Enhancing sensor duty cycle in environmental wireless sensor networks using Quantum Evolutionary Golden Jackal Optimization Algorithm

Environmental wireless sensor networks (EWSNs) are essential in environmental monitoring and are widely used in gas monitoring, soil monitoring, natural disaster early warning and other fields. EWSNs are limited by the sensor battery capacity and data collection range, and the usual deployment method is to deploy many sensor nodes in the monitoring zone. This deployment method improves the robustness of EWSNs, but introduces many redundant nodes, resulting in a problem of duty cycle design, which can be effectively solved by duty cycle optimization. However, the duty cycle optimization in EWSNs is an NP-Hard problem, and the complexity of the problem increases exponentially with the number of sensor nodes. In this way, non-heuristic algorithms often fail to obtain a deployment solution that meets the requirements in reasonable time. Therefore, this paper proposes a novel heuristic algorithm, the Quantum Evolutionary Golden Jackal Optimization Algorithm (QEGJOA), to solve the duty cycle optimization problem. Specifically, QEGJOA can effectively prolong the lifetime of EWSNs by duty cycle optimization and can quickly get a deployment solution in the face of multi-sensor nodes. New quantum exploration and exploitation operators are designed, which greatly improves the global search ability of the algorithm and enables the algorithm to effectively solve the problem of excessive complexity in duty cycle optimization. In addition, this paper designs a new sensor duty cycle model, which has the advantages of high accuracy and low complexity. The simulation shows that the QEGJOA proposed in this paper improves by 18.69, 20.15 and 26.55 compared to the Golden Jackal Optimization (GJO), Whale Optimization Algorithm (WOA) and the Simulated Annealing Algorithm (SA)

Quantitative characterization of the focusing process and dynamic behavior of differently sized microparticles in a spiral microchannel

Abstract In this paper, a spiral microchannel was fabricated to systematically investigate particle dynamics. The focusing process or migration behavior of different-sized particles in the outlet region was presented. Specifically, for focused microparticles, quantitative characterization and analysis of how particles migrate towards the equilibrium positions with the increase in flow rate (De = 0.31-3.36) were performed. For unfocused microparticles, the particle migration behavior and the particlefree region's formation process were characterized over a wide range of flow rates (De = 0.31-4.58), and the emergence of double particle-free regions was observed at De C 3.36. These results provide insights into the design and operation of high-throughput particle/cell filtration and separation. Furthermore, using the location markers prefabricated along with the microchannel structures, the focusing or migration dynamics of different-sized particles along the spiral microchannel was systematically explored. The particle migration length effects on focusing degree and particle-free region width were analyzed. These analyses may be valuable for the optimization of microchannel structures. In addition, this device was successfully used to efficiently filter rare particles from a large-volume sample and separate particles of two different sizes according to their focusing states

Sequencing and analysis of transcriptome to reveal regulation of gene expression for polysaccharide synthesis in Dendrobium officinale under different light quality

Light is a key factor affecting the growth and quality formation of Dendrobium officinale Kimura et Migo. In this study, we used D. officinale under different light conditions as experimental materials to explore the key genes that regulate its polysaccharide content. In addition, we cloned the UGPase gene and validated the gene by bioinformatics analysis and real-time quantitative PCR. Compared with the natural light control group, 494, 1630 and 599 differentially expressed genes were screened under different light quality conditions of red, blue and yellow, respectively. GO and KEGG enrichment analyses of these differentially expressed genes showed that the differentially expressed genes were enriched in the light signal transduction process under different light quality conditions. Bioinformatics analyses showed that the sequences of the genes were highly conserved with the sequences of the UGPase genes of other species, and had the highest sequence similarity with Phalaenopsis, which is also a member of the orchid family. Real-time quantitative PCR results showed that red light had the most significant promoting effect on the UGPase gene of D. officinale. In this study, we applied high-throughput sequencing technology to establish a transcriptome database of D. officinale under different light conditions and obtained a large amount of transcriptional information about D. officinale. The related genes affecting the quality of D. officinale were analysed at the transcriptional level, and the D. officinale UGPase gene was cloned, and its expression was analysed in different tissues and under different light conditions

Low-mass dark matter search results from full exposure of PandaX-I experiment

We report the results of a weakly-interacting massive particle (WIMP) dark matter search using the full 80.1\;live-day exposure of the first stage of the PandaX experiment (PandaX-I) located in the China Jin-Ping Underground Laboratory. The PandaX-I detector has been optimized for detecting low-mass WIMPs, achieving a photon detection efficiency of 9.6\%. With a fiducial liquid xenon target mass of 54.0\,kg, no significant excess event were found above the expected background. A profile likelihood analysis confirms our earlier finding that the PandaX-I data disfavor all positive low-mass WIMP signals reported in the literature under standard assumptions. A stringent bound on the low mass WIMP is set at WIMP mass below 10\,GeV/c$^2$, demonstrating that liquid xenon detectors can be competitive for low-mass WIMP searches.Comment: v3 as accepted by PRD. Minor update in the text in response to referee comments. Separating Fig. 11(a) and (b) into Fig. 11 and Fig. 12. Legend tweak in Fig. 9(b) and 9(c) as suggested by referee, as well as a missing legend for CRESST-II legend in Fig. 12 (now Fig. 13). Same version as submitted to PR

2020 roadmap on two-dimensional materials for energy storage and conversion

Energy storage and conversion have attained significant interest owing to its important applications that reduce CO2 emission through employing green energy. Some promising technologies are included metal-air batteries, metal-sulfur batteries, metal-ion batteries, electrochemical capacitors, etc. Here, metal elements are involved with lithium, sodium, and magnesium. For these devices, electrode materials are of importance to obtain high performance. Two-dimensional (2D) materials are a large kind of layered structured materials with promising future as energy storage materials, which include graphene, black phosporus, MXenes, covalent organic frameworks (COFs), 2D oxides, 2D chalcogenides, and others. Great progress has been achieved to go ahead for 2D materials in energy storage and conversion. More researchers will join in this research field. Under the background, it has motivated us to contribute with a roadmap on ‘two-dimensional materials for energy storage and conversion

A Wnt-Frz/Ror-Dsh Pathway Regulates Neurite Outgrowth in Caenorhabditis elegans

One of the challenges to understand the organization of the nervous system has been to determine how axon guidance molecules govern axon outgrowth. Through an unbiased genetic screen, we identified a conserved Wnt pathway which is crucial for anterior-posterior (A/P) outgrowth of neurites from RME head motor neurons in Caenorhabditis elegans. The pathway is composed of the Wnt ligand CWN-2, the Frizzled receptors CFZ-2 and MIG-1, the co-receptor CAM-1/Ror, and the downstream component Dishevelled/DSH-1. Among these, CWN-2 acts as a local attractive cue for neurite outgrowth, and its activity can be partially substituted with other Wnts, suggesting that spatial distribution plays a role in the functional specificity of Wnts. As a co-receptor, CAM-1 functions cell-autonomously in neurons and, together with CFZ-2 and MIG-1, transmits the Wnt signal to downstream effectors. Yeast two-hybrid screening identified DSH-1 as a binding partner for CAM-1, indicating that CAM-1 could facilitate CWN-2/Wnt signaling by its physical association with DSH-1. Our study reveals an important role of a Wnt-Frz/Ror-Dsh pathway in regulating neurite A/P outgrowth

A Systematic Review of Three-Dimensional Printing in Liver Disease

The purpose of this review is to analyse current literature related to the clinical applications of 3D printed models in liver disease. A search of the literature was conducted to source studies from databases with the aim of determining the applications and feasibility of 3D printed models in liver disease. 3D printed model accuracy and costs associated with 3D printing, the ability to replicate anatomical structures and delineate important characteristics of hepatic tumours, and the potential for 3D printed liver models to guide surgical planning are analysed. Nineteen studies met the selection criteria for inclusion in the analysis. Seventeen of them were case reports and two were original studies. Quantitative assessment measuring the accuracy of 3D printed liver models was analysed in five studies with mean difference between 3D printed models and original source images ranging from 0.2 to 20%. Fifteen studies provided qualitative assessment with results showing the usefulness of 3D printed models when used as clinical tools in preoperative planning, simulation of surgical or interventional procedures, medical education, and training. The cost and time associated with 3D printed liver model production was reported in 11 studies, with costs ranging from US$13 to US$2000, duration of production up to 100 h. This systematic review shows that 3D printed liver models demonstrate hepatic anatomy and tumours with high accuracy. The models can assist with preoperative planning and may be used in the simulation of surgical procedures for the treatment of malignant hepatic tumours