Detoxification of 1,1,2-trichloroethane to ethene by desulfitobacterium and identification of its functional reductase gene

10.1371/journal.pone.0119507PLoS ONE104e011950

Life-Cycle Cost/Benefit Assessment of Expedite Departure Path (EDP)

This report presents a life-cycle cost/benefit assessment (LCCBA) of Expedite Departure Path (EDP), an air traffic control Decision Support Tool (DST) currently under development at NASA. This assessment is an update of a previous study performed by bd Systems, Inc. (bd) during FY01, with the following revisions: The life-cycle cost assessment methodology developed by bd for the previous study was refined and calibrated using Free Flight Phase 1 (FFP1) cost information for Traffic Management Advisor (TMA, or TMA-SC in the FAA's terminology). Adjustments were also made to the site selection and deployment scheduling methodology to include airspace complexity as a factor. This technique was also applied to the benefit extrapolation methodology to better estimate potential benefits for other years, and at other sites. This study employed a new benefit estimating methodology because bd s previous single year potential benefit assessment of EDP used unrealistic assumptions that resulted in optimistic estimates. This methodology uses an air traffic simulation approach to reasonably predict the impacts from the implementation of EDP. The results of the costs and benefits analyses were then integrated into a life-cycle cost/benefit assessment

Direct Numerical Simulation of the Sedimentation of Solid Particles with Thermal Convection

Dispersed two-phase flows often involve interfacial activities such as chemical reaction and phase change, which couple the fluid dynamics with heat and mass transfer. As a step toward understanding such problems, we numerically simulate the sedimentation of solid bodies in a Newtonian fluid with convection heat transfer. The two-dimensional Navier–Stokes and energy equations are solved at moderate Reynolds numbers by a finite-element method, and the motion of solid particles is tracked using an arbitrary Lagrangian–Eulerian scheme. Results show that thermal convection may fundamentally change the way that particles move and interact. For a single particle settling in a channel, various Grashof-number regimes are identified, where the particle may settle straight down or migrate toward a wall or oscillate laterally. A pair of particles tend to separate if they are colder than the fluid and aggregate if they are hotter. These effects are analysed in terms of the competition between the thermal convection and the external flow relative to the particle. The mechanisms thus revealed have interesting implications for the formation of microstructures in interfacially active two-phase flows

Trajectory Similarity Measurement: An Efficiency Perspective

Trajectories that capture object movement have numerous applications, in which similarity computation between trajectories often plays a key role. Traditionally, the similarity between two trajectories is quantified by means of heuristic measures, e.g., Hausdorff or ERP, that operate directly on the trajectories. In contrast, recent studies exploit deep learning to map trajectories to d-dimensional vectors, called embeddings. Then, some distance measure, e.g., Manhattan or Euclidean, is applied to the embeddings to quantify trajectory similarity. The resulting similarities are inaccurate: they only approximate the similarities obtained using the heuristic measures. As distance computation on embeddings is efficient, focus has been on achieving embeddings yielding high accuracy. Adopting an efficiency perspective, we analyze the time complexities of both the heuristic and the learning-based approaches, finding that the time complexities of the former approaches are not necessarily higher. Through extensive experiments on open datasets, we find that, on both CPUs and GPUs, only a few learning-based approaches can deliver the promised higher efficiency, when the embeddings can be pre-computed, while heuristic approaches are more efficient for one-off computations. Among the learning-based approaches, the self-attention-based ones are the fastest to learn embeddings that also yield the highest accuracy for similarity queries. These results have implications for the use of trajectory similarity approaches given different application requirements

Optimal preprocessing of WiFi CSI for sensing applications

Due to its ubiquitous and contact-free nature, the use of WiFi infrastructure for performing sensing tasks has tremendous potential. However, the channel state information (CSI) measured by a WiFi receiver suffers from errors in both its gain and phase, which can significantly hinder sensing tasks. By analyzing these errors from different WiFi receivers, a mathematical model for these gain and phase errors is developed in this work. Based on these models, several theoretically justified preprocessing algorithms for correcting such errors at a receiver and, thus, obtaining clean CSI are presented. Simulation results show that at typical system parameters, the developed algorithms for cleaning CSI can reduce noise by $40$% and $200$%, respectively, compared to baseline methods for gain correction and phase correction, without significantly impacting computational cost. The superiority of the proposed methods is also validated in a real-world test bed for respiration rate monitoring (an exemplary sensing task), where they improve the estimation signal-to-noise ratio by $20$% compared to baseline methods.Comment: Paper is currently under review at IEEE Transactions on Wireless Communication

Curcumin exhibits therapeutic effect against spinal cord injury via inhibition of neuronal inflammation and apoptosis

Purpose: To investigate the effect of curcumin on spinal cord injury (SCI) in a rat model. Methods: SCI was induced in the rats using mid thoracic spinal cord compression, after which curcumin was injected intraperitoneally. Western blotting was used for assay of expressions of apoptotic proteins, viz, IL-1β, NF-κB p65, TLR4, TNF-α, LC3, Bax and Bcl-2. Malondialdehyde (MDA) and myeloperoxidase were measured using standard methods. Neuronal loss in spinal cord tissues was determined with TUNEL staining and NeuN labelling. Results: Curcumin treatment significantly (p < 0.05) suppressed SCI-mediated upregulation of myeloperoxidase activity and increase in MDA level in rat spinal cord. The reduction of glutathione (GSH) and superoxide dismutase (SOD) activities in the spinal cord of SCI rats were suppressed by curcumin treatment. Curcumin treatment also led to a significant (p < 0.02) increase in the proportion of NeuN positive cells and marked reduction in TUNEL positive cells, but it decreased caspase-3 in the spinal cord tissues of SCI rats. Moreover, curcumin reversed the effect of SCI on protein expressions of Bax and Bcl 2 in a dose-based manner. There was marked curcumin-induced decline in CD11b and GFAP levels in the spinal cord tissues of the SCI rats. Conclusion: These results demonstrate that curcumin protects rats against SCI via inhibition of oxidative stress-mediated neuronal apoptosis. Therefore, curcumin may be useful for the development of an effective treatment for spinal cord injury

Multiple Unpinned Dirac Points in Group-Va Single-layers with Phosphorene Structure

Emergent Dirac fermion states underlie many intriguing properties of graphene, and the search for them constitute one strong motivation to explore two-dimensional (2D) allotropes of other elements. Phosphorene, the ultrathin layers of black phosphorous, has been a subject of intense investigations recently, and it was found that other group-Va elements could also form 2D layers with similar puckered lattice structure. Here, by a close examination of their electronic band structure evolution, we discover two types of Dirac fermion states emerging in the low-energy spectrum. One pair of (type-I) Dirac points is sitting on high-symmetry lines, while two pairs of (type-II) Dirac points are located at generic $k$-points, with different anisotropic dispersions determined by the reduced symmetries at their locations. Such fully-unpinned (type-II) 2D Dirac points are discovered for the first time. In the absence of spin-orbit coupling, we find that each Dirac node is protected by the sublattice symmetry from gap opening, which is in turn ensured by any one of three point group symmetries. The spin-orbit coupling generally gaps the Dirac nodes, and for the type-I case, this drives the system into a quantum spin Hall insulator phase. We suggest possible ways to realize the unpinned Dirac points in strained phosphorene.Comment: 30 pages, 6 figure

Poly[octa­aquadi-μ-phosphato-trinickel(II)]

In the title compound, [Ni3(PO4)2(H2O)8]n, which was synthesized hydro­thermally, all the Ni atoms are located in slightly distorted octa­hedral coordination environments. Two phosphate groups and two Ni atoms share a centrosymmetric four-membered ring and an eight-membered ring such that the four-membered ring is inside the eight-membered ring. The eight-membered rings are connected with the other Ni atoms (lying on centres of symmetry) through phosphate anions, generating a one-dimensional chain structure. Adjacent chains are connected through hydrogen bonds, forming a three-dimensional network

Secondary development based on 3D Slicer extension modules

Slicer module is an important part of software, which provides algorithmic support for data processing for the realization of various functions of software. As an external plug-in that needs to be installed, extensions have strong independence. Developers can redevelop the original extension module and modify its functions and interfaces in order to achieve better results to meet the requirements of medical use. In this paper, the feasibility scheme and specific operation steps for the secondary development of the extended module are proposed, so as to improve efficiency, simplify the operation process, and facilitate the use of Slicer software in clinical medicine and medical research