We consider 2D Heisenberg antiferromagnets on a triangular lattice with spatially anisotropic interactions in a high magnetic field close to the saturation. We show that this system possess rich phase diagram in field/anisotropy plane due to competition between classical and quantum orders: an incommensurate noncoplanar spiral state, which is favored classically, and a commensurate co-planar state, which is stabilized by quantum fluctuations. We show that the transformation between these two states is highly non-trivial and involves two intermediate phases -the phase with co-planar incommensurate spin order and the one with non-coplanar double-Q spiral order. The transition between the two co-planar states is of commensurateincommensurate type, not accompanied by softening of spin-wave excitations. We show that a different sequence of transitions holds in triangular antiferromagnets with exchange anisotropy, such as Ba3CoSb2O9.Introduction. The field of frustrated quantum magnetism witnessed a remarkable revival of interest in the last few years due to rapid progress in synthesis of new materials and in understanding previously unknown states of matter. The two main lines of research in the field are searches for spin-liquid phases and for new ordered phases with highly non-trivial spin structures [1]. For the latter, the most promising system is a 2D Heisenberg antiferromagnet on a triangular lattice in a finite magnetic field, as this system is known to possess an "accidental" classical degeneracy: every classical spin configuration with a triad of neighboring spins satisfying S r + S r+δ1 + S r+δ2 = h/(3J), where J is the exchange interaction, belongs to the ground state manifold.An infinite degeneracy, however, holds only for an ideal Heisenberg system with isotropic nearest-neighbor interaction. Real systems have either spatial anisotropy of exchange interactions, as in Cs 2 CuCl 4 [2, 3] and Cs 2 CuBr 4 [4-6] for which the interaction J on horizontal bonds is larger than J on diagonal bonds (see insert in Fig. 1), or exchange anisotropy in spin space, as in Ba 3 CoSb 2 O 9 , for which J z < J ⊥ = J (an easy plane anisotropy) [7][8][9]. An anisotropy of either type breaks accidental degeneracy already at a classical level and for fields h = hẑ slightly below the saturation field h sat selects a non-coplanar cone state with

Ultrafast carrier relaxation dynamics in fluorescent carbon nanodots is investigated by femtosecond transient absorption spectra at different pH environments so as to understand the mechanism of fluorescence for the first time. Utilizing multi-wavelength global analysis to fit the measured signal via a sequential model, four different relaxation channels are found, which are attributed to electron-electron scattering and surface state trapping, optical phonon scattering, acoustic phonon scattering and electron-hole recombination respectively. The results reveal that the surface states are mainly composed of different oxygen-containing functional groups (epoxy, carbonyl and carboxyl) and carbon atoms on the edge of the carbon backbone and can effectively trap a large number of photo-excited electrons. The deprotonation of carboxyl groups at high pH will change the distribution of π electron cloud density between the carbon backbone and surface states and consequently, compared with the excited electrons in the acidic and neutral environments, those in the alkaline environment can be more easily trapped by the surface within 1 ps, thereby giving rise to stronger fluorescence emission.

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One-dimensional (1-D) arterial blood flow modelling was tested in a series of idealized vascular geometries representing the abdominal aorta, common carotid and iliac arteries with different sizes of stenoses and/or aneurysms. Three-dimensional (3-D) modelling and in vitro measurements were used as ground truth to assess the accuracy of 1-D model pressure and flow waves. The 1-D and 3-D formulations shared identical boundary conditions and had equivalent vascular geometries and material properties. The parameters of an experimental set-up of the abdominal aorta for different aneurysm sizes were matched in corresponding 1-D models. Results show the ability of 1-D modelling to capture the main features of pressure and flow waves, pressure drop across the stenoses and energy dissipation across aneurysms observed in the 3-D and experimental models. Under physiological Reynolds numbers ( Re ), root mean square errors were smaller than 5.4% for pressure and 7.3% for the flow, for stenosis and aneurysm sizes of up to 85% and 400%, respectively. Relative errors increased with the increasing stenosis and aneurysm size, aneurysm length and Re , and decreasing stenosis length. All data generated in this study are freely available and provide a valuable resource for future research.

One of the European gold standard measurement of vascular ageing, a risk factor for cardiovascular disease, is the carotid-femoral pulse wave velocity (cfPWV), which requires an experienced operator to measure pulse waves at two sites. In this work, two machine learning pipelines were proposed to estimate cfPWV from the peripheral pulse wave measured at a single site, the radial pressure wave measured by applanation tonometry. The study populations were the Twins UK cohort containing 3,082 subjects aged from 18 to 110 years, and a database containing 4,374 virtual subjects aged from 25 to 75 years. The first pipeline uses Gaussian process regression to estimate cfPWV from features extracted from the radial pressure wave using pulse wave analysis. The mean difference and upper and lower limits of agreement (LOA) of the estimation on the 924 hold-out test subjects from the Twins UK cohort were 0.2 m/s, and 3.75 m/s & -3.34 m/s, respectively. The second pipeline uses a recurrent neural network (RNN) to estimate cfPWV from the entire radial pressure wave. The mean difference and upper and lower LOA of the estimation on the 924 hold-out test subjects from the Twins UK cohort were 0.05 m/s, and 3.21 m/s & -3.11m/s, respectively. The percentage error of the RNN estimates on the virtual subjects increased by less than 2% when adding 20% of random noise to the pressure waveform. These results show the possibility of assessing the vascular ageing using a single peripheral pulse wave (e.g. the radial pressure wave), instead of cfPWV. The proposed code for the machine learning pipelines is available from the following online depository (https://github.com/WeiweiJin/Estimate-Cardiovascular-Risk-from-Pulse-Wave-Signal).