bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatially homogeneous black hole solutions in $$z=4$$ Hořava–Lifshitz gravity in $$(4+1)$$ dimensions with Nil geometry and $$H^2\times R$$ horizons
Authors: Naderi F. , Rezaei-Aghdam A. , Mahvelati-Shamsabadi Z. 
Published: October 2021

AbstractIn this paper, we present two new families of spatially homogeneous black hole solution for $$z=4$$

z
=
4

Hořava–Lifshitz Gravity equations in $$(4+1)$$

(
4
+
1
)

dimensions with general coupling constant $$\lambda $$
λ
and the especial case $$\lambda =1$$

λ
=
1

, considering $$\beta =-1/3$$

β
=
-
1
/
3

. The three-dimensional horizons are considered to have Bianchi types II and III symmetries, and hence the horizons are modeled on two types of Thurston 3-geometries, namely the Nil geometry and $$H^2\times R$$

H
2

×
R

. Being foliated by compact 3-manifolds, the horizons are neither spherical, hyperbolic, nor toroidal, and therefore are not of the previously studied topological black hole solutions in Hořava–Lifshitz gravity. Using the Hamiltonian formalism, we establish the conventional thermodynamics of the solutions defining the mass and entropy of the black hole solutions for several classes of solutions. It turned out that for both horizon geometries the area term in the entropy receives two non-logarithmic negative corrections proportional to Hořava–Lifshitz parameters. Also, we show that choosing some proper set of parameters the solutions can exhibit locally stable or unstable behavior.
Look Here: Learning Geometrically Consistent Refinement of Inverse-Depth Images for 3D Reconstruction
Authors: Săftescu Ştefan , Gadd Matthew , Newman Paul 
Published: October 2021

Building good 3D maps is a challenging and expensive task, which requires high-quality sensors and careful, time-consuming scanning. We seek to reduce the cost of building good reconstructions by correcting views of existing low-quality ones in a post-hoc fashion using learnt priors over surfaces and appearance. We train a convolutional neural network model to predict the difference in inverse-depth from varying viewpoints of two meshes — one of low-quality that we wish to correct, and one of high-quality that we use as a reference. Our full model runs at 11.3[Formula: see text]Hz when aggregating four input views. In contrast to previous work, we pay attention to the problem of excessive smoothing in corrected meshes. We address this with a suitable network architecture, and introduce a loss-weighting mechanism that emphasizes edges in the prediction. Furthermore, smooth predictions result in geometrical inconsistencies. To deal with this issue, we present a loss function which penalizes re-projection differences that are not due to occlusions. Future applications of this work will incorporate semantic scene understanding in a multi-task learning setting. We explore the efficacy of the proposed system in terms of gross error correction and generalization capability by showing its performance in practice on a subset of the Kitti Odometry dataset, complete with a component-wise ablation study. We evaluate correctness and completeness measures of surface reconstruction across viewpoints and show that the proposed system is introspective in regions lacking sufficient high-quality supervision — indeed, models trained with geometric consistency loss create a lot more surface in areas that were not supervised, in one case filling in 67.97% or 8010[Formula: see text]m2 of an unlabeled input region. Finally, we assess the practical applicability of our method at large-scale by experiments over the full scope of the Kitti Odometry dataset. Broadly, as a measure of effectiveness, our model reduces gross errors by 45.3–77.5%, up to five times more than previous work. We also assess the practical applicability of our method to 3D reconstruction at large scales and find that compared to the baseline our model shows better stability in correctness when improving completeness of surfaces, and is effective in reducing median total error by up to 21.8[Formula: see text]cm.
Solubility study of graphene in chlorinated dihydrolevoglucosenone by first-principle calculation
Authors: Yuan Songyang , Chen Fang , Liu Jun , Huang Peng , Zhang Shaolin 
Published: October 2021

Proper solvent matching is always a vital issue to prepare graphene-based high-concentration and stable functional inks in a printed flexible electronics field. In this work, a series of chlorinated dihydrolevoglucosenone (Cyrene) was modeled and their solubility properties toward pristine and defected graphene were evaluated. The reaction free energy, reaction rate constant and transport state of pristine Cyrene and four types of chlorinated Cyrenes have been calculated to simulate the reaction process and explore the possibility of the synthesis. The solvation free energy and [Formula: see text]-surface of pristine graphene and defected graphene in each solvent have been calculated to reveal the dissolution process and mechanism. This work evidences that the dissolution capability of pristine Cyrene towards pristine and defected graphene could be greatly enhanced by a chlorination reaction. The chlorinated Cyrene could be a powerful solvent for fabricating graphene-based electronic inks.
The influence of volcanic supply on the composition of modern river sands: the case study of the Ofanto River, southern Italy
Authors: Tenuta Mariano , Donato Paola , Dominici Rocco , De Rosa Rosanna 
Published: October 2021

Abstract
The Ofanto River drains volcanic rocks from the Monte Vulture, lacustrine–fluviolacustrine deposits associated with the same volcano and sedimentary deposits of the Southern Apennines and the Bradanic foredeep sequences. Comparing the modal composition of river sands and the outcrop area of different lithologies in the different sub-basins, an over-concentration of the volcaniclastic fraction, mainly represented by loose crystals of clinopyroxene, garnet and amphibole, is shown. This has been related to the preferential erosion of pyroclastic deposits, characterized by high production of sand-sized loose minerals, together with the carbonate lability and the low sand-sized detritus production from claystones and marls. The occurrence of volcaniclastic components upstream of Monte Vulture can be explained as a contribution from the lacustrine–fluviolacustrine deposits cropping out in the upstream sector or from pyroclastic fall deposits of Monte Vulture and/or Campanian volcanoes. This research shows that the volcanic record in the fluvial sands of the Ofanto River comes from weathering and sorting processes of volcaniclastic deposits rather than of the lavas building the main edifice. Therefore, caution must be taken during palaeoenvironmental and palaeoclimatic reconstructions when relating the type and abundance of the volcanic component in sediments to the weathering stage and evolutionary history of the volcano.
Sublinear Random Access Generators for Preferential Attachment Graphs
Authors: Even Guy , Levi Reut , Medina Moti , Rosén Adi 
Published: October 2021

We consider the problem of sampling from a distribution on graphs, specifically when the distribution is defined by an evolving graph model, and consider the time, space, and randomness complexities of such samplers.
In the standard approach, the whole graph is chosen randomly according to the randomized evolving process, stored in full, and then queries on the sampled graph are answered by simply accessing the stored graph. This may require prohibitive amounts of time, space, and random bits, especially when only a small number of queries are actually issued. Instead, we propose a setting where one generates parts of the sampled graph on-the-fly, in response to queries, and therefore requires amounts of time, space, and random bits that are a function of the actual number of queries. Yet, the responses to the queries correspond to a graph sampled from the distribution in question.

Within this framework, we focus on two random graph models: the Barabási-Albert Preferential Attachment model (BA-graphs) (
Science
, 286 (5439):509–512) (for the special case of out-degree 1) and the random recursive tree model (
Theory of Probability and Mathematical Statistics
, (51):1–28). We give on-the-fly generation algorithms for both models. With probability 1-1/poly(
n
), each and every query is answered in polylog(
n
) time, and the increase in space and the number of random bits consumed by any single query are both polylog(
n
), where
n
denotes the number of vertices in the graph.

Our work thus proposes a new approach for the access to huge graphs sampled from a given distribution, and our results show that, although the BA random graph model is defined by a sequential process, efficient random access to the graph’s nodes is possible. In addition to the conceptual contribution, efficient on-the-fly generation of random graphs can serve as a tool for the efficient simulation of sublinear algorithms over large BA-graphs, and the efficient estimation of their on such graphs.
Deep Neural Network–based Enhancement for Image and Video Streaming Systems: A Survey and Future Directions
Authors: Lee Royson , Venieris Stylianos I. , Lane Nicholas D. 
Published: October 2021

Internet-enabled smartphones and ultra-wide displays are transforming a variety of visual apps spanning from on-demand movies and 360° videos to video-conferencing and live streaming. However, robustly delivering visual content under fluctuating networking conditions on devices of diverse capabilities remains an open problem. In recent years, advances in the field of deep learning on tasks such as super-resolution and image enhancement have led to unprecedented performance in generating high-quality images from low-quality ones, a process we refer to as neural enhancement. In this article, we survey state-of-the-art content delivery systems that employ neural enhancement as a key component in achieving both fast response time and high visual quality. We first present the components and architecture of existing content delivery systems, highlighting their challenges and motivating the use of neural enhancement models as a countermeasure. We then cover the deployment challenges of these models and analyze existing systems and their design decisions in efficiently overcoming these technical challenges. Additionally, we underline the key trends and common approaches across systems that target diverse use-cases. Finally, we present promising future directions based on the latest insights from deep learning research to further boost the quality of experience of content delivery systems.
Smaller Cuts, Higher Lower Bounds
Authors: Abboud Amir , Censor-Hillel Keren , Khoury Seri , Paz Ami 
Published: October 2021

This article proves strong lower bounds for distributed computing in the
congest
model, by presenting the
bit-gadget
: a new technique for constructing graphs with small cuts.

The contribution of bit-gadgets is twofold. First, developing careful sparse graph constructions with small cuts extends known techniques to show a near-linear lower bound for computing the diameter, a result previously known only for dense graphs. Moreover, the sparseness of the construction plays a crucial role in applying it to approximations of various distance computation problems, drastically improving over what can be obtained when using dense graphs.
Second, small cuts are essential for proving super-linear lower bounds, none of which were known prior to this work. In fact, they allow us to show near-quadratic lower bounds for several problems, such as exact minimum vertex cover or maximum independent set, as well as for coloring a graph with its chromatic number. Such strong lower bounds are not limited to NP-hard problems, as given by two simple graph problems in P, which are shown to require a quadratic and near-quadratic number of rounds. All of the above are optimal up to logarithmic factors. In addition, in this context, the complexity of the all-pairs-shortest-paths problem is discussed.

Finally, it is shown that graph constructions for
congest
lower bounds translate to lower bounds for the semi-streaming model, despite being very different in its nature.
A Systematic Review of API Evolution Literature
Authors: Lamothe Maxime , Guéhéneuc Yann-Gaël , Shang Weiyi 
Published: October 2021

Recent software advances have led to an expansion of the development and usage of application programming interfaces (APIs). From millions of Android packages (APKs) available on Google Store to millions of open-source packages available in Maven, PyPI, and npm, APIs have become an integral part of software development.
Like any software artifact, software APIs evolve and suffer from this evolution. Prior research has uncovered many challenges to the development, usage, and evolution of APIs. While some challenges have been studied and solved, many remain. These challenges are scattered in the literature, which hides advances and cloaks the remaining challenges.
In this systematic literature review on APIs and API evolution, we uncover and describe publication trends and trending topics. We compile common research goals, evaluation methods, metrics, and subjects. We summarize the current state-of-the-art and outline known existing challenges as well as new challenges uncovered during this review.
We conclude that the main remaining challenges related to APIs and API evolution are (1) automatically identifying and leveraging factors that drive API changes, (2) creating and using uniform benchmarks for research evaluation, and (3) understanding the impact of API evolution on API developers and users with respect to various programming languages.
Midterm Outcomes Following Sutureless and Transcatheter Aortic Valve Replacement in Low-Risk Patients With Aortic Stenosis
Authors: Vilalta Victoria , Alperi Alberto , Cediel Germán , Mohammadi Siamak , Fernández-Nofrerias Eduard , Kalvrouziotis Dimitri , Delarochellière Robert , Paradis Jean-Michel , González-Lopera Marta , Fadeuilhe Edgar , Carrillo Xavier , Abdul-Jawad Altisent Omar , Rodríguez-Leor Oriol , Voisine Pierre , Bayés-Genís Antoni , Rodés-Cabau Josep 
Published: October 2021

Background:
Sutureless-surgical aortic valve replacement (SU-SAVR) has been proposed as a surgical alternative for treating aortic stenosis, which facilitates a minimally invasive approach. While some studies have compared the early outcomes of SU-SAVR versus transcatheter aortic valve replacement (TAVR), most data were obtained in high-risk patients and/or limited to in-hospital outcomes. This study aimed to compare in-hospital and midterm clinical outcomes following SU-SAVR and TAVR in low-risk patients with aortic stenosis.

Methods:
A total of 806 consecutive low-risk (EuroSCORE II <4%) patients underwent TAVR or SU-SAVR between 2011 and 2020 in 2 centers. A 1:1 propensity score matching was performed and identified 171 pairs with similar characteristics that were included in the analysis. Baseline characteristics, in-hospital and follow-up events (defined according to Valve Academic Research Consortium-2) were collected.

Results:

Baseline characteristics were well balanced between groups, with a median EuroSCORE II of 1.9% (1.3%–2.5%) in both SU-SAVR and TAVR groups (
P
=0.85). There were no statistically significant differences regarding in-hospital mortality (SU-SAVR: 4.1%, TAVR: 1.8%,
P
=0.199) and stroke (SU-SAVR: 2.3%, TAVR: 2.9%,
P
=0.736), but SU-SAVR recipients exhibited higher rates of bleeding and new-onset atrial fibrillation, higher residual transvalvular gradients (
P
<0.001), and a lower rate of pacemaker implantation (
P
=0.011). After a median follow-up of 2 (1–3) years, there were no differences between groups in all-cause mortality (hazard ratio, 0.97 [95% CI, 0.52–1.82],
P
=0.936) and stroke (hazard ratio, 0.83 [95% CI, 0.32–2.15],
P
=0.708), but SU-SAVR was associated with a higher risk of heart failure hospitalization (hazard ratio, 5.38 [95% CI, 1.88–15.38],
P
=0.002).

Conclusions:
In low-risk patients with aortic stenosis, TAVR was associated with improved in-hospital outcomes (except for conduction disturbances) and valve hemodynamics, compared with SU-SAVR. Although similar mortality and stroke rates were observed at 2-year follow-up, the risk of heart failure hospitalization was higher among SU-SAVR patients. These results may contribute to reinforce TAVR over SU-SAVR for the majority of such patients.

Graphic Abstract:

A
graphic abstract
is available for this article.
Impact of Delirium on Outcomes After Intracerebral Hemorrhage
Authors: Reznik Michael E. , Margolis Seth A. , Mahta Ali , Wendell Linda C. , Thompson Bradford B. , Stretz Christoph , Rudolph James L. , Boukrina Olga , Barrett A.M. , Daiello Lori A. , Jones Richard N. , Furie Karen L. 
Published: October 2021

Background and Purpose:
Delirium portends worse outcomes after intracerebral hemorrhage (ICH), but it is unclear if symptom resolution or postacute care intensity may mitigate its impact. We aimed to explore differences in outcome associated with delirium resolution before hospital discharge, as well as the potential mediating role of postacute discharge site.

Methods:
We performed a single-center cohort study on consecutive ICH patients over 2 years. Delirium was diagnosed according to DSM-5 criteria and further classified as persistent or resolved based on delirium status at hospital discharge. We determined the impact of delirium on unfavorable 3-month outcome (modified Rankin Scale score, 4–6) using logistic regression models adjusted for established ICH predictors, then used mediation analysis to examine the indirect effect of delirium via postacute discharge site.

Results:
Of 590 patients (mean age 70.5±15.5 years, 52% male, 83% White), 59% (n=348) developed delirium during hospitalization. Older age and higher ICH severity were delirium risk factors, but only younger age predicted delirium resolution, which occurred in 75% (161/215) of ICH survivors who had delirium. Delirium was strongly associated with unfavorable outcome, but patients with persistent delirium fared worse (adjusted odds ratio [OR], 7.3 [95% CI, 3.3–16.3]) than those whose delirium resolved (adjusted OR, 3.1 [95% CI, 1.8–5.5]). Patients with delirium were less likely to be discharged to inpatient rehabilitation than skilled nursing facilities (adjusted OR, 0.31 [95% CI, 0.17–0.59]), and postacute care site partially mediated the relationship between delirium and functional outcome in ICH survivors, leading to a 25% reduction in the effect of delirium (without mediator: adjusted OR, 3.0 [95% CI, 1.7–5.6]; with mediator: adjusted OR, 2.3 [95% CI, 1.2–4.3]).

Conclusions:
Acute delirium resolves in most patients with ICH by hospital discharge, which was associated with better outcomes than in patients with persistent delirium. The impact of delirium on outcomes may be further mitigated by postacute rehabilitation.
Probing Classifiers: Promises, Shortcomings, and Advances
Authors: Belinkov Yonatan 
Published: October 2021

Abstract
Probing classifiers have emerged as one of the prominent methodologies for interpreting and analyzing deep neural network models of natural language processing. The basic idea is simple—a classifier is trained to predict some linguistic property from a model’s representations—and has been used to examine a wide variety of models and properties. However, recent studies have demonstrated various methodological limitations of this approach. This squib critically reviews the probing classifiers framework, highlighting their promises, shortcomings, and advances.
Are We Reaching the Limit of Tropical Cyclone Track Predictability in the Western North Pacific?
Authors: Yu Hui , Chen Guomin , Zhou Cong , Wong Wai Kin , Yang Mengqi , Xu Yinglong , Chen Peiyan , Wan Rijin , Hu Xinrong 
Published: October 2021

Abstract
The annual-mean position errors (PE) of tropical cyclone (TC) track forecasts from three forecast agencies [WMO Regional Specialized Meteorological Center in Tokyo (RSMC-Tokyo), China Meteorological Administration (CMA), and Joint Typhoon Warning Center of the United States (JTWC)] are analyzed to document the past improvements and project future tendency in track forecast accuracy for TCs in the western North Pacific. An improvement of 48 h (2 days) in lead time has been achieved in the past 30 years, but with noticeable stepwise periods of improvements with superposed short-term fluctuations. The stepwise improvement features differ among the three forecast agencies, but are highly related to the development of objective forecast guidance and the application strategy. As demonstrated by an exponential model for the growth of PEs with lead time for TCs of tropical storm category and above, the improvements in the past 10 years have mainly been due to the reduction in analysis errors rather than the reduction in the error growth rate. If the current trend continues, a further 2-day improvement in TC track forecast lead times may be projected for the coming 15 years up to 2035, and we certainly have not reached yet the limit of TC track predictability in the western North Pacific.
An Initiation Process of Tropical Depression–Type Disturbances under the Influence of Upper-Level Troughs
Authors: Hamaguchi Yuya , Takayabu Yukari N. 
Published: October 2021

Abstract
In this study, the statistical relationship between tropical upper-tropospheric troughs (TUTTs) and the initiation of summertime tropical depression–type disturbances (TDDs) over the western and central North Pacific is investigated. By applying a spatiotemporal filter to the 34-yr record of brightness temperature and using JRA-55 products, TDD-event initiations are detected and classified as trough-related (TR) or non-trough-related (non-TR). The conventional understanding is that TDDs originate primarily in the lower troposphere; our results refine this view by revealing that approximately 30% of TDDs in the 10°–20°N latitude ranges are generated under the influence of TUTTs. Lead–lag composite analysis of both TR- and non-TR-TDDs clarifies that TR-TDDs occur under relatively dry and less convergent large-scale conditions in the lower troposphere. This result suggests that TR-TDDs can form in a relatively unfavorable low-level environment. The three-dimensional structure of the wave activity flux reveals southward and downward propagation of wave energy in the upper troposphere that converges at the midtroposphere around the region where TR-TDDs occur, suggesting the existence of extratropical forcing. Further, the role of dynamic forcing associated with the TUTT on the TR-TDD initiation is analyzed using the quasigeostrophic omega equation. The result reveals that moistening in the mid- to upper troposphere takes place in association with the sustained dynamical ascent at the southeast side of the TUTT, which precedes the occurrence of deep convective heating. Along with a higher convective available potential energy due to the destabilizing effect of TUTTs, the moistening in the mid- to upper troposphere also helps to prepare the environment favorable to TDDs initiation.