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In the Ordos Basin, the Chang 8 oil reservoir of the Triassic Yanchang Formation is the main target of oil exploration and development and there are many factors affecting the hydrocarbon accumulation. Well G20 is an important exploration well in the Yanchi area in the northwestern part of the basin, and the core of the Chang 8 reservoir was sampled and tested to determine the source rocks, trace element composition, mineral composition, reservoir physical properties, and oil-bearing properties. The results show that the rock retrieved exhibits delta plain subfacies; the range of the Chang 8 water body was large, with a gentle slope, and the climate was relatively dry. These findings suggest that this reservoir was deposited in an environment in which sedimentary sand body could easily form. The Chang 8 sandstone reservoir pores are dominated by intergranular pores and feldspar intragranular dissolution pores, indicating that the Chang 8 reservoir is a low-porosity and low-permeability reservoir. Chang 7 source rocks from this area have a type I-II1 hydrocarbon-generating potential, with an average total organic carbon (TOC) content of 5.99% and vitrinite reflectance (Ro) value of 0.48%. Combined with the regional sedimentary evolution, tectonic movement, and reservoir distribution, it is considered that due to the lack of lithologic traps or low-amplitude structural traps, G20 produced water in well testing. The Chang 8 oil reservoir in the Yanchi area can be divided into structural reservoirs and structural-lithologic reservoirs. The conventional oil and gas reservoir exploration ideas of “thick sand belt” and “reservoir sweet spot” are not applicable here. The lithology traps or low-amplitude structural traps and areas with good preservation conditions are the main directions for the next phase of exploration in the northwestern part of the Ordos Basin.

With the widespread use of medical images in telemedicine, personal information may be leaked. The traditional zero-watermarking technology has poor robustness under large-scale attacks. At the same time, most of the zero-watermarking information generated is a binary sequence with a single information structure. In order to effectively solve the poor robustness problem of traditional zero-watermarking under large-scale attacks, a color zero-watermarking algorithm for medical images based on bidimensional empirical mode decomposition (BEMD)-Schur decomposition and color visual cryptography is proposed. Firstly, the color carrier image and the color copyright logo are decomposed into R, G, and B three color components, respectively, and the feature value of each sub-block are extracted by wavelet transform, BEMD decomposition, block operation, and Schur decomposition. Then, the R, G, and B components of the copyright logo are scrambled by Arnold scramble and converted into binary watermark information. Finally, a color visual cryptography scheme is proposed to generate two color shared images based on the carrier characteristics and copyright information. One shared image is used to generate a color zero-watermark, and the other is used for copyright authentication phase. Experimental results show that this algorithm has strong robustness and stability in resisting large-scale noise attacks, filtering attacks, JPEG compression, cropping attacks, and translation attacks at different positions. Compared with similar zero-watermarking algorithms, the robust performance is improved by about 10%, and it can adapt to more complex network environments.

High body mass index (BMI) has been inconsistently associated with overall survival (OS) of digestive system cancers (DSCs). This meta-analysis was conducted to investigate whether high BMI was associated with DSCs prognosis. 34 studies were accepted, with a total of 23,946 DSC cases. Hazard ratios (HRs) with 95% confidence intervals (95% CIs) for OS in BMI categories from individual studies were extracted and pooled by random-effect model. The overall HR of DSCs except pancreatic cancer for OS of adult overweight cases was 0.76 (95% CI = 0.67–0.85). DSC individuals except pancreatic cancer with adult obesity were at decreased risk for OS (HR = 0.85, 95% CI = 0.72–0.98). Among DSC patients except pancreatic cancer, the overall HR for the highest versus the lowest BMI category was 0.82 (95% CI = 0.71–0.92). Additionally, comparing the highest and lowest BMI categories, the combined HR of pancreatic cancer was 1.22 (95% CI = 1.01–1.43). Our meta-analysis suggested an increased OS among adult overweight and obese DSC survivors except pancreatic cancer. Overweight and obesity in adulthood may be important prognostic factors that indicate an increased survival from DSC patients except pancreatic cancer.

Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease with complicated genetic inheritance. Programmed death 1 (PD-1), a negative T cell regulator to maintain peripheral tolerance, induces negative signals to T cells during interaction with its ligands and is therefore a candidate gene in the development of SLE. In order to examine whether expression levels of PD-1 contribute to the pathogenesis of SLE, 30 patients with SLE and 30 controls were recruited and their PD-1 expression levels in peripheral blood mononuclear cells (PBMCs) were measured via flow cytometry and quantitative real-time-reverse transcription polymerase chain reaction (RT-PCR). Also, whether PD-1 expression levels are associated with the variant of the SNP rs36084323 and the SLE Disease Activity Index (SLEDAI) was studied in this work. The PD-1 expression levels of SLE patients were significantly increased compared with those of the healthy controls. The upregulated PD-1 expression levels in SLE patients were greatly associated with SLEDAI scores. No significant difference was found between PD-1 expression levels and SNP rs36084323. The results suggest that increased expression of PD-1 may correlate with the pathogenesis of SLE, upregulated PD-1 expression may be a biomarker for SLE diagnosis, and PD-1 inhibitor may be useful to SLE treatment.

This paper studies a production scheduling problem with deteriorating jobs, which frequently arises in contemporary manufacturing environments. The objective is to find an optimal sequence of the set of jobs to minimize the total weighted tardiness, which is an indicator of service quality. The problem belongs to the class of NP-hard. When the number of jobs increases, the computational time required by an optimization algorithm to solve the problem will increase exponentially. To tackle large-scale problems efficiently, a two-stage method is presented in this paper. We partition the set of jobs into a few subsets by applying a neural network approach and thereby transform the large-scale problem into a series of small-scale problems. Then, we employ an improved metaheuristic algorithm (called GTS) which combines genetic algorithm with tabu search to find the solution for each subproblem. Finally, we integrate the obtained sequences for each subset of jobs and produce the final complete solution by enumeration. A fair comparison has been made between the two-stage method and the GTS without decomposition, and the experimental results show that the solution quality of the two-stage method is much better than that of GTS for large-scale problems.