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<div> <div> <div> <p>In this study, we extend the scope of the many-body TTM-nrg and MB-nrg potential energy functions (PEFs), originally introduced for halide ion–water and alkali-metal ion–water interactions, to the modeling of carbon dioxide (CO₂) and water (H₂O) mixtures as prototypical examples of molecular fluids. Both TTM-nrg and MB-nrg PEFs are derived entirely from electronic structure data obtained at the coupled cluster level of theory and are, by construction, compatible with MB-pol, a many-body PEF that has been shown to accurately reproduce the properties of water. Although both TTM-nrg and MB-nrg PEFs adopt the same functional forms for describing permanent electrostatics, polarization, and dispersion, they differ in the representation of short-range contributions, with the TTM-nrg PEFs relying on conventional Born-Mayer expressions and the MB-nrg PEFs employing multidimensional permutationally invariant polynomials. By providing a physically correct description of many-body effects at both short and long ranges, the MB-nrg PEFs are shown to quantitatively represent the global potential energy surfaces of the CO₂–CO₂ and CO₂–H₂O dimers and the energetics of small clusters as well as to correctly reproduce various properties in both gas and liquid phases. Building upon previous studies of aqueous systems, our analysis provides further evidence for the accuracy and efficiency of the MB-nrg framework in representing molecular interactions in fluid mixtures at different temperature and pressure conditions. </p> </div> </div> </div>

BackgroundRapid-onset obesity with hypothalamic dysfunction, hypoventilation and autonomic dysregulation (ROHHAD) is a rare disease with a high mortality rate. Although nocturnal hypoventilation (NH) is central to ROHHAD, the evolution of sleep disordered breathing (SDB) is not well studied. The aim of the study was to assess early manifestations of SDB and their evolution in ROHHAD syndrome.MethodsRetrospective study of children with ROHHAD at two Canadian centers. All children with suspected ROHHAD at presentation underwent polysomnography (PSG) to screen for nocturnal hypoventilation. PSG findings at baseline and follow-up were collected. Interventions and diagnostic test results were recorded.ResultsSix children were included. The median age of rapid onset obesity and nocturnal hypoventilation (NH) was 3.5 and 7.2 years respectively. On initial screening for ROHHAD 4/6 (66.7 %) children had obstructive sleep apnea (OSA), 1/6 (16.7 %) had NH and 1/6 (16.7 %) had both OSA and NH. Follow up PSGs were performed in 5/6 children as one child died following a cardiorespiratory arrest. All children at follow up had NH and required non-invasive positive pressure ventilation. Additionally, 3/6 (50 %) children demonstrated irregular breathing patterns during wakefulness.ConclusionsChildren with ROHHAD may initially present with OSA and only develop NH later as well as dysregulation of breathing during wakefulness. The recognition of the spectrum of respiratory abnormalities at presentation and over time may be important in raising the index of suspicion of ROHHAD. Early recognition and targeted therapeutic interventions may limit morbidity and mortality associated with ROHHAD.

We describe an approach to textual inference that improves alignments at both the typed dependency level and at a deeper semantic level. We present a machine learning approach to alignment scoring, a stochastic search procedure, and a new tool that finds deeper semantic alignments, allowing rapid development of semantic features over the aligned graphs. Further, we describe a complementary semantic component based on natural logic, which shows an added gain of 3.13% accuracy on the RTE3 test set.

To investigate the contribution of vascular and metabolic stimuli to the sustained hyperpnea after exercise, the respiratory effects of obstructing and then releasing the femoral blood flow were recorded in 15 normal volunteers during recovery from steady-state cycle exercise (80 W). Obstruction was achieved using cuffs around the upper thighs, inflated for the first 2 min of recovery to a pressure of 200 mmHg. Cuff inflation significantly reduced ventilation during recovery compared with control (P less than 0.001); the subsequent release of pressure was accompanied by an increase in ventilation (averaging 3.2 l/min), which began on the first breath after release. This preceded a rise in end-tidal CO2 (maximum 8.3 Torr increase), which first became significant on the fourth breath after release and led to a further rise in ventilation. The first-breath increase in ventilation after cuff release persisted, although slightly attenuated (averaging 2.5 l/min), in additional experiments with inspired O2 fraction of 1.0. The pattern of ventilatory response was also similar when the experiments were performed with 5% CO2 in air as the inspirate. The immediate rise in ventilation on cuff release, together with the persistent response on 100% O2, suggests that the vascular changes resulting from cuff release exert an influence on ventilation independent of the effects of released metabolites on the known chemoreceptors. The persistence of the response on 5% CO2 indicates that CO2-sensitive lung afferents do not have a major role in these responses.

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We describe two approaches to reducing human fatigue in Interactive Evolutionary Computation (IEC). A predictor function is used to estimate the human user's score, thus reducing the amount of effort required by the human user during the evolution process. The fuzzy system and four machine learning classifier algorithms are presented. Their performance in a real-world application, the IEC-based design of a micromachine resonating mass, is evaluated. The fuzzy system was composed of four simple rules, but was able to accurately predict the user's score 77% of the time on average. This is equivalent to a 51% reduction of human effort compared to using IEC without the predictor. The four machine learning approaches tested were k-nearest neighbors, decision tree, AdaBoosted decision tree, and support vector machines. These approaches achieved good accuracy on validation tests, but because of the great diversity in user scoring behavior, were unable to achieve equivalent results on the user test data.