Miracle-dz/UniFAR-FTUs huggingface dataset:
Reproducing past subduction and mantle flow using high‐resolution global convection models

Plate subduction drives both the internal convection and the surface geology of the solid Earth. Despite the rapid increase of computational power, it remains challenging for geodynamic models to reproduce the history of Earth‐like subduction and associated mantle flow. Here, based on an adaptive approach of sequential data assimilation, we present a high‐resolution global model since the mid‐Mesozoic. This model incorporates the thermal structure and surface kinematics of tectonic plates based on a recent plate reconstruction to reproduce the observed subduction configuration and Earth‐like convection. Introduction of temperature‐ and composition‐dependent rheology allows for incorporation of many natural complexities, such as initiation of subduction zones, reversal of subduction polarity, and detailed plate‐boundary dynamics. The resultant present‐day slab geometry well matches Benioff zones and seismic tomography at depths < 1500 km, making it possible to hindcast past subduction dynamics and mantle flow. For example, the model produces a flat Farallon slab beneath North America during the Late Cretaceous to Early Cenozoic, a feature that has been geodynamically challenging to reproduce. This high‐resolution model can also capture details of the 4‐D evolution of slabs and the ambient mantle, such as temporally and spatially varying mantle flow associated with evolving slab geometry and buoyancy flux, as well as the formation of shallow slab tears due to subduction of young seafloors and the resulting complex mantle deformation. Such a geodynamic framework serves to further constrain uncertain plate reconstruction in the geological past, and to better understand the origin of enigmatic mantle seismic features.
Multi-thread technology based autonomous underwater vehicle

An autonomous underwater vehicle (AUV) is implemented with multi-thread technology under QNX Neutrino Real time Operating System. The hybrid system and autonomous control principle of AUV are introduced. The event generator thread and event analysis and decision making thread are two key threads in the autonomous control system to handle discrete events, which are described in detail. Also the histogram in motion mapping algorithm with growth rate operator is adopted to process the sonar data and to express the uncertainty of sonar data. The obstacle avoidance algorithm based on sonar data is designed to enable vehicle to avoid obstacle immediately, effectively and safely. Finally we verify this autonomous control system with simulation study and experiment in lake. The simulation and experiment results show that the proposed AUV autonomous control system can fulfill the missions effectively.
Phosphorylation of Angiomotin by Lats1/2 Kinases Inhibits F-actin Binding, Cell Migration, and Angiogenesis*

Background: Substrates of the Hippo pathway kinases Lats1/2 are largely unknown besides YAP/TAZ. Results: Phosphorylation of angiomotin by Lats1/2 inhibits interaction with F-actin thus impairs cell migration and angiogenesis. Conclusion: AMOTp130 is a physiological and functional substrate of Lats1/2 and the Hippo pathway. Significance: Demonstrating how identification of novel substrates would facilitate understanding the physiology of the Hippo pathway. The Hippo tumor suppressor pathway plays important roles in organ size control through Lats1/2 mediated phosphorylation of the YAP/TAZ transcription co-activators. However, YAP/TAZ independent functions of the Hippo pathway are largely unknown. Here we report a novel role of the Hippo pathway in angiogenesis. Angiomotin p130 isoform (AMOTp130) is phosphorylated on a conserved HXRXXS motif by Lats1/2 downstream of GPCR signaling. Phosphorylation disrupts AMOT interaction with F-actin and correlates with reduced F-actin stress fibers and focal adhesions. Furthermore, phosphorylation of AMOT by Lats1/2 inhibits endothelial cell migration in vitro and angiogenesis in zebrafish embryos in vivo. Thus AMOT is a direct substrate of Lats1/2 mediating functions of the Hippo pathway in endothelial cell migration and angiogenesis.
Tremor migration patterns and the collective behavior of deep asperities mediated by creep

Slow-slip events (SSE) and non-volcanic tremors have revealed a broad spectrum of earthquake behavior, involving entangled seismic and aseismic slip, and offer a unique window into fault mechanics at the bottom of seismogenic zones. A hierarchy of migration patterns of tremors has been observed in the Cascadia subduction zone, including large-scale along-strike tremor propagation and Rapid Tremor Reversals (RTR) migrating in opposite directions with much higher propagation speeds. Here we show that these tremor migration patterns can be reproduced by two end-member models of a fault with heterogeneous mechanical properties, composed of competent asperities embedded in a more frictionally stable, incompetent matrix. In the SSE-driven-tremor model, SSEs are spontaneously generated by the matrix, even in absence of seismic asperities, and drive tremor. In the tremor-driven-SSE model the matrix is stable, it slips steadily in absence of asperities, and SSEs result from the collective behavior of tremor asperities interacting via transient creep in the form of local afterslip fronts. We study these two end-member models through 2D quasi-dynamic multi-cycle simulations of faults governed by rate-and-state friction with heterogeneous frictional properties and effective normal stress, using the earthquake simulation software QDYN . In both models, tremor migration patterns emerge from interactions between asperities mediated by creep transients. The models successfully reproduce forward tremor propagation and RTRs, as well as various other observed tremor migration patterns, without the need to finely tune model parameters. Our modeling results suggest that, in contrast to a common view, SSE could be a result of tremor activity. Also, the hierarchical pattern of tremor migrations provides general constraints on fault zone rheology, and the location of RTRs and other tremor patterns might shed light on the finer scale spatial variability of fault properties. We also find that, despite important interactions between asperities, tremor activity rates are proportional to the underlying aseismic slip rate, supporting an approach to estimate SSE properties with high spatial-temporal resolutions via tremor activity.
Clue Deduction: Professor Plum Teaches Logic

In this paper, we describe curricular materials that use the game of Clue to teach basic concepts of propositional logic. While there are many ways of teaching concepts of logic, this approach is distinct in that it is (1) goal-oriented, culminating in a fun project where students implement expert Clue deduction, (2) minimalistic, covering many important concepts within the simple domain of propositional logic, and (3) extensible, inviting students to extend the project further in several significant directions through advanced study of knowledge representation and reasoning topics.
Scale space searches for a periodic signal in fMRI data with spatially varying hemodynamic response

We propose a simple method for testing for a periodic signal in fMRI data where the hemodynamic response function is spatially varying with possibly different lags at different voxels. At each voxel, the test is based on the power of the spectrum at a frequency that matches the signal, divided by an estimator of the variance to produce a χ image with 2 degrees of freedom. We then apply scale space methods to search for signals of different width by smoothing the data with different Gaussian spatial filters, then searching over scale as well as location. The resulting scale space image is thresholded at a level chosen to control the false positive rate using a new result for the P-value of the maximum of scale space χ fields.
A Hybrid Smartphone Indoor Positioning Solution for Mobile LBS

Smartphone positioning is an enabling technology used to create new business in the navigation and mobile location-based services (LBS) industries. This paper presents a smartphone indoor positioning engine named HIPE that can be easily integrated with mobile LBS. HIPE is a hybrid solution that fuses measurements of smartphone sensors with wireless signals. The smartphone sensors are used to measure the user’s motion dynamics information (MDI), which represent the spatial correlation of various locations. Two algorithms based on hidden Markov model (HMM) problems, the grid-based filter and the Viterbi algorithm, are used in this paper as the central processor for data fusion to resolve the position estimates, and these algorithms are applicable for different applications, e.g., real-time navigation and location tracking, respectively. HIPE is more widely applicable for various motion scenarios than solutions proposed in previous studies because it uses no deterministic motion models, which have been commonly used in previous works. The experimental results showed that HIPE can provide adequate positioning accuracy and robustness for different scenarios of MDI combinations. HIPE is a cost-efficient solution, and it can work flexibly with different smartphone platforms, which may have different types of sensors available for the measurement of MDI data. The reliability of the positioning solution was found to increase with increasing precision of the MDI data.
Staying Under The Radar: Innovation Strategy In Information Infrastructures For Health

This paper presents an empirical study of the design, development, and initial use of a platform for patient-health provider communication in Norway. This is a bottom up initiative started in 2005 by a small project team within the IT department of a large hospital in Norway. The project team has managed to stay “under the radar” in order to survive in a quite dynamic environment characterized by mergers, reorganizations and reforms as well as of large, costly and unsuccessful ICT projects in the same hospital. In this paper, we see this project as a case of infrastructural innovation and, adopting an institutional entrepreneurship approach, we investigate how the project team managed to ‘survive’ aiming to understand the strategy they implemented.
A Comparison of LiDAR Filtering Algorithms in Vegetated Mountain Areas

Abstract Filtering of airborne light detection and ranging (LiDAR) data is a challenging task in vegetated mountain areas. Environmental features and LiDAR data characteristics have significant impacts on the performance of filtering algorithms. This study aims to determine the effects of topographic and environmental features such as slope, canopy cover, elevation variability, and LiDAR point density on five widely used filtering algorithms, including multi-scale curvature classification (MCC), interpolation-based filtering (IBF) algorithm, morphological filtering (MF) algorithm, progressive triangulated irregular network densification filtering (PTDF) algorithm, and slope-based filtering (SBF). The results show that the performances of these filtering algorithms are all significantly influenced by the chosen factors, but the dominant influential factor varies with algorithms. The MCC works well in steep and dense forests; IBF and MCC outperform the rest of filtering algorithms in areas with steep terrain but low vegetation coverage; and PTDF is more reliable for low-density LiDAR data. Our results can provide guidance for choosing the appropriate filtering algorithm based on the specific topographic and environmental features of a study area.
HARP: Adaptive abort recurrence prediction for Hardware Transactional Memory

Hardware Transactional Memory (HTM) exposes parallelism by allowing possibly conflicting sections of code, called transactions, to execute concurrently in multithreaded applications. However, conflicts among concurrent transactions result in wasted computation and expensive rollbacks. Under high contention HTM protocol overheads can, in many cases, amount to several times the useful work done. Blindly scheduling transactions in the presence of contention is therefore clearly suboptimal from a resource utilization standpoint, especially in situations where several scheduling options exist. This paper presents HARP (Hardware Abort Recurrence Predictor), a hardware-only mechanism to avoid speculation when it is likely to fail. Inspired by branch prediction strategies and prior work on contention management and scheduling in HTM, HARP uses past behavior of transactions and locality in conflicting memory references to accurately predict conflicts. The prediction mechanism adapts to variations in workload characteristics and enables better utilization of computational resources. We show that an HTM protocol that integrates HARP exhibits reductions in both wasted execution time and serialization overheads when compared to prior work, leading to a significant increase in throughput (~30%) in both single-application and multi-application scenarios.
A New Parameters Optimization Method for Screw Conveyor Based on PSO

Particle swarm optimization (PSO) is a population based stochastic optimization technique. As a result, PSO algorithm is widely used in mechanical engineering design field. Screw conveyors are used extensively in agriculture and processing industries for elevating and/or transporting bulk materials over short to medium distances. They are very effective for conveying dry particulate solids, giving good control over the throughput. Despite their apparent simplicity, the transportation action is very complex and designers have tended to rely heavily on empirical performance data. Intelligent operation parameters optimization for screw conveyor based on PSO is studied in this paper. This thesis takes a heavy driving drum of screw conveyor as an example, firstly, the optimization function is built up, then the operation parameter of screw conveyor is precision optimized with PSO algorithm, which offer a foundation to design more reasonable structure for driving drum in order to meet the application demands¿.
Estimation of Noise-Free Variance to Measure Heterogeneity

Variance is a statistical parameter used to characterize heterogeneity or variability in data sets. However, measurements commonly include noise, as random errors superimposed to the actual value, which may substantially increase the variance compared to a noise-free data set. Our aim was to develop and validate a method to estimate noise-free spatial heterogeneity of pulmonary perfusion using dynamic positron emission tomography (PET) scans. On theoretical grounds, we demonstrate a linear relationship between the total variance of a data set derived from averages of n multiple measurements, and the reciprocal of n. Using multiple measurements with varying n yields estimates of the linear relationship including the noise-free variance as the constant parameter. In PET images, n is proportional to the number of registered decay events, and the variance of the image is typically normalized by the square of its mean value yielding a coefficient of variation squared (CV 2). The method was evaluated with a Jaszczak phantom as reference spatial heterogeneity (CVr 2) for comparison with our estimate of noise-free or ‘true’ heterogeneity (CV t 2). We found that CV t 2 was only 5.4% higher than CV r 2. Additional evaluations were conducted on 38 PET scans of pulmonary perfusion using 13NN-saline injection. The mean CV t 2 was 0.10 (range: 0.03–0.30), while the mean CV 2 including noise was 0.24 (range: 0.10–0.59). CV t 2 was in average 41.5% of the CV 2 measured including noise (range: 17.8–71.2%). The reproducibility of CV t 2 was evaluated using three repeated PET scans from five subjects. Individual CV t 2 were within 16% of each subject's mean and paired t-tests revealed no difference among the results from the three consecutive PET scans. In conclusion, our method provides reliable noise-free estimates of CV t 2 in PET scans, and may be useful for similar statistical problems in experimental data.
Sulfur Dioxide Modifies Aerosol Particle Formation and Growth by Ozonolysis of Monoterpenes and Isoprene

The effect of sulfur dioxide on particle formation and growth by ozonolysis of three monoterpenes (α‐pinene, β‐pinene, and limonene) and isoprene was investigated in the presence of monodisperse ammonium sulfate seed particles and an OH scavenger in a flow tube under dry conditions. Without sulfur dioxide, new particle formation was not observed, and seed particle growth was consistent with condensation of low‐volatility oxidation products produced from each organic precursor. With sulfur dioxide, new particle formation was observed from every precursor studied, consistent with sulfuric acid formation by reaction of sulfur dioxide with stabilized Criegee Intermediates. The presence of sulfur dioxide did not significantly affect seed particle growth rates from α‐pinene and limonene ozonolysis, although chemical composition measurements revealed the presence of organosulfates in the particles following SO2 exposure. Contrarily, the growth of seeds by β‐pinene and isoprene ozonolysis was considerably enhanced by sulfur dioxide, and chemical composition measurements revealed that the enhanced growth was not due to additional organic material, suggesting that inorganic sulfate was likely responsible. The results suggest that a previously unconsidered particle‐phase pathway to growth activated by sulfur dioxide may alter production of cloud condensation nuclei over regions with significant SO2‐alkene interactions.
Compressive symbol detection via template matching

In this paper, we consider a method to detect digital modulated symbols from compressively sampled measurements in digital communication system. We describe a method to build a dictionary matrix considering signal modulations, and propose a template matching based algorithm which is effective to recover the information symbols using the dictionary. We implement the algorithm as a GPGPU program, and our experiments show that the proposed recovery method works well.
Iterative Reconstruction in X-ray Fluorescence Tomography Based on Radon Inversion

We describe a new approach for the inversion of the generalized attenuated radon transform in X-ray fluorescence computed tomography (XFCT). The approach consists of using the radon inverse as an approximation for the actual one, followed by an iterative refinement. Also, we analyze the problem of retrieving the attenuation map directly from the emission data, giving rise to a novel alternating method for the solution. We applied our approach to real and simulated XFCT data and compared its performance to previous inversion algorithms for the problem, showing its main advantages: better images than those obtained by other analytic methods and much faster than iterative methods in the discrete setting.
Mid-to-Late Holocene Aboriginal Flaked Stone Artefact Technology on the Cumberland Plain, Sydney, New South Wales, Australia: A View from the South Creek Catchment

ABSTRACT Despite being one of the most intensively investigated archaeological regions in Australia, the flaked stone technologies employed by Aboriginal people occupying the Cumberland Plain of western Sydney, New South Wales, remain poorly documented in the published literature. Here we present and discuss the results of a technological analysis of a sizeable cultural lithic assemblage recovered from a compliance-based salvage excavation completed within Woorong Park Residual Rise 1, an open air Aboriginal archaeological site located in the northwestern portion of the Plain, in the South Creek catchment. The flaked stone technology evidenced by this assemblage is characterized through descriptions of observed raw materials, reduction techniques and methods, flake attributes and tool types. The behavioral implications of the assemblage are considered in light of the region’s existing archaeological dataset and with particular reference to McDonald’s [(2008). Dreamtime superhighway: Sydney Basin rock art and prehistoric information exchange (Terra Australis 27). Canberra: Australian National University Press] comprehensive behavioral land use model for the broader Sydney region, which wholly encompasses the Cumberland Plain.
Novel Quinazoline Derivatives Bearing Various 4‐Aniline Moieties as Potent EGFR Inhibitors with Enhanced Activity Against NSCLC Cell Lines

A class of novel quinazoline derivatives bearing various C‐4 aniline moieties was synthesized and biologically evaluated as potent epidermal growth factor receptor (EGFR) inhibitors for intervention of non‐small‐cell lung cancer (NSCLC). Most of these inhibitors are comparable to gefitinib in inhibiting these cancer cell lines, and several of them even displayed superior inhibitory activity. In particular, analogue 5b with an IC50 of 0.10 μm against the EGFR wild‐type A431 cells and 5c with an IC50 of 0.001 μm against the gefitinib‐sensitive HCC827 cells (EGFR del E746‐A750) was identified as highly active EGFR inhibitors. It was also significant that the discovered analogue 2f, not only has high potency against the gefitinib‐sensitive cells (IC50 = 0.031 μm), but also possesses remarkably improved activity against the gefitinib‐resistant cells. In addition, the enzymatic assays and the Western blot analysis for evaluating the effects of the typical inhibitors indicated that these molecules strongly interfere with the EGFR target.
A Correspondence Metric for Imitation

Learning by imitation is a powerful form of learning. Different forms of imitation, like mimicry, copying, response facilitation, etc. have been studied extensively (Miklosi 1999). Recent research in robotics has begun to explore imitation as a means to allow complex robots, like humanoid robots, acquire new skills (Swinson & Bruemmer 2000). One of the key issues in imitation learning is the correspondence problem. This problem concerns the answer to the question: what action sequence of the imitator is similar to that of the demonstrator and how similar it is? The notion of “similarity” has remained subjective thus far. Robotics research in imitation has mostly focussed on action learning and classification, and not on the correspondence problem. Our aim is to develop a generalized metric that provides a scalar measure of dissimilarity/distance between any given pair of action sequences. This, we expect would be a uniform means to evaluate imitation in agents. The metric can also be used as a part of the action selection mechanism in an imitator agent.
Results of the RIMES Evaluation Campaign for Handwritten Mail Processing

This paper presents the results of the second test phase of the RIMES evaluation campaign. The latter is the first large-scale evaluation campaign intended to all the key players of the handwritten recognition and document analysis communities. It proposes various tasks around recognition and indexing of handwritten letters such as those sent by postal mail or fax by individuals to companies or administrations. In this second evaluation test, automatic systems have been evaluated on three themes: layout analysis, handwriting recognition and writer identification. The databases used are part of the RIMES database of 5605 real mails completely annotated as well as secondary databases of isolated characters and handwritten words (250,000 snippets). The paper reports on protocols and gives the results obtained in the campaign. (RIMES : Reconnaissance et Indexation de données Manuscrites et de fac similÉS / Recognition and Indexing of handwritten documents and faxes)
A Human Organization Analogy for Self-* Systems (CMU-CS-03-129)

The structure and operation of human organizations, such as corporations, offer useful insights to designers of selfsystems (a.k.a. self-managing or autonomic). Examples include worker/supervisor hierarchies, avoidance of micro-management, and complaint-based tuning. This paper explores the analogy, and describes the design of a selfstorage system that borrows from it.