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Recent studies have shed light on the emergence and evolution of oxygenic photosynthesis. It is likely that the ancestor of Terrabacteria already possessed two distinct reaction centers, and that the ability to split water via photosystem II arose early in their evolution. Consequently, it is equally probable that the emergence of thylakoid membranes played a crucial role in the accumulation of oxygen in the atmosphere. However, the study of thylakoid emergence remains less explored than the origin of photosystems. With a highly synchronized process involving numerous assembly factors, the biogenesis of thylakoid membranes suggests the existence of intermediate evolutionary states in the emergence of these compartments. Constrained by the sulfide-rich environment of the Archean, I propose a non-oxygenic origin of thylakoid membranes, which would have been initially devoted to alternative electron flows., Comment: 2 Figures, 1 Table

Labor plays a major, albeit largely unrecognized role in the development of artificial intelligence. Machine learning algorithms are predicated on data-intensive processes that rely on humans to execute repetitive and difficult-to-automate, but no less essential, tasks such as labeling images, sorting items in lists, recording voice samples, and transcribing audio files. Online platforms and networks of subcontractors recruit data workers to execute such tasks in the shadow of AI production, often in lower-income countries with long-standing traditions of informality and lessregulated labor markets. This study unveils the resulting complexities by comparing the working conditions and the profiles of data workers in Venezuela, Brazil, Madagascar, and as an example of a richer country, France. By leveraging original data collected over the years 2018-2023 via a mixed-method design, we highlight how the cross-country supply chains that link data workers to core AI production sites are reminiscent of colonial relationships, maintain historical economic dependencies, and generate inequalities that compound with those inherited from the past. The results also point to the importance of less-researched, non-English speaking countries to understand key features of the production of AI solutions at planetary scale., Comment: Jack Qiu, Shinjoung Yeo, Richard Maxwell. The Handbook of Digital Labor, Wiley Blackwell, In press, ISBN10: 1119981808

It is usually assumed that the memory of any thermo-mechanical protocol applied to a glass can be erased by heating the material in the supercooled liquid. While this is true for thermally treated amorphous solids, we show that hydrostatic compression can irreversibly modify the atomic motion, thermodynamic state and structure of a prototypical metallic glass-former, in a way which depends on the degree of ergodicity reached by the material during compression. While enhanced kinetic and thermodynamic stability can be obtained by quenching the dense liquid, high-pressure annealing in the glass leads to thermal rejuvenation and complex structural rearrangements at the level of the short and medium range order. When heated above their glass transition temperature, these compressed glasses do not convert into the pristine supercooled liquid but rather transform into different systems, challenging the generally accepted idea of an equilibrium recovery controlled solely by the microscopic $\alpha$-relaxation process.

Cosmic microwave background (CMB) temperature and polarization observations indicate that in the best-fit $\Lambda$ Cold Dark Matter model of the Universe, the local geometry is consistent with at most a small amount of positive or negative curvature, i.e., $\vert\Omega_K\vert\ll1$. However, whether the geometry is flat ($E^3$), positively curved ($S^3$) or negatively curved ($H^3$), there are many possible topologies. Among the topologies of $S^3$ geometry, the lens spaces $L(p,q)$, where $p$ and $q$ ($p>1$ and $0

Die studies are fundamental to quantifying ancient monetary production, providing insights into the relationship between coinage, politics, and history. The process requires tedious manual work, which limits the size of the corpora that can be studied. Few works have attempted to automate this task, and none have been properly released and evaluated from a computer vision perspective. We propose a fully automatic approach that introduces several innovations compared to previous methods. We rely on fast and robust local descriptors matching that is set automatically. Second, the core of our proposal is a clustering-based approach that uses an intrinsic metric (that does not need the ground truth labels) to determine its critical hyper-parameters. We validate the approach on two corpora of Greek coins, propose an automatic implementation and evaluation of previous baselines, and show that our approach significantly outperforms them., Comment: code: https://cea-list-lasti.github.io/projects/studies/studies.html

The standard cosmological model, which assumes statistical isotropy and parity invariance, predicts the absence of correlations between even-parity and odd-parity observables of the cosmic microwave background (CMB). Contrary to these predictions, large-angle CMB temperature anomalies generically involve correlations between even-$\ell$ and odd-$\ell$ angular power spectrum $C_\ell$, while recent analyses of CMB polarization have revealed non-zero equal-$\ell$ $EB$ correlations. These findings challenge the conventional understanding, suggesting deviations from statistical isotropy, violations of parity, or both. Cosmic topology, which involves changing only the boundary conditions of space relative to standard cosmology, offers a compelling framework to potentially account for such parity-violating observations. Topology inherently breaks statistical isotropy, and can also break homogeneity and parity, providing a natural paradigm for explaining observations of parity-breaking observables without the need to add parity violation to the underlying microphysics. Our investigation delves into the harmonic space implications of topology for CMB correlations, using as an illustrative example $EB$ correlations generated by tensor perturbations under both parity-preserving and parity-violating scenarios. Consequently, these findings not only challenge the foundational assumptions of the standard cosmological model but also open new avenues for exploring the topological structure of the Universe through CMB observations., Comment: 20 pages, 4 figures. v2: version published in JCAP

Here, we compare the stabilities of different III-V crystals configurations on stepped Si substrates, with or without anti-phase boundaries, for abrupt and compensated interfaces, using density functional theory. Thermodynamic stability of the different heterostructures is analyzed with an atomic scale description of charge densities distribution and mechani-cal strain. We show that the configuration where a III-V crystal adapts to a Si monoatomic step through change of charge compensation at the hetero-interface is much more stable than the configuration in which an antiphase boundary is formed. This study thus demonstrates that antiphase boundaries commonly observed in III-V/Si samples are not origi-nating from Si monoatomic step edges but from inevitable kinetically driven coalescence of monophase 3D III-V islands., Comment: 8 pages, 5figures

Non-trivial spatial topology of the Universe may give rise to potentially measurable signatures in the cosmic microwave background. We explore different machine learning approaches to classify harmonic-space realizations of the microwave background in the test case of Euclidean $E_1$ topology (the 3-torus) with a cubic fundamental domain of a size scale significantly smaller than the diameter of the last scattering surface. This is the first step toward developing a machine learning approach to classification of cosmic topology and likelihood-free inference of topological parameters. Different machine learning approaches are capable of classifying the harmonic-space realizations with accuracy greater than 99% if the topology scale is half of the diameter of the last-scattering surface and orientation of the topology is known. For distinguishing random rotations of these sky realizations from realizations of the covering space, the extreme gradient boosting classifier algorithm performs best with an accuracy of 88%. Slightly lower accuracies of 83% to 87% are obtained with the random forest classifier along with one- and two-dimensional convolutional neural networks. The techniques presented here can also accurately classify non-rotated cubic $E_1$ topology realizations with a topology scale slightly larger than the diameter of the last-scattering surface, if enough training data are provided. While information compressing methods like most machine learning approaches cannot exceed the statistical power of a likelihood-based approach that captures all available information, they potentially offer a computationally cheaper alternative. A principle challenge appears to be accounting for arbitrary orientations of a given topology, although this is also a significant hurdle for likelihood-based approaches., Comment: 34 pages, 12 figures, 4 tables

Modern detector technology and highly brilliant fourth-generation synchrotrons allow to improve the temporal resolution in time-resolved diffraction studies. Profiting from this, we applied temperature scanning X-ray photon correlation spectroscopy (XPCS) to probe the dynamics of a Pt-based metallic glass former in the glass, glass transition region, and supercooled liquid, covering up to six orders of magnitude in time scales. Our data demonstrates that the structural alpha-relaxation process is still observable in the glass, although it is partially masked by a faster source of decorrelation observed at atomic scale. We present an approach that interprets these findings as the superposition of heterogeneous liquid-like and stress-driven ballistic-like atomic motions. This work not only extends the dynamical range probed by standard isothermal XPCS, but also clarifies the fate of the alpha-relaxation across the glass transition and provides a new perception on the anomalous, compressed temporal decay of the density-density correlation functions observed in metallic glasses and many out-of-equilibrium soft materials.

Vitreous GeO$_2$ has been compressed at high temperature, to investigate the effect of thermal activation on the structural reorganization during compression. The measurements were performed in-situ using micro Raman spectroscopy under pressure up to 6 GPa and temperature up to 400$^\circ$C. The evolution of the Raman shift of the main band (400-500 cm$^{-1}$) with temperature during compression evidences a pressure window around 3 GPa within which temperature has a remarkable influence on the structure, in particular the intermediate range order. We find that this change is well correlated with previous ex-situ density measurements from high pressure-high temperature densifications. Moreover, coordination changes from tetrahedrally (GeO$_4$) to octahedrally (GeO$_6$) coordinated GeO$_2$ are accelerated with the heating during the compression.

In-situ X-ray scattering monitoring is carried out during temperature annealing on different densified SiO$_2$ glasses. Density fluctuations and intermediate range coherence from x-ray scattering (SAXS) and diffraction (WAXS) evidence a maximum in their evolution at the same relaxation time. These extrema confirm the existence of an intermediate transitory disordered state between the two more ordered high and low density amorphous states. We propose that the existence of this transitory state confirms the existence of two mega basin in the energy landscape and therefore an amorphous-amorphous transition. Including older Raman results, we show that this intermediate disorder state implies similar mechanisms at all length scales from a few angstroms to 5 nm.

Densified SiO2 glasses, obtained from different pressure and temperature routes have been annealed over a wide range of temperature far below the glass transition temperature (500$^\circ$C-900$^\circ$C). Hot and cold compressions were useful to separate the effects of pressure and the compression temperature. In-situ micro-Raman spectroscopy was used to follow the structural evolution during the thermal relaxation. A similar glass structure between the non-densified silica and the recovered densified silica after the temperature annealing demonstrates a perfect recovery of the non-densified silica glass structure. While the density decreases monotonically, the structural relaxation takes place through a more complex mechanism, which shows that density is not a sufficient parameter to fully characterize the structure of densified silica glass. The relaxation takes place through a transitory state, consisting in an increase of the network inhomogeneity, shown by an increase in intensity of the D2 band which is associated with 3 membered rings. The activation energy of these processes is 255$\pm$45 kJ/mol for the hot compressed samples. The kinetic is overall faster for the cold compressed samples. In that last case the relaxation is partially activated by internal stresses release.

Densified silica can be obtained by different pressure and temperature paths and for different stress conditions, hydrostatic or including shear. The density is usually the macroscopic parameter used to characterize the different compressed silica samples. The aim of our present study is to compare structural modifications for silica glass, densified from several routes. For this, densified silica glasses are prepared from cold and high temperature (up to 1020 $^\circ$C) compressions. The different densified glasses obtained in our study are characterized by micro-Raman spectroscopy. Intertetrahedral angles from the main band relative to the bending mode decreases and their values are larger for densified samples from high temperature compression than those samples from cold compression. The relative amount of 3-membered rings deduced from the D2 line area increases as a function of density for cold compression. The temperature increase during the compression process induces a decrease of the 3 fold ring population. Moreover, 3 fold rings are more deformed and stressed for densified samples at room temperature at the expense of those densified at high temperature. Temperature plays a main role in the reorganization structure during the densification and leads to obtaining a more relaxed structure with lower stresses than glasses densified from cold compression. The role of hydrostatic or non-hydrostatic applied stresses on the glass structure is discussed. From the Sen and Thorpe central force model, intertetrahedral angle average value and their distribution are estimated.

A new experimental setup combining X-Ray Photon Correlation Spectroscopy (XPCS) in the hard x-ray regime and a high-pressure sample environment is developed to monitor the pressure dependence of the internal motion of complex systems down to the atomic scale in the multi-GPa range, from room temperature to 600K. The high flux of coherent high energy x-rays at 4th generation synchrotron source solves the problems caused by the absorption of the Diamond Anvil Cells used to generate the high pressure, enabling the measurement of the intermediate scattering function over 6 orders of magnitude in time, from $10^{-3}$ s to $10^{3}$s. The constraints posed by the high-pressure generation such as the preservation of the x-ray's coherence, as well as the sample, pressure and temperature stability are discussed, and the feasibility of high pressure XPCS is demonstrated through results obtained on metallic glasses.

We describe a complete methodology to bridge the scales between nanoscale Molecular Dynamics and (micrometer) mesoscale Monte Carlo simulations in lipid membranes and vesicles undergoing phase separation, in which curving molecular species are furthermore embedded. To go from the molecular to the mesoscale, we notably appeal to physical renormalization arguments enabling us to rigorously infer the mesoscale interaction parameters from its molecular counterpart. We also explain how to deal with the physical timescales at stake at the mesoscale. Simulating the so-obtained mesoscale system enables us to equilibrate the long wavelengths of the vesicles of interest, up to the vesicle size. Conversely, we then backmap from the meso- to the nano- scale, which enables us to equilibrate in turn the short wavelengths down to the molecular length-scales. By applying our approach to the specific situation of the patterning of a vesicle membrane, we show that macroscopic membranes can thus be equilibrated at all length-scales in achievable computational time offering an original strategy to address the fundamental challenge of time scale in simulations of large bio-membrane systems.

In this follow-up to [M.G.~Cornet, P.~Torres, arXiv:2308.15603], where the $k$-tuple domination number and the 2-packing number in Kneser graphs $K(n,r)$ were studied, we are concerned with two variations, the $k$-domination number, ${\gamma_{k}}(K(n,r))$, and the $k$-tuple total domination number, ${\gamma_{t\times k}}(K(n,r))$, of $K(n,r)$. For both invariants we prove monotonicity results by showing that ${\gamma_{k}}(K(n,r))\ge {\gamma_{k}}(K(n+1,r))$ holds for any $n\ge 2(k+r)$, and ${\gamma_{t\times k}}(K(n,r))\ge {\gamma_{t\times k}}(K(n+1,r))$ holds for any $n\ge 2r+1$. We prove that ${\gamma_{k}}(K(n,r))={\gamma_{t\times k}}(K(n,r))=k+r$ when $n\geq r(k+r)$, and that in this case every ${\gamma_{k}}$-set and ${\gamma_{t\times k}}$-set is a clique, while ${\gamma_{k}}(r(k+r)-1,r)={\gamma_{t\times k}}(r(k+r)-1,r)=k+r+1$, for any $k\ge 2$. Concerning the 2-packing number, $\rho_2(K(n,r))$, of $K(n,r)$, we prove the exact values of $\rho_2(K(3r-3,r))$ when $r\ge 10$, and give sufficient conditions for $\rho_2(K(n,r))$ to be equal to some small values by imposing bounds on $r$ with respect to $n$. We also prove a version of monotonicity for the $2$-packing number of Kneser graphs., Comment: 15 pages, 3 tables

Glass forming liquids exhibit structural relaxation behaviors, reflecting underlying atomic rearrangements on a wide range of timescales. These behaviors play a crucial role in determining many material properties. However, the relaxation processes on the atomic scale are not well understood due to the experimental difficulties in directly characterizing the evolving correlations of atomic order in disordered systems. Here, taking the model system Ge15Te85, we demonstrate an experimental approach that probes the relaxation dynamics by scattering the coherent X-ray pulses with femtosecond duration produced by X-ray free electron lasers (XFELs). By collecting the summed speckle patterns from two rapidly successive, nearly identical X-ray pulses generated using a split-delay system, we can extract the contrast decay of speckle patterns originating from sample dynamics and observe the full decorrelation of local order on the sub-picosecond timescale. This provides the direct atomic-level evidence of fragile liquid behavior of Ge15Te85. Our results demonstrate the strategy for XFEL-based X-ray photon correlation spectroscopy (XPCS), attaining femtosecond temporal and atomic-scale spatial resolutions. This twelve orders of magnitude extension from the millisecond regime of synchrotron-based XPCS opens a new avenue of experimental studies of relaxation dynamics in liquids, glasses, and other highly disordered systems.

Here, we quantitatively estimate the impact of the inevitable Si surface passivation prior to III-V/Si hetero-epitaxy on the surface energy of the Si initial substrate, and explore its consequences for the description of wetting properties. Density Functional Theory is used to determine absolute surface energies of P- and Ga-passivated Si surfaces and their dependencies with the chemical potential. Especially, we show that, while a ~90 meV/$\r{A}^2$ surface energy is usually considered for the nude Si surface, surface passivation by Ga- or P- atoms leads to a strong stabilization of the surface, with a surface energy in the [50-75 meV/$\r{A}^2$] range. The all-ab initio analysis of the wetting properties indicate that a complete wetting situation would become possible only if the initial passivated Si surface could be destabilized by at least 15 meV/$\r{A}^2$ or if the III-V (001) surface could be stabilized by the same amount., Comment: 6 pages, 4 figures

While a number of bounds are known on the zero forcing number $Z(G)$ of a graph $G$ expressed in terms of the order of a graph and maximum or minimum degree, we present two bounds that are related to the (upper) total domination number $\gamma_t(G)$ (resp. $\Gamma_t(G)$) of $G$. We prove that $Z(G)+\gamma_t(G)\le n(G)$ and $Z(G)+\frac{\Gamma_t(G)}{2}\le n(G)$ holds for any graph $G$ with no isolated vertices of order $n(G)$. Both bounds are sharp as demonstrated by several infinite families of graphs. In particular, we show that every graph $H$ is an induced subgraph of a graph $G$ with $Z(G)+\frac{\Gamma_t(G)}{2}=n(G)$. Furthermore, we prove a characterization of graphs with power domination equal to $1$, from which we derive a characterization of the extremal graphs attaining the trivial lower bound $Z(G)\ge \delta(G)$. The class of graphs that appears in the corresponding characterizations is obtained by extending an idea from [D.D.~Row, A technique for computing the zero forcing number of a graph with a cut-vertex, Linear Alg.\ Appl.\ 436 (2012) 4423--4432], where the graphs with zero forcing number equal to $2$ were characterized., Comment: 18 pages, 1 figure

This paper considers multiple domination on Kneser graphs. We focus on $k$-tuple dominating sets, $2$-packings and the associated graph parameters $k$-tuple domination number and $2$-packing number. In particular, we compute the $2$-packing number of Kneser graphs $K(3r-2,r)$ and in odd graphs we obtain minimum $k$-tuple dominating sets of $K(7,3)$ and $K(11,5)$ for every $k$. Besides, we determine the Kneser graphs $K(n,r)$ with $k$-tuple domination number exactly $k+r$ and find all the minimum $k$-tuple dominating sets for these graphs, which generalize results for domination on Kneser graphs. Finally, we give a characterization of the $k$-tuple dominating sets of $K(n,2)$ in terms of the occurrences of the elements in $[n]$, which allows us to obtain minimum sized $k$-tuple dominating sets of $K(n,2)$ for $n\geq \Omega(\sqrt{k})$. Keywords: Kneser graphs, multiple domination, $k$-tuple domination, $2$-packings.