Fluctuations In State Research Articles

Study on energy efficiency improvement strategy of photovoltaic-hybrid energy storage DC microgrid considering green energy saving concepts

Abstract In this paper, the development of microgrid technology is discussed in close connection with the growing energy demand and the real needs of energy structure adjustment in the context of the times. Guided by green energy saving, the research focuses on constructing a hybrid energy storage DC microgrid model, especially the integrated photovoltaic power generation model and the related control strategy and power characteristics. The article further adopts a fuzzy PID control strategy to optimize the energy efficiency configuration of hybrid energy storage devices in DC microgrids. By carefully analyzing and optimizing the energy storage system in the DC microgrid, remarkable results are obtained: the optimized capacitive charge states range from 0.1 to 0.9, indicating a significant fluctuation of capacitive charge states, but at the same time avoiding the phenomenon of light abandonment and ensuring the reliability of power supply. More notably, during the increase of SOC (state of the energy storage system) from 0.40 to 0.70, the system can perform mode transitions under continuous load changes. This point shows the effectiveness of the optimization method in improving the energy storage efficiency and enhancing the system performance of the DC microgrid. Overall, the optimization method proposed in this paper provides a practical energy storage optimization scheme for developing microgrids, which is of great practical significance in promoting the research and application of microgrid technology. This not only helps to improve the efficiency of energy use, but also is a crucial step to realize sustainable energy development.

ATLAS measurement of mean momentum fluctuations and correlations with the flow in Xe+Xe and Pb+Pb collisions

The thermal fluctuations in the QGP medium formed in heavy ion collisions present themselves as event-wise mean transverse momentum ([pT]) fluctuations in the final state. Recent studies have shown that the fluctuations are sensitive to radial flow, random thermal motion, and nuclear deformation. They can provide constraints on the extent of thermalization of the QGP droplet. Recently, correlations of [pT] with flow harmonic coefficients (vn) also gained interest, as they were found to be sensitive primarily to the initial state fluctuations. This talk presents precise measurements of up to 3rd order [pT] cumulants as a function of multiplicity and centrality with an emphasis on ultra-central collisions. These results have strong implications for understanding the impacts of the initial condition, medium thermalization, and medium properties on final state [pT] fluctuations.

Tuning magnetoresistance of chromium chloride tunnel junction through the interface and multi-field effect

<sec>Magnetic tunnel junctions (MTJs) serve as essential platforms for investigating spin transport properties, magnetic phase transitions, and anisotropy in magnetic materials. Recently two-dimensional van der Waals antiferromagnetic insulators like chromium chloride (CrCl<sub>3</sub>) or chromium iodide (CrI<sub>3</sub>) have been used to develop spin-filtering magnetic tunnel junctions (sf-MTJs), improving the device performance for material property exploration and spintronic applications. However, it is crucial to recognize that the spin-filtering effect is not the sole determining factor of tunneling magnetoresistance (TMR) in these junctions; the interface magnetic exchange interactions and adjustable electrode density of states (DOS) fluctuations, response to applied electric or magnetic fields, can also influence the tunneling current.</sec><sec>In this study, we fabricate MTJ devices by using mechanically-exfoliated few-layer CrCl<sub>3</sub> as the tunnel barrier and few-layer graphene (FLG) as electrodes through dry transfer technique. Conducting low-temperature quantum transport measurements, we observe unconventional TMR behaviors, including bias-voltage-dependent TMR, oscillatory tunneling current under high magnetic fields, and tunable tunneling current via gate voltage.</sec><sec>A qualitative model of elastic tunneling current is employed to analyze the spin and band characteristics of the MTJ device. The observed bias-voltage-dependent TMR is attributed to the changes in the tunneling mechanism due to magnetic proximity effect, which induces magnetization in the FLG electrode near the FLG/CrCl<sub>3</sub> interface. The antiparallel alignment of polarized spin to CrCl<sub>3</sub>’s magnetization results in injected charge carriers facing a higher tunnel barrier, leading to negative TMR at lower bias voltages. As the bias voltage increases, the magnetic proximity effect lessens, and the device reverts to its conventional spin-filtering functionality. The oscillatory tunneling current is explained by the graphene electrode’s quantum oscillatory density of states behavior under vertical magnetic fields, which can be controlled by the applied gate voltage.</sec><sec>This study contributes to the understanding of previously unexplored TMR phenomena in two-dimensional MTJs, deepening our insights into carrier transport properties in these heterostructures and broadening avenues for investigating the physical properties of two-dimensional magnetic materials and their spintronic applications.</sec>

Protocol-based SMC for singularly perturbed switching systems with sojourn probabilities

This paper focuses on the finite-time sliding mode control for singularly perturbed switching systems in the presence of sojourn probabilities. To effectively capture the dynamic behavior of singularly perturbed switching systems, a generalized framework of piecewise-homogeneous sojourn probabilities is established. Additionally, a novel event-triggered protocol is introduced to alleviate transmission frequency, making use of dynamic quantization and adjustable triggering thresholds to accommodate system state fluctuations. Besides, an asynchronous sliding mode control law is designed, using a suitable sliding function and hidden-Markov model strategy, to ensure the trajectory of the resulting singularly perturbed switching systems reaches the predefined sliding surface within a finite-time interval. Finally, the proposed method is validated using a numerical example and two practical models, demonstrating its effectiveness and practicality.

A 2-year mental health follow-up study subsequent to COVID-19

The COVID-19 pandemic has profoundly impacted the mental health and education of college students. This study examined the interrelationships among loneliness, resilience, and COVID-19 fear among college students in Northern Michigan, a region of the United States severely affected by the pandemic. Data were collected from two student cohorts (n = 258), with half surveyed in early 2022 and the other half in mid-2022, two years after pandemic's onset. The Omicron wave peaked in Michigan in January 2022, but by June 2022, cases, hospitalizations, and deaths had significantly declined. Students completed measures of loneliness, resilience, learning difficulty, and psychological symptoms. Key findings are: 1) Participants' fear, loneliness, and academic difficulty decreased over time, reflecting fluctuations in acute situational and emotional states; 2) Unexpectedly, resilience declined from early to mid-2022, suggesting its diminishing protective role under prolonged, pandemic-induced stress; 3) Despite improvements, students continued reporting high academic difficulties. Loneliness, heightened fear, and dampened happiness together contributed to greater academic difficulties; 4) Pre-existing sex differences equalized two years after the pandemic's onset. While modest improvements were noted, enduring academic and mental health impacts signal a need for continued support.

Formation control of multi-agent systems with actuator saturation via neural-based sliding mode estimators

In this paper, the formation control problem for second-order multi-agent systems with model uncertainties and actuator saturation is investigated. An estimator-based robust formation controller is developed to ensure boundedness of the system’s formation tracking error. To estimate uncertain factors without prior knowledge of their Lipschitz constants, two new estimator designs that combine the neural-based estimation process and the sliding mode technique are proposed. Finite-time stability is achieved by introducing a new terminal estimation surface. Regarding the formation controller design, we provide a new framework to study the combined effect of input saturation and input coupling. Both an adaptive compensator and an input regulation algorithm are employed to attenuate state fluctuation led by the reverse effect. Comparative simulations regarding a multi-robot system are conducted to demonstrate the effectiveness of the proposed estimators and the estimator-based controller.

Outlining a novel psychometric model of mental flexibility and affect dynamics.

Theoretically, affective states have always been conceived as complex phenomena enabling individuals to respond flexibly and dynamically to environmental demands. Methodologically, the novel field of Affect Dynamics has started to analyze affective states as inherently dynamic and interdependent phenomena by focusing on how and why they fluctuate over time. Fluctuations of affective states can also be conceived as a function of individuals' ability to flexibly modulate their responses according to environmental demands. However, this ability has been sparsely investigated in different disciplines and domains, thus, engendering a plethora of terms and models. In this conceptual analysis, we first aimed to disentangle the puzzle of flexibility by outlining the distinctive cross-domain features of this concept, thus providing a novel comprehensive operationalization. We termed this novel unitary concept "mental flexibility," the general ability to variably adapt to environmental demands. Then, we outlined the interplay between individuals' mental flexibility and affect dynamics by proposing a novel psychometric model of affect dynamics, using Markovian chain.

Attention in hindsight: Using stimulated recall to capture dynamic fluctuations in attentional engagement.

Attentional engagement is known to vary on a moment-to-moment basis. However, few self-report methods can effectively capture dynamic fluctuations in attentional engagement over time. In the current paper, we evaluated the utility of stimulated recall, a method wherein individuals are asked to remember their subjective states while using a mnemonic cue, for the measurement of temporal changes in attentional engagement. Participants were asked to watch a video lecture, during which we assessed their in-the-moment levels of attentional engagement using intermittent thought probes. Then, we used stimulated recall by cueing participants with short video clips from the lecture to retrospectively assess the levels of attentional engagement they had experienced when they first watched those clips within the lecture. Experiment 1 assessed the statistical overlap between in-the-moment and video-stimulated ratings. Experiment 2 assessed the generalizability of video-stimulated recall across different types of lectures. Experiment 3 assessed the impact of presenting video-stimulated probe clips in non-chronological order. Experiment 4 assessed the effect of video-stimulated recall on its own. Across all experiments, we found statistically robust correspondence between in-the-moment and video-stimulated ratings of attentional engagement, illustrating a strong convergence between these two methods of assessment. Taken together, our findings indicate that stimulated recall provides a new and practical methodological approach that can accurately capture dynamic fluctuations in subjective attentional states over time.

PH-Dependent Structure and Dynamics of the Catalytic Domains of Human Carbonic Anhydrase II and IX.

Extensive computer simulation studies have been carried out to probe the pH-dependent structure and dynamics of the two most efficient isoenzymes II and IX of human carbonic anhydrase (HCA) that control the pH in the human body. The equilibrium structure and hydration of their catalytic domains are found to be largely unaffected by the variation of pH in the range studied, in close agreement with the known experimental results. In contrast, a significant effect of the change in pH is observed for the first time on the local electrostatic potential of the active site walls and the dynamics of active site water molecules. We also report for the first time the free energy and kinetics of coupled fluctuations of orientation and protonation states of the well-known His-mediated proton shuttle (His-64) in both isozymes at pH 7 and 8. The transitions between different tautomers of in or out conformations of His-64 side chain range between 109 and 106 s-1 depending on pH. Possible implications of these results on conformation-dependent pKa of His-64 side chain and its role in driving the catalysis toward hydration of CO2 or dehydration of HCO3- with varying pH are discussed.

Non-Markovian cost function for quantum error mitigation with Dirac Gamma matrices representation

This paper investigates the non-Markovian cost function in quantum error mitigation (QEM) and employs Dirac Gamma matrices to illustrate two-qubit operators, significant in relativistic quantum mechanics. Amid the focus on error reduction in noisy intermediate-scale quantum (NISQ) devices, understanding non-Markovian noise, commonly found in solid-state quantum computers, is crucial. We propose a non-Markovian model for quantum state evolution and a corresponding QEM cost function, using simple harmonic oscillators as a proxy for environmental noise. Owing to their shared algebraic structure with two-qubit gate operators, Gamma matrices allow for enhanced analysis and manipulation of these operators. We evaluate the fluctuations of the output quantum state across various input states for identity and SWAP gate operations, and by comparing our findings with ion-trap and superconducting quantum computing systems' experimental data, we derive essential QEM cost function parameters. Our findings indicate a direct relationship between the quantum system's coupling strength with its environment and the QEM cost function. The research highlights non-Markovian models' importance in understanding quantum state evolution and assessing experimental outcomes from NISQ devices.

80 Ecological Momentary Assessment of the Fluctuations in Cognitive Performance and Contextual States of Community-Dwelling Older Adults

Objective:Ecological momentary assessment (EMA) allows for tracking participant responses across multiple timepoints within the context of typical daily experiences. This study used EMA delivered via smartwatches to investigate dynamic associations between older adults’ fluctuations in cognitive performance as measured by an n-back test and self-reports of current internal (i.e., mental sharpness, fatigue, stress) and external (i.e., environmental distractions, time of day) contextual states over seven days. We hypothesized that 1) cognitive test fluctuations throughout the week would be meaningful beyond average cognitive test scores and 2) cognitive test scores would fluctuate in response to internal and external contexts.Participants and Methods:Participants were 28 community-dwelling older adults recruited for a larger clinical trial assessing the influence of lifestyle factors and compensatory strategy use on cognitive health. During week one of the trial, participants received a smartwatch which sent prompts four times a day for seven consecutive days. The prompts included a 45-second one-back shape test, along with Likert-style questions about their current experience. Questions assessing participants’ internal contexts asked about participants’ experience “right now” of mental sharpness, physical fatigue, and stress. External context was assessed via the EMA prompt, “Right now my environment is distracting,” and time of day of the response.Results:Data was screened such that all data points outside the 7-day prompt window were removed, one participant who did not respond to any prompts was removed, and participants who responded to less than 60% of the shape test prompts were removed (n = 10). The sample used for this preliminary analysis included 17 participants (Age, M = 71.94 years; Education, M = 14 years; 88% Female; 88% White) with an average compliance of 75% (Range = 17 - 26 shape test responses) and an average shape test accuracy of > 92%. Hypothesis 1 was supported by the large fluctuations of the average cognitive test scores across timepoints (M = 24.35, Min = 16, Max = 27, SD = 2.54) and by repeated-measures ANOVA of average cognitive test scores by day (F(1,7) = 5.24, p < 0.01). Hypothesis 2: Cross-correlation lags 0 to 4 were assessed. For internal contexts, cross-correlation showed a medium correlation between mental sharpness and cognition for lags 0 (r = 0.46) and 1 (r = 0.4); a small to medium correlation between physical fatigue and cognition for lags 0 (r = -0.51) and 1 (r = -0.31); and no correlation between stress and cognition (r < 0.2). For external contexts, cross-correlation revealed no correlation between environmental distraction and cognition (r < 0.3), and repeated measures ANOVA revealed no effect of time of day on cognition scores (p > 0.05).Conclusions:Older adults’ cognitive performance on an n-back shape test varied over time with internal contextual states. Cognitive performance was positively associated with feelings of mental sharpness and negatively associated with physical fatigue. Current external environmental distractions and time of day were less influential on cognitive performance. As more data is collected, influences of individual fluctuations in cognitive performance will be investigated.

Astronomical Pacing of Middle Eocene Sea‐Level Fluctuations: Inferences From Shallow‐Water Carbonate Ramp Deposits

AbstractAstrochronologically calibrated deep‐sea records document the Cenozoic (66–0 Ma) global climatic cooling in great detail, but the magnitude of sea‐level fluctuations of the middle Eocene Warmhouse state (47.8–37.7 Ma) and the ∼40.3 Ma warming event of the Middle Eocene Climatic Optimum (MECO) is not well constrained. Here, we present a sequence stratigraphic classification of a shallow marine mixed carbonate—clastic ramp system for this time interval in Paris basin, France. Based on sedimentologic, paleogeographic and biostratigraphic data, we hypothesize that the 22 elementary sequences recognized each correspond to the long cycle of orbital eccentricity (0.405 Myr). With the exception of the MECO, the shoreline trajectory of superimposed, third‐order depositional sequences evolved in phase with the very long cycles of orbital eccentricity (2.4 Myr), suggesting significant polar ice build‐up leading to sea level lowstands during nodes of the very long eccentricity cycle. Inferred from Fischer Plot methodology, Lutetian third‐order eustasy was in the order of 5–10 m and during the MECO 30 m or more. Furthermore, the shallow‐water record implies that third order sea‐level changes were astronomically paced in the middle Eocene Warmhouse climate state, but a decoupling occurred during the transient MECO warming.

Neurophysiological responses to emotional faces predict dynamic fluctuations in affect in adolescents.

The ability to accurately identify and interpret others' emotions is critical for social and emotional functioning during adolescence. Indeed, previous research has identified that laboratory-based indices of facial emotion recognition and engagement with emotional faces predict adolescent mood states. Whether socioemotional information processing relates to real-world affective dynamics using an ecologically sensitive approach, however, has rarely been assessed. In the present study, adolescents (N = 62; ages 13-18) completed a Facial Recognition Task, including happy, angry, and sad stimuli, while EEG data were acquired. Participants also provided ecological momentary assessment (EMA) data probing their current level of happiness, anger, and sadness for 1-week, resulting in indices of emotion (mean-level, inertia, instability). Analyses focused on relations between (1) accuracy for and (2) prolonged engagement with (LPP) emotional faces and EMA-reported emotions. Greater prolonged engagement with happy faces was related to less resistance to changes in happiness (i.e., less happiness inertia), whereas greater prolonged engagement with angry faces associated with more resistance to changes in anger (i.e., greater anger inertia). Results suggest that socioemotional processes captured by laboratory measures have real-world implications for adolescent affective states and highlight potentially actionable targets for novel treatment approaches (e.g., just-in-time interventions). Future studies should continue to assess relations among socioemotional informational processes and dynamic fluctuations in adolescent affective states.

Zircons reveal the history of fluctuations in oxidation state of crustal magmatism and supercontinent cycle

We apply a zircon redox index to a global compilation of detrital zircons to track the variation of oxidation state, expressed as ΔFMQ, through Earth’s history. Those from I-type rocks, which comprise mantle and crustal igneous protoliths, including tonalite–trondhjemite–granodiorites (TTGs), generally have a high oxidation state (ΔFMQ > 0). In contrast, zircons from igneous rocks derived from supracrustal source rocks (S-type) are commonly reduced (ΔFMQ < 0). With the probability density function derived from the Gaussian-Kernel-Density-Estimation, we use the maximum likelihood estimation (MLE) to distinguish S-type from I-type zircons through Earth’s history using zircon redox. Voluminous S-type magma production shows a ca. 600 Ma cyclicity that is closely related to the supercontinent cycle. We link a cyclic drop in redox values after 2.6 Ga to periodic S-type magma generation associated with burial and melting of metasedimentary rocks during supercontinent assembly and amalgamation. The ΔFMQ of the detrital zircons rise at ∼3.5 Ga followed by a consistent average ΔFMQ > 0 over the last 3 Ga. Given that the redox state of magmas is independent of crustal thickness and silica variation, and elevated values are likely more closely related to tectonic setting, we suggest that the consistent average ΔFMQ > 0 from ca. 3.5 Ga onwards relates to recycling of oceanic lithosphere back into the mantle in what eventually became established as subduction zones. The more reduced magmas associated with sedimentary sources, became established at 2.6 Ga, presumably in response to continental rocks rising above sea-level, and follow peaks of productivity associated with the supercontinent cycle.

Densely Packed CO2 Aids Charge, Spin, and Lattice Ordering Partially Fluctuated in a Porous Metal-Organic Framework Magnet.

Partial charge fluctuations in the charge-ordered state of a material, often triggered by structural disorders and/or defects, can significantly alter its physical characteristics, such as magnetic long-range ordering. However, it is difficult to post-chemically fix such accidental partial fluctuations to reconstruct a uniform charge-ordered state. Herein, we report CO2 -aided charge ordering demonstrated in a CO2 -post-captured layered magnet, [{Ru2 (o-ClPhCO2 )4 }2 {TCNQ(OMe)2 }] ⋅ CO2 (1⊃CO2 ; o-ClPhCO2 - =ortho-chlorobenzoate; TNCQ(OMe)2 =2,5-dimethoxy-7,7,8,8-tetracyanoquinodimethane). Pristine porous layered magnet 1 had a partially charge-fluctuated ordered state, which provided ferrimagnetic ordering at TC =65 K. Upon loading CO2 , 1 adsorbed one mole of CO2 , forming 1⊃CO2 , and raising TC to 100 K. This was because of the vanishing charge fluctuations without significantly changing the framework structure. This research illustrates the post-accessible host-guest chemistry delicately combined with charge, spin, and lattice ordering in a spongy magnet. Furthermore, it highlights how this innovative approach opens up new possibilities for technology and nanoscale magnetism manipulation.

Eeg-based mental states assessment of three-wheeler drivers in different environments and traffic conditions

Driving in diverse and challenging conditions, including inclement weather, poses potential risks to road safety. While previous studies have primarily focused on examining driver behavior and reactions in different weather and road conditions, there is a lack of research on assessing drivers' mental states during such situations, particularly considering the influence of factors such as road complexity, traffic, demographics, and adverse environmental conditions. This paper aims to address this research gap by evaluating the mental states of drivers across different age groups and driving experience levels through simulated driving scenarios encompassing various environments and traffic conditions. A three-wheeler driving simulator was employed, along with the DSI 7 EEG headset and Q states software, to classify and analyze the drivers' mental states. The findings of this study highlight that young novice drivers exhibit higher fluctuations in mental state compared to their mid and high-experienced counterparts. Furthermore, mid-age drivers face an elevated risk of collision due to frequent changes in mental state and attention. Additionally, it was observed that highly skilled drivers display a transition in attention level and mental state between sessions, shifting from a focused to a relaxed state—an aspect absent in inexperienced drivers. These findings enhance our comprehension of the intricate interaction among drivers' emotional states, age, experience, and driving abilities, consequently opening avenues for tailored interventions and training initiatives focused on improving road safety.

Apigenin promotes cell death in NCI-H23 cells by upregulation of PTEN: potential involvement of the binding of apigenin with WWP2 protein

The tumour suppressor protein PTEN is often down-regulated in non-small cell lung cancer. A major protein promoting the lowering of the PTEN protein is WWP2. Polyphenols have been shown to promote the expression of tumour suppressor genes like PTEN. We carry out the study to check for the ability of apigenin to bind with the WWP2 protein using in-silico investigation comprising docking and simulation. We checked for the cytotoxic effect of apigenin upon the non-small cell lung cancer cell line NCI-H23. We checked the PTEN expression status at the gene and protein levels. The expression levels of the apoptotic regulators BCL2, BAX and CASPASE3 genes along with the activity levels of the caspase-3 protein were checked. The ultrastructure of the cells was analysed. Our Autodock analysis showed that apigenin bound favourably with the WWP2 protein. Molecular dynamics simulation revealed that apigenin increased the parameters of RMSD, Rg and SASA when bound with the WWP2 protein. The protein-ligand complex had hydrogen bonding and majorly van der Wal’s interactions. PCA analysis revealed greater fluctuations in the apigenin-bound state of the protein. The mutant form of the WWP2 revealed similar results in the presence of apigenin. Apigenin showed efficacy against the NCI-H23 cell line and promoted PTEN protein levels, lowered BCL2 gene expression and up-regulated BAX and CASPASE3 gene expression. Increased caspase-3 activity and ultra-structural analysis revealed the occurrence of apoptosis. Thus the binding of apigenin with WWP2 could promote PTEN protein levels and lead to apoptotic activity in NCI-H23 cells. Communicated by Ramaswamy H. Sarma

TMS of parietal and occipital cortex locked to spontaneous transient large-scale brain states enhances natural oscillations in EEG

BackgroundFluctuating neuronal network states influence brain responses to transcranial magnetic stimulation (TMS). Our previous studies revealed that transient spontaneous bihemispheric brain states in the EEG, driven by oscillatory power, information flow and regional domination, modify cortical EEG responses to TMS. However, the impact of ongoing fluctuations of large-scale brain network states on TMS-EEG responses has not been explored. ObjectivesTo determine the effects of large-scale brain network states on TMS-EEG responses. MethodsResting-state EEG and structural MRI from 24 healthy subjects were recorded to infer large-scale brain states. TMS-EEG was acquired with TMS at state-related targets, identified by the spatial distribution of state activation power from resting-state EEG. TMS-induced oscillations were measured by event-related spectral perturbations (ERSPs), and classified with respect to the brain states preceding the TMS pulses. State-locked ERSPs with TMS at specific state-related targets and during state activation were compared with state-unlocked ERSPs. ResultsIntra-individual comparison of ERSPs by threshold free cluster enhancement (TFCE) revealed that posterior and visual state-locked TMS, respectively, increased beta and alpha responses to TMS of parietal and occipital cortex compared to state-unlocked TMS. Also, the peak frequencies of ERSPs were increased with state-locked TMS. In addition, inter-individual correlation analyses revealed that posterior and visual state-locked TMS-induced oscillation power (ERSP clusters identified by TFCE) positively correlated with state-dependent oscillation power preceding TMS. ConclusionsSpontaneous transient large-scale brain network states modify TMS-induced natural oscillations in specific brain regions. This significantly extends our knowledge on the critical importance of instantaneous state on explaining the brain's varying responsiveness to external perturbation.

Endogenous fluctuations in cortical state selectively enhance different modes of sensory processing in human temporal lobe

The degree of synchronized fluctuations in neocortical network activity can vary widely during alertness. One influential idea that has emerged over the past few decades is that perceptual decisions are more accurate when the state of population activity is desynchronized. This suggests that optimal task performance may occur during a particular cortical state – the desynchronized state. Here we show that, contrary to this view, cortical state can both facilitate and suppress perceptual performance in a task-dependent manner. We performed electrical recordings from surface-implanted grid electrodes in the temporal lobe while human subjects completed two perceptual tasks. We found that when local population activity is in a synchronized state, network and perceptual performance are enhanced in a detection task and impaired in a discrimination task, but these modulatory effects are reversed when population activity is desynchronized. These findings indicate that the brain has adapted to take advantage of endogenous fluctuations in the state of neural populations in temporal cortex to selectively enhance different modes of sensory processing during perception in a state-dependent manner.

An improved A-ECMS energy management for plug-in hybrid electric vehicles considering transient characteristics of engine

The plug-in hybrid electric vehicles (PHEVs) are playing an increasingly important role in urban public transportation systems for their unique potential for energy saving and emission reduction. However, as an enabling technology for the cost-efficient operation of PHEVs, the current energy management strategies (EMSs) rarely consider the transient characteristics of the engine, especially the limit of engine transient performance and the extra fuel consumption due to engine state changes. To improve the energy-saving effect of EMSs, an optimization study on energy management considering engine transient characteristics for PHEV is carried out in this paper. Firstly, a high-precision transient fuel consumption model is established based on artificial neural network (ANN) to accurately evaluate the real fuel consumption of engine under steady and unsteady states. Secondly, an adaptive equivalent consumption minimization strategy (A-ECMS) is constructed for PHEV, and the engine transient performance boundary is defined in the strategy to avoid unreasonable engine power surge decision. Thirdly, the transient fuel consumption model is incorporated into the equivalent fuel consumption cost function of A-ECMS to fully consider the impact of engine transient fuel consumption on the real-time power allocation of PHEV. The results show that the improved strategy weakens the state fluctuation of the engine, and makes the engine run more smoothly, resulting in a 99.16% reduction in the extra fuel consumption due to engine state changes. Finally, the fuel economy of the PHEV under the combined driving cycle based on the C-WTVC improved by 3.37%.