bluuebunny/crossref_metadata_2025_split huggingface dataset:
The environmental and resource productivity as the key element of green economy in EU
Authors: Niameshchuk H , Bozhanova V , Chala V , Hlushchenko A 
Published: November 2021

Abstract
The purpose of this study was to analyze the indicators of environmental and resource productivity of European countries to identify leaders and outsiders and study their trends over recent decades. The results of the analysis showed that the indicators are characterized by uneven development, due to the characteristics of countries and their green policies. The key indicators of the Europe 2020 policy have been used for the analysis, namely resource productivity, greenhouse gas emissions per capita, recycling rate of municipal waste, eco-innovation index, final energy consumption in households. Linear trends for the period 1995-2019 with indication of trend equations were constructed for each indicator. The slope of the functions has been analyzed in order to identify the dynamics of trends. According to the results of the analysis, all indicators except greenhouse gas emissions per capita were characterized by positive dynamics, ie increased. It has been determined that the problematic indicator for EU countries is final energy consumption in households, which requires further detailed research.
Consideration of ecologization and standardization in the management of agricultural business operations
Authors: Petrenko N , Vasylenko O , Kovalenko O , Svitovyi O , Sahaidak I , Gechbaia B 
Published: November 2021

Abstract
The article deals with the formation of financial statements of agricultural enterprises, taking into account the indicators of ecologization and standardization in their activities. It is noted that at present time there is a problem of developing innovative directions of managing the strategic development of enterprises based on the use of new forms of financial evaluation of economic activity and compliance with environmental standards. The approaches to a comprehensive assessment of the financial condition of enterprises have been defined, their characteristics and strengths and weaknesses have been outlined. During the financial estimation of the economic activity of the enterprise the set of coefficients must be taken into account, which are formed taking into consideration the indicators of the rating estimation for each parameter of ecologization and standardization. A comprehensive analysis of the financial condition of agricultural enterprises on the basis of Ukrainian and international financial reporting standards has been conducted. It is summarized that the innovative management system based on the use of environmental and unified reporting standards will ensure the improvement of strategic planning mechanisms of socio-economic policy development at the state, regional and local levels.
Spiral dynamics in the management of sustainable development of society
Authors: Ivanova S , Romin A , Gaynutdinova L , Kvitka S , Paliukh V , Arsawan I W E 
Published: November 2021

Abstract
The article discusses issues related to the implementation of the concept of sustainable development through the prism of the spiral dynamics approach. An example of sustainable models for the implementation of activities in the forestry area and considered inconsistencies in conceptual attitudes necessary to implement such an approach and in the vMems of today. The purpose of this study is consideration of the applied aspects management on the value-based change. As part of the study, an information and management scheme for the forestry industry has been developed, which allows you to see information in the process relationships. General recommendations for the management of values have been developed on a specific example of the forestry industry. Modern society requires specialists of a new formation, able to integrate spiral movements, ready to design new businesses and projects, taking into account the requirements of the 2nd level vMems.
Effect of nano TiC on microstructure and microhardness of composite additive manufacturing 316L stainless steel
Authors: Yang Weiguang , Wang Xi , Zhou Hai , Zhou Ti 
Published: November 2021

Abstract
The lower surface hardness limits the further application of 316 L stainless steel. In this study, selective laser melting (SLM)/laser metal deposition (LMD) composite additive manufacturing technology was used to prepare five kinds of 316L-nano-TiC cermet strengthening layers on the surface of 316L stainless steel, and to study the effect of nano-TiC particle content on the microstructure and the influence of microhardness. Use Laser microscope, scanning electron microscope (SEM), X-ray diffractometer (XRD) to analyze the structure, element distribution and phase composition of the strengthening layer. The hardness of the strengthened layer was analyzed using a Vickers micro-hardness tester. The study found that the composite SLM/LMD formed samples changed continuously from LMD forming to SLM forming, showing good metallurgical bonding. Diffusion of TiC particles was observed in the SLM strengthening layer, and TiC phase was detected in the strengthening layer. Compared with the 316L matrix, the microhardness of the strengthened layer is significantly improved. When 50 wt% TiC is added, the average hardness of the strengthened layer is 1.9 times that of the 316L matrix, and the highest is 408.9 HV. The results of this study show that the strengthening layer manufactured by composite additive materials can effectively improve the hardness of the 316L stainless steel matrix. As the content of nano-TiC in the preset powder increases, the microhardness of the strengthening layer first increases and then decreases, and the hardness of the 50wt% TiC strengthening layer is the highest. There are distributed nano-TiC particles in the structure of the strengthening layer, and the distribution of nano-TiC particles in the 50wt% TiC strengthening layer is more uniform than other samples. This research provides a new reference for the strengthening of 316L stainless steel through SLM/LMD composite additive manufacturing technology and the addition of nano-TiC particles.
Holographic photonic neuron
Authors: Daria Vincent R 
Published: November 2021

Abstract
The promise of artificial intelligence (AI) to process complex datasets has brought about innovative computing paradigms. While recent developments in quantum-photonic computing have reached significant feats, mimicking our brain’s ability to recognize images are poorly integrated in these ventures. Here, I incorporate orbital angular momentum (OAM) states in a classical Vander Lugt optical correlator to create the holographic photonic neuron (HoloPheuron). The HoloPheuron can memorize an array of matched filters in a single phase-hologram, which is derived by linking OAM states with elements in the array. Successful correlation is independent of intensity and yields photons with OAM states of lℏ, which can be used as a transmission protocol or qudits for quantum computing. The unique OAM identifier establishes the HoloPheuron as a fundamental AI device for pattern recognition that can be scaled and integrated with other computing platforms to build-up a robust neuromorphic quantum-photonic processor.
KCOSS: an ultra-fast k-mer counter for assembled genome analysis
Authors: Tang Deyou , Li Yucheng , Tan Daqiang , Fu Juan , Tang Yelei , Lin Jiabin , Zhao Rong , Du Hongli , Zhao Zhongming 
Published: November 2021

AbstractMotivationThe k-mer frequency in whole genome sequences provides researchers with an insightful perspective on genomic complexity, comparative genomics, metagenomics and phylogeny. The current k-mer counting tools are typically slow, and they require large memory and hard disk for assembled genome analysis.ResultsWe propose a novel and ultra-fast k-mer counting algorithm, KCOSS, to fulfill k-mer counting mainly for assembled genomes with segmented Bloom filter, lock-free queue, lock-free thread pool and cuckoo hash table. We optimize running time and memory consumption by recycling memory blocks, merging multiple consecutive first-occurrence k-mers into C-read, and writing a set of C-reads to disk asynchronously. KCOSS was comparatively tested with Jellyfish2, CHTKC and KMC3 on seven assembled genomes and three sequencing datasets in running time, memory consumption, and hard disk occupation. The experimental results show that KCOSS counts k-mer with less memory and disk while having a shorter running time on assembled genomes. KCOSS can be used to calculate the k-mer frequency not only for assembled genomes but also for sequencing data.Availabilityand implementationThe KCOSS software is implemented in C++. It is freely available on GitHub: https://github.com/kcoss-2021/KCOSS.Supplementary informationSupplementary data are available at Bioinformatics online.
The Drought Response of Eastern US Oaks in the Context of Their Declining Abundance
Authors: Novick Kimberly , Jo Insu , D'Orangeville Loïc , Benson Michael , Au Tsun Fung , Barnes Mallory , Denham Sander , Fei Songlin , Heilman Kelly , Hwang Taehee , Keyser Tara , Maxwell Justin , Miniat Chelcy , McLachlan Jason , Pederson Neil , Wang Lixin , Wood Jeffrey D , Phillips Richard P 
Published: November 2021

AbstractThe oak (Quercus) species of eastern North America are declining in abundance, threatening the many socioecological benefits they provide. We discuss the mechanisms responsible for their loss, many of which are rooted in the prevailing view that oaks are drought tolerant. We then synthesize previously published data to comprehensively review the drought response strategies of eastern US oaks, concluding that whether or not eastern oaks are drought tolerant depends firmly on the metric of success. Although the anisohydric strategy of oaks sometimes confers a gas exchange and growth advantage, it exposes oaks to damaging hydraulic failure, such that oaks are just as or more likely to perish during drought than neighboring species. Consequently, drought frequency is not a strong predictor of historic patterns of oak abundance, although long-term climate and fire frequency are strongly correlated with declines in oak dominance. The oaks’ ability to survive drought may become increasingly difficult in a drier future.
Advancing Equity in Faculty Hiring with Diversity Statements
Authors: Bombaci Sara P , Pejchar Liba 
Published: November 2021

Abstract
Hiring diverse candidates and creating an inclusive and equitable climate has emerged as a top priority for the scientific community. Diversity statements are a common but unexamined tool for recruiting a more diverse workforce. We surveyed more than 200 experts in diversity, equity, and inclusion (DEI) from US academic institutions to synthesize strengths and limitations of diversity statements and to develop guidelines for using such statements in faculty hiring. We found overwhelming agreement that diversity statements are a valuable tool for the advantages they offer the institution and applicant, but the experts indicated that diversity statements should be supported by other evidence. We further found that few institutions provide guidance on how to effectively use diversity statements in the hiring process. We address this need by providing an expert-derived evaluation framework for recognizing and rewarding DEI in the recruitment process that can be flexibly adapted to fit the unique requirements of diverse institutions and positions.
Two-Stage TMLE to reduce bias and improve efficiency in cluster randomized trials
Authors: Balzer Laura B , van der Laan Mark , Ayieko James , Kamya Moses , Chamie Gabriel , Schwab Joshua , Havlir Diane V , Petersen Maya L 
Published: November 2021

SummaryCluster randomized trials (CRTs) randomly assign an intervention to groups of individuals (e.g., clinics or communities) and measure outcomes on individuals in those groups. While offering many advantages, this experimental design introduces challenges that are only partially addressed by existing analytic approaches. First, outcomes are often missing for some individuals within clusters. Failing to appropriately adjust for differential outcome measurement can result in biased estimates and inference. Second, CRTs often randomize limited numbers of clusters, resulting in chance imbalances on baseline outcome predictors between arms. Failing to adaptively adjust for these imbalances and other predictive covariates can result in efficiency losses. To address these methodological gaps, we propose and evaluate a novel two-stage targeted minimum loss-based estimator to adjust for baseline covariates in a manner that optimizes precision, after controlling for baseline and postbaseline causes of missing outcomes. Finite sample simulations illustrate that our approach can nearly eliminate bias due to differential outcome measurement, while existing CRT estimators yield misleading results and inferences. Application to real data from the SEARCH community randomized trial demonstrates the gains in efficiency afforded through adaptive adjustment for baseline covariates, after controlling for missingness on individual-level outcomes.
Intrinsic network activity reflects the fluctuating experience of tonic pain
Authors: Deak Bettina , Eggert Thomas , Mayr Astrid , Stankewitz Anne , Filippopulos Filipp , Jahn Pauline , Witkovsky Viktor , Straube Andreas , Schulz Enrico 
Published: November 2021

Abstract
Although we know sensation is continuous, research on long-lasting and continuously changing stimuli is scarce and the dynamic nature of ongoing cortical processing is largely neglected. In a longitudinal study, 38 participants across four sessions were asked to continuously rate the intensity of an applied tonic heat pain for 20 min. Using group-independent component analysis and dual regression, we extracted the subjects’ time courses of intrinsic network activity. The relationship between the dynamic fluctuation of network activity with the varying time courses of three pain processing entities was computed: pain intensity, the direction of pain intensity changes, and temperature. We were able to dissociate the spatio-temporal patterns of objective (temperature) and subjective (pain intensity/changes of pain intensity) aspects of pain processing in the human brain. We found two somatosensory networks with distinct functions: one network that encodes the small fluctuations in temperature and consists mainly of bilateral primary somatosensory cortex (SI), and a second right-lateralized network that encodes the intensity of the subjective experience of pain consisting of SI, secondary somatosensory cortex, the posterior cingulate cortex, and the thalamus. We revealed the somatosensory dynamics that build up toward a current subjective percept of pain. The timing suggests a cascade of subsequent processing steps toward the current pain percept.
The challenges of English medium instruction for subject lecturers: a shared viewpoint
Authors: Deignan Tim , Morton Tom 
Published: November 2021

Abstract
English medium instruction (EMI) is seen as a site for improving students’ English language, yet the role of the EMI lecturer in achieving this is contested. Views on what constitutes appropriate training and professional development for EMI lecturers also differ regarding English language skills and EMI-specific methodology. Using Q methodology, this paper explores these issues from a particular perspective, a synthetic viewpoint based on six EMI lecturers with very similar views. Its voice is pro-EMI yet has significant concerns regarding the workload involved, is insecure about its own linguistic performance, fears a loss of subject content depth, and questions the effectiveness of EMI for students learning a subject. The paper highlights the importance of such feelings in relation to perceived language and pedagogy challenges and considers the broader implications for EMI teacher training interventions regarding the practices of disciplinary knowledge-building and the linguistic and communicative resources used to enact them.
The distribution of the rent–price relationship of agricultural land in Germany
Authors: Schaak Henning , Musshoff Oliver 
Published: November 2021

AbstractThis paper studies the profitability of investments in agricultural land, using the rent–price ratio (RPR) as a profitability measure. In order to allow for district-level heterogeneity, the full conditional distribution of the RPR is modelled using a generalised additive model for location, shape and scale. The analysis is based on data from Lower Saxony, Germany. The profitability of investments in land varies between and within districts. The variation can be explained by differences in the farming structure, the production programme and economic indicators. Further, differences in the distribution of the RPR between arable land and grassland are found.
Non-universality of the mass function: dependence on the growth rate and power spectrum shape
Authors: Ondaro-Mallea Lurdes , Angulo Raul E , Zennaro Matteo , Contreras Sergio , Aricò Giovanni 
Published: November 2021

ABSTRACT
The abundance of dark matter haloes is one of the key probes of the growth of structure and expansion history of the Universe. Theoretical predictions for this quantity usually assume that, when expressed in a certain form, it depends only on the mass variance of the linear density field. However, cosmological simulations have revealed that this assumption breaks, leading to 10–20 per cent systematic effects. In this paper, we employ a specially designed suite of simulations to further investigate this problem. Specifically, we carry out cosmological N-body simulations where we systematically vary growth history at a fixed linear density field, or vary the power spectrum shape at a fixed growth history. We show that the halo mass function generically depends on these quantities, thus showing a clear signal of non-universality. Most of this effect can be traced back to the way in which the same linear fluctuation grows differently into the non-linear regime depending on details of its assembly history. With these results, we propose a parameterization with explicit dependence on the linear growth rate and power spectrum shape. Using an independent suite of simulations, we show that this fitting function accurately captures the mass function of haloes over cosmologies spanning a vast parameter space, including massive neutrinos and dynamical dark energy. Finally, we employ this tool to improve the accuracy of so-called cosmology-rescaling methods and show they can deliver 2 per cent accurate predictions for the halo mass function over the whole range of currently viable cosmologies.
Deep learning Bayesian inference for low-luminosity active galactic nuclei spectra
Authors: Almeida Ivan , Duarte Roberta , Nemmen Rodrigo 
Published: November 2021

ABSTRACT
Most active supermassive black holes in present-day galaxies are underfed and consist of low-luminosity active galactic nuclei (LLAGN). LLAGNs display complex multiwavelength broadband spectral energy distributions (SED), dominated by non-thermal processes which are explained to first order by a radiatively inefficient accretion flow (RIAF) and a relativistic jet. Due to the computational cost of generating such SEDs, it has not been hitherto possible to perform statistical fits to observed broadband SEDs, since such procedures require generating many thousands of models on-the-fly. Here, we have used a deep learning (DL) method to interpolate a large grid consisting of dozens of thousands of model SEDs for RIAFs and jets covering the parameter space appropriate for LLAGNs. Not only the DL method computes accurate models, it does so hundreds of thousands of times faster than solving the underlying dynamical and radiative transfer equations. This brings RIAF and jet models to the realm of Bayesian inference. We demonstrate that the combination of a DL interpolator and a Markov chain Monte Carlo ensemble sampler can recover the ground truth parameters of Mock LLAGN data. We apply our model to existing radio-to-X-rays observations of three LLAGNs: M87, NGC 315, and NGC 4261. We demonstrate that our model can estimate the relevant parameters of these accreting black holes such as the mass accretion and outflow rate at a small fraction of the computational cost of previous approaches.
ExoMol molecular line lists – XLIII. Rovibronic transitions corresponding to the close-lying X 2Π and A 2Σ+ states of NaO
Authors: Mitev G B , Taylor S , Tennyson Jonathan , Yurchenko S N , Buchachenko A A , Stolyarov A V 
Published: November 2021

ABSTRACT
The sodium monoxide radical (NaO) is observed in night-glow in the Earth’s mesosphere and likely has astronomical importance. This study concerns the optical transitions within the ground X 2Π state and to the very low-lying (Te ≈ 2000 cm−1) excited A 2Σ+ state. A line list consisting of rovibronic term values, allowed electric dipole transitions, Einstein coefficients, and partition functions for varying temperature are produced using a variational solution of the coupled-channel Schrödinger equations using the program duo. multi-reference configuration interaction (MRCI) ab initio calculations characterizing the potential energy curves of the two states, spin-orbit and L-uncoupling non-adiabatic matrix elements, as well as permanent and transition dipole moments were integral in the formation of the final deperturbation model. Ab initio potential energy curves are represented in the analytical Extended Morse Oscillator form and refined, along with the spin-orbit and L-uncoupling functions, by least-squares fitting to the available spectroscopic data. The input experimental data consisted of pure rotational transitions within the fine-structure components of the X 2Π state for v″ ∈ [0, 3] vibrational levels as well as the rovibronic A 2Σ+(v′ = 0) ← X 2Π(v″ = 0) transitions, both with limited coverage over rotational excitation. The lack of data detailing the vibrational structure of the X and A states points to the need for further experimental study of higher excited levels, which would provide a more robust spectroscopic model. The NaO NaOUCMe line list is available via www.exomol.com and the CDS data base.
The thousand-pulsar-array programme on MeerKAT VII: polarisation properties of pulsars in the Magellanic Clouds
Authors: Johnston S , Parthasarathy A , Main R A , Ridley J P , Koribalski B S , Bailes M , Buchner S J , Geyer M , Karastergiou A , Keith M J , Kramer M , Serylak M , Shannon R M , Spiewak R , Krishnan V Venkatraman 
Published: November 2021

ABSTRACT
The Magellanic Clouds are the only external galaxies known to host radio pulsars. The dispersion and rotation measures of pulsars in the Clouds can aid in understanding their structure, and studies of the pulsars themselves can point to potential differences between them and their Galactic counterparts. We use the high sensitivity of the MeerKAT telescope to observe 17 pulsars in the Small and Large Magellanic Clouds in addition to five foreground (Galactic) pulsars. We provide polarisation profiles for 18 of these pulsars, improved measurements of their dispersion and rotation measures, and derive the mean parallel magnetic field along the lines of sight. The results are broadly in agreement with expectations for the structure and strength of the magnetic field in the Large and Small Magellanic Clouds. The Magellanic Cloud pulsars have profiles which are narrower than expected from the period-width relationship and we show this is due to selection effects in pulsar surveys rather than any intrinsic difference between the population of Galactic and Magellanic objects.