Miracle-dz/UniFAR-FTUs huggingface dataset:
Commutativity and free products in Thompson's group V

We broaden the theory of dynamical interpretation, investigate the property of commutativity and explore the subject of subgroups forming free products in Thompson’s group V . We expand Brin’s terminology [11] for a revealing pair to an any tree pair. We use it to analyse the dynamical behaviour of an arbitrary tree pair which cannot occur in a revealing pair. Hence, we design a series of algorithms generating Brin’s revealing pair [11] from any tree pair, by successively eliminating the undesirable structures. To detect patterns and transitioning between tree pairs, we introduce a new combinatorial object called the chains graph. A newly defined, unique and symmetrical type of a tree pair, called a balanced tree pair, stems from the use of the chains graphs. The main theorem of Bleak et al. [5] states the necessary structure of the centraliser of an element of V . We provide a converse to this theorem, by proving that each of the predicted structures is realisable. Hence we obtain a complete classification of centralisers in V . We give an explicit construction of an element of V with prescribed centraliser. The underlying concept is to embed a Cayley graph of a finite group into the flow graph (introduced in Bleak et al. [5]) of the desired element. To reflect the symmetry, we present the resulting element in terms of a balanced tree pair. The group V is conjectured to be a universal coCF group, which generates interest in studying its subgroups. We develop a better understanding of embeddings into V by providing a necessary and sufficient dynamical condition for two subgroups (not both torsion) to form a free product in V . For this, we use the properties, explored in Bleak and Salazar–Díaz [8], of sets of so–called important points, and the Ping–Pong action induced on them.
A fast algorithm for univariate log‐concave density estimation

A new fast algorithm for computing the nonparametric maximum likelihood estimate of a univariate log‐concave density is proposed and studied. It is an extension of the constrained Newton method for nonparametric mixture estimation. In each iteration, the newly extended algorithm includes, if necessary, new knots that are located via a special directional derivative function. The algorithm renews the changes of slope at all knots via a quadratically convergent method and removes the knots at which the changes of slope become zero. Theoretically, the characterisation of the nonparametric maximum likelihood estimate is studied and the algorithm is guaranteed to converge to the unique maximum likelihood estimate. Numerical studies show that it outperforms other algorithms that are available in the literature. Applications to some real‐world financial data are also given.
ThermoCodegen: a python/C++ package for the generation of custom thermodynamic models

Many important problems in solid-Earth science require a consistent coupling between thermodynamics and geodynamics. Examples include global mantle convection with thermodynamically consistent phase changes, the generation and flow of magma in the mantle, reactive fluid flow and geological carbon sequestration in the crust and even the coupled flow of water and ice in glaciers and ice sheets. Given the complexity of these systems, it is important that the individual user/scientist have considerable control over the formulation and computational choices involved for both the thermodynamic and geodynamic components of models while maintaining transparency and reproducibility. Access to flexible open-source software for the creation and exploration of thermodynamic models and their incorporation into large scale reactive flow simulations is essential for these endeavors.
PAS domain of flagellar histidine kinase FlrB exhibits novel architecture, and binds Heme as sensory signal in unconventional fashion

Phosphorylation of the σ54-dependent transcription activator FlrC by the sensor histidine kinase FlrB is essential in flagellar synthesis of Vibrio cholerae. Despite that, the structure, sensory signal, and mechanistic basis of function of FlrB were elusive. Here we report the crystal structure of the sensory PAS domain of FlrB in functional dimeric state that exhibits a novel architecture. Series of biochemical/biophysical experiments unequivocally established heme as sensory ligand that packs hydrophobically in the ligand binding cleft of FlrB-PAS. Intriguingly, ATP binding to the C-terminal ATP binding (CA) domain assists PAS domain to bind heme, vis-à-vis, heme binding to the PAS facilitates ATP binding to CA; suggesting a synergistic mode of heme and ATP binding to FlrB. We propose that such synergistic binding triggers conformational signaling in FlrB, leading to the downstream flagellar gene transcription. Enhanced swimming motility of V. cholerae with increased heme uptake further supports this proposition.
All-optical mapping of cAMP transport reveals rules of sub-cellular localization

Cyclic adenosine monophosphate (cAMP) is a second messenger that mediates diverse intracellular signals. Studies of cAMP transport in cells have produced wildly different results, from reports of nearly free diffusion to reports that cAMP remains localized in nanometer-scale domains. We developed an all-optical toolkit, termed cAMP-SITES, to locally perturb and map cAMP transport. In MDCK cells and in cultured neurons, cAMP had a diffusion coefficient of ∼120 µm2/s, similar to the diffusion coefficients of other small molecules in cytoplasm. In neuronal dendrites, a balance between diffusion and degradation led to cAMP domains with a length scale of ∼30 µm. Geometrical confinement by membranes led to subcellular variations in cAMP concentration, but we found no evidence of nanoscale domains or of distinct membrane-local and cytoplasmic pools. We introduce theoretical relations between cell geometry and small-molecule reaction-diffusion dynamics and transport to explain our observations.
Anatomy of a mega-radiation: Biogeography and niche evolution in Astragalus

Astragalus (Fabaceae), with more than 3,000 species, represents a successful radiation of morphologically highly similar species found across the Northern Hemisphere. It has attracted attention from systematists and biogeographers, who have asked what factors might be behind the extraordinary diversity of this important arid-adapted clade and what sets it apart from close relatives with far less species richness. Here, for the first time using extensive taxonomic sampling in a phylogenetic analysis, we ask whether (1) Astragalus is uniquely characterized by bursts of radiation or is instead similar to related taxa. Then we test whether the species diversity of Astragalus is attributable specifically to its predilection for (2) cold and arid habitats or (3) particular soils. Finally, we test (4) whether Astragalus originated in central Asia as proposed and (5) whether niche evolutionary shifts were associated with the colonization of other continents. Our results point to the importance of heterogeneity in the diversification of Astragalus, with upshifts associated with the earliest divergences but attributable to no abiotic factor or biogeographic regionalization tested here. The only potential correlate with diversification we identified was chromosome number. We find strong evidence for a central Asian origin and direct dispersals from this region responsible for much of the present-day distribution, highlighting the importance of central Asia as a biogeographic gateway. In contrast to diversification shifts, biogeographic shifts have a strong association with the abiotic environment. Our most important result was a fundamental divide in soil types and diurnal temperature variation between the Eastern and Western Hemisphere species; this divergence does not reflect differences in available habitat among these biogeographic domains but may reflect unique local gains of edaphic and abiotic stress adaptations. While large clades are logistically difficult to tackle, our investigation shows the importance of phylogenetic and evolutionary studies of “mega-radiations. ” Our findings reject any simple key innovation behind the dominance and richness of Astragalus and underline the often nuanced, multifactorial processes leading to species-rich clades.
Coordination of transporter, cargo, and membrane properties during non-vesicular lipid transport

Homeostasis of cellular membranes is maintained by fine-tuning their lipid composition. Yeast lipid transporter Osh6, belonging to the oxysterol-binding protein-related proteins family, was found to participate in the transport of phosphatidylserine (PS). PS synthesized in the endoplasmic reticulum is delivered to the plasma membrane, where it is exchanged for phosphatidylinositol-4 phosphate (PI4P). PI4P provides the driving force for the directed PS transport against its concentration gradient. In this study, we employed an in vitro approach to reconstitute the transport process into the minimalistic system of large unilamellar vesicles to reveal its fundamental biophysical determinants. Our study draws a comprehensive portrait of the interplay between the structure and dynamics of Osh6, the carried cargo lipid, and the physical properties of the involved membranes, with particular attention to their charge and fluidity. Specifically, we address the role of the cargo lipid, which, by occupying the transporter, imposes changes in its dynamics and, consequently, predisposes the cargo to disembark in the correct target membrane.
Acoustically evoked K-complexes are sufficient to boost verbal memory consolidation during sleep

The pivotal role of sleep in memory consolidation is widely acknowledged, yet which specific electrophysiological components drive this process remains a topic of intense debate. To unveil this process, a neuromodulation approach enabling the precise manipulation of specific oscillations is necessary. Here, we combined phase-targeted auditory stimulation (PTAS) during sleep in combination with high-density electroencephalography (hd-EEG) to specifically evoke K-complexes (KCs), a prominent oscillation during non-rapid-eye-movement (NREM) sleep. Over the course of two nights, one with PTAS, the other without, data from 14 young healthy adults were recorded. By targeting the down-phase of slow waves, auditory stimuli selectively evoked KCs. Strikingly, these evoked KCs were associated with improved verbal memory consolidation via enhanced cross-frequency coupling between slow waves and spindles in a right frontal region. This finding suggests that evoked KCs actively participate in the hippocampal-neocortical dialogue and thereby drive the consolidation of memories during sleep.
Six novel nsSNPs affect RUNX1 gene may leading to Acute Myeloid Leukemia (AML) using Bioinformatics approach

Background RUNX1 is one of the most frequently mutated genes in human AMLs, most of RUNX1 mutations in acute myeloid leukemia (AML) are missense or deletion-truncation and behave as loss-of-function mutations. The molecular consequences of cancer associated mutations in Acute myeloid leukemia (AML) linked factors are not very well understood. Here, we recognize possible pathogenic SNPs in the RUNX1 gene as Functional differences caused by SNPs might have harmful effects on protein structure and function using various computational tools. Methodology Data gained from NCBI database and various tools used to study nsSNPs which they are: SIFT, Polyphen-2, Provean, SNAP2, I-Mutant, Project Hope, Raptor X, PolymiRTS and Gene MANIA. Result Our study reveals six novel SNPs observed to be the most damaging SNPs that affect structure and function of RUNX1 gene using various bioinformatics tools. Conclusion This study revealed 7 damaging SNPs, 6 novel nsSNP out of them in the RUNX1 gene that leads to AML, by using different bioinformatics tools. Also, 23 functional classes were predicted in 8 SNPs in the 3’UTR, among them, 6 alleles disrupted a conserved miRNA site and 16 derived alleles created a new site of miRNA. This might result in the de regulation of the gene function. Hopefully, these results will help in genetic studying and diagnosis of AML improvement.
Hexatomic: An extensible, OS-independent platform for deep multi-layer linguistic annotation of corpora

Linguistic research aims to understand how languages work. This includes finding regularities, understanding language use and/or production in a specific context, and other linguistic research topics. The data for this research are language artifacts, e.g., recordings or transcriptions of spoken language and records of written language, that are often collected in corpora. In order to analyze languages through these corpora, linguists apply different methods. Some of these methods are computational and include automated annotation of corpora through natural language processing, or gathering statistical insights into corpora through machine learning. Other methods are computer-aided, and include manual annotation of corpora across multiple annotation layers. Linguistic phenomena often occur on different aspects of language, e.g. morphology, part-of-speech, lemmatization, constituent and dependency syntax, entities, coreference, discourse and information structure. For a deep analysis and understanding of language data it is necessary to include annotation layers for these different aspects in a single multi-layer corpus. These annotations often have to be made manually, as linguists’ insights into specific language features often surpass the generalized models used in machine learning. Additionally, for languages with fewer speakers such as those investigated in linguistic typology and language documentation projects, machine learning models may not exist or there may just not be enough language data for training model.
Modeling soil-plant-water interaction

Purpose The purpose of this paper is to numerically investigate the combined effects of canopy (leaf area index [LAI]) and root properties (root distribution function [Rdf] and root area index [RAI]) on a suction induced in soil-root composite under three different scenarios. Design/methodology/approach Richards equation coupled with sink term was solved using a commercial finite element package “HYDRUS” to investigate suction induced in soil-root composite. Findings Scenario 1 unveiled that soil-root composite induces 1 to 20 per cent higher suction than bare soil under the absence of transpiration. From Scenario 2, value of suction at depth of maximum RAI in case of linearly decreasing Rdf was found to be higher than that of other Rdfs. However, depth of suction influence zone (SIZ) for uniform Rdf and non-linear Rdf was found to be 10 and 11 per cent higher than that of linearly decreasing Rdf. Depth of evaporation dominant zone (EDZ) for uniformly decreasing Rdf and non-linear Rdf was found to be 1.08 to 3 times higher than that of linearly decreasing Rdf. From Scenario 3, influence of LAI on depth of SIZ is minimal. Depth of EDZ was found to decrease with the increase in LAI. Based on simple calculation on infinite slope stability, influence of variation in root and shoot properties was found to be significant on its factor of safety. Research limitations/implications Numerical constitutive model has limitations that it does not consider aging of plant. This model is only applicable for a particular set of soil conditions. A long-term study is required in this field to further quantify parameters for improving calibration and modeling performance. Practical implications Following are the practical implication: consideration of vegetation properties into engineered design of green infrastructure (slopes in this case) and selection of vegetation with appropriate characteristics in design for enhancement of stability of green infrastructure. Originality/value Contents of this paper are original, and they have not been submitted to any other journal.
Constraint term refinement for compressive sensing image reconstruction

With the rapid development of sensor and communication technology, the volume and the resolution of the data became increasingly high. Compressive Sensing theory allows signal compressed at a rate much lower than the Nyquist rate, which is promising to deal with big data acquisition and transmission. Compressive sensing has been applied in a variety of fields such as clutter suppression, image/video reconstruction, and real time processing. Most of the conventional algorithms for the estimation of the original signal, for instance, Total Variation (TV), consist of consistency error and constraint terms, the latter of which is quite influential on the quality of reconstructed image. The results subject to different constraints may vary greatly, for example, the conventional TV constraint suffers from the step effect, while the Higher Degree Total Variation (HDTV) may have the defect of edge blur. Besides, the computational cost is another problem, which needs to be considered. In this paper, a constraint refinement based algorithm for compressive sensing image reconstruction is proposed. Firstly, the construction of the constraint term is studied. For images that show different characteristics (for example, the richness of texture, etc.), the appropriate constraints for different cases are discussed. Secondly, a modified constraint is introduced to overcome the defect of the aforementioned algorithms. Moreover, a fast approximation algorithm to enhance the calculation efficiency is proposed based on the introducing of an auxiliary function to cross update. The visual and quantitative assessment both prove the superiority of the proposed constraint refinement method in terms of SNR, SSIM, and PSNR.
Image Zooming Using Barycentric Rational Interpolation

Image zooming is one of the important issues of image processing that maintains the quality and structure of image. Zooming an image necessitates placing the extra pixels in the image data. Moreover, adding the data to the image must be consistent with the texture in the image in order to prevent artificial blocks. In this study, the required pixels are estimated using barycentric rational interpolation. The proposed method is a non-linear one which can preserve the edges and reduces the blur and block artifacts on the zoomed image. Numerical results are presented using PSNR and SSIM fidelity measures and they are compared to some other methods. The average PSNR of the original image and image zooming was 33.08 which can prove that image zooming is very similar to the original image. The experimental results revealed that the proposed method had a better performance compared to other methods and could provide good image quality.
Reduction of leaky wave coupling in a superstrate loaded antenna using metamaterial

ABSTRACT In this paper, an approach is presented for reducing leaky wave coupling of superstrate loaded slot array using zero index metamaterial structure. The dielectric superstrate generally aims at increasing the directivity of the antenna by the generation of leaky wave. In another aspect, the leaky wave reduces the isolation between radiating elements in multiple antenna system. Here, the metamaterial has been used to mitigate the mutual coupling by reducing the generation of the leaky wave. By the help of this approach, the isolation is improved throughout the operational bandwidth and maximum 15 dB isolation improvement is achieved with an edge to edge distance of 4 mm between radiating elements.
Have We Reached the Limits of Predictability for Tropical Cyclone Track Forecasting?

The tropical cyclone is the largest single-day-impact meteorological event in the United States and worldwide through its effects from storm surge, extreme winds, freshwater flooding, and embedded tornadoes. Fortunately, over the last three decades there have been incredible advances in forecast accuracy, especially for the track of the tropical cyclone’s center. Errors have been cut by two-thirds in just 25 years due to global modeling advances, data assimilation improvements, dramatic increases in observations primarily derived from satellite platforms, and use of ensemble forecast techniques. These four factors have allowed for highly accurate synoptic-scale atmospheric initial conditions and forecasts of the steering flow out through several days into the future. However, such improvements cannot continue indefinitely. It is well known in the atmospheric sciences that there exists an inherent “limit of predictability” because of errors at the smallest scales (microscale—meters and seconds) that eventually cascade up to the largest scales (synoptic scale—thousands of kilometers and several days). While there have been estimates of the limits of predictability for tropical cyclone track prediction in the past, our current capabilities have exceeded those somewhat pessimistic earlier outlooks. This essay discusses the current state of the art for tropical cyclone track prediction and reassesses whether reaching the “limit of predictability” is imminent. The ramifications of this eventual conclusion—whether in the short-term or still decades away—could be critical for all users of tropical cyclone track forecast information, including the emergency management community/governments, the media, the private sector, and the general public.
Memory Latency Distribution-Driven Regulation for Temporal Isolation in MPSoCs

Temporal isolation is one of the most significant challenges that must be addressed before Multi-Processor Systems-on-Chip (MPSoCs) can be widely adopted in mixed-criticality systems with both time-sensitive real-time (RT) applications and performance-oriented non-real-time (NRT) applications. Specifically, the main memory subsystem is one of the most prevalent causes of interference, performance degradation and loss of isolation. Existing memory bandwidth regulation mechanisms use static, dynamic, or predictive DRAM bandwidth management techniques to restore the execution time of an application under contention as close as possible to the execution time in isolation. In this paper, we propose a novel distribution-driven regulation whose goal is to achieve a timeliness objective formulated as a constraint on the probability of meeting a certain target execution time for the RT applications. Using existing interconnect-level Performance Monitoring Units (PMU), we can observe the Cumulative Distribution Function (CDF) of the per-request memory latency. Regulation is then triggered to enforce first-order stochastical dominance with respect to a desired reference. Consequently, it is possible to enforce that the overall observed execution time random variable is dominated by the reference execution time. The mechanism requires no prior information of the contending application and treats the DRAM subsystem as a black box. We provide a full-stack implementation of our mechanism on a Commercial Off-The-Shelf (COTS) platform (Xilinx Ultrascale+ MPSoC), evaluate it using real and synthetic benchmarks, experimentally validate that the timeliness objectives are met for the RT applications, and demonstrate that it is able to provide 2.2x more overall throughput for NRT applications compared to DRAM bandwidth management-based regulation approaches.
Effects from Surface and Structural Similarity in Analogical Transfer in High and Low Familiarity Problems: First Results

Two exploratory studies were conducted in order to analyze the level of success in problem-solving transfer processes. Analogies between a «source» problem and different «target» problems were established through their Surface and Structural features. Results showed that when the context of the problems is familiar for students then Surface similarities can hide Structural differences. However, when the context of the problems is not familiar for students, the only significant effect came from the equal/different Structures. «Familiarity» with the context of the problems caused a global and systematic effect: non-familiar problems achieved lower success than familiar problems, no matter the relationship between source and target problems.