bluuebunny/crossref_metadata_2025_split huggingface dataset:
New versions of the least-squares collocation method for solving differential and integral equations
Authors: Shapeev Vasily , Golushko Sergey , Belyaev Vasily , Bryndin Luka , Kirillov Pavel 
Published: January 2021

AbstractThis paper describes new versions of the least-squares collocation method for solving differential and integral equations. A p-version of the method has been proposed and implemented to solve nonlinear systems of partial differential equations. The stationary Navier-Stokes equations are used as an example. A hp-version of the method has been implemented for the numerical solution of the Fredholm integral equations of the second kind in the one-and two-dimensional cases. This paper shows that approximate solutions obtained by various versions of the least-squares collocation method converge with a high order and agree with analytical solutions of test problems with a high degree of accuracy.
On constructing the Riemannian metrics in refraction tomography problems
Authors: Yu Derevtsov E 
Published: January 2021

AbstractA problem of the refraction tomography consists in reconstructing a function or tensor field by their attenuated ray transforms. Usually an absorption coefficient and refraction in the medium are assumed to be known. A solution to the refraction tomography problems can be obtained by approximate methods within the corresponding mathematical models, and the modeling of refraction is one of important elements of the model. We adduce summary data on the Riemannian metrics, suitable for the implementation in numerical tests, methods of their construction and main characteristics.
Identification of the energy system critical elements using the PARMONC library
Authors: Edelev A V , Marchenko M A , Yu Basharina O 
Published: January 2021

Abstract
In this paper, we presented a Monte Carlo-based approach for vulnerability analyse of energy systems. For high-performance Monte Carlo simulation the PARMONC software library was used. The PARMONC is implemented on high-performance clusters of the Siberian Supercomputer Center. The PARMONC effectively launches parallel stochastic simulation on supercomputers with different architectures. The proposed approach was applied was applied for the identification and ranking the most important elements of a real-world natural gas supply system.
A study of Hepatitis B virus infection using chi-square statistic
Authors: Odetunmibi Oluwole A , Adejumo Adebowale O , Anake Timothy A 
Published: January 2021

Abstract
Hepatitis B is caused by the hepatitis B virus (HBV) and it affects livers. It has been established that the disease is a serious medical condition caused by an overpowering immune response to infection. To this effect, there is a need for cross examination of records of patients on this disease to ascertain the factors that could be responsible for the survival or dying from this disease. Descriptive analysis of the data showed that sexually active age bracket (31 – 50) are greatly affected by the disease while female accounted for majority of those that are tested positive to the disease. Chi squared statistic was used to test for independence between age and gender of those who tested positive to disease between 2006 and 2015 in Lagos state, Nigeria. It was discovered that, both variables of age and gender are not independent which means there is association between the Age and Gender of HBV patients.
Radiological Hazard Assessment of Sharp-Sand from Ilorin-East, Kwara State, Nigeria
Authors: Orosun M. M. , Usikalu M. R. , Oyewumi K. J. , Oladapo O. F 
Published: January 2021

Abstract
Measurement of activity concentration of primordial radionuclides 40K, 232Th, 238U and the corresponding gamma dose rate over a major sharp-sand field in Ilorin, Nigeria, was carried out using Super Spec RS125 gamma ray spectrometer. The RS125 gamma spectrometer gives in-situ measurement of radioactivity concentration. Measurements were taken in 50 locations. The peak values of the measured activity concentrations of 40K, 238U, 232Th, the dose rate (D) and the resulting annual effective dose (AED) are 688.60, 48.17, 30.86 Bqkg−1, 49.50 nGyh−1 and 0.06 mSvy−1 respectively, while their corresponding lowest values are 31.30, 1.24, 0.41 Bqkg−1, 4.70 nGyh−1, and 0.01 mSvy−1 respectively. The estimated mean values of 40K, 232Th, 238U, the gamma dose rate (D) and AED are 454.48, 13.52, 11.63 Bqkg−1, 32.96 nGyh−1 and 0.04 mSvy−1 respectively. Consequently, the mean values of the measured radionuclides and the hazard parameters i.e. dose rate and annual effective dose are within the permissible levels. This follows that the risk of radiation exposure for this location is comparatively less, but the general public may not be safe from exposure to indoor ionizing radiation since no amount of radiation is safe for stochastic effects.
Geophysical investigation of road failure along Lagos-Badagry expressway using electrical resistivity imaging
Authors: Ogungbe Abiola S , Afolabi Timothy O , Onori Eugene O , Ogabi Cornelius O 
Published: January 2021

Abstract
Geophysical investigations of road failure using Two-dimensional (2D) electrical resistivity imaging was carried out along Lagos – Badagry expressway, Lagos State, Nigeria with a view to determining the subsurface geological structures that may pose a danger to the highway. The study was conducted on five worrisome parts of the highway, namely: Iyana Isashi, Iyana Era, Agbara, Magbon and Oko Afo, using Constant Separation Traversing (Wenner array) to obtain three (3) profiles at each location. ABEM Terrameter SAS 1000 was used for the survey which displays apparent resistivity values digitally. The data was processed with the aid of the RES2DINV software to produce 2D images of the study area. The subsurface images showed that the resistivity lies between 3.89 Ωm and 401 Ωm, indicating variation in soil matrix. It was found that the causes of road pavement collapse on the road examined were the result of a mixture of clay topsoil/subgrade soils with resistance varying from 3.79 m to 83.3 m, waterlogged sands. This is due to ingress with characteristically low resistance values and a thin pavement, thus unable to withstand the lane’s pressure.
Antimicrobial and antibiofilm activities of green synthesized silver nanoparticles for water treatment
Authors: Ismail A. O. , Ajayi S. O. , Alausa A. O. , Ogundile O. P. , Ademosun O. T. 
Published: January 2021

Abstract
Nanoparticles have found applications in wide areas due to their unique properties. Green synthesis of nanoparticles is an ecofriendly, safe and non-toxic approach that solve the problems associate with conventional methods. Waterborne pathogenic diseases have resulted in millions of deaths in humans especially children annually and infectious microorganism associated with water have all shown multiple resistance to conventional treatments. Bacteria biofilm accounts for majority of microbial infections and are more resistant to antimicrobial agents. The use of antibiotics is ineffective for treating biofilm-associated infections. Green synthesized silver nanoparticles (AgNps) have been reported to have important antimicrobial applications over a wide range of microorganisms, although many researchers have demonstrated in in vitro the antimicrobial activity of AgNps, few researches have been conducted on the exact mechanism of action of AgNps as antibiofilm, the possibility of infectious microbes to develop resistance and the toxicity limit of silver suitable for human consumption. This review discussed biocompatibility of green synthesis AgNps, the concept of biofilm formation, the impacts of AgNps water microbial environment, its mechanisms of action as antimicrobial agent in water treatment and the potential human toxicity.
PDTM for the solution of a time-fractional barrier option Black-Scholes model
Authors: Edeki S. O. , Jena R. M. , Ogundile O. P. , Chakraverty S. 
Published: January 2021

Abstract
This paper introduces the Fractional Projected Differential Transform Method (FPDTM) for the solution of the Time-fractional Barrier Option Black-Scholes Pricing Model (TFBOBSPM). The method seeks the solution using sufficient initial (transformed boundary conditions), without any discretization or restrictive assumptions. The efficiency and precision of the proposed methods are tested using illustrative examples. Thus, the FPDTM is suggested for strongly nonlinear differential models with financial applications.
Deforestation reshapes land-surface energy-flux partitioning
Authors: Yuan Kunxiaojia , Zhu Qing , Zheng Shiyu , Zhao Lei , Chen Min , Riley William J , Cai Xitian , Ma Hongxu , Li Fa , Wu Huayi , Chen Liang 
Published: January 2021

Abstract
Land-use and land-cover change significantly modify local land-surface characteristics and water/energy exchanges, which can lead to atmospheric circulation and regional climate changes. In particular, deforestation accounts for a large portion of global land-use changes, which transforms forests into other land cover types, such as croplands and grazing lands. Many previous efforts have focused on observing and modeling land–atmosphere–water/energy fluxes to investigate land–atmosphere coupling induced by deforestation. However, interpreting land–atmosphere–water/energy-flux responses to deforestation is often complicated by the concurrent impacts from shifts in land-surface properties versus background atmospheric forcings. In this study, we used 29 paired FLUXNET sites, to improve understanding of how deforested land surfaces drive changes in surface-energy-flux partitioning. Each paired sites included an intact forested and non-forested site that had similar background climate. We employed transfer entropy, a method based on information theory, to diagnose directional controls between coupling variables, and identify nonlinear cause–effect relationships. Transfer entropy is a powerful tool to detective causal relationships in nonlinear and asynchronous systems. The paired eddy covariance flux measurements showed consistent and strong information flows from vegetation activity (gross primary productivity (GPP)) and physical climate (e.g. shortwave radiation, air temperature) to evaporative fraction (EF) over both non-forested and forested land surfaces. More importantly, the information transfers from radiation, precipitation, and GPP to EF were significantly reduced at non-forested sites, compared to forested sites. We then applied these observationally constrained metrics as benchmarks to evaluate the Energy Exascale Earth System Model (E3SM) land model (ELM). ELM predicted vegetation controls on EF relatively well, but underpredicted climate factors on EF, indicating model deficiencies in describing the relationships between atmospheric state and surface fluxes. Moreover, changes in controls on surface energy flux partitioning due to deforestation were not detected in the model. We highlight the need for benchmarking model simulated surface-energy fluxes and the corresponding causal relationships against those of observations, to improve our understanding of model predictability on how deforestation reshapes land surface energy fluxes.
Species-specific climate–growth interactions determine tree species dynamics in mixed Central European mountain forests
Authors: Kašpar Jakub , Tumajer Jan , Šamonil Pavel , Vašíčková Ivana 
Published: January 2021

Abstract
Increasing growing season temperatures and the seasonal redistribution of precipitation due to climate change have recently been recorded across the globe. Simultaneously, increases of severe droughts and windstorm frequency have also been documented. However, the impacts of climate change on tree growth performance and fitness might largely differ among coexisting species. Consequently, ongoing temperature increases could lead to extensive changes in tree species compositions in many forest biomes including temperate mountain forests. In this study we used an extensive dataset of 2824 cored trees of three species from two sites, and parameterized a purely climate driven process-based model (Vaganov–Shaskin) to simulate the growth dynamics and climatic limitations of coexisting Picea abies, Fagus sylvatica and Abies alba in two of the oldest mountain forest reserves in Central Europe (the Boubín and Žofín Primeval Forests). We assumed that the species composition reflects climatic growth limitations, and considered between-site differences in mean temperature due to elevation as a model of future climate change effects on mountain forests. Our results show a complexity of site- and species-specific responses of Central European forests to climate change. Over the last 70 years, the proportion of F. sylvatica in Central European natural forests has increased at the expense of conifers. During the investigated period, we observed an increase in the growth rates of the studied species mainly at the higher elevation site, while for the lower elevation site there was increasing intensity of moisture limitation. Despite being the most moisture-limited species, P. abies showed the highest simulated growth rates. In contrast, A. alba was the least moisture limited of all considered species. Given its recent proportion in the forest species composition and intermediate drought resistance, we anticipate the future expansion of F. sylvatica in Central European mountain forests.
Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios
Authors: Müller Christoph , Franke James , Jägermeyr Jonas , Ruane Alex C , Elliott Joshua , Moyer Elisabeth , Heinke Jens , Falloon Pete D , Folberth Christian , Francois Louis , Hank Tobias , Izaurralde R César , Jacquemin Ingrid , Liu Wenfeng , Olin Stefan , Pugh Thomas A M , Williams Karina , Zabel Florian 
Published: January 2021

Abstract
Concerns over climate change are motivated in large part because of their impact on human society. Assessing the effect of that uncertainty on specific potential impacts is demanding, since it requires a systematic survey over both climate and impacts models. We provide a comprehensive evaluation of uncertainty in projected crop yields for maize, spring and winter wheat, rice, and soybean, using a suite of nine crop models and up to 45 CMIP5 and 34 CMIP6 climate projections for three different forcing scenarios. To make this task computationally tractable, we use a new set of statistical crop model emulators. We find that climate and crop models contribute about equally to overall uncertainty. While the ranges of yield uncertainties under CMIP5 and CMIP6 projections are similar, median impact in aggregate total caloric production is typically more negative for the CMIP6 projections (+1% to −19%) than for CMIP5 (+5% to −13%). In the first half of the 21st century and for individual crops is the spread across crop models typically wider than that across climate models, but we find distinct differences between crops: globally, wheat and maize uncertainties are dominated by the crop models, but soybean and rice are more sensitive to the climate projections. Climate models with very similar global mean warming can lead to very different aggregate impacts so that climate model uncertainties remain a significant contributor to agricultural impacts uncertainty. These results show the utility of large-ensemble methods that allow comprehensively evaluating factors affecting crop yields or other impacts under climate change. The crop model ensemble used here is unbalanced and pulls the assumption that all projections are equally plausible into question. Better methods for consistent model testing, also at the level of individual processes, will have to be developed and applied by the crop modeling community.
CO2-plant effects do not account for the gap between dryness indices and projected dryness impacts in CMIP6 or CMIP5
Authors: Scheff Jacob , S Mankin Justin , Coats Sloan , Liu Haibo 
Published: January 2021

Abstract
Recent studies have found that terrestrial dryness indices like the Palmer Drought Severity Index (PDSI), Standardized Precipitation Evapotranspiration Index (SPEI), and Aridity Index calculated from future climate model projections are mostly negative, implying a drying land surface with warming. Yet, the same models’ future runoff and bulk soil moisture projections instead show regional signals of varying sign, and their vegetation projections show widespread greening, suggesting that the dryness indices could overstate climate change’s direct impacts. Most modeling studies have attributed this gap to the indices’ omission of CO2-driven stomatal closure. However, here we show that the index-impact gap is still wide even in future-like model experiments that switch off CO2 effects on plants. In these simulations, mean PDSI, Aridity Index, and SPEI still decline broadly with strong warming, while mean runoff, bulk soil moisture, and vegetation still respond more equivocally. This implies that CO2-plant effects are not the dominant or sole reason for the simulated index-impact gap. We discuss several alternative mechanisms that may explain it.
On the singularities of the discrete Korteweg–deVries equation
Authors: Um D , Ramani A , Grammaticos B , Willox R , Satsuma J 
Published: January 2021

Abstract
We study the structure of singularities in the discrete Korteweg–deVries (d-KdV) equation. Four different types of singularities are identified. The first type corresponds to localised, ‘confined’, singularities, the confinement constraints for which provide the integrability conditions for generalisations of d-KdV. Two other types of singularities are of infinite extent and consist of oblique lines of infinities, possibly alternating with lines of zeros. The fourth type of singularity corresponds to horizontal strips where the product of the values on vertically adjacent points is equal to 1. (A vertical version of this singularity with product equal to −1 on horizontally adjacent sites also exists). Due to its orientation this singularity can, in fact, interact with the other types. This leads to an extremely rich structure for the singularities of d-KdV, which is studied in detail in this paper. Given the important role played by the fourth type of singularity we decided to give it a special name: taishi (the origin of which is explained in the text). The taishi do not exist for nonintegrable extensions of d-KdV, which explains the relative paucity of singularity structures in the nonintegrable case: the second and third type of singularities that correspond to oblique lines still exist and the localised singularities of the integrable case now become unconfined, leading to semi-infinite lines of infinities alternating with zeros.
Complex systems approaches for Earth system data analysis
Authors: Boers Niklas , Kurths Jürgen , Marwan Norbert 
Published: January 2021

Abstract
Complex systems can, to a first approximation, be characterized by the fact that their dynamics emerging at the macroscopic level cannot be easily explained from the microscopic dynamics of the individual constituents of the system. This property of complex systems can be identified in virtually all natural systems surrounding us, but also in many social, economic, and technological systems. The defining characteristics of complex systems imply that their dynamics can often only be captured from the analysis of simulated or observed data. Here, we summarize recent advances in nonlinear data analysis of both simulated and real-world complex systems, with a focus on recurrence analysis for the investigation of individual or small sets of time series, and complex networks for the analysis of possibly very large, spatiotemporal datasets. We review and explain the recent success of these two key concepts of complexity science with an emphasis on applications for the analysis of geoscientific and in particular (palaeo-) climate data. In particular, we present several prominent examples where challenging problems in Earth system and climate science have been successfully addressed using recurrence analysis and complex networks. We outline several open questions for future lines of research in the direction of data-based complex system analysis, again with a focus on applications in the Earth sciences, and suggest possible combinations with suitable machine learning approaches. Beyond Earth system analysis, these methods have proven valuable also in many other scientific disciplines, such as neuroscience, physiology, epidemics, or engineering.
Performance of the Scheduled Relaxation Jacobi method in a geometric multilevel setting. I. Linear case
Authors: Bentivegna Eloisa 
Published: January 2021

Abstract
I investigate the suitability of the Scheduled-Relaxation-Jacobi method as a smoother within a geometric multilevel (ML) solver. Its performance in the solution of a linear elliptic equation is measured, based on two metrics: absolute performance (measured by the residual reduction in a fixed number of iterations), and parallel scalability. I discuss the theoretical expectations on the effect of this hybrid scheme on the solution iterate and, especially, the solution error, and confirm them numerically.
Genome-scale de novo assembly using ALGA
Authors: Swat Sylwester , Laskowski Artur , Badura Jan , Frohmberg Wojciech , Wojciechowski Pawel , Swiercz Aleksandra , Kasprzak Marta , Blazewicz Jacek 
Published: January 2021

Abstract

Motivation
There are very few methods for de novo genome assembly based on the overlap graph approach. It is considered as giving more exact results than the so-called de Bruijn graph approach but in much greater time and of much higher memory usage. It is not uncommon that assembly methods involving the overlap graph model are not able to successfully compute greater datasets, mainly due to memory limitation of a computer. This was the reason for developing in last decades mainly de Bruijn-based assembly methods, fast and fairly accurate. However, the latter methods can fail for longer or more repetitive genomes, as they decompose reads to shorter fragments and lose a part of information. An efficient assembler for processing big datasets and using the overlap graph model is still looked out.

Results
We propose a new genome-scale de novo assembler based on the overlap graph approach, designed for short-read sequencing data. The method, ALGA, incorporates several new ideas resulting in more exact contigs produced in short time. Among these ideas, we have creation of a sparse but quite informative graph, reduction of the graph including a procedure referring to the problem of minimum spanning tree of a local subgraph, and graph traversal connected with simultaneous analysis of contigs stored so far. What is rare in genome assembly, the algorithm is almost parameter-free, with only one optional parameter to be set by a user. ALGA was compared with nine state-of-the-art assemblers in tests on genome-scale sequencing data obtained from real experiments on six organisms, differing in size, coverage, GC content and repetition rate. ALGA produced best results in the sense of overall quality of genome reconstruction, understood as a good balance between genome coverage, accuracy and length of resulting sequences. The algorithm is one of tools involved in processing data in currently realized national project Genomic Map of Poland.

Availability and implementation
ALGA is available at http://alga.put.poznan.pl.

Supplementary information
Supplementary data are available at Bioinformatics online.