Remediation mechanism of high concentrations of multiple heavy metals in contaminated soil by Sedum alfredii and native microorganisms.

Pollution accident of nonferrous metallurgy industry often lead to serious heavy metal pollution of the surrounding soil. Phytoremediation of contaminated soil is an environmental and sustainable technology, and soil native microorganisms in the process of phytoremediation also participate in the remediation of heavy metals. However, the effects of high concentrations of multiple heavy metals (HCMHMs) on plants and native soil microorganisms remain uncertain. Thus, further clarification of the mechanism of phytoremediation of HCMHMs soil by plants and native soil microorganisms is required. Using the plant Sedum alfredii (S. alfredii) to restore HCMHM-contaminated soil, we further explored the mechanism of S. alfredii and native soil microorganisms in the remediation of HCMHM soils. The results showed that (i) S. alfredii can promote heavy metals from non-rhizosphere soil to rhizosphere soil, which is conducive to the effect of plants on heavy metals. In addition, it can also enrich the absorbed heavy metals in its roots and leaves; (ii) native soil bacteria can increase the abundance of signal molecule-synthesizing enzymes, such as trpE, trpG, bjaI, rpfF, ACSL, and yidC, and promote the expression of the pathway that converts serine to cysteine, then synthesize substances to chelate heavy metals. In addition, we speculated that genes such as K19703, K07891, K09711, K19703, K07891, and K09711 in native bacteria may be involved in the stabilization or absorption of heavy metals. The results provide scientific basis for S. alfredii to remediate heavy metals contaminated soils, and confirm the potential of phytoremediation of HCMHM contaminated soil.

Effects of dissolved organic matter on distribution characteristics of heavy metals and their interactions with microorganisms in soil under long-term exogenous effects.

Long-term waste accumulation (LTWA) in soil not only alters its physical and chemical properties but also affects heavy metals and microorganisms in polluted soil through the dissolved organic matter (DOM) it produces. However, research on the impact of DOM from LTWA on heavy metals and microorganisms in polluted soil is limited, which has resulted in an incomplete understanding of the mechanisms involved in LTWA soils remediation. This study focuses on the DOM generated by waste accumulation and analyses the physicochemical properties, microbial community structure, and vertical distribution of heavy metals in four types of LTWA soils at different depths (0-100 cm). A causal analysis is conducted using structural equation modelling. The results indicate that due to the retention effect of the soil and microorganisms, heavy metal pollution is concentrated on the soil surface layer (>30 cm). With increasing depth, there is a decrease in heavy metal concentration and an increase in microbial diversity and abundance. DOM plays a significant role in regulating the concentration of soil heavy metals and the diversity and abundance of microorganisms. The DOM from different soils gradually transforms into substances dominated by tyrosine, tryptophan, and fulvic acid, which sustain the normal life activities and gene expression of microorganisms. Bacteria such as Pseudarthrobacter, Desulfurivibrio, Thiobacillus, and Sulfurimonas, which are involved in energy transformation, along with genes such as water channel protein and YDIF, which enhance heavy metal metabolism, ensure that microbial communities can maintain basic life processes in polluted environments and gradually select for dominant species that are adapted to heavy metal pollution. These novel discoveries illuminate the potential for modulating the composition of DOM to amplify microbial activity, while concurrently offering insights into the migration patterns of various long-term exogenous pollutants. This foundational knowledge provides a foundation for the development of efficacious remediation strategies.

Food wastewater treatment using a hybrid biofilm reactor: nutrient removal performance and functional microorganisms on filler biofilm and suspended sludge.

In this study, a laboratory-scale hybrid biofilm reactor (HBR) was constructed to treat food wastewater (FWW) before it is discharged into the sewer. The chemical oxygen demand (COD) of 29 860 mg L-1 in FWW was degraded to 200-350 mg L-1 using the HBR under the operating parameters of COD load 1.68 kg m-3 d-1, hydraulic retention time (HRT) of 426.63 h, dissolved oxygen (DO) of 8-9 mg L-1, and temperature of 22-23 °C. The biomass of biofilm on the surface of filler was 2.64 g L-1 for column A and 0.91 g L-1 for column O. Microbial analysis revealed richer and more diverse microorganisms in filler biofilms compared to those in suspended sludge. The hybrid filler was conducive to the development of functional microbial species, including phyla Firmicutes, Actinobacteriota, and Chloroflexi, and genus level norank_f_JG30-KF-CM45, which will improve FWW treatment efficiency. Moreover, the microorganisms on the filler biofilm had more connections and relationships than those in the suspended sludge. The combination of an up-flow anaerobic sludge bed (UASB) and HBR was demonstrated to be an economical strategy for practical applications as a shorter HRT of 118.34 h could be obtained. Overall, this study provides reliable data and a theoretical basis for the application of HBR and FWW treatments.

Floristic changes and environmental drivers of soil fungi and archaea in different salt-tolerant plant communities in the intertidal habitat of coastal wetlands.

Microorganisms are crucial elements of terrestrial ecosystems, which play significant roles in improving soil physicochemical properties, providing plant growth nutrients, degrading toxic and harmful chemicals, and biogeochemical cycling. Variations in the types and quantities of root exudates among different plants greatly alter soil physicochemical properties and result in variations in the diversity, structure, and function of soil microorganisms. Not much is understood about the differences of soil fungi and archaea communities for different plant communities in coastal wetlands, and their response mechanisms to environmental changes. In this study, fungal and archaea communities in soils of Suaeda salsa, Phragmites australis, and Spartina alterniflora in the intertidal habitat of coastal wetlands were selected for research. Soil fungi and archaea were analyzed for diversity, community structure, and function using high throughput ITS and 16S rRNA gene sequencing. The study revealed significant differences in fungi and archaea's diversity and community structure in the rhizosphere soil of three plant communities. At the same time, there is no significant difference in the functional groups. SOM, TP, AP, MC, EC and SOM, TN, TP, AP, MC, EC are the primary environmental determinants affecting changes in soil fungal and archaeal communities, respectively. Variations in the diversity, community structure, and ecological functions of fungi and archaea can be used as indicators characterizing the impact of external disturbances on the soil environment, providing a theoretical foundation for the effective utilization of soil microbial resources, thereby achieving the goal of environmental protection and health promotion.

Highly Efficient Fabrication of Fluorescent "Turn-On" Lateral Flow Strips for Highly Sensitive Detection of Small Molecules Based on Self-Assembly of AuAg Nanoclusters.

Currently, fluorescent "turn-on" lateral flow assay (FONLFA) has shown enhanced "naked eye" detection sensitivity for small molecules, while it is urgent to adopt biocompatible fluorescent nanomaterials and needs new strategies to simplify the preparation process. In this study, a highly effective method was proposed to produce FONLFA strips for the detection of small molecules. The gold-silver nanoclusters (AuAgNCs) were immobilized onto the nitrocellulose membrane of the strips by the self-assembly of poly(sodium 4-styrenesulfonate), antigen, and AuAgNCs. The immobilization process entails a straightforward mixing of the three components, taking merely 1 min, thereby bypassing the necessity for chemical modification of fluorescent nanomaterials. The strategy offers a significantly simplified process, which substantially enhances the efficiency of the strip fabrication. Utilizing this method, a FONLFA was developed for carbendazim with a visual limit of detection (vLOD) reduced by 40-fold compared with the conventional colorimetric lateral flow assay (LFA). Furthermore, the approach demonstrates versatility by enabling the immobilization of AuAgNCs and streptavidin, which facilitates the development of aptamer-based FONLFAs. The designed aptamer-based FONLFA for kanamycin exhibited a 50-fold reduction in the vLOD compared with conventional colorimetric LFAs. Therefore, FONLFA holds promising potential for widespread applications in the analysis of small molecules.

Rapid and ultra-sensitive lateral flow assay for pathogens based on multivalent aptamer and magnetic nanozyme.

Ultra-sensitive LFA methods for pathogen detection commonly depended on tedious and time-consuming nucleic acid amplification. Here, a high affinity multivalent aptamer (multi-Apt) for S. aureus was obtained through exquisite engineering design. The scaffold and conformation of the multi-Apt were found to be key factors in the detection signal of aptsensors. After optimization, the binding affinity of the multi-Apt to S. aureus was improved by more than 8-fold from 135.9 nM to 16.77 nM. By the joint use of the multi-Apt and a multifunctional nanozyme Fe3O4@MOF@PtPd, a fast and ultra-sensitive LFA for S. aureus was developed (termed MA-MN LFA). In this method, a Fe3O4@MOF@PtPd nanozyme was modified with vancomycin and could efficiently capture and separate S. aureus. Moreover, the multi-Apt worked together with the nanozyme to bind with S. aureus to form a ternary complex at the same time, which simply the fabrication of LFA strip. The developed MA-MN LFA could detect S. aureus as low as 2 CFU/mL within 30 min and a wide linear range of 10-1 × 108 CFU/mL was obtained. The detection is easily operated, fast (can be completed within 30 min) and versatile for Gram-positive pathogens, thus has great potential as a powerful tool in pathogen detection.

Fluorescence "turn-on" sensing for five PDE5 inhibitors in functional food based on bimetallic nanoclusters.

Some phosphodiesterase type-5 (PDE5) inhibitors are active ingredients of prescription drugs that are widely used in the treatment of erectile dysfunction (ED). Recently, a large number of substances with this activity have been developed. Illegal addition of PDE5 inhibitors to foods could lead to cardiovascular diseases and even death, which poses a serious threat to food safety, therefore an on-site rapid screening method is urgently needed. Herein, a host functionalized bimetallic nanoclusters, CD/Au Ag NCs, were synthesized through self-assembly of 6-Aza-2-thiothymine gold nanoclusters (ATT-Au NCs), Arginine silver nanoclusters (Arg-Ag NCs) and carboxymethyl ß-cyclodextrin (ß-CMCD). The introduction of Rhodamine 6G (R6G) could quench the fluorescence of CD/Au Ag NCs based on the inner filter effect (IFE) and fluorescence resonance energy transfer effect (FRET). Importantly, it was discovered that several PDE5 inhibitors exhibited a higher binding affinity to ß-CMCD and could displace R6G binding with CD cavity, which disrupted the fluorescence quenching effects and resulted in the fluorescence recovery of CD/Au Ag NCs. This fluorescence turn-on signal could be utilized for the detection of PDE5 inhibitors. At present, emerging PDE5 inhibitor analogues pose a great challenge to food safety due to their unknown efficacy and safety. The proposed method holds the advantages of high sensitivity, simple probe synthesis, easy operation, and simultaneous detection of multiple PDE5 inhibitors. Meanwhile, the successful application in functional food sample demonstrated its high application potential in multiple PDE5 inhibitors screening.

Material Classification and Aging Time Prediction of Structural Metals Using Laser-Induced Breakdown Spectroscopy Combined with Probabilistic Neural Network.

In this paper, laser-induced breakdown spectroscopy (LIBS) combined with a probabilistic neural network (PNN) was applied to classify engineering structural metal samples (valve stem, welding material, and base metal). Additionally, utilizing data from the plasma emission spectrum generated by laser ablation of samples with different aging times, an aging time prediction model based on a firefly optimized probabilistic neural network (FA-PNN) was established, which can effectively evaluate the service performance of structural materials. The problem of insufficient features obtained by principal component analysis (PCA) for predicting the aging time of materials is addressed by the proposal of a time-frequency feature extraction method based on short-time Fourier transform (STFT). The classification accuracy (ACC) of time-frequency features and principal component features was compared under PNN. The results indicate that, in comparison to the PCA feature extraction approach, the time-frequency feature extraction method based on STFT demonstrates higher accuracy in predicting the time of aging materials. Then, the relationship between classification accuracy (ACC) and settings of PNN was discussed. The ACC of the PNN model for both the material classification test set and the aging time test set achieved 100% with Firefly (FA) optimization algorithms. This result was also compared with the ACC of ANN, KNN, PLS-DA, and SIMCA for the aging time test set (95%, 87.5%, 85%, and 62.5%, respectively). The experimental results demonstrated that the classification model using LIBS combined with FA-PNN could realize better classification accuracy.

Step-feeding food waste fermentation liquid as supplementary carbon source for low C/N municipal wastewater treatment: Bench scale performance and response of microbial community.

Municipal wastewater treatment often lacks carbon source, while carbon-rich organics in food waste are deficiently utilized. In this study, the food waste fermentation liquid (FWFL) was step-fed into a bench-scale step-feed three-stage anoxic/aerobic system (SFTS-A/O), to investigate its performance in nutrients removal and the response of microbial community as a supplementary carbon source. The results showed that the total nitrogen (TN) removal rate increased by 21.8-109.3% after step-feeding FWFL. However, the biomass of the SFTS-A/O system was increased by 14.6% and 11.9% in the two phases of the experiment, respectively. Proteobacteria was found to be the dominant functional phyla induced by FWFL, and the increase of its abundance attributed to the enrichment of denitrifying bacteria and carbohydrate-metabolizing bacteria was responsible for the biomass increase. Azospira belonged to Proteobacteria phylum was the dominant denitrifying genera when step-fed with FWFL, its abundance was increased from 2.7% in series 1 (S1) to 18.6% in series 2 (S2) and became the keystone species in the microbial networks. Metagenomics analysis revealed that step-feeding FWFL enhanced the abundance of denitrification and carbohydrates-metabolism genes, which were encode mainly by Proteobacteria. This study constitutes a key step towards the application of FWFL as a supplementary carbon source for low C/N municipal wastewater treatment.

Ratiometric fluorescent detection of carbendazim in foods based on metallic nanoclusters self-assembled nanocomplex.

Indicator replacement assay combining with fluorescence resonance energy transfer (FRET) effect has attractive performance in sensing small molecules, however, there wasn't application in pesticide molecule sensing reported so far. In this work, we prepared a nanocomplex (NCP), AuAgNCs-CD, through self-assembly of gold nanoclusters (AuNCs), silver nanoclusters (AgNCs) and carboxymethyl-ß-cyclodextrin (CM-ß-CD) by one-step method. The emission of AuNCs was significantly enhance. It was found that FRET between the AuAgNCs-CD and rhodamine B (RhB) existed after AuAgNCs-CD combined with RhB. And carbendazim (CBZ) could induce anti-FRET effect through competing with RhB and binding to AuAgNCs-CD. Thus, this phenomenon was utilized to develop a ratiometric fluorescent detection of CBA. This method was applied in food sample detection and reliable results were obtained. Due to high sensitivity, rapidness and good selectivity, this ratiometric fluorescent method was expected to hold high application potential in monitoring CBZ in foods.

Highly Sensitive Fluorescence Detection of Three Organophosphorus Pesticides Based on Highly Bright DNA-Templated Silver Nanoclusters.

It is still challenging to achieve simultaneous and sensitive detection of multiple organophosphorus pesticides (OPs). Herein, we optimized the ssDNA templates for the synthesis of silver nanoclusters (Ag NCs). For the first time, we found that the fluorescence intensity of T base-extended DNA-templated Ag NCs was over three times higher than the original C-riched DNA-templated Ag NCs. Moreover, a "turn-off" fluorescence sensor based on the brightest DNA-Ag NCs was constructed for the sensitive detection of dimethoate, ethion and phorate. Under strong alkaline conditions, the P-S bonds in three pesticides were broken, and the corresponding hydrolysates were obtained. The sulfhydryl groups in the hydrolyzed products formed Ag-S bonds with the silver atoms on the surface of Ag NCs, which resulted in the aggregation of Ag NCs, following the fluorescence quenching. The fluorescence sensor showed that the linear ranges were 0.1-4 ng/mL for dimethoate with a limit of detection (LOD) of 0.05 ng/mL, 0.3-2 µg/mL for ethion with a LOD of 30 ng/mL, and 0.03-0.25 µg/mL for phorate with a LOD of 3 ng/mL. Moreover, the developed method was successfully applied to the detection of dimethoate, ethion and phorate in lake water samples, indicating a potential application in OP detection.

Effect of microbial network complexity and stability on nitrogen and sulfur pollutant removal during sediment remediation in rivers affected by combined sewer overflows.

Discovering the complexity and improving the stability of microbial networks in urban rivers affected by combined sewer overflows (CSOs) is essential for restoring the ecological functions of urban rivers, especially to improve their ability to resist CSO impacts. In this study, the effects of sediment remediation on the complexity and stability of microbial networks was investigated. The results revealed that the restored microbial community structure using different approaches in the river sediments differed significantly, and random matrix theory showed that sediment remediation significantly affected microbial networks and topological properties; the average path distance, average clustering coefficient, connectedness, and other network topological properties positively correlated with remediation time and weakened the small-world characteristics of the original microbial networks. Compared with other sediment remediation methods, regulating low dissolved oxygen (DO) shifts the microbial network module hubs from Actinobacteria and Bacteroidetes to Chloroflexi and Proteobacteria. This decreases the positive association of networks by 17%-18%, which intensifies the competitiveness among microorganisms, further weakening the influence and transmission of external pressure across the entire microbial network. Compared with that of the original sediment, the vulnerability of the restored network was reduced by more than 36%, while the compositional stability was improved by more than 12%, with reduced fluctuation in natural connectivity. This microbial network succession substantially increased the number of key enzyme-producing genes involved in nitrogen and sulfur metabolism, enhancing nitrification, denitrification, and assimilatory sulfate reduction, thereby increasing the removal rates of ammonia, nitrate, and acid volatile sulfide by 43.42%, 250.68% and 2.66%, respectively. This study comprehensively analyzed the succession patterns of microbial networks in urban rivers affected by CSOs before and after sediment remediation, which may provide a reference for reducing the impact of CSO pollution on urban rivers in the subsequent stages.

Biomanipulation as a strategy for minimizing ecological risks in river supplied with reclaimed water.

Reclaimed water is an effective method for addressing water pollution and shortages. However, its use may contribute to the collapse of receiving water (algal blooms and eutrophication) owing to its unique characteristics. A three-year biomanipulation project was conducted in Beijing to investigate the structural changes, stability, and potential risks to aquatic ecosystems associated with the reuse of reclaimed water in rivers. During the biomanipulation, the proportion of Cyanophyta in the community structure of phytoplankton density in river supplied with reclaimed water decreased, and the community composition shifted from Cyanophyta and Chlorophyta to Chlorophyta and Bacillariophyta. The biomanipulation project increased the number of zoobenthos and fish species and significantly increased fish density. Despite the significant difference in aquatic organisms community structure, diversity index and community stability of aquatic organisms remained stable during the biomanipulation. Our study provides a strategy for minimizing the hazards of reclaimed water through biomanipulation by reconstructing the community structure of reclaimed water, thereby making it safe for large-scale reuse in rivers.

Blue LED light induces cytotoxicity via ROS production and mitochondrial damage in bovine subcutaneous preadipocytes.

The purpose of this study was to investigate the effect and mechanism of blue light irradiation on bovine subcutaneous preadipocytes. In this study, preadipocytes were divided into dark group (control) and blue light group. Results show that blue light exposure time-dependently reduced the viability of preadipocytes and induced mitochondrial damage, in accompaniment with the accumulation of intracellular reactive oxygen species (ROS). Meanwhile, blue light caused oxidative stress, as evidenced by the increased MDA level, the reduced T-AOC contents, as well as the decreased activities of antioxidant enzymes. Additionally, blue light treatment induced apoptosis and G2/M phase arrest via Bcl-2/Bax/cleaved caspase-3 pathway and P53/GADD45 pathway, respectively. Protein expressions of LC3-II/LC3-I and P62 were up-regulated under blue light exposure, indicating blue light initiated autophagy but impeded autophagic degradation. Moreover, blue light caused an increase in the secretion of pro-inflammatory factors (TNF-α, IL-1ß, and IL-6). Pretreatment with N-acetylcysteine (NAC), a potent ROS scavenger, restored the loss of mitochondrial membrane potential (Δψ) and reduced excess ROS. Additionally, the above negative effects of blue light on cells were alleviated after NAC administration. In conclusion, this study demonstrates blue light induces cellular ROS overproduction and Δψ depolarization, resulting in the decrease of cell viability and the activation of apoptosis, autophagy, and inflammation, providing a reference for the application of blue light in the regulation of fat cells in the future.

Ursolic acid augments the chemosensitivity of drug-resistant breast cancer cells to doxorubicin by AMPK-mediated mitochondrial dysfunction.

Multidrug resistance remains the major obstacle to successful therapy for breast carcinoma. Ursolic acid (UA), a triterpenoid compound, has been regarded as a potential neoplasm chemopreventive drug in some preclinical studies since it exerts multiple biological activities. In this research, we investigated the role of UA in augmenting the chemosensitivity of drug-resistant breast carcinoma cells to doxorubicin (DOX), and we further explored the possible molecular mechanisms. Notably, we found that UA treatment led to inhibition of cellular proliferation and migration and cell cycle arrest in DOX-resistant breast cancers. Furthermore, combination treatment with UA and DOX showed a stronger inhibitory effect on cell viability, colony formation, and cell migration; induced more cell apoptosis in vitro; and generated a more potent inhibitory effect on the growth of the MCF-7/ADR xenograft tumor model than DOX alone. Mechanistically, UA effectively increased p-AMPK levels and concomitantly reduced p-mTOR and PGC-1α protein levels, resulting in impaired mitochondrial function, such as mitochondrial respiration inhibition, ATP depletion, and excessive reactive oxygen species (ROS) generation. In addition, UA induced a DNA damage response by increasing intracellular ROS production, thus causing cell cycle arrest at the G0/G1 phase. UA also suppressed aerobic glycolysis by prohibiting the expression and function of Glut1. Considered together, our data demonstrated that UA potentiated the susceptibility of DOX-resistant breast carcinoma cells to DOX by targeting energy metabolism through the AMPK/mTOR/PGC-1α signaling pathway, and it is a potential adjuvant chemotherapeutic candidate in MDR breast cancer.

Label-Free Fluorescent Turn-On Glyphosate Sensing Based on DNA-Templated Silver Nanoclusters.

In this work, a label-free fluorescent detection method for glyphosate, based on DNA-templated silver nanoclusters (DNA-Ag NCs) and a Cu2+-ion-modulated strategy, was developed. In the presence of Cu2+, the fluorescence of the DNA-Ag NCs was quenched. Glyphosate can restore the fluorescence of DNA-Ag NCs. By analyzing the storage stability of the obtained DNA-Ag NCs using different DNA templates, specific DNA-Ag NCs were selected for the construction of the glyphosate sensor. The ultrasensitive detection of glyphosate was achieved by optimizing the buffer pH and Cu2+ concentration. The sensing of glyphosate demonstrated a linear response in the range of 1.0-50 ng/mL. The limit of detection (LOD) was 0.2 ng/mL. The proposed method was successfully applied in the detection of glyphosate in a real sample, indicating its high application potential for glyphosate detection.

Candidate metabolite markers of peripheral neuropathy in Chinese patients with type 2 diabetes.

OBJECTIVES: To analyze the serum and urine metabolites present in type 2 diabetes mellitus (T2DM) patients and T2DM patients with diabetic peripheral neuropathy (DPN) and to select differentially expressed biomarkers for early diagnosis of DPN. METHODS: Serum and urine metabolites from 74 T2DM patients with peripheral neuropathy and 41 without peripheral neuropathy were analyzed using gas chromatograph system with time-of-flight mass spectrometer metabolomics to detect biomarkers of peripheral neuropathy in T2DM. RESULTS: There were increased serum triglycerides, alanine aminotransferase, and decreased C-peptide, and total cholesterol levels in T2DM patients with DPN compared to those without peripheral neuropathy. Metabolomic analysis revealed visible differences in metabolic characteristics between two groups, and overall 53 serum differential metabolites and 56 urine differential metabolites were identified with variable influence on projection (VIP) >1 and P<0.05. To further analyze the correlation between the identified metabolites and DPN, four serum metabolites and six urine metabolites were selected with VIP>2, and fold change (FC) >1, including serum ß-alanine, caproic acid, ß-alanine/L-aspartic acid, and L-arabinose/L-arabitol, and urine gluconic acid, erythritol, galactonic acid, guanidoacetic acid, cytidine, and aminoadipic acid. Furthermore, five serum biomarkers and six urine biomarkers were found to show significant changes (P<0.05, VIP>1, and FC>1) respectively in patients with mild, moderate, and severe DPN. In addition, we found that glyoxylate and dicarboxylate metabolism was a differential metabolic pathway not only between T2DM and DPN, but also among different degrees of DPN. The differential metabolites such as ß-alanine and caproic acid are expected to be biomarkers for DPN patients, and the significant changes in glyoxylate and dicarboxylate metabolism may be related to the pathogenesis of DPN. CONCLUSION: There were serum and urine spectrum metabolomic differences in patients with DPN, which could serve as biomarkers for T2DM and DPN patients.

Identification of tourists' dynamic risk perception-the situation in Tibet.

This paper proposes an identification framework for dynamic risk perception with "Questions & Answers (Q&As) + travel notes", which newly attends to the dynamic nature of risk perception and overcomes the liabilities of traditional data collection methods, such as questionnaires and interviews, which induce high costs in data acquisition, tend to produce small sample sizes and suffer from large sample deviations. Via 2627 Q&As released by tourists before travel and 17,523 travel notes released by tourists after travel, the dynamic change in 20 identified risks before and after travel to Tibet is portrayed with the help of text mining technologies, which can automatically identify risk perception types and sentiment tendencies from massive amounts of textual data. The study finds that before travel, tourists usually underestimate risks related to safety, health and time but overestimate risks related to transportation, route selection and season. The results of the study are not only informative for destination tourism risk management and image promotion but also important for tourists to form more reasonable risk assessments.

Microbial mechanisms of refractory organics degradation in old landfill leachate by a combined process of UASB-A/O-USSB.

A combined process of anaerobic digestion (UASB), shortcut nitrification-denitrification (A/O), and semi-anoxic co-metabolism (operated by an up-flow semi-anoxic sludge bed; USSB) was constructed for the treatment of old landfill leachate (>10 years). The performance and mechanism of refractory organics degradation by the combined process (UASB-A/O-USSB) were investigated. The results showed that the semi-anoxic co-metabolism contributes 57 % of the totally degraded refractory organics. Specific microorganisms and their corresponding metabolic functions drive the degradation of refractory organics in each unit of the UASB-A/O-USSB process. In detail, organics with simple molecular structures were preferentially degraded by anaerobic digestion and shortcut denitrification, whereas those with complex structures were subsequently degraded in the oxic tanks and USSB reactor by shortcut nitrification and semi-anoxic co-metabolism. The structural equation model showed that the combined process of shortcut nitrification and semi-anoxic co-metabolism had a better effect on the degradation of recalcitrant organics than the single process. These findings provide information on how refractory organics are metabolically degraded in a combined process.

Improved bat algorithm for roundness error evaluation problem.

In the production and processing of precision shaft-hole class parts, the wear of cutting tools, machine chatter, and insufficient lubrication can lead to changes in their roundness, which in turn affects the overall performance of the relevant products. To improve the accuracy of roundness error assessments, Bat algorithm (BA) is applied to roundness error assessments. An improved bat algorithm (IBA) is proposed to counteract the original lack of variational mechanisms, which can easily lead BA to fall into local extremes and induce premature convergence. First, logistic chaos initialisation is applied to the initial solution generation to enhance the variation mechanism of the population and improve the solution quality; second, a sinusoidal control factor is added to BA to control the nonlinear inertia weights during the iterative process, and the balance between the global search and local search of the algorithm is dynamically adjusted to improve the optimization-seeking accuracy and stability of the algorithm. Finally, the sparrow search algorithm (SSA) is integrated into BA, exploiting the ability of explorer bats to perform a large range search, so that the algorithm can jump out of local extremes and the convergence speed of the algorithm can be improved. The performance of IBA was tested against the classical metaheuristic algorithm on eight benchmark functions, and the results showed that IBA significantly outperformed the other algorithms in terms of solution accuracy, convergence speed, and stability. Simulation and example verification show that IBA can quickly find the centre of a minimum inclusion region when there are many or few sampling points, and the obtained roundness error value is more accurate than that of other algorithms, which verifies the feasibility and effectiveness of IBA in evaluating roundness errors.