bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tackling COVID-19 Through Ayurveda: A Review on the Herbs of
Recommended Indian Remedies
Authors: Vegad Udaykumar G , Pandya Devang J 
Published: February 2021

:
COVID-19 has rapidly spread across the globe and has been declared a pandemic. Presently, drugs or vaccines are unavailable, and patients are treated on symptom management basis. Traditional healthcare can contribute to prevent the infection in healthy individuals as well as in the treatment of infected patients. Ayurveda medicines become even more relevant as there is a descriptive illustration of causation and management of diseases similar to COVID-19 as Janapadodhwamsa. Meanwhile, Ministry of AYUSH, Govt. of India has recommended herbal remedies for prevention of COVID-19 infection. The remedies include 1. Herbal tea twice a day and 2. Golden milk for immunity boosting measures. Further, Steam inhalation and medicated honey is recommended for sore throat. In this review, we have tried to evaluate effectiveness of the recommended Indian remedies in prevention and treatment of COVID-19 conditions with available scientific literature. COVID-19, being primarily a respiratory disease, all 9 herbs of remedies have been selected for analysing their respiratory diseases related immunomodulatory and other activities, anti-viral, antibacterial activities as well as in silico effectiveness of constituents thereof against SARS-CoV-2 targets. The literature search was carried out in electronic databases namely PubMed, ScienceDirect, ACS Publications, Clinicaltrials.gov, Springer, and Google Scholar. The scientific evaluation revealed that the recommended Indian remedies might be useful in tackling COVID-19 situation, though scientific interventional studies are required to establish the claims.
Structure, Morphology Features and Photocatalytic Properties of α-Ag2WO4 Nanocrystals-modified Palygorskite Clay
Authors: Jucá Amanda Carolina Soares , Lopes Francisco Henrique Pereira , Silva-Júnior Herbert Vieira , Silva Lara Kelly Ribeiro , Longo Elson , Sczancoski Júlio César , Cavalcante Laecio S. 
Published: February 2021

Aims:
In the present study, we investigate the photocatalytic properties of α-Ag2WO4 nanocrystals-
modified Palygorskite (PAL) clay synthesized by the impregnation method. The PAL clay
was chemically purified and heat-treated (500 ºC for 2 h), which served as an excellent supporting
matrix for loading α-Ag2WO4 (α-AWO) nanocrystals.

Background:
Water contamination is one of the most serious problems affecting human health, ecosystem
survival, and the economic growth of societies. Industrial effluents, such as textile dyes, when
not treated and improperly discharged into water resources are considered the main cause of water
pollution. Thus the scientific community has been developing effective remediation technologies
based on advanced oxidative processes to reduce the harmful effects of these organic pollutants.

Objective:
This study aimed to improve the photocatalytic activity of PAL clay with α-AWO nanocrystals
to degradation of Rhodamine B (RhB) dye.

Methods:
We purify and heat-treated the PAL clay, synthesize nanocrystals ofα-AWO nanocrystals and modify PAL clay with 30% α-AWO nanocrystals by the impregnation method. The modified PAL clay was able to improve RhB dye degradation. The materials were characterized by XRD, RAMAN,FE-SEM, FT-IR, XRF, etc. The samples were used as photocatalysts under UV-C lamps for the degradation of RhB dye in order to analyze its catalytic performances.

Results:
The PAL clay modified with 30% α-AWO nanocrystals showed a catalytic efficiency of
79%, and degradation kinetics about 16 times higher when compared to PAL-500 only purified and
heat-treated at 500 ºC. In this way, this PAL-modified is an alternative as a low-cost photocatalyst for
the degradation of RhB dye.

Conclusion:
Ultraviolet-visible spectra revealed that our materials have optical band gap energies
controlled by indirect and direct electronic transitions and suitable to be activated under ultraviolet illumination.
The adequate amount (30 wt.%) of α-Ag2WO4 nanocrystals added to PAL brought significant
improvement in the photocatalytic activity for the degradation of rhodamine B. Finally, a photocatalytic
mechanism was proposed in detail.
A Hybrid Branch Prediction Approach For High-Performance Processors
Authors: Nain Sweety , Chaudhary Prachi 
Published: February 2021

Background:
In a parallel processor, the pipeline cannot fetch the conditional
instructions with the next clock cycle, leading to a pipeline stall. Therefore, conditional
instructions create a problem in the pipeline because the proper path can only be known after the
branch execution. To accurately predict branches, a significant predictor is proposed for the
prediction of the conditional branch instruction.

Method:
In this paper, a single branch prediction and a correlation branch prediction scheme are
applied to the different trace files by using the concept of saturating counters. Further, a hybrid
branch prediction scheme is proposed, which uses both global and local branch information,
providing more accuracy than the single and correlation branch prediction schemes.

Results:
Firstly, a single branch prediction and correlation branch prediction technique are applied
to the trace files using saturating counters. By comparison, it can be observed that a correlation
branch prediction technique provides better results by enhancing the accuracy rate of 2.25% than
the simple branch prediction. Further, a hybrid branch prediction scheme is proposed, which uses
both global and local branch information, providing more accuracy than the single and correlation
branch prediction schemes. The results suggest that the proposed hybrid branch prediction schemes
provide an increased accuracy rate of 3.68% and 1.43% than single branch prediction and
correlation branch prediction.

Conclusion:
The proposed hybrid branch prediction scheme gives a lower misprediction rate and
higher accuracy rate than the simple branch prediction scheme and correlation branch prediction
scheme.
Deep Learning Model for Real-Time Prediction of Intradialytic Hypotension
Authors: Lee Hojun , Yun Donghwan , Yoo Jayeon , Yoo Kiyoon , Kim Yong Chul , Kim Dong Ki , Oh Kook-Hwan , Joo Kwon Wook , Kim Yon Su , Kwak Nojun , Han Seung Seok 
Published: February 2021

Background and objectives
Intradialytic hypotension has high clinical significance. However, predicting it using conventional statistical models may be difficult because several factors have interactive and complex effects on the risk. Herein, we applied a deep learning model (recurrent neural network) to predict the risk of intradialytic hypotension using a timestamp-bearing dataset.

Design, setting, participants, & measurements
We obtained 261,647 hemodialysis sessions with 1,600,531 independent timestamps (i.e., time-varying vital signs) and randomly divided them into training (70%), validation (5%), calibration (5%), and testing (20%) sets. Intradialytic hypotension was defined when nadir systolic BP was <90 mm Hg (termed intradialytic hypotension 1) or when a decrease in systolic BP ≥20 mm Hg and/or a decrease in mean arterial pressure ≥10 mm Hg on the basis of the initial BPs (termed intradialytic hypotension 2) or prediction time BPs (termed intradialytic hypotension 3) occurred within 1 hour. The area under the receiver operating characteristic curves, the area under the precision-recall curves, and F1 scores obtained using the recurrent neural network model were compared with those obtained using multilayer perceptron, Light Gradient Boosting Machine, and logistic regression models.

Results
The recurrent neural network model for predicting intradialytic hypotension 1 achieved an area under the receiver operating characteristic curve of 0.94 (95% confidence intervals, 0.94 to 0.94), which was higher than those obtained using the other models (P<0.001). The recurrent neural network model for predicting intradialytic hypotension 2 and intradialytic hypotension 3 achieved area under the receiver operating characteristic curves of 0.87 (interquartile range, 0.87–0.87) and 0.79 (interquartile range, 0.79–0.79), respectively, which were also higher than those obtained using the other models (P≤0.001). The area under the precision-recall curve and F1 score were higher using the recurrent neural network model than they were using the other models. The recurrent neural network models for intradialytic hypotension were highly calibrated.

Conclusions
Our deep learning model can be used to predict the real-time risk of intradialytic hypotension.
BENS JURIDICOS LESADOS NO CRIME DE PORNOGRAFIA DE VINGANÇA E SUA EFETIVA TUTELA PENAL NA LEI MARIA DA PENHA
Authors: Silva Artenira da Silva e , Pinheiro Rossana Barros 
Published: February 2021

A pornografia de vingança se apresenta como crime de larga incidência na modernidade, evidenciando as percepções sexistas e machistas de gênero já observadas na convivência presencial nas plataformas virtuais, influenciando assim a percepção do agressor quanto à necessidade da vingança moral ante uma traição ou término afetivos, expondo as mulheres a julgamentos sociais que condenam a postura das vítimas, naturalizando assim a violência praticada. Considerando que a pornografia de vingança fere simultaneamente uma variedade de bens jurídicos mediante a perpetração de diferentes modalidades de violência de gênero, conclui-se que a Lei Maria da Penha apresenta-se como instrumento normativo mais adequado ao enfrentamento institucional do problema, haja vista a centralidade do conceito de violência de gênero e a consideração da complexidade das múltiplas modalidades de violências praticadas em virtude desse.
CORONAVÍRUS (COVID-19): O RESSARCIMENTO À REDE PÚBLICA DE SAÚDE PELOS GASTOS DE BENEFICIÁRIOS DE PLANOS PRIVADOS
Authors: Ferraz Miriam Olivia Knopik , Ferneda Ariê Scherreier 
Published: February 2021

O presente artigo tem por finalidade analisar o direito à saúde enquanto um direito fundamental e a possibilidade de planos privados de saúde ressarcirem o Sistema Único de Saúde em razão dos serviços prestados aos seus beneficiários no caso do COVID-19. Nesse sentido, por meio da metodologia lógico-dedutiva pretendeu-se dar ênfase ao princípio do acesso universal e igualitário à saúde para questionar a possibilidade de ressarcimento prevista no art. 32 da Lei n. 9.656/1998, sem olvidar do entendimento fixado pelo Supremo Tribunal Federal junto ao Recurso Extraordinário n. 597.064 e à Ação Direta de Inconstitucionalidade n. 1931. Ademais, ressalta-se a atualidade do debate e por isso retoma-se diante da pandemia que eclodiu no mundo em março de 2020.
Bioethanol Production from Yam (Dioscorea Rotundata) Using Simultaneous Saccharification and Fermentation (SSF)
Authors: Villadiego-del Villar Alfredo Enrique , Sarmiento-Zea Nicolás , León-Pulido Jeffrey , Rojas-Pérez Lilia Carolina 
Published: February 2021

Yam is a starchy tuber mainly used in food preparation but with high potential applications in other fields such as pharmaceutical and bioplastic production. Colombia is among the top twelve yam producing countries worldwide and ranked first in terms of yield of tons per hectare planted. Yam production has specifically been concentrated in the Caribbean region, which is why this tuber is very little known in the inland regions. In this study, we evaluated Simultaneous Saccharification and Fermentation (SSF) for bioethanol production from yam (Dioscorea rotundata) using Saccharomyces bayanus. Ethanol production technologies involve the fermentation and hydrolysis of consumable raw materials (i.e., sugar cane and corn) which are quite mature around the world. For this reason, the process under analysis combined three phases: 60 min of gelatinization, enzymatic hydrolysis (divided into 40 min of liquefaction with α-amylase and 20 min of saccharification with glucoamylase), and 27 h of fermentation with no enzyme recovery. We used different yam concentrations (10, 12.5, 15, and 18 % w/w) in a wet basis. SSF was monitored along time, and total reducing sugars and ethanol concentration were quantified. The hydrolysis yield, was calculated based on the theoretical starch available in the tuber, was 90 % of starch mass for samples with a yam concentration of 10 and 15 % w/w. Regarding ethanol, the best result (a productivity of 0.19 g/Lh-1) was obtained with the sample with a yam concentration of 10 % w/w. Therefore, yam is a starchy material suitable to produce bioethanol via SSF.
Jupyter: Thinking and Storytelling with Code and Data
Authors: Granger Brian , Pérez Fernando 
Published: February 2021

Project Jupyter is an open-source project for interactive computing
widely used in data science, machine learning, and scientific computing.
We argue that even though Jupyter helps users perform complex, technical
work, Jupyter itself solves problems that are fundamentally human in
nature. Namely, Jupyter helps humans to think and tell stories with code
and data. We illustrate this by describing three dimensions of Jupyter:
interactive computing, computational narratives, and the idea that
Jupyter is more than software. We illustrate the impact of these
dimensions on a community of practice in Earth and climate science.
Geochemistry and Petrogenetic Relationships Between Pegmatites and Host Rocks in the Keffi Area, North Central, Nigeria
Authors: Tanko I. Y. , Dzigbodi-Adjimah K. 
Published: February 2021

Keffi pegmatites area which contains numerous mineralised and non-mineralised pegmatites lie between the Wamba pegmatite field to the NE and Nasarawa pegmatite field to the SW on the North Central Pegmatite belt of Nigeria. In Keffi area exploitation of deposits is currently being done by small scale miners, whose activities are haphazard and uncoordinated, because of that information on the geology and petrology that will enable a systematic study of the pegmatites in the area is scanty. Systematic geochemical investigations of the pegmatites and surrounding host rocks aimed at establishing petrogenetic relationships amongst the various rock types in the area were conducted. Major, trace and REE investigations of the pegmatites and associated granitoids have indicated petrogenetic relationships amongst the pegmatites and between the pegmatites and surrounding granitoids of Keffi area. Also, the variation diagram of major, trace and REE in whole rocks and K-feldspar samples show patterns which categorised the pegmatites of Keffi area into; (1) Non-mineralised, (2) intermediate and (3) mineralised pegmatites. It was also deduced from the geochemical characteristics (variation diagrams in major and trace element, REE geochemistry and tectonic environment classification) that a genetic model based on the evolution of melt by partial melting of metasedimentary protolith during ultrametamorphic and deformational activities (anatexis) is proposed for the granite-pegmatite system of Keffi area. This information will be useful as guide for fruitful exploration of the pegmatites and serves as model for the exploitation of pegmatite veins in similar geologic settings.
Pengaruh Model Pembelajaran Investigasi Kelompok berbantuan Perangkat Lunak Maple terhadap Kemampuan Pemecahan Masalah Matematis
Authors: Wulandari Putri , Mujib Mujib , Putra Fredi Ganda 
Published: February 2021

This study aims to determine the effect of mathematical problem solving ability of learners who follow the learning by using an instructional model of maple assisted software assisted, with learners who use, study group investigation model, as well as learners who follow the conventional learning model conducted by researchers on participants Students of class X SMK Muhammadiyah 1 Metro. This type of research is a quasi experimental research with posttest only control design design. Hypothesis test using a one-way anava test with unequal cells and obtained the conclusion that the model of group investigation learning is better than an instructional model of maple assisted software group and both models of learning is better than conventional learning model. Based on the results of analysis and discussion of research data obtained that there is an influence on the ability of solving mathematical problems among students in class applying group investigation model assisted maple software, students in class apply only group investigation learning model, and students whose class apply the conventional learning model on the principal Discussion of the matrix.
Sebaran Generalized Extreme Value (GEV) Dan Generalized Pareto (GP) untuk Pendugaan Curah Hujan Ekstrim di Wilayah DKI Jakarta
Authors: Rinaldi Achi 
Published: February 2021

Extreme event such as extreme rainfall have been analyzed and most concern for the country all around the world. There are two common distribution for extreme value which are Generalized Extreme Value distribution and Generalized Pareto distribution. These two distribution have shown good performace to estimate the parameter of extreme value. This research was aim to estimate parameter of extreme value using GEV distribution and GP distribution, and also to characterized effect of extreme event such as flood. The rainfall data was taken from BMKG for 5 location in DKI Jakarta. Both of distribution shown a good perfromance. The resut showed that Tanjung Priok station has biggest location parameter for GEV and also the biggest scale parameter for GP, that mean the biggest probability to take flood effect of the extreme rainfall.
Meningkatkan Kemampuan Generalisasi Matematis Melalui Discovery Learning dan Model Pembelajaran Peer Led Guided Inquiry
Authors: Anggoro Bambang Sri 
Published: February 2021

The low ability of mathematical generalization of the students of SMPN 17 Bandar Lampung is because most of the students still have difficulty in drawing a conclusion from the material they have acquired and the lesson learned process of generalization aspect or less precisely the instructional model used. The purpose of this research is to know the influence of learning model of Peer Led Guided Inquiry and learning, discovery learning model with the ability of mathematical generalization. The measured variable from this research is the generalization ability in mathematics learning with the subject of algebraic factorization. This research is a quasi experimental research (quasi experimental research), where the subject of the study is students Class VIII students SMPN 17 Bandar Lampung. Data collection technique used is a test of mathematical generalization ability. The data analysis technique used analysis of variance (ANAVA) of one road with cell unlike the significance level α = 0,05 and as requirement analysis, that is a normal distribution population with liliefors model and homogenous population with Bartlett Test. Based on the result of research using ANAVA one way with cell unequal with significance level α = 0,05 it is obtained that 〖F〗 _count F_tabel IE 7,5105 3,0973, hence the decision of Ho test is rejected. So it can be concluded that there is influence of learning model Peer Led Guided Inquiry, learning model of Discovery Learning, Conventional learning model to ability of mathematical generalization of learners. The test proceeds with a double-compression test using Scheffe ' methods to see which has a significant effect on mathematical generabilizability. The calculation results show that of the three treatments, the learning model of Discovery Learning which gives a significant influence on the ability of mathematical generalization.
Analisis Persepsi Siswa SMP terhadap Pembelajaran Matematika ditinjau dari Perbedaan Gender dan Disposisi Berpikir Kreatif Matematis
Authors: Anggoro Bambang Sri 
Published: February 2021

This research is a qualitative research with the qualitative descriptive method. The technique of research subject taking in this research use purposive sampling technique. The subjects of this study amounted to 9 students. Data collection techniques used were questionnaire perception and disposition of students' mathematical creative thinking, observation, interview and documentation of mathematics learning. Data analysis techniques, namely data reduction, data presentation, and conclusions. The validity of data in this study using the content validity, construct validity and reliability and triangulation techniques. According to the results of the study and discussion, the conclusion of this study is Based on the gender and disposition of mathematical creative thinking, the perception of mathematics learning that is produced, that is for high DBKM and positive perception is only found in male students, for high DBKM and medium perception, Male and female students, for medium DBKM and medium perception, female students tend to be more than male students, for medium DBKM and negative perceptions of male students tend to be more than female students, for low DBKM and perception is being Only in boys, and for low DBKM and negative perceptions are only found in female students. The disposition of high mathematical creative thinking and positive perception is very influential on learning mathematics because students who have high DBKM and positive perception will be better in learning mathematics than students who have DBKM and perceptions other than high DBKM and positive perceptions of mathematics learning.
Pembelajaran Matematika dengan Metode Accelerated Learning untuk Meningkatkan Kemampuan Penalaran Adaptif
Authors: Putra Rizki Wahyu Yunian 
Published: February 2021

The ability of adaptive reasoning is a competence that must be possessed by students, but the reality of the field shows that students' adaptive reasoning ability is still not satisfactory. Learning with the accelerated learning method is applied in the hope of improving students' adaptive reasoning abilities. The purpose of this research is to know whether the improvement in students' adaptive reasoning ability with accelerated learning method is better than ordinary learning. This research is a quasi-experiment or quasi-experiment with pretest-posttest control group design. Implementation of this research is done on grade VIII students in one of the State Junior High School in Bandar Lampung. Problems given are questions of reasoning ability of adaptive in material relation and a function, test of ability, ability of reasoning is tested theoretically by validating with picture that test question can be well understood and empirically validity and reliability fulfill characteristic to be used in research, The degree of difficulty and distinguishing power of the problem can already be used to determine the enhancement of the ability of adaptive reasoning. Quantitative data analysis was performed using flat most different and N-Gain test. The results of this study are students whose learning to apply learning with an accelerated learning method of enhancing the ability of adaptive reasoning is significantly better than that of students whose learning using ordinary learning is reviewed in whole.