Semi-Numerical Simulation of Reionization with Semi-Analytical Modeling of Galaxy Formation

In a semi-numerical model of reionization, the evolution of ionization fraction is simulated approximately by the ionizing photon to baryon ratio criterion. In this paper we incorporate a semi-analytical model of galaxy formation based on the Millennium II N-body simulation into the semi-numerical modeling of reionization. The semi-analytical model is used to predict the production of ionizing photons, then we use the semi-numerical method to model the reionization process. Such an approach allows more detailed modeling of the reionization, and also connects observations of galaxies at low and high redshifts to the reionization history. The galaxy formation model we use was designed to match the low-$z$ observations, and it also fits the high redshift luminosity function reasonably well, but its prediction on the star formation falls below the observed value, and we find that it also underpredicts the stellar ionizing photon production rate, hence the reionization can not be completed at $z \sim 6$ without taking into account some other potential sources of ionization photons. We also considered simple modifications of the model with more top heavy initial mass functions (IMF), with which the reionization can occur at earlier epochs. The incorporation of the semi-analytical model may also affect the topology of the HI regions during the EoR, and the neutral regions produced by our simulations with the semi-analytical model appeared less poriferous than the simple halo-based models.Comment: 13 pages, 8 figures, RAA accepte

Research on the Internet of Things (IoT)

The Internet of things (IoT) has become a research hotspot in computer science. The fact it will lead to a new information revolution is considered by most researchers. The main idea of IoT is that all objects are connected to the Internet and thus to be managed and controlled remotely, even interact with each other by receiving and sending information as well as sense their surroundings and have a certain reaction through intelligent technologies. In this paper, we firstly introduce the definition and connotation of IoT briefly. Secondly, we present the enabling technologies of IoT such as RFID (Radio Frequency Identification) systems, WSN (wireless sensor networks), intelligent technologies, NT (nanotechnology), addressing schemes, data storage and analysis and visualization. Thirdly, we give a brief introduce of the applications of IoT. It includes individuals and families, enterprise, public utilities and mobile. Fourthly, some open issues and research directions are introduced. Finally, we give the conclusion

An adaptive energy efficient MAC protocol for RF energy harvesting WBANs

Continuous and remote health monitoring medical applications with heterogeneous requirements can be realized through wireless body area networks (WBANs). Energy harvesting is adopted to enable low-power health applications and long-term monitoring without battery replacement, which have drawn significant interest recently. Because energy harvesting WBANs are obviously different from battery-powered ones, network protocols should be designed accordingly to improve network performance. In this article, an efficient cross-layer media access control protocol is proposed for radio frequency powered energy harvesting WBANs. We redesigned the superframe structure, which can be rescheduled by the coordinator dynamically. A time switching (TS) strategy is used when sensors harvest energy from radio frequency signals broadcast by the coordinator, and a transmission power adjustment scheme is proposed for sensors based on the energy harvesting efficiency and the network environment. Energy efficiency can be effectively improved that more packets can be uploaded using limited energy. The length of the energy harvesting period is determined by the coordinator to balance the channel resources and energy requirements of sensors and further improve the network performance. Numerical simulation results show that our protocol can provide superior system performance for long-term periodic health monitoring applications

Joint Optimization of Computation, Communication and Caching in D2D-Assisted Caching-Enhanced MEC System

Article discusses how, in the era of intelligent applications, Mobile Edge Computing (MEC) is emerging as a promising technology that provides abundant resources for mobile devices. The authors of the article introduce a novel Device-to-Device (D2D)-assisted system to address this challenge

A Location Selection Policy of Live Virtual Machine Migration for Power Saving and Load Balancing

Green cloud data center has become a research hotspot of virtualized cloud computing architecture. And load balancing has also been one of the most important goals in cloud data centers. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on location selection (migration policy) of live VM migration for power saving and load balancing. We propose a novel approach MOGA-LS, which is a heuristic and self-adaptive multiobjective optimization algorithm based on the improved genetic algorithm (GA). This paper has presented the specific design and implementation of MOGA-LS such as the design of the genetic operators, fitness values, and elitism. We have introduced the Pareto dominance theory and the simulated annealing (SA) idea into MOGA-LS and have presented the specific process to get the final solution, and thus, the whole approach achieves a long-term efficient optimization for power saving and load balancing. The experimental results demonstrate that MOGA-LS evidently reduces the total incremental power consumption and better protects the performance of VM migration and achieves the balancing of system load compared with the existing research. It makes the result of live VM migration more high-effective and meaningful

Evaluation of a novel saliva-based epidermal growth factor receptor mutation detection for lung cancer: A pilot study.

BackgroundThis article describes a pilot study evaluating a novel liquid biopsy system for non-small cell lung cancer (NSCLC) patients. The electric field-induced release and measurement (EFIRM) method utilizes an electrochemical biosensor for detecting oncogenic mutations in biofluids.MethodsSaliva and plasma of 17 patients were collected from three cancer centers prior to and after surgical resection. The EFIRM method was then applied to the collected samples to assay for exon 19 deletion and p.L858 mutations. EFIRM results were compared with cobas results of exon 19 deletion and p.L858 mutation detection in cancer tissues.ResultsThe EFIRM method was found to detect exon 19 deletion with an area under the curve (AUC) of 1.0 in both saliva and plasma samples in lung cancer patients. For L858R mutation detection, the AUC of saliva was 1.0, while the AUC of plasma was 0.98. Strong correlations were also found between presurgery and post-surgery samples for both saliva (0.86 for exon 19 and 0.98 for L858R) and plasma (0.73 for exon 19 and 0.94 for L858R).ConclusionOur study demonstrates the feasibility of utilizing EFIRM to rapidly, non-invasively, and conveniently detect epidermal growth factor receptor mutations in the saliva of patients with NSCLC, with results corresponding perfectly with the results of cobas tissue genotyping

Jointly Optimized Energy-minimal Resource Allocation in Cache-enhanced Mobile Edge Computing Systems

Mobile edge computing (MEC) has attracted extensive studies recently due to its ability to augment the computational capabilities of mobile devices. This paper considers a cache-enhanced multiuser MEC system where the task can be cached in the MEC servers to avoid the transmission of duplicate data. To further improve the energy efficiency and satisfy the users’ requirement on delay, we jointly optimize caching, computation, and communication resources in this system. The formulated problem is a mixed integer non-convex optimization problem that is very challenging to solve. We thus propose an efficient iterative algorithm by jointly applying the block coordinate descent and convex optimization techniques, which is guaranteed to converge at least a suboptimal solution. Specifically, the formulated joint optimization problem is decomposed into two subproblems to optimize caching policy and resource allocation, respectively, which are alternately optimized by convex optimization in each iteration. To further speed up the algorithm convergence, an efficient initialization scheme based on the linear weighted method is proposed for caching policy. The extensive simulation results are provided to demonstrate that the proposed jointly optimizing caching, computation, and communication method can improve the energy efficiency with lower time cost compared with other benchmark methods

Global stability of an SIS epidemic model with feedback mechanism on networks

Abstract We study the global stability of endemic equilibrium of an SIS epidemic model with feedback mechanism on networks. The model was proposed by J. Zhang and J. Sun (Physica A 394:24–32, 2014), who obtained the local asymptotic stability of endemic equilibrium. Our main purpose is to show that if the feedback parameter is sufficiently large or if the basic reproductive number belongs to the interval (1,2] $(1, 2]$, then the endemic equilibrium is globally asymptotically stable. We also present numerical simulations to illustrate the theoretical results

Integrated Routing Protocol for Multicast and Anycast Messages

A novel eficient and dynamic integrated routing protocol for multicast and anycast messages is presented. The contributions of the protocol differ from well-known shared-tree systems in two aspects: (1) Off-tree anycast configuration and routing: multicast sources use anycast routing to select a better path from the source to one router in the group in order to avoid congestion or any fault in the network. (2) On-tree router anycast configurations: The nodes in the shared-tree are formed into a virtual anycast group. The shared-tree approach is extended with capability of a group cores (anycast group). The simulation data demonstrates the eficiency of the protocol