scholarly journals Expertise Detection in Crowdsourcing Forums Using the Composition of Latent Topics and Joint Syntactic–Semantic Cues

2021 ◽  
Vol 2 (6) ◽  
Author(s):  
Yonas Demeke Woldemariam
Keyword(s):  
Named Entities ◽  
Linguistic Feature ◽  
Semantic Cues ◽  
Adverse Conditions ◽  
Linguistic Patterns ◽  
Character Set ◽  
Complex Phenomena ◽  
Linguistic Characterization

AbstractWe develop an NLP method for inferring potential contributors among multitude of users within crowdsourcing forums (CSFs). The method basically provides a way to predict expertise from their structures (syntax–semantic patterns) when crowdsourced votes are unavailable. It primarily deals with tackling core adverse conditions, which hinder the identification of crowds’ expertise levels, and standardization of measuring linguistic quality of crowdsourced text. To solve the former, an expertise estimation and linguistic feature annotation algorithm is developed. To approach the later, a comprehensive linguistic characterization of crowdsourced text, along with extensive joint syntax–punctuation analyses, have been carried out. The entire corpora are comprised of approximately 8 different domains, 3 million and 50,000 sentences, and 32 million and 90,000 words, contributed by a crowd of 50,000 users. The analyses revealed six major linguistic patterns, identified on the basis of ordered lists of structural (syntactic) categories, learned from grammatical constructions, practiced by major groups of experts. In addition, nine different text-oriented expertise dimensions are identified, as crucial steps towards establishing standard linguistic-based expertise-framework for most CSFs. Potentially, the resulting framework simplifies the measurement of crowds’ proficiency, in those particular forums, where crowds’ tasks (e.g., answering questions, technically discerning deep features within images of galaxies for classifying them into certain categories) are intimately connected with their writing (e.g., describing answers illustratively, expressing complex phenomena observed in classified images). Moreover, wide varieties of linguistic annotations: latent topic annotations, named entities, syntactic and punctuation annotations, semantic and character set annotations, word and character n-grams (n = 2 and 3) annotations, are extracted. That is for building baseline and enhanced versions of expertise models (about 20 different models built). The successive achievements of enhancing baseline models, with iteratively adding linguistic feature annotations in a two-stage enhancement process, indicate the adaptability of the learned models.

Physicochemical and bacteriological characterization of hospital effluents and their impact on the environment

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Human Health ◽  
Fecal Coliforms ◽  
Chemical Pollution ◽  
Hospital Effluents ◽  
Biological Contaminants ◽  
Almost All ◽  
Direct Discharge ◽  
Significant Chemical

Liquid effluents discharged by hospitals may contain chemical and biological contaminants whose main source is the different substances used for the treatment of patients. This type of rejection can present a sanitary potentially dangerous risk for human health and can provoke a strong degradation of diverse environmental compartments mainly water and soils. The present study focuses on the quality of the liquid effluents of Hassani Abdelkader’s hospital of Sidi Bel-Abbes (West of Algeria). The results reveal a significant chemical pollution (COD: 879 mgO2/L, BOD5: 850 mgO2/L, NH4+ : 47.9 mg/l, NO2- : 4.2 mg/l, NO3- : 56.8 mg/l with respect to WHO standard of 90 mgO2/L, 30 mgO2/L, 0.5 mg/l, 1 mg/l and 1 mg/l respectively). However, these effluents are biodegradable since the ratio COD/BOD5 do not exceeded the value of 2 in almost all samples. The presence of pathogen germs is put into evidence such as pseudomonas, the clostridium, the staphylococcus, the fecal coliforms and fecal streptococcus. These results show that the direct discharge of these effluents constitutes a major threat to human health and the environment.

scholarly journals Proteomic Advances in Milk and Dairy Products

Molecules ◽  
2021 ◽  
Vol 26 (13) ◽  
pp. 3832
Author(s):  
Rubén Agregán ◽  
Noemí Echegaray ◽  
María López-Pedrouso ◽  
Radwan Kharabsheh ◽  
Daniel Franco ◽  
...  
Keyword(s):  
Dairy Products ◽  
Two Dimensional Gel Electrophoresis ◽  
Vast Number ◽  
Post Translational Modifications ◽  
Fundamental Parameters ◽  
Complex Fluid ◽  
Proteins And Peptides ◽  
Milk And Dairy Products

Proteomics is a new area of study that in recent decades has provided great advances in the field of medicine. However, its enormous potential for the study of proteomes makes it also applicable to other areas of science. Milk is a highly heterogeneous and complex fluid, where there are numerous genetic variants and isoforms with post-translational modifications (PTMs). Due to the vast number of proteins and peptides existing in its matrix, proteomics is presented as a powerful tool for the characterization of milk samples and their products. The technology developed to date for the separation and characterization of the milk proteome, such as two-dimensional gel electrophoresis (2DE) technology and especially mass spectrometry (MS) have allowed an exhaustive characterization of the proteins and peptides present in milk and dairy products with enormous applications in the industry for the control of fundamental parameters, such as microbiological safety, the guarantee of authenticity, or the control of the transformations carried out, aimed to increase the quality of the final product.

scholarly journals Physicochemical Characterization Cascade of Nanoadjuvant–Antigen Systems for Improving Vaccines

Vaccines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 544
Author(s):  
Giuditta Guerrini ◽  
Antonio Vivi ◽  
Sabrina Gioria ◽  
Jessica Ponti ◽  
Davide Magrì ◽  
...  
Keyword(s):  
Immune Response ◽  
Protein Structure ◽  
Physicochemical Properties ◽  
Physicochemical Characterization ◽  
Protein Antigen ◽  
Efficacy And Safety

Adjuvants have been used for decades to enhance the immune response to vaccines, in particular for the subunit-based adjuvants. Physicochemical properties of the adjuvant-protein antigen complexes, such as size, morphology, protein structure and binding, influence the overall efficacy and safety of the vaccine. Here we show how to perform an accurate physicochemical characterization of the nanoaluminum–ovalbumin complex. Using a combination of existing techniques, we developed a multi-staged characterization strategy based on measurements of increased complexity. This characterization cascade has the advantage of being very flexible and easily adaptable to any adjuvant-protein antigen combinations. It will contribute to control the quality of antigen–adjuvant complexes and immunological outcomes, ultimately leading to improved vaccines.

scholarly journals iBikeSafe: A Multi-Parameter System for Monitoring, Evaluation and Visualization of Cycling Paths in Smart Cities Targeted at Cycling Adverse Conditions

Smart Cities ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 1058-1086
Author(s):  
Franklin Oliveira ◽  
Daniel G. Costa ◽  
Luciana Lima ◽  
Ivanovitch Silva
Keyword(s):  
Urban Areas ◽  
Smart Cities ◽  
Large City ◽  
Health And Safety ◽  
Parameter System ◽  
Urban Centers ◽  
Adverse Conditions ◽  
Last Mile ◽  
Real Scenario

The fast transformation of the urban centers, pushed by the impacts of climatic changes and the dramatic events of the COVID-19 Pandemic, will profoundly influence our daily mobility. This resulted scenario is expected to favor adopting cleaner and flexible modal solutions centered on bicycles and scooters, especially as last-mile options. However, as the use of bicycles has rapidly increased, cyclists have been subject to adverse conditions that may affect their health and safety when cycling in urban areas. Therefore, whereas cities should implement mechanisms to monitor and evaluate adverse conditions in cycling paths, cyclists should have some effective mechanism to visualize the indirect quality of cycling paths, eventually supporting choosing more appropriate routes. Therefore, this article proposes a comprehensive multi-parameter system based on multiple independent subsystems, covering all phases of data collecting, formatting, transmission, and processing related to the monitoring, evaluating, and visualizing the quality of cycling paths in the perspective of adverse conditions that affect cyclist. The formal interactions of all modules are carefully described, as well as implementation and deployment details. Additionally, a case study is considered for a large city in Brazil, demonstrating how the proposed system can be adopted in a real scenario.

scholarly journals Lightly supervised acquisition of named entities and linguistic patterns for multilingual text mining

2012 ◽  
Vol 35 (1) ◽  
pp. 87-109 ◽  
Author(s):  
César de Pablo-Sánchez ◽  
Isabel Segura-Bedmar ◽  
Paloma Martínez ◽  
Ana Iglesias-Maqueda
Keyword(s):  
Text Mining ◽  
Named Entities ◽  
Linguistic Patterns ◽  
Multilingual Text

scholarly journals Gut microbiota profiles and characterization of cultivable fungal isolates in IBS patients

2021 ◽  
Author(s):  
Piero Sciavilla ◽  
Francesco Strati ◽  
Monica Di Paola ◽  
Monica Modesto ◽  
Francesco Vitali ◽  
...  
Keyword(s):  
Candida Albicans ◽  
Gut Microbiota ◽  
Healthy Subjects ◽  
Fungal Isolates ◽  
Key Points ◽  
Health Promoting ◽  
Irritable Bowel

Abstract Studies so far conducted on irritable bowel syndrome (IBS) have been focused mainly on the role of gut bacterial dysbiosis in modulating the intestinal permeability, inflammation, and motility, with consequences on the quality of life. Limited evidences showed a potential involvement of gut fungal communities. Here, the gut bacterial and fungal microbiota of a cohort of IBS patients have been characterized and compared with that of healthy subjects (HS). The IBS microbial community structure differed significantly compared to HS. In particular, we observed an enrichment of bacterial taxa involved in gut inflammation, such as Enterobacteriaceae, Streptococcus, Fusobacteria, Gemella, and Rothia, as well as depletion of health-promoting bacterial genera, such as Roseburia and Faecalibacterium. Gut microbial profiles in IBS patients differed also in accordance with constipation. Sequence analysis of the gut mycobiota showed enrichment of Saccharomycetes in IBS. Culturomics analysis of fungal isolates from feces showed enrichment of Candida spp. displaying from IBS a clonal expansion and a distinct genotypic profiles and different phenotypical features when compared to HS of Candida albicans isolates. Alongside the well-characterized gut bacterial dysbiosis in IBS, this study shed light on a yet poorly explored fungal component of the intestinal ecosystem, the gut mycobiota. Our results showed a differential fungal community in IBS compared to HS, suggesting potential for new insights on the involvement of the gut mycobiota in IBS. Key points • Comparison of gut microbiota and mycobiota between IBS and healthy subjects • Investigation of cultivable fungi in IBS and healthy subjects • Candida albicans isolates result more virulent in IBS subjects compared to healthy subjects

scholarly journals A Methodology Based on FT-IR Data Combined with Random Forest Model to Generate Spectralprints for the Characterization of High-Quality Vinegars

Foods ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1411
Author(s):  
José Luis P. Calle ◽  
Marta Ferreiro-González ◽  
Ana Ruiz-Rodríguez ◽  
Gerardo F. Barbero ◽  
José Á. Álvarez ◽  
...  
Keyword(s):  
Random Forest ◽  
Raw Materials ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Raw Material ◽  
Support Vector ◽  
Protected Designation Of Origin ◽  
Ft Ir

Sherry wine vinegar is a Spanish gourmet product under Protected Designation of Origin (PDO). Before a vinegar can be labeled as Sherry vinegar, the product must meet certain requirements as established by its PDO, which, in this case, means that it has been produced following the traditional solera and criadera ageing system. The quality of the vinegar is determined by many factors such as the raw material, the acetification process or the aging system. For this reason, mainly producers, but also consumers, would benefit from the employment of effective analytical tools that allow precisely determining the origin and quality of vinegar. In the present study, a total of 48 Sherry vinegar samples manufactured from three different starting wines (Palomino Fino, Moscatel, and Pedro Ximénez wine) were analyzed by Fourier-transform infrared (FT-IR) spectroscopy. The spectroscopic data were combined with unsupervised exploratory techniques such as hierarchical cluster analysis (HCA) and principal component analysis (PCA), as well as other nonparametric supervised techniques, namely, support vector machine (SVM) and random forest (RF), for the characterization of the samples. The HCA and PCA results present a clear grouping trend of the vinegar samples according to their raw materials. SVM in combination with leave-one-out cross-validation (LOOCV) successfully classified 100% of the samples, according to the type of wine used for their production. The RF method allowed selecting the most important variables to develop the characteristic fingerprint (“spectralprint”) of the vinegar samples according to their starting wine. Furthermore, the RF model reached 100% accuracy for both LOOCV and out-of-bag (OOB) sets.

scholarly journals Bone Pain in Multiple Myeloma (BPMM)—A Protocol for a Prospective, Longitudinal, Observational Study

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1596
Author(s):  
Marta Diaz-delCastillo ◽  
Rebecca E. Andrews ◽  
Aritri Mandal ◽  
Thomas L. Andersen ◽  
Andrew D. Chantry ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Multiple Myeloma ◽  
Observational Study ◽  
Bone Turnover ◽  
Bone Pain ◽  
Subjective Experience ◽  
Prospective Longitudinal ◽  
Bone Turnover Biomarkers

Multiple myeloma (MM) is a bone marrow neoplasia that causes bone pain in 70% patients. While preclinical models of MM have suggested that both nerve sprouting and nerve injury may be causative for the pain, there is a lack of clinical data. Thus, the primary aims of this clinical study are: (1) to provide a deep characterization of the subjective experience of pain and quality of life in MM patients; (2) to investigate disturbances in the bone innervation of MM patients. Secondary aims include exploring correlations between pain and serum inflammatory and bone turnover biomarkers. In a prospective, observational study (clinicaltrials.gov: NCT04273425), patients with suspected MM requiring a diagnostic iliac crest biopsy at Sheffield Teaching Hospital (UK) are invited to participate. Consenting patients answer seven standardized questionnaires assessing pain, quality of life and catastrophizing. Bone turnover biomarkers and inflammatory cytokines are measured in fasting serum samples, and bone innervation is evaluated in diagnostic biopsies. MM patients are invited to a follow-up upon completion of first line treatment. This will be the first deep characterization of pain in MM patients and its correlation with disturbances in bone innervation. Understanding how bone turnover and inflammation correlate to pain in MM is crucial to identify novel analgesic targets for this condition.

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