The reasonableness and accuracy of engineering design are often assessed through the use of a variety of structural design analysis software, which are then compared and verified. However, it is challenging for a single analysis software to meet the diverse and complex design requirements. In order to meet the specific engineering requirements, it is necessary to convert the MIDAS result model into an ANSYS structural model and conduct a nonlinear analysis and simulation in ANSYS. Nevertheless, the existing interface is unable to facilitate direct conversion of the model. Accordingly, this paper presents a Python-based ANSYS APDL program that enables the complete conversion of MIDAS GEN structural models to ANSYS finite element models. The program is capable of converting a range of data, including material, section, element, connection, load, node mass, constraint, time history function, and so forth. The program is capable of converting specific connection units, including elastic and general connection units. Additionally, the beam-column section direction, beam end freedom release, rigid element, and special anti-rocking structure of the structure can be considered. Ultimately, the theatre model is transformed. Following a comparison of the analysis results, it was found that the mass and mode of the model before and after the transformation were essentially identical. The maximum error of the first six orders of the structure is 2.95%, with the structural displacement under gravity load remaining essentially unchanged. The research and analysis demonstrate the accuracy and reliability of the MIDAS GEN conversion ANSYS program. The conversion program significantly reduces the time required for direct modeling in ANSYS, enhancing work efficiency. The study has considerable practical significance for the seismic sway design and analysis of buildings based on vibration isolation design.

In this study, we employ the GARCH-MIDAS (Generalised Autoregressive Conditional Heteroskedasticity variant of Mixed Data Sampling) model to explore the predictability of commodity return volatility in relation to US climate policy uncertainty (CPU). Our analysis utilizes the 20-day annualized realized commodity volatility returns of nine global commodities (Aluminium, Cocoa, Coffee, Copper, Cotton, Rice, Soybean, Sugar, and Wheat) to construct the GARCH-MIDAS model, with Climate Policy Uncertainty (CPU) serving as the predictive variable. The outcomes of our investigation reveal a consistently positive and statistically significant relationship between CPU and the selected commodities. This implies that CPU effectively serves as a robust predictor of volatility in commodity returns. The implications drawn from our results suggest that climate change policies play a pivotal role in influencing economic activities within the commodity market. This underscores the substantial impact of climate change considerations on investment decisions and further emphasizes the integral role of climate change in shaping economic choices.

Mitochondrial disorders, although heterogeneous, are traditionally described as conditions characterized by encephalomyopathy, hypotonia and progressive postnatal organ failure. Here we provide a systematic review of Linear Skin Defects with Multiple Congenital Anomalies (LSDMCA), a rare unconventional mitochondrial disorder which presents as a developmental disease; its main clinical features include microphthalmia with different degrees of severity, linear skin lesions, and central nervous system malformations. The molecular basis of this disorder has been elusive for several years. Mutations were eventually identified in three X-linked genes, i.e., HCCS, COX7B, and NDUFB11, which are all endowed with defined roles in the mitochondrial respiratory chain. A peculiar feature of this condition is its inheritance pattern: X-linked dominant male-lethal. Only female or XX male individuals can be observed, implying that nullisomy for these transcripts is incompatible with normal embryonic development in mammals. All three genes undergo X-inactivation that, according to our hypothesis, may contribute to the extreme variable expressivity observed in this condition. We propose that mitochondrial dysfunction should be considered as an underlying cause in developmental disorders. Moreover, LSDMCA should be taken into consideration by clinicians when dealing with patients with microphthalmia with or without associated skin phenotypes.