Gate Model Research Articles

Implementation of controlled unitary gates and its application in a remote-controlled quantum gate

Recently, remote-controlled quantum information processing has been proposed for its applications in secure quantum processing protocols and distributed quantum networks. For remote-controlled quantum gates, the experimental realization of controlled unitary (CU) gates between any quantum gates is an essential task. Here, we propose and experimentally demonstrate a scheme for implementing CU gates between any pair of unitary gates using the polarization and time-bin degrees of freedom of single photons. Then, we experimentally implement remote-controlled single-qubit unitary gates by controlling either the state preparation or measurement of the control qubit with high process fidelities. We believe the proposed remote-controlled quantum gate model can pave the way for secure and efficient quantum information processing.

Subthreshold Drain Current Model of Cylindrical Gate All‐Around Junctionless Transistor With Three Different Gate Materials

ABSTRACTA novel subthreshold drain current model has been developed for a cylindrical gate all‐around junctionless transistor with three different gate materials. The proposed device is built with three gate regions of different work functions that effectively reduce the short‐channel effects caused by quantum mechanical effects. The drain current equation is solved for all three operating regions to investigate the device switching characteristics and minimize the drain‐induced barrier lowering (DIBL), velocity saturation, mobility degradation, and tunneling. It is understood that the triple material gate structure enhances the transport efficiency of the device. The proposed analytical model is validated by comparison with Sentaurus TCAD numerical simulator results and good agreement is found to be achieved.

Milk production and viability of the various smallholder dairying models used in Zimbabwe.

An evaluation of milk yield, dairy products and viability of the smallholder dairy production models used in Zimbabwe was carried out. We used secondary data on 1167 smallholder dairy farmers. These were categorised into commercial dairying (119), Milk collection centre (MCC) bulking and processing (145), MCC bulking and delivering to processor (87), farm gate (468) and other (348) models. Data were analysed using SPSS version 25.0. The average daily milk yield per cows was highest in the Commercial dairying model (9.20 ± 0.4l) but was not significantly different from the MCC bulking and processing and MCC bulking and delivering to processor models. Average lactation milk yield per cow was highest (P < 0.05) in the commercial dairying model (2804.91 ± 133.9l) and was significantly different from the rest of the models. The processed milk products identified in the study were fermented milk, pasteurised milk and unspecified products but production volumes were very low in the respective models. There were no differences (P > 0.05) in gross margin across all the smallholder dairying models. The commercial dairying model surpassed all models on proportion of pure exotic dairy breeds, number of milking cows, milk yield. However, it was discovered that all models were underperforming but smallholder dairy farmers can be recommended to adopt the commercial dairying model if measures to improve milk yield per cow and reduce milk production costs are established.

An Experimental Study of Flow and Turbulence Properties near the Rising Sector Gate Mouth Considering the Gate Opening with a PIV Measuring System

Hydraulic structures, such as movable weir gates, are widely installed in rivers and streams for various purposes. Among these is the rising sector gate, which is the focus of this study. This research investigated how different gate openings affect flow velocity and turbulence distributions at the gate mouth. A hydraulic analysis of flow and turbulence characteristics near the mouth of a rising sector gate model was conducted through laboratory experiments with various flow conditions and gate openings utilizing a Particle Image Velocimetry (PIV) system. Experimental tests were carried out with two gate-opening angles (30 and 45 degrees). The PIV measurements revealed significant variations in flow velocity and turbulence properties in response to the gate openings and flow conditions. Notably, in the vicinity of the gate mouth, where the flow regime changes rapidly between the upstream and downstream regions, the turbulence properties in the upstream part of the gate mouth were more than twice those in the downstream part. Additionally, the streamwise distribution of depth-averaged relative turbulence intensity was analyzed. The results showed that the depth-averaged relative turbulence intensity decreased by nearly half as the gate opening increased from 30 to 45 degrees, with the lowest values observed at the gate mouth, followed by an increase downstream. A functional relationship between the maximum flow velocity at the gate mouth during underflow operation and the Froude number was established to guide practical gate operation in the field.

Symmetry-adapted Markov state models of closing, opening, and desensitizing in α 7 nicotinic acetylcholine receptors.

α7 nicotinic acetylcholine receptors (nAChRs) are homopentameric ligand-gated ion channels with critical roles in the nervous system. Recent studies have resolved and functionally annotated closed, open, and desensitized states of these receptors, providing insight into ion permeation and lipid binding. However, the process by which α7 nAChRs transition between states remains unclear. To understand gating and lipid modulation, we generated two ensembles of molecular dynamics simulations of apo α7 nAChRs, with or without cholesterol. Using symmetry-adapted Markov state modeling, we developed a five-state gating model. Free energies recapitulated functional behavior, with the closed state dominating in absence of agonist. Open-to-nonconducting transition rates corresponded to experimental open durations. Cholesterol relatively stabilized the desensitized state, and reduced open-desensitized barriers. These results establish plausible asymmetric transition pathways between states, define lipid modulation effects on the α7 nAChR conformational cycle, and provide an ensemble of structural models applicable to rational design of lipidic pharmaceuticals.

Effects of insertion of an h-AlN monolayer spacer in Pt-WSe2-Pt field-effect transistors

The growth of two-dimensional hexagonal aluminum nitride (h-AlN) on transition metal dichalcogenide (TMD) monolayers exhibits superior uniformity and smoothness compared to HfO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document} on silicon substrate. This makes an h-AlN monolayer an ideal spacer between the gate oxide material and the WSe2 monolayer in a two-dimensional field effect transistor (FET). From first principles approaches, we calculate and compare the transmission functions and current densities of Pt–WSe2–Pt nanojunctions without and with the insertion of an h-AlN monolayer as a spacer in the gate architecture. The inclusion of h-AlN can alter the characteristics of the Pt–WSe2–Pt FET in response to the gate voltage (Vg\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$V_\ ext {g}$$\\end{document}). The FET without (or with) h-AlN exhibits the characteristics of a P-type (or bipolar) transistor: an on/off ratio of around 2.5×106\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$2.5 \ imes 10^{6}$$\\end{document} (or 1.7×106\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$1.7 \ imes 10^{6}$$\\end{document}); and an average subthreshold swing (S.S.) of approximately 109 mV/dec.\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {dec.}$$\\end{document} (or 112 mV/dec.\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {dec.}$$\\end{document}), respectively. We observe that Vg\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$V_\ ext {g}$$\\end{document} shifts the profile of the transmission function by an energy of α(eVg)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha (e V_{\ ext {g}})$$\\end{document}, where α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document} represents the gate-controlling efficiency. We observed that αin=83%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha _{\ ext {in}}=83\\%$$\\end{document} and αout=33%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha _{\ ext {out}}=33\\%$$\\end{document}, corresponding to whether the Fermi energy is located inside or outside the band gap. Therefore, we construct an effective gate model based on the Landauer formula, with the transmission function at Vg=0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$V_\ ext {g}=0$$\\end{document} as the baseline. Our model generates results that are consistent with those obtained through first principles calculations. The relative error in current densities between model and first-principles calculations is within [ln(10)S.S.]|ΔVGeff|\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$[\\frac{ln(10)}{S.S.}] | \\Delta V_{\ ext {G}}^{\ ext {eff}} |$$\\end{document}. The 2D atomistic FETs show excellent device specifications and the ability to compete with existing transistors based on traditional silicon technology. Our findings could help advance the design of TMD-based FETs.

Simulation study: Seeking fairness in a high-stakes placement test

The primary objective of Cognitive Diagnostic Assessment (CDA) lies in problem solving processes to systematically categorize test takers in mastery/non-mastery groups. What is of concern is using some attributes in reading comprehension test item options which are suspected to bias, and is simulating unbiased test items in a reversed engineering attempt. To this end, 4200 PhD candidates who sat for the examination were randomly selected. A Q-matrix was constructed, and raw data were fed into the R-studio software. Two groups of female and male differences were considered for the Differential Item Functioning (DIF) detection based on the Deterministic Inputs, Noisy “and” Gate (DINA) model. Results of the simulation study revealed that in 100 times of item generations, items were non-significant in favor of gender bias. In conclusion, this study was an attempt to determine whether an item identified with DIF is a correct detection or failed to be identified in fine-grained details.

Modeling Skipped Items in Cognitive Diagnostic Assessments

In cognitive diagnosis assessments, examinees frequently skip some items due to various reasons, such as time constraints, lack of confidence, or the perception of item difficulty. These skipped items are usually due to lacking specific cognitive attributes or knowledge structures. However, many research studies conventionally rely on complete-case analysis, potentially compromising the validity of results by ignoring skipped items. This omission can lead to invalid inferences about the attributes profiles of examinees and introduce bias into item parameters. This study aims to develop statistical models for effectively handling missing data resulting from skipped items. Specifically, we employ an item response theory model for missing indicators and utilize the deterministic inputs, noisy “and” gate (DINA) model to describe cognitive item responses. Furthermore, we introduce a higher-order structure to describe the correlation between the higher-order ability parameters and skipping propensity parameters and the correlation of the item parameters. The proposed new model fills the gaps in missing data handling, providing a more precise evaluation for the examinees who skip items and yielding more accurate research results. This enhances our understanding of cognitive processes and strengthens support for educational policies, aligning them better with student needs and optimizing decision-making.

Molecular weight modulated FRET based logic gate probes for lysosome Al3+ and CO detection

The gas signaling molecules CO and Al3+ play important physiological roles in maintaining homeostatic processes in cells. Rapid monitoring of these two information molecules in the sub-organelle dimension has rarely been reported. To fill this blank, we proposed a new “molecular weight regulated FRET method” to construct new logic gate probes to monitor CO and Al3+ synergetically. We selected naphthalimide and rhodamine as energy transfer groups. Then we designed two silane probes, P-Si-CO and Si-CO, which display different chain lengths to investigate the probes' response to CO and Al3+. Si-CO with low molecular weight is more advantageous for generating significant FRET processes. To show the three-channel and dual detection function of the probe more intuitively, we constructed a novel logic gate model that can detect Al3+ and CO simultaneously. Si-CO also exhibited rewarding cell imaging effects for visualizing the anoxia and starvation process in lysosomes. This work provided a new method for constructing logic-gate probes for detecting Al3+ and CO based on regulating FRET theory.

Prediction method for 4D trajectory of large fixed wing UAV under multi-layer convolution and bidirectional gating model

Abstract With the increase of low-altitude flight tasks, the importance of research on low-altitude flight safety and efficient operation has gradually become prominent. Therefore, it is necessary to try to establish a low-altitude airspace flight path pre-planning method based on 4D trajectory prediction, which can effectively support the above research. In order to improve the integrity, accuracy and reliability of the long-range trajectory prediction results of large fixed wing UAV (LFW UAV), based on the standard neural network as the basic concept to form a fusion model of improved convolutional neural network (CNN) and bidirectional gated recurrent neural network (BIGRU). At the same time, the flight trajectory fitting preprocessing is added to build the completed multilayer cyclic convolutional improvement model (MCCI). The experimental results show that the MCCI model has obvious advantages in terms of prediction accuracy, deviation range and predictable duration when dealing with the LFW UAV 4D trajectory prediction problem, and better reflects the characteristics of 3D position and spatiotemporal elements. The comparative analysis shows that the error values of the MCCI model are smaller than those of the comparison prediction models in any dimension, and the prediction results have better fit and model performance.

Calcium Role in Gap Junction Channel Gating: Direct Electrostatic or Calmodulin-Mediated?

The chemical gating of gap junction channels is mediated by cytosolic calcium (Ca2+i) at concentrations ([Ca2+]i) ranging from high nanomolar (nM) to low micromolar (µM) range. Since the proteins of gap junctions, connexins/innexins, lack high-affinity Ca2+-binding sites, most likely gating is mediated by a Ca2+-binding protein, calmodulin (CaM) being the best candidate. Indeed, the role of Ca2+-CaM in gating is well supported by studies that have tested CaM blockers, CaM expression inhibition, testing of CaM mutants, co-localization of CaM and connexins, existence of CaM-binding sites in connexins/innexins, and expression of connexins (Cx) mutants, among others. Based on these data, since 2000, we have published a Ca2+-CaM-cork gating model. Despite convincing evidence for the Ca2+-CaM role in gating, a recent study has proposed an alternative gating model that would involve a direct electrostatic Ca2+-connexin interaction. However, this study, which tested the effect of unphysiologically high [Ca2+]i on the structure of isolated junctions, reported that neither changes in the channel's pore diameter nor connexin conformational changes are present, in spite of exposure of isolated gap junctions to [Ca2+]i as high at the 20 mM. In conclusion, data generated in the past four decades by multiple experimental approaches have clearly demonstrated the direct role of Ca2+-CaM in gap junction channel gating.

SAGB: self-attention with gate and BiGRU network for intrusion detection

Network traffic intrusion detection technology plays an important role in host and platform security. At present, machine learning and deep learning methods are often used for network traffic intrusion detection. However, the imbalance of relevant data sets will cause the model algorithm to learn the features of the majority categories and ignore the features of the minority categories, which will seriously affect the precision of network intrusion detection models. The number of samples of the attacks is much less than the number of normal samples. The classification performance on unbalanced data sets is poor and can not identify the minority attack samples well. To solve these problems, this paper proposed the resampling mechanism, which used random undersampling for the majority categories samples and K-Smote oversampling for the minority categories samples, so as to generate a more balanced data set and improve the model's detection rate for the minority categories. This paper proposed the Self-Attention with Gate (SAG) and BiGRU network model for intrusion detection on the CICIDS2017 data set, which can fully extract high-dimensional information from data samples and improve the detection rate of network attacks. The Self-Attention with Gate mechanism (SAG) based on the Transformer performed the feature extraction, filtered the irrelevant noise information, then extracted the long-distance dependency temporal sequence features by the BiGRU network, and obtained the classification results through the SoftMax classifier. Compared to the experimental results of other algorithms, such as Random Forest (RF) and BiGRU, it can be found that the overall classification precision for the SAG-BiGRU model in this paper is much higher and also has a good effect on the NSL-KDD data set.

Gaussian Process-Gated Hierarchical Mixtures of Experts.

In this article, we propose novel Gaussian process-gated hierarchical mixtures of experts (GPHMEs). Unlike other mixtures of experts with gating models linear in the input, our model employs gating functions built with Gaussian processes (GPs). These processes are based on random features that are non-linear functions of the inputs. Furthermore, the experts in our model are also constructed with GPs. The optimization of the GPHMEs is performed by variational inference. The proposed GPHMEs have several advantages. They outperform tree-based HME benchmarks that partition the data in the input space, and they achieve good performance with reduced complexity. Another advantage is the interpretability they provide for deep GPs, and more generally, for deep Bayesian neural networks. Our GPHMEs demonstrate excellent performance for large-scale data sets, even with quite modest sizes.

Circumventing construct-irrelevant variance in international assessments using cognitive diagnostic modeling: A curriculum-sensitive measure

International large-scale assessments such as TIMSS administer achievement tests that are based on an analysis of national curricula to compare student achievement across countries. The organizations that coordinate these studies use Rasch or more generalized item response theory (IRT) models in which all test items are assumed to measure a single latent ability. The test responses are then used to estimate this ability, and the ability scores are used to compare countries.A central but yet-to-be-contested assumption of this approach is that the achievement tests measure an unobserved unidimensional continuous variable that is comparable across countries. One threat to this assumption is the fact that countries and even regions or school tracks within countries have different curricula. When seeking to fairly compare countries, it seems legitimate to account for the fact that applicable curricula differ and that some students may not have been taught the full test content yet. When seeking to fairly compare countries, it seems imperative to account for the fact that national curricula differ and that some countries may not have taught the full test content yet. Nevertheless, existing IRT-based rankings ignore such differences.The present study proposes a direct method to deal with differing curricula and create a fair ranking of educational quality between countries. The new method compares countries solely on test content that has already been taught; it uses information on whether students have mastered skills taught in class or not and does not consider contents that have not been taught yet. Mastery is assessed via the deterministic-input, noisy, “and” gate (DINA) model, an interpretable and tractable cognitive diagnostic model. To illustrate the new method, we use data from TIMSS 1995 and compare it to the IRT-based scores published in the international study report. We find a mismatch between the TIMSS test contents and national curricula in all countries. At the same time, we observe a high correlation between the scores based on the new method and the conventional IRT scores. This finding underscores the robustness of the performance measures reported in TIMSS despite existing differences across national curricula.

Gating mechanism of the human α1β GlyR by glycine

Glycine receptors (GlyRs) are members of the Cys-loop receptors that constitute a major portion of mammalian neurotransmitter receptors. Recent resolution of heteromeric GlyR structures in multiple functional states raised fundamental questions regarding the gating mechanism of GlyR, and generally the Cys-loop family receptors. Here, we characterized in detail equilibrium properties as well as the transition kinetics between functional states. We show that, while all allosteric sites bind cooperatively to glycine, occupation of 2 sites at the α-α interfaces is sufficient for activation and necessary for high-efficacy gating. Differential glycine concentration dependence of desensitization rate, extent, and its recovery suggests separate but concerted roles of ligand-binding and ionophore reorganization. Based on these observations and available structural information, we developed a quantitative gating model that accurately predicts both equilibrium and kinetical properties throughout the glycine gating cycle. This model likely applies generally to the Cys-loop receptors and informs on pharmaceutical endeavors.

Propofol rescues voltage-dependent gating of HCN1 channel epilepsy mutants.

Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels1 are essential for pacemaking activity and neural signalling2,3. Drugs inhibiting HCN1 are promising candidates for management of neuropathic pain4 and epileptic seizures5. The general anaesthetic propofol (2,6-di-iso-propylphenol) is a known HCN1 allosteric inhibitor6 with unknown structural basis. Here, using single-particle cryo-electron microscopy and electrophysiology, we show that propofol inhibits HCN1 by binding to a mechanistic hotspot in a groove between the S5 and S6 transmembrane helices. We found that propofol restored voltage-dependent closing in two HCN1 epilepsy-associated polymorphisms that act by destabilizing the channel closed state: M305L, located in the propofol-binding site in S5, and D401H in S6 (refs. 7,8). To understand the mechanism of propofol inhibition and restoration of voltage-gating, we tracked voltage-sensor movement in spHCN channels and found that propofol inhibition is independent of voltage-sensor conformational changes. Mutations at the homologous methionine in spHCN and an adjacent conserved phenylalanine in S6 similarly destabilize closing without disrupting voltage-sensor movements, indicating that voltage-dependent closure requires this interface intact. We propose a model for voltage-dependent gating in which propofol stabilizes coupling between the voltage sensor and pore at this conserved methionine-phenylalanine interface in HCN channels. These findings unlock potential exploitation of this site to design specific drugs targeting HCN channelopathies.

Neural ensembles: role of intrinsic excitability and its plasticity.

Synaptic connectivity defines groups of neurons that engage in correlated activity during specific functional tasks. These co-active groups of neurons form ensembles, the operational units involved in, for example, sensory perception, motor coordination and memory (then called an engram). Traditionally, ensemble formation has been thought to occur via strengthening of synaptic connections via long-term potentiation (LTP) as a plasticity mechanism. This synaptic theory of memory arises from the learning rules formulated by Hebb and is consistent with many experimental observations. Here, we propose, as an alternative, that the intrinsic excitability of neurons and its plasticity constitute a second, non-synaptic mechanism that could be important for the initial formation of ensembles. Indeed, enhanced neural excitability is widely observed in multiple brain areas subsequent to behavioral learning. In cortical structures and the amygdala, excitability changes are often reported as transient, even though they can last tens of minutes to a few days. Perhaps it is for this reason that they have been traditionally considered as modulatory, merely supporting ensemble formation by facilitating LTP induction, without further involvement in memory function (memory allocation hypothesis). We here suggest-based on two lines of evidence-that beyond modulating LTP allocation, enhanced excitability plays a more fundamental role in learning. First, enhanced excitability constitutes a signature of active ensembles and, due to it, subthreshold synaptic connections become suprathreshold in the absence of synaptic plasticity (iceberg model). Second, enhanced excitability promotes the propagation of dendritic potentials toward the soma and allows for enhanced coupling of EPSP amplitude (LTP) to the spike output (and thus ensemble participation). This permissive gate model describes a need for permanently increased excitability, which seems at odds with its traditional consideration as a short-lived mechanism. We propose that longer modifications in excitability are made possible by a low threshold for intrinsic plasticity induction, suggesting that excitability might be on/off-modulated at short intervals. Consistent with this, in cerebellar Purkinje cells, excitability lasts days to weeks, which shows that in some circuits the duration of the phenomenon is not a limiting factor in the first place. In our model, synaptic plasticity defines the information content received by neurons through the connectivity network that they are embedded in. However, the plasticity of cell-autonomous excitability could dynamically regulate the ensemble participation of individual neurons as well as the overall activity state of an ensemble.

Hydrogen leakage risk assessment of HECS based on dynamic bayesian network

As a new energy system, the hydrogen-electric coupling system（HECS） involves complex conditions with multiple hazards such as electricity, hydrogen, heat, and high pressure, and there are complex safety risk issues. This paper proposes a hydrogen leakage risk assessment method of HECS based on dynamic Bayesian networks (DBN). Firstly, the bow-tie model is mapped to the DBN model, and the prior probability of the DBN model is obtained using intuitionistic fuzzy theory, Dempster-Shafer evidence theory, and an improved similarity aggregation algorithm. Then, leakage noise or gate models are introduced to improve the conditional probability table of the DBN model, and Weibull distributions are used to construct the probability transfer process between different time periods. Finally, through practical case studies, it is shown that the proposed method can effectively predict the dynamic probability and potential consequences of failure events through time series information. Sensitivity analysis proves the practicality and robustness of the proposed method. The research results can provide theoretical support for risk assessment and daily maintenance of HECS.

Evaluating a National Traditional Chinese Medicine Examination via Cognitive Diagnostic Approaches

The current research utilized diagnostic classification models (DCMs), an advanced psychometric theory, to evaluate the examination’s quality using psychometric methods for a more precise and comprehensive understanding of health professionals’ competence. Data was gathered from 16,310 fourth-year Traditional Chinese Medicine undergraduates who completed the Standardized Competence Test for Traditional Chinese Medicine Undergraduates (SCTTCMU) comprising 300 multiple-choice items. The study examined the fundamental assumptions, model-data fit, and cognitive diagnostic theory models’ item and test properties. The generalized deterministic input, noisy, “and” gate model applied in this research demonstrated a strong alignment with the real response data, meeting all the necessary assumptions. Cognitive diagnostic analysis indicated that all items exhibited satisfactory psychometric characteristics, and the reported scores offered insights into candidates’ proficiency in cognitive skills. It is expected that the advent of modern psychometric technology will contribute to the improvement of refined diagnostic information for health professional candidates. Furthermore, this research holds the potential to significantly enhance sustainability in healthcare practices, knowledge, economics, resource use, and community resilience.

Connection strength analysis for composite fuselage gate structures of civil aircraft

Civil aircraft boarding gate is an important channel for passengers to enter and exit the aircraft, and is also an important part of the aircraft structure, with the function of maintaining cockpit pressure. Traditional boarding doors are made of metal, and with the large number of composite materials used in the bearing structure of civil aircraft, composite boarding doors are also used in new civil aircraft. The strength of the connection inside the new composite boarding gate is related to the safety of passengers and crew. This paper focuses on the connection problem of the internal structure of composite boarding gate, aiming to analyze its connection strength under working conditions. This paper establishes a real finite element model of the boarding gate according to the loading condition and force transmission characteristics of the civil aircraft door and analyzes the connection strength of the structure such as the skin and the transverse and longitudinal beams, the skin and the side frame, the transverse and longitudinal beams connection, and the stop block in turn. The study shows that the strength of the connecting structures of the boarding gate designed by using composite materials is reasonable and can meet the service requirements of the boarding gate, thus demonstrating the rationality of the boarding gate structure designed with composite materials.