Summary
The adoption of diverse resource acquisition strategies is critical for plant growth and species coexistence. Root phosphatase is of particular importance in the acquisition of soil ...phosphorus (P), yet it is often overlooked in studies of root trait syndromes.
Here, we evaluated the role of root phosphatase activity (RPA) within the root economics space and the order‐based variation of RPA, as well as the correlations between RPA and a suite of leaf traits and soil properties over a range of evergreen tree species in a subtropical forest.
Root phosphatase activity exhibited a high degree of inter‐specific variation. We found that there were two leading dimensions of the multidimensional root economics space, the root diameter–specific root length axis (collaboration trait gradient) and the root tissue density–root nitrogen concentration axis (classical trait gradient), and RPA aligned with the former. Root phosphatase activity is used as a ‘do it yourself’ strategy of soil P acquisition, and was found to be inversely correlated with mycorrhizal colonization, which suggests a trade‐off in plant P acquisition strategies. Compared with soil and foliar nutrient status, root traits mattered most for the large inter‐specific changes in RPA. Furthermore, RPA generally decreased from first‐ to third‐order roots.
Taken together, such diverse P‐acquisition strategies are conducive to plant coexistence within local forest communities. The use of easily measurable root traits and their tight correlations with RPA could be a feasible and promising approach to estimating species‐specific RPA values, which would be helpful for better understanding plant P acquisition and soil P cycling.
See also the Commentary on this article by Yaffar et al., 234: 773–775.
Bayesian inverse problems often involve sampling posterior distributions on infinite-dimensional function spaces. Traditional Markov chain Monte Carlo (MCMC) algorithms are characterized by ...deteriorating mixing times upon mesh-refinement, when the finite-dimensional approximations become more accurate. Such methods are typically forced to reduce step-sizes as the discretization gets finer, and thus are expensive as a function of dimension. Recently, a new class of MCMC methods with mesh-independent convergence times has emerged. However, few of them take into account the geometry of the posterior informed by the data. At the same time, recently developed geometric MCMC algorithms have been found to be powerful in exploring complicated distributions that deviate significantly from elliptic Gaussian laws, but are in general computationally intractable for models defined in infinite dimensions. In this work, we combine geometric methods on a finite-dimensional subspace with mesh-independent infinite-dimensional approaches. Our objective is to speed up MCMC mixing times, without significantly increasing the computational cost per step (for instance, in comparison with the vanilla preconditioned Crank–Nicolson (pCN) method). This is achieved by using ideas from geometric MCMC to probe the complex structure of an intrinsic finite-dimensional subspace where most data information concentrates, while retaining robust mixing times as the dimension grows by using pCN-like methods in the complementary subspace. The resulting algorithms are demonstrated in the context of three challenging inverse problems arising in subsurface flow, heat conduction and incompressible flow control. The algorithms exhibit up to two orders of magnitude improvement in sampling efficiency when compared with the pCN method.
Multivariate data obtained using, for instance, Laser-Induced Breakdown Spectroscopy (LIBS), are quite bulky and complex. Advanced processing of spectroscopic data demands a multidisciplinary ...approach, covering not only modern machine learning tools but also a deep understanding of underlying physical mechanisms. Dimension reduction and visualization of large datasets is a task of significant interest in the spectroscopic data processing. Commonly employed linear techniques (e.g., Principal Component Analysis, PCA) cannot explain the correlations of higher-order which are present in the data. Even more, computational cost and memory limitations become way more relevant considering the size of “modern” LIBS data (millions of high-dimensional spectra). Methods based on Artificial Neural Networks (ANN) seem suitable for this task, and based on their success, they are given considerable attention within the spectroscopic community. We propose a new methodology based on Restricted Boltzmann Machine (ANN method) for dimensionality reduction of spectroscopic data and compare it to standard PCA. As an extension to successful reconstruction, we demonstrate a generation of new (unseen) spectra by the RBM model trained on a large spectroscopic dataset. This data generation is of great use not only for the extending measured datasets but also as a proper training state's confirmation of the model.
Display omitted
•A new technique for dimension reduction of a large spectroscopic data with a low reconstruction error.•The first-time employment of RBM method in LIBS data processing.•Generation of new spectra from the RBM model.•Definition and description of unique properties of spectroscopic data.
In this paper, we study the distribution of parallelograms and rhombi in a given set in the plane over arbitrary finite fields Fq2. As an application, we improve the recent result due to Fitzpatrick, ...Iosevich, McDonald, and Wyman on the Vapnik–Chervonenkis dimension of the induced distance graph.
We perform a sparse identification of nonlinear dynamics (SINDy) for low-dimensionalized complex flow phenomena. We first apply the SINDy with two regression methods, the thresholded least square ...algorithm and the adaptive least absolute shrinkage and selection operator which show reasonable ability with a wide range of sparsity constant in our preliminary tests, to a two-dimensional single cylinder wake at $Re_D=100$, its transient process and a wake of two-parallel cylinders, as examples of high-dimensional fluid data. To handle these high-dimensional data with SINDy whose library matrix is suitable for low-dimensional variable combinations, a convolutional neural network-based autoencoder (CNN-AE) is utilized. The CNN-AE is employed to map a high-dimensional dynamics into a low-dimensional latent space. The SINDy then seeks a governing equation of the mapped low-dimensional latent vector. Temporal evolution of high-dimensional dynamics can be provided by combining the predicted latent vector by SINDy with the CNN decoder which can remap the low-dimensional latent vector to the original dimension. The SINDy can provide a stable solution as the governing equation of the latent dynamics and the CNN-SINDy-based modelling can reproduce high-dimensional flow fields successfully, although more terms are required to represent the transient flow and the two-parallel cylinder wake than the periodic shedding. A nine-equation turbulent shear flow model is finally considered to examine the applicability of SINDy to turbulence, although without using CNN-AE. The present results suggest that the proposed scheme with an appropriate parameter choice enables us to analyse high-dimensional nonlinear dynamics with interpretable low-dimensional manifolds.
•How humans can dexterously pick tomatoes from a plant was explored.•A high linear correlation existed among stature, hand length and arm length.•Human body dimensions determine upperlimb workspace ...and body balance during picking.•Significant differences existed between some of hand-scaling dimensions.•The study provides inspiration for the anthropomorphic design of harvesting robots.
To explore how humans can dexterously pick fruits of various sizes from a tomato plant from different positions and postures, some anthropometric dimensions related to the hand-harvesting of the fruits were determined within 261 volunteers, and their correlations were investigated using a bivariate correlation analysis method. The heights of the body (stature), shoulder tip, waist and knee of participants ranged from 111.2 to 193.6, 87.5 to 163.0, 62.1 to 117.3, and 31.0 to 56.0 cm, respectively; the ratios of the knee height, waist height, and shoulder tip height to the stature were 0.25–0.33, 0.52–0.65, and 0.76–0.87, respectively; the shoulder tip breadth, upper limb length and foot length of participants ranged from 26.0 to 48.5, 45.4 to 85.6, and 19.5 to 28.0 cm, respectively; and the length ratios of the hand, forearm, and upper arm to the upper limb were 0.23–0.31, 0.29–0.38, and 0.35–0.45, respectively. There were high linear correlations among the stature, waist height and knee height, between the forearm and hand lengths, and among the stature, hand length and arm length and moderate linear correlations between most hand dimensions. These human body dimensions determine the upper limb workspace, body balance, working comfort and lower limb movement frequency during picking, and this information will be useful for the bionic dimensional synthesis design of a harvesting robotic arm, walking mechanism and body. The results of multiple comparisons in ANOVA showed that there were significant differences between some of the finger dimensions and between some of the hand-scaling dimensions, which is one of the main features enabling the human hand to pick various sizes of fruits. This study can provide guidance and inspiration for the anthropomorphic design of robotic tomato-harvesting end-effectors.
The study of higher-dimensional black holes is a subject which has recently attracted vast interest. Perhaps one of the most surprising discoveries is a realization that the properties of ...higher-dimensional black holes with the spherical horizon topology and described by the Kerr–NUT–(A)dS metrics are very similar to the properties of the well known four-dimensional Kerr metric. This remarkable result stems from the existence of a single object called the principal tensor. In our review we discuss explicit and hidden symmetries of higher-dimensional Kerr–NUT–(A)dS black hole spacetimes. We start with discussion of the Killing and Killing–Yano objects representing explicit and hidden symmetries. We demonstrate that the principal tensor can be used as a “seed object” which generates all these symmetries. It determines the form of the geometry, as well as guarantees its remarkable properties, such as special algebraic type of the spacetime, complete integrability of geodesic motion, and separability of the Hamilton–Jacobi, Klein–Gordon, and Dirac equations. The review also contains a discussion of different applications of the developed formalism and its possible generalizations.
Dualities and 5-brane webs for 5d rank 2 SCFTs Hayashi, Hirotaka; Kim, Sung-Soo; Lee, Kimyeong ...
The journal of high energy physics,
12/2018, Letnik:
2018, Številka:
12
Journal Article
Recenzirano
Odprti dostop
A
bstract
We consider Type IIB 5-brane configurations for 5d rank 2 superconformal theories which are classified recently by geometry in
1
. We propose all the 5-brane web diagrams for these rank 2 ...theories and show dualities between some of different gauge theories with explicit duality map of mass parameters and Coulomb branch moduli. In particular, we explicitly construct 5-brane configurations for
G
2
gauge theory with six flavors and its dual Sp(2) and SU(3) gauge theories. We also present 5-brane webs for SU(3) theories of Chern-Simons level greater than 5.
We investigate the behavior of the extension dimension of subcategories of abelian categories under recollements. Let Λ′, Λ, Λ″ be artin algebras such that (mod Λ′, mod Λ, mod Λ′) is a recollement, ...and let
D
′
and
D
′
′
be subcategories of mod Λ′ and mod Λ″ respectively. For any
n, m
≥ 0, under some conditions, we get
dim
Ω
k
(
D
)
≤
dim
Ω
n
(
D
′
)
+
dim
Ω
m
(
D
′
′
)
+
1
, where
k
= max{
m, n
} and
D
is the subcategory of mod Λ glued by
D
′
and
D
′
′
; moreover, we give a sufficient condition such that the converse inequality holds true. As applications, some results for Igusa–Todorov subcategories and syzygy finite subcategories are obtained.
Human–wildlife coexistence in a changing world König, Hannes J.; Kiffner, Christian; Kramer‐Schadt, Stephanie ...
Conservation biology,
August 2020, Letnik:
34, Številka:
4
Journal Article
Recenzirano
Odprti dostop
Human–wildlife conflict (HWC) is a key topic in conservation and agricultural research. Decision makers need evidence‐based information to design sustainable management plans and policy instruments. ...However, providing objective decision support can be challenging because realities and perceptions of human–wildlife interactions vary widely between and within rural, urban, and peri‐urban areas. Land users who incur costs through wildlife argue that wildlife‐related losses should be compensated and that prevention should be subsidized. Supporters of human–wildlife coexistence policies, such as urban‐dwelling people, may not face threats to their livelihoods from wildlife. Such spatial heterogeneity in the cost and benefits of living with wildlife is germane in most contemporary societies. This Special Section features contributions on wildlife‐induced damages that range from human perspectives (land use, psychology, governance, local attitudes and perceptions, costs and benefits, and HWC and coexistence theory) to ecological perspectives (animal behavior). Building on current literature and articles in this section, we developed a conceptual model to help frame HWC and coexistence dimensions. The framework can be used to determine damage prevention implementation levels and approaches to HWC resolution. Our synthesis revealed that inter‐ and transdisciplinary approaches and multilevel governance approaches can help stakeholders and institutions implement sustainable management strategies that promote human–wildlife coexistence.
Coexistencia Humano – Vida Silvstre en un Mundo Cambiante
Resumen
El conflicto humano – vida silvestre (HWC) es un tema muy importante para la investigación agrícola y de la conservación. Los tomadores de decisiones necesitan información basada en evidencias para diseñar planes de manejo sustentable e instrumentos políticos. Sin embargo, proporcionar un apoyo objetivo para las decisiones puede ser un reto ya que las realidades y percepciones de las interacciones humano – vida silvestre varían enormemente entre y dentro de las áreas rurales, urbanas y peri‐urbanas. Los usuarios de terrenos que incurren en costos debido a la vida silvestre argumentan que las pérdidas relacionadas a la vida silvestre deberían ser compensadas y que la prevención debería estar subsidiada. Es probable que quienes apoyan las políticas de coexistencia entre humanos y vida silvestre, como los habitantes de zonas urbanas, no enfrenten una amenaza a su medio de subsistencia debido a la vida silvestre. Dicha heterogeneidad espacial en el costo y beneficio de cohabitar con la vida silvestre es relevante en la mayoría de las sociedades contemporáneas. Esta Sección Especial presenta contribuciones sobre daños inducidos por vida silvestre que van desde las perspectivas humanas (uso de suelo, psicología, gobierno, actitudes y percepciones locales, costo y beneficio y la teoría del conflicto y la coexistencia humano‐vida silvestre) hasta las perspectivas ecológicas (comportamiento animal). A partir de los artículos y la literatura actuales en esta sección desarrollamos un modelo conceptual para ayudar a estructurar los alcances del HWC y de la coexistencia. El marco de trabajo puede usarse para determinar los niveles y estrategias de implementación de la prevención del daño a la solución del conflicto humano ‐ fauna. Nuestra síntesis reveló que las estrategias inter‐ y transdisciplinarias y las estrategias de gobierno multiniveles pueden ayudar a que los actores y las instituciones implementen estrategias de manejo sustentable para promover la coexistencia entre los humanos y la vida silvestre.
摘要
人类与野生动物的冲突是保护研究和农业研究的一个重要问题。决策者需要基于证据的信息来设计可持续的管理计划和政策工具。然而, 由于农村、城市和城郊之内或之间的人类与野生动物相互作用的现实情况和观念存在很大差异, 因此提供客观的决策支持也面临着挑战。因野生动物而遭受损失的土地使用者认为, 与野生动物相关的损失应该得到补偿, 且实施保护措施也应得到补贴。人与野生动物共存政策的支持者, 如城市居民, 则可能不会面临野生动物对生计的威胁。这种与野生动物共存的成本和收益的空间异质性普遍存在于多数当代社会。本专题包含介绍野生动物所造成破坏的系列文章, 研究的角度从人类视角 (土地利用、心理、管理、当地态度和观念、成本和收益、人类与野生动物的冲突和共存理论) 到生态视角 (动物行为) 。基于已有文献和本专题的文章, 我们设计了一个概念模型来为人类与野生动物共存及共存的维度制定框架。该框架可用于确定预防野生动物造成破坏的实施水平及解决人类与野生动物冲突的方法。我们的综合分析表明, 跨学科和多级管理方法可以帮助利益相关者和机构实施可持续管理策略, 促进人类与野生动物的共存。 【翻译: 胡怡思; 审校: 聂永刚】
Article impact statement: Integrated and participatory research are needed to provide the evidence base to address human–wildlife conflict and coexistence.
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