On the relation between the mass of Compact Massive Objects and their host galaxies

Supermassive black holes and/or very dense stellar clusters are found in the central regions of galaxies. Nuclear star clusters are present mainly in faint galaxies while upermassive black holes are common in galaxies with masses $\geq 10^{10}$ M$_\odot$. In the intermediate galactic mass range both types of central massive objects (CMOs) are found. Here we present our collection of a huge set of nuclear star cluster and massive black hole data that enlarges significantly already existing data bases useful to investigate for correlations of their absolute magnitudes, velocity dispersions and masses with structural parameters of their host galaxies. In particular, we directed our attention to some differences between the correlations of nuclear star clusters and massive black holes as subsets of CMOs with hosting galaxies. In this context, the mass-velocity dispersion relation plays a relevant role because it seems the one that shows a clearer difference between the supermassive black holes and nuclear star clusters. The $M_{MBH}-{\sigma}$ has a slope of $5.19\pm 0.28$ while $M_{NSC}-{\sigma}$ has the much smaller slope of $1.84\pm 0.64$. The slopes of the CMO mass- host galaxy B magnitude of the two types of CMOs are indistinguishable within the errors while that of the NSC mass-host galaxy mass relation is significantly smaller than for supermassive black holes. Another important result is the clear depauperation of the NSC population in bright galaxy hosts, which reflects also in a clear flattening of the NSC mass vs host galaxy mass at high host masses.Comment: 12 pages, 22 figures, 2 tables, accepted for publication in MNRA

Model of a multiverse providing the dark energy of our universe

It is shown that the dark energy presently observed in our universe can be regarded as the energy of a scalar field driving an inflation-like expansion of a multiverse with ours being a subuniverse among other parallel universes. A simple model of this multiverse is elaborated: Assuming closed space geometry, the origin of the multiverse can be explained by quantum tunneling from nothing; subuniverses are supposed to emerge from local fluctuations of separate inflation fields. The standard concept of tunneling from nothing is extended to the effect that in addition to an inflationary scalar field, matter is also generated, and that the tunneling leads to an (unstable) equilibrium state. The cosmological principle is assumed to pertain from the origin of the multiverse until the first subuniverses emerge. With increasing age of the multiverse, its spatial curvature decays exponentially so fast that, due to sharing the same space, the flatness problem of our universe resolves by itself. The dark energy density imprinted by the multiverse on our universe is time-dependent, but such that the ratio $w{=}\varrho/(c^2p)$ of its mass density and pressure (times $c^2$) is time-independent and assumes a value $-1{+}\epsilon$ with arbitrary $\epsilon{>}0$. $\epsilon$ can be chosen so small, that the dark energy model of this paper can be fitted to the current observational data as well as the cosmological constant model.Comment: 32 pages, 4 figure

Native Peptide Cyclization, Sequential Chemoselective Amidation in Water

Chemical synthesis offers robust tactics for structural alterations of peptides and proteins. It remains a labor-intensive and complex process due to the challenges in selectively modifying diverse amino acid side chains and termini. Direct α-peptide ligation without premodification is a significant hurdle, especially when aiming to include all proteinogenic amino acids at the ligation site. We introduce Native Peptide Cyclization (NPC), a chemoselective method enabling intramolecular peptidyl ligation without the need for premodification. NPC cyclizes unprotected linear peptides through controlled, sequential C- and N-terminal activation via pH modulation. Water-based NPC simplifies peptide ligation, easing the labor-intensive nature of peptide synthesis, aiding efficient cyclic peptide preparation and enabling cost-effective macrocycle-based therapeutics

TG-Pro: a SAT-based ATPG system, system description

Automatic Test Pattern Generation (ATPG) is arguably one of the practical applications that motivated the development of modern Boolean Satisfiability (SAT) solvers in the mid 90s. Despite the interest of using SAT in ATPG, the original model remained mostly unchanged for nearly two decades, even in the presence of renewed interest in applying modern SAT technology to large-scale hardware designs. This paper describes the SAT-based ATPG system TG-Pro. In contrast to all SAT-based ATPG work over the last two decades, TG-Pro is based on a new fundamentally different SAT-based ATPG model. Experimental results, obtained on well-known and publicly available benchmarks, demonstrate that TG-Pro achieves major performance improvements over other well-established SAT-based ATPG models

New and improved models for SAT-based bi-decomposition

Boolean function bi-decomposition is pervasive in logic synthesis. Bi-decomposition entails the decomposition of a Boolean function into two other simpler functions connected by a simple two-input gate. Existing solutions are based either on Binary Decision Diagrams (BDDs) or Boolean Satisfiability (SAT). Furthermore, the partition of the input set of variables is either assumed, or an automatic derivation is required. Most recent work on bi-decomposition proposed the use of Minimally Unsatisfiable Subformulas (MUSes) or Quantified Boolean Formulas (QBF) for computing, respectively, variable partitions of either approximate or optimum quality. This paper develops new grouporiented MUS-based models for addressing both the performance and the quality of bi-decompositions. The paper shows that approximate MUS search can be guided by the quality of well-known metrics. In addition, the paper improves on recent high-performance approximate models and versatile exact models, to address the practical requirements of bi-decomposition in logic synthesis. Experimental results obtained on representative benchmarks demonstrate significant improvement in performance as well as in the quality of decompositions

Additional file 1 of Housing debt and depressive symptoms: evidence from the China family panel studies

Supplementary Material

Fabrication and characterization of ceria-carbonate composite electrolyte and single layer fuel cell

<p>a) Frenet-Serret frame. Vectors N, B, and T denote normal, binormal, and tangent. b) Example of normal vectors along a curve.</p

QBF-based boolean function bi-decomposition

Boolean function bi-decomposition is ubiquitous in logic synthesis. It entails the decomposition of a Boolean function using two-input simple logic gates. Existing solutions for bidecomposition are often based on BDDs and, more recently, on Boolean Satisfiability. In addition, the partition of the input set of variables is either assumed, or heuristic solutions are considered for finding good partitions. In contrast to earlier work, this paper proposes the use of Quantified Boolean Formulas (QBF) for computing bi-decompositions. These bi-decompositions are optimal in terms of the achieved quality of the input set of variables. Experimental results, obtained on representative benchmarks, demonstrate clear improvements in the quality of computed decompositions, but also the practical feasibility of QBF-based bi-decomposition

Resliced image space construction for coronary artery collagen fibers

<div><p>Collagen fibers play an important role in the biomechanics of the blood vessel wall. The objective of this study was to determine the 3D microstructure of collagen fibers in the media and adventitia of coronary arteries. We present a novel optimal angle consistence algorithm to reform image slices in the visualization and analysis of 3D collagen images. 3D geometry was reconstructed from resliced image space where the 3D skeleton was extracted as the primary feature for accurate reconstruction of geometrical parameters. Collagen fibers (range 80–200) were reconstructed from the porcine coronary artery wall for the measurement of various morphological parameters. Collagen waviness and diameters were 1.37 ± 0.19 and 2.61 ± 0.89 μm, respectively. The biaxial distributions of orientation had two different peaks at 110.7 ± 25.2° and 18.4 ± 19.3°. Results for width, waviness, and orientation were found to be in good agreement with manual measurements. In addition to accurately measuring 2D features more efficiently than the manual approach, the present method produced 3D features that could not be measured in the 2D manual approach. These additional parameters included the tilt angle (5.10 ± 2.95°) and cross-sectional area (CSA; 5.98 ± 3.79 μm²) of collagen fibers. These 3D collagen reconstructions provide accurate and reliable microstructure for biomechanical modeling of vessel wall mechanics.</p></div

Coordinate system used to define the vessel surface.

<p>Coordinate system used to define the vessel surface.</p