Mineralogical, physical and chemical analyses of the soils derived from Xiashu loess were carried out. The primary minerals of these soils were found to be mainly composed of light minerals, such as quartz, feldspar and mica, with traces of heavy minerals. Clay minerals, more complicate in composition, were dominated by hydromica, accompanied by smectite, vermiculite, chlorite, kaolinite, 2:1/1:1 randomly interstratified minerals and small amounts of quartz, goethite, lepidocrocite and hematite, Clay minerals were characterized by low crystallinity and fine particle size. In light of the quartz/ feldspars ratio of the 0.01-0.05mm silt fraction, and the clay mineral composition, the freeness of iron oxide, and the silica/ sesquioxide and silica/ alumina ratios in 0.002mm clay fraction, it is concluded that the weathering intensity of these soils was lower than those of red soil and yellow earth, but higher than that of brown earth, and that the soil allitization, depotassication and hydroxylation of clay minerals increased from west to east and from north to south geographically. However, this general tendency did not coincide exactly with the gradual alteration of the geographic coordinates, and in some places, a reverse tendency also appeared, which could be attributed to the influence of some soil forming factors such as parent material and microtopography.
In order to improve the drying efficiency and guarantee the grain quality after drying, this paper proposed to use artificial intelligence modelling to predict the grain quality indexes after drying. With air temperature, air relative humidity, initial moisture content, air velocity and tempering rate as control parameters, three models were established, and the prediction performance of these three models was tested. The three models were regression model, Back-propagation Neural Network (BPNN) and Deep Neural Network (DNN). The results showed that the machine learning techniques, in particular DNN had the best performance, especially for predicting germination rate ratio. The contribution of this paper is to demonstrate the ability of machine learning techniques in fitting grain drying characteristics with different control parameters. This paper proved the applicability of machine learning technology in grain drying field, and established the corresponding models.
If a custom hip stem could be designed according to X-ray films, the cost of the hip stem would be reduced, and a simpler designing method could be provided than using computer tomography images. In addition, the problem, which is that hip stems cannot be designed for some revision operations because of metal artifacts in computer tomography images, could be solved. A software system for designing custom hip stems based on X-ray films was developed. In order to verify whether the software system could be used, eleven femurs were used for this study. Hip stems for these eleven femurs were designed by using the software system. Ten of these femurs were taken computer tomography scans directly. According to the data collected from the computer tomography images, models of these ten femurs were rebuilt. Ten hip stem models, designed for these ten femurs, were simulated to be inserted into corresponding femur models. Results show each of the ten hip stems matches its corresponding femur. The hip stem designed for the remaining femur was manufactured and inserted in the remaining femur. Cancellous bone, retained in the matching area, was about 1–1.5 mm thick. From the above verifications, it could be concluded that the software system for designing custom hip stems based on X-ray films could be used to design custom hip stems.
Background: It is anticipated that there will be a large rise in the number of tumor diagnoses and mortality in those aged 65 and older over the course of upcoming decades. Immune checkpoint inhibitors, often known as ICIs, boost immune system activity by selectively targeting ICI genes. On the other hand, old age may be connected with unfavorable results. Methods: The Cancer Genome Atlas (TCGA) provided gene expression data from ccRCC tissue and key clinical variables. ICI gene databases were applied and verified using the GEO database. Results: We identified 14 ICI genes as risk gene signatures among 528 ccRCC patients using univariate and multivariable cox hazard models, and the elderly group was linked with poor survival. Then, by utilizing a new nomogram method, the TNFSF15 gene and age predicting values were estimated at one, three, and five years (85%, 81%, and 81%), respectively, and our age-related risk score was significant even after multivariable analysis (HR = 1.518, p = 0.009, CI = 1.1102.076). TNFSF15 gene expression was lower in elderly ccRCC patients (p = 0.0001). A negative connection between age and the TNFSF15 gene expression was discovered by correlation analysis (p = 0.0001). The verification of the gene by utilizing GEO (GSE167093) with 604 patients was obtained as external validation that showed significant differences in the TNFSF15 gene between young and elderly patients (p = 0.007). Additionally, the protein–protein interactions of the TNFSF15 gene with other ICI genes and aging-related genes was determined. In addition, the TNFSF15 expression was significantly correlated with pathological stages (p = 0.018). Furthermore, it was discovered that the biological processes of senescence, cellular senescence, the immune system, and many immune cell infiltration and immune function types are all closely tied. Conclusions: Along with the risk score evaluation, the ICI gene TNFSF15 was identified as a tumor suppressor gene related to inequalities in age survival and is associated with pathological stages and different immunity statuses. The aging responses of ccRCC patients and related gene expression need further investigation in order to identify potential therapeutic targets.
In order to manufacture a doubly curved sheet metal, the incremental roll forming process which adopts advantages such as the flexibility of the incremental forming process and continuous bending deformation of the roll forming process has been experimentally investigated. An experimental equipment was developed which was named as unit roll set (URS) consisting of two pairs of support rolls and an upper center roll. The upper roll equipped with the servo control unit is motor-driven and can be positioned in the vertical direction according to the user's commands. Four support rolls are idle, and they freely rotate only along the axis so as to transfer the plate more stably in the tangential direction of the rotation of the driving roll. In the process, the plate is deformed incrementally as deformation proceeds simultaneously in longitudinal and transverse directions. Through the experiments using URS, information regarding to forming schedules is found out to fabricate curved hull plates. This study demonstrates the further application of the incremental roll forming process in shipbuilding industries.
Describes simulations of impact forging processes. Uses the explicit time integration finite element method, which is based on direct time integration of equation of motion, to compute the deformation of the workpiece and the dies. Uses the program developed to simulate the copper blow test performed on a 350,000J counter‐blow hammer. The calculated result reveals a good agreement in the final deformed configurations between the experiment and the explicit simulation. In order to compare this with the explicit method, the implicit time integration rigid‐plastic finite element program considering the inertia effect is also applied to the copper blow test simulation. As a result of the copper blow test simulation using the explicit program and the implicit program, finds that the calculated results have good agreements in available plastic deformation energy, forging load and equivalent plastic strain distribution. Finally, applies the developed program to simulations of multi‐blow forging processes. Presents three major findings from the multi‐blow forging simulations: (1) the continuous analysis technique used for the multi‐blow forging simulations works well; (2) the blow efficiency and the forging load generated by blow operations can be analysed efficiently and simulated results coincide with previous experimental and analytical ones; (3) the geometrical configuration of the workpiece is closely related to blow efficiency.
Fresh pork is prone to spoilage during storage, transportation, and sale, resulting in reduced freshness. The total viable count (TVC) and total volatile basic nitrogen (TVB-N) content are key indicators for evaluating the freshness of fresh pork, and when they reach unacceptable limits, this seriously threatens dietary safety. To realize the on-site, low-cost, rapid, and non-destructive testing and evaluation of fresh pork freshness, a miniaturized detector was developed based on a cost-effective multi-channel spectral sensor. The partial least squares discriminant analysis (PLS-DA) model was used to distinguish fresh meat from deteriorated meat. The detector consists of microcontroller, light source, multi-channel spectral sensor, heat-dissipation modules, display system, and battery. In this study, the multispectral data of pork samples with different freshness levels were collected by the developed detector, and its ability to distinguish pork freshness was based on different spectral shape features (SSF) (spectral ratio (SR), spectral difference (SD), and normalized spectral intensity difference (NSID)) were compared. The experimental results show that compared with the original multispectral modeling, the performance of the model based on spectral shape features is significantly improved. The model established by optimizing the spectral shape feature variables has the best performance, and the discrimination accuracy of its prediction set is 91.67%. In addition, the validation accuracy of the optimal model was 86.67%, and its sensitivity and variability were 87.50% and 85.71%, respectively. The results show that the detector developed in this study is cost-effective, compact in its structure, stable in its performance, and suitable for the on-site digital rapid non-destructive testing of freshness during the storage, transportation, and sale of fresh pork.
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