Bayesian Inference Methods Research Articles

First report of Nalanthamala vermoesenii causing pink rot of Phoenix canariensis in Mexico.

In Mexico City, the Canary Island date palm (Phoenix canariensis Chabaud) is an important plant forming part of its landscape identity. In February 2022, pink rot disease symptoms were observed on 16 P. canariensis plants in Mexico City (19°25'43.98"N, 99° 9'49.41"W). The incidence was 27%, while the severity 12%. External symptoms included necrotic lesions that advanced from the petiole towards the rachis. Internal symptoms were rotted, dark brown discoloration in bud, petiole, and rachis. Abundant conidial masses were developed on the infected tissues. Pieces of diseased tissues (5-mm cubes) were surface sterilized for 2 min in 3% sodium hypochlorite, rinsed with sterilized distilled water, plated onto potato dextrose agar (PDA), and incubated at 24°C and 12-h photoperiod, 20 pink fungal colonies were developed with sparse aerial mycelia on PDA. Conidiophores were hyaline, dimorphic, penicillate, and Acremonium-like. Conidia were dimorphic, typically with somewhat truncated ends, 4.5 to 5.7 × 1.9 to 2.3 μm (mean 4.99 × 2.15, n = 100), borne in long chains on penicillate conidiophores; on Acremonium-like conidiophores conidia were cylindrical, straight, and slightly curved, 4.55 to 10.1 × 1.2 to 2.35 μm (mean 8.2 × 1.7, n = 100). These morphological characteristics resembled those of Nalanthamala vermoesenii (Biourge) Schroers (Schroers et al. 2005). Genomic DNA was extracted from the mycelia of a representative isolate CP-SP53. The internal transcribed spacer (ITS) region and the large subunit of ribosomal ribonucleic acid (LSU) were amplified and sequenced. The sequences were deposited in GenBank with accession numbers OQ581472 (ITS) and OQ581465 (LSU). Phylogenetic trees based on ITS and LSU sequences of Nalanthamala species were reconstructed using maximum likelihood and Bayesian inference methods. Isolate CP-SP53 was placed in the clade of Nalanthamala vermoesenii. The pathogenicity test was carried out twice with isolate CP-SP53 on five 3-year-old P. canariensis plants. Four petioles per plant were surface disinfected with 75% ethanol, and wounded with a sterilized scalpel (shallow cuts 0.5 cm wide). A mycelial plug (5 mm in diam.) of a 1-week-old PDA culture was placed on each wounded site. Sterile PDA plugs were used for five non-inoculated control plants. All plants were maintained at 22 ± 2°C and a 12-h photoperiod. Twenty-five days after inoculation (dai), wounded petioles showed the same symptoms observed in the field, whereas control plants remained healthy. Forty-five dai, all inoculated plants died. Pink conidial masses developed on symptomatic tissues. To fulfill Koch's postulates, the pathogen was reisolated by placing the pink conidial masses onto PDA. The colony characteristics and morphometric measurements were identical to those of isolate CP-SP53. Nalanthamala vermoesenii has been reported on P. canariensis in Greece and United States (Feather et al. 1979; Ligoxigakis et al. 2013) and Syagrus romanzoffiana in Egypt (Mohamed et al. 2016). To our knowledge, this is the first report of Nalanthamala vermoesenii as the causal agent of pink rot on P. canariensis in Mexico. This plant is the most commonly planted ornamental palm in Mexico City. The spread of N. vermoesenii could be a threat for the estimated 15 thousand palms, therefore dramatically change the urban landscape.

Reliability assessment of civil structures with incomplete probability distribution information

The probability distribution of random variables is usually incomplete owing to a limited amount of data, making it a challenging problem for structural reliability assessments. This paper presents a novel reliability analysis method for civil structures with incomplete data. The probability distributions of the random variables were estimated using an improved Bayesian inference method. In the proposed inference method, the frequencies and mode shapes were selected as the observation data. The likelihood function is replaced by homogeneous chaos, and the computational efficiency of Bayesian inference is improved. The affine invariant ensemble algorithm was used to generate samplers for the posterior distribution. After estimating the probability distribution of the incomplete random variables, a reliability analysis was performed, and the failure probability of the structure was estimated. Numerical studies on a two-span, two-story reinforced concrete building and a five-span bridge are presented. Experimental studies were also performed on an eight-story steel frame structure. The results show that the probability distributions of random variables can be significantly updated using the proposed technique and modal properties. The proposed technique was more efficient than the Gibbs sampling method. The failure probabilities of the structures were estimated using the estimated probability distributions.

Eryn: a multipurpose sampler for Bayesian inference

ABSTRACTIn recent years, methods for Bayesian inference have been widely used in many different problems in physics where detection and characterization are necessary. Data analysis in gravitational-wave astronomy is a prime example of such a case. Bayesian inference has been very successful because this technique provides a representation of the parameters as a posterior probability distribution, with uncertainties informed by the precision of the experimental measurements. During the last couple of decades, many specific advances have been proposed and employed in order to solve a large variety of different problems. In this work, we present a Markov Chain Monte Carlo (MCMC) algorithm that integrates many of those concepts into a single MCMC package. For this purpose, we have built Eryn, a user-friendly and multipurpose toolbox for Bayesian inference, which can be utilized for solving parameter estimation and model selection problems, ranging from simple inference questions, to those with large-scale model variation requiring trans-dimensional MCMC methods, like the Laser Interferometer Space Antenna Global Fit problem. In this paper, we describe this sampler package and illustrate its capabilities on a variety of use cases.

Complete mitochondrial genome of Stethoconus japonicus (Hemiptera: Miridae): Insights into the evolutionary traits within the family Miridae

The mitochondrial (mt) genome sequence of insects possesses numerous evolutionary traits. To better understand the evolution of mt genomes within the family Miridae, the complete mt genome of the predatory Japanese plant bug Stethoconus japonicus Schumacher was sequenced before undertaking a comparative analysis of all reported plant bug mt genomes. The mt genome of S. japonicus is a closed-circular and double-stranded DNA molecule of 16,274 bp (GenBank: MK341530), which consists of 13 protein-coding genes (PCGs), 2 rRNAs, 22 tRNAs and a putative control region (CR). Consistent with other plant bugs, the mt genome of S. japonicus is strongly AT-biased (73.49 %) with A-skewed (0.202) and C-skewed (−0.248). All 13 PCGs initiate translation using ATN codons and TAA served as complete stop codons for eight PCGs, which as incomplete stop codon “T-” for cox1, nad1, nad5-6 and “TA-” for cox2. Regarding other features, all 22 tRNAs could be folded into typical cloverleaf secondary structures. The control region is 1,717 bp and contains a long tandem repeat sequence of a 165 bp unit repeated six times. Similar sequence with variable number of tandemly repeated units from intra-genus CRs is a distinct characteristic of plant bug mt genomes. Phylogenetic relationships of 15 bugs were eventually analyzed based on Maximum likelihood (ML) and Bayesian inference (BI) methods using 17 mt genome sequences. In the phylogenetic trees, species from a same genus or subfamily are clustered into a branch with high supporting values.and the result suggest that Deraeocorinae is more closely related to Mirinae than Bryocorinae. Finally, this study revealed that mutation of tRNA anticodon is a useful phylogenetic marker that could be of significance for studies of evolutionary patterns.

Bayesian inference on the isotopic building blocks of Mars and Earth

Elements with differing siderophile affinities provide insights into various stages of planetary accretion. The isotopic anomalies they exhibit offer a deeper understanding of the materials responsible for the formation of terrestrial planets. By analyzing new iron isotopic anomaly data from Martian meteorites and drawing insights from published data for O, Ca, Ti, Cr, Fe, Ni, Sr, Zr, Mo, Ru, and Si, we scrutinize potential changes in the isotopic composition of the material accreted by Mars and Earth during their formation. Our methodology employs a Bayesian inference method, executed using a Markov Chain Monte Carlo (MCMC) algorithm.The Bayesian method helps us balance the task of emulating the compositions of the terrestrial planets (reflected in the likelihood) with the flexibility to explore the isotopic compositions of mixing components within permissible intervals (indicated by the priors of the nuisance parameters). A Principal Component Analysis of isotopic anomalies in meteorites identifies three main clusters (forming the three parts of the isotopic trichotomy): CI, CC=CM + CO + CV + CR, and NC = EH + EL + H + L + LL. We adopt CI, COCV, O, and E as endmember compositions in the mixtures. We are concerned here with explaining isotopic anomalies in Mars and Earth, not their chemical compositions. Previous studies have shown that Earth's chemical composition could not be well explained by solely considering undifferentiated meteorites, as it requires incorporation of a refractory component enriched in forsterite. The endmember chondrite components considered here are assumed to be representative of isotopic reservoirs that were present in the solar nebula, but the actual building blocks could have had different chemical compositions, and we use cursive letters to denote those putative building blocks (CI for CI, COCV for COCV, O for O, and E for E).Because Earth's mantle composition is an endmember for some isotopic systems, it cannot be reproduced exactly by considering known chondrite groups only and requires involvement of a component that is missing from meteorite collections but is likely close to enstatite meteorites. With this caveat in mind, our results suggest that Earth is primarily an isotopic mixture of ~92% E, 6% CI, and < 2% COCV and O. Mars, on the other hand, appears to be a mixture of ~65% E, 33% O, and < 2% CI and COCV. We establish that Earth's CI contribution substantially increased during the latter half of its accretion. Mars began accreting a mix of O and E but predominantly accreted E later.Mars' changing isotopic makeup during accretion can be explained if it underwent gas-driven type I migration from its origin near the O - E boundary to a location well within the E region during the first few million years of solar system history. Earth's later increased CI contribution may be attributed to the stochastic impact of an interloper carbonaceous embryo that moved inside the inner solar system region while nebular gas was still present, and subsequently participated in the stage of chaotic growth.The discovery that a significant portion of Earth's building blocks closely resembles enstatite chondrites contrasts with recent findings of Si isotopic anomalies in enstatite chondrites when compared to terrestrial rocks. We suggest that this discrepancy likely stems from insufficient correction for high-temperature equilibrium isotopic fractionation, whether of nebular or planetary origin. With appropriate adjustments for this influence, both the silicate Earth and enstatite chondrites exhibit comparable Si isotopic anomalies, reaffirming a genetic link between them.

Parameter estimation in ultrafast spectroscopy using probability theory.

Ultrafast spectroscopy is a powerful technique that utilizes short pulses on the femtosecond time scale to generate and probe coherent responses in molecular systems. While the specific ultrafast methodologies vary, the most common data analysis tools rely on discrete Fourier transformation for recovering coherences that report on electronic or vibrational states and multi-exponential fitting for probing population dynamics, such as excited-state relaxation. These analysis tools are widely used due to their perceived reliability in estimating frequencies and decay rates. Here, we demonstrate that such "black box" methods for parameter estimation often lead to inaccurate results even in the absence of noise. To address this issue, we propose an alternative approach based on Bayes probability theory that simultaneously accounts for both population and coherence contributions to the signal. This Bayesian inference method offers accurate parameter estimations across a broad range of experimental conditions, including scenarios with high noise and data truncation. In contrast to traditional methods, Bayesian inference incorporates prior information about the measured signal and noise, leading to improved accuracy. Moreover, it provides estimator error bounds, enabling a systematic statistical framework for interpreting confidence in the results. By employing Bayesian inference, all parameters of a realistic model system may be accurately recovered, even in extremely challenging scenarios where Fourier and multi-exponential fitting methods fail. This approach offers a more reliable and comprehensive analysis tool for time-resolved coherent spectroscopy, enhancing our understanding of molecular systems and enabling a better interpretation of experimental data.

Genome-informed investigation of the molecular evolution and genetic reassortment of severe fever with thrombocytopenia syndrome virus.

Severe fever with thrombocytopenia syndrome virus (SFTSV) is a viral pathogen causing significant clinical signs from mild fever with thrombocytopenia to severe hemorrhages. World Health Organization has paid special attention to the dramatic increase in human SFTS cases in China, Japan, and South Korea since the 2010s. The present study investigated the molecular evolution and genetic reassortment of SFTSVs using complete genomic sequences. We collected the complete genome sequences of SFTSVs globally isolated until 2019 (L segment, n = 307; M segment, n = 326; and S segment, n = 564) and evaluated the evolutionary profiles of SFTSVs based on phylogenetic and molecular selection pressure analyses. By employing a time-scaled Bayesian inference method, we found the geographical heterogeneity of dominant SFTSV genotypes in China, Japan, and South Korea around several centuries before and locally spread by tick-born spillover with infrequent long-distance transmission. Purifying selection predominated the molecular evolution of SFTSVs with limited gene reassortment and fixed substitution, but almost all three gene segments appeared to harbor at least one amino acid residue under positive selection. Specifically, the nonstructural protein and glycoprotein (Gn/Gc) genes were preferential selective targets, and the Gn region retained the highest number of positively selected residues. Here, the large-scale genomic analyses of SFTSVs improved prior knowledge of how this virus emerged and evolved in China, Japan, and South Korea. Our results highlight the importance of SFTSV surveillance in both human and non-human reservoirs at the molecular level to fight against fatal human infection with the virus.

First mitochondrial genomes of the crane fly tribe Elephantomyiini (Diptera, Tipuloidea, Limoniidae): comparative analysis and phylogenetic implications

Limoniidae, the most speciose family in the superfamily Tipuloidea, consists of four subfamilies and more than 11,000 species. However, mitochondrial (mt) genome sequences, which have been widely used for phylogenetic study, are available for only 11 species across three subfamilies. Thus, a larger variety of mt genome sequences in Limoniidae are required to improve our understanding of tipuloid phylogeny and genomic evolution. Here we present mt genomes of Elephantomyia (Elephantomyia) inulta Alexander, 1938 and Helius (Helius) pluto Alexander, 1932, representing the first mt genomes of the tribe Elephantomyiini (Limoniidae). The two mt genomes are typical circular DNA molecules and show similar gene order, nucleotide composition and codon usage. Standard ATN start and TAR stop codons are present in most protein-coding genes. All transfer RNA (tRNA) genes exhibited the cloverleaf secondary structure typical for metazoans except in tRNASer(AGN), which lacks the dihydrouridine arm. Phylogenetic analyses were performed based on four nucleotide matrixes for the currently sequenced species of Tipuloidea using Bayesian inference and maximum likelihood methods. Four-cluster likelihood mapping was used to study incongruent signals between different topologies. Pediciidae is supported as the earliest lineage in Tipuloidea, and the sister-group relationship between Cylindrotomidae and Tipulidae is also supported, but the monophyly of Limoniidae is not supported. Our study also supports the monophyly of Elephantomyiini (Elephantomyia + Helius), as one of origins of flower-visiting in Limoniidae. Although Elephantomyiini is sister to Limoniinae + Epiphragma (Limnophilinae) in our study, a more precise understanding of its phylogenetic position in Tipuloidea will require additional studies that include a broader species sample.

Calcarisporium yuanyangense sp. nov. (Calcarisporiaceae, Hypocreales), a fungal pathogen isolated from Ophiocordyceps nutans

In this study, a new species, Calcarisporium yuanyangense, was isolated from Ophiocordyceps nutans collected from Yuanyang County, Yunnan Province, China, and described by morphology and molecular phylogeny. Based on the combined dataset of five genes including the internal transcribed spacer gene region (ITS), the nuclear ribosomal small and large subunit gene regions (nrSSU and nrLSU), the gene encoding translation elongation factor 1-α (tef-1α), and the RNA polymerase II second largest subunit gene region (rpb2), phylogenetic analyses were performed by the maximum likelihood (ML) and the Bayesian inference (BI) methods to determine the phylogenetic position of C. yuanyangense in Calcarisporium. This species was clustered with C. cordycipiticola, C. xylariicola, and C. arbuscula to form a separate branch. Calcarisporium yuanyangense had the basic morphological characteristics of Calcarisporium, but still differed morphologically from the other species in the genus. This species was similar to C. arbuscula in conidia shape, but the conidia of C. yuanyangense were larger and had a higher length/width ratio than those of C. arbuscula. This study deepens the understanding of the host diversity and the distribution of this taxonomic unit, as well as provides important taxonomic data for further exploration of the genus Calcarisporium.

BAYESIAN INFERENCE AND DYNAMIC PREDICTION FOR MULTIVARIATE LONGITUDINAL AND SURVIVAL DATA.

Alzheimer's disease (AD) is a complex neurological disorder impairing multiple domains such as cognition and daily functions. To better understand the disease and its progression, many AD research studies collect multiple longitudinal outcomes that are strongly predictive of the onset of AD dementia. We propose a joint model based on a multivariate functional mixed model framework (referred to as MFMM-JM) that simultaneously models the multiple longitudinal outcomes and the time to dementia onset. We develop six functional forms to fully investigate the complex association between longitudinal outcomes and dementia onset. Moreover, we use the Bayesian methods for statistical inference and develop a dynamic prediction framework that provides accurate personalized predictions of disease progressions based on new subject-specific data. We apply the proposed MFMM-JM to two large ongoing AD studies: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and National Alzheimer's Coordinating Center (NACC), and identify the functional forms with the best predictive performance. our method is also validated by extensive simulation studies with five settings.

Reassessment of Operating Engineering Steel Structures with the First Order Reliability Method and Bayesian Inference

AbstractSince the commencement of regulations and standards, the sustainability of civil engineering structures has been a recurrent issue for the construction industry and society at large. The practical design process of engineering structures, in accordance with national guidelines, addresses uncertainties related to the stochastic nature of parameters such as climate loads, structural materials, or model limits. These uncertainties are taken into consideration through initial probabilistic assumptions and safety factors. However, safety factors derived mathematically based on code‐driven presumptions often fail to accurately represent the unique conditions of an individual structure. Although the development of structural health monitoring (SHM) techniques allows for a significant reduction in the uncertainty of the action and resistance, the ability to transform monitoring information to reevaluate the design capacity of existing structures is limited at the practical level. This paper provides an example of how design can be enhanced by incorporating sensor data and using the Bayesian inference and First Order Reliability Method (FORM), tailored to accurately reflect the current structural condition.

A new prediction model of the jet grouting column diameter for three jet grouting systems

Jet grouting column is widely used in ground improvements of hydraulic and geotechnical structures. Estimation of the diameter of the jet grouting column is indispensable to the design of those structures. Existing prediction models of the jet grouting column perform poorly when applied to the recently emerged double and triple-jet grouting systems and cannot quantify the prediction uncertainties. This study has compiled a global-wide jet grouting database and proposed an explicit model that is suitable for all three popular jet grouting systems (i.e., single, double, and triple). The Bayesian inference method was employed to estimate the regression parameters for the proposed model and quantify the prediction uncertainty. The proposed model is compared with a widely used empirical model through a cross-validation procedure. The comparisons show the proposed model is free of systematic errors and has much higher accuracy than the existing method, although the two have similar complexities in terms of the number of unknown regression parameters. The new model can reasonably quantify the prediction uncertainty in the sense that the 95% confidence interval of jet grouting column diameter covers the actual value with a probability of around 95%. To facilitate practice use, analytical formulas have been derived to calculate the statistics of jet grouting column diameter. This unique feature developed here to quantify the prediction uncertainty provides a potentially fundamentally new tool for engineers to estimate the jet grouting column diameter and assess the associated prediction errors.

Multiple Introduction Events of Cultivated Diospyros Kaki L. of and Native Diospyros Species in Taiwan Inferred by Low Copy Nuclear Markers

Diospyros kaki L. is one of the most important fruits in Taiwan. Cultivated D. kaki cultivars are classified into four types, according to their loss of astringency in ripening fruit and their change in flesh color, namely the Pollination-Constant Non-Astringent (PCNA), the Pollination Variant Non-Astringent (PVNA), the Pollination Variant Astringent (PVA) and the Pollination Constant Astringent (PCA). Recently, persimmon breeders are paying more attention to rootstock selection for successful grafting and agricultural production. To identify suitable rootstock and to trace the origins of extant native Diospyros species in Taiwan, the 10 known native Diospyros species together with four D. kaki cultivars were analyzed by using two low-copy, nuclear-encoded DNA markers, ncpGS and PHYA. There was moderate to strong support for the major nodes within the phylogenetic tree, obtained from both the Maximum-likelihood or the Bayesian inference methods. The constructed D. kaki phylogeny using Maximum Likelihood (ML) and Bayesian Inference (BI) algorithms formed three clades. The most basal clade (clade A) comprised species distributed in the South East Asia , then species distributed in East Asia (clade B), and then D. kaki cultivars (clade C). The extant native Taiwan Diospyros species nested into clade A and B, suggesting a northward migration pattern of native Taiwan Diospyros species. In addition, the species D. oldhamii formed a sister clade with the D. kaki cultivars, suggesting that D. oldhamii may be a compatible rootstock. Lastly, D. kaki cultivars sampled from growers that were acquaintances formed corresponding subclades within clade C (C-1, C-2 and C-3), suggesting a high discrimination ability of the ncpGS and PHYA molecular markers used here.

Neural superstatistics for Bayesian estimation of dynamic cognitive models

Mathematical models of cognition are often memoryless and ignore potential fluctuations of their parameters. However, human cognition is inherently dynamic. Thus, we propose to augment mechanistic cognitive models with a temporal dimension and estimate the resulting dynamics from a superstatistics perspective. Such a model entails a hierarchy between a low-level observation model and a high-level transition model. The observation model describes the local behavior of a system, and the transition model specifies how the parameters of the observation model evolve over time. To overcome the estimation challenges resulting from the complexity of superstatistical models, we develop and validate a simulation-based deep learning method for Bayesian inference, which can recover both time-varying and time-invariant parameters. We first benchmark our method against two existing frameworks capable of estimating time-varying parameters. We then apply our method to fit a dynamic version of the diffusion decision model to long time series of human response times data. Our results show that the deep learning approach is very efficient in capturing the temporal dynamics of the model. Furthermore, we show that the erroneous assumption of static or homogeneous parameters will hide important temporal information.

First report of Neofusicoccum sinoeucalypti causing leaf spot on Terminalia catappa in China.

Terminalia catappa belonging to the family Combretaceae, spreads in tropical and subtropical coastal areas. It mainly serves as shading and decorative tree (Anand et al, 2015). It is planted as roadside tree in Southern China. A leaf spot disease of T. catappa was observed at Wencheng Town (110.805323°E, 19.524567°N), Wenchang City, Hainan province, China in June, 2022. The disease incidence of leaves reached 10%. The occurrence of this leaf spot would reduce the ornamental value of T. catappa. The early symptoms of infected leaves were small, round, dark brown spots surrounded by irregular light halos, developing to larger irregular necrotic lesions and leaves withered. Twelve diseased leaves were collected from three survey trees. Symptomatic leaf samples were collected and cut into small pieces (3×3 mm). The pieces were surface sterilized with 2.5% sodium hypochlorite for 1 min, rinsed with sterile distilled water three times, placed on potato dextrose agar (PDA) medium and incubated at 28 ℃ in the dark for 3 days. Three hyphal tip isolates (DYLR-1, DYLR-2 and DYLR-3) were cultured on PDA. Colonies on PDA reached the edge of the 90 mm plates after 3 d and had fluffy mycelia with an uneven margin, initially creamy white, becoming light grey (5 d) to mouse grey (10 d) at the surface with the black globular cavity. To induce sporulation, the isolates were transferred to 2% water agar media with sterilised pine needles placed on the surface of the media. Conidia was hyaline, unicellular, thin-walled, smooth with granular contents, aseptate, narrowly fusiform, base subtruncate to bluntly rounded, 11.1 to 16.7 (14.5±1.4) × 4.6 to 7.6 (6.2±0.7) μm (n=50). Spermatia was hyaline, unicellular, aseptate, allantoid to rod-shaped, 3.2 to 6.9 (5.1±0.9) μm × 2.0 to 3.8 (2.5±0.4) μm (n=50). Pathogenicity tests were performed both in vitro and in vivo, and replicated twice. All three isolates were used for pathogenicity tests, with 18 detached leaves used for pathogenicity tests in vitro and 3 seedlings used for pathogenicity tests in vivo. A 5-mm-diameter agar plug containing mycelia were placed on the leaves both without and with wound. Sterile PDA plugs were used as controls. The leaves were moisturized with a clear plastic bag for 24 hours in a greenhouse under 90% ± 5% RH at 25 ℃. Brown spot symptoms were observed at 1 day post-inoculation (dpi) in vitro and 3 dpi in vivo. The same strains were reisolated from lesions of inoculated leaves. Control plants were symptomless. For molecular identification, internal transcribed spacer region and intervening 5.8S nrRNA gene (ITS; ITS1/ITS4 primers; White et al. 1990), translation elongation factor 1-alpha gene (tef1-α; EF1-728F/EF1-986R primers; Carbone and Kohn 1999), beta-tubulin gene (tub2; Bt2a/Bt2b primers; Glass and Donaldson 1995) and DNA directed RNA polymerase II second largest subunit gene (rpb2; RPB2bot6F/RPB2bot7R; Sakalidis et al. 2011) regions were PCR amplified from genomic DNA. The sequences (GenBank accessions numbers: OP435357 to OP435359 of ITS; OP535354 to OP535356 of tef1-α; OP535351 to OP535353 of tub2; OP535348 to OP535350 of rpb2) had 100%, 99.7%, 100%, 100% similar to the type strain of Neofusicoccum sinoeucalypti CERC2005 (GenBank accessions numbers: KX278061, KX278166, KX278270 and KX278290), respectively. Multi-locus phylogenetic tree (ITS, tef1-α, tub2 and rpb2) of Neofusicoccum spp. (Zhang et al. 2021) showed that those three isolates were sister to N. sinoeucalypti based on the maximum likelihood and bayesian inference methods. N. sinoeucalypti was first reported pathogen causing from Eucalyptus plantations and adjacent plants in China (Li et al. 2018). To our knowledge, this is the first report of Neofusicoccum sinoeucalypti causing leaf spot disease on Terminalia catappa in China. Neofusicoccum species, commonly cause diseases in woody plants worldwide, and identification of this pathogen is important for effective disease management and control.

First report of stem-end rot caused by Botryosphaeria fabicerciana on mango fruits in China.

Mango (Mangifera indica L.), belongs to the family Anacardiacea, and is one of the most popular tropical fruits in the world. Stem-end rot is a major postharvest disease of mango fruit, causing severe losses during storage in China (Chen et al., 2015). In July 2021, the mango fruits harvested from Baise Municipal National Agricultural Science and Technology Park (23.683568 N, 106.986325 E) of Guangxi province in China developed stem-end rot during storage. The disease incidence reached ca. 8.3%. The initial symptoms appeared as light brown lesions surrounding the peduncle, which quickly expanded becoming large dark-brown lesions. Small pieces of epidermis (5 mm × 5 mm) from 8 typical diseased friuts were cut from the edges of lesions surface-sterilized with 2% sodium hypochlorite and rinsed with sterile distilled water. The tissue was plated on potato dextrose agar (PDA) and incubated at 28 ℃ in the dark for 3 days. Fifteen, similarcolonies were isolated from the symptomatic tissue. The representative isolates DF-1, DF-2 and DF-3 were selected for morphological characterization, molecular identification, and pathogenicity testing. The colonies were circular with fluffy aerial mycelium, initially white turning to smoke-gray from the center in upper side and greenish black in reverse side, covering the 90 mm diameter Petri dish after 4 days of incubationon PDAat 28 ℃in dark. Pycnidia were produced on the surface of the colony after 30 days. Conidia were fusiform, aseptate, hyaline, thin-walled with granular contents, apex sub-obtuse, base subtruncate to bluntly rounded, 14.0-20.3 (16.8±1.6) μm × 3.1-7.2 (5.1±0.9) μm (n=50). The sexual stage was absent. Based on morphology, isolates were preliminarilyidentified asBotryosphaeriaspeices.To accurately identify the pathogen, genomic DNA was extracted from the mycelium of the three isolates DF-1, DF-2 and DF-3. The internal transcribed spacer of rDNA region (ITS), elongation factor 1-alpha (EF-1α) and beta-tubulin gene (TUB) genes were amplified using primers ITS1/ITS4, EF1-728F/EF1-986R and Bt2a/Bt2b, respectively (Slippers et al., 2004). The nucleotide sequences were all deposited in GenBank (ITS: OP729176-OP729178 EF-1α: OP758194-OP758196 and TUB: OP758197-OP758199). Based on the BLASTn analysis, the ITS, EF1-α and TUB sequences of three isolates were 100%, 99% and 99% similar to the Botryosphaeria fabicerciana MFLUCC 10-0098 sequences (ITS: JX646789, EF-1α: JX646854 and TUB: JX646839). Multi-locus phylogenetic analyses (ITS, EF-1α and TUB) showed that the isolate DF-1, DF-2 and DF-3 were clustered within Botryosphaeria fabicerciana clade based on the maximum likelihood , Bayesian inference, and maximum parsimony methods. The pathogenicity test was performed by placing discs mycelium around the peduncle of mature mango fruits by pin-prick method. Each treatment carried out with 12 fruits. The inoculated fruits were placed in plastic boxes at 28 ℃ with three replicates. Three days after inoculation, typical symptoms of stem-end rot were observed. The control fruits were inoculated with sterile PDA discs, and remained symptomless. The same fungus was re-isolated from the symptomatic tissue to complete Koch's postulate. Botryosphaeria fabicerciana (basionym: Fusicoccum fabicercianum) was first reported as pathogen causing senescent twig of Eucalyptus spp. in China (Chen et al., 2011; Phillips et al., 2013). To our knowledge, this is the first report of Botryosphaeria fabicerciana causing stem-end rot of Mangifera indica in China.

Myxobolus coriumicus n.sp. (Cnidaria: Myxozoa) Causing Scale Disease Associated with Skin Lesions in Indian Cultured Carp, Cirrhinus mrigala in Punjab.

The motive of the present study was to investigate incidences of myxozoan parasite infection in commercially important fishes and their characterization using morphological attributes and molecular approach. The specimens of cultured Cirrhinus mrigala were sampled and various organs were examined. The plasmodia were detected on the scales. The identification of species was based on the myxospore morphology and 18S rDNA sequence analyses. For phylogenetic analysis, maximum likelihood (ML) and Bayesian inference (BI) methods were employed. The SEM and histological studies were performed to assess the damage to the scales. The infected fishes had white patches on the scales and red haemorrhagic lesions on the skin. The plasmodia of Myxobolus coriumicus n. sp. were located on the dorsal surface of the scale towards its exposed part. SEM study indicated that lepidonts were damaged in the infected scales. The myxospores were spherical in shape, 9.0-10.0 × 8.0-9.0[Formula: see text]m in size, with two ovoid equal polar capsules 3.13-4.0 × 2.03-2.33[Formula: see text]m in size, having 4-5 sutural edge markings at the posterior-lateral margins of the shell valves and binucleated sporoplasm. BLAST search based on 18S rDNA revealed 93.87% sequence similarity with M. rewensis, (MZ230381). The prevalence of infection was 6.3% and Scale Plasmodium Index (SPI) was 3 indicating heavy infection. Morpho-molecular data generated during this study enables us to conclude that the present species, M. coriumicus n. sp. infecting scales of C. mrigala is new to the science causing significant damage to the scales.

Bayesian inference of pit corrosion in prestressing strands using Markov Chain Monte Carlo method

Corrosion monitoring has been widely studied to maintain the structural capacity of bridges through direct visual and nondestructive inspections or indirect inverse analysis-based methods. This study proposes a Bayesian inference method for inferring pit corrosion in the prestressing strands of prestressed concrete (PSC) bridges, which is an indirect method for corrosion monitoring. First, the probabilistic relationship between the mechanical properties of the strands and the amount of pit corrosion was defined using Bayes’ rule. Subsequently, a Markov chain Monte Carlo method was introduced to infer the posterior probability, which is a conditional probability distribution of the amount of corrosion given a certain mechanical property. Based on the inference results, probabilistic bounds for the amount of corrosion were derived. The proposed method was applied to two examples: (a) probabilistic corrosion inference of strands based on the tensile test results, and (b) probabilistic corrosion inference of embedded strands in PSC girders based on the bending test results. The inference results demonstrated the applicability of the proposed method.

Phylogenetic relationships and biogeography of the ancient genus Onychorhynchus (Aves: Onychorhynchidae) suggest cryptic Amazonian diversity

We examined phylogeographic patterns and cryptic diversity within the royal flycatcher, Onychorhynchus coronatus (Aves: Onychorhynchidae), a widespread Neotropical lowland forest tyrant flycatcher. A phylogeny of the six recognized subspecies was constructed from mtDNA sequence data of the NADH dehydrogenase subunit two gene, using Bayesian Inference and Maximum Likelihood methods. Phylogenetic analyses revealed high levels of intraspecific divergence within O. coronatus, supporting the existence of at least six independent lineages. The phylogenetic results uncovered the following relationships: (O. c. swainsoni [Southern Atlantic Forest], (O. c. coronatus [western Amazonia], (O. c. castelnaui [eastern Amazonia], (O. c. mexicanus [Central America], (O. c. occidentalis [Tumbesian], O. c. fraterculus [extreme northwestern South America])))). Biogeographic and dating analyses suggest that vicariant and dispersal events acted across approximately six million years to influence lineage diversification within this genus. Some of those events include the formation of the Amazon River and its tributaries, Andean uplift, and climatically induced vegetational shifts. Phylogenetic and biogeographic analyses of O. coronatus lineages support a hypothesis of area relationships in which the first divergence event isolated the Southern Atlantic Forest from Amazonia during the Late Miocene/Early Pliocene. This event was followed by the split of western and eastern Amazonia at the Early/Late Pliocene, the divergence of cis‐ and trans‐Andean lowland regions also at the Early/Late Pliocene, the split between Central America and the extreme northwestern South America/Tumbes at the Early/Middle Pleistocene, and the split between extreme northwestern South America and Tumbes at Middle/Late Pleistocene. Subsequent divergence of the southern and northern populations in the western and eastern Onychorhynchus lineages took place during the Pleistocene. Comparison of phylogenetic trees and patterns in Onychorhynchus with those from published work suggests that across large New World radiations such as the Suboscines, some co‐distributed lineages began to diverge long before others, which exemplifies the complexity of their evolutionary history.

Approximate Gaussian variance inference for state‐space models

SummaryState‐space models require an accurate knowledge of the process error () and measurement error () covariance matrices for exact state estimation. Even though the matrix can be, in many situations, considered to be known from the measuring instrument specifications, it is still a challenge to infer the matrix online while providing reliable estimates along with a low computational cost. In this article, we propose an analytically tractable online Bayesian inference method for inferring the matrix in state‐space models. We refer to this method as approximate Gaussian variance inference (AGVI) using which we are able to treat the error variance and covariance terms in the full matrix as Gaussian hidden states and infer them simultaneously with the other hidden states in a closed‐form manner. The two case studies show that the method is able to provide statistically consistent estimates for the mean and uncertainties of the error variance terms for univariate and multivariate cases. The method also exceeds the performance of the existing adaptive Kalman filter methods both in terms of accuracy and computational efficiency.