The effects of coffee ingestion on the acute testosterone response to exercise

Abstract This study investigated the effects of coffee ingestion (COF) on serum testosterone responses to exercise in recreationally weight-trained males. Subjects ingested either 12 ounces of 6mg/kg caffeinated coffee (COF), decaffeinated coffee (DEC), or water (PLA) one hour prior to exercise in a randomized, within-subject, crossover design. The exercise session consisted of 21 minutes of high intensity interval cycling (alternating intensities corresponding to two minutes at power outputs associated with 2.0 mmol/L lactate and 4.0 mmol/L lactate) followed by resistance exercise (7 exercises, 3 sets of 10 repetitions, 65% 1RM, 1-minute rest periods). Subjects also completed repetitions to fatigue tests and soreness scales to determine muscle recovery 24 hours following the exercise. T was elevated immediately and 30-minutes post-exercise by 20.5% and 14.3% respectively (p0.05). No relationships were observed between T and any proxy of recovery, suggesting that adopting high testosterone strategies may not always improve quality of subsequent exercise bouts. The duration of T elevation indicates that this protocol is beneficial to creating a long-lasting anabolic environment. While past literature suggests caffeine may enhance T post-exercise, data from the current study suggest that augmented T response is not evident following caffeine supplementation via coffee

Channel-levee complexes and sediment flux of the upper Indus Fan

The Indus Fan with a volume of 4.5 million km³ is the second largest submarine fan on Earth, only behind its neighbor to the east The Bengal Fan. It formed off the passive margin of Pakistan-India in the northern Arabian Sea. One of the more important aspects of the Indus Fan is its mostly complete sediment record of what has been eroded from the western Himalayan and Karakoram Mountains which act as the main source for the Indus River system. Since the initiation of the Himalaya about 50 Ma, sedimentation rates have fluctuated. This study attempts to calculate a new sediment budget for the Indus Fan and compare channel-levee complex architecture to periods of high and low sediment fluxes. Due to the quality of the 2D seismic available, multiple components of the channel-levee architecture were able to be interpreted which allowed for the reconstruction of how each complex built over time. The results of this study suggest peak sedimentation occurred during the late Miocene to early Pliocene. Multiple data sources support this period of peak sedimentation was caused by the onset of global cooling that began around 3 Ma. The climate change did not allow for fluvial and glacial systems to reach equilibrium. These results differ with previous work in that a steady increase in sedimentation rates were calculated to occur up until the late Miocene. In the early Pliocene, sedimentation rates started to decrease again till recent time

Online Convex Optimization with Binary Constraints

We consider online optimization with binary decision variables and convex loss functions. We design a new algorithm, binary online gradient descent (bOGD) and bound its expected dynamic regret. We provide a regret bound that holds for any time horizon and a specialized bound for finite time horizons. First, we present the regret as the sum of the relaxed, continuous round optimum tracking error and the rounding error of our update in which the former asymptomatically decreases with time under certain conditions. Then, we derive a finite-time bound that is sublinear in time and linear in the cumulative variation of the relaxed, continuous round optima. We apply bOGD to demand response with thermostatically controlled loads, in which binary constraints model discrete on/off settings. We also model uncertainty and varying load availability, which depend on temperature deadbands, lockout of cooling units and manual overrides. We test the performance of bOGD in several simulations based on demand response. The simulations corroborate that the use of randomization in bOGD does not significantly degrade performance while making the problem more tractable

On the connection between the theorems of Gleason and of Kochen and Specker

We present an elementary proof of a reduced version of Gleason's theorem and the Kochen-Specker theorem to provide a novel perspective on the relation between both theorems. The proof is based on a set of linear equations for the values of a function $m$ on the unit sphere. In the case of Gleason's theorem the entire unit sphere needs to be considered, while a finite set of points suffices to prove the Kochen-Specker theorem.Comment: 8 pages, 5 figure

Learning to Shift Thermostatically Controlled Loads

Demand response is a key mechanism for accommodating renewable power in the electric grid. Models of loads in demand response programs are typically assumed to be known a priori, leaving the load aggregator the task of choosing the best command. However, accurate load models are often hard to obtain. To address this problem, we propose an online learning algorithm that performs demand response while learning the model of an aggregation of thermostatically controlled loads. Specifically, we combine an adversarial multi-armed bandit framework with a standard formulation of load-shifting. We develop an Exp3-like algorithm to solve the learning problems. Numerical examples based on Ontario load data confirm that the algorithm achieves sub-linear regret and performs within 1% of the ideal case when the load is perfectly known.

Second-order Online Nonconvex Optimization

We present the online Newton's method, a single-step second-order method for online nonconvex optimization. We analyze its performance and obtain a dynamic regret bound that is linear in the cumulative variation between round optima. We show that if the variation between round optima is limited, the method leads to a constant regret bound. In the general case, the online Newton's method outperforms online convex optimization algorithms for convex functions and performs similarly to a specialized algorithm for strongly convex functions. We simulate the performance of the online Newton's method on a nonlinear, nonconvex moving target localization example and find that it outperforms a first-order approach

Endperiodic maps via pseudo-Anosov flows

We show that every atoroidal endperiodic map of an infinite-type surface can be obtained from a depth one foliation in a fibered hyperbolic 3-manifold, reversing a well-known construction of Thurston. This can be done almost-transversely to the canonical suspension flow, and as a consequence we recover the Handel-Miller laminations of such a map directly from the fibered structure. We also generalize from the finite-genus case the relation between topological entropy, growth rates of periodic points, and growth rates of intersection numbers of curves. Fixing the manifold and varying the depth one foliations, we obtain a description of the Cantwell-Conlon foliation cones and a proof that the entropy function on these cones is continuous and convex.Comment: 50 pages, 12 figure

S21RS SGR No. 3 (Rouses)

A Resolution To Urge LSU Administration to request for “Rouses Markets” to address the LSU community, in light of recent controversy among the LSU community, to reassure their commitment to diversity, democracy, inclusivity, and promotion of truth