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Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.

Utilizing well logging data, outcrop profiles, and previous research, this study analyzes the sedimentary and tectonic evolution of the Yan'an Formation in the Ordos Basin, correlating the resulting sedimentary facies with hydrocarbon reservoirs to establish the necessary connections. The study reveals that: (1) Vertically, the sediment grain size shows a pattern of coarser grains at the bottom and top, with finer grains in the middle. Horizontally, the grain size tends to become finer from the northern, western, and southern parts of the basin toward the central-western region. (2) Tectonic movements during the Yan'an period controlled the sedimentary environment. These tectonic activities, through uplift and subsidence, caused the Yan'an Formation to experience four stages of sedimentary environments: braided river, lake, delta, and meandering river. (3) The Yan'an Formation exhibits four types of reservoir sandbody stacking patterns—continuous superposition, intermittent superposition, interbedded sand-mud, and single sandbody types—with continuous and intermittent stacking being the most common. (4) The hydrocarbons in the Yan'an Formation originated from the Chang 7 Member of the Yanchang Formation and migrated into the Yan'an reservoirs. The oil is characterized by its low density, low viscosity, and low pour point, indicating it is a high-maturity, high-quality crude oil. [ABSTRACT FROM AUTHOR]

The pore-throat structure is a critical factor in the study of unconventional oil and gas reservoirs, drawing particular attention from petroleum geologists, and it is of paramount significance to analyze to enhance oil and gas production. In tight sandstone, which serves as a significant hydrocarbon reservoir, the internal pore-throat structure plays a decisive role in the storage and migration of fluids such as water, gases, and hydrocarbons. This paper employs casting thin section (CTS), field emission scanning electron microscope (FE-SEM), high-pressure mercury injection (HPMI), and low-temperature nitrogen gas adsorption (LT−N2−GA) experimental tests to qualitatively and quantitatively analyze the characteristics of the pore-throat structure in tight sandstone. The results indicate that the pore types in tight sandstone include intergranular residual pores, dissolution pores, intercrystalline pores, and microfractures, while the throat types encompass sheet-shaped, curved-sheet-shaped, and tubular throats. Analysis of the physical and structural parameters from 13 HPMI and 5 LT−N2−GA samples reveals a bimodal distribution of pore-throat radii. The complexity of the pore-throat structure is identified as a primary controlling factor for reservoir permeability. The fractal dimension (D) exhibits an average value of 2.45, displaying a negative correlation with porosity (R2 = 0.22), permeability (R2 = 0.65), the pore-throat diameter (R2 = 0.58), and maximum mercury saturation (R2 = 0.86) and a positive correlation with threshold pressure (R2 = 0.56), median saturation pressure (R2 = 0.49), BET specific surface area (R2 = 0.51), and BJH total pore volume (R2 = 0.14). As D increases, reservoir pores tend to decrease in size, leading to reduced flow and deteriorated physical properties, indicative of a more complex pore-throat structure. [ABSTRACT FROM AUTHOR]

Predicting the structure of a protein from its amino acid sequence is a long-standing unsolved problem in computational biology. Its solution would be of both fundamental and practical importance as the gap between the number of known sequences and the number of experimentally solved structures widens rapidly. Currently, the most successful approaches are based on fragment/template reassembly. Lacking progress in template-free structure prediction calls for novel ideas and approaches. This article reviews trends in the development of physical and specific knowledge-based energy functions as well as sampling techniques for fragment-free structure prediction. Recent physical- and knowledge-based studies demonstrated that it is possible to sample and predict highly accurate protein structures without borrowing native fragments from known protein structures. These emerging approaches with fully flexible sampling have the potential to move the field forward.