Miracle-dz/UniFAR-FTUs huggingface dataset:
An Explainable Fake News Detector Based on Named Entity Recognition and Stance Classification Applied to COVID-19

Over the last few years, the phenomenon of fake news has become an important issue, especially during the worldwide COVID-19 pandemic, and also a serious risk for the public health. Due to the huge amount of information that is produced by the social media such as Facebook and Twitter it is becoming difficult to check the produced contents manually. This study proposes an automatic fake news detection system that supports or disproves the dubious claims while returning a set of documents from verified sources. The system is composed of multiple modules and it makes use of different techniques from machine learning, deep learning and natural language processing. Such techniques are used for the selection of relevant documents, to find among those, the ones that are similar to the tested claim and their stances. The proposed system will be used to check medical news and, in particular, the trustworthiness of posts related to the COVID-19 pandemic, vaccine and cure.
Comparative Study of Polysaccharide-Based Hydrogels: Rheological and Texture Properties and Ibuprofen Release

Polysaccharides are attractive gelling agents in pharmacy due to their safety, biocompatibility, biodegradability, relatively easy way of preparation, and low price. Due to their variable physical-chemical properties, polysaccharides have potentialities to be used for designing new drug delivery systems for controlled drug release. In this comparative study, rheological and texture properties as well as the in vitro release of model drug ibuprofen (IBU) with 11 polysaccharide-based hydrogels were investigated. The in vitro release of IBU significantly differed between (i) neutral (hydroxy/alkylcelluloses), (ii) anionic (carboxyalkylcellulose and its sodium salt, tragacanth, carrageenan, xanthan gum), and (iii) cationic (chitosans) hydrogels due to different contribution of provided interactions and viscosity within the hydrogel groups. The drug release kinetics of each hydrogel system was evaluated for five kinetic models. Several combinations of cationic hydrogels with neutral or anionic ones were performed to illustrate possibilities of providing modified IBU release profiles. In this context, chitosan was presented as an effective modifier of diffusion profiles for negatively charged drugs formulated into combined polymeric systems, providing their prolonged release. The most appropriate hydrogel for the topical application (i.e., providing favorable rheological and texture properties along with the highest drug release) was selected from a studied series of polysaccharide-based hydrogels.
Transcriptomics Reveals Discordant Lipid Metabolism Effects between In Vitro Models Exposed to Elafibranor and Liver Samples of NAFLD Patients after Bariatric Surgery

Background and aims: Non-alcoholic steatohepatitis (NASH) is a life-threatening stage of non-alcoholic fatty liver disease (NAFLD) for which no drugs have been approved. We have previously shown that human-derived hepatic in vitro models can be used to mimic key cellular mechanisms involved in the progression of NASH. In the present study, we first characterize the transcriptome of multiple in vitro NASH models. Subsequently, we investigate how elafibranor, which is a peroxisome proliferator-activated receptor (PPAR)-α/δ agonist that has recently failed a phase 3 clinical trial as a potential anti-NASH compound, modulates the transcriptome of these models. Finally, we compare the elafibranor-induced gene expression modulation to transcriptome data of patients with improved/resolved NAFLD/NASH upon bariatric surgery, which is the only proven clinical NASH therapy. Methods: Human whole genome microarrays were used for the transcriptomics evaluation of hepatic in vitro models. Comparison to publicly available clinical datasets was conducted using multiple bioinformatic application tools. Results: Primary human hepatocytes (PHH), HepaRG, and human skin stem cell-derived hepatic progenitors (hSKP-HPC) exposed to NASH-inducing triggers exhibit up to 35% overlap with datasets of liver samples from NASH patients. Exposure of the in vitro NASH models to elafibranor partially reversed the transcriptional modulations, predicting an inhibition of toll-like receptor (TLR)-2/4/9-mediated inflammatory responses, NFκB-signaling, hepatic fibrosis, and leukocyte migration. These transcriptomic changes were also observed in the datasets of liver samples of patients with resolved NASH. Peroxisome Proliferator Activated Receptor Alpha (PPARA), PPARG Coactivator 1 Alpha (PPARGC1A), and Sirtuin 1 (SIRT1) were identified as the major common upstream regulators upon exposure to elafibranor. Analysis of the downstream mechanistic networks further revealed that angiopoietin Like 4 (ANGPTL4), pyruvate dehydrogenase kinase 4 (PDK4), and perilipin 2 (PLIN2), which are involved in the promotion of hepatic lipid accumulation, were also commonly upregulated by elafibranor in all in vitro NASH models. Contrarily, these genes were not upregulated in liver samples of patients with resolved NASH. Conclusion: Transcriptomics comparison between in vitro NASH models exposed to elafibranor and clinical datasets of NAFLD patients after bariatric surgery reveals commonly modulated anti-inflammatory responses, but discordant modulations of key factors in lipid metabolism. This discordant adverse effect of elafibranor deserves further investigation when assessing PPAR-α/δ agonism as a potential anti-NASH therapy.
CK1 Is a Druggable Regulator of Microtubule Dynamics and Microtubule-Associated Processes

Simple Summary The Casein Kinase 1 (CK1) family of serine-threonine specific protein kinases regulates the activity of key regulatory proteins and signaling pathways being involved in embryonic development but also in the adult organism. Furthermore, it plays an important role in the regulation of proliferation, differentiation, apoptotic processes, circadian rhythm, chromosome segregation, and other microtubule-associated processes. Deregulation of CK1 expression and activity, as well as mutations in the coding region, contribute to the development of many human pathologies, including cancer. Alternations in the site-specific phosphorylation of α/β-tubulin and microtubule-associated proteins affect microtubule stability, finally resulting in mitotic defects and genomic instability. Here we review our knowledge about CK1 functions in general and especially in chromosome segregation. Furthermore, an update in modulating CK1 activity by small molecule inhibitors and peptides specifically inhibiting CK1 protein interactions as new therapy concepts for the treatment of cancer will be discussed. Abstract Protein kinases of the Casein Kinase 1 family play a vital role in the regulation of numerous cellular processes. Apart from functions associated with regulation of proliferation, differentiation, or apoptosis, localization of several Casein Kinase 1 isoforms to the centrosome and microtubule asters also implicates regulatory functions in microtubule dynamic processes. Being localized to the spindle apparatus during mitosis Casein Kinase 1 directly modulates microtubule dynamics by phosphorylation of tubulin isoforms. Additionally, site-specific phosphorylation of microtubule-associated proteins can be related to the maintenance of genomic stability but also microtubule stabilization/destabilization, e.g., by hyper-phosphorylation of microtubule-associated protein 1A and RITA. Consequently, approaches interfering with Casein Kinase 1-mediated microtubule-specific functions might be exploited as therapeutic strategies for the treatment of cancer. Currently pursued strategies include the development of Casein Kinase 1 isoform-specific small molecule inhibitors and therapeutically useful peptides specifically inhibiting kinase-substrate interactions.
PDMS-Encapsulated MXene@Polyester Fabric Strain Sensor for Multifunctional Sensing Applications

Flexible strain sensors based on 2D materials have been proven effective for wearable health monitoring devices, human motion detection, and fitness applications. These sensors are flexible, light, and user-friendly, but their sensitivity and detection range need to be enhanced. Among many 2D materials, MXene attracts much interest due to its remarkable properties, such as high electrical conductivity, excellent mechanical properties, flexibility, and good hydrophilicity. However, it is a challenge to fabricate strain sensors with extreme sensitivity and a wide sensing range. In this work, a multifunctional, cost-effective, and highly sensitive PDMS-encapsulated MXene@polyester fabric strain sensor was fabricated. Firstly, complete adsorption of MXene within the fabric formed conductive networks, and then PDMS was used to endow superhydrophobicity and corrosion resistance. The strain sensor demonstrated multifunctional applications and outstanding performance, such as long-term stability (over 500 cycles) and a wide sensing range (8%). The proposed sensor has promising potential for wearable electronic devices such as health monitoring systems and physiological sensing applications.
Efficacy and Safety of Baclofen for Treatment of Alcohol Dependence: An Updated Meta-Analysis and Meta-Regression Study

Baclofen is increasingly used for alcohol dependence treatment but its use remains controversial. Therefore, this study aimed to assess the efficacy and safety of baclofen use on alcohol dependence. This is systematic review and meta-analysis of randomized controlled trials. PubMed, Science Direct, Scopus and Thai databases were systematically searched. Randomized controlled trials investigating efficacy and safety of baclofen on alcohol dependence were included. Study selection, data extraction and quality assessment were performed independently by two reviewers. The clinical therapeutic efficacy and adverse events of baclofen were assessed and were pooled using a random-effects model. Heterogeneity was assessed by I 2 and chi-squared test. Sixteen studies with 1539 alcohol dependence patients were included. Baclofen increased risk of abstinence (risk ratio=1.32; 95 % confidence interval: 1.12, 1.55; p=0.0006) and abstinence duration (standard mean difference=1.07 d (95 % confidence interval: 0.13, 2.01; p=0.04) significantly. Moreover, baclofen significantly decreased heavy drinking days (standard mean difference=-1.14 d; 95 % confidence interval:-1.95, -0.34; p=0.007). However, there were no significant effects on times to relapse, craving and number of alcohol drinks. No serious adverse event associated with baclofen was reported during treatments. The meta-regression found baclofen dose was significantly associated with craving. This meta-analysis indicated that baclofen treatment in alcohol dependence patients is associated with better outcomes in risk of abstinence, abstinence duration and heavy drinking days. However, larger well-designed studies are required to confirm these conclusions
The Medicinal Natural Products of Cannabis sativa Linn.: A Review

Cannabis sativa is known among many cultures for its medicinal potential. Its complexity contributes to the historical application of various parts of the plant in ethno-medicines and pharmacotherapy. C. sativa has been used for the treatment of rheumatism, epilepsy, asthma, skin burns, pain, the management of sexually transmitted diseases, difficulties during child labor, postpartum hemorrhage, and gastrointestinal activity. However, the use of C. sativa is still limited, and it is illegal in most countries. Thus, this review aims to highlight the biological potential of the plant parts, as well as the techniques for the extraction, isolation, and characterization of C. sativa compounds. The plant produces a unique class of terpenophenolic compounds, called cannabinoids, as well as non-cannabinoid compounds. The exhaustive profiling of bioactive compounds and the chemical characterization and analysis of C. sativa compounds, which modern research has not yet fully achieved, is needed for the consistency, standardization, and the justified application of Cannabis sativa products for therapeutic purposes. Studies on the clinical relevance and applications of cannabinoids and non-cannabinoid phenols in the prevention and treatment of life-threatening diseases is indeed significant. Furthermore, psychoactive cannabinoids, when chemically standardized and administered under medical supervision, can be the legal answer to the use of C. sativa.
Change in Secondary Metabolites and Expression Pattern of Key Rosmarinic Acid Related Genes in Iranian Lemon Balm (Melissa officinalis L.) Ecotypes Using Methyl Jasmonate Treatments

The medicinal herb, lemon balm (Melissa officinalis L.), which is high in rosmarinic acid (RA), has well-known therapeutic value. The goals of this study were to investigate the effects of methyl jasmonate (MeJA) on RA content, total phenolic content (TPC), and total flavonoid content (TFC), as well as changes in expression of their biosynthesis-related key genes (MoPAL, Mo4CL, and MoRAS) in Iranian lemon balm ecotypes, as first reported. Our results revealed that MeJA doses significantly increase the RA content, TPC, and TFC in both ecotypes compared with the control samples. Additionally, the higher expression levels of MoPAL, Mo4CL, and MoRAS following treatment were linked to RA accumulation in all treatments for both Iranian lemon balm ecotypes. After 24 h of exposure to 150 µM MeJA concentration, HPLC analysis showed that MeJA significantly increased RA content in Esfahan and Ilam ecotypes, which was about 4.18- and 7.43-fold higher than untreated plants. Our findings suggested that MeJA has a considerable influence on RA, TPC, and TFC accumulation in MeJA-treated Iranian M. officinalis, which might be the result of gene activation from the phenylpropanoid pathway. As a result of our findings, we now have a better understanding of the molecular processes behind RA production in lemon balm plants.
Cytogenetic, Morphometric, and Ecological Characterization of Festuca indigesta Boiss. in the Southeast of Spain

Festuca indigesta subsp. indigesta (Poaceae) is endemic to the southeast of Spain, and until recently, it was considered that its range of distribution was restricted to the siliceous core of Sierra Nevada. However, it has been recently extended in the territory to others calcareous mountains. This study investigates the cytogenetic variability throughout the geographic range of this taxon, the possible edaphic preferences of each cytotype, and the morphological variation of cytotypes. Genome sizes and ploidy levels were estimated using flow cytometry and chromosome count. Soil samples were collected to test the nature of the substrate, i.e., pH, and calcium and magnesium contents. Finally, morphological characters were measured in herbarium specimens. This study provides the first genome size data for the species. Hidden cytogenetic diversity was detected in the taxon, comprising hexaploid (2n = 6x = 42), octoploid (2n = 8x = 56) and dodecaploid (2n = 12x = 84) individuals. No relationship between substrate nature and cytotype was observed. Morphological differences were detected for the size of floral parts and stomata among cytotypes, but these were blurred if the entire morphological variation range was considered. Our results suggest that each mountain range could act as a reservoir of morphologically cryptic genetic diversity regarding this taxon.
Investigating Indian Retail Investor Behavior through the lens of Prospect Theory

The paper explores how prospect theory of loss aversion (Kahneman & Tversky 1979) can help explain retail investor behavior in India with respect to small-cap and mid-cap stocks during periods of crisis which may influence emotional sentiments as well as stock markets. Two distinctly separate periods were analyzed and compared: the Great Recession (2008-09) and the COVID-19 global pandemic (2020-21). A combination of qualitative and quantitative methods was used – a literature review of past studies, detailed interviews with experts, and cross-correlation analysis sentiment and market indices. Statistical correlation analysis of investor sentiment was done versus stock market index movement during the two time periods. Results indicate that positive sentiment and negative sentiment have immediate-term positive and negative relationship respectively with investor behavior, and how loss aversion was stronger during 2008 than 2020. Study also identifies differences in reference points between the two periods, which is consistent with prospect theory in terms of the role of reference point in determining degree of loss-aversion. Expert interviews identified multiple factors such as prior experience with market losses, governmental actions, younger demographics, easier market participation due to technology in 2020 caused the reference point to be different from 2008. Further research needed to understand why the sentiments have an immediate effect on investor behaviors but not in future periods. In contrast, movements in stock markets were seen to have both immediate and future period relationships with sentiment, which suggest some role of herding which needs to be further investigated in future studies.
Quick-Start of XCP Based on NS2

Determining an appropriate sending rate when beginning with data transmission into a network with unknown characteristics is a fundamental issue in best-effort networks. This paper discusses a quick-start mechanism based on XCP. The goal of this mechanism is to make convergence to fairness quicker when network keeps steady . The mechanism assigns and allocates bandwidth according to the information of XCP packet hender. Massive simulation experiments are carried out with NS2 platform, and the results show that the convergence time is greatly reduced while keeping high level network utilization by using the method . Especially the network can keep stable when SYN bursts out.So the mechanism can determine appropriate sending rate when beginning wiht data transmission into a network, and improve network's application.
Discovery of Marine Natural Products as Promising Antibiotics against Pseudomonas aeruginosa

Pseudomonas aeruginosa, one of the most intractable Gram-negative bacteria, has become a public health threat due to its outer polysaccharide layer, efflux transporter system, and high level of biofilm formation, all of which contribute to multi-drug resistance. Even though it is a pathogen of the highest concern, the status of the antibiotic development pipeline is unsatisfactory. In this review, we summarize marine natural products (MNPs) isolated from marine plants, animals, and microorganisms which possess unique structures and promising antibiotic activities against P. aeruginosa. In the last decade, nearly 80 such MNPs, ranging from polyketides to alkaloids, peptides, and terpenoids, have been discovered. Representative compounds exhibited impressive in vitro anti-P. aeruginosa activities with MIC values in the single-digit nanomolar range and in vivo efficacy in infectious mouse models. For some of the compounds, the preliminary structure-activity-relationship (SAR) and anti-bacterial mechanisms of selected compounds were introduced. Compounds that can disrupt biofilm formation or membrane integrity displayed potent inhibition of multi-resistant clinical P. aeruginosa isolates and could be considered as lead compounds for future development. Challenges on how to translate hits into useful candidates for clinical development are also proposed and discussed.
Multimodal System for Audio Scene Source Counting and Analysis

Audio scene analysis (ASA) is a challenging and multifaceted task in audio signal processing that uncovers information about the nature of an audio recording. Regardless of the analysis goal, a number of audio sources are observed in any audio scene. However, this consideration is usually not explored or given considerable thought in research. This work aims to demonstrate the utility of audio source counting with a novel solution consisting of a multimodal system for ASA. Both speaker counting and sound event counting techniques use deep neural networks (DNN) to predict the number of sources. We are able to present competitive results for audio source counting by achieving prediction accuracy of 46.03% and 89.57% with a margin of error of <inline-formula><tex-math notation="LaTeX">$\pm 1$</tex-math></inline-formula> for speaker counting, which outperforms state-of-the-art systems for similar tasks. For sound event counting we achieve 50.55% and 86.59% prediction accuracy and accuracy with a margin of error of <inline-formula><tex-math notation="LaTeX">$\pm 1$</tex-math></inline-formula>, respectively, that establishes a clear baseline. Our system also demonstrates real-time aspects with an overall processing time of <inline-formula><tex-math notation="LaTeX">$\sim 0.4614$</tex-math></inline-formula> s per audio recording.
Harnessing cost data to improve early grade reading: cost evidence from a large-scale literacy initiative in Pakistan

ABSTRACT Understanding the resources needed to deliver literacy programmes at scale is critical for improving global education. We estimate the cost of early grade literacy interventions delivered at scale in government schools in Pakistan, including several teacher professional development interventions and a suite of reading materials including tablets, workbooks, readers, and libraries. The entire package cost approximately $1,531 (2019 USD) per school. Over two years of programme delivery, the primary cost driver of this literacy programme was the management, operations, and coordination costs that enabled each component; these amounted to $765 per school, or half of the total cost. Quarterly school support visits (that is, coaching) for teachers were roughly twice the cost of face-to-face trainings and were only slightly higher cost than monthly teacher inquiry groups (that is, learning circles). Using these cost estimates, we present a framework for maximising cost-effectiveness of early grade literacy programmes by using the cost of each component to set thresholds of the relative impact on student literacy that each component should deliver to be worth the cost. These incremental cost estimates of specific interventions were utilised by the government to budget for and take up components of this literacy programme.
Maximum resolution of switched capacitor converter: a graphical approach

The efficiency of a switched capacitor converter can be represented as the ratio of the output voltage to open-circuit voltage. Switched capacitor converters with adjustable gain are designed with multiple no-load voltages to obtain higher efficiency over the voltage control range. This paper aims to realize the maximum resolution of a switched capacitor converter. A graphical representation of the output voltages formation has been proposed. The voltage composition diagram reveals a switching pattern of the multiphase operation cycle that leads to the desired output voltage. The proposed method has been applied to determine all possible output voltage levels that lead to maximum resolution. A three-capacitor converter has been controlled with the proposed scheme. The simulation results show that the output voltage follows the reference voltage closely. The converter provides 60% more output voltage steps compared to the nearest comparable design in the literature.