26 research outputs found
Constrained Multiobjective Biogeography Optimization Algorithm
Multiobjective optimization involves minimizing or maximizing multiple objective functions subject to a set of constraints. In this study, a novel constrained multiobjective biogeography optimization algorithm (CMBOA) is proposed. It is the first biogeography optimization algorithm for constrained multiobjective optimization. In CMBOA, a disturbance migration operator is designed to generate diverse feasible individuals in order to promote the diversity of individuals on Pareto front. Infeasible individuals nearby feasible region are evolved to feasibility by recombining with their nearest nondominated feasible individuals. The convergence of CMBOA is proved by using probability theory. The performance of CMBOA is evaluated on a set of 6 benchmark problems and experimental results show that the CMBOA performs better than or similar to the classical NSGA-II and IS-MOEA
Case Report: A Novel COL1A1 Missense Mutation Associated With Dentineogenesis Imperfecta Type I
Background: Osteogenesis imperfecta (OI) is a clinical and genetic disorder that results in bone fragility, blue sclerae and dentineogenesis imperfecta (DGI), which is mainly caused by a mutation in the COL1A1 or COL1A2 genes, which encode type I procollagen.Case Report: A missense mutation (c.1463G > C) in exon 22 of the COL1A1 gene was found using whole-exome sequencing. However, the cases reported herein only exhibited a clinical DGI-I phenotype. There were no cases of bone disease or any other common abnormal symptom caused by a COL1A1 mutation. In addition, the ultrastructural analysis of the tooth affected with non-syndromic DGI-I showed that the abnormal dentine was accompanied by the disruption of odontoblast polarization, a reduced number of odontoblasts, a reduction in hardness and elasticity, and the loss of dentinal tubules, suggesting a severe developmental disorder. We also investigated the odontoblast differentiation ability using dental pulp stem cells (DPSCs) that were isolated from a patient with DGI-I and cultured. Stem cells isolated from patients with DGI-I are important to elucidate their pathogenesis and underlying mechanisms to develop regenerative therapies.Conclusion: This study can provide new insights into the phenotype-genotype association in collagen-associated diseases and improve the clinical diagnosis of OI/DGI-I
Investigation on the photoconductive behaviors of an individual AlN nanowire under different excited lights
Biogeography migration algorithm for traveling salesman problem
Abstract. Biogeography-based optimization algorithm(BBO) is a new kind of optimization algorithm based on Biogeography. It is designed based on the migration strategy of animals to solve the problem of optimization. In this paper, a new algorithm-Biogeography Migration Algorithm for Traveling Salesman Problem(TSPBMA) is presented. Migration operator is designed. It is tested on four classical TSP problems. The comparison results with the other nature inspired optimization algorithms show that TSPBMA is a very effective for TSP combination optimization. It provides a new way for this kinds of problem
A Physarum-Inspired Decision-Making Strategy for Multisource Task Searching of Mobile Robots
In the real world, there are many different kinds of sources, such as light, sound, and gas, distributed randomly over an area. Source search can be carried out by robotic system in applications. However, for a single robot, the multisource search has been receiving relatively little attention compared to single-source search. For multisource task searching, a single robot has a high travel cost and is easy to trap a source which has been located before. In order to overcome these shortages, two multisource search algorithms inspired by the foraging behavior of Physarum polycephalum are proposed in this paper. First, a Physarum-inspired Strategy (PS) is designed based on the gradient climbing characteristic of Physarum polycephalum during foraging. The PS is simple and effective to let a mobile robot traverse all sources. Then, an extension algorithm named Physarum-inspired Decision-making Strategy (PDS) is proposed based on PS. Therein the synthetical field gradient model is established by introducing decision-making factor to obtain more accurate gradient information estimation. The PDS also introduces an obstacle avoidance model. Various simulation results obtained in the multisource environments show that the performance of PDS is better than other algorithms
Integrating the Soil Microbiota and Metabolome Reveals the Mechanism through Which Controlled Release Fertilizer Affects Sugarcane Growth
Root−soil underground interactions mediated by soil microorganisms and metabolites are crucial for fertilizer utilization efficiency and crop growth regulation. This study employed a combined approach of soil microbial community profiling and non-targeted metabolomics to investigate the patterns of root-associated microbial aggregation and the mechanisms associated with metabolites under varying controlled-release fertilizer (CRF) application rates. The experimental treatments included five field application rates of CRF (D1: 675 kg/ha; D15: 1012.5 kg/ha; D2: 1350 kg/ha; D25: 1687.5 kg/ha; and D3: 2025 kg/ha) along with traditional fertilizer as a control (CK: 1687.5 kg/ha). The results indicated that the growth of sugarcane in the field was significantly influenced by the CRF application rate (p Leotiomycetes, Cercospora, Anaeromyxobacter, isoleucyl-proline, and methylmalonic acid. Redundancy analysis unveiled soil pH, soil organic carbon, and available nitrogen as the primary drivers of microbial communities, while the metabolic profiles were notably influenced by the available potassium and phosphorus. The correlation heatmaps illustrated potential microbial−metabolite regulatory mechanisms under CRF application conditions. These findings underscore the significant potential of CRF in sugarcane field production, laying a theoretical foundation for sustainable development in the sugarcane industry
Computer-aided ionic liquid design for alkane/cycloalkane extractive distillation process
A computer-aided ionic liquid design (CAILD) study is presented for the frequently encountered alkane/cycloalkane separations in petrochemical industry. Exhaustive experimental data are first collected to extend the UNIFAC-IL model for this system, where the proximity effect in alkanes and cycloalkanes is considered specifically by defining distinct groups. The thermodynamic performances of a large number of ILs for 4 different alkane/cycloalkane systems are then compared to select a representative example of such separations. By applying n-heptane/methylcyclohexane extractive distillation as a case study, the CAILD task is cast as a mixed-integer nonlinear programming (MINLP) problem based on the obtained task-specific UNIFAC-IL model and two semi-empirical models for IL physical properties. The top 5 IL candidates determined by solving the MINLP problem are subsequently introduced into Aspen Plus for process simulation and economic analysis, which finally identify 1-hexadecyl-methylpiperidinium tricyanomethane ([C16MPip][C(CN)3]) as the best entrainer for this separation. Keywords: CAILD, Alkane/cycloalkane extractive distillation, UNIFAC-IL, MINLP, Process performance and economic
Activation of melanocortin-1 receptor signaling in melanoma cells impairs T cell infiltration to dampen antitumor immunity
Abstract Inhibition of T cell infiltration dampens antitumor immunity and causes resistance to immune checkpoint blockade (ICB) therapy. By in vivo CRISPR screening in B16F10 melanoma in female mice, here we report that loss of melanocortin-1 receptor (MC1R) in melanoma cells activates antitumor T cell response and overcomes resistance to ICB. Depletion of MC1R from another melanocytic melanoma model HCmel1274 also enhances ICB efficacy. By activating the GNAS-PKA axis, MC1R inhibits interferon-gamma induced CXCL9/10/11 transcription, thus impairing T cell infiltration into the tumor microenvironment. In human melanomas, high MC1R expression correlates with reduced CXCL9/10/11 expression, impaired T cell infiltration, and poor patient prognosis. Whereas MC1R activation is restricted to melanoma, GNAS activation by hotspot mutations is observed across diverse cancer types and is associated with reduced CXCL9/10/11 expression. Our study implicates MC1R as a melanoma immunotherapy target and suggests GNAS-PKA signaling as a pan-cancer oncogenic pathway inhibiting antitumor T cell response