Time Aware Knowledge Extraction for Microblog Summarization on Twitter

Microblogging services like Twitter and Facebook collect millions of user generated content every moment about trending news, occurring events, and so on. Nevertheless, it is really a nightmare to find information of interest through the huge amount of available posts that are often noise and redundant. In general, social media analytics services have caught increasing attention from both side research and industry. Specifically, the dynamic context of microblogging requires to manage not only meaning of information but also the evolution of knowledge over the timeline. This work defines Time Aware Knowledge Extraction (briefly TAKE) methodology that relies on temporal extension of Fuzzy Formal Concept Analysis. In particular, a microblog summarization algorithm has been defined filtering the concepts organized by TAKE in a time-dependent hierarchy. The algorithm addresses topic-based summarization on Twitter. Besides considering the timing of the concepts, another distinguish feature of the proposed microblog summarization framework is the possibility to have more or less detailed summary, according to the user's needs, with good levels of quality and completeness as highlighted in the experimental results.Comment: 33 pages, 10 figure

Examining the physiological and genetic response of maize to low temperature conditions

peer-reviewedMaize (Zea mays) is an emerging forage crop in Ireland, originating in warmer climates. Under Irish climate conditions establishment can be problematic due to low soil temperatures at early stages of establishment. Maize varieties with improved chilling tolerance have been developed and are on the market, but maize in Ireland is still established under plastic and further varietal improvements are required to make this crop more economically viable. To date, varieties are selected principally by phenotypic traits rather than genetic response. Investigation of the physiological and genetic response of maize towards cold/chilling stress at early developmental stage, in particular the response of developing maize roots to cold stress, can make a contribution towards the understanding of the molecular mechanisms conferring plant cold tolerance. The objectives of this study were aimed to create, at first, an experimental design to test the physiological response to low temperatures, under controlled environmental conditions, of various commercial maize cultivars adapted to grow in temperate climates. Responses to abiotic stresses such as cold involve changes in gene expression, therefore, once indentified the hybrids showing contrasting degrees of cold tolerance, these were profilied to examine gene expression and identify possible cold regulated genes. The physiological experiments on twelve maize varieties identified four genotypes with contrasting cold tolerance. Microarray analysis profiling these varieties was used to identify up and down regulated genes under cold/chilling conditions. The stress induced by the cold temperature in the genotypes Picker, PR39B29, Fergus and Codisco was reflected only on the expression profiles of the two varieties with superior cold tolerance, Picker and PR39B29. No significant changes in expression were observed in Fergus and Codisco in response to cold stress. The overall number of genes up and down regulated in the two cold tolerant varieties amounted to 69, which were, however, divided in a group of 39 genes in PR39B29 and 30 genes in Picker, as the two varieties exhibited two different trancriptomic patterns in which only four genes (RNA binding protein, pathogenesis-related protein 1 and two unknown proteins) were shared, although not all with the same degree of regulation. No cold regulated genes ware detected. The gene expression of the four-shared genes was further investigated with qRT-PCR in order to estimate the expression pattern over time. Five time points were used to analyse the expression trend of the genes. The gene expression was not maintained over the five time points, but it was subjected to fluctuation. However, with the exception of the RNA binding protein gene, the expression pattern was similar between the two varieties, indicating a common response to chilling stress

Selectivity of biomolecular recognition processes: synthesis and pharmacological activity of novel biomimetic agents.

Biomimetic agents are synthetic compounds devised to resemble structures and properties of natural biomolecules with the aim to solve complex human problems. Glycomimetics, nucleoside analogues (NAs) and modified oligonucleotides (MOs) represent biomimetic agents that have found various pharmacological applications and constitute the topic of the three main sections in which this PhD thesis has been organized. The design, the synthesis and then the biological evaluation of such molecules have been undertaken; in all cases the aim was the development of new agents with targeted pharmacological activity or improved biological selectivity in several medicinal chemistry contexts

Spontaneous intracranial hypotension : two steroid-responsive cases

Purpose: Spontaneous intracranial hypotension (SIH) is characterised by orthostatic headache, low cerebrospinal fluid pressure and diffuse pachymeningeal enhancement after intravenous gadolinium contrast administration. Magnetic resonance imaging (MRI) often plays a crucial role for correct diagnosis. Case description: We described two similar cases of SIH, whose clinical and imaging features are typical for this pathology. At MRI brain scan, both patients showed diffuse and intense pachymeningeal enhancement and moderate venous distension and epidural vein engorgement. The two patients were treated with bed rest and oral steroid therapy, with complete and long-lasting symptomatic relief. Conclusions: Orthostatic nature of headache is the most indicative clinical feature suggesting SIH; contrast-enhanced MRI provides definite imaging diagnostic findings. Conservative treatment coupled to steroid therapy is often sufficient to obtain complete disappearance of symptoms

COVID-19 and pneumonia: a role for the uPA/uPAR system

Here, we highlight recent findings on the urokinase plasminogen activator (uPA)/uPA receptor (uPAR) system that suggest its potential role as a main orchestrator of fatal progression to pulmonary, kidney, and heart failure in patients with coronavirus. Patients with prolonged background inflammation can present aberrant inflammatory reactions, well recognized as the main factors that can result in death and probably sustained by a dysregulated uPA/uPAR system. SuPAR, the soluble form of uPAR, represents a biomarker of disease progression, and its levels correlate well with comorbidities associated with the death of patients with coronavirus. New drugs that regulate the uPA/uPAR system could help treat the severe complications of highly pathogenic human coronaviruses (hCoVs), including pandemic coronavirus 2019 (COVID-19)

Experimental and numerical investigations to assess the behaviour of a buried pipeline in areas with high geological instability

Ground displacements such as landslides, fault movements, soil liquefaction which may be caused by seismic activity are one of the most dangerous phenomena that can involve buried pipelines, e.g. for oil and gas transportation, or water and sewage. This aspect is currently an important part of research and a challenge for lifelines owners that are interested in prevent or limit pipeline damages. Within the framework of GIPIPE1 research program (SAFETY OF BURIED STEEL PIPELINES UNDER GROUND-INDUCED DEFORMATIONS) new full-scale facilities have been developed and adopted in order to investigate pipe-soil interaction mechanism (in particular sand and 8” 5/8 X65 steel pipes). The new experimental facilities have been designed to perform two groups of tests: simple interaction tests (axial pullout and transversal pullout test) and complex interaction tests (reproducing a pipeline crossing landslide). A system of steel containers (stationary and fixed) in which pipe samples are buried within the sand, have been assembled. Numerical analyses have been performed using strength parameters of sand and steel obtained from laboratory testing and subsequently validated by means full-scale experimental results. The outcomes of the experimental activity showed some differences in soil reaction on pipe by increasing the relative density of soil filling and using a smoother coating. Moreover peak soil resistances estimated with equations suggested by ASCE guidelines [4] cannot predict satisfactory measured axial and lateral soil reactions. This is a confirmation of previous studies in which was evidenced the effect of soil dilation in the annular soil zone around the pipe during axial relative movement between pipe and soil causes an increase of the normal stress at pipe soil interface, in particular the horizontal direction is significantly constrained by the surrounding soil mass leading to an higher increase in lateral soil stress in this direction respect to the vertical direction. Therefore this phenomenon leads to a lateral earth pressure coefficient K which is greater than K0 (coefficient of pressure at rest) as suggested in the ASCE guidelines [4], therefore for a better estimation of soil response using that equation it is suggested to measure the ratio between horizontal stress and the vertical stress during a full-scale axial pullout test. Pipes submitted to lateral soil displacement with a constrained uplifting show as expected a greater soil reaction than that estimated by ASCE [4] and PRCI [20]. As far as the landslide/fault test are concerned, the maximum soil relative density (Dr) achieved during experimental tests performed in this study was around 40%. This level of density led to a low stiffness of soil mass hence a limited global deformation of a 24 m embedded pipe during landslide/fault tests in which one caisson was moved up to 4 m respect to the initial position. These experimental findings confirm that sand with a low value of maximum achievable density may prevent from high loads developing on pipelines, in contrast to native soil which can apply higher loads. Numerical analyses and their validation gave us a suitable instrument to estimate the pipe soil response for large ground displacements phenomena

Transcriptomic response of maize primary roots to low temperatures at seedling emergence

peer-reviewedBackground Maize (Zea mays) is a C4 tropical cereal and its adaptation to temperate climates can be problematic due to low soil temperatures at early stages of establishment. Methods In the current study we have firstly investigated the physiological response of twelve maize varieties, from a chilling condition adapted gene pool, to sub-optimal growth temperature during seedling emergence. To identify transcriptomic markers of cold tolerance in already adapted maize genotypes, temperature conditions were set below the optimal growth range in both control and low temperature groups. The conditions were as follows; control (18 °C for 16 h and 12 °C for 8 h) and low temperature (12 °C for 16 h and 6 °C for 8 h). Four genotypes were identified from the condition adapted gene pool with significant contrasting chilling tolerance. Results Picker and PR39B29 were the more cold-tolerant lines and Fergus and Codisco were the less cold-tolerant lines. These four varieties were subjected to microarray analysis to identify differentially expressed genes under chilling conditions. Exposure to low temperature during establishment in the maize varieties Picker, PR39B29, Fergus and Codisco, was reflected at the transcriptomic level in the varieties Picker and PR39B29. No significant changes in expression were observed in Fergus and Codisco following chilling stress. A total number of 64 genes were differentially expressed in the two chilling tolerant varieties. These two varieties exhibited contrasting transcriptomic profiles, in which only four genes overlapped. Discussion We observed that maize varieties possessing an enhanced root growth ratio under low temperature were more tolerant, which could be an early and inexpensive measure for germplasm screening under controlled conditions. We have identified novel cold inducible genes in an already adapted maize breeding gene pool. This illustrates that further varietal selection for enhanced chilling tolerance is possible in an already preselected gene pool

CFD sensitivity analysis on bumped airfoil characteristics for inflatable winglet

The new aerospace technological milestone is aimed to reducing direct operating costs and pol- lution. In order to obtain pollution reductions via high aerodynamic efficiency, a performance anal- ysis for bumped airfoil based winglet has been pro- posed. Most conventional aircrafts are equipped with fixed winglets to decrease the induced drag; thus, saving more fuel. New projects point to- wards advanced smart materials and telescopic wing tip devices to obtain an adaptive morphing shape that gives, through performance improve- ment, a fuel consumption reduction resulting in less pollutants. The focus of this paper is to evalu- ate the aerodynamic performance, in terms of lift, drag and moment coefficient for a bumped airfoil in climb/descent flight condition at 5000 meters altitude. The performance analysis has been con- ducted via a numerical investigation of the effects of bumps number, height and width for inflatable winglet airfoil, a system that would guarantee a more comfortable arrangement of extraction sys- tem and just minor surplus of weight compared to classical winglet solutions, with all the subsequent advantages

NSL-BP: A Meta Classifier Model Based Prediction of Amazon Product Reviews

In machine learning, the product rating prediction based on the semantic analysis of the consumers' reviews is a relevant topic. Amazon is one of the most popular online retailers, with millions of customers purchasing and reviewing products. In the literature, many research projects work on the rating prediction of a given review. In this research project, we introduce a novel approach to enhance the accuracy of rating prediction by machine learning methods by processing the reviewed text. We trained our model by using many methods, so we propose a combined model to predict the ratings of products corresponding to a given review content. First, using k-means and LDA, we cluster the products and topics so that it will be easy to predict the ratings having the same kind of products and reviews together. We trained low, neutral, and high models based on clusters and topics of products. Then, by adopting a stacking ensemble model, we combine Naïve Bayes, Logistic Regression, and SVM to predict the ratings. We will combine these models into a two-level stack. We called this newly introduced model, NSL model, and compared the prediction performance with other methods at state of the art