bluuebunny/crossref_metadata_2025_split huggingface dataset:
Permanence of equilibrium points in the basin of attraction and existence of periodic solutions for autonomous measure differential equations and dynamic equations on time scales via generalized ODEs
Authors: Federson M , Grau R , Mesquita J G , Toon E 
Published: June 2022

Abstract
It is well-known that generalized ODEs encompass several types of differential equations as, for instance, functional differential equations, measure differential equations, dynamic equations on time scales, impulsive differential equations and any combinations among them, not to mention integrals equations, among others. The aim of this paper is to establish a theory of autonomous equations in the setting of generalized ODEs. Thus, we introduce the notion of autonomous generalized ODEs as well as new classes of right-hand sides for nonautonomous generalized ODEs. Amongst the main results, we prove that one of these new classes coincide with the original class of right-hand sides introduced by Kurzweil in 1957. We also prove that autonomous generalized ODEs do not enlarge the class of autonomous ODEs with uniformly continuous right-hand sides. Motivated by this fact, we then enlarge the class of autonomous generalized ODEs so that discontinuities can be taken into account. We then introduce a more general class of autonomous generalized ODEs, in whose integral form, a Stieltjes-type integral appears. A correspondence between these equations and autonomous measure differential equations is established and several results are obtained. We mention local existence and uniqueness of solutions, continuous dependence of solutions on initial values, existence of periodic solutions and permanence of asymptotically stable equilibrium point in the basin of attraction. All these results are, then, specified not only for autonomous generalized ODEs, but also for autonomous measure differential equations and dynamic equations on time scales.
On spectral structure and spectral eigenvalue problems for a class of self similar spectral measure with product form
Authors: Li Jinjun , Wu Zhiyi 
Published: June 2022

Abstract
Let μ be a Borel probability measure with compact support on

R

d

. We say that μ is a spectral measure if there exists

Λ
⊆

R

d

, called a spectrum of μ, such that

E

(

Λ

)

≔

{

e

−
2
π
i

⟨

λ
,
x

⟩

}

λ
∈
Λ

forms an orthonormal basis for L
2(μ). In this paper, we study the structure of spectra for a class of self-similar spectral measure μ

R,B
with product form on

R

. We first give a partially characterize for E
Λ to be a maximal orthogonal family in L
2(μ

R,B
) by using the notion of maximal tree mapping. Based on this, we give a sufficient condition for a maximal orthogonal family E
Λ (which corresponds to a maximal tree mapping) to be an orthonormal basis of L
2(μ

R,B
). Moreover, we completely settle two types of spectral eigenvalue problems for μ

R,B
. Precisely, on the first case, for the model spectrum (simplest spectrum) of μ

R,B
, we characterize all possible real numbers t such that tΛ is also a spectrum of μ

R,B
. On the other case, we characterize all possible real numbers t such that there exists a countable set Λ such that Λ and tΛ are both spectra of μ

R,B
.
Elliptic flowers: simply connected billiard tables where chaotic (non-chaotic) flows move around chaotic (non-chaotic) cores
Authors: Bunimovich Leonid A 
Published: June 2022

Abstract
We introduce a class of billiards with chaotic unidirectional flows (or non-chaotic unidirectional flows with ‘vortices’) which go around a chaotic or non-chaotic ‘core’, where orbits can change their orientation. Moreover, the corresponding billiard tables are simply connected in difference with many attempts to build billiards with interesting and/or exotic dynamics by putting inside billiard tables various ‘scatterers’ with funny shapes. Therefore the billiards in this new class are amenable to experimental studies in physics labs as well as to the rigorous mathematical ones, which may shed a new light on understanding of classical and quantum dynamics of Hamiltonian systems.
Brain–computer interface-based action observation combined with peripheral electrical stimulation enhances corticospinal excitability in healthy subjects and stroke patients
Authors: Kim Min Gyu , Lim Hyunmi , Lee Hye Sun , Han In Jun , Ku Jeonghun , Kang Youn Joo 
Published: June 2022

Abstract

Objective. Action observation (AO) combined with brain–computer interface (BCI) technology enhances cortical activation. Peripheral electrical stimulation (PES) increases corticospinal excitability, thereby activating brain plasticity. To maximize motor recovery, we assessed the effects of BCI-AO combined with PES on corticospinal plasticity. Approach. Seventeen patients with chronic hemiplegic stroke and 17 healthy subjects were recruited. The participants watched a video of repetitive grasping actions with four different tasks for 15 min: (A) AO alone; (B) AO + PES; (C) BCI-AO + continuous PES; and (D) BCI-AO + triggered PES. PES was applied at the ulnar nerve of the wrist. The tasks were performed in a random order at least three days apart. We assessed the latency and amplitude of motor evoked potentials (MEPs). We examined changes in MEP parameters pre-and post-exercise across the four tasks in the first dorsal interosseous muscle of the dominant hand (healthy subjects) and affected hand (stroke patients). Main results. The decrease in MEP latency and increase in MEP amplitude after the four tasks were significant in both groups. The increase in MEP amplitude was sustained for 20 min after tasks B, C, and D in both groups. The increase in MEP amplitude was significant between tasks A vs. B, B vs. C, and C vs. D. The estimated mean difference in MEP amplitude post-exercise was the highest for A and D in both groups. Significance. The results indicate that BCI-AO combined with PES is superior to AO alone or AO + PES for facilitating corticospinal plasticity in both healthy subjects and patients with stroke. Furthermore, this study supports the idea that synchronized activation of cortical and peripheral networks can enhance neuroplasticity after stroke. We suggest that the BCI-AO paradigm and PES could provide a novel neurorehabilitation strategy for patients with stroke.
Coalescence of two branch points in complex time marks the end of rapid adiabatic passage and the start of Rabi oscillations
Authors: Kaprálová-Žďánská Petra Ruth , Šindelka Milan , Moiseyev Nimrod 
Published: June 2022

Abstract
We study theoretically the population transfer in two-level atoms driven by chirped lasers. It is known that in the Hermitian case, the rapid adiabatic passage (RAP) is stable for an above-critical chirp below which the final populations of states Rabi oscillate with varying laser power. We show that if the excited state is represented by a resonance, the separatrix marking this critical phenomenon in the space of the laser pulse parameters emanates from an exceptional point (EP)—a non-Hermitian singularity formed in the atomic system by the fast laser field oscillations and encircled due to slow variations of the laser pulse envelope and instantaneous frequency. This critical phenomenon is neatly understood via extending the ‘slow’ time variable into the complex plane, uncovering a set of branch points which encode non-adiabatic dynamics, where the switch between RAP and Rabi oscillations is triggered by a coalescence of two such branch points. We assert that the intriguing interrelation between the two different singularities—the EP and the branch point coalescence in complex time plane—can motivate feasible experiments involving laser driven atoms.
Effect of chemical-heat treatment on the properties of titanium
Authors: Bricín D , Kratochvílová L , Leták R , Vojta L , Nová K , Špirit Z 
Published: June 2022

Abstract
The aim of this study is to evaluate the properties and microstructure of pure titanium after its chemical heat treatment (CHT) by boriding and nitriding. Nitriding and boriding were both done in powder backfill for ten hours. The temperature of the nitriding was 550 °C. The temperature of the boriding was 1000 °C. Both processes led to the creation of a thin surface layer of nitrides and borides which affected wear resistance and also they affected corrosion resistance of the surface of the analyzed samples.
Differential-phase-shift quantum digital signature without disclosing measurement information
Authors: Inoue Kyo , Honjo Toshimori 
Published: June 2022

Abstract
A novel quantum digital signature (QDS) scheme using differential-phase-shift signal is presented. A sender broadcasts a weak coherent pulse train with 0 or π phase to receivers, who measure its relative phases using delay interferometers with photon detectors and then employ the measurement results as authentication keys. The key distribution stage is completed with this signal transmission. Neither exchange of basis information between the sender and receivers nor exchange of a portion of a sifted key between the receivers with each other are conducted, unlike conventional QDS protocols. Therefore, our system is simpler than conventional ones. The security of the proposed scheme is discussed, and calculations evaluating system parameters to guarantee the QDS operation, such as the key length and authentication threshold, are presented.
Optimized two-step second derivative methods for the solutions of stiff systems
Authors: Sunday Joshua 
Published: June 2022

Abstract
In this research article, a pair of optimized two-step second derivative methods is derived and implemented on stiff systems. The influence of equidistant and non-equidistant hybrid points spacing on the performance of the methods derived is investigated. Firstly, the methods are derived using interpolation and collocation of a finite power series at some selected grid points. This leads to the formation of a system of nonlinear equations, which are then solved for the unknown parameters to obtain a continuous second derivative scheme. The by-products of the evaluation of the continuous second derivative scheme lead to the development of discrete methods in the form of blocks. Secondly, the basic properties of the methods derived were analysed. Numerical results were generated to investigate the influence of equidistant and non-equidistant hybrid points spacing on the performance of the methods on stiff systems. The results so obtained clearly showed that the two-step second derivative method with equidistant hybrid point spacing performed better than the two-step second derivative method with non-equidistant hybrid point spacing. This implies that equidistant hybrid point spacing enhances the accuracy of a method as opposed to non-equidistant hybrid point spacing.
Reduction in reversal of global stilling arising from correction to encoding of calm periods
*
Authors: Dunn Robert J H , Azorin-Molina Cesar , Menne Matthew J , Zeng Zhenzhong , Casey Nancy W , Shen Cheng 
Published: June 2022

Abstract
We describe an undocumented change in how calm periods in near-surface wind speed (and direction) observations have been encoded in a subset of global datasets of sub-daily data after 2013. This has resulted in the under-estimation of the number of calm periods for meteorological stations across much of Asia and Europe. Hence average wind speeds after 2013 have been over-estimated, affecting the assessment of changes in global stilling and reversal phenomena after this date. By addressing this encoding change we show that globally, since 2010, wind speeds have recovered by around 30% less than previously thought.
Minimizing environmental impacts of solar farms: a review of current science on landscape hydrology and guidance on stormwater management
Authors: Yavari Rouhangiz , Zaliwciw Demetrius , Cibin Raj , McPhillips Lauren 
Published: June 2022

Abstract
As solar energy becomes an increasingly cheap source of renewable energy, major utility-scale ground solar panel installations, often called ‘solar farms’, are rapidly growing. With these solar farms often covering hundreds of acres, there is the potential for impacts on natural hydrologic processes, including runoff generation and erosion. Here we review the current state of scientific research on the hydrology and water quality impacts of solar farms, as well as management recommendations for minimizing any impacts. The limited field measurements indicate the redistribution of soil moisture around solar farms, but the net impacts on runoff and erosion are less clear. Research focused on coupling solar farms with agriculture as ‘agrivoltaics’ demonstrates reduced evaporative water losses and associated crop stress, particularly in more arid regions. With regards to land and the stormwater management associated with solar farms, most US states currently do not have solar farm-specific recommendations and instead defer to standard stormwater management permits and guidance. In states with solar farm-specific guidance, typical recommendations include minimizing construction-related compaction, ensuring a high cover of perennial vegetation with minimal maintenance, and designing with pervious space between solar panel rows to promote infiltration of any runoff; in some cases, structural stormwater management like infiltration basins may be required. In general, solar farms can be designed to minimize the impact on landscape ecohydrological processes, but more research is needed to determine whether current recommendations are adequate. In particular, there is a need for more field research on less ideal sites such as those with higher slopes.
An effective clean energy transition must anticipate growing climate disruptions
Authors: Lesk Corey , Kornhuber Kai 
Published: June 2022

Abstract
As the clean energy transition gathers momentum, it will face myriad technical, economic, and political challenges. However, one in particular is often underappreciated: the potential disruption to the transition from surging climate extremes. We identify three ways in which extreme events may impede the transition: direct physical impacts to transitional infrastructure, strained resources due to rising recovery costs, and political backlash from disaster-affected populations. If these pitfalls materialize, the transition could stall, leading to continued emissions, additional worsening of climate extremes, and further disruption of the transition. We propose three avenues to avoid this potential positive feedback: integration of adaptation and mitigation as mutually supportive goals, fostering political and cultural commitment to a sustained transition, and an interdisciplinary research and training agenda to improve modeling and preparedness for the cascading impacts of climate extremes
HyperGraphs.jl: representing higher-order relationships in Julia
Authors: Diaz Léo P M , Stumpf Michael P H 
Published: June 2022

AbstractSummaryHyperGraphs.jl is a Julia package that implements hypergraphs. These are a generalization of graphs that allow us to represent n-ary relationships and not just binary, pairwise relationships. High-order interactions are commonplace in biological systems and are of critical importance to their dynamics; hypergraphs thus offer a natural way to accurately describe and model these systems.Availability and implementationHyperGraphs.jl is freely available under the MIT license. Source code and documentation can be found at https://github.com/lpmdiaz/HyperGraphs.jl.Supplementary informationSupplementary data are available at Bioinformatics online.
Prediction of allosteric communication pathways in proteins
Authors: Haliloglu Turkan , Hacisuleyman Aysima , Erman Burak 
Published: June 2022

AbstractMotivationAllostery in proteins is an essential phenomenon in biological processes. In this article, we present a computational model to predict paths of maximum information transfer between active and allosteric sites. In this information theoretic study, we use mutual information as the measure of information transfer, where transition probability of information from one residue to its contacting neighbors is proportional to the magnitude of mutual information between the two residues. Starting from a given residue and using a Hidden Markov Model, we successively determine the neighboring residues that eventually lead to a path of optimum information transfer. The Gaussian approximation of mutual information between residue pairs is adopted. The limits of validity of this approximation are discussed in terms of a nonlinear theory of mutual information and its reduction to the Gaussian form.ResultsPredictions of the model are tested on six widely studied cases, CheY Bacterial Chemotaxis, B-cell Lymphoma extra-large (Bcl-xL), Human proline isomerase cyclophilin A (CypA), Dihydrofolate reductase (DHFR), HRas GTPase and Caspase-1. The communication transmission rendering the propagation of local fluctuations from the active sites throughout the structure in multiple paths correlate well with the known experimental data. Distinct paths originating from the active site may likely represent a multi functionality such as involving more than one allosteric site and/or pre-existence of some other functional states. Our model is computationally fast and simple and can give allosteric communication pathways, which are crucial for the understanding and control of protein functionality.Supplementary informationSupplementary data are available at Bioinformatics online.
Deep learning for survival analysis in breast cancer with whole slide image data
Authors: Liu Huidong , Kurc Tahsin 
Published: June 2022

AbstractMotivationWhole slide tissue images contain detailed data on the sub-cellular structure of cancer. Quantitative analyses of this data can lead to novel biomarkers for better cancer diagnosis and prognosis and can improve our understanding of cancer mechanisms. Such analyses are challenging to execute because of the sizes and complexity of whole slide image data and relatively limited volume of training data for machine learning methods.ResultsWe propose and experimentally evaluate a multi-resolution deep learning method for breast cancer survival analysis. The proposed method integrates image data at multiple resolutions and tumor, lymphocyte and nuclear segmentation results from deep learning models. Our results show that this approach can significantly improve the deep learning model performance compared to using only the original image data. The proposed approach achieves a c-index value of 0.706 compared to a c-index value of 0.551 from an approach that uses only color image data at the highest image resolution. Furthermore, when clinical features (sex, age and cancer stage) are combined with image data, the proposed approach achieves a c-index of 0.773.Availability and implementationhttps://github.com/SBU-BMI/deep_survival_analysis
WAT3R: recovery of T-cell receptor variable regions from 3′ single-cell RNA-sequencing
Authors: Ainciburu Marina , Morgan Duncan M , DePasquale Erica A K , Love J Christopher , Prósper Felipe , van Galen Peter 
Published: June 2022

AbstractSummaryDiversity of the T-cell receptor (TCR) repertoire is central to adaptive immunity. The TCR is composed of α and β chains, encoded by the TRA and TRB genes, of which the variable regions determine antigen specificity. To generate novel biological insights into the complex functioning of immune cells, combined capture of variable regions and single-cell transcriptomes provides a compelling approach. Recent developments enable the enrichment of TRA and TRB variable regions from widely used technologies for 3′-based single-cell RNA-sequencing (scRNA-seq). However, a comprehensive computational pipeline to process TCR-enriched data from 3′ scRNA-seq is not available. Here, we present an analysis pipeline to process TCR variable regions enriched from 3′ scRNA-seq cDNA. The tool reports TRA and TRB nucleotide and amino acid sequences linked to cell barcodes, enabling the reconstruction of T-cell clonotypes with associated transcriptomes. We demonstrate the software using peripheral blood mononuclear cells from a healthy donor and detect TCR sequences in a high proportion of single T cells. Detection of TCR sequences is low in non-T-cell populations, demonstrating specificity. Finally, we show that TCR clones are larger in CD8 Memory T cells than in other T-cell types, indicating an association between T-cell clonotypes and differentiation states.Availability and implementationThe Workflow for Association of T-cell receptors from 3′ single-cell RNA-seq (WAT3R), including test data, is available on GitHub (https://github.com/mainciburu/WAT3R), Docker Hub (https://hub.docker.com/r/mainciburu/wat3r) and a workflow on the Terra platform (https://app.terra.bio). The test dataset is available on GEO (accession number GSE195956).Supplementary informationSupplementary data are available at Bioinformatics online.
Effectiveness of the Ad26.COV2.S (Johnson & Johnson) Coronavirus Disease 2019 (COVID-19) Vaccine for Preventing COVID-19 Hospitalizations and Progression to High Disease Severity in the United States
Authors: Lewis Nathaniel M , Self Wesley H , Gaglani Manjusha , Ginde Adit A , Douin David J , Keipp Talbot H , Casey Jonathan D , Mohr Nicholas M , Zepeski Anne , Ghamande Shekhar A , McNeal Tresa A , Shapiro Nathan I , Gibbs Kevin W , Files D Clark , Hager David N , Shehu Arber , Prekker Matthew E , Erickson Heidi L , Gong Michelle N , Mohamed Amira , Johnson Nicholas J , Srinivasan Vasisht , Steingrub Jay S , Peltan Ithan D , Brown Samuel M , Martin Emily T , Monto Arnold S , Khan Akram , Busse Laurence W , Lohuis Caitlin C ten , Duggal Abhijit , Wilson Jennifer G , Gordon Alexandra June , Qadir Nida , Chang Steven Y , Mallow Christopher , Rivas Carolina , Babcock Hilary M , Kwon Jennie H , Exline Matthew C , Lauring Adam S , Halasa Natasha , Chappell James D , Grijalva Carlos G , Rice Todd W , Rhoads Jillian P , Jones Ian D , Stubblefield William B , Baughman Adrienne , Womack Kelsey N , Lindsell Christopher J , Hart Kimberly W , Zhu Yuwei , Adams Katherine , Patel Manish M , Tenforde Mark W ,   IVY Network Collaborators
Published: June 2022

Abstract
Background . Adults in the United States (US) began receiving the adenovirus vector coronavirus disease 2019 (COVID-19) vaccine, Ad26.COV2.S (Johnson & Johnson [Janssen]), in February 2021. We evaluated Ad26.COV2.S vaccine effectiveness (VE) against COVID-19 hospitalization and high disease severity during the first 10 months of its use.
Methods . In a multicenter case-control analysis of US adults (≥18 years) hospitalized 11 March to 15 December 2021, we estimated VE against susceptibility to COVID-19 hospitalization (VEs), comparing odds of prior vaccination with a single dose Ad26.COV2.S vaccine between hospitalized cases with COVID-19 and controls without COVID-19. Among hospitalized patients with COVID-19, we estimated VE against disease progression (VEp) to death or invasive mechanical ventilation (IMV), comparing odds of prior vaccination between patients with and without progression.
Results . After excluding patients receiving mRNA vaccines, among 3979 COVID-19 case-patients (5% vaccinated with Ad26.COV2.S) and 2229 controls (13% vaccinated with Ad26.COV2.S), VEs of Ad26.COV2.S against COVID-19 hospitalization was 70% (95% confidence interval [CI]: 63–75%) overall, including 55% (29–72%) among immunocompromised patients, and 72% (64–77%) among immunocompetent patients, for whom VEs was similar at 14–90 days (73% [59–82%]), 91–180 days (71% [60–80%]), and 181–274 days (70% [54–81%]) postvaccination. Among hospitalized COVID-19 case-patients, VEp was 46% (18–65%) among immunocompetent patients.
Conclusions . The Ad26.COV2.S COVID-19 vaccine reduced the risk of COVID-19 hospitalization by 72% among immunocompetent adults without waning through 6 months postvaccination. After hospitalization for COVID-19, vaccinated immunocompetent patients were less likely to require IMV or die compared to unvaccinated immunocompetent patients.