In the last few years thousands of scientific papers have investigated sentiment analysis, several startups that measure opinions on real data have emerged and a number of innovative products related ...to this theme have been developed. There are multiple methods for measuring sentiments, including lexical-based and supervised machine learning methods. Despite the vast interest on the theme and wide popularity of some methods, it is unclear which one is better for identifying the polarity (i.e., positive or negative) of a message. Accordingly, there is a strong need to conduct a thorough apple-to-apple comparison of sentiment analysis methods,
as they are used in practice
, across multiple datasets originated from different data sources. Such a comparison is key for understanding the potential limitations, advantages, and disadvantages of popular methods. This article aims at filling this gap by presenting a benchmark comparison of twenty-four popular sentiment analysis methods (which we call the state-of-the-practice methods). Our evaluation is based on a benchmark of eighteen labeled datasets, covering messages posted on social networks, movie and product reviews, as well as opinions and comments in news articles. Our results highlight the extent to which the prediction performance of these methods varies considerably across datasets. Aiming at boosting the development of this research area, we open the methods’ codes and datasets used in this article, deploying them in a benchmark system, which provides an open API for accessing and comparing sentence-level sentiment analysis methods.
Runting and stunting syndrome (RSS) is an enteric viral disease in commercial poultry that directly affects gut health; however, its influence on gut microbiota remains unknown. This study aimed to ...investigate the compositional changes in the bacterial community of the ileum of 7-day-old broiler chicks naturally affected or not affected by RSS, using next-generation sequencing (NGS) technology. Twenty-one samples were obtained from the ileal contents and mucosa of 11 chicks with RSS and 10 healthy chicks, raised in a dark house system located on a farm in the state of Minas Gerais, Brazil. The results revealed overall changes in the gut microbiota of the chicks with RSS, including a decrease in microbial richness and diversity. In particular, there was a decrease in Lactobacillus and an increase in Candidatus Arthromitus and Clostridium sensu stricto 1. These results indicate a relationship between viral infection and the gut microbial composition, which can cause gut dysbiosis and may influence inflammation in this organ.
RESEARCH HIGHLIGHTS
RSS causes dysbiosis of the gut microbiota of the ilea of chicks.
A difference was found in gut microbiota between chicks with or without RSS.
Candidatus Arthromitus was predominant in chicks with RSS.
Clostridium sensu stricto 1 was strictly associated with chicks with RSS.
In this study, calcium ferrites with different Ca : Fe atomic ratios (1 : 1, 1 : 2, 1 : 3 and 2 : 1) were prepared from Ca and Fe nitrates treated at 300, 700 and 900 °C and evaluated for phosphate ...adsorption and recovery from wastewater. TG, XRD, Mössbauer spectroscopy, SEM, VSM magnetic measurements, and BET analyses showed the formation of two different calcium ferrite phases,
i.e.
, CaFe
2
O
4
and Ca
2
Fe
2
O
5
at 700 and 900 °C. The adsorption results indicated that the formation of calcium ferrite structure is critical for phosphate adsorption/recovery. Evaluation of the pH, initial phosphate concentration, contact time, coexisting ions and desorption conditions showed remarkable adsorption capacities of 62-75 mg g
−1
for CaFe1:2-700 and 28-43 mg g
−1
for CaFe1:2-900. The phosphate adsorption on the Ca ferrite surfaces is so strong that the recovery/desorption showed limited efficiencies,
e.g.
, 15-39%.
In this study, calcium ferrites with different Ca : Fe atomic ratios (1 : 1, 1 : 2, 1 : 3 and 2 : 1) were prepared from Ca and Fe nitrates treated at 300, 700 and 900 °C and evaluated for phosphate adsorption and recovery from wastewater.
Leptospira genus contains species that affect human health with varying degrees of pathogenicity. In this context, we aimed to evaluate the differences in the modulation of host gene expression by ...strains of Leptospira varying in virulence. Our data showed a high number of differentially expressed transcripts in murine macrophages following 6h of infection. Leptospira infection modulated a set of genes independently of their degree of virulence. However, pathway analysis indicated that Apoptosis, ATM Signaling, and Cell Cycle: G2/M DNA Damage Checkpoint Regulation were exclusively regulated following infection with the virulent strain. Taken together, results demonstrated that species and virulence play a role during host response to Leptospira spp in murine macrophages, which could contribute to understanding the pathogenesis of leptospirosis.
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Here we report the effective application of Residual Diatomaceous Earth (RDE) from brewery industry, in comparison to Residual Yeasts (RY) and Pure Diatomaceous Earth (PDE), for the ...removal of reactive blue 160 dye from aqueous solutions. RDE and the RY showed higher adsorption capacity at pH 2. Maximum dye removal capacity of PDE (1.51 mg g−1) was much lower than that observed for RDE and RY (7.96 mg g−1 and 8.66 mg g−1), respectively, indicating that the presence of yeast in the biosorbent was fundamental for improving dye biosorption. The pseudo-second order kinetic model described well the adsorption processes for all the adsorbents. Equilibrium adsorption of the dye by RDE and PDE followed Langmuir isotherm, while RY best fitted with the Freundlich isotherm, indicating that the active sites of RY are more heterogeneous. FT-IR and Scanning Electron Microscopy analysis confirmed the presence of the dye on the surface of the adsorbents after the adsorption. Furthermore, the RDE presented several operational advantages when compared to the RY, indicating that it is a promising material to be used in wastewater treatment of textile industries.
This study explored the influence of crystallite size on a nanoparticle-coated fiber optic Mach-Zehnder Interferometer (MZI). The primary aim was to enhance the magnetic properties of the ...nanoparticles for application in fiber optic sensors designed for magnetic field sensitivity. The motion of the nanoparticles within the magnetic field induced alterations in the sensor's transmission, creating an imbalance in the optical signals between the interferometer arms. Nickel ferrites (NiFe2O4) with average crystallite sizes of 3.3 nm, 51.9 nm, and 74.3 nm were used. The nanoparticles were identified by X-ray diffraction, VSM magnetic measurements, and Mössbauer spectroscopy. Structural parameters obtained from X-ray diffraction underwent refinement using the Rietveld method, and the Scherrer equation was applied to determine the average crystallite size. Magnetic sensor performance was assessed for sensitivity, precision, and accuracy for different nanoparticle sizes. The relationship between output power and applied magnetic field exhibited linearity between 87.6% and 99.2%. Sensitivity varied from 1.65 dB/Oe to 3.17 dB/Oe for different particle sizes, indicating an increase in sensitivity with nanoparticle magnetization. This study establishes a correlation between crystallite size and nanoparticle magnetization, enhancing sensor responsiveness. This optimization facilitates the development of tailored electric current and magnetic field sensors, considering nanoparticle size and their distinctive magnetic properties. Although the primary focus was on the optical sensor, a comprehensive nanoparticle characterization was crucial as it directly influenced sensor performance.
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•Development of an optical fiber sensor based on nickel ferrite.•Utilization of the MZ interferometer with nickel ferrite nanoparticles for measuring magnetic fields and electric currents.•Calculation and optimization of sensor sensitivity for different sizes of nanoparticles.
Sentiment analysis has become a key tool for several social media applications, including, analysis of user’s opinions about products and services, support for politics during campaigns and even ...identification of market trending. Multiple existing sentiment analysis methods explore different techniques, usually relying on lexical resources or learning approaches. Despite the significant interest in this theme and amount of research efforts in the field, almost all existing methods are designed to work with only English content. Most current strategies in other languages consist of adapting existing lexical resources, without presenting proper validations and basic baseline comparisons. In this work, we take a different step into this field. We focus on evaluating existing efforts proposed to do language specific sentiment analysis with a simple yet effective baseline approach. To do it, we evaluated sixteen methods for sentence-level sentiment analysis proposed for English, and compared them with three language-specific methods. Based on fourteen human labeled language-specific datasets, we provide an extensive quantitative analysis of existing multilingual approaches. Our results suggest that simply translating the input text in a specific language to English and then using one of the existing best methods developed for English can be better than the existing language-specific approach evaluated. We also rank methods according to their prediction performance and identify those that acquired the best results using machine translation across different languages. As a final contribution to the research community, we release our codes, datasets, and the iFeel 3.0 system, a Web framework and tool for multilingual sentence-level sentiment analysis11iFeel resources: https://sites.google.com/view/ifeel-resources/home.. We hope our system sets up a new baseline for future sentence-level methods developed in a wide set of languages.
•RDE is a suitable biosorbent for the removal of AB277 and AR361.•Biosorption modeling indicates better dye removal in binary solutions.•Presence of inorganic salts decrease biosorption capacity in ...single solutions.•Presence of inorganic salts increase biosorption capacity in binary solutions.
Biosorption is a well known technology for the reduction of the hazardous nature of textile wastewaters. However, its efficiency and mechanisms should be evaluated on complex conditions to be properly applied. In this work, biosorption of the textile dyes Acid Blue 277 (AB277) and Acid Red 361 (AR361) onto residual diatomaceous earth from brewing filtration (RDE) was investigated in single and binary systems with the addition of inorganic salts (NaCl, CaCl2 and MgSO4). RDE showed a maximum biosorption capacity of 6.16 mg g-1 for AB277 and 6.75 mg g-1 for AR361 for single solutions and a maximum biosorption capacity of 8.42 mg g-1 for the sum of dyes in binary systems, which is associated to a synergistic effect of one dye over the other. The presence of salts reduced biosorption capacity in single solutions due to a competitive effect of anions for the binding sites, but different electrostatic interactions by the cations increased biosorption capacity in binary solutions. Modeling indicated that the salts increased the number and density of adsorbed molecules on the binding sites. Adsorption energy values, ranging from 14.2 to 16.7 kJ/mol, demonstrate that physical interactions contribute most to the biosorption process, and the energy is independent of the addition of salts. The physical monolayer model describes the adsorption phenomena accordingly to the experimental results, showing that biosorption with the interference of salts has different mechanisms in single and binary solutions.
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