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The stability of coal pillar is extremely important to the control of rock strata movement and surface subsidence. It is of great significance for mining design to analyze the stability and failure characteristics of coal and rock pillars left after mining and to study the failure characteristics and rheological properties of coal and rock with different shapes. In this paper, based on uniaxial compression and rheological tests on rock samples, the rheological properties of rock samples with different shapes were discussed by using the nonlinear theoretical mechanics and damage theory, and the rheological mechanical characteristics of coarse yellow sandstone samples under the action of different free surface areas and the same loading contact area were investigated by means of experimental research, theoretical analysis and numerical simulation. The following conclusions were drawn: the failure characteristics and dynamic change process of rock samples with different shapes under the same loading contact area are obtained by uniaxial compression test and multi-stage rheological loading. The uniaxial compressive strengths of rock samples with the same loading contact surface area and different free surface areas are inversely proportional to their free surface areas. For the round sample, the stress level in the rheological test is obviously lower than the instantaneous peak uniaxial compression strength, while for the other samples, the stress level in the rheological test is close to the instantaneous peak uniaxial compression strength. For rock all these samples, both the ratio of steady-state rheological time to final failure time and the deformation degree decrease with the increase of free surface area. [ABSTRACT FROM AUTHOR]

Due to the harsh operating environment and ultralong operating hours of wireless sensor networks (WSNs), node failures are inevitable. Ensuring the reliability of the data collected by the WSN necessitates the utmost importance of diagnosing faults in nodes within the WSN. Typically, the initial step in the fault diagnosis of WSN nodes involves extracting numerical features from neighboring nodes. A solitary data feature is often assigned a high weight, resulting in the failure to effectively distinguish between all types of faults. Therefore, this study introduces an enhanced variant of the traditional belief rule base (BRB), called the belief rule base with adaptive attribute weights (BRB-AAW). First, the data features are extracted as input attributes for the model. Second, a fault diagnosis model for WSN nodes, incorporating BRB-AAW, is established by integrating parameters initialized by expert knowledge with the extracted data features. Third, to optimize the model's initial parameters, the projection covariance matrix adaptive evolution strategy (P-CMA-ES) algorithm is employed. Finally, a comprehensive case study is designed to verify the accuracy and effectiveness of the proposed method. The results of the case study indicate that compared with the traditional BRB method, the accuracy of the proposed model in WSN node fault diagnosis is significantly improved. [ABSTRACT FROM AUTHOR]

Due to the harsh operating environment and ultralong operating hours of wireless sensor networks (WSNs), node failures are inevitable. Ensuring the reliability of the data collected by the WSN necessitates the utmost importance of diagnosing faults in nodes within the WSN. Typically, the initial step in the fault diagnosis of WSN nodes involves extracting numerical features from neighboring nodes. A solitary data feature is often assigned a high weight, resulting in the failure to effectively distinguish between all types of faults. Therefore, this study introduces an enhanced variant of the traditional belief rule base (BRB), called the belief rule base with adaptive attribute weights (BRB-AAW). First, the data features are extracted as input attributes for the model. Second, a fault diagnosis model for WSN nodes, incorporating BRB-AAW, is established by integrating parameters initialized by expert knowledge with the extracted data features. Third, to optimize the model's initial parameters, the projection covariance matrix adaptive evolution strategy (P-CMA-ES) algorithm is employed. Finally, a comprehensive case study is designed to verify the accuracy and effectiveness of the proposed method. The results of the case study indicate that compared with the traditional BRB method, the accuracy of the proposed model in WSN node fault diagnosis is significantly improved. [ABSTRACT FROM AUTHOR]

Estuaries are dynamic and selective environments that provide frequent opportunities for the turnover of Phragmites australis populations. We studied Phragmites genetic diversity patterns in three of the major deltas of China, viz. the Yellow River, the Yangtze and the Liaohe, in relation to Phragmites global phylogeography and soil salinity. We found that two distantly related P. australis haplotypes, each with intercontinental distribution, co-occur in these deltas in China. One is European Phragmites (Haplotype O) and is related to P. japonicus; the other (Haplotype P) has its range in East Asia and Australia and is related to the Asian tropical species P. karka. The two haplotypes have differing salt tolerance, with Haplotype O in areas with the highest salinity and Haplotype P in areas with the lowest. Introgressed hybrids of Haplotype P with P. karka, and F1 hybrids with Haplotype O, have higher salt tolerance than Haplotype P. Phylogenetic diversity appears as the factor that better explains population structure and salinity tolerance in these estuaries. Future research may explain whether the two P. australis haplotypes evolved in East Asia, and East Asia is a center of Phragmites diversity, or are introduced and a threat to P. japonicus and P. karka. [ABSTRACT FROM AUTHOR]

Nitrogen (N), phosphorus (P), and potassium (K) exert various effects on adzuki bean yields. Our research was conducted in a semi-arid area, and four test sites were established in environments that have chernozem or sandy loam soils. During a five-year period, the effects of N, P, and K fertilizers on yield were comprehensively investigated in field trials (2014–2016) and for model-implementation trials (2017–2018), with models established prior to the latter. In the field trials, 23 treatments comprising different N, P, and K combinations significantly affected both yield and yield components, and regression analysis indicated that the experimental results were suitable for model establishment. The model subsequently demonstrated that the yield and the yield components were more sensitive to N and K fertilizer than to P fertilizer. Moreover, the yield and yield components increased. These yield increases were intense in response to the 0.5 to 1.34 levels in terms of the single effects; interaction effects; and the effects of combinations of N, P, and K fertilizers. Moreover, the effects of combinations of N, P, and K fertilizers were more significant on yield than were the single or interaction effects of N, P, and K fertilizers. The optimal fertilizer combination that resulted in high yields (≥1941.53 kg ha−1) comprised 57.23–68.43 kg ha−1 N, 36.04–47.32 kg ha−1 P2O5 and 50.29–61.27 kg ha−1 K2O. The fertilizer combination that resulted in the maximum yield was 62.98 kg ha−1 N, 47.04 kg ha−1 P2O5 and 59.95 kg ha−1 K2O (N:P2O5:K2O = 1:0.75:0.95), which produced the model-expected yield in trials at multiple sites. An economical fertilizer combination was determined on the basis of the best fertilizer measures in consideration of the cost of fertilizer and seed; this combination achieved yields of 2236.17 kg ha−1, the profit was 15,653.16 Yuan ha−1, and the corresponding rates were 57.60 kg ha−1 N, 47.03 kg ha−1 P2O5, and 31.64 kg ha−1 K2O (N:P2O5:K2O = 1:0.82:0.55). [ABSTRACT FROM AUTHOR]

Reservoir flood control scheduling is a challenging optimization task, particularly due to the complexity of various constraints. This paper proposes an innovative algorithm design approach to address this challenge. Combining the basic walrus optimization algorithm with the adaptive ε-constraint method and introducing the SPM chaotic mapping for population initialization, spiral search strategy, and local enhancement search strategy based on Cauchy mutation and reverse learning significantly enhances the algorithm's optimization performance. On this basis, innovate an adaptive approach ε A New Algorithm for Constraints and Multi Strategy Optimization Improvement (ε-IWOA). To validate the performance of the ε-IWOA algorithm, 24 constrained optimization test functions are used to test its optimization capabilities and effectiveness in solving constrained optimization problems. Experimental results demonstrate that the ε-IWOA algorithm exhibits excellent optimization ability and stable performance. Taking the Taolinkou Reservoir, Daheiting Reservoir, and Panjiakou Reservoir in the middle and lower reaches of the Luanhe River Basin as a case study, this paper applies the ε-IWOA algorithm to practical reservoir scheduling problems by constructing a three-reservoir flood control scheduling system with Luanxian as the control point. A comparative analysis is conducted with the ε-WOA, ε-DE and ε-PSO (particle swarm optimization) algorithms.The experimental results indicate that ε-IWOA algorithm performs the best in optimization, with the occupied flood control capacity of the three reservoirs reaching 89.32%, 90.02%, and 80.95%, respectively. The control points in Luan County can reduce the peak by 49%.This provides a practical and effective solution method for reservoir optimization scheduling models. This study offers new ideas and solutions for flood control optimization scheduling of reservoir groups, contributing to the optimization and development of reservoir scheduling work. [ABSTRACT FROM AUTHOR]

Rickettsiales are important zoonotic pathogens, causing severe disease in humans globally. Although mosquitoes are an important vector for diverse pathogens, with the exception of members of the genus Wolbachia little is known about their role in the transmission of Rickettsiales. Herein, Rickettsiales were identified by PCR in five species of mosquitoes (Anopheles sinensis, Armigeres subalbatus, Aedes albopictus, Culex quinquefasciatus and Cu. tritaeniorhynchus) collected from three Chinese provinces during 2014-2015. Subsequent phylogenetic analyses of the rrs, groEL and gltA genes revealed the presence of Anaplasma, Ehrlichia, Candidatus Neoehrlichia, and Rickettsia bacteria in mosquitoes, comprising nine documented and five tentative species bacteria, as well as three symbionts/endosybionts. In addition, bacteria were identified in mosquito eggs, larvae, and pupae sampled from aquatic environments. Hence, these data suggest that Rickettsiales circulate widely in mosquitoes in nature. Also of note was that Ehrlichia and Rickettsia bacteria were detected in each life stage of laboratory cultured mosquitoes, suggesting that Rickettsiales may be maintained in mosquitoes through both transstadial and transovarial transmission. In sum, these data indicate that mosquitoes may have played an important role in the transmission and evolution of Rickettsiales in nature. [ABSTRACT FROM AUTHOR]

Pancreatic adenocarcinoma (PAAD) is a frequent type of cancer in adults worldwide, and the search for better biomarkers is one of the current challenges. Although RAB7A is associated with tumour progression in multiple tumour types, there are only a few reports in PAAD. Therefore, in this paper, RNA sequencing data were obtained from TCGA(The Cancer Genome Atlas) and GTEx to analyse RAB7A expression and differentially expressed genes (DEGs) in PAAD. The functional enrichment of RAB7A-associated DEGs was analysed by protein‒protein interaction (PPI) networks, immune cell infiltration analysis and GO/KEGG analyses. Additionally, Kaplan‒Meier and Cox regression analyses were used to determine the clinical significance of RAB7A in PAAD. High RAB7A expression was associated with poor prognosis in 182 PAAD specimens, including subgroups of patients aged ≤ 65 years, with male sex, not receiving radiotherapy, and with a history of previous alcohol consumption (P < 0.05). Cox regression analysis showed that elevated RAB7A was an independent prognostic factor, and the prognostic nomogram model included radiotherapy status, presence of postoperative tumour residual and histologic grade. Overall, RAB7A overexpression may serve as a biomarker for poor outcome in pancreatic cancer. The DEGs and pathways revealed in this work provide a tentative molecular mechanism for the pathogenesis and progression of PAAD. [ABSTRACT FROM AUTHOR]

Pancreatic adenocarcinoma (PAAD) is a frequent type of cancer in adults worldwide, and the search for better biomarkers is one of the current challenges. Although RAB7A is associated with tumour progression in multiple tumour types, there are only a few reports in PAAD. Therefore, in this paper, RNA sequencing data were obtained from TCGA(The Cancer Genome Atlas) and GTEx to analyse RAB7A expression and differentially expressed genes (DEGs) in PAAD. The functional enrichment of RAB7A-associated DEGs was analysed by protein‒protein interaction (PPI) networks, immune cell infiltration analysis and GO/KEGG analyses. Additionally, Kaplan‒Meier and Cox regression analyses were used to determine the clinical significance of RAB7A in PAAD. High RAB7A expression was associated with poor prognosis in 182 PAAD specimens, including subgroups of patients aged ≤ 65 years, with male sex, not receiving radiotherapy, and with a history of previous alcohol consumption (P < 0.05). Cox regression analysis showed that elevated RAB7A was an independent prognostic factor, and the prognostic nomogram model included radiotherapy status, presence of postoperative tumour residual and histologic grade. Overall, RAB7A overexpression may serve as a biomarker for poor outcome in pancreatic cancer. The DEGs and pathways revealed in this work provide a tentative molecular mechanism for the pathogenesis and progression of PAAD. [ABSTRACT FROM AUTHOR]

The optimal oxygen concentration is unclear for normothermic machine perfusion (NMP) of livers from donation after circulatory death (DCD). Our purposes were to investigate the effect of air-ventilated NMP on the DCD liver, analyze the underlying mechanism and select the targets to predict liver functional recovery with NMP. NMP was performed using the NMP system with either air ventilation or oxygen ventilation for 2 h in the rat liver following warm ischemia and cold-storage preservation. Proteomics and metabolomics were used to reveal the significant molecular networks. The bioinformation analysis was validated by administering peroxisome proliferator activator receptor-γ (PPARγ) antagonist and agonist via perfusion circuit in the air-ventilated NMP. Results showed that air-ventilated NMP conferred a better functional recovery and a less inflammatory response in the rat DCD liver; integrated proteomics and metabolomics analysis indicated that intrahepatic docosapentaenoic acid downregulation and upregulation of cytochrome P450 2E1 (CYP2E1) expression and activity were associated with DCD liver functional recovery with air-ventilated NMP; PPARγ antagonist worsened liver function under air-oxygenated NMP whereas PPARγ agonist played the opposite role. In conclusion, air-ventilated NMP confers a better liver function from DCD rats through the DAP-PPARγ-CYP2E1 axis; CYP2E1 activity provides a biomarker of liver functional recovery from DCD. [ABSTRACT FROM AUTHOR]

To investigate the effects of extended light/dark (L/D) cycle period (relative to the diurnal L/D cycle) on lettuce and explore potential advantages of abnormal L/D cycles, butter leaf lettuce were grown in a plant factory with artificial light (PFAL) and exposed to mixed red (R) and blue (B) LED light with different L/D cycles that were respectively 16 h light/8 h dark (L16/D8, as control), L24/D12, L48/D24, L96/D48 and L120/D60. The results showed that, all the abnormal L/D cycles increased shoot dry weight (DW) of lettuce (by 34–83%) compared with the control, and lettuce DW increased with the L/D cycle period prolonged. The contents of soluble sugar and crude fiber in lettuce showed an overall upward trend with the length of L/D cycle extended, and the highest vitamin C content as well as low nitrate content were both detected in lettuce treated with L120/D60. The light use efficiency (LUE) and electric use efficiency (EUE) of lettuce reached the maximum (respectively 5.37% and 1.76%) under L120/D60 treatment and so were DW, Assimilation rate (A), RC/CS, ABS/CS, TRo/CS and DIo/CS, indicating that longer L/D cycle period was beneficial for the assimilation efficiency and dry matter accumulation in lettuce leaves. The highest shoot fresh weight (FW) and nitrate content detected in lettuce subjected to L24/D12 may be related to the vigorous growth of root, specific L/D cycle seemed to strengthen root growth and water absorption of lettuce. The openness level of RC in PSII (Ψo), ETo/CS, and PIabs were all the highest in lettuce treated with L24/D12, implying that slightly extending the L/D cycle period might promote the energy flowing to the final electron transfer chain. In general, irradiation modes with extended L/D cycle period had the potential to improve energy use efficiency and biomass of lettuce in PFAL. No obvious stress or injury was detected in lettuce subjected to prolonged L/D cycles in terms of plant growth and production. From the perspective of shoot FW, the optimal treatment in this study was L24/D12, while L120/D60 was the recommended treatment as regards of the energy use efficiency and nutritional quality. [ABSTRACT FROM AUTHOR]

Since red (R) and blue (B) LED light has different quantum efficiency and photoelectric conversion efficiency, mixed RB with different proportions of R and B results in varied energy consumption. In order to improve the energy use efficiency of the closed-type plant production systems, the effects of R and B proportions on the electric use efficiency (EUE), light use efficiency (LUE) as well as the quality of butter leaf lettuce were evaluated in this study. Lettuce seedlings were cultivated in a plant factory with artificial lighting (PFAL) and subjected to eleven combinations of R and B (100%R, 90%R, 80%R, 70%R, 60%R, 50%R, 40%R, 30%R, 20%R, 10%R, 0%R; the rest of the photons in each treatment were B) with the same total photosynthetic photon flux density (PPFD) and photoperiod (200 ± 3 μmol·m−2·s−1, 16 h) for 35 days. The results showed that palpable petiole distortion appeared when R proportion was more than 70% and the distortion was aggravated with the increase of R proportion. The highest EUE and LUE were both detected in lettuce under 90%R treatment, which were respectively 3.64% and 1.20%. The least number of photons and the least electricity amount required to produce 1 g dry weight of lettuce was respectively 2.92 mol and 1.67 MJ, which were both detected in lettuce treated with 90%R. The sucrose content in lettuce treated with more than 50%R was significantly higher than those treated with less than 50%R (50%R included). Lettuce treated with 80%R possessed the highest soluble sugar content as well as the lowest crude fiber and nitrate content (not significantly different with the minimum values). R proportion exceeding 50% in mixed RB light was beneficial to the accumulation of hexose and sucrose, as well as the decomposition of nitrate in lettuce. The vitamin C content in lettuce treated with 100%R was significantly higher than that in lettuce under other treatments in the study. On the whole, the study indicated that the proportions of R and B affected the energy use efficiency and quality of lettuce in closed plant factory, however the responses of plants to the proportions of R and B varied according to different indexes. Thus, some indexes of top priority should be determined before choosing the optimal proportions of R and B. [ABSTRACT FROM AUTHOR]

Accurate evaluation of liver steatosis is required from brain-dead donors (BDDs) with nonalcoholic fatty liver disease (NAFLD). Our purposes were to investigate expression and regulation of connective tissue growth factor (CTGF) expression in livers from human and rat after brain death, and further evaluate its potential application. NAFLD and brain death models were established in rats. LX2 cells were cultured under hypoxia/reoxygenation. CTGF protein and mRNA levels were measured in liver samples from BDDs of human and rat by immunohistochemistry and reverse transcription-quantitative polymerase chain reaction. YAP-regulated CTGF expression was investigated in LX2 cells via YAP small interfering RNA and Verteporfin treatment. Blood CTGF level from BDDs was measured by enzyme-linked immunosorbent assay. After brain death, CTGF, transforming growth factor-β and YAP were overexpressed in non-alcoholic steatotic liver, whereas CTGF was downregulated in non-steatotic liver. Time-series analysis revealed that CTGF and YAP expression was comparable, as confirmed by inhibited YAP expression in LX2 cells. CTGF level and NAFLD activity were linearly correlated. CTGF expression and regulation differ between non-steatosis and nonalcoholic steatosis livers from BDDs. CTGF may be an important factor to evaluate graft quality from BDDs with NAFLD. [ABSTRACT FROM AUTHOR]

Remote sensing has been used as an important means of estimating crop production, especially for the estimation of crop yield in the middle and late growth period. In order to further improve the accuracy of estimating winter wheat yield through remote sensing, this study analyzed the quantitative relationship between satellite remote sensing variables obtained from HJ-CCD images and the winter wheat yield, and used the partial least square (PLS) algorithm to construct and validate the multivariate remote sensing models of estimating the yield. The research showed a close relationship between yield and most remote sensing variables. Significant multiple correlations were also recorded between most remote sensing variables. The optimal principal components numbers of PLS models used to estimate yield were 4. Green normalized difference vegetation index (GNDVI), optimized soil-adjusted vegetation index (OSAVI), normalized difference vegetation index (NDVI) and plant senescence reflectance index (PSRI) were sensitive variables for yield remote sensing estimation. Through model development and model validation evaluation, the yield estimation model's coefficients of determination (R2) were 0.81 and 0.74 respectively. The root mean square error (RMSE) were 693.9 kg ha−1 and 786.5 kg ha−1. It showed that the PLS algorithm model estimates the yield better than the linear regression (LR) and principal components analysis (PCA) algorithms. The estimation accuracy was improved by more than 20% than the LR algorithm, and was 13% higher than the PCA algorithm. The results could provide an effective way to improve the estimation accuracy of winter wheat yield by remote sensing, and was conducive to large-area application and promotion. [ABSTRACT FROM AUTHOR]

Climatic tolerance, especially drought tolerance, is one of the major factors shaping the geographic distributions of plant species. Thus, the general decline in rainfall from the Himalaya-Hengduan Mountains (HHM) to the inner Qinghai-Tibet Plateau (QTP) might account for the significant differences in species distributions and richness between the two regions. To test this hypothesis, we conducted a water stress experiment using four Anisodus species (A. tanguticus, A. luridus, A. carniolicoides and A. acutangulus), which were treated with different levels of water stress in a glasshouse, and examined their differences in physiological responses. The results suggest that A. tanguticus, which inhabits the inner QTP, generally has higher fitness under severe water stress than the other species based on its high root:shoot ratio, long-term water use efficiency and photosynthetic rate, indicating that it possesses a genetically based drought tolerance mechanism. Our results suggest that plant species inhabiting the inner QTP may be more drought tolerant than those inhabiting the HHM regions. This provides a new example supporting the hypothesis that climatic tolerance plays a major role in shaping plant distributions on the QTP and its adjacent highlands and presents new insights into the patterns of geographic distribution and diversity of the plants inhabiting these areas. [ABSTRACT FROM AUTHOR]

The present study evaluated the growth response and sugar accumulation of lettuce exposed to different lighting modes of red and blue LED light based on the same daily light integral (7.49 μmol·m−2). Six lighting treatments were performed, that were monochromatic red light (R), monochromatic blue light (B), simultaneous red and blue light as the control (RB, R:B = 1:1), mixed modes of R, B and RB (R/RB/B, 4 h R to 4 h RB and then 4 h B), and alternating red and blue light with alternating intervals of 4 h and 1 h respectively recorded as R/B(4 h) and R/B(1 h). The Results showed that different irradiation modes led to obvious morphological changes in lettuce. Among all the treatments, the highest fresh and dry weight of lettuce shoot were both detected with R/B(1 h), significantly higher than the other treatments. Compared with plants treated with RB, the contents of fructose, glucose, crude fiber as well as the total sweetness index (TSI) of lettuce were significantly enhanced by R treatment; meanwhile, monochromatic R significantly promoted the activities of sucrose degrading enzymes such as acid invertase (AI) and neutral invertase (NI), while obviously reduced the activity of sucrose synthesizing enzyme (SPS). Additionally. The highest contents of sucrose and starch accompanied with the strongest activity of SPS were detected in plants treated with R/B(1 h). The alternating treatments R/B(4 h) and R/B(1 h) inhibited the activity of SS, while enhanced that of SPS compared with the other treatments, indicating that different light environment might influence sugar compositions via regulating the activities of sucrose metabolism enzymes. On the whole, R/B(1 h) was the optimal lighting strategy in terms of lettuce yield, taste and energy use efficiency in the present study. [ABSTRACT FROM AUTHOR]

Chiral zeolitic materials with intrinsically chiral frameworks are highly desired because they can combine both shape selectivity and enantioselectivity. In the field of zeolite, the synthesis of chiral polymorph A of zeolite Beta or chiral polymorph A-enriched zeolite Beta is one of the biggest challenges. We demonstrate here a generalized extremely concentrated fluoride route for the synthesis of chiral polymorph A-enriched zeolite Beta in the presence of five achiral organic structure-directing agents. The polymorph A-enriched Ti-Beta shows a higher enantioselectivity for the asymmetric epoxidation of alkenes than the normal Ti-Beta. [ABSTRACT FROM AUTHOR]

The aim of this study was to validate a criteria-specific long-term survival prediction model (MHCAT) in a large cohort of hepatocellular carcinoma (HCC) patients after liver transplantation (LT) in China. Independent risk factors in MHCAT were retrospectively analysed for HCC patients recorded in the China Liver Transplant Registry. Survival predictions for each patient were calculated using MHCAT scores and the Metroticket formula separately, and the prediction efficacy of MHCAT and Metroticket was compared using the area under ROC curve (c-statistic). A total of 1371 LTs for HCC were analysed in the study, with a median follow-up of 22.2 months (IQR 6.1-72.4 months). The proportions meeting the Milan, UCSF, Fudan and Hangzhou criteria were 34.4%, 39.7%, 44.2% and 51.9%, respectively. The c-statistics for MHCAT predictions of 3- and 5-year survival rates of HCC recipients were 0.712-0.727 and 0.726-0.741, respectively. Among these patients, 1298 LTs for HCC were ultimately selected for the comparison analysis for prediction efficacy. The c-statistic of MHCAT for predictions of 3-year survival with reference to the Milan, UCSF and Fudan criteria was significantly increased compared with that for Metroticket (p < 0.05). In conclusion, MHCAT can effectively predict long-term survival for HCC recipients after LT. [ABSTRACT FROM AUTHOR]