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The travel time of rock compressional waves is an essential parameter used for estimating important rock properties, such as porosity, permeability, and lithology. Current methods, like wireline logging tests, provide broad measurements but lack finer resolution. Laboratory-based rock core measurements offer higher resolution but are resource-intensive. Conventionally, wireline logging and rock core measurements have been used independently. This study introduces a novel approach that integrates both data sources. The method leverages the detailed features from limited core data to enhance the resolution of wireline logging data. By combining machine learning with random field theory, the method allows for probabilistic predictions in regions with sparse data sampling. In this framework, 12 parameters from wireline tests are used to predict trends in rock core data. The residuals are modeled using random field theory. The outcomes are high-resolution predictions that combine both the predicted trend and the probabilistic realizations of the residual. By utilizing unconditional and conditional random field theories, this method enables unconditional and conditional simulations of the underlying high-resolution rock compressional wave travel time profile and provides uncertainty estimates. This integrated approach optimizes the use of existing core and logging data. Its applicability is confirmed in an oil project in West China.

Rice–turtle co-culture is an ecological method involving a low exogenous input of chemicals and excessive feeding might increase the cost and reduce the mutual beneficial effect. To determine the optimal feeding level for co-cultured P. sinensisand for its adaptation, the turtles (878.0±10.3 g) were fed at feeding levels of 0.7 %, 1.4 % and 2.1 % for 90 days. The observation of feeding behavior showed that a low feeding level prompted the turtles to move into field paddies and prolonged their stay. The specific growth rate increased with increasing feeding level, but did not further increase when it exceeded 1.4 %, and the feed conversion ratio increased with increasing feeding level from 0.7 % to 2.1 %. The activities of digestive enzymes were higher in the group with a low feeding level. The plasma triglyceride and total cholesterol levels increased with increasing feeding level, while the creatinine level was significantly lower at a high feeding level of 2.1 %. The trend analysis of gene expression showed that the expression of most of differentially expressed genes (DEGs) in the brain decreased with increasing feeding levels from 0.7 % to 1.4 % and did not further decrease at a feeding level of 2.1 %, while in the gut, most of the genes were significantly downregulated or upregulated at a feeding level of 1.4 %. In the brain, the pathways associated with the DEGs were involved in the relaxin signaling pathway, melanogenesis and the age–rage signaling pathway in diabetic complications. In the gut, the DEGs were most associated with pancreatic secretion, protein digestion and absorption. The related genes expression was consistent with feeding behavior, growth and physiological metabolism. These findings suggest that co-cultured turtles can adapt to different feeding levels, that the optimal feeding level for co-cultured turtles is 1.4 %, and that additional feeding reduced the economic and ecological benefits of co-culture.

Long horizontal sections, small well spacings, and dense cutting are the main methods for shale reservoir development. However, there are still significant differences in oil production after large-scale fracturing of horizontal wells due to reservoir heterogeneity. This study presents a fracturing design method based on sweet spot mapping to determine the adaptability of reservoir quality and fracturing scale in order to improve the fracturing effect. First, geomechanics model is constructed utilizing logs and core laboratory tests. Then, comprehensive sweet spot mapping is captured through the two-level fuzzy comprehensive evaluation method, which considered the reservoir physical quality and engineering quality. The sweet spot divides the reservoir into three types: type I (good), type II (moderate), and type III (poor). Finally, fracturing simulation and reservoir numerical simulation are performed to optimize the fracturing parameters for different types of sweet spots. Results show that there is a strong correlation between type I sweet spot and productivity. Increasing drilling rate for type I sweet spot can improve productivity. The 5-year cumulative oil production of segmented way based on sweet spot types is 4005 m3higher than that of uniform segmented way. Reasonable stage lengths of type I, II, and III sweet spot are 66.67 m, 50 m and 40 m, respectively, and cluster spacing is between 10 m and 12 m. Reasonable single-stage fracturing fluid volume for type I and type II sweet spot is 2200 m3, and type III is 1900 m3. Specifically, the results of applying the optimized parameters to actual well demonstrate that the design scheme has a 5-year cumulative oil production of 7026 m3and NPV of $1.01 million higher than the actual scheme. This method will be helpful for engineers in developing a reasonable fracturing plan for shale oil in future operations.

A fiber optic humidity sensor based on polyvinyl alcohol (PVA)/Tween 20 film has been fabricated by modulating the intensity of light transmitted in optical fiber. PVA/Tween 20 film was used as the cladding and humidity-sensitive material of optical fiber. The logarithmic of output light intensity exhibited a linear increase with the increase of humidity (22%–82%RH). With the addition of Tween 20 in the formation of film, average sensitivity increased by 13-fold. Fast equilibrium on adsorption and desorption of water molecules were also achieved on the film. The response and recovery times were determined to be 11 s and 9 s, respectively. Moreover, the sensor possesses good repeatability. The sensing mechanism was probably based on the swelling of PVA after adsorbing water molecules, which affected scattering of evanescent waves in the cladding. The output light intensity varied with the decay of evanescent waves.

A SiO_2/TiO_2 bilayer thin-film-based fiber optic humidity sensor was fabricated via a modified dip coating process with enhanced sensitivity. SiO_2 film was coated on the surface of the fiber core, followed by deposition of the TiO_2 layer on SiO_2. The relative humidity (RH) is measured by modulation in intensity of the transmitted laser at room temperature. The optical fiber humidity sensor based on SiO_2/TiO_2 film shows two-segmented linearity in measurement with sensitivities of 5.35 and 1.94 µW/% RH at 15%–50% RH and 50%–95% RH, respectively. The response time and recovery time are 25 s and 50 s, respectively. To our knowledge, the superior response time and recovery time of the sensor in our study were achieved over those fiber optic humidity sensors reported with modulation in intensity. Furthermore, this fiber optic humidity sensor has a good reproducibility and long-term stability. The sensing mechanism is attributed to effects of moisture on the refractive index and the light absorption coefficient of SiO_2 film and modulation in the transmission characteristic of evanescent waves in the optical fiber.

Cysteine is unique among all protein-coding amino acids, owing to its intrinsically high nucleophilicity. The cysteinyl thiol group can be covalently modified by a broad range of redox mechanisms or by various electrophiles derived from exogenous or endogenous sources. Measuring the response of protein cysteines to redox perturbation or electrophiles is critical for understanding the underlying mechanisms involved. Activity-based protein profiling based on thiol-reactive probes has been the method of choice for such analyses. We therefore adapted this approach and developed a new chemoproteomic platform, termed ‘QTRP’ (quantitative thiol reactivity profiling), that relies on the ability of a commercially available thiol-reactive probe IPM (2-iodo-N-(prop-2-yn-1-yl)acetamide) to covalently label, enrich and quantify the reactive cysteinome in cells and tissues. Here, we provide a detailed and updated workflow of QTRP that includes procedures for (i) labeling of the reactive cysteinome from cell or tissue samples (e.g., control versus treatment) with IPM, (ii) processing the protein samples into tryptic peptides and tagging the probe-modified peptides with isotopically labeled azido-biotin reagents containing a photo-cleavable linker via click chemistry reaction, (iii) capturing biotin-conjugated peptides with streptavidin beads, (iv) identifying and quantifying the photo-released peptides by mass spectrometry (MS)-based shotgun proteomics and (v) interpreting MS data by a streamlined informatic pipeline using a proteomics software, pFind 3, and an automatic post-processing algorithm. We also exemplified here how to use QTRP for mining H2O2-sensitive cysteines and for determining the intrinsic reactivity of cysteines in a complex proteome. We anticipate that this protocol should find broad applications in redox biology, chemical biology and the pharmaceutical industry. The protocol for sample preparation takes 3 d, whereas MS measurements and data analyses require 75 min and <30 min, respectively, per sample.

The exploration of sweet spots in the Jimsar shale oil reservoir in Xinjiang involves creating a complex fracture network through three-dimensional well networks and advanced fracturing technology, crucial for successful shale oil reservoir development. However, the extremely low permeability of shale oil and limited natural flow capacity of crude oil pose significant challenges. The interconnection between three-dimensional well networks and artificial fracture networks, and the relationship between fracturing parameters and fracture morphology, remain unclear. This study focuses on the P2l12-2and P2l12-3layers of the Lucaogou Formation. Utilizing the Petrel geological engineering integrated platform and the Kinetix fracturing module, we conducted numerical simulations to explore coupled fracturing in different sweet spots, with a specific emphasis on well network and fracture network coupling. The study identified relevant optimized engineering parameters. Research findings indicate that, during single-well single-factor optimization, the viscosity optimization range for Class II reservoirs is smaller compared to Class I reservoirs. However, for other factors such as injection rate, liquid volume, proppant concentration, cluster count, etc., the optimization ranges are greater for Class II reservoirs than for Class I reservoirs. In the case of single-factor optimization for well networks, increasing well spacing leads to larger optimization ranges for proppant concentration and perforation numbers. Under the same well spacing, an alternating wellbore arrangement results in a smaller optimization range for proppant concentration but a larger range for perforation numbers compared to a directly opposite wellbore arrangement. Additionally, this paper summarizes the optimization ranges and provides relevant tables and figures, aiming to offer guidance for on-site construction.

A highly virulent grass carp reovirus (GCRV) strain, named GCRV-AH528, was recently purified from a diseased grass carp with hemorrhage disease in Anhui, China. GCRV-AH528 S9 segment was 1320 nucleotides in length and encoded a 418 amino acid VP6 protein. BLAST search showed that the VP6 protein owned a conserved domain belonging to the reoviral σ2 family. Phylogenetic analysis of VP6 presented that GCRV-AH528 belonged to GCRV genotype II, which was more closely related to Orthoreovirusthan GCRV genotype I and genotype III. Further analysis revealed that GCRV-AH528 S9 and mammalian orthoreovirus S8 might have evolved from a common ancestral precursor and have identical mechanism in virus assembly. The expression level of vp6gene was detected by quantitative real-time PCR (qRT-PCR). Over time, the expression level of vp6gradually increased in Ctenopharyngodon idelluskidney cells. However, the level of vp6expression in blood sharply increased at 4–6 days, and then decreased to a low level after GCRV-AH528 challenge (P< 0.05). The vp6gene was detected in all tissues examined, whereas at relatively higher levels in blood, kidney, and liver (P< 0.05). The yeast two-hybrid (Y2H) system was used to identify VP6 self-interaction, while no interaction was detected in VP6–VP6. This study not only revealed the S9 segment structure and expression pattern but also analyzed the VP6 mechanism by yeast hybridization method. The present study provides valuable informations for further experimental design and investigation of VP6 functions.

•Soil organ matter, potassium and available phosphorus were significant positively correlated with turtle stocking density.•Microbial diversity in paddy soils was higher in higher turtle stocking density groups.•Pseudomonaswas abundant in soils in summer, but the abundance decreased with increasing turtle stocking density.•Phyla Bacteroidetes and Firmicutes were positively correlated to soil pH in rice-turtle paddy soils.

•TCMs were optimized and applied to the effect of TCMs feed addition on the growth performance and serum metabolic profile of Pelodiscus sinensis.