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The primary and secondary fragmentation dynamics of iodobenzene following its ionization at 120 eV were determined using three-dimensional velocity map imaging and covariance analysis. Site-selective iodine 4d ionization was used to populate a range of excited polycationic parent states, which primarily broke apart at the carbon-iodine bond to produce I+ with phenyl or phenyl-like cations (C n H x + or C n H x 2 + , with n = 1 – 6 and x = 1 – 5). The molecular products were produced with varying degrees of internal excitation and dehydrogenation, leading to stable and unstable outcomes. This further allowed the secondary dynamics of C 6 H x 2 + intermediates to be distinguished using native-frame covariance analysis, which isolated these processes in their own centre-of-mass reference frames. The mass resolution of the imaging mass spectrometer used for these measurements enabled the primary and secondary reaction channels to be specified at the level of individual hydrogen atoms, demonstrating the ability of covariance analysis to comprehensively measure the competing fragmentation channels of aryl cations, including those involving intermediate steps. [ABSTRACT FROM AUTHOR]

The cross section of 85Rb(n,2n)84mRb and 85Rb(n,p)85mKr reactions were measured at neutron energy range 12–20 MeV using activation analysis followed by off-line γ-ray spectroscopic technique. The quasi mono-energetic neutrons were produced through 7Li(p,n)7Be reaction. The measurements were done relative to 27Al(n,α)24Na reference monitor reaction cross section. The detailed uncertainty propagation from the attributes present in measurements was performed using covariance analysis. The γ-ray self-attenuation and background low neutron energy corrections were performed in the measurement studies. Theoretical calculations were performed by TALYS-1.96 nuclear code. The comparison of measured values with the available data in EXFOR database and evaluated data from JENDL-5 and EAF-2010 shows the measured cross section values of 85Rb(n,p)85mKr reaction were slightly higher than the published values, evaluated data and theoretical data while for 85Rb(n,2n)84mRb, the measured values were consistent with the published data. [ABSTRACT FROM AUTHOR]

We develop candidate hybrid models representing the spatial distribution of earthquake occurrence in New Zealand over the next 100 yr. These models are used within the onshore/near-shore, shallow component of the distributed seismicity model within the New Zealand National Seismic Hazard Model 2022. They combine a variety of spatially gridded covariates based on smoothed seismicity, strain rates, and proximity to mapped faults and plate boundaries in both multiplicative and additive hybrids. They were optimized against a standardized catalog of New Zealand earthquakes with magnitude M ≥ 4.95 and hypocentral depth ≤40 km from 1951 to 2020. We extract smoothed seismicity covariates using three different methods. The additive models are linear combinations of earthquake likelihood models derived from individual covariates. We choose three preferred hybrid models based on the information gain statistics, consideration of the ongoing Canterbury sequence and regions of low seismicity, and inclusion of the most informative covariates. Since the hazard model is designed for the next 100 yr, the preferred hybrid models are also combined with 20-year earthquake forecasts from the "Every Earthquake a Precursor According to Scale" model. Thus, in total, six hybrid spatial distribution candidates are advanced for sensitivity analyses and expert elicitation for inclusion in the final logic tree for the New Zealand National Seismic Hazard Model. [ABSTRACT FROM AUTHOR]

Maintaining a consistent relationship between each footfall and the body's motion is a key mechanism to maintain balance while walking. However. environmental features, for example, puddles/obstacles, impose additional constraints on foot placement. This study investigated how healthy young individuals alter foot placements to simultaneously manage body-centric and environmental constraints during an obstacle-crossing task. Consistent step length promotes balance for all steps. whereas accurate foot placement around the obstacle is essential to avoid a trip. While crossing an obstacle, any error in positioning one foot relative to the obstacle can be compensated by selecting the placement of the subsequent step. However, compensation will necessarily alter step length from its average value. The interstep covariance index computed from two consecutive foot placements was used to quantify this tradeoff between body-centric and environmental constraints for six consecutive steps while approaching, crossing. and resuming unobstructed gait after crossing the obstacle. The index declined only when either one or both feet were adjacent to the obstacle. The decline was driven in part by a tendency toward higher step length variability. Thus, changes in the stepping patterns to address the environmental constraint occurred at the cost of the bodycentric constraint. However, the step length never ceased to be controlled; the interstep covariance index was positive for all steps. Overall, participants adapted foot placement control to account for the larger threat to balance. The environmental constraint was prioritized only when a potential trip posed greater threat to balance compared with the threat posed by variable step length. [ABSTRACT FROM AUTHOR]

This research introduces an innovative protection methodology designed to discriminate between disturbance events and asymmetrical/symmetrical faults within a microgrid (MG). The proposed methodology integrates a detection method utilizing covariance analysis of wavelet transform coupled with the sum of absolute differences approach and a fault classification method based on a fuzzy logic controller (FLC). The methodology leverages the advantages of covariance analysis, facilitating a straightforward demonstration of fault presence through the relationships among phases. In addition, a well-defined procedure effectively distinguishes between disturbance and asymmetrical/symmetrical events, accurately identifying the faulted phase(s) through FLC. The efficiency of the presented protection methodology is further enhanced when complemented with the identification of disturbance events. A comprehensive evaluation is conducted under diverse conditions, including variations in fault resistance, fault inception angle, and fault location. Furthermore, the methodology's performance is validated through the consideration of fluctuating solar irradiance levels and source strength variations. To verify the robustness and applicability of the proposed protection methodology, various scenarios involving an unbalanced network model, nonlinear load, uncertain parameter variations, and measurement noise are systematically addressed. The methodology's effectiveness has been demonstrated through extensive evaluation on grid-connected MG with both radial and mesh topologies. Finally, the application of this protection methodology to islanded MG is discussed, exploring potential effects and highlighting the versatility of the proposed approach. This study improves MG protection strategies by emphasizing the adaptability and efficacy of the proposed methodology in a variety of operational scenarios. [ABSTRACT FROM AUTHOR]

The E6 and E7 proteins of the high risk human papillomaviruses (HR HPVs) play a key role in the oncogenesis associated with papillomavirus infection. Data on the variability of these proteins are limited, and the factors affecting their variability are still poorly understood. We analyzed the variability of the currently known sequences of the HPV type 16 (HPV16) E6 and E7 proteins, taking into account their geographic origin and year of sample collection, as well as the direction of their evolution in the major geographic regions of the world. All sequences belonging to HPV16 genome fragments encoding the E6 and E7 oncoproteins were downloaded from the NCBI GenBank database on October 6, 2022. Samples were filtered according to the following parameters: the sequence has to include at least one of the two whole open reading frames, and given date of collection, and the country of origin. A total of 3651 full-genome nucleotide sequences encoding the E6 protein and 4578 full-genome nucleotide sequences encoding the E7 protein were sampled. The nucleotide sequences obtained after sampling and alignment were converted to amino acid sequences and analyzed using the MEGA11, R, RStudio, Jmodeltest 2.1.20, BEAST v1.10.4, Fastcov, and Biostrings software. The highest variability in the E6 protein was recorded for amino acid (AA) residues in the positions 17, 21, 32, 85, and 90. The most variable in E7 were aa positions 28, 29, 51, and 77. The samples were divided geographically into five heterogeneous groups as derived from Africa, Europe, America, South-West and South Asia, and South-East Asia. Unique amino acid substitutions (AA-substitutions) in the E6/E7 proteins of HPV16, presumably characteristic to certain ethnic groups, were identified for a number of countries. They weare mainly localized in the sites of known B- and T-cell epitopes and relatively rarely the domains critical for in structure and protein function. The revealed differences in AA-substitutions in different ethnic groups and their colocalization with the clusters of B- and T-cell epitopes suggested their possible relation to the geographical distribution of alleles and haplotypes of the major histocompatibility complex (HLA). This may lead to the recognition of a different set of B- and T-cell epitopes of the virus in different geographic areas, resulting in the regional differences in the direction of epitopic drift. Phylogenetic analysis of the nucleotide sequences encoding the E6 protein of HPV16 revealed a common ancestor, confirmed regional clustering of the E6 protein sequences sharing common AA-substitutions, and identified cases of reversion of individual AA-substitutions when the change of geographical localization. For the E7 protein, such analysis was not possible due to the high sequence homology. Covariance analysis of the pooled of E6 and E7 sequences revealed that there was no associations between amino acid residues in any aa position within E6 or E7 as well as aa positions of E6 and E7 proteins. The data presented here are important for the development of universal therapeutic vaccines against HPV of high carcinogenic risk. [ABSTRACT FROM AUTHOR]

In the present work, we investigate the bulk properties of nuclear matter and neutron stars with the newly proposed relativistic interaction NL-RS which provides an opportunity to readjust the coupling constants keeping in view the properties of finite nuclei, nuclear matter, PREX-II results for neutron skin thickness in 208Pb and astrophysical observations. The NL-RS model interaction has been proposed by fitting the ground state properties (binding energies and charge radii) of finite nuclei, bulk nuclear matter properties, and PREX-II results for neutron skin thickness of 208Pb. The relativistic interaction has been generated by including nonlinear self-interactions of σ and ω μ -mesons and mixed interactions of ω μ , and ρ μ -meson up to the quartic order. The proposed interaction harmonizes with the finite nuclei, bulk nuclear matter, and neutron star properties. A covariance analysis is performed to assess the statistical uncertainties on the model parameters and nuclear observables of interest along with correlations amongst them. The equation of state (EoS) composed of nucleons and leptons in β -equilibrium is computed with the proposed parameter set and used to study the neutron star structure. The maximum mass of the neutron star by employing the EoS computed with the NL-RS parameter set is 2.04 ± 0.03 M ⊙ and the radius of a canonical mass neutron star (R 1.4) comes out to be equal to 13.06 ± 0.16 Km. The value of dimensionless tidal deformability, for canonical mass, is 602.23 ± 33.13 which satisfies the constraints of waveform models analysis of GW170817 within 90% confidence level. [ABSTRACT FROM AUTHOR]

Excitation functions of alpha-particle induced nuclear reactions on natSn have been presented in the 11–40 MeV energy range. In the present study, the stacked-foil activation technique followed by offline gamma-ray spectrometry was used to measure the production of 119Te, 121Te, 122Sb and 126Sb from alpha-particle induced reactions on natSn. The TALYS nuclear code was used to calculate the theoretical predictions of the excitation functions of natSn(α,x) nuclear reactions. The measured data of the above-mentioned nuclear reactions were compared with the theoretical predictions and the experimental results available from EXFOR. In this study, covariance analysis was performed to calculate the uncertainty propagation in the measured cross sections. [ABSTRACT FROM AUTHOR]

This letter introduces a novel integrated framework for simultaneous localization and mapping (SLAM) tailored for general agricultural applications. The framework combines a cutting‐edge SLAM method, LIO‐SAM, with covariance intersection for sensor fusion. Agricultural robots often operate in unstructured environments with sparse feature points and encounter repeated similar information, such as trees. Therefore, a fusion framework based on 3D SLAM augmented with additional information, such as feature‐independent GPS data, becomes essential. This study proposes an integrated SLAM framework by introducing a convergence strategy based on covariance analysis, incorporating a state‐of‐the‐art 3D SLAM technique. The convergence methods, namely "dynamic weight assignment" and "winner takes all", are presented alternatively, tailored to seamlessly integrate with the proposed framework. Evaluations using a public dataset and an experiment demonstrate the effectiveness of the approach through numerical analysis and visual representation. The results illustrate that this method surpasses conventional approaches in accurately estimating the robot's position. In the future, this research will focus on automating crop cultivation and harvesting by integrating the proposed system with robot arm control. [ABSTRACT FROM AUTHOR]

This paper introduces a data-driven approach to address the long-standing challenge of modeling complex tensegrity systems. The proposed approach focuses on approximating unknown black box systems and estimating their output error covariance using input/output (IO) information. First, an approximation system that mirrors the input–output relation of the black box system is obtained. Next, output error covariance between the approximation and the black box system is calculated, which evaluates the accuracy of the identified model. This two-step approach relies exclusively on the black box system's Markov parameter sequence, eliminating the need for dynamics knowledge of the system. Nonlinear examples of a NACA 2412 tensegrity morphing airfoil and a 3D tensegrity prism are studied for validation. The proposed approach successfully identified approximation systems in state space realization in both cases with insignificant output error covariances. Compared to the widely-used Mode Displacement Method (MDM), the proposed approach exhibits an advantage in identifying velocity outputs for tensegrity systems. The developed approach in this paper applies to other tensegrity structures and structural identification problems. [ABSTRACT FROM AUTHOR]

Random vibration analysis is a mathematical tool that offers great advantages in predicting the mechanical response of structural systems subjected to external dynamic loads whose nature is intrinsically stochastic, as in cases of sea waves, wind pressure, and vibrations due to road asperity. Using random vibration analysis is possible, when the input is properly modeled as a stochastic process, to derive pieces of information about the structural response with a high quality (if compared with other tools), especially in terms of reliability prevision. Moreover, the random vibration approach is quite complex in cases of non-linearity cases, as well as for non-stationary inputs, as in cases of seismic events. For non-stationary inputs, the assessment of second-order spectral moments requires resolving the Lyapunov matrix differential equation. In this research, a numerical procedure is proposed, providing an expression of response in the state-space that, to our best knowledge, has not yet been presented in the literature, by using a formal justification in accordance with earthquake input modeled as a modulated white noise with evolutive parameters. The computational efforts are reduced by considering the symmetry feature of the covariance matrix. The adopted approach is applied to analyze a multi-story building, aiming to determine the reliability related to the maximum inter-story displacement surpassing a specified acceptable threshold. The building is presumed to experience seismic input characterized by a non-stationary process in both amplitude and frequency, utilizing a general Kanai–Tajimi earthquake input stationary model. The adopted case study is modeled in the form of a multi-degree-of-freedom plane shear frame system. [ABSTRACT FROM AUTHOR]

Predicting clinical response to repetitive transcranial magnetic stimulation (rTMS) in medication-resistant depression (MRD) has gained great importance in recent years. Mainly, the right subgenual anterior cingulate cortex (sgACC) functional connectivity has been put forward as biomarker in relation to rTMS clinical outcome. Even though the left and right sgACC may have different neurobiological functions, little is known about the possible lateralized predictive role of the sgACC in rTMS clinical outcome. In 43 right-handed antidepressant-free MRD patients, we applied a searchlight-based interregional covariance connectivity approach using the baseline 18FDG-PET scan—collected from two previous high-frequency (HF)-rTMS treatment studies delivering stimulation to the left dorsolateral prefrontal cortex (DLPFC)—and investigated whether unilateral or bilateral sgACC glucose metabolism at baseline would result in different predictive metabolic connectivity patterns. Regardless of sgACC lateralization, the weaker the sgACC seed-based baseline metabolic functional connections with the (left anterior) cerebellar areas, the significantly better the clinical outcome. However, the seed diameter seems to be crucial. Similar significant findings on sgACC metabolic connectivity with the left anterior cerebellum, also unrelated to sgACC lateralization, in relation to clinical outcome were observed when using the HCPex atlas. Although we could not substantiate that specifically right sgACC metabolic connectivity would predict HF-rTMS clinical outcome, our findings suggest considering the entire sgACC in functional connectivity predictions. Given that the interregional covariance connectivity results were significant only when using the Beck Depression Inventory (BDI-II) and not with the Hamilton Depression Rating Scale (HDRS), our sgACC metabolic connectivity observations also suggest the possible involvement of the (left) anterior cerebellum involved in higher-order cognitive processing as part of this predictive value. [ABSTRACT FROM AUTHOR]

With the increase of the number of decision variables, cooperative coevolution algorithm is easy to fall into local optimization in the process of searching the global optimal solution in large-scale high-dimensional optimization problems.Based on this, a cooperative coevolution algorithm with covariance analysis for differential evolution was proposed.After the optimization problems were grouped according to the correlation between the decision variables, the correlation between the internal variables of the subcomponents would affect the population evolution process.In the process of subcomponent optimization, covariance was used to calculate the characteristic vector of population distribution, and the correlation between variables was eliminated through coordinate rotation, which effectively avoided falling into local optimization in the process of population search and speeded up the optimization speed of the algorithm.Comparative experiments were carried out on the CEC 2014 test suite.The experimental results show that the proposed algorithm is feasible.

The internal ribosome entry site (IRES) RNA of bovine viral diarrhoea virus (BVDV), an economically significant Pestivirus, is required for the cap-independent translation of viral genomic RNA. Thus, it is essential for viral replication and pathogenesis. We applied a combination of high-throughput biochemical RNA structure probing (SHAPE-MaP) and in silico modelling approaches to gain insight into the secondary and tertiary structures of BVDV IRES RNA. Our study demonstrated that BVDV IRES RNA in solution forms a modular architecture composed of three distinct structural domains (I–III). Two regions within domain III are represented in tertiary interactions to form an H-type pseudoknot. Computational modelling of the pseudoknot motif provided a fine-grained picture of the tertiary structure and local arrangement of helices in the BVDV IRES. Furthermore, comparative genomics and consensus structure predictions revealed that the pseudoknot is evolutionarily conserved among many Pestivirus species. These studies provide detailed insight into the structural arrangement of BVDV IRES RNA H-type pseudoknot and encompassing motifs that likely contribute to the optimal functionality of viral cap-independent translation element.

The objective of this study was to verify the efficiency of using the plant stand covariate to adjust the average grain yield of common bean genotypes. Sixteen years of experiments were considered. In all years, the genetic treatments were randomized in field in a completely randomized block design. The main variable grain yield and the covariate plant stand per observation unit were evaluated. The information was submitted to analysis of variance and covariance. In approximately half of the trials (43.75%), the mean square of treatments was significant in both analyses, indicating the small improvement of the model when plant stand was included as a covariate. This information is confirmed by estimate of covariate efficiency, since in just two years (2017 and 2015) the adjustments were effective (268 and 203%, respectively). In addition, an association was observed between the average grain yield and adjustment efficiency of -0.60. Thus, the covariate was useful in years when the genotypes showed low productive performance, possibly caused by adverse environmental conditions. These conditions are responsible for plants heterogeneity number in the observation units. [ABSTRACT FROM AUTHOR]

Random vibration analysis is a mathematical tool that offers great advantages in predicting the mechanical response of structural systems subjected to external dynamic loads whose nature is intrinsically stochastic, as in cases of sea waves, wind pressure, and vibrations due to road asperity. Using random vibration analysis is possible, when the input is properly modeled as a stochastic process, to derive pieces of information about the structural response with a high quality (if compared with other tools), especially in terms of reliability prevision. Moreover, the random vibration approach is quite complex in cases of non-linearity cases, as well as for non-stationary inputs, as in cases of seismic events. For non-stationary inputs, the assessment of second-order spectral moments requires resolving the Lyapunov matrix differential equation. In this research, a numerical procedure is proposed, providing an expression of response in the state-space that, to our best knowledge, has not yet been presented in the literature, by using a formal justification in accordance with earthquake input modeled as a modulated white noise with evolutive parameters. The computational efforts are reduced by considering the symmetry feature of the covariance matrix. The adopted approach is applied to analyze a multi-story building, aiming to determine the reliability related to the maximum inter-story displacement surpassing a specified acceptable threshold. The building is presumed to experience seismic input characterized by a non-stationary process in both amplitude and frequency, utilizing a general Kanai–Tajimi earthquake input stationary model. The adopted case study is modeled in the form of a multi-degree-of-freedom plane shear frame system.

Bitter gourd (Momordica charantia L.) is a significant vegetable. Although it has a special bitter taste, it is still popular with the public. The industrialization of bitter gourd could be hampered by a lack of genetic resources. The bitter gourd's mitochondrial and chloroplast genomes have not been extensively studied. In the present study, the mitochondrial genome of bitter gourd was sequenced and assembled, and its substructure was investigated. The mitochondrial genome of bitter gourd is 331,440 bp with 24 unique core genes, 16 variable genes, 3 rRNAs, and 23 tRNAs. We identified 134 SSRs and 15 tandem repeats in the entire mitochondrial genome of bitter gourd. Moreover, 402 pairs of repeats with a length greater than or equal to 30 were observed in total. The longest palindromic repeat was 523 bp, and the longest forward repeat was 342 bp. We found 20 homologous DNA fragments in bitter gourd, and the summary insert length was 19,427 bp, accounting for 5.86% of the mitochondrial genome. We predicted a total of 447 potential RNA editing sites in 39 unique PCGs and also discovered that the ccmFN gene has been edited the most often, at 38 times. This study provides a basis for a better understanding and analysis of differences in the evolution and inheritance patterns of cucurbit mitochondrial genomes. [ABSTRACT FROM AUTHOR]

The nuclear reaction cross sections for 110Pd(n,2n)109mPd, 102Pd(n,2n)101Pd, 106Pd(n,p)106mRh, 110Pd(n,2n)109gPd and 105Pd(n,p)105Rh have been measured at the neutron energy of 14.77 ± 0.17 MeV by using the method of activation and off-line γ-ray spectrometry. The uncertainties in the various nuclear parameters in the measured reactions and their correlations were estimated by using covariance analysis. The present data were compared with literature data from the EXFOR database and nuclear data libraries, including ENDF/B-VIII.0, JEFF-3.3, JENDL-5.0 and TENDL-2021. Theoretical model calculations for the cross-sections are performed with the TALYS-1.96 nuclear model code with optimized parameters. There is good agreement between the measured, literature and evaluated data. The results are important for shielding applications in the radiation fields involving neutrons. • Cross sections of (n,2n) and (n,p) nuclear reactions for Pd isotopes at 14.77 MeV energy. • Covariance analysis of the measured cross sections for uncertainty and correlation. • Theoretical nuclear model calculations for the nuclear reactions performed with TALYS-1.96 code. • The experimental results compared with literature data and evaluated nuclear data. • The measured cross sections are important for shielding applications and nuclear data. [ABSTRACT FROM AUTHOR]

Neutron induced reaction cross sections play an important role in nuclear science and technology research, such as national defense, nuclear energy construction and development, nuclear medicine, radiation protection and nuclear safety. With the rapid development of nuclear technology, there are increasing demand for the variety and accuracy of neutron data. As an important structure material nuclide, the accuracy of neutron induced reaction cross section on 56Fe is directly related to the design and operation of reactors, spent fuel disposal and miniaturization design, and also of great significance to nuclear physics basic research. The 56Fe(n,p)56Mn reaction is usually used as the standard to monitor the neutron field flux in the experiment. It greatly influences the results of nuclear data measurement, and also has guiding significance for upon carry the determination of the parameters in the nuclear reaction model. Due to the obvious differences existing in the previous experimental data and inconsistency between the evaluation databases, the experimental measurement data evaluation and covariance analysis were carried out for the 56Fe(n,p)56Mn reaction cross section in this paper. Firstly, the existing experimental measurement data of 56Fe(n,p)56Mn reaction cross section in EXFOR and literature were downloaded and systematically collected, then summarized, contrasted, and classified in terms of neutron source, measurement method, detector kinds, etc. Secondly, the data with low reliability were discarded with checking the original papers, and the uncertainty mentioned in these papers was also analyzed. Additionally, previous experimental results which using the imprecise values were adjusted and modified with the more accurate data such as recently ratios, supervised reaction standard cross sections, and isotopic abundances. The data with significant divergence near 14 MeV were normalized, which made it more concentrated and less divergent. The polynomial curve fitting was applied to obtain the excitation curve of 56Fe(n,p)56Mn reaction between 29535 MeV which was derived from the corrected and normalized results. Following that, the correlation covariance matrix was calculated for the suggested experimental data after evaluation. Meanwhile, the energy density, optical potential parameters, energy level density parameters, and other parameters of 56Fe(n,p)56Mn reaction were adjusted within the physical model calculated by the nuclear reaction simulation program TALYS. Finally, the reaction cross section of 56Fe(n,p)56Mn was computed theoretically, compared with experimental data and evaluation databases. This paper broadened the existing evaluation method of neutron activation reaction cross section experimental data, and also improved the accuracy of the assessment data for neutroninduced 56Fe(n,p)56Mn reaction cross section measured data below 35 MeV. The recommended assessment value and its covariance of the 56Fe(n,p)56Mn reaction excitation function were given based on the evaluted results of experimental data. Excitation function input file for 56Fe(n,p)56Mn reaction derived by adjusting the TALYS parameters agree well with the experimental and evaluation data. A set of standard assessment techniques were constructed, which serves as a guide for theoretical calculation and database construction of related nuclear data.

With the increase of the number of decision variables, cooperative coevolution algorithm is easy to fall into local optimization in the process of searching the global optimal solution in large-scale high-dimensional optimization problems. Based on this, a cooperative coevolution algorithm with covariance analysis for differential evolution was proposed. After the optimization problems were grouped according to the correlation between the decision variables, the correlation between the internal variables of the subcomponents would affect the population evolution process. In the process of subcomponent optimization, covariance was used to calculate the characteristic vector of population distribution, and the correlation between variables was eliminated through coordinate rotation, which effectively avoided falling into local optimization in the process of population search and speeded up the optimization speed of the algorithm. Comparative experiments were carried out on the CEC 2014 test suite. The experimental results show that the proposed algorithm is feasible. [ABSTRACT FROM AUTHOR]

• The angles-only navigation and closed-loop guidance control for spacecraft autonomous noncooperative rendezvous are studied, and a multi-objective optimization model is established considering various constraints. • The closed-loop guidance control covariance is analyzed, and the navigation and control covariance analysis models are established. • A crowding mechanism based on vector space model (VSM) is proposed to improve the NSGA-II, and a VSM-NSGA-II is constructed to solve the proposed multi-objective optimization model. • A set of Pareto optimal solutions are simulated and analyzed by using closed-loop guidance control covariance analysis and Monte Carlo simulation, thereby proving the effectiveness of the multi-objective optimization model proposed in this paper. In this paper, the angles-only navigation and closed-loop guidance control for spacecraft autonomous noncooperative rendezvous in geosynchronous Earth orbit (GEO) are studied, and a multi-objective optimization model is established considering various constraints. The optimization objectives include the total flight time, the total fuel cost, and the observability of angles-only navigation. First of all, the angles-only navigation model is established, including relative dynamics and Line-of-Sight (LoS) measurement models. Then, the closed-loop guidance control covariance is analyzed, and the navigation and control covariance analysis models are established. And then, a multi-objective optimization model is established, including the objective functions, optimization variables, constraints, and the mathematical model. After that, a crowding mechanism based on vector space model (VSM) is proposed to improve the fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II, and a VSM-NSGA-II is constructed to solve the proposed multi-objective optimization model. Finally, a set of Pareto optimal solutions are simulated and analyzed by using closed-loop guidance control covariance analysis and Monte Carlo simulation, thereby proving the effectiveness of the multi-objective optimization model proposed in this paper. [ABSTRACT FROM AUTHOR]

Owing to the contagiousness of theft behaviors among customers, collaborative energy theft, such as village fraud, has become particularly common. In this study, a bunch of electricity thieves that steal energy at a constant ratio were considered. Conventional correlation-sorting-based methods may have some trouble handling these electricity thieves when they exist in the same area. To overcome such limitation, we firstly establish the mathematical model of non-technical loss (NTL) and the load data of fixed ratio electricity thieves (FRETs). Subsequently, an interesting correlation trend, which can be exploited to locate FRETs, was observed and analyzed. Based on this trend, we propose a correlation analysis-based detection method. It adopts a standardized covariance to measure the correlation between the NTL and user data. The detection of FRETs is realized by solving a combinatorial optimization problem. A corresponding framework in practice was also designed. Finally, numerical experiments based on a realistic dataset and an electricity theft dataset from an electricity theft emulator (ETE) are conducted to validate the effectiveness and superiority of the proposed method in terms of accuracy, stability, and scalability.

Strapdown inertial navigation usually relies on the extended Kalman filter (EKF) as the workhorse, which requires a proper initialization of the attitude. The optimization-based alignment (OBA) approach is widely employed to provide the coarse attitude information for the subsequent fine alignment or navigation stage by EKF. However, there still lacks a reliable quality index to assess the attitude accuracy of OBA. To tackle this problem, this article characterizes the OBA attitude error by vector measurement errors. For specific applications, such as the stationary alignment and odometer/GPS-aided in-motion alignment, the errors of vector measurements in OBA are further formulated in terms of raw sensor errors of gyroscopes, accelerometers, and odometer/GPS velocities. The covariance of attitude errors is analytically derived. Simulations and field experiments are performed to verify the covariance analysis. [ABSTRACT FROM AUTHOR]

Long-term configuration stability is essential for a space-based gravitational-wave observatory, which can be affected by orbit insertion errors. This paper investigated the stability of a geocentric gravitational-wave observatory from the view of the configuration uncertainty propagation. The effects of the orbit insertion errors on the configuration stability are propagated using the Unscented Transformation (UT). The best UT tuning factor is selected based on the accuracy analysis of different UT tuning factors. The effects of the position and velocity insertion errors in different directions are firstly discussed. Compared with the Monte Carlo simulations, the UT method has relative errors of no more than 2.7%, while the time cost is only 3.6%. It is found that the radial position and tangential velocity insertion errors have the largest influence on the configuration stability. Finally, based on the proposed method, the stability domain of the geocentric space gravitational-wave detection constellation is investigated by considering two kinds of insertion errors, i.e., independent and identically distributed insertion errors and insertion errors in spatial directions. The analysis results in this paper can be potentially useful for the configuration design of a geocentric gravitational-wave observatory. [ABSTRACT FROM AUTHOR]

Natural silver targets were irradiated using an alpha particle beam to measure the activation cross sections of radioisotopes within the energy range of 23–40 MeV. The newly obtained cross section data, compared with previous experimental results, underline the importance of this work in the context of nuclear reactions and medical applications. Alpha particle induced reaction with n a t Ag involved the production of radioisotopes such as 111In, 105Ag, 106 m Ag. In this study, we focused on calculating correlation matrices for the n a t Ag(α ,x) nuclear reactions. These matrices were generated by considering various interconnected variables, such as decay constants, particle number densities, γ -ray intensities and detector efficiencies for both monitor and sample nuclear reaction products. [ABSTRACT FROM AUTHOR]

This paper presents a robust trajectory design method for approaching and rendezvous with a space target considering multi-source uncertainties. A nonlinear covariance analysis method based on the state transition tensor is presented to formulate the propagation of uncertainties including environment parameter uncertainty, actuator error, sensor noise, navigation error and initial state dispersion of the closed-loop GN&C system. Then, the robust trajectory design problem is defined based on the quantified effect of the uncertainties, and an improved self-adaptive differential evolution algorithm is presented to solve the robust trajectory design problem with uncertainties. Finally, four groups of numerical simulations are carried out to show that the designed robust trajectories can satisfy the final state dispersion constraint under multi-source uncertainties. [ABSTRACT FROM AUTHOR]

Least-squares collocation (LSC) is a widely used method applied in physical geodesy to separate observations into a signal and noise part but has received only little attention when interpolating velocity fields. The advantage of the LSC is the possibility to filter and interpolate as well as extrapolate the observations. Here, we will present several extensions to the traditional LSC technique, which allows the combined interpolation of both horizontal velocity components (horizontal velocity (HV)-LSC), the separation of velocity observations on different tectonic plates, and the removal of stationarity by moving variance (the latter as HV-LSC-ex(tended) 2 ). Furthermore, the covariance analysis, which is required to find necessary input parameters for the LSC, is extended by finding a suitable variance and correlation length using both horizontal velocity components at the same time. The traditional LSC and all extensions are tested on a synthetic dataset to find the signal at known as well as newly defined points, with stations separated on four different plates with distinct plate velocities. The methodologies are evaluated by calculation of a misfit to the input data, and implementation of a leave-one-out cross-validation and a Jackknife resampling. The largest improvement in terms of reduced misfit and stability of the interpolation can be obtained when plate boundaries are considered. In addition, any small-scale changes can be filtered out using the moving-variance approach and a smoother velocity field is obtained. In comparison with interpolation using the Kriging method, the fit is better using the new HV-LSC-ex 2 technique. [ABSTRACT FROM AUTHOR]

Bitter gourd (Momordica charantia L.) is a significant vegetable. Although it has a special bitter taste, it is still popular with the public. The industrialization of bitter gourd could be hampered by a lack of genetic resources. The bitter gourd’s mitochondrial and chloroplast genomes have not been extensively studied. In the present study, the mitochondrial genome of bitter gourd was sequenced and assembled, and its substructure was investigated. The mitochondrial genome of bitter gourd is 331,440 bp with 24 unique core genes, 16 variable genes, 3 rRNAs, and 23 tRNAs. We identified 134 SSRs and 15 tandem repeats in the entire mitochondrial genome of bitter gourd. Moreover, 402 pairs of repeats with a length greater than or equal to 30 were observed in total. The longest palindromic repeat was 523 bp, and the longest forward repeat was 342 bp. We found 20 homologous DNA fragments in bitter gourd, and the summary insert length was 19,427 bp, accounting for 5.86% of the mitochondrial genome. We predicted a total of 447 potential RNA editing sites in 39 unique PCGs and also discovered that the ccmFN gene has been edited the most often, at 38 times. This study provides a basis for a better understanding and analysis of differences in the evolution and inheritance patterns of cucurbit mitochondrial genomes.

In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI) experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model.

The amount of data collected from patients involved in clinical trials is continuously growing. All baseline patient characteristics are potential covariates that could be used to improve clinical trial analysis and power. However, the limited number of patients in phases I and II studies restricts the possible number of covariates included in the analyses. In this paper, we investigate the cost/benefit ratio of including covariates in the analysis of clinical trials with a continuous outcome. Within this context, we address the long-running question "What is the optimum number of covariates to include in a clinical trial?" To further improve the benefit/cost ratio of covariates, historical data can be leveraged to pre-specify the covariate weights, which can be viewed as the definition of a new composite covariate. Here we analyze the use of a composite covariate to improve the estimated treatment effect in small clinical trials. A composite covariate limits the loss of degrees of freedom and the risk of overfitting. [ABSTRACT FROM AUTHOR]

The internal ribosome entry site (IRES) RNA of bovine viral diarrhoea virus (BVDV), an economically significant Pestivirus, is required for the cap-independent translation of viral genomic RNA. Thus, it is essential for viral replication and pathogenesis. We applied a combination of high-throughput biochemical RNA structure probing (SHAPE-MaP) and in silico modelling approaches to gain insight into the secondary and tertiary structures of BVDV IRES RNA. Our study demonstrated that BVDV IRES RNA in solution forms a modular architecture composed of three distinct structural domains (I-III). Two regions within domain III are represented in tertiary interactions to form an H-type pseudoknot. Computational modelling of the pseudoknot motif provided a fine-grained picture of the tertiary structure and local arrangement of helices in the BVDV IRES. Furthermore, comparative genomics and consensus structure predictions revealed that the pseudoknot is evolutionarily conserved among many Pestivirus species. These studies provide detailed insight into the structural arrangement of BVDV IRES RNA H-type pseudoknot and encompassing motifs that likely contribute to the optimal functionality of viral capindependent translation element. [ABSTRACT FROM AUTHOR]

In order to address the problem that the direction‐of‐arrival (DOA) estimation is restricted by the number of array elements, this study comes up with a novel DOA estimation algorithm based on discrete‐Fourier‐transformation (DFT) and multiple regression, which focuses on the direct data domain from each array element rather than the traditional covariance domain of the whole array. In this algorithm, the authors regard each channel of the array signal model as an independent form of multiple regression and achieve the DOA by estimating the regression coefficient of the reconstructed source signal from each array element one by one iteratively. In addition, the DOAs estimated from the multiple array elements are averaged to improve the accuracy by exploiting the asymptotic normality. This algorithm is proposed, modelled, and developed theoretically at first. Then the capabilities that the authors' algorithm can estimate not only the very close DOAs since they distinguish the irrelevant sources by the DFT on temporal frequency but also the DOAs when the number of sources is larger than that of array elements are fully demonstrated by simulations. Furthermore, no requirement for the known number of sources brings the algorithm broader application foreground. [ABSTRACT FROM AUTHOR]

How plants respond to density via modular plasticity is obscure, probably because relevant studies using covariance analysis (ANCOVA) and allometric analysis rarely focus on multiple stages of plant growth, and also the two approaches are seldom used simultaneously. In this study, a field experiment evaluated the effects of three density levels on resource allocation traits in Abutilon theophrasti and tested the degree to which these were explained by indirect effects of density on biomass over time. Results showed inconsistent responses in allocation traits and allometric relationships at each growth stage. At 30 days of plant growth, high density increased root/stem, root/leaf, and stem/leaf, but did not affect any allometric relationships. At 50 days, density altered most mass and ratio traits, but not for allometric exponents. At 70 days, density altered allometric relationships, but did not affect plant allocation patterns. The stage-dependent allometric relationships and the fact that allocation plasticity and allometric plasticity did not coincide both suggested that one-stage allometric plasticity might be apparent plasticity. In response to the increase of density, plants first altered the strategy of biomass partitioning and then growth rate or developmental stage, indicating that density effects intensified over time. For plasticity in a modular trait, size effects can be regarded as a component of (indirect) environmental effects, with the residual variation after removal of size effects being the other component of plant (direct) active response. The insights into apparent plasticity of allometry and two components of plasticity should be of essential importance to investigating phenotypic plasticity and its ecological and evolutionary implications. [ABSTRACT FROM AUTHOR]

Left ventricular (LV) dysfunction is mainly assessed by global contractile indices such as ejection fraction and LV Volumes in cardiac MRI. While these indices give information about the presence or not of LV alteration, they are not able to identify the location and the size of such alteration. The aim of this study is to compare the performance of three parametric imaging techniques used in cardiac MRI for the regional quantification of cardiac dysfunction. The proposed approaches were evaluated on 20 patients with myocardial infarction and 20 subjects with normal function. Three parametric images approaches: covariance analysis, parametric images based on Hilbert transform and those based on the monogenic signal were evaluated using cine-MRI frames acquired in three planes of views. The results show that parametric images generated from the monogenic signal were superior in term of sensitivity (89.69%), specificity (86.51%) and accuracy (89.06%) to those based on covariance analysis and Hilbert transform in the detection of contractile dysfunction related to myocardial infarction. Therefore, the parametric image based on themonogenic signal is likely to provide additional regional indices about LV dysfunction and it may be used in clinical practice as a tool for the analysis of the myocardial alterations. [ABSTRACT FROM AUTHOR]

Long-term configuration stability is essential for a space-based gravitational-wave observatory, which can be affected by orbit insertion errors. This paper investigated the stability of a geocentric gravitational-wave observatory from the view of the configuration uncertainty propagation. The effects of the orbit insertion errors on the configuration stability are propagated using the Unscented Transformation (UT). The best UT tuning factor is selected based on the accuracy analysis of different UT tuning factors. The effects of the position and velocity insertion errors in different directions are firstly discussed. Compared with the Monte Carlo simulations, the UT method has relative errors of no more than 2.7%, while the time cost is only 3.6%. It is found that the radial position and tangential velocity insertion errors have the largest influence on the configuration stability. Finally, based on the proposed method, the stability domain of the geocentric space gravitational-wave detection constellation is investigated by considering two kinds of insertion errors, i.e., independent and identically distributed insertion errors and insertion errors in spatial directions. The analysis results in this paper can be potentially useful for the configuration design of a geocentric gravitational-wave observatory.

The (n,2n) and (n,p) reaction cross-sections of 90Zr isotope have been measured in 10.95 to 20.02 MeV neutron energy range by using activation and off-line γ-ray spectrometric technique. 27Al(n,α)24Na and 115In(n,n')115mIn monitor reactions have been used to measure the neutron fluence. The reaction cross-sections were estimated from TALYS-1.9 and EMPIRE-3.2.2 codes by making the selection of different input parameters. The uncertainties in the measurement were estimated using covariance analysis. The present results have been compared with the data measured previously by different authors and available in different evaluated nuclear data files. [ABSTRACT FROM AUTHOR]

The aim of this study is to introduce R programming language, which became popular especially in recent years and to show how to interpret Results obtained through a sample application. For this purpose, the interface of R Studio program, its superior aspects, how to import the data to the program, a sample analysis and how to get support for the program were discussed. After explaining how R programming language emerged and its historical development, RStudio interface will be mentioned. The study shows how to perform the analysis with the help of functions after the installation of RStudio. Within the scope of sample analysis, the same achievement test for the statistics course was administered on 30 students who were randomly assigned to experimental and control groups before and after the experimental procedure. After taking the pre-test scores of the students under control, the presence of a statistically significant difference between the post-test scores of the experimental and control groups, to which two different methods were applied, was tested by covariance analysis. Within the scope of the research, it has been concluded that the use of the R program, which is free, open source and therefore can be developed, has a strong online user community and where fast software updates can be performed, should be expanded. [ABSTRACT FROM AUTHOR]

National infectious disease incidence rates are often estimated by standardizing locally derived rates using national-level age and race distributions. Data on other factors potentially associated with incidence are often not available in the form of patient-level covariates. Including characteristics of patients' area of residence may improve the accuracy of national estimates. The authors used data from the Centers for Disease Control and Prevention's Active Bacterial Core Surveillance program (2004-2005), adjusted for census-based variables, to estimate the national incidence of invasive pneumococcal disease (IPD). The authors tested Poisson and negative binomial models in a cross-validation procedure to select variables best predicting the incidence of IPD in each county. Including census-level information on race and educational attainment improved the fit of both Poisson and negative binomial models beyond that achieved by adjusting for other census variables or by adjusting for an individual's race and age alone. The Poisson model with census-based predictors led to a national estimate of IPD of 16.0 cases per 100,000 persons as compared with 13.5 per 100,000 persons using an individual's age and race alone. Accuracy of, and confidence intervals for, these estimates can only be determined by obtaining data from other randomly selected US counties. However, incorporating census-derived characteristics should be considered when estimating national incidence of IPD and other diseases.

This paper presents a robust trajectory design method for approaching and rendezvous with a space target considering multi-source uncertainties. A nonlinear covariance analysis method based on the state transition tensor is presented to formulate the propagation of uncertainties including environment parameter uncertainty, actuator error, sensor noise, navigation error and initial state dispersion of the closed-loop GN&C system. Then, the robust trajectory design problem is defined based on the quantified effect of the uncertainties, and an improved self-adaptive differential evolution algorithm is presented to solve the robust trajectory design problem with uncertainties. Finally, four groups of numerical simulations are carried out to show that the designed robust trajectories can satisfy the final state dispersion constraint under multi-source uncertainties.

The capability of full-tensor gravity gradients for spacecraft orbit determination has been demonstrated in recent studies. The advantages lie in its independence from ground-based systems and its immunity against spoofing attacks. A common practice is to use Earth rotation parameters and star sensor measurements to isolate the orientation contributions to gravity gradients, which implies that the orbit determination accuracy is affected by the quality of attitude data. This article investigates the feasibility of orbit determination using gravity gradient invariants instead of full-tensor gravity gradients in order to eliminate the necessity of attitude information for frame transformation. The orbit observability is first partially explained by formulating the geometric relationship between orbital elements and geocentric distance and latitude, the latter of which can be obtained from gravity gradient invariants. Then a covariance analysis technique based on the computation of a posterior Cramér–Rao lower bound is developed to assess the orbit determination accuracy. It is assumed that the gravity gradient biases due to bandwidth limitation have been calibrated. Simulations are carried out to analyze the effects of sampling rate, orbital inclination, orbital height, and gradiometer noise level. Results show that orbit determination from gravity gradient invariants has better position accuracy in the radial direction but has degraded accuracies in the along-track and cross-track directions compared to orbit determination using full-tensor gravity gradients. The covariance analysis technique is applied to real flight data from gravity field and steady-state ocean circulation explorer. Radial, along-track, and cross-track position accuracies of 1.8, 78, and 255 m have been achieved. Future study will deal with biases in actual measurements to fulfill real orbit determination. [ABSTRACT FROM AUTHOR]

In order to address the problem that the direction‐of‐arrival (DOA) estimation is restricted by the number of array elements, this study comes up with a novel DOA estimation algorithm based on discrete‐Fourier‐transformation (DFT) and multiple regression, which focuses on the direct data domain from each array element rather than the traditional covariance domain of the whole array. In this algorithm, the authors regard each channel of the array signal model as an independent form of multiple regression and achieve the DOA by estimating the regression coefficient of the reconstructed source signal from each array element one by one iteratively. In addition, the DOAs estimated from the multiple array elements are averaged to improve the accuracy by exploiting the asymptotic normality. This algorithm is proposed, modelled, and developed theoretically at first. Then the capabilities that the authors' algorithm can estimate not only the very close DOAs since they distinguish the irrelevant sources by the DFT on temporal frequency but also the DOAs when the number of sources is larger than that of array elements are fully demonstrated by simulations. Furthermore, no requirement for the known number of sources brings the algorithm broader application foreground. [ABSTRACT FROM AUTHOR]

The 92Mo(n,α)89Zr, 97Mo(n,p)97Nb, 148Nd(n,2n)147Nd and 146Nd(n,p)146Pr reaction cross sections with the neutron of energy of 14.54 ± 0.24 MeV have been measured by using the method of activation and off-line γ-ray spectrometry. The neutron was generated from the D-T reaction at the PURNIMA neutron generator of BARC. The 197Au(n,2n)196Au monitor reaction was used for the estimation of neutron flux. The covariance analysis for the uncertainties of the cross sections has been carried out by considering the partial uncertainties of different attributes. The present data have been compared with the literature data, evaluated data and theoretically calculated values from TALYS-1.9 code. [ABSTRACT FROM AUTHOR]

The 115In(n,2n)114mIn and 197Au(n,2n)196Au reaction cross sections have been measured relative to the 27Al(n,α)24Na monitor reaction at the two different incident neutron energies of 13.520 ± 0.005 MeV and 14.54 ± 0.24 MeV. The neutrons from the D-T fusion reaction at the Purnima neutron generator were used for activation followed by off-line γ-ray spectrometry. The uncertainty propagation and correlation of measured reaction cross sections were estimated using covariance analysis through considering the partial uncertainties in different attributes. The measured reaction cross sections from the present work have been compared with the literature data from EXFOR compilation, ENDF data of various libraries and theoretically calculated values from the TALYS-1.9 code. [ABSTRACT FROM AUTHOR]

The 93Nb(n,α)90mY, 93Nb(n,2n)92mNb and 92Mo(n,p)92mNb reaction cross sections have been measured relative to the 197Au(n,2n)196Au monitor reaction at the neutron energy of 14.54 ± 0.24 MeV. The neutrons were generated from the T(d,n)4He reaction using Purnima neutron generator. The experiment was done by using the method of activation in combination with an off-line γ -ray spectrometry technique. The uncertainties and correlations for the reaction cross sections were estimated with the use of covariance analysis by considering the partial uncertainties in individual attributes. The measured reaction cross sections have been analyzed by comparing with the data available in EXFOR compilation, various files of evaluated data and theoretically calculated values from TALYS-1.9. [ABSTRACT FROM AUTHOR]