Unified Models Research Articles

Calibrated reconstruction based adversarial autoencoder model for novelty detection

Novelty detection detects outliers located at any location, such as abnormalities (i.e., far distance outliers) and novel/unobserved patterns (i.e., close distance outliers). While many novelty detection approaches have been proposed in the literature, they generally focus on detecting one specific type of outlier, e.g., Multi-Class Open Set Recognition (MCOSR) and One-Class Novelty Detection (OCND) approaches are applied for far and close distance outlier detection, respectively. However, in practice, it is difficult to measure in advance whether the distance between outliers and inliers is far or close. Recent work on outlier detection at any location with a unified model has yielded mixed performance. In this paper, we propose a new unified model, named Calibrated Reconstruction Based Adversarial AutoEncoder (CRAAE), for location agnostic outlier detection. The key idea is to integrate implicit and explicit confidence calibration strategies into a reconstruction based model for building a more accurate decision boundary. We leverage the category information disentangled from feature space to calibrate the decision metric (i.e., reconstruction error) constructed in the original data space. CRAAE also adds Uniform or Dirichlet noise into the artificial outlier generation process to represent various outliers. Experimental results show that CRAAE can outperform state-of-the-art unified models (e.g., GPND) and achieve similar performance with OCND and MCOSR methods in close and far distance outlier detection, respectively.

Genome-Wide Association Study on Reproductive Traits Using Imputation-Based Whole-Genome Sequence Data in Yorkshire Pigs.

Reproductive traits have a key impact on production efficiency in the pig industry. It is necessary to identify the genetic structure of potential genes that influence reproductive traits. In this study, a genome-wide association study (GWAS) based on chip and imputed data of five reproductive traits, namely, total number born (TNB), number born alive (NBA), litter birth weight (LBW), gestation length (GL), and number of weaned (NW), was performed in Yorkshire pigs. In total, 272 of 2844 pigs with reproductive records were genotyped using KPS Porcine Breeding SNP Chips, and then chip data were imputed to sequencing data using two online software programs: the Pig Haplotype Reference Panel (PHARP v2) and Swine Imputation Server (SWIM 1.0). After quality control, we performed GWAS based on chip data and the two different imputation databases by using fixed and random model circulating probability unification (FarmCPU) models. We discovered 71 genome-wide significant SNPs and 25 potential candidate genes (e.g., SMAD4, RPS6KA2, CAMK2A, NDST1, and ADCY5). Functional enrichment analysis revealed that these genes are mainly enriched in the calcium signaling pathway, ovarian steroidogenesis, and GnRH signaling pathways. In conclusion, our results help to clarify the genetic basis of porcine reproductive traits and provide molecular markers for genomic selection in pig breeding.

Enhanced Bayesian Factorization With Variant Scale Partitioning for Multivariate Time Series Analysis

Multivariate time series data (Mv-TSD) portray the evolving processes of the system(s) under examination in a “multi-view” manner. Factorization methods are salient for Mv-TSD analysis with the potentials of structural feature construction correlating various data attributes. However, research challenges remain in the derivation of factors due to highly scattered data distribution of Mv-TSD and intensive interferences/outliers embedded in the source data. The proposed Enhanced Bayesian Factorization approach ( <i>Enhanced-BF</i> ) addresses the challenges in three phases: (1) variant scale partitioning applies to Mv-TSD according to degree of amplitude and obtains the blocks of variant scales; (2) hierarchical Bayesian model for tensor factorization automatically derives the factors of each block with interferences suppressed; (3) Bayesian unification model merges those block factors to construct the final structural features. <i>Enhanced-BF</i> has been evaluated using a case study of brain data engineering with multivariate electroencephalogram (EEG). Experimental results indicate that the proposed method manifests robustness to the interferences and outperforms the counterparts in terms of operation efficiency and error when factorizing EEG tensor. Besides, <i>Enhanced-BF</i> excels in factorization-based analysis of ongoing autism spectrum disorder (ASD) EEG: 3 times speed-up in factorization and <inline-formula><tex-math notation="LaTeX">$87.35\%$</tex-math></inline-formula> accuracy in ASD discrimination. The latent factors (“biomarkers”) can distinctly interpret the typical EEG characteristics of ASD subjects.

Weinberg-Salam model as non-Abelian Landau-Ginzburg theory of superconductivity

We propose that the Weinberg-Salem model well known as the standard model of the electroweak unification could also describe the non-Abelian ferromagnetic superconductivity made of two-component (spin-up and spin-down) Cooper pair, which could be viewed as the SU(2)xU(1) extension of the Abelian Landau-Ginzburg theory. In this interpretation the two gauge couplings of SU(2) and U(1) (and thus the Weinberg's mixing angle) are completely fixed by the electromagnetic coupling e. And the massless photon in the standard model plays the role of the massless non-Abelian spinon which induces the long range magnetic order and the spin waves in non-Abelian ferromagnetic superconductors. Moreover, the massive Z boson plays the role of the massive photon which generates the well known Meissner effect in ordinary superconductors, and the W boson becomes the charged massive spinon whose mass determines the range of the non-Abelian spin flip interaction in the ferromagnetic superconductors. We discuss the physical implications of the non-Abelian Landau-Ginzburg theory.

Nutritional Genomic Approach for Improving Grain Protein Content in Wheat.

Grain protein content (GPC) is a key aspect of grain quality, a major determinant of the flour functional properties and grain nutritional value of bread wheat. Exploiting diverse germplasms to identify genes for improving crop performance and grain nutritional quality is needed to enhance food security. Here, we evaluated GPC in a panel of 255 Triticum aestivum L. accessions from 27 countries. GPC determined in seeds from three consecutive crop seasons varied from 8.6 to 16.4% (11.3% on average). Significant natural phenotypic variation in GPC among genotypes and seasons was detected. The population was evaluated for the presence of the trait-linked single nucleotide polymorphism (SNP) markers via a genome-wide association study (GWAS). GWAS analysis conducted with calculated best linear unbiased estimates (BLUEs) of phenotypic data and 90 K SNP array using the fixed and random model circulating probability unification (FarmCPU) model identified seven significant genomic regions harboring GPC-associated markers on chromosomes 1D, 3A, 3B, 3D, 4B and 5A, of which those on 3A and 3B shared associated SNPs with at least one crop season. The verified SNP-GPC associations provide new promising genomic signals on 3A (SNPs: Excalibur_c13709_2568 and wsnp_Ku_c7811_13387117) and 3B (SNP: BS00062734_51) underlying protein improvement in wheat. Based on the linkage disequilibrium for significant SNPs, the most relevant candidate genes within a 4 Mbp-window included genes encoding a subtilisin-like serine protease; amino acid transporters; transcription factors; proteins with post-translational regulatory functions; metabolic proteins involved in the starch, cellulose and fatty acid biosynthesis; protective and structural proteins, and proteins associated with metal ions transport or homeostasis. The availability of molecular markers within or adjacent to the sequences of the detected candidate genes might assist a breeding strategy based on functional markers to improve genetic gains for GPC and nutritional quality in wheat.

Ensemble mapping the inner structure of luminous quasars

ABSTRACT A simple prediction of the well-known unification model of active galactic nuclei is that a sample of sources should exhibit an anticorrelation between the solid angle of the dusty torus and of the ionization cone (as the sum of them shall equal 4π); however, this has never been detected. In this work, we analyse the correlation between the [O iii] 5007 narrow emission line equivalent width and LIR(λ)/Lbol for a large sample of luminous quasars. For the first time, we detect a clear intrinsic anticorrelation between them, which immediately verifies the torus/ionization-cone geometry in luminous quasars. More interestingly, the anticorrelation significantly weakens with increasing wavelength from ∼2 to 12 $\mu$m, and disappears at ∼12 $\mu$m. Simulations show that a cool dust component (in addition to the equatorial torus) with its strength positively correlating with the solid angle of the ionization cone is required to explain the observations. This shows that the polar dust seen in nearby active galaxies also exists in luminous quasars, with its contribution to total dust emission increasing with λ (from ∼2 to 12 $\mu$m) and reaching between 39 per cent and 62 per cent (model dependent) at rest frame 12 $\mu$m. Our findings provide a unique approach to map the otherwise spatially unresolvable inner structure of quasars.

Stochastic user equilibrium based spatial-temporal distribution prediction of electric vehicle charging load

As the number of electric vehicles (EVs) connected to the grid increases, the EV electricity demand rises dramatically, affecting the grid’s planning and operation and deepening the coupling of the power and transportation systems. Therefore, accurate spatial–temporal distribution prediction of EV charging load is vital for both power system and coupled power-transportation system studies. This paper proposes a novel method based on stochastic user equilibrium (SUE) for predicting the accurate spatial–temporal distribution of EV charging load synchronized with traffic states. A prediction framework of EV charging load based on SUE and trip chain is proposed, which can effectively reflect the actual behavior of EVs in synchronous traffic states. Then, the extended logit-based SUE and equivalent mathematical model are proposed to obtain more detailed traffic states with intersection turning flows and delays. Meanwhile, the unified reachability and charging models are established to ensure that the trip chain is reachable and the charging characteristics are suitable for different EV types. Finally, the method of the successive averages (MSA) and the Dijkstra-based K-shortest paths algorithms are integrated to solve the proposed framework iteratively with stable convergence. Test results on a realistic traffic network show that the proposed method can effectively reflect the charging and trip characteristics of different EV types while ensuring reachability. And it can also accurately predict the overall and individual EV travel costs and total charging loads in detailed synchronous traffic states. In particular, even in the case of high EV penetration with higher peak-to-valley differences and charging demand, the convergence of the prediction is still stable with even more remarkable prediction effectiveness, especially during peak load hours. Furthermore, the quantitative analysis based on proposed criticality indexes reveals that traffic network failures will affect the network-wide traffic states and EV charging loads with different node-level impact characteristics, which should be considered in joint power-transportation restoration scheduling.

Unification based on the mysterious cubic-structure grouping of quarks and leptons

We present a unification model based on the well-known but mysterious cubic-structure grouping of quarks and leptons that suggests an underlying symmetry connection deemed explainable by a unified theory. It results in an extension of the Pati-Salam model that consolidates the fermions into two sixteen-dimensional chiral representations of the gauge group. Moreover, the discrete cubic flavor symmetry arbitrarily conjectured in the literature is found here to be implied by the gauge symmetry. Furthermore, the gauge algebra also describes an eleven-dimensional spacetime decomposed into the usual spacetime and the seven-sphere, which is the manifold of unit octonions. This suggests such a spacetime is apt for embracing all elementary particles and their interactions.

Identification of Candidate Genes and Functional Pathways Associated with Body Size Traits in Chinese Holstein Cattle Based on GWAS Analysis.

Body size is one of the most economically important traits of dairy cattle, as it is significantly associated with cow longevity, production, health, fertility, and environmental adaptation. The identification and application of genetic variants using a novel genetic approach, such as genome-wide association studies (GWASs), may give more insights into the genetic architecture of complex traits. The identification of genes, single nucleotide polymorphisms (SNPs), and pathways associated with the body size traits may offer a contribution to genomic selection and long-term planning for selection in dairy cows. In this study, we performed GWAS analysis to identify the genetic markers and genes associated with four body size traits (body height, body depth, chest width, and angularity) in 1000 Chinese Holstein cows. We performed SNPs genotyping in 1000 individuals, based on the GeneSeek Genomic Profiler Bovine 100 K. In total, we identified 11 significant SNPs in association with body size traits at the threshold of Bonferroni correction (5.90 × 10-7) using the fixed and random model circulating probability unification (FarmCPU) model. Several genes within 200 kb distances (upstream or downstream) of the significant SNPs were identified as candidate genes, including MYH15, KHDRBS3, AIP, DCC, SQOR, and UBAP1L. Moreover, genes within 200 kb of the identified SNPs were significantly enriched (p ≤ 0.05) in 25 Gene Ontology terms and five Kyoto Encyclopedia of Genes and Genomes pathways. We anticipate that these results provide a foundation for understanding the genetic architecture of body size traits. They will also contribute to breeding programs and genomic selection work on Chinese Holstein cattle.

Unified Singularity Crossing of a 3-(rR)PS Metamorphic Parallel Mechanism through Dynamic Modeling

Metamorphic parallel mechanisms can change into multiple configurations with different motion types and mobility, which consequently yield different solutions of inverse dynamics when crossing singularity. Thus, a unified solution of inverse dynamics to cross singularity becomes important. This solution relies on the consistency condition, the first indeterminate form, and this paper proposes an additional condition by extending into the second indeterminate form. This paper presents unified dynamic models of a 3-(rR)PS metamorphic parallel mechanism to pass through singularities. The analysis is carried out on all three configurations of the 3-(rR)PS metamorphic parallel mechanism. The dynamic models are established using Lagrange formulation, and three conditions to cross singularities are employed. The first condition is based on the consistency condition where the uncontrollable motion should be reciprocal to the wrench matrix. The denominator of inverse Jacobian is its determinant whose value is zero at singularities. This singularity can be discarded by compensating the numerator to be zero. Both the numerator and denominator are null, and this indeterminate form becomes the second condition. Both conditions are sufficient for inverse dynamics of one configuration to pass through singularity, but not for other configurations. Therefore, the second indeterminate form is proposed to be the third condition to be fulfilled. Consequently, the 11th-degree polynomial is required for path planning. The results are presented and confirmed by ADAMS simulation.

Rural Building Extraction Based on Joint U-Net and the Generalized Chinese Restaurant Franchise from Remote Sensing Images

The extraction of rural buildings from remote sensing images plays a critical role in the development of rural areas. However, automatic building extraction has a challenge because of the diverse types of buildings and complex backgrounds. In this paper, we proposed a two-layer clustering framework named gCRF_U-Net for the extraction of rural buildings. Before the building extraction, the potential built-up areas are firstly detected, which are taken as a constraint for building extraction. Then, the U-Net network is employed to obtain the prior probability of the potential buildings. After this, the calculated probability and the satellite image are put into the generalized Chinese restaurant franchise (gCRF) model to cluster for buildings and non-buildings. In addition, it is worth noting that the hierarchical spatial relationship in the images is clarified for the building extraction. According to the compared experiments on the satellite images and public building datasets, the results show that the proposed method has a better performance, compared with other methods based on the same unified hierarchical models, in terms of quantitative and qualitative evaluation.

Characteristics of Statically Indeterminate Symmetric Flexure Structures

Statically indeterminate symmetric (SIS) flexure structures are symmetric structures with “clamped-clamped” boundary conditions. The static indeterminacy and topological symmetry significantly attenuate the parasitic motions associated with statically determinate flexure structures. Hence, SIS flexure structures feature decoupled linear and angular motions, improved motion accuracy, high stiffness, and high stability. Although SIS flexure structures have been more frequently utilized as prismatic joints, they can also be utilized as revolute joints. This study systematically investigates the characteristics of SIS flexure structures. Based on the unified compliance models of a single flexure hinge, analytical compliance models of two fundamental types of SIS flexure structures are established. In 1-degree-of-freedom or planar applications, multiple SIS-based structures can also be integrated into various configurations to transmit linear or angular motions. Corresponding stiffness models are also established. The characteristics and possible applications of the SIS flexure structures are computationally investigated through case studies. Ultimately, several SIS prototypes are manufactured, and the modeling accuracy of the established stiffness models is experimentally verified.

Reinforcement Learning Inspired by Psychology and Neuroscience

Decision-making is a crucial intelligence shared by animals and humans and it helps them to act in an intricate environment to seek rewards and avoid punishments. Psychologists first became interested in this ability and studied the conditional behavioral problems associated with it, then these studies have further led to the need for unified quantitative explanation models, among which Reinforcement learning is still the most convincing and data-backed model today. The model itself, in turn, facilitates research in neuroscience. In this paper, the researcher first introduces the original framework of reinforcement learning and the potential neural correlates to it. Then the paper reviews new developments in reinforcement learning algorithms that address the limitations of the original model as well as variants further inspired by neuroscience. Finally, the study highlights some new directions for future research. This study focuses on the evolution of reinforcement learning algorithms inspired by neuroscience, shows the relationship of mutual promotion and common development between reinforcement Learning and neuroscience, and clarifies some concerns for future exploration.

Embedding of the Georgi-Glashow SU(5) model in the superconformal algebra

We present a scheme to construct grand unified models based on the superconformal algebra and the inclusion of matter fields in the adjoint representation of supersymmetry. As an illustration, we implemented the Georgi-Glashow SU(5) model. The model predicts the existence of a dark (1,24, 0) + (5,5*, −y′) + (5*,5, y′) sector and an anomalous U(1)Z.

Multi‐state unified calculation model of rail potential and stray current in DC railway systems

AbstractIn order to calculate the dynamic distribution of rail potential and stray current accurately, a multi‐state unified calculation model of rail potential and stray current is proposed, and the characteristics of different protection devices and reflux system in multi‐state DC railway systems are analysed. In the proposed model, the multi‐state characteristics of the traction substation, train, protection devices and reflux system are uniformly simulated by unified node models. The mixed simulation parameters of the catenary and reflux system are unified to lumped parameter networks, and the multi‐node voltage equations are established based on the simulation model. Then, the power flow of DC railway systems is calculated using an iterative solution, and the dynamic distribution of rail potential and stray current are solved by differential equations. The multi‐state unified calculation model is built and the distribution of rail potential and stray current in different conditions are simulated based on the parameters of Wuxi Subway Line 2. In order to verify the multi‐state unified calculation model proposed, field tests and simulations are carried out. Results show that the multi‐state unified calculation model can unify the complex states of DC railway systems and calculate the distribution of rail potential and stray current accurately.

A survey of family unification models with bifundamental matter

Extensions of the Standard Model have been attempted from the bottom up and from the top down, yet there remains a largely unexplored middle ground. In this paper, using the Mathematica package LieART, we exhaustively enumerate embeddings of the Standard Model within the class of theories with bifundamental fermions in product gauge group SU(a)×SU(b)×SU(c) with no more generators than E6, while achieving SM family unification rather than replication. We incorporate simple phenomenological constraints and find 151 unique models, including 9 that have only vector-like particle content beyond-the-Standard Model (BSM) particles, which we conjecture belong to 5 infinite families of such models. We describe the potentially most viable models: namely, the 9 with strictly vector-like BSM content along with the 29 models we found with no more than 30 additional BSM chiral particles. These include models with fractional electric charge color singlets, and hence magnetic monopoles with multiple Dirac charge. This latter collection of models predicts chiral particles with masses near the electroweak scale accessible to current and future collider experiments.

Unified Programming Models for Heterogeneous High-Performance Computers

Unified Programming Models for Heterogeneous High-Performance Computers

T-Splines for Isogeometric Analysis of the Large Deformation of Elastoplastic Kirchhoff–Love Shells

In this paper, we develop a T-spline-based isogeometric method for the large deformation of Kirchhoff–Love shells considering highly nonlinear elastoplastic materials. The adaptive refinement is implemented, and some relatively complex models are considered by utilizing the superiorities of T-splines. A classical finite strain plastic model combining von Mises yield criteria and the principle of maximum plastic dissipation is carefully explored in the derivation of discrete isogeometric formulations under the total Lagrangian framework. The Bézier extraction scheme is embedded into a unified framework converting T-spline or NURBS models into Bézier meshes for isogeometric analysis. An a posteriori error estimator is established and used to guide the local refinement of T-spline models. Both standard T-splines with T-junctions and unstructured T-splines with extraordinary points are investigated in the examples. The obtained results are compared with existing solutions and those of ABAQUS. The numerical results confirm that the adaptive refinement strategy with T-splines could improve the convergence behaviors when compared with the uniform refinement strategy.

Marker-trait association analyses revealed major novel QTLs for grain yield and related traits in durum wheat.

The growing global demand for wheat for food is rising due to the influence of population growth and climate change. The dissection of complex traits by employing a genome-wide association study (GWAS) allows the identification of DNA markers associated with complex traits to improve the productivity of crops. We used GWAS with 10,045 single nucleotide polymorphism (SNP) markers to search for genomic regions associated with grain yield and related traits based on diverse panels of Ethiopian durum wheat. In Ethiopia, multi-environment trials of the genotypes were carried out at five locations. The genotyping was conducted using the 25k Illumina Wheat SNP array to explore population structure, linkage disequilibrium (LD), and marker-trait associations (MTAs). For GWAS, the multi-locus Fixed and Random Model Circulating Probability Unification (FarmCPU) model was applied. Broad-sense heritability estimates were high, ranging from 0.63 (for grain yield) to 0.97 (for thousand-kernel weight). The population structure based on principal component analysis, and model-based cluster analysis revealed two genetically distinct clusters with limited admixtures. The LD among SNPs declined within the range of 2.02-10.04 Mbp with an average of 4.28 Mbp. The GWAS scan based on the mean performance of the genotypes across the environments identified 44 significant MTAs across the chromosomes. Twenty-six of these MTAs are novel, whereas the remaining 18 were previously reported and confirmed in this study. We also identified candidate genes for the novel loci potentially regulating the traits. Hence, this study highlights the significance of the Ethiopian durum wheat gene pool for improving durum wheat globally. Furthermore, a breeding strategy focusing on accumulating favorable alleles at these loci could improve durum wheat production in the East African highlands and elsewhere.

Universal Gas-Liquid Flow Pattern Map and Its Use on Closure Relationship Selection

Mechanistic modelling is a common approach to predict design parameters such as flow pattern, pressure drop, or liquid holdup in gas-liquid flow in pipes. This approach starts with the application of continuity and momentum balance and required supplementary relationships to close the system of the equations. These additional equations are also called closure relationships which are developed with experimental results for given conditions. These relationships evolved with time as researchers acquired experimental data under different conditions. Unfortunately, new closures are developed for the new conditions rather than universal relationships that can cover a wider set of conditions. This situation generates the need for a methodology that allows the inclusion of newly develop closures to increase the accuracy of the unified mechanistic models. This paper starts with a description of all the available two-dimension maps that can facilitate the visualization of the data. This allows the determination of regions where a particular set of closures minimize the discrepancy between calculated and measured parameters. This paper proposes a simplification of a modern solution to provide a simpler way to visualize the regions corresponding to a set of equations. The final proposed solution reveals a substantial reduction of the average discrepancy of the unified mechanistic model by selecting the most appropriate closures.