A novel prestack sparse azimuthal AVO inversion

In this paper we demonstrate a new algorithm for sparse prestack azimuthal AVO inversion. A novel Euclidean prior model is developed to at once respect sparseness in the layered earth and smoothness in the model of reflectivity. Recognizing that methods of artificial intelligence and Bayesian computation are finding an every increasing role in augmenting the process of interpretation and analysis of geophysical data, we derive a generalized matrix-variate model of reflectivity in terms of orthogonal basis functions, subject to sparse constraints. This supports a direct application of machine learning methods, in a way that can be mapped back onto the physical principles known to govern reflection seismology. As a demonstration we present an application of these methods to the Marcellus shale. Attributes extracted using the azimuthal inversion are clustered using an unsupervised learning algorithm. Interpretation of the clusters is performed in the context of the Ruger model of azimuthal AVO

Image_1_Krebs von den lungen-6 as a clinical marker for hypersensitivity pneumonitis: A meta-analysis and bioinformatics analysis.tif

AimHypersensitivity pneumonitis (HP), also referred to as exogenous allergic alveolitis, is one of the most common interstitial lung diseases (ILDs). A potential immune biomarker, Krebs von den lgen-6 (KL-6) characterizes the progression and severity of HP. The meta-analysis in this study was conducted to elucidate the variations in the concentrations of KL-6 in different types of HP.MethodsA systematic search of various databases such as EMBASE, Pubmed, CNKI, VIP, Web of Science, and WanFang was carried out to find relevant published articles between January 1980 and August 2022 that explored the relationship between KL-6 and allergic pneumonia. Standardized mean difference (SMD) and 95% confidence interval (CI) were used as effect sizes for comparison among different groups. The GSE47460 and GSE150910 datasets were downloaded to extract and validate the differences in KL-6 mRNA expression between HP lung tissue and healthy controls. Furthermore, the single-cell sequencing dataset GSE135893 was downloaded to extract KL-6 mRNA expression in type II alveolar epithelial cells to validate the differences between HP and healthy controls. Two researchers evaluated the quality of the included studies by employing Newcastle-Ottawa Scale. All the qualified studies were subjected to statistical analyses carried out utilizing RevMan 5.2, Stata 11.0, and R software 4.1.3.ResultsTwenty studies aligned perfectly with the inclusion criteria of the meta. The concentrations of KL-6 were substantially higher in the blood of HP patients as compared to the control group. Subgroup analyses were carried out in accordance with the allergen source and the results revealed that patients with different allergens had higher blood KL-6 concentrations than healthy controls. Additionally, different subgroups of subjects were created for meta-analysis as per the fibrosis status, race, measurement method, and sample type. The concentration of KL-6 in blood was much higher in all HP subgroups than in healthy control groups. Moreover, the bioinformatics analysis revealed that KL-6 mRNA expression was higher in HP lung tissue and type II alveolar epithelial cells as compared to healthy controls.ConclusionThe present meta-analysis and bioinformatics analysis suggested that the concentration levels of KL-6 varied between HP patients and healthy individuals, and the KL-6 concentrations may be higher in the blood samples of HP patients.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, CRD42022355334.</p

The primary evaluation and characterization of obsolete DDT pesticide from a precalciner of a cement kiln

<div><p>1,1,1-Trichloro-2,2-bi(4-chlorophenyl)ethane (DDT) pesticide that has been extensively used in agriculture in China in the last century, and even now, has been banned from all purposes. The disposal of obsolete DDT pesticide has been an urgent task for the Chinese government. In order to evaluate the feasibility of co-processing DDT in the current new style dry-process rotary kiln with a precalciner as the feeding point, the destruction efficiency (DE) of DDTs (including <i>p,p</i>^′-DDT, <i>o,p</i>^′-DDT, <i>p,p</i>^′-DDE and <i>p,p</i>^′-DDD), proportion of DDTs in the combustion residue and exhaust gas, and the release of chlorine were studied under different operating conditions of temperature, oxygen content and gas retention time in the laboratory. The DE of DDTs exceeded 99% when the temperature was over 800 °C with enough oxygen. As the temperature increased from 600 °C to 1200 °C, the proportion of <i>p,p</i>^′-DDD increased and <i>p,p</i>^′-DDT decreased but still the main effective component remained in the combustion residue. In the exhaust gas, the most dominant phenomenon was the rapid increase in <i>p,p</i>^′-DDE concentration as the temperature increased. The release of chlorine reached a peak between 800 °C and 900 °C. It was found that the oxygen content had a positive correlation with the process of dechlorination. The proportion of <i>p,p</i>^′-DDE increased as the oxygen content was increased in the exhaust gas. The gas retention time had almost no influenced on the DE of DDTs, but affected the degradation extent of DDTs in the gas phase. These experiments showed that co-processing of obsolete DDT pesticide in cement kiln precalciners is feasible.</p></div

A novel stock forecasting model based on High-order-fuzzy-fluctuation Trends and Back Propagation Neural Network

<div><p>In this paper, we propose a hybrid method to forecast the stock prices called High-order-fuzzy-fluctuation-Trends-based Back Propagation(HTBP)Neural Network model. First, we compare each value of the historical training data with the previous day's value to obtain a fluctuation trend time series (FTTS). On this basis, the FTTS blur into fuzzy time series (FFTS) based on the fluctuation of the increasing, equality, decreasing amplitude and direction. Since the relationship between FFTS and future wave trends is nonlinear, the HTBP neural network algorithm is used to find the mapping rules in the form of self-learning. Finally, the results of the algorithm output are used to predict future fluctuations. The proposed model provides some innovative features:(1)It combines fuzzy set theory and neural network algorithm to avoid overfitting problems existed in traditional models. (2)BP neural network algorithm can intelligently explore the internal rules of the actual existence of sequential data, without the need to analyze the influence factors of specific rules and the path of action. (3)The hybrid modal can reasonably remove noises from the internal rules by proper fuzzy treatment. This paper takes the TAIEX data set of Taiwan stock exchange as an example, and compares and analyzes the prediction performance of the model. The experimental results show that this method can predict the stock market in a very simple way. At the same time, we use this method to predict the Shanghai stock exchange composite index, and further verify the effectiveness and universality of the method.</p></div

A Photobasic Functional Group

Controlling chemical reactivity using light is a longstanding practice within organic chemistry, yet little has been done to modulate the basicity of compounds. Reported herein is a triazabutadiene that is rendered basic upon photoisomerization. The pH of an aqueous solution containing the water-soluble triazabutadiene can be adjusted with 350 nm light. Upon synthesizing a triazabutadiene that is soluble in aprotic organic solvents, we noted a similar light-induced change in basicity. As a proof of concept we took this photobase and used it to catalyze a condensation reaction

Comparison of Polyethylene Wear before and after Hip Revision with Liner Exchange Fixed with the Original Locking Mechanism

<div><p>Objective</p><p>To compare the wear of conventional ultra-high molecular weight polyethylene (CUHMWPE) and highly cross-linked polyethylene (HCLPE) in hip revision with liner exchange fixed with original locking mechanism using analysis of history medical data.</p><p>Methods</p><p>From Jan. 1, 2000, to Dec. 31, 2007, 26 patients (with 29 involved hips) underwent liner exchange revision fixed with the original locking mechanism due to wear of CUHMWPE and/or osteolysis. The mean age was 53 ± 9 years at the time of the primary total hip arthroplasty (THA) and 64 ± 9 years at the revision. The exchanged liners (Marathon, Depuy) were made of HCLPE. Annual X-rays were used to measure linear wear and osteolysis. The annual linear penetration was measured using PolyWare® software (Draftware Inc.). Annual Harris Hip Scores(HSS) were recorded.</p><p>Results</p><p>The mean follow-up time between the primary and revision THAs was 11 ± 2 years and 8 ± 2 years after revision. The mean Harris Hip Score(HHS) before primary THA, 1 year after primary THA, before revision and 1 year after revision was 43±5, 85±5, 71±6, 83±7 individually. The mean penetration of the CUHMWPE and HCLPE liners occurring in the first year were 0.44 ± 0.28 mm and 0.38 ± 0.14 mm, respectively (p = 0.211). The mean annual linear penetration of CUHMWPE and HCLPE from the second year onward were 0.29±0.09 mm and 0.08 ± 0.03 mm respectively (p <0.01). All THAs with CUHMWPE showed osteolysis on acetabular and/or femoral side before revision. No HCLPE liner showed osteolysis at the last follow-up. Conclusion: The CUHMWPE liner had a significantly higher wear rate than did the HCLPE liner. The HCLPE liner showed a satisfactory liner penetration rate after revision with isolated liner exchange fixed with the original locking mechanism.</p></div

Penetration of CUHMWPE and HCLPE liners before and after revision.

<p>Penetration of CUHMWPE and HCLPE liners before and after revision.</p

The sorting of different prediction methods based on RMSE for forecasting the TAIEX1999.

<p>The sorting of different prediction methods based on RMSE for forecasting the TAIEX1999.</p

BP neural network structure.

<p>BP neural network structure.</p

Comparison of forecasting errors for different nth-orders.

<p>Comparison of forecasting errors for different nth-orders.</p