Analyzing Disproportionate Reaction via Comparative Multilingual Targeted Sentiment in Twitter

Global events such as terrorist attacks are commented upon in social media, such as Twitter, in different languages and from different parts of the world. Most prior studies have focused on monolingual sentiment analysis, and therefore excluded an extensive proportion of the Twitter userbase. In this paper, we perform a multilingual comparative sentiment analysis study on the terrorist attack in Paris, during November 2015. In particular, we look at targeted sentiment, investigating opinions on specific entities, not simply the general sentiment of each tweet. Given the potentially inflammatory and polarizing effect that these types of tweets may have on attitudes, we examine the sentiments expressed about different targets and explore whether disproportionate reaction was expressed about such targets across different languages. Specifically, we assess whether the sentiment for French speaking Twitter users during the Paris attack differs from English-speaking ones. We identify disproportionately negative attitudes in the English dataset over the French one towards some entities and, via a crowdsourcing experiment, illustrate that this also extends to forming an annotator bias

Polarization observables of the gamma d --> PiNN reaction in the Delta(1232)-resonance region

Polarization observables of the three charge states of the pion for the $\gamma d\to\pi NN$ reaction with polarized photon beam and/or oriented deuteron target are evaluated over the whole $\Delta$(1232)-resonance region adopting a nonrelativistic model based on time-ordered perturbation theory. Results for the $\pi$-meson spectra, linear photon asymmetry, vector and tensor target asymmetries are presented. Particular attention is given, for the first time, to double polarization asymmetries for which we present results for $T_{20}^{\ell}$ and $T_{2\pm 2}^{\ell}$. We found that all other double polarization asymmetries of photon and deuteron target are vanished.Comment: 17 Pages, 8 Figures, accepted for publication in Int. J. Mod. Phys.

Preparation, characterization and antimicrobial assessment of selected ciprofloxacin salts

The formation of salts is considered a simple strategy to modify the physicochemical properties of active pharmaceutical ingredients. In this study, seven novel binary and ternary organic salts of ciprofloxacin (CP) were prepared with benzoic acid (BA), acetylsalicylic acid (ASA), p-coumaric acid (PCMA) and p-aminosalicylic acid (PASA). They were characterized by spectroscopic techniques and differential scanning calorimetry. Solubility and partition coefficients values were also measured. Evaluation of the antimicrobial activity of the organic salts against Staphylococcus aureus and Staphylococcus epidermidis revealed that most of the new salts had higher antimicrobial activity than CP-HCl against both strains. The most active compounds against S. epidermidis and S. aureus were CP-PASA and CP-PCMA, resp., which were up to fourteen times more potent than parent CP-HCl. Our findings indicated a strong correlation between the lipophilicity of the formed salts and their antimicrobial activity and showed that an optimum value of lipophilicity (logP = 0.75) seemed to be necessary to maximize the antimicrobial activity. These findings highlighted the improved physical, thermal and antimicrobial properties of the new salts of CP that can aid in providing higher bioavailability than CP-HCl

New Spectrophotometric and Fluorimetric Methods for Determination of Fluoxetine in Pharmaceutical Formulations

New simple and sensitive spectrophotometric and fluorimetric methods have been developed and validated for the determination of fluoxetine hydrochloride (FLX) in its pharmaceutical formulations. The spectrophotometric method was based on the reaction of FLX with 1,2-naphthoquinone-4-sulphonate (NQS) in an alkaline medium (pH 11) to form an orange-colored product that was measured at 490 nm. The fluorimetric method was based on the reaction of FLX with 4-chloro-7-nitrobenzo-2-oxa-1,3-diazole (NBD-Cl) in an alkaline medium (pH 8) to form a highly fluorescent product that was measured at 545 nm after excitation at 490 nm. The variables affecting the reactions of FLX with both NQS and NBD-Cl were carefully studied and optimized. The kinetics of the reactions were investigated, and the reaction mechanisms were presented. Under the optimum reaction conditions, good linear relationships were found between the readings and the concentrations of FLX in the ranges of 0.3–6 and 0.035–0.5 μg mL−1 for the spectrophotometric and fluorimetric methods, respectively. The limits of detection were 0.1 and 0.01 μg mL−1 for the spectrophotometric and fluorimetric methods, respectively. Both methods were successfully applied to the determination of FLX in its pharmaceutical formulations

Simple Spectrophotometric Method for Determination of Paroxetine in Tablets Using 1,2-Naphthoquinone-4-Sulphonate as a Chromogenic Reagent

Simple and rapid spectrophotometric method has been developed and validated for the determination of paroxetine (PRX) in tablets. The proposed method was based on nucleophilic substitution reaction of PRX with 1,2-naphthoquinone-4-sulphonate (NQS) in an alkaline medium to form an orange-colored product of maximum absorption peak (λmax) at 488 nm. The stoichiometry and kinetics of the reaction were studied, and the reaction mechanism was postulated. Under the optimized reaction conditions, Beer's law correlating the absorbance (A) with PRX concentration (C) was obeyed in the range of 1–8 μg mL−1. The regression equation for the calibration data was: A = 0.0031 + 0.1609 C, with good correlation coefficients (0.9992). The molar absorptivity (ε) was 5.9 × 105 L mol−1 1 cm−1. The limits of detection and quantitation were 0.3 and 0.8 μg mL−1, respectively. The precision of the method was satisfactory; the values of relative standard deviations did not exceed 2%. The proposed method was successfully applied to the determination of PRX in its pharmaceutical tablets with good accuracy and precisions; the label claim percentage was 97.17 ± 1.06 %. The results obtained by the proposed method were comparable with those obtained by the official method

Single-molecule electrical contacts on silicon electrodes under ambient conditions

The ultimate goal in molecular electronics is to use individual molecules as the active electronic component of a real-world sturdy device. For this concept to become reality, it will require the field of single-molecule electronics to shift towards the semiconducting platform of the current microelectronics industry. Here, we report silicon-based single-molecule contacts that are mechanically and electrically stable under ambient conditions. The single-molecule contacts are prepared on silicon electrodes using the scanning tunnelling microscopy break-junction approach using a top metallic probe. The molecular wires show remarkable current–voltage reproducibility, as compared to an open silicon/nano-gap/metal junction, with current rectification ratios exceeding 4,000 when a low-doped silicon is used. The extension of the single-molecule junction approach to a silicon substrate contributes to the next level of miniaturization of electronic components and it is anticipated it will pave the way to a new class of robust single-molecule circuits

Deep Convolutional Neural Networks for Accurate Diagnosis of COVID-19 Patients Using Chest X-Ray Image Databases from Italy, Canada, and the USA

Introduction: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), famously known as COVID-19, has quickly become a global pandemic. Chest X-ray (CXR) imaging has proven reliable, fast, and cost-effective for identifying COVID-19 infections, which proceeds to display atypical unilateral patchy infiltration in the lungs like typical pneumonia. We employed the deep convolutional neural network (DCNN) ResNet-34 to detect and classify CXR images from patients with COVID-19 and Viral Pneumonia and Normal Controls. Methods: We created a single database containing 781 source CXR images from four different international sub-databases: the Società Italiana di Radiologia Medica e Interventistica (SIRM), the GitHub Database, the Radiology Society of North America (RSNA), and the Kaggle Chest X-ray Database for COVID-19 (n = 240), Viral Pneumonia (n = 274), and Normal Controls (n = 267). Images were resized, normalized, without any augmentation, and arranged in m batches of 16 images before supervised training, testing, and cross-validation of the DCNN classifier. Results: The ResNet-34 had a diagnostic accuracy as of the receiver operating characteristic (ROC) curves of the true-positive rate versus the false-positive rate with the area under the curve (AUC) of 1.00, 0.99, and 0.99, for COVID-19 and Viral Pneumonia patient and Normal control CXR images; respectively. This accuracy implied identical high sensitivity and specificity values of 100, 99, and 99% for the three groups, respectively. ResNet-34 achieved a success rate of 100%, 99.6%, and 98.9% for classifying CXR images of the three groups, with an overall accuracy of 99.5% for the testing subset for diagnosis/prognosis. Conclusions: Based on this high classification precision, we believe the output activation map of the final layer of the ResNet-34 is a powerful tool for the accurate diagnosis of COVID-19 infection from CXR images

Oncogenic challenge of bromocriptine and L-arginine versus conventional antidiabetics on diethyl nitrosamine-induced liver tumorigenesis in diabetic rats: focus on AMPK activation

Background: Diabetes mellitus (DM) is associated with a spectrum of cancers where the metabolic antecedents, consequences, and therapy might affect cancer risk. The association between hepatocellular carcinoma (HCC) and DM had been confirmed. Approaches to HCC prevention focus on the molecular regulators of the disease process defined as the inflammation-fibrosis-cancer axis. The AMP-activated protein kinase (AMPK) is an interesting metabolic tumor suppressor and a promising target for cancer prevention and therapy. This study aimed to investigate the effects of bromocriptine mesylate and L-arginine on hepatic carcinogenesis on a rat model of hepatic neoplasia induced by diethyl nitrosamine (DENA) and promoted by type-2 DM in contrast to the conventional antidiabetics.Methods: One hundred male Wistar rats were randomly assigned into two sets; control set (normal, HCC, DM, and combined HCC/DM) and treated set where rats received one of the following drugs for another 5 weeks: insulin glargine, glimepiride, metformin, pioglitazone, bromocriptine mesylate, or L-arginine. Bodyweight changes, blood glucose level, liver functions tests, serum C-peptide and alpha-fetoprotein (AFP), and hepatic activated AMPK were assessed beside the hepatic histopathological changes.Results: Equivalent to metformin, bromocriptine and L-arginine treatment significantly reduced AFP, despite their minor glycemic control. L-arginine induced AMPK activation, yet less than metformin. Histopathologic examination revealed a reduction in hepatic intra-lobular chronic inflammatory cell infiltration, steatosis and necrosis by metformin, bromocriptine, and L-arginine. Hepatic necro-inflammatory changes were most prominent in insulin-treated rats.Conclusions: L-arginine and bromocriptine mesylate prevent early neoplastic changes almost equivalent to metformin at least partially via hepatic AMPK activation