Search Results (9)

The production of flue gas desulfurization gypsum poses a serious threat to the environment. Thus, utilizing gypsum-based self-leveling mortar (GSLM) stands out as a promising and effective approach to address the issue. β-hemihydrate gypsum, cement, polycarboxylate superplasticizer, hydroxypropyl methyl cellulose ether (HPMC), retarder, and defoamer were used to prepare GSLM. The impact of mineral admixtures (steel slag (SS), silica fume (SF), and fly ash (FA)) on the physical, mechanical, and microstructural properties of GSLM was examined through hydration heat, X-ray diffractometry (XRD), Raman spectroscopy, and scanning electron microscopy (SEM) analyses. The GSLM benchmark mix ratio was determined as follows: 94% of desulfurization building gypsum, 6% of cement, 0.638% each of water reducer and retarder, 0.085% each of HPMC and defoamer (calculated additive ratio relative to gypsum), and 0.54 water-to-cement ratio. Although the initial fluidity decreased in the GSLM slurry with silica fume, there was minimal change in 30 min fluidity. Notably, at an SS content of 16%, the GSLM exhibited optimal flexural strength (6.6 MPa) and compressive strength (20.4 MPa). Hydration heat, XRD, and Raman analyses revealed that a small portion of SS actively participated in the hydration reaction, while the remaining SS served as a filler. Full article

As the world’s energy demand continues to expand, shale oil has a substantial influence on the global energy reserves. The third submember of the Mbr 3 of the Shahejie Fm, characterized by complicated mudrock lithofacies, is one of the significant shale oil enrichment intervals of the Bohai Bay Basin. The classification and identification of lithofacies are key to shale oil exploration and development. However, the efficiency and reliability of lithofacies identification results can be compromised by qualitative classification resulting from an incomplete workflow. To address this issue, a comprehensive technical workflow for mudrock lithofacies classification and logging prediction was designed based on machine learning. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were conducted to realize the automatic classification of lithofacies, which can classify according to the internal relationship of the data without the disturbance of human factors and provide an accurate lithofacies result in a much shorter time. The PCA and HCA results showed that the third submember can be split into five lithofacies: massive argillaceous limestone lithofacies (MAL), laminated calcareous claystone lithofacies (LCC), intermittent lamellar argillaceous limestone lithofacies (ILAL), continuous lamellar argillaceous limestone lithofacies (CLAL), and laminated mixed shale lithofacies (LMS). Then, random forest (RF) was performed to establish the identification model for each of the lithofacies and the obtained model is optimized by grid search (GS) and K-fold cross validation (KCV), which could then be used to predict the lithofacies of the non-coring section, and the three validation methods showed that the accuracy of the GS–KCV–RF model were all above 93%. It is possible to further enhance the performance of the models by resampling, incorporating domain knowledge, and utilizing the mechanism of attention. Our method solves the problems of the subjective and time-consuming manual interpretation of lithofacies classification and the insufficient generalization ability of machine-learning methods in the previous works on lithofacies prediction research, and the accuracy of the model for mudrocks lithofacies prediction is also greatly improved. The lithofacies machine-learning workflow introduced in this study has the potential to be applied in the Bohai Bay Basin and comparable reservoirs to enhance exploration efficiency and reduce economic costs. Full article

Chronic neuropathic pain resulting from peripheral nerve damage is a significant clinical problem, which makes it imperative to develop the mechanism-based therapeutic approaches. Enhancement of endogenous cannabinoids by blocking their hydrolysis has been shown to reduce inflammation and neuronal damage in a number of neurological disorders and neurodegenerative diseases. However, recent studies suggest that inhibition of their hydrolysis can shift endocannabinoids 2-arachidonoyl glycerol (2-AG) and anandamide (AEA) toward the oxygenation pathway mediated by cyclooxygenase-2 (COX-2) to produce proinflammatory prostaglandin glycerol esters (PG-Gs) and prostaglandin ethanolamides (PG-EAs). Thus, blocking both endocannabinoid hydrolysis and oxygenation is likely to be more clinically beneficial. In this study, we used the chronic constriction injury (CCI) mouse model to explore the therapeutic effects of simultaneous inhibition of AEA hydrolysis and oxygenation in the treatment of neuropathic pain. We found that the fatty acid amide hydrolase (FAAH) inhibitor PF04457845 and the substrate-selective COX-2 inhibitor LM4131 dose-dependently reduced thermal hyperalgesia and mechanical allodynia in the CCI mice. In addition to ameliorating the pain behaviors, combined treatment with subeffective doses of these inhibitors greatly attenuated the accumulation of inflammatory cells in both sciatic nerve and spinal cord. Consistently, the increased proinflammatory cytokines IL-1β, IL-6, and chemokine MCP-1 in the CCI mouse spinal cord and sciatic nerve were also significantly reduced by combination of low doses of PF04457845 and LM4131 treatment. Therefore, our study suggests that simultaneous blockage of endocannabinoid hydrolysis and oxygenation by using the substrate-selective COX-2 inhibitor, which avoids the cardiovascular and gastrointestinal side effects associated with the use of general COX-2 inhibitors, might be a suitable strategy for the treatment of inflammatory and neuropathic pain. Full article

Three genotypes of wheat grown at two CO₂ concentrations were used in a drought experiment, where water was withheld from the pots at anthesis until stomatal conductance (g_s) dropped below 10% of the control and photosynthesis (A) approached zero. The genotypes had different leaf area (Gladius < LM19 < LM62) and while photosynthesis and shoot growth were boosted by elevated CO₂, the water use and drying rate were more determined by canopy size than by stomatal density and conductance. The genotypes responded differently regarding number of fertile tillers, seeds per spike and 1000 kernel weight and, surprisingly, the largest genotype (LM62) with high water use showed the lowest relative decrease in grain yield. The maximum photochemical efficiency of photosystem II (F_v/F_m) was only affected on the last day of the drought when the stomata were almost closed although some variation in A was still seen between the genotypes. A close correlation was found between F_v/F_m and % loss of grain yield. It indicates that the precise final physiological stress level measured by F_v/F_m at anthesis/early kernel filling could effectively predict percentage final yield loss, and LM62 was slightly less stressed than the other genotypes, due to only a small discrepancy in finalising the drying period. Therefore, F_v/F_m can be used as a proxy for estimating the yield performance of wheat after severe drought at anthesis. Full article

Groundwater plays a significant role in influencing the growth and distribution of Robinia pseudoacacia L. plantations, with the largest planting area in the Yellow River Delta, by affecting the soil water–salt environment. This study aimed to clarify the mechanism of groundwater’s influence on the growth of R. pseudoacacia under different levels of groundwater mineralization (GWM) and groundwater depth (GWD). We simulated GWM of 0, 2 and 4 g L⁻¹, and GWD of 0.8, 1.3 and 1.8 m. As GWM increased, soil relative water content (SRWC) and soil salt (dissolved salt) content (SSC) increased; sapling biomass (SB), stem mass (SM), leaf mass (LM), photosynthesis characteristics (maximum net photosynthetic rate (P_n), stomatal conductance (g_s), intercellular CO₂ concentration (C_i), transpiration rate (E) and water use efficiency (WUE)) decreased; root mass (RM), root mass ratio (RMR) and root–shoot ratio (RSR) first increased then decreased; stem mass ratio (SMR) first decreased then increased; and leaf mass ratio (LMR) increased. As GWD increased, SRWC decreased, but SSC first increased then decreased; SB, RM, RMR, RSR, and photosynthesis characteristics increased; SM and LM first increased then decreased; and SMR and LMR decreased. SRWC and SSC were negatively correlated with SB and photosynthesis characteristics. SRWC was negatively correlated with RMR and RSR, whereas it was positively correlated with LMR. SSC was negatively correlated with SMR, whereas it was positively correlated with LMR. The first principal component, including SB, RM, and photosynthesis characteristics, was related to sapling growth. The second principal component, including RMR, SMR, and RSR, was mainly related to biomass allocation. In conclusion, GWM and GWD affected the soil water and salt content, which were key factors influencing the photosynthesis and growth of R. pseudoacacia. Adjustments in biomass allocation and photosynthesis were the main adaptive strategies of R. pseudoacacia to salt, drought, and flooding stress. Full article

In this work, we began to take forward kinematics of the Gough–Stewart (G-S) platform as an unconstrained optimization problem on the Lie group-structured manifold SE(3) instead of simply relaxing its intrinsic orthogonal constraint when algorithms are updated on six-dimensional local flat Euclidean space or adding extra unit norm constraint when orientation parts are parametrized by a unit quaternion. With this thought in mind, we construct two kinds of iterative problem-solving algorithms (Gauss–Newton (G-N) and Levenberg–Marquardt (L-M)) with mathematical tools from the Lie group and Lie algebra. Finally, a case study for a general G-S platform was carried out to compare these two kinds of algorithms on SE(3) with corresponding algorithms that updated on six-dimensional flat Euclidean space or seven-dimensional quaternion-based parametrization Euclidean space. Experiment results demonstrate that those algorithms on SE(3) behave better than others in convergence performance especially when the initial guess selection is near to branch solutions. Full article

To address inaccurate prediction in remaining useful life (RUL) in current Lithium-ion batteries, this paper develops a Long Short-Term Memory Network, Sliding Time Window (LSTM-STW) and Gaussian or Sine function, Levenberg-Marquardt algorithm (GS-LM) fusion batteries RUL prediction method based on ensemble empirical mode decomposition (EEMD). Firstly, EEMD is used to decompose the original data into high-frequency and low-frequency components. Secondly, LSTM-STW and GS-LM are used to predict the high-frequency and low-frequency components, respectively. Finally, the LSTM-STW and GS-LM prediction results are effectively integrated in order to obtain the final prediction of the lithium-ion battery RUL results. This article takes the lithium-ion battery data published by NASA as input. The experimental results show that the method has higher accuracy, including the phenomenon of sudden capacity increase, and is less affected by the prediction starting point. The performance of the proposed method is better than other typical battery RUL prediction methods. Full article

This study aimed to investigate the relationship between back muscle strength and proprioception or mechanoreceptor control strategies used for postural balance in elderly adults with lumbar spondylosis. The displacement of the center of pressure (COP) excursion was determined in 24 elderly adults with lumbar spondylosis and 24 healthy young adults while the participants were standing upright on a balance board with their eyes closed. Vibratory stimulations of 30, 60, and 240 Hz were applied to the gastrocnemius (GS) and lumbar multifidus (LM) muscles to evaluate the effect of different proprioceptive signals on postural control. Back muscle strength was evaluated. Spearman’s rank correlation analysis was performed to determine the relationship between back muscle strength and significant COP excursion. Compared with young adults, elderly adults with lumbar spondylosis showed an increase in COP excursion displacement when a vibratory stimulation of 240 Hz was applied to the GS (P = 0.002) and LM muscles (P < 0.001). LM stimulation at 240 Hz was significantly associated with back muscle strength (P = 0.038). Postural control assessment with 240-Hz mechanoreceptor stimulation of the trunk could be a good indicator of postural instability due to over-dependence on mechanoreceptors and back muscle weakness in elderly adults with lumbar spondylosis. Full article

Proprioceptive input may greatly affect postural stability. However, the proprioceptive postural strategy in elderly, middle-aged, and young people has not been investigated sufficiently. Hence, in this study, we aimed to investigate differences in proprioceptive postural strategies of elderly, middle-aged, and young people. The center of pressure displacement was determined in 23 elderly, 23 middle-aged, and 23 young people during upright stance on a balance board with their eyes closed. Vibratory stimulations at 30, 60, and 240 Hz were applied to the lumbar multifidus (LM) and gastrocnemius (GS) muscles to evaluate the contributions of different proprioceptive signals used in balance control. Compared with middle-aged and young people, elderly people showed a high dependence on postural control of the GS at 30 Hz (p-values: Young and elderly: 0.033; middle-aged and elderly: 0.001). Moreover, compared with young people, elderly people were more dependent on postural control of the LM at 240 Hz (p = 0.016). There were no significant differences with respect to the GS at 60 and 240 Hz, and with respect to the LM at 30 and 60 Hz between the elderly, young, and middle-aged people. Thus, the postural control strategy of elderly people depends on the GS at 30 Hz. Full article