bluuebunny/crossref_metadata_2025_split huggingface dataset:
How viral proteins bind short linear motifs and intrinsically disordered domains
Authors: Madhu Priyanka , Davey Norman E. , Ivarsson Ylva 
Published: December 2022

Abstract
Viruses are the obligate intracellular parasites that exploit the host cellular machinery to replicate their genome. During the viral life cycle viruses manipulate the host cell through interactions with host proteins. Many of these protein–protein interactions are mediated through the recognition of host globular domains by short linear motifs (SLiMs), or longer intrinsically disordered domains (IDD), in the disordered regions of viral proteins. However, viruses also employ their own globular domains for binding to SLiMs and IDDs present in host proteins or virus proteins. In this review, we focus on the different strategies adopted by viruses to utilize proteins or protein domains for binding to the disordered regions of human or/and viral ligands. With a set of examples, we describe viral domains that bind human SLiMs. We also provide examples of viral proteins that bind to SLiMs, or IDDs, of viral proteins as a part of complex assembly and regulation of protein functions. The protein–protein interactions are often crucial for viral replication, and may thus offer possibilities for innovative inhibitor design.
Astrocytes as metabolic suppliers to support neuronal activity and brain functions
Authors: Roumes Hélène , Pellerin Luc , Bouzier-Sore Anne-Karine 
Published: December 2022

Abstract
Energy metabolism is essential for brain function. In recent years, lactate shuttling between astrocytes and neurons has become a fundamental concept of neuroenergetics. However, it remains unclear to what extent this process is critical for different aspects of cognition, their underlying mechanisms, as well as for the signals used to monitor brain activation.
L 363-38 b: A planet newly discovered with ESPRESSO orbiting a nearby M dwarf star
Authors: Sartori Lia F. , Lovis Christophe , Delisle Jean-Baptiste , Lendl Monika , Cugno Gabriele , Boehle Anna , Dannert Felix , Krenn Andreas , Gubler Jonas L. , Quanz Sascha P. 
Published: December 2022

Context. Planets around stars in the solar neighbourhood will be prime targets for characterisation with upcoming large space- and ground-based facilities. Since large-scale exoplanet searches will not be feasible with such telescopes, it is crucial to use currently available data and instruments to find possible target planets before next-generation facilities come online.
Aims. We aim to detect new extrasolar planets around stars in the solar neighbourhood via blind radial velocity (RV) searching with ESPRESSO. Our target sample consists of nearby stars (d < 11 pc) with few (<10) or no previous RV measurements.
Methods. We used 31 radial velocity measurements obtained with ESPRESSO at the VLT between December 2020 and February 2022 of the nearby M dwarf star (M★ = 0.21 M⊙, d = 10.23 pc) L 363-38 to derive the orbital parameters of the newly discovered planet. In addition, we used TESS photometry and archival VLT/NaCo high-contrast imaging data to put further constraints on the orbit inclination and the possible planetary system architecture around L 363-38.
Results. We present the detection of a new extrasolar planet orbiting the nearby M dwarf star L 363-38. L 363-38 b is a planet with a minimum mass of mp sin(i) = 4.67 ± 0.43 M⊕ orbiting its star with a period of P = 8.781 ± 0.007 days, corresponding to a semi-major axis of a = 0.048 ± 0.006 AU, which is smaller than the inner edge of the habitable zone. We further estimate a minimum radius of rp sin(i) ≈ 1.55–2.75 R⊕ and an equilibrium temperature of Teq ≈ 330 K.
Conclusions. With this study, we further demonstrate the potential of the state-of-the-art spectrograph ESPRESSO in detecting and investigating planetary systems around nearby M dwarf stars, which were inaccessible to previous instruments such HARPS.
Der Mensch und seine Schmerzen – Möglichkeiten und Grenzen der Erfahrbarkeit der Schmerzen des anderen
Authors: Henß Peter Uwe 
Published: December 2022

ZusammenfassungDer Schmerz nimmt als primum movens für den Arztbesuch, durch seinen diagnostischen Stellenwert und als Indikator für die Therapiewirksamkeit eine zentrale Stellung im Arzt-Patienten-Verhältnis ein.Die Frage, ob und ggf. wie der Schmerz des anderen erfahrbar ist, hat epistemische Bedeutung. Der Schmerz als Sinneszustand muss vom Schmerz als Bewusstseinsphänomen unterschieden werden.Qualia werden von Nagel als „what is it like“- Zustände beschrieben, die im phänomenalen Bewusstsein erlebt werden. Sie sind phänomenale Zustände und charakterisiert durch den qualitativen Charakter eines unmittelbar gegebenen subjektiven Gefühlsinhaltes. Der Schmerz als Quale ist subjektiv und an die Erste-Person-Perspektive gebunden. Phänomenale Zustände entziehen sich der begrifflichen Beschreibbarkeit.Wissenschaftler und Ärzte untersuchen den Schmerz objektiv aus der Dritte-Person-Perspektive. Abstraktion und Objektivierung werden dem subjektiven phänomenalen Schmerzerleben nicht gerecht.Die Erklärungslücke bei Levine besteht, weil es keinen Nexus zwischen der physischen Reizung einer C-Schmerzfaser und dem Auftreten der phänomenalen Eigenschaft des Schmerzes (Bewusstseinsphänomen) gibt. Nagels Thesen zeigen, dass Tatsachen, die phänomenale Zustände betreffen, keine physikalischen Tatsachen sind. Erstere sind nur Wesen zugänglich, die die geeignete Erfahrungsperspektive einnehmen können.Der Schmerz des anderen als Quale ist für den Arzt nicht erfahrbar. Medizinische Untersuchungsverfahren in der Medizin sind Surrogate für das Schmerzverständnis, die zugleich für die ärztliche Diagnostik und Therapie unverzichtbar sindWiehl postuliert (in der Auseinandersetzung mit Viktor von Weizsäckers Aufsatz „Die Schmerzen“), aufgrund der polaren Struktur des Schmerzes, dass der Schmerz, indem er individuell und spezifisch sei, gerade auch ein allgemeiner Schmerz sei. Wenn in der empathischen Begegnung von Patient und Arzt der Schmerz des anderen mitteilbar wird, könnte durch diesen sprachlichen Annäherungsversuch auf der Seite des Therapeuten modifiziert etwas vom phänomenalen Erleben des Patienten erfahrbar werden.
Methodological challenges and insights for future international business research
Authors: Aguinis Herman , Bergh Donald , Molina-Azorin José F. 
Published: December 2022

AbstractGiven the diverse, interdisciplinary, and multilevel nature of international business (IB) research, it is critical to address methodological challenges prior to data collection. Thus, we suggest that an ounce of methodological prevention is worth a pound of cure. We describe the following challenges: (1) researching an important and relevant issue; (2) making meaningful theoretical progress; (3) recognizing, anticipating, and resolving dilemmas in research design and execution decisions; (4) integrating quantitative and qualitative research by using mixed methods; and (5) reducing the “distal proxy fallacy” through measurement error management. We then offer specific and actionable recommendations and implementation guidelines for authors, journal editors, and reviewers for addressing each of these methodological challenges with the overall goal of advancing IB theory.
Health or wealth? The influence of perceived health and wealth threats and style of thinking on protective behaviours and well-being during the COVID-19 pandemic in Spain (¿Salud o riqueza? La influencia de las amenazas percibidas contra la salud y la riqueza y del estilo de pensamiento en las conductas de protección y el bienestar durante la pandemia de COVID-19 en España)
Authors: Carrera Pilar , Aguilar Pilar , Fernández Itziar , Caballero Amparo 
Published: December 2022

The present research explored the influence of thinking style and the perception of threats to health and wealth on protective actions and well-being within the framework of the first wave of COVID-19 in Spain. We expected that an abstract (versus concrete) thinking style would be related to greater protective behaviours while maintaining a higher sense of well-being. Through an online questionnaire ( N = 1,043), we explored these relationships and found that the most severe perceived threats to health and wealth and the highest degree of abstraction were associated with the greatest protective behaviours. Importantly, when people did not feel very threatened, those who thought abstractly reported more protective behaviours. Regarding well-being, when people perceived greater threats, those who had an abstract thinking style reported greater well-being. Against the backdrop of the COVID-19 pandemic, the present research provides support indicating that an abstract thinking style is a protective factor against adversities because it is related to protective behaviours and increased well-being even when people perceive severe health and wealth threats.
Search for exotic physics in double-β decays with GERDA Phase II
Authors: Agostini M. , Alexander A. , Araujo G. , Bakalyarov A.M. , Balata M. , Barabanov I. , Baudis L. , Bauer C. , Belogurov S. , Bettini A. , Bezrukov L. , Biancacci V. , Bossio E. , Bothe V. , Brugnera R. , Caldwell A. , Calgaro S. , Cattadori C. , Chernogorov A. , Comellato T. , D'Andrea V. , Demidova E.V. , Di Giacinto A. , Di Marco N. , Doroshkevich E. , Fischer F. , Fomina M. , Gangapshev A. , Garfagnini A. , Gooch C. , Grabmayr P. , Gurentsov V. , Gusev K. , Hakenmüller J. , Hemmer S. , Hofmann W. , Huang J. , Hult M. , Inzhechik L.V. , Janicskó Csáthy J. , Jochum J. , Junker M. , Kazalov V. , Kermaïdic Y. , Khushbakht H. , Kihm T. , Kilgus K. , Kirpichnikov I.V. , Klimenko A. , Knöpfle K.T. , Kochetov O. , Kornoukhov V.N. , Krause P. , Kuzminov V.V. , Laubenstein M. , Lindner M. , Lippi I. , Lubashevskiy A. , Lubsandorzhiev B. , Lutter G. , Macolino C. , Majorovits B. , Maneschg W. , Manzanillas L. , Marshall G. , Miloradovic M. , Mingazheva R. , Misiaszek M. , Morella M. , Müller Y. , Nemchenok I. , Pandola L. , Pelczar K. , Pertoldi L. , Piseri P. , Pullia A. , Ransom C. , Rauscher L. , Redchuk M. , Riboldi S. , Rumyantseva N. , Sada C. , Sailer S. , Salamida F. , Schönert S. , Schreiner J. , Schütt M. , Schütz A-K. , Schulz O. , Schwarz M. , Schwingenheuer B. , Selivanenko O. , Shevchik E. , Shirchenko M. , Shtembari L. , Simgen H. , Smolnikov A. , Stukov D. , Vasenko A.A. , Veresnikova A. , Vignoli C. , von Sturm K. , Wester T. , Wiesinger C. , Wojcik M. , Yanovich E. , Zatschler B. , Zhitnikov I. , Zhukov S.V. , Zinatulina D. , Zschocke A. , Zsigmond A.J. , Zuber K. , Zuzel G. 
Published: December 2022

Abstract
A search for Beyond the Standard Model double-β decay modes of 76Ge has been
performed with data collected during the Phase II of the GERmanium Detector Array
(Gerda) experiment,
located at the Laboratori
Nazionali del Gran Sasso of INFN (Italy). Improved
limits on the decays involving Majorons have been obtained, compared to previous experiments with
76Ge, with half-life values on the order of 1023 yr. For the first time with
76Ge, limits on Lorentz invariance violation effects in double-β decay have been
obtained. The isotropic coefficient åof
(3), which embeds Lorentz
violation in double-β decay, has been constrained at the order of 10-6 GeV. We also
set the first experimental limits on the search for light exotic fermions in double-β decay,
including sterile neutrinos.
A tomographic spherical mass map emulator of the KiDS-1000 survey using conditional generative adversarial networks
Authors: Yiu Timothy Wing Hei , Fluri Janis , Kacprzak Tomasz 
Published: December 2022

Abstract
Large sets of matter density simulations are becoming increasingly important in large-scale structure cosmology. Matter power spectra emulators, such as the Euclid Emulator and
CosmicEmu, are trained on simulations to correct the non-linear part of the power spectrum.
Map-based analyses retrieve additional non-Gaussian information from the density field, whether
through human-designed statistics such as peak counts, or via machine learning methods such as
convolutional neural networks. The simulations required for these methods are very
resource-intensive, both in terms of computing time and storage. This creates a computational
bottleneck for future cosmological analyses, as well as an entry barrier for testing new,
innovative ideas in the area of cosmological information retrieval. Map-level density field
emulators, based on deep generative models, have recently been proposed to address these
challenges. In this work, we present a novel mass map emulator of the KiDS-1000 survey footprint,
which generates noise-free spherical maps in a fraction of a second. It takes a set of
cosmological parameters (Ω
M
, σ
8) as input and produces a consistent set of 5 maps,
corresponding to the KiDS-1000 tomographic redshift bins. To construct the emulator, we use a
conditional generative adversarial network architecture and the spherical convolutional neural
network DeepSphere, and train it on N-body-simulated mass maps. We compare its
performance using an array of quantitative comparison metrics: angular power spectra Cℓ
,
pixel/peaks distributions, Cℓ
correlation matrices, and Structural Similarity Index.
Overall, the average agreement on these summary statistics is <10% for the cosmologies at the
centre of the simulation grid, and degrades slightly on grid edges. However, the quality of the
generated maps is worse at high negative κ values or large scale, which can significantly
affect summaries sensitive to such observables. Finally, we perform a mock cosmological parameter
estimation using the emulator and the original simulation set. We find good agreement in these
constraints, for both likelihood and likelihood-free approaches. The emulator is available at
tfhub.dev/cosmo-group-ethz/models/kids-cgan.
Statistical properties of inflationary saddles in Gaussian random landscapes
Authors: Low Lerh Feng , Easther Richard , Hotchkiss Shaun 
Published: December 2022

Abstract
Random, multifield functions can set generic expectations for landscape-style cosmologies. We consider the inflationary implications of a landscape defined by a Gaussian random function, which is perhaps the simplest such scenario. Many key properties of this landscape, including the distribution of saddles as a function of height in the potential, depend only on its dimensionality, N, and a single parameter, γ, which is set by the power spectrum of the random function. We show that for saddles with a single downhill direction the negative mass term grows smaller relative to the average mass as N increases, a result with potential implications for the η-problem in landscape scenarios. For some power spectra, Planck-scale saddles have η ∼ 1 and eternal, topological inflation would be common in these scenarios. Lower-lying saddles typically have large η, but the fraction of these saddles which would support inflation is computable, allowing us to identify which scenarios can deliver a universe that resembles ours. Finally, by drawing inferences about the relative viability of different multiverse proposals we also illustrate ways in which quantitative analyses of multiverse scenarios are feasible.
The effect of outflows on CMB bounds from Primordial Black Hole accretion
Authors: Piga Lorenzo , Lucca Matteo , Bellomo Nicola , Bosch-Ramon Valentí , Matarrese Sabino , Raccanelli Alvise , Verde Licia 
Published: December 2022

Abstract
Should Primordial Black Holes (PBHs) exist in nature, they would inevitably accrete baryonic matter in their vicinity. In turn, the consequent emission of high-energy radiation could affect the thermal history of the universe to an extent that can be probed with a number of cosmological observables such as the Cosmic Microwave Background (CMB) anisotropies. However, our understanding of the accretion and radiation emission processes in the context of PBHs is still in its infancy, and very large theoretical uncertainties affect the resulting constraints on the PBH abundance. Building on state-of-the-art literature, in this work we take a step towards the development of a more realistic picture of PBH accretion by accounting for the contribution of outflows. Specifically, we derive CMB-driven constraints on the PBH abundance for various accretion geometries, ionization models and mass distributions in absence and in presence of mechanical feedback and non-thermal emissions due to the outflows. As a result, we show that the presence of such outflows introduces an additional layer of uncertainty that needs to be taken into account when quoting cosmological constraints on the PBH abundance, with important consequences in particular in the LIGO-Virgo-KAGRA observational window.
WIMPs during reheating
Authors: Bernal Nicolás , Xu Yong 
Published: December 2022

Abstract
Weakly Interacting Massive Particles (WIMPs) are among the best-motivated dark matter candidates. In the standard scenario where the freeze-out happens well after the end of inflationary reheating, they are in tension with the severe experimental constraints. Here, we investigate the thermal freeze-out of WIMPs occurring during reheating, while the inflaton ϕ coherently oscillates in a generic potential ∝ ϕn
. Depending on the value of n and the spin of the inflaton decaying products, the evolution of the radiation and inflaton energy densities can show distinct features, therefore, having a considerable impact on the freeze-out behavior of WIMPs. As a result of the injection of entropy during reheating, the parameter space compatible with the observed DM relic abundance is enlarged. In particular, the WIMP thermally averaged annihilation cross-section can be several magnitudes lower than that in the standard case. Finally, we discuss the current bounds from dark matter indirect detection experiments, and explore future challenges and opportunities.
The impact of gravitational lensing in the reconstruction of stellar orbits around Sgr A*
Authors: Pietroni S. , Bozza V. 
Published: December 2022

Abstract
After the amazing discoveries by the GRAVITY collaboration in the last few years on the star S2 orbiting the black hole Sgr A* in the center of the Milky Way, we present a detailed investigation of the impact of gravitational lensing on the reconstruction of stellar orbits around this massive black hole.
We evaluate the lensing astrometric effects on the stars S2, S38 and S55 and how these systematically affect the derived orbital parameters. The effect is below current uncertainties, but not negligible. With the addition of more observations on these stars, it will be possible to let the astrometric shift by lensing emerge from the statistical noise and be finally detected.

By repeating the analysis on a smaller semimajor axis a and various inclinations i, we are able to quantify the lensing effects on a broader range of parameters. As expected, for smaller semimajor axes and for nearly edge-on orbits lensing effects increase by about an order of magnitude.
Phonon-phonon interaction and parametric down-conversion generation in multimode optomechanical systems
Authors: Peng Zhen-Yang , Wang Ying-Dan 
Published: December 2022

Abstract
We studied the process of polariton conversion in a 3-mode nonlinear optomechanical system. Compared with the standard 2-mode optomechanical system, we find a much larger conversion rate of polariton modes can be achieved under typical dissipation conditions. To obtain a transparent understanding of the relevant physical process, we show that in the large detuned case, the cavity can be eliminated adiabatically, resulting in a parametric down-conversion (PDC) interaction between two phononic polariton modes. By tuning cavity detuning, the nonlinear interaction can be enhanced with the frequency-matching condition. Results from analytical treatment based on the effective PDC model agree with the numerical simulation. Such a system provides potential applications in nonlinear phononics.
Two Methods of Matrix Factorization and Their Applications
Authors: Zhang Wantong 
Published: December 2022

Abstract
Many problems in real life are summed up as mathematical models. Linear equation set is a more common approach among all mathematical models. Given particular scenarios and conditions, linear equation sets can solve problems such as resource allocation. This paper mainly introduces two basic methods of matrix factorization, explains how to simplify the solving process of linear equations by using elimination method, and applies the model into a real-life problem.
Comparison of Statistical Estimators for Estimating the Orders of Markov Chains
Authors: Meng Jingxiang 
Published: December 2022

Abstract
High order discrete Markov chain is essential to analyze the dependency structure of data sets. To apply Markov chain correctly, even though the true order is an unknown parameter, statisticians have developed multiple order estimators. It is natural to identify the strongest order estimators under different parameter combinations. Aim for evaluating the performance of estimators, we study four of them in this paper: Akaike information criteria (AIC), Bayesian information criteria (BIC), Maximal fluctuation estimation method (PS), and approximate χ
2 − distribution method (Dk
). We simulated Cr
× C transition matrices to generate word-count-based Markov sequences with the most straightforward initial distribution. We found PS and Dk
give more accurate discrete Markov order estimation. Although AIC and BIC are commonly applied, their performances are not the most accurate. The accuracy declines approximately exponentially as the Markov model gets more complex, i.e. r ≥ 1 and C ≥ 3. AIC’s accuracy is higher when the Markov chain length is relatively small, but Dk
yields a slightly higher accuracy under the same setting. PS give a more reasonable estimation when Markov order is the variable, i.e. 1 ≥ r ≥ 3. Dk
gives more reasonable estimations when the length L and alphabet size C are variable, i.e. 150 ≥ L ≥ 800 and 3 ≥ C ≥ 5.
Development of Computational Chemistry and Application of Computational Methods
Authors: Ma Xiaoyue 
Published: December 2022

Abstract
This paper discussed the development of computational chemistry, some representative computational chemistry methods and some machine learning algorithms applied to computational chemistry. Computational chemistry has grown considerably since the 1920s and is rapidly becoming an important and emerging sub-discipline in the whole field of chemistry. In recent years, the introduction of machine learning algorithms such as support vector machines and deep learning has made computational chemistry processes more accurate and efficient. The application of computational chemistry in areas such as conformational prediction has brought about a revolutionary change in chemical research.