Miracle-dz/UniFAR-FTUs huggingface dataset:
Magnetohydrodynamic activity inside a sphere

We present a computational method to solve the magnetohydrodynamic equations in spherical geometry. The technique is fully nonlinear and wholly spectral, and uses an expansion basis that is adapted to the geometry: Chandrasekhar-Kendall vector eigenfunctions of the curl. The resulting lower spatial resolution is somewhat offset by being able to build all the boundary conditions into each of the orthogonal expansion functions and by the disappearance of any difficulties caused by singularities at the center of the sphere. The results reported here are for mechanically and magnetically isolated spheres, although different boundary conditions could be studied by adapting the same method. The intent is to be able to study the nonlinear dynamical evolution of those aspects that are peculiar to the spherical geometry at only moderate Reynolds numbers. The code is parallelized, and will preserve to high accuracy the ideal magnetohydrodynamic invariants of the system (global energy, magnetic helicity, cross helic.
Supplements to : Isotropic stress reduces cell proliferation in tumor spheroids

We use confocal microscopy to extract the detailed shape of the spheroids. A spheroid is placed in a solution of wheat germ agglutinin conjugated with FITC ( Invitrogen Ref. W11261) for 10 min and rinsed. This protocol leads to the fluorescent labeling of the lipids at surface of the spheroid. We then acquire a stack of optical slices I(i,j,k) separated by 1 μm in the z direction. These images are analyzed using a home-made algorithm. For each pixel (i,j) we choose which z-index k correspond to the maximum focus for this lateral position. As the fluorescent labeling is positioned on the surface of the spheroid we obtain a 3D surface (smoothened to the level of one cell) which correspond to the shape of the spheroid. We then obtain the radial profile of the aggregate by calculating the average radius for every z position. This curve as shown on Fig. 1 can be readily fitted by a quarter of a circle. This validates our assumption that the cell aggregates can be considered as spheres. In addition it enables us to extract the contact angle between the surface and the support (here a PEG-PLL treated glass) which in this case is about 157◦.
Phase transitions triggered by dumbbell equipotential hypersurfaces

In a recent paper a toy model (called hypercubic model) undergoing a first-order $\mathbb{Z}_2$ symmetry breaking phase transition (SBPT) has been introduced. The hypercubic model was inspired by the \emph{topological hypothesis}, according to which a phase transition may be entailed by suitable topological changes of the equipotential hypersurfaces $\Sigma_v$ of configuration space. The $\Sigma_v$'s of the hypercubic model have a single topological change, which, under further particular hypotheses of geometric nature, entails the $\mathbb{Z}_2$-SBPT. In this paper we introduce an extended version of the hypercubic model in which no topological change in the $\Sigma_v$'s is present anymore, but nevertheless the $\mathbb{Z}_2$-SBPT occurs the same. We introduce a geometric property of the $\Sigma_v$'s (i.e. dumbbell $\Sigma_v$'s suitably defined) that is sufficient to entail a $\mathbb{Z}_2$-SBPT regardless their topology. The paper ends by applying the picture of the dumbbell $\Sigma_v$'s to a physical model, i.e. the mean-field $\phi^4$ model.
Robustness Analysis of Discrete State-Based Reinforcement Learning Models in Traffic Signal Control

With the growing traffic congestion problem, more and more deep reinforcement learning (DRL) methods have been applied in traffic signals control(TSC). But researches show that DRL is very fragile with abnormal data. In this paper, special traffic state abnormal data (TSAD) are simulated, based on which the robustness of DRL is analyzed and improved for traffic signals control. Firstly, the perturbation noise is generated based on the Discrete Carlin&Wagner attack, which is then added to the normal data to simulate the TSAD. Secondly, under different type of TSAD, the robustness of DRL models for traffic signals control is explored, which are demonstrated to have certain vulnerability, especially with high traffic flows. Finally, induction model based on reward detection (IMR) and mask the activation values of decision neurons (MVN) are proposed to effectively improve the robustness of DRL models for traffic signals control.
Correlated fluctuations in luminosity distance and the importance of peculiar motion in supernova surveys

Large scale structure introduces two different kinds of errors in the luminosity distance estimates from standardizable candles such as supernovae Ia (SNe)--a Poissonian scatter for each SN and a coherent component due to correlated fluctuations between different SNe. Increasing the number of SNe helps reduce the first type of error but not the second. The coherent component has been largely ignored in forecasts of dark energy parameter estimation from upcoming SN surveys. For instance it is commonly thought, based on Poissonian considerations, that peculiar motion is unimportant, even for a low redshift SN survey such as the Nearby Supernova Factory (SNfactory; z=0.03-0.08), which provides a useful anchor for future high redshift surveys by determining the SN zero point. We show that ignoring coherent peculiar motion leads to an underestimate of the zero-point error by about a factor of 2, despite the fact that SNfactory covers almost half of the sky. More generally, there are four types of fluctuations: peculiar motion, gravitational lensing, gravitational redshift and what is akin to the integrated Sachs-Wolfe effect. Peculiar motion and lensing dominates at low and high redshifts, respectively. Taking into account all significant luminosity distance fluctuations due to large scale structure leads to amore » degradation of up to 60% in the determination of the dark energy equation of state from upcoming high redshift SN surveys, when used in conjunction with a low redshift anchor such as the SNfactory. The most relevant fluctuations are the coherent ones due to peculiar motion and the Poissonian ones due to lensing, with peculiar motion playing the dominant role. We also discuss to what extent the noise here can be viewed as a useful signal, and whether corrections can be made to reduce the degradation. « less
Retinal Cyclic Nucleotide-Gated Channel Regulation by Calmodulin

Retinal cyclic nucleotide-gated (CNG) ion channels bind to intracellular cGMP and mediate visual phototransduction in photoreceptor rod and cone cells. Retinal rod CNG channels form hetero-tetramers comprised of three CNGA1 and one CNGB1 protein subunits. Cone CNG channels are similar tetramers consisting of three CNGA3 and one CNGB3 subunits. Calmodulin (CaM) binds to two distinct sites (CaM1: residues 565–587 and CaM2: residues 1120–1147) within the cytosolic domains of rod CNGB1. The binding of Ca2+-bound CaM to CNGB1 promotes the Ca2+-induced desensitization of CNG channels in retinal rods that may be important for photoreceptor light adaptation. Mutations that affect Ca2+-dependent CNG channel function are responsible for inherited forms of blindness. In this review, we propose structural models of the rod CNG channel bound to CaM that suggest how CaM might cause channel desensitization and how dysregulation of the channel may lead to retinal disease.
Perturbing the ground ring of 2D string theory

We use free field techniques in D=2 string theory to calculate the perturbation of the special state algebras when the cosmological constant is turned on. In particular, we find that the “ground cone” preserved by the ring structure is promoted to a three-dimensional hyperboloid as conjectured by Witten. On the other hand, the perturbed (1, 1) current algebra of moduli deformations is computed completely, and no simple geometrical interpretation is found. We also quote some facts concerning the Liouville matrix model dictionary in this class of theories.
Dynamics of GVC Position of v4 Automotive Suppliers: Implications for Public Policy

In the post-covid world, governments explore options to enhance their policies so that corporations can act as successful motors of recovery and sustainable growth. Countries select various objectives related to global value chains (GVC), such as participation, value capture, inclusiveness and resilience, yet might be unaware of the position of corporations they are supposed to motivate. In this paper, we aim to (re-)investigate the position of Visegrad Four (V4) suppliers within the regional automotive value chains and to compare results with suppliers in other EU member states using the trade in value added (TiVA) statistics. We set two research questions: How does the position of V4 in automotive GVCs differ from the positions of other EU member states and significant other automotive-producing countries? What is the link between the domestic value added in gross exports of final automotive products and the selected policy variables? A multiple linear regression model is run with TiVA in the automotive industry as the dependent variable and independent variables embodying proxies of GVC-oriented policy consequences. The analysis identifies significant differences in value-added levels between V4 countries and other EU countries, and other large automotive-producing economies. Labour costs, productivity, investment in R&D and innovation support are among the factors where V4 countries fall behind. Implications for Central European audience: The results of our research might be helpful for respective authorities and governments in V4 and other Central and Eastern European countries. They can be of use when setting goals and implementing policies targeted at promoting innovation, upgrading within existing GVCs and in cooperation between universities and research centres on the one hand and the automotive industry on the other. © 2023, Central European Business Review. All Rights Reserved.
Submitted to Magnetic Resonance in Medicine Natively Fat-Suppressed 5D Whole-Heart MRI with a Radial Free-Running Fast- Interrupted Steady-State (FISS) Sequence at 1.5T and 3T

Purpose: To implement, optimize and test fast interrupted steady-state (FISS) for natively fat-suppressed free-running 5D whole-heart MRI at 1.5T and 3T. Methods: FISS was implemented for fully self-gated free-running cardiacand respiratory-motion-resolved radial imaging of the heart at 1.5T and 3T. Numerical simulations and phantom scans were performed to compare fat suppression characteristics and to determine parameter ranges (readouts per FISS module (NR) and repetition time (TR)) for effective fat suppression. Subsequently, free-running FISS data were collected in ten healthy volunteers. All acquisitions were compared with a continuous bSSFP version of the same sequence, and both fat suppression and scan times were analyzed. Results: Simulations demonstrate a variable width and location of suppression bands in FISS that was dependent on TR and NR. For a fat suppression bandwidth of 100Hz and NR≤8, simulations demonstrated that a TR between 2.2ms and 3.0ms is required at 1.5T while a range of 3.0ms to 3.5ms applies at 3T. Fat signal increases with NR. These findings were corroborated in phantom experiments. In volunteers, fat SNR was significantly decreased using FISS compared with bSSPF (p<0.05) at both field strengths. After protocol optimization, high-resolution (1.1mm) 5D whole-heart free-running FISS can be performed with effective fat suppression in under 8 min at 1.5T and 3T at a modest scan time increase compared to bSSFP. Conclusion: An optimal FISS parameter range was determined enabling natively fatsuppressed 5D whole-heart free-running MRI with a single continuous scan at 1.5T and 3T, demonstrating potential for cardiac imaging and noncontrast angiography.
Efficient Methods for Evaluation on Ploidy Level of Cucurbita pepo L. Regenerant Plants Obtained in Unpollinated Ovule Culture In Vitro

An important stage in doubled haploid (DH) production is to evaluate and to differentiate the ploidy level of regenerant plants at least two–three times during the technology. Therefore, rapid and reliable methods are necessary for particular species taken into the technology. In this study, Cucurbita pepo regenerants obtained through unpollinated ovule culture in vitro were evaluated including three different methods: direct chromosome counting in apical meristems, flow cytometry of the cell nucleus, and estimation of morphological parameters of the abaxial epidermis. Methods were optimized for each of three evaluations, and main criteria were determined for ploidy level differentiation. As a result, four ploidy levels, namely, 2n, 3n, 4n, and 8n, were defined among regenerant plants adapted to ex vitro conditions, while true haploids were only found among plants that remained in the in vitro culture. In total, 32.35%, 26.47%, 33.82%, 4.41%, and 2.94% of regenerant plants of courgette and patisson were diploid, triploid, tetraploid, octaploid, and aneuploid, respectively. According to results of flow cytometry of the cell nucleus, two cytotypes in diploid samples with DNA content of 2C = 1.07 ± 0.03 pg for courgette belonging to subsp. pepo and 2C = 0.95 ± 0.03 pg for patisson samples belonging to subsp. ovifera were revealed. The images of metaphase chromosomes of haploid, triploid, and tetraploid C. pepo specimens obtained using the propion–lacmoid chromosome staining method were presented for the first time. Parameters of abaxial epidermis in diploid samples of courgette and patisson grown in open-field and greenhouse conditions were described and compared. It was shown that the most robust parameter not depending on external factors was the number of chloroplasts in stomatal guard cells, which contained 9.41 to 11.31, 14.84 to 16.3, and up to 17.58 chloroplasts in diploid, triploid, and tetraploid samples, respectively. The application of several methods for estimation enables avoiding the misidentification of ploidy levels in adapted regenerant plants produced with the use of DH technology.
Review of pedestrian trajectory prediction methods

Urban driverless vehicles will inevitably interact with pedestrians in the process of driving. In order to avoid path conflict with pedestrians, the research on pedestrian trajectory prediction is of great significance. This paper mainly summarizes the technical classification and research status of pedestrian trajectory prediction at this stage in detail. According to the different modeling methods, the existing trajectory prediction methods are divided into shallow learning-based trajectory prediction methods and depth learning based trajectory prediction methods. The advantages and disadvantages of the depth learning based trajectory prediction methods are compared, and the current mainstream pedestrian trajectory prediction public dataset is summarized, and the performance of the mainstream pedestrian trajectory prediction methods is compared in the dataset. Finally, the challenges and development trend of pedestrian trajectory prediction at this stage are prospected.
How has “Management of Ba” been developed? Itami’s research from Management control systems to Management of Ba

This research aims to reveal the background of the “management of ba ” (a Japanese term meaning “field”), which is proposed by Hiroyuki Itami, because his research has been shifted from management control systems to management of ba . We review Itami’s articles from the 1970s to the present to clarify why Itami created the management of ba . Itami revised his assumption of the organization to describe real-life management practices based on his research results. In addition, it was important to investigate how Itami’s assumption of human nature had shifted to include individuals’ autonomy and self-organization, key aspects of the management of ba. A management approach that enhances psychological energy is needed in order to increase individuals’ autonomy and self-organization. That approach is indeed refers to the management of ba. By reviewing Itami’s research, we identified that Itami’s research question was, “how can the liberty of an individual be ensured within an organization? ” Itami noted that management control systems need to balance liberty and discipline; thus, we focused on the problem of the liberty of individuals in organizations from the point of view of management accounting research.
Hanbury Brown–Twiss correlations and multi-mode dynamics in quenched, inhomogeneous density spinor Bose–Einstein condensates

We have studied the effects of multiple, competing spatial modes that are excited by a quantum quench of an antiferromagnetic spinor Bose–Einstein condensate. We observed Hanbury Brown–Twiss correlations and associated super-Poissonian noise in the mode populations. The decay of these correlations was consistent with experimentally observed spin domain patterns. Data were compared with a real-space Bogoliubov theory as well as numerical solution of the coupled Gross–Pitaevskii equations that were seeded by quantum noise via the truncated Wigner approximation. The spatial modes that were both observed experimentally and deduced theoretically are intimately connected to the inhomogeneous density profile of the condensate. Unique features were observed not present in a homogeneous system, including unstable modes located near the center of the cloud, where the dynamics were initiated.
Connexin43 in Musculoskeletal System: New Targets for Development and Disease Progression

Connexin43, which is the most highly expressed connexin subtype in the musculoskeletal system, exists in a variety of bone cells, synovial tissue, and cartilage tissue. Connexin43 has been suggested to be a key regulator of bone homeostasis. Studies have shown aberrant Connexin43 expression in musculoskeletal disorders, such as osteoporosis, osteoarthritis, and rheumatoid arthritis. During cellular activities, Connexin43 can participate in the formation of functionally specific gap junctions and hemichannels and can exert independent cellular regulatory and signaling functions through special C-termini. The critical role of Connexin43 in physiological development and disease progression has been gradually revealed. In this article, the function of Connexin43 in musculoskeletal tissues is summarized, revealing the potential role of Connexin43 as a key target in the treatment of related bone and muscle disorders and the need for further discovery.
Kiselev/ CFT correspondence and thermodynamic black hole

In this paper, we consider Kiselev black hole solution as dust and radiation. We obtain the inner and outer horizons and investigate the thermal properties of corresponding black hole. We find the area and entropy products and show that they are independent of mass. So, they are universal relations and is satisfied by $T_{+}S_{+}=-T_{-}S_{-}$. Such universal relations lead us to calculate the central charge of conformal field theory $(CFT)$. Finally, we see that the left and right of central charge of $CFT$ are same.
FedDual: Pair-Wise Gossip Helps Federated Learning in Large Decentralized Networks

There is a significant recent interest in collaboratively training a machine learning (ML) model without collecting data to a central server. Federated learning (FL) emerges as an efficient solution mitigating systemic privacy risks and communication costs. However, conventional FL inherited from parameter server designs relies too much on a central server, which may lead to privacy risks, communication bottlenecks, or a single point of failure. In this paper, we propose an asynchronous and hierarchical local gradient aggregation and global model update algorithm, FedDual, under three different security considerations for FL in large decentralized networks. Particularly, FedDual preserves privacy by introducing local differential privacy (LDP) and aggregates local gradients asynchronously and hierarchically via a pair-wise gossip algorithm, which is more competitive than previous gossip-based decentralized FL methods in terms of privacy preservation and communication efficiency, and offers more computational efficiency compared to existing blockchain-assisted decentralized FL methods. Further, we devise a noise cutting trick based on Private Set Intersection (PSI) to mitigate the prediction performance loss of the global model caused by the leveraged LDP. Rigorous analyses show that FedDual helps decentralized FL achieve the same convergence rate of $\mathcal {O}\left({\frac {1}{T}}\right) $ as centralized ML theoretically. Ingenious experiments on MNIST, CIFAR-10, and FEMNIST confirm that the model prediction performance gained from FedDual is close to centralized ML. More importantly, the proposed noise cutting trick helps FedDual to train better global models than LDP-based FL methods in terms of prediction performance and convergence rate.
From causes to consequences: Investigating the effects of differentiated integration on citizens’ EU support

Research on differentiated integration has paid considerable attention to its causes. However, we know very little about its consequences. Using the synthetic control method and interactive factor models, this article investigates the effects of differentiated integration on citizens’ support for the EU. We find that in cases where member states are granted an opt-out or are allowed to integrate into a policy area they were previously excluded from, support increases. In contrast, support decreases when member states are not granted a requested opt-out or are excluded from a policy area they would like to join. These findings carry important implications for the EU's legitimacy. While differentiated integration has the potential to enhance citizens’ legitimacy perceptions, it can also undermine them simultaneously.
10-nm-thick quinary (AlCrTaTiZr)N film as effective diffusion barrier for Cu interconnects at 900 °C

In this study, an ultrathin quinary nitride film (AlCrTaTiZr)N of only 10 nm thick has been developed as a diffusion barrier layer for Cu interconnects. The (AlCrTaTiZr)N nanocomposite film was constructed of nanocrystallites embedded in an amorphous matrix. At an extremely high temperature of 900 °C, the Si/(AlCrTaTiZr)N/Cu film stack remained thermally stable. Neither interdiffusion between Si and Cu through the (AlCrTaTiZr)N layer nor formation of any silicides occurred. The nanocomposite structure and severe lattice distortions attributed to the addition of multiple elements were expected as the dominant factors for the superior diffusion resistance of the (AlCrTaTiZr)N film.
Comparing Neutron Star Kicks to Supernova Remnant Asymmetries

Supernova explosions are inherently asymmetric and can accelerate new-born neutron stars (NSs) to hundreds of km s−1. Two prevailing theories to explain NS kicks are ejecta asymmetries (e.g., conservation of momentum between NS and ejecta) and anisotropic neutrino emission. Observations of supernova remnants (SNRs) can give us insights into the mechanism that generates these NS kicks. In this paper, we investigate the relationship between NS kick velocities and the X-ray morphologies of 18 SNRs observed with the Chandra X-ray Observatory and the Röntgen Satellite (ROSAT). We measure SNR asymmetries using the power-ratio method (a multipole expansion technique), focusing on the dipole, quadrupole, and octupole power ratios. Our results show no correlation between the magnitude of the power ratios and NS kick velocities, but we find that for Cas A and G292.0+1.8, whose emission traces the ejecta distribution, their NSs are preferentially moving opposite to the bulk of the X-ray emission. In addition, we find a similar result for PKS 1209–51, CTB 109, and Puppis A; however, their emission is dominated by circumstellar/interstellar material, so their asymmetries may not reflect their ejecta distributions. Our results are consistent with the theory that NS kicks are a consequence of ejecta asymmetries as opposed to anisotropic neutrino emission. In the future, additional observations to measure NS proper motions within ejecta-dominated SNRs are necessary to robustly constrain the NS kick mechanism.