Desirability Function Analysis (DFA) in Multiple Responses Optimization of Abrasive Water Jet Cutting Process

This paper introduces optimization of machining parameters for high-pressure abrasive water jet cutting of Hardox 500 steel utilizing desirability function analysis (DFA). The tests were carried out according to the orthogonal matrix (Taguchi) L9. The control parameters of the process such as pressure, abrasive flow rate, and traverse speed was optimized under multi-response conditions namely cutting depth and surface roughness. The optimal set of control parameters was established on the basis of the composite desirability value obtained from desirability function analysis and the significance of these parameters was determined by analysis of variance (ANOVA). The effects show that optimal sets for high cutting depth and small surface roughness is high pressure, middle abrasive flow rate, and small traverse speed. A confirmation test was also leaded to validate the test results. Results of the research have shown that machining efficiency at keeping good level quality of cut surface can be improved this approach.

The lithospheric folding model applied to the Bighorn uplift during the Laramide orogeny

ABSTRACT The Bighorn uplift, Wyoming, developed in the Rocky Mountain foreland during the 75–55 Ma Laramide orogeny. It is one of many crystalline-cored uplifts that resulted from low-amplitude, large-wavelength folding of Phanerozoic strata and the basement nonconformity (Great Unconformity) across Wyoming and eastward into the High Plains region, where arch-like structures exist in the subsurface. Results of broadband and passive-active seismic studies by the Bighorn EarthScope project illuminated the deeper crustal structure. The seismic data show that there is substantial Moho relief beneath the surface exposure of the basement arch, with a greater Moho depth west of the Bighorn uplift and shallower Moho depth east of the uplift. A comparable amount of Moho relief is observed for the Wind River uplift, west of the Bighorn range, from a Consortium for Continental Reflection Profiling (COCORP) profile and teleseismic receiver function analysis of EarthScope Transportable Array seismic data. The amplitude and spacing of crystalline-cored uplifts, together with geological and geophysical data, are here examined within the framework of a lithospheric folding model. Lithospheric folding is the concept of low-amplitude, large-wavelength (150–600 km) folds affecting the entire lithosphere; these folds develop in response to an end load that induces a buckling instability. The buckling instability focuses initial fold development, with faults developing subsequently as shortening progresses. Scaled physical models and numerical models that undergo layer-parallel shortening induced by end loads determine that the wavelength of major uplifts in the upper crust occurs at approximately one third the wavelength of folds in the upper mantle for strong lithospheres. This distinction arises because surface uplifts occur where there is distinct curvature upon the Moho, and the vergence of surface uplifts can be synthetic or antithetic to the Moho curvature. In the case of the Bighorn uplift, the surface uplift is antithetic to the Moho curvature, which is likely a consequence of structural inheritance and the influence of a preexisting Proterozoic suture upon the surface uplift. The lithospheric folding model accommodates most of the geological observations and geophysical data for the Bighorn uplift. An alternative model, involving a crustal detachment at the orogen scale, is inconsistent with the absence of subhorizontal seismic reflectors that would arise from a throughgoing, low-angle detachment fault and other regional constraints. We conclude that the Bighorn uplift—and possibly other Laramide arch-like structures—is best understood as a product of lithospheric folding associated with a horizontal end load imposed upon the continental margin to the west.

Extended Function Analysis of Urban Planning and Design Based on Automatic Extraction Algorithm of Closed Area Boundary

With the continuous development of social economy, the expansion of cities often leads to the disorderly utilization of land resources and even waste. In view of these limitations and requirements, this paper introduces the automatic extraction algorithm of closed area boundary, combs the requirements of urban boundary extraction involved in urban planning and design, and uses the technology of geospatial analysis to carry out spatial analysis practice from three angles, so as to realize the expansion of functional analysis of urban planning and design and improve the efficiency and rationality of urban planning. The simulation results show that the automatic extraction algorithm of closed area boundary is effective and can support the functional analysis of urban planning and design expansion.

Trophic guilds of suction-feeding fishes are distinguished by their characteristic hydrodynamics of swimming and feeding

Suction-feeding in fishes is a ubiquitous form of prey capture whose outcome depends both on the movements of the predator and the prey, and on the dynamics of the surrounding fluid, which exerts forces on the two organisms. The inherent complexity of suction-feeding has challenged previous efforts to understand how the feeding strikes are modified when species evolve to feed on different prey types. Here, we use the concept of dynamic similarity, commonly applied to understanding the mechanisms of swimming, flying, walking and aquatic feeding. We characterize the hydrodynamic regimes pertaining to (i) the forward movement of the fish (ram), and (ii) the suction flows for feeding strikes of 71 species of acanthomorph fishes. A discriminant function analysis revealed that feeding strikes of zooplanktivores, generalists and piscivores could be distinguished based on their hydrodynamic regimes. Furthermore, a phylogenetic comparative analysis revealed that there are distinctive hydrodynamic adaptive peaks associated with zooplanktivores, generalists and piscivores. The scaling of dynamic similarity across species, body sizes and feeding guilds in fishes indicates that elementary hydrodynamic principles govern the trophic evolution of suction-feeding in fishes.

Characterising the Area Under the Curve Loss Function Landscape

One of the most common metrics to evaluate neural network classifiers is the area under the receiver operating characteristic curve (AUC). However, optimisation of the AUC as the loss function during network training is not a standard procedure. Here we compare minimising the cross-entropy (CE) loss and optimising the AUC directly. In particular, we analyse the loss function landscape (LFL) of approximate AUC (appAUC) loss functions to discover the organisation of this solution space. We discuss various surrogates for AUC approximation and show their differences. We find that the characteristics of the appAUC landscape are significantly different from the CE landscape. The approximate AUC loss function improves testing AUC, and the appAUC landscape has substantially more minima, but these minima are less robust, with larger average Hessian eigenvalues. We provide a theoretical foundation to explain these results. To generalise our results, we lastly provide an overview of how the LFL can help to guide loss function analysis and selection.

Identification and Evolutionary Characteristic Analysis of STARD Gene Family, and Overexpression VvSTARD5 Responses to Salt Stress in Tomato

This study aimed to have a full understanding of the steroidogenic acute regulatory gene family member and evolutionary relationship in grape. 23 VvSTARD gene members were identified and divided into five groups in different species. Analyses of the gene codon preference, selective pressure, and tandem duplication of the VvSTARD, AtSTARD, and OsSTARD genes indicated that synteny relationship occurred in grapes, Arabidopsis thaliana, and rice genomes. The 8 lipid transporter proteins were found in the tertiary structure of the STARD gene family in grape. Expression profiles of the three species microarrays showed that the expression levels of the STARD genes in different organs and the response to abiotic stress in the same subgroup had similar characteristics. In addition, analysis of the VvSTARD genes expression levels was detected in response to different hormones and abiotic stresses by quantitative real-time polymerase chain reaction (qRT-PCR), and the results were the same as those predicted by the cis-elements and the expression profiles. Meanwhile, VvSTARD5 gene was screened in high concentration NaCl treatment by qRT-PCR. Furthermore, the VvSTARD5 was located at the nucleus by subcellular location. Through the function analysis of salt tolerance in transgenic tomato, overexpression VvSTARD5 obviously improved tolerance to salt stress. Taken together, our findings Preliminary identify the functions of VvSTARD gene family and vertify STARD5 that be likely involved in regulating salt tolerance, which may have potential application molecular breeding in grape.

Open-Bundle Structure as the Unfolding Intermediate of Cytochrome c′ Revealed by Small Angle Neutron Scattering

The dynamic structure changes, including the unfolding, dimerization, and transition from the compact to the open-bundle unfolding intermediate structure of Cyt c′, were detected by a small-angle neutron scattering experiment (SANS). The structure of Cyt c′ was changed into an unstructured random coil at pD = 1.7 (Rg = 25 Å for the Cyt c′ monomer). The four-α-helix bundle structure of Cyt c′ at neutral pH was transitioned to an open-bundle structure (at pD ~13), which is given by a numerical partial scattering function analysis as a joint-clubs model consisting of four clubs (α-helices) connected by short loops. The compactly folded structure of Cyt c′ (radius of gyration, Rg = 18 Å for the Cyt c′ dimer) at neutral or mildly alkaline pD transited to a remarkably larger open-bundle structure at pD ~13 (Rg = 25 Å for the Cyt c′ monomer). The open-bundle structure was also supported by ab initio modeling.

Probability Density Function Analysis Based on Logistic Regression Model

The data fitting level in probability density function analysis has great influence on the analysis results, so it is of great significance to improve the data fitting level. Therefore, a probability density function analysis method based on logistic regression model is proposed. The logistic regression model with kernel function is established, and the optimal window width and mean square integral error are selected to limit the solution accuracy of probability density function. Using the real probability density function, the probability density function with the smallest error is obtained. The estimated probability density function is analyzed from two aspects of consistency and convergence speed. The experimental results show that compared with the traditional probability density function analysis method, the probability density function analysis method based on logistics regression model has a higher fitting level, which is more suitable for practical research projects.