English Teaching Reform in Local Undergraduate Colleges Based on Interlanguage Fossilization

The interlanguage fossilization is a distinguishing characteristic of second language acquisition and plays an important role in promoting the foreign language teaching in China. According to survey four main problems of English teaching in local undergraduate colleges have been found, involving language environment, teaching methods, teacher-student relationship and test mode. Therefore, this paper expounds the characteristics, classification and basic causes of interlanguage petrochemical phenomena, and proposes the main measures of English teaching reform in local undergraduate colleges from the perspective of theory of interlanguage fossilization. The reform measures are as follows (a)foster a good language learning environment, (b) emphasize learning strategy in the teaching process, (c) innovate teaching concepts and teaching models,(d) select high-quality teaching materials and strengthen teacher promotion

On the Influence of Charging Stations Spatial Distribution on Aerial Wireless Networks

Using drones for cellular coverage enhancement is a recent technology that has shown a great potential in various practical scenarios. However, one of the main challenges that limits the performance of drone-enabled wireless networks is the limited flight time. In particular, due to the limited on-board battery size, the drone needs to frequently interrupt its operation and fly back to a charging station to recharge/replace its battery. In addition, the charging station might be responsible to recharge multiple drones. Given that the charging station has limited capacity, it can only serve a finite number of drones simultaneously. Hence, in order to accurately capture the influence of the battery limitation on the performance, it is required to analyze the dynamics of the time spent by the drones at the charging stations. In this paper, we use tools from queuing theory and stochastic geometry to study the influence of each of the charging stations limited capacity and spatial density on the performance of a drone-enabled wireless network

A Dominant Interferer-based Approximation for Uplink SINR Meta Distribution in Cellular Networks

This work studies the signal-to-interference-plus-noise-ratio (SINR) meta distribution for the uplink transmission of a Poisson network with Rayleigh fading by using the dominant interferer-based approximation. The proposed approach relies on computing the mix of exact and mean-field analysis of interference. In particular, it requires the distance distribution of the nearest interferer and the conditional average of the rest of the interference. Using the widely studied fractional path-loss inversion power control and modeling the spatial locations of base stations (BSs) by a Poisson point process (PPP), we obtain the meta distribution based on the proposed method and compare it with the traditional beta approximation, as well as the exact results obtained via Monte-Carlo simulations. Our numerical results validate that the proposed method shows good matching and is time competitive.Comment: arXiv admin note: text overlap with arXiv:2302.0357

On the Peak AoI of UAV-assisted IoT Networks: A Stochastic Geometry Approach

In this paper, we analyze the peak age of information (PAoI) in UAV-assisted internet of thing (IoT) networks, in which the locations of IoT devices are modeled by a Mat\'{e}rn cluster process (MCP) and UAVs are deployed at the cluster centers to collect the status updates from the devices. Specifically, we consider that IoT devices can either monitor the same physical process or different physical processes and UAVs split their resources, time or bandwidth, to serve the devices to avoid inter-cluster interference. Using tools from stochastic geometry, we are able to compute the mean activity probability of IoT devices and the conditional success probability of an individual device. We then use tools from queuing theory to compute the PAoI under two load models and two scenarios for devices, respectively. Our numerical results show interesting system insights. We first show that for a low data arrival rate, increasing the number of correlated devices can improve the PAoI for both load models. Next, we show that even though the time-splitting technique causes higher interference, it has a limited impact on the mean PAoI, and the mean PAoI benefits more from the time-splitting technique. This is because of the nature of UAV communication, especially at places where devices (users) are spatially-clustered: shorter transmission distances and better communication channels, comparing the links established by the cluster UAV and serving devices (users) to links established by interferers

Stochastic Geometry-based Trajectory Design for Multi-Purpose UAVs: Package and Data Delivery

With the advancements achieved in drones' flexibility, low cost, and high efficiency, they obtain huge application opportunities in various industries, such as aerial delivery and future communication networks. However, the increasing transportation needs and expansion of network capacity demands for UAVs will cause aerial traffic conflicts in the future. To address this issue, in this paper, we explore the idea of multi-purpose UAVs, which act as aerial wireless communication data relays and means of aerial transportation simultaneously to deliver data and packages at the same time. While UAVs deliver the packages from warehouses to residential areas, we design their trajectories which enable them to collect data from multiple Internet of Things (IoT) clusters and forward the collected data to terrestrial base stations (TBSs). To select the serving nearby IoT clusters, UAVs rank them based on their priorities and distances. From the perspectives of data and package delivery, respectively, we propose two algorithms that design the optimal UAVs trajectory to maximize the transmitted data or minimize the round trip time. Specifically, we use tools from stochastic geometry to model the locations of IoT clusters and TBSs. Given the nature of random locations, the proposed algorithm applies to general cases. Our numerical results show that multi-purpose UAVs are practical and have great potential to enhance the energy/time-efficiency of future networks

Performance Evaluation of UAV-enabled Cellular Networks with Battery-limited Drones

Unmanned aerial vehicles (UAVs) can be used as flying base stations (BSs) to offload Macro-BSs in hotspots. However, due to the limited battery on-board, UAVs can typically stay in operation for less than 1.5 hours. Afterward, the UAV has to fly back to a dedicated charging station that recharges/replaces the UAV's battery. In this paper, we study the performance of a UAV-enabled cellular network while capturing the influence of the spatial distribution of the charging stations. In particular, we use tools from stochastic geometry to derive the coverage probability of a UAV-enabled cellular network as a function of the battery size, the density of the charging stations, and the time required for recharging/replacing the battery

On the Uplink SINR Meta Distribution of UAV-assisted Wireless Networks

This letter studies the signal-to-interference-plus-noise (SINR) meta distribution of uplink transmission of UAV-enabled wireless networks with inversion power control. Within a framework of stochastic geometry, the Matern cluster process (MCP) is used to model the locations of users and UAVs. Conditional success probability and moments are derived to compute the exact expression and moment matching approximation of SINR meta distribution (beta approximation). Specifically, the effect of the power control compensation factor and UAV altitude are studied. Our numerical results show that UAV altitude has a higher impact on the system reliability than transmit power at low values of SINR threshold since users benefit more from establishing line-of-sight (LoS) links with UAVs

Distributed Information-based Source Seeking

In this paper, we design an information-based multi-robot source seeking algorithm where a group of mobile sensors localizes and moves close to a single source using only local range-based measurements. In the algorithm, the mobile sensors perform source identification/localization to estimate the source location; meanwhile, they move to new locations to maximize the Fisher information about the source contained in the sensor measurements. In doing so, they improve the source location estimate and move closer to the source. Our algorithm is superior in convergence speed compared with traditional field climbing algorithms, is flexible in the measurement model and the choice of information metric, and is robust to measurement model errors. Moreover, we provide a fully distributed version of our algorithm, where each sensor decides its own actions and only shares information with its neighbors through a sparse communication network. We perform intensive simulation experiments to test our algorithms on large-scale systems and physical experiments on small ground vehicles with light sensors, demonstrating success in seeking a light source

Incomplete Wood-Ljungdahl pathway facilitates one-carbon metabolism in organohalide-respiring Dehalococcoides mccartyi.

The acetyl-CoA "Wood-Ljungdahl" pathway couples the folate-mediated one-carbon (C1) metabolism to either CO2 reduction or acetate oxidation via acetyl-CoA. This pathway is distributed in diverse anaerobes and is used for both energy conservation and assimilation of C1 compounds. Genome annotations for all sequenced strains of Dehalococcoides mccartyi, an important bacterium involved in the bioremediation of chlorinated solvents, reveal homologous genes encoding an incomplete Wood-Ljungdahl pathway. Because this pathway lacks key enzymes for both C1 metabolism and CO2 reduction, its cellular functions remain elusive. Here we used D. mccartyi strain 195 as a model organism to investigate the metabolic function of this pathway and its impacts on the growth of strain 195. Surprisingly, this pathway cleaves acetyl-CoA to donate a methyl group for production of methyl-tetrahydrofolate (CH3-THF) for methionine biosynthesis, representing an unconventional strategy for generating CH3-THF in organisms without methylene-tetrahydrofolate reductase. Carbon monoxide (CO) was found to accumulate as an obligate by-product from the acetyl-CoA cleavage because of the lack of a CO dehydrogenase in strain 195. CO accumulation inhibits the sustainable growth and dechlorination of strain 195 maintained in pure cultures, but can be prevented by CO-metabolizing anaerobes that coexist with D. mccartyi, resulting in an unusual syntrophic association. We also found that this pathway incorporates exogenous formate to support serine biosynthesis. This study of the incomplete Wood-Ljungdahl pathway in D. mccartyi indicates a unique bacterial C1 metabolism that is critical for D. mccartyi growth and interactions in dechlorinating communities and may play a role in other anaerobic communities