Dynamical Reweighting for Biased Rare Event Simulations.

Dynamical reweighting techniques aim to recover the correct molecular dynamics from a simulation at a modified potential energy surface. They are important for unbiasing enhanced sampling simulations of molecular rare events. Here, we review the theoretical frameworks of dynamical reweighting for modified potentials. Based on an overview of kinetic models with increasing level of detail, we discuss techniques to reweight two-state dynamics, multistate dynamics, and path integrals. We explore the natural link to transition path sampling and how the effect of nonequilibrium forces can be reweighted. We end by providing an outlook on how dynamical reweighting integrates with techniques for optimizing collective variables and with modern potential energy surfaces.

Inequality of opportunity in the double burden of malnutrition in Mexico.

This paper proposes a pseudo-birth-cohort approach to deal with a lack of longitudinal data to measure health inequities over time. Using Roemer's framework for inequality of opportunity, this study measures ex-ante and ex-post inequalities in malnutrition, a concept that spans both sides of the nutrition continuum. The total contribution of observed circumstances and the direct contribution of observed efforts to the variation of malnutrition are disentangled for people born between 1983 and 1988 in Mexico. Results indicate that inequality of opportunity has been persistent across this 30-year lifespan for that cohort. Some evidence suggests that a lack of opportunities has been transmitted from parents to children and that people's circumstances account for most of the explained variation in the double burden of malnutrition. However, stratifying the analysis by sex shows that efforts account for more of the explained variation of inequality of opportunity for women in their middle adulthood than for men in most of the outcomes analyzed.

Multisensory and biomechanical influences on postural control in children.

Children's ability to maintain balance requires effective integration of multisensory and biomechanical information. The current project examined the interaction between such sensory inputs, manipulating visual input (presence vs. absence), haptic (somatosensory) input (presence vs. absence of contact with a stable or unstable finger support surface), and biomechanical (sensorimotor) input (varying stance widths). Analyses of mean velocity of the center of pressure and the percentage stability gain highlighted the role of varying multisensory inputs in postural control. Developmentally, older children (6-11 years) showed a multisensory integration advantage compared with their younger counterparts (3-5.9 years), with the impact of varying sensory inputs more closely akin to that seen in adults. Subsequent analyses of the impact of anthropometric individual difference parameters (e.g., height, leg length, weight, areas of base of support) revealed a shifting pattern across development. For younger children, these parameters were positively related to postural stability across experimental conditions (i.e., increasing body size was related to increasing postural control). This pattern transitioned for older children, who showed a nonsignificant relation between body size and balance. Interestingly, because adults show a negative relation between anthropometric factors and stability (i.e., increasing body size is related to decreasing postural control), this shift for the older children can be seen as a developmental transition from child-like to adult-like balance control.

LncRNA-protein interaction prediction with reweighted feature selection.

LncRNA-protein interactions are ubiquitous in organisms and play a crucial role in a variety of biological processes and complex diseases. Many computational methods have been reported for lncRNA-protein interaction prediction. However, the experimental techniques to detect lncRNA-protein interactions are laborious and time-consuming. Therefore, to address this challenge, this paper proposes a reweighting boosting feature selection (RBFS) method model to select key features. Specially, a reweighted apporach can adjust the contribution of each observational samples to learning model fitting; let higher weights are given more influence samples than those with lower weights. Feature selection with boosting can efficiently rank to iterate over important features to obtain the optimal feature subset. Besides, in the experiments, the RBFS method is applied to the prediction of lncRNA-protein interactions. The experimental results demonstrate that our method achieves higher accuracy and less redundancy with fewer features.

Brain and Behavioral Evidence for Reweighting of Vestibular Inputs with Long-Duration Spaceflight.

Microgravity alters vestibular signaling. In-flight adaptation to altered vestibular afferents is reflected in post-spaceflight aftereffects, evidenced by declines in vestibularly mediated behaviors (e.g., walking/standing balance), until readaptation to Earth's 1G environment occurs. Here we examine how spaceflight affects neural processing of applied vestibular stimulation. We used fMRI to measure brain activity in response to vestibular stimulation in 15 astronauts pre- and post-spaceflight. We also measured vestibularly-mediated behaviors, including balance, mobility, and rod-and-frame test performance. Data were collected twice preflight and four times postflight. As expected, vestibular stimulation at the preflight sessions elicited activation of the parietal opercular area ("vestibular cortex") and deactivation of somatosensory and visual cortices. Pre- to postflight, we found widespread reductions in this somatosensory and visual cortical deactivation, supporting sensory compensation and reweighting with spaceflight. These pre- to postflight changes in brain activity correlated with changes in eyes closed standing balance, and greater pre- to postflight reductions in deactivation of the visual cortices associated with less postflight balance decline. The observed brain changes recovered to baseline values by 3 months postflight. Together, these findings provide evidence for sensory reweighting and adaptive cortical neuroplasticity with spaceflight. These results have implications for better understanding compensation and adaptation to vestibular functional disruption.

Reverberation-Robust Self-Calibration and Synchronization of Distributed Microphone Arrays by Mitigating Heteroscedasticity and Outlier Occurrence in TDoA Measurements.

The network of distributed microphone arrays is usually established in an ad hoc manner; hence, network parameters such as the mutual positioning and rotation of the arrays, positions of sources, and synchronization of their recording onset times are initially unknown. In this article, we consider the problem of passively jointly self-calibrating and synchronizing distributed arrays in reverberant rooms. We use a typical two-step approach where, initially, the relative geometry of the network is estimated using Direction of Arrival (DoA) measurements. Subsequently, the absolute scale and synchronization parameters are estimated using Time Difference of Arrival (TDoA) measurements. This article presents methods to improve the robustness and accuracy of estimation of the absolute geometric scaling and synchronization parameters in reverberant conditions, in which TDoA measurements do not follow a normal distribution; furthermore, outliers often occur. To remedy these issues, we propose a Weighted Least Squares (WLS) estimator and schema for weighting the TDoA measurements to increase the estimation accuracy from heteroscedastic TDoA measurements. In addition, we propose an iterative reweighing algorithm with a binary weight to detect and reject TDoA outliers, which exploits the residuals of the parametric model in the least absolute value minimization. A numerical evaluation shows significant improvements in the proposed method over the state of the art in terms of the relative scaling error and mean absolute value of the synchronization parameters.

Simulation of ligand dissociation kinetics from the protein kinase PYK2.

Early-stage drug discovery projects often focus on equilibrium binding affinity to the target alongside selectivity and other pharmaceutical properties. The kinetics of drug binding are ignored but can have significant influence on drug efficacy. Therefore, increasing attention has been paid on evaluating drug-binding kinetics early in a drug discovery process. Simulating drug-binding kinetics at the atomic level is challenging for the long time scale involved. Here, we used the transition-based reweighting analysis method (TRAM) with the Markov state model to study the dissociation of a ligand from the protein kinase PYK2. TRAM combines biased and unbiased simulations to reduce computational costs. This work used the umbrella sampling technique for the biased simulations. Although using the potential of mean force from umbrella sampling simulations with the transition-state theory over-estimated the dissociation rate by three orders of magnitude, TRAM gave a dissociation rate within an order of magnitude of the experimental value.

Generalizability of ORIENT-11 trial results to a US standard-of-care cohort with advanced non-small-cell lung cancer.

Aim: This retrospective study estimated efficacy and safety of sintilimab + pemetrexed + platinum (SPP) versus placebo + pemetrexed + platinum (PPP) in untreated locally advanced/metastatic, nonsquamous non-small-cell lung cancer (NSCLC), after adjusting each ORIENT-11 trial patient's contribution to ORIENT-11 data based on characteristics of a target US population. Materials & methods: The target US population (n = 557) was selected from a real-world deidentified advanced NSCLC database based on key ORIENT-11 eligibility criteria. Inverse probability weights for ORIENT-11 patients (n = 397) relative to US patients were calculated. Efficacy and safety of SPP versus PPP were adjusted by inverse probability weights. Results: After adjustment, progression-free survival remained superior for SPP. Other efficacy and safety outcomes were consistent. Conclusion: These results provide evidence on how the effects observed with SPP in ORIENT-11 could translate to a US population with untreated locally advanced/metastatic nonsquamous NSCLC.

Sintilimab is an immunotherapy drug that was successfully developed and tested in China for untreated locally advanced/metastatic nonsquamous non-small-cell lung cancer. To assess if results from the Chinese ORIENT-11 trial are applicable to the US population, this study used US real-world patient data to adjust the ORIENT-11 trial analysis. After adjustment, progression-free survival benefit observed in ORIENT-11 with the addition of sintilimab to standard chemotherapy remained superior, and other efficacy and safety end points were consistent. This finding may help inform clinical decisions about the applicability of ORIENT-11 trial results to US patients with untreated locally advanced/metastatic nonsquamous NSCLC. In addition, this study offers another way real-world evidence can be applied to help complement clinical trial evidence and optimize treatment decisions.

Retention Effects of Long-Term Balance Training with Vibrotactile Sensory Augmentation in Healthy Older Adults.

Vibrotactile sensory augmentation (SA) decreases postural sway during real-time use; however, limited studies have investigated the long-term effects of training with SA. This study assessed the retention effects of long-term balance training with and without vibrotactile SA among community-dwelling healthy older adults, and explored brain-related changes due to training with SA. Sixteen participants were randomly assigned to the experimental group (EG) or control group (CG), and trained in their homes for eight weeks using smart-phone balance trainers. The EG received vibrotactile SA. Balance performance was assessed before, and one week, one month, and six months after training. Functional MRI (fMRI) was recorded before and one week after training for four participants who received vestibular stimulation. Both groups demonstrated significant improvement of SOT composite and MiniBESTest scores, and increased vestibular reliance. Only the EG maintained a minimal detectable change of 8 points in SOT scores six months post-training and greater improvements than the CG in MiniBESTest scores one month post-training. The fMRI results revealed a shift from activation in the vestibular cortex pre-training to increased activity in the brainstem and cerebellum post-training. These findings showed that additional balance improvements were maintained for up to six months post-training with vibrotactile SA for community-dwelling healthy older adults.

A comparison of approaches to reweighting anthropometric data.

The objective of this work is to identify the most effective techniques for reweighting anthropometric data such that it accurately represents a target user population. Seven methods are compared, including uniform weighting, stratification and permutations of nearest neighbour (NN) reweighting. The analysis illuminates the performance of existing and novel approaches to reweighting data specifically for approximating body size and shape ('anthropometry'). While uniform weighting and stratified sampling are often used in this field, the present analysis indicates that lower-order NN approaches will produce more representative results. Although anthropometric data are crucial to the design of artefacts, tasks and environments, finding appropriate representative data is challenging. Designers and ergonomists are unlikely to find data that are simultaneously accessible, up-to-date, detailed and from the relevant population. The application of new statistical weights - reweighting - is one useful strategy for meeting this shortfall. This research indicates the best methods for reweighting and provides guidance for sampling strategies in future data collection efforts. Practitioner Summary: Reweighting anthropometric data is one strategy for matching available data to a target user population. Stratified sampling is often used as the method for calculating weights, but it has been shown to produce inaccurate estimates. This research examines seven strategies and finds low-order NN approaches are the more accurate methods.

Contribution of vision and tactile sensation on body sway during quiet stance.

[Purpose] This study examines the contribution of vision and tactile sensation on body sway during quiet stance. [Participants and Methods] Sixteen healthy participants maintained quiet stance. The mean distance between the neutral center of pressure (COP) and that at the peak deviated position, indicating how quickly humans initiate the swaying of the body back to the neutral position, was calculated (COPpeak). [Results] The displacement of the COP in both the anterior-posterior and medial-lateral axes was greater when vision was occluded. The anterior or posterior COPpeak was also greater when vision was occluded. The leftward COPpeak was greater when the tactile sensation of the sole was masked. Visual occlusion decreased the tactile perception threshold of the sole. There was no significant interaction between the effect of vision and that of tactile sensation on body sway during quiet stance. [Conclusion] Vision plays a role in returning the body to the neutral position, particularly in the anterior-posterior axis. Tactile sensation contributes particularly to recovery from the leftward body sway during quiet stance. Tactile sensitivity is enhanced by visual occlusion through inter-modal reweighting. However, inter-modal reweighting between vision and tactile sensation is not specifically for postural control during quiet stance.

Progressive Visual Occlusion and Postural Control Responses in Individuals With and Without Chronic Ankle Instability.

CONTEXT: Prophylactic and rehabilitative balance training is needed to maximize postural control and develop appropriate sensory organization strategies. Partially occluding vision during functional exercise may promote appropriate sensory organization strategies, but little is known about the influence of partially occluded vision on postural control in those with and without a history of musculoskeletal injury. OBJECTIVE: To determine the effect of increasing levels of visual occlusion on postural control in a heterogeneous sample of those with and without chronic ankle instability (CAI). The secondary objective was to explore postural control responses to increasing levels of visual occlusion among those with unilateral and bilateral CAI relative to uninjured controls. DESIGN: Cross-sectional. SETTING: Sports medicine research laboratory. PATIENTS OR OTHER PARTICIPANTS: Twenty-five participants with unilateral CAI, 10 with bilateral CAI, and 16 participants with no history of lower extremity injury. MAIN OUTCOME MEASURES: All participants completed four 3-minute postural control assessments in double-limb stance under the following 4 visual conditions: (1) eyes open, (2) low occlusion, (3) high occlusion, and (4) eyes closed. Low- and high-occlusion conditions were produced using stroboscopic eyewear. Postural control outcomes included time-to-boundary minima means in the anteroposterior (TTB-AP) and mediolateral directions (TTB-ML). Repeated-measures analysis of variances tested the effects of visual condition on TTB-AP and TTB-ML. RESULTS: Postural control under the eyes-open condition was significantly better (ie, higher) than the limited visual occlusion and eyes-closed conditions (P < .001) for TTB-AP and TTB-ML. For TTB-AP only, partially occluded vision resulted in better postural control than the eyes-closed condition (P ≤ .003). CONCLUSIONS: Partial and complete visual occlusion impaired postural control during dual-limb stance in a heterogeneous sample of those with and without CAI. Stroboscopic eyewear appears to induce postural control impairments to the same extent as complete visual occlusion in the mediolateral direction.

Sensorimotor adaptation and cue reweighting compensate for distorted 3D shape information, accounting for paradoxical perception-action dissociations.

Visually guided movements can show surprising accuracy even when the perceived three-dimensional (3D) shape of the target is distorted. One explanation of this paradox is that an evolutionarily specialized "vision-for-action" system provides accurate shape estimates by relying selectively on stereo information and ignoring less reliable sources of shape information like texture and shading. However, the key support for this hypothesis has come from studies that analyze average behavior across many visuomotor interactions where available sensory feedback reinforces stereo information. The present study, which carefully accounts for the effects of feedback, shows that visuomotor interactions with slanted surfaces are actually planned using the same cue-combination function as slant perception and that apparent dissociations can arise due to two distinct supervised learning processes: sensorimotor adaptation and cue reweighting. In two experiments, we show that when a distorted slant cue biases perception (e.g., surfaces appear flattened by a fixed amount), sensorimotor adaptation rapidly adjusts the planned grip orientation to compensate for this constant error. However, when the distorted slant cue is unreliable, leading to variable errors across a set of objects (i.e., some slants are overestimated, others underestimated), then relative cue weights are gradually adjusted to reduce the misleading effect of the unreliable cue, consistent with previous perceptual studies of cue reweighting. The speed and flexibility of these two forms of learning provide an alternative explanation of why perception and action are sometimes found to be dissociated in experiments where some 3D shape cues are consistent with sensory feedback while others are faulty.NEW & NOTEWORTHY When interacting with three-dimensional (3D) objects, sensory feedback is available that could improve future performance via supervised learning. Here we confirm that natural visuomotor interactions lead to sensorimotor adaptation and cue reweighting, two distinct learning processes uniquely suited to resolve errors caused by biased and noisy 3D shape cues. These findings explain why perception and action are often found to be dissociated in experiments where some cues are consistent with sensory feedback while others are faulty.

Postural control and perturbation response in aging populations: fall risk implications.

Falls are an increasing cause of mortality in an ever-growing aging population. The main factors to consider in reducing mortality rates due to falls are postural control, consisting of the vestibular, visual, and proprioceptive system, and perturbation response. This Neuro Forum article reviews recent literature highlighting the developmental changes that occur in aging populations and the possible avenues for interventions and training to mitigate fall risk.

Alchemical free energy calculations via metadynamics: Application to the theophylline-RNA aptamer complex.

We propose a computational workflow for robust and accurate prediction of both binding poses and their affinities at early stage in designing drug candidates. Small, rigid ligands with few intramolecular degrees of freedom, for example, fragment-like molecules, have multiple binding poses, even at a single binding site, and their affinities are often close to each other. We explore various structures of ligand binding to a target through metadynamics using a small number of collective variables, followed by reweighting to obtain the atomic coordinates. After identifying each binding pose by cluster analysis, we perform alchemical free energy calculations on each structure to obtain the overall value. We applied this protocol in computing free energy of binding for the theophylline-RNA aptamer complex. Of the six (meta)stable structures found, the most favorable binding structure is consistent with the structure obtained by NMR. The overall free energy of binding reproduces the experimental values very well.

Reweighting national survey data for small area behaviour estimates: modelling alcohol consumption in Local Authorities in England.

BACKGROUND: There are likely to be differences in alcohol consumption levels and patterns across local areas within a country, yet survey data is often collected at the national or sub-national/regional level and is not representative for small geographic areas. METHODS: This paper presents a method for reweighting national survey data-the Health Survey for England-by combining survey and routine data to produce simulated locally representative survey data and provide statistics of alcohol consumption for each Local Authority in England. RESULTS: We find a 2-fold difference in estimated mean alcohol consumption between the lightest and heaviest drinking Local Authorities, a 4.5-fold difference in abstention rates, and a 3.5-fold difference in harmful drinking. The method compares well to direct estimates from the data at regional level. CONCLUSIONS: The results have important policy implications in itself, but the reweighted data can also be used to model local policy effects. This method can also be used for other public health small area estimation where locally representative data are not available.

Reduction of cybersickness during and immediately following noisy galvanic vestibular stimulation.

The mechanism underlying cybersickness during virtual reality (VR) exposure is still poorly understood, although research has highlighted a causal role for visual-vestibular sensory conflict. Recently established methods for reducing cybersickness include galvanic vestibular stimulation (GVS) to mimic absent vestibular cues in VR, or vibration of the vestibular organs to add noise to the sensory modality. Here, we examined if applying noise to the vestibular system using noisy-current GVS affects sickness severity in VR. Participants were exposed to one of the two VR games that were classified as either moderately or intensely nauseogenic. The VR content lasted for 50 min and was broken down into three blocks: 30 min of gameplay during exposure to either noisy GVS (± 1750 µA) or sham stimulation (0 µA), and 10 min of gameplay before and after this block. We characterized the effects of noisy GVS in terms of post-minus-pre-exposure cybersickness scores. In the intense VR condition, we found a main effect of noisy vestibular stimulation on a verbal cybersickness scale, but not for questionnaire measures of cybersickness. Participants reported lower cybersickness scores during and directly after exposure to GVS. However, this difference was quickly extinguished (~ 3-6 min) after further VR exposure, indicating that sensory adaptation did not persist after stimulation was terminated. In contrast, there were no differences between the sham and GVS group for the moderate VR content. The results show the potential for reducing cybersickness with non-invasive sensory stimulation. We address possible mechanisms for the observed effects, including noise-induced sensory re-weighting.

Can the validity of a cohort be improved by reweighting based on register data? Evidence from the Swedish MDC study.

BACKGROUND: In any study with voluntary participation, self-selection risks leading to invalid conclusions. If the determinants of selection are observed, it is however possible to restore the parameters of interest by reweighting the sample to match the population, but this approach has seldom been applied in epidemiological research. METHODS: We reweighted the Malmö Diet and Cancer (MDC) study based on population register data on background variables, including socio-demographics and hospital admissions for both participants and the background population. Following individuals from baseline in 1991-1996 and at most until 2016, we studied mortality (all-cause, cancer, and CVD), incidences (cancer and CVD), and associations between these outcomes and background variables. Results from the unweighted and reweighted participant sample were compared with those from the background population. RESULTS: Mortality was substantially lower in participants than in the background population, but reweighting the sample helped only little to make the numbers similar to those in the background population. For incidences and associations, numbers were generally similar between participants and the background population already without reweighting, rendering reweighting unnecessary. CONCLUSION: Reweighting samples based on an extensive range of sociodemographic characteristics and previous hospitalizations does not necessarily yield results that are valid for the population as a whole. In the case of MDC, there appear to be important factors related to both mortality and selection into the study that are not observable in registry data, making it difficult to obtain accurate numbers on population mortality based on cohort participants. These issues seem less relevant for incidences and associations, however. Overall, our results suggest that representativeness must be judged on a case-by-case basis.

A Subspace Based Transfer Joint Matching with Laplacian Regularization for Visual Domain Adaptation.

In a real-world application, the images taken by different cameras with different conditions often incur illumination variation, low-resolution, different poses, blur, etc., which leads to a large distribution difference or gap between training (source) and test (target) images. This distribution gap is challenging for many primitive machine learning classification and clustering algorithms such as k-Nearest Neighbor (k-NN) and k-means. In order to minimize this distribution gap, we propose a novel Subspace based Transfer Joint Matching with Laplacian Regularization (STJML) method for visual domain adaptation by jointly matching the features and re-weighting the instances across different domains. Specifically, the proposed STJML-based method includes four key components: (1) considering subspaces of both domains; (2) instance re-weighting; (3) it simultaneously reduces the domain shift in both marginal distribution and conditional distribution between the source domain and the target domain; (4) preserving the original similarity of data points by using Laplacian regularization. Experiments on three popular real-world domain adaptation problem datasets demonstrate a significant performance improvement of our proposed method over published state-of-the-art primitive and domain adaptation methods.

A Sparse Conjugate Gradient Adaptive Filter.

In this letter, we propose a novel conjugate gradient (CG) adaptive filtering algorithm for online estimation of system responses that admit sparsity. Specifically, the Sparsity-promoting Conjugate Gradient (SCG) algorithm is developed based on iterative reweighting methods popular in the sparse signal recovery area. We propose an affine scaling transformation strategy within the reweighting framework, leading to an algorithm that allows the usage of a zero sparsity regularization coefficient. This enables SCG to leverage the sparsity of the system response if it already exists, while not compromising the optimization process. Simulation results show that SCG demonstrates improved convergence and steady-state properties over existing methods.