PSO-based Parameter Estimation of Nonlinear Kinetic Models for β-Mannanase Fermentation

Particle swarm optimization (PSO), as a novel evolutionary algorithm involved in social interaction for global space search, was firstly used in kinetic parameter estimation. Based on three developed nonlinear kinetic equations for bacterial cell growth, total sugar utilization and β-mannanase production by Bacillus licheniformis under the support of a batch fermentation process, various PSO algorithms as well as gene algorithms (GA) were developed to estimate kinetic parameters. The performance comparison among these algorithms indicates the improved PSO (Trelea 1) is most suitable for kinetic parameter estimation of β-mannanase fermentation. In order to find the physical-chemical-meanings of kinetic parameters from many optimized results, multiobjective optimization with a normalized weight method was adopted. The 9 desired parameters in equations were obtained by the Trelea 1 type PSO with two batches fermentation data, and the results predicted by the models were also in good agreement with the experimental observations

Analysis of Gas Nitriding Characteristics under Different Cold Hardening and Nitriding Pressure Conditions for Low-Carbon Low-Alloy Steel

A new approach to quick preparation of a nitrided case for low-carbon low-alloy steels was proposed. It is based on cold hardening and pressurized gas nitriding. The microstructure, surface hardness, thickness, and corrosion resistance of the nitrided layer on low-carbon low-alloy steel (20CrMnTi) were investigated after the nitriding at 510°C for 5 h under different cold rolling reduction (0–60% CR) and nitriding pressure (1–5 atm).Предложен новый способ получения азотированного слоя на малоуглеродистых низколегированных сталях с использованием холодного деформирования и газового азотирования давлением. Изучены микроструктура, поверхностная твердость, толщина и коррозионная стойкость азотированного слоя на стали 20CrMnTi после азотирования при 510°С в течение 5 ч в различных условиях обжатия при холодной прокатке (0-60% СR) и давлении азотирования (1-5 атм)

Targeting Wnt/β-catenin signaling by TET1/FOXO4 inhibits metastatic spreading and self-renewal of cancer stem cells in gastric cancer

Metastasis is the main cause of death for patients suffering gastric cancer. Epithelial-mesenchymal transition (EMT) and cancer stem cells (CSC) are critical attributes of metastasis, both of which are regulated tightly by DNA methylation and Wnt/β-catenin signaling. Here, we studied the functions of DNA dioxygenase TET1 in regulating Wnt signaling and in gastric cancer metastasis. Knocking-down and overexpressing TET1 in gastric cancer cells promoted and inhibited metastatic spreading to the liver in immune-deficient mice, respectively. TET1 showed inhibitory effects on metastasis-related features -EMT and CSC, which were reversed by interfering with Wnt/β-catenin signaling. RNA-sequencing identified FOXO4 as a direct transactivating target of TET1. FOXO4 directly interacted with β-catenin and recruited it in the cytoplasm, so as to inhibit β-catenin-mediated transcription of Wnt target genes, including CSC marker EpCAM. Moreover, modulation of FOXO4 could reverse the effects of TET1 manipulation on EMT and self-renewal of CSCs. The analysis with clinical samples confirmed the value of FOXO4 as an independent prognostic predictor of patients' overall survival. Taken together, regulation of Wnt signaling by TET1/FOXO4 is essential for metastasis-associated cellular properties, and targeting TET1/FOXO4/β-catenin pathway may serve as promising therapeutics in the prevention and treatment of gastric cancer metastasis

Fabrication of CuO nanoparticle interlinked microsphere cages by solution method

Here we report a very simple method to convert conventional CuO powders to nanoparticle interlinked microsphere cages by solution method. CuO is dissolved into aqueous ammonia, and the solution is diluted by alcohol and dip coating onto a glass substrate. Drying at 80 °C, the nanostructures with bunchy nanoparticles of Cu(OH)2can be formed. After the substrate immerges into the solution and we vaporize the solution, hollow microspheres can be formed onto the substrate. There are three phases in the as-prepared samples, monoclinic tenorite CuO, orthorhombic Cu(OH)2, and monoclinic carbonatodiamminecopper(II) (Cu(NH3)2CO3). After annealing at 150 °C, the products convert to CuO completely. At annealing temperature above 350 °C, the hollow microspheres became nanoparticle interlinked cages

Performance investigation of hybrid excited switched flux permanent magnet machines using frozen permeability method

This study investigates the electromagnetic performance of a hybrid excited switched flux permanent magnet (SFPM) machine using the frozen permeability (FP) method. The flux components due to PMs, field excitation windings and armature windings have been separated using the FP method. It has been used to separate the torque components due to the PMs and excitations, providing a powerful insight into the torque generation mechanism of hybrid excited SFPM machines. It also allows the accurate calculation of d- and q-axis inductances, which will then be used to calculate the torque, power and power factor against rotor speed to compare the relative merits of hybrid excited SFPM machines with different types of PMs (i.e. NdFeB, SmCo and Ferrite). This offers the possibility of choosing appropriate PMs for different applications (maximum torque or maximum speed). Although only one type of hybrid excited PM machine has been employed to carry out the investigations, the method used in this study can also be extended to other hybrid excited PM machines. The predicted results have been validated by tests

Fine structure in the α decay of 223U

Fine structure in the α decay of 223U was observed in the fusion-evaporation reaction 187Re(40Ar, p3n) by using fast digital pulse processing technique. Two α-decay branches of 223U feeding the ground state and 244 keV excited state of 219Th were identified by establishing the decay chain 223U →α1 219Th →α2 215Ra →α3 211Rn. The α-particle energy for the ground-state to ground-state transition of 223U was determined to be 8993(17) keV, 213 keV higher than the previous value, the half-life was updated to be 62−10+14 μs. Evolution of nuclear structure for N = 131 even-Z isotones from Po to U was discussed in the frameworks of nuclear mass and reduced α-decay width, a weakening octupole deformation in the ground state of 223U relative to its lighter isotones 219Ra and 221Th was suggested

Neuroimaging-based classification of PTSD using data-driven computational approaches: a multisite big data study from the ENIGMA-PGC PTSD consortium

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.Stress-related psychiatric disorders across the life spa

Precision Measurement of the Proton Flux in Primary Cosmic Rays from Rigidity 1 GV to 1.8 TV with the Alpha Magnetic Spectrometer on the International Space Station

A precise measurement of the proton flux in primary cosmic rays with rigidity (momentum/charge) from 1 GV to 1.8 TV is presented based on 300 million events. Knowledge of the rigidity dependence of the proton flux is important in understanding the origin, acceleration, and propagation of cosmic rays. We present the detailed variation with rigidity of the flux spectral index for the first time. The spectral index progressively hardens at high rigidities.</p