Digital assessment of cognitive-affective biases related to mental health.

With an increasing societal need for digital therapy solutions for poor mental health, we face a corresponding rise in demand for scientifically validated digital contents. In this study we aimed to lay a sound scientific foundation for the development of brain-based digital therapeutics to assess and monitor cognitive effects of social and emotional bias across diverse populations and age-ranges. First, we developed three computerized cognitive tasks using animated graphics: 1) an emotional flanker task designed to test attentional bias, 2) an emotional go-no-go task to measure bias in memory and executive function, and 3) an emotional social evaluation task to measure sensitivity to social judgments.

Cognotyping by What-Where-When Retrieval Reveals the Potential Role of Temporal Memory and Its Neural Correlates in Understanding Individual Differences across Aging and Alzheimer Disease.

Despite distinct neural representation of what, where, and when information, studies of individual differences in episodic memory have neglected to test the three components separately. Here, we used a componential episodic memory task to measure cognitive profiles across a wide age range and in Alzheimer disease (AD) and to examine the role of theta oscillations in explaining performance. In Experiment 1, we tested a group of 47 young adults (age 21-30 years, 21 women) while recording their scalp EEG.

Domain-General and Domain-Specific Electrophysiological Markers of Cognitive Distance Coding for , , and Memory Retrieval.

The , , and components of episodic memory can be differentiated based on their distinctive domain-specific underlying neural correlates. However, recent studies have proposed that a common neural mechanism of conceptual mapping may be involved in the coding of cognitive distance across all domains. In this study, we provide evidence that both domain-specific and domain-general processes occur simultaneously during memory retrieval by identifying distinctive and common neural representations for mapping (i.

Strong Anionic Repulsion for Fast Na Kinetics in P2-Type Layered Oxides.

An intriguing mechanism for enabling fast Na kinetics during oxygen redox (OR) is proposed to produce high-power-density cathodes for sodium-ion batteries (SIBs) based on the P2-type oxide models, Na [Mn Ni ]O (NMNO) and Na [Ti Mn Ni ]O (NTMNO) using the "potential pillar" effect. The critical structural parameter of NTMNO lowers the Na migration barrier in the desodiated state because the electrostatic repulsion of O(2p)O(2p) that occurs between transition metal layers is combined with the chemically stiff Ti (3d)O(2p) bond to locally retain the strong repulsion effect. The NTMNO interlayer distance moderately decreases upon charging with oxygen oxidation, whereas that of NMNO decreases at a much faster rate, which can be explained by the dependence of OR activity on the coordination environment.

Determining Factors in Triggering Hysteretic Oxygen Capacities in Lithium-Excess Sodium Layered Oxides.

Oxygen redox (OR) reactions in sodium layered oxide cathodes have been studied intensively to harness their full potential in achieving high energy density for sodium-ion batteries (SIBs). However, OR triggers a large hysteretic voltage during discharge after the first charge process for OR-based oxides, and its intrinsic origin is unclear. Therefore, in this study, an in-depth reinvestigation on the fundamentals of the reaction mechanism in Na[LiMn]O with a Mn/Li ratio () of 2 was performed to determine the factors that polarize the OR activity and to provide design rules leading to nonhysteretic oxygen capacity using first-principles calculations.

Intrinsic Origin of Nonhysteretic Oxygen Capacity in Conventional Na-Excess Layered Oxides.

An intriguing redox chemistry via oxygen has emerged to achieve high-energy-density cathodes and has been intensively studied for practical use of anion-utilization oxides in A-ion batteries (A: Li or Na). However, in general, the oxygen redox disappears in the subsequent discharge with a large voltage hysteresis after the first charge process for A-excess layered oxides exhibiting anion redox. Unlike these hysteretic oxygen redox cathodes, the two Na-excess oxide models NaIrO and NaRuO unambiguously exhibit nonhysteretic oxygen capacities during the first cycle, with honeycomb-ordered superstructures.

A framework for designing data-driven optimization systems for neural modulation.

Neural modulation is a fundamental tool for understanding and treating neurological and psychiatric diseases. However, due to the high-dimensional space, subject-specific responses, and variability within each subject, it is a major challenge to select the stimulation parameters that have the desired effect. Data-driven optimization provides a range of different algorithms and tools for addressing this challenge, but each of these algorithms has specific strengths and limitations, and therefore must be carefully designed for a given neural modulation problem.

Industrial carbon dioxide capture and utilization: state of the art and future challenges.

Dramatically increased CO concentration from several point sources is perceived to cause severe greenhouse effect towards the serious ongoing global warming with associated climate destabilization, inducing undesirable natural calamities, melting of glaciers, and extreme weather patterns. CO capture and utilization (CCU) has received tremendous attention due to its significant role in intensifying global warming. Considering the lack of a timely review on the state-of-the-art progress of promising CCU techniques, developing an appropriate and prompt summary of such advanced techniques with a comprehensive understanding is necessary.

Dynamic adsorption/desorption of p-xylene on nanomorphic MFI zeolites: Effect of zeolite crystal thickness and mesopore architecture.

Zeolites have attracted great interest as an adsorbent for the removal of volatile organic compounds. However, they suffer from low adsorption capacities due to severe diffusion limitations. Here, the effects of zeolite thickness and mesopore architecture on dynamic adsorption of p-xylene have been examined with a number of MFI-type zeolites with different crystal thicknesses and mesopore openings (i.

Optimizing neuromodulation based on surrogate neural states for seizure suppression in a rat temporal lobe epilepsy model.

Objective: Developing a new neuromodulation method for epilepsy treatment requires a large amount of time and resources to find effective stimulation parameters and often fails due to inter-subject variability in stimulation effect. As an alternative, we present a novel data-driven surrogate approach which can optimize the neuromodulation efficiently by investigating the stimulation effect on surrogate neural states.

Approach: Medial septum (MS) optogenetic stimulation was applied for modulating electrophysiological activities of the hippocampus in a rat temporal lobe epilepsy model.

Learning State-Dependent Neural Modulation Policies with Bayesian Optimization.

Neural modulation is becoming a fundamental tool for understanding and treating neurological diseases and their implicated neural circuits. Given that neural modulation interventions have high dimensional parameter spaces, one of the challenges is selecting the stimulation parameters that induce the desired effect. Moreover, the effect of a given set of stimulation parameters may change depending on the underlying neural state.

A characterization of epileptogenesis presented in hippocampal neural activity in a rat tetanus toxin model.

We built a regression model to describe the progress of epileptogenesis in a rat intrahippocampal tetanus toxin (TeNT) epilepsy model by identifying informative neural features from hippocampal local field potentials (LFPs). The LFPs were recorded from the awake and freely behaving animals during the latent period and the active-seizure period. Frequency domain neural features including power spectral density, coherence and phase coherence were calculated from the hippocampal LFPs.

A Machine Learning Approach to Characterize the Modulation of the Hippocampal Rhythms Via Optogenetic Stimulation of the Medial Septum.

The medial septum (MS) is a potential target for modulating hippocampal activity. However, given the multiple cell types involved, the changes in hippocampal neural activity induced by MS stimulation have not yet been fully characterized. We combined MS optogenetic stimulation with local field potential (LFP) recordings from the hippocampus and leveraged machine learning techniques to explore how activating or inhibiting multiple MS neuronal subpopulations using different optical stimulation parameters affects hippocampal LFP biomarkers.

A machine learning approach to characterizing the effect of asynchronous distributed electrical stimulation on hippocampal neural dynamics in vivo.

Asynchronous distributed microelectrode theta stimulation (ADMETS) of the hippocampus has been shown to reduce seizure frequency in the tetanus toxin rat model of mesial temporal lobe epilepsy suggesting a hypothesis that ADMETS induces a seizure resistant state. Here we present a machine learning approach to characterize the nature of neural state changes induced by distributed stimulation. We applied the stimulation to two animals under sham and ADMETS conditions and used a combination of machine learning techniques on intra-hippocampal recordings of Local Field Potentials (LFPs) to characterize the difference in the neural state between sham and ADMETS.

Predicting the stimulation effectiveness using pre-stimulation neural states via optogenetic activation of the medial septum glutamatergic neurons modulating the hippocampal neural activity.

In this study, we explored the role of pre-stimulation neural states on the effectiveness of optogenetic stimulation. Optogenetic stimulation was applied to the medial septum glutamatergic neurons to modulate the hippocampal neural activity in a rat tetanus toxin seizure model. The hippocampal local field potential was recorded using a multi electrode array in an awake and behaving rat.

Novelty of Dynamic Process in the Synthesis of Biocompatible Silica Nanotubes by Biomimetic Glycyldodecylamide as a Soft Template.

A dynamic process in the synthesis of silica nanotubes (SNTs) by utilizing glycyldodecylamide (GDA) as a soft template was thoroughly investigated. The morphological evolution from GDA to SNTs was deeply explored to elucidate the formation mechanism for optimizing the synthesis procedure. Various analytical tools, namely, XRD, FTIR, SEM, TEM, Z-potential, and N adsorption/desorption isotherms, were employed during the synthesis procedure.

Highly selective BTX from catalytic fast pyrolysis of lignin over supported mesoporous silica.

The post synthesis of Al(3+) or Zr(4+) substituted MCM-48 framework with controlled acidity is challenging because the functional groups exhibiting acidity often jeopardize the framework integrity. Herein, we report the post-synthesis of two hierarchically porous MCM-48 composed of either aluminum (Al(3+)) or zirconium (Zr(4+)) clusters with high throughput. All prepared catalysts have been characterized by HR-TEM, XRD, IR, N2-adsorption, NH3-TPD, TGA and MAS NMR.

Encapsulation of hexahydro-1,3,5-trinitro-s-triazine (RDX) onto amino-functionalized mesoporous silica.

Amine functionalized disk type mesoporous silica was directly synthesized by co-condensation method for the encapsulation of hexahydro-1,3,5-trinitro-s-triazine (RDX), aiming for the desensitization of such high energetic material. The adsorption capacities were measured by TG analysis and pore-filling adsorption efficiencies of RDX were estimated based on sorption amounts with respect to pore volume of amino-functionalized mesoporous silica. The RDX was encapsulated as nanoparticles in the (NH2)-INC-2 due to the confinement effect within the size of mesopores and shows adsorption efficiency upto 80% at with respect to pore-filling.

Tetraethylenepentamine embedded zeolite A for carbon dioxide adsorption.

Tetraethylenepentamine (TEPA) embedded zeolite A crystals were synthesized by using TEPA and the preformed zeolite A precursor under the microwave irradiation. The presence of TEPA in zeolite A crystal was confirmed by TG analysis and FTIR, Raman spectra. The CO2 adsorptive behavior of TEPA embedded zeolite A samples was investigated by CO2 isotherms measured at 25 degrees C comparing with zeolite A.

High throughput detection and selective enrichment of histidine-tagged enzymes with Ni-doped magnetic mesoporous silica.

This work reports a simple and facile method to prepare novel magnetic mesoporous silica (MMS) materials with high magnetic strength for the convenient and high throughput detection of histidine-tagged enzymes with Ni-doped surfaces. These materials are designed by the incorporation of high-abundance and homogeneously dispersed iron nanoparticles within the mesopores by thermal hydrogen reduction after the incorporation of ferrous ions and demonstrated the selective enrichment and high-throughput recognition of His-tagged enzymes with multi-point anchoring by selective conjugation between the His-tag and Ni ions. Selective His-tagged enzyme enrichment efficiency was compared with nickel-based MMS materials, such as Ni-MMS and Ni-MMS, and nickel ion doped silica-coated magnetic nanoparticles (Ni-MNPs).

trans-1,2-Diaminocyclohexane mesoporous silica for asymmetric catalysis: enhancement of chirality through confinement space by the plug effect.

trans-1,2-Diaminocyclohexane functionalized mesoporous silica was applied as an ideal catalyst for asymmetric Michael addition of various nitroalkane derivatives. Short channels and plugs in the pore structure offered chiral enhancement in Michael addition.

Synthesis of olive-shaped mesoporous platinum nanoparticles (MPNs) with a hard-templating method using mesoporous silica (SBA-15).

Well-ordered mesoporous Pt nanoparticles (MPNs) with uniform olive shapes are synthesized by using two-dimensional (2D) hexagonal mesoporous silica (SBA-15) as a hard template. The average particle sizes are controllable in the range of 150 to 230 nm by changing the reduction time. Low-angle XRD profiles for the obtained MPNs show three distinct peaks assignable to the (10), (11), and (20) planes of a highly ordered 2D hexagonal symmetry.

Mesoporous MFI zeolites by microwave induced assembly between sulfonic acid functionalized MFI zeolite nanoparticles and alkyltrimethylammonium cationic surfactants.

Mesoporous MFI zeolites (ZSM-5, TS-1, S-1) having intracrystalline mesoporosity within zeolite crystals were synthesized by microwave induced assembly through the ionic interaction between the sulfonic acid functionalized MFI zeolite nanoparticles and alkyltrimethylammonium cationic surfactants.

Direct synthesis of plugged SBA-15 type mesoporous silica using alcoholamines.

Plugged mesoporous SBA-15 having a 2-D hexagonal pore structure could be directly synthesized under acidic conditions using P123 as a supramolecular template, sodium metasilicate and alcoholamines. The use of alcoholamines seemed to play roles as capturing agents for silica sources that could form internal porous plugs.

Removal of Cu(II) from water by tetrakis(4-carboxyphenyl) porphyrin-functionalized mesoporous silica.

Various adsorbents are available for the removal of heavy and toxic metals, silica-based materials have been the most popular. Recently, there has been considerable interest for the modification of organic moieties and mesostructured materials to enable their use as efficient adsorbent for metal removal. In this study, here we are reporting successful incorporation of tetrakis(4-carboxyphenyl)porphyrin (TCPP) in mesoporous silica by the post-synthetic method.