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The two-sided bimodality property of Alternate Rician Shadowed (ARS) fading channels makes it a suitable fading model for body-centric wireless communication. The ARS fading model consists of two fluctuating specular components in which only one is active at a time. To provide excellent spectral efficiency with higher quality of service, system transmitter employs an adaptive transmission scheme. This paper derives the exact closed-form expressions of the ARS fading channels capacity. Various adaptive transmission schemes such as channel inversion with a fixed-rate, truncated channel inversion with a fixed-rate, and optimal rate adaptation are considered. A comparison of these schemes is also highlighted. Performance expressions such as binary bit error rate for various coherent and non-coherent modulation schemes and the outage probability are also derived. The derived results are plotted and analyzed for varying fading parameters of the ARS channel. Finally, the results of all performance metrics are verified with Monte-Carlo simulation results. [ABSTRACT FROM AUTHOR]

Resistivity inversion plays a significant role in recent geological exploration, which can obtain formation information through logging data. However, resistivity inversion faces various challenges in practice. Conventional inversion approaches are always time-consuming, nonlinear, non-uniqueness, and ill-posed, which can result in an inaccurate and inefficient description of subsurface structure in terms of resistivity estimation and boundary location. In this paper, a robust inversion approach is proposed to improve the efficiency of resistivity inversion. Specifically, inspired by deep neural networks (DNN) remarkable nonlinear mapping ability, the proposed inversion scheme adopts DNN architecture. Besides, the batch normalization algorithm is utilized to solve the problem of gradient disappearing in the training process, as well as the k-fold cross-validation approach is utilized to suppress overfitting. Several groups of experiments are considered to demonstrate the feasibility and efficiency of the proposed inversion scheme. In addition, the robustness of the DNN-based inversion scheme is validated by adding different levels of noise to the synthetic measurements. Experimental results show that the proposed scheme can achieve faster convergence and higher resolution than the conventional inversion approach in the same scenario. It is very significant for geological exploration in layered formations. [ABSTRACT FROM AUTHOR]

Meiotic recombination is a crucial cellular process, being one of the major drivers of evolution and adaptation of species. In plant breeding, crossing is used to introduce genetic variation among individuals and populations. While different approaches to predict recombination rates for different species have been developed, they fail to estimate the outcome of crossings between two specific accessions. This paper builds on the hypothesis that chromosomal recombination correlates positively to a measure of sequence identity. It presents a model that uses sequence identity, combined with other features derived from a genome alignment (including the number of variants, inversions, absent bases, and CentO sequences) to predict local chromosomal recombination in rice. Model performance is validated in an inter-subspecific indica x japonica cross, using 212 recombinant inbred lines. Across chromosomes, an average correlation of about 0.8 between experimental and prediction rates is achieved. The proposed model, a characterization of the variation of the recombination rates along the chromosomes, can enable breeding programs to increase the chances of creating novel allele combinations and, more generally, to introduce new varieties with a collection of desirable traits. It can be part of a modern panel of tools that breeders can use to reduce costs and execution times of crossing experiments. [ABSTRACT FROM AUTHOR]

This document is an obituary for Prof. Wyatt Anderson, who passed away in 2023 at the age of 84. Prof. Anderson was a renowned geneticist and evolutionary biologist who made significant contributions to the field. He had strong connections with Serbian scientists and collaborated with geneticists from the University of Belgrade. Prof. Anderson mentored several Serbian graduates, including Dr. Aleksandar Popadić, who is now a Professor of Genetics at Wayne State University. Throughout his career, Prof. Anderson held leadership roles in various scientific organizations and made important contributions to science education and minority participation in college science curricula. He was also dedicated to the arts and made significant contributions to the UGA Performing Arts Center and the Museum of Arts. Prof. Anderson's research interests included evolutionary genetics, chromosomal polymorphisms of Drosophila species, and science education. His mentor, Prof. Theodosius Dobzhansky, had a significant influence on his career. The document also highlights the historical connection between the genetics departments at the University of Belgrade and the University of Georgia, which can be traced back to Prof. Dobzhansky's mentorship. The author of the document, Dr. Mirjana Milosevic Brockett, shares her personal experiences working with Prof. Anderson and emphasizes his excellence as a mentor and educator. The document concludes with a selection of Prof. Anderson's research papers. [Extracted from the article]

This paper concerns with the time-variant neural computing in a semi-global sense, taking into account initial conditions located within a region with a definitely finite radius. Both the conventional single and double power-rate RNN models are characterized and the closed-form expressions of the settling time functions are presented for given initial conditions, by which the fixed/predefined-time convergence can be assured in the semi-global sense. Despite asymptotic convergence behavior, the conventional linear RNN model is examined for comparison purposes. Modified RNN models adopt the inverse of the bound, according to the fixed-time convergence results, and the prescribed time can be an adjustable parameter. A novel two-phase RNN model with the pre-specified transition state is proposed, which has not only semi-global fixed/predefined-time stability but also a faster convergence rate than that of the conventional models. The proposed models are applied and compared, through numerical simulation, for time-variant matrix inversion, linear equation solving, and repeatable motion planning of a redundant manipulator in the presence of initial errors. [ABSTRACT FROM AUTHOR]

Directed energy deposition (DED) is capable in producing complex or high-value components with good mechanical properties. Despite these potential advantages, the quality and integrity of multi-material DED parts, remains a challenging issue that limits its wide applications. Material porosity in multi-material components is detrimental since it may lead to premature structural failure. This paper proposes a two-stage ultrasonic method to characterise the internal structure to enhance the understanding of the process parameters on material porosity. In this method, the low-frequency model building aims at reconstructing background structure and the high-frequency imaging targets at small defects. The first stage is based on the gradient sampling full-waveform inversion for the estimation of the velocity model, which is then used as the initial model for the reverse time migration for reflectivity. The experimental results show that accurate reconstructions of the interface between two materials and defects in multi-material DED components can be achieved. [ABSTRACT FROM AUTHOR]

Soil organic matter (SOM) is an important source of nutrients required during crop growth and is an important component of cultivated soil. In this paper, we studied the possibility of using deep learning methods to establish a multi-feature model to predict SOM content. Moreover, using Nong'an County of Changchun City as the study area, Sentinel-2A remote sensing images were taken as the data source to construct the dataset by using field sampling and image processing. The LeNet-5 convolutional neural network model was chosen as the deep learning model, which was improved based on the basic model. The evaluation metrics were selected as the root mean square error (RMSE) and the coefficient of determination R2. Through comparison, the R2 of the improved model was found to be higher than that of the linear regression method, Support Vector Machines (SVM) (RMSE = 2.471, R2 = 0.4035), and Random Forest (RF) (RMSE = 2.577, R2 = 0.4913). The result shows that: (1) It is feasible to use the multispectral data extracted from remote sensing images for soil organic matter content inversion based on the deep learning model with a minimum RMSE of 2.979 and with the R2 reaching 0.89. (2) The choice of features has an impact on the prediction of the model to a certain extent. After ranking the importance of features, selecting the appropriate number of features for inversion provides better results than full feature inversion, and the computational speed is improved. [ABSTRACT FROM AUTHOR]

The creep parameters of rockfill materials obtained from engineering analogy method or indoor tests often cannot accurately reflect the long-term deformation of high Concrete-Faced Rockfill Dams (CFRDs). This paper introduces an optimized inversion method based on multi-population genetic algorithm-improved BP neural network and response surface method (MPGA-BPNN RSM). The parameters used for inversion are determined by parameter sensitivity analysis based on the statistical orthogonal test method. MPGA-BPNN RSM, validated by root-mean-square error, mean absolute percentage error, squared correlation coefficient (R2), etc., completely reflects the response between the creep parameters and the settlement calculation values obtained by finite element method (FEM). MPGA optimized the objective function to obtain the optimal creep parameters. The results show that the settlement values of Xujixia CFRD calculated by FEM using the inversion parameters has great consistency with the monitored values both in size and in distribution, suggesting that the model parameters obtained by the introduced creep parameter inversion method are feasible and effective. The introduced method can improve the inversion efficiency and the prediction accuracy in FEM applications. [ABSTRACT FROM AUTHOR]

Despite advanced seismological techniques, automatic source characterization for microseismic earthquakes remains difficult and challenging since current inversion and modelling of high-frequency signals are complex and time consuming. For real-time applications such as induced seismicity monitoring, the application of standard methods is often not fast enough for true complete real-time information on seismic sources. In this paper, we present an alternative approach based on recent advances in deep learning for rapid source-parameter estimation of microseismic earthquakes. The seismic inversion is represented in compact form by two convolutional neural networks, with individual feature extraction, and a fully connected neural network, for feature aggregation, to simultaneously obtain full moment tensor and spatial location of microseismic sources. Specifically, a multibranch neural network algorithm is trained to encapsulate the information about the relationship between seismic waveforms and underlying point-source mechanisms and locations. The learning-based model allows rapid inversion (within a fraction of second) once input data are available. A key advantage of the algorithm is that it can be trained using synthetic seismic data only, so it is directly applicable to scenarios where there are insufficient real data for training. Moreover, we find that the method is robust with respect to perturbations such as observational noise and data incompleteness (missing stations). We apply the new approach on synthesized and example recorded small magnitude (M ≤ 1.6) earthquakes at the Hellisheiði geothermal field in the Hengill area, Iceland. For the examined events, the model achieves excellent performance and shows very good agreement with the inverted solutions determined through standard methodology. In this study, we seek to demonstrate that this approach is viable for microseismicity real-time estimation of source parameters and can be integrated into advanced decision-support tools for controlling induced seismicity. [ABSTRACT FROM AUTHOR]

As an air pollution phenomenon, haze has become one of the focuses of social discussion. Research into the causes and concentration prediction of haze is significant, forming the basis of haze prevention. The inversion of Aerosol Optical Depth (AOD) based on remote sensing satellite imagery can provide a reference for the concentration of major pollutants in a haze, such as PM2.5 concentration and PM10 concentration. This paper used satellite imagery to study haze problems and chose PM2.5, one of the primary haze pollutants, as the research object. First, we used conventional methods to perform the inversion of AOD on remote sensing images, verifying the correlation between AOD and PM2.5. Subsequently, to simplify the parameter complexity of the traditional inversion method, we proposed using the convolutional neural network instead of the traditional inversion method and constructing a haze level prediction model. Compared with traditional aerosol depth inversion, we found that convolutional neural networks can provide a higher correlation between PM2.5 concentration and satellite imagery through a more simplified satellite image processing process. Thus, it offers the possibility of researching and managing haze problems based on neural networks. [ABSTRACT FROM AUTHOR]

Ground-penetrating radar (GPR) crosshole tomography is widely applied to subsurface media images. However, the inadequacies of ray methods may limit the resolution of crosshole radar images, since the ray method is a type of high-frequency approximation. To solve this problem, the full waveform method is introduced for GPR inversion. However, full waveform inversion is computationally expensive. In this paper, we introduce a trained neural network that can be evaluated very quickly to replace a computationally intensive forward model. Additionally, the forward error of the trained neural network can be statistically analyzed. We demonstrate a methodology for a full waveform inversion of crosshole ground-penetrating radar data using the Markov chain Monte Carlo (MCMC) method. An accurate forward model based on Maxwell's equations is replaced by a quickly trained neural network. This method achieves a high computation efficiency, which is four orders of magnitude faster than the accurate forward model. The inversion result of the synthetic waveform data shows a good performance of the trained neural network, which greatly improves the calculation efficiency. [ABSTRACT FROM AUTHOR]

Modified bitumen is a critical material to ensure the durability of asphalt pavements. Traditional polymer-modified bitumen (PMB) has been widely researched and applied in the past two to three decades. Recently, a high-content SBS (Styrene-Butadiene-Styrene) polymer-modified bitumen (HSBSMB) with a higher SBS content of up to 7–9% by weight has started attracting interest from researchers. There are, however, still few specifications or technical guidelines for HSBSMB. To gain a better understanding of HSBSMB, the composition and structure of typical polymer SBS and base bitumen, the micromorphology and micromechanics of HSBSMB, its rheological and aging characteristics, as well as its asphalt mixture and field pavement performance were reviewed comprehensively in this paper. The content covered in this paper is primarily derived from 210 pertinent papers published between 1990 and 2023 in two databases, Web of Science and Google Scholar. It appears from our review that HSBSMB has a stronger internal polymer network than conventional SBSMB and thus exhibits better resistance to rutting, fatigue, and cracking as well as better aging resistance. Furthermore, findings from both laboratory scale and field pavement scale indicate that HSBSMB not only offers higher performance and durability but also leads to reduced pavement structural layer thicknesses in ensuring performance. However, many issues and challenges still remain before HSBSMB will become a viable option for large-scale application in road infrastructure, aspects such as the mechanism of its internal structural changes, the optimization of methods for evaluating its rheological properties, the life cycle assessment of its long-term benefits, as well as the storage stability and workability of HSBSMB. It is hoped that this review will contribute to a better understanding of HSBSMB and promote its application. • The chemical properties of SBS polymer and base bitumen as well as their interactions were comprehensively summarized. • The mechanisms of SBS in bitumen and polymer phase inversion were discussed under different microscopy techniques. • The current standard rheological evaluation methods may need to be improved for high-content SBS polymer-modified bitumen. • High-content SBS polymer-modified bitumen exhibits better resistance to rutting, fatigue, cracking, and aging. [ABSTRACT FROM AUTHOR]

Deep Learning is an effective tool to invert the underground electrical conductivity structure. In this study, we build a new 8-layer residual neural network (ResNet1D-8) for audio magnetotelluric (AMT) data inversion based on the deep learning theory. In terms of the network structure, the degradation of the model with the increase of depth is effectively avoided by adding shortcut connections. Meanwhile, adding a batch normalization layer greatly improves the model training speed and network generalization ability. This study uses the parallel technology to quickly generate millions of samples, which effectively reduces the computational time and provides a large number of high-quality samples for deep learning model training. Compared with the simulated annealing algorithm, the neural network model in this paper has the advantages of high reliability, short inversion time, and strong model generalization ability. Moreover, we add Gaussian noise to the data of testing samples, and inversion results show that the model has good robustness. The inversion test is carried out on the field measured AMT data set collected in the Dachaidan area of Qinghai Province, China. The results show that the ResNet1D-8 residual neural network model established in this paper can effectively invert the underground electrical structure. • A new residual neural network model (ResNet1D-8) for 1-D MT inversion is constructed. • A uniform stochastic model and parallel techniques are used to rapidly generate samples. • The generalizability and robustness of ResNet1D-8 are verified through numerical experiments. [ABSTRACT FROM AUTHOR]

Over a century after the first description of a polymorphism controlled by a supergene, these genetic architectures still puzzle biologists. Supergenes are groups of tightly linked loci facilitating the co-segregation of combinations of alleles underlying alternative, complex adaptive strategies. The suppression of recombination at supergenes is generally caused by polymorphic chromosomal rearrangements, such as inversions. The existence of inversion polymorphisms and supergene raises theoretical and empirical questions. Why do these architectures evolve? How can alternative combinations of alleles be formed? How and why is polymorphism maintained? The purpose of this paper is to provide answers to these questions by reviewing recent advances in the study of Heliconius numata, an Amazonian butterfly displaying a striking diversity of wing color patterns. In a broad context, this review highlightsmechanisms that play an important role in the evolution of new genomic architecture and in the adaptation of species. [ABSTRACT FROM AUTHOR]

In order to obtain high-quality electrical resistivity imaging (ERI) inversion results, this paper proposes a wavelet-based neural network inversion method. In addition, it is applied to 2D electrical resistivity tomography imaging. Firstly, a sample set suitable for wavelet neural network training is designed to optimize neural network parameters and improve the accuracy of electrical resistivity inversion. Secondly, a hybrid multi-layer wavelet neural network is designed, which uses Mexican-hat and Morlet wavelets as activation functions for different hidden layers, to improve the generalization ability and stability of the network. Finally, the superiority of the WNN is verified through two experiments and applied for inversion in field examples. The inversion results of the synthetic and field examples show that the introduced method is superior to other algorithms in terms of prediction accuracy and computational efficiency, which contribute to better inversion results. • In applying resistivity inversion, WNN can describe the outline of the abnormal body, and the inversion time is short. • This paper designs a sample set suitable for wavelet neural network training. • Two cases are used to verify the accuracy and superiority of WNN in resistivity inversion. • WNN is applied to practical engineering, and its accuracy is verified by core drilling sampling. [ABSTRACT FROM AUTHOR]

• A neural network-based inversion method that can be used to streamline the acquisition of polymethyl methacrylate (PMMA) material target plate constitutive model parameters for explosive cutting simulations is presented. • The parameters of target plate material constitutive model are derived by parameter inversion and verified by numerical simulation. • The BP neural network-based parameter inversion method not only accurately simulated the jet penetration depth, impact fracture thickness, and spallation thickness of the PMMA target plate, but also effectively characterized the damage features and notch morphology of the damaged areas. • This method ensuring high accuracy while reducing experimental costs and risks compared to traditional methods. In this paper, a neural network-based inversion method that can be used to streamline the acquisition of polymethyl methacrylate (PMMA) material constitutive model parameters for explosive cutting simulations is presented. This approach mitigates the need for multiple tests, a requirement of traditional methods. Initially, three categories of the damage, penetration depth, impact fracture thickness and spallation damage thickness, were distinguished and quantified by cutting the14 mm PMMA target plate with a 2.5 mm wide linear shaped charge, and the adjustment interval for the constitutive model parameters could be determined by combining the explosive cutting experiment data and the empirical parameters of the Johnson Holmquist Ceramics (JH-2) constitutive model. Subsequently, the numerical simulations of the cutting process of the performed target plate tests were carried out using LS-DYNA, and a dataset of target plate damage incorporating the three types of damage data was amassed. Ultimately, a neural network model correlating the parameters of the PMMA target plate constitutive model with the damage data was developed and trained using the plate damage dataset, and several supplementary experiments as well as finite element numerical simulations involving a 4.2 mm wide linear shaped charge cutting a 19 mm PMMA target plate were conducted. The numerical results displayed minimal variance from the experimental results in terms of fracture characteristics and damage data, suggesting that the inverted JH-2 constitutive model parameters can be effectively applied to PMMA target plate explosive cutting simulations. The parameter inversion method allows for the acquisition of more accurate material constitutive model parameters with fewer experiments and will be beneficial for further theoretical studies and practical applications of target plates in the future. [ABSTRACT FROM AUTHOR]

Background: Recently, Pereira Zanetti, Biller and Meidanis have proposed a new definition of a rearrangement distance between genomes. In this formulation, each genome is represented as a matrix, and the distance d is the rank distance between these matrices. Although defined in terms of matrices, the rank distance is equal to the minimum total weight of a series of weighted operations that leads from one genome to the other, including inversions, translocations, transpositions, and others. The computational complexity of the median-of-three problem according to this distance is currently unknown. The genome matrices are a special kind of permutation matrices, which we study in this paper. In their paper, the authors provide an O n 3 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$O\left (n^{3}\right)$\end{document} algorithm for determining three candidate medians, prove the tight approximation ratio 4 3 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\frac {4}{3}$\end{document} , and provide a sufficient condition for their candidates to be true medians. They also conduct some experiments that suggest that their method is accurate on simulated and real data. Results: In this paper, we extend their results and provide the following: Three invariants characterizing the problem of finding the median of 3 matrices A sufficient condition for uniqueness of medians that can be checked in O(n) A faster, O n 2 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$O\left (n^{2}\right)$\end{document} algorithm for determining the median under this condition A new heuristic algorithm for this problem based on compressed sensing A O n 4 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$O\left (n^{4}\right)$\end{document} algorithm that exactly solves the problem when the inputs are orthogonal matrices, a class that includes both permutations and genomes as special cases. Conclusions: Our work provides the first proof that, with respect to the rank distance, the problem of finding the median of 3 genomes, as well as the median of 3 permutations, is exactly solvable in polynomial time, a result which should be contrasted with its NP-hardness for the DCJ (double cut-and-join) distance and most other families of genome rearrangement operations. This result, backed by our experimental tests, indicates that the rank distance is a viable alternative to the DCJ distance widely used in genome comparisons. [ABSTRACT FROM AUTHOR]

Confronted with severe frost damage to plants, methods, technologies and equipment have been developed and applied during the past century. The paper presents a comprehensive review on the most effective and active technology to protect plants from radiation frost based on air disturbance technology. The working principle of the technology was elaborated with frost protection mechanism, structures and applicability of three types of working patterns: conventional wind machines, selective inverted sink and portable vertical blowing. As an automatic mechanized technology, control strategy, applicable occasion and proper parameters are introduced for each type of working pattern. The operation of the technology and equipment depends on plant critical temperature, prevailing climatic conditions, thermal inversions strength, as well as costs. The frost protection performance and effectiveness of conventional horizontal wind machines, selective inverted sinks and helicopters are discussed and compared from the cost-effectiveness and application aspects, and the feasibility of selective inverted sinks is still controversial. Therefore, conventional wind machines are the best choice for plant frost protection and consequently are widely used in temperate and subtropical areas throughout the world. The frost protection application with helicopters is not easy to use during the frost nights with high cost. The paper also provides researchers with some perspectives on improving air disturbance technology and its equipment, and some practice recommendations for growers. [ABSTRACT FROM AUTHOR]

Currently available genome assemblies for Atlantic cod (Gadus morhua) have been constructed from fish belonging to the Northeast Arctic Cod (NEAC) population; a migratory population feeding in the Barents Sea. These assemblies have been crucial for the development of genetic markers which have been used to study population differentiation and adaptive evolution in Atlantic cod, pinpointing four discrete islands of genomic divergence located on linkage groups 1, 2, 7 and 12. In this paper, we present a high-quality reference genome from a male Atlantic cod representing a southern population inhabiting the Celtic sea. The genome assembly (gadMor_Celtic) was produced from long-read nanopore data and has a combined contig length of 686 Mb with an N50 of 10 Mb. Integrating contigs with genetic linkage mapping information enabled us to construct 23 chromosome sequences which mapped with high confidence to the latest NEAC population assembly (gadMor3) and allowed us to characterize, to an extent not previously reported large chromosomal inversions on linkage groups 1, 2, 7 and 12. In most cases, inversion breakpoints could be located within single nanopore contigs. Our results suggest the presence of inversions in Celtic cod on linkage groups 6, 11 and 21, although these remain to be confirmed. Further, we identified a specific repetitive element that is relatively enriched at predicted centromeric regions. Our gadMor_Celtic assembly provides a resource representing a ‘southern’ cod population which is complementary to the existing ‘northern’ population based genome assemblies and represents the first step towards developing pan-genomic resources for Atlantic cod. [ABSTRACT FROM AUTHOR]

Summary: During meiosis, recombination ensures allelic exchanges through crossovers (COs) between the homologous chromosomes. Advances in our understanding of the rules of COs have come from studies of mutations including structural chromosomal rearrangements that, when heterozygous, are known to impair COs in various organisms. In this work, we investigate the effect of a large heterozygous pericentric inversion on male and female recombination in Arabidopsis. The inversion was discovered in the Atmcc1 mutant background and was characterized through genetic and next‐generation sequencing analysis. Reciprocal backcross populations, each consisting of over 400 individuals, obtained from the mutant and the wild type, both crossed with Landsberg erecta, were analyzed genome‐wide by 143 single‐nucleotide polymorphisms. The negative impact of inversion became evident in terms of CO loss in the rearranged chromosome in both male and female meiosis. No single‐CO event was detected within the inversion, consistent with a post‐meiotic selection operating against unbalanced gametes. Cytological analysis of chiasmata in F1 plants confirmed that COs were reduced in male meiosis in the chromosome with inversion. Crossover suppression on the rearranged chromosome is associated with a significant increase of COs in the other chromosomes, thereby maintaining unchanged the number of COs per cell. The CO pattern observed in our study is consistent with the interchromosomal (IC) effect as first described in Drosophila. In contrast to male meiosis, in female meiosis no IC effect is visible. This may be related to the greater strength of interference that constrains the CO number in excess of the minimum value imposed by CO assurance in Arabidopsis female meiosis. Significance Statement: This work provides further information into the poorly described phenomenon of the interchromosomal (IC) effect in plants. Indeed, the few studies on this phenomenon in maize date back to the 1960s and 1970s and have low resolution, being limited to a few specific regions and genetic markers. In this paper we underscore the significance for plant scientists of the IC effect during meiosis and provide more detailed data and analyses. [ABSTRACT FROM AUTHOR]

This paper aims to elucidate the central role floating rice has played in the formation of water management infrastructure in the Chao Phraya delta in Thailand. Operating in the background of everyday activities, infrastructures often remain overlooked by the actors that rely on them. However at certain moments, such as breakdowns, infrastructures make visible usually hidden connections between humans and non-humans. In recent years, the infrastructural role of floating rice has become a matter of concern for many actors in and around the Chao Phraya delta. This paper examines the particular multispecies relations between water management infrastructure, farmers and rice in the delta. In particular, the paper traces moments of infrastructural inversion that shed light on rice's involutions as part of a multispecies infrastructure. Attention to these involutions, the paper argues, facilitates a reconsideration of infrastructure's relationship with nature. [ABSTRACT FROM PUBLISHER]

Inversions may contribute to ecological adaptation and phenotypic diversity, and with the advent of "second" and "third" generation sequencing technologies, the ability to detect inversion polymorphisms has been enhanced dramatically. A key molecular consequence of an inversion is the suppression of recombination allowing independent accumulation of genetic changes between alleles over time. This may lead to the development of divergent haplotype blocks maintained by balancing selection. Thus, divergent haplotype blocks are often considered as indicating the presence of an inversion. In this paper, we first review the features of a 7.7 Mb inversion causing the Rose‐comb phenotype in chicken, as a model for how inversions evolve and directly affect phenotypes. Second, we compare the genetic basis for alternative mating strategies in ruff and timing of reproduction in Atlantic herring, both associated with divergent haplotype blocks. Alternative male mating strategies in ruff are associated with a 4.5 Mb inversion that occurred about 4 million years ago. In fact, the ruff inversion shares some striking features with the Rose‐comb inversion such as disruption of a gene at one of the inversion breakpoints and generation of a new allele by recombination between the inverted and noninverted alleles. In contrast, inversions do not appear to be a major reason for the fairly large haplotype blocks (range 10–200 kb) associated with ecological adaptation in the herring. Thus, it is important to note that divergent haplotypes may also be maintained by natural selection in the absence of structural variation. [ABSTRACT FROM AUTHOR]

Besansky is also developing moleculartoolswiththegoalofelucidatingpatternsof malaria vector movement, which is fundamental for disease control and population biology. Comparative Genomics Resources for Anopheles In 2003, with encouragement from Harvard University molecular biologist William Gelbart, Besansky began to write a white paper proposing the sequencing of a cluster of eight Anopheles malaria vectors, including multipleAn.gambiaecomplexmembers.Theproposal resulted in the funding of a pilot genome-sequencing project that she led: The National Human Genome ResearchInstitute-sponsoredsequencingofAn.gambiaeM and S, now considered separate species and named Anopheles coluzzii and An. gambiae sensu stricto,respectively. The genome sequencing enabled tracing 100 million years of anopheline vector evolution and helped elucidate Anopheles species complexes. 4 N. J. Besansky et al., Molecular phylogeny of the Anopheles gambiae complex suggests genetic introgression between principal malaria vectors. [Extracted from the article]

Neural networks have recently gained attention in the context of solving inverse problems. Physics-Informed Neural Networks (PINNs) are a prominent methodology for the task of solving both forward and inverse problems. In the paper at hand, full waveform inversion is the inverse problem under consideration. The performance of PINNs is compared against classical adjoint optimization. The comparison focuses on three key aspects: the forward-solver, the representation of the material, and the sensitivity computation for the gradient-based minimization. Starting from PINNs, each of these key aspects is investigated and adapted individually until the classical adjoint optimization emerges. It is shown that it is beneficial to use the neural network only for the discretization of the unknown spatially varying material field. Here the neural network produces reconstructions without oscillatory artifacts as typically encountered in classical full waveform inversion approaches. Due to this finding, a hybrid method is proposed. It exploits both the efficient gradient computation with the continuous adjoint method as well as the neural network ansatz for the unknown material field. This new hybrid method outperforms Physics-Informed Neural Networks and the classical adjoint optimization in two-dimensional and three-dimensional settings. [ABSTRACT FROM AUTHOR]

• A novel ultrasonic guided wave tomography method, incorporating recurrent neural network into full waveform inversion, is proposed. • The wave equation of an acoustic model is solved by a forward model with the cyclic calculation units of an RNN. • The gradient of the objective function can be obtained by automatic differentiation while the parameters of the waveform velocity model are updated by the adaptive momentum estimation algorithm. • The U-Net deep image prior (DIP) is used as the velocity model regularization in each iteration. Corrosion quantitative detection of plate or plate-like structure materials is crucial in industrial Non-Destructive Testing (NDT) for determining their remaining life. For doing that, a novel ultrasonic guided wave tomography method, incorporating recurrent neural network (RNN) into full waveform inversion (FWI) called as RNN-FWI, is proposed in this paper. When the wave equation of an acoustic model is solved by a forward model with the cyclic calculation units of an RNN, it is shown that the inversion of the forward model can be obtained iteratively by minimizing a waveform misfit function of quadratic Wasserstein distance between the modeled and measured data. It is also demonstrated that the gradient of the objective function can be obtained by automatic differentiation while the parameters of the waveform velocity model are updated by the adaptive momentum estimation algorithm (Adam). The U-Net deep image prior (DIP) is used as the velocity model regularization in each iteration. The final thickness maps of the plate or plate-like structure materials shown can be archived by the dispersion characteristics of guided waves. Both the numerical simulation and experimental results show that the proposed RNN-FWI tomography method performs better than the conventional time-domain FWI in terms of convergence rate, initial model requirement, and robustness. [ABSTRACT FROM AUTHOR]

In the present paper, we show, by means of numerical simulations, that electromagnetic field data obtained from the radiation of a return-stroke lightning discharge and measured over a short-duration time-window can be exploited to reconstruct the attenuation function of the lightning channel. To this end, we discretize the current-field equations derived in the first part of this work and then formulate an inversion algorithm whose output is the attenuation function to be computed. Next, as a numerical application, this algorithm is tested under different conditions, i.e., by considering a variety of time windows and underlying models for the attenuation function. As a result, the possibility of obtaining satisfactory reconstructions, even for short-duration time-windows, is highlighted. • A regularized inversion procedure is formulated in the frequency domain to reconstruct the attenuation function of a lightning channel. • The regularization procedure can effectively cope with synthetic data affected by realistic noise levels. • The proposed method represents an advancement towards the inversion of real lightning measurements [ABSTRACT FROM AUTHOR]

Ground-penetrating radar (GPR) is becoming a mainstream tool in planetary exploration, and one of the few in-situ planetary geophysical methods. There are currently three missions (Perseverance, Tianwen-1, Chang'E-4) with GPR-equipped rovers, and two future missions (Chang'E-7, ExoMars) that will include GPR in their scientific payload. The large number of GPR data, combined with the novel setup of the measurements, creates the need for new data processing and interpretation techniques to address the unique challenges of in-situ planetary radar. The current paper proposes an interpretation pipeline that starts with a novel stochastic hyperbola fitting that estimates the probability kernel density of the bulk permittivity at different depths. Subsequently, the bulk permittivity distribution is transformed via a novel probabilistic inversion to a 1-dimensional (1D) permittivity profile. The inverted 1D permittivity profile is then used as an input to a bespoke reverse-time migration (RTM) using the finite-difference time-domain (FDTD) method. RTM using FDTD does not assume a clinical homogeneous half-space; instead, it accounts for the expected layered structure of the investigated medium. Lastly, the migrated radargram is clustered in order to identify subsurface targets and distinguish them from the background medium. Each of the processing steps has never been reported in planetary radar; and together act as a complete processing toolbox tuned for planetary science. The suggested interpretation pipeline is validated numerically in a 1D case study with a complex layered structure and multiple subsurface targets. The proposed processing scheme is then applied to the GPR data from the Chang'E-4 mission at the Von Kármán crater, revealing a previously unseen layered structure and a complex distribution of rocks/boulders. • Novel processing tools for planetary radar. • Detailed images of the Chang'E-4 landing site. [ABSTRACT FROM AUTHOR]

In this paper, based on reciprocal chiral substrate specificity, taking achiral molecules, ethanolamine (EA) and malachite green (MG) as two model targets, biostable L- DNA aptamers and L -RNA aptamers were generated respectively by chiral inversion of existing D -aptamers. In the detection of EA with L -DNA aptamer-based sensors, the feasibility of our strategy was confirmed, while in the detection of MG with L -RNA aptamers, linear calibration curves were obtained in the range from 0.1 to 5 µm with the detection limit of 0.065 µm under optimized experimental conditions. The results demonstrated that the mirror-image L -aptamers have identical recognition capability as D-aptamers. Meanwhile, L -aptamers have superior biostability to resist nuclease digestion, protein binding interference and off-target effects, enabling their applications in complex practical samples, such as lake water and fish tissue extractions. Our work provides a simple, yet universal and efficient way to develop biostable aptamers. [ABSTRACT FROM AUTHOR]

Background: Although many algorithms are now available that aim to characterize different classes of structural variation, discovery of balanced rearrangements such as inversions remains an open problem. This is mainly due to the fact that breakpoints of such events typically lie within segmental duplications or common repeats, which reduces the mappability of short reads. The algorithms developed within the 1000 Genomes Project to identify inversions are limited to relatively short inversions, and there are currently no available algorithms to discover large inversions using high throughput sequencing technologies. Results: Here we propose a novel algorithm, VALOR, to discover large inversions using new sequencing methods that provide long range information such as 10X Genomics linked-read sequencing, pooled clone sequencing, or other similar technologies that we commonly refer to as long range sequencing. We demonstrate the utility of VALOR using both pooled clone sequencing and 10X Genomics linked-read sequencing generated from the genome of an individual from the HapMap project (NA12878). We also provide a comprehensive comparison of VALOR against several state-of-the-art structural variation discovery algorithms that use whole genome shotgun sequencing data. Conclusions: In this paper, we show that VALOR is able to accurately discover all previously identified and experimentally validated large inversions in the same genome with a low false discovery rate. Using VALOR, we also predicted a novel inversion, which we validated using fluorescent in situ hybridization. [ABSTRACT FROM AUTHOR]

This paper describes an evolutionary process likely involved in hierarchic transitions in biological evolution at many levels, from genetics to social organization. It is related to the evolutionary process described as contingent neutral evolution (CNE). It involves a sequence of stages initiated by the spontaneous appearance of functional redundancy. This redundancy can be the result of gene duplication, symbiosis, cell-cell interactions, environmental supports, etc. The availability of redundant sources of biological functionality relaxes purifying selection and allows degenerative changes to accumulate in one or more of the duplicates, potentially degrading or otherwise fractionating its function. This degeneration will be effectively neutral so long as another maintains functional integrity. Sexual recombination can potentially sample different combinations of these sub functional alternatives, with the result that favorable synergistic interactions between independently degenerate duplicates will have a non-negligible probability of being uncovered. The expression of such a synergistic combinatorial effect will result in the irreversible degradation of any remaining autonomous functionality, thereby initiating selection to prevent breakup of co-dependency. This becomes relevant to the evolution of hierarchic transitions when two or more organisms reciprocally duplicate functions that each other requires. If the resulting relaxation of selection reliably persists for an extended evolutionary period it will tend to produce complementary degenerative effects in each organism, leading to their irreversible codependency and purifying selection to avoid loss of integrity of their higher order functional unity. This provides a partial inversion of Darwinian logic that explains how the potential costs of the loss of organism autonomy can be mitigated, enabling the incremental transition to a synergistic higher order unit of evolution. [ABSTRACT FROM AUTHOR]

Fluorescence in situ hybridization (FISH), especially chromosome painting, has been extensively exploited in the phylogenetic reconstruction of primate evolution. Although chromosome painting is a key method to map translocations, it is not effective in detecting chromosome inversions, which may be up to four times more frequent than other chromosomal rearrangements. BAC-FISH instead can economically delineate marker order and reveal intrachromosomal rearrangements. However, up to now, BAC-FISH was rarely used to study the chromosomes of New World monkeys partly due to technical difficulties. In this paper, we used BAC-FISH to disentangle the complex evolutionary history of the ancestral 14/15 association in NWMs, beginning from the squirrel monkey ( Saimiri boliviensis). To improve the hybridization efficiency of BAC-FISH in NWMs, we 'translated' the human BACs into Callithrix jacchus (CJA) BACs, which yielded much higher hybridization efficiencies on other NWM species than human BACs. Our results disclosed 14 synteny blocks in squirrel monkeys, 7 more than with chromosome painting. We then applied a subset of CJA BACs on six other NWM species. The comparison of the hybridization pattern of these species contained phylogenetic information to discriminate evolutionary relationships. Notably Aotus was found to share an inversion with Callithrix, thus definitely assigning the genus Aotus to Cebidae. The present study can be seen as a paradigmatic approach to investigate the phylogenetics of NWMs by molecular cytogenetics. [ABSTRACT FROM AUTHOR]

Large-scale mutational events that occur when stretches of DNA sequence move throughout genomes are called genome rearrangements. In bacteria, inversions are one of the most frequently observed rearrangements. In some bacterial families, inversions are biased in favor of symmetry as shown by recent research. In addition, several results suggest that short segment inversions are more frequent in the evolution of microbial genomes. Despite the fact that symmetry and length of the reversed segments seem very important, they have not been considered together in any problem in the genome rearrangement field. Here, we define the problem of sorting genomes (or permutations) using inversions whose costs are assigned based on their lengths and asymmetries. We consider two formulations of the same problem depending on whether we know the orientation of the genes. Several procedures are presented and we assess these procedure performances on a large set of more than 4.4 × 109 permutations. The ideas presented in this paper provide insights to solve the problem and set the stage for a proper theoretical analysis. [ABSTRACT FROM AUTHOR]

Photothermal membrane distillation (PMD) is a promising configuration of membrane distillation (MD), which can overcome the temperature polarization problem and allows using solar thermal energy. However, the effect on wetting of the incorporation of plasmonic nanoparticles (NPs) into a membrane is still unknown. This paper aims supporting the development of photoplasmonic membranes for PMD, by studying their wetting in vacuum MD operation, thanks to two methods recently developed in our group: the ex-situ detection of dissolved tracer intrusion (DDTI) and an in-operando optical method. Different composite membranes with Ag-NPs included in PVDF were elaborated by phase-inversion for checking if the proportion of NPs influences membrane wetting. This study demonstrates the importance of considering wetting in the earlier stages of the development of new membranes. Indeed, whatever the NP load, at global scale partial wetting was detected and the pore wetting ratio increased with the NP load, whereas the PVDF membrane remained un-wetted. Wetting dynamics was highly impacted by the presence of NPs and wetting occurred faster with increasing NP load, thus reducing the duration of the MD operation for the highest load. For limiting short-term wetting, a limited proportion of Ag-NPs (≤25 %) is recommended to membrane manufacturers or developers. [Display omitted] • Preparation of photothermal PVDF membrane with different loads of silver NPs • Identification of wetting mechanisms & quantification of wetting by the DDTI method • Wetting evaluation and dynamic study in operando by the optical method • Demonstration of the impact of silver NPs in PVDF on wetting indicators and dynamics • Guidelines on the maximal NPs load in photothermal PVDF distillation membranes [ABSTRACT FROM AUTHOR]

Optimal sensor distribution in explosion testing is important in saving test costs and improving experiment efficiency. Aiming at travel time tomography in an explosion, an optimizing method in sensor distribution is proposed to improve the inversion stability. The influence factors of inversion stability are analyzed and the evaluating function on optimizing sensor distribution is proposed. This paper presents a sub-region and multi-scale cell partition method, according to the characteristics of a shock wave in an explosion. An adaptive escaping particle swarm optimization algorithm is employed to achieve the optimal sensor distribution. The experimental results demonstrate that optimal sensor distribution has improved both indexes and inversion stability. [ABSTRACT FROM AUTHOR]

The variation in genome arrangements among bacterial taxa is largely due to the process of inversion. Recent studies indicate that not all inversions are equally probable, suggesting, for instance, that shorter inversions are more frequent than longer, and those that move the terminus of replication are less probable than those that do not. Current methods for establishing the inversion distance between two bacterial genomes are unable to incorporate such information. In this paper we suggest a group-theoretic framework that in principle can take these constraints into account. In particular, we show that by lifting the problem from circular permutations to the affine symmetric group, the inversion distance can be found in polynomial time for a model in which inversions are restricted to acting on two regions. This requires the proof of new results in group theory, and suggests a vein of new combinatorial problems concerning permutation groups on which group theorists will be needed to collaborate with biologists. We apply the new method to inferring distances and phylogenies for published Yersinia pestis data. [ABSTRACT FROM AUTHOR]

• Mapping hydraulic transmissivity from temporal data in multiple tracer tests, • Principle based on an encoder-decoder convolutional neural network, • Time required for training is on the order of a Gauss-Newton algorithm, • Provide an end-to-end inversion with an accurate reconstruction, perform instantly, • Reconstruction quality relies on training data, less influenced by data noise. This paper introduces a new concept for mapping hydraulic transmissivity from temporal concentration data collected in multiple tracer tests. Based on convolutional neural network, the principle uses an encoder-decoder architecture with multiple neural layers to establish a relationship between the concentration data and the transmissivity field. This relationship is established in two phases with two networks. The first network is designated and trained to reconstruct a transmissivity field using data from a single tracer test. To improve the reconstruction quality, the second network then performs a joint interpretation for multiple tracer tests, which reprocesses all the transmissivity resulted from the first network for each individual tracer test. Both networks are trained by synthetic data, where the transmissivity models are generated with a Gaussian variogram and its properties are considered as prior information on the aquifer heterogeneity. Tracer tests are derived numerically by solving the forward problem to obtain the corresponding concentration data that feed the training. The trained networks accurately map the transmissivity fields, of which the accuracy relies on the volume and nature of the heterogeneities of training models, as well as the number of piezometers used to monitor the concentration changes. Reconstruction quality, on the other hand, is less influenced by data noise. Effective training requires a large dataset, but the time required for dataset generation is only on the order of the Gauss-Newton algorithm in a conventional inversion, while the trained network performs inference instantly. [ABSTRACT FROM AUTHOR]

Introduction: This paper presents a detailed study of inversion in chromosome 9 and its correlation with sub-fertility amongst 26 couples. Until now, there have been conflicting views on the clinical outcome of the pericentric inversion in chromosome 9. Many researchers consider this anomaly as a predisposing factor for infertility. Methods: In the present study, the karyotyping analysis of 500 couples was carried out to investigate the genetic basis for infertility in these subjects. Results and Conclusion: It was observed that a significant fraction (5.2%) of the total group had a pericentric inversion in chromosome 9 as the only known abnormality. The incidence of this abnormality in infertile patients was significantly higher than the reported value of 1%-3% in the normal population. Moreover, it was observed that the incidence of the inv (9) karyotype in the male patients was 2.5 times higher than that in females. These correlations clearly indicated that the inv (9) karyotype was not a normal karyotype but that it had a harmful effect on fertility. [ABSTRACT FROM AUTHOR]

Although disproportionate inversion effects have often been considered manifestations of the special processes recruited by upright faces, several papers using sequential matching tasks have reported that body postures also produce sizeable inversion effects. However, comparison of inversion effects observed with transient body postures and effects elicited by judgements of facial structure is complicated by qualitative differences between the stimuli and the tasks. Here we report a series of experiments that use attractiveness judgements to provide a better comparison of the effect of inversion as well as contrast negation on face and body perception. Significant effects of inversion and negation were observed for both face and body stimuli. While the magnitude of the inversion effects was broadly comparable, the negation effect was considerably larger for faces. These effects converge with evidence from cognitive neuroscience to suggest that both faces and bodies recruit similar orientation-specific processes distinct from processes used for generic objects. [ABSTRACT FROM AUTHOR]

A genetic algorithm is a time consuming technique, especially for the big complex problems. Therefore, any run-time optimization regarding applying the genetic operators is very useful, taking into account that these operators apply many times in every generation. In this paper we propose run-time efficient implementations for three well-known mutation operators, specific to the permutation encoding needed in the vast area of scheduling problems. These operators are: frame-shift, translocation and inversion. [ABSTRACT FROM AUTHOR]

Abstract: The inverted tube can be used as an energy absorber in transport vehicles like aircraft and automobiles. The aim of this paper is to contribute to an extension of the actual knowledge of the deformation process and mechanical parameters by means of finite element simulation. Experiments were performed on 3A21 alumimium alloy tubes and 1Cr18Ni9Ti stainless steel tubes, mainly utilized for supporting and validating the results of finite element simulation. An experimental setup to investigate the energy absorbing capacity of inverted tube was designed. The investigation indicates: (1) the value of die radius or half-tapered-angle makes an important influence on the stability of external inversion and quality of the inverted tube; (2) the deforming load of inverted tubes under quasi-static load is very stable with a good energy absorbing capacity; (3) the finite element simulation results agree with the experimental ones. [Copyright &y& Elsevier]

Evolution operates on whole genomes through direct rearrangements of genes, such as inversions, transpositions, and inverted transpositions, as well as through operations, such as duplications, losses, and transfers, that also affect the gene content of the genomes. Because these events are rare relative to nucleotide substitutions, gene order data offer the possibility of resolving ancient branches in the tree of life; the combination of gene order data with sequence data also has the potential to provide more robust phylogenetic reconstructions, since each can elucidate evolution at different time scales. Distance corrections greatly improve the accuracy of phylogeny reconstructions from DNA sequences, enabling distance-based methods to approach the accuracy of the more elaborate methods based on parsimony or likelihood at a fraction of the computational cost. This paper focuses on developing distance correction methods for phylogeny reconstruction from whole genomes. The main question we investigate is how to estimate evolutionary histories from whole genomes with equal gene content, and we present a technique, the empirically derived estimator (EDE), that we have developed for this purpose. We study the use of EDE on whole genomes with identical gene content, and we explore the accuracy of phylogenies inferred using EDE with the neighbor joining and minimum evolution methods under a wide range of model conditions. Our study shows that tree reconstruction under these two methods is much more accurate when based on EDE distances than when based on other distances previously suggested for whole genomes. [ABSTRACT FROM AUTHOR]

Abstract: In the present paper, we report a molecular cytogenetic study of 1q abnormalities associated with t(8;14)(q24;q32) in an adult common B acute lymphoblastic leukemia case with FAB-L2 morphology. The use of appropriate molecular cytogenetic probes allowed us to detect 13 different subclones showing heterogeneous chromosome 1 abnormalities. A complex pattern of rearrangements consisting of translocations, duplications, and inversions was observed. Breakage-fusion-bridge cycle and jumping translocation are hypothesized to have been involved in generating the large number of aberrations we detected. [Copyright &y& Elsevier]

The influence of epistatic interactions of lethal and non-lethal genes upon viability of Drosophila inversion karyotypes is poorly known. In this paper we present comparative results for viabilities of 21 originally natural O-inversion homo- and 38 heterokaryotypes in a D. subobscura population. We observed strong heterotic effect in viability of O-lethal heterozygotes irrespective of different inversion backgrounds, which indicates a mechanism for protection of a great number of lethal genes. In O-non-lethal heterozygotes the heterotic effect in viability was absent irrespective of different inversion backgrounds. Our results showed a great extent of genetic load and high abundance of O-chromosomal arrangements in the population analyzed. It belongs to the set of central European populations. An epistasis of lethal genes present in O-inversion hetero- and not present in O-inversion homokaryotypes of moderate or low frequencies could be good example for co-adaptation of chromosomal inversions with regard to the genetic load. This represents a more efficient mechanism for limitation of genetic load than alternative mechanisms for protection of lethals. Except for lethal genes, possible epistatic interactions of mildly deleterious (subvital) genes, could also be responsible for limiting the extent of genetic load in natural D. subobscura populations. We demonstrated a non-random distribution of several combinations of viability classes among different O-inversion homo- and heterokaryotypes. As a consequence of that, the viabilities of the O-inversion homokaryotypes compared to heterokaryotypes were significantly higher at low frequencies than in moderate or high frequencies. This shows frequency-dependence as a mechanism of balancing selection for protection of O-chromosomal inversions in natural D. subobscura populations. In addition, the viabilities of the O-inversion homokaryotypes of lower frequency, compared to homokaryotypes of moderate or high frequency, were significantly higher. This again indicates the existence of supergene selection as another mechanism for protection of chromosomal inversions, as co-adapted complexes in natural D. subobscura populations. [ABSTRACT FROM AUTHOR]

In this paper, a novel Taylor-type difference rule with O ( τ 4 ) pattern error is provided for the first-order derivative approximation. Then, a high accuracy noise-tolerant five-step discrete-time zeroing neural network (ZNN) (termed as FDNTZNN model) is proposed to solve the time-varying matrix inversion problem in real-time. In addition, to obtain the derivative value of time-varying variables in real-world applications, the backward-difference rule is exploited to develop the FD-NTZNN model when the derivative information is unknown (FD-NTZNN-U). Theoretical analysis demonstrates that the proposed FD-NTZNN models have the properties of 0 − stability, consistency and convergence. For comparative analysis, the classical Euler-type discrete-time ZNN model (EDZNN), five-step Taylor-type discrete-time ZNN model (FDZNN) and Euler-type discrete-time noise-tolerant ZNN (NTZNN) model (ED-NTZNN) are reconsidered. Ultimately, two illustrative numerical simulations and an application example to motion generation of manipulator are simulated to substantiate the feasibility and effectiveness of the proposed FD-NTZNN model and FD-NTZNN-U model for online time-varying matrix inversion in the presence of different types of noise. • Two models are developed for time varying matrix inversion with different noises. • Theoretical analyses show the proposed models have higher accuracy than ZNN model. • Two models have superior stability and robustness under different noises. [ABSTRACT FROM AUTHOR]

Based on the inversion characteristic of the truncated Airy pulse in linear regime with third-order dispersion (TOD), we discuss the related dynamics of the truncated Airy pulse in a nonlinear femtosecond optical system. The influence of the initial total power and the Airy pulse width on the nonlinear effect is studied in detail. The results show that when the initial total power is less than one kilowatt, the inversion characteristics of the truncated Airy pulse with several femtosecond width can be observed, and increasing TOD coefficient will lead to tight-focusing of the truncated Airy pulse near the reversed distance. The interaction between the truncated Airy pulses is also studied. These properties are useful for manipulating pulse propagation in fiber system. • In this paper, based on the inversion characteristic of the truncated Airy pulse in linear regime with third-order dispersion (TOD), we discuss the related dynamics of the truncated Airy pulse in a nonlinear femtosecond optical system. • The influence of the initial total power and the Airy pulse width on the nonlinear effect is studied in detail. • The results show that when the initial total power is less than one kilowatt, the inversion characteristics of the truncated Airy pulse with several femtosecond width can be observed, and increasing TOD coefficient will lead to tight-focusing of the truncated Airy pulse near the reversed distance. • The interaction between the truncated Airy pulses is also studied. • These properties are useful for manipulating pulse propagation in fiber system. [ABSTRACT FROM AUTHOR]

Based on cytogenetic studies, non-random chromosomal translocations which involve the HOX11 gene at locus 10q24 and the TCR genes at loci 7q35 or 14q11 have been reported to occur in 5% of T-ALL. HOX11, a member of the homeobox family of genes, has been shown to play a role in T-ALL. The activation of the HOX11 gene by translocations to the TCR locus results in the inappropriate expression of a 2.3 kb transcript. In this paper we describe a t(10;14)(q24;q11) breakpoint from a T-ALL patient specimen. The breakpoint appears to be mediated by errors in the TCR/V(D)J recombination system, but is more complex than commonly described reciprocal translocations between the HOX11 and TCR genes, since it involves an inversion event of the TCRdelta genes. In addition, the breakpoint was characterised to a previously unsequenced area of the 10q24 locus, 3.4 kb upstream of the HOX11 gene. This breakpoint is more centromeric than the breakpoint cluster region previously shown to be involved in the majority of reported t(10;14)(q24;q11) translocations. Hence, our investigations of the translocation breakpoint in this patient identify another breakpoint region in the 10q24 locus and may define a novel recombination 'hot spot'. Surprisingly, our studies provide a mechanism for a previously unexplained complex translocation described by another group which involves the same region of the HOX11 promoter. [ABSTRACT FROM AUTHOR]

• Dynamic constitutive parameters is considered as random variables in inversion calculation. • Model error is added to improve the ability to predict experimental observations under other conditions. • Peak stress error is added to improve peak stress fitting accuracy. • Fitting accuracy and prediction accuracy are superior to traditional optimization algorithms. The difference in dynamic mechanical properties of different rock samples leads to a random process of deformation and stress. Uncertainties exist in the parameters of the rock material dynamic constitutive model. Unlike traditional inversion analysis methods, this paper treats model parameters as random variables. Bayesian theory and Differential Evolution Adaptive Metropolis algorithm (DREAM) are used to accurately quantify the uncertainty of the dynamic constitutive model parameters. The error function of the DREAM algorithm is divided into prediction error and model error to mitigate the effect of parameter compensation and improve the prediction ability. Peak stress error term is added to the DREAM prediction error to increase the peak stress fitting accuracy. Experiments of shock compression under freezing and high temperature cooling damage are presented to illustrate the proposed method. Different optimization algorithms such as Genetic Algorithm and Ant Colony Optimization are used to compare the accuracy of inversion parameters. The results show that the obtained peak stress fitting accuracy of the dynamic constitutive model is significantly improved. The 95% confidence interval considering model errors almost completely covers the experimental observations, indicating that the parameter probability distribution interval can accurately cover the true value while reflecting the model uncertainty. Using inversion parameters to predict other working conditions, 95% confidence interval considering model errors has high coverage. Thus, stochastic inversion method can accurately fit and predict the deformation and failure law of rock under impact load. [ABSTRACT FROM AUTHOR]

Seismic reflection coefficient inversion in the joint time-frequency domain is a method for inverting reflection coefficients using time domain and frequency domain information simultaneously. It can effectively improve the time-frequency resolution of seismic data. However, existing research lacks an analysis of the factors that affect the resolution of inversion results. In this paper, we analyze the influence of parameters, such as the length of the time window, the size of the sliding step, the dominant frequency band, and the regularization factor of the objective function on inversion results. The SPGL1 algorithm for basis pursuit denoising was used to solve our proposed objective function. The applied geological model and experimental field results show that our method can obtain a high-resolution seismic reflection coefficient section, thus providing a potential avenue for high-resolution seismic data processing and seismic inversion, especially for thin reservoir inversion and prediction. [ABSTRACT FROM AUTHOR]

• Anopheles subpictus in Thailand is genetically and/or morphologically distinct from An. subpictus species A, B, C and D described elsewhere. • Crossing experiments between three Thai COI clades of An. subpictus revealed no genetic incompatibility, suggesting that they were conspecific. • Anopheles subpictus from South Sulawesi is genetically distinct from those found in mainland Asia. The Anopheles subpictus complex consists of four species informally designated, based on fixed inversions of polytene chromosomes and morphology, as species A, B, C and D in India. However, recent studies revealed the presence of only species A and B in Sri Lanka. Little is known about the specific identity of the taxon in other countries in Asia. This paper reports the results of a molecular and morphological study of An. subpictus in Thailand and South Sulawesi, Indonesia. The maxillary palpi of most females from Thailand have the apical pale band longer than the subapical dark band, seta 7-I of pupae branched and short, and eggs with 18–25 float ridges. These characters do not agree with those described for species A, B, C and D in India. The females of An. subpictus from South Sulawesi usually have the subapical dark band of the maxillary palpus equal in length to the apical pale band. Phylogenetic analyses of sequences of the internal transcribed spacer 2 (ITS2) region of rDNA and the cytochrome c oxidase subunit I (COI) gene of mtDNA of specimens from Thailand, and South Sulawesi, and from various localities in GenBank, were conducted. ITS2 sequences of specimens from all localities in Thailand were identical, except for a small divergence in specimen from Phang Nga Province. Three distinct COI clades were detected in specimens from Chiang Mai Province in northern Thailand. However, crossing experiments between the three clades revealed no genetic incompatibility, suggesting that they were conspecific. ITS2 and COI sequences of most specimens from Thailand fell in clades other than those of An. subpictus species A and B and An. subpictus from Indonesia (East Nusa Tenggara, Java, South Sulawesi) and the Philippines. ITS2 sequences from South Sulawesi and East Nusa Tenggara were very similar, and fell in a clade consisting of specimen from Phang Nga in southern Thailand and sequences of some specimens from Cambodia and Vietnam, but their COI sequences were distinct. DNA sequences and morphological differences suggest the presence of two species within An. subpictus in Thailand, and more than one species in Indonesia. Image, graphical abstract [ABSTRACT FROM AUTHOR]