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DOE OSTI2024

Human Factors Design for Particle Accelerator Control Room Interfaces

Fermilab, the birthplace of many scientific discoveries in physics and particle accelerator sciences, is in the midst of a widescale modernization effort. The Accelerator Control Operations Research Network (ACORN project’s goal is to modernize the accelerator control system by replacing end-of-life power supplies and enhance future operations of the Fermilab accelerator complex with megawatt particle beams. Within ACORN, opportunities for process improvement concerning software development, human-system interface design, and task performance are also being considered. Human factors researchers from Idaho National Laboratory in collaboration with usability experts from Fermilab, are currently investigating human-centered design improvements for the accelerator control system. For example, substantial tribal knowledge and memory recall are required to effectively operate the accelerator system. This contributes to high cognitive workload and potential burnout of accelerator operators. Developing guidance for consistent visual and functional design enables a more intuitive interaction and relieves operators of cognitive burden. Additionally, developing more intuitive and integrated interfaces can also lead to improved accelerator efficacy by empowering operators with greater understanding and control of the systems. The challenge in developing such interfaces is in designing for a wide variety of user goals, system specifications, and level of experience in users. The challenges need to be met while e also considering the maintainability of the control system. The purpose of this paper is to detail the human factors process and design within the ACORN project, describe results gathered thus far, and discuss the larger implications for this work.

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Machine Intelligence to Detect, Characterise, and Defend against Influence Operations in the Information Environment

Social media has enabled a new era of manipulation in the information and cognitive domains. Deceptive content—misleading, falsified, and fabricated—is routinely created and spread in the modern social media environment with the intent to create confusion and widen political and social divides, and exploit the societal conflict exacerbated by these divides in the real-world (aka physical domain). Such disinformation campaigns demonstrate a threat to the integrity of economic, political, cultural, public health, and national security institutions around the world. In this work we overview our artificial intelligence (AI) capabilities to detect, describe, and defend against information operations on Twitter as an example social platform to understand the influence of misleading and falsified content diffusion and better enable those charged with defending against such manipulation to enable responsive parties to counter it. We first present novel linguistically-informed deep learning (DL) models for misinformation and disinformation detection, and present an in-depth linguistic analysis of psycho-linguistic markers across broad deception categories. We then demonstrate how our models perform in the multilingual and multimodal setting and categorize falsified and misleading content based on the intent to deceive. We also provide a large-scale analysis to describe user behavior and spread patterns while engaging with deceptive content and report novel findings about the immediate diffusion of deceptive content by characterizing the vulnerable sub-populations and their demographics, and explicitly measuring speed and scale of deception spread to uncover who shares deceptive content, how quickly, how much, and how evenly. In addition, we measure audience reactions to misinformation and disinformation at scale, distinguishing the reactions of users identified as bots versus humans. Finally, we take advantage of deep translation and generation models to create unique solutions for real-time defense against digital deception and discuss how to apply causal inference to prescribe and intervene into strategic communications jointly across information, cognitive, and physical domains.

artificial intelligence, deep learning, neural lan↗

DOE OSTI2021

Tonal Emergence: An agent-based model of tonal coordination

Humans have a remarkable capacity for coordination. Our ability to interact and act jointly in groups is crucial to our success as a species. Joint Action (JA) research has often concerned itself with simplistic behaviors in highly constrained laboratory tasks. But there has been a growing interest in understanding complex coordination in more open-ended contexts. In this regard, collective music improvisation has emerged as a fascinating model domain for studying basic JA mechanisms in an unconstrained and highly sophisticated setting. A number of empirical studies have begun to elucidate coordination mechanisms underlying joint musical improvisation, but these empirical findings have yet to be cached out in a working computational model. The present work fills this gap by presenting TonalEmergence, an idealized agent-based model of improvised musical coordination. TonalEmergence models the coordination of notes played by improvisers to generate harmony (i.e., tonality), by simulating agents that stochastically generate notes biased towards maximizing harmonic consonance given their partner’s previous notes. Here, the model replicates an interesting empirical result from a previous study of professional jazz pianists: feedback loops of mutual adaptation between interacting agents support the production of consonant harmony. The model is further explored to show how complex tonal dynamics, such as the production and dissolution of stable tonal centers, are supported by agents that are characterized by (i) a tendency to strive toward consonance, (ii) stochasticity, and (iii) a limited memory for previously played notes. TonalEmergence thus provides a grounded computational model to simulate and probe the coordination mechanisms underpinning one of the more remarkable feats of human cognition: collective music improvisation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Non-DNA radiosensitive targets that initiate persistent behavioral deficits in rats exposed to space radiation

Predicting future CNS risks for astronauts during deep-space missions will rely substantially on ground-based rodent data with space-relevant ions and behaviors. For rats, the accumulated evidence indicates that less densely ionizing radiation, such as 4 He and 12 C ions, induce behavior deficits at lower doses than densely ionizing ions, such as 48 Ti and 56 Fe. However, this observation conflicts with standard somatic radiobiology, in which densely ionizing ions are generally more effective than less densely ionizing ions, and where the DNA/nucleus is the accepted target for radiation-induced tumorigenesis, cytogenetic aberrations, genetic mutations, and reproductive cell death. To gain deeper insight into the subcellular nature of the radiation targets for behavior risks, we compared the effects of dose, fluence, and linear energy transfer (LET) of 4 He and 56 Fe particles using existing datasets for four distinct behavioral outcomes in rats: elevated plus maze (EPM-anxiety), novel object recognition (NOR-memory), operant responding (OR-response to environmental stimuli), and attentional set-shifting (ATSET-cognitive flexibility). We confirmed that less densely ionizing particles (except protons) showed ~100-fold lower threshold doses than densely ionizing particles for behavioral deficits (0.1–1 cGy for 4 He vs. 15–100 cGy for 56 Fe). However, when analyzed by fluence the behavioral responses converged, indicating that 4 He and 56 Fe were equally effective on a per-track basis. When analyzed by LET, there were ~100-fold differences in the LET for maximum effectiveness for behavioral deficits and DNA endpoints (~1 vs ~100 keV/μm, respectively). These unique features of radiation-induced behavioral deficits (high sensitivity to particles in the 1-keV/μm range, insensitivity to protons in the 0.2 keV/μm range, and isofluence dependence for particles with LET>1 keV/μm) provide evidence in support of a new hypothesis of sub-micron sized radiosensitive targets for behavioral effects consistent with the thickness of plasma membranes and/or small subcellular structures, smaller than a whole synapse. Like our behavior findings, mouse immature oocyte killing which is known to have a plasma membrane target was also better explained by fluence, rather than dose. In contrast, fluence analyses for DNA/nuclear endpoints in somatic cells (e.g., tumor induction, chromosome aberrations) showed opposite results, suggesting that behavior targets are not DNA. Our findings raise questions regarding the identity of subcellular targets and the multi-cellular functional unit for behavior risks, low-dose susceptibility, and generalizability from rat to other species and astronauts.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2025

Subventricular Accumulation of Cu in the Aging Mouse Brain Does Not Associate with Anticipated Increases in Markers of Oxidative Stress

Natural aging is associated with mild memory loss and cognitive decline, and age is the greatest risk factor for neurodegenerative diseases, such as Alzheimer’s disease. There is substantial evidence that oxidative stress is a major contributor to both natural aging and neurodegenerative disease, and coincidently, levels of redox active metals such as Fe and Cu are known to be elevated later in life. Recently, a pronounced age-related increase in Cu content has been reported to occur in mice and rats around a vital regulatory brain region, the subventricular zone of lateral ventricles. In our study herein, we have characterized lateral ventricle Cu content in a unique murine model of accelerated aging, senescence accelerated mouse-prone 8 (SAMP8) mice. Our results confirm an age-related increase in ventricle Cu content, consistent with the studies by others in wild-type mice and rats. Specifically, we observed Cu content to increase over the time frame 1 to 5 months and 5 to 9 months, but interestingly, no significant increase occurred between 9 and 12 months (although brain Cu content at 12 months was significantly elevated relative to 1 and 5 month-old animals). Despite the magnitude of Cu increase observed within the cells that comprise the subventricular zone of lateral ventricles (average 3 mM Cu, with isolated subcellular concentrations of 17 mM), we did not detect spectroscopic markers of thiol oxidation, protein aggregation, or lipid oxidation. The lack of evidence for oxidative stress in ex vivo animal tissue is in contrast to in vitro studies demonstrating that thiol, protein, and lipid oxidation is pronounced at these Cu concentrations. We suggest that our findings most likely indicate that the Cu ions in this brain region are sequestered in an unreactive form, possibly extended chains of Cu-thiolate complexes, which do not readily redox cycle in the aqueous cytosol. In conclusion, these results also appear to partially challenge the long-held view that age-related increases in brain metal content drive oxidative stress as we did not observe a concomitant association between age-related Cu increase and markers of oxidative stress, nor did we observe a net increase in Cu content between mice aged 9 and 12 months.

X-ray fluorescence↗

DOE OSTI2021

Usability Evaluation of the Innovation Portal and Integrated Capability Analysis Platform

The usability evaluation of the ICAP and IP tools was conducted as part of the United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) ION effort with two evaluators for the Idaho National Laboratory. Many nuclear operations in the United States are facing challenges of increased business, operations, and maintenance costs due to subsidized renewables and natural gas. The commercial NPP industry has looked to other industries to develop methods such as Integrated Operations (IO) to use available technologies to reduce operating costs. One concept for reducing costs that has been developed is the Integrated Operations for Nuclear (ION). A capability Stack model was developed as part of the ION effort to break down information related to People, Technology, Processes, and Governance (PTPG). The Innovation Portal (IP) and Integrated Capability Analysis Platform (ICAP) were created from the Capability Stack model as part of the ION effort to help utilities reduce O&M costs by identifying work reduction opportunities. Two heuristic evaluations and a cognitive walkthrough of the ICAP and IP tools were completed to identify usability issues to further develop the tools for use in the ION effort. Usability issues identified were rated by priority levels and across both tools. The priority levels identified were high (5), medium (11), and low (10). Recommendation were made to help reduce usability issues of the systems and help increase the user response rate of using the systems once they are implemented for utilities. Future work on designs for the IP tool and additional heuristic evaluations and external testing are being developed to continue refinement of the ICAP and IP tools for the ION effort.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

High Value Opportunities to Advance Automation in Electric Grid Control Rooms

Grid operators and electric utilities are increasingly driven to develop automated processes and introduce decision support tools to reduce cognitive demand on System Operations staff and aid in the operational decision-making process. However, System Operation staff are traditionally hesitant to implement and accept new solutions, automation processes, and tools within the control room. This paper explores high-value opportunities to advance automation in electric grid control rooms for the purpose of improving grid safety, reliability, and resiliency during normal and emergency operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Neural correspondence to spectrum of environmental uncertainty in multiple-cue probability judgment system with time delay

Despite state-of-the-art technologies like artificial intelligence, human judgment is critically essential in cooperative systems, such as the multi-agent system (MAS), which collect information among agents based on multiple-cue judgment. Human agents can prevent impaired situational awareness of automated agents by confirming situations under environmental uncertainty. System error caused by uncertainty can result in an unreliable system environment, and this environment affects the human agent, resulting in non-optimal decision-making in MAS. Thus, it is necessary to know how human behavior is changed to capture system reliability under uncertainty. Another issue affecting MAS is time delay, which can delay agent information transfer, resulting in low performance and instability. However, it is difficult to find studies on the influence of time delay on human agents. This study is about understanding the human decision-making process under a specific system reliability environment by uncertainty with time delay. We used concepts of expected and unexpected uncertainty to implement reliability of the system usage environment with three types of time delay conditions: no time delay, regular time delay, and irregular time delay conditions. We used electroencephalogram (EEG) for human cognitive neural mechanisms in multiple-cue judgment systems to understand human decision-making. In the reliability of system usage environment, the unreliable system environment significantly creates less memory load by less utilization of system rules for decision-making. In terms of time delay, delayed information delivery does not significantly affect memory load for decision-making.

cognitive process↗

DOE OSTI2026

Multi-Semester Mentoring and GPA Trajectories in SPINS: A Longitudinal Program Evaluation of STEM Scholars

This exploratory longitudinal program evaluation examined GPA trajectories among 14 STEM scholars participating in the Scholarly Partnership in Nuclear Security (SPINS) mentoring program at an HBCU. Using de-identified administrative data (37 scholar-semester observations), the study compared baseline and latest term GPAs anchored to each scholar’s first funded semester. A Wilcoxon signed-rank test was used to assess within-student change. Mean GPA increased modestly from 3.46 (SD = 0.30) at baseline to 3.61 (SD = 0.33) at the latest observed semester, with 12 of 14 scholars (85.7%) showing net improvement (median change = +0.12). The Wilcoxon signed-rank test indicated a statistically significant positive shift (W = 18, p = 0.030). However, scholars entered the program with a high baseline GPA, and ceiling effects were evident for several participants. Grounded in Social Cognitive Career Theory, findings suggest that multi-semester participation in SPINS is associated with GPA stability and modest improvement in an already high-performing cohort. Results should be interpreted cautiously given the small sample size and single-group design. The study highlights the value of sustained, culturally responsive mentoring at an HBCU while underscoring the need for larger evaluations with comparison cohorts and broader psychosocial outcomes. An evidence-informed mentoring framework is proposed to strengthen multi-semester support.

42 ENGINEERING↗

DOE OSTI2023

Evaluation of Plasma Phosphorylated Tau217 for Differentiation Between Alzheimer Disease and Frontotemporal Lobar Degeneration Subtypes Among Patients With Corticobasal Syndrome

Plasma phosphorylated tau217 (p-tau217), a biomarker of Alzheimer disease (AD), is of special interest in corticobasal syndrome (CBS) because autopsy studies have revealed AD is the driving neuropathology in up to 40% of cases. This differentiates CBS from other 4-repeat tauopathy (4RT)–associated syndromes, such as progressive supranuclear palsy Richardson syndrome (PSP-RS) and nonfluent primary progressive aphasia (nfvPPA), where underlying frontotemporal lobar degeneration (FTLD) is typically the primary neuropathology. To validate plasma p-tau217 against positron emission tomography (PET) in 4RT-associated syndromes, especially CBS. This multicohort study with 6, 12, and 24-month follow-up recruited adult participants between January 2011 and September 2020 from 8 tertiary care centers in the 4RT Neuroimaging Initiative (4RTNI). All participants with CBS (n = 113), PSP-RS (n = 121), and nfvPPA (n = 39) were included; other diagnoses were excluded due to rarity (n = 29). Individuals with PET-confirmed AD (n = 54) and PET-negative cognitively normal control individuals (n = 59) were evaluated at University of California San Francisco. Operators were blinded to the cohort. Plasma p-tau217, measured by Meso Scale Discovery electrochemiluminescence, was validated against amyloid-β (Aβ) and flortaucipir (FTP) PET. Imaging analyses used voxel-based morphometry and bayesian linear mixed-effects modeling. Clinical biomarker associations were evaluated using longitudinal mixed-effect modeling. Of 386 participants, 199 (52%) were female, and the mean (SD) age was 68 (8) years. Plasma p-tau217 was elevated in patients with CBS with positive Aβ PET results (mean [SD], 0.57 [0.43] pg/mL) or FTP PET (mean [SD], 0.75 [0.30] pg/mL) to concentrations comparable to control individuals with AD (mean [SD], 0.72 [0.37]), whereas PSP-RS and nfvPPA showed no increase relative to control. Within CBS, p-tau217 had excellent diagnostic performance with area under the receiver operating characteristic curve (AUC) for Aβ PET of 0.87 (95% CI, 0.76-0.98; P < .001) and FTP PET of 0.93 (95% CI, 0.83-1.00; P < .001). At baseline, individuals with CBS-AD (n = 12), defined by a PET-validated plasma p-tau217 cutoff 0.25 pg/mL or greater, had increased temporoparietal atrophy at baseline compared to individuals with CBS-FTLD (n = 39), whereas longitudinally, individuals with CBS-FTLD had faster brainstem atrophy rates. Individuals with CBS-FTLD also progressed more rapidly on a modified version of the PSP Rating Scale than those with CBS-AD (mean [SD], 3.5 [0.5] vs 0.8 [0.8] points/year; P = .005). In this cohort study, plasma p-tau217 had excellent diagnostic performance for identifying Aβ or FTP PET positivity within CBS with likely underlying AD pathology. Plasma P-tau217 may be a useful and inexpensive biomarker to select patients for CBS clinical trials.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Individuals with Alzheimer's disease and low tau burden: Characteristics and implications

Abnormal amyloid-beta (Aβ) and tau deposition define Alzheimer's Disease (AD), but non-elevated tau is relatively frequent in patients on the AD pathway. We examined characteristics and regional patterns of 397 Aβ+ unimpaired and impaired individuals with low tau (A+T-) in relation to their higher tau counterparts (A+T+). Seventy-one percent of Aβ+ unimpaired and 42% of impaired Aβ+ individuals were categorized as A+T- based on global tau. In impaired individuals only, A+T- status was associated with older age, male sex, and greater cardiovascular risk. α-synuclein was linked to poorer cognition, particularly when tau was low. Tau burden was most frequently elevated in a common set of temporal regions regardless of T+/T- status. Low tau is relatively common in patients on the AD pathway and is linked to comorbidities that contribute to impairment. These findings have implications for the selection of individuals for Aβ- and tau-modifying therapies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Smart connected worker edge platform for smart manufacturing: Part 2—Implementation and on‐site deployment case study

Abstract In this paper, we describe specific deployments of the Smart Connected Worker (SCW) Edge Platform for Smart Manufacturing through implementation of four instructive real‐world use cases that illustrate the role of people in a Smart Manufacturing paradigm through which affordable, scalable, accessible, and portable (ASAP) information technology (IT) acquires and contextualizes data into information for transmission to operation technologies (OT). For case one, the platform captures the relationships between energy consumption and human workflows for improved energy productivity while workers interact with machines during semiconductor manufacturing. The platform utilizes human cognition to identify anomalous machine behavior for root cause analysis of system faults via neural network (NN) that recognize alarm postures of workers with cameras. For case two, a smart assembly line is demonstrated for state monitoring and fault detection. Machine learning (ML) models are used to recognize system states and identify fault scenarios with human intervention. For case three, the platform monitors human–machine interactions to classify manufacturing machine states for proper operations and energy productivity. Internal energy states of individual or collections of manufacturing equipment are determined via NN based algorithms that disaggregate signals associated with smart metering typically deployed at manufacturing facilities. These methods predict the real time energy profile of each machine from the total energy profile of a manufacturing site. For case four, a software defined sensor system built with scientific workflow engines is demonstrated for contextualizing data from laser surface refraction for characterization, and diagnostics in the processing of additively manufactured titanium alloy.

Donovan, Richard P.↗

DOE OSTI2025

Immersive Analytics in Critical Spatial Domains: From Materials to Energy Systems

Immersive analytics (IA) leverages virtual reality, augmented reality, and mixed reality to transform how users interact with complex datasets across domains such as science, industry, and education. These immersive technologies offer spatial and multimodal environments that foster intuitive exploration, but they also introduce challenges related to cognitive load, interface design, and system performance. Here, this article presents a comprehensive review of visualization techniques, interaction models, and multimodal inputs utilized in IA. Drawing on case studies in scientific visualization, industrial training, and educational communication, we examine both the potential and limitations of current systems. Finally, we propose future research directions, focusing on real‐time collaboration, adaptive user interfaces, and scalable data exploration strategies to advance the field.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Connectivity, Pathology, and ApoE4 Interactions Predict Longitudinal Tau Spatial Progression and Memory

ABSTRACT Tau pathology spread into neocortex indicates a transition from healthy aging to Alzheimer's disease (AD). Connectivity between tau epicenters and later accumulating regions of cortex has been proposed as a mechanism of tau spread, but how this relationship changes with greater AD pathology burden or genotype is not understood. We investigated tau accumulation in two key regions, precuneus and inferior temporal cortex, using resting state functional connectivity (rsFC) and longitudinal PET imaging from a multicohort sample of cognitively unimpaired older adults. We examined how baseline tau PET, Aβ PET, and ApoE4 genotype status interact with rsFC between hippocampus and these downstream regions to predict rate of tau accumulation in neocortex. We found that the 3‐way interaction between connectivity, baseline tau, and baseline Aβ or ApoE4 status was associated with neocortical tau accumulation in precuneus and inferior temporal cortex. In addition, baseline tau, Aβ, and ApoE4 status also moderated the association between connectivity and rate of memory decline. Together, these results suggest that the extent and distribution of future tau accumulation may be predicted by the interaction of baseline connectivity, AD pathology, and genetic risk.

Neurosciences & Neurology↗

DOE OSTI2024

In-Depth Proteome Profiling of the Hippocampus of LDLR Knockout Mice Reveals Alternation in Synaptic Signaling Pathway

The low-density lipoprotein receptor (LDLR) is a major apolipoprotein receptor that regulates cholesterol homeostasis. LDLR deficiency is associated with cognitive impairment by the induction of synaptopathy in the hippocampus. Despite the close relationship between LDLR and neurodegenerative disorders, proteomics research for protein profiling in the LDLR knockout (KO) model remains insufficient. Therefore, understanding LDLR KO-mediated differential protein expression within the hippocampus is crucial for elucidating a role of LDLR in neurodegenerative disorders. In this study, we conducted first-time proteomic profiling of hippocampus tissue from LDLR KO mice using tandem mass tag (TMT)-based MS analysis. LDLR deficiency induces changes in proteins associated with the transport of diverse molecules, and activity of kinase and catalyst within the hippocampus. Additionally, significant alterations in the expression of components in the major synaptic pathways were found. Furthermore, these synaptic effects were verified using a data-independent acquisition (DIA)-based proteomic method. In conclusion, our data will serve as a valuable resource for further studies to discover the molecular function of LDLR in neurodegenerative disorders.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Impact of simulated reduced injected dose on the assessment of amyloid PET scans

To investigate the impact of reduced injected doses on the quantitative and qualitative assessment of the amyloid PET tracers [ 18 F]flutemetamol and [ 18 F]florbetaben. Cognitively impaired and unimpaired individuals (N = 250, 36% Aβ-positive) were included and injected with [ 18 F]flutemetamol (N = 175) or [ 18 F]florbetaben (N = 75). PET scans were acquired in list-mode (90–110 min post-injection) and reduced-dose images were simulated to generate images of 75, 50, 25, 12.5 and 5% of the original injected dose. Images were reconstructed using vendor-provided reconstruction tools and visually assessed for Aβ-pathology. SUVRs were calculated for a global cortical and three smaller regions using a cerebellar cortex reference tissue, and Centiloid was computed. Absolute and percentage differences in SUVR and CL were calculated between dose levels, and the ability to discriminate between Aβ- and Aβ + scans was evaluated using ROC analyses. Finally, intra-reader agreement between the reduced dose and 100% images was evaluated. At 5% injected dose, change in SUVR was 3.72% and 3.12%, with absolute change in Centiloid 3.35CL and 4.62CL, for [ 18 F]flutemetamol and [ 18 F]florbetaben, respectively. At 12.5% injected dose, percentage change in SUVR and absolute change in Centiloid were < 1.5%. AUCs for discriminating Aβ- from Aβ + scans were high (AUC ≥ 0.94) across dose levels, and visual assessment showed intra-reader agreement of > 80% for both tracers. This proof-of-concept study showed that for both [ 18 F]flutemetamol and [ 18 F]florbetaben, adequate quantitative and qualitative assessments can be obtained at 12.5% of the original injected dose. However, decisions to reduce the injected dose should be made considering the specific clinical or research circumstances.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2024

Sensory integration for neuroprostheses: from functional benefits to neural correlates

In the field of sensory neuroprostheses, one ultimate goal is for individuals to perceive artificial somatosensory information and use the prosthesis with high complexity that resembles an intact system. To this end, research has shown that stimulation elicited somatosensory information improves prosthesis perception and task performance. While studies strive to achieve sensory integration, a crucial phenomenon that entails naturalistic interaction with the environment, this topic has not been commensurately reviewed. Therefore, here we present a perspective for understanding sensory integration in neuroprostheses. First, we review the engineering aspects and functional outcomes in sensory neuroprosthesis studies. In this context, we summarize studies that have suggested sensory integration. We focus on how they have used stimulation-elicited percepts to maximize and improve the reliability of somatosensory information. Next, we review studies that have suggested multisensory integration. These works have demonstrated that congruent and simultaneous multisensory inputs provided cognitive benefits such that an individual experiences a greater sense of authority over prosthesis movements (i.e., agency) and perceives the prosthesis as part of their own (i.e., ownership). Thereafter, we present the theoretical and neuroscience framework of sensory integration. We investigate how behavioral models and neural recordings have been applied in the context of sensory integration. Sensory integration models developed from intact-limb individuals have led the way to sensory neuroprosthesis studies to demonstrate multisensory integration. Neural recordings have been used to show how multisensory inputs are processed across cortical areas. Lastly, we discuss some ongoing research and challenges in achieving and understanding sensory integration in sensory neuroprostheses. Here, resolving these challenges would help to develop future strategies to improve the sensory feedback of a neuroprosthetic system.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Advances and perspectives on mass transfer and enzymatic hydrolysis in the enzyme-mediated lignocellulosic biorefinery: A review

We report enzymatic hydrolysis is a critical process for the cellulase-mediated lignocellulosic biorefinery to produce sugar syrups that can be converted into a whole range of biofuels and biochemicals. Such a process operating at high-solid loadings (i.e., scarcely any free water or roughly ≥ 15% solids, w/w) is considered more economically feasible, as it can generate a high sugar concentration at low operation and capital costs. However, this approach remains restricted and incurs “high-solid effects”, ultimately causing the lower hydrolysis yields with increasing solid loadings. The lack of available water leads to a highly viscous system with impaired mixing that exhibits strong transfer resistance and reaction limitation imposed on enzyme action. Evidently, high-solid enzymatic hydrolysis involves multi-scale mass transfer and multi-phase enzyme reaction, and thus requires a synergistic perspective of transfer and biotransformation to assess the interactions among water, biomass components, and cellulase enzymes. Porous particle characteristics of biomass and its interface properties determine the water form and distribution state surrounding the particles, which are summarized in this review aiming to identify the water-driven multi-scale/multi-phase bioprocesses. Further aided by the cognition of rheological behavior of biomass slurry, solute transfer theories, and enzyme kinetics, the coupling effects of flow-transfer-reaction are revealed under high-solid conditions. Based on the above basic features, this review lucidly explains the causes of high-solid hydrolysis hindrances, highlights the mismatched issues between transfer and reaction, and more importantly, presents the advanced strategies for transfer and reaction enhancements from the viewpoint of process optimization, reactor design, as well as enzyme/auxiliary additive customization.

45 multi-scale, multi-phase, enzymatic reaction↗