Multi-objective latent space optimization of generative molecular design models.

Molecular design based on generative models, such as variational autoencoders (VAEs), has become increasingly popular in recent years due to its efficiency for exploring high-dimensional molecular space to identify molecules with desired properties. While the efficacy of the initial model strongly depends on the training data, the sampling efficiency of the model for suggesting novel molecules with enhanced properties can be further enhanced via latent space optimization (LSO). In this paper, we propose a multi-objective LSO method that can significantly enhance the performance of generative molecular design (GMD).

Feasibility of Using Inertial Measurement Units (IMUs) to Augment Cadaveric Temporal Training.

Objective: Insertional speed of cochlear implant electrode arrays (EA) during surgery is correlated with force. Low insertional speed, and therefore force, may allow for preservation of intracochlear structures leading to improved outcomes. Given the importance of low insertional speeds, we investigate the feasibility of using inertial sensors for kinematic analysis during EA insertion to augment otolaryngology-head and neck surgery training.

Sense of control and noise sensitivity affect frustration from interfering noise.

In order to develop effective strategies to address noise annoyance, it is essential to develop an explanatory model of the psychological mechanism(s) by which noise becomes annoying. Two online studies were conducted in which a total of 193 participants completed speech perception tasks with varying degrees of background noise. Signal-to-noise ratio levels ranged from -2 to -10 dB.

Just Keep Spinning? The Impact of Auditory and Somatosensory Cues on Rotary Chair Testing.

Purpose: The purpose of this study was to determine whether providing realistic auditory or somatosensory cues to spatial location would affect measures of vestibulo-ocular reflex gain in a rotary chair testing (RCT) context.

Method: This was a fully within-subject design. Thirty young adults age 18-30 years (16 men, 14 women by self-identification) completed sinusoidal harmonic acceleration testing in a rotary chair under five different conditions, each at three rotational frequencies (0.

Pathway-based analyses of gene expression profiles at low doses of ionizing radiation.

Radiation exposure poses a significant threat to human health. Emerging research indicates that even low-dose radiation once believed to be safe, may have harmful effects. This perception has spurred a growing interest in investigating the potential risks associated with low-dose radiation exposure across various scenarios.

The role of attention in immersion: The two-competitor model.

Currently, we face an exponentially increasing interest in immersion, especially sensory-driven immersion, mainly due to the rapid development of ideas and business models centered around a digital virtual universe as well as the increasing availability of affordable immersive technologies for education, communication, and entertainment. However, a clear definition of 'immersion', in terms of established neurocognitive concepts and measurable properties, remains elusive, slowing research on the human side of immersive interfaces. To address this problem, we propose a conceptual, taxonomic model of attention in immersion.

Effects of background noise on autonomic arousal (skin conductance level).

This study was designed to investigate the relationship between sound level and autonomic arousal using acoustic signals similar in level and acoustic properties to common sounds in the built environment. Thirty-three young adults were exposed to background sound modeled on ventilation equipment noise presented at levels ranging from 35 to 75 dBA sound pressure level (SPL) in 2 min blocks while they sat and read quietly. Autonomic arousal was measured in terms of skin conductance level.

Optimal decision-making in high-throughput virtual screening pipelines.

The need for efficient computational screening of molecular candidates that possess desired properties frequently arises in various scientific and engineering problems, including drug discovery and materials design. However, the enormous search space containing the candidates and the substantial computational cost of high-fidelity property prediction models make screening practically challenging. In this work, we propose a general framework for constructing and optimizing a high-throughput virtual screening (HTVS) pipeline that consists of multi-fidelity models.

Sensitivity Analysis of Genome-Scale Metabolic Flux Prediction.

TRIMER, Transcription Regulation Integrated with MEtabolic Regulation, is a genome-scale modeling pipeline targeting at metabolic engineering applications. Using TRIMER, regulated metabolic reactions can be effectively predicted by integrative modeling of metabolic reactions with a transcription factor-gene regulatory network (TRN), which is modeled through a Bayesian network (BN). In this article, we focus on sensitivity analysis of metabolic flux prediction for uncertainty quantification of BN structures for TRN modeling in TRIMER.

The Effects of Speech Task on Lexical Stress in Parkinson's Disease.

Purpose: Hypokinetic dysarthria associated with Parkinson's disease (PD) is characterized by dysprosody, yet the literature is mixed with respect to how dysprosody affects the ability to mark lexical stress, possibly due to differences in speech tasks used to assess lexical stress. The purpose of this study was to compare how people with and without PD modulate acoustic dimensions of lexical stress-fundamental frequency, intensity, and duration-to mark lexical stress across three different speech tasks.

Method: Twelve individuals with mild-to-moderate idiopathic PD and 12 age- and sex-matched older adult controls completed three speech tasks: picture description, word production in isolation, and word production in lists.

Revisiting the left ear advantage for phonetic cues to talker identification.

Previous research suggests that learning to use a phonetic property [e.g., voice-onset-time, (VOT)] for talker identity supports a left ear processing advantage.

Adding noise is a confounded nuisance.

A wide variety of research and clinical assessments involve presenting speech stimuli in the presence of some kind of noise. Here, I selectively review two theoretical perspectives and discuss ways in which these perspectives may help researchers understand the consequences for listeners of adding noise to a speech signal. I argue that adding noise changes more about the listening task than merely making the signal more difficult to perceive.

Robust importance sampling for error estimation in the context of optimal Bayesian transfer learning.

Classification has been a major task for building intelligent systems because it enables decision-making under uncertainty. Classifier design aims at building models from training data for representing feature-label distributions-either explicitly or implicitly. In many scientific or clinical settings, training data are typically limited, which impedes the design and evaluation of accurate classifiers.

Synthetic data for design and evaluation of binary classifiers in the context of Bayesian transfer learning.

Transfer learning (TL) techniques can enable effective learning in data scarce domains by allowing one to re-purpose data or scientific knowledge available in relevant source domains for predictive tasks in a target domain of interest. In this Data in Brief article, we present a synthetic dataset for binary classification in the context of Bayesian transfer learning, which can be used for the design and evaluation of TL-based classifiers. For this purpose, we consider numerous combinations of classification settings, based on which we simulate a diverse set of feature-label distributions with varying learning complexity.

Protocol for condition-dependent metabolite yield prediction using the TRIMER pipeline.

This protocol explains the pipeline for condition-dependent metabolite yield prediction using Transcription Regulation Integrated with MEtabolic Regulation (TRIMER). TRIMER targets metabolic engineering applications via a hybrid model integrating transcription factor (TF)-gene regulatory network (TRN) with a Bayesian network (BN) inferred from transcriptomic expression data to effectively regulate metabolic reactions. For and yeast, TRIMER achieves reliable knockout phenotype and flux predictions from the deletion of one or more TFs at the genome scale.

TRIMER: Transcription Regulation Integrated with Metabolic Regulation.

There has been extensive research in predictive modeling of genome-scale metabolic reaction networks. Living systems involve complex stochastic processes arising from interactions among different biomolecules. For more accurate and robust prediction of target metabolic behavior under different conditions, not only metabolic reactions but also the genetic regulatory relationships involving transcription factors (TFs) affecting these metabolic reactions should be modeled.

Psychophysiological responses to potentially annoying heating, ventilation, and air conditioning noise during mentally demanding work.

Exposure to noise-or unwanted sound-is considered a major public health issue in the United States and internationally. Previous work has shown that even acute noise exposure can influence physiological response in humans and that individuals differ markedly in their susceptibility to noise. Recent research also suggests that specific acoustic properties of noise may have distinct effects on human physiological response.

Attentional Disengagement and the Locus Coeruleus - Norepinephrine System in Children With Autism Spectrum Disorder.

Background: Differences in non-social attentional functions have been identified as among the earliest features that distinguish infants later diagnosed with autism spectrum disorder (ASD), and may contribute to the emergence of core ASD symptoms. Specifically, slowed attentional disengagement and difficulty reorienting attention have been found across the lifespan in those at risk for, or diagnosed with, ASD. Additionally, the locus coeruleus-norepinephrine (LC-NE) system, which plays a critical role in arousal regulation and selective attention, has been shown to function atypically in ASD.

Fall-Related Injuries Mediate the Relationship Between Self-Reported Hearing Loss and Mortality in Middle-Aged and Older Adults.

Background: Hearing loss is associated with a greater risk of death in older adults. This relationship has been attributed to an increased risk of injury, particularly due to falling, in individuals with hearing loss. However, the link between hearing loss and mortality across the life span is less clear.

Listener characteristics differentially affect self-reported and physiological measures of effort associated with two challenging listening conditions.

Listeners vary in their ability to understand speech in adverse conditions. Differences in both cognitive and linguistic capacities play a role, but increasing evidence suggests that such factors may contribute differentially depending on the listening challenge. Here, we used multilevel modeling to evaluate contributions of individual differences in age, hearing thresholds, vocabulary, selective attention, working memory capacity, personality traits, and noise sensitivity to variability in measures of comprehension and listening effort in two listening conditions.

Towards Contactless Estimation of Electrodermal Activity Correlates.

This paper presents a proof-of-concept for contactless and nonintrusive estimation of electrodermal activity (EDA) correlates using a camera. RGB video of the palm under three different lighting conditions showed that for a suitably chosen illumination strategy the data from the camera is sufficient to estimate EDA correlates which agree with the measurements done using laboratory grade physiological sensors. The effects we see in the recorded video can be attributed to sweat gland activity, which inturn is known to be correlated with EDA.

Brief Report: Reduced Heart Rate Variability in Children with Autism Spectrum Disorder.

Dysregulation of the autonomic nervous system (ANS), which can be indexed by heart rate variability (HRV), has been posited to contribute to core features of autism spectrum disorder (ASD). However, the relationship between ASD and HRV remains uncertain. We assessed tonic and phasic HRV of 21 children with ASD and 21 age- and IQ-matched typically developing (TD) children and examined (1) group differences in HRV and (2) associations between HRV and ASD symptomatology.

Exascale applications: skin in the game.

As noted in Wikipedia, refers to having 'incurred risk by being involved in achieving a goal', where ' is a synecdoche for the person involved, and is the metaphor for actions on the field of play under discussion'. For exascale applications under development in the US Department of Energy Exascale Computing Project, nothing could be more apt, with the being exascale applications and the being delivering comprehensive science-based computational applications that effectively exploit exascale high-performance computing technologies to provide breakthrough modelling and simulation and data science solutions. These solutions will yield high-confidence insights and answers to the most critical problems and challenges for the USA in scientific discovery, national security, energy assurance, economic competitiveness and advanced healthcare.