Miracle-dz/UniFAR-FTUs huggingface dataset:
Does competitive asymmetry confer polyploid advantage under changing environments?

Competitive interactions drive critical ecological processes in plant communities. Yet, how competitive interactions are influenced by polyploidy that has a widespread incidence in plants remains largely unknown. To evaluate the hypothesis of competitive asymmetry between polyploids and diploids, we competed tetraploid and diploid plants of perennial herbaceous Chrysanthemum indicum L. (Asteraceae) at different relative frequencies under contrasting soil water contents. We quantified the interaction intensity between competing plants of the same (intraploidy) and different ploidy levels (interploidy), and measured functional traits related to gas exchange and plant water use to understand the underlying mechanisms. The stronger competitive effect of tetraploids on diploids than that of diploids on tetraploids provided evidence for the competitive asymmetry. As a stronger competitor, tetraploids were limited more by individuals of their own than by diploids. Such competitive asymmetry was not only maintained under reduced soil water content, but also translated into higher above‐ground biomass of tetraploids. Tetraploids showed more resource‐acquisitive traits than diploids under high soil water content and more resource‐conservative traits under reduced soil water content. As such, the higher trait plasticity in tetraploids than diploids likely explained the competitive asymmetry. Synthesis. These results elucidate the nature and magnitude of species interactions between polyploid and diploid plants under changing environments and the underlying mechanisms, and provide important insights into the prevalence and persistence of polyploid plants under a changing climate.
TRANSLATING 'VECTOR SYMBOLS' FROM LABAN'S (1926) CHOREOGRAPHIE

A group of notation symbols were experimented with by Rudolf Laban (1926) in his early German work Choreographie but were not used subsequently during the development of choreutics and Kinetography Laban (Labanotation). This paper presents details of a stepby-step process of translating these early symbols into modern-day Labanotation direction symbols. To anticipate, it is found that these early symbols represent orientations of linesof-motion without any reference to locations, coordinates, or points in space. Thus, for convenience they are referred to here as ‘vector symbols’, noting that Laban (1926) did not designate any name (Fig. 1). These early vector symbols are then considered as to what they reveal about Laban’s choreutic conception of spatial harmony when it was still embedded within the notation system.
Combined addition of plant litter altered remediating effects on petroleum‐contaminated soil in Northern Shaanxi, China

In the present study, we assessed whether the nonadditive effects of mixed litter decomposition on soil biological and chemical properties, which was usually recognized in clean soils, could be used to enhance the efficiency of petroleum‐contaminated soil necrophytoremediation. In particular, six common plant species from the petroleum production region of Northern Shaanxi, China were collected, forming nine mixture types. The single and mixed litters were used to treat petroleum‐contaminated soil with a proportion of 45 g kg−1 at 25°C and a constant humidity for 150 days. The possible nonadditive effects on the efficiency of removing contaminants and recovering the damaged soil traits caused by the mixed litter addition were then investigated. The results indicate that monospecific litter treatments significantly increased the degradation rates of petroleum contaminants, the available N and P contents, and the catalase and dehydrogenase activities by 36%–74%, 28%–455%, and 8%–102%, respectively (p < 0.05). The mixed addition of the litters from Lespedeza davurica and Artemisia scoparia or those from Agropyron cristatum and Bromus inermis caused significant synergistic effects, enhancing the overall petroleum component removal, replenishing nutrients (particularly nitrogen) or stimulating enzymatic activities (especially for sucrase, phosphatase, catalase, and urease). The observed values of the corresponding indicators following mixed litter treatment were observed to significantly increase by 12%–18%, 23%–58%, and 9%–24% (p < 0.05), relative to their predicted values, which were calculated based on the observed values from the monospecific litter treatments and the proportion of the litter in the mixture. However, other litter combinations may weaken the remediation effects of the litter addition. In general, a high content of nutrients, primary metabolites (e.g., soluble sugars and amino acids), and the potential bio‐surfactants and co‐metabolized substrates (including terpenoids and flavonoids) of mixed litters enhanced the remediation efficiency of mixed litters. Notably, an increase in the chemical diversity of mixed litter may weaken its synergistic effects on the degradation of petroleum components and the simulation of soil polyphenol oxidase activity. Our results demonstrate that appropriate litter mixing combinations can effectively enhance the efficiency of necrophytoremediation, thus providing new approaches for the more convenient and economical remediation of petroleum‐contaminated soil.
Spin‐glass state induced low field magnetization‐step effect in a Hg1−xMnxTe single crystal

The low field magnetization‐step effect was observed in the spin‐glass (SG) regime of p‐type Hg0.8Mn0. 2Te single crystal when the temperature was less than about 3 K. The main features of this effect were (i) the magnetic susceptibility suddenly reduced to almost zero as the magnetic field decreased below a critical value; (ii) the critical magnetic field correlated reversely to temperature. In addition, X‐ray diffraction, Raman scattering, and temperature‐dependent Hall measurements manifested this effect was the intrinsic nature of the Hg1−xMnxTe single crystal. Qualitative theoretical analysis suggests that the possible mechanism of low field magnetization‐step effect is the combined effect of SG transition and (long‐range) antiferromagnetic interactions among Mn2+ ions in randomly frustrated spins system.
The H2 control problem with internal stability

AbstracI- A solution ofthe Hz control problem is presented for linear systems described by mfional transfer matrices. These rational matrices are not required to be proper and no assumption is made on the location of their poles and zeros. The control system is considered in the srnndord configuration, which includes the synthesis model of the plant and the controller. The H, control problem consists of internally stabilizing the control system while minimizing the H2 norm of its transfer function. The notion of internalstability is based on input-output stability and means that the subsystems defined by any pair of input and output terminals within the control system all are input-output stable. The solution proceeds in three steps. Firstly, the set of all controllers that stabilize internally the control system is parametrized. Then the subset of the stabilizing controllers that achieve a finite value of the H2 nurm of the system transfer function is described, also in parametric form. Finally, the optimal controller is obtained by selecting the parameter that -miles the norm. The existence of these three sets of controllers is established in terms of the given data. The mathematical tool applied are doubly coprime, proper stable factorizations of rational matrices. Based on this description of the plant, two synthesis algorithms are derived the primal and the dud one. The construction of the optimal controller requires two specific operations with proper stable rational matrices: inner-outer factorizstion and proper stable projection. The solution obtained is general in the sense that no assumptions on the plant are made other than those securing the outer factors to be square. I. INTRODUCTTON
Research and scholarly methods: Audit studies

Audit study methodologies have been utilized in pharmacy field research to obtain greater understanding of potential gaps in real‐world care and assess the accessibility of medications, services, and providers. Many audit studies utilize a secret‐shopper approach in which auditors follow specific assessment protocols and the subjects being audited are unaware of the audit taking place. The benefit of utilizing this approach, as compared to surveys or interviews, is that researchers are able to collect real‐world measures with minimized social desirability and recall biases. There are multiple audit study approaches investigators must consider. Additionally, successful audit studies often rely upon congruence of multiple auditors, and it is therefore essential to develop a study protocol that includes detailed guidance documents, data collection tools, and rigorous training and fidelity assessments. Audit methodologies must be conducted with meticulous auditor training and oversight, especially when investigators seek to audit a large sample and rely on auditors who may be participating on an unpaid volunteer basis. The purpose of this review is to provide an orientation to audit study methodologies and to describe best practices for conducting a successful audit study.
Adaptive Dynamic Analysis of MEMS Gyroscope Random Noise Based on PID-DAVAR

As a MEMS gyroscope is susceptible to environmental interference, its performance is degraded due to random noise. Accurate and rapid analysis of random noise of MEMS gyroscope is of great significance to improve the gyroscope’s performance. A PID-DAVAR adaptive algorithm is designed by combining the PID principle with DAVAR. It can adaptively adjust the length of the truncation window according to the dynamic characteristics of the gyroscope’s output signal. When the output signal fluctuates drastically, the length of the truncation window becomes smaller, and the mutation characteristics of the intercepted signal are analyzed detailed and thoroughly. When the output signal fluctuates steadily, the length of the truncation window becomes larger, and the intercepted signals are analyzed swiftly and roughly. The variable length of the truncation window ensures the confidence of the variance and shortens the data processing time without losing the signal characteristics. Experimental and simulation results show that the PID-DAVAR adaptive algorithm can shorten the data processing time by 50%. The tracking error of the noise coefficients of angular random walk, bias instability, and rate random walk is about 10% on average, and the minimum error is about 4%. It can accurately and promptly present the dynamic characteristics of the MEMS gyroscope’s random noise. The PID-DAVAR adaptive algorithm not only satisfies the requirement of variance confidence but also has a good signal-tracking ability.
IDENTIFICATION OF WIENER SYSTEM WITH MONOTONOUS NONLINEARITY

A Wiener system is composed of a linear dynamic subsystem followed by a static nonlinearity. It is well known in the literature that the identification of the linear subsystem of a Wiener system can be separated from that of the output nonlinearity, if the input signal is Gaussian distributed. In order to deal with the non Gaussian input case, two new algorithms are proposed in this paper for direct identification of the linear subsystem, regardless of any parametrization of the output nonlinearity. The essential assumption required in this paper is the strict monotonousness of the output nonlinearity.
Synchrotron–laser interactions in hexagonal boron nitride: an examination of charge trapping dynamics at the boron K-edge

Synchrotron–laser pump-probe (PP) luminescence measurements have been undertaken in hexagonal-phase boron nitride. For non-resonant excitation below the boron K-edge, the dynamics of the transients induced by the application of laser probes at 1.49, 2.33 and 3.07 eV are determined, as well as the signal recovery to equilibrium after the probes are removed. The transients are shown to be entirely related to the presence of trapping states within the material. By varying the synchrotron pump energy, the system dynamics are shown to change significantly, due to alteration in competition between the defect centres. As the synchrotron energy is scanned across the near-edge x-ray absorption (NEXAFS) region of the boron K-edge (190–205 eV), PP NEXAFS can be extracted directly from the trapping rate changes, and this opens the possibilities for directly linking particular charge trapping centres with their chemical environments. This is the first report where such processes have been used to obtain luminescence-based PP x-ray absorption spectra.
A Semidefinite Optimization Approach to Quadratic Fractional Optimization with a Strictly Convex Quadratic Constraint

In this paper we consider a fractional optimization problem that minimizes the ratio of two quadratic functions subject to a strictly convex quadratic constraint. First using the extension of Charnes-Cooper transformation, an equivalent homogenized quadratic reformulation of the problem is given. Then we show that under certain assumptions, it can be solved to global optimality using semidenite optimization relaxation in polynomial time.
Evaluation Technique of Chloride Penetration Using Apparent Diffusion Coefficient and Neural Network Algorithm

Diffusion coefficient from chloride migration test is currently used; however this cannot provide a conventional solution like total chloride contents since it depicts only ion migration velocity in electrical field. This paper proposes a simple analysis technique for chloride behavior using apparent diffusion coefficient from neural network algorithm with time-dependent diffusion phenomena. For this work, thirty mix proportions of high performance concrete are prepared and their diffusion coefficients are obtained after long term-NaCl submerged test. Considering time-dependent diffusion coefficient based on Fick’s 2nd Law and NNA (neural network algorithm), analysis technique for chloride penetration is proposed. The applicability of the proposed technique is verified through the results from accelerated test, long term submerged test, and field investigation results.
Parametrization of solar radiation in inhomogeneous stratocumulus: Albedo bias

Low‐level cloud fields with typical albedos between 50% and 70% contribute significantly to short‐wave cloud radiative forcing. Consequently, the earth's radiative budget is sensitive to extended stratocumulus which typically occurs in sub‐tropical subsidence regions over the oceans. It is therefore vital to represent the cloud albedo of such cloud fields accurately in climate models. Nevertheless, cloud fields are modelled as homogeneous plane‐parallel clouds, which leads to an overestimation of the albedo by up to 15% compared with real inhomogeneous clouds, both types of cloud fields having the same mean cloud optical depth. This so‐called plane‐parallel cloud albedo bias has given rise to a number of studies that present methods for reducing the albedo bias for stratiform clouds in climate models.
Fuzzy predictive Stanley lateral controller with adaptive prediction horizon

The challenge of trajectory tracking of autonomous vehicles (AVs) is a critical aspect that must be effectively addressed. Recent studies are concerned with maintaining the yaw stability to guarantee the customers’ comfort throughout the journey. Most of the geometrical controllers solve this task by dividing it into consecutive point stabilization problems, limiting the controllers’ ability to handle sudden trajectory changes. One research presented a predictive Stanley lateral controller that uses a discrete prediction model to mimic human behavior by anticipating the vehicle’s future states. That controller is limited in its use, as the parameters must be manually tuned for every change in the maneuver or vehicle velocity. This article presents a novel approach for trajectory tracking in autonomous vehicles, by introducing a fuzzy supervisory controller that automatically adapts to changes in the vehicle’s velocity and maneuver by estimating the prediction horizon’s length and providing different weights for each controller. The proposed method overcomes the limitations of traditional controllers that require manual tuning of parameters, making it ready for real-world experiments. This is the main contribution of the research in this paper. The suggested technique demonstrated an advantage over the Basic Stanley controller and the manually tuned predictive Stanley controller in terms of the total lateral error and the model predictive control (MPC) in terms of computational time. The performance is determined by performing various simulations on V-Rep and hardware-in-the-loop (HIL) experiments on an E-CAR golf bus. A broad selection of velocities is used to validate the behavior of the vehicle while working on different maneuvers (double lane change, hook road, S road, and curved road).
Quantum kernel methods for solving regression problems and differential equations

We propose several approaches for solving differential equations (DEs) with quantum kernel methods. We compose quantum models as weighted sums of kernel functions, where variables are encoded using feature maps and model derivatives are represented using automatic differentiation of quantum circuits. While previously quantum kernel methods primarily targeted classification tasks, here we consider their applicability to regression tasks, based on available data and differential constraints. We use two strategies to approach these problems. First, we devise a mixed model regression with a trial solution represented by kernel-based functions, which is trained to minimize a loss for specific differential constraints or datasets. Second, we use support vector regression that accounts for the structure of differential equations. The developed methods are capable of solving both linear and nonlinear systems. Contrary to prevailing hybrid variational approaches for parametrized quantum circuits, we perform training of the weights of the model classically. Under certain conditions this corresponds to a convex optimization problem, which can be solved with provable convergence to global optimum of the model. The proposed approaches also favor hardware implementations, as optimization only uses evaluated Gram matrices, but require quadratic number of function evaluations. We highlight trade-offs when comparing our methods to those based on variational quantum circuits such as the recently proposed differentiable quantum circuits (DQC) approach. The proposed methods offer potential quantum enhancement through the rich kernel representations using the power of quantum feature maps, and start the quest towards provably trainable quantum DE solvers.
The classification of [p]-nilpotent restricted Lie algebras of dimension 5

In this thesis, we will classify p-nilpotent restricted Lie algebras of dimension 5. Any finite dimensional p-nilpotent restricted Lie algebras is nilpotent by Engel’s theorem. Therefore, we use as our starting point, the classification of nilpotent Lie algebras of dimension 5 and classify the possible equivalence classes of p-maps on these Lie algebras. We first explain the method that we used to classify p-nilpotent restricted Lie algebras of dimension 5 which is the analogue of Skjelbred-Sund method for classifying nilpotent Lie algebras. Then, we will give a complete classification of p-nilpotent restricted Lie algebras of dimension 5 over perfect fields of characteristic p > 5.
Anti‐windup design for uncertain nonlinear systems subject to actuator saturation and external disturbance

A novel anti‐windup design method is provided for a class of uncertain nonlinear systems subject to actuator saturation and external disturbance. The controller considered incorporates both an active disturbance rejection controller as well as an anti‐windup compensator. The dynamical uncertainties and external disturbance are treated as an extended state of the plant, and then estimate it using an extended state observer and compensate for it in the control action, in real time. The anti‐windup compensator produces a signal based on the difference between the controller output and the saturated actuator output, and then augment the signal to the control to deal with the windup phenomenon caused by actuator saturation. We first show that, with the application of the proposed controller, the considered nonlinear system is asymptotically stable in a region including the origin. Then, in the case that the controller in linear form, we establish a linear matrix inequality‐based framework to compute the extended state observer gain and the anti‐windup compensation gain that maximize the estimate of the domain of attraction of the resulting closed‐loop system. The effectiveness of the proposed method is illustrated by a numerical example. Copyright © 2016 John Wiley & Sons, Ltd.
In Vitro Antibiofilm Activity of Resveratrol against Aeromonas hydrophila

Aeromonas hydrophila is a Gram-negative bacterium that widely exists in various aquatic environments and causes septicemia in fish and humans. Resveratrol, a natural polyterpenoid product, has potential chemo-preventive and antibacterial properties. In this study, we investigated the effect of resveratrol on A. hydrophila biofilm formation and motility. The results demonstrated that resveratrol, at sub-MIC levels, can significantly inhibit the biofilm formation of A. hydrophila, and the biofilm was decreased with increasing concentrations. The motility assay showed that resveratrol could diminish the swimming and swarming motility of A. hydrophila. Transcriptome analyses (RNA-seq) showed that A. hydrophila treated with 50 and 100 μg/mL resveratrol, respectively, presented 230 and 308 differentially expressed genes (DEGs), including 90 or 130 upregulated genes and 130 or 178 downregulated genes. Among them, genes related to flagellar, type IV pilus and chemotaxis were significantly repressed. In addition, mRNA of virulence factors OmpA, extracellular proteases, lipases and T6SS were dramatically suppressed. Further analysis revealed that the major DEGs involved in flagellar assembly and bacterial chemotaxis pathways could be regulated by cyclic-di-guanosine monophosphate (c-di-GMP)- and LysR-Type transcriptional regulator (LTTR)-dependent quorum sensing (QS) systems. Overall, our results indicate that resveratrol can inhibit A. hydrophila biofilm formation by disturbing motility and QS systems, and can be used as a promising candidate drug against motile Aeromonad septicemia.
Degree correlations in the group preferential model

We focus on the study of degree correlations of the group preferential model, in which a link is established with a pre-existing vertex according to an attachment probability which depends on the degree of the m targeted vertices of the new vertex. By using the rate equation approach, we have obtained asymptotic expressions for two vertex and three vertex degree correlations. Finally, all analytical solutions are successfully contrasted with computer simulations.