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The stock of shale gas in the Shahezi shale reservoir in the Changling fault depression, Songliao Basin, is believed to be worth exploring. In-depth study on the pore structure and fractal characterization of organic matter (OM) can help better understand the pore system of shale reservoir, which has implications for the exploration of lacustrine shale. To demonstrate the nanoscale pore structure and irregularity of the isolated OM, we collected a large number of samples and then conducted a series of laboratory experiments, such as X-ray diffraction, scanning electron microscopy, and [Formula: see text] and [Formula: see text] adsorption experiments to determine the pore structure parameters and reveal their heterogeneity according to Frenkel-Halsey-Hill theory. As suggested by the experimental results, the pore size distribution curve of the [Formula: see text] and [Formula: see text] exhibits similar pore peaks, whereas the trends of change in bulk shale and isolated OM samples are basically paralleled. The pore volume of the isolated OM ranges between 0.034 and [Formula: see text], which is approximately 0.90–3.06 times that of bulk shale samples. As for the fractal dimensions [Formula: see text] (2.594 on average) and [Formula: see text] (2.657 on average) of bulk shale, they are larger as compared with isolated OM, indicating that inorganic minerals can make a significant difference in the heterogeneity of shale pores. The fractal dimensions ([Formula: see text] and [Formula: see text]) of bulk shales indicate a close correlation with the parameters of pore structure, whereas there is no significant correlation observed between the dimensions of isolated OM and its parameters. In addition, thermal maturity and solid bitumen have only limited impact on the OM pore structure of isolated OM samples. Then, we conducted further research to reveal that the insoluble OM macerals derived from terrestrial higher plants can be used to explain the difference in pore structure and heterogeneity between isolated OM samples. Therefore, we arrived at the conclusion that the composition of macerals depends on the exact pore structure and fractal characteristics of isolated OM samples with similarity in thermal maturity.

To understand the characteristics of variation in porosity and permeability, the physical properties of the shale reservoir under different stress conditions play an important role in guiding shale gas production. With the shale of the Wufeng-Longmaxi Formation in the south of the Sichuan Basin as the research object, stress-dependent porosity and permeability test, high-pressure mercury injection, and scanning electron microscope test were performed in this study to thoroughly analyze the variation in physical properties of different shale lithofacies with effective stress. Besides, the stress sensitivity of different lithofacies reservoirs was evaluated by using parameters such as pore compressibility coefficient (PCC) and porosity sensitivity exponent (PSE), while the optimized support vector machine (SVM) algorithm was adopted to predict the coefficient of reservoir porosity sensitivity. According to the research results, the porosity and permeability of shale reservoirs decline as a negative exponential function. When the effective stress falls below 15 MPa, the damage rate of permeability/porosity increases rapidly with the rise of effective stress. By contrast, the permeability curvature of the shale reservoirs plunges with the rise of effective stress. It was discovered that a higher siliceous content results in a higher permeability curvature of shale, indicating the greater stress sensitivity of the reservoir. The ratio of matrix porosity to microfracture porosity determines the PSE, which is relatively low, and low aspect ratio pores contribute to high porosity compressibility and stress sensitivity. Young's modulus shows a negative correlation with pore compressibility and a positive correlation with Poisson's ratio. High clay minerals have a large number of low aspect ratio pores and a low elastic modulus, which leads to both high PCC and low PSE. Based on the principal component analysis, a multiclassification SVM model was established to predict the PSE, revealing that the accuracy of the sigmoid, radial basis function (RBF), and linear kernel function is consistently above 70%. According to error analysis, the accuracy can exceed 80% with the RBF kernel function and appropriate penalty factor. The research results serve to advance the research on the parameters related to overburden pressure, porosity, and permeability. Moreover, the optimized SVM algorithm is applied to make a classification prediction, which provides a reference for shale reservoir exploration and development both in theory and practice.

The success of shale oil exploration and production is highly dependent on the heterogeneous nature of the reservoir pore structure. Despite this, there remains limited research on the heterogeneity characteristics of pores at different scales in lacustrine shale oil reservoirs and the factors that impact them. This study aims to quantitatively characterize the multi-scale pore heterogeneity differences of the lacustrine shale found in the Funing Formation in Gaoyou Sag. Additionally, the study seeks to clarify the impact of the total organic carbon (TOC) and lithofacies type on pore structure heterogeneity. To achieve this, nitrogen adsorption, scanning electronic microscope (SEM), mercury intrusion porosimetry (MIP), and other experimental means were adopted in combination with the fractal dimension model of FHH and capillary. The results show that the predominant lithofacies of the Funing Formation shale samples are mixed shale (MS) and siliceous shale (SS), with a limited presence of calcareous shale (CS). The micro-pores of lacustrine shale are dominated by inorganic mineral pores and fewer organic pores. Intragranular pores and clay mineral pores are two types of inorganic mineral pores that are widely found. Small pores (pore diameter < 50 nm) make up 89% of the pore volume (PV) and 99% of the specific surface area (SSA). The fractal dimensions D1, D2, and D3 were calculated to characterize the roughness of the pore surface, the structural complexity of small pores, and the structural complexity of large pores (pore diameter > 50 nm), respectively. The increase in the total organic carbon (TOC) resulted in a decrease in the D1, D2, PV, and SSA, while connectivity showed a slight improvement. The fractal dimension of shale across all lithofacies followed the pattern: D3 > D2 > D1. The pore structure is more complex than the pore surface, and the large pores showed a greater heterogeneity than the small pores. Among the three lithofacies, CS had the largest PV, SSA, D1, and D2, indicating the development of a more complex pore structure network. This expands the space required for shale oil occurrence. However, the connectivity of the CS lithofacies is the lowest among the three, which hinders shale oil production. Although the PV of SS is slightly lower than that of CS, its average pore diameter (AVE PD) and connectivity are significantly advantageous, making SS an ideal shale reservoir. This study provides an important reference for the reservoir evaluation required to better develop lacustrine shale oil around the world.

Transcriptome profiling of maize inbred and hybrid seedlings subjected to heat or cold stress was used to identify key cis-regulatory elements and develop models to predict gene expression responses., Changes in gene expression are important for responses to abiotic stress. Transcriptome profiling of heat- or cold-stressed maize genotypes identifies many changes in transcript abundance. We used comparisons of expression responses in multiple genotypes to identify alleles with variable responses to heat or cold stress and to distinguish examples of cis- or trans-regulatory variation for stress-responsive expression changes. We used motifs enriched near the transcription start sites (TSSs) for thermal stress-responsive genes to develop predictive models of gene expression responses. Prediction accuracies can be improved by focusing only on motifs within unmethylated regions near the TSS and vary for genes with different dynamic responses to stress. Models trained on expression responses in a single genotype and promoter sequences provided lower performance when applied to other genotypes but this could be improved by using models trained on data from all three genotypes tested. The analysis of genes with cis-regulatory variation provides evidence for structural variants that result in presence/absence of transcription factor binding sites in creating variable responses. This study provides insights into cis-regulatory motifs for heat- and cold-responsive gene expression and defines a framework for developing models to predict expression responses across multiple genotypes.

Understanding the anisotropy-controlling factors of shale within organic matter can provide novel insight into the transport process and gas storage in typical shale. A series of techniques, such a...

Responding to the environment is a core aspect of plant growth and development. Mounting an effective response is important for plants to balance growth and survival. The HEAT SHOCK FACTOR (HSF) transcription factor family is a central and required component of plant heat stress responses and acquired thermotolerance. The HSF family has dramatically expanded in plant lineages, often including a repertoire of 20 or more genes. Here we assess the composition and heat responsiveness of the HSF family in Setaria viridis (Setaria), a model C4 panicoid grass, and make targeted comparisons between the HSF families of Setaria and maize. Examples of both conserved and variable expression responses to a heat stress event were observed when comparing the two species. Novel and existing data on chromatin accessibility, histone modifications, and genome-wide DNA binding profiles were utilized to assess the chromatin of HSF family members with distinct responses to heat stress. We observed significant variability for both expression and chromatin state within syntenic and orthologous sets of HSFs between Setaria and maize, as well as between syntenic pairs of maize HSFs retained following its most recent genome duplication event. These observations collectively support a complex scenario of expansion and sub-functionalization within this transcription factor family that has significant untapped potential for better understanding the evolution of large gene families.Significance StatementA comparison of the Heat Shock Factor transcription factors in maize and Setaria reveals examples of consistent and variable expression responses to heat stress and provides insights into the role of chromatin in predicting expression responses.

Linking natural genetic variation to trait variation can help determine the functional roles ofdifferent genes. Variations of one or several traits are often assessed separately. High-throughput phenotyping and data mining can capture dozens or hundreds of traits from the same individuals. Here, we test the association between markers within a gene and many traits simultaneously. This genome–phenome wide association study (GPWAS) is both a multi-marker and multi-trait test. Genes identified using GPWAS with 260 phenotypic traits in maize were enriched for genes independently linked to phenotypic variation. Traits associated with classical mutants were consistent with reported phenotypes for mutant alleles. Genes linked to phenomic variation in maize using GPWAS shared molecular, population genetic, and evolutionary features with classical mutants in maize. Genes linked to phenomic variation in Arabidopsis using GPWAS are significantly enriched in genes with known loss-of-function phenotypes. GPWAS may be an effective strategy to identify genes in which loss-of-function alleles produce mutant phenotypes. The shared signatures present in classical mutants and genes identified using GPWAS may be markers for genes with a role in specifying plant phenotypes generally or pleiotropy specifically.

Compared to the pencil-beam algorithm, the Monte-Carlo (MC) algorithm is more accurate for dose calculation but time-consuming in proton therapy. To solve this problem, this study uses deep learning to provide fast 3D dose prediction for prostate cancer patients treated with intensity-modulated proton therapy (IMPT).A novel recurrent U-net (RU-net) architecture was trained to predict the 3D dose distribution. Doses, CT images, and beam spot information from IMPT plans were used to train the RU-net with a five-fold cross-validation. However, predicting the complicated dose properties of the IMPT plan is difficult for neural networks. Instead of the peak-monitor unit (MU) model, this work develops the multi-MU model that adopted more comprehensive inputs and was trained with a combinational loss function. The dose difference between the prediction dose and Monte Carlo (MC) dose was evaluated with gamma analysis, dice similarity coefficient (DSC), and dose-volume histogram (DVH) metrics. The MC dropout was also added to the network to quantify the uncertainty of the model.Compared to the peak-MU model, the multi-MU model led to smaller mean absolute errors (3.03% vs. 2.05%, p = 0.005), higher gamma-passing rate (2 mm, 3%: 97.42% vs. 93.69%, p = 0.005), higher dice similarity coefficient, and smaller relative DVH metrics error (clinical target volume (CTV) DThis method was a nearly real-time IMPT dose prediction algorithm with accuracy comparable to the pencil beam (PB) analytical algorithms used in prostate cancer. This RU-net might be used in plan robustness optimization and robustness evaluation in the future.

The DOMAINS REARRANGED METHYLTRANSFERASEs (DRMs) are crucial for RNA-directed DNA methylation (RdDM) in plant species. Setaria viridis is a model monocot species with a relatively compact genome that has limited transposable element (TE) content. CRISPR-based genome editing approaches were used to create loss-of-function alleles for the two putative functional DRM genes in S. viridis to probe the role of RdDM. Double mutant (drm1ab) plants exhibit some morphological abnormalities but are fully viable. Whole-genome methylation profiling provided evidence for the widespread loss of methylation in CHH sequence contexts, particularly in regions with high CHH methylation in wild-type plants. Evidence was also found for the locus-specific loss of CG and CHG methylation, even in some regions that lack CHH methylation. Transcriptome profiling identified genes with altered expression in the drm1ab mutants. However, the majority of genes with high levels of CHH methylation directly surrounding the transcription start site or in nearby promoter regions in wild-type plants do not have altered expression in the drm1ab mutant, even when this methylation is lost, suggesting limited regulation of gene expression by RdDM. Detailed analysis of the expression of TEs identified several transposons that are transcriptionally activated in drm1ab mutants. These transposons are likely to require active RdDM for the maintenance of transcriptional repression.

The Domains Rearranged Methyltransferases (DRMs) are crucial for RNA-directed DNA methylation (RdDM) in plant species. Setaria viridis is a model monocot species with a relatively compact genome that has limited transposable element content. CRISPR-based genome editing approaches were used to create loss-of-function alleles for the two putative functional DRM genes in S. viridis to probe the role of RdDM. The analysis of drm1ab double mutant plants revealed limited morphological consequences for the loss of RdDM. Whole-genome methylation profiling provided evidence for wide-spread loss of methylation in CHH sequence contexts, particularly in regions with high CHH methylation in wild-type plants. Evidence was also found for locus-specific loss of CG and CHG methylation, even in some regions that lack CHH methylation. Transcriptome profiling identified a limited number of genes with altered expression in the drm1ab mutants. The majority of genes with elevated CHH methylation directly surrounding the transcription start site or in nearby promoter regions do not have altered expression in the drm1ab mutant even when this methylation is lost, suggesting limited regulation of gene expression by RdDM. Detailed analysis of the expression of transposable elements identified several transposons that are transcriptionally activated in drm1ab mutants. These transposons likely require active RdDM for maintenance of transcriptional repression.Significance statementMethylation profiling of Setaria viridis plants that lack functional Domains Rearranged Methyltransferase genes reveal widespread loss of DNA methylation in the CHH sequence context. Transcriptome analysis reveals a small set of genes and transposons that are silenced by RNA-directed DNA methylation.

For complex mineral compositions and ultra-fine grain embedded structure, beneficiation of iron from low-grade ore resources has been a realistic problem. In this work, an innovative technology named rapid but low-temperature direct reduction followed by magnetic separation was developed to process this kind of refractory iron ore. Ore-coal composite prepared by a typical low-grade iron ore (silica: 41.81%; iron: 31.24%) was reduced by lignite at 960 °C for 35 min, and crud iron powder assaying 83.10% of total iron can be obtained with recovery of 81.48% by subsequent magnetic separation based on laboratory tests. However, there is no precedent for an industrial reduction method to process either low-grade ore or ore-coal composites. Thus, a pilot scale rotary kiln (φ1.5 m × 15 m) reduction test was carried out for months to explore a possible approach for processing this type of iron ore. Reduced samples with a metallization ratio of 85.15% were obtained under stable operating conditions using this method. A post-mortem study was then carried out to better understand and optimize this new reduction process. The results demonstrated that the minerals evolution course during rotary kiln reduction can be summarized as follows: hematite was reduced to magnetite, wustite, and therefore partial quartz transformed to fayalite as materials were preheated within 15–11.5 m position → reduction occurred rapidly in 11.5–5.5 m zone, magnetite and wustite were reduced to iron, fayalite transformed to iron and amorphous silica → migration and growth of metallic iron particles in the length of 4.5–0 m. Rapid reduction at low temperature lessened the fayalite formation, creating favorable beneficiation conditions for iron element.

With the shortage of high-grade iron ore resources, there is an increasing demand to utilize low-grade iron ores. However, the utilization of refractory low-grade iron ore resources has always been...

To further understand fractal characteristics of nanopores in lacustrine shales, core samples from Chang-7 and Chang-9 members of the Triassic Yanchang Formation, southern Ordos Basin were investigated. Total organic carbon content, vitrinite reflectance, X-ray diffraction, field emission-scanning electron microscopy and low pressure N2 physisorption (LPNP) experiments were performed. The Frenkel-Halsey-Hill (FHH) method was applied to characterize the fractal dimensions using LPNP isotherms. Two fractal dimensions (D1 and D2) were determined at relative pressures of 0-0.45 and 0.45-1, respectively. The Chang-7 shales have a D1 and D2 range of 2.17-2.36 and 2.46-2.63, while the Chang-9 shales have D1values of 2.23-2.40 and D2 values of 2.46-2.64. Fractal dimensions of the selected lacustrine shales are affected by shale mineral compositions and pore structure parameters. Positive correlations of D1 and D2 with clay minerals and quartz contents, and negative correlations of D1 and D2 with TOC contents were presented in the present study. Observations of few organic matter pores and abundant inorganic pores hosted in the Yanchang shales may contribute to these correlations. In addition, comparisons of matrix composition, nanopore fractal characteristics between the Chang-7 shales and the Chang-9 shales suggest that the latter may have more irregular and heterogeneous pore structure.

Intact transposable elements (TEs) account for 65% of the maize genome and can impact gene function and regulation. Although TEs comprise the majority of the maize genome and affect important phenotypes, genome-wide patterns of TE polymorphisms in maize have only been studied in a handful of maize genotypes, due to the challenging nature of assessing highly repetitive sequences. We implemented a method to use short-read sequencing data from 509 diverse inbred lines to classify the presence/absence of 445,418 nonredundant TEs that were previously annotated in four genome assemblies including B73, Mo17, PH207, and W22. Different orders of TEs (i.e., LTRs, Helitrons, and TIRs) had different frequency distributions within the population. LTRs with lower LTR similarity were generally more frequent in the population than LTRs with higher LTR similarity, though high-frequency insertions with very high LTR similarity were observed. LTR similarity and frequency estimates of nested elements and the outer elements in which they insert revealed that most nesting events occurred very near the timing of the outer element insertion. TEs within genes were at higher frequency than those that were outside of genes and this is particularly true for those not inserted into introns. Many TE insertional polymorphisms observed in this population were tagged by SNP markers. However, there were also 19.9% of the TE polymorphisms that were not well tagged by SNPs (R2 < 0.5) that potentially represent information that has not been well captured in previous SNP-based marker-trait association studies. This study provides a population scale genome-wide assessment of TE variation in maize and provides valuable insight on variation in TEs in maize and factors that contribute to this variation.

Significance The same gene is often regulated differently in response to stress in even closely related plant species. Directly measuring stress-responsive gene expression can be financially and logistically challenging in nonmodel species. Here, we show that models trained using data on which genes respond to cold in one species can predict which genes will respond to cold in related species, even when the training and target species vary in their degree of tolerance to cold. The prediction models we used require only genomic sequence and gene models. As a result, data from well-studied model species may be used to predict which genes will respond to stress in less-studied species with sequenced genomes., Although genome-sequence assemblies are available for a growing number of plant species, gene-expression responses to stimuli have been cataloged for only a subset of these species. Many genes show altered transcription patterns in response to abiotic stresses. However, orthologous genes in related species often exhibit different responses to a given stress. Accordingly, data on the regulation of gene expression in one species are not reliable predictors of orthologous gene responses in a related species. Here, we trained a supervised classification model to identify genes that transcriptionally respond to cold stress. A model trained with only features calculated directly from genome assemblies exhibited only modest decreases in performance relative to models trained by using genomic, chromatin, and evolution/diversity features. Models trained with data from one species successfully predicted which genes would respond to cold stress in other related species. Cross-species predictions remained accurate when training was performed in cold-sensitive species and predictions were performed in cold-tolerant species and vice versa. Models trained with data on gene expression in multiple species provided at least equivalent performance to models trained and tested in a single species and outperformed single-species models in cross-species prediction. These results suggest that classifiers trained on stress data from well-studied species may suffice for predicting gene-expression patterns in related, less-studied species with sequenced genomes.

Changes in gene expression are important for response to abiotic stress. Transcriptome profiling performed on maize inbred and hybrid genotypes subjected to heat or cold stress identifies many transcript abundance changes in response to these environmental conditions. Motifs that are enriched near differentially expressed genes were used to develop machine learning models to predict gene expression responses to heat or cold. The best performing models utilize the sequences both upstream and downstream of the transcription start site. Prediction accuracies could be improved using models developed for specific co-expression clusters compared to using all up- or down-regulated genes or by only using motifs within unmethylated regions. Comparisons of expression responses in multiple genotypes were used to identify genes with variable response and to identifycis-ortrans-regulatory variation. Models trained on B73 data have lower performance when applied to Mo17 or W22, this could be improved by using models trained on data from all genotypes. However, the models have low accuracy for correctly predicting genes with variable responses to abiotic stress. This study provides insights intocis-regulatory motifs for heat- and cold-responsive gene expression and provides a framework for developing models to predict expression response to abiotic stress across multiple genotypes.One sentence summaryTranscriptome profiling of maize inbred and hybrid seedlings subjected to heat or cold stress was used to identify key cis-regulatory elements and develop models to predict gene expression responses.

Transposable elements (TEs) pervade most eukaryotic genomes. The repetitive nature of TEs complicates the analysis of their expression. Evaluation of the expression of both TE families (using unique and multi-mapping reads) and specific elements (using uniquely mapping reads) in leaf tissue of three maize (Zea mays) inbred lines subjected to heat or cold stress reveals no evidence for genome-wide activation of TEs; however, some specific TE families generate transcripts only in stress conditions. There is substantial variation for which TE families exhibit stress-responsive expression in the different genotypes. In order to understand the factors that drive expression of TEs, we focused on a subset of families in which we could monitor expression of individual elements. The stress-responsive activation of a TE family can often be attributed to a small number of elements in the family that contains regions lacking DNA methylation. Comparisons of the expression of TEs in different genotypes revealed both genetic and epigenetic variation. Many of the specific TEs that are activated in stress in one inbred are not present in the other inbred, explaining the lack of activation. Among the elements that are shared in both genomes but only expressed in one genotype, we found that many exhibit differences in DNA methylation such that the genotype without expression is fully methylated. This study provides insights into the regulation of expression of TEs in normal and stress conditions and highlights the role of chromatin variation between elements in a family or between genotypes for contributing to expression variation. The highly repetitive nature of many TEs complicates the analysis of their expression. Although most TEs are not expressed, some exhibits expression in certain tissues or conditions. We monitored the expression of both TE families (using unique and multi-mapping reads) and specific elements (using uniquely mapping reads) in leaf tissue of three maize (Zea mays) inbred lines subjected to heat or cold stress. While genome-wide activation of TEs did not occur, some TE families generated transcripts only in stress conditions with variation by genotype. To better understand the factors that drive expression of TEs, we focused on a subset of families in which we could monitor expression of individual elements. In most cases, stress-responsive activation of a TE family was attributed to a small number of elements in the family. The elements that contained small regions lacking DNA methylation regions showed enriched expression while fully methylated elements were rarely expressed in control or stress conditions. The cause of varied expression in the different genotypes was due to both genetic and epigenetic variation. Many specific TEs activated by stress in one inbred were not present in the other inbred. Among the elements shared in both genomes, full methylation inhibited expression in one of the genotypes. This study provides insights into the regulation of TE expression in normal and stress conditions and highlights the role of chromatin variation between elements in a family or between genotypes for contributing to expression.

Intact transposable elements (TEs) account for 65% of the maize genome and can impact gene function and regulation. Although TEs comprise the majority of the maize genome and affect important phenotypes, genome wide patterns of TE polymorphisms in maize have only been studied in a handful of maize genotypes, due to the challenging nature of assessing highly repetitive sequences. We implemented a method to use short read sequencing data from 509 diverse inbred lines to classify the presence/absence of 445,418 non-redundant TEs that were previously annotated in four genome assemblies including B73, Mo17, PH207, and W22. Different orders of TEs (i.e. LTRs, Helitrons, TIRs) had different frequency distributions within the population. LTRs with lower LTR similarity were generally more frequent in the population than LTRs with higher LTR similarity, though high frequency insertions with very high LTR similarity were observed. LTR similarity and frequency estimates of nested elements and the outer elements in which they insert revealed that most nesting events occurred very near the timing of the outer element insertion. TEs within genes were at higher frequency than those that were outside of genes and this is particularly true for those not inserted into introns. Many TE insertional polymorphisms observed in this population were tagged by SNP markers. However, there were also 19.9% of the TE polymorphisms that were not well tagged by SNPs (R2 < 0.5) that potentially represent information that has not been well captured in previous SNP based marker-trait association studies. This study provides a population scale genome-wide assessment of TE variation in maize, and provides valuable insight on variation in TEs in maize and factors that contribute to this variation.

SummaryTransposable elements (TEs) pervade most eukaryotic genomes but the repetitive nature of TEs has complicated the analysis of their expression. Although the majority of TEs are silent, we document the activation of some TEs during abiotic stress.TE expression was monitored in seedling leaf tissue of maize inbreds subjected to heat or cold stress conditions. DNA methylation profiles and comparative genomics were used to probe the variability of TE expression responses.Although there was no evidence for a genome-wide activation of TEs, a subset of TE families generate transcripts only in stress conditions. There is substantial variation for which TE families exhibit stress-responsive expression in the three genotypes. The stress-responsive activation of a TE family can often be attributed to a small number of elements in the family. These elements that are activated often contain small regions lacking DNA methylation, while fully methylated elements are rarely expressed. A comparison of the expression of specific TEs in different maize genotypes reveals high levels of variability that can be attributed to both genome content differences and epigenetic variation.This study provides insights into the genetic and epigenetic factors that influence TE regulation in normal and stress conditions.

The increasing enthusiasm for continental shale gas exploration in China has made the Shahezi shale in the Changling Fault Depression an important research target due to its impressive demonstrated gas capacity. In this work, geochemical and petrologic analyses, field emission-scanning electron microscopy (FE-SEM) observation, low-pressure adsorption isotherms and mercury intrusion porosimetry (MIP) were conducted on 19 core samples to comprehensively analyze the reservoir characteristics of different lithofacies. The results show that the Shahezi shale has the characteristics of low content of organic matter (OM), high Ro, high content of clay minerals and small fractions of calcite. The kerogen is type III, dominated by vitrinite and inertinite. Clay minerals are dominated by the mixed illite-smectite, followed by illite and a small amount of chlorite. The Shahezi shale develops three kind of stratification structures according to the thickness of laminae: laminated structures, bedded structures, and massive structures. On the basis of TOC, mineral composition and petrologic texture, eight types of lithofacies were recognized. The organic pores show strong heterogeneity and are poorly developed, while clay-related pores are ubiquitous. The Shahezi shale has a high pore volume (PV) (0.005–0.031 ml/g, averaging 0.0173 ml/g) and specific surface area (SSA) (2.57–27.48 m2/g, averaging 16.61 m2/g), indicating an excellent storage capacity. Low-pressure CO2 and N2 isotherms and MIP were utilized to construct the whole-range pore size distribution (PSD). Based on the whole-range PSDs, mesopores were observed to contribute most to the PV, followed by macropores. Micropores and mesopores account for more than 99% of SSA. The reservoir capacity of different lithofacies is following the order in terms of PV and SSA, from high to low: organic-medium massive mixed shale (OMMMS), organic-medium massive argillaceous shale (OMMAS), organic-rich laminated argillaceous shale (ORLAS), organic-medium laminated argillaceous shale (OMLAS), organic-rich bedded mixed shale (ORBMS), organic-rich bedded siliceous shale (ORBSS), organic-medium bedded argillaceous shale (OMBAS), organic-poor shale (OPS). The main controlling factors of pore structure for the Shahezi shale are clay minerals rather than OM, which is similar to the continental Chang 7th shale but contrary to the Longmaxi shale. However, the Shahezi shale is mainly of low TOC and strong heterogeneity pores development result from OM macerals, while the Chang 7th shale is mainly of low maturity. Ro play an important role in promoting pore development. Only high content of calcite can greatly improve the pore space due to its solubility. This work contributes to the theory of continental shales and how to identify continental high-quality shale reservoirs.

A proton therapy facility based on an isochronous superconducting cyclotron is under construction in Huazhong University of Science and Technology (HUST). To meet the clinical requirements, an energy degrader is essential in the beamline to modulate the fixed beam energy extracted from the cyclotron. Because of the multiple Coulomb scattering in the degrader, the beam emittance and the energy spread will be considerably increased during the energy degradation process. Therefore, a set of collimators is designed to restrict the increase in beam emittance after the energy degradation. The energy spread will be reduced in the following beam line which is not discussed in this paper. In this paper, the design considerations of an energy degrader and collimators are introduced, and the properties of the degrader material, degrader structure and the initial beam parameters are discussed using the Geant4 Monte-Carlo toolkit, with the main purpose of improving the overall performance of the degrader by multiple parameter optimization.