bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of interrelations of demographic and socio-economic parameters of rural development
Authors: Balashova N N , Popova S A , Korobeynikov D A , Tarasova E A , Tokarev K E 
Published: October 2020

Abstract
The article offers an algorithm for evaluating the relationship between demographic and economic parameters of rural development, which assumes the classification and paired comparisons of regions based on the studied characteristics. The demographic matrix represents a multi level grouping of rural territories in Russia based on three subordinated characteristics: natural reproduction, internal migration, demographic burden. For a matrix grouping of regions by the level of economic well-being of rural territories, an integral index is proposed, structured according to indicators of employment, rural income and budgets of rural settlements. According to demographic characteristics, rural territories are divided into four typological groups – well-off, relatively well – off, not well-off, and depressive regions-whose superimposition on the matrix of economic development of territories showed the existence of an incomplete correlation of the studied parameters. The most significant relationship was found for the third and fourth quartiles of the matrices, which indicates a fairly significant relationship between the unfavorable demographic situation in the region and ego-economic problems. At the same time, the presence of distorting factors requires the addition of a cluster approach to formal assessments, in which it is possible to take into account the individual characteristics of each territory.
Accounting model for determining the amount of the estimated liability for agricultural leasing participants
Authors: Tokareva E V , Chernovanova N V , Yagupova E V , Zabaznova D O 
Published: October 2020

Abstract
The existing system of participants in leasing relationships in terms of debt formation is unacceptable, as it completely contradicts the strategy of development of agriculture in Russia. The assessment of additional costs should certainly be considered as a risk management tool. Thus, if a deliberately unprofitable agricultural leasing agreement is defined, risks will arise both for the lessee in terms of a lack of liquidity to pay lease payments and for the lessor in terms of the risks of losing the collateral and increasing the risks of nonpayment. Such obligations must be formed in the supplier’s accounting records, which affects not only the organization’s operational stability, but also its financial stability. The article suggests a fundamentally new approach to the formation of universally applicable information data on estimated obligations of participants in agricultural leasing agreements. Proposals for the practical application of organizational and methodological aspects of accounting based on the modernization of the settlement system the amounts of reserves, estimated reserves, and estimated liabilities are substantiated. Practical implementation of the research results by managers and accountants can greatly contribute to forecasting and minimizing risks for participants in leasing agreements.
Irrigation management model based on soil moisture distribution profile
Authors: Borodychev V V , Lytov M N 
Published: October 2020

Abstract
The article is devoted to the actual problem solving of precision irrigation in terms of an irrigation management model creating based on the soil moisture spatial variation. The research key element is that the model being created takes into account the soil moisture content variability not according the area of the irrigated plot, but in the vertical profile of the agricultural crops active root water consumption zone. This approach avoids the necessity for the irrigation equipment design complication for irrigation moisture differentiated distribution and therefore the technology application allows us to avoid unnecessary costs. The irrigation requirement assessing block according to the moisture content differentiating in the active soil layer profile is new in the proposed model architecture. The block algorithm assumes the two-stage irrigation requirement assessment, first, based on the total level of soil moisture variation in the active layer profile and second, on the layers sum of the active soil horizon with a moisture content below the threshold level. Together, these estimates allow us to make a decision about the irrigation necessity if soil moisture excessive variation in the profile layers and the moisture distribution nature in the soil profile have a significant impact on the irrigated crop productivity.
Electrical characterization of 2D materials-based field-effect transistors
Authors: Mitta Sekhar Babu , Choi Min Sup , Nipane Ankur , Ali Fida , Kim Changsik , Teherani James T , Hone James , Yoo Won Jong 
Published: October 2020

Abstract
Two-dimensional (2D) materials hold great promise for future nanoelectronics as conventional semiconductor technologies face serious limitations in performance and power dissipation for future technology nodes. The atomic thinness of 2D materials enables highly scaled field-effect transistors (FETs) with reduced short-channel effects while maintaining high carrier mobility, essential for high-performance, low-voltage device operations. The richness of their electronic band structure opens up the possibility of using these materials in novel electronic and optoelectronic devices. These applications are strongly dependent on the electrical properties of 2D materials-based FETs. Thus, accurate characterization of important properties such as conductivity, carrier density, mobility, contact resistance, interface trap density, etc is vital for progress in the field. However, electrical characterization methods for 2D devices, particularly FET-related measurement techniques, must be revisited since conventional characterization methods for bulk semiconductor materials often fail in the limit of ultrathin 2D materials. In this paper, we review the common electrical characterization techniques for 2D FETs and the related issues arising from adapting the techniques for use on 2D materials.
Complete solution of the tight binding model on a Cayley tree: strongly localised versus extended states
Authors: Aryal Deepak , Kettemann Stefan 
Published: October 2020

Abstract
The complete set of Eigenstates and Eigenvalues of the nearest neighbour tight binding model on a Cayley tree with branching number b = 2 and M branching generations with open boundary conditions is derived. We find that of the N = 1 + 3(2
M
− 1) total states only 3M + 1 states are extended throughout the Cayley tree. The remaining N − (3M + 1) states are found to be strongly localised states with finite amplitudes on only a subset of sites. In particular, there are, for M > 1, 3 × 2
M−2 surface states which are each antisymmetric combinations of only two sites on the surface of the Cayley tree and have energy eactly at E = 0, the middle of the band. The ground state and the first two excited states of the Cayley tree are found to be extended states with amplitudes on all sites of the Cayley tree, for all M. We use the results on the complete set of Eigenstates and Eigenvalues to derive the total density of states and a local density of states.
Enhanced photocatalytic hydrogen production by loading histidine on TiO2
Authors: Han Xiaojing , Ma Hongrui , Wang Chuanyi , Li Yingxuan 
Published: October 2020

Abstract
Although TiO2 exhibits excellent photocatalytic properties, its application has been limited owing to rapid e−/h+ recombination. Therefore, TiO2 has failed to reach the desired effect in terms of efficient photocatalytic hydrogen production. In this study, a range of titanium dioxide catalysts loaded with histidine (His) were prepared by an easy dipping method, viz. by treating TiO2 in His aqueous solutions with different concentrations at ambient temperature. Photocatalytic hydrogen evolution by splitting water was performed on His-modified TiO2 under 300-W Xe irradiation. His-loaded TiO2 catalysts exhibited improved photocatalytic performance compared with pristine TiO2; TiO2 treated in 1 × 10−3 mol · L−1 His showed the highest photocatalytic H2 evolution activity (4.77 μmol g−1 h−1 gm−2), which was 3.77 times higher than that of pure TiO2. Infrared and XPS analysis showed that His was successfully combined to the TiO2 surface by hydrogen bonding, constructing a fast channel for interfacial charge transfer. In the photocatalytic process, the photogenerated holes could migrate from the valence band of TiO2 to the highest occupied molecular orbital of His, which reduced the recombination rate of photogenerated e−/h+ pairs, consequently, improved H2 production efficiency. Importantly, the composite catalyst exhibited no decline in photocatalytic activity over 30 h of operation. This research provides an alternative approach for creating high-efficiency photocatalysts for H2 production.
Non-equilibrium phenomena in thermal plasmas
Authors: Cressault Y , Teulet Ph , Baumann X , Gleizes A 
Published: October 2020

Abstract
This tutorial is intended to provide a basic overview of non-equilibrium phenomena for thermal plasmas. Thermal plasmas (TPs) mainly issued from electrical discharges are often assumed to be in ≪ equilibrium ≫ as opposed to ≪ non-equilibrium plasmas ≫ where non-equilibrium phenomena are more pronounced. As a first approximation it can be shown that TPs are close to a local thermodynamic equilibrium (LTE) which is often taken as their reference state. However, in many situations, deviations from LTE can clearly exist. The main goal of this brief tutorial is to explain to interested scientists the main phenomena, mechanisms and characteristics associated to TPs or quasi-TPs. Then we introduce the different laws of the thermodynamic equilibrium applied to these plasmas and show that not all of them are valid in TPs, which lead us to define the LTE. However, even if the transport phenomena are non-equilibrium mechanisms, we show with illustrations that they are studied and estimated within the framework of the LTE. The next sections focus on phenomena named ‘departures from equilibrium’ for thermal plasmas. For convenience and educational reasons, we split them into the departures from the chemical and the thermal equilibria respectively. In each case we present and clearly define the mechanisms that promote equilibrium and those that tend to create departures. We present not only experimental setups that highlight these deviations but also the basis for the mathematical models that allow them to be simulated, before concluding the tutorial with the outlooks and challenges currently under research.
Deformable polyvinyl chloride gel for fabrication of varifocal microlens array
Authors: Yamada Yasumi , Emori Hideyuki , Hirai Toshihiro 
Published: October 2020

Abstract
Limitations in further miniaturization of lenses and arrays to achieve varifocal capabilities in compact 2D/3D switchable imaging devices have spurred investigations into the use of alternative materials. To this end, we fabricated a new deformable microlens array (MLA) utilizing polyvinyl chloride (PVC) gel, containing 67–90 wt.% of dibutyl adipate (DBA), sandwiched between an anode with apertures, 20–300 μm in diameter, and a cathode made of a transparent conductive film. The effects of applied voltage and DBA content on the protrusion of the PVC gel were studied and the protrusion mechanism was investigated. The gel was deformed from a flat shape in the absence of voltage to a lens shape at 100–600 V. When a voltage was applied, the negatively charged PVC chains accumulated near the anode and induced deformation of the PVC gel, which rose along the aperture walls and protruded from the apertures. Furthermore, the protrusion level of the PVC gel increased with DBA content, which lowered its elastic modulus and increased the negative charge density. Thus, the deformation of the PVC gel was mainly governed by the effects of electrostriction and PVC chain dynamics. Additionally, aperture diameter was found to influence the shape of the lens. The protrusion profile was concave at aperture diameters of 50 and 100 μm but became convex at 20 μm. At an applied voltage of 600 V, the focal length of the MLA was −0.20 mm at aperture diameters of 50 and 100 μm, representing a concave lens, but +0.05 mm at 20 μm, representing a convex lens. The MLA functioned more as a deformable lens, which transformed from a flat shape into a lens shape, than as a variable lens whose focal length changed continuously. The roles of plasticizer content, PVC chain dynamics, and aperture diameter in achieving greater control over lens curvature merit further investigation.
Quantum machine learning in high energy physics
Authors: Guan Wen , Perdue Gabriel , Pesah Arthur , Schuld Maria , Terashi Koji , Vallecorsa Sofia , Vlimant Jean-Roch 
Published: October 2020

Abstract
Machine learning has been used in high energy physics (HEP) for a long time, primarily at the analysis level with supervised classification. Quantum computing was postulated in the early 1980s as way to perform computations that would not be tractable with a classical computer. With the advent of noisy intermediate-scale quantum computing devices, more quantum algorithms are being developed with the aim at exploiting the capacity of the hardware for machine learning applications. An interesting question is whether there are ways to apply quantum machine learning to HEP. This paper reviews the first generation of ideas that use quantum machine learning on problems in HEP and provide an outlook on future applications.
Moving beyond promoting ‘Happiness’ in gerontology interventions
Authors: Hill Patrick L , Burrow Anthony L , Allemand Mathias 
Published: October 2020

Abstract
Researchers have called for gerontologists to spend greater attention on promoting happiness in older adulthood, a point aligned with the general public’s interest in finding the keys to being happy later in life. However, targeting and even defining happiness comes with several caveats and challenges, leaving researchers to make difficult decisions regarding measurement and intervention strategies. Instead, the current commentary suggests that gerontology interventions may fare better if researchers focus on specific components of positive psychological functioning. We present sense of purpose and life enjoyment as examples of two such components, and note the potential merit in developing these more focussed intervention programmes. As such, the commentary suggests the value of moving beyond targeting happiness when developing intervention programmes for older adult participants.
Evolution of pollination syndromes and corolla symmetry in Balsaminaceae reconstructed using phylogenetic comparative analyses
Authors: Ruchisansakun Saroj , Mertens Arne , Janssens Steven B , Smets Erik F , van der Niet Timotheüs 
Published: October 2020

AbstractBackground and AimsFloral diversity as a result of plant–pollinator interactions can evolve by two distinct processes: shifts between pollination systems or divergent use of the same pollinator. Although both are pollinator driven, the mode, relative importance and interdependence of these different processes are rarely studied simultaneously. Here we apply a phylogenetic approach using the Balsaminaceae (including the species-rich genus Impatiens) to simultaneously quantify shifts in pollination syndromes (as inferred from the shape and colour of the perianth), as well as divergent use of the same pollinator (inferred from corolla symmetry).MethodsFor 282 species we coded pollination syndromes based on associations between floral traits and known pollination systems, and assessed corolla symmetry. The evolution of these traits was reconstructed using parsimony- and model-based approaches, using phylogenetic trees derived from phylogenetic analyses of nuclear ribosomal and plastid DNA sequence data.Key ResultsA total of 71 % of studied species have a bee pollination syndrome, 22 % a bimodal syndrome (Lepidoptera and bees), 3 % a bird pollination syndrome and 5 % a syndrome of autogamy, while 19 % of species have an asymmetrical corolla. Although floral symmetry and pollination syndromes are both evolutionarily labile, the latter shifts more frequently. Shifts in floral symmetry occurred mainly in the direction towards asymmetry, but there was considerable uncertainty in the pattern of shift direction for pollination syndrome. Shifts towards asymmetrical flowers were associated with a bee pollination syndrome.ConclusionFloral evolution in Impatiens has occurred through both pollination syndrome shifts and divergent use of the same pollinator. Although the former appears more frequent, the latter is likely to be underestimated. Shifts in floral symmetry and pollination syndromes depend on each other but also partly on the region in which these shifts take place, suggesting that the occurrence of pollinator-driven evolution may be determined by the availability of pollinator species at large geographical scales.
GraphDTA: predicting drug–target binding affinity with graph neural networks
Authors: Nguyen Thin , Le Hang , Quinn Thomas P , Nguyen Tri , Le Thuc Duy , Venkatesh Svetha 
Published: October 2020

Abstract

Summary
The development of new drugs is costly, time consuming and often accompanied with safety issues. Drug repurposing can avoid the expensive and lengthy process of drug development by finding new uses for already approved drugs. In order to repurpose drugs effectively, it is useful to know which proteins are targeted by which drugs. Computational models that estimate the interaction strength of new drug–target pairs have the potential to expedite drug repurposing. Several models have been proposed for this task. However, these models represent the drugs as strings, which is not a natural way to represent molecules. We propose a new model called GraphDTA that represents drugs as graphs and uses graph neural networks to predict drug–target affinity. We show that graph neural networks not only predict drug–target affinity better than non-deep learning models, but also outperform competing deep learning methods. Our results confirm that deep learning models are appropriate for drug–target binding affinity prediction, and that representing drugs as graphs can lead to further improvements.

Availability of implementation
The proposed models are implemented in Python. Related data, pre-trained models and source code are publicly available at https://github.com/thinng/GraphDTA. All scripts and data needed to reproduce the post hoc statistical analysis are available from https://doi.org/10.5281/zenodo.3603523.

Supplementary information
Supplementary data are available at Bioinformatics online.
Conditional surrender in one generation: determining the reproductive roles of mouse embryo lethal genes by embryo complementation
Authors: Schimenti John C 
Published: October 2020

Abstract
The laboratory mouse is the most widely used animal model for studying the genetics and biology of mammalian development and reproduction. Embryonic stem cell (ESC) gene targeting technology, and the sophisticated genomic manipulations it allowed, was unique to this organism for a long period of time; this was a major factor in the mouse’s rise to pre-eminence as a model system over the past three decades or so. The recent advent of CRISPR/Cas9 technology has democratized the application of genome editing to essentially all organisms. Nevertheless, the scientific infrastructure behind the mouse still makes it the organism of choice for studying molecular mechanisms of mammalian development, and for modeling human development and disease.
When You Put It that Way: Framing Gender Equality Initiatives to Improve Engagement among STEM Academics
Authors: Farrell Lynn , Petzel Zachary W , McCormack Teresa , Turner Rhiannon N , Rafferty Karen , Latu Ioana M 
Published: October 2020

Abstract
A number of high-profile gender equality initiatives (GEIs) are intended to address women's underrepresentation in science. However, attitudes toward such initiatives can be negative. In two experiments with STEM academics, we examined how GEIs can be best framed to improve attitudes toward them. In study 1 (N = 113), we manipulated the framing of GEI leadership (led by a man or woman) and GEI focus (benefitting men and women or benefitting women only). The men were more supportive of GEIs benefitting both men and women because of fewer concerns of unfair treatment and more internal motivations to engage with GEIs. The women's level of support was unaffected by framing. In study 2 (N = 151), we framed GEIs as either supported by university management or not and either internally or externally driven. Support was greater for internally driven GEIs. The impact of management support depended on the academics’ experience with GEIs. This research makes evidence-based recommendations for the implementation of GEIs to improve their effectiveness.
The impact of human mobility networks on the global spread of COVID-19
Authors: Hâncean Marian-Gabriel , Slavinec Mitja , Perc Matjaž 
Published: October 2020

Abstract
Human mobility networks are crucial for a better understanding and controlling the spread of epidemics. Here, we study the impact of human mobility networks on the COVID-19 onset in 203 different countries. We use exponential random graph models to perform an analysis of the country-to-country global spread of COVID-19. We find that most countries had similar levels of virus spreading, with only a few acting as the main global transmitters. Our evidence suggests that migration and tourism inflows increase the probability of COVID-19 case importations while controlling for contiguity, continent co-location and sharing a language. Moreover, we find that air flights were the dominant mode of transportation while male and returning travellers were the main carriers. In conclusion, a mix of mobility and geography factors predicts the COVID-19 global transmission from one country to another. These findings have implications for non-pharmaceutical public health interventions and the management of transborder human circulation.
VarStack: a web tool for data retrieval to interpret somatic variants in cancer
Authors: Howard Morgan , Kane Bruce , Lepry Mary , Stey Paul , Ragavendran Ashok , Gamsiz Uzun Ece D 
Published: October 2020

AbstractAdvances in tumor genome sequencing created an urgent need for bioinformatics tools to support the interpretation of the clinical significance of the variants detected. VarStack is a web tool which is a base to retrieve somatic variant data relating to cancer from existing databases. VarStack incorporates data from several publicly available databases and presents them with an easy-to-navigate user interface. It currently supports data from the Catalogue of Somatic Mutations in Cancer, gnomAD, cBioPortal, ClinVar, OncoKB, CiViC and UCSC Genome Browser. It retrieves the data from these databases and returns them back to the user in a fraction of the time it would take to manually navigate each site independently. Users submit a variant with a gene symbol, peptide change and coding sequence change. They may select a variety of tumor-specific studies in cBioPortal to search through in addition to their original query. The results from the databases are presented in tabs. Users can export the results as an Excel file. VarStack also has the batch search feature in which the user can submit a list of variants and download an Excel file with the data from the databases. With the batch search and data download options, users can easily incorporate VarStack into their workflow or tools. VarStack saves time by providing somatic variant information to the user from multiple databases in an easy-to-export and interpretable format. VarStack is freely available under https://varstack.brown.edu.