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Optimization-based weight learning approaches that incorporate multiple sensor signals or vibration spectral components have demonstrated their effectiveness in monitoring mechanical systems. However, the current weight learning methods are limited by their reliance on linear fusion functions. The exploration of nonlinear link functions, particularly in the context of fusing spectral components in vibration spectra for health indices (HIs) construction, remains largely unexplored. Additionally, the development of formulas for interpreting HIs constructed using nonlinear fusion functions poses significant theoretical challenges. To address these limitations, this study proposes a novel nonlinear optimization-based weight learning model for constructing an HI that captures the nonlinear relationships among spectral components. This HI is designed to pinpoint fault characteristic frequencies while also highlighting other spectral lines associated with bearing degradation modelling. Furthermore, we derive formulas that enable the calculation of the contributions of frequency components to nonlinearly constructed HIs, thereby enhancing the interpretability of the model. By selecting an appropriate kernel function, subtle changes resulting from incipient faults and the underlying degradation process can be effectively captured. The effectiveness of the proposed model in detecting incipient faults, modelling degradation, and identifying fault types is validated through two run-to-failure case studies and a gearbox bearing experiment. [ABSTRACT FROM AUTHOR]

• The use of CR-ACVA for incipient fault detection. • The use of data captured from two operational industrial centrifugal pumps. • The combination of canonical residuals and recursive canonical variate analysis. • Early fault detection for the case of time-varying dynamic processes. • Comparison with existing techniques for incipient fault detection. Condition monitoring signals obtained from rotating machines often demonstrate a highly non-stationary and transient nature due to internal natural deterioration characteristics of their constituent components and external time-varying operational conditions. Traditional multivariate statistical monitoring approaches are based on the assumption that the underlying processes are linear and static and are apt to interpret the normal changes in operating conditions as faults, which would result in high false positive rates. On the other hand, the development of robust diagnostic techniques for the detection of incipient faults remains a challenge for researchers, given the difficulty of finding an appropriate trade-off between a low false positive ratio and early detection of emerging faults. To address these issues, this paper proposes a novel adaptive fault detection approach based on the canonical residuals (CR) induced by the combination of canonical variate analysis (CVA) and matrix perturbation theory for the monitoring of dynamic processes where variations in operating conditions are incurred. The canonical residuals are calculated based upon the distinctions between past and future measurements and are able to effectively detect emerging faults while still maintaining a low false positive rate. The effectiveness of the developed diagnostic model for the detection of abnormalities in industrial processes was demonstrated for slow involving faults in case studies of two operational industrial high-pressure pumps. In comparison with the variable-based and canonical correlation-based statistical monitoring approaches, the proposed canonical residuals-adaptive canonical variate analysis (CR-ACVA) fault detection method has demonstrated its superiorities by the detailed performance comparisons. [ABSTRACT FROM AUTHOR]

Calcium intercalates of MoS 2 with nominal composition Ca x MoS 2 (0 ≤ x ≤ 0.50) were prepared in liquid ammonia. Ammonia molecules were also intercalated into MoS 2 along with Ca as revealed by thermogravimetric and gravimetric analysis. The intercalated products have a composition of Ca x (NH 3 ) y MoS 2 (0 ≤ y ≤ 0.40). The crystal structure of Ca 0.50 (NH 3 ) 0.40 MoS 2 was solved and refined from powder X-ray diffraction data. It exhibits a hexagonal symmetry (space group P -3 m 1) with a = 3.198(4) Å, c = 18.543(9) Å. The crystal structure of Ca 0.50 (NH 3 ) 0.40 MoS 2 was also investigated by Raman spectroscopy and transmission electron microscopy. Superstructure in the ab-plane and phase transition from 2H to 1T were not observed. Only samples with x in the range from 0.10 to 0.35 show superconducting properties and the T c - x phase diagram of the Ca x (NH 3 ) y MoS 2 system exhibits a dome-like behavior. The maximum T c of 8.6 K was observed in Ca 0.20 (NH 3 ) 0.17 MoS 2 , which is higher than the T c reported before in chemically doped transition metal dichalcogenides. The Ca 0.20 (NH 3 ) 0.17 MoS 2 is a type-II superconductor with H c2 (0) around 0.098 T and ξ (0) about 58.0 nm. [ABSTRACT FROM AUTHOR]

Coiled-coil tropomyosin, localized on actin filaments in virtually all eukaryotic cells, serves as a gatekeeper regulating access of the motor protein myosin and other actin-binding proteins onto the thin filament surface. Tropomyosin’s modular pseudo-repeating pattern of approximately 39 amino acid residues is designed to allow binding of the coiled-coil to successive actin subunits along thin filaments. Even though different tropomyosin isoforms contain varying numbers of repeat modules, the pseudo-repeat length, in all cases, matches that of a single actin subunit. Thus, the seven pseudo-repeats of 42 nm long muscle tropomyosin bind to seven successive actin subunits along thin filaments, while simultaneously bending into a super-helical conformation that is preshaped to the actin filament helix. In order to form a continuous cable on thin filaments that is free of gaps, adjacent tropomyosin molecules polymerize head-to-tail by means of a short (∼9 residue) overlap. Several laboratories have engineered peptides to mimic the N- and C-terminal tropomyosin association and to characterize the overlap structure. All overlapping domains examined show a compact N-terminal coiled-coil inserting into a partially opened C-terminal partner, where the opposing coiled-coils at the overlap junction face each other at up to ∼90° twist angles. Here, Molecular Dynamics (MD) simulations were carried out to determine constraints on the formation of the tropomyosin overlap complex and to assess the amount of twisting exhibited by full-length tropomyosin when bound to actin. With the exception of the last 20–40 C- and N-terminal residues, we find that the average tropomyosin structure closely resembles a “canonical” model proposed in the classic work of McLachlan and Stewart, displaying perfectly symmetrical supercoil geometry matching the F-actin helix with an integral number of coiled-coil turns, a coiled-coil helical pitch of 137 Å, a superhelical pitch of 770 Å, and no localized pseudo-rotation. Over the middle 70% of tropomyosin, the average twisting of the coiled-coil deviates only by 10° from the canonical model and the torsional freedom is very small (std. dev. of 7°). This small degree of twisting cannot yield the orthogonal N- and C-termini configuration observed experimentally. In marked contrast, considerable coiled-coil unfolding, splaying and twisting at N- and C-terminal ends is observed, providing the conformational plasticity needed for head-to-tail nexus formation. [Copyright &y& Elsevier]

Highlights: [•] Head-to-tail linkage is required for tropomyosin cable formation on F-actin. [•] Molecular dynamics of tropomyosin overlap domains were carried out. [•] N- to C-terminal coiled-coils face each other at an orthogonal angle. [•] The bending angle of the overlap domain and the rest of the molecule are comparable. [•] This curvature ensures tropomyosin assembly as an uninterrupted cable on F-actin. [ABSTRACT FROM AUTHOR]

Abstract: Point mutations targeting muscle thin filament proteins are the cause of a number of cardiomyopathies. In many cases, biological effects of the mutations are well-documented, whereas their structural and mechanical impact on filament assembly and regulatory function is lacking. In order to elucidate molecular defects leading to cardiac dysfunction, we have examined the structural mechanics of two tropomyosin mutants, E180G and D175N, which are associated with hypertrophic cardiomyopathy (HCM). Tropomyosin is an α-helical coiled-coil dimer which polymerizes end-to-end to create an elongated superhelix that wraps around F-actin filaments of muscle and non-muscle cells, thus modulating the binding of other actin-binding proteins. Here, we study how flexibility changes in the E180G and D175N mutants might affect tropomyosin binding and regulatory motion on F-actin. Electron microscopy and Molecular Dynamics simulations show that E180G and D175N mutations cause an increase in bending flexibility of tropomyosin both locally and globally. This excess flexibility is likely to increase accessibility of the myosin-binding sites on F-actin, thus destabilizing the low-Ca2+ relaxed-state of cardiac muscle. The resulting imbalance in the on–off switching mechanism of the mutants will shift the regulatory equilibrium towards Ca2+-activation of cardiac muscle, as is observed in affected muscle, accompanied by enhanced systolic activity, diastolic dysfunction, and cardiac compensations associated with HCM and heart failure. [Copyright &y& Elsevier]

Abstract: The Hill two-state cooperativity model and the McKillop–Geeves (McK–G) three-state model predict very similar binding traces of myosin subfragment 1 (S1) binding to regulated actin filaments in the presence and absence of calcium, and both fit the experimental data reasonably well [Chen et al., Biophys. J., 80, 2338–2349]. Here, we compared the Hill model and the McK–G model for binding myosin S1 to regulated actin against three sets of experimental data: the titration of regulated actin with S1 and the kinetics of S1 binding of regulated actin with either excess S1 to actin or excess actin to S1. Each data set was collected for a wide range of specified calcium concentrations. Both models were able to generate reasonable fits to the time course data and to titration data. The McK–G model can fit all three data sets with the same calcium-concentration-sensitive parameters. Only K B and K T show significant calcium dependence, and the parameters have a classic pCa curve. A unique set of the Hill model parameters was extremely difficult to estimate from the best fits of multiple sets of data. In summary, the McK–G cooperativity model more uniquely resolves parameters estimated from kinetic and titration data than the Hill model, predicts a sigmoidal dependence of key parameters with calcium concentration, and is simpler and more suitable for practical use. [Copyright &y& Elsevier]

Abstract: While mutations in the myosin subfragment 1 motor domain can directly disrupt the generation and transmission of force along myofibrils and lead to myopathy, the mechanism whereby mutations in the myosin rod influences mechanical function is less clear. Here, we used a combination of various imaging techniques and molecular dynamics simulations to test the hypothesis that perturbations in the myosin rod can disturb normal sarcomeric uniformity and, like motor domain lesions, would influence force production and propagation. We show that disrupting the rod can alter its nanomechanical properties and, in vivo, can drive asymmetric myofilament and sarcomere formation. Our imaging results indicate that myosin rod mutations likely disturb production and/or propagation of contractile force. This provides a unifying theory where common pathological cascades accompany both myosin motor and specific rod domain mutations. Finally, we suggest that sarcomeric inhomogeneity, caused by asymmetric thick filaments, could be a useful index of myopathic dysfunction. [Copyright &y& Elsevier]

Abstract: The inherent flexibility of rod-like tropomyosin coiled-coils is a significant factor that constrains tropomyosin’s complex positional dynamics on actin filaments. Flexibility of elongated straight molecules typically is assessed by persistence length, a measure of lengthwise thermal bending fluctuations. However, if a molecule’s equilibrium conformation is curved, this formulation yields an “apparent” persistence length (∼100nm for tropomyosin), measuring deviations from idealized straight conformations which then overestimate actual dynamic flexibility. To obtain the “dynamic” persistence length, a true measurement of flexural stiffness, the average curvature of the molecule must be taken into account. Different methods used in our studies for measuring the dynamic persistence length directly from Molecular Dynamics (MD) simulations of tropomyosin are described here in detail. The dynamic persistence length found, 460±40nm, is ∼12-times longer than tropomyosin and 5-times the apparent persistence length, showing that tropomyosin is considerably stiffer than previously thought. The longitudinal twisting behavior of tropomyosin during MD shows that the amplitude of end-to-end twisting fluctuation is ∼30° when tropomyosin adopts its near-average conformation. The measured bending and twisting flexibilities are used to evaluate different models of tropomyosin motion on F-actin. [Copyright &y& Elsevier]

Abstract: Complementarity between the tropomyosin supercoil and the helical contour of actin-filaments is required for the binding interaction of actin and tropomyosin (). Clusters of small alanine residues in place of canonical leucines along coiled-coil tropomyosin may be responsible for pre-shaping tropomyosin and promoting conformational complementarity to F-actin. A longitudinal displacement between the two chains of the tropomyosin coiled-coil induced by the alanine clusters could produce localized bending or limited flexibility along tropomyosin needed to shape tropomyosin (). To evaluate the influence of alanine clusters on tropomyosin curvature, we calculated the longitudinal displacement between amino acid residues on adjacent chains of the tropomyosin coiled-coil and related this “Z-displacement” to the position of the alanine clusters. Measurements were made on high-resolution crystal structures of tropomyosin fragments and on trajectories from molecular dynamics simulations of full-length αα-tropomyosin. We found no strict one-for-one spatial correlation between alanine cluster position and the Z-displacement. Neither did we find any direct correspondence between the clusters and the local curvature of tropomyosin. Rather than just causing specific local structural effects, the overall influence of alanine clusters is complex and delocalized, leading to a gradually changing bending pattern along the length of tropomyosin. [Copyright &y& Elsevier]

Summary: Wrapped superhelically around actin filaments, the coiled-coil α-helices of tropomyosin regulate muscle contraction by cooperatively blocking or exposing myosin-binding sites on actin. In non-muscle cells, tropomyosin additionally controls access of actin-binding proteins involved in cytoskeletal actin filament maintenance and remodeling. Tropomyosin''s global shape and flexibility play a key role in the assembly, maintenance, and regulatory switching of thin filaments yet remain insufficiently characterized. Here, electron microscopy and molecular dynamics simulations yielded conformations of tropomyosin closely resembling each other. The electron microscopy and simulations show that isolated tropomyosin has an average curved conformation with a design well matched to its superhelical shape on F-actin. In addition, they show that tropomyosin bends smoothly yet anisotropically about its distinctive helically curved conformation, without any signs of unfolding, chain separation, localized kinks, or joints. Previous measurements, assuming tropomyosin to be straight on average, mistakenly suggested considerable flexibility (with persistence lengths only ∼3 times the protein''s length). However, taking the curved average structure determined here as reference for the flexibility measurements yields a persistence length of ∼12 lengths, revealing that tropomyosin actually is semirigid. Corresponding simulation of a triple mutant (A74L–A78V–A81L) with weak actin affinity shows that it lacks shape complementarity to F-actin. Thus, tropomyosin''s pre-shaped semirigid architecture is essential for the assembly of actin filaments. Further, we propose that once bound to thin filaments, tropomyosin will be stiff enough to act as a cooperative unit and move on actin in a concerted way between known regulatory states. [Copyright &y& Elsevier]

• Proposes a JITL-data-driven prognostic model for in-service reciprocating compressors. • Develops a JITL scheme realizes automatic instance clustering. • Develops a RS-GBDT model with improved predictive performance and uncertainty quantification. • Presents the degradation data of a large-scale in-service compressor. Historical failure instances of a system with diversified degradation patterns will pose great challenge for prognostics. Consequently, it is challenging to accurately predict the remaining useful life (RUL) using a prognostic model trained from such data. To solve this problem, this paper proposes a just-in-time learning-based data-driven prognostic method for reciprocating compressors with diverse degradation patterns and operating modes. The proposed framework employs a just-in-time learning (JITL) scheme to deal with the stochastic nature of fault evolution and the diversity of degradation patterns. Moreover, a data-driven forecasting model that features a randomized and smoothed gradient boosting decision tree (RS-GBDT) is developed for RUL and uncertainty predictions. The effectiveness of the proposed approach was validated on temperature measurements collected from 13 valve failure cases of an industrial reciprocating compressor. [ABSTRACT FROM AUTHOR]

At present, the main super-resolution (SR) method based on convolutional neural network (CNN) is to increase the layer number of the network by skip connection so as to improve the nonlinear expression ability of the model. However, the network also becomes difficult to be trained and converge. In order to train a smaller but better performance SR model, this paper constructs a novel image SR network of multiple attention mechanism(MAMSR), which includes channel attention mechanism and spatial attention mechanism. By learning the relationship between the channels of the feature map and the relationship between the pixels in each position of the feature map, the network can enhance the ability of feature expression and make the reconstructed image more close to the real image. Experiments on public datasets show that our network surpasses some current state-of-the-art algorithms in PSNR, SSIM, and visual effects. [ABSTRACT FROM AUTHOR]

The ends of coiled-coil tropomyosin molecules are joined together by nine to ten residue-long head-to-tail “overlapping domains”. These short four-chained interconnections ensure formation of continuous tropomyosin cables that wrap around actin filaments. Molecular Dynamics simulations indicate that the curvature and bending flexibility at the overlap is 10–20% greater than over the rest of the molecule, which might affect head-to-tail filament assembly on F-actin. Since the penultimate residue of striated muscle tropomyosin, Ser283, is a natural target of phosphorylating enzymes, we have assessed here if phosphorylation adjusts the mechanical properties of the tropomyosin overlap domain. MD simulations show that phosphorylation straightens the overlap to match the curvature of the remainder of tropomyosin while stiffening it to equal or exceed the rigidity of canonical coiled-coil regions. Corresponding EM data on phosphomimetic tropomyosin S283D corroborate these findings. The phosphorylation-induced change in mechanical properties of tropomyosin likely results from electrostatic interactions between C-terminal phosphoSer283 and N-terminal Lys12 in the four-chain overlap bundle, while promoting stronger interactions among surrounding residues and thus facilitating tropomyosin cable assembly. The stiffening effect of D283-tropomyosin noted correlates with previously observed enhanced actin–tropomyosin activation of myosin S1-ATPase, suggesting a role for the tropomyosin phosphorylation in potentiating muscle contraction. [ABSTRACT FROM AUTHOR]

Vibration-based Robotic Ground Classification (V-RGC) is an ability of a field robot identifying the ground types (e.g., grass and clay) according to the proprioceptive vibration sequence. It has proved that the accurate and read-time V-RGC contributes a lot to the avoidance of non-geometric hazards, route planning, and pose estimation. However, V-RGC in a dynamic environment (i.e., data distribution may drift) has not yet been taken into consideration, which motivates us to propose a novel classification method named Joint Domain Adaptation Semi-Supervised Extreme Learning Machine (JDA-S2ELM). First, the projected maximum mean discrepancy (MMD) criterion is introduced to expand the classification boundaries from the source domain to the target domain in a computationally-efficient way. Second, the joint-distribution domain adaptation (DA) is proposed to realize a cascaded marginal- and conditional-distribution DA training framework, which shows a higher and more stable accuracy. Third, target-domain manifold regularization is added to smooth the classification boundaries to cut through low-density regions, thus further increasing the target-domain classification accuracy. The real-world experiment demonstrates that the proposed JDA-S2ELM could increase the target-domain accuracy from about 30% to 90%, which means that V-RGC is adaptable to a dynamic environment. • A novel vibration-based robotic ground classifier (V-RGC) is proposed. • Projected maximum mean discrepancy is used to estimate distribution discrepancy. • Target-domain manifold regularization is used to improve classification consistency. [ABSTRACT FROM AUTHOR]