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Abstract The multilayer development of coalbed methane (CBM) is affected by many factors, and the gas production contribution of each seam is unclear. In this study, 12 geological and 10 engineering parameters were adopted to reveal the key factors affecting the combined‐layer drainage productivity of CBM wells before using numerical simulation to clarify the contribution of each coal seam. The results show that the coal reservoir in the Laochang mining area exhibited the advantages of high gas content, intact coal body structure, and large thickness of the combined coal seams, and it was deficient with low saturation and ratio of critical desorption pressure to reservoir pressure. The medium permeability after fracturing and the influence of a small range of fracturing leads to the steep and deep pressure drop funnel of the coal reservoir, and most of the reservoir pressure drop is ineffective; this may be the reason for the unstable production and rapid attenuation of most CBM wells in the study area. The gas production of the Nos. 13 and 18 coal seams is stable and makes a significant contribution, and they can be used as the key objects of follow‐up CBM exploration and development in this area. Geological factors, such as coal body structure, ratio of critical desorption pressure to reservoir pressure, thickness of combined coal seams, and gas saturation, as well as engineering factors, such as permeability and half length of fractures after fracturing, are the main factors affecting the productivity of the CBM wells in the Laochang mining area.

A rapid, green synthesis strategy assisted by a self-exothermic reaction was designed to prepare highly luminescent carbon dots (CDs) from Ganpu tea infusion (G-CDs) within 5 min using H2O2 and diethylenetriamine (DETA) as the exothermic reactants. G-CDs were successfully obtained through a self-exothermic reaction The prepared G-CDs exhibited clear excitation-dependent characteristics and displayed a strong ultraviolet fluorescence emission (385 nm) at the excitation wavelength of 320 nm. The fluorescence of G-CDs was quantitatively quenched by para-nitrophenol (p-NP) with a concentration range of 0.05–50 µM through inner filter effect (IFE). Since p-NP is one of the hydrolysates of the substrate pNPG under the action of Beta-glucosidase (β-Glu), a new fluorescence assay was developed for the indirect determination of β-Glu activity. The detection limits of G-CDs based fluorescence assays are 14.6 nM for p-NP and 0.074 U·L-1 for β-Glu activity, respectively. The developed fluorescence assays were successfully applied to the detection of p-NP in water and human urine samples and β-Glu activity in fruit samples with satisfactory results.

In this study, nitrogen-doped carbon dots (N-CDs) with excellent peroxidase-like activity were prepared using locust powder as the carbon source by a self-exothermic reaction. The obtained N-CDs could catalyze the oxidation of the chromogenic substrate 3,3′,5,5′-tetramethylbenzidine (TMB) in the presence of H2O2 to generate a blue oxidized product (TMBox) with a maximum absorption peak at 654 nm. The catalytic reaction conditions were optimized; furthermore, steady-state kinetic analysis indicated that N-CDs exhibited high affinity toward both TMB and H2O2, and the Michaelis-Menten constant (km) values were 0.115 mM (TMB) and 0.764 mM (H2O2). A smartphone-based colorimetric method was developed for quantitative detection. The 1/L values (L stands for lightness in HSL color space) of the TMBox solution were recorded via an iPhone application Color Analyzer. Since H2O2 is the by-product of glucose (Glu) oxidation in the presence of glucose oxidase (GOx), a simple, sensitive, and selective smartphone-based colorimetric method was developed for the determination of Glu, and the detection limit was 1.09 μM. The smartphone-based method was successfully applied to determine Glu in different food samples with recoveries in the range of 88.5–109.0 %.

Abstract The current in situ stress regime is of great significance to the exploration and development of coalbed methane (CBM). In this study, the vertical stress (σV), maximum horizontal principal stress (σH), and minimum horizontal principal stress (σh) in the Liupanshui Coalfield were studied. Variations of the maximum and minimum envelopes and trend lines of the lateral pressure coefficient (λ) with depth were obtained, and the non‐monotonic decrease of permeability with burial depth was determined. On this basis, the effect of in situ stress on the coal reservoir permeability was evaluated. The results show that the average vertical stress gradient of the main coal seam in the Liupanshui Coalfield is 0.024 MPa/m. Generally, there are two stress regimes of σH > σV > σh (44.23%) and σV > σH > σh (46.15%); σH > σh > σV accounts for a smaller proportion (9.62%), and only occurs in relatively shallow coal seams ( σV > σh is dominant; σV > σH > σh is dominant between 600 and 800 m; and between 800 and 980 m, the coal reservoir is affected by both σH > σV > σh and σV > σH > σh, representing a transition zone between the two stress states. With the increase of burial depth, the permeability of the coal reservoir shows a complex non‐monotonic decline, and the variation of the permeability of the coal reservoir differs under the influence of different stress regimes. Further analysis shows that under the background of stress regime transformation, permeability is mainly affected by the stress value, horizontal principal stress difference, stress regime, and coal cleat, indicating that in situ stress is the main controlling factor of coal reservoir permeability in the Liupanshui Coalfield.

Coalbed methane (CBM) resources are abundant in the Baoan blocks of the Xinjing coalfield, China; their exploration and development remain in infancy. Suitable development blocks can be selected by evaluating their development potential; that of the No. 8 and 15 CBM systems in the Baoan blocks was evaluated using three quantitative evaluation methods via existing geological data: multi-level fuzzy mathematics (MLFM), technique for order preference by similarity to ideal solution (TOPSIS), and principal component analysis (PCA). The results demonstrated that the CBM development potential in the central part of the Baoan blocks is low and unbecoming. The favorable areas of the No. 8 coal seam are distributed in the northeast and northwest, and that of No. 15 in the northwest and southwest Differences exist in quantitative selection; with limited data, the evaluation of the TOPSIS method is considerably different from actuality, and is unbecoming for evaluating the development potential.

The polyphosphoric acid (PPA) modified asphalt binder is a potential choice as one of the pavement materials for its excellent high-temperature performance and low cost. To further analyze the influences of temperature and load on the service life of pavement from the perspective of deformation behavior, six kinds of asphalt binders with different PPA dosages were prepared for Multiple Stress Creep and Recovery (MSCR) tests at five temperature levels. The deformation behavior is investigated by basic deformation parameters, rheological simulation, and energy parameter changes. The results show that the percent recovery (R) drops sharply while non-recoverable creep compliance (Jnr) goes up slightly with the increase in temperature. Three-element model, composed by E1, η1, and η2, can be used to describe the creep behavior. PPA-modified asphalt binder exhibits nonlinear creep behavior, and the logarithmic model can simulate recovery behavior better than the power–law model. Stored energy and dissipated energy can characterize the change of energy in the creep process under different conditions and show a significant correlation to deformation parameters. It is concluded that the elastic component of asphalt binders is increased by PPA, which is beneficial to the improvement of the deformation resistance and recovery capacity of asphalt binders. The recommended dosage of PPA is 1.5%. This investigation is conducive to a better understanding of the deformation behavior of PPA-modified asphalt binders and provides a reference for its engineering applications.

Tomato leaf mold disease caused by Cladosporium fulvum (C. fulvum) is one of the most common diseases affecting greenhouse tomato production. Cf proteins can recognize corresponding AVR proteins produced by C. fulvum, and Cf genes are associated with leaf mold resistance. Given that there are many physiological races of C. fulvum and that these races rapidly mutate, resistance to common Cf genes (such as Cf-2, Cf-4, Cf-5, and Cf-9) has decreased. In the field, Ont7813 plants (carrying the Cf-13 gene) show effective resistance to C. fulvum; thus, these plants could be used as new, disease-resistant materials. To explore the mechanism of the Cf-13-mediated resistance response, transcriptome sequencing was performed on three replicates each of Ont7813 (Cf-13) and Moneymaker (MM; carrying the Cf-0 gene) at 0, 9, and 15 days after inoculation (dai) for a total of 18 samples. In total, 943 genes were differentially expressed, specifically in the Ont7813 response process as compared to the Moneymaker response process. Gene ontology (GO) classification of these 943 differentially expressed genes (DEGs) showed that GO terms, including “hydrogen peroxide metabolic process (GO_Process)”, “secondary active transmembrane transporter activity (GO_Function)”, and “mismatch repair complex (GO_Component)”, which were the same as 11 other GO terms, were significantly enriched. An analysis of the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that many key regulatory genes of the Cf-13-mediated resistance response processes were involved in the “plant hormone signal transduction” pathway, the “plant–pathogen interaction” pathway, and the “MAPK signaling pathway–plant” pathway. Moreover, during C. fulvum infection, jasmonic acid (JA) and salicylic acid (SA) contents significantly increased in Ont7813 at the early stage. These results lay a vital foundation for further understanding the molecular mechanism of the Cf-13 gene in response to C. fulvum infection.

A novel, magnetic silica sorbent with polyelectrolyte multilayers (PEMs) on its surface was prepared, and was used for Magnetic Solid Phase Extraction (MSPE) of trace A+ via Flame Atomic Absorption Spectrometry (FAAS). The experimental parameters for the MSPE procedure, such as the pH, type, and concentration of eluent, ultrasonic time and effects of co-existing ions were investigated. The detection limit of the developed method was 0.17 ng/mL for Ag+ with an enrichment factor of 35. This method was also successfully applied to the determination of trace Ag+ in the leaching solution of different antibacterial products with satisfactory results.

In order to overcome the disadvantage that the dynamic sliding mode surface of the discrete global sliding mode control has a too long evolution time, a quick discrete global sliding mode control method is proposed. A decay function of the dynamic sliding mode surface which can decay to zero in the finite time is constructed. Thereby, the dynamic sliding mode surface can evolve into the linear sliding mode surface at the given time. Thus, the method not only is strong global robustness, but also can quicken the response of the system and shorten the transition time. The method can be applied in the tension control system of the time delay carbon fiber multilayer diagonal loom. Simulation results prove the validity of the method.

Heterosis and combining ability are two important considerations in the utilization of heterosis, which can be used to generate excellent hybrid resource candidates and is very important in conventional hybrid breeding. In this study, the combining ability, heritability, and heterosis of eight major agronomic traits were analyzed in 10 tomato parents and 45 crosses between them. As well as TY-301, a recognized and official excellent variety that is currently selling well on the market was used as a control to conduct a control heterosis analysis, with the goal of selecting ideal parents with high combining ability and new hybrids with commodity value, high yield, early maturity, and high quality. The results showed that both additive and nonadditive genetic effects are involved in the expression of the traits and that the additive genetic effect is dominant in trait inheritance. Although general combining ability (GCA) and specific combining ability (SCA) were not correlated, and the strength of heterosis depends on SCA, the sum of the parental GCA values (GCAsum) did predict heterosis for some traits with higher predictive accuracy than did SCA. Compared with heterosis, GCAsum can better predict hybrid performance. Finally, the parent 17,969 was the breeding material with the best comprehensive trait performance, especially in yield. We screened a high-yielding candidate combination 17,927 × 17,969 and a precocious and good taste candidate combination 17,666 × 17,927. This information may play an important role in the selection of superior parents and hybrid combinations based on combining ability and heterosis analysis.

A super-twisting sliding mode controller is proposed for nonlinear system with external disturbance in order to reduce chattering phenomenon. A criterion is obtained that guarantees the convergence of system states in finite time by Lyapunov stability method. Finally, the results of simulation for carbon fiber multilayer diagonal loom are presented to confirm the effectiveness of the super-twisting sliding mode controller design in agreement.

A new method for the determination of trace copper(II) in food samples by Cloud Point Extraction(CPE) combined with Flame Atomic Absorption Spectrometry(FAAS) is presented and evaluated. The method is based on the fact that hydrophobic complex of copper(II) with sodium diethyldithiocarbamate (DDTC) was formed at pH 6.0 and subsequently the hydrophobic complex was extracted into surfactant-rich phase. Copper(II) in surfactant-rich phase was analyzed by FAAS after dilution the surfactant-rich phase to 0.5 mL by nitric acid in methanol(0.1 mol L-1). The main factors affecting CPE, such as pH, concentration of DDTC and Triton X-114, equilibrium temperature and incubation time, sample volume were investigated in detail. The effect of coexisting ions on the recovery of copper(II) was also investigated. Under the optimum conditions, the detection limit(3σ) of this method was 1.1 ng mL-1 for copper(II), and the relative standard deviation was 3.4 % (c=100 ng mL-1, n=7). The analytical results for the certified reference tea sample(GBW07605) were in a good agreement with the certified value. The proposed method was successfully applied to determination of trace copper(II) in milk powder and mineral water with satisfactory results.

Objectives: To investigate risk factors for severe maternal morbidity (SMM) in pregnant women with hypertensive disorders of pregnancy (HDP) and to develop a risk prediction model. Methods: A prospective observational cohort study was conducted among pregnant women who were hospitalized for hypertensive disorders of pregnancy (HDP) between January 2016 and December 2020 in Fujian College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Province, China (a training set), and a risk predictive model was constructed. Pregnant women with HDP who were hospitalized between January 2021 and December 2021 were selected as a validation set. Concordance index (C-index) and calibration curves were used to test predictive model discrimination and calibration. Results: We included 970 pregnant women (790 in the training set and 180 in the validation set). Least absolute shrinkage and selection operator regression was used to screen for nine related variables such as intra-uterine growth retardation (IUGR), diastolic blood pressure (DBP) and systolic blood pressure (SBP) at suspected diagnosis, total bilirubin, albumin (ALB), uric acid, total cholesterol, serum magnesium, and suspected gestational age. SBP at suspected diagnosis (OR =1.22, 95%CI:1.08-1.42) and total cholesterol (OR = 1.78, 95% CI:1.17-2.80) were independent risk factors of severe maternal morbidity in pregnant women with HDP. A nomogram was constructed, and internal validation of the nomogram model was done using the bootstrap self-sampling method. C-index in the training and the validation set was 0.798 and 0.909, respectively. Conclusion: Our prediction model can be used to determine gestational hypertension severity in pregnant women. [ABSTRACT FROM AUTHOR]

To address the issue of non-uniform fiber volume fraction between layers in the compression compaction process of C/C soft-hard mixed preforms, a multi-unit variable duration cyclic compression compaction process based on the inter-laminar fiber compression viscoelastic deformation behavior is proposed. This process aims to gradually eliminate the rebound characteristics of inter-laminar fibers and reduce the error of inter-laminar fiber volume fraction. The mapping relationships between the number of units, holding duration, and compaction times with the rebound height of inter-laminar fibers are established using data fitting. The compression compaction process is determined using the Box Behnken response surface design method, and digital devices are utilized for preform compaction experiments. The micro-morphology of the preform is observed using an optical microscope, and the density of inter-laminar fibers before and after process optimization is compared. Experimental results indicate that when the number of units is 3, the holding duration is 57 s, and the compaction times is 2, the fiber volume fraction of the soft-hard mixed preform is 42.90%, which is 12.16% higher than before process optimization, and the error of inter-laminar fiber volume fraction is less than 6.5%. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a detection algorithm for foreign fiber during the processing of cotton textile. By collecting a large number of samples, we determine the color model and establish its characteristic parameters of a foreign fiber. We found foreign fibers of multiple types (classes) and proposed a classification-recognition algorithm based on clustering analysis. The maximum error of the studied recognition algorithm is 0.012, which meets the requirement to recognize foreign fibers. Through many experiments, the optimal parameters for the foreign fiber detection system were determined, and the fiber recognition rates for different types were obtained. The lowest recognition rate is 85%. This is sufficiently high to reject foreign fibers and reach the standards of the textile industry. Experimental results show that foreign fiber clustering analysis algorithm is feasible, and it not only improves the quality of foreign fiber detection significantly, but also has high theoretical value and practical value. [ABSTRACT FROM AUTHOR]

The detecting of foreign fiber may not be very effective, particularly around the detection zone where many types of foreign fibers may coexist. In order to eliminate the fibers more effectively, a model has been established to detect foreign fiber faults in yarn. Relevant data were collected through investigation of a number of standard samples, with the length and area of foreign fibers as the independent variables, and the number of defects as the dependent variable, which were combined using linear regression theory to establish a regression equation for different fiber defects. The equations to find the regression coefficients, which include the model fitting degree, the Durbin-Watson value, the standard error, and the Cook distance, were rigorously tested, and the regression equation was eventually compiled to produce the yarn faults model. When the fiber detection equipment recognizes fibers with a foreign profile, the calculated profile fiber size is used in a corresponding regression equation which obtains the defect points and compares them with each other, so that foreign fibers which are potentially more dangerous can be identified and preferentially eliminated. In order to verify the model, spinning experiments are performed. The actual defects from the experiment are compared with the predicted theoretical defects from the equation, and the prediction accuracy was found to reach more than 95%, showing that the foreign fiber yarn faults model, which lays a theoretical foundation for foreign fiber detection, is accurate and effective. [ABSTRACT FROM AUTHOR]

The multilayer films of low molecular weight dye methylene blue (MB) and horseradish peroxidase (HRP) were fabricated by layer-by-layer assembly through electrostatic force. MB was pre-absorbed with anionic polyelectrolyte poly(sodium-p-styrenesulfonate) (PSS). The MB/HRP multilayer film-modified Au electrode functioned as a biosensor for H2O2. [ABSTRACT FROM AUTHOR]

A novel magnetic silica sorbent with polyelectrolyte multilayers (PEMs) on its surface was prepared, and the sorbent was used for the magnetic solid phase extraction (MSPE) of trace Cu2+ in drinking water with flame atomic absorption spectrometry (FAAS) as the detector. The experimental parameters for the MSPE procedure, such as the pH, desorption conditions, ultrasonic time and co-existing ions effects, were investigated. The adsorption capacity of the new sorbent was 14.7 mg g-1 for Cu2+. The detection limit of the developed method was 0.23 ng mL-1 for Cu2+ with an enrichment factor of 95.7. The analytical data obtained from the certified reference water and rice samples were in good agreement with the certified values. This method was also successfully applied to the determination of trace Cu2+ in different food samples with satisfactory results. [ABSTRACT FROM AUTHOR]

Objectives: To investigate risk factors for severe maternal morbidity (SMM) in pregnant women with hypertensive disorders of pregnancy (HDP) and to develop a risk prediction model., Methods: A prospective observational cohort study was conducted among pregnant women who were hospitalized for hypertensive disorders of pregnancy (HDP) between January 2016 and December 2020 in Fujian College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Province, China (a training set), and a risk predictive model was constructed. Pregnant women with HDP who were hospitalized between January 2021 and December 2021 were selected as a validation set. Concordance index (C-index) and calibration curves were used to test predictive model discrimination and calibration., Results: We included 970 pregnant women (790 in the training set and 180 in the validation set). Least absolute shrinkage and selection operator regression was used to screen for nine related variables such as intra-uterine growth retardation (IUGR), diastolic blood pressure (DBP) and systolic blood pressure (SBP) at suspected diagnosis, total bilirubin, albumin (ALB), uric acid, total cholesterol, serum magnesium, and suspected gestational age. SBP at suspected diagnosis (OR =1.22, 95%CI:1.08-1.42) and total cholesterol (OR = 1.78, 95%CI:1.17-2.80) were independent risk factors of severe maternal morbidity in pregnant women with HDP. A nomogram was constructed, and internal validation of the nomogram model was done using the bootstrap self-sampling method. C-index in the training and the validation set was 0.798 and 0.909, respectively., Conclusion: Our prediction model can be used to determine gestational hypertension severity in pregnant women., Competing Interests: Competing Interests: None., (Copyright: © Pakistan Journal of Medical Sciences.)