bluuebunny/crossref_metadata_2025_split huggingface dataset:
Greatly increased electrical conductivity of PBTTT-C14 thin film via controllable single precursor vapor phase infiltration
Authors: Mu Xueyang , Wang Weike , Sun Chongcai , Zhao Dan , Ma Chuang , Zhu Jiankang , Knez Mato 
Published: October 2022

Abstract
Doping is an important strategy for effectively regulating the charge carrier concentration of semiconducting materials. In this study, the electronic properties of organic–inorganic hybrid semiconducting polymers, synthesized via in situ controlled vapor phase infiltration (VPI) of poly[2,5-bis(3-tetradecylthiophen-2-yl)thieno[3,2-b]thiophene] (PBTTT-C14) with the metal precursors molybdenum pentachloride (MoCl5) and titanium tetrachloride (TiCl4), were altered and characterized. The conductivities of the infiltration-doped PBTTT-C14 thin films were enhanced by up to 9 and 4 orders of magnitude, respectively. The significantly improved electrical properties may result from interactions between metal atoms in the metal precursors and sulfur of the thiophene rings, thus forming new chemical bonds. Importantly, VPI doping has little influence on the structure of the PBTTT-C14 thin films. Even if various dopant molecules infiltrate the polymer matrix, the interlayer spacing of the films will inevitably expand, but it has negligible effects on the overall morphology and structure of the film. Also, Lewis acid-doped PBTTT-C14 thin films exhibited excellent environmental stability. Therefore, the VPI-based doping process has great potential for use in processing high-quality conductive polymer films.
Investigation on the surface morphologies of reduced graphene oxide coating on the interfacial characteristics and electro-catalytic capacity of enzymatic glucose sensors
Authors: Zhou Fan , Wang Jiyuan , Tang Yimei , Liu Shu , Du Yanrui , Jing Weixuan , Li Yan , Hai Lixin , Li Wenqiang , Gao Feng 
Published: October 2022

Abstract
In this study, reduced graphene oxide (rGO) were subject to ultrasonic treatment to acquire varied morphologies, and the enzymatic glucose sensors were constructed by coating the rGO onto indium tin oxide electrodes and physically linking glucose oxidase to the rGO coatings. The effects of the surface morphologies of the rGO coatings on the interfacial characteristics and the electro-catalytic capacity of the enzymatic glucose sensors were systematically investigated. It turns out that, the rGO coating with a rough surface is more hydrophilic, and exhibits uniform glucose oxidase adsorption and higher electron migration rate at the solid/liquid interface between the analytical liquid and the working electrode. As a result, the corresponding glucose sensor shows excellent electro-catalytic capacity towards glucose with a broader linear range of 0–10.0 mM, a higher sensitivity of 38.9 μA·mM−1·cm−2, and a lower detection limit of 0.1 μM (signal-to-noise ratio of 3). Additionally, the as-prepared glucose sensor exhibits excellent accuracy for detecting actual blood samples as well as superior resistance to interference from other substances (such as L-phenylalanine, urea, ascorbic acid, uric acid, NaCl, and KCl). These results establish the theoretical and experimental foundation for the application of rGO coating in the field of biosensors.
Molecular dynamics study on the effect of electric current on electrically-assisted scratching for crystal copper
Authors: Yu Li , Qiu-Yang Zheng , Zhen-Yu Zhou , Cong Ding , Sen-Bin Ye , Zhong-Yu Piao 
Published: October 2022

Abstract
Investigation of the effect of electric current on the plastic deformation mechanism of metals during the electrically-assisted machining process is significant in further improving surface properties. In this paper, the molecular dynamics (MD) method is adopted to simulate the electrically-assisted scratching process of crystal copper, obtaining and analyzing the surface morphology, potential energy change, von Mises stress distribution, and crystal defect structure evolution. The MD simulation results show that the electric current effectively expands the dislocation slip range, resulting in a larger plastic deformation zone. Meanwhile, the combined action of the electron wind forces and Joule heating causes more dislocations to proliferate and increases the dislocation density limit, enhancing the plastic deformation ability of the single-crystal copper. Furthermore, the electric current strengthens the dislocation-grain boundary interactions and reduces the hindering effect of the grain boundaries on dislocations, promoting more dislocations to cross the grain boundaries. This work will be helpful for guiding the optimization of surface strengthening techniques to get better surface properties of metals.
On single-photon and classical interference
Authors: Barnett Stephen M 
Published: October 2022

Abstract
It has often been remarked that single-photon interference experiments, however complicated, seem to behave very much in the same way as those performed in the classical regime, using the field generated by a laser. This observation has the status of being ‘well-known to those who know it’, but perhaps mysterious to others. We discuss the reasons underlying the similarity and also some of the limitations of this simple idea.
Natural Inflation with non minimal coupling to gravity in R
2 gravity under the Palatini formalism
Authors: AlHallak M. , Chamoun N. , Eldaher M.S. 
Published: October 2022

Abstract
Natural Inflation with non-minimal coupling (NMC) to gravity, embodied by a Lagrangian term ξϕ
2
R, is investigated in the context of an extended gravity of the form R + αR
2. The treatment is performed in the Palatini formalism. We discuss various limits of the model “α ≫ 1” and “α ≪ 1” in light of two scenarios of inflation: a “Slow roll” and a “Constant roll” scenario. By analyzing the observational consequences of the model, our results show a significant improvement regarding compatibility between the theoretical results of this model and the observational constraints from Planck 2018 and BICEP/Keck 2018, as exemplified by the tensor-to-scalar ratio and spectral index. Furthermore, a broader range for the parameter space of natural inflation is now compatible with the confidence contours of Planck & BICEP/Keck results.
The joint effects of the contributions of both the NMC to gravity and the αR
2 make a significant improvement: αR
2 gravity influences scalar-tensor ratio values, whereas NMC to gravity has a more significant impact on the spectral index values. Contributions from both terms allow more previously excluded intervals to be included being compatible now with observational data. These conclusions about the roles of NMC to gravity and, particularly, the extended gravity remain mainly valid with a periodic NMC similar in form to the natural inflation potential.
Optical depth to reionization from perturbative 21 cm clustering
Authors: Sailer Noah , Chen Shi-Fan , White Martin 
Published: October 2022

AbstractThe optical depthτis the least well determined parameter in the standard model of cosmology, and one whose precise value is important for both understanding reionization and for inferring fundamental physics from cosmological measurements. We forecast how well future epoch of reionization experiments could constraintτusing a symmetries-based bias expansion that highlights the special role played by anisotropies in the power spectrum on large scales. Given a parametric model for the ionization evolution inspired by the physical behavior of more detailed reionization simulations, we find that future 21 cm experiments could place tight constraints on the timing and duration of reionization and hence constraints onτthat are competitive with proposed, space-based CMB missions provided they can measurek≈ 0.1hMpc-1with a clean foreground wedge across redshifts spanning the most active periods of reionization, corresponding to ionization fractions 0.2 ≲x≲ 0.8. Significantly improving upon existing CMB-based measurements with next-generation 21 cm surveys would require substantially longer observations (∼ 5 years) than standard 𝒪(1000 hour) integration times. Precise measurements of smaller scales will not improve constraints onτuntil a better understanding of the astrophysics of reionization is achieved. In the presence of noise and foregrounds even future 21 cm experiments will struggle to constrainτif the ionization evolution deviates significantly from simple parametric forms.
Regularization of energy-dependent pointlike interactions in 1D quantum mechanics
Authors: Granet Etienne 
Published: October 2022

Abstract
We construct a family of Hermitian potentials in 1D quantum mechanics that converges in the zero-range limit to a
δ
interaction with an energy-dependent coupling. It does not belong to the standard four-parameter family of pointlike interactions in 1D, obtained by requiring hermiticity. But we show that although our Hamiltonian is Hermitian for the standard inner product when the range of the potential is finite, the eigenstates become orthogonal for a different inner product in the zero-range limit. This inner product attributes a finite probability (and not probability density) for the particle to be exactly located at the position of the potential. Such pointlike interactions can then be used to construct potentials with a finite support with an energy-dependent coupling.
Efficient spatio-temporal feature clustering for large event-based datasets
Authors: Oubari Omar , Exarchakis Georgios , Lenz Gregor , Benosman Ryad , Ieng Sio-Hoi 
Published: October 2022

Abstract
Event-based cameras encode changes in a visual scene with high temporal precision and low power consumption, generating millions of events per second in the process. Current event-based processing algorithms do not scale well in terms of runtime and computational resources when applied to a large amount of data. This problem is further exacerbated by the development of high spatial resolution vision sensors. We introduce a fast and computationally efficient clustering algorithm that is particularly designed for dealing with large event-based datasets. The approach is based on the expectation-maximization (EM) algorithm and relies on a stochastic approximation of the E-step over a truncated space to reduce the computational burden and speed up the learning process. We evaluate the quality, complexity, and stability of the clustering algorithm on a variety of large event-based datasets, and then validate our approach with a classification task. The proposed algorithm is significantly faster than standard k-means and reduces computational demands by two to three orders of magnitude while being more stable, interpretable, and close to the state of the art in terms of classification accuracy.
Some topological results of Ricci limit spaces
Authors: Pan Jiayin , Wang Jikang 
Published: October 2022

We study the topology of a Ricci limit space

(
X
,
p
)

(X,p)

, which is the Gromov-Hausdorff limit of a sequence of complete

n
n

-manifolds

(

M
i

,

p
i

)

(M_i, p_i)

with

R
i
c

≥
−
(
n
−
1
)

\mathrm {Ric}\ge -(n-1)

. Our first result shows that, if

M
i

M_i

has Ricci bounded covering geometry, i.e. the local Riemannian universal cover is non-collapsed, then

X
X

is semi-locally simply connected. In the process, we establish a slice theorem for isometric pseudo-group actions on a closed ball in the Ricci limit space. In the second result, we give a description of the universal cover of

X
X

if

M
i

M_i

has a uniform diameter bound; this improves a result by Ennis and Wei [Differential Geom. Appl. 24 (2006), pp. 554-562].
Transnational arbitration agreements as contracts: in search of the parties’ common intention
Authors: Bantekas Ilias 
Published: October 2022

Abstract
Although agreements to arbitrate constitute contracts that are distinct from those in which they are contained, the practice of arbitral statutes, international instruments, and arbitral tribunals is to conflate the parties’ common intention to be bound with the particular form required of the arbitral agreement. This sui generis (conflated) contractual nature is unique to arbitral agreements and serves the transnational character of international arbitration. The required form, which is conflated with the parties’ common intention, is meant to serve a procedural, rather than a substantive/contractual purpose, namely the triggering of the jurisdiction of the arbitral tribunal. All this is in sharp contrast with the rigid assessment of offer, acceptance and common intention to be bound that permeates contracts under national laws, all three of which are distinct actions. It further serves as evidence that transnational law does not neatly distinguish between substantive and procedural law, with contracts being an inextricable part of this transnational legal process.
The GR2D2 estimator for the precision matrices
Authors: Gan Dailin , Yin Guosheng , Zhang Yan Dora 
Published: October 2022

Abstract
Biological networks are important for the analysis of human diseases, which summarize the regulatory interactions and other relationships between different molecules. Understanding and constructing networks for molecules, such as DNA, RNA and proteins, can help elucidate the mechanisms of complex biological systems. The Gaussian Graphical Models (GGMs) are popular tools for the estimation of biological networks. Nonetheless, reconstructing GGMs from high-dimensional datasets is still challenging. The current methods cannot handle the sparsity and high-dimensionality issues arising from datasets very well. Here, we developed a new GGM, called the GR2D2 (Graphical $R^2$-induced Dirichlet Decomposition) model, based on the R2D2 priors for linear models. Besides, we provided a data-augmented block Gibbs sampler algorithm. The R code is available at https://github.com/RavenGan/GR2D2. The GR2D2 estimator shows superior performance in estimating the precision matrices compared with the existing techniques in various simulation settings. When the true precision matrix is sparse and of high dimension, the GR2D2 provides the estimates with smallest information divergence from the underlying truth. We also compare the GR2D2 estimator with the graphical horseshoe estimator in five cancer RNA-seq gene expression datasets grouped by three cancer types. Our results show that GR2D2 successfully identifies common cancer pathways and cancer-specific pathways for each dataset.
Molecular insights to the sperm–cervix interaction and the consequences for cryopreserved sperm
Authors: Warr Sophie , Pini Taylor , de Graaf Simon P , Rickard Jessica P 
Published: October 2022

AbstractCryopreserved ram spermatozoa are limited in their capacity to traverse the ovine cervix and achieve fertilization. This altered interaction may be related to modified molecular communication between frozen-thawed ram spermatozoa, seminal plasma, and the female tract. As such, this review aims to identify the biological processes which underpin sperm maturation and transport throughout the female reproductive tract to elucidate factors which may alter this natural process in cryopreserved ram spermatozoa. We also assess critical barriers to ram spermatozoa specific to the ovine cervix and the role of seminal plasma in mitigating these barriers. Transcriptomics is explored as a new approach to understand the sperm–cervix interaction. Recent studies have demonstrated that both spermatozoa and seminal plasma contain a complex profile of coding and non-coding RNAs. These molecular species have clear links with functional fertility, and mounting evidence suggests they may be altered by cryopreservation. Emerging in vitro cell culture models are also investigated as a “next step” in studying this interaction, utilizing transcriptomics to identify subtle changes in female tract gene expression in response to spermatozoa. The application of such models is proposed as an exciting opportunity to investigate the unique challenges faced by cryopreserved spermatozoa traversing the ovine cervix prior to fertilization.
Genetic and environmental factors influencing neonatal resting-state functional connectivity
Authors: Blanchett Reid , Chen Yuanyuan , Aguate Fernando , Xia Kai , Cornea Emil , Burt S Alexandra , de Los Campos Gustavo , Gao Wei , Gilmore John H , Knickmeyer Rebecca C 
Published: October 2022

AbstractFunctional magnetic resonance imaging has been used to identify complex brain networks by examining the correlation of blood-oxygen-level-dependent signals between brain regions during the resting state. Many of the brain networks identified in adults are detectable at birth, but genetic and environmental influences governing connectivity within and between these networks in early infancy have yet to be explored. We investigated genetic influences on neonatal resting-state connectivity phenotypes by generating intraclass correlations and performing mixed effects modeling to estimate narrow-sense heritability on measures of within network and between-network connectivity in a large cohort of neonate twins. We also used backwards elimination regression and mixed linear modeling to identify specific demographic and medical history variables influencing within and between network connectivity in a large cohort of typically developing twins and singletons. Of the 36 connectivity phenotypes examined, only 6 showed narrow-sense heritability estimates greater than 0.10, with none being statistically significant. Demographic and obstetric history variables contributed to between- and within-network connectivity. Our results suggest that in early infancy, genetic factors minimally influence brain connectivity. However, specific demographic and medical history variables, such as gestational age at birth and maternal psychiatric history, may influence resting-state connectivity measures.
Sustained upregulation of widespread hippocampal–neocortical coupling following memory encoding
Authors: Folvik Line , Sneve Markus H , Ness Hedda T , Vidal-Piñeiro Didac , Raud Liisa , Geier Oliver M , Walhovd Kristine B , Fjell Anders M 
Published: October 2022

AbstractSystems consolidation of new experiences into lasting episodic memories involves hippocampal–neocortical interactions. Evidence of this process is already observed during early post-encoding rest periods, both as increased hippocampal coupling with task-relevant perceptual regions and reactivation of stimulus-specific patterns following intensive encoding tasks. We investigate the spatial and temporal characteristics of these hippocampally anchored post-encoding neocortical modulations. Eighty-nine adults participated in an experiment consisting of interleaved memory task- and resting-state periods. We observed increased post-encoding functional connectivity between hippocampus and individually localized neocortical regions responsive to stimuli encountered during memory encoding. Post-encoding modulations were manifested as a nearly system-wide upregulation in hippocampal coupling with all major functional networks. The configuration of these extensive modulations resembled hippocampal–neocortical interaction patterns estimated from active encoding operations, suggesting hippocampal post-encoding involvement exceeds perceptual aspects. Reinstatement of encoding patterns was not observed in resting-state scans collected 12 h later, nor when using other candidate seed regions. The similarity in hippocampal functional coupling between online memory encoding and offline post-encoding rest suggests reactivation in humans involves a spectrum of cognitive processes engaged during the experience of an event. There were no age effects, suggesting that upregulation of hippocampal–neocortical connectivity represents a general phenomenon seen across the adult lifespan.
Age-related reorganization of functional network architecture in semantic cognition
Authors: Martin Sandra , Williams Kathleen A , Saur Dorothee , Hartwigsen Gesa 
Published: October 2022

AbstractCognitive aging is associated with widespread neural reorganization processes in the human brain. However, the behavioral impact of such reorganization is not well understood. The current neuroimaging study investigated age differences in the functional network architecture during semantic word retrieval in young and older adults. Combining task-based functional connectivity, graph theory and cognitive measures of fluid and crystallized intelligence, our findings show age-accompanied large-scale network reorganization even when older adults have intact word retrieval abilities. In particular, functional networks of older adults were characterized by reduced decoupling between systems, reduced segregation and efficiency, and a larger number of hub regions relative to young adults. Exploring the predictive utility of these age-related changes in network topology revealed high, albeit less efficient, performance for older adults whose brain graphs showed stronger dedifferentiation and reduced distinctiveness. Our results extend theoretical accounts on neurocognitive aging by revealing the compensational potential of the commonly reported pattern of network dedifferentiation when older adults can rely on their prior knowledge for successful task processing. However, we also demonstrate the limitations of such compensatory reorganization and show that a youth-like network architecture in terms of balanced integration and segregation is associated with more economical processing.
Fear of negative evaluation modulates the processing of social evaluative feedback with different valence and contexts
Authors: Zhang Yinling , Li Yanju , Mai Xiaoqin 
Published: October 2022

AbstractFear of negative evaluation (FNE) is a susceptible and maintaining factor of social anxiety disorders. However, the question, how people process negative evaluation is influenced by individual differences in FNE, is poorly understood. To clarify the habitual processing characteristics of individuals with different levels of FNE, electroencephalography was recorded when two groups of participants with high FNE (hFNE) and low FNE (lFNE) performed a social evaluation perception task in which the feedback context/source (human vs. a computer) and valence (thumb-up/like vs. thumb-down/dislike) were manipulated. We found effects of feedback source and valence on N1, P2, and P3, which reflect early attention, integrated perception, and elaborative processing, respectively, as well as general reward effects on reward positivity (RewP) across contexts. Importantly, compared to the lFNE group, the hFNE group showed larger midfrontal N1 and theta oscillation in response to negative feedback indicating dislike (vs. like), and also showed larger P3. These findings suggest that individuals with hFNE are more attentional vigilance to negative (vs. positive) social feedback, implying that individuals with different levels of FNE assign different implicit threat values to social-evaluation threat stimuli.