We use FPGA to optimize the simulation of quantum computing in two aspects. (a) The if-else state is used in place of tensor product calculation. This allows the tensor product of each quantum operator to be generated...
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Negative life events are often implicated as a near-term risk factor for suicidal ideation (SI); however ruminative processes may play a critical role in amplifying the distress following experiences of negative life ...
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Negative life events are often implicated as a near-term risk factor for suicidal ideation (SI); however ruminative processes may play a critical role in amplifying the distress following experiences of negative life events, ultimately leading to greater suicide risk. In the present work, we examined whether rumination indirectly impacted the association between negative events and SI intensity in a day-level ecological momentary assessment (EMA) study. Participants ( N = 107; M age = 35.9 years, 65% female, 81% white) completed an EMA protocol for 65 days following psychiatric hospitalization. We used dynamic structural equation modeling to test a day-level, within-persons model of direct and indirect effects between negative events, rumination, and SI intensity. After fitting the model across all people, we derived person-specific estimates to examine heterogeneity in the model parameters (i.e., while the indirect effect may be significant in the full sample, effect sizes may vary across individuals). Results indicated that the indirect effect of rumination was significant in the full sample (unstandardized estimate = 0.026) and represented 38.058% of the total effect. Moreover, results for the person-specific examination indicated that the indirect effect was present for nearly all participants who reported SI at any point in their EMA data. Thus, in addition to highlighting the critical role that rumination can play in SI, this study also highlights the value in conducting person-specific research to understand the complexity and heterogeneity of psychological processes involved in suicide risk.
Interest in the two-dimensional (2D) semiconducting transition metal dichalcogenides (TMDs) continues to intensify, driven by their suitable band gaps to supplant silicon as next-generation semiconductor materials. Am...
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Interest in the two-dimensional (2D) semiconducting transition metal dichalcogenides (TMDs) continues to intensify, driven by their suitable band gaps to supplant silicon as next-generation semiconductor materials. Among various TMDs, tungsten diselenide (WSe2) is renowned for its superior electrical properties in carrier density and mobility under ambient conditions. Despite its notable attributes, the behavior of monolayer WSe2 in the electron-doped regime under cryogenic conditions remains largely uncharted, particularly concerning its magnetotransport properties. In this study, we reveal the transport mechanisms of monolayer WSe2 from high temperatures down to the cryogenic regime. As evident by Efros–Shklovskii variable-range hopping (E-S VRH) in the cryogenic regime, strong Coulomb interactions arise between electrons. Above 8 K, an uncommon nonsaturated quadratic large magnetoresistance (MR) can be explained by the wave-function shrinkage model, which is consistent with the E-S VRH transport mechanism. Notably, the nonsaturated quadratic large MR shows a magnitude up to 1740% at 13 T. These findings underscore the potential applications for monolayer WSe2 in cryogenic field-effect devices, magnetic sensors, and memory devices and mark a significant advance in magnetotransport research.
Decomposition theory is concerned with the structures that arise in the decomposition of systems. It states from the premise that any method of system decomposition is based, either explicitly or implicitly, on some c...
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Decomposition theory is concerned with the structures that arise in the decomposition of systems. It states from the premise that any method of system decomposition is based, either explicitly or implicitly, on some concept of dependence. The formal setting of decomposition theory is the dependence, an ordered-triple ( E , M , D ), where E is a nonempty set, M is a collection of subsets of E , and D is a relation from nonempty subsets of M to subsets of M . If ( A , B )∈ D , it is said that ` A depends on B '. Duality is considered here. In particular, given a dependence ( E , M , D ), its dual is a dependence ( E , M , D '). Duality plays a role here similar to duality in other formal systems such as graphs, matroids, lattices, circuits, control systems, and so forth. It deepens our understanding of dependence by pairing seemingly different concepts.
We report a mechanistic understanding of a moisture-driven intermediate-phase transition that improves the quality of perovskite thin films based on a lead-acetate precursor, improving the power-conversion effidency. ...
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We report a mechanistic understanding of a moisture-driven intermediate-phase transition that improves the quality of perovskite thin films based on a lead-acetate precursor, improving the power-conversion effidency. We clarify the composition of the intermediate phase and attribute the transition of this phase to the hygroscopic nature of the organic product, i.e., methylammonium acetate. Thermal annealing aids in the coarsening of the grains. These decoupled processes result in better crystal formation with a lower spatial and energetic distribution of traps. Thermal annealing of the films without exposure to air results in a faster intermediate-phase transition and grain coarsening, which occur simultaneously, leading to disorder in the films and a higher deep trap-state density. Our results indicate the need for a humid environment for the growth of high-quality perovskite films and provide insight into intermediate-phase dissociation and conversion kinetics. Thus, they are useful for the large-scale production of effident solution-processed perovskite solar cells.
Molecular dynamics (MD) simulations in explicit lipid bilayers enable modeling of protein-lipid interactions essential for membrane protein functions and regulation. The newly developed computational web tool, OPRLM (...
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The design of enzymes with complex active sites that mediate multistep reactions remains an outstanding challenge. With serine hydrolases as a model system, we combined the generative capabilities of RFdiffusion with ...
The design of enzymes with complex active sites that mediate multistep reactions remains an outstanding challenge. With serine hydrolases as a model system, we combined the generative capabilities of RFdiffusion with an ensemble generation method for assessing active site preorganization at each step in the reaction to design enzymes starting from minimal active site descriptions. Experimental characterization revealed catalytic efficiencies (kcat/Km) up to 2.2 × 105 M-1 s-1 and crystal structures that closely match the design models (Cα root mean square deviations <1 angstrom). Selection for structural compatibility across the reaction coordinate enabled identification of new catalysts remove with five different folds distinct from those of natural serine hydrolases. Our de novo approach provides insight into the geometric basis of catalysis and a roadmap for designing enzymes that catalyze multistep transformations.
Nonsimultaneous measurements of voltage and current harmonics associated with the distribution and utility-interactive photovoltaic systems at the Southwest Residential Experiment Station are summarized in this paper....
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Nonsimultaneous measurements of voltage and current harmonics associated with the distribution and utility-interactive photovoltaic systems at the Southwest Residential Experiment Station are summarized in this paper. A qualitative analysis of the data is presented. The harmonic impacts of the prototypes-on the distribution system appear to be minimal. Needs in the area of measurement and analysis of harmonic propagation in general systems are identified.
An application was developed to address the time-consuming and subjective nature of physical examination and human judgment to classify the diverse families of Coleoptera more efficiently. Specifically focusing on the...
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This study presents an AI-based model using ECG signals to predict left ventricular systolic dysfunction (LVSD) in pacemaker patients. A 1D convolutional neural network (CNN) combined with large language models proces...
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ISBN:
(纸本)9798400706295
This study presents an AI-based model using ECG signals to predict left ventricular systolic dysfunction (LVSD) in pacemaker patients. A 1D convolutional neural network (CNN) combined with large language models processed both sequential ECG data and nonsequential clinical metadata. The model achieved an AUROC of 0.97 on both general and pacemaker-specific datasets, demonstrating its high accuracy. This approach offers a fast, cost-effective alternative to traditional echocardiography, improving LVSD detection in patients with pacemakers.
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