Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Localized Irrigation and Fertilizer on Woody Plant Establishment in Degraded Semi-Arid Environments

Reclamation of mine and associated waste rock dumps can improve site aesthetics and ecosystem function. In the mountain west region of the United States, mining activities commonly occur in zones dominated by native woody plant cover. Woody plants are important to ecological function for many reasons, including reducing erosion and providing food and shelter for wildlife. Unfortunately, restoration of woody plants to these areas has proven to be challenging. Direct seeding efforts can be hindered by poor germination and low seedling emergence. To overcome this, seedling transplants are often used in harsh sites. However, transplanted woody plant seedlings frequently experience high mortality during the first year, particularly as plants are stressed during the summer drought period. This study evaluated the use of Waterboxx® devices as a tool for establishing seedlings on a waste rock pile. The Waterboxx® device collects precipitation and condensates into a polypropylene reservoir and then slowly releases the water into the soil next to the seedling. We planted 400 seedlings composed of five native woody plants, with and without a Waterboxx®, between the fall of 2020 and spring of 2021. Species planted included Atriplex canescens, Cercocarpus ledifolius, Pinus edulis, Purshia tridentata and Rhus glabra. The Waterboxx® device improved soil water availability and subsequently survival for four of the five species. The Waterboxx® device also improved vigor for three of the five species depending on the planting season. Based on the results obtained, Waterboxx® devices appear to be a viable method for most of these species in improving their establishment on mine land overburden sites in the semi-arid mountain west. The effectiveness of the Waterboxx® device in the semi-arid west of Utah suggests this technology could be used globally where water is a limiting factor for seedling establishment of some species; however, additional research is merited for other areas of the world.
Stochastic curvature of enclosed semiflexible polymers.

The conformational states of a semiflexible polymer enclosed in a compact domain of typical size a are studied as stochastic realizations of paths defined by the Frenet equations under the assumption that stochastic "curvature" satisfies a white noise fluctuation theorem. This approach allows us to derive the Hermans-Ullman equation, where we exploit a multipolar decomposition that allows us to show that the positional probability density function is well described by a telegrapher's equation whenever 2a/ℓ_{p}>1, where ℓ_{p} is the persistence length. We also develop a Monte Carlo algorithm for use in computer simulations in order to study the conformational states in a compact domain. In addition, the case of a semiflexible polymer enclosed in a square domain of side a is presented as an explicit example of the formulated theory and algorithm. In this case, we show the existence of a polymer shape transition similar to the one found by Spakowitz and Wang [Phys. Rev. Lett. 91, 166102 (2003)PRLTAO0031-900710.1103/PhysRevLett.91. 166102] where in this case the critical persistence length is ℓ_{p}^{*}≃a/8 such that the mean-square end-to-end distance exhibits an oscillating behavior for values ℓ_{p}>ℓ_{p}^{*}, whereas for ℓ_{p}
FLAIR #1: semantic segmentation and domain adaptation dataset

The French National Institute of Geographical and Forest Information (IGN) has the mission to document and measure land-cover on French territory and provides referential geographical datasets, including high-resolution aerial images and topographic maps. The monitoring of land-cover plays a crucial role in land management and planning initiatives, which can have significant socio-economic and environmental impact. Together with remote sensing technologies, artificial intelligence (IA) promises to become a powerful tool in determining land-cover and its evolution. IGN is currently exploring the potential of IA in the production of high-resolution land cover maps. Notably, deep learning methods are employed to obtain a semantic segmentation of aerial images. However, territories as large as France imply heterogeneous contexts: variations in landscapes and image acquisition make it challenging to provide uniform, reliable and accurate results across all of France. The FLAIR-one dataset presented is part of the dataset currently used at IGN to establish the French national reference land cover map"Occupation du sol \`a grande \'echelle"(OCS- GE).
Correspondence between theory and observations of polar motion

SUMMARY The Earth’s orientation in space changes in response to the action of a variety of torques, generated both externally and internally. External torques arising from the gravitational forces of the Sun and Moon act upon the Earth, causing it to undergo periodic motions known as the lunisolar precession and nutations. Internal dynamical processes that change the deformable Earth’s inertia tensor, or that generate relative angular momentum, also cause the Earth’s orientation in space to change, the resulting motions being known as wobble (or polar motion) and changes to the length-of-day. Historically, it was thought that observations determined the location of the rotation pole within some rotating reference frame fixed to the solid Earth, and theoretical expressions for the nutations and wobble were developed and given in terms of the Earth’s rotation axis. However, it has been (relatively recently) argued that observatories, being located on the surface of the Earth, are more nearly moving with the Earth’s surface, and hence observations more nearly reflect the motion of the Earth’s figure axis, rather than its rotation or angular momentum axes. This argument was accepted by the International Astronomical Union, and the current 1980 Theory of Nutation refers to an axis, the celestial ephemeris pole, that is more closely associated with the Earth’s figure axis than it is with the Earth’s rotation axis. Polar motion values, as reported by modern Earth rotation services, give the location of the celestial ephemeris pole within some rotating, body-fixed reference frame. The celestial ephemeris pole does not correspond to either the Earth’s instantaneous figure axis, its instantaneous rotation axis, or its instantaneous angular momentum axis, but rather corresponds to an axis that exhibits no nearly diurnal motions in either the terrestrial, body-fixed reference frame or the celestial, space-fixed frame. The focus of this paper is not on the nutational motions of the Earth generated by external torques, but rather on the wobble. The goal of this paper is to write in terms of reported values the standard theoretical equation describing the Earth’s wobble, namely, the linearized conservation of angular momentum equation known as the Liouville equation. In terms of the location m(t) =rn,(t)+irn2(t) of the rotation pole, the Liouville equation is usually written as
STATIONARY MEASURES FOR BRANCHING PROCESSES

Conversely, if a solution ir(s) of (4) admits a power-series expansion (2) with non-negative coefficients, then the 7rj form a stationary measure. Harris has conjectured that the stationary measure for any Galton-Watson process is unique up to a constant multiplicative factor, or, equivalently, that there is exactly one stationary measure satisfying (3). The purpose of this note is to provide a counterexample to this conjecture. Let w be any entire function, not identically zero, which has period 1, and satisfies co(0) = 0. It follows from a well-known property of the equation (4) first noticed by Abel (cf. [1, ? 11.4]) that, if {ir1} is a
Gibbon: An Efficient Co-Exploration Framework of NN Model and Processing-In-Memory Architecture

The memristor-based processing-in-memory (PIM) architectures have been proven to be a potential architecture to store enormous parameters and execute the complicated computations of deep neural networks (DNNs) efficiently. Existing PIM studies focus on designing high energy-efficient hardware architecture and algorithm-hardware co-optimization for better performance. However, the impacts of the algorithms and hardware architectures on the performance intersect with each other. Only optimizing the algorithms or the hardware architectures cannot realize the optimal design. Therefore, the co-exploration of NN models and PIM architecture is necessary. However, for one thing, the co-exploration space size of NN models and PIM architectures is extremely huge, and is challenging to search. For another, during the co-exploration process, time-consuming PIM simulators are needed to evaluate various design candidates and pose a heavy time burden. To tackle these problems, we propose an efficient co-exploration framework of NN models and PIM architectures, named Gibbon. In Gibbon, the co-exploration space is carefully designed to adapt both NN models and PIM architectures. Besides, in order to improve search efficiency, we propose an evolutionary search algorithm with adaptive parameter priority (ESAPP). In addition, Gibbon introduces a multilevel joint simulator to alleviate the problem of time-consuming evaluation. The experimental results show that the proposed co-exploration framework can find better NN models and PIM architectures than existing studies in only six GPU hours (<inline-formula> <tex-math notation="LaTeX">$9.8\times $ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$48.2\times $ </tex-math></inline-formula> speed-up). At the same time, Gibbon can improve the accuracy of co-design results by 15.3% and reduce the energy–delay-product (EDP) by <inline-formula> <tex-math notation="LaTeX">$5.96\times $ </tex-math></inline-formula> compared with existing work.
PDDD-PreTrain: A Series of Commonly Used Pre-Trained Models Support Image-Based Plant Disease Diagnosis

Plant diseases threaten global food security by reducing crop yield; thus, diagnosing plant diseases is critical to agricultural production. Artificial intelligence technologies gradually replace traditional plant disease diagnosis methods due to their time-consuming, costly, inefficient, and subjective disadvantages. As a mainstream AI method, deep learning has substantially improved plant disease detection and diagnosis for precision agriculture. In the meantime, most of the existing plant disease diagnosis methods usually adopt a pre-trained deep learning model to support diagnosing diseased leaves. However, the commonly used pre-trained models are from the computer vision dataset, not the botany dataset, which barely provides the pre-trained models sufficient domain knowledge about plant disease. Furthermore, this pre-trained way makes the final diagnosis model more difficult to distinguish between different plant diseases and lowers the diagnostic precision. To address this issue, we propose a series of commonly used pre-trained models based on plant disease images to promote the performance of disease diagnosis. In addition, we have experimented with the plant disease pre-trained model on plant disease diagnosis tasks such as plant disease identification, plant disease detection, plant disease segmentation, and other subtasks. The extended experiments prove that the plant disease pre-trained model can achieve higher accuracy than the existing pre-trained model with less training time, thereby supporting the better diagnosis of plant diseases. In addition, our pre-trained models will be open-sourced at https://pd.samlab. cn/ and Zenodo platform https://doi.org/10.5281/zenodo.7856293.
A tight stability version of the Complete Intersection Theorem

A set family F is said to be t-intersecting if any two sets in F share at least t elements. The Complete Intersection Theorem of Ahlswede and Khachatrian (1997) determines the maximal size f(n,k,t) of a t-intersecting family of k-element subsets of {1,2,. ,n}, and gives a full characterisation of the extremal families. In this paper, we prove the following `stability version' of the theorem: if k/n is bounded away from 0 and 1/2, and F is a t-intersecting family of k-element subsets of {1,2,. ,n} such that $|F| \geq f(n,k,t) - O \binom{n-d}{k}$, then there exists an extremal family G such that $|F \setminus G| = O \binom{n-d}{k-d}$. For fixed t, this assertion is tight up to a constant factor. This proves a conjecture of Friedgut from 2008. Our proof combines classical shifting arguments with a `bootstrapping' method based upon an isoperimetric argument.
Development and Application of nanoPCR Method for Detection of Feline Panleukopenia Virus

Simple Summary Feline panleukopenia is a severe infectious disease caused by the feline panleukopenia virus. It has caused great obstacles to the breeding of pet cats and the protection of rare feline animals such as lions and tigers. There is currently no effective therapy for FPV infection. The virus is extensively dispersed in the environment, and infected animals expel the virus in their feces, allowing the virus to spread; young kittens are especially vulnerable. Infection in kittens frequently is acute, and some cats may die unexpectedly without any signs, posing a significant challenge to early clinical identification. Some of the existing detection methods, such as qPCR, immunohistochemical analysis, colloidal gold test strips, etc., are time-consuming, laborious, costly, and difficult to operate, which is not conducive to popularization. Although colloidal gold test strips are fast and convenient, they have low sensitivity. A nanoPCR reaction was successfully created in this work by adding gold nanoparticles to the traditional PCR reaction system, and was capable of detecting FPV infection in the clinical situation. Abstract Feline panleukopenia (FP) is a severe viral illness caused by the feline panleukopenia virus (FPV), putting sectors like companion cat breeding and endangered feline conservation at risk. The virus has a high morbidity and fatality rate and is found all over the world. We created a novel FPV assay using nanoPCR technology and assessed the method’s specificity and sensitivity. The approach amplified a 345 bp nucleic acid fragment with a minimum detection limit of 7.97 × 102 copies/μL, which is about 100 times greater than traditional PCR. We collected anal swabs from 83 cats suspected of FPV infection for practical application, and the FPV-positive rate determined by the nanoPCR approach was 77.1%. In conclusion, the approach is more sensitive than conventional PCR and more convenient and cost-effective than qPCR methodology and may be utilized for the clinical detection of FPV.
Low regularity local well-posedness for the higher-dimensional Yang-Mills equation in Lorenz gauge

We prove that the Yang-Mills equation in Lorenz gauge in the (n+1)-dimensional case, $n \ge 4$, is locally well-posed for data of the gauge potential in $H^s$ and the curvature in $H^r$ , where $s >\frac{n}{2}-\frac{7}{8}$ , $r > \frac{n}{2}-\frac{7}{4}$ , respectively. The proof is based on the fundamental results of Klainerman-Selberg \cite{KS} and on the null structure of most of the nonlinear terms detected by Selberg-Tesfahun \cite{ST} and Tesfahun \cite{Te}.
Sustainable Fishery Systems

Series Foreword. Preface and Acknowledgements. Introduction. Part I: The Fishery System: Structure and Dynamics. 1 Fishery Systems. 2 The Natural System. 3 The Human System. 4 The Management System: Policy and Planning. 5 Fishery Management. 6 Fishery Development. 7 Fishery Research. 8 Dynamics of the Fishery System. 9 Case Studies of Fishery Systems. Part II: Toward Sustainable Fishery Systems. 10 Sustainability in Fishery Systems. 11 Uncertainty and the Precautionary Approach. 12 Complexity, Diversity and the Ecosystem Approach. 13 Fishery Conflicts and the Co-management Approach. 14 Rights in Fishery Systems. 15 Resilient Fishery Systems and Robust Management. Appendix: Integrated Biosocioeconomic Analysis of Fishery Systems. References. Index.
Investigation on the use of NCEP/NCAR, MERRA and NCEP/CFSR reanalysis data in wind resource analysis

This study aims to investigate the use of different reanalysis datasets in energy production estimates. Wind data from three distinct datasets are analyzed for the territory of Sweden. These are the NCEP/NCAR, the MERRA and the NCEP/CFSR reanalysis datasets. NCEP/NCAR has been commonly used in wind resource analysis during the last decade, while MERRA and NCEP/CFSR were recently released. The higher spatial and temporal resolutions of MERRA and NCEP/CFSR reanalysis data allow a better representation of the local wind climate. An average improvement of 16% in correlation coefficient with local wind measurements is obtained for MERRA and 15% for NCEP/CFSR when compared to NCEP/NCAR. Although the three reanalysis datasets appear to be fairly consistent in space, the temporal consistency of some grid data is rather poor. Wind speed data from some NCEP/NCAR and NCEP/CFSR grid points show strong upward long-term trends for the period of 1980-2009. MERRA wind speed data present a high temporal consistency shown by the typically weak downward long-term trends. A case study is presented where the use of inconsistent reanalysis wind data is shown to infer an error of 14% in the energy production estimate, which is highly significant. The use of MERRA and NCEP/CFSR reanalysis wind data represents a relevant improvement in accuracy for energy production estimates. However, the choice of the most appropriate grid data and the evaluation of the associated uncertainty should be carefully analyzed for each specific case.
Airborne measurements of HCl from the marine boundary layer to the lower stratosphere over the North Pacific Ocean during

S. Kim, L. G. Huey, R. E. Stickel, R. B. Pierce, G. Chen, M. A. Avery, J. E. Dibb, G. S. Diskin, G. W. Sachse, C. S. McNaughton, A. D. Clarke, B. E. Anderson, and D. R. Blake School of Earth and Atmospheric Sciences, Georgia Institute of Technology, USA NASA Langley Research Center, USA Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, USA Department of Oceanography, University of Hawaii, USA Department of Chemistry, University of California, Irvine, USA now at: Advanced Study Program, NCAR, Boulder CO, USA now at: NOAA/NESDIS Advanced Satellite Products Branch, Madison Wiv now at: National Institute of Aerospace, Hampton VA, USA
Soil evaporative fluxes for geotechnical engineering problems

Predicting the flow of water between the soil surface and the atmosphere is a critical issue which geotechnical engineers must resolve for many practical problems. The analysis of saturated-unsaturated groundwater flow problems requires the specification of the flux of water at the upper soil boundary. The flow of moisture at the ground surface is also important for many problems in soil mechanics. These include the analysis of volume change in expansive soils and the stability of slopes. The transfer of water across the soil-atmosphere surface occurs as infiltration and evaporation. The mechanics of infiltration into the soil surface is well understood and has been widely addressed in the literature. Alternately, the process of evaporation from the soil surface is poorly understood. Extreme difficulties frequently arise while predicting evaporation from unsaturated soil surfaces. Empirical methods of estimating evaporation from unsaturated soil surfaces can be found in the literature: however, the suitability and accuracy of these methods can be questioned. A theoretical approach for evaluating the rate of evaporation from an unsaturated soil surface is developed. The theory is based on the principles of Darcy's Law and Fick's Law to describe the flow of liquid water and water vapour in the saturated-unsaturated soil below the surface. Dalton's Law and a modified form of Penman's Method for evaporation are utilized to predict evaporation from the soil surface. Drying tests were conducted using three distinct soil types of sand, silt and clay. The soil surfaces were found to evaporate at the same rate as free water surfaces when saturated. The rate of evaporation begins to decline once the soil surfaces become unsaturated and total suction exceed approximately 3000 kPa. The rate of evaporation is proportional to total suction and continues to decline as suction increases. This principle appears independent of soil type and universal for the three texturally distinct soils selected for testing. The rate of evaporation may be predicted on the basis of the water content of the soil and its moisture retention curve established using routine test procedures. The proposed theory was used to simulate the results of a 42 day evaporation test for a column of fine, uniform, clean sand. Good agreement was generally found between the computed and measured values of evaporation rate, soil water content and soil temperature. Additional analyses were conducted using various values of the saturated coefficient of permeability and the pore-size distribution index. The computed evaporative fluxes were found to be very sensitive to the permeability of the soil. Varying the coefficient of molecular diffusion for water vapour was also found to influence the rate of evaporation. The modified Penman expression was applied to an example evaporation problem for Saskatoon, Saskatchewan during a 10 day period in July. The evaporative fluxes were computed with the watertable positioned at several depths below the…
Surviving chronic physical illness: psychosocial outcome in adult life

Recent advances in physical treatments have changed the implications of receiving a diagnosis of chronic physical illness in childhood. Individuals with disorders such as diabetes, cystic fibrosis, renal failure, and cancer, who may previously have had a limited life expectancy are now surviving into adulthood. During childhood, chronic physical illness confers an increased risk of emotional and behavioural disorders,1 although the majority of children and families successfully adapt to the diagnosis. The increased likelihood of psychiatric disorder during childhood does not seem to be specific to the diagnostic category beyond those involving brain dysfunction,2 3 but reflects the difficulties inherent in living with a chronic illness. Children at greater risk are those with more severe physical disorder,4 and perhaps those with illnesses carrying a greater degree of life threat.5 The risk also varies with the stage of the illness. Adjustment disorders (emotional and/or behavioural symptoms clearly linked in onset to a stressful event and time limited in manifestation) are probably the most frequent psychiatric sequelae and are particularly common at the time of initial diagnosis and after changes in treatment have occurred. For example, psychological problems were reported in almost 60% of children at the time of starting dialysis. One year later, after stabilisation of their physical condition, the prevalence of disturbance was reduced to 21%. 6 Similarly, 36% of 8–13 year olds with newly diagnosed insulin dependent diabetes mellitus developed an adjustment disorder (most commonly dominated by depressive symptoms) within the first three months of diagnosis; 50% had recovered within two months.7 While interest is frequently focused on the physical outcome of this group of children as they progress through adolescence into adult life, much less attention has been given to psychosocial outcome. How are they functioning emotionally and socially after their discharge from …