Theory and technique of permeability enhancement and coal mine gas extraction by fracture network stimulation of surrounding beds and coal beds

AbstractThe existing reservoir stimulating technologies are only applicable to hard coal but helpless for soft coal, which is one of the main factors hindering the CBM industrialization in China. Therefore, it is urgent to develop a universal stimulating technology which can increase the permeability in various coal reservoirs. Theoretical analysis and field tests were used to systematically analyze the mechanical mechanisms causing the formation of various levels and types of fractures, such as radial tensile fractures, peripheral tensile fractures, and shear fractures in hydraulic fracturing, and reveal the mechanism of permeability enhancement by fracture network stimulating in surrounding beds and coal reservoirs. The results show that multi-staged perforation fracturing of horizontal wells, hydraulic-jet staged fracturing, four-variation hydraulic fracturing and some auxiliary measures are effective technical approaches to fracture network stimulation, especially the four-variation hydraulic fracturing can stimulate the fracture network in vertical and cluster wells. It is concluded that the fracture network stimulating technology for surrounding beds has significant advantages, such as safe drilling operation, strong stimulation effect, strong adaptability to stress-sensitive and velocity-sensitive beds, and is suitable for coal reservoirs of any structure. Except for the limitation in extremely water-sensitive and high water-yield surrounding beds, the technology can be universally used in all other beds. The successful industrial tests in surface coal bed methane and underground coal mines gas extraction prove that the theory and technical system of fracture network stimulating in surrounding beds and coal reservoirs, as a universally applicable measure, will play a role in the CBM development in China

Transcriptomic response for revealing the molecular mechanism of oat flowering under different photoperiods

Proper flowering is essential for the reproduction of all kinds of plants. Oat is an important cereal and forage crop; however, its cultivation is limited because it is a long-day plant. The molecular mechanism by which oats respond to different photoperiods is still unclear. In this study, oat plants were treated under long-day and short-day photoperiods for 10 days, 15 days, 20 days, 25 days, 30 days, 40 days and 50 days, respectively. Under the long-day treatment, oats entered the reproductive stage, while oats remained vegetative under the short-day treatment. Forty-two samples were subjected to RNA-Seq to compare the gene expression patterns of oat under long- and short-day photoperiods. A total of 634-5,974 differentially expressed genes (DEGs) were identified for each time point, while the floral organ primordium differentiation stage showed the largest number of DEGs, and the spikelet differentiation stage showed the smallest number. Gene Ontology (GO) analysis showed that the plant hormone signaling transduction and hormone metabolism processes significantly changed in the photoperiod regulation of flowering time in oat. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Mapman analysis revealed that the DEGs were mainly concentrated in the circadian rhythm, protein antenna pathways and sucrose metabolism process. Additionally, transcription factors (TFs) involved in various flowering pathways were explored. Combining all this information, we established a molecular model of oat flowering induced by a long-day photoperiod. Taken together, the long-day photoperiod has a large effect at both the morphological and transcriptomic levels, and these responses ultimately promote flowering in oat. Our findings expand the understanding of oat as a long-day plant, and the explored genes could be used in molecular breeding to help break its cultivation limitations in the future

Blind timing error estimation based on the phasic relationship between nonoverlapping frequency points in time-interleaved ADCS

A time-interleaved analog-to-digital converter (TIADC) system is a good option to significantly increase the sampling rate of an ADC. However, the performance of a TIADC suffers from mismatch errors among the sub-channels, especially the timing error. This paper presents a method to estimate the channel timing error by using the output data from TIADC and its corresponding reference channel. The proposed method introduces an estimate model based on the phase relationship at the non-overlapping frequency points. The only assumption we need is that the spectrum of input signal is sparse. The simulations show that the proposed method can estimate the timing error with high accuracy. ? 2014 IEEE.EI

Adaptive semiblind background calibration of timing mismatches in a two-channel time-interleaved analog-to-digital converter

This paper introduces an adaptive semiblind background calibration of timing mismatches in a two-channel time-interleaved analog-to-digital converter (TIADC). By injecting a test tone at the frequency of half the overall sampling frequency of TIADC, the timing mismatch between two sub-ADCs can be quickly estimated with great accuracy without affecting the normal operation of the TIADC. The estimated coefficient can then be used in compensation module formed by a fixed structure to calibrate the timing mismatches. Simulation results demonstrate the effectiveness of the proposed estimation and correction technique.Beijing Natural Science FoundationNational Natural Science Foundation of Chin

A Study on the Effects of Starches on the Properties of Alkali-Activated Cement and the Potential of Starch as a Self-Degradable Additive

An urgent problem of geothermal energy source development is how to cut down the production costs. The use of temporary sealing materials can reduce the costs associated with the circulation lost by plugging, and increase the production by self-degradation. Based on the utilization of starches as self-degradable additives in the medical field, this paper investigated the effects of three kinds of starches, namely corn starch (CS), hydroxypropyl starch (HPS) and carboxymethyl starch (CMS) on the properties of alkali-activated cement (AAC). In addition, the thermal properties of starch, the compressive strength and microstructures of the cement with starch were tested, to evaluate the potentiality of starch as self-degradable additive for geothermal cement. The analysis showed that: (1) all the starches have the effect of increasing the apparent viscosity, prolonging the setting time and reducing the static fluid loss of alkali-activated cement; (2) the addition of starch increased the number of pores in 200 °C-heated cement, facilitated the leaching process, and thus promoted the self-degradation; and (3) among the three starches, CMS has the most potential as a self-degradable additive

Incidence, survival, and associated factors estimation in osteosarcoma patients with lung metastasis: a single-center experience of 11 years in Tianjin, China

Abstract Background Osteosarcoma is the most common primary malignant bone tumor. The current study was conducted to describe the general condition of patients with primary osteosarcoma in a single cancer center in Tianjin, China and to investigate the associated factors in osteosarcoma patients with lung metastasis. Methods From February 2009 to October 2020, patients from Tianjin Medical University Cancer Institute and Hospital, China were retrospectively analyzed. The Kaplan–Meier method was used to evaluate the overall survival of osteosarcoma patients. The Cox proportional hazard regression analysis was performed to analyze the prognostic factors of all osteosarcoma patients and those patients with lung metastasis, respectively. Furthermore, risk factors for developing lung metastasis were identified in synchronous lung metastasis (SLM) and metachronous lung metastasis (MLM) patients. Results A total of 203 patients were involved and 150 patients were successfully followed up for survival status. The 5-year survival rate of osteosarcoma was 70.0% and the survival months for patients with SLM and MLM were 33.3 ± 12.6 and 45.8 ± 7.4 months, respectively. The presence of lung metastasis was one of the independent prognostic factors for prognosis of osteosarcoma. In patients with lung metastasis, twenty-one (10.3%) showed lung metastasis at the diagnosis of osteosarcoma and 67 (33%) were diagnosed with lung metastases during the later course. T3 stage (OR = 11.415, 95%CI 1.362–95.677, P = 0.025) and bone metastasis (OR = 6.437, 95%CI 1.69–24.51, P = 0.006) were risk factors of SLM occurrence. Bone metastasis (OR = 1.842, 95%CI 1.053–3.224, P = 0.032), good necrosis (≥ 90%, OR = 0.032, 95%CI 0.050–0.412, P < 0.001), elevated Ki-67 (OR = 2.958, 95%CI 1.098–7.969, P = 0.032) and elevated LDH (OR = 1.791, 95%CI 1.020–3.146, P = 0.043) were proved to be independent risk factors for developing MLM. Conclusion The overall survival, prognostic factors and risk factors for lung metastasis in this single center provided insight about osteosarcoma management

Estimating Plant Nitrogen Concentration of Rice through Fusing Vegetation Indices and Color Moments Derived from UAV-RGB Images

Estimating plant nitrogen concentration (PNC) has been conducted using vegetation indices (VIs) from UAV-based imagery, but color features have been rarely considered as additional variables. In this study, the VIs and color moments (color feature) were calculated from UAV-based RGB images, then partial least square regression (PLSR) and random forest regression (RF) models were established to estimate PNC through fusing VIs and color moments. The results demonstrated that the fusion of VIs and color moments as inputs yielded higher accuracies of PNC estimation compared to VIs or color moments as input; the RF models based on the combination of VIs and color moments (R2 ranging from 0.69 to 0.91 and NRMSE ranging from 0.07 to 0.13) showed similar performances to the PLSR models (R2 ranging from 0.68 to 0.87 and NRMSE ranging from 0.10 to 0.29); Among the top five important variables in the RF models, there was at least one variable which belonged to the color moments in different datasets, indicating the significant contribution of color moments in improving PNC estimation accuracy. This revealed the great potential of combination of RGB-VIs and color moments for the estimation of rice PNC

Biodegradation of Cyanide by a New Isolated <i>Aerococcus viridans</i> and Optimization of Degradation Conditions by Response Surface Methodology

Microbial treatment of cyanide pollution is an effective, economical, and environmentally friendly method compared with physical or chemical approaches. A cyanide-degrading bacterium was isolated from electroplating sludge and identified as Aerococcus viridans (termed A. viridans T1) through an analysis of the biochemical reaction and 16 S rDNA gene sequence. A. viridans T1 showed a maximum resistance to 550 mg L−1 CN−. The effect of pH and temperature on cyanide degradation and bacterial growth was evaluated. The highest cyanide removal efficiency and bacterial growth occurred at pH 8 and pH7, respectively. The optimum temperature for cyanide degradation and bacterial growth was 34 ∘C. In addition, the carbon source and nitrogen source for cyanide degradation were optimized. The optimal carbon source and nitrogen source were glycerol and peptone, respectively. The cyanide degradation experiment indicated that A. viridans T1 was able to remove 84.1% of free cyanide at an initial concentration of 200 mg L−1 CN− within 72 h and 86.7% of free cyanide at an initial concentration of 150 mg L−1 CN− within 56 h. To improve the cyanide-degrading efficiency of A. viridans T1, eight process variables were further optimized using a response surface methodology. Three significant variables (soybean meal, corn flour, and L-cysteine) were identified using a Plackett–Burman design, and the variable levels were optimized using a central composite design. The optimal values of soybean meal, corn flour, and L-cysteine were 1.11%, 1.5%, and 1.2%, respectively. Under these optimal conditions, the confirmatory experiments showed that the actual degradation rate was 97.3%, which was similar to the predicted degradation rate of 98.87%. Its strong resistance to cyanide and cyanide-degrading activity may allow A. viridans T1 to be a candidate for the bioremediation of cyanide-contaminated environments

Solution-processed self-assemble engineering PDI derivative polymorphisms with optoelectrical property tuning in organic field-effect transistors

The crystal polymorphism study leads to an explosion of science research, related to many fields, such as organic semiconductors, pharmaceuticals, pigments, food, and explosives. Two different crystal phases of a perylene diimide derivative (4FPEPTC) have been prepared via a simple and efficient solution method. Via changing the concentration of the solution, we observed the polymorphisms clearly, wire-shape (α phase) and ribbon-like (β phase) crystals differed in the stacking mode and short-contacts. Moreover, the as-prepared n-channel microcrystal-based devices demonstrated distinct electron mobilities that of α phase architecture higher than β phase structure and obvious photoresponse discrepancy. Theoretical calculations further confirmed this phenomena, which help us to understand the structure-property relationship in this crystal polymorph. Our study indicates that the investigation of polymorphisms could be considered as a very useful method to realize functional property modulation and benefits the development of organic (opto)electronics.SCOPUS: ar.jinfo:eu-repo/semantics/publishe