Reconstructed Rough Growing Interfaces; Ridgeline Trapping of Domain Walls

We investigate whether surface reconstruction order exists in stationary growing states, at all length scales or only below a crossover length, $l_{\rm rec}$. The later would be similar to surface roughness in growing crystal surfaces; below the equilibrium roughening temperature they evolve in a layer-by-layer mode within a crossover length scale $l_{\rm R}$, but are always rough at large length scales. We investigate this issue in the context of KPZ type dynamics and a checker board type reconstruction, using the restricted solid-on-solid model with negative mono-atomic step energies. This is a topology where surface reconstruction order is compatible with surface roughness and where a so-called reconstructed rough phase exists in equilibrium. We find that during growth, reconstruction order is absent in the thermodynamic limit, but exists below a crossover length $l_{\rm rec}>l_{\rm R}$, and that this local order fluctuates critically. Domain walls become trapped at the ridge lines of the rough surface, and thus the reconstruction order fluctuations are slaved to the KPZ dynamics

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Simulation of emotional behaviours for virtual agents with personalities

We have proposed an improved emotion model based on the well-known PAD model in affective computing and the NEO PI-R personality model in psychology. A novel parameter Emotion Intensity (EI) is proposed to represent different strength of anger, disgust, fear, happiness and sadness. Another novel Resistant formulation is also proposed to effectively simulate the complicated negative emotions. Eight experiments are conducted to simulate different emotional responses under different stimuli with different personality traits

Roadmap on data-centric materials science

Science is and always has been based on data, but the terms ‘data-centric’ and the ‘4th paradigm’ of materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift towards managing vast data collections, digital repositories, and innovative data analytics methods. The integration of artificial intelligence and its subset machine learning, has become pivotal in addressing all these challenges. This Roadmap on Data-Centric Materials Science explores fundamental concepts and methodologies, illustrating diverse applications in electronic-structure theory, soft matter theory, microstructure research, and experimental techniques like photoemission, atom probe tomography, and electron microscopy. While the roadmap delves into specific areas within the broad interdisciplinary field of materials science, the provided examples elucidate key concepts applicable to a wider range of topics. The discussed instances offer insights into addressing the multifaceted challenges encountered in contemporary materials research

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Atomic-Scale Identification of the Electrochemical Roughening of Platinum

Electrode degradation under oxidizing conditions is a major drawback for large-scale applications of platinumelectrocatalysts. Subjecting Pt(111) to oxidation−reduction cycles is known to lead to the growth of nanoislands. We study thisphenomenon using a combination of simultaneous in situ electrochemical scanning tunneling microscopy and cyclicvoltammetry. Here, we present a detailed analysis of the formed islands, deriving the (evolution of the) average island growthshape. From the island shapes, we determine the densities of atomic-scale defect sites, e.g., steps and facets, which show anexcellent correlation with the different voltammetric hydrogen adsorption peaks. Based on this combination of electrochemicalscanning tunneling microscopy (EC-STM) and CV data, we derive a detailed atomistic picture of the nanoisland evolutionduring potential cycling, delivering new insights into the initial stages of platinum electrode degradation

The dualism between adatom- and vacancy-based single crystal growth models

In homoepitaxial crystal growth, four basic growth morphologies (idealized growth modes) have been established that describe the deposition of atoms on single crystal surfaces: step-flow, layer-by-layer, mound formation, and random/self-affine growth. Mound formation leads to nano-scale surface patterning. However, the formation of (nano)-islands, patterns, and roughness occurs also during ion bombardment, electrochemical etching and oxidation/reduction cycling. Here we show, in analogy to many particle/anti-particle formalisms in physics, the existence of the dualism between individual adatom and single vacancy growth modes. We predict that all standard adatom growth modes do exist also in their counter, vacancy version. For the particular case of mound formation, we derive the theoretical equations and show the inverse similarity of the solution. We furthermore treat simultaneous growth by adatoms and vacancies, and derive the analytical solution of the growth shape evolution of the mounds. Finally, we present an experimental verification, in which both adatom and vacancy mound formation are active. The theoretically predicted mound shape nicely fits the experimental observation