Periodization for Massive Strength Gains

In order to create the perfect resistance training program for their athletes, coaches must master the ability to control all variables of training over time in order to maximize physiological responses - this is a concept known as periodization (3, 6, 7, 8, 9, 10, 19, 21, 24, 25, 26). Periodization was first established in Russia, after the conclusion of the 1956 Olympic games (7, 21). Though simple in its principle and aim, periodization is frequently misunderstood due to the hyper-specific research that surrounds it (3, 4, 7, 8, 10, 15, 21, 23, 25). Over the last five decades, researchers have produced a multitude of studies that look at specific variables of periodization, which this paper will later examine, but many of them prove to be inconclusive due to uncontrollable factors outside of training (3, 4, 7, 8, 13, 14, 19, 21). These uncontrollable factors make it difficult to be absolute in any conclusions surrounding the topic of periodization, though there are a number of considerations that make periodization very valuable (25). Periodization is of paramount importance when creating resistance training plans due to its role in the manipulation and subsequent control of variables over time (3, 6, 7, 8, 9, 10, 19, 21, 24, 25, 26). Without control of variables, resistance training becomes an aimless and non goal-oriented task (25, 43). In comparison with non-periodized resistance programs, periodized plans prove to be significantly more effective in strength gained, lean mass gained, and percent body fat lost (1, 5, 6, 11, 15, 25). Periodization will likely remain a topic of controversy for a long time to come, as coaches continue to seek the most effective combination and manipulation of training variables at their disposal (23)

Exchange Bias driven by Dzyaloshinskii-Moriya interactions

The exchange bias effect in compensated IrMn3/Co(111) system is studied using multiscale modeling from "ab initio" to atomistic calculations. We evaluate numerically the out-of-plane hysteresis loops of the bi-layer for different thickness of the ferromagnetic layer. The results show the existence of a perpendicular exchange bias field and an enhancement of the coercivity of the system. In order to elucidate the possible origin of the exchange bias, we analyze the hysteresis loops of a selected bi-layer by tuning the different contributions to the exchange interactions across the interface. Our results indicate that the exchange bias is primarily induced by the Dzyaloshinskii-Moriya interactions, while the coercivity is increased mainly due to a spin-flop mechanism

El asno zamorano-leonés, tradición cultural viva y bienestar

El asno Zamorano-Leonés pertenece a una raza autóctona, hoy en peligro de extinción, que ha formado parte de economías de autoabastecimiento a las que ha servido de manera notable con su sistema de provechamiento, y que aún es una parte viva de una cultura tradicional. En la actualidad continúa prestando en buena medida los mismos servicios a sus propietarios tradicionales, pero han aparecido otros nuevos. Se ha tenido como objetivo de estudio el aprovechamiento tradicional actual, los nuevos usos, así como la evolución surgida en la relación de su tenencia y los beneficios que otorga

Censored deep reinforcement patrolling with information criterion for monitoring large water resources using Autonomous Surface Vehicles

© 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)Monitoring and patrolling large water resources is a major challenge for nature conservation. The problem of acquiring data of an underlying environment that usually changes within time involves a proper formulation of the information. The use of Autonomous Surface Vehicles equipped with water quality sensor modules can serve as an early-warning system for contamination peak-detection, algae blooms monitoring, or oil-spill scenarios. In addition to information gathering, the vehicle must plan routes that are free of obstacles on non-convex static and dynamics maps. This work proposes a novel framework to obtain a collision-free policy using deterministic knowledge of the environment by means of a censoring operator and noisy networks that addresses the informative path planning with emphasis in temporal patrolling. Using information gain as a measure of the uncertainty reduction over data, it is proposed a Deep Q-Learning algorithm improved by a Q-Censoring mechanism for model-based obstacle avoidance. The obtained results demonstrate the effectiveness of the proposed algorithm for both cases in the Ypacaraí monitorization task. Simulations showed that the use of noisy-networks are a good choice for enhanced exploration, with 3 times less redundancy in the paths with respect to — greedy policy. Previous coverage strategies are also outperformed both in the accuracy of the obtained contamination model by a 13% on average and by a 37% in the detection of dangerous contamination peaks. Finally, the achieved results indicate the appropriateness of the proposed framework for monitoring scenarios with autonomous vehicles

A Multiagent Deep Reinforcement Learning Approach for Path Planning in Autonomous Surface Vehicles: The Ypacaraí Lake Patrolling Case

Article number 9330612Autonomous surfaces vehicles (ASVs) excel at monitoring and measuring aquatic nutrients due to their autonomy, mobility, and relatively low cost. When planning paths for such vehicles, the task of patrolling with multiple agents is usually addressed with heuristics approaches, such as Reinforcement Learning (RL), because of the complexity and high dimensionality of the problem. Not only do efficient paths have to be designed, but addressing disturbances in movement or the battery’s performance is mandatory. For this multiagent patrolling task, the proposed approach is based on a centralized Convolutional Deep Q-Network, designed with a final independent dense layer for every agent to deal with scalability, with the hypothesis/assumption that every agent has the same properties and capabilities. For this purpose, a tailored reward function is created which penalizes illegal actions (such as collisions) and rewards visiting idle cells (cells that remains unvisited for a long time). A comparison with various multiagent Reinforcement Learning (MARL) algorithms has been done (Independent Q-Learning, Dueling Q-Network and multiagent Double Deep Q-Learning) in a case-study scenario like the Ypacaraí lake in Asunción (Paraguay). The training results in multiagent policy leads to an average improvement of 15% compared to lawn mower trajectories and a 6% improvement over the IDQL for the case-study considered. When evaluating the training speed, the proposed approach runs three times faster than the independent algorithm.Ministerio de Ciencia, Innovación y Universidades (España) RTI2018-098964-B-I00Junta de Andalucía(España) PY18-RE000

Constrained Monte Carlo Method and Calculation of the Temperature Dependence of Magnetic Anisotropy

We introduce a constrained Monte Carlo method which allows us to traverse the phase space of a classical spin system while fixing the magnetization direction. Subsequently we show the method's capability to model the temperature dependence of magnetic anisotropy, and for bulk uniaxial and cubic anisotropies we recover the low-temperature Callen-Callen power laws in M. We also calculate the temperature scaling of the 2-ion anisotropy in L10 FePt, and recover the experimentally observed M^2.1 scaling. The method is newly applied to evaluate the temperature dependent effective anisotropy in the presence of the N'eel surface anisotropy in thin films with different easy axis configurations. In systems having different surface and bulk easy axes, we show the capability to model the temperature-induced reorientation transition. The intrinsic surface anisotropy is found to follow a linear temperature behavior in a large range of temperatures

Mediators of Interpersonal Psychotherapy for Depressed Adolescents On Outcomes in Latinos: The Role of Peer and Family Interpersonal Functioning

Peer and family interpersonal functioning were examined as mediators of the impact of Interpersonal Psychotherapy for Depressed Adolescents (IPT-A; Mufson, Dorta, Moreau, & Weissman, 2004) on depression and suicidal ideation among Latino youth. Only youth self-identifying as Latino (n = 50) were included in the analyses. The majority were female (86%) with a mean age of 14.58 (SD = 1.91). The current sample was drawn from the intent to treat sample of a clinical trial examining the effectiveness of IPT-A as compared with treatment as usual (TAU; Mufson, Dorta, Wickramaratne et al., 2004). Youth were randomly assigned to receive IPT-A or TAU delivered by school-based mental health clinicians. Assessments, completed at baseline and at Weeks 4, 8, and 12 (or at early termination), included self-report measures of depression and interpersonal functioning as well as clinician-Administered measures of depression. Multilevel modeling indicated that IPT-A led to greater improvement in interpersonal functioning with family and peers. Improved family and peer interpersonal functioning emerged as significant partial mediators of the relationship between IPT-A and depression. Only improved family interpersonal functioning emerged as a significant partial mediator of the relationship between IPT-A and suicidal ideation. However, this indirect effect was small, suggesting that most of the benefit of IPT-A for suicidal ideation appears to proceed through a pathway other than family interpersonal functioning. These results suggest that the impact of IPT-A on depressive symptoms is partially mediated by family and peer interpersonal functioning and contributes to our understanding of the mechanisms of IPT-A

Severe glomerular disease in juvenile grey snapper Lutjanus griseus L. in the Gulf of Mexico caused by the myxozoan Sphaerospora motemarini n. sp.

AbstractIn the eastern Gulf of Mexico, off the coast of Florida, grey snapper, Lutjanus griseus was found to be infected with the myxozoan parasite Sphaerospora motemarini n. sp., with high prevalence (83%) and intensity of infection occuring in age-0 fish, and with parasite levels decreasing with age (age-1 snapper 40%; age-2 snapper 0%). The morphological, molecular and phylogenetic characterisation of the myxozoan showed that it is a member of the typically marine, polysporoplasmid Sphaerospora spp. which form a subclade within the Sphaerospora sensu stricto clade of myxozoans, which is characterised by large expansion segments in their SSU rDNA sequences. Presporogonic stages of S. motemarini n. sp. were detected in the blood, using PCR. Pseudoplasmodia and spores were found to develop in the renal corpuscles of the host, causing their massive expansion. Macroscopic and histopathological changes were observed in age-0 fish and show that S. motemarini n. sp. causes severe glomerulonephritis in L. griseus leading to a compromised host condition, which makes it more susceptible to stress (catch-and-release, predators, water quality) and can result in mortalities. These results are discussed in relation to the exploitation of grey snapper populations by commercial and recreational fisheries and with the observed increased mortalities with temperature along the coast of Florida. In the future, we would like to determine prevalence and intensity of infection with S. motemarini n. sp. in juvenile L. griseus in different areas of the Gulf of Mexico in order to be able to estimate the temperature dependence of S. motemarini n. sp. proliferation and to be able to predict its distribution and severity during climatic changes in the Gulf