Aerodynamic Parameter Estimation of a Symmetric Projectile Using Adaptive Chaotic Mutation Particle Swarm Optimization

This article details a new optimizing algorithm called Adaptive Chaotic Mutation Particle Swarm Optimization (ACM-PSO). The new algorithm is used to perform aerodynamic parameter estimation on a spinning symmetric projectile. The main creative ideas of this new algorithm are as follows. First, a self-adaptive weight function is used so that the inertial weight can be adjusted dynamically by itself. Second, the initialized particle is generated by chaos theory. Last, a method that can be used to judge whether the algorithm has fallen into a local optimum is established. The common testing function is used to test the new algorithm, and the result shows that, compared with the basic particle swarm optimization (PSO) algorithm, it is more likely to have a quick convergence and high accuracy and precision, leading to extensive application. Simulated ballistic data are used as testing data, and the data are subjected to the new algorithm to identify the aerodynamic parameters of a spinning symmetric projectile. The result shows that the algorithm proposed in this paper can effectively identify the aerodynamic parameters with high precision and a quick convergence velocity and is therefore suitable for use in actual engineering

Markov probabilistic decision making of self-driving cars in highway with random traffic flow: a simulation study

Purpose - Decision-making is one of the key technologies for self-driving cars. The high dependency of previously existing methods on human driving data or rules makes it difficult to model policies for different driving situations. Design/methodology/approach - In this research, a probabilistic decision-making method based on the Markov decision process (MDP) is proposed to deduce the optimal maneuver automatically in a two-lane highway scenario without using any human data. The decision-making issues in a traffic environment are formulated as the MDP by defining basic elements including states, actions and basic models. Transition and reward models are defined by using a complete prediction model of the surrounding cars. An optimal policy was deduced using a dynamic programing method and evaluated under a two-dimensional simulation environment. Findings - Results show that, at the given scenario, the self-driving car maintained safety and efficiency with the proposed policy. Originality/value - This paper presents a framework used to derive a driving policy for self-driving cars without relying on any human driving data or rules modeled by hand

Distinguishing Emission-Associated Ambient Air PM2.5 Concentrations and Meteorological Factor-Induced Fluctuations

Although PM2.5 (particulate matter with aerodynamic diameters less than 2.5 μm) in the air originates from emissions, its concentrations are often affected by confounding meteorological effects. Therefore, direct comparisons of PM2.5 concentrations made across two periods, which are commonly used by environmental protection administrations to measure the effectiveness of mitigation efforts, can be misleading. Here, we developed a two-step method to distinguish the significance of emissions and meteorological factors and assess the effectiveness of emission mitigation efforts. We modeled ambient PM2.5 concentrations from 1980 to 2014 based on three conditional scenarios: realistic conditions, fixed emissions, and fixed meteorology. The differences found between the model outputs were analyzed to quantify the relative contributions of emissions and meteorological factors. Emission-related gridded PM2.5 concentrations excluding the meteorological effects were predicted using multivariate regression models, whereas meteorological confounding effects on PM2.5 fluctuations were characterized by probabilistic functions. When the regression models and probabilistic functions were combined, fluctuations in the PM2.5 concentrations induced by emissions and meteorological factors were quantified for all model grid cells and regions. The method was then applied to assess the historical and future trends of PM2.5 concentrations and potential fluctuations on global, national, and city scales. The proposed method may thus be used to assess the effectiveness of mitigation actions

Impacts of air pollutants from rural Chinese households under the rapid residential energy transition

Rural residential energy consumption in China is experiencing a rapid transition towards clean energy, nevertheless, solid fuel combustion remains an important emission source. Here we quantitatively evaluate the contribution of rural residential emissions to PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) and the impacts on health and climate. The clean energy transitions result in remarkable reductions in the contributions to ambient PM2.5, avoiding 130,000 (90,000-160,000) premature deaths associated with PM2.5 exposure. The climate forcing associated with this sector declines from 0.057 ± 0.016 W/m2 in 1992 to 0.031 ± 0.008 W/m2 in 2012. Despite this, the large remaining quantities of solid fuels still contributed 14 ± 10 μg/m3 to population-weighted PM2.5 in 2012, which comprises 21 ± 14% of the overall population-weighted PM2.5 from all sources. Rural residential emissions affect not only rural but urban air quality, and the impacts are highly seasonal and location dependent

Novel emerging nano-assisted anti-cancer strategies based on the STING pathway

Activation of simulator of interferon genes (STING), which induces the production of proinflammatory factors and immune effector cell activation, is considered a promising strategy for enhanced anti-cancer intervention. However, several obstacles prevent STING signaling in solid tumors, such as delivered molecules’ rapid degradation, restriction to tumor sites, insufficient intracellular concentrations, and low responsivity. Well-designed, multifunctional nano-formulations have emerged as optimized platforms for STING activation. Recently, a variety of nano-formulations have been developed and used in STING activation, thus facilitating immunotherapy in preclinical and clinical stages. Herein, we summarize recent advances in nanotechnology-based delivery, activation, and application strategies, which have advanced various aspects of immunotherapy. Novel STING agonists and their mechanisms in STING-activation-mediated tumor interventions are highlighted herein, to provide a comprehensive overview and discuss future directions for boosting immunotherapy via STING regulation

Effects of salt stress and nitrogen application on growth and ion accumulation of Suaeda salsa plants

Suaeda salsa is a typical pioneer species which can grow well in high salt environmental conditions. The objective of this study is to evaluate the effect of different levels of salinity (5.25, 10.5 and 21g NaCl per kg soil) and nutrient supply (0, 0.3, 0.6 and 1.2g urea per kg soil) on plant morphology, biomass, accumulation of ions and C/N ratio in leaves of S. salsa. The results showed that the plant height, number of branches, length of branches and diameter of shoot were significantly affected by salt stress, and the nitrogen released the negative effects of salt. The nitrogen treatment increased the biomass ofleaf, shoot and root. Leaf water content was significantly affected by the interaction of salt stress andnitrogen treatment. The content of Na + and Cl- increased significantly as increasing of salt, the content ofK+, Ca2+, Mg2+ and SO 42- decreased simultaneously to keep ion balance. The C/N ratio decreased significantly as increasing of nitrogen treatment. The content of proline increased significantly with the increasing of salt and nitrogen treatments. The results together indicated that at different saltenvironment, different amount of nitrogen supply can be used to improve the population growth of S.salsa plants, and the restoration of degraded wetland could be accelerated by nutrient supply reasonably.&nbsp

A Mutation in Intracellular Loop 4 Affects the Drug-Efflux Activity of the Yeast Multidrug Resistance ABC Transporter Pdr5p

Multidrug resistance protein Pdr5p is a yeast ATP-binding cassette (ABC) transporter in the plasma membrane. It confers multidrug resistance by active efflux of intracellular drugs. However, the highly polymorphic Pdr5p from clinical strain YJM789 loses its ability to expel azole and cyclohexmide. To investigate the role of amino acid changes in this functional change, PDR5 chimeras were constructed by segmental replacement of homologous BY4741 PDR5 fragments. Functions of PDR5 chimeras were evaluated by fluconazole and cycloheximide resistance assays. Their expression, ATPase activity, and efflux efficiency for other substrates were also analyzed. Using multiple lines of evidence, we show that an alanine-to-methionine mutation at position 1352 located in the predicted short intracellular loop 4 significantly contributes to the observed transport deficiency. The degree of impairment is likely correlated to the size of the mutant residue

Comparison of transcriptional responses in liver tissue and primary hepatocyte cell cultures after exposure to hexahydro-1, 3, 5-trinitro-1, 3, 5-triazine

BACKGROUND: Cell culture systems are useful in studying toxicological effects of chemicals such as Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), however little is known as to how accurately isolated cells reflect responses of intact organs. In this work, we compare transcriptional responses in livers of Sprague-Dawley rats and primary hepatocyte cells after exposure to RDX to determine how faithfully the in vitro model system reflects in vivo responses. RESULTS: Expression patterns were found to be markedly different between liver tissue and primary cell cultures before exposure to RDX. Liver gene expression was enriched in processes important in toxicology such as metabolism of amino acids, lipids, aromatic compounds, and drugs when compared to cells. Transcriptional responses in cells exposed to 7.5, 15, or 30 mg/L RDX for 24 and 48 hours were different from those of livers isolated from rats 24 hours after exposure to 12, 24, or 48 mg/Kg RDX. Most of the differentially expressed genes identified across conditions and treatments could be attributed to differences between cells and tissue. Some similarity was observed in RDX effects on gene expression between tissue and cells, but also significant differences that appear to reflect the state of the cell or tissue examined. CONCLUSION: Liver tissue and primary cells express different suites of genes that suggest they have fundamental differences in their cell physiology. Expression effects related to RDX exposure in cells reflected a fraction of liver responses indicating that care must be taken in extrapolating from primary cells to whole animal organ toxicity effects

Assessing Reproducibility of Inherited Variants Detected With Short-Read Whole Genome Sequencing

Background: Reproducible detection of inherited variants with whole genome sequencing (WGS) is vital for the implementation of precision medicine and is a complicated process in which each step affects variant call quality. Systematically assessing reproducibility of inherited variants with WGS and impact of each step in the process is needed for understanding and improving quality of inherited variants from WGS. Results: To dissect the impact of factors involved in detection of inherited variants with WGS, we sequence triplicates of eight DNA samples representing two populations on three short-read sequencing platforms using three library kits in six labs and call variants with 56 combinations of aligners and callers. We find that bioinformatics pipelines (callers and aligners) have a larger impact on variant reproducibility than WGS platform or library preparation. Single-nucleotide variants (SNVs), particularly outside difficult-to-map regions, are more reproducible than small insertions and deletions (indels), which are least reproducible when \u3e 5 bp. Increasing sequencing coverage improves indel reproducibility but has limited impact on SNVs above 30×. Conclusions: Our findings highlight sources of variability in variant detection and the need for improvement of bioinformatics pipelines in the era of precision medicine with WGS