A Noise-Tolerant Zeroing Neural Network for Time-Dependent Complex Matrix Inversion Under Various Kinds of Noises

Complex-valued time-dependent matrix inversion (TDMI) is extensively exploited in practical industrial and engineering fields. Many current neural models are presented to find the inverse of a matrix in an ideal noise-free environment. However, the outer interferences are normally believed to be ubiquitous and avoidable in practice. If these neural models are applied to complex-valued TDMI in a noise environment, they need to take a lot of precious time to deal with outer noise disturbances in advance. Thus, a noise-suppression model is urgent to be proposed to address this problem. In this article, a complex-valued noise-tolerant zeroing neural network (CVNTZNN) on the basis of an integral-type design formula is established and investigated for finding complex-valued TDMI under a wide variety of noises. Furthermore, both convergence and robustness of the CVNTZNN model are carefully analyzed and rigorously proved. For comparison and verification purposes, the existing zeroing neural network (ZNN) and gradient neural network (GNN) have been presented to address the same problem under the same conditions. Numerical simulation consequences demonstrate the effectiveness and excellence of the proposed CVNTZNN model for complex-valued TDMI under various kinds of noises, by comparing the existing ZNN and GNN models

Multiple Events of Allopolyploidy in the Evolution of the Racemose Lineages in Prunus (Rosaceae) Based on Integrated Evidence from Nuclear and Plastid Data.

Prunus is an economically important genus well-known for cherries, plums, almonds, and peaches. The genus can be divided into three major groups based on inflorescence structure and ploidy levels: (1) the diploid solitary-flower group (subg. Prunus, Amygdalus and Emplectocladus); (2) the diploid corymbose group (subg. Cerasus); and (3) the polyploid racemose group (subg. Padus, subg. Laurocerasus, and the Maddenia group). The plastid phylogeny suggests three major clades within Prunus: Prunus-Amygdalus-Emplectocladus, Cerasus, and Laurocerasus-Padus-Maddenia, while nuclear ITS trees resolve Laurocerasus-Padus-Maddenia as a paraphyletic group. In this study, we employed sequences of the nuclear loci At103, ITS and s6pdh to explore the origins and evolution of the racemose group. Two copies of the At103 gene were identified in Prunus. One copy is found in Prunus species with solitary and corymbose inflorescences as well as those with racemose inflorescences, while the second copy (II) is present only in taxa with racemose inflorescences. The copy I sequences suggest that all racemose species form a paraphyletic group composed of four clades, each of which is definable by morphology and geography. The tree from the combined At103 and ITS sequences and the tree based on the single gene s6pdh had similar general topologies to the tree based on the copy I sequences of At103, with the combined At103-ITS tree showing stronger support in most clades. The nuclear At103, ITS and s6pdh data in conjunction with the plastid data are consistent with the hypothesis that multiple independent allopolyploidy events contributed to the origins of the racemose group. A widespread species or lineage may have served as the maternal parent for multiple hybridizations involving several paternal lineages. This hypothesis of the complex evolutionary history of the racemose group in Prunus reflects a major step forward in our understanding of diversification of the genus and has important implications for the interpretation of its phylogeny, evolution, and classification

Estimation of monthly pan evaporation using support vector machine in Three Gorges Reservoir Area, China

Pan evaporation plays a critical role in estimating water budget and modeling crop water requirements. However, it has been measured at a very limited number of meteorological stations. Estimation of pan evaporation from measured meteorological variables offers an important alternative and drawn increasing attention in the recent years. This paper investigated the performance of support vector machine (SVM) in the estimation of monthly pan evaporation using commonly measured meteorological variables in Three Gorges Reservoir Area in China. Evaluation suggested that SVM models showed remarkable performances and significantly outperformed the empirical model. The SVM model with polynomial as kernel function outperformed that with radial basis function. In the case of unavailable measurements of pan evaporation and meteorological variables to construct the SVM model, pan evaporation can be well-estimated by SVM model developed using data at other sites. The results indicated that the SVM method would be a promising alternative over the traditional approaches for estimating pan evaporation from measured meteorological variables

The Effects of Five-Order Nonlinear on the Dynamics of Dark Solitons in Optical Fiber

We study the influence of five-order nonlinear on the dynamic of dark soliton. Starting from the cubic-quintic nonlinear Schrodinger equation with the quadratic phase chirp term, by using a similarity transformation technique, we give the exact solution of dark soliton and calculate the precise expressions of dark soliton's width, amplitude, wave central position, and wave velocity which can describe the dynamic behavior of soliton's evolution. From two different kinds of quadratic phase chirps, we mainly analyze the effect on dark soliton’s dynamics which different fiver-order nonlinear term generates. The results show the following two points with quintic nonlinearities coefficient increasing: (1) if the coefficients of the quadratic phase chirp term relate to the propagation distance, the solitary wave displays a periodic change and the soliton’s width increases, while its amplitude and wave velocity reduce. (2) If the coefficients of the quadratic phase chirp term do not depend on propagation distance, the wave function only emerges in a fixed area. The soliton’s width increases, while its amplitude and the wave velocity reduce

Coupling meteorological variables with Moderate Resolution Imaging Spectroradiometer atmospheric products for estimating global solar radiation

Global solar radiation is a crucial variable for scientific researches and solar energy application, while it is measured at very few sites mainly due to the technical and fiscal obstacles. Developing robust and accurate models for estimating global solar radiation had been being a focus for many studies. This study was conducted to develop integrated models combining Moderate Resolution Imaging Spectroradiometer atmospheric products and meteorological variables. 43 empirical models based on the meteorological variables were collected. A total of 645 integrated models incorporating atmospheric constituents into the empirical models were developed. The researched models were evaluated and compared at Chongqing in Three Gorges Reservoir Area, China. The results showed that the integrated models outperformed the empirical models. The best integrated model had the root mean square error of 0.817 MJ m−2 and relative root mean square error of 8.11%. On average, the integrated models had the root mean square error of 1.071 MJ m−2, 15.6% smaller than the empirical models. The results suggest that coupling Moderate Resolution Imaging Spectroradiometer atmospheric products with meteorological variables can enhance the performance of the conventional empirical models, which may provide a promising alternative to generate global solar radiation data with better accuracy

Transcriptome sequencing and phylogenomic resolution within Spalacidae (Rodentia)

BACKGROUND: Subterranean mammals have been of great interest for evolutionary biologists because of their highly specialized traits for the life underground. Owing to the convergence of morphological traits and the incongruence of molecular evidence, the phylogenetic relationships among three subfamilies Myospalacinae (zokors), Spalacinae (blind mole rats) and Rhizomyinae (bamboo rats) within the family Spalacidae remain unresolved. Here, we performed de novo transcriptome sequencing of four RNA-seq libraries prepared from brain and liver tissues of a plateau zokor (Eospalax baileyi) and a hoary bamboo rat (Rhizomys pruinosus), and analyzed the transcriptome sequences alongside a published transcriptome of the Middle East blind mole rat (Spalax galili). We characterize the transcriptome assemblies of the two spalacids, and recover the phylogeny of the three subfamilies using a phylogenomic approach. RESULTS: Approximately 50.3 million clean reads from the zokor and 140.8 million clean reads from the bamboo ratwere generated by Illumina paired-end RNA-seq technology. All clean reads were assembled into 138,872 (the zokor) and 157,167 (the bamboo rat) unigenes, which were annotated by the public databases: the Swiss-prot, Trembl, NCBI non-redundant protein (NR), NCBI nucleotide sequence (NT), Gene Ontology (GO), Cluster of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genomes (KEGG). A total of 5,116 nuclear orthologous genes were identified in the three spalacids and mouse, which was used as an outgroup. Phylogenetic analysis revealed a sister group relationship between the zokor and the bamboo rat, which is supported by the majority of gene trees inferred from individual orthologous genes, suggesting subfamily Myospalacinae is more closely related to subfamily Rhizomyinae. The same topology was recovered from concatenated sequences of 5,116 nuclear genes, fourfold degenerate sites of the 5,116 nuclear genes and concatenated sequences of 13 protein coding mitochondrial genes. CONCLUSIONS: This is the first report of transcriptome sequencing in zokors and bamboo rats, representing a valuable resource for future studies of comparative genomics in subterranean mammals. Phylogenomic analysis provides a conclusive resolution of interrelationships of the three subfamilies within the family Spalacidae, and highlights the power of phylogenomic approach to dissect the evolutionary history of rapid radiations in the tree of life

Can Overconfidence be Debiased by Low-Probability/High-Consequence Events?

During the first half of 2008, China suffered three natural disasters: a heavy snow storm, an outbreak of hand-foot-mouth disease, and a severe earthquake. The aim of the present study is to explore how low-probability/high-consequence events influence overconfidence. In Study 1, opportunity samples were obtained by recruiting residents in three different types of disaster-hit areas to answer a peer-comparison probability judgment questionnaire about 1 month after the corresponding disaster occurred. The performance of 539 participants in disaster-hit areas was compared with that of 142 residents in a nondisaster area. The findings indicate that residents in disaster-hit areas were less overconfident than those in the nondisaster area on both positive and negative events. In Study 2, we surveyed a total of 336 quake-victims 4 and 11 months after the earthquake to examine whether the impact of disasters on overconfidence would decay with time. The resulting data indicate that the disaster victims became more overconfident as time elapsed. The overall findings suggest that low-probability/high-consequence events could make people less overconfident and more rational and seem to serve as a function of debiasing.</p

Rhodiola rosea L. Improves Learning and Memory Function: Preclinical Evidence and Possible Mechanisms

Rhodiola rosea L. (R. rosea L.) is widely used to stimulate the nervous system, extenuate anxiety, enhance work performance, relieve fatigue, and prevent high altitude sickness. Previous studies reported that R. rosea L. improves learning and memory function in animal models. Here, we conducted a systematic review and meta-analysis for preclinical studies to assess the current evidence for R. rosea L. effect on learning and memory function. Ultimately, 36 studies involving 836 animals were identified by searching 6 databases from inception to May 2018. The primary outcome measures included the escape latency in Morris water maze (MWM) test on behalf of learning ability, the frequency and the length of time spent on the target quadrant in MWM test representing memory function, and the number of errors in step down test, dark avoidance test and Y maze test on behalf of memory function. The secondary outcome measures were mechanisms of R. rosea L. for learning and/or memory function. Compared with control, the pooled results of 28 studies showed significant effects of R. rosea L. for reducing the escape latency (P &lt; 0.05); 23 studies for increasing the frequency and the length of time spent on the target quadrant (P &lt; 0.05); and 6 studies for decreasing the number of errors (P &lt; 0.01). The possible mechanisms of R. rosea L. are largely through antioxidant, cholinergic regulation, anti-apoptosis activities, anti-inflammatory, improving coronary blood flow, and cerebral metabolism. In conclusion, the findings suggested that R. rosea L. can improve learning and memory function