The metaphoric nature of the ordinal position effect

Serial orders are thought to be spatially represented in working memory: The beginning items in the memorised sequence are associated with the left side of space and the ending items are associated with the right side of space. However, the origin of this ordinal position effect has remained unclear. It was suggested that the direction of serial order–space interaction is related to the reading/writing experience. An alternative hypothesis is that it originates from the “more is right”/“more is up” spatial metaphors we use in daily life. We can adjudicate between the two viewpoints in Chinese readers; they read left-to-right but also have a culturally ancient top-to-bottom reading/writing direction. Thus, the reading/writing viewpoint predicts no or a top-to-bottom effect in serial order–space interaction; whereas the spatial metaphor theory predicts a clear bottom-to-top effect. We designed four experiments to investigate this issue. First, we found a left-to-right ordinal position effect, replicating results obtained in Western populations. However, the vertical ordinal position effect was in the bottom-to-top direction; moreover, it was modulated by hand position (e.g., left hand bottom or up). We suggest that order–space interactions may originate from different sources and are driven by metaphoric comprehension, which itself may ground cognitive processing

Assessing the causal relationship between genetically determined inflammatory biomarkers and low back pain risk: a bidirectional two-sample Mendelian randomization study

BackgroundObservational studies have suggested an association between inflammatory markers and low back pain (LBP), but the causal relationship between these factors remains uncertain.MethodsWe conducted a bidirectional two-sample Mendelian randomization analysis (MR) study to investigate whether there is a causal relationship between inflammatory markers and low back pain. We obtained genetic data for CRP, along with its upstream inflammatory markers IL-6, IL-8, and IL-10, as well as low back pain from publicly available genome-wide association studies (GWAS). We applied several MR methods, including inverse variance weighting, weighted median, MR-Egger, Wald Ratio, and MR-PRESSO, to test for causal relationships. Sensitivity analyses were also conducted to assess the robustness of the results.ResultsOur analyses utilizing the Inverse Variance Weighted (IVW) method, the MR-Egger method, and the weighted median method indicated that IL-6 may be associated with an increased risk of LBP (Effect Size: -0.009, 95% Confidence Interval: -0.013–0.006, p = 9.16e-08); however, in the reverse direction, there was no significant causal effect of LBP on inflammatory markers.ConclusionOur study used a Mendelian randomization approach and found that elevated IL-6 levels may reduce the risk of LBP

Addition and Subtraction but Not Multiplication and Division Cause Shifts of Spatial Attention

Many studies have shown that solving addition and subtraction problems can induce overt shifts of spatial attention. In particular, right-side targets are detected faster than left-side targets when preceded by an addition operation, while left-side targets are detected faster than right-side targets when preceded by a subtraction operation. However, the interaction between space and arithmetic in multiplication or division is hardly studied and remains controversial. In order to make a strong case for the interaction between space and mental arithmetic, we attempted to replicate the spatial-arithmetic association in addition and subtraction (Experiment 1), and at the same time investigated whether shift of spatial attention would also be induced by multiplication or division operations (Experiment 2). We found that solving addition problems facilitated the detection of right-side targets, whereas left-side targets were detected faster after solving subtraction problems. However, no interaction between space and arithmetic operation was observed in multiplication or division. The implication of these findings is discussed

Estimation of biomass in wheat using random forest regression algorithm and remote sensing data

Wheat biomass can be estimated using appropriate spectral vegetation indices. However, the accuracy of estimation should be further improved for on-farm crop management. Previous studies focused on developing vegetation indices, however limited research exists on modeling algorithms. The emerging Random Forest (RF) machine-learning algorithm is regarded as one of the most precise prediction methods for regression modeling. The objectives of this study were to (1) investigate the applicability of the RF regression algorithm for remotely estimating wheat biomass, (2) test the performance of the RF regression model, and (3) compare the performance of the RF algorithm with support vector regression (SVR) and artificial neural network (ANN) machine-learning algorithms for wheat biomass estimation. Single HJ-CCD images of wheat from test sites in Jiangsu province were obtained during the jointing, booting, and anthesis stages of growth. Fifteen vegetation indices were calculated based on these images. In-situ wheat above-ground dry biomass was measured during the HJ-CCD data acquisition. The results showed that the RF model produced more accurate estimates of wheat biomass than the SVR and ANN models at each stage, and its robustness is as good as SVR but better than ANN. The RF algorithm provides a useful exploratory and predictive tool for estimating wheat biomass on a large scale in Southern China

Electrophysiological signatures of hierarchical learning

Human perception and learning is thought to rely on a hierarchical generative model that is continuously updated via precision-weighted prediction errors (pwPEs). However, the neural basis of such cognitive process and how it unfolds during decision-making remain poorly understood. To investigate this question, we combined a hierarchical Bayesian model (i.e., Hierarchical Gaussian Filter [HGF]) with electroencephalography (EEG), while participants performed a probabilistic reversal learning task in alternatingly stable and volatile environments. Behaviorally, the HGF fitted significantly better than two control, nonhierarchical, models. Neurally, low-level and high-level pwPEs were independently encoded by the P300 component. Low-level pwPEs were reflected in the theta (4-8 Hz) frequency band, but high-level pwPEs were not. Furthermore, the expressions of high-level pwPEs were stronger for participants with better HGF fit. These results indicate that the brain employs hierarchical learning and encodes both low- and high-level learning signals separately and adaptively

Design and Implementation of Digital Twin Diesel Generator Systems

In stationary power generation units such as distributed remote site power systems and ship power systems, diesel engine generator systems are essential for supplying electricity. This paper proposes a digital twin diesel generator system for teaching and research purposes. A five-layer resilient architecture, including a web interface layer, server cluster layer, real-time data layer, controller layer, and equipment layer, is proposed in this paper. Based on the resilient architecture, users are able to build, implement and monitor the digital twin through web interfaces. Apart from MATLAB/Simulink, a modeling tool called M2PLink is developed to allow users to create mathematical models using a block diagram editor similar to Simulink. Various basic blocks for control systems are provided for users to form sophisticated models. These models are converted into executable codes which are downloaded to the simulator in the controller layer, where the real-time simulations are implemented. A web-based real-time monitoring interface with many widgets such as charts, oscilloscopes, and three-dimensional (3D) animation is also provided for users to customize their monitoring interface. All the signals can be traced and all the parameters can be tuned in the monitoring interface. The users are able to interact with the digital twin just like they do with the real system. The proposed system can not only be used for research such as digital twin-assisted real-time online monitoring but also for educational purposes, which is not only cost-effective but can also ensure the safety of the user as well as the equipment

Frontostriatal Functional Connectivity Underlies the Association between Punishment Sensitivity and Procrastination

Procrastination is defined as putting off an intended course of action voluntarily despite the harmful consequences. Previous studies have suggested that procrastination is associated with punishment sensitivity in that high punishment sensitivity results in increased negative utility for task performance. We hypothesized the effects of punishment sensitivity on procrastination would be mediated by a network connecting the caudate nucleus and prefrontal cortex, both of which have been previously associated with self-control and emotional control during procrastination. We employed voxel-based morphometry (VBM) and resting-state functional connectivity (rsFC) to examine the neural substrates of punishment sensitivity and its relationship with procrastination (N = 268). The behavioral results indicated a strong positive correlation between measures of punishment sensitivity and procrastination. The VBM analysis revealed that the gray matter (GM) volume of the right caudate was significantly positively correlated with punishment sensitivity. The primary rsFC analysis revealed connectivity between this caudate location and the bilateral middle frontal gyrus (MFG) was significantly negatively correlated with punishment sensitivity. A mediation model indicated punishment sensitivity completely mediated the relation between functional connectivity within a caudate–bilateral MFG network and procrastination. Our results support the theory that those with higher punishment sensitivity have weaker effective emotional self-control supported by the caudate–MFG network, resulting in greater procrastination