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IntroductionFollowing early cell specification and tenocyte differentiation at the sites of future tendons, very little is known about how tendon maturation into robust load-bearing tissue is regulated. Between embryonic day (E)16 and E18 in the chick, there is a rapid change in mechanical properties which is dependent on normal embryo movement. However, the tissue, cellular and molecular changes that contribute to this transition are not well defined. MethodsHere we profiled aspects of late tendon development (collagen fibre alignment, cell organisation and Yap pathway activity), describing changes that coincide with tissue maturation. We compared effects of rigid (constant static loading) and flaccid (no loading) immobilisation to gain insight into developmental steps influenced by mechanical cues. ResultsWe show that YAP signalling is active and responsive to movement in late tendon. Collagen fibre alignment increased over time and under static loading. Cells organise into end-to-end stacked columns with increased distance between adjacent columns, where collagen fibres are deposited; this organisation was lost following both types of immobilisation. DiscussionWe conclude that specific aspects of tendon maturation require controlled levels of dynamic muscle-generated stimulation. Such a developmental approach to understanding how tendons are constructed will inform future work to engineer improved tensile load-bearing tissues. 

The central difference is a popular algorithm used to integrate the equations of motion, yet suffers from two drawbacks: (1) it is only conditionally stable and requires a small-time step to maintain numerical stability; (2) it is nondissipative, and high-frequency spurious oscillations may appear and compromise the accuracy of the solution. These drawbacks are detrimental to applying the algorithm to the real-time hybrid simulation of large, complex nonlinear structural systems. In this paper, the conventional central difference algorithm is modified to overcome these drawbacks, and the modified algorithm is applied to the real-time hybrid simulation of complex structural systems. 

Abstract We investigate the applicability and performance of the plasma physics based WINDMI model to the analysis and identification of substorm onsets. There are several substorm onset criteria that have been developed into event lists, either from auroral observations or from auroral electrojet features. Five of these substorm onset lists are available at the SuperMAG website. We analyze these lists, aggregate them and use the WINDMI model to assess the identified events, emphasizing the loading/unloading mechanism in substorm dynamics. The WINDMI model employs eight differential equations utilizing solar wind data measured at L1 by the ACE satellite as input to generate outputs such as the magnetotail current, the ring current and the field‐aligned currents (FACs). In particular, the WINDMI model current output represents the westward auroral electrojet, which is related to the substorm SML index. We analyze a decade of solar wind and substorm onset data from 1998 to 2007, encompassing 39,863 onsets. Our findings reveal a significant correlation, with WINDMI‐derived enhancements in FAC coinciding with the identified substorm events approximately 32% of the time. This suggests that a substantial proportion of substorms may be attributed to solar wind driving that results in the loading and unloading of energy in the magnetotail. 

Abstract Radiation Belt Storm Probes (RBSP) data show that seed electrons generated by sub‐storm injections play a role in amplifying chorus waves in the magnetosphere. The wave‐particle interaction leads to rapid heating and acceleration of electrons from 10's of keV to 10's of MeV energies. In this work, we examined the changes in the radiation belt during geomagnetic storm events by studying the RBSP REPT, solar wind, AL, SML, and Dst data in conjunction with the WINDMI model of the magnetosphere. The field‐aligned current output from the model is integrated to generate a proxy E index for various energy bands. These E indices track electron energization from 40 KeV to 20 MeV in the radiation belts. The indices are compared to RBSP data and GOES data. Our proxy indices correspond well to the energization data for electron energy bands between 1.8 and 7.7 MeV. Each E index has a unique empirical loss rate term (τ_L), an empirical time delay term (τ_D), and a gain value, that are fit to the observations. These empirical parameters were adjusted to examine the delay and charging rates associated with different energy bands. We observed that theτ_Landτ_Dvalues are clustered for each energy band.τ_Landτ_Dconsistently increase going from 1.8 to 7.7 MeV in electron energy fluxE_eand the dropout interval increases with increasing energy level. The average trend of Δτ_D/ΔE_ewas 4.1 hr/MeV and the average trend of Δτ_L/ΔE_ewas 2.82 hr/MeV.