruses in severe respiratory disease and hospitalizations among adults, particularly in lower-income settings. Methods and findings We aggregated published data from a systematic review and unpublished data from surveillance platforms to generate global meta-analytic estimates for the proportion of acute respiratory hospitalizations associated with influenza viruses among adults. We searched 9 online databases (Medline, Embase, CINAHL, Cochrane Library, Scopus, Global Health, LILACS, WHOLIS, and CNKI; 1 January 1996–31 December 2016) to identify observational studies of influenza-associated hospitalizations in adults, and assessed eligible papers for bias using a simplified Newcastle–Ottawa scale for observational data. We applied meta-analytic proportions to global estimates of lower respiratory infections (LRIs) and hospitalizations from the Global Burden of Disease study in adults ≥20 years and by age groups (20–64 years and ≥65 years) to obtain the number of influenza-associated LRI episodes and hospitalizations for 2016. Data from 63 sources showed that influenza was associated with 14.1% (95% CI 12.1%–16.5%) of acute respiratory hospitalizations among all adults, with no significant differences by age group. The 63 data sources represent published observational studies (n = 28) and unpublished surveillance data (n = 35), from all World Health Organization regions (Africa, n = 8; Americas, n = 11; Eastern Mediterranean, n = 7; Europe, n = 8; Southeast Asia, n = 11; Western Pacific, n = 18). Data quality for published data sources was predominantly moderate or high (75%, n = 56/75). We estimate 32,126,000 (95% CI 20,484,000–46,129,000) influenza-associated LRI episodes and 5,678,000 (95% CI 3,205,000–9,432,000) LRI hospitalizations occur each year among adults. While adults, In this meta-analysis, Kathryn E. Lafond and colleagues estimate the global hospitalisation burden from influenza infections in adults., Author summary Why was this study done? Every year, millions of people become infected with influenza viruses, which infect the airways and cause symptoms that include a fever, tiredness and weakness, general aches and pains, sore throat, and cough. Most infected individuals recover quickly, but some develop more severe illness such as pneumonia, and may require hospitalization. Influenza vaccination can prevent infections and severe disease, but decisions on how to prioritize risk groups, particularly in limited-resource settings, require a robust evidence base, including global, regional, and local data. What did the researchers do and find? We conducted a systematic review to identify published articles on influenza-associated respiratory disease in hospitalized adults. We then aggregated the data from these articles with data collected by hospital-based influenza surveillance, to calculate a pooled estimate of the proportion of adults hospitalized with respiratory disease who are positive for influenza. Through this approach, we estimated that influenza was associated with 14% of acute respiratory hospitalizations among adults worldwide. This equates to over 5 million influenza-associated hospitalizations per year, with the highest rates among those 65 years and older. What do these findings mean? Estimating the disease burden of influenza allows researchers and policymakers to better understand its global impact across different target groups and allows comparisons with other causes of morbidity and mortality. As global populations age, the importance of vaccinating adults, particularly older adults, is likely to increase.

Made available in DSpace on 2021-06-25T10:53:23Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-02-01 Alder Hey Children's NHS Foundation Trust The aim of this study was to examine aspects of children's health literacy; the information sources they were accessing, their information preferences, their perceived understanding of and their reported information needs in relation to COVID-19. An online survey for children aged 7-12 years of age and parent/caregivers from the UK, Sweden, Brazil, Spain, Canada and Australia was conducted between 6th of April and the 1st of June 2020. The surveys included demographic questions and both closed and open questions focussing on access to and understanding of COVID-19 information. Descriptive statistics and qualitative content analysis procedures were conducted. The findings show that parents are the main source of information for children during the pandemic in most countries (89%, n = 347), except in Sweden where school was the main source of information. However, in many cases parents chose to shield, filter or adapt their child's access to information about COVID-19, especially in relation to the death rates within each country. Despite this, children in this study reported knowing that COVID-19 was deadly and spreads quickly. This paper argues for a community rather than individual approach to addressing children's health literacy needs during a pandemic. Faculty of Health Social Care and Medicine Edge Hill University UQO Departement de Sciences Infirmieres Botucatu Medical School - Unesp - Nursing Department Centre for Education and Research - Nursing and Midwifery Tasmanian Health Service South and University of Tasmania Sant Joan de Deu Research Foundation Department of Nursing Faculty of Medicine Umea University Institute of Health and Care Sciences Centre for Person-Centred Care Sahlgrenska Academy University of Gothenburg Department of Health Sciences Department of Learning The Swedish Red Cross University College Informatics Management and Ethics LIME Karolinska Institutet Keele Medical School Faculty of Medicine and Health Sciences Keele University Botucatu Medical School - Unesp - Nursing Department

In order to understand and represent the importance of nodes within networks better, most of the studies that investigate graphs compute the nodes' centrality within their network(s) of interest. In the literature, the most frequent measures used are degree, closeness and/or betweenness centrality, even if other measures might be valid candidates for representing the importance of nodes within networks. The main contribution of this paper is the development of a methodology that allows one to understand, compare and validate centrality indices when studying a particular network of interest. The proposed methodology integrates the following steps: choosing the centrality measures for the network of interest; developing a theoretical taxonomy of these measures; identifying, by means of Principal Component Analysis (PCA), latent dimensions of centrality within the network of interest; verifying the proposed taxonomy of centrality measures; and identifying the centrality measures that best represent the network of interest. Also, we applied the proposed methodology to an existing graph of interest, in our case a real friendship student network. We chose eighteen centrality measures that were developed in SNA and are available and computed in a specific library (CINNA), defined them thoroughly, and proposed a theoretical taxonomy of these eighteen measures. PCA showed the emergence of six latent dimensions of centrality within the student network and saturation of most of the centrality indices on the same categories as those proposed by the theoretical taxonomy. Additionally, the results suggest that indices other than the ones most frequently applied might be more relevant for research on friendship student networks. Finally, the integrated methodology that we propose can be applied to other centrality indices and/or other network types than student graphs. ispartof: PLOS ONE vol:15 issue:12 ispartof: location:United States status: published

Social axioms or general social beliefs represent people’s cognitive map of their social world acquired through social experiences. Empirical research has related the central constructs in the study of psychology and social axioms, establishing a broad nomological network in various cultural settings. This paper studies the validity of the Social Axioms Survey II (SASII) short form, Spanish version, on the individual level in Melilla as North Africa´s borderland. Participants were 410 high school students from 14 to 18 years of age. The reliability analysis, the discriminant validity analysis, and the confirmatory factor analysis through the structural model equation, showed similar results to previous studies in other contexts and allowing the use of the survey in Melilla. In addition it is presented a fitted model that improves the psychometric results showing significant differences with the initial model. The confirmatory multi-group analysis of the fitted model shows measurement invariance across educational centers, allowing new research possibilities in the cultural context of Melilla.

Background The psychological health of female sex workers (FSWs) has emerged as a major public health concern in many low- and middle-income countries (LMICs). Key risk factors include poverty, low education, violence, alcohol and drug use, human immunodeficiency virus (HIV), and stigma and discrimination. This systematic review and meta-analysis aimed to quantify the prevalence of mental health problems among FSWs in LMICs, and to examine associations with common risk factors. Method and findings The review protocol was registered with PROSPERO, number CRD42016049179. We searched 6 electronic databases for peer-reviewed, quantitative studies from inception to 26 April 2020. Study quality was assessed with the Centre for Evidence-Based Management (CEBM) Critical Appraisal Tool. Pooled prevalence estimates were calculated for depression, anxiety, post-traumatic stress disorder (PTSD), and suicidal behaviour. Meta-analyses examined associations between these disorders and violence, alcohol/drug use, condom use, and HIV/sexually transmitted infection (STI). A total of 1,046 studies were identified, and 68 papers reporting on 56 unique studies were eligible for inclusion. These were geographically diverse (26 countries), representing all LMIC regions, and included 24,940 participants. All studies were cross-sectional and used a range of measurement tools; none reported a mental health intervention. Of the 56 studies, 14 scored as strong quality, 34 scored as moderate, and 8 scored as weak. The average age of participants was 28.9 years (age range: 11–64 years), with just under half (46%) having up to primary education or less. The pooled prevalence rates for mental disorders among FSWs in LMICs were as follows: depression 41.8% (95% CI 35.8%–48.0%), anxiety 21.0% (95% CI: 4.8%–58.4%), PTSD 19.7% (95% CI 3.2%–64.6%), psychological distress 40.8% (95% CI 20.7%–64.4%), recent suicide ideation 22.8% (95% CI 13.2%–36.5%), and recent suicide attempt 6.3% (95% CI 3.4%–11.4%). Meta-analyses found significant associations between violence experience and depression, violence experience and recent suicidal behaviour, alcohol use and recent suicidal behaviour, illicit drug use and depression, depression and inconsistent condom use with clients, and depression and HIV infection. Key study limitations include a paucity of longitudinal studies (necessary to assess causality), non-random sampling of participants by many studies, and the use of different measurement tools and cut-off scores to measure mental health problems and other common risk factors. Conclusions In this study, we found that mental health problems are highly prevalent among FSWs in LMICs and are strongly associated with common risk factors. Study findings support the concept of overlapping vulnerabilities and highlight the urgent need for interventions designed to improve the mental health and well-being of FSWs., Tara Beattie and co-workers assess the evidence on mental ill-health in female sex workers in low- and middle-income countries., Author summary Why was this study done? Understanding the prevalence of mental health problems, and key risk factors associated with poor mental health, is essential for building evidence-based prevention. To our knowledge, there has been no previous quantitative synthesis of the literature examining the prevalence of mental health problems among female sex workers (FSWs) in low- and middle-income countries (LMICs). This evidence is critical to inform evidence-based policymaking and intervention design and is timely given the growing interest in mental health globally. What did the researchers do and find? We undertook a quantitative systematic review to estimate the prevalence of mental health problems and to estimate the magnitude of associations between mental health problems and sex workers’ experience of violence, harmful alcohol and drug use, condom use, and human immunodeficiency virus (HIV) and sexually transmitted infections (STIs). Meta-analyses across 31 studies with 18,524 FSWs in 17 LMICs suggest that mental health problems—including depression, anxiety, post-traumatic stress disorder (PTSD), and suicidal thoughts and attempts—are highly prevalent among FSWs. Sex workers with a mental health problem were more likely to have experienced violence, to report harmful alcohol or drug use, to report inconsistent condom use with clients (but not regular partners), and to be HIV positive compared with sex workers who did not have a mental health problem (18 studies with 14,115 FSWs). What do these findings mean? The quantitative evidence clearly demonstrates that mental health problems are an important burden of disease experienced by many FSWs in LMICs, with levels substantially greater than those experienced by women in the general population. As no study described a mental health intervention, evidence-based mental health interventions for FSWs are urgently required to address the current treatment gap. The prevention and treatment of key risk factors such as violence and harmful alcohol and drug use would also help improve the mental health of FSWs. Longitudinal research is needed in order to unpack pathways of causation. Future studies should use validated tools and consistent cut-offs and timeframes to enable more rigorous comparisons between studies.

IntroductionHigh rates of pre-treatment loss to care among persons diagnosed with HIV persist. Linkage to care can be improved through active digitally-based surveillance. Currently, record-keeping for HIV diagnoses in South Africa is paper-based. Aggregated testing data are reported routinely, and only discordant findings result in a specimen being tested at a laboratory and digitised. The Western Cape Province in South Africa has a Provincial Health Data Centre (PHDC) where person-level routine electronic data are consolidated in a single database, leveraging the existence of a unique patient identifier. To facilitate improved HIV surveillance, a pre-carbonated point-of-care test (PoCT) form was piloted, where one copy was routed to a central point and digitised for PHDC inclusion.MethodsWe evaluated the utility of the intervention using cross-sectional and retrospective cohort analyses, as well as comparisons with aggregate data. Data were linked to the Patient Master Index of the PHDC using unique identifiers. Prior evidences of HIV within the PHDC were used to differentiate newly diagnosed patients and those retesting, as well as linkage to care and treatment.ResultsFrom May 2017 to June 2018, 11337 digitised point-of-care HIV testing records were linked to the PHDC. Overall, 96% of records in the aggregate dataset were digitised, with 97% linked to the PHDC. Of those tested, 79% were female (median age 27 years). Linkage demonstrated that 51.3% (95% CI 48.4-54.1%) of patients testing HIV-positive were retesting. Of those newly diagnosed, 81% (95% CI 77.9-84.3%) were linked to HIV care and 25% (95% CI 21.6-28.7%) were initiated on antiretroviral therapy immediately.ConclusionDigitisation of PoCT results provides individuated HIV testing data to assist in linkage to care and in differentiating newly diagnosed patients from positive patients retesting. Actionable and accurate data can improve the measurement of performance towards the UNAIDS 90-90-90 targets.

PubMed: 32271853 In this paper, we generalize and compare Gompertz and Logistic dynamic equations in order to describe the growth patterns of bacteria and tumor. First of all, we introduce two types of Gompertz equations, where the first type 4-paramater and 3-parameter Gompertz curves do not include the logarithm of the number of individuals, and then we derive 4- parameter and 3-parameter Logistic equations. We notice that Logistic curves are better in modeling bacteria whereas the growth pattern of tumor is described better by Gompertz curves. Increasing the number of parameters of Logistic curves give favorable results for bacteria while decreasing the number of parameters of Gompertz curves for tumor improves the curve fitting. Moreover, our results overshadow some of the existing results in the literature. © 2020 This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Recent studies suggest that a large proportion of new HIV-1 infections in mature epidemics occurs within discordant couples, making discordancy a major contributor to the spread of HIV/AIDS in Africa. This paper aims at assessing changes over a five-year period (2009-2015) on the (risk) factors associated with HIV serodiscordance among couples in Mozambique, using cross-sectional data from the INSIDA and IMASIDA surveys. The pooled data of both surveys were analyzed using a joint model for three parameters characterizing in a particular way disagreement and sero(con/dis)corance between the HIV statuses of couples, as introduced by Aerts et al.: the probability that the female partner is HIV positive, given that both partners differ in their HIV status, the probability that only one partner is HIV positive, given that at least one of the two partners is positive ("positive" serodiscordance), and the probability that both partners are negative given that at most one of the two partners is positive ("negative" seroconcordance). The results reveal similar significant factors and estimates as in Aerts et al. (HIV prevalence, union number for woman, STI for man, condom use by woman and wealth index), but the additional significant factors "condom use by man" (no use had a negative effect on the positive serodiscordance) and "union number for man" (for couples where the man has been married or co-habiting with a woman before had a decreased negative seroconcordance) were identified. The only factor that had a different effect over time (IMASIDA as compared to INSIDA) was the effect of "HIV prevalence of province" on the negative seroconcordance. The negative effect of a higher HIV prevalence was less pronounced in 2015 for negative seroconcordance. This study was financially supported by the Flemish Interuniversity Council (VLIR-UOS) in collaboration with Eduardo Mondlane University (UEM) through the DESAFIO Program, in Mozambique to AJCJ. Juga, AJC (corresponding author), Eduardo Mondlane Univ, Fac Sci, Dept Math & Informat, Maputo, Mozambique; Hasselt Univ, Data Sci Inst, I BioStat, Diepenbeek, Belgium. adelino.juga@gmail.com

Multiword Expressions (MWEs) are idiosyncratic combinations of words which pose important challenges to Natural Language Processing. Some kinds of MWEs, such as verbal ones, are particularly hard to identify in corpora, due to their high degree of morphosyntactic flexibility. This paper describes a linguistically motivated method to gather detailed information about verb+noun MWEs (VNMWEs) from corpora. Although the main focus of this study is Spanish, the method is easily adaptable to other languages. Monolingual and parallel corpora are used as input, and data about the morphosyntactic variability of VNMWEs is extracted. This information is then tested in an identification task, obtaining an F score of 0.52, which is considerably higher than related work. This work was funded by the Basque Government, who qualified the IXA research group (of which the authors of this article are members) as an A type research group (IT1343-19). It is also part of the project entitled "MODENA: advanced neural modeling for high-quality translation" (KK-2018/00087).

Dengue and influenza-like illness (ILI) are two of the leading causes of viral infection in the world and it is estimated that more than half the world’s population is at risk for developing these infections. It is therefore important to develop accurate methods for forecasting dengue and ILI incidences. Since data from multiple sources (such as dengue and ILI case counts, electronic health records and frequency of multiple internet search terms from Google Trends) can improve forecasts, standard time series analysis methods are inadequate to estimate all the parameter values from the limited amount of data available if we use multiple sources. In this paper, we use a computationally efficient implementation of the known variable selection method that we call the Autoregressive Likelihood Ratio (ARLR) method. This method combines sparse representation of time series data, electronic health records data (for ILI) and Google Trends data to forecast dengue and ILI incidences. This sparse representation method uses an algorithm that maximizes an appropriate likelihood ratio at every step. Using numerical experiments, we demonstrate that our method recovers the underlying sparse model much more accurately than the lasso method. We apply our method to dengue case count data from five countries/states: Brazil, Mexico, Singapore, Taiwan, and Thailand and to ILI case count data from the United States. Numerical experiments show that our method outperforms existing time series forecasting methods in forecasting the dengue and ILI case counts. In particular, our method gives a 18 percent forecast error reduction over a leading method that also uses data from multiple sources. It also performs better than other methods in predicting the peak value of the case count and the peak time., Author summary Dengue and influenza-like illness (ILI) are leading causes of viral infection in the world and hence it is important to develop accurate methods for forecasting their incidence. We use Autoregressive Likelihood Ratio method, which is a computationally efficient implementation of the variable selection method, in order to obtain a sparse (non-lasso) representation of time series, Google Trends and electronic health records (for ILI) data. This method is used to forecast dengue incidence in five countries/states and ILI incidence in USA. We show that this method outperforms existing time series methods in forecasting these diseases. The method is general and can also be used to forecast other diseases.

Cereals, in addition to being a major ingredient in daily meals, also play a role in the preparation of foodstuffs for ritual purposes. This paper deals with finds that may correspond to such ritual preparations retrieved from the hillfort site of Stillfried an der March. The site, spreading across an area of ca. 23 ha, held a very important position among settlements of Late Urnfield period (particularly during the 10th- 9th c. BCE), acting as a central place where large scale storage of grain as well as textile and metal production took place under the control of local elites. Three incomplete ring-shaped charred organic objects, found together with 14 rings and ring fragments made of clay were discovered in a secondary filled silo pit, excavated among a total of about 100 pits of this kind at the site. The overall good state of preservation of the organic ring fragments suggests that they were deposited intact on the bottom of the pit and covered well so that no re-deposition or damage occurred. This could be indicate their intentional placement in this position. Light and scanning electron microscopy revealed that the charred organic rings are cereal products containing hulled barley and a wheat species. Indications that the objects were shaped from a wet cereal mixture and had been subsequently dried without baking are discussed, as well as the possible significance of the find assemblage. The annular objects are put in context with the contemporary cereal spectrum as well as other cereal preparations from Stillfried, outlining their different chaînes opératoires for handling cereal food. ispartof: PLOS ONE vol:14 issue:6 ispartof: location:United States status: published

We generalize the notion of lambda-superstrings, presented in a previous paper, to the notion of weighted lambda-superstrings. This generalization entails an important improvement in the applications to vaccine designs, as it allows epitopes to be weighted by their immunogenicities. Motivated by these potential applications of constructing short weighted lambda-superstrings to vaccine design, we approach this problem in two ways. First, we formalize the problem as a combinatorial optimization problem (in fact, as two polynomially equivalent problems) and develop an integer programming (IP) formulation for solving it optimally. Second, we describe a model that also takes into account good pairwise alignments of the obtained superstring with the input strings, and present a genetic algorithm that solves the problem approximately. We apply both algorithms to a set of 169 strings corresponding to the Nef protein taken from patiens infected with HIV-1. In the IP-based algorithm, we take the epitopes and the estimation of the immunogenicities from databases of experimental epitopes. In the genetic algorithm we take as candidate epitopes all 9-mers present in the 169 strings and estimate their immunogenicities using a public bioinformatics tool. Finally, we used several bioinformatic tools to evaluate the properties of the candidates generated by our method, which indicated that we can score high immunogenic lambda-superstrings that at the same time present similar conformations to the Nef virus proteins. This research was supported in part by the Basque Government, grants IT753-13 and IT974-16 and by the UPV/EHU and Basque Center of Applied Mathematics, grant US18/21. This research was also in part by the Slovenian Research Agency (I0-0035, research program P1-0285, and research projects N1-0032, J1-7051, and J1-9110). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

BackgroundHealthcare coverage in Ethiopia has improved dramatically in recent decades. However, facility-based delivery remains persistently low, while maternal mortality remains high. This paper presents the prevalence and associated factors of disrespect and abuse (D&A) during childbirth in public health facilities of western Oromia, Ethiopia.MethodA facility-based cross-sectional study was conducted among 612 women from February 2017 to May 2017. Exit interview with the mothers were conducted upon discharge from the maternity ward. We measured D&A during childbirth using seven dimensions. Multivariable logistic regression model was used to assess the association between experience of D&A and client characteristics and institutional factors.ResultThree quarters (74.8%) of women reported experiencing at least one form of D&A during their facility childbirth. The types of D&A experienced by the women were; physical abuse (37.1%), non-dignified care (34.6%), non-consented care (54.1%), non-confidential care (40.4%), neglect (25.2%), detention (2.9%), and discrimination (13.2%). Experiences of D&A were 1.6 times more likely to be reported by women delivering at hospitals than health centers (OR: 1.64, 95% CI: 1.01, 2.66). Women without a companion throughout their delivery were almost 10 times more likely than women who had a companion to encounter D&A (OR: 9.94, 95% CI: 5.72, 17.28). On the other hand, women with more than 1,368-birr (USD 57) monthly income were less likely to experience any type of D&A (OR: 0.36, 95% CI: .21, .65).ConclusionThree in four women reported experiencing at least one form of D&A during labor and delivery. This demonstrates a real disconnect between what the health system intends to achieve and what is practiced and calls for fundamental solutions in terms of both improving quality of facility-based delivery and ensuring women's right to receive health care with dignity.

First published online: August 7, 2019 Institution-centered accounts of generalized trust rely on the idea that law-breaking and state's unfairness lower individuals' propensity to trust fellow citizens because of a weaker confidence in the state. Despite the theoretical relevance attributed to this mediation mechanism, no empirical analysis in the literature has focused on examining its correlational validity. Using data from the European Social Survey (2010), the Quality of Government EU Regional data, and EUROSTAT, this paper assesses the intervening role of institutional trust on the relationship between crime rates, state's fairness, and generalized trust. Results from a Multilevel SEM (MSEM) mediation analysis indicate that trust in institutions strongly mediates the relationship between violent crimes (i.e. homicide) and generalized trust but not the one between property crimes (i.e. vehicle thefts and robberies) and generalized trust. On the other hand, indicators of fairness (i.e. impartiality and corruption) are all mediated by institutional trust, though impartiality maintains a significant direct effect. Overall, findings support the institutional approach, confirming that the negative relationship between ineffective and unfair institutions and generalized trust passes mostly through people's lost faith in the state. Economic & Social Research Council (ESRC) [ES/J500045/1]

A brain-computer interface (BCI), based on motor imagery EEG, uses information extracted from the electroencephalography signals generated by a person who intends to perform any action. One of the most important issues of current research is how to detect automatically whether the user intends to send some message to a certain device. This study presents a proposal, based on a hierarchical structured system, for recognising intentional and non-intentional mental tasks on a BCI system by applying machine learning techniques to the EEG signals. First-level clustering is performed to distinguish between intentional control (IC) and non-intentional control (NC) state patterns. Then, the patterns recognised as IC are passed on to a second stage where supervised learning techniques are used to classify them. In BCI applications, it is critical to correctly classify NC states with a low false positive rate (FPR) to avoid undesirable effects. According to the literature, we selected a maximum FPR of 10%. Under these conditions, our proposal achieved an average test accuracy of 66.6%, with an 8.2% FPR, for the BCI competition IIIa dataset. The main contribution of this paper is the hierarchical approach, based on machine learning paradigms, which performs intentional and non-intentional discrimination and, depending on the case, classifies the intended command selected by the user. This work was partially supported by the ERDF/Spanish Ministry of Science, Innovation and Universities - National Research Agency/PhysComp project, TIN2017-85409-P and by the Department of Education, Universities and Research of the Basque Government (ADIAN research group, grant IT980-16).

Lately, discourse structure has received considerable attention due to the benefits its application offers in several NLP tasks such as opinion mining, summarization, question answering, text simplification, among others. When automatically analyzing texts, discourse parsers typically perform two different tasks: i) identification of basic discourse units (text segmentation) ii) linking discourse units by means of discourse relations, building structures such as trees or graphs. The resulting discourse structures are, in general terms, accurate at intra-sentence discourse-level relations, however they fail to capture the correct inter-sentence relations. Detecting the main discourse unit (the Central Unit) is helpful for discourse analyzers (and also for manual annotation) in improving their results in rhetorical labeling. Bearing this in mind, we set out to build the first two steps of a discourse parser following a top-down strategy: i) to find discourse units, ii) to detect the Central Unit. The final step, i.e. assigning rhetorical relations, remains to be worked on in the immediate future. In accordance with this strategy, our paper presents a tool consisting of a discourse segmenter and an automatic Central Unit detector. This study was carried out within the framework of the following projects: IXA Group: natural language processing IT1343-19 (Basque Government), DL4NLP KK-2019/00045 (Basque Government), PROSA-MED TIN2016-77820-C3-1-R (MINECO) and DeepReading: RTI2018-096846-B-C21 (MCIU/AEI/FEDER, UE).

Needles are commonly used in the clinic for percutaneous procedures. The outcome of such procedures heavily depends on accurate placement of the needle. There are two main challenges to achieve high accuracy: First, aligning the needle with the targeted lesion, and second, compensating for the deflection of the needle in the tissue. In order to address these challenges, scientists have developed several robotic setups for needle steering. However, the subject is still under research and reliable implementations which can be used in clinical practice are not yet available. In this paper, we have taken some steps in order to bring needle steering closer to practice. A new hybrid control algorithm is developed, which enables us to control a flexible needle by combing base-manipulation and beveled-tip steering methods. A pre-operative path planner is developed which considers the clinical requirements. The proposed method is tested in the lung of a fresh-frozen human cadaver. The work-flow of the experiments are similar to the current clinical practice. Three experimental cases are used to evaluate the proposed steering algorithm. Experimental Case I shows that using the proposed steering algorithm controllability of the needle is increased. In Case II and Case III, the needle is steered in a gelatin phantom and a human cadaver, respectively. The targeting accuracy of 1.35 +/- 0.49mm in gelatin phantom and 1.97 +/- 0.89mm in cadave is achieved. A feasibility study is performed, in which a fine needle aspiration (FNA) needle is steered in the lungs of a human cadaver under computed tomography guidance. The targeting error for the feasibility study is 2.89 +/- 0.22mm. The results suggest that such a robotic system can be beneficial for clinical use and the patient receives less x-ray radiation.

TP53 is the most mutated gene in all cancers. The mutant protein also accumulates in cells. The high frequency of p53 mutations makes the protein a promising target for anti-cancer therapy. Only a few molecules have been found, using in vitro screening, to reactivate the mutant protein. APR-246 is currently the most successful mutant p53 activator, which reactivates the transcriptional activity of p53 by covalently binding to C124 of the protein. We have recently created in silico models of G245S-mp53 in its apo and DNA-bound forms. In this paper we further report on our in silico screening for potential activators of G245S-mp53. We filtered the ZINC15 database (13 million compounds) to only include drug-like molecules with moderate to standard reactivity. Our filtered database of 130,000 compounds was screened using the DOCKTITE protocol in the Molecular Operating Environment software. We performed covalent docking at C124 of G245S-mp53 to identify potential activators of the mutant protein. The docked compounds were ranked using a consensus scoring approach. We also used ADMET Predictor™ to predict pharmacokinetics and the possible toxicities of the compounds. Our screening procedure has identified compounds, mostly thiosemicarbazones and halo-carbonyls, with the best potential as G245S-mp53 activators, which are described in this work. Based on its binding scores and ADMET risk score, compound 2 is likely to have the best potential as a G245S-mp53 activator compared to the other top hits.

Background This is an extension of a paper published earlier. We investigated the association between the tendency to detect speech illusion in random noise and levels of positive schizotypy in a sample of 185 adult healthy controls. Materials and methods Subclinical positive, negative and depressive symptoms were assessed with the Community Assessment of Psychic Experiences (CAPE); positive and negative schizotypy was assessed with the Structured Interview for Schizotypy-Revised (SIS-R). Results Speech illusions were associated with positive schizotypy (OR: 4.139, 95% CI: 1.074-15.938; p = 0.039) but not with negative schizotypy (OR: 1.151, 95% CI: 0.183-7.244; p = 0.881). However, the association of positive schizotypy with speech illusions was no longer significant after adjusting for age, sex and WAIS-III (OR: 2.577, 95% CI: 0.620-10.700; p = 0.192). Speech illusions were not associated with self-reported CAPE measures. Conclusions The association between schizotypy and the tendency to assign meaning in random noise in healthy controls may be mediated by cognitive ability and not constitute an independent trait.

Music genre classification is a challenging research concept, for which open questions remain regarding classification approach, music piece representation, distances between/within genres, and so on. In this paper an investigation on the classification of generated music pieces is performed, based on the idea that grouping close related known pieces in different sets -or clusters- and then generating in an automatic way a new song which is somehow "inspired" in each set, the new song would be more likely to be classified as belonging to the set which inspired it, based on the same distance used to separate the clusters. Different music pieces representations and distances among pieces are used; obtained results are promising, and indicate the appropriateness of the used approach even in a such a subjective area as music genre classification is. This work was supported by IT900-16 Research Team from the Basque Government.

Background: Many studies show large differences in life expectancy across the range of education, intelligence, and socio-economic status. As educational attainment, intelligence, and socio-economic status are highly interrelated, appropriate methods are required to disentangle their separate effects. The aim of this paper is to present a novel method to estimate gains in life expectancy specifically associated with increased education. Our analysis is based on a structural model in which education level, IQ at age 18 and mortality all depend on (latent) intelligence. The model allows for (selective) educational choices based on observed factors and on an unobserved factor capturing intelligence. Our estimates are based on information from health examinations of military conscripts born in 1944–1947 in The Netherlands and their vital status through age 66 (n = 39,798). Results: Our empirical results show that men with higher education have lower mortality. Using structural models to account for education choice, the estimated gain in life expectancy for men moving up one educational level ranges from 0.3 to 2 years. The estimated gain in months alive over the observational period ranges from -1.2 to 5.7 months. The selection effect is positive and amounts to a gain of one to two months. Decomposition of the selection effect shows that the gain from selection on (latent) intelligence is larger than the gain from selection on observed factors and amounts to 1.0 to 1.7 additional months alive. Conclusion: Our findings confirm the strong selection into education based on socio-economic status and intelligence. They also show significant higher life expectancy among individuals with higher education after the selectivity of education choice has been taken into account. Based on these estimates, it is plausible therefore that increases in education could lead to increases in life expectancy.

The model of population growth is revised in this paper. A new model is proposed based on the concept of fractional differentiation that uses the generalized Mittag-Leffler function as kernel of differentiation. The new model includes the choice of sexuality. The existence of unique solution is investigated and numerical solution is provided.

Preterm delivery affects about one tenth of human births and is associated with an increased perinatal morbimortality as well as with remarkable costs. Even if there are a number of predictors and markers of preterm delivery, none of them has a high accuracy. In order to find quantitative indicators of the immediacy of labor, 142 cardiotocographies (CTG) recorded from women consulting because of suspected threatened premature delivery with gestational ages comprehended between 24 and 35 weeks were collected and analyzed. These 142 samples were divided into two groups: the delayed labor group (n = 75), formed by the women who delivered more than seven days after the tocography was performed, and the anticipated labor group (n = 67), which corresponded to the women whose labor took place during the seven days following the recording. As a means of finding significant differences between the two groups, some key informational properties were analyzed by applying nonlinear techniques on the tocography recordings. Both the regularity and the persistence levels of the delayed labor group, which were measured by Approximate Entropy (ApEn) and Generalized Hurst Exponent (GHE) respectively, were found to be significantly different from the anticipated labor group. As delivery approached, the values of ApEn tended to increase while the values of GHE tended to decrease, suggesting that these two methods are sensitive to labor immediacy. On this paper, for the first time, we have been able to estimate childbirth immediacy by applying nonlinear methods on tocographies. We propose the use of the techniques herein described as new quantitative diagnosis tools for premature birth that significantly improve the current protocols for preterm labor prediction worldwide. Work by the first author was supported by the Basque Government grant PRE-2015-1-194,and work by the first and second authors by the Basque Government grant IT974-16. This work was also supported in part by FERRING laboratories Madrid, Spain (RM), https://www.ferring.com/en/home/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Maternal smoking during pregnancy is linked to reduced birth weight but the gestation at onset of this relationship is not certain. We present a systematic review of the literature describing associations between maternal smoking during pregnancy and ultrasound measurements of fetal size, together with an accompanying meta-analysis. Studies were selected from electronic databases (OVID, EMBASE and Google Scholar) that examined associations between maternal smoking or smoke exposure and antenatal fetal ultrasound measurements. Outcome measures were first, second or third trimester fetal measurements. There were 284 abstracts identified, 16 papers were included in the review and the meta-analysis included data from eight populations. Maternal smoking was associated with reduced second trimester head size (mean reduction 0.09 standard deviation (SD) [95% CI 0.01, 0.16]) and femur length (0.06 [0.01, 0.10]) and reduced third trimester head size (0.18 SD [0.13, 0.23]), femur length (0.27 SD [0.21, 0.32]) and estimated fetal weight (0.18 SD [0.11, 0.24]). Higher maternal cigarette consumption was associated with a lower z score for head size in the second (mean difference 0.09 SD [0, 0.19]) and third (0.15 SD [0.03, 0.26]) trimesters compared to lower consumption. Fetal measurements were not reduced for those whose mothers quit before or after becoming pregnant compared to mothers who had never smoked. Maternal smoking during pregnancy is associated with reduced fetal measurements after the first trimester, particularly reduced head size and femur length. These effects may be attenuated if mothers quit or reduce cigarette consumption during pregnancy. The study was supported by the European Cooperation in Science and Technology, who provided funds for publication. KMG is supported by the National Institute for Health Research through the NIHR Southampton Biomedical Research Centre and by the European Union's Seventh Framework Programme (FP7/2007-2013), projects Early Nutrition and ODIN under grant agreement numbers 289346 and 613977.

This paper proposes a new method for blind inversion of a monotonic nonlinear map applied to a sum of random variables. Such kinds of mixtures of random variables are found in source separation and Wiener system inversion problems, for example. The importance of our proposed method is based on the fact that it permits to decouple the estimation of the nonlinear part (nonlinear compensation) from the estimation of the linear one (source separation matrix or deconvolution filter), which can be solved by applying any convenient linear algorithm. Our new nonlinear compensation algorithm, the MaxEnt algorithm, generalizes the idea of Gaussianization of the observation by maximizing its entropy instead. We developed two versions of our algorithm based either in a polynomial or a neural network parameterization of the nonlinear function. We provide a sufficient condition on the nonlinear function and the probability distribution that gives a guarantee for the MaxEnt method to succeed compensating the distortion. Through an extensive set of simulations, MaxEnt is compared with existing algorithms for blind approximation of nonlinear maps. Experiments show that MaxEnt is able to successfully compensate monotonic distortions outperforming other methods in terms of the obtained Signal to Noise Ratio in many important cases, for example when the number of variables in a mixture is small. Besides its ability for compensating nonlinearities, MaxEnt is very robust, i.e. showing small variability in the results. This work has been partly funded by the University of Vic - Central University of Catalonia under the grant R0947 to JSC and grants from ANPCyT - PICT 2012 -1519 and CONICET - PIP 114-201101-00021, Argentina, to CFC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This work has been partly funded by the University of Vic - Central University of Catalonia under the grant R0947 and grants from ANPCyT - PICT 2012-1519 and CONICET - PIP 114-201101-00021, Argentina. The authors would like to acknowledge Prof. Christian Jutten (GIPSA Lab, Grenoble, France) for his discussions and guidance across this research work. The authors thank reviewers for providing deep and useful comments on the first version of the manuscript.

The world is still recovering from the financial crisis peaking in September 2008. The triggering event was the bankruptcy of Lehman Brothers. To detect such turmoils, one can investigate the time-dependent behaviour of correlations between assets or indices. These cross-correlations have been connected to the systemic risks within markets by several studies in the aftermath of this crisis. We study 37 different US indices which cover almost all aspects of the US economy and show that monitoring an average investor's behaviour can be used to quantify times of increased risk. In this paper the overall investing strategy is approximated by the ground-states of the mean-variance model along the efficient frontier bound to real world constraints. Changes in the behaviour of the average investor is utlilized as a early warning sign.

Made available in DSpace on 2018-11-26T16:19:18Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-01-14 Background Malignant cerebral artery strokes have a poor prognosis, with nearly 80% of mortality in some series despite intensive care. After a large randomized trial, decompressive hemicraniectomy has been performed more often in stroke patients. Here, we describe patients in a tertiary teaching hospital in Brazil, emphasizing the impact of age on outcomes. Methods A retrospective cohort of patients, with malignant strokes which received a decompressive hemicraniectomy, from paper and electronic medical records, from January 2010 to December 2013 was divided into two groups according to age. Results The final analysis included 60 patients. The overall mortality was higher among patients older than 60 yrs (67% vs. 41%; p = 0.039), whose group also had a worse outcome (76% with mRS 5 or 6) at 90 days (OR 3.91 CI95% 1.30-11.74), whereas only 24% had mRS of 0-4 (p = 0.015). All patients who presented with sepsis died (p = 0.003). The incidence of pulmonary infection was very high in the elderly group (76%) with significant intergroup differences (p = 0.027, OR 8.32 CI95% 0.70-98.48). Conclusions Older patients present more commonly with infections, more disabilities and a higher mortality, highlighting very poor results in elderly population. These results should be proved with a South American trial, and if confirmed, it can impact on future decisions regarding decompressive craniectomy for acute ischemic stroke in our region. Univ Estadual Paulista, Botucatu Med Sch, Dept Neurol Psychol & Psychiat, Botucatu, SP, Brazil Univ Estadual Paulista, Botucatu Med Sch, Dept Publ Hlth Med, Botucatu, SP, Brazil Univ Estadual Paulista, Botucatu Med Sch, Dept Anesthesiol, Botucatu, SP, Brazil Univ Estadual Paulista, Botucatu Med Sch, Dept Neurol Psychol & Psychiat, Botucatu, SP, Brazil Univ Estadual Paulista, Botucatu Med Sch, Dept Publ Hlth Med, Botucatu, SP, Brazil Univ Estadual Paulista, Botucatu Med Sch, Dept Anesthesiol, Botucatu, SP, Brazil

Multi-Agent Reinforcement Learning (MARL) algorithms face two main difficulties: the curse of dimensionality, and environment non-stationarity due to the independent learning processes carried out by the agents concurrently. In this paper we formalize and prove the convergence of a Distributed Round Robin Q-learning (D-RR-QL) algorithm for cooperative systems. The computational complexity of this algorithm increases linearly with the number of agents. Moreover, it eliminates environment non sta tionarity by carrying a round-robin scheduling of the action selection and execution. That this learning scheme allows the implementation of Modular State-Action Vetoes (MSAV) in cooperative multi-agent systems, which speeds up learning convergence in over-constrained systems by vetoing state-action pairs which lead to undesired termination states (UTS) in the relevant state-action subspace. Each agent's local state-action value function learning is an independent process, including the MSAV policies. Coordination of locally optimal policies to obtain the global optimal joint policy is achieved by a greedy selection procedure using message passing. We show that D-RR-QL improves over state-of-the-art approaches, such as Distributed Q-Learning, Team Q-Learning and Coordinated Reinforcement Learning in a paradigmatic Linked Multi-Component Robotic System (L-MCRS) control problem: the hose transportation task. L-MCRS are over-constrained systems with many UTS induced by the interaction of the passive linking element and the active mobile robots. This research has been partially funded by EU through SandS project, grant agreement no 317947. This research has been partially funded by grant TIN2011-23823 of the Ministerio de Ciencia e Innovacion of the Spanish Government (MINECO), with FEDER funds. The GIC has been supported by grant IT874-13 as university research group category AMG was supported by EC under FP7, Coordination and Support Action, Grant Agreement Number 316097, ENGINE European Research Centre of Network Intelligence for Innovation Enhancement. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Editorial

Background Although depressive symptoms in first episode psychosis have been associated with cannabis abuse, their influence on the long-term functional course of FEP patients who abuse cannabis is unknown. The aims of the study were to examine the influence of subclinical depressive symptoms on the long-term outcome in first episode-psychosis patients who were cannabis users and to assess the influence of these subclinical depressive symptoms on the ability to quit cannabis use. Methods 64 FEP patients who were cannabis users at baseline were followed-up for 5 years. Two groups were defined: (a) patients with subclinical depressive symptoms at least once during follow-up (DPG), and (b) patients without subclinical depressive symptoms during follow-up (NDPG). Psychotic symptoms were measured using the Positive and Negative Syndrome Scale (PANSS), depressive symptoms using the Hamilton Depression Rating Scale (HDRS)-17, and psychosocial functioning was assessed using the Global Assessment of Functioning (GAF). A linear mixed-effects model was used to analyze the combined influence of cannabis use and subclinical depressive symptomatology on the clinical outcome. Results Subclinical depressive symptoms were associated with continued abuse of cannabis during follow-up (beta=4.45; 95% confidence interval [CI]: 1.78 to 11.17; P=.001) and with worse functioning (beta=-5.50; 95% CI: -9.02 to -0.33; P=.009). Conclusions Subclinical depressive symptoms and continued cannabis abuse during follow-up could be predictors of negative outcomes in FEP patients. This work was supported by health research funds from the Spanish Government (PS09/02002 CIBER Network; EC10-333, PI10/01430, PI10/01746, PI11/01977, PI11/02708, 2011/1064, 11-BI-01, 1677-DJ-030, and EC10-220); European Regional Development Funds, and local grants from the Basque Country Government (2008111010, 2009111047, 2010111170, 2010112009, 2011111110, 2011111113, SAIO10-PC10BF01, SAIO11-PE11BF006, SAIO11-PE11BF007, SAIO10-PR10BF01, GIC 10/80, and KRONIK 11/010); the Basque Foundation for Health Innovation and Research (BIOEF; BIO09/EM/010); the Spanish Clinical Research Network (CAIBER; 1392-D-079) and the University of the Basque Country (GIC10/80, US10/08, and EHU08/54). The psychiatric research department in University Hospital of Alava-Santiago is supported by the Stanley Research Foundation (03-RC-003). These institutions had no further role in the study design, data collection, analysis or interpretation, writing of the report, or in the decision to submit the paper for publication.

Background Schistosomiasis is the second-most widespread tropical parasitic disease after malaria. Various research strategies and treatment programs for achieving the objective of eradicating schistosomiasis within a decade have been recommended and supported by the World Health Organization. One of these approaches is based on the control of snail vectors in endemic areas. Previous field studies have shown that competitor or predator introduction can reduce snail numbers, but no systematic investigation has ever been conducted to identify snail microbial pathogens and evaluate their molluscicidal effects. Methodology/Principal findings In populations of Biomphalaria glabrata snails experiencing high mortalities, white nodules were visible on snail bodies. Infectious agents were isolated from such nodules. Only one type of bacteria, identified as a new species of Paenibacillus named Candidatus Paenibacillus glabratella, was found, and was shown to be closely related to P. alvei through 16S and Rpob DNA analysis. Histopathological examination showed extensive bacterial infiltration leading to overall tissue disorganization. Exposure of healthy snails to Paenibacillus-infected snails caused massive mortality. Moreover, eggs laid by infected snails were also infected, decreasing hatching but without apparent effects on spawning. Embryonic lethality was correlated with the presence of pathogenic bacteria in eggs. Conclusions/Significance This is the first account of a novel Paenibacillus strain, Ca. Paenibacillus glabratella, as a snail microbial pathogen. Since this strain affects both adult and embryonic stages and causes significant mortality, it may hold promise as a biocontrol agent to limit schistosomiasis transmission in the field., Author Summary The present paper reports the isolation and the characterization of a new microbial pathogen of the freshwater snail, Biomphalaria glabrata. Genetic analyses revealed that the species has not been previously described and could be classified into the Paenibacillus genus. These bacteria invade most snail tissues and proliferate, causing massive lethality. Moreover, the bacterial infection can be transmitted both vertically and horizontally to other snails, causing their death in 30 days. This discovery is potentially important because B. glabrata, as an intermediate host, plays an important role in transmitting schistosomiasis, the second-most widespread human parasitic disease. The World Health Organization’s objective of schistosomiasis eradication in a decade encourages the development of multiple approaches for countering the disease, one of which is vector population control. This new bacterial strain clearly could be a potential agent for such a strategy.

Background Large ornithopod tracks are known from the Upper Jurassic to the uppermost Cretaceous rocks of all continents but Antarctica. They include the tracks historically called Iguanodon footprints, iguanodontid footprints, hadrosaur/hadrosaurid footprints, and other large ornithopod tracks that have been used to define ichnotaxa. More than 40 ichnospecies based on large ornithopod tracks have been defined, but the validity of many of them is questionable. Methodology/Principal Findings 34 ichnogenera and 44 ichnospecies have been analysed in this work. Many of them are considered to be invalid because they have been defined on the basis of poorly preserved tracks without diagnostic features, have an inadequate diagnosis, or are based on temporal and/or geographical criteria. Only eight ichnospecies belonging to the ichnogenera Caririchnium, lguanodontipus and Hadrosauropodus are here regarded as valid. Conclusions/Significance The monospecific ichnogenus lguanodontipus (I. burrep) is characterized by a small, rounded heel and elongate, narrow digit impressions. Its distribution is limited to the Berriasian-Valanginian of Europe. Caririchnium consists of four ichnospecies (C. magnificum [type ichnospecies], C. kortmeyeri, C. billsarjeanti and C. lotus) with a large, rounded heel and short, wide digit impressions. This ichnogenus ranges from the Berriasian-Hauterivian to the Aptian-Albian of South America, North America, Asia and Europe. Finally, Hadrosauropodus (three ichnospecies: H. langstoni [type ichnospecies], H. leonardii and H. kyoungsookimi) shows a large, bibbed heel and short, wide digit impressions. It is known from the Aptian-Albian to the Maastrichtian of North America, Asia and Europe. The ichnofamily lguanodontipodidae includes large iguanodontian tracks characterized mainly by mesaxonic, tridactyl and subsymmetrical pes tracks that are as wide as (or wider than) long and have one pad impression in each digit and one in the heel. Its distribution is confidently limited to the Cretaceous of Europe, Asia, North America and South America. This paper is a contribution to the projects: IT834-13 of the Gobierno Vasco/Eusko Jaurlaritza; CGL2010-16447 subsidized by the Spanish Ministerio de Economia y Competitividad (MINECO), the European Regional Development Fund, and the Government of Aragon ("Grupos Consolidados" and "Direccion General de Patrimonio Cultural"); the project CGL2010-18851/BTE (MINECO); and the project CGL2013-47521-P (MINECO). IDM is the beneficiary of a Postdoctoral grant from the Gobierno de Argentina (CONICET). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Landscapes and features of the everyday world were scarcely represented in Paleolithic art, especially those features associated with the human landscape (huts and campsites). On the contrary, other figurative motifs (especially animals) and signs, traditionally linked to the magic or religious conceptions of these hunter-gatherer societies, are the predominant themes of Upper Paleolithic art. This paper seeks to present an engraved schist slab recently found in the Moli del Salt site (North-eastern Iberia) and dated at the end of the Upper Paleolithic, ca. 13,800 years ago. This slab displays seven semicircular motifs that may be interpreted as the representation of dome-shaped huts. The analysis of individual motifs and the composition, as well as the ethnographic and archeological contextualization, suggests that this engraving is a naturalistic depiction of a hunter-gatherer campsite. Campsites can be considered the first human landscape, the first area of land whose visible features were entirely constructed by humans. Given the social meaning of campsites in hunter-gatherer life-styles, this engraving may be considered one of the first representations of the domestic and social space of a human group. Fieldwork in the Moli del Salt is possible thanks to the financial support of Generalitat de Catalunya, Consell Comarcal de la Conca de Barbera, Ajuntament de Vimbodi i Poblet, and SOREO. The research is carried out within the framework of the project Paleoenvironmental evolution and prehistoric settlements in the Francoli, Gaia and Siurana river basins and Camp de Tarragona streams, funded by Generalitat de Catalunya. This research has also been supported by Generalitat de Catalunya grants 2014SGR-900, 2008ACOM-00073, 2009ACOM-00103, and 2010ACOM-00001. The research of Marcos Garcia-Diez was carried out with the financial support of the Basque Government (Research Group on Prehistory UPV/EHU IT622-13).

Study of emotions in human-computer interaction is a growing research area. This paper shows an attempt to select the most significant features for emotion recognition in spoken Basque and Spanish Languages using different methods for feature selection. RekEmozio database was used as the experimental data set. Several Machine Learning paradigms were used for the emotion classification task. Experiments were executed in three phases, using different sets of features as classification variables in each phase. Moreover, feature subset selection was applied at each phase in order to seek for the most relevant feature subset. The three phases approach was selected to check the validity of the proposed approach. Achieved results show that an instance-based learning algorithm using feature subset selection techniques based on evolutionary algorithms is the best Machine Learning paradigm in automatic emotion recognition, with all different feature sets, obtaining a mean of 80,05% emotion recognition rate in Basque and a 74,82% in Spanish. In order to check the goodness of the proposed process, a greedy searching approach (FSS-Forward) has been applied and a comparison between them is provided. Based on achieved results, a set of most relevant non-speaker dependent features is proposed for both languages and new perspectives are suggested. This work has been done within the Basque Government Research Team grant under project TIN2010-15549 of the Spanish Ministry and the University of the Basque Country UPV/EHU, under grant UFI11/45 (BAILab). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.