RESUMEN

Simplifying summaries of scholarly publications has been a popular method for conveying scientific discoveries to a broader audience. While text summarization aims to shorten long documents, simplification seeks to reduce the complexity of a document. To accomplish these tasks collectively, there is a need to develop machine learning methods to shorten and simplify longer texts. This study presents a new Simplification Aware Text Summarization model (SATS) based on future n-gram prediction. The proposed SATS model extends ProphetNet, a text summarization model, by enhancing the objective function using a word frequency lexicon for simplification tasks. We have evaluated the performance of SATS on a recently published text summarization and simplification corpus consisting of 5,400 scientific article pairs. Our results in terms of automatic evaluation demonstrate that SATS outperforms state-of-the-art models for simplification, summarization, and joint simplification-summarization across two datasets on ROUGE, SARI, and CSS1 . We also provide human evaluation of summaries generated by the SATS model. We evaluated 100 summaries from eight annotators for grammar, coherence, consistency, fluency, and simplicity. The average human judgment for all evaluated dimensions lies between 4.0 and 4.5 on a scale from 1 to 5 where 1 means low and 5 means high.

RESUMEN

We argue that social computing and its diverse applications can contribute to the attainment of sustainable development goals (SDGs)-specifically to the SDGs concerning gender equality and empowerment of all women and girls, and to make cities and human settlements inclusive. To achieve the above goals for the sustainable growth of societies, it is crucial to study gender-based violence (GBV) in a smart city context, which is a common component of violence across socio-economic groups globally. This paper analyzes the nature of news articles reported in English newspapers of Pakistan, India, and the UK-accumulating 12,693 gender-based violence-related news articles. For the qualitative textual analysis, we employ Latent Dirichlet allocation for topic modeling and propose a Doc2Vec based word-embeddings model to classify gender-based violence-related content, called GBV2Vec. Further, by leveraging GBV2Vec, we also build an online tool that analyzes the sensitivity of Gender-based violence-related content from the textual data. We run a case study on GBV concerning COVID-19 by feeding the data collected through Google News API. Finally, we show different news reporting trends and the nature of the gender-based violence committed during the testing times of COVID-19. The approach and the toolkit that this paper proposes will be of great value to decision-makers and human rights activists, given the prompt and coordinated performance against gender-based violence in smart city context-and can contribute to the achievement of SDGs for sustainable growth of human societies.

RESUMEN

Present study is engrossed in identification of phyto-constituents from aerial part extracts of Tamarix gallica and appraisal of its anti-oxidant, anti-diabetic and anti-inflammatory potential based upon its folktale use. The methanol and n-hexane fractions of aerial parts were analysed using high performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS) respectively. Inhibitory concentration (IC50) showed better results in case of methanolic extract for both in antioxidant (IC50= 15.47 µg/mL) and alpha amylase (IC50=18.75 µg/mL) assays. Significantly higher quantities of phenolic and flavonoid contents were present in methanolic extract. A significant correlation was found to be existed between these contents and IC50 of antioxidant assay. Alloxan induced hyperglycaemia declined along with improvement in lipid profile, C-reactive proteins (CRP), liver function tests (LFTs) and renal function tests (RFTs). Methanolic fraction (500 mg/kg) was also related to significant reduction in levels of inflammatory markers i.e. tumour necrosis factor-alpha, TNF- α (1.28 ± 0.13 g/L) and interleukin-6, IL-6 (98 ± 10.4 pg/L) as observed in diabetic rats. Based upon the above findings, the study suggests that methanolic fraction from aerial parts of the T. gallica has better anti-diabetic profile which might be attributed to its alpha amylase, anti-oxidant and anti-inflammatory potential.

Asunto(s)

Diabetes Mellitus Experimental , Hiperglucemia , Tamaricaceae , Ratas , Animales , Aloxano/uso terapéutico , Antioxidantes/farmacología , Antioxidantes/uso terapéutico , Hiperglucemia/tratamiento farmacológico , Tamaricaceae/metabolismo , Interleucina-6 , Diabetes Mellitus Experimental/tratamiento farmacológico , Metanol , Citocinas , Hipoglucemiantes/farmacología , Hipoglucemiantes/uso terapéutico , Hipoglucemiantes/química , Extractos Vegetales/farmacología , Extractos Vegetales/uso terapéutico , Extractos Vegetales/química , Factor de Necrosis Tumoral alfa , alfa-Amilasas/metabolismo , alfa-Amilasas/uso terapéutico , Antiinflamatorios/farmacología , Antiinflamatorios/uso terapéutico , Flavonoides/farmacología , Flavonoides/uso terapéutico , Lípidos

RESUMEN

Type 2 diabetes mellitus is a complicated metabolic disorder with no definite treatment. Cyperus iria (Cyperaceae) possess several traditional therapeutic uses. According to the folklore tales, the whole plant of Cyperus iria possesses antihyperglycemic activity. The present study was undertaken to investigate whether aqueous-ethanol extract of Cyperus iria can ameliorate the altered activities of carbohydrate metabolism in streptozotocin (STZ)-induced diabetic rats along with appraisal of inflammatory and stress markers involved in endocrine dysfunction. Presence of biophenolics and flavonoids might be responsible for the antidiabetic potential. STZ-induced diabetic rats were treated orally with Cyperus iria extract (125, 250, and 500 mg/kg) for 15 days. Blood samples were collected. Metformin was used as positive control. Significantly higher quantities of phenolic (82.79±0.003 mg/g GAE) and flavonoid (13.61±0.002 mg/g QE) contents were present. Inhibitory concentration (IC50) exhibited an excellent potential for both antioxidant (IC50= 3.22 µg/mL) and alpha amylase (IC50=36.29 µg/mL) inhibitory assays. High-performance liquid chromatography (HPLC) confirmed the existence of myercetin, quercetin, kaempferol, and ferulic acid. Cyperus iria aqueous-ethanol extract exhibits good tolerance against glucose at 90 min in normal rats. Streptozotocin-induced hyperglycemia declined significantly at day 9 (265 mg/dL) along with improvement in inflammatory (TNF-α=15.6± 0.2 g/l, COX-2=357±0.396 U/l, IL-6= 572±0.99 pg/l) and oxidative stress markers (SOD= 163±0.616 and GSH-ST= 95.8±0.44 U/mL) along with biochemical parameters in a dose-dependent manner. Present study suggests that Cyperus iria aqueous-ethanol extract possesses hypoglycemic potential which might be attributed to the decrease in oxidative stress and inflammatory markers.

Asunto(s)

Cyperus , Diabetes Mellitus Experimental , Hiperglucemia , Estrés Oxidativo , Extractos Vegetales/farmacología , Animales , Glucemia , Cyperus/química , Citocinas , Diabetes Mellitus Experimental/tratamiento farmacológico , Diabetes Mellitus Tipo 2/tratamiento farmacológico , Etanol , Hiperglucemia/tratamiento farmacológico , Estrés Oxidativo/efectos de los fármacos , Ratas , Estreptozocina

RESUMEN

Ethereum, the second-largest cryptocurrency after Bitcoin, has attracted wide attention in the last few years and accumulated significant transaction records. However, the underlying Ethereum network structure is still relatively unexplored. Also, very few attempts have been made to perform link predictability on the Ethereum transactions network. This paper presents a Detailed Analysis of the Ethereum Network on Transaction Behavior, Community Structure, and Link Prediction (DANET) framework to investigate various valuable aspects of the Ethereum network. Specifically, we explore the change in wealth distribution and accumulation on Ethereum Featured Transactional Network (EFTN) and further study its community structure. We further hunt for a suitable link predictability model on EFTN by employing state-of-the-art Variational Graph Auto-Encoders. The link prediction experimental results demonstrate the superiority of outstanding prediction accuracy on Ethereum networks. Moreover, the statistic usages of the Ethereum network are visualized and summarized through the experiments allowing us to formulate conjectures on the current use of this technology and future development.