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Mead Brandt posted an update 6 months ago
The study of the microstructure of random heterogeneous materials, related to an electrochemical device, is relevant because their effective macroscopic properties, e.g., electrical or proton conductivity, are a function of their effective transport coefficients (ETC). The magnitude of ETC depends on the distribution and properties of the material phase. In this work, an algorithm is developed to generate stochastic two-phase (binary) image configurations with multiple geometries and polydispersed particle sizes. The recognizable geometry in the images is represented by the white phase dispersed and characterized by statistical descriptors (two-point and line-path correlation functions). Percolation is obtained for the geometries by identifying an infinite cluster to guarantee the connection between the edges of the microstructures. Finally, the finite volume method is used to determine the ETC. Agglomerate phase results show that the geometry with the highest local current distribution is the triangular geometry. In the matrix phase, the most significant results are obtained by circular geometry, while the lowest is obtained by the 3-sided polygon. The proposed methodology allows to establish criteria based on percolation and surface fraction to assure effective electrical conduction according to their geometric distribution; results provide an insight for the microstructure development with high projection to be used to improve the electrode of a Membrane Electrode Assembly (MEA).Molecular modeling is widely utilized in subjects including but not limited to physics, chemistry, biology, materials science and engineering. Impressive progress has been made in development of theories, algorithms and software packages. To divide and conquer, and to cache intermediate results have been long standing principles in development of algorithms. Not surprisingly, most important methodological advancements in more than half century of molecular modeling are various implementations of these two fundamental principles. In the mainstream classical computational molecular science, tremendous efforts have been invested on two lines of algorithm development. The first is coarse graining, which is to represent multiple basic particles in higher resolution modeling as a single larger and softer particle in lower resolution counterpart, with resulting force fields of partial transferability at the expense of some information loss. The second is enhanced sampling, which realizes “dividing and conquering” anle formulations and algorithms for “dividing and conquering” and “caching” in complex molecular systems.Antimicrobial resistance is one of the biggest threats to global health as current antibiotics are becoming useless against resistant infectious pathogens. Consequently, new antimicrobial strategies are urgently required. Drug delivery systems represent a potential solution to improve current antibiotic properties and reverse resistance mechanisms. Among different drug delivery systems, solid lipid nanoparticles represent a highly interesting option as they offer many advantages for nontoxic targeted drug delivery. Several publications have demonstrated the capacity of SLNs to significantly improve antibiotic characteristics increasing treatment efficiency. In this review article, antibiotic-loaded solid lipid nanoparticle-related works are analyzed to summarize all information associated with applying these new formulations to tackle the antibiotic resistance problem. The main antimicrobial resistance mechanisms and relevant solid lipid nanoparticle characteristics are presented to later discuss the potential of these nanoparticles to improve current antibiotic treatment characteristics and overcome antimicrobial resistance mechanisms. Moreover, solid lipid nanoparticles also offer new possibilities for other antimicrobial agents that cannot be administrated as free drugs. The advantages and disadvantages of these new formulations are also discussed in this review. Finally, given the progress of the studies carried out to date, future directions are discussed.The study aimed to investigate the acute effects of handheld loading on standing broad jump (SBJ) performance and biomechanics. Fifteen youth male athletes (mean age 14.7 ± 0.9 years; body mass 59.3 ± 8.0 kg; height 1.73 ± 0.07 m) volunteered to participate in the study. Participants were assigned to perform SBJ with and without 4 kg dumbbells in a random order. Kinematic and kinetic data were collected using 10 infrared high-speed motion-capture cameras at a 250 Hz sampling rate and two force platforms at a 1000 Hz sampling rate. A paired t-test was applied to all variables to determine the significance between loading and unloading SBJs. Horizontal distance (p less then 0.001), take-off distance (p = 0.001), landing distance (p less then 0.001), horizontal velocity of center of mass (CoM; p less then 0.001), push time (p less then 0.001), vertical impulse (p = 0.003), and peak horizontal and vertical ground reaction force (GRF; p less then 0.001, p = 0.017) were significantly greater in loading SBJ than in unloading SBJ. The take-off vertical velocity of CoM (p = 0.001), take-off angle (p less then 0.001), peak knee and hip velocity (p less then 0.001, p = 0.007), peak ankle and hip moment (p = 0.006, p = 0.011), and peak hip power (p = 0.014) were significantly greater in unloading SBJ than in loading SBJ. Conclusions Acute enhancement in SBJ performance was observed with handheld loading. Barasertib concentration The present findings contribute to the understanding of biomechanical differences in SBJ performance with handheld loading and are highly applicable to strength and conditioning training for athletes.We previously reported lower counts of lactobacilli and Bifidobacterium in the gut microbiota of patients with major depressive disorder (MDD), compared with healthy controls. This prompted us to investigate the possible efficacy of a probiotic strain, Lacticaseibacillus paracasei strain Shirota (LcS; basonym, Lactobacillus casei strain Shirota; daily intake of 8.0 × 1010 colony-forming units), in alleviating depressive symptoms. A single-arm trial was conducted on 18 eligible patients with MDD or bipolar disorder (BD) (14 females and 4 males; 15 MDD and 3 BD), assessing changes in psychiatric symptoms, the gut microbiota, and biological markers for intestinal permeability and inflammation, over a 12-week intervention period. Depression severity, evaluated by the Hamilton Depression Rating Scale, was significantly alleviated after LcS treatment. The intervention-associated reduction of depressive symptoms was associated with the gut microbiota, and more pronounced when Bifidobacterium and the Atopobium clusters of the Actinobacteria phylum were maintained at higher counts.