Aerothermal databases and load predictions for Retro Propulsion-Assisted Launch Vehicles (RETALT)

The assessment of thermal loads occurring on reusable launch vehicles during the entire trajectory is essential for the correct dimensioning of the thermal protection system. Due to the costs and limitations of ground-based testing for large-scale vehicles, these predictions rely intensively on numerical simulations (CFD). The need of aero-thermal databases, as a fast-response surrogate model for the aero-thermodynamic heating, arises from the practical impossibility of performing unsteady CFD analysis over the entire trajectory due to the large disparity of fluid mechanical and structural time scales. The construction of these databases is based on a representative set of CFD simulations which cover, at a minimum, the flight regimes with significant thermal loads. The aim of this paper is to analyse the results of these representative CFD simulations during both the ascent flight and atmospheric entry for the RETALT1 vehicle to show typical flow field phenomena occurring during these phases and the resulting heating patterns.

Anonymous Stochastic Routing

We propose and analyze a recipient-anonymous stochastic routing model to study a fundamental trade-off between anonymity and routing delay. An agent wants to quickly reach a goal vertex in a network through a sequence of routing actions, whereas an overseeing adversary observes the agent’s entire trajectory and tries to identify the agent’s goal among those vertices traversed. We are interested in understanding the probability that the adversary can correctly identify the agent’s goal (anonymity) as a function of the time it takes the agent to reach it (delay). A key feature of our model is the presence of intrinsic uncertainty in the environment, so that each of the agent’s intended steps is subject to random perturbation and thus may not materialize as planned. Using large-network asymptotics, our main results provide near-optimal characterization of the anonymity–delay trade-off under a number of network topologies. Our main technical contributions are centered on a new class of “noise-harnessing” routing strategies that adaptively combine intrinsic uncertainty from the environment with additional artificial randomization to achieve provably efficient obfuscation.

Frontiers in mathematical modelling of the lipid metabolism under normal conditions and its alterations in heart diseases

Pathophysiology of ischemic heart disease is a complex phenomenon determined by the interaction of multiple processes including the inflammatory, immunological, infectious, mechanical, biochemical and epigenetic ones. A predictive clinically relevant modelling of the entire trajectory of the human organism, from the initial alterations in lipid metabolism through to atherosclerotic plaque formation and finally to the pathologic state of the ischemic heart disease, is an open insufficiently explored problem. In the present review, we consider the existing mathematical frameworks which are used to describe, analyze and predict the dynamics of various processes related to cardiovascular diseases at the molecular, cellular, tissue, and holistic human organism level. The mechanistic, statistical and machine learning models are discussed in detail with special focus on the underlying assumptions and their clinical relevance. All together, they provide a solid computational platform for further expansion and tailoring for practical applications.

Simulative Analysis of a Family of DNA Tetrahedrons Produced by Changing the Twisting Number of Each Double Helix

In this paper, three tetrahedral nanocages, composed of six DNA double helix edges with all having the twist number 1, 2 or 3, have been characterized using classical molecular dynamics simulation to measure the specific structural and conformational features produced by only changing the twisting number of each double helix. The simulation result indicates that three tetrahedral cages are relatively stable and are maintained along the entire trajectory. Each double helix is more inclined to behave as a whole in the 2TD and 3TD cages than in the 1TD cage according to the cross-correlation maps for three nanocages, and also their local motions are more easily induced by the conformational variability of the thymidine linkers due to the increased flexibility of each helix. Hence, the double helices become the important factors on the structural stability of total cages with the DNA twisting number, and also give the signification contributions to the sizes of these cages conferring the larger spaces of the 2TD and 3TD cages than the 1TD cage. Our result provides an insight into which roles the double helix edges play in assembling DNA polyhedron, and also contribute to improving the loading capacity of DNA tetrahedron in drug delivery.

Pyrolyzed substrates induce aromatic compound metabolism in the post-fire fungus,Pyronema domesticum

ABSTRACTWildfires represent a fundamental and profound disturbance in many ecosystems, and their frequency and severity are increasing in many regions of the world. Fire affects soil by removing carbon in the form of CO2and transforming remaining surface carbon into pyrolyzed organic material (PyOM). Fires also generate substantial necromass at depths where the heat kills soil organisms but does not catalyze the formation of PyOM.Pyronemaspecies strongly dominate soil fungal communities within weeks to months after fire. However, the carbon pool (i.e. necromass or PyOM) that fuels their rise in abundance is unknown. We used aPyronema domesticumisolate from the catastrophic 2013 Rim Fire (CA, USA) to ask ifP. domesticumis capable of metabolizing PyOM.P. domesticumgrew readily on agar media where the sole carbon source was PyOM (specifically, pine wood PyOM produced at 750 °C). Using RNAseq, we investigated the response ofP. domesticumto PyOM and observed a comprehensive induction of genes involved in the metabolism and mineralization of aromatic compounds, typical of those found in PyOM. Lastly, we used13C-labeled 750 °C PyOM to demonstrate thatP. domesticumis capable of mineralizing PyOM to CO2. Collectively, our results indicate a robust potential forP. domesticumto liberate carbon from PyOM in post-fire ecosystems and return it to the bioavailable carbon pool.IMPORTANCEFires are increasing in frequency and severity in many regions across the world. Thus, it’s critically important to understand how our ecosystems respond to inform restoration and recovery efforts. Fire transforms the soil, removing many nutrients while leaving behind both nutritious necromass and complex pyrolyzed organic matter, which is often recalcitrant. Filamentous fungi of the genusPyronemastrongly dominate soil fungal communities soon after fire. While Pyronema are key pioneer species in post-fire environments, the nutrient source that fuels their rise in abundance is unknown. In this manuscript, we used a P. domesticum isolate from the catastrophic 2013 Rim Fire (CA, USA) to demonstrate thatP. domesticummetabolizes pyrolyzed organic material, effectively liberating this complex pyrolyzed carbon and returning it to the bioavailable carbon pool. The success of Pyronema in post-fire ecosystems has the potential to kick-start growth of other organisms and influence the entire trajectory of post-fire recovery.

Prognostic Values of Serum Ferritin and D-Dimer Trajectory in Patients with COVID-19

Cytokine storm syndrome in patients with COVID-19 is mediated by pro-inflammatory cytokines resulting in acute lung injury and multiorgan failure. Elevation in serum ferritin and D-dimer is observed in COVID-19 patients. To determine prognostic values of optimal serum cutoff with trajectory plots for both serum ferritin and D-dimer in COVID-19 patients with invasive ventilator dependence and in-hospital mortality. We used retrospective longitudinal data from the Cerner COVID-19 de-identified cohort. COVID-19 infected patients with valid repeated values of serum ferritin and D-dimer during hospitalization were used in mixed-effects logistic-regression models. Among 52,411 patients, 28.5% (14,958) had valid serum ferritin and 28.6% (15,005) D-dimer laboratory results. Optimal cutoffs of ferritin (714 ng/mL) and D-dimer (2.1 mg/L) revealed AUCs ≥ 0.99 for in-hospital mortality. Optimal cutoffs for ferritin (502 ng/mL) and D-dimer (2.0 mg/L) revealed AUCs ≥ 0.99 for invasive ventilator dependence. Optimal cutoffs for in-house mortality, among females, were lower in serum ferritin (433 ng/mL) and D-dimer (1.9 mg/L) compared to males (740 ng/mL and 2.5 mg/L, respectively). Optimal cutoffs for invasive ventilator dependence, among females, were lower in ferritin (270 ng/mL) and D-dimer (1.3 mg/L) compared to males (860 ng/mL and 2.3 mg/L, respectively). Optimal prognostic cutoffs for serum ferritin and D-dimer require considering the entire trajectory of laboratory values during the disease course. Females have an overall lower optimal cutoff for both serum ferritin and D-dimer. The presented research allows health professionals to predict clinical outcomes and appropriate allocation of resources during the COVID-19 pandemic, especially early recognition of COVID-19 patients needing higher levels of care.

Evolutionary development of the Homo antecessor scapulae (Gran Dolina site, Atapuerca) suggests a modern-like development for Lower Pleistocene Homo

Two well-preserved, subadult 800 ky scapulae from Gran Dolina belonging to Homo antecessor, provide a unique opportunity to investigate the ontogeny of shoulder morphology in Lower Pleistocene humans. We compared the H. antecessor scapulae with a sample of 98 P. troglodytes and 108 H. sapiens representatives covering seven growth stages, as well as with the DIK-1-1 (Dikika; Australopithecus afarensis), KNM-WT 15000 (Nariokotome; H. ergaster), and MH2 (Malapa; A. sediba) specimens. We quantified 15 landmarks on each scapula and performed geometric morphometric analyses. H. sapiens scapulae are mediolaterally broader with laterally oriented glenoid fossae relative to Pan and Dikika shoulder blades. Accordingly, H. antecessor scapulae shared more morphological affinities with modern humans, KNM-WT 15000, and even MH2. Both H. antecessor and modern Homo showed significantly more positive scapular growth trajectories than Pan (slopes: P. troglodytes = 0.0012; H. sapiens = 0.0018; H. antecessor = 0.0020). Similarities in ontogenetic trajectories between the H. antecessor and modern human data suggest that Lower Pleistocene hominin scapular development was already modern human-like. At the same time, several morphological features distinguish H. antecessor scapulae from modern humans along the entire trajectory. Future studies should include additional Australopithecus specimens for further comparative assessment of scapular growth trends.

Leveraging Deep Learning for Visual Odometry Using Optical Flow

In this paper, we study deep learning approaches for monocular visual odometry (VO). Deep learning solutions have shown to be effective in VO applications, replacing the need for highly engineered steps, such as feature extraction and outlier rejection in a traditional pipeline. We propose a new architecture combining ego-motion estimation and sequence-based learning using deep neural networks. We estimate camera motion from optical flow using Convolutional Neural Networks (CNNs) and model the motion dynamics using Recurrent Neural Networks (RNNs). The network outputs the relative 6-DOF camera poses for a sequence, and implicitly learns the absolute scale without the need for camera intrinsics. The entire trajectory is then integrated without any post-calibration. We evaluate the proposed method on the KITTI dataset and compare it with traditional and other deep learning approaches in the literature.

Robot Localisation Using UHF-RFID Tags: A Kalman Smoother Approach †

Autonomous vehicles enable the development of smart warehouses and smart factories with an increased visibility, flexibility and efficiency. Thus, effective and affordable localisation methods for indoor vehicles are attracting interest to implement real-time applications. This paper presents an Extended Kalman Smoother design to both localise a mobile agent and reconstruct its entire trajectory through a sensor-fusion employing the UHF-RFID passive technology. Extensive simulations are carried out by considering the smoother optimal-window length and the effect of missing measurements from reference tags. Monte Carlo simulations are conducted for different vehicle trajectories and for different linear and angular velocities to evaluate the method accuracy. Then, an experimental analysis with a unicycle wheeled robot is performed in real indoor scenario, showing a position and orientation root mean square errors of 15 cm, and 0.2 rad, respectively.