bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative study between ethanolic and chloroform extracts of mucuna pruriens seeds extract in male wistar rats for the screening of anti-ulcer activity
Authors: Srivastava Kalyani , Amit Kaushik , Srivastava Amit Kishor , Gupta Amresh 
Published: September 2022

Background: Well documented neuroprotective profile as well as antioxidant potential of mucuna pruriens seeds with lesser side effects, we are intended to compare study between ethanolic (MPEE) and chloroform extracts (MPCE) of mucuna pruriens seeds extract in albino Wistar rats for the screening of anti-ulcer activity.
Materials and methods: The pylorus ligation induced ulcer was used to explore the activity of the ethanolic and chloroform extract. Male albino Wistar rats weighing 100-150g were selected and grouped them among normal control, standard (Omeprazole; 20mg/kg) and treatment groups (MPEE; 50 mg/kg and MPCE; 50 mg/kg) respectively.
Results: In our study, the chloroform and ethanolic extract of the seeds of Mucuna pruriens showed antiulcer efficacy as evidenced by a considerable decrease in gastric volume, free and total acidities, ulcer index, and pH. Consequently it might be predicted that both the extracts prevent suppress gastric damage induced by aggressive factors. Preventive anti-oxidants like catalase (CAT) enzymes and reduced glutathione (GSH) constitute the first line of defense in order to combat reactive oxygen species.
Conclusion: The ethanolic and chloroform extracts were significantly inhibited the growth of ulcers. Based on the findings, it was determined that the ethanolic extract had superior antiulcer activity over the chloroform extract. In comparison to ulcer control rats, the administration of herbal extract (50 mg/kg p.o.) raised CAT, SOD, and GSH levels, indicating its efficiency in reducing free radical-induced damage. The preliminary phytochemical investigation showed the presence of glycosides, flavonoids, carbohydrate, and tannins in the ethanolic extract, whereas glycosides, sterols, triterpines and tannins in the chloroform extract. The MPEE exhibited a better ulcer protective activity than the MPCE extract.
Rolling vs. seasonal PMF: real-world multi-site and synthetic dataset comparison
Authors: Via Marta , Chen Gang , Canonaco Francesco , Daellenbach Kaspar R. , Chazeau Benjamin , Chebaicheb Hasna , Jiang Jianhui , Keernik Hannes , Lin Chunshui , Marchand Nicolas , Marin Cristina , O'Dowd Colin , Ovadnevaite Jurgita , Petit Jean-Eudes , Pikridas Michael , Riffault Véronique , Sciare Jean , Slowik Jay G. , Simon Leïla , Vasilescu Jeni , Zhang Yunjiang , Favez Olivier , Prévôt André S. H. , Alastuey Andrés , Cruz Minguillón María 
Published: September 2022

Abstract. Particulate matter (PM) has become a major concern in terms of human health
and climate impact. In particular, the source apportionment (SA) of organic
aerosols (OA) present in submicron particles (PM1) has gained relevance
as an atmospheric research field due to the diversity and complexity of its
primary sources and secondary formation processes. Moreover, relatively
simple but robust instruments such as the Aerosol Chemical Speciation
Monitor (ACSM) are now widely available for the near-real-time online
determination of the composition of the non-refractory PM1. One of the
most used tools for SA purposes is the source-receptor positive matrix
factorisation (PMF) model. Even though the recently developed rolling PMF technique has
already been used for OA SA on ACSM datasets, no study has assessed its
added value compared to the more common seasonal PMF method using a practical
approach yet. In this paper, both techniques were applied to a synthetic
dataset and to nine European ACSM datasets in order to spot the main output
discrepancies between methods. The main advantage of the synthetic dataset
approach was that the methods' outputs could be compared to the expected
“true” values, i.e. the original synthetic dataset values. This approach
revealed similar apportionment results amongst methods, although the
rolling PMF profile's adaptability feature proved to be advantageous, as it
generated output profiles that moved nearer to the truth points. Nevertheless,
these results highlighted the impact of the profile anchor on the solution,
as the use of a different anchor with respect to the truth led to
significantly different results in both methods. In the multi-site study,
while differences were generally not significant when considering year-long
periods, their importance grew towards shorter time spans, as in intra-month
or intra-day cycles. As far as correlation with external measurements is
concerned, rolling PMF performed better than seasonal PMF globally for the ambient
datasets investigated here, especially in periods between seasons. The results of this
multi-site comparison coincide with the synthetic dataset in terms of
rolling–seasonal similarity and rolling PMF reporting moderate improvements. Altogether, the
results of this study provide solid evidence of the robustness of both
methods and of the overall efficiency of the recently proposed rolling PMF
approach.
A new machine-learning-based analysis for improving satellite-retrieved atmospheric composition data: OMI SO2 as an example
Authors: Li Can , Joiner Joanna , Liu Fei , Krotkov Nickolay A. , Fioletov Vitali , McLinden Chris 
Published: September 2022

Abstract. Despite recent progress, satellite retrievals of
anthropogenic SO2 still suffer from relatively low signal-to-noise
ratios. In this study, we demonstrate a new machine learning data analysis
method to improve the quality of satellite SO2 products. In the absence
of large ground-truth datasets for SO2, we start from SO2 slant
column densities (SCDs) retrieved from the Ozone Monitoring Instrument (OMI)
using a data-driven, physically based algorithm and calculate the ratio
between the SCD and the root mean square (rms) of the fitting residuals for
each pixel. To build the training data, we select presumably clean pixels
with small SCD / rms ratios (SRRs) and set their target SCDs to zero. For polluted pixels with relatively large SRRs, we set the target to the
original retrieved SCDs. We then train neural networks (NNs) to reproduce
the target SCDs using predictors including SRRs for individual pixels, solar zenith, viewing zenith and phase angles, scene reflectivity, and O3 column amounts, as well as the monthly mean SRRs. For data analysis, we employ two NNs: (1) one trained daily to produce analyzed SO2 SCDs for polluted pixels each day and (2) the other trained once every month to produce analyzed SCDs for less polluted pixels for the entire month. Test results for 2005 show that our method can significantly reduce noise and artifacts over background regions. Over polluted areas, the monthly mean NN-analyzed and original SCDs generally agree to within ±15 %, indicating that our method can retain SO2 signals in the original retrievals except for large volcanic eruptions. This is further confirmed by running both the NN-analyzed and original SCDs through a top-down emission algorithm to estimate the annual SO2 emissions for ∼500 anthropogenic sources, with the two datasets yielding similar results. We also explore two alternative approaches to the NN-based analysis method. In one, we employ a simple linear interpolation model to
analyze the original SCD retrievals. In the other, we develop a PCA–NN
algorithm that uses OMI measured radiances, transformed and
dimension-reduced with a principal component analysis (PCA) technique, as
inputs to NNs for SO2 SCD retrievals. While the linear model and the
PCA–NN algorithm can reduce retrieval noise, they both underestimate
SO2 over polluted areas. Overall, the results presented here
demonstrate that our new data analysis method can significantly improve the
quality of existing OMI SO2 retrievals. The method can potentially be
adapted for other sensors and/or species and enhance the value of satellite
data in air quality research and applications.
Gridded 5 arcmin datasets for simultaneously farm-size-specific and crop-specific harvested areas in 56 countries
Authors: Su Han , Willaarts Bárbara , Luna-Gonzalez Diana , Krol Maarten S. , Hogeboom Rick J. 
Published: September 2022

Abstract. Farms are not homogeneous. Smaller farms generally have different planted
crops, yields, agricultural inputs, and irrigation applications compared to
larger farms. However, gridded farm-size-specific data that are moreover
crop specific, are currently lacking. This obscures our understanding of
differences between small-scale and large-scale farms, e.g., with respect to
climate change adaptation and mitigation strategies, contribution to (local)
food security, and water consumption patterns. This study fills a
significant part of the current data gap, by developing high-resolution
gridded, simultaneously farm-size-specific and crop-specific datasets of harvested
areas for 56 countries (i.e., covering about half the global cropland).
Hereto, we downscaled the most complete global direct measurements of farm
size and crop type by compiling state of the art datasets, including crop
maps, cropland extent maps, and dominant field size distribution,
representative for the year 2010. Using two different crop map sources, we
were able to produce two new 5 arcmin gridded datasets on simultaneously
derived farm-size-specific and crop-specific harvested areas: one for 11 farm sizes,
27 crops, and 2 farming systems, and one for 11 farm sizes, 42 crops, and 4
farming systems. In line with previous findings, our resulting datasets show
major differences in planted crops and irrigated area (%) between farm
sizes. Consistency between our resulting datasets and (i) observations from
satellite images on farm-size-specific oil palm, (ii) household surveys on
the farm-size-specific irrigated area (%), and (iii) previous studies that
mapped noncrop-specific farm sizes and support the validity of our datasets.
Although at grid level some uncertainties remain to be overcome,
particularly those stemming from uncertainties in crop maps, results at
country level seem robust. Source data, code, and resulting datasets are
open access and freely available at https://doi.org/10.5281/zenodo.6976249
(Su et al., 2022).
Vulnerabilidade física e ambiental da zona costeira sob a influência de parques eólicos nos municípios de Pedra Grande e São Miguel do Gostoso/RN, Brasil
Authors: Clemente de Lacerda Ivens Lorran , Amaro Venerando Eustáquio , De Matos Maria de Fátima Alves , Scudelari Ada Cristina 
Published: September 2022

Este estudo visa à determinação da vulnerabilidade física e ambiental da zona costeira de São Miguel do Gostoso e Pedra Grande/RN antes e depois da instalação de parques eólicos. Além disso, é realizada uma análise de vulnerabilidade na linha de costa da área mencionada, levando-se em consideração as alterações espaciais concretizadas nos últimos 30 anos, análise esta que é apresentada separadamente. Calcularam-se os índices de vulnerabilidade natural (IVN) e ambiental (IVA) por meio de análises espaciais baseadas em mapas temáticos das variáveis do meio físico e antrópico, conforme métodos de análise multicritérios hierarquizada e de redução de dimensionalidade por processo analítico hierárquico (PAH) e pela análise de componentes principais (ACP). As vulnerabilidades alta e muito alta, somadas, apresentaram proporções entre 18 e 30% em todos os cenários do IVN e IVA. O índice de vulnerabilidade costeira (IVC) foi definido por dois métodos para três cenários de aumento do nível do mar estabelecidos pelo Painel Intergovernamental de Mudanças Climáticas (IPCC): um com seis variáveis físicas e hidrodinâmicas, e outro que inclui, além destas, outras três variáveis de ação antrópica. Para todos os cenários, toda a extensão da linha de costa mostrase, majoritariamente, com vulnerabilidades média e alta. Conclui-se que a implantação do complexo de parques eólicos contribuiu para o aumento da vulnerabilidade dos ecossistemas locais nos três índices avaliados, mas não foi o fator preponderante para a definição do grau de vulnerabilidade do IVC.
Patterns of Teaching Presence during One Semester of a Large Online Graduate Nursing Course
Authors: Baker Micah , Richardson Stephanie , Rubio Fernando 
Published: September 2022

Extensive research supports the claim that student-instructor interaction is an essential element of successful online teaching. It is less clear, however, whether teaching presence is discipline-specific, or how it may be affected by the personal and professional background of individual instructors.
This article describes the qualitative portion of a mixed-methods study to analyze patterns of commenting behaviors in a graduate-level online nursing course. Following the Community of Inquiry theoretical framework (Garrison, Anderson & Archer, 2000), we compare experienced and inexperienced instructors and specifically focus on how teaching presence evolved over a fifteen-week course. Our findings indicate that teaching experience affects the types and density of comments used by teachers. Experience played a role in how density and overall level of activity evolved as the semester progressed. No differences in teaching presence emerged when comparing instructions for each assignment, but there were differences when comparing instructions to teacher posts.
Analisis Faktor-Faktor Yang Menentukan Penerbitan Opini Audit Going Concern
Authors: Muchayatin Muchayatin , Eka Lupita Herniyah 
Published: September 2022

Penelitian ini didasari tentang opini audit going concern pada umumnya diberikan oleh auditor jika dalam pelaporan keuangan suatu perusahaan tidak terbukti terdapat kesalahan dalam penyampaian informasi atau mengandung informasi yang berlawanan. Pada saat ini, auditor mulai diminta tanggung jawabanya untuk mengungkap kelangsungan usaha suatu entitas, tidak hanya mendeteksi kecurangan dalam laporan keuangan tetapi juga sanggup memprediksi kemampuan perusahaan dalam melangsungkan hidupnya. Dalam pengeluaran atau pemberian opini audit going concern terdapat faktor-faktor non keuangan yang dirasa bisa mempengaruhi seorang auditor dalam mengeluarkan opini audit going concern. Penelitian ini bertujuan untuk mendapatkan bukti empiris pengaruh opini audit tahun sebelumnya, reputasi auditor, dan opinion shopping terhadap opini audit going concern. Populasi dalam penelitian ini adalah perusahaan dalam Industri Barang Konsumsi yang terdaftar pada Bursa Efek Indonesia. Seluruh perusahaan sampel telah memenuhi kriteria yang ditentukan dalam metode purposive sampling dengan jumlah perusahaan sebanyak 187 data perusahaan selama tahun 2017-2020. Berdasarkan hasil penelitian dapat diperoleh simpulan bahwa opini audit tahun sebelumnya, reputasi auditor dan opinion shopping secara statistik berpengaruh positif dan signifikan terhadap opini audit going concern sehingga hasil ini sesuai dengan hipotesis yang diajukan.
Feasibility Study of Small-Spacing Twin Well Salt Cavern Gas Storage in Ultra Deep Formation
Authors: Li Haitao , Wanyan Qiqi , Li Kang , Ding Guosheng , Gou Yanxia , Ran Lina , Bai Song , Deng Jingen 
Published: September 2022

ABSTRACT:
As a new type of cavern, small-spacing twin well (SSTW) salt cavern has an extensive application prospect in underground gas storage (UGS) due to its good performance such as rapid construction rate, adaptability of thin salt layer, and high injection-production efficiency. While it has not been found to be used in ultra deep formation. Based on the geological condition and rock mechanical parameters of Pingdingshan Salt Mine, Henan province, China, a 3D geomechanical model considering viscoelastic plasticity of target stratum rock is established to numerically investigate the feasibility of SSTW salt cavern gas storage with the upper height of 70 m, well spacing of 25 m and cavern height of 235 m in ultra deep formation (more than 1700 m). A set of assessment index is introduced to evaluate the safety and stability of salt cavern UGS. The results show that the displacement, plastic zone volume and volume loss rate of the salt cavity increase with the decreasing of internal gas pressure while the stress-strength ratio has a decreasing trend, showing the cavern tends to be unstable. The operation pressure has a large influence on the stability of the UGS. Properly increasing the minimum operating pressure can still maintain the stability of salt cavity in extra deep formation. The deformation in long axis direction is smaller than that in short axis direction, which indicates the pillar needs to be lengthened in short axis direction when the cavern groups are planned. The cavern shows good stability under cycle internal gas pressure as well. All the evaluation indexes present that it is feasible to build the SSTW cavern gas storage in such ultra-deep formation when the proper internal gas pressure is chosen. This research provides a theoretical reference for the application of SSTW salt cavern UGS in similar geological condition.
The Qualitative Stability Graph for Open Stope Design – Recent Developments
Authors: Suorineni F. T. , Madenova Y. 
Published: September 2022

ABSTRACT:
The Stability Graph is an accepted tool for open stope design in the metalliferous underground mining community. Since its development in 1981, it has undergone several modifications and remains active research subject to date. Admittedly, while some of the suggested changes have been called into question for their practical relevance, others have gone a long way to improve the reliability of the method in minimizing dilution in open stope mining. One of the major concerns that has emerged in researching some suggested modifications to the design tool appears to show some authors do not understand the assumptions and purpose behind the tool. Such authors rely on application of statistics to the database with no idea of the practical implications of the outcome of their analysis. The downside of this is that so much confusion has been created in the mining industry as to what is useful in using the method for open stope design. This paper cautions against the misuse of statistics in geo-engineering with emphasis on the Stability Graph and provides recent developments relevant to improving the reliability of the method in reducing dilution in open stope s. Furthermore, the long outstanding question of whether the original Stability Graph number factors or the modified Stability Graph number factors should be used or not is that there is no difference between the two.

1. INTRODUCTION
In 1980 the Department of Energy, Mines and Resources of the Canadian Center for Mineral and Energy Technology (CANMET) commissioned Golder Associates Consulting Geotechnical and Mining Engineers to determine the information that is required to predict stable spans for open stopes at mining depths below 1 000 m. The method developed in the report for the design of open stopes by Golder Associates has since been referred to as the Mathews Stability Graph Method (Mathews et al., 1981).
Approaches to Determine Fault Shear Strength in Large-Scale Direct Shear Test Simulations Using Discrete Fracture Networks
Authors: Kim B. H. , Larson M. K. 
Published: September 2022

ABSTRACT:
In this study, 3DEC modeling in conjunction with the Discrete Fracture Networks (DFNs) technique was performed to better understand the behavior of shearing faults in a relatively large-scale direct shear test model. The DFNs explicitly generated two different geometries of the fault plane surface indicating the stepped or smooth waviness of the surface using probability distribution functions to generate orientation, fracture density (or frequency), and size of the discrete fractures. A 3-dimensional block model of hundreds of meters was constructed for the direct shear test using 3DEC modeling software. After the completion of the direct shear test simulations, a shear strength of the fault plane was estimated by back calculation. The DFNs with subhorizontal/vertical dip angles created an imbricate structure that resulted in a stepped geometry and strong shear response in the fault plane. Under direct shear, the fault plane needed to break the asperities or block before any frictional behavior was allowed or the fault plane would dilate significantly. This resulted in higher shear strength of the fault plane. On the other hand, the DFNs with oblique dip angles generated a relatively smooth surface of the fault plane. The smooth surface of the fault plane allowed deformation principally parallel to the fault plane, and only a few failures developed across the rock blocks in the model. Consequently, the 3DEC model explicitly replicated the complicated geometries of the fault plane using the two very contrasting DFNs and allowed researchers to investigate different shear behaviors of fault planes as a function of surface conditions.

1. INTRODUCTION
The highly anisotropic characteristics of coal seams that result from geologic structures when mining takes place, such as cleats, bedding, faults, and spatial redistribution of induced stress in coal pillars, cause many uncertainties that affect safety. Dynamic failure in coal mines, known as "bumps," is one of the most challenging and persistent engineering problems associated with coal mining in highly stressed conditions. These events occur when stresses in a coal pillar, used for support in underground workings, exceed the critical strength of the pillar, causing the pillar to rupture without warning. These events can be exceptionally violent, ejecting coal and rock with explosive force [1, 2].