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Marine sediments can contain large amounts of alkanes and methylated aromatic hydrocarbons that are introduced by natural processes or anthropogenic activities. These compounds can be biodegraded by anaerobic microorganisms via enzymatic addition of fumarate. However, the identity and ecological roles of a significant fraction of hydrocarbon degraders containing fumarate-adding enzymes (FAE) in various marine sediments remains unknown. By combining phylogenetic reconstructions, protein homolog modelling, and functional profiling of publicly available metagenomes and genomes, 61 draft bacterial and archaeal genomes encoding anaerobic hydrocarbon degradation via fumarate addition were obtained. Besides Desulfobacterota (previously known as Deltaproteobacteria) that are well-known to catalyze these reactions, Chloroflexi are dominant FAE-encoding bacteria in hydrocarbon-impacted sediments, potentially coupling sulfate reduction or fermentation to anaerobic hydrocarbon degradation. Among Archaea, besides Archaeoglobi previously shown to have this capability, genomes of Heimdallarchaeota, Lokiarchaeota, Thorarchaeota and Thermoplasmata also suggest fermentative hydrocarbon degradation using archaea-type FAE. These bacterial and archaeal hydrocarbon degraders occur in a wide range of marine sediments, including high abundances of FAE-encoding Asgard archaea associated with natural seeps and subseafloor ecosystems. Our results expand the knowledge of diverse archaeal and bacterial lineages engaged in anaerobic degradation of alkanes and methylated aromatic hydrocarbons.

Du, P.; Zhang, C., and Yang, L., 2020. The impact of perceived value and group norm on environmentally friendly behavior of mangrove reserves in coastal cities: The mediating role of tourism satisfaction. In: Liu, X. and Zhao, L. (eds.), Today's Modern Coastal Society: Technical and Sociological Aspects of Coastal Research. Journal of Coastal Research, Special Issue No. 111, pp. 243–247. Coconut Creek (Florida), ISSN 0749-0208.With the rapid development of China's coastal cities, mangrove conservation faces various environmental influences brought on by the thousands of visitors. This study proposes the hypothesis that latent variables such as environmental knowledge, perceived value, group norms, and satisfaction have significant positive effects on environmentally friendly behavior and refine influencing aspects and paths. The Mangrove Nature Reserve of Shenzhen is used as the study area, and the following model analysis results are found: (1) Perceived value contributes the most to environmentally friendly behavior, (2) group norms have the second-greatest effect on environmentally friendly behavior, which indicates that tourists in the same group are easily affected by the people around them; and (3) tourism satisfaction mediates the relationship between environmental knowledge and environmentally friendly behavior. The findings could help managers of mangrove conservation recognize the paths for influencing environmentally friendly behavior and improve the level of environmental management and tourism services.

While widely used for flow tables in SDN switches, TCAM faces challenges for rule updates. Both the computation time and interrupt time need to be short. We propose FastUp, a new TCAM update algorithm, which improves the previous dynamic programming-based algorithms. Evaluations show that FastUp shortens the computation time by 40~100× and the interrupt time by 1.2~2.5×. In addition, we are the first to prove the NP-hardness of the optimal TCAM update problem, and provide a practical method to evaluate an algorithm’s degree of optimality. Experiments show that FastUp’s optimality reaches 90%.

Background: Marine sediments can contain large amounts of alkanes and methylated aromatic hydrocarbons that are introduced by natural processes or anthropogenic activities. These compounds can be biodegraded by anaerobic microorganisms via enzymatic addition of fumarate. Previous gene- and genome-based surveys have detected ubiquitous and novel fumarate-adding enzymes (FAE), but these were neither confirmed as occurring within full degradation pathways nor affiliated with known organisms. The identity and ecological roles of a significant fraction of anaerobic hydrocarbon degraders in marine sediments therefore remains unknown.Results: By combining phylogenetic reconstructions, protein homolog modelling, and functional profiling of publicly available and newly sequenced metagenomes and genomes, 61 draft bacterial and archaeal genomes encoding anaerobic hydrocarbon degradation via fumarate addition were obtained. Besides Deltaproteobacteria that are well-known to catalyze these reactions, Chloroflexi are dominant FAE-encoding bacteria in hydrocarbon-impacted sediments, potentially coupling sulfate reduction or fermentation to anaerobic hydrocarbon degradation. Among Archaea, besides Archaeoglobi previously shown to have this capability, genomes of Heimdallarchaeota, Lokiarchaeota, Thorarchaeota and Thermoplasmata also suggest fermentative hydrocarbon degradation using archaea-type FAE. The biogeography survey reveals these bacterial and archaeal hydrocarbon degraders occur in a wide range of marine sediments, including high abundances of FAE-encoding Asgard archaea associated with natural seeps and subseafloor ecosystems.Conclusions: Our results expand the knowledge of novel microbial lineages engaged in anaerobic degradation of alkanes and methylated aromatic hydrocarbons, and shed new light on the importance of marine sedimentary archaea in hydrocarbon degradation.

Ternary Content Addressable Memory (TCAM) is widely used by modern routers and switches to support policy-based forwarding. However, the limited TCAM capacity does not scale with the ever-increasing rule table size. Using TCAM just as a rule cache is a plausible solution, but one must resolve several tricky issues including the rule dependency and the associated TCAM updates. In this paper, we propose a new approach which can generate dependency-free rules to cache. By removing the rule dependency, the TCAM update problem also disappears. We provide the complete T-cache system design including slow path processing and cache replacement. Evaluations based on real-world and synthesized rule tables and traces show that T-cache is efficient and robust for network traffic in various scenarios.

Intelligent Transport System (ITS) raises the increasing demand on accurate vehicle trajectory prediction for navigation efficiency. The rapidly developing 5G networks provides communications with high transmission bandwidth and super-low latency, paving the way for Mobile Edge Computing (MEC) to calculate more accurate trajectory prediction for vehicles, as the MEC server holds more comprehensive vehicular information. However, the current methods for trajectory prediction are not efficient due to the dynamical environment. To address this issue, we propose GlobalInsight, a Long Short-Term Memory (LSTM) based model, which runs on the MEC to perform accurate trajectory prediction for multiple vehicles no matter how scenario changes. In particular, we use three auxiliary layers to respectively capture the principal component of vehicle features, social interaction of adjacent vehicles, and the cross-vehicle correlation of similar vehicles. We further integrate the above information into LSTM in the main layer to enhance the trajectory learning and prediction. We evaluate our model under the NGSIM dataset, and experimental results exhibit that our model outperforms the state-of-the-art approaches.

Existing routing algorithms that based on traditional Vehicular Ad-Hoc NETwork (VANET) architectures cannot provide fast and diverse routing services due to dynamic and unstable environment. To address this issue, we propose a three-level routing hierarchy in improved Software-Defined VANET architecture based on Mobile Edge Computing (SDN-MEC-VANET) to improve routing performance and enrich the data transmission mode for the VANET. Moreover, it can be applied to almost all VANET protocols, enabling protocol-independent forwarding. Besides, this improved architecture can coordinate different edge devices to timely adjust the service delivery strategy under the predictive correction from controllers, providing high-bandwidth and low-delay transmission for Internet of Vehicles (IoV). Meanwhile, MEC technology is introduced to perform local control, leveraging the storage and computing capabilities of edge devices to reduce the processing pressure of the controller. Simulation results show that our routing algorithm in improved network architecture can achieve a higher packet delivery ratio within a reasonable delay than other approaches under different scenarios of network scale, communication frequency and vehicular velocity.

Vehicular Ad hoc network (VANET) has received great attention in recent research, but many challenges still lie in innovating efficient routing protocols to support the highly dynamic environment. Existing ID-based routing protocols cannot fundamentally tackle the dynamic topology problem in VANET. The recent emerging Information-Centric Networking (ICN) makes routing decisions based on data itself instead of a particular host, seeming to have the potential to handle the dynamic topology, but problems (e.g., severe flooding overhead) still remain. Therefore, inspired by the idea of ICN, we propose a name/ID hybrid routing (NIHR) protocol that combines the data-namebased routing and host-ID-based routing to address the above two issues simultaneously. In particular, we develop an announce strategy to improve the efficiency of the in-network cache, and we design a bloom filter based structure to achieve fast content lookup. Simulation results show NIHR's high performance in terms of Packet Delivery Ratio (PDR), Roundtrip time (RTT) and roundtrip hop count. Especially, to verify NIHR’s performance in real-world scenarios, we have implemented a vehicular real-time video conference system based on MK5 OBU [1] (On-Board Unit).

Molecular hydrogen (H2) is a major energy source supporting bacterial growth and persistence in soil ecosystems. While recent studies have uncovered mediators of atmospheric H2 consumption, far less is understood about how soil microbial communities respond to elevated H2 levels produced through natural or anthropogenic processes. Here we performed microcosm experiments to resolve how microbial community composition, capabilities, and activities change in upland and wetland soils following H2 supplementation (at mixing doses from 0.5 to 50,000 ppmv). Genome-resolved metagenomic profiling revealed that these soils harbored diverse bacteria capable of using H2 as an electron donor for aerobic respiration (46 of the 196 MAGs from eight phyla) and carbon fixation (15 MAGs from three phyla). H2 stimulated the growth of several of these hydrogenotrophs in a dose-dependent manner, though the lineages stimulated differed between the soils; whereas actinobacterial lineages encoding group 2a [NiFe]-hydrogenases grew most in the upland soils (i.e. Mycobacteriaceae, Pseudonocardiaceae), proteobacterial lineages harboring group 1d [NiFe]-hydrogenases were most enriched in wetland soils (i.e. Burkholderiaceae). Hydrogen supplementation also influenced the abundance of various other genes associated with biogeochemical cycling and bioremediation pathways to varying extents between soils. Reflecting this, we observed an enrichment of a hydrogenotrophic Noviherbaspirillum MAG capable of biphenyl hydroxylation in the wetland soils and verified that H2 supplementation enhanced polychlorinated biphenyl (PCB) degradation in these soils, but not the upland soils. This study constitutes the first genome-resolved analysis of how soil microbial communities respond to elevated H2 availability. Overall, our findings suggest that soils harbour different hydrogenotrophic bacteria that rapidly grow following elevated H2 exposure. In turn, this adds to growing evidence of a large and robust soil H2 sink capable of counteracting growing anthropogenic emissions.

This paper introduces a mid-term planning model for scheduling assembly and test operations aimed at minimising the difference between customer demand and product completions each day. A secondary objective is to maximise daily surplus which is a surrogate for throughput. Typically, semiconductor companies have 1000s of products or devices in their catalogue that can be organised into unique groups of up to a 100 devices each. This simplifies the planning process because it is only necessary to consider the groups as a whole rather than the individual devices when constructing schedules. In all, we developed and tested three related models. Each provides daily production rates at each process step for each device group for up to one month at a time. The models are distinguished by how cycle time is treated. The first takes a steady-state approach and uses Little’s Law to formulate a WIP target constraint based on the average cycle time at each processing step. The second and third include integer and frac...

High topology dynamics and intermittent connectivity in Vehicular Ad hoc Network (VANET) bring huge challenges to end-to-end communication. Existing routing protocols for MANET such as AODV and OLSR work fine under modest mobility, but have a difficult time to handle frequent topology changes in VANET. This paper proposes Peeking at the Past and Present Routing (P3R), a routing protocol that will calculate next-hops when the past forwarding is considered invalid. The next-hop calculation is based on the predicted locations of forwarder's neighbors and the packet's destination node, overcoming the inaccuracy caused by stale location information. Furthermore, we differentiate vehicles on crossroads as they have high connectivity in actual urban streets. In this way, P3R is able to deal with link breakages quickly and exploit new links. Simulation results show that P3R outperforms state-of-the-art alternatives in terms of packet delivery ratio, delay and cost, while maintaining strong scalability and robustness. We also implement P3R in a real vehicular testbed and the results reveal it has high connectivity on real streets.

In Vehicular Ad Hoc NETworks (VANET), dynamic topology changes of network and inconstant bandwidth make it hard to maintain an end-to-end path to complete long-time stable data transmission. Facing this challenge, researchers have proposed the hybrid routing approach, which tries to combine both the advantages of recalculating route when topology changes and looking up routing table as long as the network topology is relatively stable. However, the existing hybrid routing algorithms can easily cause the blind path problem, meaning a route entry is kept in the routing table without expiration according to the timeout mechanism but it is actually invalid, because the next hop is already unavailable. To address this issue, we propose a Reinforcement learning based Hybrid Routing algorithm (RHR) that can online track the available paths with their status and use packet-carry-on information as real-time feedback to guide routing. RHR keeps the forwarding path always the freshest and thus improves the system performance. Simulation results show that RHR achieves better performance in packet delivery ratio (PDR), roundtrip time (RTT) and overhead than other peers under different scenarios of network scale, request frequency and vehicle velocity.

Information Centric Networking (ICN) has been proposed to solve the problem of mobility in Vehicular Ad hoc network (VANET). By using content name as the addressing key instead of IP address to obtain data from adjacent vehicles, ICN works better than traditional IP networks under high topology dynamics and intermittent connectivity. In this work, we for the first time propose Neighbor Cache Explore Routing based on Trajectory Prediction (PNCE), a content-driven routing protocol which gives priority to inquiring the content in neighbors' cache. In PNCE, vehicles periodically notify neighbors of their local cache information and maintain a local table containing neighbors' cached contents, which contributes to select the nearest vehicle from the requester for forwarding decision. Simulation results show that PNCE can significantly improve network performance in terms of packet delivery ratio, delay and Cache hit ratio, and maintain good scalability and strong robustness.

Software-based IP route lookup is one of the key components in Software Defined Networks. To address challenges on density, power and cost, Commodity CPU is preferred over other platforms to run lookup algorithms. As network functions become richer and more dynamic, route updates are more frequent. Unfortunately, previous works put less effort on fast incremental updates. On the other hand, The cache in CPU could be a performance limiter due to its small size, which requires algorithm designers to give high priority on storage efficiency in addition to time complexity. In this paper, we propose a new route lookup algorithm, OBMA, which improves update performance and storage efficiency while maintaining high lookup speed. The extensive experiments over real-word traces show that OBMA reduces the memory footprint to just 4.52 bytes/prefix, supports update speed up to 7.2 M/s which is 12.5 times faster than the state-of-the-art algorithm Poptrie. Besides, OBMA achieves up to 195.87 Mpps lookup speed with a single thread. Tests on comprehensive performance of lookup and update show that OBMA can sustain high lookup speed with update speed increasing.

Microstructural changes following oxidation at high temperatures of a complex coating or alloy can significantly influence its properties. This paper investigates possible solutions that can accurately model alloy microstructures that result from such a process in a cobalt-rich CoNiCrAlReY bond coat alloy system. Four different alloys with varying aluminum content were studied after heat treatments at 1000 °C or 1150 °C. SEM, EPMA and XRD were used to characterize the alloy microstructure, and hardness testing was performed to determine the role of microstructure on mechanical properties. Experimental microstructures were modeled using two databases of Thermo-Calc, namely TTNI8 and SSOL5. Effects of Al content on phase changes and materials properties were quantitatively investigated. Data showed that a 1 wt. % increase of Al in the alloy caused an 8% increase in the beta phase, and a Cr and Re rich sigma phase precipitated preferentially at high Al concentrations. In addition, alloy hardness was found to increase by 4 and 81%, respectively, with a 10% increase in the beta and sigma phases. Modeled results using the TTNI8 database showed excellent agreement with experimental observations, but the SSOL5 database produced erroneous information.

Vanadium carbide coatings on AISI H13 steel were prepared by thermo-reactive deposition/diffusion process (TRD) in molten salt bath for 1 to 6 h at 920 °C and 1000 °C, respectively. The obtained coatings were characterized by scanning electron microscopy (SEM), energy dispersive X-ray spectrometry (EDX) and X-ray diffraction analysis (XRD). Equiaxed grains were observed throughout the coatings. The grain size gradually increased from the coating/substrate interface to the top surface. The coatings were composed of ordered state V6C5 phase and disordered state VCx (x = 0.83–0.88) phases and had a preferential orientation of (111) and (200) planes. The values of nano-indentation hardness and elastic modulus of the coating are 28.1 ± 0.7 GPa and 421 ± 14 GPa, respectively. The growth of the vanadium carbide coating by the TRD process followed a parabolic kinetics with an activation energy of 199.3 kJ/mol. The variation of the coating thickness on the AISI H13 steel with treating time and temperature can be determined.

The microstructures of VC coatings on AISI H13 and 9Cr18 steel obtained by thermo-reactive deposition at 920 °C for 4 h were studied. The coating on AISI H13 was composed of equiaxed grains with an average size of 0.27 ± 0.12 μm; the coating on 9Cr18 was composed of elongated grains. The average size was 1.56 ± 0.54 μm in the direction parallel to coating/substrate interface and 0.69 ± 0.09 μm perpendicular to coating/substrate interface. The increase in grain size of the coating formed on 9Cr18 was caused by the poor-supplying of carbon atoms for the formation reaction of vanadium carbide. These tendencies of the formation of equiaxed and elongated grains were attributed to the high and low carbon activities in the substrates, respectively.

A new frame structure based on time-domain synchronous orthogonal frequency division multiplexing for digital terrestrial television broadcasting (DTTB) uplink systems is proposed, whereby multicarrier pseudonoise (PNMC) training sequences are used as the frame header (FH). Sub-sequences of FH are inserted between signal frames as guard intervals. Simple multi-user channel estimation and equalisation can be applied and good performance is illustrated by simulations.

A wireless switch designated for battery-supplied implantable medical devices is designed and verified based on a passive RF receiver. The switch employs wireless energy recovery and wireless identification, and consumes zero standby power. Unlike the commonly used dry reed switch, the proposed switch features high tolerance to noise and disturbance, as well as compatibility with integrated circuits. The proposed wireless switch circuit has been implemented using 0.18 µm CMOS technology, and verified in a wireless capsule endoscope prototype system.