Miracle-dz/UniFAR-FTUs huggingface dataset:
Insight into the Economic Effects of a Severe Korean PRRSV1 Outbreak in a Farrow-to-Nursery Farm

Simple Summary The impairment of reproductive and growth performance of pigs by disease is directly connected to the economic loss of a farm. Porcine Reproductive and Respiratory Syndrome (PRRS) is one of the diseases with the highest economic impact prevailing globally. However, the impact of PRRS outbreaks on swine production in South Korea has been rarely reported. By monitoring before and after a PRRS outbreak in a PRRS-negative farm with mass vaccination in sows and gilts, we found that a potential vaccine failure caused by PRRSV infection in this farm caused severe losses in both the farrowing period and growing period, which is similar to or exceeds reports from other countries. As a result, the pig farm in this study suffered extensive production and economic losses due to PRRSV infection, and further studies are needed to estimate the total cost of economic losses due to PRRS outbreaks in the South Korean swine industry. Abstract Porcine reproductive and respiratory syndrome (PRRS) is a disease that has inflicted economic losses in the swine industry. The causative agent, porcine reproductive and respiratory syndrome virus (PRRSV), is known to have a high genetic diversity which leads to heterogeneous pathogenicity. To date, the impact of PRRS outbreaks on swine production and the economy of the swine industry in South Korea has been rarely reported. In this study, we compare the reproductive performance in the breeding-farrowing phase and growth performance in the nursery phase, in two 27-week periods, one before and one after a PRRSV1 outbreak on a 650-sow farrow-to-nursery farm caused by a Korean PRRSV1 isolate which was genetically distinct from vaccine strains or other global strains. The reproductive performance of sows and the growth performance of nursery pigs were compared using row data consisting of 1907 mating records, 1648 farrowing records, and 17,129 weaning records from 32 breeding batches. The following variables were significantly different between the pre-PRRS outbreak period and the post-PRRS outbreak period: the farrowing rate (−7.1%, p < 0.0001), the abortion rate (+3.9%, p < 0.0001), the return rate (+2.9%, p = 0.0250), weaning to estrus interval days (+1.9 days, p < 0.0001), total piglets born (−1.2 pigs/litter, p < 0.0001), piglets born alive (−2.2 pigs/litter, p < 0.0001), weaned piglets (−2.7 pigs/litter, p < 0.0001), pre-weaning mortality (+7.4%, p < 0.0001), weaning weight (−0.9 kg/pig, p = 0.0015), the mortality rate (+2.8%, p < 0.0001), average daily gain (−69.8 g/d, p < 0.0001), and the feed conversion ratio (+0.26, p = 0.0036). Economic losses for a period of 27 weeks after a PRRS outbreak were calculated at KRW 99,378 (USD 82.8) per mated female for the breeding-farrowing phase, KRW 8,968 (USD 7.5) per pig for the nursery growth phase, and KRW 245,174 (USD 204.3) per sow in the post-outbreak period. In conclusion, the farrow-to-nursery farm in our study suffered extensive production and economic losses as a result of a PRRSV1 outbreak.
SOME RELATIONS BETWEEN THE SPECTRA OF SIMPLE AND NON-BACKTRACKING RANDOM WALKS

We establish some relations between the spectra of simple and non-backtracking random walks on non-regular graphs, generalizing some well-known facts for regular graphs. Our two main results are 1) a quantitative relation between the mixing rates of the simple random walk and of the non-backtracking random walk 2) a variant of the " Ihara determinant formula " which expresses the characteristic polynomial of the adjacency matrix, or of the laplacian, as the determinant of a certain non-backtracking random walk with holomorphic weights.
A Robust Fault Detection Method Based on Neighborhood Preserving Embedding

Industrial data are in general corrupted by noises and outliers, which do not meet the application assumptions in neighborhood preserving embedding (NPE). Many existing NPE-like algorithms are not robust, overly consider the local features of the data, and cannot capture the key features of the data. To this end, multilevel NPE (MNPE) is incorporated into the self-paced learning (SPL) framework in this study. Compared with single-projection feature extraction algorithms, MNPE consists of two projections: the nonreduced and reduced dimensionality projections. The nonreduced dimensionality projection can remove the redundant features that are unrelated to the key features of the data. The reduced dimensionality projection can reduce the dimensionality of the data and further extract the features of the data. Moreover, the L21 -norm can enhance the robustness of the proposed algorithm, and the SPL framework can avoid the local optimal solution problem caused by nonconvex optimization. Extensive experiments have been conducted on multiple image classification datasets to demonstrate that the proposed method is more effective than other state-of-the-art methods. The numerical simulation and blast furnace fault detection experiment results further validated the effectiveness of the proposed method.
Learning Stretch-Shrink Latent Representations With Autoencoder and K-Means for Software Defect Prediction

Detecting defective source code to localize and fix bugs is important to reduce software development efforts. Although deep learning models have made a breakthrough in this field, many issues have not been resolved, such as labeled data shortage and the small size of defective elements. Given two similar programs that differ from each other by an operator or statement, one may be clean while the other may be defective. To address these issues, this study proposes a new deep learning model to facilitate the learning of distinguishing features. The model comprises of three main components: 1) a convolutional neural network-based classifier, 2) an autoencoder, and 3) a k-means cluster. In our model, the autoencoder assists the classifier in generating program latent representations. The k-means cluster provides penalty functions to increase the distinguishability among latent representations. We evaluated the effectiveness of the model according to performance metrics and latent representation quality. The experimental results on the four defect prediction datasets show that the proposed model outperforms the baselines thanks to the generation of sophisticated features.
A Novel Method of Clustering Using a Stochastic Approach

The cluster analysis of real-life data often encounters the challenges of noisy data or may rely heavily on the uncertainty of the main clustering variable owing to its stochastic nature, which has a potential influence on its performance. In this paper, we propose a novel clustering technique that is efficient in dealing with noise and uncertainty in a dataset by adopting a stochastic approach that uses realistic values of data points by assuming a continuous probability distribution instead of exact values. By estimating the best-fit probability distribution of the clustering variable, the proposed method formulates the problem of determining the most homogeneous clusters by determining the optimum cluster partitions (OCP) as a mathematical programming problem (MPP). A computer-intensive dynamic programming technique was used to solve the MPP and determine the OCP, which minimized the sum of the weighted intracluster standard deviations. The proposed technique is then demonstrated in this study using univariate data that follows a normal distribution, which is a symmetric distribution, as well as the Weibull distribution, which is a skewed distribution. Numerical examples were also presented to illustrate the computational details of the proposed method. Finally, using both simulated and real datasets, a comparative analysis of the effectiveness of the proposed technique was performed against four advanced clustering methods: k-means, fuzzy c-means, expectation maximization, and Genie++ hierarchical clustering. The results reveal that the proposed method works well and produces more efficient clusters than other methods.
A finite element method for the Monge-Amp\`ere equation with transport boundary conditions

We address the numerical solution via Galerkin type methods of the Monge-Amp\`ere equation with transport boundary conditions arising in optimal mass transport, geometric optics and computational mesh or grid movement techniques. This fully nonlinear elliptic problem admits a linearisation via a Newton-Raphson iteration, which leads to an oblique derivative boundary value problem for elliptic equations in nondivergence form. We discretise these by employing the nonvariational finite element method, which lead to empirically observed optimal convergence rates, provided recovery techinques are used to approximate the gradient and the Hessian of the unknown functions. We provide extensive numerical testing to illustrate the strengths of our approach and the potential applications in optics and mesh movement.
Revised marine reservoir offset (ΔR) values for molluscs and marine mammals from Arctic North America

Appropriate marine–terrestrial reservoir offset (ΔR) values are essential for accurate calibration of marine radiocarbon dates. However, ΔR values are only valid for the specific calibration curve that their calculation is based on. Here, we present revised ΔR values for the Marine20 calibration curve from Arctic North America, based on previously published 14C dates on pre‐bomb live‐collected marine molluscs (n = 124) and cetaceans (beluga whales; tooth dentine; n = 12), and bowhead whale–driftwood age comparisons from the same glacio‐isostatically uplifted shorelines (n = 18). Molluscan‐based ΔR are: Chukchi/Beaufort sea coasts, 265±116 14C years; NW Canadian Arctic Archipelago, 188±91 14C years; NE Baffin Island, 81±18 14C years; SE Baffin Island, 14±58 14C years; Hudson Strait, −73±64 14C years; Ungava Bay, 0±86 14C years; Foxe Basin, 175±89 14C years; Hudson Bay, −21±72 14C years; James Bay, 209±114 14C years; West Greenland, −93±111 14C years. Species‐specific marine mammal ΔR terms are 107±59 14C years for beluga and 24±58 14C years for bowheads. Our revised ΔR values are applicable for as long as the same broad oceanographic conditions (circulation, ventilation) have persisted, i.e. through the Holocene. While molluscan values are applicable to other marine carbonate (e.g. foraminifera), cetacean ΔR are valid only for the species they were calculated for and should not be applied to other marine mammals. Importantly, the ΔR terms calculated here are only valid for Marine20 and should not be used with earlier or later calibration curves.
DESIGN AND SIMULATION OF A MULTI-RECEIVER WIRELESS POWER TRANSFER SYSTEM BASED ON TRANSMITTER CONTROL METHOD

As is usual in a multiple-receiver wireless power transfer (WPT) system based on s-s geometry, the power of load obtained and system efficiency are very sensitive to changes in the number of receivers. An improved multi-receivers WPT system is introduced that ensures the power given for each load remains stable while other receivers enter or exit the system. This study proposes a multiple-load WPT system operated by a class E amplifier. The equivalent system circuit model is analyzed of major parameters such as receiver power, transmitter power, transmission efficiency, and each load power allocation. A control circuit is proposed to obtain high transmission efficiency, power control for the transmitter, and arbitrary power distribution ratios of receivers for different loads. The cross-coupling between the receiver coils is prevented by adding compensating capacitors at the receiver side in series. This further increases the power stability obtained by loads. Finally, in order to verify the feasibility of the proposed process, simulation results are presented.
On point transformations of linear equations of maximal symmetry

An effective method for generating linear equations of maximal symmetry in their much general normal form is obtained. In the said normal form, the coefficients of the equation are differential functions of the coefficient of the term of third highest order. As a result, an explicit expression for the point transformation reducing the equation to its canonical form is obtained, and a simple formula for the expression of the general solution in terms of those of the second-order source equation is recovered. New expressions for the general solution are also obtained, as well as a direct proof of the fact that a linear equation is iterative if and only if it is reducible to the canonical form by a point transformation. New classes of solvable equations parameterized by arbitrary functions are also derived, together with simple algebraic expressions for the corresponding general solution.
Label-Free Micro Probe Optical Fiber Biosensor for Selective and Highly Sensitive Glucose Detection

Blood glucose monitoring is very important for the prevention, control, and treatment of diabetes. However, the application of existing glucose sensors is limited by poor bio-compatibility, complex readout approaches, slow response, and complex fabrication. Most significantly, most sensors cannot meet the necessities of high sensitivity and large range simultaneously. Herein, we proposed a high-selective microprobe glucose optical fiber biosensor based on surface plasmon resonance (SPR), which might not solely bring high-sensitivity detection, but additionally cover the concentration range of human glucose. The experimental results demonstrate that the detection range reaches 0–200 mg/dL, and the maximum glucose concentration sensitivity reaches 0.1688 nm/(mg/dL). The limit of detection (LOD) was calculated to be 4 mg/dL. Furthermore, it is verified that the sensor resists the interference of sodium ions, potassium ions, sucrose, and chitosan. The designed sensor with the advantage of high selectivity, high sensitivity, and large range has great potential for real-time, continuous glucose monitoring in the biological medicine fields.
Numerical analysis of an asymptotic-preserving scheme for anisotropic elliptic equations

The main purpose of the present paper is to study from a numerical analysis point of view some robust methods designed to cope with stiff (highly anisotropic) elliptic problems. The so-called asymptotic-preserving schemes studied in this paper are very efficient in dealing with a wide range of $\varepsilon$-values, where $0 < \varepsilon \ll 1$ is the stiffness parameter, responsible for the high anisotropy of the problem. In particular, these schemes are even able to capture the macroscopic properties of the system, as $\varepsilon$ tends towards zero, while the discretization parameters remain fixed. The objective of this work shall be to prove some $\varepsilon$-independent convergence results for these numerical schemes and put hence some more rigor in the construction of such AP-methods.
1 1 D ec 2 01 7 Elements of contemporary mathematical theory of dynamical chaos . Part 1 . Pseudohyperbolic attractors

The paper deals with topical issues of modern mathematical theory of dynamical chaos and its applications. At present, it is customary to assume that dynamical chaos in finitedimensional smooth systems can exist in three different forms. This is dissipative chaos, the mathematical image of which is a strange attractor; conservative chaos, for which the entire phase space is a large “chaotic sea“ with randomly spaced elliptical islands inside it; and mixed dynamics, characterized by the principal inseparability in the phase space of attractors, repellers and conservative elements of dynamics. In the present paper (which opens a cycle of three our papers), elements of the theory of pseudo-hyperbolic attractors of multidimensional maps are presented. Such attractors, as well as hyperbolic ones, are genuine strange attractors, but they allow the existence of homoclinic tangencies. We give a mathematical definition of a pseudo-hyperbolic attractor for the case of multidimensional maps, from which we derive the necessary conditions for its existence in the three-dimensional case, formulated using the Lyapunov exponents. We also describe some phenomenological scenarios for the appearance of pseudo-hyperbolic attractors of various types in one-parameter families of three-dimensional diffeomorphisms, we propose new methods for studying such attractors (in particular, a method of saddle charts and a modified method of Lyapunov diagrams). We consider also three-dimensional generalized Hénon maps as examples. In the second part, we plan to review the theory of spiral attractors, which compose an important class of attractors often meeting in applications. The third part will be devoted to mixed dynamics – a new type of chaos, which is characteristic, in particular for reversible systems, i.e. systems invariant with respect to the time reversal. It is well known that such systems are met in many problems of mechanics, electrodynamics and other fields of natural science.
A computer-assisted existence proof for Emden's equation on an unbounded L-shaped domain

We prove existence, non-degeneracy, and exponential decay at infinity of a non-trivial solution to Emden's equation $-\Delta u = | u |^3$ on an unbounded $L$-shaped domain, subject to Dirichlet boundary conditions. Besides the direct value of this result, we also regard this solution as a building block for solutions on expanding bounded domains with corners, to be established in future work. Our proof makes heavy use of computer assistance: Starting from a numerical approximate solution, we use a fixed-point argument to prove existence of a near-by exact solution. The eigenvalue bounds established in the course of this proof also imply non-degeneracy of the solution.
The Impacts of Bio-Based and Synthetic Hydrogels on Soil Hydraulic Properties: A Review

Soil hydraulic properties are important for the movement and distribution of water in agricultural soils. The ability of plants to easily extract water from soil can be limited by the texture and structure of the soil, and types of soil amendments applied to the soil. Superabsorbent polymers (hydrogels) have been researched as potential soil amendments that could help improve soil hydraulic properties and make water more available to crops, especially in their critical growing stages. However, a lack of a comprehensive literature review on the impacts of hydrogels on soil hydraulic properties makes it difficult to recommend specific types of hydrogels that positively impact soil hydraulic properties. In addition, findings from previous research suggest contrasting effects of hydrogels on soil hydraulic properties. This review surveys the published literature from 2000 to 2020 and: (i) synthesizes the impacts of bio-based and synthetic hydrogels on soil hydraulic properties (i.e., water retention, soil hydraulic conductivity, soil water infiltration, and evaporation); (ii) critically discusses the link between the source of the bio-based and synthetic hydrogels and their impacts as soil amendments; and (iii) identifies potential research directions. Both synthetic and bio-based hydrogels increased water retention in soil compared to unamended soil with decreasing soil water pressure head. The application of bio-based and synthetic hydrogels both decreased saturated hydraulic conductivity, reduced infiltration, and decreased soil evaporation. Hybrid hydrogels (i.e., a blend of bio-based and synthetic backbone materials) may be needed to prolong the benefit of repeated water absorption in soil for the duration of the crop growing season.
Analytic functions relative to a covariance map $\eta$: I. Generalized Haagerup products and analytic relations

We generalize module weak-* Haagerup tensor products to obtain complete quotients of normal Haagerup tensor product included in canonical Hilbert spaces associated to completely positive normal (covariance) maps $\eta$ on a finite von Neumann algebra $B$. We construct in this way dual operator spaces, providing new examples even in the case of module extended Haagerup tensor products. This is the basis for defining a matrix normed algebra of analytic functions that captures the relations of free semicircular variables with covariance $\eta$. We prove that a class of non-commutative random variables having finite Fisher information relative to $\eta$ have also no analytic relations among our class of analytic functions.
On $L^p$-improving for averages associated to mixed homogeneous polynomial hypersurfaces in $\mathbb{R}^3$

We establish $L^p-L^q$ estimates for averaging operators associated to mixed homogeneous polynomial hypersurfaces in $\mathbb{R}^3$. These are described in terms of the mixed homogeneity and the order of vanishing of the polynomial hypersurface and its Gaussian curvature transversally to their zero sets.
Weak Arithmetic Cobordism

In the early 2000's Levine and Morel have given a geometric construction of an algebraic cobordism group defined for all smooth quasi projective varieties over a field. We show how we can refine their construction to build an Arakelov version of this group for Arakelov varieties over a number field, and how this integrates well in the general philosophy of Arakelov geometry.
Design of Self-Decoupling Dielectric Resonator Antenna With Shared Radiator

The method of mode cancellation to design a two-port dielectric resonator antenna (DRA) for an in-band full-duplex (IBFD) application is investigated in this communication. The whole antenna structure is straightforward, only composed of a single DRA element, a pair of feeding lines, and a pair of metallic probes. Attributing to the features of different modes used in this design, mutual coupling between the exciting port and the passive port can be suppressed to an extremely low level without using an extra decoupling structure. A prototype is fabricated and measured for verification. The measured results demonstrate that the proposed antenna has broad bandwidth and high isolation level can be achieved throughout the whole working band.
Research on Simulation System for Human-SRL Collaborative Motion Planning

At present, there is a problem of visual area switching in the existing SRL (supernumerary robotic limb) operation methods. In response to this problem, the authors’ previous work proposed a new SRL operation method called relatively independent operation, and proposed a corresponding software architecture. The purpose of this paper is to solve the theoretical problems and engineering realization problems of the human-SRL skeleton algorithm module in the software architecture. Therefore, modeling, data collection, data processing, and visualization of a human-SRL system are studied in this paper. Firstly, a human-SRL skeleton visualization simulation system is developed. The condition setting, the applications, and the core algorithm of the simulation system are introduced. The core algorithm mainly contains four types of important functions, namely skeleton model building functions, human-SRL data collection functions, human-SRL data processing functions, and skeleton visualization functions. Secondly, the implementation principles of these four functions are described: (1) For the skeleton model building functions, a human-SRL skeleton model is proposed which is an integration of a human skeleton model and an SRL skeleton model. The construction methods of these three skeleton models are described. (2) For the remaining functions, how to collect and process human data, SRL data, human-SRL data, and how to visualize a human-SRL skeleton are described. Finally, the visualization effect of the developed simulation system on human-SRL skeleton movement is verified by experiments, which proves the correctness of the functions in the simulation system.