Core Subsystem Research Articles

A default mode network subsystem supports both item and associative word encoding: Insights from a meta-analysis

Abstract Recent meta-analytic evidence has underscored the significant role of the default mode network (DMN) in facilitating item word encoding. This study builds on this finding through a comprehensive meta-analysis of fMRI-based subsequent memory studies that use words as stimuli. The results highlight several key functions within the DMN. Firstly, the dorsomedial prefrontal cortex (dmPFC) subsystem of the DMN plays a pivotal role in enhancing successful word encoding, suggesting its vital involvement in the semantic processing of incoming verbal information. Secondly, the utility of the dmPFC subsystem extends beyond item word encoding to associative word encoding tasks, demonstrating its broad applicability in verbal information encoding. Thirdly, regions within the left inferior frontal cortex, a core component of the dmPFC subsystem, show increased activity during associative compared to item word encoding, emphasizing their role in integrating verbal information with contextual details. Contrary to previous research that linked the DMN with encoding interference—often attributed to the core subsystem’s tendency for mind-wandering—this study highlights the facilitative role of the dmPFC subsystem in memory encoding. The contrasting roles of the DMN subsystems, both interfering and facilitating, challenge traditional views and advocate for a more nuanced understanding of the network’s role in memory encoding.

Reduced resting-state functional connectivity of default mode network subsystems in patients with obsessive-compulsive disorder

ObjectivesNeuroimaging studies have reported extensive resting-state functional connectivity (rsFC) abnormalities in the default mode network (DMN) in patients with obsessive-compulsive disorder (OCD), but findings are inconsistent. DMN can be divided into three subsystems: core, dorsal medial prefrontal cortex (dMPFC), and medial temporal lobe (MTL). This study aimed to explore abnormalities in rsFC strength within and between DMN subsystems in OCD patients, and their relationship with clinical symptoms. MethodsThis study recruited 39 OCD patients and 45 healthy controls (HCs). OCD symptoms were assessed using the Yale-Brown Obsessive-Compulsive Scale (YBOCS). The seed-to-seed method was used to construct rsFC matrix. The rsFC strength within and between the three DMN subsystems were calculated. ResultsCompared to the HC group, the OCD group exhibited reduced rsFC strength within core subsystem (F = 7.799, p = 0.007, Bonferroni corrected p = 0.042). Further, this reduction was also observed in the unmedicated OCD group (n = 19), but not in the medicated OCD group (n = 18). In addition, rsFC strength within core subsystem was negatively correlated with the obsession subscale of YBOCS in the OCD group (r = −0.512, p = 0.004, Bonferroni corrected p = 0.008). Further, this correlation was also significant in the unmedicated OCD group, but not in the medicated OCD group. ConclusionsOur findings suggest that reduced rsFC strength within core subsystem is a feature of OCD patients and may serve as a potential biomarker of obsession severity. Moreover, pharmacological treatments may affect rsFC strength in DMN.

Defining and identifying the critical elements of operational readiness for public health emergency events: a rapid scoping review

IntroductionCOVID-19 showed that countries must strengthen their operational readiness (OPR) capabilities to respond to an imminent pandemic threat rapidly and proactively. We conducted a rapid scoping evidence review to understand...

Dynamic characteristics of scraper conveyor chain drive system under the impact condition of lump coal.

Scraper conveyor is the most important transportation equipment in the comprehensive mining equipment, and the chain drive system is its core subsystem, its dynamic characteristics will significantly affect the efficiency of coal transportation in the comprehensive mining face. In this paper, the dynamic characteristics of chain drive system when impacted by falling coal are investigated by means of test. The impact test bench of scraper conveyor was set up to analyze the effects of chain speed, impact height and impact load mass on the dynamic characteristics of the chain drive system of scraper conveyor under the working conditions of unloaded and loaded. The results show that the longitudinal vibration of the scraper conveyor is most obvious when it is impacted by the falling coal, and the chain speed, impact height and impact load mass of the scraper conveyor all play an excitation role on the vibration of the chain drive system, and the vibration of the chain ring is the most intense in the chain drive system, and the loaded coal pile conveyed on the scraper conveyor plays an inhibiting role on the vibration of the chain drive system. This study can help to identify the location where the scraper conveyor fails first in the impact condition, so as to provide a basis for its structural design and improvement, which is of great significance for the stable operation and structural optimization of the scraper conveyor.

Batch testing and noise rate optimization of MRPC3b for CBM-TOF/STAR-eTOF

The Compressed Baryonic Matter (CBM) experiment is one of the major scientific spectrometers of the future Facility for Antiproton and Ion Research (FAIR) in Darmstadt. As one of the core sub-systems in CBM experiment for charged hadron identification, the Time-of-Flight (TOF) system is required to have a time resolution better than 80 ps. According to the final state particle flux distribution, the CBM-TOF will be constructed with several types of Multi-gap Resistive Plate Chambers (MRPC). In the outer region of the TOF wall where the particle fluxes are around 1 kHz/cm2, MRPCs with ultra-thin float glass electrodes are considered as a cost effective solution. MRPC3b prototypes have been developed and tested with excellent performance which could meet all the requirements. Before the construction of CBM-TOF, approximately 80 MRPC3bs are assembled for the STAR endcap TOF (STAR-eTOF) upgrade at RHIC as part of the FAIR Phase-0 programs for CBM-TOF which provides a valuable opportunity for detector stability test under high flux environments. This paper will introduce the batch test of the MRPC3bs for STAR-eTOF upgrade. Time resolution of better than 70 ps and efficiency of around 95% are achieved. Notably, during the batch test, it has been observed that the noise rates of the two edge strips in each counter are significantly higher than those of the middle strips. Simulations with Computer Simulation Technology (CST) Studio Suite are carried out and several kinds of MRPC prototypes are designed and tested accordingly. Based on the simulation and test results, the design of the MRPC3b has been further optimized by modify the shape and position of High-Voltage injection pad and increasing the distance between the glass edge and both end strips, resulting in a significant suppression of noise rates in the edge strips.

Identification of Lossy Y-Type Two-Port Circuit Models under Measurement Uncertainties: Closed-Form Solution and Statistical–Perturbative Characterization

The present paper treats a black-box estimation of the three independent parameters of a reciprocal lossy two-port network whose terminals are supposed to be accessible to an impedance measurement device. The discussed estimation method is based on the availability of a number of data pairs made of external load admittances paired to equivalent external admittances affected by measurement errors. The proposed method is framed as a squared-estimation-error minimization problem that leads to a system of three nonlinear equations in the three unknown parameters. A key observation is, however, that a core subsystem of two equations may be turned exactly to a linear form and hence may be solved in closed form. The purely real-valued case is treated first since it serves to clarify the optimization problem at hand and the structure of its solution. In the purely real-valued case, a statistical analysis is carried out as well, which affords the evaluation of the effects of the measurement errors. The results of the statistical analysis afford quantifying the dependence of the estimation errors from the number of samples and from the variance of the measurement errors. Subsequently, the full complex-valued case is treated. Results of numerical simulations complement and illustrate the theoretical findings. The obtained numerical results confirm the statistical analysis and that the proposed external identification method is effective.

Dynamic Characteristics of the Chain Drive System under Multiple Working Conditions

The chain drive system, being one of the core subsystems of the scraper conveyor, greatly influences the coal-conveying efficiency due to its dynamic characteristics. Therefore, this paper employed an experimental method to compare the dynamic characteristics of the chain rings at various positions within the chain drive system. This article simulated the three most common working conditions. The results indicated that the chain speed, load, and surface undulation had a stimulating effect on chain vibration, with the most significant impact observed on the chain ring located in the middle of the adjacent scraper. The scraper exerted an inhibitory effect on the vibration of the chain ring. Among the factors studied, the load had the most significant influence on the transverse direction. When there was surface undulation, the vibration of the chain ring in the running direction formed an ‘N’ shape. This condition intensified the vibration during uphill and downhill stages while suppressing vibration at the slope peak. This research holds great significance in enhancing operation stability.

Differences in the Default Mode Network of Temporal Lobe Epilepsy Patients Detected by Hilbert-Huang Transform Based Dynamic Functional Connectivity.

Resting-state functional connectivity, constructed via functional magnetic resonance imaging, has become an essential tool for exploring brain functions. Aside from the methods focusing on the static state, investigating dynamic functional connectivity can better uncover the fundamental properties of brain networks. Hilbert-Huang transform (HHT) is a novel time-frequency technique that can adapt to both non-linear and non-stationary signals, which may be an effective tool for investigating dynamic functional connectivity. To perform the present study, we investigated time-frequency dynamic functional connectivity among 11 brain regions of the default mode network by first projecting the coherence into the time and frequency domains, and subsequently by identifying clusters in the time-frequency domain using k-means clustering. Experiments on 14 temporal lobe epilepsy (TLE) patients and 21 age and sex-matched healthy controls were performed. The results show that functional connections in the brain regions of the hippocampal formation, parahippocampal gyrus, and retrosplenial cortex (Rsp) were reduced in the TLE group. However, the connections in the brain regions of the posterior inferior parietal lobule, ventral medial prefrontal cortex, and the core subsystem could hardly be detected in TLE patients. The findings not only demonstrate the feasibility of utilizing HHT in dynamic functional connectivity for epilepsy research, but also indicate that TLE may cause damage to memory functions, disorders of processing self-related tasks, and impairment of constructing a mental scene.

Dewey, Implementation, and Creating a Democratic Civic University

Dewey, Implementation, and Creating a Democratic Civic University

Failure Hazard Assessment of Three Gorges Ship Lift Drive System Based on Combined Weighting and TOPSIS Method

As the core subsystem of the ship lift, the drive system of the Three Gorges ship lift provides power for the operation of the ship lift, and its failure will directly affect the stable and safe operation of the ship lift. In view of the shortcomings of the existing evaluation methods for the failure hazard of the Three Gorges ship lift drive system, such as strong subjectivity and unreasonable weight of evaluation indexes, a failure hazard evaluation method for the Three Gorges ship lift drive system was proposed based on combined weighting and TOPSIS method. The effectiveness and feasibility of this method are verified by simulation of the Three Gorges ship lift drive system, which provides a new evaluation method for failure hazard analysis of key components of the Three Gorges ship lift.

Subsystem mechanisms of default mode network underlying white matter hyperintensity-related cognitive impairment.

Functional changes of default mode network (DMN) have been proven to be closely associated with white matter hyperintensity (WMH) related cognitive impairment (CI). However, subsystem mechanisms of DMN underlying WMH-related CI remain unclear. The present study recruited WMH patients (n=206) with mild CI and normal cognition, as well as healthy controls (HC, n=102). Static/dynamic functional connectivity (FC) of the DMN's three subsystems were calculated using resting-state functional MRI. K-means clustering analyses were performed to extract distinct dynamic connectivity states. Compared with the WMH-NC group, the WMH-MCI group displayed lower static FC within medial temporal lobe (MTL) and core subsystem, between core-MTL subsystem, as well as between core and dorsal medial prefrontal cortex subsystem. All these static alterations were positively associated with information processing speed (IPS). Regarding dynamic FC, the WMH-MCI group exhibited higher dynamic FC within MTL subsystem than the HC and WMH-NC groups. Altered dynamic FC within MTL subsystem mediated the relationship between WMH and memory span (indirect effect: -0.2251, 95% confidence interval [-0.6295, -0.0267]). Additionally, dynamic FCs of DMN subsystems could be clustered into two recurring states. For dynamic FCs within MTL subsystem, WMH-MCI subjects exhibited longer mean dwell time (MDT) and higher reoccurrence fraction (RF) in a sparsely connected state (State 2). Altered MDT and RF in State 2 were negatively associated with IPS. Taken together, these findings indicated static/dynamic FC of DMN subsystems can provide relevant information on cognitive decline from different aspects, which provides a comprehensive view of subsystem mechanisms of DMN underlying WMH-related CI.

Functional disconnection between subsystems of the default mode network in bipolar disorder

BackgroundDisruption in connectivity between default mode network (DMN) regions has previously been reported in bipolar disorder (BD). The current study aimed to investigate the dysfunction of the DMN subsystem in patients with BD during manic and depressive episodes and to explore its relationship with the symptoms of BD. MethodsFifty-two patients with bipolar disorder and 39 healthy controls were recruited. Eleven seed points were selected from three DMN subsystems. We performed seed-based resting-state functional connectivity (FC) analysis and obtained individual DMN FC matrices by computing the spatial correlations between pairs of FC maps. The strength of the connections within and between the three DMN subsystems, including the core subsystem, dorsal medial prefrontal cortex subsystem, and medial temporal lobe (MTL) subsystem, was used for group analyses. ResultsCompared with healthy controls, reduced FC between the core and MTL subsystem was observed in BD patients, especially in those with depressive episodes, but not in those with manic episodes. There were significant differences in core-MTL connectivity strength between the two patient groups during manic and depressive episodes. Moreover, core-MTL subsystem connectivity was negatively correlated with the depression scale. The FC within the core subsystem was negatively correlated with anxiety and negatively correlated with depression. ConclusionThis study provides evidence for an abnormal default network subsystem connection in bipolar disorder during manic and depressive episodes, revealing the neuropathological mechanism of the disease from the perspective of brain functional connectivity.

An approach for radical innovative design based on cross-domain technology mining in patents

The key to radical innovation lies in technological breakthroughs, and the key to technical breakthroughs lies in the application of cross-domain knowledge. However, in the conceptual design stage of new product development, the designer’s cognition and knowledge are limited and the retrieval and evaluation of cross-domain technologies is often subjective, making it difficult to generate radical concepts. To address the above issues, this paper proposes a method for cross-domain technology recommendation based on patent analysis. In this method, feature words in various domains of patents are used to generalise the abstract functions of product core subsystems, where designers can obtain more comprehensive cross-domain technologies. This is conducive to breaking the design fixation of designers. Subject–Action–Object structural and functional similarity are combined to quickly extract cross-domain technologies in patents. Then multiple technical indicators are used to objectively evaluate and rank cross-domain technologies. This approach helps designers objectively select cross-domain technologies to change the way next-generation products work, enabling early planning of production conditions and a head start in the market. The method has been verified in a new product development project on peeling equipment, a new product that meets radical indicators is finally obtained.

Functional connectivity of the default mode network subsystems in patients with major depressive episodes with mixed features

BackgroundThe neuroimaging mechanism of major depressive episodes with mixed features (MMF) is not clear.AimsThis study aimed to investigate the functional connectivity of the default mode network (DMN) subsystems among patients...

Neural underpinnings of default mode network on empathy revealed by intracranial stereoelectroencephalography.

Empathy is the ability to understand and share the feelings of others. It is fundamental to emotional intelligence and social iterations. Neuroimaging studies have demonstrated that empathy activates brain regions associated with the social cognition network. To explore the neural underpinnings of empathy revealed by stereoelectroencephalography utilizing recurrence quantification analysis (RQA). This retrospective cohort included 38 epilepsy patients with stereoelectroencephalography implantation. RQA metrics were applied to parameterize the network organization of default mode network (DMN) brain regions. The relationships between DMN, seizure burden activity, and empathy, as measured using the Interpersonal Reactivity Index, were examined using partial least-square regression and mediation analysis. RQA metrics with DMN (R2 = 0.75, PBonferroni < 0.001) and its subsystems (medial temporal subsystem: R2 = 0.53, PBonferroni < 0.001; core subsystem: R2 = 0.70, PBonferroni < 0.001; dorsal medial subsystem: R2 = 0.48, PBonferroni < 0.001) were positively correlated with empathy scores. Of 13 RQA metrics, the mean diagonal line length, entropy of the diagonal line lengths, trapping time, maximal vertical line length, and recurrence time of second type were found to be statistically higher in patient cohorts with reportedly high empathy. Furthermore, DMN characteristics (b path: F= 3.69, P= 0.04), rather than seizure burdens (direct effect: t= 0.33, P= 0.74, c'= - 0.007), mediated empathy status. The present study used various RQA metrics to parameterize the network organization of DMN and determine the neural underpinning of DMN for empathy modulation.

Inflammation Disrupts Cognitive Integrity via Plasma Neurofilament Light Chain Coupling Brain Networks in Alzheimer's Disease.

Background: Plasma neurofilament light chain (NFL) is a recognized biomarker for Alzheimer's disease (AD) and inflammation. Intrinsically organized default mode network core subsystem and frontoparietal network (FPN) and their interactions support complex cognitive function. The present study investigated the inflammatory effect on cognitive integrity via plasma NFL coupling internetwork interactions in AD. Objective: This study investigates the hypothesis that inflammation-related plasma NFL could affect the interactions of the core subsystem and FPN, which leads to the aggravation of the clinical symptoms of AD-spectrum patients. Methods: A total of 112 AD-spectrum participants underwent complete resting-state fMRI, neuropsychological tests, and plasma NFL at baseline (n = 112) and after approximately 17 months of follow-up (n = 112). The specific intersystem changes in the core subsystem and FPN were calculated and compared across groups. Then, the classifications of different AD-spectrum groups were analyzed using the association of plasma NFL and the changed intersystem interacting regions. Finally, mediation analysis was applied to investigate the significance of plasma NFL coupling networks on cognitive impairments in these subjects. Results: Discrimination of disease-related interactions of the core subsystem and FPN was found in AD-spectrum patients, which was the neural circuit fundamental to plasma NFL disrupting cognitive integrity. Furthermore, the clinical significance of plasma NFL coupling networks on AD identification and monitoring cognitive impairments were revealed in these subjects. The characteristic change in inflammation-related plasma NFL coupled with brain internetwork interactions could be used as a potential observation indicator in the progression of AD patients.

Conceptual Modeling of Extended Collision Warning System from the Perspective of Smart Product-Service System.

While Product-Service Systems (PSS) have a potential sustainability impact by increasing a product’s life and reducing resource consumption, the lack of ownership might lead to less responsible user behavior. Smart PSS can overcome this obstacle and guarantee correct and safe PSS use. In this context, intelligent connected vehicles (ICVs) with PSS can effectively reduce traffic accidents and ensure the safety of vehicles and pedestrians by guaranteeing optimal and safe vehicle operation. A core subsystem to support that is the collision-warning system (CWS). Existing CWSs are, however, limited to in-car warning; users have less access to the warning information, so the result of CWS for collision avoidance is insufficient. Therefore, CWS needs to be extended to include more elements and stakeholders in the collision scenario. This paper aims to provide a novel understanding of extended CWS (ECWS), outline the conceptual framework of ECWS, and contribute a conceptual modeling approach of ECWS from the smart PSS perspective at the functional level. It defines an integrated solution of intelligent products and warning services. The function is modeled based on the Theory of Inventive Problem Solving (TRIZ). Functions of an ECWS from the perspective of smart PSS can be comprehensively expressed to form an overall solution of integrated intelligent products, electronic services, and stakeholders. Based on the case illustration, the proposed method can effectively help function modeling and development of the ECWS at a conceptual level. This can effectively avoid delays due to traffic accidents and ensure the safety of vehicles and pedestrians.

Research on the Transformation from Financial Accounting to Management Accounting Based on Drools Rule Engine.

With the development of Internet economy and the advent of artificial intelligence era, the transformation from financial accounting to management accounting has become an inevitable trend of financial management among companies. In this paper, the significance of the transformation from financial accounting to management accounting is expounded under the background of artificial intelligence, and the current situation, problems and reasons of the transition are analyzed. In addition, the development of self-management accounting system based on Drools rule engine is put forward, including rule management, rule engine and so on. The core processes such as pattern matching and auto-billing are analyzed, and then the core subsystems such as data receiving and processing, accounting rule engine are designed in detail. Finally, the technological advancement and structural stability of this system are discussed, which can provide reference for promoting the transformation from financial accounting to management accounting under artificial intelligence.

Evaluating the Function of the Foot Core System in the Elderly.

As a complex structure to link the body and the ground, the foot contributes to postural control in human static and dynamic activities. The foot core is rooted in the functional interdependence of the passive, active, and neural subsystems, which combine into the foot core system controlling foot motion and stability. The foot arch (passive subsystem), responsible for load, is considered the functional core of the foot, and its stability is necessary for normal foot functions. The functional abnormalities of the foot have been widely reported in the elderly, such as weakness of toe flexor muscles, abnormal foot postures, and decreased plantar sensory sensitivity. In this paper, a comprehensive approach is introduced for evaluating the foot function based on foot core subsystems. The strength and morphology of the foot intrinsic and extrinsic muscles were used to evaluate the foot muscle (active subsystem) function. The doming strength test was applied to determine the function of foot intrinsic muscles, while the toe flexion strength test focused more on the function of extrinsic muscles. The navicular drop test and foot posture index were applied to evaluate foot arch (passive subsystem) function. For the neural subsystem, the plantar light touch threshold test and two-point discrimination test were used to assess plantar tactile sensitivity at nine regions of the foot. This study provides new insights into the foot core function in the elderly and other populations.

Default mode network connectivity and attention-deficit/hyperactivity disorder in adolescence: Associations with delay aversion and temporal discounting, but not mind wandering

BackgroundAttention-deficit/hyperactivity disorder (ADHD) has been associated with reduced resting state connectivity in the core subsystem of the default mode network (DMN; medial prefrontal cortex – posterior cingulate cortex). However, the neuropsychological consequences of this hypoconnectivity remain to be determined. Building on recent theoretical models of DMN function, we tested the association between DMN hypo-connectivity and three neuropsychological processes previously implicated in ADHD: (i) excessive task-unrelated spontaneous thought (i.e., mind-wandering); (ii) sub-optimal decision-making due to exaggerated temporal discounting; and (iii) delay aversion – a heightened emotional response to the imposition or experience of delay. MethodsTwenty male adolescents with a clinical diagnosis of ADHD and 18 typically developing adolescents (all aged 11–16 years) underwent a resting-state fMRI scan to assess DMN connectivity. An experimental paradigm was used to assess temporal discounting and self-report questionnaires were used to measure mind wandering and delay aversion. ResultsADHD was significantly associated with DMN hypo-connectivity specifically in the core subsystem, elevated levels of mind-wandering, delay aversion, and temporal discounting. Mediation analysis suggested that DMN hypoconnectivity mediated the link between ADHD and delay aversion. ConclusionThe results provide initial evidence that disturbances in the DMN may impair ability to regulate delay-related negative affect in adolescents with ADHD.