SIRIS-Lab/unlabelled-sti-corpus huggingface dataset:
Towards identification of the unifying principles of vertebrate adaptive immunity

About 500 million years ago, the two sister groups of vertebrates independently evolved alternative forms of adaptive immunity, representing a striking example of convergent evolution. Whereas the components and functions of the immune system in jawed vertebrates (ranging from sharks to humans) are well characterized, much remains to be learned about adaptive immunity in jawless vertebrates (lampreys and hagfishes). Up to now, progress in understanding immunity in jawless fishes was hampered by their complex life-cycle, long generation time, and the difficulty of raising fish in the laboratory for extended periods, particularly after in vitro fertilization. Based on our recent methodological advances in aquatic husbandry and successful CRISPR/Cas9-mediated genetic modification, we propose to conduct a large-scale analysis of cellular immunity in lampreys laying the foundations for the identification of the unifying principles of vertebrate immunity. Our experiments will address the development and characteristics of different T cell subsets, the molecular basis of antigen receptor assembly, and the function of the two principal T cell lineages during the immune response. We will also examine the structure and function of the stromal microenvironment in the lamprey thymus equivalent, which is considered to be the site of T cell development. A particular focus will be on the functional analysis of a recently discovered MHC-like locus in the context of T cell development, and in the essential self/nonself discrimination mechanism(s) at play during the immune response. We expect that the identification of common design principles of adaptive immunity in vertebrates will provide us with an unprecedented view on immune functions in humans, potentially guiding the development of novel strategies for the treatment of failing immunity in patients with immunodeficiency and/or autoimmunity.
SOHC type internal combustion engine.

A SOHC type internal combustion engine includes a pair of intake valves VI1 and VI2 and a pair of exhaust valves VE1,VE2. The intake valve driving means 171 comprises a plurality of rocker arms 241, 251, 261 disposed adjacent one another, including a pair of driving rocker arms 241 251 operatively connected separately to the intake valves and a connection switchover mechanism 50 capable of switching-over the connection and disconnection of the adjacent rocker arms in accordance with the operational condition of the engine. The exhaust valve driving means 181 comprises a pair of exhaust valve-side rocker arms 291, 301 operatively connected separately to the exhaust valves and disposed on opposite sides of the intake valve driving means in positions opposed to the cam shaft 16, respectively. In the intake valve driving means, the opening and closing mode of the intake valves can be changed in accordance with the operational condition of the engine by operation of the connection switchover mechanism, thereby providing an improvement in output from the engine. The intake valve driving means is constructed compactly by disposition of the plurality of rocker arms constituting the intake valve driving means adjacent one another in the positions opposed to the cam shaft, thereby enabling an effective and compact construction of the connection switchover mechanism provided in the intake valve driving means. <IMAGE>
IRON SOLEPLATE COMPRISING A NON-OXIDE OR AT LEAST PARTIALLY NON-OXIDE CERAMIC PROTECTIVE COATING

The invention relates to an iron soleplate comprising a support having an ironing surface, said ironing surface being coated with a protective coating. According to the invention, the protective coating comprises at least one continuous thin film of non-oxide or at least partially non-oxide polymer-derived ceramic, said thin film forming the ironing surface. The invention also relates to a method for covering the ironing surface of an iron soleplate.
ANDREA MALASPINA

THE ARCHITECTURAL FIRM ANDREA MALASPINA, ENROLLED IN THE ORDER OF ARCHITECTS, PLANNERS, LANDSCAPERS AND CONSERVATIONISTS OF THE PROVINCE OF GENOA N.3287 SINCE 2004 AND IN THE REGISTER OF PLANT VERIFIERS N.128 IN THE CHAMBER OF COMMERCE OF GENOA SINCE 2004 AND MEMBER OF THE MUNICIPAL AND PROVINCIAL CONSULTATION FOR PROBLEMS DEGLIHANDICAPPATI OF GENOA AND OF THE REGIONAL CONSULTATION OF THE LIGURIA REGION SINCE 2007. The MASTER EUROPEAN II LEVEL “URBAN QUALITY AND LIGHT PIANIFICATION” IN 2008.CERTIFICATION OF IMPORTANT STIMES CCS-B01 SECOND ISO 17024 FROM 2009.CONSULTING IN THE ACCESSIBILITY OF THE COMMUNITY OF GENOVA FROM 2010.ENERGICAL CERTIFICATION OF THE LIGURY REGION N.4346 FROM 2011.REGOGNISED EUROPEAN Valuer (TEGOVA & IsIVI) FROM 01/06/2014 N.61
Division of labour and the evolution of complexity

Division of labour is fundamental to the evolution of life on earth, allowing genes to work together to form genomes, cells to build organisms, pathogens to escape immune attack, and eusocial insect societies to achieve ecological dominance. Consequently, if we want to understand how life on earth evolved, we need to understand why division of labour does or, just as importantly, does not evolve.  There are two major outstanding problems for our understanding of division of labour: First, how can we explain why division of labour has evolved with some traits, in some species, but not others? Given the potential benefits of dividing labour, why does it not arise more frequently in cooperative species? Second, in cases where division of labour has evolved, how can we explain the form that it takes? Why do factors such as the degree of specialisation, or mechanism used to produce different phenotypes, vary across species?  I will combine my social evolution expertise with novel synthetic and genomic approaches to address these problems. I will explain the distribution and form of division of labour in the natural world, with an interdisciplinary research programme, divided into four work packages: (1) I will provide the first experimental test of the fundamental assumption that division of labour provides an efficiency benefit, by synthetically manipulating bacteria. (2) I will test how selection has acted for and against the evolution of division of labour in natural populations of bacteria, using novel genomic analysis techniques. (3) I will determine why division of labour evolved in some species, but not others, with an across species study on insects, and experimental evolution of bacteria. (4) I will establish a new field of research on why different species use different mechanisms to divide labour: genetic differences, environmental cues, or random assignment of roles. I will develop theory to explain this variation, and test this theory experimentally.
Real-Time early detection and alert system for online terrorist content based on natural language processing, social network analysis, artificial intelligence and complex event processing

The RED-Alert project will bring data mining and predictive analytics tools to the next level, developing novel natural language processing (NLP), semantic media analysis (SMA), social network analysis (SNA), Complex Event Processing (CEP) and artificial intelligence (AI) technologies. These technologies will be combined for the first time and validated by 6 law enforcement agencies (LEAs) to collect, process, visualize and store online data related to terrorist groups, allowing them to take coordinated action in real-time while preserving the privacy of citizens. 
The RED-Alert solution will outperform state-of-the-art solutions in terms of number of languages supported, privacy-preserving capabilities, usability, detection performance, real-time capabilities and integration capabilities. The RED-Alert approach combines for the first time the CEP methodology with NLP/SMA and SNA applications in the context of social media data analytics, transforming (unstructured) social media data into (structured) events enhanced by semantic attributes. For example, a tweet will be an event consisting of content (expressed as NLP features e.g. concepts, sentiment, entities, etc.) and context (time and the author including SNA features e.g. number of followers, number of links, etc.). Turning unstructured social media data into structured events is key, as it allows the system to use (event) rules (event temporal logic, event logic patterns, even counting, absence of events) to infer insights or create alerts in real-time.
The project impact is supported by the participation of Europol and specific dissemination activities around the World Counter-Terrorism Summit, organized by one of the partners. The total requested EC funding is 5M Euros and the project duration 36 months.
Interdisciplinary synthesis of tools for understanding land governance

InSiTe-LandGov combines big data with qualitative approaches to generate new open access datasets and methods on natural resource governance—a critical data gap in sustainability science. It will test these using existing data from a unique network of >5000 research plots across the world’s biggest savannah woodland, spanning 12 countries in southern Africa. This biome is key to European and global climate change, biodiversity and poverty alleviation goals: it supports the livelihoods of 150 million people, stores as much carbon as the Congo Basin, and is home to iconic megafauna, yet it suffers some of the highest rates of deforestation and poverty on Earth. Improved understandings of resource governance will be crucial to meeting these challenges, but empirical methods for assessing governance remain opaque, costly and spread across several disciplines. First, I will produce a typology of current methods for observing resource governance that bridges the divide between positivist and constructivist approaches. I will do this through a systematic review and workshops with experts from Europe, North America and southern Africa. Second, I will generate a new open access dataset on governance for the entire southern African woodland biome. I will use machine learning, open access ‘big’ satellite and census data, the >5000 research plots, and a field visit to Mozambique and Zimbabwe. Finally, I will produce a world-first analysis on how aspects of resource governance affect environmental degradation and poverty across the region. I will use a novel approach combining qualitative and big data methods. In this fellowship I aim to build on my existing skills to define myself as a global expert in interdisciplinary governance research, and to secure a long term job at a European university. I will draw on the expertise of supervisors at three world-class hubs of sustainability research: McGill University, University of Edinburgh and the Stockholm Resilience Centre.
Paclitaxel Drug-eluting Balloons to Recurrent In-stent Stenoses in Autogenous Dialysis Fistulas: A Retrospective Study

To assess the effect of the Medtronic paclitaxel drug-eluting balloon (DEB) on re-intervention to in-stent stenoses in autogenous dialysis arteriovenous fistulas (AVFs).AVF is the optimum haemodialysis access. The commonest problem is stenosis, preventing maturation, causing inadequate dialysis or precipitating occlusion. Conventional angioplasty has a high recurrence rate. Successful drug elution in the coronary circulation led us to use DEBs in recurrent AVF stenoses since 2010.This is a retrospective study, based on prospective audit data, using DEBs on recurrent in-stent stenotic lesions in the AVF circuit of our haemodialysis population. To analyse the effect of DEBs on re-intervention, we created two Kaplan-Meier curves. The first curve compares the last "disease-free-interval" pre-DEB intervention to the first "disease-free interval" post-DEB, giving us "re-intervention-free percentage at 12 months" pre- and post-DEB. The second curve takes into account the multiple pre- and post-DEB interventions to the index lesion, and uses a marginal proportional hazards model to estimate the hazard ratio for "DEBpresent vs. DEBabsent".From 1 September 2010 to 1 December 2013, we treated 625 AVF stenoses with endovascular techniques. In 86 of these stenoses, DEBs were used. Of the 86 DEB interventions, 37 were included for this study, 49 were excluded. In the study group, there was a significant difference in "re-intervention-free percentage at 12 months" before and after DEB: 19% vs. 69%. The hazard ratio for "DEBpresent" vs. "DEBabsent" was 0.23 (95% CI 0.14 to 0.36, p&lt;0.001).This retrospective study suggests that DEBs significantly reduce re-intervention on recurrent in-stent AVF stenoses.
Probabilistic modelling of electronic health records

The growing worldwide adoption of Electronic Health Records (EHR) enables new research opportunities to analyse massive amounts of medical information, motivated by the promise of improving health systems while providing significant budget savings. Biomedical research increasingly uses machine learning methods as a data-driven approach to learn complex comorbidity patterns of diseases, study drug interactions, and form predictions. The analysis of EHRs may not only lead to knowledge discovery, but it also facilitates personalised medical treatment and early diagnosis of the diseases through the design of clinical support systems.

However, current approaches for the analysis of EHRs are still in their early stages. The two main technical challenges that need to be addressed are integration of heterogeneous data and scalability to massive datasets. Most of the existing methods are tailored to homogeneous data and, therefore, to a single source of information, and hence they cannot handle EHR datasets. Scalability also represents a difficulty for most of the current machine learning techniques, which are limited to the analysis to moderate-sized datasets.

In this project, we will develop novel tools for the analysis of heterogeneous EHR data. Our approach will be based on probabilistic modelling techniques, since they are an effective approach for understanding real-world data in many areas of science. We will make use of Bayesian nonparametric modelling techniques, coupled with stochastic variational inference to allow for scalable inference. Probabilistic models, including BNPs, are amenable to both descriptive and predictive analysis at the same time. We will collaborate with the Department of Biomedical Informatics, who will provide their knowledge about the problem, allowing for good model formulations and results analysis.
Deconstructing pain with predictive models: from neural architecture to pain relief

Pain is a burden for millions of people in terms of suffering, as well as for society in terms of costs. While it is well established that the perception of pain is not necessarily related to the amount of sensory input, a mechanistic framework for this is still lacking at the neurobiological level, although it would be of utmost importance for inspiring new therapeutic approaches. In PredictingPain, I will provide such a framework by applying recent insights from computational neuroscience in the form of ‘predictive coding’ to pain. Predictive coding models assume that perception is an active process in which the brain is not just passively responding to sensory inputs, but is instead constantly generating predictions about its sensory inputs.

I will employ three complementary work packages (WP) – all of which use cutting-edge neuroimaging methods in human volunteers – to answer the important question of whether predictive coding can serve as a fundamental mechanism underlying the perception of pain. In WP1, I will elucidate whether the neural architecture of the nociceptive system is capable of implementing a predictive coding scheme. With WP2, I will unravel how the subjective experience of pain is constructed from a rich array of predictive signals. Finally, in WP3 I will employ an experimental model of chronic pain to test how predictions of pain relief exert their beneficial effects when pain is ongoing. A large part of the research in PredictingPain will focus on the human spinal cord, in order to capture predictive signals at this earliest level of central nervous system pain processing, since they will exert a profound effect on processing at higher levels and the resulting pain perception.

Together, the outcomes from PredictingPain will provide a novel and mechanistic understanding of pain perception that will provide impetus for the development of new therapeutic approaches in order to reduce the suffering and financial burden that pain imposes.
A synopsis of Convolvulaceae from the Upper Turi-Gurupi region in the Amazon of Maranhão, Brazil

A synopsis of Convolvulaceae species from the Upper Turi-Gurupi region, a strategic area for the conservation of Amazonian biodiversity in the state of Maranhão, is presented. Field samples and herbarium collections were analyzed to build a list of species, indicating the most representative taxa and providing data on growth habit, geographic distribution, occurrence in Brazilian phytogeographic domains, and distribution in the Upper Turi-Gurupi region. Twenty-one species and nine genera (Aniseia Choisy, Bonamia Thouars, Camonea Raf., Distimake Raf., Evolvulus L., Ipomoea L., Maripa Aubl., Odonellia K.R. Robertson, and Operculina Silva Manso) were recorded. Ipomoea was the most representative genus, with 10 species, and Ipomoea asarifolia was the most collected species. Maripa scandens Aubl. is a new record for the state of Maranhão and in relation to the last taxonomic work of Convolvulaceae in the Amazon, which covered Maranhão, 10 species are new records for the state. A heterogeneous distribution of the species and sampling gaps of Convolvulaceae were observed in the region, pointing to the need for further surveys. This study contributes to the knowledge of this botanical family in the Amazon territory and stimulates the conservation of the Amazonian flora in Maranhão, since the study area is under strong pressure from environmental degradation and is one of the most threatened in terms of biodiversity loss in the Amazon.
The effect of highly active antiretroviral therapy on liver function in human immunodeficiency virus-infected pediatric patients with or without hepatitis virus co-infection.

Co-infection of hepatitis virus is common in human immunodeficiency virus (HIV) infected adults in China. But little is known about hepatitis virus co-infection in pediatric HIV-infected subjects. The study aimed to investigate the impact of hepatitis B virus (HBV) and/or hepatitis C virus (HCV) co-infection and highly active antiretroviral therapy (HAART) on liver function of pediatric HIV-infected subjects.A cohort study including 101 pediatric HIV-infected subjects with HBV/HCV co-infection and 44 pediatric comparators with HIV mono-infection was carried out in Henan Province of China from September 2011 to September 2012. All patients received HAART for 1-year. HBV and HCV infection was determined by antibody tests. HIV RNA load, CD4(+) T-cell counts and liver function were determined before and after HAART. The Student's t-test or a one-way ANOVA was used for normally distributed values and A Mann-Whitney U-test was performed for values without normal distribution using SPSS statistical package 18.0 (SPSS Inc.).After HAART for 1-year, the median levels of viral load were decreased to lower limit of detection in 90.34% pediatric HIV-infected subjects with/without HBV/HCV co-infection (P < 0.001), and CD4(+) T-cell counts increased significantly (P < 0.001). Compared with the pre-HAART, mean level of alanine aminotransferase (ALT) in each group had a significant increase after HAART (P < 0.01). The mean levels of ALT and aspartate aminotransferase (AST) in nevirapine (NVP) based HAART group increased significantly after HAART (P < 0.01). Mean change values of ALT and AST were significantly higher in the NVP based regimen group than in the efavirenz (EFV) based regimen group (P < 0.01). For HIV/HBV/HCV co-infected patients, mean change values of ALT and AST in NVP-based HAART group was significantly higher than that in EFV-based HAART group (P < 0.01).Highly active antiretroviral therapy can damage liver function in pediatric HIV-infected subjects, especially in those with HBV/HCV co-infection. NVP was more harmful to liver function of pediatric HIV-infected subjects than EFV.
The Iceberg Effect: Behind the User Interface of Mobile Collaborative Systems

Advances in mobile technologies are opening new possibilities to support collaborative activities through mobile devices. Unfortunately, mobile collaborative systems have been difficult to conceive, design and implement. These difficulties are caused in part by their unclear requirements and developers' lack of experience with this type of systems. However, several requirements involved in the collaborative back-end of these products are recurrent and should be considered in every development. This paper introduces a characterization of mobile collaboration and a framework that specifies a list of general requirements to be considered during the conception and design of a system in order to increase its probability of success. This framework was used in the development of two mobile collaborative systems, providing developers with a base of back-end requirements to aid system design and implementation. The systems were positively evaluated by their users.
Thirdhand tobacco smoke: chemical characterization, human exposure and urinary carcinogen biomarkers

Tobacco smoking is the leading cause of preventable disease worldwide. Compared with the rest of the world, the WHO European region has one of the highest proportions of deaths attributable to tobacco. Although most of EU countries have introduced smoking bans in public places, domestic environments are still an important source of passive smoking exposure. Environmental tobacco smoke contains more than 4,000 chemicals many of which are toxic and carcinogenic and is estimated to be the cause of about 1.0% of worldwide mortality. In addition to passive inhalation, non-smokers, especially children, are also at risk through contact with surfaces and dust contaminated with residual smoke gases and particles, the so-called thirdhand tobacco smoke (THS). Despite the emerging evidence on THS harms, the specific role of THS in tobacco-related illnesses has been questioned so far by the public health community because of the poor level of characterisation of THS constituents and mechanisms of formation, as well as the lack of studies focused on human exposure. 
The aim of this proposal is to fill some of the important gaps on our current understanding of the chemistry, toxicology and exposure of THS, including an accurate characterisation of THS composition and the development and validation of specific human urine biomarkers of this exposure. The developed tools will be used for the monitoring of matching samples of THS from smoking and non-smoking houses and human urine from their households in order to find correlations between tobacco exposure and urine biomarkers. The final objective of the proposal is the public diffusion of the results obtained in this study as evidences of THS harms to influence in present and future health educational programs, especially addressed to smoking parents, and in present and future European health policies.