Post-Fire Seismic Performance of Concrete-Filled Steel Tube Frame Structures Considering Soil-Structure Interaction (SSI)

Currently, reinforced thin-walled irregular steel tube concrete frame structures have been applied in engineering, but there are few researches on the seismic performance of this type of structures after fire. The seismic performance of structures after fire is generally carried out based on rigid foundation conditions. Therefore, it is of certain engineering and theoretical value to study the seismic performance considering the SSI (soil–structure interaction) in this paper. ABAQUS is employed to establish the finite element models of the reinforced thin-walled irregular steel tube concrete frame structure considering the SSI after a fire. The paper analyzes the impact of different site conditions and fire durations on the structural natural vibration period, maximum acceleration, inter-story shear force, and maximum inter-story displacement angle. The results show that the consideration of the SSI increases the basic natural vibration period of the structure by 10–30%. The softer the soil and the longer the fire duration, the more significant the increase. For harder soil, lower seismic intensity, and shorter fire duration, the acceleration assigned to the structure and foundation after considering the SSI is smaller than the results assuming a rigid foundation. The change in inter-story shear force is mainly determined by the acceleration of the structure and foundation. The inter-story displacement angle increases when considering the SSI, and the increase is more significant with softer soil, larger seismic wave acceleration amplitude, and longer fire duration

Review on Phase Behavior in Tight Porous Media and Microscopic Flow Mechanism of CO2 Huff-n-Puff in Tight Oil Reservoirs

The successful development of tight oil reservoirs in the U.S. shows the bright future of unconventional reservoirs. Tight oil reservoirs will be the main target of exploration and development in the future, and CO2 huff-n-puff is one of the most important methods to enhance oil recovery factor of tight oil reservoirs in North America. To improve the performance of CO2 huff-n-puff, injection and production parameters need to be optimized through numerical simulation. The phase behavior and microscopic flow mechanism of CO2 huff-n-puff in porous media need to be further investigated. This paper presents a detailed review of phase behavior and microscopic flow mechanism in tight porous media by CO2 huff-n-puff. Phase behavior in tight porous media is different from that in a PVT cylinder since the capillary pressure in tight porous media reduces the bubble point pressure and increases the miscibility pressure and critical temperature. The condensate pressure in tight porous media and nonequilibrium phase behavior need to be further investigated. The microscopic flow mechanism during CO2 huff-n-puff in tight porous media is complicated, and the impact of molecular diffusion, gas-liquid interaction, and fluid-rock interaction on multiphase flow is significant especially in tight porous media. Nuclear magnetic resonance (NMR) and molecular simulation are efficient methods to describe the microscopic flow in tight oil reservoirs, while the NMR is not cost-effective and molecular simulation needs to be improved to better characterize and model the feature of porous media. The improved molecular simulation is still a feasible method to understand the microscopic flow mechanism of CO2 huff-n-puff in tight oil reservoirs in the near future. The microscopic flow model in micropore network based on digital core is worth to be established, and phase behavior needs to be further incorporated into the microscopic flow model of CO2 huff-n-puff in tight porous media

Comparison of ANN and LR models for predicting Carbapenem-resistant Klebsiella pneumoniae isolates from a southern province of China's RNSS data

ABSTRACT: Objectives: Carbapenem-resistant Klebsiella pneumoniae (CRKP) is a serious threat to public health due to its limited treatment options and high mortality rate. This study aims to identify the risk factors of carbapenem resistance in patients with K. pneumoniae isolates and develop CRKP prediction models using logistic regression (LR) and artificial neural network (ANN) methods. Methods: We retrospectively analysed the data of 49,774 patients with Klebsiella pneumoniae isolates from a regional nosocomial infection surveillance system (RNSS) between 2018 and 2021. We performed logistic regression analyses to determine the independent predictors for CRKP. We then built and evaluated LR and ANN models based on these predictors using calibration curves, ROC curves, and decision curve analysis (DCA). We also applied the Synthetic Minority Over-Sampling Technique (SMOTE) to balance the data of CRKP and non-CRKP groups. Results: The LR model showed good discrimination and calibration in both training and validation sets, with areas under the ROC curve (AUROC) of 0.824 and 0.825, respectively. The DCA indicated that the LR model had clinical usefulness for decision making. The ANN model outperformed the LR model both in the training set and validation set. The SMOTE technique improved the performance of both models for CRKP detection in training set, but not in the validation set. Conclusion: We developed and validated LR and ANN models for predicting CRKP based on RNSS data. Both models were feasible and reliable for CRKP inference and could potentially assist clinicians in selecting appropriate empirical antibiotics and reducing unnecessary medical resource utilization

Design and Embedded Implementation of Secure Image Encryption Scheme Using DWT and 2D-LASM

In order to further improve the information effectiveness of digital image transmission, an image-encryption algorithm based on 2D-Logistic-adjusted-Sine map (2D-LASM) and Discrete Wavelet Transform (DWT) is proposed. First, a dynamic key with plaintext correlation is generated using Message-Digest Algorithm 5 (MD5), and 2D-LASM chaos is generated based on the key to obtain a chaotic pseudo-random sequence. Secondly, we perform DWT on the plaintext image to map the image from the time domain to the frequency domain and decompose the low-frequency (LF) coefficient and high-frequency (HF) coefficient. Then, the chaotic sequence is used to encrypt the LF coefficient with the structure of “confusion-permutation”. We perform the permutation operation on HF coefficient, and we reconstruct the image of the processed LF coefficient and HF coefficient to obtain the frequency-domain ciphertext image. Finally, the ciphertext is dynamically diffused using the chaotic sequence to obtain the final ciphertext. Theoretical analysis and simulation experiments show that the algorithm has a large key space and can effectively resist various attacks. Compared with the spatial-domain algorithms, this algorithm has great advantages in terms of computational complexity, security performance, and encryption efficiency. At the same time, it provides better concealment of the encrypted image while ensuring the encryption efficiency compared to existing frequency-domain methods. The successful implementation on the embedded device in the optical network environment verifies the experimental feasibility of this algorithm in the new network application

Effects of hormone replacement therapy on glucose and lipid metabolism in peri- and postmenopausal women with a history of menstrual disorders

Abstract Background Previous studies have indicated that women with a history of menstrual disorders have an increased risk of metabolic and cardiovascular diseases. This has been attributed to the high proportion of polycystic ovary syndrome (PCOS) among this group. The favorable effects of hormone replacement therapy (HRT) on serum lipid profiles and glucose homeostasis in postmenopausal women is widely accepted. Whether HRT can also show positive effects on metabolic homeostasis in menopausal women with prior menstrual disorders (a putative PCOS phenotype) has not been reported yet. The aim of the study was to compare the effects of HRT on glucose and lipid metabolism in peri- and postmenopausal women with prior menstrual disorders and controls who did not have prior menstrual disorders. Methods A retrospective multicenter study was conducted including 595 peri- and postmenopausal women who received HRT at four hospitals in the Zhejiang Province from May 31, 2010 to March 8, 2021. Participants were divided into the Normal menstruation group and the Menstrual disorders group according to their prior usual menstrual cycle pattern. Glucose and lipid metabolism indicators were assessed at baseline and after HRT. The results were compared between and within the groups, and data from peri- and postmenopausal women were analyzed separately. Results HRT significantly decreased fasting insulin and homeostasis model assessment of insulin resistance in perimenopausal users, and fasting plasma glucose levels in postmenopausal users with prior menstrual disorders, compared with baseline. Furthermore, HRT decreased low-density lipoprotein cholesterol, total cholesterol, fasting insulin, fasting plasma glucose and homeostasis model assessment of insulin resistance in both peri- and postmenopausal controls, compared with baseline. Nevertheless, no significant differences were observed in any of the glucose or lipid metabolism indicators at baseline and follow-up, as well as changes from baseline levels between menopausal women with and without prior menstrual disorders. Conclusions HRT shows more obvious within-group improvements in glucose and lipid metabolism in controls, but there is no significant between-group difference. Further prospective studies are required for confirmation

MiR-452 promotes an aggressive colorectal cancer phenotype by regulating a Wnt/β-catenin positive feedback loop

Abstract Background Aberrant activation of Wnt/β-catenin signaling pathway is considered to be an important issue in progression and metastasis of various human cancers, especially in colorectal cancer (CRC). MiR-452 could activate of Wnt/β-catenin signaling. But the mechanism remains unclear. Methods The expression of miR-452 in CRC and normal tissues was detected by real-time quantitative PCR. The effect of miR-452 on CRC growth and invasion was conducted by functional experiments in vitro and in vivo. Bioinformatics and cell luciferase function studies verified the direct regulation of miR-452 on the 3’-UTR of the GSK3β, which leads to the activation of Wnt/β-catenin signaling. Results MiR-452 was upregulated in CRC compared with normal tissues and was correlated with clinical significance. The luciferase reporter system studies affirmed the direct regulation of miR-452 on the 3’-UTR of the GSK3β, which activate the Wnt/β-catenin signaling. The ectopic upregulation of miR-452 significantly inhibited the expression of GSK3β and enhanced CRC proliferation and invasion in vitro and in vivo. Meanwhile, knockdown of miR-452 significantly recovered the expression of GSK3β and attenuated Wnt/β-catenin-mediated cell metastasis and proliferation. More important, T-cell factor/lymphoid enhancer factor (TCF/LEF) family of transcription factors, which are crucial downstream molecules of the Wnt/β-catenin signaling pathway was verified as a valid transcription factor of miR-452’s promoter. Conclusions Our findings first demonstrate that miR-452-GSK3β-LEF1/TCF4 positive feedback loop induce CRC proliferation and migration