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Intensification of world trade is responsible for an increase in the number of alien species introductions. Human-mediated dispersal promotes not only introductions but also expansion of the species distribution via long-distance dispersal. Thus, understanding the role of anthropogenic pathways in the spread of invading species has become one of the most important challenges nowadays.We analysed the invasion pattern of the pinewood nematode in China based on invasion data from 1982 to 2005 and monitoring data on 7 locations over 15 years. Short distance spread mediated by long-horned beetles was estimated at 7.5 km per year. Infested sites located further away represented more than 90% of observations and the mean long distance spread was estimated at 111-339 km. Railways, river ports, and lakes had significant effects on the spread pattern. Human population density levels explained 87% of the variation in the invasion probability (P<0.05). Since 2001, the number of new records of the nematode was multiplied by a factor of 5 and the spread distance by a factor of 2. We combined a diffusion model to describe the short distance spread with a stochastic, individual based model to describe the long distance jumps. This combined model generated an error of only 13% when used to predict the presence of the nematode. Under two climate scenarios (stable climate or moderate warming), projections of the invasion probability suggest that this pest could expand its distribution 40-55% by 2025.This study provides evidence that human-induced dispersal plays a fundamental role in the spread of the pinewood nematode, and appropriate control measures should be taken to stop or slow its expansion. This model can be applied to Europe, where the nematode had been introduced later, and is currently expanding its distribution. Similar models could also be derived for other species that could be accidentally transported by humans.

AbstractLocal oxidation lithography has the potential for patterning proteins on conductive substrates such as silicon with nanometer accuracy, guided by and extending the nanoscale architectures found in native bioenergetic membranes. Such membranes foster energy and electron transfers between two or more types of protein complex, so the potential of this lithographic technique is investigated for copatterning multiple types of protein complex. Composite patterns consisting of light‐harvesting 2 (LH2) and reaction center‐light‐harvesting 1‐PufX (RCLH1) complexes purified from Rhodobacter (Rba.) sphaeroides, and light‐harvesting complex II (LHCII) purified from spinach, are fabricated. Atomic force microscopy (AFM) images demonstrate the successful sequential deposition of single‐molecule layers of RCLH1 and LH2 molecules. In the case of LHCII, a mixture of single‐layer and multilayer patterns is found on the silicon substrate. Experimental conditions are established for the most efficient substrate surface modification and for protein immobilization. Spectral imaging and fluorescence lifetime imaging microscopy (FLIM) show that the immobilized photosynthetic complexes retain their native light‐harvesting and energy transfer functions, and provide evidence for excitation energy transfer from LH2 to RCLH1. Local oxidation lithography has the capacity to pattern proteins singly, or in small domains, for fabricating bioinspired nanoscale architectures for biosensors and solar cells.

The adoption of dense wireless sensor networks in industrial plants is mandatorily paired with the development of methods and tools for connectivity prediction. These are needed to certify the quality (or reliability) of the network information flow in industrial scenarios which are typically characterized by harsh propagation conditions. Connectivity prediction must account for the possible coexistence of heterogeneous radio-access technologies, as part of the Industrial Internet of Things (IIoT) paradigm, and easily allow postlayout validation steps. The goal of this paper is to provide a practical evaluation of relevant coexistence problems that may occur between industrial networks employing standards such as WirelessHART IEC 62591, IEEE 802.15.4, and IEEE 802.11. A number of coexistence scenarios are experimentally tested using different radio platforms. For each case, experimental results are analyzed to assess tolerable interference levels and sensitivity thresholds for different configurations of channel overlapping. Finally, the problem of over-the-air spectrum sensing is investigated in real scenarios with heterogeneous industrial networks to enable a cognitive resource allocation that avoids intolerable interference conditions.

Abstract Background The rumen microbiota provides essential services to its host and, through its role in ruminant production, contributes to human nutrition and food security. A thorough knowledge of the genetic potential of rumen microbes will provide opportunities for improving the sustainability of ruminant production systems. The availability of gene reference catalogs from gut microbiomes has advanced the understanding of the role of the microbiota in health and disease in humans and other mammals. In this work, we established a catalog of reference prokaryote genes from the bovine rumen. Results Using deep metagenome sequencing we identified 13,825,880 non-redundant prokaryote genes from the bovine rumen. Compared to human, pig, and mouse gut metagenome catalogs, the rumen is larger and richer in functions and microbial species associated with the degradation of plant cell wall material and production of methane. Genes encoding enzymes catalyzing the breakdown of plant polysaccharides showed a particularly high richness that is otherwise impossible to infer from available genomes or shallow metagenomics sequencing. The catalog expands the dataset of carbohydrate-degrading enzymes described in the rumen. Using an independent dataset from a group of 77 cattle fed 4 common dietary regimes, we found that only &lt;0.1% of genes were shared by all animals, which contrast with a large overlap for functions, i.e., 63% for KEGG functions. Different diets induced differences in the relative abundance rather than the presence or absence of genes, which explains the great adaptability of cattle to rapidly adjust to dietary changes. Conclusions These data bring new insights into functions, carbohydrate-degrading enzymes, and microbes of the rumen to complement the available information on microbial genomes. The catalog is a significant biological resource enabling deeper understanding of phenotypes and biological processes and will be expanded as new data are made available.

3-D Networks-on-Chip (NoC) emerge as a potent solution to address both the interconnection and design complexity problems facing future Multiprocessor System-on-Chips (MPSoCs). Effective run-time mapping on such 3-D NoC-based MPSoCs can be quite challenging, as the arrival order and task graphs of the target applications are typically not known a priori, which can be further complicated by stringent energy requirements for NoC systems. This paper thus presents an energy-aware run-time incremental mapping algorithm (ERIM) for 3-D NoC which can minimize the energy consumption due to the data communications among processor cores, while reducing the fragmentation effect on the incoming applications to be mapped, and simultaneously satisfying the thermal constraints imposed on each incoming application. Specifically, incoming applications are mapped to cuboid tile regions for lower energy consumption of communication and the minimal routing. Fragment tiles due to system fragmentation can be gleaned for better resource utilization. Extensive experiments have been conducted to evaluate the performance of the proposed algorithm ERIM, and the results are compared against the optimal mapping algorithm (branch-and-bound) and two heuristic algorithms (TB and TL). The experiments show that ERIM outperforms TB and TL methods with significant energy saving (more than 10%), much reduced average response time, and improved system utilization.

AbstractPolymorphism of organic semiconducting materials exerts critical effects on their physical properties such as optical absorption, emission and electrical conductivity, and provides an excellent platform for investigating structure–property relations. It is, however, challenging to efficiently tune the polymorphism of conjugated polymers in aggregated, semi-crystalline phases due to their conformational freedom and anisotropic nature. Here, two distinctly different semi-crystalline polymorphs (β1 and β2) of a low-bandgap diketopyrrolopyrrole polymer are formed through controlling the solvent quality, as evidenced by spectroscopic, structural, thermal and charge transport studies. Compared to β1, the β2 polymorph exhibits a lower optical band gap, an enhanced photoluminescence, a reduced π-stacking distance, a higher hole mobility in field-effect transistors and improved photocurrent generation in polymer solar cells. The β1 and β2 polymorphs provide insights into the control of polymer self-organization for plastic electronics and hold potential for developing programmable ink formulations for next-generation electronic devices.