Ambiguous Correlation Research Articles

The Ambiguous Correlation of Blautia with Obesity: A Systematic Review.

Obesity is a complex and multifactorial disease with global epidemic proportions, posing significant health and economic challenges. Whilst diet and lifestyle are well-established contributors to the pathogenesis, the gut microbiota's role in obesity development is increasingly recognized. Blautia, as one of the major intestinal bacteria of the Firmicutes phylum, is reported with both potential probiotic properties and causal factors for obesity in different studies, making its role controversial. To summarize the current understanding of the Blautia-obesity correlation and to evaluate the evidence from animal and clinical studies, we used "Blautia" AND "obesity" as keywords searching through PubMed and SpringerLink databases for research articles. After removing duplicates and inadequate articles using the exclusion criteria, we observed different results between studies supporting and opposing the beneficial role of Blautia in obesity at the genus level. Additionally, several studies showed probiotic effectiveness at the species level for Blautia coccoides, B. wexlerae, B. hansenii, B. producta, and B. luti. Therefore, the current evidence does not demonstrate Blautia's direct involvement as a pathogenic microbe in obesity development or progression, which informs future research and therapeutic strategies targeting the gut Blautia in obesity management.

Accurate and Efficient Stereo Matching via Attention Concatenation Volume.

Stereo matching is a fundamental building block for many vision and robotics applications. An informative and concise cost volume representation is vital for stereo matching of high accuracy and efficiency. In this article, we present a novel cost volume construction method, named attention concatenation volume (ACV), which generates attention weights from correlation clues to suppress redundant information and enhance matching-related information in the concatenation volume. The ACV can be seamlessly embedded into most stereo matching networks, the resulting networks can use a more lightweight aggregation network and meanwhile achieve higher accuracy. We further design a fast version of ACV to enable real-time performance, named Fast-ACV, which generates high likelihood disparity hypotheses and the corresponding attention weights from low-resolution correlation clues to significantly reduce computational and memory cost and meanwhile maintain a satisfactory accuracy. Furthermore, we design a highly accurate network ACVNet and a real-time network Fast-ACVNet based on our ACV and Fast-ACV respectively, which achieve state-of-the-art performance on several benchmarks.

Synthetic Meta-Signal Observations: The Beidou Case.

A Global Navigation Satellite System (GNSS) meta-signal is obtained when two or more side-band components from different frequencies are jointly processed as a single entity. This requires advanced signal processing techniques able to cope with the subcarrier, generated by the interaction of the side-band components, and handle possibly multi-peaked ambiguous correlation functions. An alternative approach to meta-signal processing is to reconstruct meta-signal observations using side-band measurements. Meta-signal high-accuracy pseudoranges can be reconstructed from the side-band code and carrier observations. The success of the reconstruction depends on several factors, including the frequency separation of the side-band components and the presence of measurement biases. The Beidou Navigation Satellite System (BDS), with its second- and third-generation signals, provides a wide range of components with various frequency separations. In this paper, we experimentally investigate the performance and limitations of the measurement reconstruction approach using Beidou observations. When the B1I and B1C components are considered, their reduced frequency separation leads to unambiguous measurements fully exploiting the potential of meta-signals. For larger frequency separations, jumps and discontinuities are observed in the position domain, which is a major limiting factor of this type of approach.

Robust investment for insurers with correlation ambiguity

This paper investigates the investment decision of insurers when there is ambiguous correlation between the financial market and the insurance business. The robust decision model that accommodates correlation ambiguity between a risky financial asset and the insurer’s non-tradable surplus is solved under the G-expectation framework. We find that correlation ambiguity leads to a more conservative investment strategy in financial assets, providing a plausible explanation for insurers’ under- or zero investment in the financial market during normal economic times. We also show that the range of priors set of correlation coefficients can be statistically inferred, and insurers will quit the financial market when the range of priors set exceeds a certain level, which is more likely to happen when the remaining investment horizon is long.

Flight to quality and portfolio diversification under ambiguity of correlation

We argue that ambiguous correlation between asset payoffs plays an important role in the occurrence of “flight to quality”, which in some circumstances leads investors with incomplete information to portfolio under-diversification. In this paper, we consider a multi-asset economy with four types of investors who have heterogeneous beliefs on correlation coefficients, and in which ambiguity-averse traders make decisions in a maxmin expected utility framework. A unique general equilibrium presents in four scenarios according to the dispersion of asset quality. We define a measure to gauge the degree of portfolio under-diversification, with which we show that correlation ambiguity will drive less-informed investors to hold a nondiversified portfolio if the correlation coefficient is negative, while a positive correlation drives some less-informed investors to hold a fully diversified portfolio.

High-risk antibiotics positively correlated with antibiotic resistance genes in five typical urban wastewater

Antibiotic resistance genes (ARGs) and antibiotic amount increased within close proximity to human dominated ecosystems. However, few studies assessed the distribution of antibiotics and ARGs in multiple ecosystems especially the different urban wastewater. In this study, the spatial distribution of ARGs and antibiotics across the urban wastewater included domestic, livestock, hospital, pharmaceutical wastewater, influent of the wastewater treatment plant (WWTP) in Northeast China. The q-PCR results showed that ARGs were most abundant in community wastewater and followed by WWTP influent, livestock wastewater, pharmaceutical wastewater and hospital wastewater. The ARG composition differed among the five ecotypes with qnrS was the dominant ARG subtypes in WWTP influent and community wastewater, while sul2 dominant in livestock, hospital, pharmaceutical wastewater. The concentration of antibiotics was closely related to the antibiotic usage and consumption data. In addition to the high concentration of azithromycin at all sampling points, more than half of the antibiotics in livestock wastewater were veterinary antibiotics. However, antibiotics that closely related to humankind such as roxithromycin and sulfamethoxazole accounted for a higher proportion in hospital wastewater (13.6%) and domestic sewage (33.6%), respectively. The ambiguous correlation between ARGs and their corresponding antibiotics was detected. However, antibiotics that exhibited high ecotoxic effects were closely and positively correlated with ARGs and the class 1 integrons (intI1), which indicated that high ecotoxic compounds might affect antimicrobial resistance of bacteria by mediating horizontal gene transfer of ARGs. The coupling mechanism between the ecological risk of antibiotics and bacterial resistance needed to be further studied, and thereby provided a new insight to study the impact of environmental pollutants on ARGs in various ecotypes.

River Surface Velocimetry Based on Virtual River Dataset and Modulated-RAFT

Many image-based velocimetry methods, such as large-scale particle image velocimetry (LSPIV), space-time image velocimetry (STIV) and optical flow velocimetry (OFV), have been proposed to estimate river surface velocity (RSV) efficiently and precisely. Among these methods, OFV-based methods have drawn great attention due to its high field resolution and low requirement of tracers. As a powerful approach for estimate optical flow accurately and efficiently, deep optical flow estimation is utilized in OFV-based methods as well. However, these methods often use irrelevant datasets for training due to the immeasurability of optical flow. Models obtained by such approaches suffer from limited generalization because of domain drift. Besides, high similarity of river surfaces often leads to ambiguous correlation volume extracted by deep optical flow estimation model, which can cause mismatch. This work proposed a method for accurately and robustly RSV estimation under velocity range of 0-6.0 m/s. Specifically, we introduced a method for generating relative optical flow datasets and proposed MRAFT, a deep optical flow estimation model combining with correlation volume modulation. Experiment results demonstrate that the generated virtual river datasets effectively improve the generalization of the model and MRAFT remarkably alleviates the mismatch. Our work facilitates the application of deep optical flow on RSV estimation and provides other related researches with optical flow datasets for fine-tuning.

Closing the gap: a new phylogeny and classification of the chemosymbiotic bivalve family Lucinidae with molecular evidence for 73% of living genera

AbstractNew molecular phylogenies of the chemosymbiotic bivalve family Lucinidae, using 18S rRNA, 28S rRNA and cytochrome b genes, include species from genera not previously analysed. Notable additions from Myrteinae are sequences from Rostrilucina, Solelucina and Taylorina species, species of Ustalucina, Gonimyrtea from Leucosphaerinae and additional species of Ctena, Codakia, Lucinoma and Divalucina from Codakiinae. New sequences of Lucininae include the type species of Parvilucina (P. tenuisculpta), Liralucina, Falsolucinoma, Easmithia, Jallenia, Radiolucina and Cardiolucina as well as samples of Loripes orbiculatus from multiple localities. Five major clades, defined as subfamilies, are recognized: Pegophyseminae, Myrteinae, Leucosphaerinae, Codakiinae and Lucininae. Two branches, Fimbriinae and Monitilorinae, are represented by single species. Pegophyseminae are an extremely long-branched group with a sister-group relationship to Leucosphaerinae, while Codakiinae are a sister clade to the Lucininae. In various gene trees, the position of Myrteinae is unstable in relation to Pegophyseminae + Leucosphaerinae, Monitilorinae and Fimbriinae. The Myrteinae are not well resolved, with an ambiguous correlation of molecular and morphological characters. Codakiinae now include Divalucina cumingi, shown to be related to Lucinoma rather than Divaricella and Divalinga of the Lucininae. Leucosphaerinae are a well-supported clade but morphologically disparate, with the positions of Gonimyrtea and Callucina unresolved. Several molecularly distinct subclades are recognized within the Lucininae, especially the Lucinisca, Loripes and Parvilucina groups. Parvilucina species are paraphyletic with P. tenuisculpta, the type species, distinct from the western Atlantic species. Codakia, Ctena and Pegophysema have pan-tropical distributions with former connections disrupted by vicariant events of the closure of the eastern Tethyan and Central American Seaways. Species of Radiolucina, Pleurolucina and Lucinisca are present on either side of the Isthmus of Panama. A new classification of the 96 living lucinid genera is presented, providing a framework for future studies of systematics, ecology, biogeography and bacterial symbioses.

Portfolio concentration, portfolio inertia, and ambiguous correlation

When an investor is ambiguous about the asset returns' correlation and evaluates the portfolio in a multi-prior framework, we show that the optimal portfolio may contain only a fraction of risky assets. In particular, if the level of ambiguity is high enough, the optimal portfolio contains only the one with the highest Sharpe ratio. Moreover, we demonstrate that the optimal portfolio may be independent of feasible correlation matrices and may not change when the Sharpe ratios of some assets change. Ambiguity-aversion on correlation uncertainty explains portfolio concentration and portfolio inertia in household portfolios and retirement accounts, and the model can explain the growth of indexing and ETFs from an optimal portfolio choice perspective. We further show that these properties do not hold in an alternative smooth ambiguity model, suggesting that the smooth ambiguity model does not depart from the standard model sufficiently to explain portfolio concentration and portfolio inertia.

Особенности строения и нефтегазоносности осадочного бассейна Гвинейского залива

The article deals with the issues of the structure and development of the oil and gas content in the Guinea Gulf sedimentary basin located in the western regions of Africa and the Atlantic Ocean. The features of the basin formations are given that provided a complex structure and often ambiguous correlation of deposits. The factors that led to the development of the main hydrocarbon deposits in the province of the Niger Delta and other regions are identified. It is concluded that it is necessary to continue exploration work in the basin due to the increased prospects for oil and gas potential.

Gender Balance of University Professors: European Experience and Its Relevance for Russia

The article compares measures to support female teachers in universities in the UK, Germany and Russia with gender statistics from the OECD. An ambiguous correlation was revealed: the broader the measures to support female university teachers, the lower their share in higher education. The purpose of the work is to identify the reasons for this relationship. Within the framework of the hypothesis, the following thesis was put forward: high competition in higher education affects the decrease in the proportion of female teachers and forces the states to introduce a wide range of support tools to achieve gender balance. Comparison of the specifics of the spheres of higher education in the studied countries: R&D expenditures in the field of higher education and the working conditions of teachers (average salary, mobility, a specificity of contracts, hours worked, career opportunities) made it possible to identify the level of competition in universities. The obtained results confirmed the hypothesis about the direct influence of the level of competition on the share of female teachers in higher education. In conclusion, the relevance of the experience of European countries in building a gender balance among university teachers for Russia is considered. It is concluded that significant differences in the specifics of the sphere of higher education in Russia and the studied European countries, as well as the dominant share of female university teachers in our country, are not a sufficient reason for refusing to study foreign experience. On the contrary, the measures taken by the Government and the Ministry of Education and Science of Russia in recent years, if successfully implemented, will significantly increase the level of competition in the field of domestic higher education and the issue of gender balance will become relevant. In order to prevent a possible generational gap among female university teachers and the aggravation of the problem of gender balance in the future, it is necessary to study and adapt foreign experience, avoiding mistakes.

Machine Learning Based Preprocessing to Ensure Validity of Cross-Correlated Ultrasound Signals for Time-of-Flight Measurements

High precision ultrasonic time-of-flight measurement is a well known part of non-destructive evaluation used in many scientific and industrial applications, for example stress evaluation or defect detection. Although ultrasonic time-of-flight measurements are widely used there are some limitations where high noise and distorted ultrasonic signals are conflicting with the demand for high precision measurements. Cross-correlation based time-of-flight measurement is one strategy to increase reliability but also exhibits some ambiguous correlation states yielding to wrong time-of-flight results. To improve the reliability of these measurements a new machine learning based approach is presented based on experimental data collected on tightened bolts. Due to the complex structure of the bolts the ultrasonic signal is influenced by boundary conditions of the geometry which lead to high number of the ambiguous cross-correlation results in practice. In this particular application, bolts are in practice evaluated discontinuously and without knowledge of the time-of-flight in the unloaded condition which prevents the use of all other available comparative preprocessing techniques to detect time-of-flight shifts. Three different preprocessing strategies were investigated based on variations in the bolting configurations to ensure a machine learning based model capable of predicting the state of the cross-correlation function for different bolting parameters. With this approach, we achieve up to 100% classification accuracy for both longitudinal and transversal ultrasonic signals under laboratory conditions. In the future the method should be extended to become more robust and be applicable in real-time for industrial applications.

An Extended McKean — Vlasov Dynamic Programming Approach to Robust Equilibrium Controls under Ambiguous Covariance Matrix

This paper studies a general class of time-inconsistent stochastic control problems under ambiguous covariance matrix. The time-inconsistency is caused in various ways by a general objective functional and thus the associated control problem does not admit Bellman's principle of optimality. Moreover, we model the state by a McKean — Vlasov dynamics under a set of non-dominated probability measures induced by the ambiguous covariance matrix of the noises. We apply a game-theoretic concept of subgame perfect Nash equilibrium to develop a robust equilibrium control approach, which can yield robust time-consistent decisions. We characterize the robust equilibrium control and equilibrium value function by an extended optimality principle and then we further deduce a system of Bellman — Isaacs equations to determine the equilibrium solution on the Wasserstein space of probability measures. The proposed analytical framework is illustrated with its applications to robust continuous-time mean-variance portfolio selection problems with risk aversion coefficient being constant or state-dependent, under the ambiguity stemming from ambiguous volatilities of multiple assets or ambiguous correlation between two risky assets. The explicit equilibrium portfolio solutions are represented in terms of the probability law.

Limited Diversification, Portfolio Inertia, and Ambiguous Correlation

We study the effects of correlation ambiguity on portfolio choice in a market with multiple risky assets. We find that the optimal portfolio contains only a fraction of risky assets under correlation ambiguity, and in particular, just one risky asset enters the optimal portfolio if the level of correlation ambiguity is substantial. We demonstrate that the optimal portfolio does not change when assets’ Sharpe ratios change within a range. Our ambiguity-aversion model on correlation explains both the limited diversification property and the portfolio inertia property in household portfolios and retirement accounts. We further provide simulation evidences of the limited diversification and portfolio inertia feature of the optimal portfolio by a broad set of stocks. This paper suggests that correlation ambiguity has important implications for portfolio choice.

Quantitative characterization of low-rank coal reservoirs in the southern Junggar Basin, NW China: Implications for pore structure evolution around the first coalification jump

Abstract The assessment of coalbed methane (CBM) reservoirs can provide insights into the evolution of the pore structure systems around the first coalification jump (FCJ). The southern Junggar Basin, a typical low-rank coal-bearing basin in northwestern China, has been of interest to scientists and policy-makers due to its abundance of CBM resources and favourable conditions for CBM enrichment. A total of 28 coal samples from the Middle Jurassic Xishanyao Formation collected from 11 sampling sites in the central segment of the southern Junggar Basin were analyzed in this study. These samples were quantitatively characterized and comprehensively evaluated using macroscopic to nanometer-scale methods including macroscopic coal description, proximate analysis, vitrinite reflectance measurements, maceral analysis, low pressure nitrogen adsorption (LPNA), scanning electron microscopy (SEM), mercury intrusion porosimetry (MIP) and nuclear magnetic resonance (NMR). The results show that the Xishanyao low-rank coals are characterized by low moisture contents, low or low-medium ash yields (eastern and western parts), high volatile matter contents, moderate vitrinite contents, and high inertinite contents. The physical property of the Xishanyao coals generally displays heterogeneity, with the specific surface area, the total pore volume, the air permeability and the transverse relaxation time (T2) ranging from 0.116 to 15.983 m2/g, 0.461 × 10−3 to 13.37 × 10−3 cm3/g, 0.001 to 151.66 mD (0.987 × 10−6 to 0.149 μm2) and 1.44–174.22 ms, respectively. A new parameter, namely micropore volume proportion per unit nano-meter, is proposed. Micropore and transition pore volume per nm, specific surface area, total pore volume, DN1 and DN2 (LPNA fractal dimension) all first increase, then decrease and finally increase with rising coal rank, while the maximum and minimum values of the maximum vitrinite reflectance (Ro, max) occur at 0.58–0.59% and 0.65–0.66%. The boundary of Ro, max corresponding to the FCJ can be further defined from 0.5-0.6% to 0.58–0.59% based on the evolution of adsorption pore structures. Thus, pore structure parameters related to adsorption capacity are controlled predominantly by coal rank. In addition, tectonic deformation has a strong impact on seepage pore structure but only a slight impact on that of adsorption pore, which leads to an ambiguous correlation or a complex trend between mesopore, macropore content, DMIP (fractal dimension of MIP) and coal rank around the FCJ. This study reveals the complex variation of pore structure evolution of low-rank coals and the significant influence of the FCJ on physical properties of coalbed methane reservoirs.

P1610The genetic background of the disease in a group of patients with severe course of hypertrophic cardiomyopathy

Abstract Background End-stage hypertrophic cardiomyopathy (esHCM) indicates the most progressive form of HCM with progression to left ventricle remodeling and systolic dysfunction and is common indication to heart transplant. It affects 2.4–15.7% of HCM cases and is associated with a poor prognosis (mortality in this group of patients reaches 11%). Purpose In this study patients with esHCM were investigated using next generation sequencing in order to examine the genetic causes of the most severe course of the disease. Despite huge amount of data from many studies, a clear genotype-phenotype correlation is still lacking and predictive value of genetic testing is sometimes undermined. However, there is an ongoing need for a prediction factors in HCM patients. Methods Fifty seven patients (21 male, 36.8%) with esHCM were genetically investigated with next generation sequencing of a TruSight Cardio panel by Illumina that provides coverage of 174 genes with known associations to cardiac conditions including cardiomyopathies (n=52) or custom panel of 35 cardiomyopathies genes (n=5). Results Disease-causing variants where found in 47 probands (82.5%). Thirty-two probands (77.2%) had a single pathogenic or potentially pathogenic mutation in one of the sarcomeric genes: MYBPC3 (13, 22.8%), MYH7 (11, 19.3%), TNNT2 (3, 5.3%), TNNI3 (3, 5.3%), MYL3 (1, 1.8), TPM1 (1, 1.8%). In 13 (22.8%) probands we found a double mutation: in 7 (12.3) both variants sarcomeric (MYBPC3 and TNNT2 with MYH7, MYBPC3 and ACTA1) and in 5 (8.8%) one sarcomeric and the second non-sarcomeric cardiomyopathy variant (BAG3, ILK, PRKAG2, RBM20, SCN5A). In 3 (5.3%) probands we identified mutations or potentially disease-causing variants in genes associated Danon disease (LAMP2), glycogen storage disease of heart (PRKAG2) and double mutation FHL1 + PTPN11 (myopathy/Emery-Dreifuss muscular dystrophy and Noonan syndrome). In 10 (17.5%) patients, genetic examination did not reveal a candidate for disease-causing mutation. Surprisingly, a half of them had documented familial history of the disease. The majority of mutations in MYBPC3 were truncating variants (14/18, 78%). Thirty-three probands (57.9%) had a heart transplant or qualification to the procedure. Conclusion Despite a similar background of typical HCM and esHCM and still ambiguous genotype-phenotype correlation, results may indicate that certain mutations (and not genes) may determine a more severe course of the disease. The majority of truncating variants in MYBPC3 gene may suggest their very strong impact on the course of the disease. Also, 3 neighboring variants in TNNT2 gene indicate a hot spot region for esHCM in our population. As expected, in single cases esHCM was related to specific non-sarcomeric genes (LAMP2, PRKAG2, FHL1). 17.5% of unsolved cases suggests that in such cases whole exome/genome sequencing might be needed to recognize the disease-causing mutation, especially when disease is familial. Acknowledgement/Funding This work was supported by a grant 2.7/II/17 from the Institute of Cardiology, Warsaw, Poland.

On dealing with multiple correlation peaks in PIV

A novel algorithm to analyse PIV images in the presence of strong in-plane displacement gradients and reduce sub-grid filtering is proposed in this paper. Interrogation windows subjected to strong in-plane displacement gradients often produce correlation maps presenting multiple peaks. Standard multi-grid procedures discard such ambiguous correlation windows using a signal to noise (SNR) filter. The proposed algorithm improves the standard multi-grid algorithm allowing the detection of splintered peaks in a correlation map through an automatic threshold, producing multiple displacement vectors for each correlation area. Vector locations are chosen by translating images according to the peak displacements and by selecting the areas with the strongest match. The method is assessed on synthetic images of a boundary layer of varying intensity and a sinusoidal displacement field of changing wavelength. An experimental case of a flow exhibiting strong velocity gradients is also provided to show the improvements brought by this technique.

Robust Markowitz mean‐variance portfolio selection under ambiguous covariance matrix

AbstractThis paper studies a robust continuous‐time Markowitz portfolio selection problem where the model uncertainty affects the covariance matrix of multiple risky assets. This problem is formulated into a min–max mean‐variance problem over a set of nondominated probability measures that is solved by a McKean–Vlasov dynamic programming approach, which allows us to characterize the solution in terms of a Bellman–Isaacs equation in the Wasserstein space of probability measures. We provide explicit solutions for the optimal robust portfolio strategies and illustrate our results in the case of uncertain volatilities and ambiguous correlation between two risky assets. We then derive the robust efficient frontier in closed form, and obtain a lower bound for the Sharpe ratio of any robust efficient portfolio strategy. Finally, we compare the performance of Sharpe ratios for a robust investor and for an investor with a misspecified model.

Ambiguous Correlation

Ambiguous Correlation

Pre-event water contributions and streamwater residence times in different land use settings of the transboundary mesoscale Lužická Nisa catchment

AbstractThe objective of the study was to evaluate the spatial distribution of peakflow pre-event water contributions and streamwater residence times with emphasis on land use patterns in 38 subcatchments within the 687 km2large mesoscale transboundary catchment Lužická Nisa. Mean residence times between 8 and 27 months and portions of pre-event water between 10 and 97% on a storm event peakflow were determined, using18O data in precipitation and streamwater from a weekly monitoring of nearly two years. Only a small tracer variation buffering effect of the lowland tributaries on the main stem was observed, indicating the dominant impact on the mountainous headwaters on the runoff generation. Longest mean streamwater residence times of 27 months were identified in the nearly natural headwaters of the Jizera Mountains, revealing no ambiguous correlation between the catchment area and altitude and the mean residence time of streamwater. Land use control on the pre-event water portions were determined for three land use categories with percentage of urban areas from 0 to 10%, 10 to 20% and more than 20%. The fraction of pre-event water in the first category decreases from 97% to 65% with the increasing percentage of forest from 76% to 100%, revealing that forests may provide only a limited infiltration of precipitation due to leaf interception and soil water use for transpiration. Fractions of pre-event water of 39–87% in the second (agricultural catchments) and of 10–35% in the third (urbanized catchments) category increase with percentage of non-urban areas.