Miracle-dz/UniFAR-FTUs huggingface dataset:
Asymptotics for Nonlinear Transformations of Fractionally Integrated Time Series

The asymptotic theory for nonlinear transformations of fractionally integrated time series is developed.By the use of fractional Occupation Times Formula,various nonlinear functions of fractionally integrated series such as ARFIMA time series are studied,and the asymptotic distributions of the sample moments of such functions are obtained and analyzed.The transformations considered in this paper includes a variety of functions such as regular functions,integrable functions and asymptotically homogeneous functions that are often used in practical nonlinear econometric analysis.It is shown that the asymptotic theory of nonlinear transformations of original and normalized fractionally integrated processes is different from that of fractionally integrated processes,but is similar to the asymptotic theory of nonlinear transformations of integrated processes.
Drainage Pattern Recognition of River Network Based on Graph Convolutional Neural Network

Drainage network pattern recognition is a significant task with wide applications in geographic information mining, map cartography, water resources management, and urban planning. Accurate identification of spatial patterns in river networks can help us understand geographic phenomena, optimize map cartographic quality, assess water resource potential, and provide a scientific basis for urban development planning. However, river network pattern recognition still faces challenges due to the complexity and diversity of river networks. To address this issue, this study proposes a river network pattern recognition method based on graph convolutional networks (GCNs), aiming to achieve accurate classification of different river network patterns. We utilize binary trees to construct a hierarchical tree structure based on river reaches and progressively determine the tree hierarchy by identifying the upstream and downstream relationships among river reaches. Based on this representation, input features for the graph convolutional model are extracted from both spatial and geometric perspectives. The effectiveness of the proposed method is validated through classification experiments on four types of vector river network data (dendritic, fan-shaped, trellis, and fan-shaped). The experimental results demonstrate that the proposed method can effectively classify vector river networks, providing strong support for research and applications in related fields.
C OST -E FFICIENT D RAGONFLY T OPOLOGY FOR L ARGE -S CALE S YSTEMS

The interconnection network that connects processors and memory modules in scalable multiprocessors and largescale systems significantly impacts the system’s overall performance and cost. As processor and memory performance continue to increase, large-scale interconnection networks are becoming even more critical because they largely determine the bandwidth and latency of remote memory access. A good interconnection network is designed around the capabilities and constraints of available technology. Previous interconnection networks have been built with low-radix routers—that is, routers with a small number of ports. As a result, these networks used low-radix topologies such as 2D or 3D mesh or torus networks. Examples of machines employing such networks include the Cray T3D, T3E, and XT3, SGI Origin2000, and Alpha 21364. Earlier work showed that, for the packaging and technology constraints of the 1980s and 1990s—and the relatively low pin bandwidth available at that time—lowradix networks provided optimal latency for a given cost. However, this is no longer the case. Over the past 20 years, the pin bandwidth of router chips has increased by approximately an order of magnitude every five years—a rate similar to Moore’s law (see Figure 1). This increase in bandwidth is a result of both an increase in the signaling rate and an increase in the number of signals available to a router chip. However, the best way to exploit this increasing off-chip bandwidth isn’t just to make the ports wider—that is, building low-radix routers with fat channels. Rather, it’s more efficient to increase the number of ports—to build high-radix routers with thin channels. The use of high radix reduces hop count and leads to lower latency and lower cost. The zero-load latency consists of header latency, which is proportional to the mmi2009010033.3d 2/2/09 10:40 Page 33
Time Course of Reactive Brain Activities during a Stroop Color-Word Task: Evidence of Specific Facilitation and Interference Effects

The Stroop test represents a widely used task in basic and clinical research for approaching the cognitive system functioning in humans. However, a clear overview of the neurophysiological signatures associated with the different sub-domains of this task remains controversial. In the present study, we leveraged the EEG technique to explore the modulation of specific post-stimulus ERPs components during the Stroop test. Critically, to better disentangle the contribution of facilitation (i.e., faster color identification times for color-congruent Stroop words) and interference (i.e., longer color identification times for color-incongruent Stroop words) processes prompted by the Stroop test, we delivered congruent and incongruent trials in two separate experimental blocks, each including the respective neutral condition. Thanks to this methodological manipulation, we were able to clearly dissociate the two sub-processes. Electrophysiological results suggest specific markers of brain activity for the facilitation and the interference effects. Indeed, distinctive Stroop-related ERPs (i.e., the P3, the N450, and the LPC) were differently modulated in the two sub-processes. Collectively, we provide evidence of selected brain activities involved in the reactive stage of processing associated with the Stroop effect.
Re-Imagining Community and School through Youth and Artists’ Critical Superhero Storytelling

In this article, we describe the methods and pedagogy that guided a superhero storytelling project, located in a midwestern middle school library, where youth were invited to work with a university-based research team and community-based artists who actively displaced historically formed practices of surveillance and silencing in the service of amplifying youth artistry and knowledge production. We recognize that school practices in many schools, by virtue of their complicity with hierarchical and evaluative mandates, undermine open and exploratory forms of youth expression. The arts-based project we describe, informed by a ten-year history of small-scale storytelling projects in the same school, offers a theoretical and related pedagogical framework for working with community-based artists to re-imagine and remake oppressive relational, epistemological, and material practices in school spaces. At the center of our report are two groups of youth and the artists and educators who supported them as they invented superheroes and activated the imaginative potential of their local community spaces for their storytelling.
LPE-Unet: An Improved UNet Network Based on Perceptual Enhancement

In Computed Tomography (CT) images of the coronary arteries, the segmentation of calcified plaques is extremely important for the examination, diagnosis, and treatment of coronary heart disease. However, one characteristic of the lesion is that it has a small size, which brings two difficulties. One is the class imbalance when computing loss function and the other is that small-scale targets are prone to losing details in the continuous downsampling process, and the blurred boundary makes the segmentation accuracy less satisfactory. Therefore, the segmentation of calcified plaques is a very challenging task. To address the above problems, in this paper, we design a framework named LPE-UNet, which adopts an encoder–decoder structure similar to UNet. The framework includes two powerful modules named the low-rank perception enhancement module and the noise filtering module. The low-rank perception enhancement module extracts multi-scale context features by increasing the receptive field size to aid target detection and then uses an attention mechanism to filter out redundant features. The noise filtering module suppresses noise interference in shallow features to high-level features in the process of multi-scale feature fusion. It computes a pixel-wise weight map of low-level features and filters out useless and harmful information. To alleviate the problem of class imbalance caused by small-sized lesions, we use a weighted cross-entropy loss function and Dice loss to perform mixed supervised training on the network. The proposed method was evaluated on the calcified plaque segmentation dataset, achieving a high F1 score of 0.941, IoU of 0.895, and Dice of 0.944. This result verifies the effectiveness and superiority of our approach for accurately segmenting calcified plaques. As there is currently no authoritative publicly available calcified plaque segmentation dataset, we have constructed a new dataset for coronary artery calcified plaque segmentation (Calcified Plaque Segmentation Dataset, CPS Dataset).
Pathophysiological Roles of the TRPV4 Channel in the Heart

The transient receptor potential vanilloid 4 (TRPV4) channel is a non-selective cation channel that is mostly permeable to calcium (Ca2+), which participates in intracellular Ca2+ handling in cardiac cells. It is widely expressed through the body and is activated by a large spectrum of physicochemical stimuli, conferring it a role in a variety of sensorial and physiological functions. Within the cardiovascular system, TRPV4 expression is reported in cardiomyocytes, endothelial cells (ECs) and smooth muscle cells (SMCs), where it modulates mitochondrial activity, Ca2+ homeostasis, cardiomyocytes electrical activity and contractility, cardiac embryonic development and fibroblast proliferation, as well as vascular permeability, dilatation and constriction. On the other hand, TRPV4 channels participate in several cardiac pathological processes such as the development of cardiac fibrosis, hypertrophy, ischemia–reperfusion injuries, heart failure, myocardial infarction and arrhythmia. In this manuscript, we provide an overview of TRPV4 channel implications in cardiac physiology and discuss the potential of the TRPV4 channel as a therapeutic target against cardiovascular diseases.
MXene-Based Nanocomposites for Piezoelectric and Triboelectric Energy Harvesting Applications

Due to its superior advantages in terms of electronegativity, metallic conductivity, mechanical flexibility, customizable surface chemistry, etc., 2D MXenes for nanogenerators have demonstrated significant progress. In order to push scientific design strategies for the practical application of nanogenerators from the viewpoints of the basic aspect and recent advancements, this systematic review covers the most recent developments of MXenes for nanogenerators in its first section. In the second section, the importance of renewable energy and an introduction to nanogenerators, major classifications, and their working principles are discussed. At the end of this section, various materials used for energy harvesting and frequent combos of MXene with other active materials are described in detail together with the essential framework of nanogenerators. In the third, fourth, and fifth sections, the materials used for nanogenerators, MXene synthesis along with its properties, and MXene nanocomposites with polymeric materials are discussed in detail with the recent progress and challenges for their use in nanogenerator applications. In the sixth section, a thorough discussion of the design strategies and internal improvement mechanisms of MXenes and the composite materials for nanogenerators with 3D printing technologies are presented. Finally, we summarize the key points discussed throughout this review and discuss some thoughts on potential approaches for nanocomposite materials based on MXenes that could be used in nanogenerators for better performance.
Design Investigation of Potential Long-Range Hydrogen Combustion Blended Wing Body Aircraft with Future Technologies

Present work investigates the potential of a long-range commercial blended wing body configuration powered by hydrogen combustion engines with future airframe and propulsion technologies. Future technologies include advanced materials, load alleviation techniques, boundary layer ingestion, and ultra-high bypass ratio engines. The hydrogen combustion configuration was compared to the configuration powered by kerosene with respect to geometric properties, performance characteristics, energy demand, equivalent CO2 emissions, and Direct Operating Costs. In addition, technology sensitivity studies were performed to assess the potential influence of each technology on the configuration. A multi-fidelity sizing methodology using low- and mid-fidelity methods for rapid configuration sizing was created to assess the configuration and perform robust analyses and multi-disciplinary optimizations. To assess potential uncertainties of the fidelity of aerodynamic analysis tools, high-fidelity aerodynamic analysis and optimization framework MACH-Aero was used for additional verification. Comparison of hydrogen and kerosene blended wing body aircraft showed a potential reduction of equivalent CO2 emission by 15% and 81% for blue and green hydrogen compared to the kerosene blended wing body and by 44% and 88% with respect to a conventional B777-300ER aircraft. Advancements in future technologies also significantly affect the geometric layout of aircraft. Boundary layer ingestion and ultra-high bypass ratio engines demonstrated the highest potential for fuel reduction, although both technologies conflict with each other. However, operating costs of hydrogen aircraft could establish a significant problem if pessimistic and base hydrogen price scenarios are achieved for blue and green hydrogen respectively. Finally, configurational problems featured by classical blended wing body aircraft are magnified for the hydrogen case due to the significant volume requirements to store hydrogen fuel.
Dynamic Adaptive Mixture Models

In this paper we propose a new class of Dynamic Mixture Models (DAMMs) being able to sequentially adapt the mixture components as well as the mixture composition using information coming from the data. The information driven nature of the proposed class of models allows to exactly compute the full likelihood and to avoid computer intensive simulation schemes. An extensive Monte Carlo experiment reveals that the new proposed model can accurately approximate the more complicated Stochastic Dynamic Mixture Model previously introduced in the literature as well as other kind of models. The properties of the new proposed class of models are discussed through the paper and an application in financial econometrics is reported.
Genome-Wide Identification of the PP2C Gene Family and Analyses with Their Expression Profiling in Response to Cold Stress in Wild Sugarcane

Type 2C protein phosphatases (PP2Cs) represent a major group of protein phosphatases in plants, some of which have already been confirmed to play important roles in diverse plant processes. In this study, analyses of the phylogenetics, gene structure, protein domain, chromosome localization, and collinearity, as well as an identification of the expression profile, protein–protein interaction, and subcellular location, were carried out on the PP2C family in wild sugarcane (Saccharum spontaneum). The results showed that 145 PP2C proteins were classified into 13 clades. Phylogenetic analysis suggested that SsPP2Cs are evolutionarily closer to those of sorghum, and the number of SsPP2Cs is the highest. There were 124 pairs of SsPP2C genes expanding via segmental duplications. Half of the SsPP2C proteins were predicted to be localized in the chloroplast (73), with the next most common predicted localizations being in the cytoplasm (37) and nucleus (17). Analysis of the promoter revealed that SsPP2Cs might be photosensitive, responsive to abiotic stresses, and hormone-stimulated. A total of 27 SsPP2Cs showed cold-stress-induced expressions, and SsPP2C27 (Sspon.01G0007840-2D) and SsPP2C64 (Sspon.03G0002800-3D) were the potential hubs involved in ABA signal transduction. Our study presents a comprehensive analysis of the SsPP2C gene family, which can play a vital role in the further study of phosphatases in wild sugarcane. The results suggest that the PP2C family is evolutionarily conserved, and that it functions in various developmental processes in wild sugarcane.
A Global Structure and Adaptive Weight Aware ICP Algorithm for Image Registration

As an important technology in 3D vision, point-cloud registration has broad development prospects in the fields of space-based remote sensing, photogrammetry, robotics, and so on. Of the available algorithms, the Iterative Closest Point (ICP) algorithm has been used as the classic algorithm for solving point cloud registration. However, with the point cloud data being under the influence of noise, outliers, overlapping values, and other issues, the performance of the ICP algorithm will be affected to varying degrees. This paper proposes a global structure and adaptive weight aware ICP algorithm (GSAW-ICP) for image registration. Specifically, we first proposed a global structure mathematical model based on the reconstruction of local surfaces using both the rotation of normal vectors and the change in curvature, so as to better describe the deformation of the object. The model was optimized for the convergence strategy, so that it had a wider convergence domain and a better convergence effect than either of the original point-to-point or point-to-point constrained models. Secondly, for outliers and overlapping values, the GSAW-ICP algorithm was able to assign appropriate weights, so as to optimize both the noise and outlier interference of the overall system. Our proposed algorithm was extensively tested on noisy, anomalous, and real datasets, and the proposed method was proven to have a better performance than other state-of-the-art algorithms.
First-Principle Study of Two-Dimensional SiP2 for Photocatalytic Water Splitting with Ultrahigh Carrier Mobility

Two-dimensional materials present abundant novel properties when used in advanced applications, which develops considerable focus. In this investigation, the first-principles calculations are explored to study the structural characteristic of the monolayered SiP2, which is stable even at 1200 K. The SiP2 monolayer is a semiconductor with an indirect bandgap of 2.277 eV. The decent band alignment and light absorption capacity imply that the application is a suitable photocatalyst for water splitting. Furthermore, the SiP2 monolayer possesses an ultrafast electron mobility at 33,153 cm2·V−1·s−1 in the transport direction. The excellent Gibbs free energy of the SiP2 monolayer is also addressed in an examination of the hydrogen evolution reaction.
Positional Faithfulness, Non-locality, and the Harmonic Serialism Solution

Positional Faithfulness constraints (Beckman 1997, 1998, Casali 1996, Lombardi 1999) are widely used in modeling contextual asymmetries in the realization of segmental features. As this paper shows, however, positional faithfulness constraints are also associated with a number of unwanted predictions. These problems arise whenever the constraints responsible for determining which segments fall into positions of privilege fail to dominate the positional faithfulness constraints. The result is pathological opaque and non-local patterns.
Overexpression of Rice Histone H1 Gene Reduces Tolerance to Cold and Heat Stress

Temperature stresses, including low- and high-temperature stresses, are the main abiotic stresses affecting rice yield. Due to global climate change, the impact of temperature pressure on rice yield is gradually increasing, which is also a major concern for researchers. In this study, an H1 histone in Oryza sativa (OsHis1.1, LOC_Os04g18090) was cloned, and its role in rice’s response to temperature stresses was functionally characterized. The GUS staining analysis of OsHis1.1 promoter-GUS transgenic rice showed that OsHis1.1 was widely expressed in various rice tissues. Transient expression demonstrated that OsHis1.1 was localized in the nucleus. The overexpression of OsHis1.1 reduces the tolerance to temperature stress in rice by inhibiting the expression of genes that are responsive to heat and cold stress. Under stress conditions, the POD activity and chlorophyll and proline contents of OsHis1.1-overexpression rice lines were significantly lower than those of the wild type, while the malondialdehyde content was higher than that of the wild type. Compared with Nip, OsHis1.1-overexpression rice suffered more serious oxidative stress and cell damage under temperature stress. Furthermore, OsHis1.1-overexpression rice showed changes in agronomic traits.
Genetic and Epigenetic Study of Monozygotic TwinsAffected by Parkinson’s Disease

Background: Genetic and epigenetic modifiers of age at onset of Parkinson’s disease (PD) are largely unknown. It remains unclear whether DNA methylation (DNAm) age acceleration is linked to age at onset in PD patients of different ethnicities with a similar genetic background. We aim to characterize the clinical, genomic and epigenomic features of three pairs of Chinese monozygotic twins discordant for PD onset by up to 10 years. Methods: We conducted whole genome sequencing, multiplex ligation-dependent probe amplification and genome-wide DNAm array to evaluate the three pairs of Chinese monozygotic twins discordant for age at onset of PD (families A–C). Results: We identified two heterozygous PRKN mutations (exon 2–4 deletion and p.Met1Thr) in PD affected members of one family. Somatic mutation analyses of investigated families did not reveal any variants that could explain the phenotypic discordance in the twin pairs. Of note, our epigenetic study revealed that the twins with earlier-onset had a trend of faster DNAm age acceleration than the later-onset/asymptomatic twins, but without statistical significance. Conclusion: The link between DNAm age acceleration and PD onset in Chinese patients should be interpreted with cautious, and need to be further verified in an extended PD cohort with similar genetic background.