Prediction of World Crude Oil Price with the Method of Missing Data

As the fluctuation of oil price plays an important role in global political and economic situation, forecasting the price of oil is significant. In this paper, we analyze the data of the world crude oil price using ideas of treating with the missing data, i.e. we take the predictor as missing data and use the EM algorithm to establish time series model. We give the predictive values of weekly world crude oil price of January and February in 2011 using the data of 2009 and 2010. Meanwhile, we found that the method based on missing data is more effective than normal time series method by comparing the predictive value with reality data. In addition, this method is also applicable to the case that historical observations have missing data. Key words: World Crude Oil Price; Forecast; Missing Data; EM Algorithm; Time Serie

Xin-Li-Fang efficacy and safety for patients with chronic heart failure: A study protocol for a randomized, double-blind, and placebo-controlled trial

IntroductionXin-Li-Fang (XLF), a representative Chinese patent medicine, was derived from years of clinical experience by academician Chen Keji, and is widely used to treat chronic heart failure (CHF). However, there remains a lack of high-quality evidence to support clinical decision-making. Therefore, we designed a randomized controlled trial (RCT) to evaluate the efficacy and safety of XLF for CHF.Methods and designThis multicenter, double-blinded RCT will be conducted in China. 300 eligible participants will be randomly assigned to either an XLF group or a control group at a 1:1 ratio. Participants in the XLF group will receive XLF granules plus routine care, while those in the control group will receive placebo granules plus routine care. The study period is 26 weeks, including a 2-week run-in period, a 12-week treatment period, and a 12-week follow-up. The primary outcome is the proportion of patients whose serum NT-proBNP decreased by more than 30%. The secondary outcomes include quality of life, the NYHA classification evaluation, 6-min walking test, TCM symptom evaluations, echocardiography parameters, and clinical events (including hospitalization for worsening heart failure, all-cause death, and other major cardiovascular events).DiscussionThe results of the study are expected to provide evidence of high methodological and reporting quality on the efficacy and safety of XLF for CHF.Clinical trial registrationChinese Clinical Trial Registration Center (www.chictr.org.cn). The trial was registered on 13 April 2022 (ChiCTR2200058649)

Autophagy-related IFNG is a prognostic and immunochemotherapeutic biomarker of COAD patients

BackgroundNumerous studies have shown autophagy affects cellular immune responses. This study aims to explore prognosis and immunotherapeutic biomarkers related to autophagy in colon adenocarcinoma (COAD).MethodsBased on R software, we performed the ssGSEA, differential expression analysis, Kaplan-Meier survival analysis, correlation analysis, and enrichment analysis. For wet experiment, we did qRT-PCR, immunohistochemistry and CCK-8 experiments.ResultsUsing autophagy-related genes (ARGs) and the ssGSEA, COAD patients were divided into low and high autophagy groups. For immune score, stromal score, tumor purity, tumor infiltrating immune cells, co-signaling molecules, tumor mutational burden, microsatellite instability, mismatch repair, immune-related pathways, immune signatures, somatic mutations and subtype analysis, high autophagy group might benefit more from immunotherapy. Among 232 ARGs, IFNG was generally significantly correlated with tumor immunotherapy biomarkers (PD-L1, CD8A and cytotoxic T lymphocytes (CTL)). The disease-free survival of high IFNG group was significantly longer than that of low group. On above-mentioned immune-related research, the high IFNG group reached the same conclusion. The qRT-PCR and IHC analysis confirmed that IFNG was significantly higher expressed in dMMR samples compared to pMMR samples. For chemotherapy, the autophagy and IFNG were significantly negatively related to the chemosensitivity to cisplatin; IFNG inhibitor glucosamine increased cisplatin chemoresistance while IFNG increased cisplatin chemosensitivity; IFNG could reverse glucosamine induced chemoresistance. The functional enrichment analysis of IFNG, PD-L1, CD8A and 20 similar proteins were related to the activation of the immune system. The GSEA and ceRNA network partly described interaction mechanisms of IFNG with PD-L1 and CD8A.ConclusionAutophagy score and IFNG expression were novel immunotherapy predictive biomarkers, which might play predictive effects through the JAK-STAT signaling pathway. IFNG might be a potential targeted therapy for cisplatin resistant colon cancer. Besides, IFNG was also a prognostic indicator

Global analysis of the rat and human platelet proteome - the molecular blueprint for illustrating multi-functional platelets and cross-species function evolution

Emerging evidences indicate that blood platelets function in multiple biological processes including immune response, bone metastasis and liver regeneration in addition to their known roles in hemostasis and thrombosis. Global elucidation of platelet proteome will provide the molecular base of these platelet functions. Here, we set up a high throughput platform for maximum exploration of the rat/human platelet proteome using integrated proteomics technologies, and then applied to identify the largest number of the proteins expressed in both rat and human platelets. After stringent statistical filtration, a total of 837 unique proteins matched with at least two unique peptides were precisely identified, making it the first comprehensive protein database so far for rat platelets. Meanwhile, quantitative analyses of the thrombin-stimulated platelets offered great insights into the biological functions of platelet proteins and therefore confirmed our global profiling data. A comparative proteomic analysis between rat and human platelets was also conducted, which revealed not only a significant similarity, but also an across-species evolutionary link that the orthologous proteins representing ‘core proteome’, and the ‘evolutionary proteome’ is actually a relatively static proteome

A Fast Implicit Finite Difference Method for Fractional Advection-Dispersion Equations with Fractional Derivative Boundary Conditions

Fractional advection-dispersion equations, as generalizations of classical integer-order advection-dispersion equations, are used to model the transport of passive tracers carried by fluid flow in a porous medium. In this paper, we develop an implicit finite difference method for fractional advection-dispersion equations with fractional derivative boundary conditions. First-order consistency, solvability, unconditional stability, and first-order convergence of the method are proven. Then, we present a fast iterative method for the implicit finite difference scheme, which only requires storage of O(K) and computational cost of O(Klog⁡K). Traditionally, the Gaussian elimination method requires storage of O(K2) and computational cost of O(K3). Finally, the accuracy and efficiency of the method are checked with a numerical example

Modeling SARS coronavirus-2 omicron variant dynamic via novel fractional derivatives with immunization and memory trace effects

The objective of this paper is to recommend an adjusted Susceptible-Exposed-Infectious-Removed (SEIR) model that characterizes the temporal patterns of various individuals affected by the omicron variant in an epidemic. This model considers factors such as vaccination, asymptomatic cases, indoor and outdoor air, hospitalizations, and deaths, as well as the impact of immunization and memory trace. While many recent studies overlook the complexities of multiple strains, including their diverse transmission rates and reaction to vaccines, this study introduces a new fractional derivative model to examine the spread of the omicron variant of COVID-19 and the implementation of a vaccination campaign. A thorough theoretical analysis is conducted, and the critical factor (Rcrnz) is calculated using the model equations. It is demonstrated that when Rcrnz is less than 1, the disease-free state is globally asymptotically stable, meaning that the epidemic diminishes. Moreover, the stability of both global and local equilibrium points is examined. Numerical simulations are employed to demonstrate the alignment between the numerical findings and theoretical characteristics. The model is adjusted to experimental data that reflect the progression of the omicron variant of COVID-19 in Guangzhou, exhibiting a satisfactory performance in predicting the number of infected individuals, thereby suggesting its capability to accurately estimate asymptomatic cases. Furthermore, to emphasize the benefits of employing fractional differential equations, the paper provides examples related to memory trace and hereditary characteristics. Moreover, the examined models are expected to be applied and expanded upon in order to contribute to the formulation of policies for disease control during times of limited vaccine availability. To summarize, the model appears to be a sufficient tool for researching and managing infectious diseases. It is projected that as the Omicron variant's prevalence declines, there will be a reduced need for respiratory-focused precautions

Type 2 diabetes and inflammatory bowel disease: a bidirectional two-sample Mendelian randomization study

Abstract To investigate the association between T2DM and IBD by bidirectional two-sample Mendelian randomization (MR) to clarify the casual relationship. Independent genetic variants for T2DM and IBD were selected as instruments from published genome-wide association studies (GWAS), mainly in European ancestry. Instrumental variables (IVs) associated with T2DM and IBD were extracted separately from the largest GWAS meta-analysis. MR analyses included inverse variance weighting, weighted median estimator, MR Egger regression, and sensitivity analyses with Steiger filtering and MR PRESSO. In the data samples for Ulcerative colitis (UC) (6968 cases, 20,464 controls) and Crohn's disease (CD) (5956 cases, 14,927 controls), there was a negative causal relationship between T2DM and UC [IVW, OR/95%CI: 0.882/(0.826,0.942), p  0.05). The results of the bidirectional MR Study suggest that T2DM has a negative causal effect on UC, which provides implications for clinical treatment decisions in IBD patients with T2DM. The findings do not support a causal relationship between T2DM and CD, UC and T2DM, or CD and T2DM, and the impact of IBD on T2DM needs further investigation

A Second-Order Accurate Numerical Approximation for a Two-Sided Space-Fractional Diffusion Equation

In this paper, we investigate a practical numerical method for solving a one-dimensional two-sided space-fractional diffusion equation with variable coefficients in a finite domain, which is based on the classical Crank-Nicolson (CN) method combined with Richardson extrapolation. Second-order exact numerical estimates in time and space are obtained. The unconditional stability and convergence of the method are tested. Two numerical examples are also presented and compared with the exact solution

Neural network method for lossless two-conductor transmission line equations based on the IELM algorithm

With the increasing demands for vast amounts of data and high-speed signal transmission, the use of multi-conductor transmission lines is becoming more common. The impact of transmission lines on signal transmission is thus a key issue affecting the performance of high-speed digital systems. To solve the problem of lossless two-conductor transmission line equations (LTTLEs), a neural network model and algorithm are explored in this paper. By selecting the product of two triangular basis functions as the activation function of hidden layer neurons, we can guarantee the separation of time, space, and phase orthogonality. By adding the initial condition to the neural network, an improved extreme learning machine (IELM) algorithm for solving the network weight is obtained. This is different to the traditional method for converting the initial condition into the iterative constraint condition. Calculation software for solving the LTTLEs based on the IELM algorithm is developed. Numerical experiments show that the results are consistent with those of the traditional method. The proposed neural network algorithm can find the terminal voltage of the transmission line and also the voltage of any observation point. It is possible to calculate the value at any given point by using the neural network model to solve the transmission line equation

Gradation Design of Phosphorus Tailing–Graded Waste Rock Subgrade Filling Using Discrete Element Method

The method of using silt phosphorus tailing instead of traditional sand and filler as subgrade filling has been suggested to greatly improve the comprehensive utilization of solid waste phosphorus tailing. A suitable combination of phosphorus tailing and graded waste rock can be adopted to improve the stability of the structure of filling, which can then improve the soil properties of phosphorus tailing and prevent the formation of quicksand and landslides. In this research, a discrete element model was established by combining a graded mixing method and the concept of equivalent particle size, and the discontinuous gradation design of a phosphorus tailing–graded waste rock mixture was carried out. Using the filling coefficient, different structural types of mixture composition were verified, and the California Bearing Ratio was used to test and analyze the specimens with different mixtures, grading, and structural type. The results show that the porosity of the main skeleton calculated with the model established using the discrete element software Particle Flow Code and the porosity obtained with the tamping test fit well, with the minimum porosity of the optimal main skeleton coarse aggregate being 30.44%. At the same time, by analyzing the effect of filling the porosity of graded waste rock with different mass fractions of phosphorus tailing and by determining the California Bearing Ratio of the corresponding filling structure, it was shown that the skeleton-dense structure with the best gradation of the mixture displayed better road performance and that the phosphorus tailing–graded waste rock system with improved performance can be used as subgrade filling or in the preparation of pavement base material