Machine learning accelerated random structure searching: Application to yttrium superhydrides.

The search for new superhydrides, promising materials for both hydrogen storage and high temperature superconductivity, made great progress, thanks to atomistic simulations and Crystal Structure Prediction (CSP) algorithms. When they are combined with Density Functional Theory (DFT), these methods are highly reliable and often match a great part of the experimental results. However, systems of increasing complexity (number of atoms and chemical species) become rapidly challenging as the number of minima to explore grows exponentially with the number of degrees of freedom in the simulation cell. An efficient sampling strategy preserving a sustainable computational cost then remains to be found. We propose such a strategy based on an active-learning process where machine learning potentials and DFT simulations are jointly used, opening the way to the discovery of complex structures. As a proof of concept, this method is applied to the exploration of tin crystal structures under various pressures. We showed that the α phase, not included in the learning process, is correctly retrieved, despite its singular nature of bonding. Moreover, all the expected phases are correctly predicted under pressure (20 and 100 GPa), suggesting the high transferability of our approach. The method has then been applied to the search of yttrium superhydrides (YHx) crystal structures under pressure. The YH6 structure of space group Im-3m is successfully retrieved. However, the exploration of more complex systems leads to the appearance of a large number of structures. The selection of the relevant ones to be included in the active learning process is performed through the analysis of atomic environments and the clustering algorithm. Finally, a metric involving a distance based on x-ray spectra is introduced, which guides the structural search toward experimentally relevant structures. The global process (active-learning and new selection methods) is finally considered to explore more complex and unknown YHx phases, unreachable by former CSP algorithms. New complex phases are found, demonstrating the ability of our approach to push back the exponential wall of complexity related to CSP.

Interspecies radiative transition in warm and superdense plasma mixtures.

Superdense plasmas widely exist in planetary interiors and astrophysical objects such as brown-dwarf cores and white dwarfs. How atoms behave under such extreme-density conditions is not yet well understood, even in single-species plasmas. Here, we apply thermal density functional theory to investigate the radiation spectra of superdense iron-zinc plasma mixtures at mass densities of ρ = 250 to 2000 g cm-3 and temperatures of kT = 50 to 100 eV, accessible by double-shell-target implosions. Our ab initio calculations reveal two extreme atomic-physics phenomena-firstly, an interspecies radiative transition; and, secondly, the breaking down of the dipole-selection rule for radiative transitions in isolated atoms. Our first-principles calculations predict that for superdense plasma mixtures, both interatomic radiative transitions and dipole-forbidden transitions can become comparable to the normal intra-atomic Kα-emission signal. These physics phenomena were not previously considered in detail for extreme high-density plasma mixtures at super-high energy densities.

Quantifying the degree of locking in weakly forced stochastic systems.

Controlling an stochastic nonlinear system with a small amplitude signal is a fundamental problem with many practical applications. Quantifying locking is challenging, and current methods, such as spectral or correlation analysis, do not provide a precise measure of the degree of locking. Here we study locking in an experimental system, consisting of a semiconductor laser with optical feedback operated in the regime where it randomly emits abrupt spikes. To quantify the locking of the optical spikes to small electric perturbations, we use two measures, the success rate (SR) and the false positive rate (FPR). The SR counts the spikes that are emitted shortly after each perturbation, while the FPR counts the additional extra spikes. We show that the receiver operating characteristic (ROC) curve (SR versus FPR plot) uncovers parameter regions where the electric perturbations fully control the laser spikes, such that the laser emits, shortly after each perturbation, one and only one spike. To demonstrate the general applicability of the ROC analysis we also study a stochastic bistable system under square-wave forcing and show that the ROC curve allows identifying the parameters that produce best locking.

Differentiating resting brain states using ordinal symbolic analysis.

Symbolic methods of analysis are valuable tools for investigating complex time-dependent signals. In particular, the ordinal method defines sequences of symbols according to the ordering in which values appear in a time series. This method has been shown to yield useful information, even when applied to signals with large noise contamination. Here, we use ordinal analysis to investigate the transition between eyes closed (EC) and eyes open (EO) resting states. We analyze two electroencephalography datasets (with 71 and 109 healthy subjects) with different recording conditions (sampling rates and the number of electrodes in the scalp). Using as diagnostic tools the permutation entropy, the entropy computed from symbolic transition probabilities, and an asymmetry coefficient (that measures the asymmetry of the likelihood of the transitions between symbols), we show that the ordinal analysis applied to the raw data distinguishes the two brain states. In both datasets, we find that, during the EC-EO transition, the EO state is characterized by higher entropies and lower asymmetry coefficient, as compared to the EC state. Our results thus show that these diagnostic tools have the potential for detecting and characterizing changes in time-evolving brain states.

State space reconstruction of spatially extended systems and of time delayed systems from the time series of a scalar variable.

The space-time representation of high-dimensional dynamical systems that have a well defined characteristic time scale has proven to be very useful to deepen the understanding of such systems and to uncover hidden features in their output signals. By using the space-time representation many analogies between one-dimensional spatially extended systems (1D SESs) and time delayed systems (TDSs) have been found, including similar pattern formation and propagation of localized structures. An open question is whether such analogies are limited to the space-time representation, or it is also possible to recover similar evolutions in a low-dimensional pseudo-space. To address this issue, we analyze a 1D SES (a bistable reaction-diffusion system), a scalar TDS (a bistable system with delayed feedback), and a non-scalar TDS (a model of two delay-coupled lasers). In these three examples, we show that we can reconstruct the dynamics in a three-dimensional phase space, where the evolution is governed by the same polynomial potential. We also discuss the limitations of the analogy between 1D SESs and TDSs.

Experimental study of modulation waveforms for entraining the spikes emitted by a semiconductor laser with optical feedback.

The entrainment phenomenon, by which an oscillator adjusts its natural rhythm to an external periodic signal, has been observed in many natural systems. Recently, attention has focused on which are the optimal conditions for achieving entrainment. Here we use a semiconductor laser with optical feedback, operating in the low-frequency fluctuations (LFFs) regime, as a testbed for a controlled entrainment experiment. In the LFF regime the laser intensity displays abrupt spikes, which can be entrained to a weak periodic signal that directly modulates the laser pump current. We compare the performance of three modulation waveforms for producing 1:1 locking (one spike is emitted in each modulation cycle), as well as higher order locking regimes. We characterize the parameter regions where high-quality locking occurs, and those where the laser emits spikes which are not entrained to the external signal. The role of the modulation amplitude and frequency, and the role of the dc value of the laser pump current (that controls the natural spike frequency) in the entrainment quality are discussed.

Chiral magnetic-nanobiofluids for rapid electrochemical screening of enantiomers at a magneto nanocomposite graphene-paste electrode.

The development of highly sensitive and selective enantiomeric platforms towards the rapid screening of active pharmaceutical ingredients (APIs) is nowadays a crucial challenge in several fields related to pharmacology, biomedicine, biotechnology and (bio)sensors. Herein, it is presented a novel, facile and generic methodology focused on exploiting the synergistically and electrocatalytic properties of chiral magnetic-nanobiofluids (mNBFs) with electrochemical enantiobiosensing at a magneto nanocomposite graphene paste electrode (mNC-GPE). The feasibility of this approach has been validated by chirally recognizing tryptophan (TRP) enantiomers as a proof-of-concept. For this aim, a specific chiral mNBF based on an aqueous dispersion of cobalt ferrite loaded with gold nanoparticles carrying a thiolated ß-cyclodextrin (ß-CD-SH/Au/CoFe2O4-NPs) has been synthesized and used towards the supramolecular discrimination of TRP enantiomers at an advanced graphene-paste transducer via cyclic voltammetry. This strategy, which is the first demonstration of applicability of chiral mNBFs for electrochemical enantiorecognition, opens up new approaches into enantio(bio)sensing.

Experimental characterization of the transition to coherence collapse in a semiconductor laser with optical feedback.

Semiconductor lasers with time-delayed optical feedback display a wide range of dynamical regimes, which have found various practical applications. They also provide excellent testbeds for data analysis tools for characterizing complex signals. Recently, several of us have analyzed experimental intensity time-traces and quantitatively identified the onset of different dynamical regimes, as the laser current increases. Specifically, we identified the onset of low-frequency fluctuations (LFFs), where the laser intensity displays abrupt dropouts, and the onset of coherence collapse (CC), where the intensity fluctuations are highly irregular. Here we map these regimes when both, the laser current and the feedback strength vary. We show that the shape of the distribution of intensity fluctuations (characterized by the standard deviation, the skewness, and the kurtosis) allows to distinguish among noise, LFFs and CC, and to quantitatively determine (in spite of the gradual nature of the transitions) the boundaries of the three regimes. Ordinal analysis of the inter-dropout time intervals consistently identifies the three regimes occurring in the same parameter regions as the analysis of the intensity distribution. Simulations of the well-known time-delayed Lang-Kobayashi model are in good qualitative agreement with the observations.

Influence of point defects and impurities on the dynamical stability of δ-plutonium.

We use first-principles calculations to provide direct evidence of the effect of aluminum, gallium, iron and uranium on the dynamical stability of δ-plutonium. We first show that the δ phase is dynamically unstable at low temperature, as seen in experiments, and that this stability directly depends on the plutonium 5f orbital occupancies. Then, we demonstrate that both aluminum and gallium stabilize the δ phase, contrary to iron. As for uranium, which is created during self-irradiation and whose effect on plutonium has yet to be understood, we show that it leaves a few unstable vibrational modes and that higher concentrations lead to an almost complete stabilization. Finally, we provide an attempt at a consistent analysis of the experimental Pu-Ga phonon density of states. We show that the presence of gallium can reproduce only partially the experimental measurements, and we investigate how point defects, such as interstitials and vacancies, affect the calculated phonon density of states.

Metastatic neuroblastoma in infants: are survival rates excellent only within the stringent framework of clinical trials?

Introduction. SIOPEN INES protocol yielded excellent 5-year survival rates for MYCN-non-amplified metastatic neuroblastoma. Patients deemed ineligible due to lack or delay of MYCN status or late registration were treated, but not included in the study. Our goal was to analyse survival at 10 years among the whole population. Materials and methods. Italian and Spanish metastatic INES patients’ data are reported. SPSS 20.0 was used for statistical analysis. Results. Among 98 infants, 27 had events and 19 died, while 79 were disease free. Five- and 10-year event-free survival (EFS) were 73 and 70 %, and overall survival (OS) was 81 and 74 %, respectively. MYCN status was significant for EFS, but not for OS in multivariate analysis. Conclusions. The survival rates of patients who complied with all the inclusion criteria for INES trials are higher compared to those that included also not registered patients. Five-year EFS and OS for INES 99.2 were 87.8 and 95.7 %, while our stage 4s population obtained 78 and 87 %. Concerning 99.3, 5-year EFS and OS were 86.7 and 95.6 %, while for stage 4 we registered 61 and 68 %. MYCN amplification had a strong impact on prognosis and therefore we consider it unacceptable that many patients were not studied for MYCN and probably inadequately treated. Ten-year survival rates were shown to decrease: EFS from 73 to 70 % and OS from 81 to 74 %, indicating a risk of late events, particularly in stage 4s. Population-based registries like European ENCCA WP 11-task 11 will possibly clarify these data (AU)

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Metastatic neuroblastoma in infants: are survival rates excellent only within the stringent framework of clinical trials?

INTRODUCTION: SIOPEN INES protocol yielded excellent 5-year survival rates for MYCN-non-amplified metastatic neuroblastoma. Patients deemed ineligible due to lack or delay of MYCN status or late registration were treated, but not included in the study. Our goal was to analyse survival at 10 years among the whole population. MATERIALS AND METHODS: Italian and Spanish metastatic INES patients' data are reported. SPSS 20.0 was used for statistical analysis. RESULTS: Among 98 infants, 27 had events and 19 died, while 79 were disease free. Five- and 10-year event-free survival (EFS) were 73 and 70 %, and overall survival (OS) was 81 and 74 %, respectively. MYCN status was significant for EFS, but not for OS in multivariate analysis. CONCLUSIONS: The survival rates of patients who complied with all the inclusion criteria for INES trials are higher compared to those that included also not registered patients. Five-year EFS and OS for INES 99.2 were 87.8 and 95.7 %, while our stage 4s population obtained 78 and 87 %. Concerning 99.3, 5-year EFS and OS were 86.7 and 95.6 %, while for stage 4 we registered 61 and 68 %. MYCN amplification had a strong impact on prognosis and therefore we consider it unacceptable that many patients were not studied for MYCN and probably inadequately treated. Ten-year survival rates were shown to decrease: EFS from 73 to 70 % and OS from 81 to 74 %, indicating a risk of late events, particularly in stage 4s. Population-based registries like European ENCCA WP 11-task 11 will possibly clarify these data.

Quantitative identification of dynamical transitions in a semiconductor laser with optical feedback.

Identifying transitions to complex dynamical regimes is a fundamental open problem with many practical applications. Semi- conductor lasers with optical feedback are excellent testbeds for studying such transitions, as they can generate a rich variety of output signals. Here we apply three analysis tools to quantify various aspects of the dynamical transitions that occur as the laser pump current increases. These tools allow to quantitatively detect the onset of two different regimes, low-frequency fluctuations and coherence collapse, and can be used for identifying the operating conditions that result in specific dynamical properties of the laser output. These tools can also be valuable for analyzing regime transitions in other complex systems.

Emergence of spike correlations in periodically forced excitable systems.

In sensory neurons the presence of noise can facilitate the detection of weak information-carrying signals, which are encoded and transmitted via correlated sequences of spikes. Here we investigate the relative temporal order in spike sequences induced by a subthreshold periodic input in the presence of white Gaussian noise. To simulate the spikes, we use the FitzHugh-Nagumo model and to investigate the output sequence of interspike intervals (ISIs), we use the symbolic method of ordinal analysis. We find different types of relative temporal order in the form of preferred ordinal patterns that depend on both the strength of the noise and the period of the input signal. We also demonstrate a resonancelike behavior, as certain periods and noise levels enhance temporal ordering in the ISI sequence, maximizing the probability of the preferred patterns. Our findings could be relevant for understanding the mechanisms underlying temporal coding, by which single sensory neurons represent in spike sequences the information about weak periodic stimuli.

The independent role of prenatal and postnatal exposure to active and passive smoking on the development of early wheeze in children.

Maternal smoking during pregnancy increases childhood asthma risk, but health effects in children of nonsmoking mothers passively exposed to tobacco smoke during pregnancy are unclear. We examined the association of maternal passive smoking during pregnancy and wheeze in children aged ≤2 years.Individual data of 27 993 mother-child pairs from 15 European birth cohorts were combined in pooled analyses taking into consideration potential confounders.Children with maternal exposure to passive smoking during pregnancy and no other smoking exposure were more likely to develop wheeze up to the age of 2 years (OR 1.11, 95% CI 1.03-1.20) compared with unexposed children. Risk of wheeze was further increased by children's postnatal passive smoke exposure in addition to their mothers' passive exposure during pregnancy (OR 1.29, 95% CI 1.19-1.40) and highest in children with both sources of passive exposure and mothers who smoked actively during pregnancy (OR 1.73, 95% CI 1.59-1.88). Risk of wheeze associated with tobacco smoke exposure was higher in children with an allergic versus nonallergic family history.Maternal passive smoking exposure during pregnancy is an independent risk factor for wheeze in children up to the age of 2 years. Pregnant females should avoid active and passive exposure to tobacco smoke for the benefit of their children's health.

Unveiling Temporal Correlations Characteristic of a Phase Transition in the Output Intensity of a Fiber Laser.

We use advanced statistical tools of time-series analysis to characterize the dynamical complexity of the transition to optical wave turbulence in a fiber laser. Ordinal analysis and the horizontal visibility graph applied to the experimentally measured laser output intensity reveal the presence of temporal correlations during the transition from the laminar to the turbulent lasing regimes. Both methods unveil coherent structures with well-defined time scales and strong correlations both, in the timing of the laser pulses and in their peak intensities. Our approach is generic and may be used in other complex systems that undergo similar transitions involving the generation of extreme fluctuations.

A surface confined yttrium(iii) bis-phthalocyaninato complex: a colourful switch controlled by electrons.

SAMs of a Y(iii) double-decker complex on ITO have been prepared and their electrical and optical properties explored, exhibiting three accessible stable redox states with characteristic absorption bands in the visible spectra, corresponding to three complementary colors (i.e., green, blue and red). These absorption bands are exploited as output signals of this robust ternary electrochemical switch, behaving hence as an electrochromic molecular-based device.

Early-life house dust mite allergens, childhood mite sensitization, and respiratory outcomes.

BACKGROUND: Exposure to indoor allergens during early life may play a role in the development of the immune system and inception of asthma. OBJECTIVE: To describe the house dust mite (HDM) allergen concentrations in bedroom dust during early life and to evaluate its associations with HDM sensitization, wheezing, and asthma, from birth to school age, in 5 geographically spread European birth cohorts. METHODS: We included 4334 children from INMA-Menorca (Spain), BAMSE (Sweden), LISAplus and MAS (Germany), and PIAMA-NHS (the Netherlands). Dust samples were collected from bedrooms during early life and analyzed for Dermatophagoides pteronyssinus (Der p1) and Dermatophagoides farinae (Der f1). HDM concentrations were divided into four categories. Sensitization was determined by specific IgE. Wheezing and asthma information up to 8/10 years was collected through questionnaires. We performed mixed-effects logistic regression models and expressed associations as odds ratios with 95% confidence intervals. RESULTS: House dust mite concentrations varied across cohorts. Mean allergen concentrations were highest in INMA-Menorca (geometric mean (GM) Der p1 = 3.3 µg/g) and LISAplus (GM Der f1 = 2.1 µg/g) and lowest in BAMSE (GM Der p1 = 0.1 µg/g, Der f1 = 0.3 µg/g). Moderate and high HDM concentrations were significantly (P-values < 0.05) associated with 50-90% higher prevalence of HDM sensitization. No significant associations were observed with respiratory outcomes. CONCLUSION: Our study based on geographically spread regions, a large sample size, and a wide range of allergen concentration shows that HDM allergen concentrations vary across regions and that exposure during early life plays a role in the development of allergic sensitization but not in the development of respiratory outcomes.

Effects of periodic forcing on the temporally correlated spikes of a semiconductor laser with feedback.

Optical excitable devices that mimic neuronal behavior can be building-blocks of novel, brain-inspired information processing systems. A relevant issue is to understand how such systems represent, via correlated spikes, the information of a weak external input. Semiconductor lasers with optical feedback operating in the low frequency fluctuations regime have been shown to display optical spikes with intrinsic temporal correlations similar to those of biological neurons. Here we investigate how the spiking laser output represents a weak periodic input that is implemented via direct modulation of the laser pump current. We focus on understanding the influence of the modulation frequency. Experimental sequences of inter-spike-intervals (ISIs) are recorded and analyzed by using the ordinal symbolic methodology that identifies and characterizes serial correlations in datasets. The change in the statistics of the various symbols with the modulation frequency is empirically shown to be related to specific changes in the ISI distribution, which arise due to different phase-locking regimes. A good qualitative agreement is also found between simulations of the Lang and Kobayashi model and observations. This methodology is an efficient way to detect subtle changes in noisy correlated ISI sequences and may be applied to investigate other optical excitable devices.