Distributed deep reinforcement learning for functional split control in energy harvesting virtualized small cells

To meet the growing quest for enhanced network capacity, mobile network operators (MNOs) are deploying dense infrastructures of small cells. This, in turn, increases the power consumption of mobile networks, thus impacting the environment. As a result, we have seen a recent trend of powering mobile networks with harvested ambient energy to achieve both environmental and cost benefits. In this paper, we consider a network of virtualized small cells (vSCs) powered by energy harvesters and equipped with rechargeable batteries, which can opportunistically offload baseband (BB) functions to a grid-connected edge server depending on their energy availability. We formulate the corresponding grid energy and traffic drop rate minimization problem, and propose a distributed deep reinforcement learning (DDRL) solution. Coordination among vSCs is enabled via the exchange of battery state information. The evaluation of the network performance in terms of grid energy consumption and traffic drop rate confirms that enabling coordination among the vSCs via knowledge exchange achieves a performance close to the optimal. Numerical results also confirm that the proposed DDRL solution provides higher network performance, better adaptation to the changing environment, and higher cost savings with respect to a tabular multi-agent reinforcement learning (MRL) solution used as a benchmark

Progressive feature transmission for split classification at the wireless edge

We consider the scenario of inference at the wire-less edge , in which devices are connected to an edge server and ask the server to carry out remote classification, that is, classify data samples available at edge devices. This requires the edge devices to upload high-dimensional features of samples over resource-constrained wireless channels, which creates a communication bottleneck. The conventional feature pruning solution would require the device to have access to the inference model, which is not available in the current split inference scenario. To address this issue, we propose the progressive feature transmission (ProgressFTX) protocol, which minimizes the overhead by progressively transmitting features until a target confidence level is reached. A control policy is proposed to accelerate inference, comprising two key operations: importance-aware feature selection at the server and transmission-termination control . For the former, it is shown that selecting the most important features, characterized by the largest discriminant gains of the corresponding feature dimensions, achieves a sub-optimal performance. For the latter, the proposed policy is shown to exhibit a threshold structure. Specifically, the transmission is stopped when the incremental uncertainty reduction by further feature transmission is outweighed by its communication cost. The indices of the selected features and transmission decision are fed back to the device in each slot. The control policy is first derived for the tractable case of linear classification, and then extended to the more complex case of classification using a convolutional neural network . Both Gaussian and fading channels are considered. Experimental results are obtained for both a statistical data model and a real dataset. It is shown that ProgressFTX can substantially reduce the communication latency compared to conventional feature pruning and random feature transmission strategies

Additive Manufacturing of High Solids Loading Hybrid Rocket Fuel Grains

Hybrid rocket motors offer many of the benefits of both liquid and solid rocket systems. Like liquid engines, hybrid rocket motors are able to be throttled, can be stopped and restarted, and are safer than solid rocket motors since the fuel and oxidizer are in different physical states. Hybrid rocket motors are similar to solid motors in that they are relatively simple and have a high density-specific impulse. One of the major drawbacks of hybrid rocket motors is a slower burning rate than solid rocket motors. Complex port geometries provide greater burning surface area to compensate for lower burning rates but are difficult and expensive to manufacture. Additive manufacturing can reduce manufacturing costs of these complex port geometry fuel grains. It has also been shown that the addition of energetic materials, such as aluminum, can increase the burning rate and density-specific impulse of the rocket motor. Previously, additive manufacturing was restricted to plastics or fast-setting paraffin wax, both with low solids concentrations. This paper investigates the process of printing hybrid rocket fuel grains and the differences in physical characteristics between printed and conventionally cast samples. Using a proprietary printing system, we have successfully printed 85% solids loading aluminum and HTPB fuel samples. Material creep was significant and resulted in samples bulging and sagging as well as gaps between print lines being filled in more completely. The finish and cross sections of printed samples were of comparable quality to cast samples. This indicates that the manufacturing process has not significantly affected the physical characteristics of the fuel samples

Investigation the anterior mandibular lingual concavity by using cone-beam computed tomography

Background: In the presence of lingual concavity in the mandible, the cortical perforation and consequently the life-threatening intraoral hemorrhages obstructing the upper respiratory tract may be seen during the surgical intervention. In the present study, it was aimed to determine the prevalence of lingual concavity in the interforaminal region and to determine its relationship with gender and dentate status. Material and methods: The images of 106 patients undergone cone-beam computed tomography (CBCT) between 2016 and 2017 in Department of Dental and Maxillofacial Radiology Department of Faculty of Dentistry of Ondokuz Mayıs University were retrospectively examined. The images were obtained using a Galileos device (98 kVp, 15-30 mA). The bone height and width in interforaminal region and the frequency of lingual concavity were analyzed. Results: Of patients involved in the present study, 42.5% were male and 57.5% were female After the examinations performed, the bone was morphologically classified into four classes as Type I lingual concavity, Type II inclined to lingual, Type III enlarging towards labiolingual and Type IV buccal concavity. Type III (77.9%) was the most common type in the anterior region, followed by Type II (16.5%), Type I (4.7%) and Type IV (0.9%). The lingual concavity angle was 76.5 ± 3.69º and the concavity depth was 2.09 ± 0.34 mm. Conclusions: The lingual concavity can be detected by using the cross-sectional CBCT images and the complications related with lingual cortical perforation can be prevented

The tracking of speech envelope in the human cortex

Abstract Humans are highly adept at processing speech. Recently, it has been shown that slow temporal information in speech (i.e., the envelope of speech) is critical for speech comprehension. Furthermore, it has been found that evoked electric potentials in human cortex are correlated with the speech envelope. However, it has been unclear whether this essential linguistic feature is encoded differentially in specific regions, or whether it is represented throughout the auditory system. To answer this question, we recorded neural data with high temporal resolution directly from the cortex while human subjects listened to a spoken story. We found that the gamma activity in human auditory cortex robustly tracks the speech envelope. The effect is so marked that it is observed during a single presentation of the spoken story to each subject. The effect is stronger in regions situated relatively early in the auditory pathway (belt areas) compared to other regions involved in speech processing, including the superior temporal gyrus (STG) and the posterior inferior frontal gyrus (Broca's region). To further distinguish whether speech envelope is encoded in the auditory system as a phonological (speech-related), or instead as a more general acoustic feature, we also probed the auditory system with a melodic stimulus. We found that belt areas track melody envelope weakly, and as the only region considered. Together, our data provide the first direct electrophysiological evidence that the envelope of speech is robustly tracked in non-primary auditory cortex (belt areas in particular), and suggest that the considered higher-order regions (STG and Broca's region) partake in a more abstract linguistic analysis

Learning to speak on behalf of a group: medium access control for sending a shared message

The rapid development of Internet of Things (IoT) technologies has not only enabled new applications, but also presented new challenges for reliable communication with limited resources. In this work, we define a novel problem that can arise in these scenarios, in which a set of sensors need to communicate a joint observation. This observation is shared by a random subset of the nodes, which need to propagate it to the rest of the network, but coordination is complex: as signaling constraints require the use of random access schemes over shared channels, sensors need to implicitly coordinate, so that at least one transmission gets through without collisions. Unlike the majority of existing medium access schemes, the goal is to make sure that the shared message gets through, regardless of the sender. We analyze this coordination problem theoretically and provide low-complexity solutions. While a clustering-based approach is near-optimal if the sensors have prior knowledge, we provide a distributed multi-armed bandit (MAB) solution for the more general case and validate it by simulation

The Influence of the effect of solute on the thermodynamic driving force on grain refinement of Al alloys

Grain refinement is known to be strongly affected by the solute in cast alloys. Addition of some solute can reduce grain size considerably while others have a limited effect. This is usually attributed to the constitutional supercooling which is quantified by the growth restriction factor, Q. However, one factor that has not been considered is whether different solutes have differing effects on the thermodynamic driving force for solidification. This paper reveals that addition of solute reduces the driving force for solidification for a given undercooling, and that for a particular Q value, it is reduced more substantially when adding eutectic-forming solutes than peritectic-forming elements. Therefore, compared with the eutectic-forming solutes, addition of peritectic-forming solutes into Al alloys not only possesses a higher initial nucleation rate resulted from the larger thermodynamic driving force for solidification, but also promotes nucleation within the constitutionally supercooled zone during growth. As subsequent nucleation can occur at smaller constitutional supercoolings for peritectic-forming elements, a smaller grain size is thus produced. The very small constitutional supercooling required to trigger subsequent nucleation in alloys containing Ti is considered as a major contributor to its extraordinary grain refining efficiency in cast Al alloys even without the deliberate addition of inoculants.The Australian Research Council (ARC DP10955737)

Identification of a novel gene regulating amygdala-mediated fear extinction.

Recent years have seen advances in our understanding of the neural circuits associated with trauma-related disorders, and the development of relevant assays for these behaviors in rodents. Although inherited factors are known to influence individual differences in risk for these disorders, it has been difficult to identify specific genes that moderate circuit functions to affect trauma-related behaviors. Here, we exploited robust inbred mouse strain differences in Pavlovian fear extinction to uncover quantitative trait loci (QTL) associated with this trait. We found these strain differences to be resistant to developmental cross-fostering and associated with anatomical variation in basolateral amygdala (BLA) perineuronal nets, which are developmentally implicated in extinction. Next, by profiling extinction-driven BLA expression of QTL-linked genes, we nominated Ppid (peptidylprolyl isomerase D, a member of the tetratricopeptide repeat (TPR) protein family) as an extinction-related candidate gene. We then showed that Ppid was enriched in excitatory and inhibitory BLA neuronal populations, but at lower levels in the extinction-impaired mouse strain. Using a virus-based approach to directly regulate Ppid function, we demonstrated that downregulating BLA-Ppid impaired extinction, while upregulating BLA-Ppid facilitated extinction and altered in vivo neuronal extinction encoding. Next, we showed that Ppid colocalized with the glucocorticoid receptor (GR) in BLA neurons and found that the extinction-facilitating effects of Ppid upregulation were blocked by a GR antagonist. Collectively, our results identify Ppid as a novel gene involved in regulating extinction via functional actions in the BLA, with possible implications for understanding genetic and pathophysiological mechanisms underlying risk for trauma-related disorders