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The rate of force development (RFD) in the isometric leg press (ILP), the countermovement jump (CMJ) and the squat jump (SJ) were examined in twenty-three (9 females) team sport athletes aged 21-24 years. Peak force (Fpeak), peak rate of force development (RFDpeak) and RFD at different time epochs (0-50, 50-100, 100-150, 150-200) were calculated from the force-time curve, as well as CMJ and SJ height and the center of mass displacement. RFDpeak, RFD at 0-50, 50-100 and 100-150 ms and Fpeak were similar between the CMJ and the SJ (p = 0.26 to 0.99). Furthermore, RFD0-50 ms was similar between the ILP, the CMJ, and the SJ (p = 0.99 to 0.57). Higher values were observed in the ILP compared with the CMJ and the SJ in RFD50-100 ms and RFD100-150 ms (p < 0.001) and these differences were maintained even when RFD was scaled to body mass. The higher RFD normalized to Fpeak was attained at the 50-100 ms time interval with no differences between the ILP, CMJ and SJ and between males and females. These results suggest that the ability to exert rapid force is similar between the CMJ and the SJ, irrespective of the type of muscle action. Furthermore, RFD normalized to Fpeak is a muscle-force independent index of explosive force production, facilitating comparisons between individuals with different levels of muscle strength. The similarities between the CMJ and the SJ in RFDpeak, Fpeak, and RFD at different time epochs may imply that these types of jumps could be used interchangeably to assess explosive lower limb performance.

The development of modern computing architectures with ever-increasing amounts of parallelism has allowed for the solution of previously intractable problems across a variety of scientific disciplines. Despite these advances, multiscale computing problems continue to pose an incredible challenge to modern architectures because they require resolving scales that often vary by orders of magnitude in both space and time. Such complications have led us to consider alternative discretizations for partial differential equations (PDEs) which use expansions involving integral operators to approximate spatial derivatives (Christlieb et al. in J Comput Phys 379:214–236, 2019; Christlieb et al. J Sci Comput 82:52(3):1–29, 2020; Christlieb et al. J Comput Phys 415:1–25, 2020). These constructions use explicit information within the integral terms, but treat boundary data implicitly, which contributes to the overall speed of the method. This approach is provably unconditionally stable for linear problems and stability has been demonstrated experimentally for nonlinear problems. Additionally, it is matrix-free in the sense that it is not necessary to invert linear systems and iteration is not required for nonlinear terms. Moreover, the scheme employs a fast summation algorithm that yields a method with a computational complexity of $${\mathcal {O}}(N)$$ , where N is the number of mesh points along a coordinate direction. While much work has been done to explore the theory behind these methods, their practicality in large scale computing environments is a largely unexplored topic. In this work, we explore the performance of these methods by developing a domain decomposition algorithm suitable for distributed memory systems along with shared memory algorithms. As a first pass, we derive an artificial Courant–Friedrichs–Lewy condition that enforces a nearest-neighbor (N-N) communication pattern and briefly discuss possible generalizations. We also analyze several approaches for implementing the parallel algorithms by optimizing predominant loop structures and maximizing data reuse. Using a hybrid design that employs MPI and Kokkos (Edwards and Trott in J Parallel Distrib Comput 74:3202–3216, 2014) for the distributed and shared memory components of the algorithms, respectively, we show that our methods are efficient and can sustain an update rate $$> 1\times 10^8$$ DOF/node/s. We provide results that demonstrate the scalability and versatility of our algorithms using several different PDE test problems, including a nonlinear example, which employs an adaptive time-stepping rule.

In \cite{christlieb2019kernel}, the authors developed a class of high-order numerical schemes for the Hamilton-Jacobi (H-J) equations, which are unconditionally stable, yet take the form of an explicit scheme. This paper extends such schemes, so that they are more effective at capturing sharp gradients, especially on nonuniform meshes. In particular, we modify the weighted essentially non-oscillatory (WENO) methodology in the previously developed schemes by incorporating an exponential basis and adapting the previously developed nonlinear filters used to control oscillations. The main advantages of the proposed schemes are their effectiveness and simplicity, since they can be easily implemented on higher-dimensional nonuniform meshes. We perform numerical experiments on a collection of examples, including H-J equations with linear, nonlinear, convex and non-convex Hamiltonians. To demonstrate the flexibility of the proposed schemes, we also include test problems defined on non-trivial geometry.

Understanding the face structure of the balanced minimal evolution (BME) polytope, especially its top-dimensional facets, is crucially important to phylogenetic applications. We show that BME polytope has a sub-lattice of its poset of faces which is isomorphic to a quotient of the well-studied permutoassociahedron. This sub-lattice corresponds to compatible sets of splits displayed by phylogenetic trees, and extends the lattice of faces of the BME polytope found by Hodge, Haws, and Yoshida. Each of the maximal elements in our new poset of faces corresponds to a single split of the leaves. Nearly all of these turn out to actually be facets of the BME polytope, a collection of facets which grows exponentially.

Biologists use phylogenetic trees, or phylogenies, to visualize genetic relatedness of organisms. Phylogenetic trees can be used at any scales—from determining the population structure of a single species, to displaying all life on planet Earth—under the assumption of a branching tree-like structure. This chapter introduces the key concept of using a distance matrix (created from genetic data) in order to infer phylogenies via the principle of Balanced Minimum Evolution (BME). Then we focus on finding the phylogeny via linear programming techniques, especially branch-and-bound on relaxations of the BME polytope. Related methods for finding a BME phylogeny include edge-walking with tree moves (as in the program FastMe ) and Neighbor Joining, a popular greedy algorithm for approximating the BME phylogeny. The skills used to infer and interpret a phylogenetic tree can be useful to many biological fields, including genetics and molecular biology, as well as applied research ranging from conservation of endangered species to tracking the spread of infectious diseases.

A phylogenetic tree is a way to organize a finite set of species, individuals or other sources of related data. The species for which we have existing DNA data make up the set of leaves of the tree. The balanced minimal evolution method of creating phylogenetic trees can be formulated as a linear programming problem, minimizing an inner product over the vertices of the BME polytope. In this paper we undertake the first steps of describing the facets of this polytope., Comment: 11 figures

MRL/MP-lpr/lpr (MRL/lpr) mice have a single mutation (lpr) of the fasapoptosis gene. The mutant mice developed significantly smaller lesions than the wild-type mice at the earlier stage of infection with the intracellular protozoan parasite Leishmania major. However, while all the wild-type mice achieved complete lesion resolution, the disease in the mutant mice progressed inexorably. The mutant mice had more IL-12 and nitrite/nitrate in the serum than wild-type mice following infection. Lymphoid cells from infected MRL/lpr mice produced more IFN-γ but less IL-4 and IL-5 than cells from MRL-+/+ mice. Peritoneal macrophages from the mutant mice also produced more IL-12 and NO after stimulation with LPS. Thus, Fas expression is essential for resistance against leishmaniasis, and Fas-mediated apoptosis may form an integral part of the Th1-mediated microbicidal function.

Scar tissue formation during healing of extensive skin wounds may be related to delayed reepithelialization, while elevated levels of hyaluronan may suppress scar tissue formation. This study investigates the expression of hyaluronan by human skin fibroblasts in response to keratinocyte-conditioned medium (KCM), and attempts to identify any active factors within the conditioned medium. Serum-free KCM was assessed for its ability to stimulate the incorporation of (3) H-glucosamine into fibroblast glycosaminoglycans, and hyaluronan synthesis. Conditioned medium was concentrated with an ultrafiltration membrane with a 30 kDa cutoff. Stratifin was assessed for its ability to stimulate hyaluronan synthesis and its role in KCM. KCM stimulated fibroblast glycosaminoglycan synthesis up to a 3.3-fold increase and a 6.5-fold increase in hyaluronan synthesis compared with serum-free controls. Preliminary characterization of the active factors showed that they are retained by a30 kDa ultrafiltration membrane, and are protease sensitive and heat resistant. Emmprin and stratifin were shown to stimulate fibroblast hyaluronan synthesis, and the hyaluronan-stimulating activity of KCM was removed following stratifin depletion and to a lesser extent by emmprin depletion. Keratinocytes release soluble factors, including stratifin, that stimulate fibroblast hyaluronan synthesis, and this stimulation of fibroblast hyaluronan may contribute to the suppression of scar tissue formation.

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