157 research outputs found
La conmutación cognitiva afecta la selección de estrategia aritmética: Evidencia de patrones de mirada y medidas conductuales
Although many studies of cognitive switching have been conducted, little is known about whether and how cognitive switching affects individuals’ use of arithmetic strategies. We used estimation and numerical comparison tasks within the operand recognition paradigm and the choice/no-choice paradigm to explore the effects of cognitive switching on the process of arithmetic strategy selection. Results showed that individuals’ performance in the baseline task was superior to that in the switching task. Presentation mode and cognitive switching clearly influenced eye-gaze patterns during strategy selection, with longer fixation duration in the number presentation mode than in the clock presentation mode. Furthermore, the number of fixation was greater in the switching task than it was in the the baseline task. These results indicate that the effects of cognitive switching on arithmetic strategy selection are clearly constrained by the manner in which numbers are presented. Aunque se han realizado muchos estudios sobre el cambio cognitivo, se sabe poco acerca de si el cambio cognitivo afecta el uso de las estrategias aritméticas por parte de las personas y cómo lo hace. Utilizamos las tareas de estimación y comparación numérica dentro del paradigma de reconocimiento de operandos y el paradigma de elección / no elección para explorar los efectos del cambio cognitivo en el proceso de selección de estrategia aritmética. Los resultados mostraron que el rendimiento de los individuos en la tarea de referencia fue superior al de la tarea de cambio. El modo de presentación y la conmutación cognitiva influyeron claramente en los patrones de la mirada durante la selección de estrategia, con duraciones de fijación más largas en el modo de presentación numérica que en el modo de presentación de reloj. Además, el número de fijaciones fue mayor en la tarea de conmutación que en la tarea de línea de base. Estos resultados indican que los efectos del cambio cognitivo en la selección de la estrategia aritmética están claramente limitados por la forma en que se presentan los números
Structure and laminar flame speed of an ammonia/methane/air premixed flame under varying pressure and equivalence ratio
This paper presents a joint experimental and numerical study on premixed laminar ammonia/methane/air flames, aiming to characterize the flame structures and NO formation and determine the laminar flame speed under different pressure, equivalence ratio, and ammonia fraction in the fuel. The experiments were carried out in a lab-scale pressurized vessel with a Bunsen burner installed with a concentric co-flow of air. Measurements of NH and NO distributions in the flames were made using planar laser-induced fluorescence. A novel method was presented for determination of the laminar flame speed from Bunsen-burner flame measurements, which takes into account the non-uniform flow in the unburned mixture and local flame stretch. NH profiles were chosen as flame front markers. Direct numerical simulation of the flames and one-dimensional chemical kinetic modeling were performed to enhance the understanding of flame structures and evaluate three chemical kinetic mechanisms recently reported in the literature. The stoichiometric and fuel-rich flames exhibit a dual-flame structure, with an inner premixed flame and an outer diffusion flame. The two flames interact, which affects the NO emissions. The impact of the diffusion flame on the laminar flame speed of the inner premixed flame is however minor. At elevated pressures or higher ammonia/methane ratios, the emission of NO is suppressed as a result of the reduced radical mass fraction and promoted NO reduction reactions. It is found that the laminar flame speed measured in the present experiments can be captured by the investigated mechanisms, but quantitative predictions of the NO distribution require further model development
Automated Lane Change and Robust Safety
69A3551747119Firstly, to guarantee stability and robustness in the face of parametric uncertainties, non-linearities, and modeling errors , we have proposed a data-driven optimal control algorithm to solve the lane-changing problem of AVs which is inspired by reinforcement learning and adaptive dynamic programming. Secondly, we have developed a lane change decision-making algorithm to ensure safe and efficient lane change. Thirdly, the lane change risk index (LCRI) is used to evaluate the AV lane change safety obtained by using the proposed data-driven optimal control algorithm. Fourthly, we have combined the data-driven optimal controller with the lane change decision-making algorithm by using control barrier functions (CBFs). Lastly, we have developed an experimental setup that includes prototypes of AV and highway lanes
Genomes shed light on the evolution of Begonia, a mega‐diverse genus
Clarifying the evolutionary processes underlying species diversification and adaptation is a key focus of evolutionary biology. Begonia (Begoniaceae) is one of the most species-rich angiosperm genera with ~2,000 species, most of which are shade-adapted. Here, we present chromosome-scale genome assemblies for four species of Begonia (B. loranthoides, B. masoniana, B. darthvaderiana, and B. peltatifolia), and whole genome shot-gun data for an additional 74 Begonia representatives to investigate lineage evolution and shade adaptation of the genus. The four genome assemblies range in size from 331.75 Mb (B. peltatifolia) to 799.83 Mb (B. masoniana), and harbor 22,059 - 23,444 protein-coding genes. Synteny analysis revealed a lineage specific whole-genome duplication (WGD) that occurred just before the diversification of the Begonia. Functional enrichment of gene families retained after WGD highlight the significance of modified carbohydrate metabolism and photosynthesis possibly linked to shade-adaptation in the genus, which is further supported by expansions of gene families involved in light perception and harvesting. Phylogenomic reconstructions and genomics studies indicate that genomic introgression has also played a role in the evolution of Begonia. Overall, this study provides valuable genomic resources for Begonia and suggests potential drivers underlying the diversity and adaptive evolution of this mega-diverse clade
Climate change : strategies for mitigation and adaptation
The sustainability of life on Earth is under increasing threat due to humaninduced climate change. This perilous change in the Earth's climate is caused by increases in carbon dioxide and other greenhouse gases in the atmosphere, primarily due to emissions associated with burning fossil fuels. Over the next two to three decades, the effects of climate change, such as heatwaves, wildfires, droughts, storms, and floods, are expected to worsen, posing greater risks to human health and global stability. These trends call for the implementation of mitigation and adaptation strategies. Pollution and environmental degradation exacerbate existing problems and make people and nature more susceptible to the effects of climate change. In this review, we examine the current state of global climate change from different perspectives. We summarize evidence of climate change in Earth’s spheres, discuss emission pathways and drivers of climate change, and analyze the impact of climate change on environmental and human health. We also explore strategies for climate change mitigation and adaptation and highlight key challenges for reversing and adapting to global climate change
Facilitating Memory for Novel Characters by Reducing Neural Repetition Suppression in the Left Fusiform Cortex
Gui Xue is with Beijing Normal University and University of Southern California, Leilei Mei is with Beijing Normal University and University of California Irvine, Chuansheng Chen is with University of California Irvine, Zhong-Lin Lu is with University of Southern California, Russell A. Poldrack is with UT Austin, Qi Dong is with Beijing Normal University.Background -- The left midfusiform and adjacent regions have been implicated in processing and memorizing familiar words, yet its role in memorizing novel characters has not been well understood. Methodology/Principal Findings -- Using functional MRI, the present study examined the hypothesis that the left midfusiform is also involved in memorizing novel characters and spaced learning could enhance the memory by enhancing the left midfusiform activity during learning. Nineteen native Chinese readers were scanned while memorizing the visual form of 120 Korean characters that were novel to the subjects. Each character was repeated four times during learning. Repetition suppression was manipulated by using two different repetition schedules: massed learning and spaced learning, pseudo-randomly mixed within the same scanning session. Under the massed learning condition, the four repetitions were consecutive (with a jittered inter-repetition interval to improve the design efficiency). Under the spaced learning condition, the four repetitions were interleaved with a minimal inter-repetition lag of 6 stimuli. Spaced learning significantly improved participants' performance during the recognition memory test administered one hour after the scan. Stronger left midfusiform and inferior temporal gyrus activities during learning (summed across four repetitions) were associated with better memory of the characters, based on both within- and cross-subjects analyses. Compared to massed learning, spaced learning significantly reduced neural repetition suppression and increased the overall activities in these regions, which were associated with better memory for novel characters. Conclusions/Significance -- These results demonstrated a strong link between cortical activity in the left midfusiform and memory for novel characters, and thus challenge the visual word form area (VWFA) hypothesis. Our results also shed light on the neural mechanisms of the spacing effect in memorizing novel characters.This study was supported by the Program for New Century Excellent Talents in University, the National Science Foundation (grant numbers BCS 0823624 and BCS 0823495), the National Institute of Health (grant number HD057884-01A2), and the 111 Project of China (B07008). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Psycholog
Primary surveys on molecular epidemiology of bovine viral diarrhea virus 1 infecting goats in Jiangsu province, China
Correlation between Gene Expression and Osteoarthritis Progression in Human
Osteoarthritis (OA) is a multifactorial disease characterized by gradual degradation of joint cartilage. This study aimed to quantify major pathogenetic factors during OA progression in human cartilage. Cartilage specimens were isolated from OA patients and scored 0–5 according to the Osteoarthritis Research Society International (OARSI) guidelines. Protein and gene expressions were measured by immunohistochemistry and qPCR, respectively. Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assays were used to detect apoptotic cells. Cartilage degeneration in OA is a gradual progress accompanied with gradual loss of collagen type II and a gradual decrease in mRNA expression of SOX9, ACAN and COL2A1. Expression of WNT antagonists DKK1 and FRZB was lost, while hypertrophic markers (RUNX2, COL10A1 and IHH) increased during OA progression. Moreover, DKK1 and FRZB negatively correlated with OA grading, while RUNX2 and IHH showed a significantly positive correlation with OA grading. The number of apoptotic cells was increased with the severity of OA. Taken together, our results suggested that genetic profiling of the gene expression could be used as markers for staging OA at the molecular level. This helps to understand the molecular pathology of OA and may lead to the development of therapies based on OA stage
Joint players: Endogenous WNT antagonists determine joint health
Signaling of the secreted wingless-type MMTV integration site (WNT) has been implicated as a driving factor in osteoarthritis (OA). The induction of chondrocyte hypertrophy is a role attributed to WNT in OA, which may explain why chondrocytes in articular cartilage express high levels of WNT antagonists to modulate the activity of WNT signaling. Dickkopf 1 homolog (DKK1) and frizzled-related protein (FRZB) are naturally occurring antagonists of the WNT signaling pathway. Previously, we identified DKK1 and FRZB as key factors in controlling the articular chondrocyte phenotype by preventing endochondral ossification.\ud
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The aim of this thesis is to study the role of WNT signaling and its antagonists DKK1 and FRZB in human articular cartilage. In this thesis, we have provided answers for the following questions: i) how does expression of joint-related factors change in cartilage and synovial fluid during OA progression, with a focus on the changes in expression of WNT and WNT antagonists; ii) what is the fundamental role of WNT/β-catenin signaling and its antagonists (DKK1 and FRZB) in human chondrocytes and mesenchymal stem cells; iii) how are WNT antagonists regulated by the inflammatory factor IL1β; and iv) how can we use our knowledge to improve the understanding OA pathology and its treatment
Construction project risk prediction model based on EW-FAHP and one dimensional convolution neural network.
In order to solve the problem of low accuracy of traditional construction project risk prediction, a project risk prediction model based on EW-FAHP and 1D-CNN(One Dimensional Convolution Neural Network) is proposed. Firstly, the risk evaluation index value of construction project is selected by literature analysis method, and the comprehensive weight of risk index is obtained by combining entropy weight method (EW) and fuzzy analytic hierarchy process (FAHP). The risk weight is input into the 1D-CNN model for training and learning, and the prediction values of construction period risk and cost risk are output to realize the risk prediction. The experimental results show that the average absolute error of the construction period risk and cost risk of the risk prediction model proposed in this paper is below 0.1%, which can meet the risk prediction of construction projects with high accuracy
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