31 research outputs found
Small world network based dynamic topology for particle swarm optimization
Abstract: A new particle optimization algorithm with dynamic topology is proposed based on ‘small world’ network. The technique imitates the dissemination of information in a ‘small world network’ by dynamically updating the neighborhood topology of particle swarm optimization. The proposed dynamic neighborhood strategy can effectively coordinate the exploration and exploitation ability of particle swarm optimization. Simulations demonstrated that convergence of the swarms is guaranteed. Experiments demonstrated that the proposed method maintained the population diversity and enhanced the global search ability
Niching particle swarm optimization based euclidean distance and hierarchical clustering for multimodal optimization
Abstract : Multimodal optimization is still one of the most challenging tasks in the evolutionary computation field, when multiple global and local optima need to be effectively and efficiently located. In this paper, a niching Particle Swarm Optimization (PSO) based Euclidean Distance and Hierarchical Clustering (EDHC) for multimodal optimization is proposed. This technique first uses the Euclidean distance based PSO algorithm to perform preliminarily search. In this phase, the particles are rapidly clustered around peaks. Secondly, hierarchical clustering is applied to identify and concentrate the particles distributed around each peak to finely search as a whole. Finally, a small world network topology is adopted in each niche to improve the exploitation ability of the algorithm. At the end of this paper, the proposed EDHC-PSO algorithm is applied to the Traveling Salesman Problems (TSP) after being discretized. The experiments demonstrate that the proposed method outperforms existing niching techniques on benchmark problems, and is effective for TSP
Dynamic small world network topology for particle swarm optimization
Abstract: A new particle optimization algorithm with dynamic topology is proposed based on a small world network. The technique imitates the dissemination of information in a small world network by dynamically updating the neighborhood topology of the particle swarm optimization(PSO). In comparison with other four classic topologies and two PSO algorithms based on small world network, the proposed dynamic neighborhood strategy is more eÆective in coordinating the exploration and exploitation ability of PSO. Simulations demonstrated that the convergence of the swarms is faster than its competitors. Meanwhile, the proposed method maintains population diversity and enhances the global search ability for a series of benchmark problems
Ultrasound-directed enzyme-prodrug therapy (UDEPT) using self-immolative doxorubicin derivatives
Background: Enzyme-activatable prodrugs are extensively employed in oncology and beyond. Because enzyme concentrations and their (sub)cellular compartmentalization are highly heterogeneous in different tumor types and patients, we propose ultrasound-directed enzyme-prodrug therapy (UDEPT) as a means to increase enzyme access and availability for prodrug activation locally. Methods: We synthesized β-glucuronidase-sensitive self-immolative doxorubicin prodrugs with different spacer lengths between the active drug moiety and the capping group. We evaluated drug conversion, uptake and cytotoxicity in the presence and absence of the activating enzyme β-glucuronidase. To trigger the cell release of β-glucuronidase, we used high-intensity focused ultrasound to aid in the conversion of the prodrugs into their active counterparts. Results: More efficient enzymatic activation was observed for self-immolative prodrugs with more than one aromatic unit in the spacer. In the absence of β-glucuronidase, the prodrugs showed significantly reduced cellular uptake and cytotoxicity compared to the parent drug. High-intensity focused ultrasound-induced mechanical destruction of cancer cells resulted in release of intact β-glucuronidase, which activated the prodrugs, restored their cytotoxicity and induced immunogenic cell death. Conclusion: These findings shed new light on prodrug design and activation, and they contribute to novel UDEPT-based mechanochemical combination therapies for the treatment of cancer
Microstructure and composition of rare earth-transition metal-aluminium-magnesium alloys
The effects of vacuum annealing temperatures on the microstructure, mechanical properties and electrical resistivity of Mg-3Al-1Zn alloy ribbons
This paper investigates the influence of vacuum annealing temperature on the microstructure, mechanical properties and electrical resistivity of Mg-3Al-1Zn rapid solidification (RS) magnesium ribbons. The results indicate that when the annealing temperature is increased, the grain size of the ribbons is dramatically reduced from 10 to 1 μm. The highest break stress and micro-hardness is obtained at 673 K. These effects are ascribed to the dispersion strengthening caused by the high amount of fine nanoparticles distributed in the material. Electrical resistivity-temperature (ρ-T) curves have been used to provide useful information about the effects of the annealing temperature on the grain size, grain orientation and crystal structure of the ribbons. In this way, a new lightweight electric wire or connection cable line could be produced which would have good electromagnetic interference (EMI)
Research on Information Integration Method of Agricultural Products Producing and Managing Based on Knowledge Graph
International audienceIn order to improve the integration and access efficiency of agricultural information, this paper propose an agricultural information integration framework based on knowledge graph. A knowledge graph of agricultural products producing and managing was constructed, covering the basic process of “Planting - farming - processing - quality inspection - warehousing - Transportation - Sales” and realizing the storage, mapping and inquiry of knowledge graph. Improves the method of mapping data linkage based on database mapping relation, and realizes the transformation of elements from database to knowledge graph elements. Map data link method of database based on mapping relations, realize the conversion of database elements to the knowledge graph elements, the iterative discovery of relation and pattern in text information is realized by means of weak supervised machine learning method. This method integrates the application in the Green-Cloud-Grid platform, and improves the efficiency of information source integration, correlation analysis and mining utilization under the platform
Enhancing Tumor Penetration of Nanomedicines
Tumor-targeted nanomedicines have been extensively applied to alter the drawbacks and enhance the efficacy of chemotherapeutics. Despite the large number of preclinical nanomedicine studies showing initial success, their therapeutic benefit in the clinic has been rather modest, which is partially due to the inefficient tumor penetration caused by the tumor microenvironment (high density of cells and extracellular matrix, increased interstitial fluid pressure). Furthermore, tumor penetration of nanomedicines is significantly influenced by physicochemical characteristics, such as size, surface chemistry, and shape. The effect of size on tumor penetration has been exploited to design nanomedicines with switchable size to tackle this challenge. Moreover, several pharmacological and physical approaches have been developed to enhance the tumor penetration of nanomedicines, by penetration-promoting ligands, intratumoral drug release, and modulating the tumor microenvironment and vasculature. Overall, these efforts have resulted in nanomedicines with better tumor penetration properties and with enhanced therapeutic efficacy. Future research should be directed to penetration-promoting strategies with broad applicability and with high translational potential
Screening of Concentration and Antimicrobial Effectiveness of Antimicrobial Preservative in Betastatin Besylate Nasal Spray
Objective. To explore the optimal concentration and antimicrobial effectiveness of antimicrobial preservative in betastatin besylate nasal spray. Methods. By using Staphylococcus aureus, Pseudomonas aeruginosa, Escherichia coli, Candida albicans, and Aspergillus niger as test strains, the antimicrobial effectiveness of betastatin besylate nasal spray containing different concentrations of antimicrobial preservative (0.02%, 0.0125%, and 0.005% benzalkonium chloride, respectively) was determined by using bacteriostatic effect test (Chinese Pharmacopoeia, 2015 edition). Results. The antimicrobial effectiveness of betastatin besylate nasal spray containing 0.02% and 0.0125% benzalkonium chloride, respectively, complied with the regulations of Chinese Pharmacopoeia (2015 Edition) against five test strains. However, the antimicrobial effectiveness of betastatin besylate nasal spray containing 0.005% benzalkonium chloride against P. aeruginosa did not meet the requirements of Chinese Pharmacopoeia. Conclusion. Benzalkonium chloride at a concentration of 0.125% can be used as an added antimicrobial preservative in betastatin besylate nasal spray
State-of-the-Art Internet of Things in Protected Agriculture
The Internet of Things (IoT) has tremendous success in health care, smart city, industrial production and so on. Protected agriculture is one of the fields which has broad application prospects of IoT. Protected agriculture is a mode of highly efficient development of modern agriculture that uses artificial techniques to change climatic factors such as temperature, to create environmental conditions suitable for the growth of animals and plants. This review aims to gain insight into the state-of-the-art of IoT applications in protected agriculture and to identify the system structure and key technologies. Therefore, we completed a systematic literature review of IoT research and deployments in protected agriculture over the past 10 years and evaluated the contributions made by different academicians and organizations. Selected references were clustered into three application domains corresponding to plant management, animal farming and food/agricultural product supply traceability. Furthermore, we discussed the challenges along with future research prospects, to help new researchers of this domain understand the current research progress of IoT in protected agriculture and to propose more novel and innovative ideas in the future