Search

The comprehensive crystallographic, NMR and spectroscopic data reveals a united and a self-consistent picture of a symmetrical molecule with a low-barrier hydrogen-bond. The temperature dependence of the NMR properties confirms the existence of a thermally accessible vibrationally excited state for the bond and as other short hydrogen bonds show similar NMR behavior, it is likely the no 'strong' hydrogen bond of this sort has yet been discovered.

In this paper, an adaptive neural network controller is designed for non-strict feedback systems with full-state constraints. According to practical applications, both input saturation and unmodeled dynamics are also taken into account. By using a logarithm nonlinear mapping, non-strict feedback systems with full-state constraints can be converted to unconstrained ones, which may result in some exponential terms. Here, a new variable separation method is proposed based on Taylor's formula to cope with the exponential terms and non-strict structure. Then, the relationship between the norm of state vector and error functions is established. A hyperbolic tangent function and a dynamic signal are introduced to deal with input saturation and unmodeled dynamics, respectively. It is proved that all signals of the closed-loop system are uniformly ultimately bounded and the requirement of full-state constraints is satisfied. Two illustrative examples are provided to demonstrate the effectiveness of the presented method. [ABSTRACT FROM AUTHOR]

Various techniques have been used for management of congenital atlantoaxial dislocation. Recently, the reduction of atlantoaxial dislocation through a single posterior approach has attracted more and more attention. Here, we present a modified technique including direct interfacet release and distraction between C1 and C2 by a specially designed distractor, posterior internal fixation and bone graft fusion. The illustrated technique was performed in 15 consecutive patients, and the outcomes were recorded and analyzed. Follow-up ranged from 12 to 26 months. Clinical symptoms improved in 14 patients (93.3%) and were stable in 1 patient (6.7%). Radiologically, 60–100% reduction was achieved in 13 patients (86.6%). Bone fusion was obtained in all patients at 12 months after the operation. The two-tailed Wilcoxon signed-rank test was used to analyze the preoperative and postoperative Japanese Orthopedic Association scores (JOA), atlas-dens interval (ADI), and cervicomedullary angle (CMA) (P < 0.001). Our results suggested that this direct interfacet release and distraction technique with a specially designed C1–2 distractor can provide a definite effective C1–2 facet distraction and odontoid process restoration through a single posterior approach. [ABSTRACT FROM AUTHOR]

A major factor blocking the practical application of brain-computer interfaces (BCI) is the long calibration time. To obtain enough training trials, participants must spend a long time in the calibration stage. In this paper, we propose a new framework to reduce the calibration time through knowledge transferred from the electroencephalogram (EEG) of other subjects. We trained the motor recognition model for the target subject using both the target's EEG signal and the EEG signals of other subjects. To reduce the individual variation of different datasets, we proposed two data mapping methods. These two methods separately diminished the variation caused by dissimilarities in the brain activation region and the strength of the brain activation in different subjects. After these data mapping stages, we adopted an ensemble method to aggregate the EEG signals from all subjects into a final model. We compared our method with other methods that reduce the calibration time. The results showed that our method achieves a satisfactory recognition accuracy using very few training trials (32 samples). Compared with existing methods using few training trials, our method achieved much greater accuracy. Graphical abstract The framework of the proposed method. The workflow of the framework have three steps: 1, process each subjects EEG signals according to the target subject's EEG signal. 2, generate models from each subjects' processed signals. 3, ensemble these models to a final model, the final model is a model for the target subject. [ABSTRACT FROM AUTHOR]

Neuroplasticity, also known as brain plasticity, is an inclusive term that covers the permanent changes in the brain during the course of an individual's life, and neuroplasticity can be broadly defined as the changes in function or structure of the brain in response to the external and/or internal influences. Long-term potentiation (LTP), a well-characterized form of functional synaptic plasticity, could be influenced by rapid-frequency stimulation (or "tetanus") within in vivo human sensory pathways. Also, stochastic resonance (SR) has brought new insight into the field of visual processing for the study of neuroplasticity. In the present study, a brain-computer interface (BCI) intervention based on rapid and repetitive motion-reversal visual stimulation (i.e., a "tetanizing" stimulation) associated with spatiotemporal visual noise was implemented. The goal was to explore the possibility that the induction of LTP-like plasticity in the visual cortex may be enhanced by the SR formalism via changes in the amplitude of visual evoked potentials (VEPs) measured non-invasively from the scalp of healthy subjects. Changes in the absolute amplitude of P1 and N1 components of the transient VEPs during the initial presentation of the steady-state stimulation were used to evaluate the LTP-like plasticity between the non-noise and noise-tagged BCI interventions. We have shown that after adding a moderate visual noise to the rapid-frequency visual stimulation, the degree of the N1 negativity was potentiated following an ~40-min noise-tagged visual tetani. This finding demonstrated that the SR mechanism could enhance the plasticity-like changes in the human visual cortex. [ABSTRACT FROM AUTHOR]

As part of the Consortium for Advanced Simulation of Light Water Reactors, the subchannel code CTF is being used for single-phase and two-phase flow analysis under light water reactor operating conditions. Accurate determination of flow distribution, pressure drop, and void content is crucial for predicting margins to thermal crisis and ensuring more efficient plant performance. In preparation for the intended applications, CTF has been validated against data from experimental facilities comprising the General Electric (GE) 3 × 3 bundle, the boiling water reactor full-size fine-mesh bundle tests (BFBTs), the Risø tube, and the pressurized water reactor subchannel and bundle tests (PSBTs). Meanwhile, the licensed, well-recognized subchannel code VIPRE-01 was used to generate a baseline set of simulations for the targeted tests and solution parameters were compared to the CTF results. The flow split verification problem and single-phase GE 3 × 3 results are essentially in perfect agreement between the two codes. For the two-phase GE 3 × 3 cases, flow and quality discrepancies arise in the annular-mist flow regime, yet significant improvement is observed in CTF when void drift and two-phase turbulent mixing enhancement are considered. The BFBT pressure drop benchmark shows close agreement between predicted and measured results in general, although considerable overprediction by CTF is observed at relatively high void locations of the facility. This overestimation tendency is confirmed by the Risø cases. While overall statistics are satisfactory, both BFBT and PSBT bubbly-to-churn flow void contents are markedly overpredicted by CTF. The issues with two-phase closures such as turbulent mixing, interfacial and wall friction, and subcooled boiling heat transfer need to be addressed. Preliminary sensitivity studies are presented herein, but more advanced models and code stability analysis require further investigation. [ABSTRACT FROM AUTHOR]