bluuebunny/crossref_metadata_2025_split huggingface dataset:
Situación actual de la competitividad y sustentabilidad y el COVID-19
Authors: Espinoza-Audelo Luis Fernando 
Published: December 2021

Plantearse cuál será el futuro no es tarea fácil, el año 2020 ha marcado ampliamente el sentido de nuestras vidas, modificando todas las dinámicas tanto sociales, económicas y ambientales. A finales del siglo pasado la Organización de las Naciones Unidas (ONU) en su publicación “Nuestro futuro común” (1987) advertía una sobre explotación de los recursos naturales dado que el crecimiento económico se convirtió en el objetivo primordial de los países (Costanza et al., 2014). Así mismo, la ONU proponía trabajar simultáneamente y con equilibrio en las dimensiones económica, humana, ambiental, institucional y tecnológica para asegurar la sustentabilidad, donde la mezcla de estas daba paso a la competitividad mediante la optimización de los recursos, así como las formas y actuación de los agentes sociales, económicos y políticos para alcanzar un crecimiento y un desarrollo adecuado y sostenido (Lombana & Rozas, 2009).
Recibido: 26/11/2020. Aceptado: 28/11/2020. Publicado: 01/12/2020
The Duration and Geodynamics of Formation of the Angara–Vitim Batholith: Results of U–Pb Isotope (LA-ICP-MS) Dating of Magmatic and Detrital Zircons
Authors: Khubanov V.B. , Tsygankov A.A. , Burmakina G.N. 
Published: December 2021

Abstract
—We present results of U–Pb (LA-ICP-MS) dating of detrital zircons from the alluvial deposits of the Angarakan River (North Muya Ridge, northern Baikal region), whose drainage basin is composed mainly of granitoids of the Barguzin Complex, typomorphic for the late Paleozoic Angara–Vitim batholith (AVB). Three age clusters with peaks at 728, 423, and 314 Ma have been identified in the studied population of detrital zircons. It is shown that small outliers of igneous and metamorphic rocks, probably similar to the large AVB roof pendants mapped beyond the drainage basin, are the source of Neoproterozoic and early Paleozoic zircons. The late Paleozoic cluster comprises two close peaks at 314 and 28 Ma, which totally “overlap” with the time of the AVB formation and mark a granitoid source of the zircons. The results of detrital-zircon geochronology, together with the data on bedrocks, point to the prolonged (~40 Myr) formation of the AVB, but the intensity of magmatism during this period calls for additional study. Based on the analysis of published geological, geochemical, and geochronological data, we assume that the AVB resulted from the plume–lithosphere interaction that began in the compression setting and gave way to extension 305–300 Ma (the Carboniferous–Permian boundary), which caused replacement of “crustal” granitoids by granitoids formed from a mixed mantle–crustal source.
Methane Fluxes at the Water–Atmosphere Interface and Gas-Geochemical Anomalies in the Bottom Sediments in the Northwestern Part of the Sea of Japan
Authors: Mishukova G.I. , Yatsuk A.V. , Shakirov R.B. , Syrbu N.S. , Valitov M.G. , Ponomareva A.L. , Mishukova O.V. 
Published: December 2021

Abstract
—We present results of an integrated research into the spatial distribution of methane in the area of the northern closure of the Central Basin of the Sea of Japan and in the southern part of the Tatar Trough. Methane emissions have been revealed in the study area. The methane fluxes are distributed unevenly within the area (1 to 23 mol/(km2·day)). The discrete high-frequency measurements and calculation of methane fluxes at the water–atmosphere interface, combined with the study of the content of natural gases and microbiologic parameters in sediment cores, allow us to explain the formation of local methane emission zones in the water area. Despite the great sea depths, there are sources and fluid-conducting zones that determine methane concentrations (exceeding the equilibrium ones) and high methane emissions from the water area. The data obtained provide new information and suggest the presence of deep gas sources, which determine gas dispersion in the bottom sediments, the methane content in the surface water layer, and the distribution of methane fluxes at the water–atmosphere interface in the study area. This study is part of the integrated program of geological and geophysical expeditionary research performed by V.I. Il’ichev Pacific Oceanological Institute (Vladivostok) in the northern part of the Sea of Japan.
A Decision Fusion Method Based on Classification Models for Water Quality Monitoring
Authors: LADJAL Mohamed , BOUAMAR Mohamed , BRIK Youcef , DJERIOUI Mohamed 
Published: December 2021

Abstract
Monitoring of water quality is one of the world's main intentions of countries. In this paper we present the use of Principal Component Analysis (PCA) combined with Support Vector Machines (SVM) and Artificial Neural Network (ANN) based on Decision Templates combination data fusion method. SVM and ANN are employed in classification stage. Decision Templates is applied to increase accuracy of the water quality classification compared to others combination data fusion methods. This work concerned the water quality assessment from Tilesdit dam (Algeria) that it permitted us to acquire additional knowledge and information about study area and to obtain an intelligent monitoring system. The Multi-Layer Perceptron network (MLP) and the One-Against-All strategy for SVM method are have been widely used. The training step is performed in this paper using these techniques to classify water quality from various physicochemical parameters such as temperature, pH, electrical conductivity and turbidity, etc. Eight of them were collected in the period 2009-2018 from the study area. The selection of the excellent parameters of the used models can be improving the performance of classification process. In order to assess their results, an experiment step using collected data set corresponding to the accuracy and running time of training and test phases, and robustness, is carried out. Various scenarios are examined in comparative study to obtain the most results of decision step with and without features selection of the input data. The combination by Decision Templates of two classifiers enhanced expressively the results of the proposed monitoring framework that had prove a considerable ability in surface water quality assessment.
Deployment of Continuous Miner in Under Ground Coal Mine – A Case Study of Sarpi Mine.
Authors: Samanta Subrata , Sinha Rabindra Kumar , Chakrabarty Pulak Baran , Kumar Hemant 
Published: December 2021

Abstract
The continuous miner technology (CMT) is being adopted extensively in underground coal mines of India as Mass Production Technology (MPT). This technology potentially eliminates the two-unit operating, namely the drilling and blasting. This elimination helps for better strata control and avoids the drillers working in unsafe conditions, maybe under the loose coal roof. This CMT improves the quality of the coal extracted and increases the output per man shift (OMS) by reducing the deployment of face crew. It also reduces the accident as it is operated by remote and workforce exposure to faces is limited. The method also helps for better roof and side control, thus preventing side and roof fall danger. With the changing time now, continuous miners of different heights are available, which helps for optimum use of technology to mine out varying insitu height of coal seam. This paper discusses the performance of the CMT in the Sarpi mine and compares the technology available globally.
An Image Enhancement Method for Few-shot Classification
Authors: Wu Yirui , Wu Benze , Zhang Yunfei , Wan Shaohua 
Published: December 2021

Abstract
With the development of 5G/6G, IoT, and cloud systems, the amount of data generated, transmitted, and calculated is increasing, and fast and effective close-range image classification becomes more and more important. But many methods require a large number of samples to support in order to achieve sufficient functions. This allows the entire network to zoom in to meet a large number of effective feature extractions, which reduces the efficiency of small sample classification to a certain extent. In order to solve these problems, we propose an image enhancement method for the problems of few-shot classification. This method is an expanded convolutional network with data enhancement function. This network can not only meet the features required for image classification without increasing the number of samples, but also has the advantage of using a large number of effective features without sacrificing efficiency. structure. The cutout structure can enhance the matrix in the data image input process by adding a fixed area 0 mask. The structure of FAU uses dilated convolution and uses the characteristics of the sequence to improve the efficiency of the network. We conduct a comparative experiment on the miniImageNet and CUB datasets, and the proposed method is superior to the comparative method in terms of effectiveness and efficiency measurement in the 1-shot and 5-shot cases.
Willingness To COVID-19 Vaccination: Empirical Evidence From EU
Authors: Rahman Imran Ur , Austin Arslan , Nelson Naveed 
Published: December 2021

Abstract
The unforgettable COVID-19 shock can only be reversed by a viable vaccination strategy. In this paper, we investigate willingness to be vaccinated (WTV) against the COVID-19. We provide first of its kind empirical evidence on the citizens (N=11,932) of the EU-27 by employing the recent data from the European Commission. Controlling for the correlations in the error terms, we utilize a simulated multivariate probit regression model. Our results show that amongst all the statistically significant drivers of the WTV, the positive perception (vaccination works and has no side effects); R&D information (clarity on how vaccination is developed, tested, authorized) has the largest impact on the WTV. We find that the group of variables on social feedback, and on trustworthy sources of information are to be considered for WTV policy. The counteracting policy gaps are also identified. Our work is novel and has implications for COVID-19 vaccination policies across the EU.
A Remote Sensing and Machine Learning Based Framework For The Assessment of Spatiotemporal Water Quality Along The Middle Ganga Basin
Authors: Krishnaraj Ashwitha , H Ramesh 
Published: December 2021

Abstract
Exploring qualitative measures of any waterbody is as vital as quantitative analysis for the sustainability of our water resources. Thus, examining the dynamics of spatiotemporal behaviour of dominant Water Quality Parameters (WQPs) along any waterbody is indeed critical for proposing the appropriate water resource management. This study aims to create a Machine learning model for mapping the dominant optical and non-optical WQPs such as Electrical Conductivity (EC), pH, Temperature (Temp), Total Dissolved Solids (TDS), Silicon Dioxide (SiO2) and Dissolved Oxygen (DO) using satellite data. However, the association between WQPs and satellite data is strenuous to model precisely using simple regression theory. In this context, we developed remote sensing-based Extreme Gradient Boosting (XGBoost) and Multilayer Perceptron (MLP) regressor with optimized Hyperparameters to understand the spatiotemporal variations of WQPs using Landsat-8 imageries. We evaluated six years of satellite data for the geographical area covering from Ankinghat to Chopan (20 sampling stations under Central Water Commission (CWC), Middle Ganga Division (MGD) II) for characterizing the trends of dominant Physico-chemical WQPs across the four clusters identified in our previous study. Through the developed XGBoost and MLP regression models between measured WQPs and the remote sensing reflectance for the pixels corresponding to the sampling stations, a significant coefficient of determination (R2) in the range of 0.88- 0.98 for XGBoost and 0.72-0.97 for MLP have generated with bands B1-B4 and their ratios more consistent. Indeed, our findings recommend fewer in-situ measurements to generate reliable Landsat-8 based ML models to estimate Spatio-temporal variations of Physico-chemical and biological WQPs to facilitate better management of our waterbodies.
Global Trends and Current Status in Osteonecrosis of the Femoral Head: A Bibliometric Analysis of Publications in Recent 30 Years
Authors: Wen Zeqin , Li Yusheng , Cai Zijun , Fan Meng , Wang Jian , Ding Ran , Huang Cheng , Xiao Wenfeng 
Published: December 2021

Abstract
Background: Osteonecrosis of the femoral head (ONFH) is a progressive and disabling disease with heavy socioeconomic burdens. The purpose of our study was to summarize the global trends and current status in ONFH.Methods: Publications related to ONFH from 1991 to 2020 were searched from the Web of Science (WOS) core collection database. The data were analyzed with bibliometric methods. Microsoft Excel was used to statistical analysis and draw bar charts. SPSS was applied to perform linear regression analysis. VOSviewer was used to conduct bibliographic coupling analysis, co-authorship analysis, co-citation analysis, and co-occurrence analysis. Results: A total of 5,523 publications were covered. The United States consistently ranked first in total publications, sum of times cited, average citations per item, and H-index. Kyushu University was the main contributor to ONFH. Clinical Orthopaedics and Related Research was the major publishing channels for ONFH-related articles. Takuaki Yamamoto published the most ONFH-related articles. Studies regarding ONFH could be divided into 5 clusters: mechanism study, treatment study, complication study, radiological study, and etiological study. Mechanism study might become the hot spot in the future.Conclusions: This study identified the last 30 years’ articles in ONFH and summarized their global trends and current status, which classified them by country, institution and author, publication, funding agency, and direction. This study will help researchers understand the research perspectives, hot spots, and trends of ONFH.
Reaction Mechanism About Isomerization of Resin Acids and Synthesis of Acrylopimaric Acid Based on DFT Calculation
Authors: Lai Wu-Ji , Lu Jia-Hao , Jiang Rui , Zeng Lei , Wu Ai-qun , shen liqun 
Published: December 2021

Abstract
Acrylopimaric acid is considered one of the possible substitutes for petroleum-based polymeric monomers, which is an important industrial product. Resin acids were isomerized to form levopimaric acid(4), which reacted with acrylic acid to synthesize isomers of acrylopimaric acid. Density functional theory calculation was used to investigate the reaction mechanisms with seven reaction paths in five different solutions. The values of ΔG were sorted from highest to lowest by levopimaric acid(4), neoabietic acid(3), palustric acid(2), and bietic acid(1). From the perspective of dynamics, the energy barrier in the isomerization of palustric acid(2) to levopimaric acid(4) was the lowest, whereas the highest energy barrier was the isomerization of neoabietic acid(3) to levopimaric acid(4) in the same solution. The addition reaction of levopimaric acid(4) and acrylic acid(5) to acrylopimaric acid c(8) was the optimal reaction path dynamically. However, ΔG of acrylopimaric acid c(8) was higher than that of acrylopimaric acid d(9). In general, the rates of isomerization reactions for rosin resin acids and addition reaction for acrylopimaric acid in water were higher than those in other solvents. HOMO-LUMO and ESP were analyzed for 8 kinds of molecules. For acylpyimaric acid, the non-planar six-memed ring and the C-C double bonds were easily attacked by nucleophile, while the non-planar six-memed ring and the carboxyl group are easily reacted with electrophiles. The highest electrostatic potential of the eight molecules is located at H of the carboxyl group, while the highest electrostatic potential is located at C-O double bond of the carboxyl group.
How Do Self-Examination Interventions For The Early Detection of Cancer Work? An Umbrella Review Protocol.
Authors: Goldrick Niall Mc , Cassie Heather , Young Linda , McGregor Scott , Conway David I , Clarkson Janet 
Published: December 2021

Abstract
Background: Cancer is a major contributor to mortality and morbidity globally. A key prognostic factor for many cancers is early detection. Self-examination is often promoted as a method to detect cancer early for cancers that have early physical signs and symptoms. The type(s) of interventions capable of delivering behaviour change such as self-examination are complex with their description historically lacking. This umbrella review protocol sets out the methodology for summarising the evidence surrounding self-examination for four major cancers; breast, testicular, oral and skin. The review aims to answer the following question: What are the components of self-examination programmes for early detection of cancer and are they effective in bringing about actions that could lead to early detection of cancer in post pubescent people. Methods: The methodology has been informed by the PRISMA-P checklist for systematic reviews and the JBI methodology for umbrella reviews. Narrative synthesis will include detail on effectiveness of interventions alongside coding of intervention components using Intervention Taxonomy and the Behaviour Change Technique Taxonomy Version 1. AMSTAR-2 will be used to assess quality of included studies. Discussion: The review will provide a summary of the existing evidence with descriptions of interventions whilst identifying gaps for future research in this area.Registration: Prospero: CRD42021285966
Palliative Sedation for Children at End of Life: a Retrospective Cohort Study
Authors: Chen Yang , Jiang Jianjun , Peng Wei , Zhang Chuan 
Published: December 2021

Abstract
Background: Palliative sedation is consciously reducing the patient's consciousness to alleviate the refractory symptoms. However, studies on palliative sedation for children are scarce. We aimed to survey the symptom control and risks for children with sedative therapy in end of life.Method: This study was a single center retrospective cohort study. Children who died in the Department of Palliative Medicine were divided into palliative sedation (Group A) and non-palliative sedation group (Group B). The symptoms relief, survival time, and last hospitalization time were compared between two groups. Results: From January 2012 to November 2019, 41 children died in department of palliative care. 24 children were sedated (Group A), meanwhile 17 children were not (Group B). The symptoms in Group A were more complex than Group B (p =0.013). Overall symptom relief in Group A was higher than that in Group B (24/24, 10/15 p =0.041). Pain relief rates（7/7, 20/21 p =0.714）, maximum/pre-death opioid dose [30(20, 77.5), 18(9, 45) p =0.175, 30(20, 60), 18(9, 45) p =0.208]and pain intensity difference [5(4,6.5), 4(2,6) p =0.315] were not statistically significant difference in both group. After diagnosis, the survival time of the Group A was longer than the Group B (p =0.047). However, the length of hospitalization before death was similar in two groups (p =0.385).Conclusion: Palliative sedation controls complicated, painful symptoms at the end of life and does not shorten the hospitalization time in children.
Hospitalization Costs of Respiratory Diseases Attributable to Temperature in the Context of Climate Change in Australia
Authors: Tong Michael , Wondmagegn Berhanu , Xiang Jianjun , Williams Susan , Hansen Alana , Dear Keith , Pisaniello Dino , Varghese Blesson , Xiao Jianguo , Jian Le , Scalley Ben , Nitschke Monika , Nairn John , Bambrick Hilary , Karnon Jonathan , Bi Peng 
Published: December 2021

Abstract
Background: The association between temperatures and respiratory diseases has been extensively reported. However, the associated healthcare costs and attributable fractions due to temperature have scarcely been explored. The aims of this study were to estimate respiratory disease hospitalization costs attributable to non-optimum ambient temperature, to quantify the attributable fraction from cold and hot temperatures, and to estimate the future hospitalization costs in two Australian cities. Methods: The associations between daily hospitalization costs for respiratory diseases and temperatures in Sydney and Perth over the study period of 2010-2016 were analyzed using distributed lag non-linear models. Future hospitalization costs for respiratory diseases were estimated based on three predicted climate change scenarios - RCP2.6, RCP4.5 and RCP8.5. Results: The estimated respiratory disease hospitalization costs attributable to non-optimum ambient temperatures increased from 493.2 million Australian dollars (AUD) in 2010s to more than 700 million AUD in 2050s in Sydney, and from 98.0 million AUD to about 150 million AUD during the same period in Perth, in large part due to population growth. In the context of climate change, the current cold attributable fraction in Sydney (23.7%) and Perth (11.2%) is estimated to decline by the middle of this century to (18.1-20.1%) and (5.1-6.6%) respectively, while the heat-attributable fraction for respiratory disease is expected to gradually increase from 2.6% up to 5.5% in Perth. Conclusions: This study found both cold and hot temperatures increased the overall hospitalization costs for respiratory diseases in two major Australian cities, although the attributable fractions varied. The largest contributor was cold temperatures. While respiratory disease hospitalization costs will increase in the future, climate change will result in a decrease in the cold attributable fraction and an increase in the heat attributable fraction, depending on the location.
The Effects of Environmental Tax On Ecological Footprint and Carbon Dioxide Emissions: a Nonlinear Cointegration Analysis On Turkey
Authors: Telatar Osman Murat , Birinci Nagihan 
Published: December 2021

Abstract
This article presents a nonlinear analysis in Turkey on the effect of an environmental tax (ET) on the ecological footprint (EF) and carbon dioxide (CO2) emissions. In the literature, most of the studies examining the effects of Environmental Taxes (ETs) on Environmental Degradation (ED) have used linear methods. The number of studies examining this relationship with nonlinear methods is few. However, there is no study examining the long-run effects of ETs on the EF, which is one of the most important indicators of ED, using nonlinear analysis. This study contributes to the literature by investigating the long-run effects of ETs on EF and CO2 emissions in Turkey by nonlinear analysis. Therefore, the model consisting of annual data for the period 1994–2019 was estimated by Dufrénot et al. (2006) nonlinear cointegration test. According to the estimation results obtained, ETs do not have any long-run effects on EF and CO2 emissions. Accordingly, it can be concluded that ETs in Turkey do not affect preventing ED.