Controls of Multi-Scale Fractures in Tight Sandstones: A Case Study in the Second Member of Xujiahe Formation in Xinchang Area, Western Sichuan Depression

Different scales of fractures affect the reservoir quality in tight sandstone. There are more studies on macroscopic tectonic fractures but less on bedding fractures and microfractures. The control factors of multi-scale fractures are unclear. In this paper, we analyzed the types and controls of fractures in the second member of the Xinchang region in Western Sichuan. We use core and outcrops observations, imaging logging, scanning energy spectra, and rock slices. Natural fractures can be classified into tectonic, bedding, and microscopic types. The tectonic fractures are mainly low- to medium-angle tensile fractures. The bedding fractures are nearly horizontally distributed along the bedding surface, including parallel, dark mineral interface, and carbonaceous fragments interface bedding fractures. The microfractures develop intra-grain, edge-grain, and inter-grain types. The intra-grain microfractures are inside quartz or feldspar grains, whereas inter-grain types penetrate multiple grains with larger extension lengths. The tectonic fractures are related to the stress, grain size, mineral component, argillaceous content, and lithologic thickness. Parallel bedding fractures are controlled by the coupling of water depth and flow velocity. Bedding fractures at the interface are controlled by rock component. The microfractures are controlled by the length-width axis ratio of the grain, grain element content, and brittleness index. Fractures of different scales form a three-dimensional fracture system that has a substantial impact on the gas production

Comparison of radiation dose calculation differences between uRT-TPS and Monaco-TPS for the same linear accelerator in multiple cancers

Background and Purpose: In recent years, domestic radiotherapy equipment and related software have made great progress, and testing the functionality and stability of the equipment and software is an essential step. This paper focused on comparing the differences in intensity-modulated radiation therapy (IMRT) plans dosimetry and organ at risk (OAR) volume calculations for common cancers between uRT-treatment planning system (TPS) and Monaco-TPS, and to evaluate the feasibility of dose calculation for Infinity linac (linear accelerator, Elekta, Sweden) using uRT-TPS. Methods: Twenty cases of rectal cancer, lung cancer, breast cancer and nasopharyngeal carcinoma were selected. The IMRT plans were completed in uRT-TPS and Monaco-TPS. The dose uniformity and conformity, mean dose, maximum dose of planning target volume (PTV) and OAR between two plans under the same prescribed dose of PTV were compared. And the pass rates of two TPS plans validated at the same linear accelerator were compared. Meanwhile, monitor units (MU), source skin distance (SSD) and the volume of OAR in uRT-TPS and Monaco-TPS were compared. Results: Wonderful plans that met the clinical requirements were obtained in uRT-TPS and Monaco-TPS. Comparable uniformity and conformability was received in PTV, and the maximum dose of PTV was reduced by 1.1 Gy for uRT-TPS (P = 0.006). For breast cancer and lung cancer, the dose in lung was lower for Monaco-TPS (P<0.05). For nasopharyngeal carcinoma, the dose indicators that oral cavity and throat in the uRT-TPS was reduced by 9.2% and 5.1%, respectively. The verification results of absolute point dose (<3%) and three-dimensional surface dose (>95%) for both plans met the clinical requirements. The region of interest in uRT-TPS was smaller compared with Monaco-TPS (P<0.05). Conclusion: A comparable IMRT plan was obtained for common tumors in uRT-TPS and Monaco-TPS. It is feasible to calculate the dose of Infinity linac using uRT-TPS

On a New Hardware Trojan Attack on Power Budgeting of Many Core Systems

In this paper, we study stealthy false-data attacks that exploit the vulnerabilities of power budgeting scheme in NoC, which can cause catastrophic denial of service (DoS) effects. Essentially, when a power budget request packet is routed through a Trojan-infected network-on-chip node's router, the power budget request can be unknowingly modified. The global manager then tends to make really bad power budget allocation decisions with all the tampered power requests it received. That is, legitimate applications will be victimized with lower power budgets than what they initially asked for, and thus, could suffer serious performance degradation; malicious applications, on the other hand, may be entitled to high power budgets and thus see performance boost that they do not deserve. Our study has shown that this new type of DoS attack can be initiated and sustained by a simple hardware Trojan (HT) circuit that is extremely hard to be detected. The effects of this new DoS attack are simulated using a network model, and all the major parameters and factors that impact the attack effects are identified and quantified

Identifying the substrate proteins of U-box E3s E4B and CHIP by orthogonal ubiquitin transfer

E3 ubiquitin (UB) ligases E4B and carboxyl terminus of Hsc70-interacting protein (CHIP) use a common U-box motif to transfer UB from E1 and E2 enzymes to their substrate proteins and regulate diverse cellular processes. To profile their ubiquitination targets in the cell, we used phage display to engineer E2-E4B and E2-CHIP pairs that were free of cross-reactivity with the native UB transfer cascades. We then used the engineered E2-E3 pairs to construct “orthogonal UB transfer (OUT)” cascades so that a mutant UB (xUB) could be exclusively used by the engineered E4B or CHIP to label their substrate proteins. Purification of xUB-conjugated proteins followed by proteomics analysis enabled the identification of hundreds of potential substrates of E4B and CHIP in human embryonic kidney 293 cells. Kinase MAPK3 (mitogen-activated protein kinase 3), methyltransferase PRMT1 (protein arginine N-methyltransferase 1), and phosphatase PPP3CA (protein phosphatase 3 catalytic subunit alpha) were identified as the shared substrates of the two E3s. Phosphatase PGAM5 (phosphoglycerate mutase 5) and deubiquitinase OTUB1 (ovarian tumor domain containing ubiquitin aldehyde binding protein 1) were confirmed as E4B substrates, and b-catenin and CDK4 (cyclin-dependent kinase 4) were confirmed as CHIP substrates. On the basis of the CHIP-CDK4 circuit identified by OUT, we revealed that CHIP signals CDK4 degradation in response to endoplasmic reticulum stress

Mining bone metastasis related key genes of prostate cancer from the STING pathway based on machine learning

BackgroundProstate cancer (PCa) is the second most prevalent malignant tumor in male, and bone metastasis occurs in about 70% of patients with advanced disease. The STING pathway, an innate immune signaling mechanism, has been shown to play a key role in tumorigenesis, metastasis, and cancerous bone pain. Hence, exploring regulatory mechanism of STING in PCa bone metastasis will bring novel opportunities for treating PCa bone metastasis.MethodsFirst, key genes were screened from STING-related genes (SRGs) based on random forest algorithm and their predictive performance was evaluated. Subsequently, a comprehensive analysis of key genes was performed to explore their roles in prostate carcinogenesis, metastasis and tumor immunity. Next, cellular experiments were performed to verify the role of RELA in proliferation and migration in PCa cells, meanwhile, based on immunohistochemistry, we verified the difference of RELA expression between PCa primary foci and bone metastasis. Finally, based on the key genes to construct an accurate and reliable nomogram, and mined targeting drugs of key genes.ResultsIn this study, three key genes for bone metastasis were mined from SRGs based on the random forest algorithm. Evaluation analysis showed that the key genes had excellent prediction performance, and it also showed that the key genes played a key role in carcinogenesis, metastasis and tumor immunity in PCa by comprehensive analysis. In addition, cellular experiments and immunohistochemistry confirmed that overexpression of RELA significantly inhibited the proliferation and migration of PCa cells, and RELA was significantly low-expression in bone metastasis. Finally, the constructed nomogram showed excellent predictive performance in Receiver Operating Characteristic (ROC, AUC = 0.99) curve, calibration curve, and Decision Curve Analysis (DCA) curve; and the targeted drugs showed good molecular docking effects.ConclusionIn sum, this study not only provides a new theoretical basis for the mechanism of PCa bone metastasis, but also provides novel therapeutic targets and novel diagnostic tools for advanced PCa treatment

Wastewater Discharge Quality Prediction Using Stratified Sampling and Wavelet De-Noising ANFIS Model

The monitoring of wastewater quality is vitally important for the stability of an ecosystem. Among many machine learning techniques proposed for predicting the quality of wastewater, the adaptive neuro-fuzzy inference system (ANFIS) can achieve the best accuracy. However, due to data size limitations, the uneven distribution of randomly sampled training data can cause out-of-range prediction errors in the ANFIS model. In this study, a general-purpose input parameter selection method is proposed, combined with an optimized wavelet de-noising ANFIS model, to predict salinity parameters in wastewater discharge samples from the Las Vegas Wash, Nevada, USA. A statistical, stratified sampling strategy is used to preprocess the wastewater quality dataset. Compared with existing artificial intelligence models, the experimental results prove that the proposed model has the best performance, in which the R2 testing value achieves 0.976, 0.975, 0.988, and 0.986 in predicting chloride, sulfate, electrical conductivity, and total dissolved solids, respectively