bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimal attitude maneuvers in the presence of prohibited directions
Authors: Ailabouni David , Meister Andreas , Spindler Karlheinz 
Published: May 2023

AbstractWe consider the problem of realigning a space telescope from one observation target to the next in the presence of prohibited directions. More specifically, we want to steer the space telescope – modelled as a gyrostat – from an initial attitude at rest to a final attitude at rest within a fixed time interval. During the motion, the line of sight of the telescope must be kept away from forbidden directions towards bright objects like the sun, moon or earth due to power or thermal requirements. The kinematics of the spacecraft motion are governed by a differential equation on the rotation group SO(3). Treating the angular velocities as control variables, this equation takes the form of a controlled dynamical system. To ensure reorientation maneuvers satisfying these pointing constraints, we introduce a cost functional penalizing proximity of the line of sight of the telescope to any of the forbidden directions. Furthermore, we include penalty terms which provide a smooth motion of the satellite and ensure the execution of a rest‐to‐rest maneuver. The chosen cost functional is minimized over all possible trajectories of the controlled dynamical system between the prescribed initial and target attitudes, which leads to an optimal control problem on SO(3), which is solved by applying a version of Pontryagin's Maximum Principle tailor‐made for optimal control problems on Lie groups. Parametrizing SO(3) in terms of Cardan angles, the solution is formulated as a boundary‐value problem on Euclidean space and hence can be solved numerically by conventional methods. The existence of two first integrals is established and exploited to reduce the computational effort. The applicability of this approach is shown in concrete examples.
System Order Reduction for Gas and Energy Networks
Authors: Himpe Christian , Grundel Sara 
Published: May 2023

AbstractNo matter if natural gas, biogas or hydrogen, gas transport needs to be simulated ahead of dispatch to account for volatilities in demand and supply, so denominations are delivered reliably. The emancipation from producing countries alongside the renewable energy transition increases the number of scenarios to be simulated manifold, which in turn requires the acceleration of computational models to ensure completion of computer simulations before deadlines.Gas is transported through a network of pipelines which can be mathematically modeled as large‐scale nonlinear port‐Hamiltonian input‐output systems. To reduce computational complexity we propose unsupervised learning via synthetic data of the model's system‐theoretic properties which then enables data‐driven control or model reduction.We summarize the aspects of nonlinear model reduction techniques adapted to gas pipeline networks and orchestrated to reduce the order of this challenging class of systems originating from hyperbolic systems of partial differential‐algebraic equations, and demonstrate the applicability of our approach numerically.
Augmenting Basis Sets by Normalizing Flows
Authors: Saleh Yahya , Iske Armin , Yachmenev Andrey , Küpper Jochen 
Published: May 2023

AbstractApproximating functions by a linear span of truncated basis sets is a standard procedure for the numerical solution of differential and integral equations. Commonly used concepts of approximation methods are well‐posed and convergent, by provable approximation orders. On the down side, however, these methods often suffer from the curse of dimensionality, which limits their approximation behavior, especially in situations of highly oscillatory target functions. Nonlinear approximation methods, such as neural networks, were shown to be very efficient in approximating high‐dimensional functions. We investigate nonlinear approximation methods that are constructed by composing standard basis sets with normalizing flows. Such models yield richer approximation spaces while maintaining the density properties of the initial basis set, as we show. Simulations to approximate eigenfunctions of a perturbed quantum harmonic oscillator indicate convergence with respect to the size of the basis set.
Optimal photovoltaic plant dimensioning using consumption data
Authors: Hackenberg Annika , Kappertz Lars , Rapol Satish , Solovievskyi Viacheslav , Büskens Christof 
Published: May 2023

AbstractIn the transition away from fossil energy, the use of renewable energy is gaining more importance. Agricultural businesses have a high energy demand as well as space for the installation of renewable energies, such as photovoltaic systems (PV). However, with the growing difference between electricity prices and feed‐in tariffs, the profitability of photovoltaic systems increasingly depends on the share of self‐consumption. Farmers who want to invest in a PV system are facing the challenge which configuration they should buy. To determine the optimal size and orientation of a PV system, an optimization problem can be formulated which maximizes the profit after 20 years. The cost function is composed of the net present value (NPV), which takes into account the investment and maintenance costs, as well as sales profits and electricity purchase costs. To calculate these, the flow of electricity for one year in a hourly resolution is simulated. For this purpose, the individual consumption curve, which is obtained through measurements, and the power generation of the photovoltaic plant is considered. The power generation is based on physical equations and uses the geographical location of the farm. The size and orientation, such as azimuth and tilt of the system, are included as variable parameters in the optimization problem. Due to the annual curve, both the high‐yield summer months and the winter months are considered. Depending on this generation power curve and its overlap with the consumption power curve, differently oriented and sized photovoltaic systems are recommended. In this paper, the influence of the photovoltaic system orientation is analyzed using different artificially generated consumer curves, each with increased consumption at different times of the day.
A 3rd/2nd order MOOD limited scheme for the shallow water equations
Authors: Hörnschemeyer Sophie , Bacigaluppi Paola , Noelle Sebastian , Chen Guoxian 
Published: May 2023

AbstractWe present a high‐order accurate, positivity‐preserving and well‐balanced finite volume scheme for the shallow water equations with variable topography. An unlimited third‐order scheme is combined with the recent, second‐order accurate Bottom‐Surface‐Gradient Method (BSGM, [5]). This is monitored by an a‐posteriori MOOD (Multidimensional Optimal Order Detection) limiting step [2, 7–9], which detects possible local instabilities of a high‐order candidate solution such as loss of positivity or local oscillations, and switches locally to a lower order, stable and robust “parachute” scheme if necessary. We demonstrate the accuracy, effectiveness and robustness of the proposed adaptive methodology with numerical experiments, both for near‐equilibrium and non‐equilibrium depth‐averaged flows.
Data‐driven inverse design and optimisation of silica aerogel model networks
Authors: Pandit Prakul , Abdusalamov Rasul , Itskov Mikhail , Milow Barbara , Rege Ameya 
Published: May 2023

AbstractSilica aerogels are highly porous ultralight materials with extremely low density and thermal conductivity. These exceptional properties of silica aerogels are often accounted to microstructure morphology, thus making them of keen research interest for analysing their structure‐property relationships. The classical approach for this involved the microstructure modelling of the silica aerogels with aggregation‐based modelling algorithm viz., diffusion‐limited cluster‐cluster aggregation (DLCA) and then performing finite element method (FEM) on the generated representative volume element (RVEs). However, the process often requires large computation time and resources.The objective of this work was thus to introduce an artificial intelligence approach based on neural networks and reinforcement learning to eliminate the necessity of generating and simulating 3D silica aerogel models for predicting their structural and mechanical properties. To this end for the forward prediction of the elastic modulus and fractal dimension of the silica aerogels from DLCA parameters, an artificial neural network was developed. Furthermore, to reverse engineer the material and perform inverse material design, a reinforcement learning framework was developed, that is shown to have learned to determine appropriate DLCA model parameters as actions for a desired fractal dimension and elastic modulus.
Pipe Flow Development and Transition in CoSmaPipe Facility
Authors: Richter Stefan , Zanoun El-Sayed , Peixinho Jorge , Egbers Christoph 
Published: May 2023

AbstractThe current research focuses on understanding the transition of pipe flow by using a triggering device. In particular, a transition rod was installed within the CoSma‐Pipe at the Brandenburg University of Technology Cottbus‐Senftenberg. The effect of the transition rod, which has a variable height perpendicular to the axis at the pipe inlet, was examined in a range of 2,500 ≤ Re ≤ 31,000 where Re is the Reynolds number based on the mean velocity, the diameter, and the air's viscosity. This study used constant temperature hot‐wire anemometry to measure the flow. The observed effect of the transition rod was compared to previously published work in which a ring obstacle was used. The main objective of this research is to improve our understanding of the transition of pipe flow by using a triggering device such as the transition rod. By studying the effect of the transition rod on the flow, researchers can gain valuable insights into the dynamics of the transition from laminar to turbulent flow and its implications for various practical applications. This could ultimately lead to the development of more effective ways of controlling and mitigating turbulence in piping systems, engines, turbines, and other applications.
Dual inhibition of the endothelin and angiotensin receptor ameliorates renal and inner ear pathologies in Alport mice
Authors: Cosgrove Dominic , Gratton Michael Anne , Madison Jacob , Vosik Denise , Samuelson Gina , Meehan Daniel , Delimont Duane , Phillips Grady , Smyth Brendan , Pramparo Tiziano , Jarocki Diana , Nguyen Mai , Komers Radko , Jenkinson Celia 
Published: May 2023

AbstractAlport syndrome (AS), a type IV collagen disorder, leads to glomerular disease and, in some patients, hearing loss. AS is treated with inhibitors of the renin–angiotensin system; however, a need exists for novel therapies, especially those addressing both major pathologies. Sparsentan is a single‐molecule dual endothelin type‐A and angiotensin II type 1 receptor antagonist (DEARA) under clinical development for focal segmental glomerulosclerosis and IgA nephropathy. We report the ability of sparsentan to ameliorate both renal and inner ear pathologies in an autosomal‐recessive Alport mouse model. Sparsentan significantly delayed onset of glomerulosclerosis, interstitial fibrosis, proteinuria, and glomerular filtration rate decline. Sparsentan attenuated glomerular basement membrane defects, blunted mesangial filopodial invasion into the glomerular capillaries, increased lifespan more than losartan, and lessened changes in profibrotic/pro‐inflammatory gene pathways in both the glomerular and the renal cortical compartments. Notably, treatment with sparsentan, but not losartan, prevented accumulation of extracellular matrix in the strial capillary basement membranes in the inner ear and reduced susceptibility to hearing loss. Improvements in lifespan and in renal and strial pathology were observed even when sparsentan was initiated after development of renal pathologies. These findings suggest that sparsentan may address both renal and hearing pathologies in Alport syndrome patients. © 2023 Travere Therapeutics, Inc and The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Is hybridisation with non‐native congeneric species a threat to the UK native bluebell Hyacinthoides non‐scripta?
Authors: Ruhsam Markus , Kohn Deborah , Marquardt Jeannine , Leitch Andrew R. , Schneider Harald , Vogel Johannes , Barrett Spencer C. H. , Hulme Philip E. , Squirrell Jane , Hollingsworth Peter M. 
Published: May 2023

Societal Impact StatementHybridisation is an important evolutionary force in plants, but it can potentially lead to genetic swamping and extinction of one or both parental species. The threat of extinction is of particular concern if hybridisation occurs between native and introduced species, especially when the native is of national importance. The widespread occurrence of non‐native bluebells in the United Kingdom has raised concerns that the iconic native bluebell could be at risk due to extinction by hybridisation from introduced non‐native bluebells. This study determines the taxonomic identity of non‐natives and investigates the amount of hybridisation occurring in natural and semi‐natural UK bluebell populations.Summary

The widespread occurrence of a non‐native bluebell taxon in the UK has raised concerns that the iconic native bluebell H. non‐scripta (Asparagaceae) could be at risk due to extinction by hybridisation from introduced non‐native congeners. Understanding the nature of this threat requires quantification of the extent of hybridisation between the native and non‐native taxa. An additional complication is taxonomic uncertainty regarding the identity of the non‐native bluebells in the United Kingdom that are colloquially referred to as the ‘Spanish’ bluebell (H. hispanica).
We collected 501 bluebell samples from 56 populations in the United Kingdom (H. non‐scripta and non‐natives) and the Iberian Peninsula (H. hispanica). The samples were assayed for variation at 1871 nuclear and 17 plastid single nucleotide polymorphisms.
Our genetic analyses demonstrated that non‐native bluebells in the United Kingdom are not H. hispanica but the hybrid between H. hispanica and H. non‐scripta. Moreover, they supported the hypothesis that Portugal is the country of origin of the first H. hispanica introductions to the United Kingdom. The frequency of hybrids was about 16%. Backcrosses between the (hybrid) non‐native bluebell and the native H. non‐scripta were primarily found in public parks. Of the sampled individuals for H. non‐scripta from natural habitats, only 2% showed evidence of introgression.
Although hybridisation might be frequent in locations where non‐native bluebells have been introduced, we found no evidence of large‐scale introgression in natural H. non‐scripta populations. Therefore, our results do not support concerns of an ‘extinction by hybridisation’ scenario.
Innovation capability, global cooperation, and sustainable development along the Belt and Road Initiative
Authors: Wang Bo , Gong Siyu , Yang Yang 
Published: May 2023

AbstractAlthough the Belt and Road Initiative (BRI) has become the largest global platform for economic, social, and energy cooperation, there remains a question of how to effectively utilize its globalizing role to promote sustainable development among the countries along the route. Innovation capability is identified as the key to resolving sustainable development issue, because innovation capability has the potential to effectively reconcile the conflict between economic development and environmental conservation. Therefore, this study has opted to utilize a sample of 99 countries across the globe, comprising of 78 BRI countries and 21 non‐BRI countries. The DDD model has been employed to examine the impact of innovation capability on sustainable development in the BRI. The result shows that BRI can contribute to the achievement of green sustainable development. Innovation serves as an effective means to improve green sustainable development, which can be achieved through green technical progress and green technical efficiency. In addition, global cooperation has a significant moderating effect on this outcome, with the foreign direct investment and trade capability being the main moderators of economic global cooperation, while digital capability, infrastructure, and social exchange are the main moderators of social global cooperation. Finally, in the regional heterogeneity analysis, we find that the results of the role of the four continents are more consistent with the regression results of the total world sample, the difference being that the moderating role of global cooperation is not consistent across states.
Estimating the dynamic environmental footprints of the global finance and business sector towards sustainable development goals
Authors: Chen Xi , Shuai Chenyang , Zhao Bu 
Published: May 2023

AbstractThe global finance and business is a trillion‐dollar sector whose final demand drives a significant amount of economic production and services in other sectors through trade systems. As economic production and services have a significant impact on the environment, they play a fundamental role in supporting the global sustainable development goals (SDGs). Despite this, little attention has been paid to environmental impact driven by the final demand of global finance and business sector (i.e., environmental footprint). In this paper, we estimated the carbon dioxide (CO2), sulfur dioxide (SO2) and particular matter 10 (PM10) footprints of finance and business sector of 187 economies from 2000 to 2016 using a global multi‐regional input–output model. Our results show that global environmental footprints peaked 10 years ago, and the latest CO2, SO2 and PM10 footprints are approximately 1371, 8.2 and 6.1 million tons, respectively. We also found that 99% of environmental footprints originate from 20% economy‐sectors, and the critical economy‐sectors are identified. In addition, policy interventions on environmental intensity, production efficiency and trade network for mitigating the environmental footprints are proposed as well. Our findings provide a holistic and dynamic picture of the environmental footprints of the global finance and business sector.
Systematic analysis of the prognostic and immunological role of DHX33 in pan‐cancer
Authors: Ding Jingjing , Zhou Jun , Shen Xiaoyi , Zhang Min , Feng Xianzhen , Xu Zhongqing 
Published: May 2023

AbstractDEAH‐box helicase 33 (DHX33) is a potent oncogenic agent on patients with hepatocellular carcinoma and colon cancer. Nevertheless, the prognostic significance of DHX33 in human pan‐cancers remains unclear. Various bioinformatics tools have been used to clarify the oncogenic effects of DHX33 in pan‐cancers. The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) were used to evaluate DHX33 at the mRNA and protein levels, respectively. The pan‐cancer prognostic prediction value of DHX33 was evaluated using the Kaplan–Meier plotter. The association between DHX33 levels and clinicopathological features was then determined using the UALCAN database. In addition, gene set enrichment analysis and nomogram prediction models were constructed. The association between DHX33 levels and immune cell infiltration was then assessed using TISIDB. We determined that DHX33 is aberrantly overexpressed in pan‐cancers and related to lung adenocarcinoma (LUAD) clinical stage (p < .001). Moreover, DHX33 overexpression was indicative of poor overall survival, disease‐free survival, and progression‐free interval in patients with LUAD (p < .05). Furthermore, DHX33 levels were associated with age, N stage, T stage, and pathologic stage in patients with LUAD (p < .001). Additionally, multivariate Cox analysis revealed that DHX33 was an independent risk factor for OS in patients with LUAD. A nomogram model between DHX33 levels and characteristic clinical parameters was developed. Additionally, DHX33 levels correlated with immunomodulators and chemokines. Finally, gene set enrichment analysis revealed that the amyloid fiber formation pathway and the WICH complex positively regulates RNA expression pathway, which was the most enriched in LUAD. Our data revealed oncogenic effects of DHX33 in various cancers. We suggest that DHX33 may serve as a biomarker for poor prognosis in LUAD.
Faecal microbiome transplantation improves clinical signs of chronic idiopathic large bowel diarrhoea in working dogs
Authors: Alves João C. , Santos Ana , Jorge Patrícia , Pitães Ângelo 
Published: May 2023

AbstractBackgroundChronic diarrhoea is a common clinical sign in dogs with chronic enteropathy, and psyllium husk has been shown to improve clinical signs in affected dogs. The aim of this study was to investigate whether faecal microbiome transplant has a similar effect in alleviating clinical signs in dogs with chronic large bowel diarrhoea.MethodThirty large‐breed working dogs with chronic large bowel diarrhoea were divided into a psyllium group (PG) and a faecal microbiome transplant group (FMTG). To the PG, 16 g/day of psyllium husk was administered for 30 days. The FMTG received faecal microbiome transplantation (FMT) once via enema. A daily log of faecal characteristics was kept, and the dogs' canine inflammatory bowel disease index (CIBDAI) and body condition scores (BCS) were determined. A Wilcoxon–Mann–Whitney test was used to compare group results. In addition, the Kaplan–Meier test was used to evaluate the occurrence rate of 1 day or more of diarrhoea and 2 days or more of diarrhoea by day 30.ResultsThe sample had a mean age of 3.9 ± 2.1 years and a bodyweight of 25.3 ± 6.8 kg. The FMTG showed a more rapid onset of CIBDAI improvement but no difference in other measures. At 30 days, the FMTG showed a greater improvement in bodyweight and BCS, but no differences were observed in faecal scores, defaecation frequency and time of appearance of episodes of diarrhoea. Time played a significant positive role in the results observed across both groups (p < 0.05).LimitationsThis study did not compare the microbiomes of the dogs before and after treatment, so the role of specific types of bacteria cannot be determined.ConclusionPsyllium husk and FMT had similar effects in improving clinical signs of chronic large bowel diarrhoea.
Infinite-dimensional R-matrices for the relativistic scattering of massless modes on AdS2
Authors: García Juan Miguel Nieto , Ruiz Roberto , Torrielli Alessandro 
Published: May 2023

Abstract
We construct infinite-dimensional R-matrices that generalise the relativistic scattering of massless modes with the same chirality on AdS2 near the Berestein-Maldacena-Nastase vacuum. We show that the infrared limit of the R-matrices reproduces finite-dimensional scattering of massless modes on AdS2, from which the R-matrices borrow modified braiding unitary. We also prove that the R-matrices enjoy an infinite-dimensional symmetry superalgebra that embeds that of AdS2. Finally, we verify that the R-matrices are also invariant under crossing symmetry.
Full higher-dimensional analysis of moduli oscillation and radiation in expanding universe
Authors: Otsuka Hajime , Sakamura Yutaka 
Published: May 2023

Abstract
We investigate effects of the radiation and the moduli oscillation around the stabilized values on the evolution of a 6-dimensional spacetime compactified on S2. In order to see the transition from the 5-dimensional space to the 3-dimensional one, we develop a procedure to pursue the spacetime evolution with appropriate approximations, which is valid until the spacetime behaves like 4-dimensional. In the case that the moduli stabilization process cannot be described in the context of the 4-dimensional effective theory, it takes quite a long time for the moduli oscillation to dominate the total energy density, in contrast to the conventional result obtained by the 4-dimensional effective theory approach. We also found that even if the moduli are set at the stabilized values, they start to oscillate due to the pressure in the extra space S2 in some cases.