Explore the vast range of titles available.

Vibrational dynamics in the glass transition and the cold crystallization process of (S)-4′-(1-methyloctyloxycarbonyl) biphenyl-4-yl 4-[7-(2,2,3,3,4,4,4-heptafluorobutoxy) heptyl-1-oxy]-benzoate (3F7HPhH7) was studied by Fourier transform infrared spectroscopy (FTIR) during cooling/heating experimental runs. The measured spectra processing was supported by quantum chemical density functional theory (DFT) calculations (frequency assignments). The perturbation-correlation moving window two-dimensional analysis (PCMW2D) was performed to examine how the height of individual absorption bands change under with temperature. Two-dimensional correlation analysis (2D-COS) was used to detect freezing-in or activation of the stochastic movements during the vitrification and the cold crystallization processes. Upon cooling, the vitrification process involves freezing-in of the stochastic movements of ester groups. Upon heating, as the cold crystallization process begins, the first to respond are the vibrations of the C–O–C and C=O groups in the rigid core.

Purpose Female athletes are at greater risk of non-contact ACL injury. Three-dimensional kinematic analyses have shown that at-risk female athletes have a greater knee valgus angle during drop jumping. The purpose of this study was to evaluate the relationship between knee valgus angle and non-contact ACL injury in young female athletes using coronal-plane two-dimensional (2D) kinematic analyses of single-leg landing. Methods Two hundred ninety-one female high school athletes newly enrolled in basketball and handball clubs were assessed. Dynamic knee valgus was analysed during single-leg drop jumps using 2D coronal images at hallux–ground contact and at maximal knee valgus. All subjects were followed up for 3 years for ACL injury. Twenty-eight (9.6%) of 291 athletes had ACL rupture, including 27 non-contact ACL injuries. The injured group of 27 knees with non-contact ACL injury was compared with a control group of 27 randomly selected uninjured knees. The relationship between initial 2D movement analysis results and subsequent ACL injury was investigated. Results Dynamic knee valgus was significantly greater in the injured group compared to the control group at hallux–ground contact (2.1 ± 2.4 vs. 0.4 ± 2.2 cm, P  = 0.006) and at maximal knee valgus (8.3 ± 4.3 vs. 5.1 ± 4.1 cm, P  = 0.007). Conclusion The results of this study confirm that dynamic knee valgus is a potential risk factor for non-contact ACL injury in female high school athletes. Fully understanding the risk factors that increase dynamic knee valgus will help in designing more appropriate training and interventional strategies to prevent injuries in at-risk athletes. Level of evidence Prognostic studies, Level II.

Recently, the rapid development of deep learning has greatly improved the performance of image classification. However, a central problem in hyperspectral image (HSI) classification is spectral uncertainty, where spectral features alone cannot accurately and robustly identify a pixel point in a hyperspectral image. This paper presents a novel HSI classification network called MS-RPNet, i.e., multiscale superpixelwise RPNet, which combines superpixel-based S3-PCA with two-dimensional singular spectrum analysis (2D-SSA) based on the Random Patches Network (RPNet). The proposed frame can not only take advantage of the data-driven method, but can also apply S3-PCA to efficiently consider more global and local spectral knowledge at the super-pixel level. Meanwhile, 2D-SSA is used for noise removal and spatial feature extraction. Then, the final features are obtained by random patch convolution and other steps according to the cascade structure of RPNet. The layered extraction superimposes the different sparial information into multi-scale spatial features, which complements the features of various land covers. Finally, the final fusion features are classified by SVM to obtain the final classification results. The experimental results in several HSI datasets demonstrate the effectiveness and efficiency of MS-RPNet, which outperforms several current state-of-the-art methods.

The nonlinear coupled longitudinal-transverse vibrations and stability of an axially moving beam, subjected to a distributed harmonic external force, which is supported by an intermediate spring, are investigated. A case of three-to-one internal resonance as well as that of non-resonance is considered. The equations of motion are obtained via Hamilton’s principle and discretized into a set of coupled nonlinear ordinary differential equations using Galerkin’s method. The resulting equations are solved via two different techniques: the pseudo-arclength continuation method and direct time integration. The frequency-response curves of the system and the bifurcation diagrams of Poincaré maps are analyzed.

This study investigates the active earth pressure exerted on rigid vertical retaining walls subjected to translational motion, utilizing a two-dimensional analytical approach that does not rely on prior assumptions regarding the shape of the soil arch (or the trajectory of the minor principal stress). This method significantly differs from the existing approach that combines soil arch shape and horizontal flat-element analysis. Various failure surfaces were examined and particular attention was given to a parabolic surface, which was extensively discussed. The proposed formula enables the prediction of earth pressure distribution on the wall and stresses within the failure zone. Moreover, the analytical expression for the trajectory of the minor principal stress within the failure zone was derived from the stress equations. In order to verify the accuracy and applicability of the proposed analysis, a comparative assessment is conducted against experimental data and existing theories. The proposed earth pressure distribution aligns well with the experimental data. Finally, a concise yet pragmatic formulation was developed to facilitate the estimation of active earth pressure in the field.

Goethite is the most ubiquitous iron oxide mineral in soils, and adsorption of organic pollutants on goethite dominates the fate and transportation in the environment. In this study, the facet-dependent adsorption behavior of ciprofloxacin (CIP) on goethite was systematically investigated with in situ attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectra and two-dimensional correlation analysis (2D-COS). The experimental results indicated that the goethite samples with higher facet proportion of {021}/{110} exhibited the better adsorption capacity compared to goethite with lower facet proportion of {021}/{110}. The reason is the more existence of singly coordinated sites with higher reactivity on the {021} facet. Moreover, CIP was found to be adsorbed on {021} and {110} facets by forming a tridentate complex involving the bridge coordination of bidentate ligands, H-bonding, and a bidentate chelate complex.

Dissolved organic matter (DOM) derived from biochar takes a crucial role in transport and bioavailability toward contaminants; hence, it is undeniable that a thorough analysis of its properties is important. So far, the effect of pyrolysis temperature on the functional groups, components, and evolutionary sequence of manure-based biochar DOM has not been adequately investigated. Here, DOM was released from two typical livestock manures (cow and pig) at five pyrolysis temperatures (300 ~ 700°C), and it was explored in depth with the aid of moving window 2D correlation spectroscopy (MW-2D-COS) and heterogeneous 2D correlation spectroscopy (hetero-2D-COS). The results demonstrated that the concentration, aromaticity, and hydrophobicity of DOM were greater at high temperatures, and more DOM was liberated from cow manure-based biochar at identical temperature. Protein-like compounds dominated at high temperatures. The pyrolysis temperatures of final configuration transformation points of the fulvic acid-like component and the aromatic ring C=C in DOM were 400°C and 500°C, respectively. Moreover, Fourier transform infrared spectroscopy combined with two-dimensional correlation analysis indicated that the functional group evolution of DOM depends on the pyrolysis temperature and feedstock type. The study provides a new perspective on manure management and environmental applications of biochar.

The recently proposed L2-norm linear discriminant analysis criterion based on Bhattacharyya error bound estimation (L2BLDA) was an effective improvement over linear discriminant analysis (LDA) and was used to handle vector input samples. When faced with two-dimensional (2D) inputs, such as images, converting two-dimensional data to vectors, regardless of the inherent structure of the image, may result in some loss of useful information. In this paper, we propose a novel two-dimensional Bhattacharyya bound linear discriminant analysis (2DBLDA). 2DBLDA maximizes the matrix-based between-class distance, which is measured by the weighted pairwise distances of class means and minimizes the matrix-based within-class distance. The criterion of 2DBLDA is equivalent to optimizing the upper bound of the Bhattacharyya error. The weighting constant between the between-class and within-class terms is determined by the involved data that make the proposed 2DBLDA adaptive. The construction of 2DBLDA avoids the small sample size (SSS) problem, is robust, and can be solved through a simple standard eigenvalue decomposition problem. The experimental results on image recognition and face image reconstruction demonstrate the effectiveness of 2DBLDA.

The reliability of using abrupt changes in the spatial Hurst exponent for identifying temporal points of abrupt change in climate dynamics is explored. If a spatio-temporal dynamical system undergoes an abrupt change at a particular time, the time series of spatial Hurst exponent obtained from the data of any variable of the system should also show an abrupt change at that time. As expected, spatial Hurst exponents for each of the two variables of a model spatio-temporal system – a globally coupled map lattice based on the Burgers' chaotic map – showed abrupt change at the same time that a parameter of the system was changed. This method was applied for the identification of change points in climate dynamics using the NCEP/NCAR data on air temperature, pressure and relative humidity variables. Different abrupt change points in spatial Hurst exponents were detected for the data of these different variables. That suggests, for a dynamical system, change point detected using the two-dimensional detrended fluctuation analysis method on a single variable alone is insufficient to comment about the abrupt change in the system dynamics and should be based on multiple variables of the dynamical system.

l 2 -norm 2-directional 2-dimensional LDA ( ( 2 D ) 2 LDA) is an effective matrix-based supervised dimensionality reduction method by considering left-and-right side dimensionality reduction at the same time. However, ( 2 D ) 2 LDA maybe face the singularity issue when facing with the small sample size (SSS) problem. To cope with this issue, this paper proposes a novel bilateral two-dimensional linear discriminant analysis, called B2DLDA. The objective function of B2DLDA maximizes the matrix-based between-class distance and meanwhile minimizes the matrix-based within-class distance. Compared with ( 2 D ) 2 LDA, our B2DLDA is solved effectively through standard eigenvalue decomposition problems, which does not involve the inverse of a matrix and hence avoids the SSS problem. The experimental results on five image data sets demonstrate the effectiveness of B2DLDA.