Scientific Basis Research Articles

Extraction, Isolation Characterization and Antiasthamatic Activity of The Leaves of Abelmoschus Esculenutus (okra)

Aims: The aim of study was to evaluate the scientific basis for the traditional use of Amebelmoschus esculentus leaves. Materials and Methods: In the present study, petroleum ether extract of Abelmoschus esculentus leaves was evaluated for preliminary phytochemical screening and antiasthmatic activity using histamine induced bronchospasm and histamine induced constriction on isolated goat tracheal chain at different dose levels. Student's t-Test and Dunett's test were used for statistical analysis. Results: The result of present investigation showed that the petroleum ether extract of Abelmoschus esculentus significantly (P<0.001) decreased the bronchospasm induced by histamine and It also decreased the histamine induce constriction on isolated goat trachea in dose-dependent manner. Phytochemical studies revealed the presence of flavonoids, and phenolic compounds in the extract. Conclusions: The present study concludes that the antiasthmatic activity of ethanolic extract of A.esculentus leaves may be due to the presence of flavonoids, Alkaloids glycosides, tannins, protein. Antiasthmatic action of the A. esculentus could be due to its antihistaminic, anticholinergic and mast-cell-stabilizing property.

From KMS Fusion to HB11 Energy and Xcimer Energy, a personal 50 year IFE perspective

Shortly after the laser was invented in 1960, scientists sought to use it for thermonuclear fusion. By 1963, Livermore had a classified laser inertial confinement fusion (ICF) program and leaders predicted scientific breakeven by 1973. In 1974, KMS Fusion, Inc. announced thermonuclear neutrons from a laser target and promised grid electricity within 10 years. Private capital was attracted, but the data fell far short of the optimistic simulations. Magnetic fusion energy has had civilian funding (DOE), while ICF has primarily received military funding (DOE Defense Programs and now NNSA). As bigger lasers have been built and better simulations performed, optimism about ICF breakeven has waxed and waned. The achievement of ignition and gain on NIF has validated ICF's scientific basis, and the DOE and venture capital funded private companies are again interested in inertial fusion energy (IFE). The new DOE Milestone-Based Fusion Development Program is creating public–private partnerships to accelerate progress toward fusion pilot plants. ARPA-E, DOE INFUSE, and DOE IFE STAR are also building a U.S. IFE program within DOE. The U.S. leads in ICF, but developing IFE is an international competition. Private companies are leading the way. HB11 Energy Pty Ltd. is pursuing the aneutronic proton–boron fuel cycle. Xcimer Energy is developing a disruptive IFE technology to achieve high laser energies at dramatically lower costs. This 50-year perspective discusses where the U.S. IFE program is headed and promising strategies for progress in establishing an effective U.S. IFE program from both public and private perspectives.

Construction of a Cu@hollow TS‐1 nanoreactor based on a hierarchical full‐spectrum solar light utilization strategy for photothermal synergistic artificial photosynthesis

AbstractThe artificial photosynthesis technology has been recognized as a promising solution for CO2 utilization. Photothermal catalysis has been proposed as a novel strategy to promote the efficiency of artificial photosynthesis by coupling both photochemistry and thermochemistry. However, strategies for maximizing the use of solar spectra with different frequencies in photothermal catalysis are urgently needed. Here, a hierarchical full‐spectrum solar light utilization strategy is proposed. Based on this strategy, a Cu@hollow titanium silicalite‐1 zeolite (TS‐1) nanoreactor with spatially separated photo/thermal catalytic sites is designed to realize high‐efficiency photothermal catalytic artificial photosynthesis. The space–time yield of alcohol products over the optimal catalyst reached 64.4 μmol g−1 h−1, with the selectivity of CH3CH2OH of 69.5%. This rationally designed hierarchical utilization strategy for solar light can be summarized as follows: (1) high‐energy ultraviolet light is utilized to drive the initial and difficult CO2 activation step on the TS‐1 shell; (2) visible light can induce the localized surface plasmon resonance effect on plasmonic Cu to generate hot electrons for H2O dissociation and subsequent reaction steps; and (3) low‐energy near‐infrared light is converted into heat by the simulated greenhouse effect by cavities to accelerate the carrier dynamics. This work provides some scientific and experimental bases for research on novel, highly efficient photothermal catalysts for artificial photosynthesis.

Evaluation of the key ingredient from the main production areas of Phellodendri Amurensis Cortex using ultra-high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry and ultra-high-performance liquid chromatography coupled to triple-quadrupole mass spectrometry.

Phellodendri Amurensis Cortex (PAC) is a medicinal herb that has been generally used to treat diarrhea and jaundice. In order to comprehensively evaluate the PAC in the main production areas quality, a qualitative and quantitative method with highly effective, sensitive, and reliable was developed. The chemical compositions of PAC were analyzed, and fingerprints were established by ultra-high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS). Then, the determination of berberine, canthin-6-one, dictamnine, γ-fagarine, and magnoflorine from PAC samples was simultaneously performed using UPLC-QQQ-MS. Furthermore, the chemical components of PAC from different regions were compared and analyzed by combining hierarchical cluster analysis, principal component analysis, and orthogonal partial least squares discriminant analysis. A total of 58 compounds were identified, including 36 alkaloids, four phenylpropanoids, seven terpenoids, four flavonoids and their glycosides, an organic acid compound, and six other components. The fingerprint results show that samples have good similarity. Meanwhile, the content of the five ingredients in different habitats is quite different. By multivariate statistical analysis, 18 batches of PAC could be divided into three categories, and 20 components were identified as differential markers of various origins. A comprehensive method of PAC quality evaluation and chemical composition difference analysis was established, which provided the scientific basis for quality evaluation and further pharmacological mechanism research.

Spatiotemporal Changes of Center Pivot Irrigation Farmland in the Mu Us Region and Its Impact on the Surrounding Vegetation Growth

Accurately understanding the distribution and changing trends of Center Pivot Irrigation (CPI) farmland in the Mu Us region and exploring the impact of CPI farmland construction on sandy land vegetation growth hold significant importance for local sustainable development. By using Landsat images to extract CPI farmland information and applying buffer zone analysis to explore the impact of CPI farmland construction on the surrounding vegetation growth, the results revealed the following key findings: (1) The number and area of CPI farmland units showed a continuous growth trend from 2008 to 2022. Spatially, Etoke Front Banner was the focal point of the CPI farmland unit construction, gradually expanding outward. In terms of scale, small-scale CPI farmland units (0–0.2 km2) dominated, while large-scale CPI farmland units (>0.4 km2) were primarily distributed in Yulin City (Mu Us). (2) The growth rate of CPI farmland units in Yulin City gradually slowed down, while that in Ordos City (Mu Us) continued to exhibit a high growth trend. Affected by water-resource pressure and policies, CPI farmland units in Ordos City may continue to increase in the future, while they may stop growing or even show a downward trend in Yulin City. (3) CPI farmland mainly came from the conversion of cultivated land, but over time, more and more grassland was reclaimed as CPI farmland. The absence of cover planting after crop harvesting and the lack of shelterbelt construction may exacerbate land desertification in the region. (4) Within the typical region, CPI farmland unit construction promoted vegetation growth within the CPI units and the 500 m buffer zone but had an inhibitory effect on vegetation growth within the 500–3000 m buffer zone and no significant effect on vegetation growth within the 3000–5000 m buffer zone. (5) The decrease in groundwater reserves caused by CPI farmland unit construction was the primary reason for inhibiting the vegetation growth within the 500–3000 m buffer zone of CPI farmland units in the Mu Us region. This study can provide a scientific basis for the sustainable development of CPI farmland in semi-arid areas.

Evaluation metric of smile classification by peri-oral tissue segmentation for the automation of digital smile design

ObjectivesThis study aimed to develop and validate evaluation metric for an automated smile classification model termed the “smile index.” This innovative model uses computational methods to numerically classify and analyze conventional smile types. MethodsThe datasets used in this study consisted of 300 images to verify, 150 images to validate, and 9 images to test the evaluation metric. Images were annotated using Labelme. Computational techniques were used to calculate smile index values for the study datasets, and the resulting values were evaluated in three stages. ResultsThe smile index successfully classified smile types using cutoff values of 0.0285 and 0.193. High accuracy (0.933) was achieved, along with an F1 score greater than 0.09. The smile index successfully reclassified smiles into six types (low, low-to-medium, medium, medium-to-high, high, and extremely high smiles), thereby providing a clear distinction among different smile characteristics. ConclusionThe smile index is a novel dimensionless parameter for classifying smile types. The index acts as a robust evaluation tool for artificial intelligence models that automatically classify smile types, thereby providing a scientific basis for largely subjective aesthetic elements. Clinical significanceThe computational approach employed by the smile index enables quantitative numerical classification of smile types. This fosters the application of computerized methods in quantifying and analyzing real smile characteristics observed in clinical practice, paving the way for a more objective evidence-based approach to aesthetic dentistry.

Molecular mechanism of Caulis Spatholobi in the treatment of Chronic Myeloid Leukemia based on Network Pharmacology and Experimental Verification.

This study aimed to predict the relevant targets of the treatment of chronic myeloid leukemia (CML) with Caulis Spatholobi by applying the network pharmacology method, and in vitro cell experiments were conducted to verify the mechanism of Caulis Spatholobi in the treatment of CML. TCMSP, ETCM, Genecards, and GisGeNET databases were used to obtain relevant targets of Caulis Spatholobi in the treatment of CML. Go and KEGG analyses were performed using the David database. Using Cytoscape 3.7.2, the "active compounds-targets-pathways" network was constructed. Further validation was carried out by pharmacological experiments in vitro. The proliferation and apoptosis of K562 cells were observed by the MTT method and Hoechst 33242 fluorescence staining method. The predicted targets and their related signal pathways were verified by western blotting. In this study, 18 active compounds and 43 potential targets were obtained. The results of the MTT method showed that compared with the normal control group, 62.5-500 μg/mL alcohol extract of Caulis Spatholobi had an obvious inhibitory effect on K562 and the IC50 value was less than 100 μg/mL. The Hoechst 33242 fluorescence staining method showed that the alcohol extract of Caulis Spatholobi could promote apoptosis. The results of western blotting showed that compared with the normal control group, the expressions of Bax and Caspase-3 proteins in the 62.5 and 125 μg/mL alcohol extract of Caulis Spatholobi groups were significantly up-regulated (P<0.05). The expression of Bcl-2 in the 125 μg/mL alcohol extract of the Caulis Spatholobi group was significantly down-regulated (P<0.01), and the expression of Bcl-2 in the 62.5 and 31.25 μg/mL alcohol extract of Caulis Spatholobi groups was also significantly down-regulated (P<0.05). It showed that the ethanol extract of Caulis Spatholobus could promote apoptosis by up-regulating the expression of Bax and caspase-3 and down-regulating the expression of the Bcl-2 protein. The treatment of Caulis Spatholobi for CML has the characteristics of multi-targets and multi-pathways. The results of in vitro pharmacological experiments demonstrated that its mechanism of action might be based on the expression of key target proteins, such as Caspase-3, Bcl-2, and Bax, thereby inhibiting cell proliferation and promoting cell apoptosis, which provides a scientific basis for the treatment of CML.

The Effect of Familism Emotions on Post-Traumatic Growth Among the Elderly in China: The Mediating Roles of Taoist Personality and Sense of Community.

Post-traumatic growth is a significant social issue in the management of active aging in elderly people. This study investigates the influence of familism emotions on post-traumatic growth (PTG) of the elderly, and the mediating role of Taoist personality and sense of community (SOC) therein, to provide a scientific basis for the development of positive aging in the elderly. A cross-sectional study was conducted in several communities of Hubei Province in China. A total of 338 elderly people were investigated with the Familism Emotion Scale, PTG Scale, Taoist Personality Scale and SOC Scale. SPSS 23.0 was used to derive descriptive statistics and conduct a common method bias test, Pearson correlation analysis, and multiple stepwise regression analysis. Mplus 7.3 was used for structural equation modeling to test the significance of parallel mediation effects on the data. The results show that: (1) Familism emotions, Taoist personality and SOC are positively correlated with PTG; (2) Familism emotions, Taoist personality and SOC can all positively predict PTG in the elderly; (3) Both Taoist personality and SOC partially mediated the link between familism emotions and PTG in the elderly. In the context of particularly constraining societal events such as COVID-19, it is necessary to pay careful attention to the impact of external environmental influences upon the elderly, such as family and community, and to encourage elderly people to cultivate a more Taoist personality. The formation of a Taoist personality offers a promising new focus for research in elderly healthcare.

Mechanism of inhibition of growth and metastasis of colon cancer by celecoxib analog OSU-03013 via wnt signaling pathway

OSU-03013 is a structurally modified analog of celecoxib. This study probed the antitumor activity of OSU-03013 on colon cancer (CC) and explored its possible mechanism. CCK-8 method was used to evaluate the activity of OSU-03013 on CC cell SW480 and normal colon epithelial cell FHC, and the anti-proliferation effect of OSU-03013 was detected by CCK-8 and colony formation assay. In addition, flow cytometry and Annexin V-FITC/PI were applied to detect apoptosis of SW480 cells, and Transwell was to detect cell migration and invasion. β-catenin, c-myc, and Wnt1 genes were assessed by RT-qPCR, and E-cadherin, N-cadherin, and β-catenin, c-myc, mTOR, p-mTOR, and Wnt1 proteins were detected by Western Blot. OSU-03013 had dose-dependent and time-dependent antitumor activity on SW480 cells, which can promote tumor cell apoptosis, up-regulate E-cadherin, and down-regulate β-catenin, c-myc, Wnt1, and N-cadherin. OSU-03013 has anti-tumor activity on CC cells. The anti-cancer mechanism of OSU-03013 is achieved by inhibiting the activation of Wnt pathway genes and inhibiting tumor invasion and metastasis. This study provides a scientific basis for the clinical application of OSU-03013 in the treatment of CC.

Distribution, Source, and Ecological Risk of Heavy Metals in Sewage Irrigation of Taiyuan, Shanxi Province, China.

The pollution of agricultural soil by heavy metals is a significant environmental issue that has a serious impact on human health and food security. This study focused on investigating the presence of heavy metal pollution in sewage-irrigated soils in Taiyuan city. A total of 110 soil samples were analyzed for the presence of As, Hg, Cd, Pb, Cr, Cu and Zn. The results showed that the concentrations of these metals ranged from 0.06 to 26.74 mg/kg for As, 0.00 to 0.84 mg/kg for Hg, 0.03 to 0.69 mg/kg for Cd, 44.32 to 100.09 mg/kg for Pb, 9.85 to 42.19 mg/kg for Cr, 13.38 to 53.72 mg/kg for Cu, and 42.77 to 145.47 mg/kg for Zn. The average concentrations of these metals were found to be below the risk values specified in the "Soil environmental quality (GB15618-2018)", except for As and Cd in three sampling points in Xiaodian District. The heavy metal pollution in these areas can be attributed to various sources, such as industrial activities, the use of fertilizers and pesticides, and the irrigation process. According to the geo-accumulation index, the agricultural soil in the Taiyuan irrigation area was found to be uncontaminated by Zn, Cr, Cu, and As, and lightly contaminated by Cd, Hg, and Pb. The Nemerow Pollution Index indicated that the soil at all sampling points exhibited a slight level of pollution. Moreover, the ecological risk assessment indicated that all heavy metals posed a slight level of pollution. The findings of this study provide a scientific basis for the development of effective policies and measures for soil environmental protection and pollution control.

Risk analysis of serum chemical residues for metabolic associated fatty liver disease based on exposome-lipidome wide association study

Metabolic associated fatty liver disease (MAFLD) is a common liver disease with a prevalence of up to 25%; it not only adversely affects human health but also aggravates the economic burden of society. An increasing number of studies have suggested that the occurrence of chronic noncommunicable diseases is affected by both environmental exposures and genetic factors. Research has also shown that environmental pollution may increase the risk of MAFLD and promote its occurrence and development. However, the relationship between these concepts, as well as the underlying exposure effects and mechanism, remains incompletely understood. Lipidomics, a branch of metabolomics that studies lipid disorders, can help researchers investigate abnormal lipid metabolites in various disease states. Lipidome-exposome wide association studies are a promising paradigm for investigating the health effects of cumulative environmental exposures on biological responses, and could provide new ideas for determining the associations between metabolic and lipid changes and disease risk caused by chemical-pollutant exposure. Hence, in this study, targeted exposomics and nontargeted lipidomics studies based on ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) and ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) were used to characterize exogenous chemical pollutants and endogenous lipid metabolites in the sera of patients with MAFLD and healthy subjects. The results demonstrated that fipronil sulfone, malathion dicarboxylic acid, and monocyclohexyl phthalate may be positively associated with the disease risk of patients diagnosed as simple fatty liver disease (hereafter referred to as MAFLD(0)). Moreover, fipronil sulfone, acesulfame potassium, perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluoroundecanoic acid (PFUnDA), 4-hydroxybenzophenone, and 3,5-di-tert-butyl-4-hydroxybenzoic acid (DBPOB) may be positively associated with the disease risk of patients diagnosed as fatty liver complicated by single or multiple metabolic disorders. Association analysis was carried out to explore the lipid metabolites induced by chemical residues. Triglyceride (TG) and diglyceride (DG) were significantly increased in MAFLD and MAFLD(0). The numbers of carbons of significantly changed DGs and TGs were mainly in the ranges of 32-40 and 35-60, respectively, and both were mainly characterized by changes in polyunsaturated lipids. Most of the lipid-effect markers were positively correlated with chemical residues and associated with increased disease risk. Our research provides a scientific basis for studies on the association and mechanism between serum chemical-pollutant residues and disease outcomes.

Research on Collaborative Evaluation of Offshore Wind Power Value Chain in Guangxi-Based on BWM-FVIKOR Model

With the dynamic development of the offshore wind power industry and the global value chain, the traditional wind power industry is gradually turning to the offshore wind power value chain system that focuses on the value effect of the value chain, and it is of great significance to carry out value chain collaborative evaluation research. This paper puts forward the evaluation index system of Guangxi offshore wind power value chain from the comprehensive system dimension, key node dimension, subject contribution dimension and resource endowment dimension, builds the BWM-FVIKOR evaluation model, and proves the validity of the evaluation index and the feasibility of the evaluation model through example analysis, and this paper provides scientific and effective decision-making basis for the coordination of Guangxi offshore wind power value chain.

Cooperative Exploration Model of Coal–Gallium Deposit: A Case Study of the Heidaigou Coal–Gallium Deposit in the Jungar Coalfield, Inner Mongolia, China

Gallium (Ga) is a typical scattered trace element that is irreplaceable in strategic sectors such as national defense, wireless communications, new materials, renewable energy, and healthcare. The coal–Ga deposit is an important complement to traditional Ga resources and has become a significant focus for Ga mineral resource exploration. Therefore, there is an urgent need to research the coal–Ga cooperative exploration model from both technical and economic perspectives. Taking the Heidaigou coal–Ga deposit as an example, the enrichment zone of coal–Ga is predominantly situated in the northern part of the exploration area, adjacent to the fault zone. The Ga concentration demonstrates a gradual decline from the north–central region towards the northeast and southeast. Similar vertical Ga distribution patterns are observed in adjacent drillings, with notably higher concentrations in the roof, floor, and parting layers. The cooperative exploration model for coal–Ga deposits is proposed based on the above features. The model employs a comprehensive set of cooperative technical methods, such as remote sensing, geological mapping, seismic exploration, drilling, petrogeochemistry, and well logging. The layout of exploration engineering and the concentration of Ga provide the basis for the estimation of Ga resources. Additionally, the model provides an important scientific basis for the improvement of the strategic coordination ability of Ga mineral resources.

Impact of LTCI on Degree of Life Satisfaction and Psychological Blessedness of the Elderly Population: An Empirical Analysis of Psychological Mechanisms and Moderating Effects

Objectives: In order to keep a proactive watch on the economic aspect of old age care, the Chinese government strives not only to build the sense of life satisfaction and blessedness in families, but also ensure social development through social support mechanisms, including the Long-Term Care Insurance (LTCI) plan. This study examines the impact of LTCI on the degree of life satisfaction and psychological blessedness of the old and further investigates the psychological mechanisms and moderating factors involved. Methods: In order to use authentic data related to coping measures for population aging, the CHARLS (China Health and Retirement Longitudinal Study) database was chosen to examine the impact of the LTCI system. Results: The study results found that LTCI significantly improved the degree of life satisfaction of middle-aged and older people. The effect was found to be heterogeneous at the level of gender, marital status, and the number of children through heterogeneity analysis. The results revealed that LTCI had a significant improvement effect on the degree of life satisfaction of middle-aged and older adults, particularly of the male population, in variables such as marital status, having fewer children, increased intergenerational financial support, all of which wove a mechanism showing how LTCI made an improvement effect on the degree of life satisfaction of middle-aged and older people. Conclusion: These results are of great significance in promoting the formulation and implementation of LTCI policies. It provides useful insights to the government, social organizations, and individuals with a scientific basis for the impact of LTCI on the mental health of the old. It also provides a valuable reference for improving the quality of life and blessedness of the elderly population.

Methods for controlling heavy metals in environmental soils based on artificial neural networks

The problem of heavy metal pollution in soil has become a global environmental problem, and it is very important to predict and manage the heavy metals in the environmental soil in a timely manner. The changes in heavy metal content in soil have characteristics such as nonlinearity and large delay, making it difficult to predict heavy metals in soil using traditional methods. Traditional prediction methods are complex and cumbersome, which can lead to longer treatment time and easy secondary pollution. This article analyzed the Back Propagation neural network (BPNN) in artificial neural networks (ANN) and applied it to the prediction of heavy metals in environmental soils. BPNN has good nonlinear function approximation ability, so it can be well applied to complex problems such as soil heavy metal prediction. The methods of treating soil heavy metals include physical repair method, chemical repair method, microbial repair method, plant repair method, plant microbial combined repair method and so on. The use of BPNN can predict heavy metals in environmental soils through adaptive dynamic learning. However, the training time of the BPNN is relatively long and the convergence speed is relatively slow. Therefore, additional momentum terms were added to adjust the weights and thresholds of the network to improve the BPNN. In the experiment, the prediction performance of the improved BPNN was compared before and after the improvement. This article took 50 monitoring data of heavy metals in the same soil in a certain region in 2021 as sample data and predicted the content of heavy metals in the soil using improved and improved BPNN. Due to time constraints, this article only conducted experimental analysis on heavy metals such as lead and cadmium. In the first experiment, when the soil sample data was 50, the prediction accuracy of the BPNN for cadmium before and after improvement was 75.95% and 89.56%, respectively. In the second experiment, when the soil sample data was 50, the prediction accuracy of the BPNN for cadmium before and after improvement was 77.99% and 89.85%, respectively. The improved BPNN has good prediction accuracy and can effectively predict the status of heavy metals in soil. The analysis in this article can provide scientific basis for the comprehensive prevention and control of heavy metals in regional soil, and also provide reference for the development of pollution-free agriculture and ensuring food safety.

Circular Economy: an analysis of state-of-theart to identify a re-search agenda

In the last decade's new models of development considering the integration between the economic and ecological systems have appeared in response to the scarcity of resources and environmental impacts; the circular economy is one of these models. Although it is possible to find extensive literature on the subject, mainly in the last decade, the concept still lacks theoretical deepening. This article aims to and characterize the literature on the circular economy, published from 2008 through 2019 at the scientific bases Science Direct, Scopus and Web of Science.To achieve this goal, an integrative literature review was conducted, based on the Methodi Ordinatio Protocol, considering 2,661 papers from Web of Science, Science Direct and Scopus databases. The findings demonstrated the main characteristics of the papers published in the period considered for this ILR, showing the prominent authors, the distribution of the papers over the year, the central countries and journals of the publications, and the primary methods. In addition, we identified a research agenda with many topics until not addressed. The contribution of this study lies in the analysis of the main characteristics of the international literature on the circular economy, published in journals with impact factors, as well as identifying a research agenda that can help researchers, practitioners and other stakeholders in the area.

Biological activities, identification, method development, and validation for analysis of polyphenolic compounds in Nymphaea rubra flowers and leaves by UHPLC-Q-cIM-TOF-MS and UHPLC-TQ-MS.

Nymphaea rubra belongs to the Nymphaea family and is regarded as a vegetable used in traditional medicine to cure several ailments. These species are rich in phenolic acid, flavonoids, and hydrolysable tannin. This study aimed to assess the biological activities of Nymphaea rubra flowers (NRF) and leaves (NRL) by identifying and quantifying their polyphenolic compounds using ultra-performance liquid chromatography coupled to quadrupole cyclic ion mobility time-of-flight mass spectrometry (UHPLC-Q-cIM-TOF-MS) and triple quadrupole mass spectrometry (UHPLC-TQ-MS). NRF and NRL powder was extracted with methanol and fractionated using hexane, ethylacetate, and water. Antioxidant and α-glucosidase, and tyrosinase enzyme inhibitory activities were evaluated. The polyphenolic components of NRF and NRL were identified and quantified using UHPLC-Q-cIM-TOF-MS and UHPLC-TQ-MS. The method was validated using linearity, precision, accuracy, limit of detection (LOD), and lower limit of quantification (LLOQ). Bioactive substances and antioxidants were highest in the ethylacetate fraction of flowers and leaves. Principal component analysis showed how solvent and plant components affect N. rubra's bioactivity and bioactive compound extraction. A total of 67 compounds were identified, and among them 21 significant polyphenols were quantified. Each calibration curve had R2 > 0.998. The LOD and LLOQ varied from 0.007 to 0.09 μg/mL and from 0.01 to 0.1 μg/mL, respectively. NRF contained a significant amount of gallic acid (10.1 mg/g), while NRL contained abundant pentagalloylglucose (2.8 mg/g). The developed method is simple, rapid, and selective for the identification and quantification of bioactive molecules. These findings provide a scientific basis for N. rubra's well-documented biological effects.

Biosensors for ocean acidification detection

Ocean acidification is a global environmental problem that significantly impacts Marine ecosystems and biodiversity. The traditional chemical analysis method has the problems of complex equipment and high cost in ocean acidification monitoring. In recent years, fluorescent protein biosensor technology, as an innovative monitoring method, has provided a new solution for the real-time detection of ocean acidification. Compared with traditional chemical analysis methods, fluorescent protein biosensors have the advantages of simple operation, high sensitivity and low cost. Current studies have demonstrated the potential of fluorescent protein biosensors for ocean acidification monitoring. The researchers designed a variety of fluorescent protein biosensors and conducted indoor and outdoor experimental validation. These results show that fluorescent protein biosensors can detect ocean acidification quickly and accurately and maintain stable performance under different environmental conditions. Further studies are needed to verify the consistency and reliability of fluorescent protein biosensors and traditional chemical analysis methods for ocean acidification monitoring. Future research directions include further improving the performance of the fluorescent protein biosensor, increasing its sensitivity and stability, and verifying its application in real Marine environments. This will help establish a better monitoring network for ocean acidification and provide a reliable scientific basis for Marine environmental protection and management decisions. The development and application of fluorescent protein biosensor technology will provide important support and guidance for us to better understand the impact of ocean acidification.

Forecast Zoning of Forest Fire Occurrence: A Case Study in Southern China

Forest fires in the southern region of China pose significant threats to ecological balance, human safety, and socio-economic stability. Forecast zoning the occurrence of these fires is crucial for timely and effective response measures. This study employs the random forest algorithm and geospatial analysis, including kernel density and standard deviation ellipse methods, to predict forest fire occurrences. Historical fire data analysis reveals noteworthy findings: (i) Decreasing Trend in Forest Fires: The annual forest fire count in the southern region exhibits a decreasing trend from 2001 to 2019, indicating a gradual reduction in fire incidence. Spatial autocorrelation in fire point distribution is notably observed. (ii) Excellent Performance of Prediction Model: The constructed forest fire prediction model demonstrates outstanding performance metrics, achieving high accuracy, precision, recall, F1-scores, and AUC on the testing dataset. (iii) Seasonal Variations in High-Risk Areas: The probability of high-risk areas for forest fires in the southern region shows seasonal variations across different months. Notably, March to May sees increased risk in Guangxi, Guangdong, Hunan, and Fujian. June to August concentrates risk in Hunan and Jiangxi. September to November and December to February have distinct risk zones. These findings offer detailed insights into the seasonal variations of fire risk, providing a scientific basis for the prevention and control of forest fires in the southern region of China.

Guided wave-based crack detection in U-shaped flexural plate butt welds

Based on the guided wave, a crack detection method for U-shaped flexural plate (UFP) butt welds is established to realize damage localization and quantitative identification. Firstly, the semi-analytical finite element (SAFE) method was used to obtain the dispersion curve in a plate with weld by discretizing the cross-section and then solving the characteristic equation. Subsequently, numerical studies were performed to investigate the mode conversion and energy transfer efficiency in weld bending. Then the method was determined after the wave packet analysis of voltage responses under different damage conditions. Finally, a validation experiment was conducted in an actual UFP butt weld. The result indicates that there exist 10 guided wave modes in a plate with weld at 150 kHz, while only 2 modes in a flat plate; For curvature radius of weld bending substantially greater than the weld thickness, the guided wave energy mainly passes through the bending in the form of transmitted waves and the reflected wave formed in the bending can be ignored; The damage can be located with the defect echo of the specific guided wave and the error distance only accounting for 1.5% of the total weld length. It is effective to take wavelet energy as an indicator to characterize the damage degree. The method significantly improves crack detection efficiency and provides a scientific basis for monitoring similar structures.