Constitutive model of 3Cr23Ni8Mn3N heat-resistant steel based on back propagation (BP) neural network (NN)

The 3Cr23Ni8Mn3N heat-resistant steel was subjected to isothermal constant strain rate compression experiments using a Gleeble - 1 500D thermal simulator. The thermal deformation behavior in the range of deformation temperature 1 000 - 1 180 °C and strain rate 0,01 - 10 s-1 was studied. Based on experimental data, the stress-strain curves of 3Cr23Ni8Mn3N were established. And the constitutive relation of BP neural network (3 × 10 × 10 × 1) was constructed. The flow stress was predicted and compared by the ANN constitutive model. The correlation coefficient (R) is 0,999, and the average relative error (AARE) is 0,697 %. The results show that the ANN constitutive model has high accuracy for predicting the thermal deformation behavior of 3Cr23Ni8Mn3N. The model can provide a good reference value for thermal processing

Recombinant expression and functional analysis of a Chlamydomonas reinhardtii bacterial-type phosphoenolpyruvate carboxylase gene fragment

To investigate the function of a bacterial-type phosphoenolpyruvate carboxylase (PEPC2) derived from photosynthetically-grown Chlamydomonas reinhardtii, a fragment of the pepc2 gene was cloned and expressed in Escherichia coli. After optimal induction for 6 h, PEPC activity in the reverse mutant was lower than wild type (0.9 vs. 1.7 U/mg protein), and soluble protein was also lower than wild type (119 vs. 186 mg/g dry wt). In contrast, the total lipid content was increased from 56 (in wild type) to 71 mg/g dry wt, despite the growth rate being slightly diminished. The changes in PEPC activity, soluble protein and total lipid in the forward mutant were the opposite (2.4 U/mg, 230 mg/g, and 44 mg/g dry wt, respectively). Together, these data indicate that PEPC may function as a metabolic pivot in the regulation of protein and lipid accumulation in this alga

Experimental study of organic Rankine cycle in the presence of non-condensable gases

Non-condensable gases (NCGs) are inevitable in organic Rankine cycle (ORC) system, and they have adverse impacts. A small-scale ORC test platform using scroll expander and R123 was constructed to investigate the NCGs effect. The expander backpressure (i.e. condenser outlet pressure) and electricity output were examined on different conditions of NCGs mass fraction (xNCG), hot side temperature (Th) and condensation temperature (Tc). Two new parameters, namely reduced coefficient of pressure ratio (RCOPR) and filling ratio of reservoir (FROR), were proposed to reveal the mechanism of ORC performance degradation in the presence of NCGs. The results show that the partial pressure of NCGs (PNCG) in reservoir at work differed from that at static state. Unlike R123, NCGs were blocked by the reservoir and had no access to the pump. The accumulation of NCGs led to unexpected expander backpressure, which could be 0.68 bar higher than the saturation pressure when Th = 140 °C, Tc = 50 °C and xNCG = 1.3%. PNCG generally increased as FROR rose. The FROR changed with Th, Tc and R123 mass flow rate. The relative increment in electricity output of the ORC with xNCG = 1.3% over that with xNCG = 12% was significant, and could reach 114% when Th = 100 °C and Tc = 50 °C

Machine learning analysis reveals aberrant dynamic changes in amplitude of low-frequency fluctuations among patients with retinal detachment

BackgroundThere is increasing evidence that patients with retinal detachment (RD) have aberrant brain activity. However, neuroimaging investigations remain focused on static changes in brain activity among RD patients. There is limited knowledge regarding the characteristics of dynamic brain activity in RD patients.AimThis study evaluated changes in dynamic brain activity among RD patients, using a dynamic amplitude of low-frequency fluctuation (dALFF), k-means clustering method and support vector machine (SVM) classification approach.MethodsWe investigated inter-group disparities of dALFF indices under three different time window sizes using resting-state functional magnetic resonance imaging (rs-fMRI) data from 23 RD patients and 24 demographically matched healthy controls (HCs). The k-means clustering method was performed to analyze specific dALFF states and related temporal properties. Additionally, we selected altered dALFF values under three distinct conditions as classification features for distinguishing RD patients from HCs using an SVM classifier.ResultsRD patients exhibited dynamic changes in local intrinsic indicators of brain activity. Compared with HCs, RD patients displayed increased dALFF in the bilateral middle frontal gyrus, left putamen (Putamen_L), left superior occipital gyrus (Occipital_Sup_L), left middle occipital gyrus (Occipital_Mid_L), right calcarine (Calcarine_R), right middle temporal gyrus (Temporal_Mid_R), and right inferior frontal gyrus (Frontal_Inf_Tri_R). Additionally, RD patients showed significantly decreased dALFF values in the right superior parietal gyrus (Parietal_Sup_R) and right paracentral lobule (Paracentral_Lobule_R) [two-tailed, voxel-level p < 0.05, Gaussian random field (GRF) correction, cluster-level p < 0.05]. For dALFF, we derived 3 or 4 states of ALFF that occurred repeatedly. There were differences in state distribution and state properties between RD and HC groups. The number of transitions between the dALFF states was higher in the RD group than in the HC group. Based on dALFF values in various brain regions, the overall accuracies of SVM classification were 97.87, 100, and 93.62% under three different time windows; area under the curve values were 0.99, 1.00, and 0.95, respectively. No correlation was found between hamilton anxiety (HAMA) scores and regional dALFF.ConclusionOur findings offer important insights concerning the neuropathology that underlies RD and provide robust evidence that dALFF, a local indicator of brain activity, may be useful for clinical diagnosis