As DenseNet conserves intermediate features with diverse receptive fields by aggregating them with dense connection, it shows good performance on the object detection task. Although feature reuse enables DenseNet to produce strong features with a small number of model parameters and FLOPs, the detector with DenseNet backbone shows rather slow speed and low energy efficiency. We find the linearly increasing input channel by dense connection leads to heavy memory access cost, which causes computation overhead and more energy consumption. To solve the inefficiency of DenseNet, we propose an energy and computation efficient architecture called VoVNet comprised of One-Shot Aggregation (OSA). The OSA not only adopts the strength of DenseNet that represents diversified features with multi receptive fields but also overcomes the inefficiency of dense connection by aggregating all features only once in the last feature maps. To validate the effectiveness of VoVNet as a backbone network, we design both lightweight and largescale VoVNet and apply them to one-stage and two-stage object detectors. Our VoVNet based detectors outperform DenseNet based ones with 2× faster speed and the energy consumptions are reduced by 1.6× -4.1×. In addition to DenseNet, VoVNet also outperforms widely used ResNet backbone with faster speed and better energy efficiency. In particular, the small object detection performance has been significantly improved over DenseNet and ResNet. Inception-V4 [24], ResNet [7], and DenseNet [9], it has become mainstream in object detector to adopt the modern state-of-the-art CNN models as feature extractor. As DenseNet is reported to achieve state-of-the-art performance in the classification task recently, it is natural to attempt to expand its usage to detection tasks. In our experiment (Table 4), we find that the DenseNet based detectors with fewer parameters and FLOPs outperform the detectors with ResNet, which is most widely used for the backbone of object detections. The main difference between ResNet and DenseNet is the way they aggregate their features; ResNet aggregates the features from shallower by summation while DenseNet does it by concatenation. As mentioned by Zhu et al. [32], arXiv:1904.09730v1 [cs.CV]

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This paper provides an overview of the current literature and scientific evidence surrounding inorganic nitrate (NO3−) supplementation and its potential for improving human health and physical performance. As indicative of the ever-expanding organic and natural food consumer market, athletes and health enthusiasts alike are constantly searching for ingredient-specific “super foods” and dietary supplements capable of eliciting health and performance benefits. Evidence suggests that NO3− is the viable active component within beetroot juice (BRJ) and other vegetables, responsible for health-promoting and ergogenic effects. Indeed, multiple studies support NO3− supplementation as an effective method to improve exercise performance. NO3− supplementation (either as BRJ or sodium nitrate [NaNO3−]) has also demonstrated modest benefits pertaining to cardiovascular health, such as reducing blood pressure (BP), enhancing blood flow, and elevating the driving pressure of O2 in the microcirculation to areas of hypoxia or exercising tissue. These findings are important to cardiovascular medicine/exercise physiology and suggest a possible role for NO3− supplementation: (1) as a low-cost prevention and treatment intervention for patients suffering from blood flow disorders; and (2) an effective, natural ergogenic aid for athletes. Benefits have been noted following a single bolus, as well as daily supplementation of NO3−. While results are promising, additional research is needed to determine the impact of NO3− supplementation on anaerobic exercise performance, to identify principle relationships between isolated nitrate and other ingredients found in nitrate-rich vegetables (e.g., vitamin C, polyphenols, fatty acids, thiocyanate), to explore the specific dose-response relationships needed to elicit health and ergogenic benefits, to prolong the supplementation period beyond a relatively short period (i.e., >15 days), to determine if more robust effects can be observed with longer-term treatment, and to fully examine the safety of chronic NO3− supplementation, as this continues to be a concern of some.

HFD-induced obesity adversely affected function in middle-aged mice. Atrophy of the soleus in HFD but not C suggests sensitivity of oxidative muscle to HFD-dependent catabolism more so than aging. In the muscles containing fast/mixed fibers, aging effects may have concealed the catabolic nature of HFD; however, morphological changes in the gastrocnemius including decreased fiber area, satellite cells, and myonuclei are consistent with an atrophic phenotype related to HFD.

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