TechMiner: Extracting Technologies from Academic Publications

In recent years we have seen the emergence of a variety of scholarly datasets. Typically these capture ‘standard’ scholarly entities and their connections, such as authors, affiliations, venues, publications, citations, and others. However, as the repositories grow and the technology improves, researchers are adding new entities to these repositories to develop a richer model of the scholarly domain. In this paper, we introduce TechMiner, a new approach, which combines NLP, machine learning and semantic technologies, for mining technologies from research publications and generating an OWL ontology describing their relationships with other research entities. The resulting knowledge base can support a number of tasks, such as: richer semantic search, which can exploit the technology dimension to support better retrieval of publications; richer expert search; monitoring the emergence and impact of new technologies, both within and across scientific fields; studying the scholarly dynamics associated with the emergence of new technologies; and others. TechMiner was evaluated on a manually annotated gold standard and the results indicate that it significantly outperforms alternative NLP approaches and that its semantic features improve performance significantly with respect to both recall and precision

Media use during adolescence: the recommendations of the Italian Pediatric Society.

BACKGROUND: The use of media device, such as smartphone and tablet, is currently increasing, especially among the youngest. Adolescents spend more and more time with their smartphones consulting social media, mainly Facebook, Instagram and Twitter because. Adolescents often feel the necessity to use a media device as a means to construct a social identity and express themselves. For some children, smartphone ownership starts even sooner as young as 7 yrs, according to internet safety experts. MATERIAL AND METHODS: We analyzed the evidence on media use and its consequences in adolescence. RESULTS: In literature, smartphones and tablets use may negatively influences the psychophysical development of the adolescent, such as learning, sleep and sigh. Moreover, obesity, distraction, addiction, cyberbullism and Hikikomori phenomena are described in adolescents who use media device too frequently. The Italian Pediatric Society provide action-oriented recommendations for families and clinicians to avoid negative outcomes. CONCLUSIONS: Both parents and clinicians should be aware of the widespread phenomenon of media device use among adolescents and try to avoid psychophysical consequences on the youngest

Semantic Modelling of Citation Contexts for Context-Aware Citation Recommendation

Contents The four CSV files are the data used for the evaluation in: Saier T., Färber M. (2020) Semantic Modelling of Citation Contexts for Context-Aware Citation Recommendation. In: Advances in Information Retrieval. ECIR 2020. Lecture Notes in Computer Science, vol 12035. DOI: 10.1007/978-3-030-45439-5_15 Code: github.com/IllDepence/ecir2020 The evaluation was conducted in a citation re-prediction setting. CSV Format 7 columns divided by \u241E cited document ID for *_nomarker.csv: citation marker position ambiguous for *_withmarker.csv: citation marker position at 'MAINCIT' in citation context adjacent cited document IDs only given in citrec_unarxive_*.csv divided by \u241F order matches 'CIT' markers in citation context citing document ID citation context MAG field of study IDs divided by \u241F predicate:argument tuples generated based on PredPatt JSON noun phrases for *_nomarker.csv: divided by \u241F for *_withmarker.csv: divided by \u241D into noun phrases noun phrase directly preceding citation marker Data Sources citrec_unarxive_cs_withmarker.csv data set unarXive Paper DOI: 10.1007/s11192-020-03382-z Data DOI: 10.5281/zenodo.2553522 filter citing doc from computer science cited doc is cited at least 5 times citrec_mag_cs_en.csv data set Microsoft Academic Graph (MAG) Paper DOI: 10.1145/2740908.2742839 filter citing doc from computer science and in English citing doc abstract in MAG given cited doc is cited at least 50 times citrec_refseer.csv data set RefSeer Paper URL: ojs.aaai.org/index.php/AAAI/article/view/9528 Data URL: psu.app.box.com/v/refseer filter for citing and cited docs title, venue, venuetype, abstract, and year not NULL citrec_acl-arc_withmarker.csv data set ACL ARC Paper URL: aclanthology.org/L08-1005 Data URL: acl-arc.comp.nus.edu.sg/ filter cited doc has a DBLP ID Paper Citation @inproceedings{Saier2020ECIR, author = {Tarek Saier and Michael F{\"{a}}rber}, title = {{Semantic Modelling of Citation Contexts for Context-aware Citation Recommendation}}, booktitle = {Proceedings of the 42nd European Conference on Information Retrieval}, pages = {220--233}, year = {2020}, month = apr, doi = {10.1007/978-3-030-45439-5_15},

Microbiota network and mathematic microbe mutualism in colostrum and mature milk collected in two different geographic areas: Italy versus Burundi

Human milk is essential for the initial development of newborns, as it provides all nutrients and vitamins, such as vitamin D, and represents a great source of commensal bacteria. Here we explore the microbiota network of colostrum and mature milk of Italian and Burundian mothers using the auto contractive map (AutoCM), a new methodology based on artificial neural network (ANN) architecture. We were able to demonstrate the microbiota of human milk to be a dynamic, and complex, ecosystem with different bacterial networks among different populations containing diverse microbial hubs and central nodes, which change during the transition from colostrum to mature milk. Furthermore, a greater abundance of anaerobic intestinal bacteria in mature milk compared with colostrum samples has been observed. The association of complex mathematic systems such as ANN and AutoCM adopted to metagenomics analysis represents an innovative approach to investigate in detail specific bacterial interactions in biological samples

Development of a One-Dimensional Model for the Prediction of Leakage Flows in Regenerative Pumps

Regenerative pumps are characterized by a low specific speed that place them between rotary positive displacement pumps and purely radial centrifugal pumps. They are interesting for many industrial applications since, for a given flow rate and a specified head, they allow for a reduced size and can operate at a lower rotational speed with respect to purely radial pumps. The complexity of the flow within regenerative machines makes the theoretical performance estimation a challenging task. The prediction of the leakage flow rate between the rotating and the static disks is the one that more than others has an impact on the prediction of global performance. All the classical approaches to the disk clearance problem assume that there is no relevant circumferential pressure gradient. In the present case, the flow develops along the tangential direction and the pressure gradient is intrinsically non-zero. The aim of the present work is to develop a reliable approach for the prediction of leakage flows in regenerative pumps. The method assumes that the flow inside of the disk clearance can be decomposed into several stream-tubes. Energy balance is performed for each tube, thus generating a system that can be solved numerically. The new methodology has been tuned using data obtained from the numerical simulation of virtual prototypes of regenerative pumps where the disk clearance is part of the control volume. After that, the methodology has been integrated into an existing one-dimensional code called DART (developed at the University of Florence in cooperation with Pierburg Pump Technology Italy S.p.A.) and the new algorithm is verified using available experimental and numerical data. It is here demonstrated that an appropriate calibration of the leakage flow model allows for an improved reliability of the one-dimensional code

Impact of delivery mode on the colostrum microbiota composition.

BACKGROUND: Breast milk is a rich nutrient with a temporally dynamic nature. In particular, numerous alterations in the nutritional, immunological and microbiological content occur during the transition from colostrum to mature milk. The objective of our study was to evaluate the potential impact of delivery mode on the microbiota of colostrum, at both the quantitative and qualitative levels (bacterial abundance and microbiota network). METHODS: Twenty-nine Italian mothers (15 vaginal deliveries vs 14 Cesarean sections) were enrolled in the study. The microbiota of colostrum samples was analyzed by next generation sequencing (Ion Torrent Personal Genome Machine). The colostrum microbiota network associated with Cesarean section and vaginal delivery was evaluated by means of the Auto Contractive Map (AutoCM), a mathematical methodology based on Artificial Neural Network (ANN) architecture. RESULTS: Numerous differences between Cesarean section and vaginal delivery colostrum were observed. Vaginal delivery colostrum had a significant lower abundance of Pseudomonas spp., Staphylococcus spp. and Prevotella spp. when compared to Cesarean section colostrum samples. Furthermore, the mode of delivery had a strong influence on the microbiota network, as Cesarean section colostrum showed a higher number of bacterial hubs if compared to vaginal delivery, sharing only 5 hubs. Interestingly, the colostrum of mothers who had a Cesarean section was richer in environmental bacteria than mothers who underwent vaginal delivery. Finally, both Cesarean section and vaginal delivery colostrum contained a greater number of anaerobic bacteria genera. CONCLUSIONS: The mode of delivery had a large impact on the microbiota composition of colostrum. Further studies are needed to better define the meaning of the differences we observed between Cesarean section and vaginal delivery colostrum microbiota

Development of an electrochemical immunosensor for Phakopsora pachyrhizi detection in the early diagnosis of soybean rust

Soybean rust is a disease that occurs on soybean leaves and is considered very aggressive, reducing product quality. Early identification of fungus in the plants prevents severe farming losses as well as spreading to neighboring cultures. In this paper, a label-free immunosensor was developed based on impedance measurements to detect Asian rust on soybean leaf extract at the early stages of the disease. The antibody anti-mycelium of Phakopsora pachyrhizi fungus (disease agent) was immobilized on a gold substrate via a self-assembled monolayer (SAM) of thiols using covalent cysteamine coupling. This immunosensor presents a limit of detection of 385 ng mL-1. The optimization of experimental conditions and surface blocking to minimize non-specific adsorption on the immunosensor response were evaluated. These studies, based on electrochemical impedance spectroscopy (EIS), provide new perspectives on using this method for early diagnosis of soybean rust

Pathways of 4-hydroxy-2-nonenal detoxification in a human astrocytoma cell line

One of the consequences of the increased level of oxidative stress that often characterizes the cancer cell environment is the abnormal generation of lipid peroxidation products, above all 4-hydroxynonenal. The contribution of this aldehyde to the pathogenesis of several diseases is well known. In this study, we characterized the ADF astrocytoma cell line both in terms of its pattern of enzymatic activities devoted to 4-hydroxynonenal removal and its resistance to oxidative stress induced by exposure to hydrogen peroxide. A comparison with lens cell lines, which, due to the ocular function, are normally exposed to oxidative conditions is reported. Our results show that, overall, ADF cells counteract oxidative stress conditions better than normal cells, thus confirming the redox adaptation demonstrated for several cancer cells. In addition, the markedly high level of NADP+-dependent dehydrogenase activity acting on the glutahionyl-hydroxynonanal adduct detected in ADF cells may promote, at the same time, the detoxification and recovery of cell-reducing power in these cells

High genetic diversity within and among bitter cassava cultivated in three soil types in Central Amazonia.

Bitter cassava is an important food crop that was domesticated in Amazonia. Although it is exclusively propagated by stem cuttings, cassava retained its ability of sexual reproduction. The occurrence and incorporation of sexual plants into the stock of clonal varieties contributes to the high genetic diversity observed within the crop. Despite being well adapted to nutrient deprived soils of Amazonia, ethnobotanical observations showed that communities of smallholder farmers along the middle Madeira River, in Central Amazonia, also cultivate cassava in the highly fertile soils of the floodplains and Amazonian dark earths (ADE). These farmers grow different sets of varieties in each soil type, which may also contribute to the maintenance of high levels of genetic diversity within the crop. We evaluated with 10 nuclear microsatellite markers the genetic diversity within and among some of the most commonly cultivated bitter cassava varieties grown on ADE, floodplain and Oxisols soils in the middle Madeira region. High levels of genetic diversity within varieties were observed (HO ranging from 0.495 to 0.707, and HE ranging from 0.250 to 0.460). Additionally, varieties were generally highly differentiated from each other. Although high levels of genetic diversity were previously observed in studies carried out in regions of low soil fertility in other parts of Amazonia, we identified that management of different soil types is important to the maintenance of genetically distinct stocks of varieties, which also contributes to the maintenance of the genetic diversity within the crop

Genetic diversity in Brazilian sweet potato (Ipomoea batatas (L.) Lam., Solanales, Convolvulaceae) landraces assessed with microsatellite markers

We used simple sequence repeat (SSR) markers to investigate the genetic diversity of 78 sweet potato (Ipomoea batatas) accessions (58 landraces and 20 putative clones) from traditional agricultural households from 19 local communities in the Vale do Ribeira, São Paulo, Brazil. Eight SSR loci were assessed using 6% (w/v) polyacrylamide gels stained with silver nitrate and the accessions genotyped considering the presence or absence of bands. The results were subjected to analysis of molecular variance (AMOVA), and cluster and principal coordinate analyses. Spatial structure was assessed using Mantel's test to compare genetic and geographic distances. Each primer pair generated between three and ten clearly scorable polymorphic fragments. Cluster analyses showed a Jaccard's index from 0.3 to 1.0, indicating high genetic and intravarietal diversity. Accessions from all 19 communities were not spatially structured (r = 0.15, p < 0.054), with AMOVA indicating that most of the variability (58.2%) was distributed within households and only 18.1% of the variability was distributed between households within communities. The outcrossing mating system of sweet potato, and anthropic factors such as selection of different varieties and their maintenance within household small plots and home gardens, as well as an extensive exchange system between agriculturists, may all be contributing to these results.FAPESPCNP